Cardiac Strain Imaging in Asymptomatic Carriers of Transthyretin Variants

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Bagherzadeh, Nancy Herrera-Leaño, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8745379/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: Explore different echocardiographic parameters, particularly strain imaging, for early pathological changes in asymptomatic ATTR variant carriers. Background: With the rise in genetic testing and availability of multiple echocardiographic parameters, determining which features are most sensitive for detecting early changes in asymptomatic carriers of hereditary transthyretin cardiac amyloidosis (ATTRv-CM) could be helpful for guiding monitoring strategies and implementation. Methods: TTR variant carriers (n=39) were identified after a positive genetic test in individuals without evidence of cardiomyopathy based on routine echocardiography or PYP scan. Baseline echocardiograms were analyzed and compared to matched controls and patients with ATTRv-CM. Structural indices, diastolic parameters, and myocardial and atrial 2D strain analyses were measured and compared for differences in rank and in effect size. Results: TTR variant carriers had a mean age of 51±11 years; 71% were female. Mutations were mainly V30M(29%), T60A(26%), and V122I(24%). Wall thickness measures were significantly higher in carriers compared to controls; however, the largest effect size for differences were observed left atrial(LA), right atrial(RA), and right ventricular(RV) strains (cliff delta >0.33). The proportion of TTR variant carriers meeting abnormal thresholds was different from controls for relative wall thickness>0.42 (16% vs. 0%), p<0.01), |RV strain|<20% (12.8% vs. 1.4%, p=0.02) and |RA reservoir strain|<25% (21.6% vs. 1.3%, p<0.01). After a median follow-up of 3.22 years, 4/26 (15%) TTR carriers developed ATTRv-CM and did not have major baseline dysfunctions. Conclusion: TTR variant carriers show subtle echocardiographic differences from controls, particularly in LA, RA, and RV strains. The implementation of echocardiography for early detection in asymptomatic TTR carriers can be challenging. Future studies should further investigate the usefulness of routinely measuring these features to guide monitoring strategies in this population. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Systemic amyloidosis is characterized by misfolded protein accumulation in tissues, eventually impairing organ function. 1 The most common subtypes are light chain (AL) and transthyretin (ATTR) amyloidosis, with the latter being either acquired (wild-type) or inherited (variant). 1 Hereditary/variant transthyretin amyloidosis (ATTRv) remains frequently overlooked in diagnosis, due to variable clinical presentations, ranging from predominantly neurologic to predominantly cardiac. 2 Among those harboring a TTR genetic mutation, some may develop cardiomyopathy during their lifetime, manifesting as symptoms of conduction blocks, arrhythmias, and ultimately heart failure. 3 Cardiac involvement is a significant predictor of poor prognosis, thus early detection and timely intervention are essential. 4,5 Available treatments for hereditary transthyretin cardiomyopathy (ATTRv-CM), although very promising, prevent further TTR deposition in the heart but do not meaningfully reverse existing damage. 6 With multiple echocardiographic parameters available, determining which features are most useful for detecting early changes in asymptomatic TTR mutation carriers can be helpful for guiding clinical monitoring strategies and resource allocation. While conventional structural measures and diastolic parameters are commonly assessed, the comparative utility of advanced strain imaging techniques in this population remains unclear. 1,7 Echocardiography plays a major role in the non-invasive assessment of ATTR-CM, being a widely available non-invasive imaging tool that can detect structural and functional abnormalities associated with amyloid build-up in the heart. 8 Although echocardiography alone cannot definitely diagnose or distinguish the amyloidosis subtype, it remains an essential component in the diagnosis, prognosis and ongoing management of patients with this condition. 8 In this study, we aim to compare different echocardiographic parameters, particularly strain imaging, in asymptomatic TTR variant carriers, and to investigate whether the relative ranking of echocardiographic features observed in TTR variant carriers is consistent in patients with ATTRv-CM. Methods 1. Study Population: The study was approved by the Stanford in University Institutional Review Board. Patients referred to the Stanford Amyloid Center for cardiac evaluation from 2010 to 2023 were considered, and only those with a positive ATTR genetic test were included (Figure 1) . Patients without baseline echocardiograms around the date of the genetic test were excluded. Two groups of patients were then identified. The first group included TTR variant carriers, defined as those with no echocardiographic evidence of ATTR-CM, as previously outlined, 8,9 and judged by amyloidosis experts; and/or negative technetium pyrophosphate (PYP) scan at the time of the genetic testing; all with normal NT-proBNP and troponin levels. Of note, not all individuals in this group had PYP scans, which were performed only when echocardiograms and the clinical picture were judged suspicious of ATTRv-CM. TTR variant carriers were matched 2:1 for age, sex, and comorbidities with healthy controls identified from the Stanford Healthy Cohort database. A second group consisted of ATTRv-CM patients with confirmed cardiac involvement by either a PYP scan or endomyocardial biopsy, as recommended by national guidelines. 8 To eliminate confounders and advanced cardiac involvement, we excluded patients with prior myocardial infarction, atrial fibrillation/flutter (at the time of echocardiography), and ejection fraction less than 50%. None met these exclusion criteria among the TTR variant carriers group; however, we excluded one patient who was found to have hypertensive cardiomyopathy with high filling pressures (Figure 1) . Baseline demographic, clinical, and imaging data around the date of the genetic test were derived from an electronic chart review. 2. Echocardiography Baseline echocardiograms were re-analyzed by the Stanford Cardiovascular Institute Imaging Core Laboratory. Echocardiographic measurements, chamber quantification, assessment of diastolic function, and strain analysis were performed by experienced echocardiography personnel following the American Society of Echocardiography recommendations, and blinded to patients’ clinical data. 10 Measured echocardiographic parameters included wall thickness, relative wall thickness (RWT), left ventricular (LV) mass using the linear method and scaled to body surface area (LVMI), left atrial volume using the biplane Simpson method and scaled to body surface area (LAVI), septal and lateral early mitral tissue doppler annular velocity (e’), early and late diastolic peak velocities of mitral inflow ratio (E/A), the ratio of early diastolic inflow velocity to e’ (E/e’) and right ventricular (RV) systolic pressure (RVSP). Strain analyses were performed using TomTec software (TTA2.51) and included measurements of LV global longitudinal strain (LV GLS), left atrial reservoir strain (LASr), left atrial conduit strain (LAScd), left atrial contraction strain (LASct), RV free wall longitudinal strain (RV FWLS), right atrial reservoir strain (RASr), right atrial conduit strain (RAScd), right atrial contraction strain (RASct). Low quality images or images with foreshortened LV or RV were excluded from analysis. 10 3. Statistical Analysis The characteristics of the study population were summarized using descriptive statistics. Continuous variables were reported as means ± standard deviation or medians [interquartile range (IQR) 25 th -75 th ] and compared using the non-parametric Mann-Whitney U test. Categorical variables were reported as frequencies (percentages) and compared using Fisher exact and Chi-square tests. To report the estimation of the effect size of the differences between two groups, we adopted the non-parametric Cliff’s delta test. Cliff’s delta calculates the probability that a randomly selected value from one group will be greater than a randomly selected value from another group, minus the reverse probability. 11 In other words, Cliff’s delta can be interpreted as the degree of distributional non-overlap between two distributions. One major advantage of Cliff’s delta is that it considers the entire distribution rather than simply estimating the magnitude of the effect for those in the center. Cliff’s delta ranges from -1 to 1, where a value of 0 indicates no difference between the two groups. 11 Positive values indicate that the first group tends to have higher values than the second group, while negative values indicate the opposite. Cliff’s delta was used to compare the TTR variant carriers distributions relative to controls, and the ATTRv-CM group relative to the TTR variant carriers. Since the TTR variant carriers group is inherently younger in our population than the ATTRv-CM, the main analysis excluded echocardiography parameters (septal/lateral e’, E/A, E/e’) known to be heavily affected by age, 12 as it will influence the comparison, however, the full analysis was shown in the supplements. For all tested hypotheses, the significance level of 0.05 was considered. All analyses were done using Python version 3.9.6. To study the relationship between the different imaging parameters and understand their connectivity, a network from the major echocardiographic variables was developed, with connections weighted by the maximal information coefficient (MIC). 13 MIC quantifies the strength of association, varying from 0 (no statistical relationship) to 1 (noise-free connection). We chose MIC over alternative measures of association because it can detect both linear and non-linear associations, as well as assign equal scores to similarly noisy relationships of diverse types. 13 We also used the Eigenvector centrality, which assigns relative scores to all nodes in the network and determines the most influential parameters in the network. 14 MICs and Eigenvector centrality scores were computed using the Python minepy library and MIC-network was visualized using networkX3.1. Results 1. Baseline characteristics of the TTR variant carriers: The baseline characteristics of the study groups are reported in Table 1 . Among the genetic ATTR population reviewed, 38 carriers had TTR variants without evidence of cardiomyopathy at the time of referral. PYP scans, all with negative findings, were performed in 10 (26%) of those carriers in addition to the echocardiography. Their mean age was 51±11 years, 71% were female, 71% were white, and 18% had hypertension. Median NT-proBNP was normal at 53 pg/ml [IQR 28-77]. The most common variants were V30M (29%), T60A (26%), and V122I (24%). Neurologic symptoms were prevalent in 13 individuals, secondary to peripheral neuropathy (10/38), carpal tunnel syndrome (5/38), and/or spinal stenosis (1/38). No patients were on ATTR therapies (stabilizers or silencers) at the time of their baseline echocardiogram. 2. TTR variant carriers vs. healthy Controls The TTR variant carriers had normal median septal (IVSd) and posterior (LVPWd) wall thicknesses at 0.79 [0.71, 0.93] and 0.79 [0.72, 0.96] cm respectively, with a median RWT of 0.34 [0.30, 0.42] and LVMI of 60.20 [54.33, 70.23] g/m 2 (Table 2) . Diastolic function parameters showed median septal and lateral e' values of 7.9 [6.4, 9.8] and 10.2 [8.7-12.1] cm/s, respectively, with a median E/e’ of 8.20 [6.40, 9.40], and a median LAVI of 29.55 [22.75, 34.69] ml/m 2 . Strain analysis revealed a median LV GLS of -21.70 % [-22.90, -20.85], median LASr of 29.65 %[27.79, 36.78], median RV FWLS of -24.70% [-27.30, -22.30] and median RASr of 33.50 % [25.82, 36.11]. Compared to controls, the TTR variant carriers had higher wall thickness measures and RWT, but lower LVMI (p<0.05). Notably, the distribution of the non-routinely measured LAS, RV FWLS, and RAS were the most significantly different from healthy controls (p<0.001) (Table 2) . The magnitude of the difference between the TTR variant carriers and the healthy controls was quantified using Cliff’s delta (95% CI) as a measure of effect size (Figure 2A) .Structural parameters and diastolic function indices had negligible to small differences, while the medium to largest effect sizes were observed for LASr, RASr, RAScd and RV FWLS. A sensitivity analysis was performed on TTR variant carriers without hypertension ( Supplementary Figure 1A ) as well as on carriers with and without baseline PYP scans ( Supplementary Figure 1B, Supplementary Figure 1C ); compared to their specific 2:1 matched controls. Some experts have suggested starting ATTR screening 10 years before the predicted age of onset of disease, and although controls are matched for age, we have also performed a sensitivity analysis of individuals >40 years old (Supplementary Figure 1D) ; all yielding similar results. The proportion of individuals with values above or below conventional echocardiography reference limits is presented in Figure 2B . There was a trend towards higher proportions of abnormalities in the TTR variant carriers for most measures. Statistically significant differences were observed between controls and the TTR carriers for RWT >0.42 (0% vs. 16%), septal e' <7 cm/s (17% vs. 35%), |RV FWSL| <20% (1% vs. 13%), and |RASr| <25% (1% vs 22%). 3. Genetic ATTR: a spectrum of abnormalities To better understand the complete spectrum of abnormalities in genetic ATTR, we have also explored a cohort of ATTRv-CM patients. The ATTRv-CM group (n=43) was older than the TTR variant carriers group, with a mean age of 68±10 years, and had more male (79%) and Black race (37%) representation (Supplementary Table 1) . Most patients exhibited symptoms corresponding to NYHA class II (51%), while the remaining patients were distributed between NYHA class I (28%) and class III (21%). According to the Columbia ATTR-CM disease staging, the distribution of early, intermediate, and late ATTRv-CM was 65%, 26%, and 9%, respectively. Comorbidities included hypertension (51%), a history of atrial fibrillation (16%), diabetes mellitus type II (14%), and chronic kidney disease (14%). Their median NT-proBNP was 812 pg/ml [31-1630]. As expected, the ATTRv-CM cohort differed substantially from the TTR variant carriers in all the measured echocardiographic indices (Table 3) . Wall thickness measures were abnormally high, and there was evident LV hypertrophy, LA enlargement, and elevated filling pressures. Strain analysis indicated abnormal left heart strains and borderline abnormal readings for right chamber strains ( Table 3 ). Apical sparing of LV longitudinal strain, known as the “cherry-on-top” pattern, was observed in n=21/43 (49%) of the patients. Compared with the TTR variant carriers, both structural and functional parameters of the ATTRv-CM group had large effect sizes of their distributions, with Cliff’s delta exceeding 0.9 for IVSd, LVPWd, RWT, and LV GLS ( Figure 3A) .We excluded from this comparison diastolic function parameters as they change substantially with age and would not provide a fair comparison given our ATTRv-CM cohort is more than 10 years older than the TTR variant carriers group. However, the full analysis is provided in Supplementary Figure 2 . The proportion of individuals with ATTRv-CM meeting the conventional echocardiographic thresholds of normality was significantly higher than that of the TTR variant carriers for all structural and functional parameters ( Figure 3B) . The most commonly observed abnormalities among ATTRv-CM patients was for RWT>0.42 (95%) and lateral e’<10 cm/s (93%), followed by septal e’<7cm/s (88%) and LASr<25% (84%). To better understand the interrelationships between all these various echocardiography parameters and identify the strongest relationships that may reflect underlying cardiac involvement, we visualized an MIC network including major echocardiographic indices and NT-proBNP ( Figure 4, Supplementary Figure 3) . A strong relationship between structural and functional parameters was evident, with LVMI being at the center, strongly associated with RWT (MIC 0.92), LV GLS (MIC 0.69), septal/lateral e’ (MIC 0.67), and with E/e’ (MIC 0.63). Another robust association was observed between RWT and LV GLS (MIC 0.81), and between RWT and LASr (MIC 0.65). NT-proBNP was moderately correlated to the echocardiographic indices, notably with RASr (MIC 0.60), LASr (MIC 0.53) and E/e’ (MIC 0.53). LVMI and RWT had the highest Eigenvector centrality compared with diastolic parameters and strain measures, reflecting their central role in the network and their importance in characterizing cardiac involvement in ATTRv-CM. 13,14 4. Clinical progression from TTR variant carriers to ATTRv-CM Cardiac follow-up information was present in 26/38 (68%) TTR variant carriers. Aside from echocardiography, 18/26 (69%) had performed PYP scans. At our institution, follow-up frequency with cardiac biomarkers, electrocardiography, and echocardiography, was equally divided between either every 3-6 months, every year, or every 2-3 years, depending on clinician judgment of each case. After a median follow-up of 3.22 years, 4 (15%) individuals developed ATTRv-CM and cardiac involvement was confirmed by either endomyocardial biopsy (2/4) or PYP scan (2/4). The mean age was 64 ±10 years, 3/4 were females. All four individuals had the T60A mutation (out of 10 total Thr60Ala carriers). Three of them had neurological symptoms/involvement (bilateral CPS and/or polyneuropathy) prior to their baseline cardiac visit.Two had a baseline RWT>0.42 without a prior history of hypertension. None of the patients who progressed had abnormal diastolic function nor abnormal left heart strains, except one with borderline LV GLS at -17.6%. All four had their baseline |RV FWSL| <25%. The distribution of baseline echocardiography measures of individuals who progressed to ATTRv-CM and those who did not are both presented in Supplementary Table 2 . To note that the comparison has unbalanced sample sizes and is not powered to reach significance or draw conclusions, and follow-up echocardiograms were not available for analysis. Discussion In this study, we compared the sensitivity of different echocardiographic parameters in asymptomatic TTR variant carriers to determine which features show the most pronounced differences from healthy controls. While we observed minor differences in standard echocardiographic parameters (e.g. wall thicknesses) between TTR variant carriers and healthy controls, these variations are subtle, with values largely remaining within normal ranges. This highlights a critical challenge for echocardiography as a screening tool in this population—single metrics with fixed thresholds show limited discriminatory power. However, when examining effect sizes rather than simple statistical differences, the most pronounced differences from controls were found in strain parameters, particularly left atrial strain (LASr) and right heart strain measures (RASr, RV FWSL). These findings suggest that while conventional structural parameters show statistically significant differences, advanced functional imaging with strain analysis may offer greater sensitivity for characterizing early cardiac involvement. The better discriminatory ability of strain parameters compared to conventional structural measures likely reflects several pathophysiological factors. Myocardial strain represents direct assessment of myocardial deformation and may detect early functional impairment before gross structural changes become apparent. Furthermore, amyloid deposition may initially affect myocardial contractility before causing measurable increases in wall thickness. The sensitivity of atrial strain parameters may reflect the vulnerability of atrial myocardium to early infiltration, while RV strain abnormalities may indicate early involvement of this often-overlooked chamber in amyloid cardiomyopathy. With several disease-modifying therapies now available for ATTR-CM, understanding the full phenotypic spectrum of amyloidosis presentation across subgroups is critical to scaling efforts to better diagnose and optimally treat ATTR-CM. 8 While most studies have focused on characterizing abnormalities in overt ATTR-CM, few have investigated TTR variant carriers. 15,16 The increasing availability of genetic testing has led to a growing identification of individuals carrying pathogenic/likely pathogenic TTR mutations, without evidence of cardiac involvement. 7 This cohort presents a unique set of challenges, characterized by the complex interplay between genetics and disease manifestation. 7 The TTR gene has over 130 known pathogenic variants, each with its own pattern of expressivity and penetrance. Different mutations can lead to distinct clinical presentations. 2 For instance, the Val122Ile mutation is the primary cause of late-onset ATTR-CM in the United States. In contrast, the Thr60Ala mutation typically results in early-onset ATTR-CM. The Val30Met mutation presents differently based on age of onset: early-onset cases primarily manifest as polyneuropathy, while late-onset cases often have cardiac involvement. 2 While previous observational surveys (e.g. THAOS study) have described the natural progression of TTR variant carriers, these studies relied solely on symptom occurrence to describe the transition to ATTRv amyloidosis. 15 Moreover, the time-to-HF symptoms and prognosis of asymptomatic patients with positive evidence of ATTR-CM on imaging has been also described. 16 However, longitudinal studies focusing on the natural progression of TTR variant carriers with negative cardiac imaging have not been conducted, and are still critically needed to guide patient counseling and management. In addition, the exact criteria for classifying an individual as cardiac “phenotype-negative” remains challenging and subject to debate. While more specific and likely sensitive diagnostic modalities such as PYP scans do exist, their application for screening purposes is not universal, due to limited availability and cost-effectiveness. 17,18 Consequently, many genetic carriers undergo evaluation primarily through echocardiography, electrocardiography, and clinical tests, with more sensitive diagnostic modalities reserved for cases with concerning findings. 7 Echocardiography offers a rich array of features, providing comprehensive insights into the structure and function of the heart. 19 In this study, the MIC network demonstrated how most echocardiographic features are interconnected along the spectrum of genetic ATTR. The centrality of the structural parameters of remodeling (RWT) and hypertrophy (LVMI) to diastolic and strain function, and to NT-proBNP, suggest a complex but synergistic relationship between cardiac morphology, function, and physiology. Due to this intertwined nature, many features will have comparable effect sizes for differentiating overt ATTR-CM cases. This finding was evident in the ATTRv-CM cohort with preserved EF, where classical echocardiography findings of increased wall thickness, abnormal strain, and diastolic dysfunction were observed in conjunction, and had large effect sizes. These observations were less evident in the TTR variant carriers, where the differences compared to controls were mostly subtle, and might be missed by routine echocardiography of standard parameters, as values largely remained within the normal range in our population. These findings highlight the opportunity for new diagnostic scores that would explore different combination of structural and functional parameters with various weights and more sensitive thresholds. 20 Sensitive functional parameters such as LV myocardial strain have been proposed to detect early cardiac involvement in ATTR amyloidosis, and an abnormal value is considered a red flag for ATTR-CM. 9 LV regional strain patterns (e.g. the cherry-on-top) were also described, with unclear diagnostic specificity for amyloidosis in the literature. 9,21–23 In our cohort, while none of the controls or the TTR variant carriers had apical sparing pattern, around half of those with ATTRv-CM did exhibit this pattern. Beyond LV strain, our study highlighted the additional importance of atrial and RV strains in this population. Most recently, LA strain has gained considerable attention in the diagnosis and grading of LV diastolic dysfunction, with mounting evidence supporting its eventual incorporation into diastolic assessment guidelines. 24–26 In ATTR-CM, it is still unknown whether the observed worse LA function in ATTR-CM is solely a consequence of LV dysfunction as opposed to reflecting a true infiltrative atrial myopathy. 27–30 Regarding the right heart, previous reports focused on patients with cardiac AL amyloidosis, 31–35 moreso than ATTR-CM, 36 demonstrating worse prognosis with the presence of RA or RV dysfunction, even in the absence of pulmonary hypertension or clear left heart involvement. Moreover, Uzan et al. have suggested using RV FWLS, with an optimal cut-off of -21%, to discriminate AL amyloidosis from hypertension or hypertrophic cardiomyopathy. 37 Along with these findings, our analysis of the ATTRv-CM group confirmed previous observations, showing that impaired strain analysis could be present not only in the LV, but also in all four cardiac chambers. Another distinctive aspect of our study was our investigation of TTR variant carriers, which revealed that although their LV GLS was similar to controls, they showed significantly worse strain in the atria (LASr, RASr) and right ventricle (RV FWLS). Whether routine evaluation of left atrial and right heart strains plays an important role in routine echocardiography screening for early CM in TTR carriers, is a question raised by our findings and still requires validation. Future studies may also help establish appropriate cut-off limits and identify which combinations of abnormal parameters could be most appropriate for risk-stratification or early detection. Follow-up and future perspectives: While not the main objective of our analysis, this study also highlights the importance of close follow-up of TTR mutation carriers. Despite a small sample size and a relatively short follow-up time of 3.22 years, 15% of ATTR G+/P- progressed to ATTR-CM in our population. The cardiac penetrance of the Thr60Ala mutation was 25%. This progression rate warrants consideration in the management of these at-risk individuals, given the lack of standardized protocols for follow-up timing and imaging modalities. 7,38,39 Current practices vary widely, with follow-up intervals ranging from every few months to every 5 years, largely dictated by individual providers or judgment or patient ability. Moreover, this variability is compounded by the limited availability and financial burden of advanced screening and diagnostic tools. 18 Reliance on echocardiography alone for follow-up presents its own challenges. While widely accessible, routine echocardiographic assessment is subject to reader variability and may lack the sensitivity required to detect early-stage disease. Interestingly, our cohort who developed ATTRv-CM did not exhibit significant baseline structural or functional abnormalities, except for lower right heart strain (all had |RVFWLS| <25%) that could not be quantified due to the lack of validated reference values. These observations call for larger and longer longitudinal studies to elucidate whether patients with baseline cardiac abnormalities, or stage B HF, warrant more frequent monitoring and with what modalities. When both structural and functional changes are present in imaging, amyloid deposition is already present. However, it is unknown if there is a role for prevention by initiating therapy for those with earlier presentations on imaging. From an implementation perspective, our findings highlight important challenges for using echocardiography as a standalone screening tool in asymptomatic genetic carriers. The subtle nature of differences and substantial overlap of individual parameters with normal ranges suggest that fixed thresholds for single metrics have limited utility. In the management of asymptomatic TTR carriers, genetic screening remains the primary diagnostic modality, with echocardiography serving to characterize the degree of early cardiac involvement rather than functioning as a screening test. This distinction is critical for appropriate resource allocation and clinical workflow design. Limitations: Limitations of this study include its retrospective nature and the relatively small TTR variant carriers sample size, particularly when stratified per specific TTR mutation. Another limitation is the small proportion of individuals with baseline PYP scans. While echocardiography parameters are subject to variable measurement practices, these were minimized by our experienced Core Laboratory professionals who followed guideline-recommended measurement practices. Longitudinal studies with larger cohorts and complete multimodal imaging are indeed needed in TTR carriers to validate our findings and influence management in this challenging population. Conclusion In our study, asymptomatic TTR variant carriers show subtle differences in echocardiographic parameters compared to healthy controls, with LA, RA, and RV strain measures exhibiting the largest effect sizes. While echocardiography remains valuable for assessing early cardiac changes, with particular attention to right heart and atrial function, our findings highlight significant challenges for using echo as a screening tool in this population. Single metrics with fixed thresholds have limited discriminatory power given the subtle nature of early changes and considerable overlap with normal ranges. Future implementation strategies will likely require development of integrated tools that combine multiple parameters rather than relying on individual thresholds. In asymptomatic genetic carriers, genetic screening remains the primary diagnostic approach, with echocardiography serving to characterize early disease rather than as a standalone screening modality. Abbreviations AL Light chain amyloidosis ATTR Transthyretin amyloidosis ATTRv Hereditary/Variant transthyretin amyloidosis ATTRv-CM Hereditary transthyretin cardiomyopathy CPS Carpal tunnel syndrome EF Ejection fraction E/A Early to late diastolic peak velocities of mitral inflow ratio E/e' Ratio of early diastolic inflow velocity to early mitral tissue Doppler annular velocity GLS Global longitudinal strain HF Heart failure IVSd Interventricular septal thickness at end-diastole LA Left atrium LAVI Left atrial volume index LAScd Left atrial conduit strain LASct Left atrial contraction strain LASr Left atrial reservoir strain LV Left ventricle LVMI Left ventricular mass index LVPWd Left ventricular posterior wall thickness at end-diastole MIC Maximal information coefficient NT-proBNP N-terminal pro-B-type natriuretic peptide NYHA New York Heart Association PYP Technetium pyrophosphate RA Right atrium RAScd Right atrial conduit strain RASct Right atrial contraction strain RASr Right atrial reservoir strain RV Right ventricle RV FWLS Right ventricular free wall longitudinal strain RVSP Right ventricular systolic pressure RWT Relative wall thickness TTR Transthyretin V30M Valine 30 Methionine mutation T60A Threonine 60 Alanine mutation V122I Valine 122 Isoleucine mutation Declarations Disclosures: KMA has received consulting fees from Arbor Biotechnologies, Alexion, Alnylam, Novo Nordisk, and Pfizer. RMW has received consulting fees from Pfizer, Alnylam, AstraZeneca, Alexion, Novo Nordisk, and BridgeBio. All other authors have no disclosures/COI. Funding support: None. Ethics Approval and Consent to Participate This study was approved by the Stanford University Institutional Review Board (IRB). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. All participants provided written informed consent prior to participation in this study. For retrospective data analysis, informed consent was waived by the Stanford University Institutional Review Board in accordance with institutional guidelines. Consent for Publication Not applicable. Availability of Data and Materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests RMW has received consulting fees from Pfizer, Alnylam, AstraZeneca, Alexion, and Novo Nordisk. All other authors declare that they have no competing interests. Funding None. Authors’ Contributions FH and KMA contributed equally to this work. GF, FH, KMA, NHL, JIJ and SPB contributed to study conception and design, data acquisition, analysis and interpretation, and manuscript preparation. NHL, YB, LC, XT, PC, MS, RMW, KMA and FH contributed to data interpretation and critical manuscript revision. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Gertz MA, Dispenzieri A. Systemic Amyloidosis Recognition, Prognosis, and Therapy: A Systematic Review. JAMA. 2020;324(1):79–89. 10.1001/jama.2020.5493 . Manganelli F, Fabrizi GM, Luigetti M, Mandich P, Mazzeo A, Pareyson D. Hereditary transthyretin amyloidosis overview. Neurol Sci. 2022;43(Suppl 2):595–604. 10.1007/s10072-020-04889-2 . Klaassen SHC, Tromp J, Nienhuis HLA, et al. Frequency of and Prognostic Significance of Cardiac Involvement at Presentation in Hereditary Transthyretin-Derived Amyloidosis and the Value of N-Terminal Pro-B-Type Natriuretic Peptide. Am J Cardiol. 2018;121(1):107–12. 10.1016/j.amjcard.2017.09.029 . Adams D, Algalarrondo V, Polydefkis M, Sarswat N, Slama MS, Nativi-Nicolau J. Expert opinion on monitoring symptomatic hereditary transthyretin-mediated amyloidosis and assessment of disease progression. Orphanet J Rare Dis. 2021;16(1):411. 10.1186/s13023-021-01960-9 . Gillmore JD, Damy T, Fontana M, et al. A new staging system for cardiac transthyretin amyloidosis. Eur Heart J. 2018;39(30):2799–806. 10.1093/eurheartj/ehx589 . Bampatsias D, Wardhere A, Maurer MS. Treatment of transthyretin cardiac amyloidosis. Curr Opin Cardiol. 2024;39(5):407–16. 10.1097/HCO.0000000000001156 . Conceição I, Damy T, Romero M, et al. Early diagnosis of ATTR amyloidosis through targeted follow-up of identified carriers of TTR gene mutations. Amyloid. 2019;26(1):3–9. 10.1080/13506129.2018.1556156 . Garcia-Pavia P, Rapezzi C, Adler Y, et al. Diagnosis and treatment of cardiac amyloidosis: a position statement of the ESC Working Group on Myocardial and Pericardial Diseases. Eur Heart J. 2021;42(16):1554–68. 10.1093/eurheartj/ehab072 . Cuddy SAM, Chetrit M, Jankowski M, et al. Practical Points for Echocardiography in Cardiac Amyloidosis. J Am Soc Echocardiogr. 2022;35(9):A31–40. 10.1016/j.echo.2022.06.006 . Lang RM, Badano LP, Mor-Avi V, et al. Recommendations for Cardiac Chamber Quantification by Echocardiography in Adults: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16(3):233–71. 10.1093/ehjci/jev014 . Meissel K, Yao E. Using Cliff’s Delta as a Non-Parametric Effect Size Measure: An Accessible Web App and R Tutorial. Published online January. 2024;22. 10.7275/PARE.1977 . Miyoshi T, Addetia K, Citro R, et al. Left Ventricular Diastolic Function in Healthy Adult Individuals: Results of the World Alliance Societies of Echocardiography Normal Values Study. J Am Soc Echocardiogr. 2020;33(10):1223–33. 10.1016/j.echo.2020.06.008 . Reshef DN, Reshef YA, Finucane HK, et al. Detecting Novel Associations in Large Data Sets. Science. 2011;334(6062):1518–24. 10.1126/science.1205438 . Bonacich P. Some unique properties of eigenvector centrality. Social Networks. 2007;29(4):555–64. 10.1016/j.socnet.2007.04.002 . Coelho T, Conceição I, Waddington-Cruz M, et al. A natural history analysis of asymptomatic TTR gene carriers as they develop symptomatic transthyretin amyloidosis in the Transthyretin Amyloidosis Outcomes Survey (THAOS). Amyloid. 2022;29(4):228–36. 10.1080/13506129.2022.2070470 . Gonzalez-Lopez E, Escobar-Lopez L, Obici L, et al. Prognosis of Transthyretin Cardiac Amyloidosis Without Heart Failure Symptoms. JACC CardioOncol. 2022;4(4):442–54. 10.1016/j.jaccao.2022.07.007 . Maurer MS, Bokhari S, Damy T, et al. Expert Consensus Recommendations for the Suspicion and Diagnosis of Transthyretin Cardiac Amyloidosis. Circ Heart Fail. 2019;12(9):e006075. 10.1161/CIRCHEARTFAILURE.119.006075 . Bourque JM, Schepart A, Bhambri R, et al. Temporal Trends in Diagnostic Testing Patterns for Wild-Type Transthyretin Amyloid Cardiomyopathy in the Medicare Fee-for-Service Population. Am J Cardiol. 2022;167:98–103. 10.1016/j.amjcard.2021.11.048 . Liang S, Liu Z, Li Q, He W, Huang H. Advance of echocardiography in cardiac amyloidosis. Heart Fail Rev. 2023;28(6):1345–56. 10.1007/s10741-023-10332-3 . Davies DR, Redfield MM, Scott CG, et al. A Simple Score to Identify Increased Risk of Transthyretin Amyloid Cardiomyopathy in Heart Failure With Preserved Ejection Fraction. JAMA Cardiol. 2022;7(10):1036–44. 10.1001/jamacardio.2022.1781 . Wali E, Gruca M, Singulane C, et al. How Often Does Apical Sparing of Longitudinal Strain Indicate the Presence of Cardiac Amyloidosis? Am J Cardiol. 2023;202:12–6. 10.1016/j.amjcard.2023.06.022 . Cotella J, Randazzo M, Maurer MS, et al. Limitations of apical sparing pattern in cardiac amyloidosis: a multicentre echocardiographic study. Eur Heart J Cardiovasc Imaging. 2024;25(6):754–61. 10.1093/ehjci/jeae021 . Miller WL. Echocardiographic Longitudinal Strain Pattern of Apical Sparing and the Search for Cardiac Amyloidosis: Importance of Clinical Context or Not All That Sparkles is Gold. Am J Cardiol. 2023;202:235–6. 10.1016/j.amjcard.2023.06.076 . Ntalianis E, Sabovčik F, Cauwenberghs N, et al. Unsupervised Time-Series Clustering of Left Atrial Strain for Cardiovascular Risk Assessment. J Am Soc Echocardiogr. 2023;36(7):778–87. 10.1016/j.echo.2023.03.007 . Nagueh SF, Khan SU. Left Atrial Strain for Assessment of Left Ventricular Diastolic Function: Focus on Populations With Normal LVEF. JACC Cardiovasc Imaging. 2023;16(5):691–707. 10.1016/j.jcmg.2022.10.011 . Singh A, Addetia K, Maffessanti F, Mor-Avi V, Lang RM. LA Strain for Categorization of LV Diastolic Dysfunction. JACC Cardiovasc Imaging. 2017;10(7):735–43. 10.1016/j.jcmg.2016.08.014 . Brand A, Frumkin D, Hübscher A, et al. Phasic left atrial strain analysis to discriminate cardiac amyloidosis in patients with unclear thick heart pathology. Eur Heart J Cardiovasc Imaging. 2021;22(6):680–7. 10.1093/ehjci/jeaa043 . Usuku H, Takashio S, Yamamoto E, et al. Prognostic value of right ventricular global longitudinal strain in transthyretin amyloid cardiomyopathy. J Cardiol. 2022;80(1):56–63. 10.1016/j.jjcc.2022.02.010 . Vergaro G, Aimo A, Rapezzi C, et al. Atrial amyloidosis: mechanisms and clinical manifestations. Eur J Heart Fail. 2022;24(11):2019–28. 10.1002/ejhf.2650 . Tremblay-Gravel M, Ichimura K, Picard K, et al. Intrinsic Atrial Myopathy Precedes Left Ventricular Dysfunction and Predicts Atrial Fibrillation in Lamin A/C Cardiomyopathy. Circ Genom Precis Med. 2023;16(1):e003480. 10.1161/CIRCGEN.121.003480 . Nemes A, Földeák D, Domsik P, et al. Right Atrial Deformation Analysis in Cardiac Amyloidosis - Results from the Three-Dimensional Speckle-Tracking Echocardiographic MAGYAR-Path Study. Arq Bras Cardiol. 2018;111(3):384–91. 10.5935/abc.20180150 . Tjahjadi C, Fortuni F, Stassen J, et al. Prognostic Implications of Right Ventricular Systolic Dysfunction in Cardiac Amyloidosis. Am J Cardiol. 2022;173:120–7. 10.1016/j.amjcard.2022.02.048 . Tana M, Tana C, Palmiero G, et al. Imaging findings of right cardiac amyloidosis: impact on prognosis and clinical course. J Ultrasound. 2023;26(3):605–14. 10.1007/s40477-023-00789-1 . Ghio S, Perlini S, Palladini G, et al. Importance of the echocardiographic evaluation of right ventricular function in patients with AL amyloidosis. Eur J Heart Fail. 2007;9(8):808–13. 10.1016/j.ejheart.2007.05.006 . Bellavia D, Pellikka PA, Dispenzieri A, et al. Comparison of right ventricular longitudinal strain imaging, tricuspid annular plane systolic excursion, and cardiac biomarkers for early diagnosis of cardiac involvement and risk stratification in primary systematic (AL) amyloidosis: a 5-year cohort study. Eur Heart J Cardiovasc Imaging. 2012;13(8):680–9. 10.1093/ehjci/jes009 . Singulane CC, Slivnick JA, Addetia K, et al. Prevalence of Right Atrial Impairment and Association with Outcomes in Cardiac Amyloidosis. J Am Soc Echocardiogr. 2022;35(8):829–e8351. 10.1016/j.echo.2022.03.022 . Uzan C, Lairez O, Raud-Raynier P, et al. Right ventricular longitudinal strain: a tool for diagnosis and prognosis in light-chain amyloidosis. Amyloid. 2018;25(1):18–25. 10.1080/13506129.2017.1417121 . Obici L, Kuks JB, Buades J, et al. Recommendations for presymptomatic genetic testing and management of individuals at risk for hereditary transthyretin amyloidosis. Curr Opin Neurol. 2016;29(Supplement 1):S27–35. 10.1097/WCO.0000000000000290 . Ueda M, Sekijima Y, Koike H, et al. Monitoring of asymptomatic family members at risk of hereditary transthyretin amyloidosis for early intervention with disease-modifying therapies. J Neurol Sci. 2020;414:116813. 10.1016/j.jns.2020.116813 . Tables Table 1 General characteristics of the TTR variant Carriers and their matched Controls. Healthy Controls * n = 78 TTR variant Carriers n = 38 Age, y † 52 ± 13 51 ± 11 Females, n (%) 56 (72%) 27 (71%) Body mass index, kg/m 2 24.2 [21.8–27.0] 26.6 [23.6–33.2] Systolic BP, mm Hg 118 [107-122.8] 122 [112–137] Diastolic BP, mm Hg 71 [66–69] 76 [69–82] Race, n (%) White 61 (78%) 27 (71%) Black 1 (1%) 7 (19%) Asian 13 (17%) 2 (5%) Not reported 3 (4%) 2 (5%) Comorbidities, n (%) Hypertension 11 (15%) 7 (18%) Atrial fibrillation - - Diabetes mellitus - - CKD - - NTproBNP, pg/ml ‡ - 53 [28–77] Creatinine, mg/dL - 0.87 [0.76–0.97] eGFR, ml/min/1.73m 2 - 84.0 [74.0–97.0] TTR gene variants, n (%) V30M - 11 (29%) V122I - 9 (24%) T60A - 10 (26%) Others - 8 (21%) * Healthy Controls were matched with the TTR variant carriers group; p > 0.05 for all characteristics except race between these two groups. † Age is reported in mean ± SD, the rest as median [IQR 25th-75th]. ‡ NTproBNP values were available for n = 31 in the TTR variant carriers group. Table 2 Echocardiographic characteristics of the Controls and TTR variant Carriers. Echocardiographic Parameter Controls (n = 78) Median [IQR 25,75] TTR variant Carriers (n = 38) Median [IQR 25,75] P-value IVSDd, cm 0.74 [0.68, 0.80] 0.79 [0.71, 0.93] 0.008 LVPWd, cm 0.77 [0.71, 0.80] 0.79 [0.72, 0.96] 0.040 LVIDd, cm 4.80 [4.60, 5.20] 4.60 [4.30, 5.00] 0.028 Relative wall thickness (RWT) 0.31 [0.29, 0.35] 0.34 [0.30,0.42] 0.005 LV mass index (LVMI), g/m 2 66.21 [59.49, 75.78] 60.20 [54.33, 70.23] 0.032 E/A 1.23 [0.93, 1.57] 1.10 [0.96, 1.30] 0.142 Lateral e', cm/s 10.90 [9.75, 12.98] 10.20 [8.70, 12.10] 0.205 Septal e', cm/s 8.20 [7.40, 10.50] 7.90 [6.40, 9.80] 0.227 E/e' Average 7.18 [6.32, 8.15] 8.20 [6.40, 9.40] 0.040 LA volume index (LAVI), ml/m 2 29.93 [24.65, 37.63] 29.55 [22.75, 34.69] 0.281 LV Global Longitudinal Strain (GLS) -22.40 [-23.87, -21.50] -21.70 [-22.90, -20.85] 0.057 LA reservoir strain (LASr) 38.15 [33.73, 42.38] 29.65 [27.79, 36.78] < 0.001 LA conduit strain (LAScd) -23.70 [-29.08,-18.65] -20.45 [-24.75,-16.80] 0.0238 LA contraction strain (LASct) -11.75 [-18.13,-8.78] -11.00 [-15.05,-7.20] 0.1575 RV free wall longitudinal strain (RV FWLS) -28.20 [-31.90, -24.90] -24.70 [-27.30, -22.30] < 0.001 RA reservoir strain (RASr) 42.10 [35.25, 48.60] 33.50 [25.82, 36.11] < 0.001 RA conduit strain (RAScd) -30.02 [-36.0,-22.9] -21.72 [-29.12, -18.09] < 0.001 RA contraction strain (RASct) -12.32 [-15.80,-7.15] -9.31 [-15.40,-5.41] 0.070 Table 3 Echocardiographic characteristics of the genetic ATTR groups. Echocardiographic Parameter TTR variant Carriers (n = 38) ATTRv-CM patients (n = 43) P-value IVSd, cm 0.79 [0.71, 0.93] 1.60 [1.40, 1.80] < 0.0001 LVPWd, cm 0.79 [0.72, 0.96] 1.50 [1.35, 1.60] < 0.0001 LVIDd, cm 4.60 [4.30, 5.00] 4.16 [3.80, 4.50] 0.0006 Relative wall thickness (RWT) 0.34 [0.30,0.42] 0.70 [0.61,0.85] < 0.0001 LV mass index (LVMI), g/m 2 60.20 [54.33, 70.23] 137.42 [114.11, 156.06] < 0.0001 E/A 1.10 [0.96, 1.30] 1.50 [0.97, 2.05] 0.0090 Lateral e', cm/s 10.20 [8.70, 12.10] 5.95 [5.35, 7.50] < 0.0001 Septal e', cm/s 7.90 [6.40, 9.80] 4.80 [3.71, 5.70] < 0.0001 E/e' Average 8.20 [6.40, 9.40] 15.65 [10.66, 21.85] < 0.0001 LA volume index (LAVI), ml/m 2 29.55 [22.75, 34.69] 45.63 [33.16, 59.04] < 0.0001 LV Global Longitudinal Strain (GLS) -21.70 [-22.90, -20.85] -14.00 [-15.90, -10.60] < 0.0001 LA reservoir strain (LASr) 29.65 [27.79, 36.78] 14.55 [10.25, 22.58] < 0.0001 LA conduit strain (LAScd) -20.45 [-24.75,-16.80] -8.85 [-11.83, -5.6] < 0.0001 LA contraction strain (LASct) -11.00 [-15.05,-7.20] -6.6 [-11.90, -3.98] 0.0087 RV free wall longitudinal strain (RV FWLS) -24.70 [-27.30, -22.30] -20.70 [-24.00, -14.93] 0.0001 RA reservoir strain (RASr) 33.50 [25.82, 36.11] 22.10 [15.50, 30.30] 0.001 RA conduit strain (RAScd) -21.72 [-29.12, -18.09] -11.40 [-16.70,-7.50] < 0.0001 RA contraction strain (RASct) -9.31 [-15.40,-5.41] -9.60 [-14.3, -5.8] 0.7488 Additional Declarations No competing interests reported. Supplementary Files floatimage1.png Graphical Abstract: Subclinical Heart Failure and Clinical Progression in Transthyretin (TTR) Variant Carriers. E/e’ ave, ratio of early diastolic inflow velocity (E) to average early mitral tissue Doppler annular velocity (e’); HF, heart failure; LA, left atrium; LAVI, left atrial volume index; LASr, left atrial reservoir strain; LV GLS, left ventricular global longitudinal strain; RA, right atrium; RASr, right atrial reservoir strain; RV, right ventricle; RVFWSL, right ventricular free wall longitudinal strain; RWT, relative wall thickness; TTR, transthyretin. TTRcarriersSupplements1.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8745379","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588850467,"identity":"511ac0c6-fef1-4c4e-9392-8cd7a237798c","order_by":0,"name":"Gracia Fahed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYDAC5gNsDAxsNmD2ByAXSCUQ0MKWANKSxsDDwMA4gxQth0nQIu/G/OzBh7Lz9vbsZw82fNxjzcDPnmOAV4vhMTZzwxnnbif28OQlNs54ls4g2fOGgJb5DWbSvG23E3gYcswf8xw4zGBwg5AtbezfpP+2nbPn4X9j2AzSYk9Iizwbj5k0Y9sBxh6JHIgWAwkCWgzYeMoke84lJ/bceGPYOONAOo/EmWcF+G1pY98m8aPMzp69P8ew4cMBazn+9uQN+G05gCbAg1c52JYGgkpGwSgYBaNgxAMAEIVFjWd0yZwAAAAASUVORK5CYII=","orcid":"","institution":"Stanford Medicine","correspondingAuthor":true,"prefix":"","firstName":"Gracia","middleName":"","lastName":"Fahed","suffix":""},{"id":588850468,"identity":"680e3a49-e08e-451e-b0d1-83e59a599387","order_by":1,"name":"John I Jimenez","email":"","orcid":"","institution":"Stanford Medicine","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"I","lastName":"Jimenez","suffix":""},{"id":588850469,"identity":"a1d3949b-267d-4599-b848-ef306adfa657","order_by":2,"name":"Shadi P. 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Alexander","email":"","orcid":"","institution":"Stanford Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"M.","lastName":"Alexander","suffix":""}],"badges":[],"createdAt":"2026-01-30 23:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8745379/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8745379/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102462953,"identity":"b2584ab4-c64a-494b-9e38-e00e6d54a07d","added_by":"auto","created_at":"2026-02-12 01:12:36","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":412377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow chart of the study population.\u003c/strong\u003e\u003csup\u003e\u003cbr\u003e\n*\u003c/sup\u003eAll patients satisfying these exclusion criteria had confirmed ATTRv-CM.\u003cbr\u003e\n\u003cem\u003eATTR, amyloid transthyretin; ATTRv, hereditary amyloid transthyretin; CM, cardiomyopathy; EMbx, endomyocardial biopsy; PYP, pyrophosphate scintigraphy.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/b2912e2a41db8fcb286f24de.jpeg"},{"id":102746088,"identity":"aaac2f93-42d7-42e7-b9a3-4a1927ca6452","added_by":"auto","created_at":"2026-02-16 08:55:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":219257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEchocardiographic parameters analysis: TTR variant Carriers vs. Healthy Controls.\u003c/strong\u003e \u003cstrong\u003eA. Effect size forest plot (TTR variant Carriers vs. Controls).\u003c/strong\u003e \u003cbr\u003e\nCliff’s delta interpretation: |δ|\u0026lt;0.33: Negligible (\u0026lt;0.147) to Small effect; 0.33 ≤|δ|\u0026lt;0.474: Medium effect; |δ|≥0.474: Large effect. Cliff's delta ranges from -1 to +1, with values further from zero indicating greater separation between groups. Higher values suggest parameters with stronger discriminatory ability. Strain parameters (LA, RA, RV) demonstrate larger effect sizes compared to conventional structural measures in asymptomatic carriers. \u003cstrong\u003eB. Proportions of individuals meeting abnormal thresholds.\u003c/strong\u003e \u003cbr\u003e\nNS, non-significant (p-value \u0026gt;0.05). \u003cem\u003eE/e’ ave, ratio of early diastolic inflow velocity (E) to average early mitral tissue Doppler annular velocity (e’); HF, heart failure; LA, left atrium; LAVI, left atrial volume index; LASr, left atrial reservoir strain; LV GLS, left ventricular global longitudinal strain; RA, right atrium; RASr, right atrial reservoir strain; RV, right ventricle; RVFWSL, right ventricular free wall longitudinal strain; RWT, relative wall thickness; TTR, transthyretin.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/ab59a3d2af534906cf4cfa19.png"},{"id":102462947,"identity":"bde077b9-5925-4540-a5ab-71b9a88391af","added_by":"auto","created_at":"2026-02-12 01:12:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":219592,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEchocardiographic parameters analysis of the genetic ATTR groups. A. Effect size forest plot (ATTRv-CM patients vs. TTR variant Carriers).\u003c/strong\u003e \u003cbr\u003e\nCliff’s delta interpretation: |δ|\u0026lt;0.33: Negligible (\u0026lt;0.147) to Small effect; 0.33 ≤|δ|\u0026lt;0.474: Medium effect; |δ|≥0.474: Large effect. Cliff's delta ranges from -1 to +1, with values further from zero indicating greater separation between groups. Higher values suggest parameters with stronger discriminatory ability. \u003cstrong\u003eB. Proportions of individuals meeting abnormal thresholds.\u003c/strong\u003e \u003cem\u003eE/e’ ave, ratio of early diastolic inflow velocity (E) to average early mitral tissue Doppler annular velocity (e’); HF, heart failure; LA, left atrium; LAVI, left atrial volume index; LASr, left atrial reservoir strain; LV GLS, left ventricular global longitudinal strain; RA, right atrium; RASr, right atrial reservoir strain; RV, right ventricle; RVFWSL, right ventricular free wall longitudinal strain; RWT, relative wall thickness; TTR, transthyretin.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/d2e4580ceef56903e1ca65a4.png"},{"id":102746495,"identity":"7063d124-d3d0-4ae4-ad0e-fc5c55863f61","added_by":"auto","created_at":"2026-02-16 08:57:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1043642,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultidimensional network of echocardiographic parameters and NT-proBNP in the ATTRv population. \u003c/strong\u003e\u003cem\u003eE/e’ ave, ratio of early diastolic inflow velocity (E) to average early mitral tissue Doppler annular velocity (e’); HF, heart failure; LA, left atrium; LAVI, left atrial volume index; LASr, left atrial reservoir strain; LV GLS, left ventricular global longitudinal strain; RA, right atrium; RASr, right atrial reservoir strain; RV, right ventricle; RVFWSL, right ventricular free wall longitudinal strain; RWT, relative wall thickness; TTR, transthyretin.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/3bc268318787ae1418e452a3.png"},{"id":108181309,"identity":"161ea449-0630-4264-9ef9-6463cd82eb32","added_by":"auto","created_at":"2026-04-30 08:58:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1860677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/598ad651-b854-4563-b76c-6752d0752e13.pdf"},{"id":102462948,"identity":"2aac92fb-bfa1-4849-8f1c-15d036d1c48a","added_by":"auto","created_at":"2026-02-12 01:12:35","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1222540,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical Abstract: Subclinical Heart Failure and Clinical Progression in Transthyretin (TTR) Variant Carriers. \u003c/strong\u003e\u003cem\u003eE/e’ ave, ratio of early diastolic inflow velocity (E) to average early mitral tissue Doppler annular velocity (e’); HF, heart failure; LA, left atrium; LAVI, left atrial volume index; LASr, left atrial reservoir strain; LV GLS, left ventricular global longitudinal strain; RA, right atrium; RASr, right atrial reservoir strain; RV, right ventricle; RVFWSL, right ventricular free wall longitudinal strain; RWT, relative wall thickness; TTR, transthyretin.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/7ea750491976f62a646b51c5.png"},{"id":102462952,"identity":"50d942f8-0b69-45e5-94a5-570660db80fb","added_by":"auto","created_at":"2026-02-12 01:12:36","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":896308,"visible":true,"origin":"","legend":"","description":"","filename":"TTRcarriersSupplements1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8745379/v1/24bf2aec7e7b46e497296ffe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cardiac Strain Imaging in Asymptomatic Carriers of Transthyretin Variants","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSystemic amyloidosis is characterized by misfolded protein accumulation in tissues, eventually impairing organ function.\u003csup\u003e1\u003c/sup\u003e The most common subtypes are light chain (AL) and transthyretin (ATTR) amyloidosis, with the latter being either acquired (wild-type) or inherited (variant).\u003csup\u003e1\u003c/sup\u003e Hereditary/variant transthyretin amyloidosis (ATTRv) remains frequently overlooked in diagnosis, due to variable clinical presentations, ranging from predominantly neurologic to predominantly cardiac.\u003csup\u003e2\u003c/sup\u003e Among those harboring a TTR genetic mutation, some may develop cardiomyopathy during their lifetime, manifesting as symptoms of conduction blocks, arrhythmias, and ultimately heart failure.\u003csup\u003e3\u003c/sup\u003e Cardiac involvement is a significant predictor of poor prognosis, thus early detection and timely intervention are essential.\u003csup\u003e4,5\u003c/sup\u003e Available treatments for hereditary transthyretin cardiomyopathy (ATTRv-CM), although very promising, prevent further TTR deposition in the heart but do not meaningfully reverse existing damage.\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eWith multiple echocardiographic parameters available, determining which features are most useful for detecting early changes in asymptomatic TTR mutation carriers can be helpful for guiding clinical monitoring strategies and resource allocation. While conventional structural measures and diastolic parameters are commonly assessed, the comparative utility of advanced strain imaging techniques in this population remains unclear. \u003csup\u003e1,7\u003c/sup\u003e Echocardiography plays a major role in the non-invasive assessment of ATTR-CM, being a widely available non-invasive imaging tool that can detect structural and functional abnormalities associated with amyloid build-up in the heart.\u003csup\u003e8\u003c/sup\u003e Although echocardiography alone cannot definitely diagnose or distinguish the amyloidosis subtype, it remains an essential component in the diagnosis, prognosis and ongoing management of patients with this condition.\u003csup\u003e8\u003c/sup\u003e In this study, we aim to compare different echocardiographic parameters, particularly strain imaging, in asymptomatic TTR variant carriers, and to investigate whether the relative ranking of echocardiographic features observed in TTR variant carriers is consistent in patients with ATTRv-CM.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e1.\u0026nbsp; \u0026nbsp;Study Population:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Stanford in\u0026nbsp;University Institutional Review Board. Patients referred to the Stanford Amyloid Center for cardiac evaluation from 2010 to 2023 were considered, and only those with a positive ATTR genetic test were included \u003cstrong\u003e(Figure 1)\u003c/strong\u003e. Patients without baseline echocardiograms around the date of the genetic test were excluded. Two groups of patients were then identified. The first group included TTR variant carriers, defined as those with no echocardiographic evidence of ATTR-CM, as previously outlined,\u003csup\u003e8,9\u003c/sup\u003e and judged by amyloidosis experts; and/or negative technetium pyrophosphate (PYP) scan at the time of the genetic testing; all with normal NT-proBNP and troponin levels. Of \u0026nbsp;note, not all individuals in this group had PYP scans, which were performed only when echocardiograms and the clinical picture were judged suspicious of ATTRv-CM. TTR variant carriers were matched 2:1 for age, sex, and comorbidities with healthy controls identified from the Stanford Healthy Cohort database. A second group consisted of ATTRv-CM patients with confirmed cardiac involvement by either a PYP scan or endomyocardial biopsy, as recommended by national guidelines.\u003csup\u003e8\u003c/sup\u003e To eliminate confounders and advanced cardiac involvement, we excluded patients with prior myocardial infarction, atrial fibrillation/flutter (at the time of echocardiography), and ejection fraction less than 50%. None met these exclusion criteria among the TTR variant carriers group; however, we excluded one patient who was found to have hypertensive cardiomyopathy with high filling pressures \u003cstrong\u003e(Figure 1)\u003c/strong\u003e. Baseline demographic, clinical, and imaging data around the date of the genetic test were derived from an electronic chart review.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. \u0026nbsp; \u0026nbsp; \u0026nbsp;Echocardiography\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline echocardiograms were re-analyzed by the Stanford Cardiovascular Institute Imaging Core Laboratory. Echocardiographic measurements, chamber quantification, assessment of diastolic function, and strain analysis were performed by experienced echocardiography personnel following the American Society of Echocardiography recommendations, and blinded to patients’ clinical data.\u003csup\u003e10\u003c/sup\u003e Measured echocardiographic parameters included wall thickness, relative wall thickness (RWT), left ventricular (LV) mass using the linear method and scaled to body surface area (LVMI), left atrial volume using the biplane Simpson method and scaled to body surface area (LAVI), septal and lateral early mitral tissue doppler annular velocity (e’), early and late diastolic peak velocities of mitral inflow ratio (E/A), the ratio of early diastolic inflow velocity to e’ (E/e’) and right ventricular (RV) systolic pressure (RVSP). Strain analyses were performed using TomTec software (TTA2.51) and included measurements of LV global longitudinal strain (LV GLS), left atrial reservoir strain (LASr), left atrial conduit strain (LAScd), left atrial contraction strain (LASct), RV free wall longitudinal strain (RV FWLS), right atrial reservoir strain (RASr), right atrial conduit strain (RAScd), right atrial contraction strain (RASct).\u0026nbsp;Low quality images or images with foreshortened LV or RV were excluded from analysis.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Statistical Analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe characteristics of the study population were summarized using descriptive statistics. Continuous variables were reported as means ± standard deviation or medians [interquartile range (IQR) 25\u003csup\u003eth\u003c/sup\u003e -75\u003csup\u003eth\u003c/sup\u003e] and compared using the non-parametric Mann-Whitney U test. Categorical variables were reported as frequencies (percentages) and compared using Fisher exact and Chi-square tests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo report the estimation of the effect size of the differences between two groups, we adopted the non-parametric Cliff’s delta test. Cliff’s delta calculates the probability that a randomly selected value from one group will be greater than a randomly selected value from another group, minus the reverse probability.\u003csup\u003e11\u003c/sup\u003e In other words, Cliff’s delta can be interpreted as the degree of distributional non-overlap between two distributions. One major advantage of Cliff’s delta is that it considers the entire distribution rather than simply estimating the magnitude of the effect for those in the center. Cliff’s delta ranges from -1 to 1, where a value of 0 indicates no difference between the two groups.\u003csup\u003e11\u003c/sup\u003e Positive values indicate that the first group tends to have higher values than the second group, while negative values indicate the opposite. Cliff’s delta was used to compare the TTR variant carriers distributions relative to controls, and the ATTRv-CM group relative to the TTR variant carriers. Since the TTR variant carriers group is inherently younger in our population than the ATTRv-CM, the main analysis excluded echocardiography parameters (septal/lateral e’, E/A, E/e’) known to be heavily affected by age,\u003csup\u003e12\u003c/sup\u003e as it will influence the comparison, however, the full analysis was shown in the supplements. For all tested hypotheses, the significance level of 0.05 was considered. All analyses were done using Python version 3.9.6.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo study the relationship between the different imaging parameters and understand their connectivity, a network from the major echocardiographic variables was developed, with connections weighted by the maximal information coefficient (MIC).\u003csup\u003e13\u003c/sup\u003e MIC quantifies the strength of association, varying from 0 (no statistical relationship) to 1 (noise-free connection). We chose MIC over alternative measures of association because it can detect both linear and non-linear associations, as well as assign equal scores to similarly noisy relationships of diverse types.\u003csup\u003e13\u003c/sup\u003eWe also used the Eigenvector centrality, which assigns relative scores to all nodes in the network and determines the most influential parameters in the network.\u003csup\u003e14\u003c/sup\u003e MICs and Eigenvector centrality scores were computed using the Python minepy library and MIC-network was visualized using networkX3.1. \u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. Baseline characteristics of the TTR variant carriers:\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of the study groups are reported in \u003cstrong\u003eTable 1\u003c/strong\u003e. Among the genetic ATTR population reviewed, 38 carriers had TTR variants without evidence of cardiomyopathy at the time of referral. PYP scans, all with negative findings, were performed in 10 (26%) of those carriers in addition to the echocardiography. Their mean age was 51±11 years, 71% were female, 71% were white, and 18% had hypertension. Median NT-proBNP was normal at 53 pg/ml [IQR 28-77]. The most common variants were V30M (29%), T60A (26%), and V122I (24%). Neurologic symptoms were prevalent in 13 individuals, secondary to peripheral neuropathy (10/38), carpal tunnel syndrome (5/38), and/or spinal stenosis (1/38). No patients were on ATTR therapies (stabilizers or silencers) at the time of their baseline echocardiogram.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. TTR variant carriers vs. healthy Controls\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe TTR variant carriers had normal median septal (IVSd) and posterior (LVPWd) wall thicknesses at 0.79 [0.71, 0.93] and 0.79 [0.72, 0.96] cm respectively, with a median RWT of 0.34 [0.30, 0.42] and LVMI of 60.20 [54.33, 70.23] g/m\u003csup\u003e2\u003c/sup\u003e \u003cstrong\u003e(Table 2)\u003c/strong\u003e. Diastolic function parameters showed median septal and lateral e' values of 7.9 [6.4, 9.8] and 10.2 [8.7-12.1] cm/s, respectively, with a median E/e’ of 8.20 [6.40, 9.40], and a median LAVI of 29.55 [22.75, 34.69] ml/m\u003csup\u003e2\u003c/sup\u003e. Strain analysis revealed a median LV GLS of -21.70 % [-22.90, -20.85], median LASr of 29.65 %[27.79, 36.78], median RV FWLS of -24.70% [-27.30, -22.30] and median RASr of 33.50 % [25.82, 36.11]. Compared to controls, the TTR variant carriers had higher wall thickness measures and RWT, but lower LVMI (p\u0026lt;0.05). Notably, the distribution of the non-routinely measured LAS, RV FWLS, and RAS were the most significantly different from healthy controls (p\u0026lt;0.001) \u003cstrong\u003e(Table 2)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe magnitude of the difference between the TTR variant carriers and the healthy controls was quantified using Cliff’s delta (95% CI) as a measure of effect size \u003cstrong\u003e(Figure 2A)\u003c/strong\u003e.Structural parameters and diastolic function indices had negligible to small differences, while the medium to largest effect sizes were observed for LASr, RASr, RAScd and RV FWLS. A sensitivity analysis was performed on TTR variant carriers without hypertension (\u003cstrong\u003eSupplementary Figure 1A\u003c/strong\u003e) as well as on carriers with and without baseline PYP scans (\u003cstrong\u003eSupplementary Figure 1B, Supplementary Figure 1C\u003c/strong\u003e); compared to their specific 2:1 matched controls. Some experts have suggested starting ATTR screening 10 years before the predicted age of onset of disease, and although controls are matched for age, we have also performed a sensitivity analysis of individuals \u0026gt;40 years old \u003cstrong\u003e(Supplementary Figure 1D)\u003c/strong\u003e; all yielding similar results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe proportion of individuals with values above or below conventional echocardiography reference limits is presented in \u003cstrong\u003eFigure 2B\u003c/strong\u003e. There was a trend towards higher proportions of abnormalities in the TTR variant carriers for most measures. Statistically significant differences were observed between controls and the TTR carriers for RWT \u0026gt;0.42 (0% vs. 16%), septal e' \u0026lt;7 cm/s (17% vs. 35%), |RV FWSL| \u0026lt;20% (1% vs. 13%), and |RASr| \u0026lt;25% (1% vs 22%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Genetic ATTR: a spectrum of abnormalities\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo better understand the complete spectrum of abnormalities in genetic ATTR, we have also explored a cohort of ATTRv-CM patients. \u0026nbsp;The ATTRv-CM group (n=43) was older than the TTR variant carriers group, with a mean age of 68±10 years, and had more male (79%) and Black race (37%) representation \u003cstrong\u003e(Supplementary Table 1)\u003c/strong\u003e. Most patients exhibited symptoms corresponding to NYHA class II (51%), while the remaining patients were distributed between NYHA class I (28%) and class III (21%). According to the Columbia ATTR-CM disease staging, the distribution of early, intermediate, and late ATTRv-CM was 65%, 26%, and 9%, respectively. Comorbidities included hypertension (51%), a history of atrial fibrillation (16%), diabetes mellitus type II (14%), and chronic kidney disease (14%). Their median NT-proBNP was 812 pg/ml [31-1630].\u003c/p\u003e\n\u003cp\u003eAs expected, the ATTRv-CM cohort differed substantially from the TTR variant carriers in all the measured echocardiographic indices \u003cstrong\u003e(Table 3)\u003c/strong\u003e. Wall thickness measures were abnormally high, and there was evident LV hypertrophy, LA enlargement, and elevated filling pressures. Strain analysis indicated abnormal left heart strains and borderline abnormal readings for right chamber strains (\u003cstrong\u003eTable 3\u003c/strong\u003e). Apical sparing of LV longitudinal strain, known as the “cherry-on-top” pattern, was observed in n=21/43 (49%) of the patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompared with the TTR variant carriers, both structural and functional parameters of the ATTRv-CM group had large effect sizes of their distributions, with Cliff’s delta exceeding 0.9 for IVSd, LVPWd, RWT, and LV GLS (\u003cstrong\u003eFigure 3A)\u003c/strong\u003e.We excluded from this comparison diastolic function parameters as they change substantially with age and would not provide a fair comparison given our ATTRv-CM cohort is more than 10 years older than the TTR variant carriers group. However, the full analysis is provided in \u003cstrong\u003eSupplementary Figure 2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThe proportion of individuals with ATTRv-CM meeting the conventional echocardiographic thresholds of normality was significantly higher than that of the TTR variant carriers for all structural and functional parameters (\u003cstrong\u003eFigure 3B)\u003c/strong\u003e. The most commonly observed abnormalities among ATTRv-CM patients was for RWT\u0026gt;0.42 (95%) and lateral e’\u0026lt;10 cm/s (93%), followed by septal e’\u0026lt;7cm/s (88%) and LASr\u0026lt;25% (84%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo better understand the interrelationships between all these various echocardiography parameters\u0026nbsp;and identify the strongest relationships that may reflect underlying cardiac involvement, we visualized an MIC network including major echocardiographic indices and NT-proBNP (\u003cstrong\u003eFigure 4, Supplementary Figure 3)\u003c/strong\u003e. A strong relationship between structural and functional parameters was evident, with LVMI being at the center, strongly associated with RWT (MIC 0.92), LV GLS (MIC 0.69), septal/lateral e’ (MIC 0.67), and with E/e’ (MIC 0.63). Another robust association was observed between RWT and LV GLS (MIC 0.81), and between RWT and LASr (MIC 0.65). NT-proBNP was moderately correlated to the echocardiographic indices, notably with RASr (MIC 0.60), LASr (MIC 0.53) and E/e’ (MIC 0.53). LVMI and RWT had the highest Eigenvector centrality compared with diastolic parameters and strain measures, reflecting their central role in the network and their importance in characterizing cardiac involvement in ATTRv-CM.\u003csup\u003e13,14\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. Clinical progression from TTR variant carriers to ATTRv-CM\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCardiac follow-up information was present in 26/38 (68%) TTR variant carriers. Aside from echocardiography, 18/26 (69%) had performed PYP scans. At our institution, follow-up frequency with cardiac biomarkers, electrocardiography, and echocardiography, was equally divided between either every 3-6 months, every year, or every 2-3 years, depending on clinician judgment of each case.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter a median follow-up of 3.22 years, 4 (15%) individuals developed ATTRv-CM and cardiac involvement was confirmed by either endomyocardial biopsy (2/4) or PYP scan (2/4). The mean age was 64 ±10 years, 3/4 were females. All four individuals had the T60A mutation (out of 10 total Thr60Ala carriers). Three of them had neurological symptoms/involvement (bilateral CPS and/or polyneuropathy) prior to their baseline cardiac visit.Two had a baseline RWT\u0026gt;0.42 without a prior history of hypertension. None of the patients who progressed had abnormal diastolic function nor abnormal left heart strains, except one with borderline LV GLS at -17.6%.\u0026nbsp;All four had their baseline |RV FWSL| \u0026lt;25%. The distribution of baseline echocardiography measures of individuals who progressed to ATTRv-CM and those who did not are both presented in \u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e. To note that the comparison has unbalanced sample sizes and is not powered to reach significance or draw conclusions, and follow-up echocardiograms were not available for analysis.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we compared the sensitivity of different echocardiographic parameters in asymptomatic TTR variant carriers to determine which features show the most pronounced differences from healthy controls. While we observed minor differences in standard echocardiographic parameters (e.g. wall thicknesses)\u0026nbsp;between TTR variant carriers and healthy controls, these variations are subtle, with values largely remaining within normal ranges. This highlights a critical challenge for echocardiography as a screening tool in this population—single metrics with fixed thresholds show limited discriminatory power. However, when examining effect sizes rather than simple statistical differences, the most pronounced differences from controls were found in strain parameters, particularly left atrial strain (LASr) and right heart strain measures (RASr, RV FWSL). These findings suggest that while conventional structural parameters show statistically significant differences, advanced functional imaging with strain analysis may offer greater sensitivity for characterizing early cardiac involvement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe better discriminatory ability of strain parameters compared to conventional structural measures likely reflects several pathophysiological factors. Myocardial strain represents direct assessment of myocardial deformation and may detect early functional impairment before gross structural changes become apparent. Furthermore, amyloid deposition may initially affect myocardial contractility before causing measurable increases in wall thickness. The sensitivity of atrial strain parameters may reflect the vulnerability of atrial myocardium to early infiltration, while RV strain abnormalities may indicate early involvement of this often-overlooked chamber in amyloid cardiomyopathy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;With several \u0026nbsp;disease-modifying therapies now available for ATTR-CM, understanding the full phenotypic spectrum of amyloidosis presentation across subgroups is critical to scaling efforts to better diagnose and optimally treat ATTR-CM.\u003csup\u003e8\u003c/sup\u003e While most studies have focused on characterizing abnormalities in overt ATTR-CM, few have investigated TTR variant carriers.\u003csup\u003e15,16\u003c/sup\u003eThe increasing availability of genetic testing has led to a growing identification of individuals carrying pathogenic/likely pathogenic TTR mutations, without evidence of cardiac involvement.\u003csup\u003e7\u003c/sup\u003e This cohort presents a unique set of challenges, characterized by the complex interplay between genetics and disease manifestation.\u003csup\u003e7\u003c/sup\u003e The TTR gene has over 130 known pathogenic variants, each with its own pattern of expressivity and penetrance. Different mutations can lead to distinct clinical presentations.\u003csup\u003e2\u003c/sup\u003e For instance, the Val122Ile mutation is the primary cause of late-onset ATTR-CM in the United States. In contrast, the Thr60Ala mutation typically results in early-onset ATTR-CM. The Val30Met mutation presents differently based on age of onset: early-onset cases primarily manifest as polyneuropathy, while late-onset cases often have cardiac involvement.\u003csup\u003e2\u003c/sup\u003e While previous observational surveys (e.g. THAOS study) have described the natural progression of TTR variant carriers, these studies relied solely on symptom occurrence to describe the transition to ATTRv amyloidosis.\u003csup\u003e15\u003c/sup\u003eMoreover, the time-to-HF symptoms and prognosis of asymptomatic patients with positive evidence of ATTR-CM on imaging has been also described.\u003csup\u003e16\u003c/sup\u003e However, longitudinal studies focusing on the natural progression of TTR variant carriers with negative cardiac imaging have not been conducted, and are still critically needed to guide patient counseling and management. In addition, the exact criteria for classifying an individual as cardiac “phenotype-negative” remains challenging and subject to debate. While more specific and likely sensitive diagnostic modalities such as PYP scans do exist, their application for screening purposes is not universal, due to limited availability and cost-effectiveness.\u003csup\u003e17,18\u003c/sup\u003e Consequently, many genetic carriers undergo evaluation primarily through echocardiography, electrocardiography, and clinical tests, with more sensitive diagnostic modalities reserved for cases with concerning findings.\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Echocardiography offers a rich array of features, providing comprehensive insights into the structure and function of the heart.\u003csup\u003e19\u003c/sup\u003e In this study, the MIC network demonstrated how most echocardiographic features are interconnected along the spectrum of genetic ATTR. The centrality of the structural parameters of remodeling (RWT) and hypertrophy (LVMI) to diastolic and strain function, and to NT-proBNP, suggest a complex but synergistic relationship between cardiac morphology, function, and physiology. Due to this intertwined nature, many features will have comparable effect sizes for differentiating overt ATTR-CM cases. This finding was evident in the ATTRv-CM cohort with preserved EF, where classical echocardiography findings of increased wall thickness, abnormal strain, and diastolic dysfunction were observed in conjunction, and had large effect sizes. These observations were less evident in the TTR variant carriers, where the differences compared to controls were mostly subtle, and might be missed by routine echocardiography of standard parameters, as values largely remained within the normal range in our population. These findings highlight the opportunity for new diagnostic scores that would explore different combination of structural and functional parameters with various weights and more sensitive thresholds.\u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eSensitive functional parameters such as LV myocardial strain have been proposed to detect early cardiac involvement in ATTR amyloidosis, and an abnormal value is considered a red flag for ATTR-CM.\u003csup\u003e9\u003c/sup\u003e LV regional strain patterns (e.g. the cherry-on-top) were also described, with unclear diagnostic specificity for amyloidosis in the literature.\u003csup\u003e9,21–23\u003c/sup\u003e In our cohort, while none of the controls or the TTR variant carriers had apical sparing pattern, around half of those with ATTRv-CM did exhibit this pattern. Beyond LV strain, our study highlighted the additional importance of atrial and RV strains in this population. Most recently, LA strain has gained considerable attention in the diagnosis and grading of LV diastolic dysfunction, with mounting evidence supporting its eventual incorporation into diastolic assessment guidelines.\u003csup\u003e24–26\u003c/sup\u003e In ATTR-CM, it is still unknown whether the observed worse LA function in ATTR-CM is solely a consequence of LV dysfunction as opposed to reflecting a true infiltrative atrial myopathy.\u003csup\u003e27–30\u003c/sup\u003eRegarding the right heart, previous reports focused on patients with cardiac AL amyloidosis,\u003csup\u003e31–35\u003c/sup\u003e moreso than ATTR-CM,\u003csup\u003e36\u003c/sup\u003e demonstrating worse prognosis with the presence of RA or RV dysfunction, even in the absence of pulmonary hypertension or clear left heart involvement.\u0026nbsp;Moreover, Uzan et al. have suggested using RV FWLS, with an optimal cut-off of -21%, to discriminate AL amyloidosis from hypertension or hypertrophic cardiomyopathy.\u003csup\u003e37\u003c/sup\u003e Along with these findings, our analysis of the ATTRv-CM group confirmed previous observations, showing that impaired strain analysis could be present not only in the LV, but also in all four cardiac chambers. Another distinctive aspect of our study was our investigation of TTR variant carriers, which revealed that although their LV GLS was similar to controls, they showed significantly worse strain in the atria (LASr, RASr) and right ventricle (RV FWLS). Whether routine evaluation of left atrial and right heart strains plays an important role in routine echocardiography screening for early CM in TTR carriers, is a question raised by our findings and still requires validation. Future studies may also help establish appropriate cut-off limits and identify which combinations of abnormal parameters could be most appropriate for risk-stratification or early detection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFollow-up and future perspectives:\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eWhile not the main objective of our analysis, this study also highlights the importance of close follow-up of TTR mutation carriers. Despite a small sample size and a relatively short follow-up time of 3.22 years, 15% of ATTR G+/P- progressed to ATTR-CM in our population. The cardiac penetrance of the Thr60Ala mutation was 25%. This progression rate warrants consideration in the management of these at-risk individuals, given the lack of standardized protocols for follow-up timing and imaging modalities.\u003csup\u003e7,38,39\u003c/sup\u003e Current practices vary widely, with follow-up intervals ranging from every few months to every 5 years, largely dictated by individual providers or judgment or patient ability. Moreover, this variability is compounded by the limited availability and financial burden of advanced screening and diagnostic tools.\u003csup\u003e18\u003c/sup\u003e Reliance on echocardiography alone for follow-up presents its own challenges. While widely accessible, routine echocardiographic assessment is subject to reader variability and may lack the sensitivity required to detect early-stage disease.\u0026nbsp;Interestingly, our cohort who developed ATTRv-CM did not exhibit significant baseline structural or functional abnormalities, except for lower right heart strain (all had |RVFWLS| \u0026lt;25%) that could not be quantified due to the lack of validated reference values. These observations call for larger and longer longitudinal studies to elucidate whether patients with baseline cardiac abnormalities, or stage B HF, warrant more frequent monitoring and with what modalities. When both structural and functional changes are present in imaging, amyloid deposition is already present. However, it is unknown if there is a role for prevention by initiating therapy for those with earlier presentations on imaging.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom an implementation perspective, our findings highlight important challenges for using echocardiography as a standalone screening tool in asymptomatic genetic carriers. The subtle nature of differences and substantial overlap of individual parameters with normal ranges suggest that fixed thresholds for single metrics have limited utility. In the management of asymptomatic TTR carriers, genetic screening remains the primary diagnostic modality, with echocardiography serving to characterize the degree of early cardiac involvement rather than functioning as a screening test. This distinction is critical for appropriate resource allocation and clinical workflow design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLimitations of this study include its retrospective nature and the relatively small TTR variant carriers sample size, particularly when stratified per specific TTR mutation. Another limitation is the small proportion of individuals with baseline PYP scans. While echocardiography parameters are subject to variable measurement practices, these were minimized by our experienced Core Laboratory professionals who followed guideline-recommended measurement practices. Longitudinal studies with larger cohorts and complete multimodal imaging are indeed needed in TTR carriers to validate our findings and influence management in this challenging population.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn our study, asymptomatic TTR variant carriers show subtle differences in echocardiographic parameters compared to healthy controls, with LA, RA, and RV strain measures exhibiting the largest effect sizes. While echocardiography remains valuable for assessing early cardiac changes, with particular attention to right heart and atrial function, our findings highlight significant challenges for using echo as a screening tool in this population. Single metrics with fixed thresholds have limited discriminatory power given the subtle nature of early changes and considerable overlap with normal ranges. Future implementation strategies will likely require development of integrated tools that combine multiple parameters rather than relying on individual thresholds. In asymptomatic genetic carriers, genetic screening remains the primary diagnostic approach, with echocardiography serving to characterize early disease rather than as a standalone screening modality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLight chain amyloidosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eATTR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransthyretin amyloidosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eATTRv\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHereditary/Variant transthyretin amyloidosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eATTRv-CM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHereditary transthyretin cardiomyopathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCPS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCarpal tunnel syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEjection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eE/A\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEarly to late diastolic peak velocities of mitral inflow ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eE/e'\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRatio of early diastolic inflow velocity to early mitral tissue Doppler annular velocity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGLS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal longitudinal strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIVSd\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterventricular septal thickness at end-diastole\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft atrium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLAVI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft atrial volume index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLAScd\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft atrial conduit strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLASct\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft atrial contraction strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLASr\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft atrial reservoir strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft ventricle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLVMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft ventricular mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLVPWd\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft ventricular posterior wall thickness at end-diastole\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMIC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximal information coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNT-proBNP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-terminal pro-B-type natriuretic peptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNYHA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNew York Heart Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePYP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTechnetium pyrophosphate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight atrium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRAScd\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight atrial conduit strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRASct\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight atrial contraction strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRASr\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight atrial reservoir strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight ventricle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRV FWLS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight ventricular free wall longitudinal strain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRVSP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRight ventricular systolic pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRWT\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRelative wall thickness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTTR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransthyretin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eV30M\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eValine 30 Methionine mutation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eT60A\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThreonine 60 Alanine mutation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eV122I\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eValine 122 Isoleucine mutation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosures:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKMA has received consulting fees from Arbor Biotechnologies, Alexion, Alnylam, Novo Nordisk, and Pfizer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRMW has received consulting fees from Pfizer, Alnylam, AstraZeneca, Alexion, Novo Nordisk, and BridgeBio.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All other authors have no disclosures/COI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding support:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Stanford University Institutional Review Board (IRB). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. All participants provided written informed consent prior to participation in this study. For retrospective data analysis, informed consent was waived by the Stanford University Institutional Review Board in accordance with institutional guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRMW has received consulting fees from Pfizer, Alnylam, AstraZeneca, Alexion, and Novo Nordisk. All other authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFH and KMA contributed equally to this work. GF, FH, KMA, NHL, JIJ and SPB contributed to study conception and design, data acquisition, analysis and interpretation, and manuscript preparation. NHL, YB, LC, XT, PC, MS, RMW, KMA and FH contributed to data interpretation and critical manuscript revision. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGertz MA, Dispenzieri A. Systemic Amyloidosis Recognition, Prognosis, and Therapy: A Systematic Review. JAMA. 2020;324(1):79\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2020.5493\u003c/span\u003e\u003cspan address=\"10.1001/jama.2020.5493\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManganelli F, Fabrizi GM, Luigetti M, Mandich P, Mazzeo A, Pareyson D. Hereditary transthyretin amyloidosis overview. Neurol Sci. 2022;43(Suppl 2):595\u0026ndash;604. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10072-020-04889-2\u003c/span\u003e\u003cspan address=\"10.1007/s10072-020-04889-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlaassen SHC, Tromp J, Nienhuis HLA, et al. Frequency of and Prognostic Significance of Cardiac Involvement at Presentation in Hereditary Transthyretin-Derived Amyloidosis and the Value of N-Terminal Pro-B-Type Natriuretic Peptide. Am J Cardiol. 2018;121(1):107\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amjcard.2017.09.029\u003c/span\u003e\u003cspan address=\"10.1016/j.amjcard.2017.09.029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdams D, Algalarrondo V, Polydefkis M, Sarswat N, Slama MS, Nativi-Nicolau J. Expert opinion on monitoring symptomatic hereditary transthyretin-mediated amyloidosis and assessment of disease progression. Orphanet J Rare Dis. 2021;16(1):411. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13023-021-01960-9\u003c/span\u003e\u003cspan address=\"10.1186/s13023-021-01960-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGillmore JD, Damy T, Fontana M, et al. A new staging system for cardiac transthyretin amyloidosis. Eur Heart J. 2018;39(30):2799\u0026ndash;806. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/eurheartj/ehx589\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehx589\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBampatsias D, Wardhere A, Maurer MS. Treatment of transthyretin cardiac amyloidosis. Curr Opin Cardiol. 2024;39(5):407\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/HCO.0000000000001156\u003c/span\u003e\u003cspan address=\"10.1097/HCO.0000000000001156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConcei\u0026ccedil;\u0026atilde;o I, Damy T, Romero M, et al. Early diagnosis of ATTR amyloidosis through targeted follow-up of identified carriers of TTR gene mutations. Amyloid. 2019;26(1):3\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13506129.2018.1556156\u003c/span\u003e\u003cspan address=\"10.1080/13506129.2018.1556156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia-Pavia P, Rapezzi C, Adler Y, et al. Diagnosis and treatment of cardiac amyloidosis: a position statement of the ESC Working Group on Myocardial and Pericardial Diseases. Eur Heart J. 2021;42(16):1554\u0026ndash;68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/eurheartj/ehab072\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehab072\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCuddy SAM, Chetrit M, Jankowski M, et al. Practical Points for Echocardiography in Cardiac Amyloidosis. J Am Soc Echocardiogr. 2022;35(9):A31\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.echo.2022.06.006\u003c/span\u003e\u003cspan address=\"10.1016/j.echo.2022.06.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang RM, Badano LP, Mor-Avi V, et al. Recommendations for Cardiac Chamber Quantification by Echocardiography in Adults: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16(3):233\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ehjci/jev014\u003c/span\u003e\u003cspan address=\"10.1093/ehjci/jev014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeissel K, Yao E. Using Cliff\u0026rsquo;s Delta as a Non-Parametric Effect Size Measure: An Accessible Web App and R Tutorial. Published online January. 2024;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7275/PARE.1977\u003c/span\u003e\u003cspan address=\"10.7275/PARE.1977\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiyoshi T, Addetia K, Citro R, et al. Left Ventricular Diastolic Function in Healthy Adult Individuals: Results of the World Alliance Societies of Echocardiography Normal Values Study. J Am Soc Echocardiogr. 2020;33(10):1223\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.echo.2020.06.008\u003c/span\u003e\u003cspan address=\"10.1016/j.echo.2020.06.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReshef DN, Reshef YA, Finucane HK, et al. Detecting Novel Associations in Large Data Sets. Science. 2011;334(6062):1518\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.1205438\u003c/span\u003e\u003cspan address=\"10.1126/science.1205438\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonacich P. Some unique properties of eigenvector centrality. Social Networks. 2007;29(4):555\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.socnet.2007.04.002\u003c/span\u003e\u003cspan address=\"10.1016/j.socnet.2007.04.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoelho T, Concei\u0026ccedil;\u0026atilde;o I, Waddington-Cruz M, et al. A natural history analysis of asymptomatic TTR gene carriers as they develop symptomatic transthyretin amyloidosis in the Transthyretin Amyloidosis Outcomes Survey (THAOS). Amyloid. 2022;29(4):228\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13506129.2022.2070470\u003c/span\u003e\u003cspan address=\"10.1080/13506129.2022.2070470\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonzalez-Lopez E, Escobar-Lopez L, Obici L, et al. Prognosis of Transthyretin Cardiac Amyloidosis Without Heart Failure Symptoms. JACC CardioOncol. 2022;4(4):442\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jaccao.2022.07.007\u003c/span\u003e\u003cspan address=\"10.1016/j.jaccao.2022.07.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaurer MS, Bokhari S, Damy T, et al. Expert Consensus Recommendations for the Suspicion and Diagnosis of Transthyretin Cardiac Amyloidosis. Circ Heart Fail. 2019;12(9):e006075. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCHEARTFAILURE.119.006075\u003c/span\u003e\u003cspan address=\"10.1161/CIRCHEARTFAILURE.119.006075\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBourque JM, Schepart A, Bhambri R, et al. Temporal Trends in Diagnostic Testing Patterns for Wild-Type Transthyretin Amyloid Cardiomyopathy in the Medicare Fee-for-Service Population. Am J Cardiol. 2022;167:98\u0026ndash;103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amjcard.2021.11.048\u003c/span\u003e\u003cspan address=\"10.1016/j.amjcard.2021.11.048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang S, Liu Z, Li Q, He W, Huang H. Advance of echocardiography in cardiac amyloidosis. Heart Fail Rev. 2023;28(6):1345\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10741-023-10332-3\u003c/span\u003e\u003cspan address=\"10.1007/s10741-023-10332-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies DR, Redfield MM, Scott CG, et al. A Simple Score to Identify Increased Risk of Transthyretin Amyloid Cardiomyopathy in Heart Failure With Preserved Ejection Fraction. JAMA Cardiol. 2022;7(10):1036\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamacardio.2022.1781\u003c/span\u003e\u003cspan address=\"10.1001/jamacardio.2022.1781\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWali E, Gruca M, Singulane C, et al. How Often Does Apical Sparing of Longitudinal Strain Indicate the Presence of Cardiac Amyloidosis? Am J Cardiol. 2023;202:12\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amjcard.2023.06.022\u003c/span\u003e\u003cspan address=\"10.1016/j.amjcard.2023.06.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCotella J, Randazzo M, Maurer MS, et al. Limitations of apical sparing pattern in cardiac amyloidosis: a multicentre echocardiographic study. Eur Heart J Cardiovasc Imaging. 2024;25(6):754\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ehjci/jeae021\u003c/span\u003e\u003cspan address=\"10.1093/ehjci/jeae021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller WL. Echocardiographic Longitudinal Strain Pattern of Apical Sparing and the Search for Cardiac Amyloidosis: Importance of Clinical Context or Not All That Sparkles is Gold. Am J Cardiol. 2023;202:235\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amjcard.2023.06.076\u003c/span\u003e\u003cspan address=\"10.1016/j.amjcard.2023.06.076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNtalianis E, Sabovčik F, Cauwenberghs N, et al. Unsupervised Time-Series Clustering of Left Atrial Strain for Cardiovascular Risk Assessment. J Am Soc Echocardiogr. 2023;36(7):778\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.echo.2023.03.007\u003c/span\u003e\u003cspan address=\"10.1016/j.echo.2023.03.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagueh SF, Khan SU. Left Atrial Strain for Assessment of Left Ventricular Diastolic Function: Focus on Populations With Normal LVEF. JACC Cardiovasc Imaging. 2023;16(5):691\u0026ndash;707. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcmg.2022.10.011\u003c/span\u003e\u003cspan address=\"10.1016/j.jcmg.2022.10.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh A, Addetia K, Maffessanti F, Mor-Avi V, Lang RM. LA Strain for Categorization of LV Diastolic Dysfunction. JACC Cardiovasc Imaging. 2017;10(7):735\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcmg.2016.08.014\u003c/span\u003e\u003cspan address=\"10.1016/j.jcmg.2016.08.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrand A, Frumkin D, H\u0026uuml;bscher A, et al. Phasic left atrial strain analysis to discriminate cardiac amyloidosis in patients with unclear thick heart pathology. Eur Heart J Cardiovasc Imaging. 2021;22(6):680\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ehjci/jeaa043\u003c/span\u003e\u003cspan address=\"10.1093/ehjci/jeaa043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUsuku H, Takashio S, Yamamoto E, et al. Prognostic value of right ventricular global longitudinal strain in transthyretin amyloid cardiomyopathy. J Cardiol. 2022;80(1):56\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jjcc.2022.02.010\u003c/span\u003e\u003cspan address=\"10.1016/j.jjcc.2022.02.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVergaro G, Aimo A, Rapezzi C, et al. Atrial amyloidosis: mechanisms and clinical manifestations. Eur J Heart Fail. 2022;24(11):2019\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ejhf.2650\u003c/span\u003e\u003cspan address=\"10.1002/ejhf.2650\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTremblay-Gravel M, Ichimura K, Picard K, et al. Intrinsic Atrial Myopathy Precedes Left Ventricular Dysfunction and Predicts Atrial Fibrillation in Lamin A/C Cardiomyopathy. Circ Genom Precis Med. 2023;16(1):e003480. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCGEN.121.003480\u003c/span\u003e\u003cspan address=\"10.1161/CIRCGEN.121.003480\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNemes A, F\u0026ouml;lde\u0026aacute;k D, Domsik P, et al. Right Atrial Deformation Analysis in Cardiac Amyloidosis - Results from the Three-Dimensional Speckle-Tracking Echocardiographic MAGYAR-Path Study. Arq Bras Cardiol. 2018;111(3):384\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5935/abc.20180150\u003c/span\u003e\u003cspan address=\"10.5935/abc.20180150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTjahjadi C, Fortuni F, Stassen J, et al. Prognostic Implications of Right Ventricular Systolic Dysfunction in Cardiac Amyloidosis. Am J Cardiol. 2022;173:120\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amjcard.2022.02.048\u003c/span\u003e\u003cspan address=\"10.1016/j.amjcard.2022.02.048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTana M, Tana C, Palmiero G, et al. Imaging findings of right cardiac amyloidosis: impact on prognosis and clinical course. J Ultrasound. 2023;26(3):605\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40477-023-00789-1\u003c/span\u003e\u003cspan address=\"10.1007/s40477-023-00789-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhio S, Perlini S, Palladini G, et al. Importance of the echocardiographic evaluation of right ventricular function in patients with AL amyloidosis. Eur J Heart Fail. 2007;9(8):808\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ejheart.2007.05.006\u003c/span\u003e\u003cspan address=\"10.1016/j.ejheart.2007.05.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBellavia D, Pellikka PA, Dispenzieri A, et al. Comparison of right ventricular longitudinal strain imaging, tricuspid annular plane systolic excursion, and cardiac biomarkers for early diagnosis of cardiac involvement and risk stratification in primary systematic (AL) amyloidosis: a 5-year cohort study. Eur Heart J Cardiovasc Imaging. 2012;13(8):680\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ehjci/jes009\u003c/span\u003e\u003cspan address=\"10.1093/ehjci/jes009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingulane CC, Slivnick JA, Addetia K, et al. Prevalence of Right Atrial Impairment and Association with Outcomes in Cardiac Amyloidosis. J Am Soc Echocardiogr. 2022;35(8):829\u0026ndash;e8351. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.echo.2022.03.022\u003c/span\u003e\u003cspan address=\"10.1016/j.echo.2022.03.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUzan C, Lairez O, Raud-Raynier P, et al. Right ventricular longitudinal strain: a tool for diagnosis and prognosis in light-chain amyloidosis. Amyloid. 2018;25(1):18\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/13506129.2017.1417121\u003c/span\u003e\u003cspan address=\"10.1080/13506129.2017.1417121\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObici L, Kuks JB, Buades J, et al. Recommendations for presymptomatic genetic testing and management of individuals at risk for hereditary transthyretin amyloidosis. Curr Opin Neurol. 2016;29(Supplement 1):S27\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/WCO.0000000000000290\u003c/span\u003e\u003cspan address=\"10.1097/WCO.0000000000000290\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUeda M, Sekijima Y, Koike H, et al. Monitoring of asymptomatic family members at risk of hereditary transthyretin amyloidosis for early intervention with disease-modifying therapies. J Neurol Sci. 2020;414:116813. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jns.2020.116813\u003c/span\u003e\u003cspan address=\"10.1016/j.jns.2020.116813\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eGeneral characteristics of the TTR variant Carriers and their matched Controls.\u003c/div\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eHealthy Controls\u003csup\u003e*\u003c/sup\u003e\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003en\u0026thinsp;=\u0026thinsp;78\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eTTR variant Carriers\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003en\u0026thinsp;=\u0026thinsp;38\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAge, y \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e52\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eFemales, n (%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e56 (72%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e27 (71%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eBody mass index, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e24.2\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[21.8\u0026ndash;27.0]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e26.6\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[23.6\u0026ndash;33.2]\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSystolic BP, mm Hg\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e118\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[107-122.8]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e122\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[112\u0026ndash;137]\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eDiastolic BP, mm Hg\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e71\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[66\u0026ndash;69]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e76\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[69\u0026ndash;82]\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRace, n (%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eWhite\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e61 (78%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e27 (71%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eBlack\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (1%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7 (19%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAsian\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e13 (17%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e2 (5%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNot reported\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e3 (4%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e2 (5%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eComorbidities, n (%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eHypertension\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e11 (15%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7 (18%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAtrial fibrillation\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eDiabetes mellitus\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCKD\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNTproBNP, pg/ml \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e53\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[28\u0026ndash;77]\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCreatinine, mg/dL\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.87\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.76\u0026ndash;0.97]\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eeGFR, ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e84.0\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[74.0\u0026ndash;97.0]\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eTTR gene variants, n (%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eV30M\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e11 (29%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eV122I\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e9 (24%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eT60A\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e10 (26%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eOthers\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e8 (21%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003csup\u003e*\u003c/sup\u003eHealthy Controls were matched with the TTR variant carriers group; p\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all characteristics except race between these two groups.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e Age is reported in mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, the rest as median [IQR 25th-75th].\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003csup\u003e\u0026Dagger;\u003c/sup\u003e NTproBNP values were available for n\u0026thinsp;=\u0026thinsp;31 in the TTR variant carriers group.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eEchocardiographic characteristics of the Controls and TTR variant Carriers.\u003c/div\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eEchocardiographic\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eParameter\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eControls\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(n\u0026thinsp;=\u0026thinsp;78)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eMedian [IQR 25,75]\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eTTR variant Carriers (n\u0026thinsp;=\u0026thinsp;38)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eMedian [IQR 25,75]\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eP-value\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eIVSDd, cm\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.74\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.68, 0.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.79\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.71, 0.93]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.008\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLVPWd, cm\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.77\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.71, 0.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.79\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.72, 0.96]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.040\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLVIDd, cm\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e4.80\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[4.60, 5.20]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e4.60\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[4.30, 5.00]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.028\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRelative wall thickness (RWT)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.31\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.29, 0.35]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.34\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.30,0.42]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.005\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLV mass index (LVMI), g/m\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e66.21\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[59.49, 75.78]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e60.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[54.33, 70.23]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.032\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eE/A\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.23\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.93, 1.57]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.10\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.96, 1.30]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.142\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLateral e\u0026apos;, cm/s\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e10.90\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[9.75, 12.98]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e10.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[8.70, 12.10]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.205\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSeptal e\u0026apos;, cm/s\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e8.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[7.40, 10.50]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7.90\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[6.40, 9.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.227\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eE/e\u0026apos; Average\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7.18\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[6.32, 8.15]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e8.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[6.40, 9.40]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.040\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA volume index (LAVI), ml/m\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29.93\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[24.65, 37.63]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29.55\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[22.75, 34.69]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.281\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLV Global Longitudinal Strain (GLS)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-22.40\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-23.87, -21.50]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-21.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-22.90, -20.85]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.057\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA reservoir strain (LASr)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e38.15\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[33.73, 42.38]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29.65\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[27.79, 36.78]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA conduit strain (LAScd)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-23.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-29.08,-18.65]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-20.45\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-24.75,-16.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0238\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA contraction strain (LASct)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-11.75\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-18.13,-8.78]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-11.00\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-15.05,-7.20]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.1575\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRV free wall longitudinal strain (RV FWLS)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-28.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-31.90, -24.90]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-24.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-27.30, -22.30]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRA reservoir strain (RASr)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e42.10\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[35.25, 48.60]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e33.50\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[25.82, 36.11]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRA conduit strain (RAScd)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-30.02\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-36.0,-22.9]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-21.72\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-29.12, -18.09]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRA contraction strain (RASct)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-12.32\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-15.80,-7.15]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-9.31\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-15.40,-5.41]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.070\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eEchocardiographic characteristics of the genetic ATTR groups.\u003c/div\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eEchocardiographic\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eParameter\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eTTR variant Carriers (n\u0026thinsp;=\u0026thinsp;38)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eATTRv-CM patients (n\u0026thinsp;=\u0026thinsp;43)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eP-value\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eIVSd, cm\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.79\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.71, 0.93]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.60\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[1.40, 1.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLVPWd, cm\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.79\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.72, 0.96]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.50\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[1.35, 1.60]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLVIDd, cm\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e4.60\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[4.30, 5.00]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e4.16\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[3.80, 4.50]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0006\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRelative wall thickness (RWT)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.34\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.30,0.42]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.61,0.85]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLV mass index (LVMI), g/m\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e60.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[54.33, 70.23]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e137.42\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[114.11, 156.06]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eE/A\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.10\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.96, 1.30]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.50\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[0.97, 2.05]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0090\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLateral e\u0026apos;, cm/s\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e10.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[8.70, 12.10]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e5.95\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[5.35, 7.50]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSeptal e\u0026apos;, cm/s\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7.90\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[6.40, 9.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e4.80\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[3.71, 5.70]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eE/e\u0026apos; Average\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e8.20\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[6.40, 9.40]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e15.65\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[10.66, 21.85]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA volume index (LAVI), ml/m\u003csup\u003e2\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29.55\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[22.75, 34.69]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e45.63\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[33.16, 59.04]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLV Global Longitudinal Strain (GLS)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-21.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-22.90, -20.85]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-14.00\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-15.90, -10.60]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA reservoir strain (LASr)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29.65\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[27.79, 36.78]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e14.55\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[10.25, 22.58]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA conduit strain (LAScd)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-20.45\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-24.75,-16.80]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-8.85\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-11.83, -5.6]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLA contraction strain (LASct)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-11.00\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-15.05,-7.20]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-6.6\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-11.90, -3.98]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0087\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRV free wall longitudinal strain (RV FWLS)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-24.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-27.30, -22.30]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-20.70\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-24.00, -14.93]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRA reservoir strain (RASr)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e33.50\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[25.82, 36.11]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e22.10\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[15.50, 30.30]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRA conduit strain (RAScd)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-21.72\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-29.12, -18.09]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-11.40\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-16.70,-7.50]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eRA contraction strain (RASct)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-9.31\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-15.40,-5.41]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e-9.60\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e[-14.3, -5.8]\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.7488\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8745379/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8745379/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e Explore different echocardiographic parameters, particularly strain imaging, for early pathological changes in asymptomatic ATTR variant carriers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eWith the rise in genetic testing and availability of multiple echocardiographic parameters, determining which features are most sensitive for detecting early changes in asymptomatic carriers of hereditary transthyretin cardiac amyloidosis (ATTRv-CM) could be helpful for guiding monitoring strategies and implementation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eTTR variant carriers (n=39) were identified after a positive genetic test in individuals without evidence of cardiomyopathy based on routine echocardiography or PYP scan. Baseline echocardiograms were analyzed and compared to matched controls and patients with ATTRv-CM. Structural indices, diastolic parameters, and myocardial and atrial 2D strain analyses were measured and compared for differences in rank and in effect size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eTTR variant carriers had a mean age of 51±11 years; 71% were female. Mutations were mainly V30M(29%), T60A(26%), and V122I(24%). Wall thickness measures were significantly higher in carriers compared to controls; however, the largest effect size for differences were observed left atrial(LA), right atrial(RA), and right ventricular(RV) strains (cliff delta \u0026gt;0.33). The proportion of TTR variant carriers meeting abnormal thresholds was different from controls for relative wall thickness\u0026gt;0.42 (16% vs. 0%), p\u0026lt;0.01), |RV strain|\u0026lt;20% (12.8% vs. 1.4%, p=0.02) and |RA reservoir strain|\u0026lt;25% (21.6% vs. 1.3%, p\u0026lt;0.01). After a median follow-up of 3.22 years, 4/26 (15%) TTR carriers developed ATTRv-CM and did not have major baseline dysfunctions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eTTR variant carriers show subtle echocardiographic differences from controls, particularly in LA, RA, and RV strains. The implementation of echocardiography for early detection in asymptomatic TTR carriers can be challenging. Future studies should further investigate the usefulness of routinely measuring these features to guide monitoring strategies in this population.\u003c/p\u003e","manuscriptTitle":"Cardiac Strain Imaging in Asymptomatic Carriers of Transthyretin Variants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 01:12:31","doi":"10.21203/rs.3.rs-8745379/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0f177e32-b533-4741-bb1f-6633c7b425cd","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T18:24:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 01:12:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8745379","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8745379","identity":"rs-8745379","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}