The Role of Remnant Cholesterol Beyond Low-Density Lipoprotein Cholesterol in Left Ventricular Hypertrophy among Patients with Diabetes

The Role of Remnant Cholesterol Beyond Low-Density Lipoprotein Cholesterol in Left Ventricular Hypertrophy among Patients with Diabetes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Role of Remnant Cholesterol Beyond Low-Density Lipoprotein Cholesterol in Left Ventricular Hypertrophy among Patients with Diabetes Zhelong Liu, Tian Yu, Ying Zhao, Bihong Sun, Xinran Liu, Lu Fang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8266571/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 Aims: This study aims to investigate remnant cholesterol (RC), its discordance/concordance with low-density lipoprotein cholesterol (LDL-C), and its interaction with high-sensitivity C-reactive protein (hs-CRP) for left ventricular hypertrophy (LVH) risk in type 2 diabetes mellitus (T2DM). Methods: This cross-sectional study analyzed 30 865 T2DM patients from Tongji Hospital. RC was calculated as total cholesterol minus LDL-C and high-density lipoprotein cholesterol. Multivariable logistic regression and three discordance analyses (cut-off grouping, percentile distance, and residual regression) were used to evaluate the associations of RC and LDL-C with LVH. The interaction between RC and hs-CRP was assessed using clinical cut-offs and the residual cholesterol inflammation index (RCII). Subgroup and sensitivity analyses were employed to verify the results. Results: Elevated LVH risk was associated with the highest quartile (Q4) of RC (odds ratio [OR] = 1.02, 95% confidence interval [CI] 0.99–1.05) compared to Q4 of LDL-C (OR = 1.02, 95% CI 0.99–1.05). Discordance analyses confirmed that high RC, but not high LDL-C, was consistently associated with LVH, notably in the residual model (OR for RC residual = 1.07, 95% CI 1.04–1.10 vs. OR for LDL-C residual = 1.02, 95% CI 0.99–1.05). A synergistic effect on LVH was observed between hs-CRP and RC, with ORs of 1.60 (95% CI 1.45–1.76) in the high RC/hs-CRP group and 1.41 (95% CI 1.30–1.53) in the RCII Q4 group. Results were robust in subgroup and sensitivity analyses. Conclusions: The association of RC with LVH risk in T2DM goes beyond LDL-C and is synergistically enhanced by hs-CRP. Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Diabetes complications Health sciences/Risk factors Remnant cholesterol Low-density lipoprotein cholesterol Type 2 diabetes mellitus Left ventricular hypertrophy Discordance High-sensitivity C-reactive protein Introduction Type 2 diabetes mellitus (T2DM) affects an increasing number of people worldwide, with cardiovascular complications constituting its primary cause of mortality[ 1 ]. Left ventricular hypertrophy (LVH), an early manifestation of cardiovascular disease (CVD), represents a threatening prognostic sign and an independent risk factor for heart failure (HF) and cardiac death[ 2 ]. The presence of T2DM frequently precipitates LVH, initiating a mutually reinforcing cycle. Specifically, LVH amplifies T2DM-related deterioration of the coronary and cardiac microcirculation, which in turn promotes further left ventricular (LV) remodeling. The co-existence of these conditions leads to a 2- to 4-fold increase in the risk of heart failure and cardiac death compared to non-diabetic individuals, even in the absence of hypertension or obesity[ 3 , 4 ]. Dyslipidemia appears in the early stages of T2DM and continues to be involved in the disease progression throughout its entire course[ 5 ]. Together with lipotoxic lipid accumulation, it synergistically induces damage to the endothelial barrier and exacerbates cardiomyocyte stress, thereby creating a vicious microenvironment for LV remodeling[ 6 ]. Low-density lipoprotein cholesterol (LDL-C) is the central target in conventional lipid management, while significant residual risk still exists after controlling LDL-C level below the recommendation of guidelines[ 7 ]. Researches into the discordance/concordance between RC and LDL-C in adverse cardiovascular outcomes has led to the recognition that remnant cholesterol (RC) is a significant contributor to residual risk, independent of LDL-C level[ 8 ]. However, whether this pattern extends to early and subclinical stages of CVD—specifically LVH—has not yet been clearly established. In the context of T2DM-associated LVH, previous studies using conventional analytical approaches examined RC and LDL-C separately or merely as covariates have yielded inconsistent conclusions[ 9 – 12 ], let alone clarifying their distinct roles and possible interactions in relation to LVH risk. Discordance analysis has since emerged as a robust methodological approach to address this limitation, providing insights into their independent and combined effects. RC exhibited strong pro-inflammatory properties owing to their larger size and higher cholesterol load[ 13 ], which have been documented in the pathogenesis of CVD and diabetes[ 14 , 15 ]. However, the interaction between RC and inflammatory marker hs-CRP in relation to LVH is limited in T2DM. This study aims to elucidate the association of RC, its discordance/concordance with LDL-C, and its interaction with of hs-CRP in terms of LVH risk in patients with T2DM. Materials & Methods Study design and population This cross-sectional study included 162 596 T2DM patients hospitalized in the Tongji Hospital, Tongji medical college, Huazhong University of Science and Technology (Wuhan, China) with measurements of echocardiography between January 2014 and January 2024. We excluded participants who were younger than 18 years (n = 220); missing records for necessary information such as RC (n = 131 160); and with acute myocardial infarction, hypertrophic cardiomyopathy, LV assist device implantation, heart transplantation, moderate and severe valvular heart disease, a history of HF (n = 351). Ultimately, 30 865 participants were included. According to the Private Information Protection Law, information that might identify subjects was safeguarded by the Computer Center. The study was approved by the institutional review board of Tongji Hospital, Huazhong University of Science and Technology (Ethics Approval Number: TJ-IRB202509019). Because we only retrospectively accessed a de-identified database for purposes of analysis, informed consent requirement was exempted by the institutional review board. Clinical measurements Data on patients' age, sex, smoking, drinking, current and past medical histories as well as treatments were obtained from medical records. Height, weight, and blood pressure were measured according to the standardized protocol of the World Health Organization. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. After a 5-minute rest, sitting blood pressure (BP) was measured on the patient's right arm with a sphygmomanometer twice every 5 minutes. Data were analyzed using the mean of the two readings. Laboratory measurements Overnight fasting (for at least 8 h) blood samples were collected from each patient. All blood specimens were tested immediately after collection. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), LDL-C, triglycerides (TG), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), uric acid (UA), serum creatinine (Scr) and hs-CRP were determined by using an autoanalyzer (Cobas C8000, Roche, Mannheim, Germany). RC was calculated as TC - HDL-C - LDL-C[ 16 ]. RC inflammatory index (RCII) was calculated as RC (mg/dL) × hs-CRP (mg/L) / 10[ 17 ].Glycated hemoglobin (HbA1c) was measured using high performance liquid chromatography (D-10™; Bio-Rad Laboratories, Hercules, CA, USA). Echocardiography All participants underwent standard two-dimensional transthoracic echocardiographic examination using a commercially available system (EPIQ 7C, Philips Medical Systems) by qualified and experienced cardiac sonographers. Echocardiographic measurements were performed following standardized protocols previously described[ 18 ]. Cross-sectional image was recorded from the parasternal long-axis view to measure LV internal diameter in diastole (LVIDd), the diastolic thickness of the interventricular septum (IVSTd) and posterior wall thickness in end-diastole (PWTd). LV mass was calculated according to the Devereux formula[ 19 ]. LV mass index (LVMI) was calculated by dividing LVM by body surface area according to the recommendation of the American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) guidelines[ 19 ]. Definitions The criteria for LVH diagnosis were an LVMI > 115 g/m 2 in males and ≥ 95 g/m 2 in females. T2DM was diagnosed according to the 2025 American Diabetes Association (ADA) criteria[ 20 ]. According to the ADA criteria, poor glycemic control was defined as HbA1c level ≥ 7.0%; poor cholesterol control as LDL-C level ≥ 100 mg/dL; poor TG control as TG level ≥ 150 mg/dL; poor BP control as BP ≥ 130/80 mmHg[ 21 , 22 ]. Using hs-CRP cut-off points of 1.0 mg/L and 3.0 mg/L, the population was categorized into three groups: low-risk ( 3.0 mg/L)[ 23 ]. Obesity was defined as a BMI ≥ 28 kg/m² in accordance with Chinese-specific criteria established by the Working Group on Obesity in China (WGOC)[ 24 ]. 2.6 Statistical analysis Continuous variables with normal distribution were expressed as mean ± (standard deviation [SD]), while those with skewed distribution were reported as median (interquartile range [IQR]). Between-group differences were compared using t-tests or rank sum tests. Categorical variables were expressed as numbers (percentages) and compared using chi-square or Fisher's exact tests. Logistic regression models were used to assess the associations of RC and the risk of LVH. Model 1 was a crude model. Model 2 was adjusted for age, gender, BMI, smoking status, history of hypertension, anti-hypertensive medications and HbA1c. Model 3 was further adjusted for hs-CRP. Using the same models, we assessed the association between RC/LDL-C concordant/discordant groups and LVH with three analytical strategies: (1) clinical cut-off points; (2) 10th percentile difference; and (3) residuals. We first divided patients into four combined groups according to the clinical cut-off points for LDL-C (2.60 mmol/L) and RC (0.62 mmol/L) [ 7 , 25 ](Group 1: low RC/low LDL-C, Group 2: low RC/high LDL-C, Group 3: high RC/low LDL-C, and Group 4: high RC/high LDL-C). We assessed the association between concordant/discordant RC/LDL-C groups and LVH risk using Group 1 as the reference. Second, we classified patients into three groups by their percentile distance between RC and LDL-C: discordant low RC group (RC percentile LDL-C percentile by 10 percentile units), and concordant group (RC percentile minus LDL-C percentile within ± 10 percentile units)[ 25 ]. We assessed the association between LDL-C/RC concordant/discordant groups and LVH risk using discordant low RC group as the reference. Third, we employed the regression residual analysis of RC and LDL-C in relation to LVH. The RC residual was created by regressing RC on LDL-C using a linear regression model, representing the portion of RC that is not explained by LDL-C. And the LDL-C residual was created by regressing LDL-C on RC, representing the portion of LDL-C unexplained by RC. Then, two separate multivariable regression models were run for each analysis: one with LDL-C and the RC residual and the other with RC and the LDL-C residual. To elucidate the relationship between RC and hs-CRP with LVH, we introduced RCII, a novel index integrating RC and hs-CRP, and analyzed the combined effects of RC and hs-CRP on the risk of LVH based on its quartiles using model 1 and model 2 as previously described. Second, we divided patients into six combined groups, according to the cut-off points for the RC (0.62 mmol/L) and hs-CRP (1.0 mg/L and 3.0 mg/L). Interaction of the effects between RC and hs-CRP was also conducted by using the likelihood ratio test. We further performed subgroup analyses stratified by age, sex, BMI, HbA1c and hypertension status, and assessed interaction effects of these subgroups with likelihood ratio tests. Three sensitivity analyses were conducted to explore the stability of our findings. We employed the stricter clinical cut-off points (1.80 mmol/L for LDL-C and 0.44 mmol/L for RC) to examine the results, additionally in individuals with normal lipid levels (TG < 1.70 mmol/L and LDL < 2.60 mmol/L) (n = 12 230). We further repeated the analyses after excluding individuals with a history of lipid-lowering therapy (n = 28 863). R, version 4.2.2, was used to conduct all the statistical analyses (The R Foundation for Statistical Computing, Vienna, Austria). P values < 0.05 were considered statistically significant. Result Clinical characteristics Of the 30 865 diabetic patients included, the median age was 63 years, 11 681 (37.9%) were men, 9 789 (41.3%) were with LVH and 18 228 (59.1%) were with hypertension. As shown in Table 1, T2DM patients with LVH were older and more likely to be females, smokers, drinkers (all P < 0.05). They also exhibited higher BP, BMI, UA, Scr, TG, and RC, coupled with lower eGFR levels and worse glycemic control (all P < 0.05). While ALT and AST levels showed no significant differences between two groups. The association of RC with LVH Table S1 delineates quartile-based associations of RC and LDL-C with LVH using logistic regression. Compared with the first quartile (Q1), elevated RC levels (Q2-Q4) were significantly associated with LVH after multivariable adjustment (odds ratio [OR] for Q2 = 1.00, 95% confidence interval [CI]: 0.92–1.08; OR for Q3 = 1.22, 95% CI: 1.13–1.32; OR for Q4 = 1.27, 95% CI: 1.17–1.38). However, LDL-C showed no significant association with LVH in T2DM (OR for Q2 = 0.97, 95% CI: 0.90–1.05; OR for Q3 = 0.96, 95% CI: 0.89–1.04; OR for Q4 = 0.97, 95% CI: 0.90–1.06). Effects of the discordance/concordance between RC and LDL-C on LVH risk As shown in Table 2, RC was significantly associated with LVH irrespective of which methods we take, whereas no significant association was found for LDL-C. Patients in the high RC group consistently exhibited a significantly higher risk of LVH, whereas those in the low RC group showed no increased risk, regardless of LDL-C levels. For example, with the cut-off points approach, the high RC groups had a significantly greater risk of LVH (OR for the high RC/low LDL-C group = 1.16, 95% CI: 1.08–1.26; OR for the high RC/high LDL-C group = 1.21, 95% CI 1.12–1.32) compared to the reference group. In contrast, no significant increased risk was observed in the low RC/high LDL-C group (OR = 0.94, 95% CI 0.87–1.02). For the percentile differences approach, the discordant high RC group presented the highest risk of LVH (OR = 1.17, 95% CI 1.09–1.24) among three groups. For residual analysis, in the logistic regression model with LDL-C and the RC residual, adjusted for age, gender, BMI, HbA1c, smoking, history of hypertension and hs-CRP, the RC residual was significantly associated with the risk of LVH (OR = 1.07, 95% CI 1.04–1.10). However, no significant association was observed between LDL-C and LVH (OR = 1.01, 95% CI 0.98–1.04). Similarly, in the model with RC and the LDL-C residual (Table 3), adjusted for the same covariates, RC was also significantly associated with the risk of LVH (OR = 1.07, 95% CI 1.04–1.10), while the LDL-C residual did not show a significant association with LVH (OR = 1.02. 95% CI 0.99–1.05). Subgroup analyses The association between the discordance/concordance of RC/LDL-C and LVH risk was consistent across subgroups defined by obesity, hypertension, age, sex, and HbA1c status (Table S2). And this association was stronger in males, elderly individuals and those with obesity or hypertension. Using likelihood ratio tests, we identified that only hypertension significantly modified the association between the concordant/discordant LDL-C/RC groups and LVH ( P for interaction 0.05). Association of RC and hs-CRP with LVH risk Table 3 summarized the effects of RC and hs-CRP on LVH. Elevated levels of RCII were significantly associated with an increased risk of LVH (OR = 1.41, 95% CI: 1.30–1.53). When we divided patients into six groups according to the cut-offs of RC (0.62 mmol/L) and hs-CRP (1.0 mg/L and 3.0 mg/L), hs-CRP and RC showed a synergistic effect on LVH, with the highest risk of LVH observed in the group with RC > 0.62 mmol/L and hs-CRP > 3.0 mg/L (OR = 1.60, 95% CI: 1.45–1.76). And there was no significant interaction between RC and hs-CRP ( P for interaction = 0.704). Sensitivity analyses We repeated all analyses after excluding participants receiving lipid-lowering medications, and the results remained consistent (Table S1-S6). We observed consistent results when using stricter cut-offs (1.80 mmol/L for LDL-C and 0.44 mmol/L for RC) (Table S3). Additionally, the findings from individuals with normal lipid levels (TG < 1.70 mmol/L and LDL-C < 2.60 mmol/L) consistently showed that the high RC group maintained a significantly higher risk of LVH, independent of LDL-C levels (Table S4). Discussion This is, as far as we known, the first report to describe the association of RC, its discordance/concordance with LDL-C, and its interaction with hs-CRP with the risk of LVH among patients with T2DM. Our principal findings are as follows: (1) RC was positively associated with LVH risk, independent of traditional cardiovascular risk factors, while LDL-C was not; (2) discordantly high RC, but not discordantly high LDL-C, was consistently significantly associated with increased risk of LVH; (3) RC and hs-CRP had synergistic effects on LVH risk in T2DM. Our findings suggest that RC measurement is more clinically relevant than LDL-C for distinguishing patients who are predisposed to LVH in T2DM. The significant and independent association between RC and LVH has been established in the general population[ 26 , 27 ], and our study extends this association to patients with T2DM. However, we found no significant association between LDL-C and LVH in T2DM. Previous researches into the discordance/concordance between RC and LDL-C in relation to adverse cardiovascular events revealed that RC is a significant contributor to residual risk, and discordantly high RC, not discordantly high LDL-C, was associated with a higher risk of adverse cardiovascular events[ 8 , 25 , 28 ]. However, whether this pattern extends to early stages of CVD—specifically LVH—has not yet been clearly established. We used three approaches to do the discordance analyses: clinical cut-off points, 10th percentile difference, and residuals, which is the least arbitrary and captures the maximum of the differing information between RC and LDL-C. In the present study, discordance analyses consistently demonstrated a significantly elevated risk of LVH for the discordant high RC group, but not for the discordant high LDL-C group. Nevertheless, elevated LDL-C level amplified LVH risk only in the presence of concurrent high RC. These findings indicated that RC, rather than LDL-C, may serve as a critical index for risk stratification of LVH in patients with T2DM. Methodological constraints in previous studies, which failed to control for confounding by lipid-lowering medications (usage rates ranging from 4% to 77%), may have obscured the true relationship between the concordance/discordance of RC/LDL-C and LV remodeling[ 27 , 29 ]. To address this, we repeated the analyses after excluding participants who were taking lipid-lowering medications, thereby minimizing confounding and strengthening the validity of our findings. Additionally, our findings were validated in patients with strictly normal lipid profiles (TG < 1.70 mmol/L and LDL-C < 2.60 mmol/L), enabling RC to serve as an index for early risk stratification of LVH in T2DM patients with optimal LDL-C and TG control. RC exhibited consistently a superior role over LDL-C in assessing LVH risk across all the subgroups. And this association was stronger in high-risk subgroups, including hypertensive patients, males, elderly individuals, and those with obesity, whereas HbA1c levels had negligible influence on the RC-LVH risk association. Results from subgroup analyses suggested universal RC monitoring in T2DM, particularly in high-risk individuals who may derive greater cardiovascular benefits from RC control. Moreover, we identified hypertension as a significant effect modifier in the relationship between the concordance/discordance of RC/LDL-C and LVH ( P for interaction < 0.001), which aligns with the observations by Zhang et al[ 30 ]. The effect modification by hypertension is biologically plausible. Hypertension induces endothelial dysfunction and vascular stiffness, potentially amplifying the atherogenic effects of RC through increased lipid penetration and oxidative stress[ 31 ]. Although hypertension is a known LVH driver, no prior studies have reported its interaction with the RC/LDL-C concordance/discordance. Our data implied that diabetic patients with comorbid hypertension may require stricter, dual targeting of both BP and RC, as their vasculature may be more vulnerable to RC-mediated damage. RC's stronger effect on LVH than LDL-C might be attributed to multiple mechanisms. First, the remnant lipoproteins contain up to 4-fold more cholesterol molecules than an LDL-C particle[ 32 , 33 ], thus exhibiting stronger endothelial penetration ability. Apolipoprotein (Apo) metabolism dysfunction also plays an important role in the pathogenic process. Compared to LDL-C, RC particles are characteristically enriched in apoE and apoC-III, both collectively drive arterial lipid retention within the coronary endothelium[ 33 ]. Similar to yet more potent than LDL-C, the denaturation of cholesterol-rich remnant particles may lead to the formation of cholesterol monohydrate crystals[ 34 ], which play a central role in driving the development of the necrotic core in atherosclerotic plaques[ 33 , 35 ]. Additionally, current evidence that RC primarily promotes cardiac disease pathogenesis through proinflammatory mechanisms, distinguishing its atherogenic profile from LDL-C[ 8 ]. Specifically, the chronic inflammation induced by RC not only contributes to obstructive disease, but also impair myocardial energy metabolism via the release of free fatty acids during lipolysis of TG-rich lipoproteins lipolysis.[ 36 – 38 ] These pathological mechanisms collectively lead to cardiomyocyte apoptosis and ventricular remodeling. There is so far no evidence that supports a role for inflammation in the relationship between RC and LVH in T2DM. We addressed this fundamental knowledge gap in the present study. Our results demonstrate that RC and hs-CRP exert additive effects on LVH risk in T2DM, suggesting that RC-driven systemic inflammation may contribute to LVH pathogenesis. Moreover, this synergistic effect between RC and hs-CRP exhibited a dose-dependent relationship, with progressively stronger LVH risk amplification as hs-CRP levels increased. This study has several strengths that deserve emphasis. The main strength of this study is the large number of T2DM patients included from an academic hospital, with access to detailed clinical, laboratory, and imaging data that are typically unavailable in large epidemiological surveys. Secondly, the present study is the first to evaluate the independent effects of RC as a continuous measure in the context of T2DM, but also its superiority over LDL-C as a risk factor, as identified by three kinds of discordance analyses. Moreover, we employed sensitivity analyses that excluded individuals taking lipid-lowering medications, thereby addressing a key limitation of most previous studies. Several limitations of the current study should be recognized also. Due to the cross-sectional design, we cannot establish a direct causal relationship between RC and LVH. Future longitudinal studies tracking participants over time would provide more definitive insights into how blood lipids influence LVH development. Another limitation stems from the indirect method used for RC quantification. Despite being clinically practical and cost-effective, this approach may overestimate RC levels relative to direct measurement techniques,especially in cases of severe hypertriglyceridemia[ 39 ]. However, several methodological strengths help mitigate these limitations: our validation analyses in the subgroup with well-controlled lipid levels (TG < 1.70 mmol/L and LDL-C < 2.60 mmol/L) showed consistent results, and all blood samples were collected after standardized fasting to ensure lipid profile reliability. Although the indirect RC estimation may introduce some measurement bias, our rigorous study design makes it unlikely that this substantially affected our overall findings. The accessibility and affordability of this calculation method nevertheless maintain its value for clinical practice. Further research is needed to address these limitations and deepen our understanding of the relationship between RC and LVH. Conclusion In conclusion, we found that elevated RC levels exhibit a robust association with LVH risk in T2DM. Further, discordance analyses showed that the discordantly high RC was significantly associated with higher LVH risk in T2DM rather than discordantly high LDL-C, even among patients with optimal LDL-C and TG levels. Moreover, hs-CRP potentiates the association between RC and LVH in T2DM. Our findings suggest that RC may serve as a potential target for prevention and intervention for LVH in T2DM. Future studies are warranted to determine whether lowering the RC level can produce benefits for LVH. Declarations Acknowledgements The authors thank all study participants for their cooperation and the support by Big Data Platform of Tongji Hospital. Funding This work was supported by Noncommunicable Chronic Diseases-National Science and Technology Major Project (grant number 2024ZD0532300). Competing Interests All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Author Contributions Tian Yu: Conceptualization, Methodology, Investigation, Data Curation, Software, Formal analysis, Visualization, Validation, Writing–original draft, Writing–review and editing. Ying Zhao: Conceptualization, Methodology, Investigation, Data Curation, Software, Validation, Writing–original draft. Bihong Sun: Conceptualization, Methodology, Investigation, Data Curation. Xinran Liu: Data Curation, Software, Formal analysis, Visualization. Lu Fang: Investigation, Data Curation, Formal analysis. Tingting Du: Conceptualization, Methodology, Visualization, Resources, Supervision, Funding acquisition, Project administration, Writing–review and editing. Zhelong Liu: Conceptualization, Methodology, Visualization, Resources, Supervision, Funding acquisition, Project administration, Writing–review and editing. Ethics approval and consent to participate The study was approved by the institutional review board of Tongji Hospital, Huazhong University of Science and Technology (Ethics Approval Number: TJ-IRB202509019). Because we only retrospectively accessed a de-identified database for purposes of analyses, informed consent requirement was exempted by the institutional review board. Data Availability Statement: The data utilized in this study are housed within and cannot be transferred from the Big Data Platform of Tongji Hospital due to security restrictions. On-site access for analysis is possible upon reasonable request and in compliance with the hospital's data governance framework. Appendices An additional file provides supplementary information for this article: Supplemental file. 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Circ Cardiovasc Imaging 16(11):e015589 Huang Q, Qiu W, Chen C, Wang J, Ou Y, Feng Y (2025) Relationship Between Remnant Cholesterol and Risk of Heart Failure in a Community Population Without Cardiovascular Disease: Results of the China Patient-Centered Evaluative Assessment of Cardiac Events Million Persons Project. J Am Heart Assoc 14(11):e040039 Zhou Y, Madsen JM, Ozbek BT, Kober L, Bang LE, Lonborg JT et al (2024) The role of remnant cholesterol in patients with ST-segment elevation myocardial infarction. Eur J Prev Cardiol 31(10):1227–1237 Wang Z, Zhu Z, Shen J, Zhang Y, Wang T, Xu Y et al (2024) Predictive value of remnant cholesterol for left ventricular hypertrophy and prognosis in hypertensive patients with heart failure: a prospective study. Lipids Health Dis 23(1):294 Zhang X, Li G, Shi C, Zhang D, Sun Y (2022) Combined superposition effect of hypertension and dyslipidemia on left ventricular hypertrophy. Anim Model Exp Med 5(3):227–238 Nwabuo CC, Vasan RS (2020) Pathophysiology of Hypertensive Heart Disease: Beyond Left Ventricular Hypertrophy. Curr Hypertens Rep 22(2):11 Salinas CAA, Chapman MJ (2020) Remnant lipoproteins: are they equal to or more atherogenic than LDL? Curr Opin Lipidol 31(3):132–139 Ginsberg HN, Packard CJ, Chapman MJ, Boren J, Aguilar-Salinas CA, Averna M et al (2021) Triglyceride-rich lipoproteins and their remnants: metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strategies-a consensus statement from the European Atherosclerosis Society. Eur Heart J 42(47):4791–4806 Lehti S, Nguyen SD, Belevich I, Vihinen H, Heikkila HM, Soliymani R et al (2018) Extracellular Lipids Accumulate in Human Carotid Arteries as Distinct Three-Dimensional Structures and Have Proinflammatory Properties. Am J Pathol 188(2):525–538 Kataoka Y, Puri R, Hammadah M, Duggal B, Uno K, Kapadia SR et al (2015) Cholesterol crystals associate with coronary plaque vulnerability in vivo. J Am Coll Cardiol 65(6):630–632 Zlobine I, Gopal K, Ussher JR (2016) Lipotoxicity in obesity and diabetes-related cardiac dysfunction. Biochim Biophys Acta 1861(10):1555–1568 Higgins LJ, Rutledge JC (2009) Inflammation associated with the postprandial lipolysis of triglyceride-rich lipoproteins by lipoprotein lipase. Curr Atheroscler Rep 11(3):199–205 Schwartz EA, Reaven PD (2012) Lipolysis of triglyceride-rich lipoproteins, vascular inflammation, and atherosclerosis. Biochim Biophys Acta 1821(5):858–866 Friedewald WT, Levy RI, Fredrickson DS (1972) Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18(6):499–502 Tables Table 1 to 3 are available in the Supplementary Files section. Additional Declarations There is NO conflict of interest to disclose Supplementary Files tables.doc Table 1, Table 2, Table 3 Supplementalfile1.pdf Table S1 Supplementalfile2.xlsx Table S2 Supplementalfile3.pdf Table S3,Table S4,Table S5,Table S6 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8266571","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588372141,"identity":"d318577f-1f51-44d3-bcac-caa18114a4d5","order_by":0,"name":"Zhelong Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACPmYGBiCyADKZDxz48IMILWwQLRIgZuLBmT3EaGGAa+ExPszBRowWdh7jzwUVEnLm/Gs+HGbgYZDnFztAyGE8BsYzzkgYW854u+FwgQWD4czZCYS1JPO2SSRuuHF2w+EZPAwJBreJ0HKY9x9Iy5kHh3nYiNNi2MzbANRyvoeBWC1sxcw8xySMDW6wGQADWYKwX/j5D2/+zFNjI2dw/vDjDx9+2MjzSxPQggASYJUSxCoH23eAFNWjYBSMglEwkgAAYmc9w0AJkboAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-2567-2287","institution":"Tongji Hospital, Tongji Medical College HUST","correspondingAuthor":true,"prefix":"","firstName":"Zhelong","middleName":"","lastName":"Liu","suffix":""},{"id":588372142,"identity":"f695fd2f-6bbb-45a3-863e-85f440fb22cd","order_by":1,"name":"Tian Yu","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Yu","suffix":""},{"id":588372143,"identity":"929bedf4-0e5a-41f2-a58c-401bdf6d53e7","order_by":2,"name":"Ying Zhao","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Zhao","suffix":""},{"id":588372144,"identity":"46807b0a-edd1-4cc7-8e5c-7d8fd2c18f24","order_by":3,"name":"Bihong Sun","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Bihong","middleName":"","lastName":"Sun","suffix":""},{"id":588372145,"identity":"cae77a9e-539b-40a3-a254-7e0dfaf36896","order_by":4,"name":"Xinran Liu","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Xinran","middleName":"","lastName":"Liu","suffix":""},{"id":588372146,"identity":"683a6e7d-0991-4206-bb9b-7dac670533e7","order_by":5,"name":"Lu Fang","email":"","orcid":"","institution":"Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Fang","suffix":""},{"id":588372147,"identity":"c43b8509-fc28-4675-a5bc-24aefa1b48d7","order_by":6,"name":"Tingting Du","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Du","suffix":""}],"badges":[],"createdAt":"2025-12-03 06:26:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8266571/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8266571/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108807717,"identity":"825330d7-94ce-4911-8c45-b1d9a8398a88","added_by":"auto","created_at":"2026-05-08 15:31:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":213278,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8266571/v1/916e927b-1620-4ec8-b351-def05b9fccbc.pdf"},{"id":102745465,"identity":"767f3d0f-1a29-484e-b2f9-edde962ccf92","added_by":"auto","created_at":"2026-02-16 08:50:54","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":95744,"visible":true,"origin":"","legend":"Table 1, Table 2, Table 3","description":"","filename":"tables.doc","url":"https://assets-eu.researchsquare.com/files/rs-8266571/v1/016ab902097eea0d047146ce.doc"},{"id":102379936,"identity":"f4ea8774-884a-4920-aa37-99614060ed54","added_by":"auto","created_at":"2026-02-11 06:31:04","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":101309,"visible":true,"origin":"","legend":"Table S1","description":"","filename":"Supplementalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8266571/v1/65e4323691aa7aa9863965b0.pdf"},{"id":102379935,"identity":"a75526c5-03d4-4068-917a-f1062550da0c","added_by":"auto","created_at":"2026-02-11 06:31:04","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":14990,"visible":true,"origin":"","legend":"Table S2","description":"","filename":"Supplementalfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8266571/v1/b2fe194e9a143cb1fd0ef7f0.xlsx"},{"id":102379950,"identity":"714d6220-cd38-4894-b869-bfdc5d90a701","added_by":"auto","created_at":"2026-02-11 06:31:15","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":119743,"visible":true,"origin":"","legend":"Table S3,Table S4,Table S5,Table S6","description":"","filename":"Supplementalfile3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8266571/v1/90e76c9f9ebd76ee38f2d575.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"The Role of Remnant Cholesterol Beyond Low-Density Lipoprotein Cholesterol in Left Ventricular Hypertrophy among Patients with Diabetes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) affects an increasing number of people worldwide, with cardiovascular complications constituting its primary cause of mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Left ventricular hypertrophy (LVH), an early manifestation of cardiovascular disease (CVD), represents a threatening prognostic sign and an independent risk factor for heart failure (HF) and cardiac death[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The presence of T2DM frequently precipitates LVH, initiating a mutually reinforcing cycle. Specifically, LVH amplifies T2DM-related deterioration of the coronary and cardiac microcirculation, which in turn promotes further left ventricular (LV) remodeling. The co-existence of these conditions leads to a 2- to 4-fold increase in the risk of heart failure and cardiac death compared to non-diabetic individuals, even in the absence of hypertension or obesity[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDyslipidemia appears in the early stages of T2DM and continues to be involved in the disease progression throughout its entire course[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Together with lipotoxic lipid accumulation, it synergistically induces damage to the endothelial barrier and exacerbates cardiomyocyte stress, thereby creating a vicious microenvironment for LV remodeling[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Low-density lipoprotein cholesterol (LDL-C) is the central target in conventional lipid management, while significant residual risk still exists after controlling LDL-C level below the recommendation of guidelines[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Researches into the discordance/concordance between RC and LDL-C in adverse cardiovascular outcomes has led to the recognition that remnant cholesterol (RC) is a significant contributor to residual risk, independent of LDL-C level[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, whether this pattern extends to early and subclinical stages of CVD\u0026mdash;specifically LVH\u0026mdash;has not yet been clearly established. In the context of T2DM-associated LVH, previous studies using conventional analytical approaches examined RC and LDL-C separately or merely as covariates have yielded inconsistent conclusions[\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], let alone clarifying their distinct roles and possible interactions in relation to LVH risk. Discordance analysis has since emerged as a robust methodological approach to address this limitation, providing insights into their independent and combined effects.\u003c/p\u003e \u003cp\u003eRC exhibited strong pro-inflammatory properties owing to their larger size and higher cholesterol load[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], which have been documented in the pathogenesis of CVD and diabetes[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the interaction between RC and inflammatory marker hs-CRP in relation to LVH is limited in T2DM.\u003c/p\u003e \u003cp\u003eThis study aims to elucidate the association of RC, its discordance/concordance with LDL-C, and its interaction with of hs-CRP in terms of LVH risk in patients with T2DM.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThis cross-sectional study included 162 596 T2DM patients hospitalized in the Tongji Hospital, Tongji medical college, Huazhong University of Science and Technology (Wuhan, China) with measurements of echocardiography between January 2014 and January 2024. We excluded participants who were younger than 18 years (n = 220); missing records for necessary information such as RC (n = 131 160); and with acute myocardial infarction, hypertrophic cardiomyopathy, LV assist device implantation, heart transplantation, moderate and severe valvular heart disease, a history of HF (n = 351). Ultimately, 30 865 participants were included. According to the Private Information Protection Law, information that might identify subjects was safeguarded by the Computer Center. The study was approved by the institutional review board of Tongji Hospital, Huazhong University of Science and Technology (Ethics Approval Number: TJ-IRB202509019). Because we only retrospectively accessed a de-identified database for purposes of analysis, informed consent requirement was exempted by the institutional review board.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical measurements\u003c/h3\u003e\n\u003cp\u003eData on patients' age, sex, smoking, drinking, current and past medical histories as well as treatments were obtained from medical records. Height, weight, and blood pressure were measured according to the standardized protocol of the World Health Organization. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. After a 5-minute rest, sitting blood pressure (BP) was measured on the patient's right arm with a sphygmomanometer twice every 5 minutes. Data were analyzed using the mean of the two readings.\u003c/p\u003e\n\u003ch3\u003eLaboratory measurements\u003c/h3\u003e\n\u003cp\u003eOvernight fasting (for at least 8 h) blood samples were collected from each patient. All blood specimens were tested immediately after collection. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), LDL-C, triglycerides (TG), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), uric acid (UA), serum creatinine (Scr) and hs-CRP were determined by using an autoanalyzer (Cobas C8000, Roche, Mannheim, Germany). RC was calculated as TC - HDL-C - LDL-C[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. RC inflammatory index (RCII) was calculated as RC (mg/dL) × hs-CRP (mg/L) / 10[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].Glycated hemoglobin (HbA1c) was measured using high performance liquid chromatography (D-10™; Bio-Rad Laboratories, Hercules, CA, USA).\u003c/p\u003e\n\u003ch3\u003eEchocardiography\u003c/h3\u003e\n\u003cp\u003eAll participants underwent standard two-dimensional transthoracic echocardiographic examination using a commercially available system (EPIQ 7C, Philips Medical Systems) by qualified and experienced cardiac sonographers. Echocardiographic measurements were performed following standardized protocols previously described[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Cross-sectional image was recorded from the parasternal long-axis view to measure LV internal diameter in diastole (LVIDd), the diastolic thickness of the interventricular septum (IVSTd) and posterior wall thickness in end-diastole (PWTd). LV mass was calculated according to the Devereux formula[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. LV mass index (LVMI) was calculated by dividing LVM by body surface area according to the recommendation of the American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) guidelines[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eDefinitions\u003c/h3\u003e\n\u003cp\u003eThe criteria for LVH diagnosis were an LVMI \u0026gt; 115 g/m\u003csup\u003e2\u003c/sup\u003e in males and ≥ 95 g/m\u003csup\u003e2\u003c/sup\u003e in females. T2DM was diagnosed according to the 2025 American Diabetes Association (ADA) criteria[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. According to the ADA criteria, poor glycemic control was defined as HbA1c level ≥ 7.0%; poor cholesterol control as LDL-C level ≥ 100 mg/dL; poor TG control as TG level ≥ 150 mg/dL; poor BP control as BP ≥ 130/80 mmHg[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Using hs-CRP cut-off points of 1.0 mg/L and 3.0 mg/L, the population was categorized into three groups: low-risk (\u0026lt; 1.0 mg/L), intermediate-risk (1.0–3.0 mg/L), and high-risk (\u0026gt; 3.0 mg/L)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Obesity was defined as a BMI ≥ 28 kg/m² in accordance with Chinese-specific criteria established by the Working Group on Obesity in China (WGOC)[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.6 Statistical analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eContinuous variables with normal distribution were expressed as mean ± (standard deviation [SD]), while those with skewed distribution were reported as median (interquartile range [IQR]). Between-group differences were compared using t-tests or rank sum tests. Categorical variables were expressed as numbers (percentages) and compared using chi-square or Fisher's exact tests.\u003c/p\u003e \u003cp\u003eLogistic regression models were used to assess the associations of RC and the risk of LVH. Model 1 was a crude model. Model 2 was adjusted for age, gender, BMI, smoking status, history of hypertension, anti-hypertensive medications and HbA1c. Model 3 was further adjusted for hs-CRP.\u003c/p\u003e \u003cp\u003eUsing the same models, we assessed the association between RC/LDL-C concordant/discordant groups and LVH with three analytical strategies: (1) clinical cut-off points; (2) 10th percentile difference; and (3) residuals. We first divided patients into four combined groups according to the clinical cut-off points for LDL-C (2.60 mmol/L) and RC (0.62 mmol/L) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e](Group 1: low RC/low LDL-C, Group 2: low RC/high LDL-C, Group 3: high RC/low LDL-C, and Group 4: high RC/high LDL-C). We assessed the association between concordant/discordant RC/LDL-C groups and LVH risk using Group 1 as the reference. Second, we classified patients into three groups by their percentile distance between RC and LDL-C: discordant low RC group (RC percentile \u0026lt; LDL-C percentile by 10 percentile units), discordant high RC group (RC percentile \u0026gt; LDL-C percentile by 10 percentile units), and concordant group (RC percentile minus LDL-C percentile within ± 10 percentile units)[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. We assessed the association between LDL-C/RC concordant/discordant groups and LVH risk using discordant low RC group as the reference. Third, we employed the regression residual analysis of RC and LDL-C in relation to LVH. The RC residual was created by regressing RC on LDL-C using a linear regression model, representing the portion of RC that is not explained by LDL-C. And the LDL-C residual was created by regressing LDL-C on RC, representing the portion of LDL-C unexplained by RC. Then, two separate multivariable regression models were run for each analysis: one with LDL-C and the RC residual and the other with RC and the LDL-C residual.\u003c/p\u003e \u003cp\u003eTo elucidate the relationship between RC and hs-CRP with LVH, we introduced RCII, a novel index integrating RC and hs-CRP, and analyzed the combined effects of RC and hs-CRP on the risk of LVH based on its quartiles using model 1 and model 2 as previously described. Second, we divided patients into six combined groups, according to the cut-off points for the RC (0.62 mmol/L) and hs-CRP (1.0 mg/L and 3.0 mg/L). Interaction of the effects between RC and hs-CRP was also conducted by using the likelihood ratio test.\u003c/p\u003e \u003cp\u003eWe further performed subgroup analyses stratified by age, sex, BMI, HbA1c and hypertension status, and assessed interaction effects of these subgroups with likelihood ratio tests.\u003c/p\u003e \u003cp\u003eThree sensitivity analyses were conducted to explore the stability of our findings. We employed the stricter clinical cut-off points (1.80 mmol/L for LDL-C and 0.44 mmol/L for RC) to examine the results, additionally in individuals with normal lipid levels (TG \u0026lt; 1.70 mmol/L and LDL \u0026lt; 2.60 mmol/L) (n = 12 230). We further repeated the analyses after excluding individuals with a history of lipid-lowering therapy (n = 28 863).\u003c/p\u003e \u003cp\u003eR, version 4.2.2, was used to conduct all the statistical analyses (The R Foundation for Statistical Computing, Vienna, Austria). \u003cem\u003eP\u003c/em\u003e values \u0026lt; 0.05 were considered statistically significant.\u003c/p\u003e "},{"header":"Result","content":"\u003cp\u003e\u003cstrong\u003eClinical characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 30 865 diabetic patients included, the median age was 63 years, 11 681 (37.9%) were men, 9 789 (41.3%) were with LVH and 18 228 (59.1%) were with hypertension. As shown in Table 1, T2DM patients with LVH were older and more likely to be females, smokers, drinkers (all \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). They also exhibited higher BP, BMI, UA, Scr, TG, and RC, coupled with lower eGFR levels and worse glycemic control (all \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). While ALT and AST levels showed no significant differences between two groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe association of RC with LVH\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable S1 delineates quartile-based associations of RC and LDL-C with LVH using logistic regression. Compared with the first quartile (Q1), elevated RC levels (Q2-Q4) were significantly associated with LVH after multivariable adjustment (odds ratio [OR] for Q2 = 1.00, 95% confidence interval [CI]: 0.92\u0026ndash;1.08; OR for Q3 = 1.22, 95% CI: 1.13\u0026ndash;1.32; OR for Q4 = 1.27, 95% CI: 1.17\u0026ndash;1.38). However, LDL-C showed no significant association with LVH in T2DM (OR for Q2 = 0.97, 95% CI: 0.90\u0026ndash;1.05; OR for Q3 = 0.96, 95% CI: 0.89\u0026ndash;1.04; OR for Q4 = 0.97, 95% CI: 0.90\u0026ndash;1.06).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffects of the discordance/concordance between RC and LDL-C on LVH risk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2, RC was significantly associated with LVH irrespective of which methods we take, whereas no significant association was found for LDL-C. Patients in the high RC group consistently exhibited a significantly higher risk of LVH, whereas those in the low RC group showed no increased risk, regardless of LDL-C levels. For example, with the cut-off points approach, the high RC groups had a significantly greater risk of LVH (OR for the high RC/low LDL-C group = 1.16, 95% CI: 1.08\u0026ndash;1.26; OR for the high RC/high LDL-C group =\u0026nbsp;1.21, 95% CI\u0026nbsp;1.12\u0026ndash;1.32) compared to the reference group. In contrast, no significant increased risk was observed in the low RC/high LDL-C group (OR =\u0026nbsp;0.94, 95% CI\u0026nbsp;0.87\u0026ndash;1.02). For the percentile differences approach, the discordant high RC group presented the highest risk of LVH (OR = 1.17, 95% CI 1.09\u0026ndash;1.24) among three groups. For residual analysis, in the logistic regression model with LDL-C and the RC residual, adjusted for age, gender, BMI, HbA1c, smoking, history of hypertension and hs-CRP, the RC residual was significantly associated with the risk of LVH (OR = 1.07, 95% CI 1.04\u0026ndash;1.10). However, no significant association was observed between LDL-C and LVH (OR = 1.01, 95% CI 0.98\u0026ndash;1.04). Similarly, in the model with RC and the LDL-C residual (Table 3), adjusted for the same covariates, RC was also significantly associated with the risk of LVH (OR = 1.07, 95% CI 1.04\u0026ndash;1.10), while the LDL-C residual did not show a significant association with LVH (OR = 1.02. 95% CI 0.99\u0026ndash;1.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubgroup analyses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe association between the discordance/concordance of RC/LDL-C and LVH risk was consistent across subgroups defined by obesity, hypertension, age, sex, and HbA1c status (Table S2). And this association was stronger in males, elderly individuals and those with obesity or hypertension. Using likelihood ratio tests, we identified that only hypertension significantly modified the association between the concordant/discordant LDL-C/RC groups and LVH (\u003cem\u003eP\u003c/em\u003e for interaction \u0026lt; 0.05). Meanwhile, no significant interactions were found for age, gender, BMI, or HbA1c (all \u003cem\u003eP\u003c/em\u003e for interaction \u0026gt; 0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation of RC and hs-CRP with LVH risk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 summarized the effects of RC and hs-CRP on LVH. Elevated levels of RCII were significantly associated with an increased risk of LVH (OR = 1.41, 95% CI: 1.30\u0026ndash;1.53). When we divided patients into six groups according to the cut-offs of RC (0.62 mmol/L) and hs-CRP (1.0 mg/L and 3.0 mg/L), hs-CRP and RC showed a synergistic effect on LVH, with the highest risk of LVH observed in the group with RC \u0026gt; 0.62 mmol/L and hs-CRP \u0026gt; 3.0 mg/L (OR = 1.60, 95% CI: 1.45\u0026ndash;1.76).\u0026nbsp;And there was no significant interaction between RC and hs-CRP (\u003cem\u003eP\u003c/em\u003e for interaction = 0.704).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analyses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe repeated all analyses after excluding participants receiving lipid-lowering medications, and the results remained consistent (Table S1-S6). We observed consistent results when using stricter cut-offs (1.80 mmol/L for LDL-C and 0.44 mmol/L for RC) (Table S3). Additionally, the findings from individuals with normal lipid levels (TG \u0026lt; 1.70 mmol/L and LDL-C \u0026lt; 2.60 mmol/L) consistently showed that the high RC group maintained a significantly higher risk of LVH, independent of LDL-C levels (Table S4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is, as far as we known, the first report to describe the association of RC, its discordance/concordance with LDL-C, and its interaction with hs-CRP with the risk of LVH among patients with T2DM. Our principal findings are as follows: (1) RC was positively associated with LVH risk, independent of traditional cardiovascular risk factors, while LDL-C was not; (2) discordantly high RC, but not discordantly high LDL-C, was consistently significantly associated with increased risk of LVH;\u003c/p\u003e \u003cp\u003e(3) RC and hs-CRP had synergistic effects on LVH risk in T2DM. Our findings suggest that RC measurement is more clinically relevant than LDL-C for distinguishing patients who are predisposed to LVH in T2DM.\u003c/p\u003e \u003cp\u003eThe significant and independent association between RC and LVH has been established in the general population[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and our study extends this association to patients with T2DM. However, we found no significant association between LDL-C and LVH in T2DM. Previous researches into the discordance/concordance between RC and LDL-C in relation to adverse cardiovascular events revealed that RC is a significant contributor to residual risk, and discordantly high RC, not discordantly high LDL-C, was associated with a higher risk of adverse cardiovascular events[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, whether this pattern extends to early stages of CVD\u0026mdash;specifically LVH\u0026mdash;has not yet been clearly established. We used three approaches to do the discordance analyses: clinical cut-off points, 10th percentile difference, and residuals, which is the least arbitrary and captures the maximum of the differing information between RC and LDL-C. In the present study, discordance analyses consistently demonstrated a significantly elevated risk of LVH for the discordant high RC group, but not for the discordant high LDL-C group. Nevertheless, elevated LDL-C level amplified LVH risk only in the presence of concurrent high RC. These findings indicated that RC, rather than LDL-C, may serve as a critical index for risk stratification of LVH in patients with T2DM. Methodological constraints in previous studies, which failed to control for confounding by lipid-lowering medications (usage rates ranging from 4% to 77%), may have obscured the true relationship between the concordance/discordance of RC/LDL-C and LV remodeling[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. To address this, we repeated the analyses after excluding participants who were taking lipid-lowering medications, thereby minimizing confounding and strengthening the validity of our findings. Additionally, our findings were validated in patients with strictly normal lipid profiles (TG\u0026thinsp;\u0026lt;\u0026thinsp;1.70 mmol/L and LDL-C\u0026thinsp;\u0026lt;\u0026thinsp;2.60 mmol/L), enabling RC to serve as an index for early risk stratification of LVH in T2DM patients with optimal LDL-C and TG control.\u003c/p\u003e \u003cp\u003eRC exhibited consistently a superior role over LDL-C in assessing LVH risk across all the subgroups. And this association was stronger in high-risk subgroups, including hypertensive patients, males, elderly individuals, and those with obesity, whereas HbA1c levels had negligible influence on the RC-LVH risk association. Results from subgroup analyses suggested universal RC monitoring in T2DM, particularly in high-risk individuals who may derive greater cardiovascular benefits from RC control. Moreover, we identified hypertension as a significant effect modifier in the relationship between the concordance/discordance of RC/LDL-C and LVH (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which aligns with the observations by Zhang et al[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The effect modification by hypertension is biologically plausible. Hypertension induces endothelial dysfunction and vascular stiffness, potentially amplifying the atherogenic effects of RC through increased lipid penetration and oxidative stress[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Although hypertension is a known LVH driver, no prior studies have reported its interaction with the RC/LDL-C concordance/discordance. Our data implied that diabetic patients with comorbid hypertension may require stricter, dual targeting of both BP and RC, as their vasculature may be more vulnerable to RC-mediated damage.\u003c/p\u003e \u003cp\u003eRC's stronger effect on LVH than LDL-C might be attributed to multiple mechanisms. First, the remnant lipoproteins contain up to 4-fold more cholesterol molecules than an LDL-C particle[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], thus exhibiting stronger endothelial penetration ability. Apolipoprotein (Apo) metabolism dysfunction also plays an important role in the pathogenic process. Compared to LDL-C, RC particles are characteristically enriched in apoE and apoC-III, both collectively drive arterial lipid retention within the coronary endothelium[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Similar to yet more potent than LDL-C, the denaturation of cholesterol-rich remnant particles may lead to the formation of cholesterol monohydrate crystals[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], which play a central role in driving the development of the necrotic core in atherosclerotic plaques[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, current evidence that RC primarily promotes cardiac disease pathogenesis through proinflammatory mechanisms, distinguishing its atherogenic profile from LDL-C[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Specifically, the chronic inflammation induced by RC not only contributes to obstructive disease, but also impair myocardial energy metabolism via the release of free fatty acids during lipolysis of TG-rich lipoproteins lipolysis.[\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] These pathological mechanisms collectively lead to cardiomyocyte apoptosis and ventricular remodeling.\u003c/p\u003e \u003cp\u003eThere is so far no evidence that supports a role for inflammation in the relationship between RC and LVH in T2DM. We addressed this fundamental knowledge gap in the present study. Our results demonstrate that RC and hs-CRP exert additive effects on LVH risk in T2DM, suggesting that RC-driven systemic inflammation may contribute to LVH pathogenesis. Moreover, this synergistic effect between RC and hs-CRP exhibited a dose-dependent relationship, with progressively stronger LVH risk amplification as hs-CRP levels increased.\u003c/p\u003e \u003cp\u003eThis study has several strengths that deserve emphasis. The main strength of this study is the large number of T2DM patients included from an academic hospital, with access to detailed clinical, laboratory, and imaging data that are typically unavailable in large epidemiological surveys. Secondly, the present study is the first to evaluate the independent effects of RC as a continuous measure in the context of T2DM, but also its superiority over LDL-C as a risk factor, as identified by three kinds of discordance analyses. Moreover, we employed sensitivity analyses that excluded individuals taking lipid-lowering medications, thereby addressing a key limitation of most previous studies. Several limitations of the current study should be recognized also. Due to the cross-sectional design, we cannot establish a direct causal relationship between RC and LVH. Future longitudinal studies tracking participants over time would provide more definitive insights into how blood lipids influence LVH development. Another limitation stems from the indirect method used for RC quantification. Despite being clinically practical and cost-effective, this approach may overestimate RC levels relative to direct measurement techniques,especially in cases of severe hypertriglyceridemia[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. However, several methodological strengths help mitigate these limitations: our validation analyses in the subgroup with well-controlled lipid levels (TG\u0026thinsp;\u0026lt;\u0026thinsp;1.70 mmol/L and LDL-C\u0026thinsp;\u0026lt;\u0026thinsp;2.60 mmol/L) showed consistent results, and all blood samples were collected after standardized fasting to ensure lipid profile reliability. Although the indirect RC estimation may introduce some measurement bias, our rigorous study design makes it unlikely that this substantially affected our overall findings. The accessibility and affordability of this calculation method nevertheless maintain its value for clinical practice. Further research is needed to address these limitations and deepen our understanding of the relationship between RC and LVH.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, we found that elevated RC levels exhibit a robust association with LVH risk in T2DM. Further, discordance analyses showed that the discordantly high RC was significantly associated with higher LVH risk in T2DM rather than discordantly high LDL-C, even among patients with optimal LDL-C and TG levels. Moreover, hs-CRP potentiates the association between RC and LVH in T2DM. Our findings suggest that RC may serve as a potential target for prevention and intervention for LVH in T2DM. Future studies are warranted to determine whether lowering the RC level can produce benefits for LVH.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all study participants for their cooperation and the support by Big Data Platform of Tongji Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Noncommunicable Chronic Diseases-National Science and Technology Major Project (grant number 2024ZD0532300).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTian Yu:\u003c/strong\u003e Conceptualization, Methodology, Investigation, Data Curation, Software, Formal analysis, Visualization, Validation, Writing\u0026ndash;original draft, Writing\u0026ndash;review and editing. \u003cstrong\u003eYing Zhao:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Investigation, Data Curation, Software, Validation, Writing\u0026ndash;original draft. \u003cstrong\u003eBihong Sun:\u003c/strong\u003e Conceptualization, Methodology, Investigation, Data Curation. \u003cstrong\u003eXinran Liu:\u003c/strong\u003e Data Curation, Software, Formal analysis, Visualization. \u003cstrong\u003eLu Fang:\u003c/strong\u003e Investigation, Data Curation, Formal analysis. \u003cstrong\u003eTingting Du:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Visualization, Resources, Supervision, Funding acquisition, Project administration, Writing\u0026ndash;review and editing. \u003cstrong\u003eZhelong Liu:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Visualization, Resources, Supervision, Funding acquisition, Project administration, Writing\u0026ndash;review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the institutional review board of Tongji Hospital, Huazhong University of Science and Technology (Ethics Approval Number: TJ-IRB202509019). Because we only retrospectively accessed a de-identified database for purposes of analyses, informed consent requirement was exempted by the institutional review board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data utilized in this study are housed within and cannot be transferred from the Big Data Platform of Tongji Hospital due to security restrictions. On-site access for analysis is possible upon reasonable request and in compliance with the hospital\u0026apos;s data governance framework.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAppendices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn additional file provides supplementary information for this article: Supplemental file.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhmad E, Lim S, Lamptey R, Webb DR, Davies MJ (2022) Type 2 diabetes. 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Circ Cardiovasc Imaging 16(11):e015589\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang Q, Qiu W, Chen C, Wang J, Ou Y, Feng Y (2025) Relationship Between Remnant Cholesterol and Risk of Heart Failure in a Community Population Without Cardiovascular Disease: Results of the China Patient-Centered Evaluative Assessment of Cardiac Events Million Persons Project. J Am Heart Assoc 14(11):e040039\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Y, Madsen JM, Ozbek BT, Kober L, Bang LE, Lonborg JT et al (2024) The role of remnant cholesterol in patients with ST-segment elevation myocardial infarction. Eur J Prev Cardiol 31(10):1227\u0026ndash;1237\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Zhu Z, Shen J, Zhang Y, Wang T, Xu Y et al (2024) Predictive value of remnant cholesterol for left ventricular hypertrophy and prognosis in hypertensive patients with heart failure: a prospective study. Lipids Health Dis 23(1):294\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Li G, Shi C, Zhang D, Sun Y (2022) Combined superposition effect of hypertension and dyslipidemia on left ventricular hypertrophy. Anim Model Exp Med 5(3):227\u0026ndash;238\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNwabuo CC, Vasan RS (2020) Pathophysiology of Hypertensive Heart Disease: Beyond Left Ventricular Hypertrophy. Curr Hypertens Rep 22(2):11\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalinas CAA, Chapman MJ (2020) Remnant lipoproteins: are they equal to or more atherogenic than LDL? Curr Opin Lipidol 31(3):132\u0026ndash;139\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGinsberg HN, Packard CJ, Chapman MJ, Boren J, Aguilar-Salinas CA, Averna M et al (2021) Triglyceride-rich lipoproteins and their remnants: metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strategies-a consensus statement from the European Atherosclerosis Society. Eur Heart J 42(47):4791\u0026ndash;4806\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLehti S, Nguyen SD, Belevich I, Vihinen H, Heikkila HM, Soliymani R et al (2018) Extracellular Lipids Accumulate in Human Carotid Arteries as Distinct Three-Dimensional Structures and Have Proinflammatory Properties. Am J Pathol 188(2):525\u0026ndash;538\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKataoka Y, Puri R, Hammadah M, Duggal B, Uno K, Kapadia SR et al (2015) Cholesterol crystals associate with coronary plaque vulnerability in vivo. J Am Coll Cardiol 65(6):630\u0026ndash;632\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZlobine I, Gopal K, Ussher JR (2016) Lipotoxicity in obesity and diabetes-related cardiac dysfunction. Biochim Biophys Acta 1861(10):1555\u0026ndash;1568\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiggins LJ, Rutledge JC (2009) Inflammation associated with the postprandial lipolysis of triglyceride-rich lipoproteins by lipoprotein lipase. Curr Atheroscler Rep 11(3):199\u0026ndash;205\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwartz EA, Reaven PD (2012) Lipolysis of triglyceride-rich lipoproteins, vascular inflammation, and atherosclerosis. Biochim Biophys Acta 1821(5):858\u0026ndash;866\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedewald WT, Levy RI, Fredrickson DS (1972) Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18(6):499\u0026ndash;502\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 3 are available in the Supplementary Files section.\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":"Remnant cholesterol, Low-density lipoprotein cholesterol, Type 2 diabetes mellitus, Left ventricular hypertrophy, Discordance, High-sensitivity C-reactive protein","lastPublishedDoi":"10.21203/rs.3.rs-8266571/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8266571/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims:\u003c/h2\u003e \u003cp\u003eThis study aims to investigate remnant cholesterol (RC), its discordance/concordance with low-density lipoprotein cholesterol (LDL-C), and its interaction with high-sensitivity C-reactive protein (hs-CRP) for left ventricular hypertrophy (LVH) risk in type 2 diabetes mellitus (T2DM).\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis cross-sectional study analyzed 30 865 T2DM patients from Tongji Hospital. RC was calculated as total cholesterol minus LDL-C and high-density lipoprotein cholesterol. Multivariable logistic regression and three discordance analyses (cut-off grouping, percentile distance, and residual regression) were used to evaluate the associations of RC and LDL-C with LVH. The interaction between RC and hs-CRP was assessed using clinical cut-offs and the residual cholesterol inflammation index (RCII). Subgroup and sensitivity analyses were employed to verify the results.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eElevated LVH risk was associated with the highest quartile (Q4) of RC (odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.02, 95% confidence interval [CI] 0.99\u0026ndash;1.05) compared to Q4 of LDL-C (OR\u0026thinsp;=\u0026thinsp;1.02, 95% CI 0.99\u0026ndash;1.05). Discordance analyses confirmed that high RC, but not high LDL-C, was consistently associated with LVH, notably in the residual model (OR for RC residual\u0026thinsp;=\u0026thinsp;1.07, 95% CI 1.04\u0026ndash;1.10 vs. OR for LDL-C residual\u0026thinsp;=\u0026thinsp;1.02, 95% CI 0.99\u0026ndash;1.05). A synergistic effect on LVH was observed between hs-CRP and RC, with ORs of 1.60 (95% CI 1.45\u0026ndash;1.76) in the high RC/hs-CRP group and 1.41 (95% CI 1.30\u0026ndash;1.53) in the RCII Q4 group. Results were robust in subgroup and sensitivity analyses.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eThe association of RC with LVH risk in T2DM goes beyond LDL-C and is synergistically enhanced by hs-CRP.\u003c/p\u003e","manuscriptTitle":"The Role of Remnant Cholesterol Beyond Low-Density Lipoprotein Cholesterol in Left Ventricular Hypertrophy among Patients with Diabetes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 06:30:54","doi":"10.21203/rs.3.rs-8266571/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":"5a287873-6cc4-4f41-acd0-725e1e6b551e","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject after peer review","date":"2026-05-08T12:38:08+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62595433,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases/Diabetes/Diabetes complications"},{"id":62595434,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-08T12:41:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 06:30:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8266571","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8266571","identity":"rs-8266571","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}