In vivo-measured Lewy body pathology is associated with neuropsychiatric symptoms across the Alzheimer’s disease continuum

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Post-mortem studies have shown a higher frequency of neuropsychiatric symptoms among individuals with AD and LB co-pathology. However, the effects of in vivo-measured LB pathology on neuropsychiatric symptoms in AD remain underexplored. This study aimed to evaluate cross-sectional and longitudinal effects of in vivo-measured LB pathology on neuropsychiatric symptoms across the AD continuum. We analyzed data from 1,169 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants had in vivo measures of LB pathology (assessed using an alpha-synuclein seed amplification assay), amyloid-beta (Aβ) and phosphorylated tau (p-tau) levels in cerebrospinal fluid (CSF), and neuropsychiatric symptoms evaluated using the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Logistic and Cox proportional hazards regression models were used to assess cross-sectional and longitudinal effects, respectively, adjusting for age, sex, and cognitive status. Participants had a mean baseline age of 73.05 (SD 7.22) years, 47.13% were women, 426 (36.44%) cognitively unimpaired, and 743 (63.56%) cognitively impaired. In cross-sectional analyses, LB pathology was associated with higher rates of anxiety, apathy, motor disturbances, and appetite disturbances. In longitudinal analyses, LB pathology increased the risk of developing psychosis and anxiety. These effects were independent of Aβ and p-tau. Our results suggest that in vivo-measured LB pathology is closely associated with neuropsychiatric symptoms across the AD continuum. These findings underscore the potential of in vivo LB detection as a marker for identifying individuals at increased risk of neuropsychiatric symptoms, both in clinical trials and in clinical practice. Health sciences/Diseases Health sciences/Biomarkers/Predictive markers Figures Figure 1 Figure 2 Figure 3 Introduction Co-pathology is frequently observed in individuals with Alzheimer’s disease (AD) dementia, with alpha-synuclein deposition being one of the most common findings ( 1 , 2 ). Intracellular aggregates of alpha-synuclein are denominated Lewy bodies (LB) and are the hallmark of Lewy body dementia (LBD). LBD is clinically characterized by progressive cognitive impairment, parkinsonism, and rapid eye movement (REM) sleep behavior disorder, and is commonly associated with prominent neuropsychiatric symptoms ( 3 ). Post-mortem studies report that 33–66% of individuals with AD exhibit abnormal brain alpha-synuclein aggregates ( 4 ), which have been shown to exacerbate cognitive decline ( 5 ) and brain hypometabolism ( 6 ) in living humans. Therefore, a deeper understanding of the impact of LB co-pathology in AD is essential to more accurately characterize the clinical presentations and progression of the disease. Neuropsychiatric symptoms are common and debilitating clinical manifestations in AD, affecting 60–90% of individuals with this condition ( 7 – 10 ). The prevalence of neuropsychiatric symptoms increases as AD pathology becomes more severe ( 11 ), and a wide body of literature demonstrates their association with greater functional impairment ( 12 – 14 ). Post-mortem studies support a higher frequency of neuropsychiatric symptoms in individuals with AD and LB co-pathology. For example, Chung, Babulal ( 15 ) found higher rates of delusions, hallucinations, and aberrant motor behavior in individuals with AD and LB when compared to AD without LB. Other authors observed a higher prevalence of hallucinations, anxiety, irritability, nighttime behaviors, appetite disturbances, agitation, and apathy in individuals with concomitant AD and LB pathology ( 16 – 18 ). To date, however, the effects of LB pathology measured in vivo on neuropsychiatric symptoms in AD remain underexplored. Recent advances in alpha-synuclein seed amplification assays (SAAs) have enabled accurate detection of in vivo LB pathology that is comparable to the gold standard post-mortem confirmation ( 4 , 19 ). This technique provides an opportunity to study the effects of LB in living individuals, allowing earlier identification of pathology and facilitating longitudinal tracking of disease progression, thus addressing some of the limitations inherent in retrospective post-mortem analyses. In light of these advancements, the present study was designed to evaluate the cross-sectional and longitudinal effects of in vivo-detected LB pathology on distinct neuropsychiatric symptoms in a large sample of cognitively unimpaired (CU) and cognitively impaired (CI) individuals across the AD continuum. Materials and methods Participants We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of AD ( http://adni.loni.usc.edu ). ADNI’s inclusion criteria included having a study partner with frequent contact with the participant, age between 55 and 90 years, a Geriatric Depression Scale (GDS) score less than 6, and a Modified Hachinski Ischemic Score less than or equal to 4. CU individuals had a Mini-Mental State Exam (MMSE) score between 24 and 30 and a Clinical Dementia Rating global score (CDR-GS) of 0. Individuals with mild cognitive impairment (MCI) had a MMSE score between 24 and 30 and a CDR-GS of 0.5, with a Memory Box score of at least 0.5. Participants with AD dementia had an MMSE score between 20 and 24 and a CDR-GS of 0.5 or 1. The full inclusion and exclusion criteria for ADNI can be found elsewhere ( 20 ). For this study, we included CU and CI (comprising MCI and AD dementia) individuals from the ADNI cohort, for whom alpha-synuclein status was determined using the cerebrospinal fluid (CSF) alpha-synuclein SAA test. Participants were also required to have a clinical and neuropsychiatric assessment within two years of the alpha synuclein SAA status. Their first neuropsychiatric assessment was defined as their baseline. Complete data (including clinical and neuropsychiatric assessments) were available for 1,169 individuals, and 977 participants had CSF amyloid (Aβ) and tau pathology measurements within two years of the baseline assessment. For the longitudinal analyses, we analyzed data from individuals who had at least two neuropsychiatric assessments within a 10-year period after their baseline. All data were downloaded from the ADNI data repository in July 2024. Institutional Review Boards of all participating sites approved the ADNI study, and all research participants or their authorized representatives provided written informed consent. Neuropsychiatric symptoms Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory-Questionnaire (NPI-Q) ( 21 ). The NPI-Q is a validated, self-administered questionnaire completed by informants covering the following neuropsychiatric domains: delusions, hallucinations, agitation/aggression, dysphoria/depression, anxiety, euphoria/elation, apathy/indifference, disinhibition, irritability/lability, motor disturbances, nighttime behavioral disturbances, and appetite/eating disturbances. Symptoms are rated for severity on a three-point scale (1 = mild, 2 = moderate, 3 = severe). In ADNI, the NPI-Q was administered at baseline and every six months for two years, then annually thereafter. For this study, individuals were categorized as positive (NPI-Q score of 1, 2, or 3) or negative (NPI-Q score of 0) for each core neuropsychiatric domain. Delusions and hallucinations were combined as “psychosis” for our analyses, due to their low baseline prevalence in our sample. CSF biomarkers The presence of alpha-synuclein aggregates (LB pathology) was detected using an SAA performed at the Amprion Clinical Laboratory ( 22 ). CSF samples were classified as alpha-synuclein aggregates “detected”, “not detected”, or “indeterminate” (indicating that a result determination could not be made for a sample after being tested twice). A total of nine samples were classified as “indeterminate” and excluded from the analyses (Supplementary Fig. 1). CSF Aβ 1–42 (Aβ1–42) and tau phosphorylated at threonine 181 (p-tau181) were quantified using fully automated Elecsys immunoassays (Roche Diagnostics). Measurements outside the analytical range ( 1700 pg/mL for Aβ1–42; 120pg/mL for p-tau181) were set to the lower or upper detection limit, as previously done ( 23 ). Aβ positivity was defined as CSF Aβ1–42 24 pg/mL, as previously described ( 24 ). Statistical analysis Differences in the rate of neuropsychiatric symptoms (categorized as present or absent) at baseline between LB- (samples with no detected α-syn aggregates) and LB+ (samples with detected α-syn aggregates) individuals were investigated using logistic regression analyses adjusting for age, sex, and cognitive status (model 1, Supplementary Material), with results reported as odds ratio (OR) and 95% confidence interval (CI). Next, in baseline cross-sectional analyses, we explored the effects of Aβ, p-tau and LB pathologies on neuropsychiatric symptoms. All three pathologies were used in the same model alongside sex, age, and cognitive status (model 2, Supplementary Material). To decrease the risk of false positive results, model 2 was performed only for neuropsychiatric symptoms showing significant statistical association with LB in model 1. Dichotomized Aβ and p-tau scores, as described above, were used to facilitate the comparison of estimates. After identifying pathologies with significant independent effects on neuropsychiatric symptoms in model 2, we performed post-hoc analyses to test the interaction between them. Additionally, as a sensitivity analysis, we replicated model 1 stratifying the population into CU and CI groups. We performed longitudinal analyses to investigate the effects of LB on the development of neuropsychiatric symptoms. Only individuals who did not exhibit each specific symptom at baseline were included in these analyses, and the event was defined as the first onset of that symptom during follow-up. To compare the time-to-event data between groups (individuals with or without LB pathology), Kaplan-Meier survival curves were generated. Additionally, we used Cox proportional hazards regression models to account for sex, age, and cognitive status (model 3, Supplementary Material), with results reported as hazard ratios (HR) and 95% CI. Next, Aβ, p-tau and LB pathologies were included in the same Cox proportional hazard regression model together with sex, age, and cognitive status (model 4, Supplementary Material). Model 4 was performed only for neuropsychiatric symptoms showing significant statistical association with LB in model 3. After identifying pathologies with significant independent effects on the development of neuropsychiatric symptoms in model 4, we performed post-hoc analyses to test the interaction between them. Additionally, as a sensitivity analysis, we replicated model 3 stratifying the population into CU and CI groups. A two-sided p-value of less than 0.05 was considered statistically significant. Multiple comparison corrections were performed using the false discovery rate method ( 25 ) at alpha = 0.05, applying correction per model (models 1 and 3 with 11 analyses each, models 2 and 4 with 3 analyses for each neuropsychiatric domain). Finally, to assess model adequacy, we performed standard diagnostic analyses, including the Hosmer-Lemeshow goodness-of-fit test and link tests for logistic regressions, as well as Schoenfeld residuals tests to evaluate the proportional hazards assumption in Cox models (for details, see Supplementary Material, Supplementary Tables 1 and 2). All analyses were conducted using Stata version 18.0 (StataCorp, College Station, Texas, USA). Results We analyzed data from 1,169 participants, of whom 977 had CSF Aβ and p-tau measurements. The flowchart is presented in Supplementary Fig. 1. The mean (SD) age at baseline was 73.05 (7.22) years, and 551 (47.13%) were women. A total of 426 (36.44%) individuals were classified as CU and 743 (63.56%) as CI at baseline. Baseline demographic and clinical characteristics are shown in Table 1 . Table 1 Baseline demographic and clinical characteristics. Overall ( N = 1,169 ) LB- ( N = 888) LB+ ( N = 281) Age, y, mean (SD) 73.05 (7.22) 72.59 (7.18) 74.49 (7.16) Sex, No. (%) Female 551 (47.13) 437 (49.21) 114 (40.57) Male 618 (52.87) 451 (50.79) 167 (59.43) Race, No. (%) White 1091 (93.33) 821 (92.45) 270 (96.09) Black 41 (3.51) 36 (4.05) 5 (1.78) Asian 20 (1.71) 15 (1.69) 5 (1.78) Hawaiian/Other PI 1 (0.09) 1 (0.11) 0 More than one 12 (1.03) 11 (1.24) 1 (0.36) Unknown 2 (0.17) 2 (0.23) Ethnicity, No. (%) Not Hispanic/Latino 1127 (96.41) 853 (96.06) 274 (97.51) Hispanic/Latino 36 (3.08) 30 (3.38) 6 (2.14) Unknown 6 (0.51) 5 (0.56) 1 (0.36) Cognitive status, No. (%) CU 426 (36.44) 347 (39.08) 79 (28.11) CI 743 (63.56) 541 (60.92) 202 (71.89) MMSE, mean (SD) 1168 (27.02) 27.35 (2.85) 25.95 (3.75) CDR-SB, mean (SD) 1.74 (2.14) 1.55 (2.05) 2.34 (2.30) APOE ε4, No. carries (%) 530 (46.61) 388 (44.04) 142 (50.53) CSF Aβ1–42, No. positive (%) 604 (61.82) 417 (57.12) 187 (75.71) CSF Aβ1–42, pg/mL, mean (SD) 934.51 (446.97) 980.31 (448.36) 799.18 (415.09) CSF p-tau181, No. positive (%) 525 (53.74) 384 (52.60) 141 (57.09) CSF p-tau181, pg/mL, mean (SD)* 28.65 (15.30) 28.66 (15.85) 28.62 (13.58) Participants with follow-up data, No. (%) 850 (72.71) 638 (71.84) 212 (75.44) Follow-up, y, mean (SD)* 2.64 (2.13) 2.75 (2.21) 2.32 (1.82) Table 1 presents baseline demographic and clinical characteristics of the overall study population, stratified by LB status (LB- and LB+). Missing CSF Aβ1-42 and p-tau181: 158 LB-, 34 LB+. Missing MMSE: 1 LB-. Missing CDR-SB:. 2 LB-, 1 LB+. Missing APOE ε4: 7 LB- * For participants with available follow-up data. Abbreviations: LB, Lewy body; SD, standard deviation; y, years; PI, Pacific Islander; CU, cognitively unimpaired; CI, cognitively impaired; CSF, cerebrospinal fluid. A total of 850 participants (72.71%) had two or more neuropsychiatric assessments using the NPI-Q within 10 years from baseline. For those participants, the mean and median observation times were 2.64 and 1.99 years, respectively (SD = 2.13; interquartile range = 1.03–3.02; with maximum and minimum follow-up times of 9.9 and 0.45 years, respectively). Participants had a mean and median number of observations of 3.46 and 3, respectively (SD = 1.70; interquartile range = 2–4; maximum of 11 and minimum of 2 observations, respectively). Associations between LB pathology and baseline neuropsychiatric symptoms The frequency of neuropsychiatric symptoms at baseline is presented in Fig. 1 a. In cross-sectional analyses, LB + individuals showed higher rates of anxiety (OR = 1.61, 95% CI = 1.13 to 2.29, p-value = 0.008), apathy (OR = 1.67, 95% CI = 1.17 to 2.37, p-value = 0.004), motor disturbances (OR = 1.96, 95% CI = 1.18 to 3.24, p-value = 0.008), and appetite disturbances (OR = 1.63, 95% CI = 1.11 to 2.40, p-value = 0.01) compared to LB- individuals (Fig. 1 b, model 1). No significant differences were observed for psychosis, agitation, depression, elation, disinhibition, irritability, or sleep (Fig. 1 b, model 1) after controlling for multiple comparisons. Figures 2 a, c, e, and g show the percentage of individuals presenting with anxiety, apathy, motor disturbances, or appetite/eating disturbances (statistically significant in model 1) according to their Aβ, p-tau, and LB pathology status at baseline. When including all three pathologies in the model (model 2), the presence of Aβ, p-tau, and LB was associated with higher rates of anxiety (Fig. 2 b). For apathy, the presence of Aβ and LB was associated with a higher prevalence of symptoms (Fig. 2 d). For motor disturbances and appetite disturbances, only LB was associated with a higher prevalence of symptoms (Fig. 2 f, h). The prevalence of neuropsychiatric symptoms according to AD and LB pathology can be found in Supplementary Table 3. We found no significant interactions between LB and Aβ on anxiety (OR = 0.69, 95% CI = 0.28 to 1.72, p-value = 0.43) or apathy (OR = 1.48, 95% CI = 0.57 to 3.81, p-value = 0.41). Similarly, we observed no interaction between LB and p-tau on anxiety (OR = 0.77, 95% CI = 0.36 to 1.64, p-value = 0.50). When stratifying participants by cognitive status, we found no differences in the frequency of neuropsychiatric symptoms in CU participants (Supplementary Table 4). In CI individuals, the presence of LB was associated with higher rates of anxiety, apathy, disinhibition, motor disturbances, and appetite/eating disturbances (Supplementary Table 4). Associations between LB pathology and longitudinal neuropsychiatric symptoms Cox proportional hazards regression models showed that LB + individuals had a higher risk of developing psychosis (HR = 2.15, 95% CI = 1.30 to 3.56, p-value = 0.003) and anxiety (HR = 1.70, 95% CI = 1.22 to 2.36, p-value = 0.001) during follow-up compared to LB- individuals (model 3, Fig. 3 a). The Kaplan-Meier survival curves illustrating time to onset of psychosis and anxiety symptoms are presented in Figs. 3 b and 3 c. No differences in risk were observed for agitation, depression, elation, apathy, disinhibition, irritability, motor disturbances, sleep, or appetite disturbances (model 3, Fig. 3 a). After including Aβ and p-tau in the model, the presence of Aβ and LB was associated with higher risks of developing psychosis and anxiety during follow-up (model 4, Table 2 ). Table 2 Effects of LB, Aβ, and p-tau on the development of neuropsychiatric symptoms. Aβ p-tau LB HR (95% CI) p-value HR (95% CI) p-value HR (95% CI) p-value Psychosis 3.40 (1.54 to 7.49) 0.002 1.78 (0.98 to 3.22) 0.05 1.81 (1.08 to 3.04) 0.02 Anxiety 1.85 (1.26 to 2.71) 0.002 1.03 (0.73 to 1.46) 0.82 1.61 (1.15 to 2.24) 0.005 Table 2 presents the results of longitudinal analyses using Cox proportional hazards regression exploring the effects of Aβ, p-tau and LB status on the development of neuropsychiatric symptoms. All three pathologies were included in the same model, alongside sex, age, and cognitive status (model 4, Supplementary Material). For each neuropsychiatric symptom (psychosis and anxiety), HR with 95% CI and corresponding p-values are provided. HR > 1 indicates an increased risk of developing the symptom in the presence of the pathology. Abbreviations: Aβ, amyloid-beta; LB, Lewy body; HR, hazard ratio; CI, confidence interval. We found no significant interactions between LB and Aβ for psychosis (HR = 0.83, 95% CI = 0.15 to 5.51, p-value = 0.83) or anxiety (HR = 0.99, 95% CI = 0.44 to 2.21, p-value = 0.98). When stratifying participants by cognitive status, Cox proportional hazard regression models showed no differences in the risk of developing neuropsychiatric symptoms in CU individuals when comparing LB + and LB- (Supplementary Table 5). For CI individuals, the presence of LB was associated with a higher risk of developing psychosis and anxiety (Supplementary Table 5). Discussion This study aimed to explore the cross-sectional and longitudinal effects of LB pathology on neuropsychiatric symptoms across the AD continuum. We observed that in vivo presence of LB was associated with higher baseline rates of anxiety, apathy, motor disturbances, and appetite disturbances. Furthermore, in longitudinal analyses, the presence of LB was associated with an increased risk of developing psychotic and anxiety symptoms. The effects of LB were independent of Aβ and p-tau pathology and were more pronounced in CI individuals. These findings reinforce that LB pathology contributes to the development of neuropsychiatric symptoms in AD and suggest that in vivo detection of LB can assist in identifying individuals at risk for psychosis and anxiety. Our findings are consistent with previous research demonstrating high rates of behavioral disturbances in patients presenting LB pathology ( 26 ). Specifically, results from our cross-sectional analyses provide new evidence that LB pathology detected in vivo is associated with increased rates of anxiety, apathy, motor disturbances, and appetite/eating disturbances independent of Aβ or p-tau pathology. These symptoms have been previously shown to occur frequently in individuals with a clinical diagnosis of LBD, with reported rates ranging from 40–60% for anxiety ( 27 – 31 ), 30–55% for apathy ( 29 – 31 ), 20–60% for motor disturbances ( 30 , 31 ), and 15–30% for appetite/eating disturbances ( 29 , 31 ). The spectrum of neuropsychiatric disturbances observed in individuals with a clinical diagnosis of LBD is broad, and includes visual hallucinations, delusions, REM sleep behavior disorder, and depression ( 26 ). In our study, we observed a trend toward a higher frequency of agitation, depression, and disinhibition that did not reach statistical significance after adjusting for covariates and multiple comparisons. One possible explanation for the weak association of these symptoms in our analysis is that we studied participants at earlier stages of LB pathology compared with those who reach full criteria for a clinical diagnosis of LBD. This observation aligns with literature suggesting that in vivo detection of LB can identify individuals in the early stages of symptom development ( 32 ). In this sense, we propose that anxiety, apathy, motor disturbances, and appetite/eating disturbances are early neuropsychiatric manifestations potentially arising from LB pathology across the AD continuum. Our findings suggest that LB and AD pathology (Aβ and p-tau) independently contribute to elevated baseline rates of anxiety, while LB and Aβ pathology significantly increase the risk of developing anxiety over a 10-year period. Clinical and preclinical evidence suggests that LB pathology accumulation in the limbic system plays a role in anxiety development in LBD ( 28 ). However, most of the supporting evidence thus far comes from post-mortem studies, which have demonstrated that LB and AD pathology independently contribute to elevated rates of anxiety ( 16 , 18 ). When comparing individuals with both AD and LB pathology to those with AD alone, findings have been mixed. One study reported that anxiety was more frequent in individuals with LB and AD pathology ( 17 ), while others did not observe this association ( 15 , 16 , 18 ). In contrast, our current study employs in vivo detection of LB pathology, which allows us to examine the risk of developing anxiety over a 10-year period. In line with our observations showing a higher risk of developing anxiety in participants with Aβ pathology, previous studies have found that CU individuals with high Aβ burden experience increasing anxiety levels over time ( 33 , 34 ). Collectively, our findings reinforce the notion that LB and AD pathology independently contribute to anxiety symptoms across the AD continuum and highlight the potential of in vivo LB detection as a valuable marker for identifying individuals at risk for developing high levels of anxiety. While delusions and hallucinations are hallmark neuropsychiatric symptoms in diagnosed LBD, we did not find differences in psychosis rates in our cross-sectional analyses. On the other hand, over a 10-year follow-up period, we found that individuals with LB pathology were more likely to develop psychotic symptoms. The association between LB pathology and psychotic symptoms has been well-established in post-mortem studies ( 15 – 18 ), and the presence of neocortical LB has been linked to psychosis in LBD ( 35 ). Unlike our cross-sectional findings, Quadalti, Palmqvist ( 5 ) observed higher rates of hallucinations in CI individuals with in vivo detected LB pathology in cross-sectional analyses. This discrepancy may derive from the low baseline rates of psychotic symptoms, including hallucinations and delusions, in our study population, which might have limited our power to detect cross-sectional differences. This can potentially be attributed to self-selection bias, as individuals with high levels of psychosis are less likely to enroll in AD-related studies. Overall, our findings support an association between LB pathology measured in vivo and the development of psychotic symptoms during the AD continuum. Findings from this study should be interpreted with consideration of the following limitations. The cohort consisted of individuals motivated to participate in a dementia study, which may introduce self-selection bias and limit the generalizability of our findings to the broader elderly population. The NPI-Q provides a brief assessment of neuropsychiatric symptoms and may not capture the full complexity and nuance of psychiatric symptomatology. For instance, it may not detect specific nighttime behaviors typically seen in REM sleep behavior disorder. As the NPI-Q is completed by informants, recall bias may influence the accuracy of reported symptoms, particularly for symptoms with subtle or fluctuating presentations. Varying follow-up durations and assessment among participants may introduce bias in the longitudinal analyses. To address this, we employed survival analyses to account for censored data, though residual bias cannot be entirely ruled out. It would be desirable to replicate our results in a population-based cohort. To conclude, this study demonstrates that LB pathology measured in vivo is associated with a higher frequency of neuropsychiatric symptoms. These effects were independent of Aβ and p-tau pathologies. Our findings highlight the value of in vivo LB detection in the identification of individuals at a high risk for anxiety and psychosis. Future studies with expanded longitudinal follow-up and comprehensive neuropsychiatric assessments will be critical in further elucidating the temporal relationship between in vivo-measured LB pathology and neuropsychiatric symptom development. Declarations Conflicts of Interest: J.T. has served as a paid consultant for Neurotorium and Alzheon Inc, outside of the scope of the current work. E.R.Z. has served on the scientific advisory board or as a consultant for Nintx, Novo Nordisk, Magdalena Biosciences and Masima. He is also a co-founder and minority shareholder of Masima. Acknowledgements: Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) NIH Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). The ADNI is funded by the National Institute on Aging (NIH), the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. T.A.P. is supported by National Institute on Aging awards 5R01AG073267 and 5R01AG075336. B.B., M.S.R., G.B.N., G.P., and P.C.L.F. are supported by the Alzheimer’s Association Research Fellowship to promote diversity (AARFD-22-974627; AARFD-24-1313939; AARFD-23-1150249; 24AARFD-1243899; AARFD-22-923814). C.S.A. is supported by the Global Brain Health Institute, Alzheimer’s Association, and Alzheimer’s Society (GBHI ALZ UK-23-971089), Alzheimer’s Association (24AACSF-1200375), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, 88887.951210/2024-00). J.T. is funded by the McGill University Faculty of Medicine student fellowship, and the Colin J Adair foundation fellowship. References Robinson JL, Richardson H, Xie SX, Suh E, Van Deerlin VM, Alfaro B, et al. The development and convergence of co-pathologies in Alzheimer’s disease. Brain. 2021;144(3):953–62. DeTure MA, Dickson DW. The neuropathological diagnosis of Alzheimer's disease. Mol Neurodegener. 2019;14(1):32. Taylor J-P, McKeith IG, Burn DJ, Boeve BF, Weintraub D, Bamford C, et al. New evidence on the management of Lewy body dementia. The Lancet Neurology. 2020;19(2):157–69. Baiardi S, Hansson O, Levin J, Parchi P. 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A cross-sectional study of α-synuclein seed amplification assay in Alzheimer's disease neuroimaging initiative: Prevalence and associations with Alzheimer's disease biomarkers and cognitive function. Alzheimer's & Dementia. 2024;20(8):5114–31. Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, et al. Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 2010;74(3):201–9. Kaufer DI, Cummings JL, Ketchel P, Smith V, MacMillan A, Shelley T, et al. Validation of the NPI-Q, a brief clinical form of the Neuropsychiatric Inventory. J Neuropsychiatry Clin Neurosci. 2000;12(2):233–9. Concha-Marambio L, Pritzkow S, Shahnawaz M, Farris CM, Soto C. Seed amplification assay for the detection of pathologic alpha-synuclein aggregates in cerebrospinal fluid. Nat Protoc. 2023;18(4):1179–96. Hansson O, Seibyl J, Stomrud E, Zetterberg H, Trojanowski JQ, Bittner T, et al. CSF biomarkers of Alzheimer's disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement. 2018;14(11):1470–81. Blennow K, Shaw LM, Stomrud E, Mattsson N, Toledo JB, Buck K, et al. Predicting clinical decline and conversion to Alzheimer's disease or dementia using novel Elecsys Aβ(1–42), pTau and tTau CSF immunoassays. Sci Rep. 2019;9(1):19024. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B (Methodological). 1995;57(1):289–300. Ballard C, Aarsland D, Francis P, Corbett A. Neuropsychiatric Symptoms in Patients with Dementias Associated with Cortical Lewy Bodies: Pathophysiology, Clinical Features, and Pharmacological Management. Drugs & Aging. 2013;30(8):603–11. Ballard C, Holmes C, McKeith I, Neill D, O’Brien J, Cairns N, et al. Psychiatric Morbidity in Dementia With Lewy Bodies: A Prospective Clinical and Neuropathological Comparative Study With Alzheimer’s Disease. American Journal of Psychiatry. 1999;156(7):1039–45. Segers K, Benoit F, Meyts JM, Surquin M. Anxiety symptoms are quantitatively and qualitatively different in dementia with Lewy bodies than in Alzheimer's disease in the years preceding clinical diagnosis. Psychogeriatrics. 2020;20(3):242–6. Borroni B, Agosti C, Padovani A. Behavioral and psychological symptoms in dementia with Lewy-bodies (DLB): frequency and relationship with disease severity and motor impairment. Arch Gerontol Geriatr. 2008;46(1):101–6. Aarsland D, Brønnick K, Ehrt U, De Deyn PP, Tekin S, Emre M, et al. Neuropsychiatric symptoms in patients with Parkinson's disease and dementia: frequency, profile and associated care giver stress. J Neurol Neurosurg Psychiatry. 2007;78(1):36–42. Schwertner E, Pereira JB, Xu H, Secnik J, Winblad B, Eriksdotter M, et al. Behavioral and Psychological Symptoms of Dementia in Different Dementia Disorders: A Large-Scale Study of 10,000 Individuals. Journal of Alzheimer's Disease. 2022;87:1307–18. Rossi M, Candelise N, Baiardi S, Capellari S, Giannini G, Orrù CD, et al. Ultrasensitive RT-QuIC assay with high sensitivity and specificity for Lewy body-associated synucleinopathies. Acta Neuropathol. 2020;140(1):49–62. Donovan NJ, Locascio JJ, Marshall GA, Gatchel J, Hanseeuw BJ, Rentz DM, et al. Longitudinal Association of Amyloid Beta and Anxious-Depressive Symptoms in Cognitively Normal Older Adults. Am J Psychiatry. 2018;175(6):530–7. Babulal GM, Ghoshal N, Head D, Vernon EK, Holtzman DM, Benzinger TLS, et al. Mood Changes in Cognitively Normal Older Adults are Linked to Alzheimer Disease Biomarker Levels. Am J Geriatr Psychiatry. 2016;24(11):1095–104. Ballard CG, Jacoby R, Ser TD, Khan MN, Munoz DG, Holmes C, et al. Neuropathological Substrates of Psychiatric Symptoms in Prospectively Studied Patients With Autopsy-Confirmed Dementia With Lewy Bodies. American Journal of Psychiatry. 2004;161(5):843–9. Additional Declarations Yes J.T. has served as a paid consultant for Neurotorium and Alzheon Inc, outside of the scope of the current work. E.R.Z. has served on the scientific advisory board or as a consultant for Nintx, Novo Nordisk, Magdalena Biosciences and Masima. He is also a co-founder and minority shareholder of Masima. Supplementary Files Supplementarymaterialmar2025.docx Supplementary material Cite Share Download PDF Status: Published Journal Publication published 14 Dec, 2025 Read the published version in Molecular Psychiatry → Version 1 posted Editorial decision: revise 28 Jul, 2025 Review # 1 received at journal 05 Jun, 2025 Reviewer # 1 agreed at journal 21 May, 2025 Reviewers invited by journal 19 May, 2025 Editor assigned by journal 24 Mar, 2025 Submission checks completed at journal 24 Mar, 2025 First submitted to journal 21 Mar, 2025 Unknown event 21 Mar, 2025 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. 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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-6270682","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433196171,"identity":"1f9dbba3-9fa5-4216-ac7b-b4c07597975d","order_by":0,"name":"Douglas Leffa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIie3RvUrEQBDA8RkCm2ZjKQsqeYUNln7cq2QJnI2gIKROWBibgG3Al7A77O7Y4hpZHyAgOQJWFilT3IGnd4ogidpZ7L8c5lcMA+By/cswA5AAO4B1C+x4O2X9gH8QBl5UAhv/hnzuvBPzMxn5mkR7+RQyX2PWpY9qsmtqaFPTSzif6aiUVxFxg3lhK3V/O5ZY2gEiVN5wGSOJi3kdUKXuqnPwAhog4SIzSxmPKGwwX5HdkNUQEZg3IGNFwkMd0HRDcIg8KB0VMk6IJ6j3bXL4dsussGe9xL+eP4tuGZ/c+OvzX9LTg8lesqi79KiXfG/9Vpj+YX9LXC6Xy/W1V7CAVx9YMunKAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4890-8451","institution":"University of Pittsburgh","correspondingAuthor":true,"prefix":"","firstName":"Douglas","middleName":"","lastName":"Leffa","suffix":""},{"id":433196172,"identity":"0bfaa63d-e3a5-47e8-bc1c-ada497e114ae","order_by":1,"name":"Guilherme Povala","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Guilherme","middleName":"","lastName":"Povala","suffix":""},{"id":433196173,"identity":"3bf98b4e-4a17-465b-bc1d-ddb0885f6522","order_by":2,"name":"Pamela Ferreira","email":"","orcid":"https://orcid.org/0000-0003-2134-9829","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Pamela","middleName":"","lastName":"Ferreira","suffix":""},{"id":433196174,"identity":"8cd87021-2f48-4daf-8cb6-88762c2874ae","order_by":3,"name":"João Pedro Ferrari-Souza","email":"","orcid":"https://orcid.org/0000-0003-2183-1551","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"João","middleName":"Pedro","lastName":"Ferrari-Souza","suffix":""},{"id":433196175,"identity":"c2ce2cb1-0a13-4559-b68a-8746b44dfbf3","order_by":4,"name":"Guilherme Bauer-Negrini","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Guilherme","middleName":"","lastName":"Bauer-Negrini","suffix":""},{"id":433196176,"identity":"1af037f6-61cc-46c3-bb0c-f44f9e6bcc5c","order_by":5,"name":"Matheus Rodrigues","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Matheus","middleName":"","lastName":"Rodrigues","suffix":""},{"id":433196177,"identity":"42d39dae-35f7-48ce-a9ec-444365175731","order_by":6,"name":"Livia Amaral","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Livia","middleName":"","lastName":"Amaral","suffix":""},{"id":433196178,"identity":"a1df584f-570e-4a90-8f37-a7c7ce1a443c","order_by":7,"name":"Firoza Lussier","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Firoza","middleName":"","lastName":"Lussier","suffix":""},{"id":433196179,"identity":"4980f9a8-9cf4-4bf9-8b3e-1dbc244d601c","order_by":8,"name":"Marina Medeiros","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Medeiros","suffix":""},{"id":433196180,"identity":"427d694f-414b-42f7-8963-6bdfc5eb121f","order_by":9,"name":"Carolina Soares","email":"","orcid":"https://orcid.org/0000-0002-2338-4495","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Carolina","middleName":"","lastName":"Soares","suffix":""},{"id":433196181,"identity":"f4db6788-5121-4df9-9f59-ac14bd2690e4","order_by":10,"name":"Cristiano S. Aguzzoli","email":"","orcid":"https://orcid.org/0000-0002-7378-3830","institution":"Brain Institute of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Cristiano","middleName":"S.","lastName":"Aguzzoli","suffix":""},{"id":433196182,"identity":"08fb4c7d-2967-4652-9618-982b51db1e57","order_by":11,"name":"Arthur Macedo","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Arthur","middleName":"","lastName":"Macedo","suffix":""},{"id":433196183,"identity":"de9fd9fa-f295-4a5f-a3d2-b7ab704adf02","order_by":12,"name":"Joseph Therriault","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Therriault","suffix":""},{"id":433196184,"identity":"1d7e9bc9-8464-41a3-b37d-54b464b250fc","order_by":13,"name":"Pedro Rosa-Neto","email":"","orcid":"https://orcid.org/0000-0001-9116-1376","institution":"McGill Univeristy","correspondingAuthor":false,"prefix":"","firstName":"Pedro","middleName":"","lastName":"Rosa-Neto","suffix":""},{"id":433196185,"identity":"10f4e538-0527-43c4-b8dd-a282c5295709","order_by":14,"name":"Dana Tudorascu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Dana","middleName":"","lastName":"Tudorascu","suffix":""},{"id":433196186,"identity":"5659af27-181f-4a3d-9c5c-22021a518473","order_by":15,"name":"Eduardo Zimmer","email":"","orcid":"https://orcid.org/0000-0002-5349-0053","institution":"Universidade Federal do Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Eduardo","middleName":"","lastName":"Zimmer","suffix":""},{"id":433196187,"identity":"12cfd67d-ace8-43bb-beba-37f30bbafc44","order_by":16,"name":"Bruna Bellaver","email":"","orcid":"https://orcid.org/0000-0002-2212-3373","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Bruna","middleName":"","lastName":"Bellaver","suffix":""},{"id":433196188,"identity":"93e71f96-f5ca-4dda-94a0-0bc9843d1f1b","order_by":17,"name":"Tharick Pascoal","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Tharick","middleName":"","lastName":"Pascoal","suffix":""}],"badges":[],"createdAt":"2025-03-20 14:50:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6270682/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6270682/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41380-025-03400-7","type":"published","date":"2025-12-14T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79263377,"identity":"986096f5-2cde-41b2-b8e7-93b6205b0c93","added_by":"auto","created_at":"2025-03-26 09:51:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":163949,"visible":true,"origin":"","legend":"\u003cp\u003eCross-sectional associations between LB and neuropsychiatric symptoms.\u003c/p\u003e\n\u003cp\u003eFigure 1a shows the percentage of individuals with positive neuropsychiatric symptoms in each NPI-Q domain. LB- and LB+ represent participants with CSF samples classified as α-synuclein aggregates “not detected” and “detected”, respectively. Figure 1b shows the ORs and 95% CIs from logistic regression models investigating differences in the rate of neuropsychiatric symptoms between LB- and LB+ individuals (OR\u0026gt;1 indicates higher rates of neuropsychiatric symptoms in LB+ compared to LB-). Models were adjusted for age, sex, and cognitive status (model 1, Supplementary Material). P-values in bold are statistically significant after correcting for multiple comparisons using the false discovery rate method at alpha = 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003eLB, Lewy body; CSF, cerebrospinal fluid; NPI-Q, Neuropsychiatric Inventory Questionnaire; OR, odds ratio; CI, confidence interval.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6270682/v1/651e12ccfbac070511325901.png"},{"id":79263378,"identity":"b0b638be-d703-4123-ba4c-360ac7fc882f","added_by":"auto","created_at":"2025-03-26 09:51:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":104340,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of LB, Aβ, and p-tau on neuropsychiatric symptoms at baseline.\u003c/p\u003e\n\u003cp\u003eFigures 2a, c, e, and g show the percentage of individuals with positive anxiety, apathy, motor disturbances, and appetite/eating disturbances, respectively, according to the NPI-Q and categorized by Aβ, p-tau, and LB status. We selected these domains based on their significant statistical association with LB in model 1. Figures 2b, d, f, and h show the ORs and 95% CIs from logistic regression models exploring the effects of Aβ, p-tau and LB pathologies on neuropsychiatric symptoms. All three pathologies were included in the same model, along with sex, age, and cognitive status (model 2, Supplementary Material). OR\u0026gt;1 indicates higher rates of neuropsychiatric symptoms in the presence of the pathology. P-values in bold are statistically significant after correcting for multiple comparisons within each neuropsychiatric domain using the false discovery rate method at alpha = 0.05.\u003c/p\u003e\n\u003cp\u003eAbbreviations: LB, Lewy body; Aβ, amyloid-beta; NPI-Q, Neuropsychiatric Inventory Questionnaire; OR, odds ratio; CI, confidence interval.\u003c/p\u003e","description":"","filename":"FIgure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6270682/v1/b9e51f892f09b32136fd76e5.png"},{"id":79265327,"identity":"2e1b855a-f580-4c39-aa67-d0cf607fcab9","added_by":"auto","created_at":"2025-03-26 09:59:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52346,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of LB on the development of neuropsychiatric symptoms.\u003c/p\u003e\n\u003cp\u003eFigure 3a shows the HR and 95% CIs from Cox proportional hazard regression models investigating the effects of LB on the development of neuropsychiatric symptoms, adjusted for sex, age, and cognitive status (model 3, Supplementary Material). P-values in bold are statistically significant after correcting for multiple comparisons using the false discovery rate method at alpha = 0.05. Figures 3b and c show the Kaplan-Meier survival curves, with shaded areas indicating the 95% CI.\u003c/p\u003e\n\u003cp\u003eAbbreviations: LB, Lewy body; HR, hazard ratio; CI, confidence interval.\u003c/p\u003e","description":"","filename":"FIgure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6270682/v1/c94d40e7b35509c7347647c2.png"},{"id":98154494,"identity":"5a9100d6-39cb-4658-9f1f-a48ea56512ee","added_by":"auto","created_at":"2025-12-14 08:06:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":939751,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6270682/v1/fefc8a0a-fec2-4e68-bc49-0af7b8e64104.pdf"},{"id":79263380,"identity":"589af7c4-d4dc-4045-b379-857e041051d9","added_by":"auto","created_at":"2025-03-26 09:51:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":84747,"visible":true,"origin":"","legend":"Supplementary material","description":"","filename":"Supplementarymaterialmar2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-6270682/v1/3aa994c810f536c56cd0f27e.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e\nJ.T. has served as a paid consultant for Neurotorium and Alzheon Inc, outside of the scope of the current work. E.R.Z. has served on the scientific advisory board or as a consultant for Nintx, Novo Nordisk, Magdalena Biosciences and Masima. He is also a co-founder and minority shareholder of Masima.","formattedTitle":"In vivo-measured Lewy body pathology is associated with neuropsychiatric symptoms across the Alzheimer’s disease continuum","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCo-pathology is frequently observed in individuals with Alzheimer\u0026rsquo;s disease (AD) dementia, with alpha-synuclein deposition being one of the most common findings (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Intracellular aggregates of alpha-synuclein are denominated Lewy bodies (LB) and are the hallmark of Lewy body dementia (LBD). LBD is clinically characterized by progressive cognitive impairment, parkinsonism, and rapid eye movement (REM) sleep behavior disorder, and is commonly associated with prominent neuropsychiatric symptoms (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Post-mortem studies report that 33\u0026ndash;66% of individuals with AD exhibit abnormal brain alpha-synuclein aggregates (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), which have been shown to exacerbate cognitive decline (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and brain hypometabolism (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) in living humans. Therefore, a deeper understanding of the impact of LB co-pathology in AD is essential to more accurately characterize the clinical presentations and progression of the disease.\u003c/p\u003e \u003cp\u003eNeuropsychiatric symptoms are common and debilitating clinical manifestations in AD, affecting 60\u0026ndash;90% of individuals with this condition (\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The prevalence of neuropsychiatric symptoms increases as AD pathology becomes more severe (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), and a wide body of literature demonstrates their association with greater functional impairment (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Post-mortem studies support a higher frequency of neuropsychiatric symptoms in individuals with AD and LB co-pathology. For example, Chung, Babulal (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) found higher rates of delusions, hallucinations, and aberrant motor behavior in individuals with AD and LB when compared to AD without LB. Other authors observed a higher prevalence of hallucinations, anxiety, irritability, nighttime behaviors, appetite disturbances, agitation, and apathy in individuals with concomitant AD and LB pathology (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). To date, however, the effects of LB pathology measured in vivo on neuropsychiatric symptoms in AD remain underexplored.\u003c/p\u003e \u003cp\u003eRecent advances in alpha-synuclein seed amplification assays (SAAs) have enabled accurate detection of in vivo LB pathology that is comparable to the gold standard post-mortem confirmation (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This technique provides an opportunity to study the effects of LB in living individuals, allowing earlier identification of pathology and facilitating longitudinal tracking of disease progression, thus addressing some of the limitations inherent in retrospective post-mortem analyses. In light of these advancements, the present study was designed to evaluate the cross-sectional and longitudinal effects of in vivo-detected LB pathology on distinct neuropsychiatric symptoms in a large sample of cognitively unimpaired (CU) and cognitively impaired (CI) individuals across the AD continuum.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eParticipants\u003c/p\u003e \u003cp\u003eWe used data from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI), a longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of AD (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://adni.loni.usc.edu\u003c/span\u003e\u003cspan address=\"http://adni.loni.usc.edu\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). ADNI\u0026rsquo;s inclusion criteria included having a study partner with frequent contact with the participant, age between 55 and 90 years, a Geriatric Depression Scale (GDS) score less than 6, and a Modified Hachinski Ischemic Score less than or equal to 4. CU individuals had a Mini-Mental State Exam (MMSE) score between 24 and 30 and a Clinical Dementia Rating global score (CDR-GS) of 0. Individuals with mild cognitive impairment (MCI) had a MMSE score between 24 and 30 and a CDR-GS of 0.5, with a Memory Box score of at least 0.5. Participants with AD dementia had an MMSE score between 20 and 24 and a CDR-GS of 0.5 or 1. The full inclusion and exclusion criteria for ADNI can be found elsewhere (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor this study, we included CU and CI (comprising MCI and AD dementia) individuals from the ADNI cohort, for whom alpha-synuclein status was determined using the cerebrospinal fluid (CSF) alpha-synuclein SAA test. Participants were also required to have a clinical and neuropsychiatric assessment within two years of the alpha synuclein SAA status. Their first neuropsychiatric assessment was defined as their baseline. Complete data (including clinical and neuropsychiatric assessments) were available for 1,169 individuals, and 977 participants had CSF amyloid (Aβ) and tau pathology measurements within two years of the baseline assessment. For the longitudinal analyses, we analyzed data from individuals who had at least two neuropsychiatric assessments within a 10-year period after their baseline. All data were downloaded from the ADNI data repository in July 2024. Institutional Review Boards of all participating sites approved the ADNI study, and all research participants or their authorized representatives provided written informed consent.\u003c/p\u003e \u003cp\u003eNeuropsychiatric symptoms\u003c/p\u003e \u003cp\u003eNeuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory-Questionnaire (NPI-Q) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The NPI-Q is a validated, self-administered questionnaire completed by informants covering the following neuropsychiatric domains: delusions, hallucinations, agitation/aggression, dysphoria/depression, anxiety, euphoria/elation, apathy/indifference, disinhibition, irritability/lability, motor disturbances, nighttime behavioral disturbances, and appetite/eating disturbances. Symptoms are rated for severity on a three-point scale (1\u0026thinsp;=\u0026thinsp;mild, 2\u0026thinsp;=\u0026thinsp;moderate, 3\u0026thinsp;=\u0026thinsp;severe). In ADNI, the NPI-Q was administered at baseline and every six months for two years, then annually thereafter. For this study, individuals were categorized as positive (NPI-Q score of 1, 2, or 3) or negative (NPI-Q score of 0) for each core neuropsychiatric domain. Delusions and hallucinations were combined as \u0026ldquo;psychosis\u0026rdquo; for our analyses, due to their low baseline prevalence in our sample.\u003c/p\u003e \u003cp\u003eCSF biomarkers\u003c/p\u003e \u003cp\u003eThe presence of alpha-synuclein aggregates (LB pathology) was detected using an SAA performed at the Amprion Clinical Laboratory (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). CSF samples were classified as alpha-synuclein aggregates \u0026ldquo;detected\u0026rdquo;, \u0026ldquo;not detected\u0026rdquo;, or \u0026ldquo;indeterminate\u0026rdquo; (indicating that a result determination could not be made for a sample after being tested twice). A total of nine samples were classified as \u0026ldquo;indeterminate\u0026rdquo; and excluded from the analyses (Supplementary Fig.\u0026nbsp;1). CSF Aβ 1\u0026ndash;42 (Aβ1\u0026ndash;42) and tau phosphorylated at threonine 181 (p-tau181) were quantified using fully automated Elecsys immunoassays (Roche Diagnostics). Measurements outside the analytical range (\u0026lt;\u0026thinsp;200 pg/mL or \u0026gt;\u0026thinsp;1700 pg/mL for Aβ1\u0026ndash;42; \u0026lt;8 pg/mL or \u0026gt;\u0026thinsp;120pg/mL for p-tau181) were set to the lower or upper detection limit, as previously done (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Aβ positivity was defined as CSF Aβ1\u0026ndash;42\u0026thinsp;\u0026lt;\u0026thinsp;976.6 pg/mL, and tau positivity as p-tau181\u0026thinsp;\u0026gt;\u0026thinsp;24 pg/mL, as previously described (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDifferences in the rate of neuropsychiatric symptoms (categorized as present or absent) at baseline between LB- (samples with no detected α-syn aggregates) and LB+ (samples with detected α-syn aggregates) individuals were investigated using logistic regression analyses adjusting for age, sex, and cognitive status (model 1, Supplementary Material), with results reported as odds ratio (OR) and 95% confidence interval (CI). Next, in baseline cross-sectional analyses, we explored the effects of Aβ, p-tau and LB pathologies on neuropsychiatric symptoms. All three pathologies were used in the same model alongside sex, age, and cognitive status (model 2, Supplementary Material). To decrease the risk of false positive results, model 2 was performed only for neuropsychiatric symptoms showing significant statistical association with LB in model 1. Dichotomized Aβ and p-tau scores, as described above, were used to facilitate the comparison of estimates. After identifying pathologies with significant independent effects on neuropsychiatric symptoms in model 2, we performed post-hoc analyses to test the interaction between them. Additionally, as a sensitivity analysis, we replicated model 1 stratifying the population into CU and CI groups.\u003c/p\u003e \u003cp\u003eWe performed longitudinal analyses to investigate the effects of LB on the development of neuropsychiatric symptoms. Only individuals who did not exhibit each specific symptom at baseline were included in these analyses, and the event was defined as the first onset of that symptom during follow-up. To compare the time-to-event data between groups (individuals with or without LB pathology), Kaplan-Meier survival curves were generated. Additionally, we used Cox proportional hazards regression models to account for sex, age, and cognitive status (model 3, Supplementary Material), with results reported as hazard ratios (HR) and 95% CI. Next, Aβ, p-tau and LB pathologies were included in the same Cox proportional hazard regression model together with sex, age, and cognitive status (model 4, Supplementary Material). Model 4 was performed only for neuropsychiatric symptoms showing significant statistical association with LB in model 3. After identifying pathologies with significant independent effects on the development of neuropsychiatric symptoms in model 4, we performed post-hoc analyses to test the interaction between them. Additionally, as a sensitivity analysis, we replicated model 3 stratifying the population into CU and CI groups. A two-sided p-value of less than 0.05 was considered statistically significant. Multiple comparison corrections were performed using the false discovery rate method (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) at alpha\u0026thinsp;=\u0026thinsp;0.05, applying correction per model (models 1 and 3 with 11 analyses each, models 2 and 4 with 3 analyses for each neuropsychiatric domain). Finally, to assess model adequacy, we performed standard diagnostic analyses, including the Hosmer-Lemeshow goodness-of-fit test and link tests for logistic regressions, as well as Schoenfeld residuals tests to evaluate the proportional hazards assumption in Cox models (for details, see Supplementary Material, Supplementary Tables\u0026nbsp;1 and 2). All analyses were conducted using Stata version 18.0 (StataCorp, College Station, Texas, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe analyzed data from 1,169 participants, of whom 977 had CSF A\u0026beta; and p-tau measurements. The flowchart is presented in Supplementary Fig. 1. The mean (SD) age at baseline was 73.05 (7.22) years, and 551 (47.13%) were women. A total of 426 (36.44%) individuals were classified as CU and 743 (63.56%) as CI at baseline. Baseline demographic and clinical characteristics are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline demographic and clinical characteristics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOverall (\u003cem\u003eN\u0026thinsp;=\u003c/em\u003e\u0026thinsp;1,169\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLB- (\u003cem\u003eN\u0026thinsp;=\u003c/em\u003e\u0026thinsp;888)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLB+ (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;281)\u003c/p\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 \u003cp\u003eAge, y, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.05 (7.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72.59 (7.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.49 (7.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex, No. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e551 (47.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e437 (49.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114 (40.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e618 (52.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e451 (50.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (59.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRace, No. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1091 (93.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e821 (92.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e270 (96.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (3.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36 (4.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20 (1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHawaiian/Other PI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMore than one\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11 (1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (0.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity, No. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot Hispanic/Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1127 (96.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e853 (96.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e274 (97.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic/Latino\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36 (3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30 (3.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCognitive status, No. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e426 (36.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e347 (39.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (28.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e743 (63.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e541 (60.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e202 (71.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMSE, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1168 (27.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.35 (2.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.95 (3.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCDR-SB, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.74 (2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.55 (2.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34 (2.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPOE \u0026epsilon;4, No. carries (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e530 (46.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e388 (44.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e142 (50.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSF A\u0026beta;1\u0026ndash;42, No. positive (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e604 (61.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e417 (57.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e187 (75.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSF A\u0026beta;1\u0026ndash;42, pg/mL, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e934.51 (446.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e980.31 (448.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e799.18 (415.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSF p-tau181, No. positive (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e525 (53.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e384 (52.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141 (57.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSF p-tau181, pg/mL, mean (SD)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28.65 (15.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28.66 (15.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.62 (13.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParticipants with follow-up data, No. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e850 (72.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e638 (71.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e212 (75.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFollow-up, y, mean (SD)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.64 (2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.75 (2.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.32 (1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 presents baseline demographic and clinical characteristics of the overall study population, stratified by LB status (LB- and LB+).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMissing CSF A\u0026beta;1-42 and p-tau181: 158 LB-, 34 LB+. Missing MMSE: 1 LB-. Missing CDR-SB:. 2 LB-, 1 LB+. Missing APOE \u0026epsilon;4: 7 LB-\u003c/p\u003e\n\u003cp\u003e* For participants with available follow-up data.\u003c/p\u003e\n\u003cp\u003eAbbreviations: LB, Lewy body; SD, standard deviation; y, years; PI, Pacific Islander; CU, cognitively unimpaired; CI, cognitively impaired; CSF, cerebrospinal fluid.\u003c/p\u003e\n\u003cp\u003eA total of 850 participants (72.71%) had two or more neuropsychiatric assessments using the NPI-Q within 10 years from baseline. For those participants, the mean and median observation times were 2.64 and 1.99 years, respectively (SD\u0026thinsp;=\u0026thinsp;2.13; interquartile range\u0026thinsp;=\u0026thinsp;1.03\u0026ndash;3.02; with maximum and minimum follow-up times of 9.9 and 0.45 years, respectively). Participants had a mean and median number of observations of 3.46 and 3, respectively (SD\u0026thinsp;=\u0026thinsp;1.70; interquartile range\u0026thinsp;=\u0026thinsp;2\u0026ndash;4; maximum of 11 and minimum of 2 observations, respectively).\u003c/p\u003e\n\u003cp\u003eAssociations between LB pathology and baseline neuropsychiatric symptoms\u003c/p\u003e\n\u003cp\u003eThe frequency of neuropsychiatric symptoms at baseline is presented in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea. In cross-sectional analyses, LB\u0026thinsp;+\u0026thinsp;individuals showed higher rates of anxiety (OR\u0026thinsp;=\u0026thinsp;1.61, 95% CI\u0026thinsp;=\u0026thinsp;1.13 to 2.29, p-value\u0026thinsp;=\u0026thinsp;0.008), apathy (OR\u0026thinsp;=\u0026thinsp;1.67, 95% CI\u0026thinsp;=\u0026thinsp;1.17 to 2.37, p-value\u0026thinsp;=\u0026thinsp;0.004), motor disturbances (OR\u0026thinsp;=\u0026thinsp;1.96, 95% CI\u0026thinsp;=\u0026thinsp;1.18 to 3.24, p-value\u0026thinsp;=\u0026thinsp;0.008), and appetite disturbances (OR\u0026thinsp;=\u0026thinsp;1.63, 95% CI\u0026thinsp;=\u0026thinsp;1.11 to 2.40, p-value\u0026thinsp;=\u0026thinsp;0.01) compared to LB- individuals (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb, model 1). No significant differences were observed for psychosis, agitation, depression, elation, disinhibition, irritability, or sleep (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb, model 1) after controlling for multiple comparisons.\u003c/p\u003e\n\u003cp\u003eFigures \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea, c, e, and g show the percentage of individuals presenting with anxiety, apathy, motor disturbances, or appetite/eating disturbances (statistically significant in model 1) according to their A\u0026beta;, p-tau, and LB pathology status at baseline. When including all three pathologies in the model (model 2), the presence of A\u0026beta;, p-tau, and LB was associated with higher rates of anxiety (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb). For apathy, the presence of A\u0026beta; and LB was associated with a higher prevalence of symptoms (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed). For motor disturbances and appetite disturbances, only LB was associated with a higher prevalence of symptoms (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef, h).\u003c/p\u003e\n\u003cp\u003eThe prevalence of neuropsychiatric symptoms according to AD and LB pathology can be found in Supplementary Table\u0026nbsp;3. We found no significant interactions between LB and A\u0026beta; on anxiety (OR\u0026thinsp;=\u0026thinsp;0.69, 95% CI\u0026thinsp;=\u0026thinsp;0.28 to 1.72, p-value\u0026thinsp;=\u0026thinsp;0.43) or apathy (OR\u0026thinsp;=\u0026thinsp;1.48, 95% CI\u0026thinsp;=\u0026thinsp;0.57 to 3.81, p-value\u0026thinsp;=\u0026thinsp;0.41). Similarly, we observed no interaction between LB and p-tau on anxiety (OR\u0026thinsp;=\u0026thinsp;0.77, 95% CI\u0026thinsp;=\u0026thinsp;0.36 to 1.64, p-value\u0026thinsp;=\u0026thinsp;0.50). When stratifying participants by cognitive status, we found no differences in the frequency of neuropsychiatric symptoms in CU participants (Supplementary Table\u0026nbsp;4). In CI individuals, the presence of LB was associated with higher rates of anxiety, apathy, disinhibition, motor disturbances, and appetite/eating disturbances (Supplementary Table\u0026nbsp;4).\u003c/p\u003e\n\u003cp\u003eAssociations between LB pathology and longitudinal neuropsychiatric symptoms\u003c/p\u003e\n\u003cp\u003eCox proportional hazards regression models showed that LB\u0026thinsp;+\u0026thinsp;individuals had a higher risk of developing psychosis (HR\u0026thinsp;=\u0026thinsp;2.15, 95% CI\u0026thinsp;=\u0026thinsp;1.30 to 3.56, p-value\u0026thinsp;=\u0026thinsp;0.003) and anxiety (HR\u0026thinsp;=\u0026thinsp;1.70, 95% CI\u0026thinsp;=\u0026thinsp;1.22 to 2.36, p-value\u0026thinsp;=\u0026thinsp;0.001) during follow-up compared to LB- individuals (model 3, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). The Kaplan-Meier survival curves illustrating time to onset of psychosis and anxiety symptoms are presented in Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec. No differences in risk were observed for agitation, depression, elation, apathy, disinhibition, irritability, motor disturbances, sleep, or appetite disturbances (model 3, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). After including A\u0026beta; and p-tau in the model, the presence of A\u0026beta; and LB was associated with higher risks of developing psychosis and anxiety during follow-up (model 4, Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of LB, A\u0026beta;, and p-tau on the development of neuropsychiatric symptoms.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eA\u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ep-tau\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLB\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.40 (1.54 to 7.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.78 (0.98 to 3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.81 (1.08 to 3.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.85 (1.26 to 2.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03 (0.73 to 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.61 (1.15 to 2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable 2 presents the results of longitudinal analyses using Cox proportional hazards regression exploring the effects of A\u0026beta;, p-tau and LB status on the development of neuropsychiatric symptoms. All three pathologies were included in the same model, alongside sex, age, and cognitive status (model 4, Supplementary Material). For each neuropsychiatric symptom (psychosis and anxiety), HR with 95% CI and corresponding p-values are provided. HR \u0026gt; 1 indicates an increased risk of developing the symptom in the presence of the pathology.\u003c/p\u003e\n\u003cp\u003eAbbreviations: A\u0026beta;, amyloid-beta; LB, Lewy body; HR, hazard ratio; CI, confidence interval.\u003c/p\u003e\n\u003cp\u003eWe found no significant interactions between LB and A\u0026beta; for psychosis (HR\u0026thinsp;=\u0026thinsp;0.83, 95% CI\u0026thinsp;=\u0026thinsp;0.15 to 5.51, p-value\u0026thinsp;=\u0026thinsp;0.83) or anxiety (HR\u0026thinsp;=\u0026thinsp;0.99, 95% CI\u0026thinsp;=\u0026thinsp;0.44 to 2.21, p-value\u0026thinsp;=\u0026thinsp;0.98). When stratifying participants by cognitive status, Cox proportional hazard regression models showed no differences in the risk of developing neuropsychiatric symptoms in CU individuals when comparing LB\u0026thinsp;+\u0026thinsp;and LB- (Supplementary Table 5). For CI individuals, the presence of LB was associated with a higher risk of developing psychosis and anxiety (Supplementary Table 5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to explore the cross-sectional and longitudinal effects of LB pathology on neuropsychiatric symptoms across the AD continuum. We observed that in vivo presence of LB was associated with higher baseline rates of anxiety, apathy, motor disturbances, and appetite disturbances. Furthermore, in longitudinal analyses, the presence of LB was associated with an increased risk of developing psychotic and anxiety symptoms. The effects of LB were independent of Aβ and p-tau pathology and were more pronounced in CI individuals. These findings reinforce that LB pathology contributes to the development of neuropsychiatric symptoms in AD and suggest that in vivo detection of LB can assist in identifying individuals at risk for psychosis and anxiety.\u003c/p\u003e \u003cp\u003eOur findings are consistent with previous research demonstrating high rates of behavioral disturbances in patients presenting LB pathology (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Specifically, results from our cross-sectional analyses provide new evidence that LB pathology detected in vivo is associated with increased rates of anxiety, apathy, motor disturbances, and appetite/eating disturbances independent of Aβ or p-tau pathology. These symptoms have been previously shown to occur frequently in individuals with a clinical diagnosis of LBD, with reported rates ranging from 40\u0026ndash;60% for anxiety (\u003cspan additionalcitationids=\"CR28 CR29 CR30\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), 30\u0026ndash;55% for apathy (\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), 20\u0026ndash;60% for motor disturbances (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), and 15\u0026ndash;30% for appetite/eating disturbances (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The spectrum of neuropsychiatric disturbances observed in individuals with a clinical diagnosis of LBD is broad, and includes visual hallucinations, delusions, REM sleep behavior disorder, and depression (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In our study, we observed a trend toward a higher frequency of agitation, depression, and disinhibition that did not reach statistical significance after adjusting for covariates and multiple comparisons. One possible explanation for the weak association of these symptoms in our analysis is that we studied participants at earlier stages of LB pathology compared with those who reach full criteria for a clinical diagnosis of LBD. This observation aligns with literature suggesting that in vivo detection of LB can identify individuals in the early stages of symptom development (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). In this sense, we propose that anxiety, apathy, motor disturbances, and appetite/eating disturbances are early neuropsychiatric manifestations potentially arising from LB pathology across the AD continuum.\u003c/p\u003e \u003cp\u003eOur findings suggest that LB and AD pathology (Aβ and p-tau) independently contribute to elevated baseline rates of anxiety, while LB and Aβ pathology significantly increase the risk of developing anxiety over a 10-year period. Clinical and preclinical evidence suggests that LB pathology accumulation in the limbic system plays a role in anxiety development in LBD (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). However, most of the supporting evidence thus far comes from post-mortem studies, which have demonstrated that LB and AD pathology independently contribute to elevated rates of anxiety (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). When comparing individuals with both AD and LB pathology to those with AD alone, findings have been mixed. One study reported that anxiety was more frequent in individuals with LB and AD pathology (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), while others did not observe this association (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In contrast, our current study employs in vivo detection of LB pathology, which allows us to examine the risk of developing anxiety over a 10-year period. In line with our observations showing a higher risk of developing anxiety in participants with Aβ pathology, previous studies have found that CU individuals with high Aβ burden experience increasing anxiety levels over time (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Collectively, our findings reinforce the notion that LB and AD pathology independently contribute to anxiety symptoms across the AD continuum and highlight the potential of in vivo LB detection as a valuable marker for identifying individuals at risk for developing high levels of anxiety.\u003c/p\u003e \u003cp\u003eWhile delusions and hallucinations are hallmark neuropsychiatric symptoms in diagnosed LBD, we did not find differences in psychosis rates in our cross-sectional analyses. On the other hand, over a 10-year follow-up period, we found that individuals with LB pathology were more likely to develop psychotic symptoms. The association between LB pathology and psychotic symptoms has been well-established in post-mortem studies (\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), and the presence of neocortical LB has been linked to psychosis in LBD (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Unlike our cross-sectional findings, Quadalti, Palmqvist (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) observed higher rates of hallucinations in CI individuals with in vivo detected LB pathology in cross-sectional analyses. This discrepancy may derive from the low baseline rates of psychotic symptoms, including hallucinations and delusions, in our study population, which might have limited our power to detect cross-sectional differences. This can potentially be attributed to self-selection bias, as individuals with high levels of psychosis are less likely to enroll in AD-related studies. Overall, our findings support an association between LB pathology measured in vivo and the development of psychotic symptoms during the AD continuum.\u003c/p\u003e \u003cp\u003eFindings from this study should be interpreted with consideration of the following limitations. The cohort consisted of individuals motivated to participate in a dementia study, which may introduce self-selection bias and limit the generalizability of our findings to the broader elderly population. The NPI-Q provides a brief assessment of neuropsychiatric symptoms and may not capture the full complexity and nuance of psychiatric symptomatology. For instance, it may not detect specific nighttime behaviors typically seen in REM sleep behavior disorder. As the NPI-Q is completed by informants, recall bias may influence the accuracy of reported symptoms, particularly for symptoms with subtle or fluctuating presentations. Varying follow-up durations and assessment among participants may introduce bias in the longitudinal analyses. To address this, we employed survival analyses to account for censored data, though residual bias cannot be entirely ruled out. It would be desirable to replicate our results in a population-based cohort.\u003c/p\u003e \u003cp\u003eTo conclude, this study demonstrates that LB pathology measured in vivo is associated with a higher frequency of neuropsychiatric symptoms. These effects were independent of Aβ and p-tau pathologies. Our findings highlight the value of in vivo LB detection in the identification of individuals at a high risk for anxiety and psychosis. Future studies with expanded longitudinal follow-up and comprehensive neuropsychiatric assessments will be critical in further elucidating the temporal relationship between in vivo-measured LB pathology and neuropsychiatric symptom development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflicts of Interest:\u003c/h2\u003e\n\u003cp\u003eJ.T. has served as a paid consultant for Neurotorium and Alzheon Inc, outside of the scope of the current work. E.R.Z. has served on the scientific advisory board or as a consultant for Nintx, Novo Nordisk, Magdalena Biosciences and Masima. He is also a co-founder and minority shareholder of Masima.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\n\u003cp\u003eData collection and sharing for this project was funded by the Alzheimer\u0026apos;s Disease Neuroimaging Initiative (ADNI) NIH Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). The ADNI is funded by the National Institute on Aging (NIH), the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer\u0026apos;s Association; Alzheimer\u0026apos;s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research \u0026amp; Development, LLC.; Johnson \u0026amp; Johnson Pharmaceutical Research \u0026amp; Development LLC.; Lumosity; Lundbeck; Merck \u0026amp; Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.fnih.org\u003c/span\u003e\u003c/span\u003e). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer\u0026apos;s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. T.A.P. is supported by National Institute on Aging awards 5R01AG073267 and 5R01AG075336. B.B., M.S.R., G.B.N., G.P., and P.C.L.F. are supported by the Alzheimer\u0026rsquo;s Association Research Fellowship to promote diversity (AARFD-22-974627; AARFD-24-1313939; AARFD-23-1150249; 24AARFD-1243899; AARFD-22-923814). C.S.A. is supported by the Global Brain Health Institute, Alzheimer\u0026rsquo;s Association, and Alzheimer\u0026rsquo;s Society (GBHI ALZ UK-23-971089), Alzheimer\u0026rsquo;s Association (24AACSF-1200375), and Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior (CAPES, 88887.951210/2024-00). J.T. is funded by the McGill University Faculty of Medicine student fellowship, and the Colin J Adair foundation fellowship.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRobinson JL, Richardson H, Xie SX, Suh E, Van Deerlin VM, Alfaro B, et al. The development and convergence of co-pathologies in Alzheimer\u0026rsquo;s disease. Brain. 2021;144(3):953\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeTure MA, Dickson DW. The neuropathological diagnosis of Alzheimer's disease. Mol Neurodegener. 2019;14(1):32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor J-P, McKeith IG, Burn DJ, Boeve BF, Weintraub D, Bamford C, et al. New evidence on the management of Lewy body dementia. The Lancet Neurology. 2020;19(2):157\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaiardi S, Hansson O, Levin J, Parchi P. In vivo detection of Alzheimer's and Lewy body disease concurrence: Clinical implications and future perspectives. Alzheimer's \u0026amp; Dementia. 2024;20(8):5757\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuadalti C, Palmqvist S, Hall S, Rossi M, Mammana A, Janelidze S, et al. Clinical effects of Lewy body pathology in cognitively impaired individuals. Nature Medicine. 2023;29(8):1964\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollij LE, Mastenbroek SE, Mattsson-Carlgren N, Strandberg O, Smith R, Janelidze S, et al. 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JAMA Psychiatry. 2022;79(4):359\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBayram E, Shan G, Cummings JL. Associations between Comorbid TDP-43, Lewy Body Pathology, and Neuropsychiatric Symptoms in Alzheimer\u0026rsquo;s Disease. Journal of Alzheimer's Disease. 2019;69:953\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGibson LL, Grinberg LT, ffytche D, Leite REP, Rodriguez RD, Ferretti-Rebustini REL, et al. Neuropathological correlates of neuropsychiatric symptoms in dementia. Alzheimer's \u0026amp; Dementia. 2023;19(4):1372\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTosun D, Hausle Z, Iwaki H, Thropp P, Lamoureux J, Lee EB, et al. A cross-sectional study of α-synuclein seed amplification assay in Alzheimer's disease neuroimaging initiative: Prevalence and associations with Alzheimer's disease biomarkers and cognitive function. Alzheimer's \u0026amp; Dementia. 2024;20(8):5114\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, et al. Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 2010;74(3):201\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaufer DI, Cummings JL, Ketchel P, Smith V, MacMillan A, Shelley T, et al. Validation of the NPI-Q, a brief clinical form of the Neuropsychiatric Inventory. J Neuropsychiatry Clin Neurosci. 2000;12(2):233\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConcha-Marambio L, Pritzkow S, Shahnawaz M, Farris CM, Soto C. Seed amplification assay for the detection of pathologic alpha-synuclein aggregates in cerebrospinal fluid. Nat Protoc. 2023;18(4):1179\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHansson O, Seibyl J, Stomrud E, Zetterberg H, Trojanowski JQ, Bittner T, et al. CSF biomarkers of Alzheimer's disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement. 2018;14(11):1470\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlennow K, Shaw LM, Stomrud E, Mattsson N, Toledo JB, Buck K, et al. Predicting clinical decline and conversion to Alzheimer's disease or dementia using novel Elecsys Aβ(1\u0026ndash;42), pTau and tTau CSF immunoassays. Sci Rep. 2019;9(1):19024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B (Methodological). 1995;57(1):289\u0026ndash;300.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBallard C, Aarsland D, Francis P, Corbett A. Neuropsychiatric Symptoms in Patients with Dementias Associated with Cortical Lewy Bodies: Pathophysiology, Clinical Features, and Pharmacological Management. Drugs \u0026amp; Aging. 2013;30(8):603\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBallard C, Holmes C, McKeith I, Neill D, O\u0026rsquo;Brien J, Cairns N, et al. Psychiatric Morbidity in Dementia With Lewy Bodies: A Prospective Clinical and Neuropathological Comparative Study With Alzheimer\u0026rsquo;s Disease. American Journal of Psychiatry. 1999;156(7):1039\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSegers K, Benoit F, Meyts JM, Surquin M. Anxiety symptoms are quantitatively and qualitatively different in dementia with Lewy bodies than in Alzheimer's disease in the years preceding clinical diagnosis. Psychogeriatrics. 2020;20(3):242\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorroni B, Agosti C, Padovani A. Behavioral and psychological symptoms in dementia with Lewy-bodies (DLB): frequency and relationship with disease severity and motor impairment. Arch Gerontol Geriatr. 2008;46(1):101\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAarsland D, Br\u0026oslash;nnick K, Ehrt U, De Deyn PP, Tekin S, Emre M, et al. Neuropsychiatric symptoms in patients with Parkinson's disease and dementia: frequency, profile and associated care giver stress. J Neurol Neurosurg Psychiatry. 2007;78(1):36\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwertner E, Pereira JB, Xu H, Secnik J, Winblad B, Eriksdotter M, et al. Behavioral and Psychological Symptoms of Dementia in Different Dementia Disorders: A Large-Scale Study of 10,000 Individuals. Journal of Alzheimer's Disease. 2022;87:1307\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRossi M, Candelise N, Baiardi S, Capellari S, Giannini G, Orr\u0026ugrave; CD, et al. Ultrasensitive RT-QuIC assay with high sensitivity and specificity for Lewy body-associated synucleinopathies. Acta Neuropathol. 2020;140(1):49\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonovan NJ, Locascio JJ, Marshall GA, Gatchel J, Hanseeuw BJ, Rentz DM, et al. Longitudinal Association of Amyloid Beta and Anxious-Depressive Symptoms in Cognitively Normal Older Adults. Am J Psychiatry. 2018;175(6):530\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabulal GM, Ghoshal N, Head D, Vernon EK, Holtzman DM, Benzinger TLS, et al. Mood Changes in Cognitively Normal Older Adults are Linked to Alzheimer Disease Biomarker Levels. Am J Geriatr Psychiatry. 2016;24(11):1095\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBallard CG, Jacoby R, Ser TD, Khan MN, Munoz DG, Holmes C, et al. Neuropathological Substrates of Psychiatric Symptoms in Prospectively Studied Patients With Autopsy-Confirmed Dementia With Lewy Bodies. American Journal of Psychiatry. 2004;161(5):843\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"mp","sideBox":"Learn more about [Molecular Psychiatry](http://www.nature.com/mp/)","snPcode":"41380","submissionUrl":"https://mts-mp.nature.com/cgi-bin/main.plex","title":"Molecular Psychiatry","twitterHandle":"@molpsychiatry","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6270682/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6270682/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntracellular alpha-synuclein aggregates, known as Lewy bodies (LB), are commonly observed in Alzheimer\u0026rsquo;s disease (AD) dementia. Post-mortem studies have shown a higher frequency of neuropsychiatric symptoms among individuals with AD and LB co-pathology. However, the effects of in vivo-measured LB pathology on neuropsychiatric symptoms in AD remain underexplored. This study aimed to evaluate cross-sectional and longitudinal effects of in vivo-measured LB pathology on neuropsychiatric symptoms across the AD continuum. We analyzed data from 1,169 participants from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI). Participants had in vivo measures of LB pathology (assessed using an alpha-synuclein seed amplification assay), amyloid-beta (Aβ) and phosphorylated tau (p-tau) levels in cerebrospinal fluid (CSF), and neuropsychiatric symptoms evaluated using the Neuropsychiatric Inventory-Questionnaire (NPI-Q). Logistic and Cox proportional hazards regression models were used to assess cross-sectional and longitudinal effects, respectively, adjusting for age, sex, and cognitive status. Participants had a mean baseline age of 73.05 (SD 7.22) years, 47.13% were women, 426 (36.44%) cognitively unimpaired, and 743 (63.56%) cognitively impaired. In cross-sectional analyses, LB pathology was associated with higher rates of anxiety, apathy, motor disturbances, and appetite disturbances. In longitudinal analyses, LB pathology increased the risk of developing psychosis and anxiety. These effects were independent of Aβ and p-tau. Our results suggest that in vivo-measured LB pathology is closely associated with neuropsychiatric symptoms across the AD continuum. These findings underscore the potential of in vivo LB detection as a marker for identifying individuals at increased risk of neuropsychiatric symptoms, both in clinical trials and in clinical practice.\u003c/p\u003e","manuscriptTitle":"In vivo-measured Lewy body pathology is associated with neuropsychiatric symptoms across the Alzheimer’s disease continuum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-26 09:51:23","doi":"10.21203/rs.3.rs-6270682/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-07-28T09:09:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-06-05T13:30:41+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-05-21T15:29:42+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-05-19T21:57:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-24T13:19:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-24T13:18:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Psychiatry","date":"2025-03-21T14:31:29+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-03-21T14:23:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"mp","sideBox":"Learn more about [Molecular Psychiatry](http://www.nature.com/mp/)","snPcode":"41380","submissionUrl":"https://mts-mp.nature.com/cgi-bin/main.plex","title":"Molecular Psychiatry","twitterHandle":"@molpsychiatry","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8e5461ec-ac4d-4436-a1af-bc9a3b137f2f","owner":[],"postedDate":"March 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46127152,"name":"Health sciences/Diseases"},{"id":46127153,"name":"Health sciences/Biomarkers/Predictive markers"}],"tags":[],"updatedAt":"2025-12-14T08:05:47+00:00","versionOfRecord":{"articleIdentity":"rs-6270682","link":"https://doi.org/10.1038/s41380-025-03400-7","journal":{"identity":"molecular-psychiatry","isVorOnly":false,"title":"Molecular Psychiatry"},"publishedOn":"2025-12-14 05:00:00","publishedOnDateReadable":"December 14th, 2025"},"versionCreatedAt":"2025-03-26 09:51:23","video":"","vorDoi":"10.1038/s41380-025-03400-7","vorDoiUrl":"https://doi.org/10.1038/s41380-025-03400-7","workflowStages":[]},"version":"v1","identity":"rs-6270682","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6270682","identity":"rs-6270682","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}