Browsing by Author "Klinedinst, Brandon"

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    A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores
    (BMC, 2023-06-22) Kang, Moonil; Ang, Ting Fang Alvin; Devine, Sherral A.; Sherva, Richard; Mukherjee, Shubhabrata; Trittschuh, Emily H.; Gibbons, Laura E.; Scollard, Phoebe; Lee, Michael; Choi, Seo-Eun; Klinedinst, Brandon; Nakano, Connie; Dumitrescu, Logan C.; Durant, Alaina; Hohman, Timothy J.; Cuccaro, Michael L.; Saykin, Andrew J.; Kukull, Walter A.; Bennett, David A.; Wang, Li-San; Mayeux, Richard P.; Haines, Jonathan L.; Pericak-Vance, Margaret A.; Schellenberg, Gerard D.; Crane, Paul K.; Au, Rhoda; Lunetta, Kathryn L.; Mez, Jesse B.; Farrer, Lindsay A.; Radiology and Imaging Sciences, School of Medicine
    Background: More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. Methods: We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. Results: Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. Conclusion: Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.
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    White Matter Abnormalities and Cognition in Aging and Alzheimer Disease
    (American Medical Association, 2025-06-09) Peter, Christopher; Sathe, Aditi; Shashikumar, Niranjana; Pechman, Kimberly R.; Workmeister, Abigail W.; Jackson, T. Bryan; Huo, Yuankai; Mukherjee, Shubhabrata; Mez, Jesse; Dumitrescu, Logan C.; Gifford, Katherine A.; Bolton, Corey J.; Gaynor, Leslie S.; Risacher, Shannon L.; Beason-Held, Lori L.; An, Yang; Arfanakis, Konstantinos; Erus, Guray; Davatzikos, Christos; Tosun-Turgut, Duygu; Habes, Mohamad; Wang, Di; Toga, Arthur W.; Thompson, Paul M.; Zhang, Panpan; Schilling, Kurt G.; Albert, Marilyn; Kukull, Walter; Biber, Sarah A.; Landman, Bennett A.; Bendlin, Barbara B.; Johnson, Sterling C.; Schneider, Julie; Barnes, Lisa L.; Bennett, David A.; Jefferson, Angela L.; Resnick, Susan M.; Saykin, Andrew J.; Crane, Paul K.; Cuccaro, Michael L.; Hohman, Timothy J.; Archer, Derek B.; Alzheimer’s Disease Sequencing Project Phenotype Harmonization Consortium (ADSP-PHC) Analyst Team; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Biomarkers of Cognitive Decline Among Normal Adults (BIOCARD) Study Team; Alzheimer’s Disease Sequencing Project (ADSP); Zaras, Dimitrios; Yang, Yisu; Durant, Alaina; Kanakaraj, Praitayini; Kim, Michael E.; Gao, Chenyu; Newlin, Nancy R.; Ramadass, Karthik; Khairi, Nazirah Mohd; Li, Zhiyuan; Yao, Tianyuan; Choi, Seo-Eun; Klinedinst, Brandon; Lee, Michael L.; Scollard, Phoebe; Trittschuh, Emily H.; Sanders, Elizabeth A.; Radiology and Imaging Sciences, School of Medicine
    Importance: There has yet to be a large-scale study quantifying the association between white matter microstructure and cognitive performance and decline in aging and Alzheimer disease (AD). Objective: To investigate the associations between tract-specific white matter microstructure and cognitive performance and decline in aging and AD-related cognitive impairment. Design, setting, and participants: This prognostic study of aging and AD, a secondary data analysis of multisite cohort studies, acquired data from 9 cohorts between September 2002 and November 2022. Participants were eligible if they had diffusion-weighted magnetic resonance imaging (dMRI) data, domain-specific cognitive composite z scores, demographic and clinical data, were aged 50 years or older, and passed neuroimaging quality control. Demographic and clinical covariates included age, sex, education, race and ethnicity, APOE haplotype status (ε2, ε3, ε4), and clinical status. The present study was conducted from June 2024 to February 2025. Exposures: White matter microstructure and cognitive performance and decline. Main outcomes and measures: Clinical diagnosis, imaging measures (dMRI, T1-weighted MRI, and amyloid and tau positron emission tomography), and cognitive tests. Results: Of 4467 participants who underwent 9208 longitudinal cognitive sessions, 2698 (60.4%) were female, and the mean age (SD) was 74.3 (9.2) years; 3213 were cognitively unimpaired, 972 had mild cognitive impairment, and 282 had AD dementia. White matter free water (FW) showed the strongest associations with cross-sectional cognitive performance and longitudinal cognitive decline across all domains, particularly memory. FW in limbic tracts, such as the cingulum, presented the strongest associations with both memory performance (cingulum: β = -0.718; P < .001; fornix: β = -1.069; P < .001) and decline (cingulum: β = -0.115; P < .001; fornix: β = -0.153; P < .001). White matter FW measures interacted with baseline diagnosis, gray matter atrophy, APOE ε4 status, and amyloid positivity to predict poorer cognitive performance and accelerated cognitive decline. Noteworthy interactions include fornix FW and hippocampal volume (β = 10.598; P < .001), cingulum FW and SPARE-AD index (β = -0.532; P < .001), and inferior temporal gyrus transcallosal tract FW and baseline diagnosis (β = -0.537; P < .001), all predicting poorer memory performance. Conclusions and relevance: White matter microstructural changes, particularly FW, play a critical role in cognitive decline in aging and AD-related cognitive impairment. These findings highlight the importance of FW correction in dMRI studies and highlight the limbic system, especially the cingulum and fornix, as key regions associated with cognitive decline; the interaction models highlight that integrating FW-corrected metrics with other AD biomarkers may further elucidate the biological mechanisms of neurodegeneration in aging.