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Browsing by Subject "Cognitive domains"
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Item 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 MedicineBackground: 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.Item Blood-based gene and co-expression network levels are associated with AD/MCI diagnosis and cognitive phenotypes(Wiley, 2025-01-09) Chen, Xuan; Reddy, Joseph S.; Wang, Xue; Quicksall, Zachary; Nguyen, Thuy; Reyes, Denise A.; Graff-Radford, Jonathan; Jack, Clifford R., Jr.; Lowe, Val J.; Knopman, David S.; Petersen, Ronald C.; Kantarci, Kejal; Nho, Kwangsik; Allen, Mariet; Carrasquillo, Minerva M.; Saykin, Andrew J.; Ertekin-Taner, Nilüfer; Radiology and Imaging Sciences, School of MedicineBackground: Alzheimer’s disease (AD) patients have decline in cognitive domains including memory, language, visuospatial, and/or executive function and brain pathology including amyloid‐β and tau deposition, neurodegeneration, and frequent vascular co‐pathologies detectable by neuroimaging and/or cerebrospinal fluid biomarkers. However, molecular disease mechanisms are complex and heterogeneous. It is necessary to develop cost‐effective blood‐based biomarkers reflecting brain molecular perturbations in AD. We identified blood‐based gene and co‐expression network level changes associated with AD/mild cognitive impairment (MCI) diagnosis and AD‐related phenotypes. Method: We performed differential gene expression and weighted gene co‐expression network analysis, followed by meta‐analysis, using blood transcriptome data of 391 participants from the Mayo Clinic Study of Aging and 654 participants from the Alzheimer's Disease Neuroimaging Initiative. The neuroimaging phenotypes include microhemorrhages, infarcts, amyloid burden, hippocampal volume, and white matter hyperintensities. The cognitive phenotypes include standardized cognitive subtest scores and composite scores for memory, language, visuospatial, and executive function. Result: Five out of 18 modules(M) are significantly associated with diagnosis or cognition (FDR‐adjusted p<0.05). M1 and M15 both positively associates with memory, M1 positively associated with language and M15 with visuospatial function. M1 and M15 are enriched in differentially expressed genes (DEGs) associated with language and executive function, respectively. M2 negatively associates with logical memory delayed recall scores(LMDR), memory, executive, and language functions and is enriched in DEGs for these phenotypes. M8 negatively associates with memory, language and executive functions and is enriched in DEGs for memory and language. M12 positively associates with LMDR. M1 and M15 are down‐regulated while M2 and M8 are up‐regulated in AD/MCI patients. Cell‐type enrichment analysis showed M2 is enriched in monocytes and neutrophils; M8 in monocytes; M15 in B cells (FDR <0.05). Gene ontology terms enriched in these modules indicated broad consistency with their cell types. Conclusion: We identified five modules significantly associated with AD/MCI or cognitive phenotypes using blood transcriptome data. These findings nominate blood transcriptome changes and their enriched biological processes as potential pathomechanisms in cognitive decline and AD/MCI development. We aim to investigate these blood transcripts as potential biomarkers for AD or AD‐related phenotypes and therapeutic targets through additional replication and experimental validation studies.