Browsing by Subject "Genome‐wide association studies (GWAS)"

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    Characterization of the A1527G variant of ABCA7 in an animal model for late‐onset Alzheimer’s disease
    (Wiley, 2025-01-03) Bernabe, Cristian S.; Kotredes, Kevin P.; Pandey, Ravi S.; Carter, Gregory W.; Sasner, Michael; Oblak, Adrian L.; Howell, Gareth R.; Lamb, Bruce T.; Territo, Paul R.; MODEL-AD consortium; Medicine, School of Medicine
    Background: Genome‐wide association studies (GWAS) identified the ATP binding cassette subfamily A member 7 (ABCA7) gene as increasing risk for Alzheimer’s disease (AD). ABC proteins transport various molecules across extra and intra‐cellular membranes. ABCA7 is part of the ABC1 subfamily and is expressed in brain cells including neurons, astrocytes, microglia, endothelial cells and pericytes. However, the mechanisms by which variations in ABCA7 increase risk for AD are not known. Method: The IU/JAX/PITT MODEL‐AD Center identified the A1527G variant in ABCA7 (ABCA7*A1527G) as a putative LOAD risk factor. CRISPR/CAS9 was first used to introduce Abca7*A1527G variant to B6.APOE4.Trem2*R47H (LOAD1) mice to assess the transcriptional profiling on brain hemispheres from different ages. The Abca7*A1527G was then incorporated into B6.APOE4.Trem2*R47H.hAb (LOAD2) mice to further evaluate its contribution to LOAD. Female and male LOAD2.Abca7*A1527G and LOAD2 mice were characterized at 4, 12, and 24 months using the following phenotyping pipeline: behavior, PET/CT, multi‐omics, fluid biomarkers, electrophysiology, cognition, and neuropathology. Result: Brain transcriptional profiling showed that Abca7*A1527G induced changes in gene expression that are similar to some of those observed in human AD (e.g., granulocyte/neutrophil migration, and insulin receptor signaling). LOAD2.Abca7*A1527G showed no aging cognitive deficit but did show significant sex‐ and region‐dependent increases in brain glycolysis paralleled by reduced tissue perfusion yielding progressive age‐related uncoupled phenotypes between 4‐12 and 4‐24 months. While multi‐resolution consensus clustering of regional covariance matrices revealed an increase in cluster number and organization in LOAD2.Abca7*A1527G over LOAD2 for both sexes at 4 months, the cluster number and complexity were reduced by 24 months. Importantly, LOAD2.Abca7*A1527G, but not LOAD2, displayed a similar age‐dependent reduction in cluster number for both sexes. Consistent with the uncoupled phenotype, IL6, IL10, and TNFα were elevated in plasma with genotype, but were not age dependent. Conversely, brain levels of IL4, IL12, TNFα, and CXCL1 were decreased, whereas IL2 and IL10 were elevated in LOAD2.Abca7*A1527G relative to LOAD2. Lastly, assessment of plasma levels of Ab40‐Ab42 revealed an age‐dependent increase in both genotypes. Conclusion: Data collected to date support a model whereby variations in ABCA7 exert risk for AD through interactions between cerebrovasculature, microglia, and peripheral immune cells.
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    Polygenic scores for Alzheimer’s disease risk and resilience predict age at onset of amyloid‐β
    (Wiley, 2025-01-03) O’Brien, Eleanor K.; Porter, Tenielle; Fernandez, Shane; Cox, Timothy; Dore, Vincent; Bourgeat, Pierrick; Goudey, Benjamin; Doecke, James D.; Masters, Colin L.; Rowe, Christopher C.; Villemagne, Victor L.; Cruchaga, Carlos; Saykin, Andrew J.; Laws, Simon M.; ADOPIC Consortium (AIBL, ADNI, OASIS); Radiology and Imaging Sciences, School of Medicine
    Background: Genome‐wide association studies (GWAS) have identified numerous genetic variants associated with Alzheimer’s disease (AD) risk, but genetic variation in the onset and progression of AD pathology is less understood. Accumulation of amyloid‐β (Aβ) in the brain is a key pathological hallmark of AD beginning 10 – 20 years prior to cognitive symptoms. We investigated the genetic basis of variation in age at onset (AAO) of brain Aβ by comparing the performance of polygenic scores (PGSs) based on AD risk and resilience with a Aβ‐AAO trait‐specific PGS. Method: 1122 participants from the Alzheimer’s Dementia Onset and Progression in International Cohorts (ADOPIC) study underwent genome‐wide SNP genotyping and assessment of brain Aβ using positron emission tomography (PET) imaging at two or more timepoints. AAO was the age at which participants were estimated to have crossed the 20 centiloid (CL) threshold for high Aβ. We utilised AD risk and resilience GWAS summary statistics and conducted a GWAS for AAO using a cross‐validation approach (10 test‐validation folds). We used PRSice to identify optimal PGSs for Aβ‐AAO for risk (PGSRisk), resilience (PGSResilience) and Aβ‐AAO (PGSAAO). Result: PGSRisk and PGSResilience were both significantly associated with Aβ‐AAO, such that higher PGSRisk and lower PGSResilience were associated with an earlier Aβ‐AAO. PGSRisk showed the strongest association and explained more variance in Aβ‐AAO than did PGSAAO. When stratified by APOE ε4 carriage, the strongest genetic risk factor for AD, the association of PGSRisk with Aβ‐AAO was stronger among ε4 non‐carriers, whilst PGSResilience, was more strongly associated with Aβ‐AAO in ε4 carriers. Conclusion: PGS based on genetic risk and resilience for AD are both significant predictors of the age at which people are estimated to cross the threshold for high brain Aβ burden. Predicting the age at which a person will pass this threshold would enable treatment at an earlier stage, when it may more effectively delay or prevent symptom onset.