Imaging genomics in the ENIGMA Consortium: Multi‐omics and big data analytics: From understanding disease heterogeneity to precision diagnostics. (7th December 2020)

• Record Type: Journal Article
• Authors: Thompson, Paul M
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.037325
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: We offer an update on recent work by the ENIGMA Consortium, CHARGE Consortium, and UK Biobank ‐ and a worldwide alliance of over 1, 400 scientists ‐ to understand how human genetic and epigenetic variation affect biomarkers of brain aging and Alzheimer's disease (AD). Method: For 10 years, ENIGMA, CHARGE, and (more recently) the UK Biobank have screened the genomes and neuroimaging data from over 50, 000 persons worldwide, as well as epigenome‐wide methylation data, to ask: (1) which common and rare genetic variants affect the brain throughout life? (2) which variants affect brain aging and biomarkers of AD ‐ such as hippocampal volume, longitudinal brain atrophy rates over time, and white matter hyperintensities? (3) how do AD risk variants, in APOE and elsewhere, affect brain biomarkers from youth to old age? For 10 years, we harmonized analyses of worldwide anaotmical MRI, diffusion MRI, rsFMRI, and EEG markers across over 200 cohorts, to examine how genome‐wide genomic variation and epigenetic variants affect structural and functional biomarkers of aging and AD. Result: GWAS in over 51, 662 persons revealed over 200 common genetic variants affecting cortical architecture; of 255 nominally significant loci ( P ≤ 5 × 10 −8 ); 199 survived multiple testing correction ( P ≤ 8.3 × 10 −10 ; 187 surface area; 12 thickness). Variation in cortical and hippocampal structure is genetically correlated with cognitive function, AD, Parkinson's disease, insomnia, major depression and ADHD. ENIGMA's Plasticity Working Group analyzed longitudinal MRI data of 10, 163 persons aged 4 to 99 years, and discovered 5 genome‐wide significant loci and 15 genes influencing brain change rates at different times throughout life, and an age‐dependent effect of the APOE haplotype on brain structure. These age‐dependent influences of common genetic variants implicate immunological and metabolic processes. Epigenome‐wide screens revealed additional loci where methylation levels robustly associate with hippocampal volume in cohorts worldwide. Conclusion: Common genetic variants affect rates of brain change, hippocampal and regional cortical measures, throughout life; coordinated analyses of harmonized data are revealing the timing of genetic and epigenetic drivers of brain aging, and the first catalogs of common variants that associate with longitudinal markers of brain aging.