Copy-number variants (CNVs) are major contributors to human disease. In Alzheimer disease (AD), APP duplications cause autosomal-dominant forms, but the role of CNVs in non-monogenic AD remains poorly characterized. We analyzed rare CNVs (frequency <1%) from 22,319 exomes (4,150 early-onset AD [EOAD, ≤65 years], 8,519 late-onset AD [LOAD], 9,650 unaffected control subjects) using harmonized calling and quality control. After identifying 17 individuals with a pathogenic CNV, we performed exome-wide and gene-set burden analyses. EOAD-affected individuals showed increased burdens of rare CNVs affecting coding genes, particularly deletions in AD-related genes. Integrated loss-of-function (LoF) analysis gathering short truncating variants with deletions showed that ABCA1 (odds ratio [OR] = 5.77 [95% confidence interval 2.25; 17.06], p = 0.0002) and ABCA7 deletions contribute to this deletion burden (OR = 2.29 [1.44; 3.65], p = 0.0006), while CTSB LoF alleles appear as candidates (OR = 5.03 [1.50; 20.71], p = 0.0089). We then performed exome-wide gene-level dosage analysis and highlighted 18 genes across five loci with a false discovery rate of <10%, including the 22q11.21 central region, where deletions were restricted to EOAD (including one de novo event) and duplications were enriched in control individuals, with intermediate frequencies in LOAD. We narrowed this locus to the SCARF2-KLHL22-MED15 region after integrating short truncating variants. Replication in 33,977 affected individuals and 362,322 control subjects confirmed association for 22q11.21 dosage with exome-wide significance (ORSCARF2 = 0.34 [0.21; 0.53]; mega-p value = 5.52 × 10-7). SCARF2 overexpression significantly increased amyloid-β uptake, congruent with duplication-associated decreased AD risk. We conclude that rare coding CNVs in a proportion of AD-associated genes and 22q11.21 deletions, including some found in DiGeorge syndrome, increase AD risk. Conversely, we identify 22q11.21 duplication as a strong AD-risk-decreasing factor.
O. Quenez, Catherine Schramm, K. Cassinari et al.· American Journal of Human Ge...· 1 citation
This study illustrates that GWAS with high-scale imputation may still help to unravel the biological mechanism behind circulating lipid levels and identifies more new rare and low-frequency functional variants associated with circulating lipid levels.
E. V. van Leeuwen, A. Sabo, J. Bis et al.· 0 citations
Genetic variation shapes brain structure, yet it remains unclear whether this neuroanatomical expression of genotype is reflected in circulating proteomic profiles, which provide functional molecular readouts of biological processes. Addressing this question requires integrating genetic, neuroimaging, and proteomic data within the same individuals, which is methodologically non-trivial. To address this challenge, we used brain-genotype scores, an approach recently developed in our lab that allows the creation of individual-level, SNP-specific neuroanatomical representations of genotype learned directly from whole-brain structural MRI. Adapting these scores to proteomics, we tested associations in UK Biobank between 120 brain-genotype scores and plasma levels of 2,920 proteins, followed by pathway and tissue-enrichment analyses to assess biological coherence. After FDR correction, brain-genotype scores yielded 116 significant genomic-neuroimaging-proteomic associations across 49 scores and 52 proteins; none were detected using conventional SNP dosage models, and they explained substantially more variance in protein levels than genotype alone. Enrichment analyses identified convergent immune, metabolic, signalling, and cell-cycle pathways, with tissue enrichment spanning brain, liver, pancreas, and hypothalamus. Several identified proteins overlapped with prior imaging-proteomic literature, supporting biological plausibility. These findings demonstrate that brain-genotype scores reveal biologically meaningful proteomic variation beyond conventional genotype analyses, providing a framework for linking genetic variation, brain structure, and the circulating proteome.
K. Alhasani, U. Ghose, L. Winchester et al.· medRxiv· 0 citations
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