Analysis of individual families implicates noncoding DNA variation and multiple biological pathways in Alzheimer's disease risk: Genetics/genetic factors of Alzheimer's disease. (7th December 2020)

• Record Type: Journal Article
• Authors: Wijsman, Ellen M.; Day, Tyler R.; Thornton, Timothy A.; Horimoto, Andrea R.; Blue, Elizabeth E.; Bis, Josh C.; Sohi, Harkirat K.; Nato, Alejandro Q.; Nafikov, Rafael A.; Navas, Patrick; Saad, Mohamad; Tsuang, Debby W.; Barral, Sandra; Vardarajan, Badri N.; Beecham, Gary W.; Martin, Eden R.; van Duijn, Cornelia M.; Pericak‐Vance, Margaret A.; Mayeux, Richard
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 3
• 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.046456
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Late‐onset Alzheimer's disease (AD) is a complex disorder with multiple genetic risk factors. Linkage and association analysis have mapped dozens of loci in pooled analysis of many pedigrees or large numbers of unrelated cases and controls. Identification of the underlying DNA risk variants in the regions of interest (ROIs) has been complicated by both the genetic heterogeneity and the cost, until recently, of comprehensive DNA sequencing in ROIs. The known loci also leave much heritability unexplained. Method: We used the families in the AD Sequencing Project (ADSP) discovery family sample to identify variants of interest from whole genome sequences (WGS), and through the variants, genes implicated in risk. We used SNP‐based multipoint linkage analysis to identify ROIs with rare VOIs, carrying out analysis without trimming pedigrees. We pursued all ROIs with family‐specific lodmax scores >1.9, reducing the variants of interest by several filters. We carried out pedigree‐based genotype imputation from the available WGS data, followed by family‐based association analysis, filtered for low population minor allele frequency. We prioritized genes with a low false‐discovery rate for association of single‐cell transcription in brain with AD disease state (PMID:31209304), and genes with high expression in bulk brain (PMID: 24309898). Result: We obtained 46 distinct ROIs representing lodmax 1.9‐3.5 per ROI in each of 26 of the 110 ADSP discovery families analyzed. 29 ROIs further investigated in 16 of the families yielded 59 prioritized genes, with 1‐11 genes/ROI. Only 4 out of 321 variants that passed all filters in these genes were in exons, with minimal overlap with genes identified in AD GWASs. Only one ROI occurred in two families, with evidence for a shared‐haplotype between these families, implicating FBXO2 and FBXO44 . Both genes are implicated in ubiquitination, while FBXO2 interacts with BACE1 . Multiple pathways, both known and new, are implicated, including the ubiquitin‐proteasome system, neural development and maintenance, and mitochondrial functions. Conclusion: This analysis underscores the evidence for extensive genetic heterogeneity and rare variants underlying AD risk, along with multiple potential mechanisms. The preponderance of prioritize non‐coding variants suggests alterations in gene regulation and/or expression as an aspect of AD genetic risk.