Dataset Information

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

ABSTRACT:

Introduction

Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants.

Methods

Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members.

Results

AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously implicated in AD pathology; rs141402160 (NOTCH3) and rs140914494 (NOTCH3) were previously reported; rs200290640 (PIDD1) and rs199752248 (PIDD1) were present in more than one cousin pair; rs61729902 (SNAP91), rs140129800 (COX6A2, AC026471), and rs191804178 (MUC16) were not present in a longevity cohort; and rs148294193 (PELI3) and rs147599881 (FCHO1) approached significance from analysis of AD-related phenotypes. Three variants were validated via evidence of co-segregation to additional relatives (PELI3, ABCA7, and SNAP91).

Discussion

These analyses support ABCA7 and TTR as AD risk genes, expand on previously reported NOTCH3 variant identification, and prioritize seven additional candidate variants.

SUBMITTER: Teerlink CC

PROVIDER: S-EPMC9291865 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

Teerlink Craig C CC Miller Justin B JB Vance Elizabeth L EL Staley Lyndsay A LA Stevens Jeffrey J Tavana Justina P JP Cloward Matthew E ME Page Madeline L ML Dayton Louisa L Cannon-Albright Lisa A LA Kauwe John S K JSK

Alzheimer's & dementia : the journal of the Alzheimer's Association 20210620 2

<h4>Introduction</h4>Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants.<h4>Methods</h4>Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affec ...[more]

PMID: 34151536

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Project description:BackgroundLongevity as a phenotype entails living longer than average and typically includes living without chronic age-related diseases. Recently, several common genetic components to longevity have been identified. This study aims to identify additional genetic variants associated with longevity using unique and powerful analyses of pedigrees with a statistical excess of healthy elderly individuals identified in the Utah Population Database (UPDB).MethodsFrom an existing biorepository of Utah pedigrees, six independent cousin pairs were selected from four extended pedigrees that exhibited an excess of healthy elderly individuals; whole exome sequencing (WES) was performed on two elderly individuals from each pedigree who were either first cousins or first cousins once removed. Rare (<.01 population frequency) variants shared by at least one elderly cousin pair in a region likely to be identical by descent were identified as candidates. Ingenuity Variant Analysis was used to prioritize putative causal variants based on quality control, frequency, and gain or loss of function. The variant frequency was compared in healthy cohorts and in an Alzheimer's disease cohort. Remaining variants were filtered based on their presence in genes reported to have an effect on the aging process, aging of cells, or the longevity process. Validation of these candidate variants included tests of segregation on other elderly relatives.ResultsFifteen rare candidate genetic variants spanning 17 genes shared within cousins were identified as having passed prioritization criteria. Of those variants, six were present in genes that are known or predicted to affect the aging process: rs78408340 (PAM), rs112892337 (ZFAT), rs61737629 (ESPL1), rs141903485 (CEBPE), rs144369314 (UTP4), and rs61753103 (NUP88 and RABEP1). ESPL1 rs61737629 and CEBPE rs141903485 show additional evidence of segregation with longevity in expanded pedigree analyses (p-values = .001 and .0001, respectively).DiscussionThis unique pedigree analysis efficiently identified several novel rare candidate variants that may affect the aging process and added support to seven genes that likely contribute to longevity. Further analyses showed evidence for segregation for two rare variants, ESPL1 rs61737629 and CEBPE rs141903485, in the original longevity pedigrees in which they were initially observed. These candidate genes and variants warrant further investigation.

Project description:IntroductionThe SORL1 locus exhibits protective effects against Alzheimer's disease (AD) across ancestries, yet systematic studies in diverse populations are sparse.MethodsLogistic regression identified AD-associated SORL1 haplotypes in East Asian (N = 5249) and European (N = 8588) populations. Association analysis between SORL1 haplotypes and AD-associated traits or plasma biomarkers was conducted. The effects of non-synonymous mutations were assessed in cell-based systems.ResultsProtective SORL1 variants/haplotypes were identified in the East Asian and European populations. Haplotype Hap_A showed a strong protective effect against AD in East Asians, linked to less severe AD phenotypes, higher SORL1 transcript levels, and plasma proteomic changes. A missense variant within Hap_A, rs2282647-C allele, was linked to a lower risk of AD and decreased expression of a truncated SORL1 protein isoform.DiscussionOur transethnic analysis revealed key SORL1 haplotypes that exert protective effects against AD, suggesting mechanisms of the protective role of SORL1 in AD.HighlightsWe examined the AD-protective mechanisms of SORL1 in the general population across diverse ancestral backgrounds by jointly analyzing data from three East Asian cohorts (ie, mainland China, Hong Kong, and Japan) and a European cohort. Comparative analysis unveiled key ethnic-specific SORL1 genetic variants and haplotypes. Among these, the SORL1 minor haplotype, Hap_A, emerged as the primary AD-protective factor in East Asians. Hap_A exerts significant AD-protective effects in both APOE ε4 carriers and non-carriers. SORL1 haplotype Hap_A is associated with cognitive function, brain volume, and the activity of specific neuronal and immune-related pathways closely connected to AD risk. Protective variants within Hap_A are linked to increased SORL1 expression in human tissues. We identified an isoform-specific missense variant in Hap_A that modifies the function and levels of a truncated SORL1 protein isoform that is poorly investigated.

Project description:Biomedical research studies have generated large multi-omic datasets to study complex diseases like Alzheimer's disease (AD). An important aim of these studies is the identification of candidate genes that demonstrate congruent disease-related alterations across the different data types measured by the study. We developed a new method to detect such candidate genes in large multi-omic case-control studies that measure multiple data types in the same set of samples. The method is based on a gene-centric integrative coefficient quantifying to what degree consistent differences are observed in the different data types. For statistical inference, a Bayesian hierarchical model is used to study the distribution of the integrative coefficient. The model employs a conditional autoregressive prior to integrate a functional gene network and to share information between genes known to be functionally related. We applied the method to an AD dataset consisting of histone acetylation, DNA methylation, and RNA transcription data from human cortical tissue samples of 233 subjects, and we detected 816 genes with consistent differences between persons with AD and controls. The findings were validated in protein data and in RNA transcription data from two independent AD studies. Finally, we found three subnetworks of jointly dysregulated genes within the functional gene network which capture three distinct biological processes: myeloid cell differentiation, protein phosphorylation and synaptic signaling. Further investigation of the myeloid network indicated an upregulation of this network in early stages of AD prior to accumulation of hyperphosphorylated tau and suggested that increased CSF1 transcription in astrocytes may contribute to microglial activation in AD. Thus, we developed a method that integrates multiple data types and external knowledge of gene function to detect candidate genes, applied the method to an AD dataset, and identified several disease-related genes and processes demonstrating the usefulness of the integrative approach.

Dataset Information

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

Introduction

Methods

Results

Discussion

Publications

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease.

Similar Datasets

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