Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition

ADSP Whole Genome Sequencing (WGS) Release 3 data update from Genome Center for Alzheimer’s Disease

Background The Genome Center for Alzheimer’s Disease (GCAD) coordinates the integration and meta‐analysis of all available Alzheimer’s disease (AD) relevant whole genome sequencing (WGS) data with the goal of identifying AD risk or protective genetic variants and eventual therapeutic targets. The WGS datasets are generated via the collaboration of scientists from the Alzheimer’s Disease Sequencing Project (ADSP) and GCAD. With the vision to minimize data heterogeneity, introduced by different sequencing protocols and machines, GCAD processes all samples using identical pipelines and performs quality assurance (QA) checks. Methods Raw sequencing data (FASTQs or BAMs) were aligned to GRCh38/hg38 by BWA, and variant calling and joint genotyping were done by GATK. Furthermore, Smoove, Manta and Streka were applied to generate structural variant (SV) calls per sample. QA checks including sex, contamination and genotype concordance as well as the ADSP QC protocol were performed to evaluate the quality of samples and variants. To facilitate the access and usage of the big joint‐genotyped VCF files, we introduced a compact version for storing variant info and sample genotypes only. Results We dropped 235 (1.3%) samples of poor coverage (30x). All samples’ CRAMs, gVCFs from GATK, and VCFs from the three SV callers were deposited into NIAGADS Data Sharing Service (DSS) (https://dss.niagads.org/) for public distribution. In addition, joint‐genotype VCFs are available in both compact and QC versions. This joint‐genotype VCF contains >206M bi‐allelic single‐nucleotide variants, 16M bi‐allelic indels and 28M multi‐allelic variants, with 96% of variants remaining after stringent QC. Conclusion The ADSP and GCAD generate high quality genotype calls and SV calls. Currently the project is processing ∼37,000 WGS samples sequenced primarily through the ADSP Follow‐Up Study, which will contain a more ancestrally diverse set of populations. We anticipate this 2022 release will continue to benefit the research community studying AD genetics

Identification of rare coding variants associated with Alzheimer’s disease

Abstract Background Previous whole exome sequencing (WES) studies of Alzheimer’s disease (AD) have identified genome‐wide significant associations with rare variants in several novel genes and highlighted the need for investigations in larger samples. We combined WES and whole genome sequencing (WGS) data assembled by the Alzheimer Disease Sequencing Project (ADSP) to increase the power for detecting associations of AD with rare variants in gene coding regions. Method We developed an efficient computational pipeline to perform both pre‐merging and post‐merging genotype, variant and sample‐level quality control (QC) on WGS data containing 16,905 individuals and WES data for 20,504 individuals. The resultant sample included participants from European (EA, 11,279 AD cases, 8,924 controls), African American (AA, 2,757 AD cases, 4,336 controls), and Caribbean Hispanic (CH 1,438 AD cases, 3,256 controls) ancestries. We employed GENESIS to test association of AD with 250,465 bi‐allelic QC’d variants using a logistic model including covariates for age, sex, exome capture kit, read length, and ancestry principal components (PCs). Result In the total sample, variants from APOE and other known AD genes including SORL1 (P = 5.30×10‐7), NECTIN2 (P = 6.94×10‐7), and TREM2 R47H (P = 2.34×10‐13) crossed or neared the study‐wide significance (SWS) threshold of P = 2.00×10‐7 (0.05/250,465). SWS or borderline significant associations were also found with variants in several novel loci including TKTL2 (P = 2.35×10‐8), D2HGDH , (P = 1.09×10‐7) , CECR1 (P = 4.02×10‐7), PDHA2 (P = 2.76×10‐7), GOLGA1 (P = 1.72×10‐7), CYLD (P = 1.84×10‐7), and RP11‐243M5.4 (P = 1.37×10‐7). PSEN1 missense mutation G206A (rs63750082) previously associated with early onset AD in the CH group, was significantly associated with late onset AD in the same population (P = 1.58×10‐13). SWS association of AD with APOE was observed in all groups. Significant associations were also observed with variants in SERPINB8 (P = 3.77×10‐9) and FAM171A (P = 7.20×10‐7) in EAs and TLR4 (P = 4.58×10‐7) in CH. Associations with several top‐ranked variants were replicated in the Alzheimer’s Disease Genetics Consortium GWAS dataset that were imputed using the TOPMed reference panel and ADSP 5K WGS dataset. Conclusion We demonstrated that merging WGS and WES datasets can increase power to detect associations with rare coding variants in genes including ones previously implicated in AD ( CYLD and TLR4) and early‐onset stroke ( CECR1 )

The Alzheimer’s disease sequencing project–follow up study (ADSP‐FUS): Increasing ethnic diversity in Alzheimer’s genetics research with addition of potential new cohorts

Background The ADSP‐FUS is a National Institute on Aging (NIA) initiative focused on identifying genetic risk and protective variants for late‐onset Alzheimer Disease (LOAD). A major concern in AD genetic studies is a lack of racial‐ethnic diversity. The ADSP‐FUS collects and sequences existing both ethnically diverse and unique cohorts with extensive clinical data to expand the utility of new discoveries for individuals from all populations. Additional multi‐ethnic cohorts are presently being recruited (e.g. Amerindian, Korean and Indian). Method The cohorts consist of participants from studies of AD, dementia, and aging‐related conditions. Clinical classification (i.e., AD, dementia, and non‐affected) is implemented using algorithms based on a minimal set of criteria derived from standard measures (e.g., global cognitive screeners, dementia rating scales, etc.) and pertinent clinical history. Data dictionaries are generated for each cohort by clinical staff at Columbia University and University of Miami (UM). In total, ADSP‐FUS intends to sequence over 40,000 individuals. Existing biospecimens were obtained and processed through the National Centralized Repository for Alzheimer’s (NCRAD), the primary site for preparation and allocation of DNA, which is then delivered to the Uniformed Services University of the Health Sciences (USUHS) for whole genome sequencing (WGS). The resulting raw sequence data is delivered to the Genome Center for Alzheimer’s Disease (GCAD) for processing and harmonization followed by quality control analysis at University of Pennsylvania and University of Miami into analysis‐ready genotype data. The final step is delivery of clinical, genotype and sequence data to the NIA Genetics of Alzheimer Disease Data Storage Site (NIAGADS), which serves as the ASDP‐FUS data storage, management and sharing center. Results Over 30,000 samples have been ascertained and are distributed as follows: 7,896 with African ancestry; 9,475 with Hispanic ancestry; 13,531 with non‐Hispanic white ancestry (1,400 EOAD and 3,745 autopsy) and 89 with Amerindian ancestry. Conclusion The ADSP‐FUS is designed to enhance ongoing efforts for the identification of shared and novel genetic risk factors for LOAD among different populations. This project will expand our current knowledge of potential genetic risk and protective variants for LOAD across all populations with the hope of developing new treatments