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

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

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

The Alzheimer's Disease Sequencing Project - Follow Up Study (ADSP-FUS): Increasing ethnic diversity in Alzheimer's genetics research with the addition of potential new cohorts

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 concern in AD genetic studies is a lack of racial-ethnic diversity. The ADSP-FUS collects and sequences existing ethnically diverse and unique cohorts with 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, Asian and Indian). 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 clinical history. Data dictionaries are curated for each cohort by the FUS clinical staff. In total, the ADSP-FUS intends to sequence over 60,000 individuals. Biospecimens are processed and DNA is prepared and allocated through the National Centralized Repository for Alzheimer's (NCRAD). The DNA is delivered to the Uniformed Services University of the Health Sciences (USUHS) for whole genome sequencing (WGS). The resulting raw sequence data is conveyed to the Genome Center for Alzheimer's Disease (GCAD) for processing and harmonization followed QC analysis at University of Pennsylvania and University of Miami resulting in analysis-ready genotype data. Lastly, all clinical, genotype and sequence data are sent to the NIA Genetics of Alzheimer Disease Data Storage Site (NIAGADS), serving as the ASDP-FUS data storage, management and sharing center. Over 60,000 samples have been ascertained and are distributed by ancestry as follows: 7,686 African; 9,652 Hispanic; 40,575 non-Hispanic white (1,400 EOAD and 3,745 autopsy); 89 Amerindian; 4,003 Asian and 2,000 Indian. To date, we have sequenced 8,208 NHW; 5,528 African; 6,149 Hispanic & 89 Amerindian. The ADSP-FUS will enhance ongoing efforts to identify shared and novel genetic risk factors for LOAD among different populations. This project will expand our knowledge of potential genetic risk and protective variants for LOAD across all populations with the hope of developing new treatments that work for everyone

Human whole-exome genotype data for Alzheimer's disease

The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer's Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community