Multi-ancestry meta-analysis and fine-mapping in Alzheimer’s disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published and de novo GWAS from European, East Asian, African American, and Caribbean Hispanic populations to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci and globally assessed the heterogeneity of known risk factors across populations. Additionally we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to Alzheimer's disease risk.

[1]  Y. J. Kim,et al.  Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. , 2022, Nature genetics.

[2]  Michael F. Green,et al.  Mapping genomic loci implicates genes and synaptic biology in schizophrenia , 2022, Nature.

[3]  Nick C Fox,et al.  New insights into the genetic etiology of Alzheimer’s disease and related dementias , 2022, Nature Genetics.

[4]  E. Reiman,et al.  A neurodegenerative disease landscape of rare mutations in Colombia due to founder effects , 2022, Genome medicine.

[5]  J. Haines,et al.  Progranulin mutations in clinical and neuropathological Alzheimer's disease , 2022, Alzheimer's & dementia : the journal of the Alzheimer's Association.

[6]  P. Roussos,et al.  Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits , 2022, Nature Genetics.

[7]  Christopher D. Brown,et al.  The power of genetic diversity in genome-wide association studies of lipids , 2021, Nature.

[8]  Kathryn S. Burch,et al.  On powerful GWAS in admixed populations , 2021, Nature Genetics.

[9]  Alan E. Murphy,et al.  MungeSumstats: a Bioconductor package for the standardization and quality control of many GWAS summary statistics , 2021, Bioinform..

[10]  Laurent F. Thomas,et al.  A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease , 2021, Nature Genetics.

[11]  Alexandra M. Binder,et al.  Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging , 2021, Genome Biology.

[12]  D. Y. Lee,et al.  Potential Novel Genes for Late-Onset Alzheimer’s Disease in East-Asian Descent Identified by APOE-Stratified Genome-Wide Association Study , 2021, Journal of Alzheimer's disease : JAD.

[13]  V. Reus Faculty Opinions recommendation of Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. , 2021, Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature.

[14]  M. Nalls,et al.  Evidence for GRN connecting multiple neurodegenerative diseases. , 2021, Brain communications.

[15]  T. Morizono,et al.  Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer’s disease risk , 2021, Translational Psychiatry.

[16]  Qingqin S. Li,et al.  Differentially expressed genes in Alzheimer’s disease highlighting the roles of microglia genes including OLR1 and astrocyte gene CDK2AP1 , 2021, Brain, behavior, & immunity - health.

[17]  Daniel J. Gaffney,et al.  Genome-wide meta-analysis, fine-mapping, and integrative prioritization implicate new Alzheimer’s disease risk genes , 2021, Nature Genetics.

[18]  O. Andreassen,et al.  The genetic architecture of human complex phenotypes is modulated by linkage disequilibrium and heterozygosity. , 2021, Genetics.

[19]  K. D. Sørensen,et al.  Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction , 2021, Nature genetics.

[20]  E. McDonagh,et al.  Open Targets Platform: supporting systematic drug–target identification and prioritisation , 2020, Nucleic Acids Res..

[21]  R. Mägi,et al.  The genetic architecture of sporadic and multiple consecutive miscarriage , 2020, Nature Communications.

[22]  K. Lunetta,et al.  Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis. , 2020, JAMA neurology.

[23]  Blaine R. Roberts,et al.  Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture , 2020, Nature Communications.

[24]  Dai Zhang,et al.  Independent replications and integrative analyses confirm TRANK1 as a susceptibility gene for bipolar disorder , 2020, Neuropsychopharmacology.

[25]  D. Noh,et al.  Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants , 2020, Nature Communications.

[26]  J. Aguiar,et al.  ABCF1 Regulates dsDNA-induced Immune Responses in Human Airway Epithelial Cells , 2020, bioRxiv.

[27]  William J. Astle,et al.  Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations , 2020, Cell.

[28]  A. Ruiz,et al.  The MAPT H1 Haplotype Is a Risk Factor for Alzheimer’s Disease in APOE ε4 Non-carriers , 2019, Front. Aging Neurosci..

[29]  Sonja W. Scholz,et al.  Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies , 2019, The Lancet Neurology.

[30]  E. Wijsman,et al.  Local ancestry at APOE modifies Alzheimer's disease risk in Caribbean Hispanics , 2019, Alzheimer's & Dementia.

[31]  L. Tan,et al.  Genome-wide association study identifies Alzheimer's risk variant in MS4A6A influencing cerebrospinal fluid sTREM2 levels , 2019, Neurobiology of Aging.

[32]  Christopher D. Brown,et al.  Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx , 2019, Genome Biology.

[33]  Jun Yu,et al.  Genome-Wide Association Studies for Cerebrospinal Fluid Soluble TREM2 in Alzheimer’s Disease , 2019, Front. Aging Neurosci..

[34]  Douglas G. Altman,et al.  Analysing data and undertaking meta‐analyses , 2019, Cochrane Handbook for Systematic Reviews of Interventions.

[35]  Karsten B. Sieber,et al.  Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria , 2019, Nature Communications.

[36]  Karsten B. Sieber,et al.  Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels , 2019, Nature Genetics.

[37]  K. Blennow,et al.  The MS4A gene cluster is a key modulator of soluble TREM2 and Alzheimer’s disease risk , 2019, Science Translational Medicine.

[38]  Kathleen F. Kerr,et al.  Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction , 2019, bioRxiv.

[39]  Karsten B. Sieber,et al.  A catalog of genetic loci associated with kidney function from analyses of a million individuals , 2019, Nature Genetics.

[40]  Michael J. Gloudemans,et al.  Abundant associations with gene expression complicate GWAS follow-up , 2019, Nature Genetics.

[41]  S. Djurovic,et al.  Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes , 2019, Front. Neurosci..

[42]  Jennifer G. Robinson,et al.  Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids , 2019, Nature Genetics.

[43]  Zachary A. Szpiech,et al.  Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations , 2019, Nature Communications.

[44]  M. Kanai,et al.  Genetic and phenotypic landscape of the major histocompatibilty complex region in the Japanese population , 2019, Nature Genetics.

[45]  Jacob F. Degner,et al.  Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval , 2019, bioRxiv.

[46]  James M. Eales,et al.  Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies , 2019, Nature Communications.

[47]  M. Cuccaro,et al.  Ancestral origin of ApoE ε4 Alzheimer disease risk in Puerto Rican and African American populations , 2018, PLoS genetics.

[48]  C. Gieger,et al.  Genome-wide meta-analysis identifies novel determinants of circulating serum progranulin , 2018, Human molecular genetics.

[49]  Y. Kamatani,et al.  A genome-wide association study identifies two novel susceptibility loci and trans population polygenicity associated with bipolar disorder , 2017, Molecular Psychiatry.

[50]  F. McMahon,et al.  Sodium valproate rescues expression of TRANK1 in iPSC-derived neural cells that carry a genetic variant associated with serious mental illness , 2017, bioRxiv.

[51]  R. Mägi,et al.  Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution , 2017, Human molecular genetics.

[52]  Kevin L. Boehme,et al.  Fine-mapping of the human leukocyte antigen locus as a risk factor for Alzheimer disease: A case–control study , 2017, PLoS medicine.

[53]  Janice M. Fullerton,et al.  Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder , 2016, bioRxiv.

[54]  P. Visscher,et al.  Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets , 2016, Nature Genetics.

[55]  V. Pascali,et al.  Unravelling the hidden ancestry of American admixed populations , 2015, Nature Communications.

[56]  Carson C Chow,et al.  Second-generation PLINK: rising to the challenge of larger and richer datasets , 2014, GigaScience.

[57]  S. Marino,et al.  Toll-like receptors in Alzheimer's disease: a therapeutic perspective. , 2014, CNS & neurological disorders drug targets.

[58]  B. Tang,et al.  Investigation of TREM2, PLD3, and UNC5C variants in patients with Alzheimer's disease from mainland China , 2014, Neurobiology of Aging.

[59]  Janice M. Fullerton,et al.  Genome-wide association study reveals two new risk loci for bipolar disorder , 2014, Nature Communications.

[60]  Gad Abraham,et al.  Fast Principal Component Analysis of Large-Scale Genome-Wide Data , 2014, bioRxiv.

[61]  Oscar L Lopez,et al.  Variants in the ATP-binding cassette transporter (ABCA7), apolipoprotein E ϵ4,and the risk of late-onset Alzheimer disease in African Americans. , 2013, JAMA.

[62]  J. Haines,et al.  SORL1 Is Genetically Associated with Late-Onset Alzheimer’s Disease in Japanese, Koreans and Caucasians , 2013, PloS one.

[63]  S. Cichon,et al.  Genome-wide association study meta-analysis of European and Asian-ancestry samples identifies three novel loci associated with bipolar disorder , 2013, Molecular Psychiatry.

[64]  G. Landreth,et al.  Toll-like receptors in Alzheimer's disease. , 2009, Current topics in microbiology and immunology.

[65]  F. Schmidt Meta-Analysis , 2008 .

[66]  M. Burns,et al.  Case-Control Study , 2020, Definitions.

[67]  Tom H. Pringle,et al.  The human genome browser at UCSC. , 2002, Genome research.

[68]  Lars Bertram,et al.  New Frontiers in Alzheimer's Disease Genetics , 2001, Neuron.

[69]  K. Tokunaga,et al.  Genetic link between Asians and native Americans: evidence from HLA genes and haplotypes. , 2001, Human immunology.

[70]  A. Rzhetsky,et al.  The human ATP-binding cassette (ABC) transporter superfamily. , 2001, Genome research.

[71]  C. Williamson,et al.  Therapeutic perspective. , 1951, California medicine.