Browsing by Subject "Genetic loci"
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Item A meta-analysis of two genome-wide association studies to identify novel loci for maximum number of alcoholic drinks(Springer, 2013) Kapoor, Manav; Wang, Jen-Chyong; Wetherill, Leah; Le, Nhung; Bertelsen, Sarah; Hinrichs, Anthony L.; Budde, John; Agrawal, Arpana; Bucholz, Kathleen; Dick, Danielle; Harari, Oscar; Hesselbrock, Victor; Kramer, John; Nurnberger, John I., Jr.; Rice, John; Saccone, Nancy; Schuckit, Marc; Tischfield, Jay; Porjesz, Bernice; Edenberg, Howard J.; Bierut, Laura; Foroud, Tatiana; Goate, Alison; Medical and Molecular Genetics, School of MedicineMaximum number of alcoholic drinks consumed in a 24-h period (maxdrinks) is a heritable (>50 %) trait and is strongly correlated with vulnerability to excessive alcohol consumption and subsequent alcohol dependence (AD). Several genome-wide association studies (GWAS) have studied alcohol dependence, but few have concentrated on excessive alcohol consumption. We performed two GWAS using maxdrinks as an excessive alcohol consumption phenotype: one in 118 extended families (N = 2,322) selected from the Collaborative Study on the Genetics of Alcoholism (COGA), and the other in a case-control sample (N = 2,593) derived from the Study of Addiction: Genes and Environment (SAGE). The strongest association in the COGA families was detected with rs9523562 (p = 2.1 × 10(-6)) located in an intergenic region on chromosome 13q31.1; the strongest association in the SAGE dataset was with rs67666182 (p = 7.1 × 10(-7)), located in an intergenic region on chromosome 8. We also performed a meta-analysis with these two GWAS and demonstrated evidence of association in both datasets for the LMO1 (p = 7.2 × 10(-7)) and PLCL1 genes (p = 4.1 × 10(-6)) with maxdrinks. A variant in AUTS2 and variants in INADL, C15orf32 and HIP1 that were associated with measures of alcohol consumption in a meta-analysis of GWAS studies and a GWAS of alcohol consumption factor score also showed nominal association in the current meta-analysis. The present study has identified several loci that warrant further examination in independent samples. Among the top SNPs in each of the dataset (p ≤ 10(-4)) far more showed the same direction of effect in the other dataset than would be expected by chance (p = 2 × 10(-3), 3 × 10(-6)), suggesting that there are true signals among these top SNPs, even though no SNP reached genome-wide levels of significance.Item Beyond GWAS: Investigating Structural Variants and Their Segregation in Familial Alzheimer’s Disease(Wiley, 2025-01-09) Gunasekaran, Tamil Iniyan; Reyes-Dumeyer, Dolly; Corvelo, André; Clarke, Wayne E.; Evani, Uday S.; Byrska-Bishop, Marta S.; Basile, Anna O.; Runnels, Alexi; Musunuri, Rajeeva O.; Narzisi, Giuseppe; Faber, Kelley M.; Goate, Alison M.; Boeve, Brad F.; Cruchaga, Carlos; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Rosenberg, Roger N.; Tsuang, Debby W.; Rivera Mejia, Diones; Medrano, Martin; Lantigua, Rafael A.; Sweet, Robert; Bennett, David A.; Wilson, Robert S.; Foroud, Tatiana M.; Dalgard, Clifton L.; Mayeux, Richard; Zody, Michael; Vardarajan, Badri N.; Medical and Molecular Genetics, School of MedicineBackground: Late‐Onset Alzheimer’s Disease (LOAD) is characterized by genetic heterogeneity and there is no single model explaining the genetic mode of inheritance. To date, more than 70 genetic loci associated with AD have been identified but they explain only a small proportion of AD heritability. Structural variants (SVs) may explain some of the missing AD heritability, and specifically, their segregation in AD families has yet to be investigated. Method: We analyzed WGS data from 197 NHW families (926 subjects, 58.5% affected) and 214 CH families (1,340 subjects, 59.17% affected). Manta, Absinthe, and MELT were used for large insertions/deletions calling from short‐read WGS, combined with Sniffles2 calls from 4 ONT‐sequenced genomes and an external SV call set from HGSVC on 32 PacBio‐sequenced genomes from the 1000 Genomes Project. Genotyping produced a unified project‐level VCF. We identified 45,251 insertions and 76,566 deletions genome‐wide. Variants were tested for segregation and pathogenicity using Annot‐SV, cadd‐SV, and Variant Effect Predictor. Segregation required SV presence in all affected family members and only in unaffected members five years younger than average disease onset. Result: We identified 453 insertions and 598 deletions segregating in 78.68% and 87.31% of NHW families, respectively. In CH families, 432 insertions and 460 deletions were segregating in 75.23% and 72.90% of the families, respectively. Genes overlapping with the SVs exhibited high expression levels in brain tissues. Notably, around 93% of insertions and 76% of deletions segregating in NHW and CH families were less than 1 kilobase pair (1kbp) in length. A total of 79 insertions and 96 deletions were found to be segregating in both NHW and CH families. Interestingly, a segregating insertion was observed in CH families overlapping within the CACNA2D3 gene, which was previously reported in a CH GWAS for clinical AD. A deletion segregating in NHW overlapped with the PSEN1, and another in a CH family overlapped with the PTK2B gene. Conclusion: Our findings suggested that there are several SVs associated with familial AD across CH and NHW families. Prioritizing the SVs based on their effects on gene function and expression will be helpful in understanding their contributions in AD.Item CHRNB3 is more strongly associated with Fagerström test for cigarette dependence-based nicotine dependence than cigarettes per day: phenotype definition changes genome-wide association studies results(Wiley, 2012) Rice, John P.; Hartz, Sarah M.; Agrawal, Arpana; Almasy, Laura; Bennett, Siiri; Breslau, Naomi; Bucholz, Kathleen K.; Doheny, Kimberly F.; Edenberg, Howard J.; Goate, Alison M.; Hesselbrock, Victor; Howells, William B.; Johnson, Eric O.; Kramer, John; Krueger, Robert F.; Kuperman, Samuel; Laurie, Cathy; Manolio, Teri A.; Neuman, Rosalind J.; Nurnberger, John I.; Porjesz, Bernice; Pugh, Elizabeth; Ramos, Erin M.; Saccone, Nancy; Saccone, Scott; Schuckit, Marc; Bierut, Laura J.; GENEVA Consortium; Biochemistry and Molecular Biology, School of MedicineAims: Nicotine dependence is a highly heritable disorder associated with severe medical morbidity and mortality. Recent meta-analyses have found novel genetic loci associated with cigarettes per day (CPD), a proxy for nicotine dependence. The aim of this paper is to evaluate the importance of phenotype definition (i.e., CPD versus Fagerström test for cigarette dependence (FTCD) score as a measure of nicotine dependence) on genome-wide association studies of nicotine dependence. Design: Genome-wide association study. Setting: Community sample. Participants: A total of 3365 subjects who had smoked at least one cigarette were selected from the Study of Addiction: Genetics and Environment (SAGE). Of the participants, 2267 were European Americans, 999 were African Americans. Measurements: Nicotine dependence defined by FTCD score ≥4, CPD. Findings: The genetic locus most strongly associated with nicotine dependence was rs1451240 on chromosome 8 in the region of CHRNB3 [odds ratio (OR) = 0.65, P = 2.4 × 10(-8) ]. This association was further strengthened in a meta-analysis with a previously published data set (combined P = 6.7 × 10(-16) , total n = 4200). When CPD was used as an alternate phenotype, the association no longer reached genome-wide significance (β = -0.08, P = 0.0004). Conclusions: Daily cigarette consumption and the Fagerstrom Test for Cigarette Dependence show different associations with polymorphisms in genetic loci.Item Genetic loci associated with skin pigmentation in African Americans and their effects on vitamin D deficiency(Public Library of Science, 2021-02-18) Batai, Ken; Cui, Zuxi; Arora, Amit; Shah-Williams, Ebony; Hernandez, Wenndy; Ruden, Maria; Hollowell, Courtney M. P.; Hooker, Stanley E.; Bathina, Madhavi; Murphy, Adam B.; Bonilla, Carolina; Kittles, Rick A.; Medical and Molecular Genetics, School of MedicineA recent genome-wide association study (GWAS) in African descent populations identified novel loci associated with skin pigmentation. However, how genomic variations affect skin pigmentation and how these skin pigmentation gene variants affect serum 25(OH) vitamin D variation has not been explored in African Americans (AAs). In order to further understand genetic factors that affect human skin pigmentation and serum 25(OH)D variation, we performed a GWAS for skin pigmentation with 395 AAs and a replication study with 681 AAs. Then, we tested if the identified variants are associated with serum 25(OH) D concentrations in a subset of AAs (n = 591). Skin pigmentation, Melanin Index (M-Index), was measured using a narrow-band reflectometer. Multiple regression analysis was performed to identify variants associated with M-Index and to assess their role in serum 25(OH)D variation adjusting for population stratification and relevant confounding variables. A variant near the SLC24A5 gene (rs2675345) showed the strongest signal of association with M-Index (P = 4.0 x 10-30 in the pooled dataset). Variants in SLC24A5, SLC45A2 and OCA2 together account for a large proportion of skin pigmentation variance (11%). The effects of these variants on M-Index was modified by sex (P for interaction = 0.009). However, West African Ancestry (WAA) also accounts for a large proportion of M-Index variance (23%). M-Index also varies among AAs with high WAA and high Genetic Score calculated from top variants associated with M-Index, suggesting that other unknown genomic factors related to WAA are likely contributing to skin pigmentation variation. M-Index was not associated with serum 25(OH)D concentrations, but the Genetic Score was significantly associated with vitamin D deficiency (serum 25(OH)D levels less than 12 ng/mL) (OR, 1.30; 95% CI, 1.04-1.64). The findings support the hypothesis suggesting that skin pigmentation evolved responding to increased demand for subcutaneous vitamin D synthesis in high latitude environments.Item Genome-wide association study identifies 48 common genetic variants associated with handedness(Springer Nature, 2021) Cuellar-Partida, Gabriel; Tung, Joyce Y.; Eriksson, Nicholas; Albrecht, Eva; Aliev, Fazil; Andreassen, Ole A.; Barroso, Inês; Beckmann, Jacques S.; Boks, Marco P.; Boomsma, Dorret I.; Boyd, Heather A.; Breteler, Monique M. B.; Campbell, Harry; Chasman, Daniel I.; Cherkas, Lynn F.; Davies, Gail; de Geus, Eco J. C.; Deary, Ian J.; Deloukas, Panos; Dick, Danielle M.; Duffy, David L.; Eriksson, Johan G.; Esko, Tõnu; Feenstra, Bjarke; Geller, Frank; Gieger, Christian; Giegling, Ina; Gordon, Scott D.; Han, Jiali; Hansen, Thomas F.; Hartmann, Annette M.; Hayward, Caroline; Heikkilä, Kauko; Hicks, Andrew A.; Hirschhorn, Joel N.; Hottenga, Jouke-Jan; Huffman, Jennifer E.; Hwang, Liang-Dar; Ikram, M. Arfan; Kaprio, Jaakko; Kemp, John P.; Khaw, Kay-Tee; Klopp, Norman; Konte, Bettina; Kutalik, Zoltan; Lahti, Jari; Li, Xin; Loos, Ruth J. F.; Luciano, Michelle; Magnusson, Sigurdur H.; Mangino, Massimo; Marques-Vidal, Pedro; Martin, Nicholas G.; McArdle, Wendy L.; McCarthy, Mark I.; Medina-Gomez, Carolina; Melbye, Mads; Melville, Scott A.; Metspalu, Andres; Milani, Lili; Mooser, Vincent; Nelis, Mari; Nyholt, Dale R.; O'Connell, Kevin S.; Ophoff, Roel A.; Palmer, Cameron; Palotie, Aarno; Palviainen, Teemu; Pare, Guillaume; Paternoster, Lavinia; Peltonen, Leena; Penninx, Brenda W. J. H.; Polasek, Ozren; Pramstaller, Peter P.; Prokopenko, Inga; Raikkonen, Katri; Ripatti, Samuli; Rivadeneira, Fernando; Rudan, Igor; Rujescu, Dan; Smit, Johannes H.; Smith, George Davey; Smoller, Jordan W.; Soranzo, Nicole; Spector, Tim D.; St. Pourcain, Beate; Starr, John M.; Stefánsson, Hreinn; Steinberg, Stacy; Teder-Laving, Maris; Thorleifsson, Gudmar; Stefánsson, Kári; Timpson, Nicholas J.; Uitterlinden, André G.; van Duijn, Cornelia M.; van Rooij, Frank J. A.; Vink, Jaqueline M.; Vollenweider, Peter; Vuoksimaa, Eero; Waeber, Gérard; Wareham, Nicholas J.; Warrington, Nicole; Waterworth, Dawn; Werge, Thomas; Wichmann, H-Erich; Widen, Elisabeth; Willemsen, Gonneke; Wright, Alan F.; Wright, Margaret J.; Xu, Mousheng; Zhao, Jing Hua; Kraft, Peter; Hinds, David A.; Lindgren, Cecilia M.; Mägi, Reedik; Neale, Benjamin M.; Evans, David M.; Medland, Sarah E.; Epidemiology, School of Public HealthHandedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10-8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.Item Insights into the genetic architecture of the human face(Springer Nature, 2021) White, Julie D.; Indencleef, Karlijne; Naqvi, Sahin; Eller, Ryan J.; Hoskens, Hanne; Roosenboom, Jasmien; Lee, Myoung Keun; Li, Jiarui; Mohammed, Jaaved; Richmond, Stephen; Quillen, Ellen E.; Norton, Heather L.; Feingold, Eleanor; Swigut, Tomek; Marazita, Mary L.; Peeters, Hilde; Hens, Greet; Shaffer, John R.; Wysocka, Joanna; Walsh, Susan; Weinberg, Seth M.; Shriver, Mark D.; Claes, Peter; Biology, School of ScienceThe human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study meta-analysis of 8,246 European individuals, we identified 203 genome-wide-significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses indicate that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In summary, our analyses provide insights into the understanding of how complex morphological traits are shaped by both individual and coordinated genetic actions.Item LD‐informed deep learning for Alzheimer's gene loci detection using WGS data(Wiley, 2025-01-16) Jo, Taeho; Bice, Paula; Nho, Kwangsik; Saykin, Andrew J.; Alzheimer’s Disease Sequencing Project; Radiology and Imaging Sciences, School of MedicineIntroduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk. Methods: The Deep-Block was applied to a large-scale whole genome sequencing (WGS) dataset from the Alzheimer's Disease Sequencing Project (ADSP), comprising 7416 non-Hispanic white (NHW) participants (3150 cognitively normal older adults (CN), 4266 AD). Results: 30,218 LD blocks were identified and then ranked based on their relevance with Alzheimer's disease. Subsequently, the Deep-Block identified novel SNPs within the top 1500 LD blocks and confirmed previously known variants, including APOE rs429358 and rs769449. Expression Quantitative Trait Loci (eQTL) analysis across 13 brain regions provided functional evidence for the identified variants. The results were cross-validated against established AD-associated loci from the European Alzheimer's and Dementia Biobank (EADB) and the GWAS catalog. Discussion: The Deep-Block framework effectively processes large-scale high throughput sequencing data while preserving SNP interactions during dimensionality reduction, minimizing bias and information loss. The framework's findings are supported by tissue-specific eQTL evidence across brain regions, indicating the functional relevance of the identified variants. Additionally, the Deep-Block approach has identified both known and novel genetic variants, enhancing our understanding of the genetic architecture and demonstrating its potential for application in large-scale sequencing studies. Highlights: Growing genomic datasets require advanced tools to identify genetic loci in sequencing. Deep-Block, a novel AI framework, was used to process large-scale ADSP WGS data. Deep-Block identified both known and novel AD-associated genetic loci.rs429358 (APOE) was key; rs11556505 (TOMM40), rs34342646 (NECTIN2) were significant. The AI framework uses biological knowledge to enhance detection of Alzheimer's loci.Item Linkage Disequilibrium-Informed Deep Learning Framework to Identify Genetic Loci for Alzheimer’s Disease Using Whole Genome Sequencing Data(medRxiv, 2024-09-22) Jo, Taeho; Bice, Paula; Nho, Kwangsik; Saykin, Andrew J.; Alzheimer’s Disease Sequencing Project; Radiology and Imaging Sciences, School of MedicineThe exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk. The Deep-Block was applied to a large-scale whole genome sequencing (WGS) dataset from the Alzheimer's Disease Sequencing Project (ADSP), comprising 7,416 non-Hispanic white participants (3,150 cognitively normal older adults (CN), 4,266 AD). First, 30,218 LD blocks were identified and then ranked based on their relevance with Alzheimer's disease. Subsequently, the Deep-Block identified novel SNPs within the top 1,500 LD blocks and confirmed previously known variants, including APOE rs429358 and rs769449. The results were cross-validated against established AD-associated loci from the European Alzheimer's and Dementia Biobank (EADB) and the GWAS catalog. The Deep-Block framework effectively processes large-scale high throughput sequencing data while preserving interactions between SNPs in performing the dimensionality reduction, which can potentially introduce bias or lead to information loss. The Deep-Block approach identified both known and novel genetic variation, enhancing our understanding of the genetic architecture of and demonstrating the framework's potential for application in large-scale sequencing studies.Item Meta-analysis of Parkinson disease: Identification of a novel locus, RIT2(Wiley, 2012) Pankratz, Nathan; Beecham, Gary W.; DeStefano, Anita L.; Dawson, Ted M.; Doheny, Kimberly F.; Factor, Stewart A.; Hamza, Taye H.; Hung, Albert Y.; Hyman, Bradley T.; Ivinson, Adrian J.; Krainc, Dmitri; Latourelle, Jeanne C.; Clark, Lorraine N.; Marder, Karen; Martin, Eden R.; Mayeux, Richard; Ross, Owen A.; Scherzer, Clemens R.; Simon, David K.; Tanner, Caroline; Vance, Jeffery M.; Wszolek, Zbigniew K.; Zabetian, Cyrus P.; Myers, Richard H.; Payami, Haydeh; Scott, William K.; Foroud, Tatiana; PD GWAS Consortium; Medical and Molecular Genetics, School of MedicineObjective: Genome-wide association (GWAS) methods have identified genes contributing to Parkinson's disease (PD); we sought to identify additional genes associated with PD susceptibility. Methods: A 2-stage design was used. First, individual level genotypic data from 5 recent PD GWAS (Discovery Sample: 4,238 PD cases and 4,239 controls) were combined. Following imputation, a logistic regression model was employed in each dataset to test for association with PD susceptibility and results from each dataset were meta-analyzed. Second, 768 single-nucleotide polymorphisms (SNPs) were genotyped in an independent Replication Sample (3,738 cases and 2,111 controls). Results: Genome-wide significance was reached for SNPs in SNCA (rs356165; G: odds ratio [OR]=1.37; p=9.3×10(-21)), MAPT (rs242559; C: OR=0.78; p=1.5×10(-10)), GAK/DGKQ (rs11248051; T: OR=1.35; p=8.2×10(-9)/rs11248060; T: OR=1.35; p=2.0×10(-9)), and the human leukocyte antigen (HLA) region (rs3129882; A: OR=0.83; p=1.2×10(-8)), which were previously reported. The Replication Sample confirmed the associations with SNCA, MAPT, and the HLA region and also with GBA (E326K; OR=1.71; p=5×10(-8) Combined Sample) (N370; OR=3.08; p=7×10(-5) Replication sample). A novel PD susceptibility locus, RIT2, on chromosome 18 (rs12456492; p=5×10(-5) Discovery Sample; p=1.52×10(-7) Replication sample; p=2×10(-10) Combined Sample) was replicated. Conditional analyses within each of the replicated regions identified distinct SNP associations within GBA and SNCA, suggesting that there may be multiple risk alleles within these genes. Interpretation: We identified a novel PD susceptibility locus, RIT2, replicated several previously identified loci, and identified more than 1 risk allele within SNCA and GBA.Item Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel(American Medical Association, 2021-01-01) Kunkle, Brian W.; Schmidt, Michael; Klein, Hans-Ulrich; Naj, Adam C.; Hamilton-Nelson, Kara L.; Larson, Eric B.; Evans, Denis A.; De Jager, Phil L.; Crane, Paul K.; Buxbaum, Joe D.; Ertekin-Taner, Nilufer; Go, Rodney C.P.; Obisesan, Thomas O.; Kamboh, Ilyas; Bennett, David A.; Hall, Kathleen S.; Goate, Alison M.; Foroud, Tatiana M.; Martin, Eden R.; Wang, Li-Sao; Byrd, Goldie S.; Farrer, Lindsay A.; Haines, Jonathan L.; Schellenberg, Gerard D.; Mayeux, Richard; Pericak-Vance, Margaret A.; Reitz, Christiane; Graff-Radford, Neill R.; Martinez, Izri; Ayodele, Temitope; Logue, Mark W.; Cantwell, Laura B.; Jean-Francois, Melissa; Kuzma, Amanda B.; Adams, L.D.; Vance, Jeffery M.; Cuccaro, Michael L.; Chung, Jaeyoon; Mez, Jesse; Lunetta, Kathryn L.; Jun, Gyungah R.; Lopez, Oscar L.; Hendrie, Hugh C.; Reiman, Eric M.; Kowall, Neil W.; Leverenz, James B.; Small, Scott A.; Levey, Allan I.; Golde, Todd E.; Saykin, Andrew J.; Starks, Takiyah D.; Albert, Marilyn S.; Hyman, Bradley T.; Petersen, Ronald C.; Sano, Mary; Wisniewski, Thomas; Vassar, Robert; Kaye, Jeffrey A.; Henderson, Victor W.; DeCarli, Charles; LaFerla, Frank M.; Brewer, James B.; Miller, Bruce L.; Swerdlow, Russell H.; Van Eldik, Linda J.; Paulson, Henry L.; Trojanowski, John Q.; Chui, Helena C.; Rosenberg, Roger N.; Craft, Suzanne; Grabowski, Thomas J.; Asthana, Sanjay; Morris, John C.; Strittmatter, Stephen M.; Kukull, Walter A.; Psychiatry, School of MedicineImportance: Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals, ABCA7, TREM2, and an intergenic locus at 5q35 were previously implicated. Objective: To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel. Design, setting, and participants: This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019. Main outcomes and measures: Diagnosis of Alzheimer disease. Results: A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking gene EDEM1 (3p26; P = 8.9 × 10-7), near the immune response gene ALCAM (3q13; P = 9.3 × 10-7), within GPC6 (13q31; P = 4.1 × 10-7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and within VRK3 (19q13.33; P = 3.5 × 10-7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus near IGF1R at 15q26 (P = 1.7 × 10-9) and 6 additional loci with suggestive significance (P ≤ 5 × 10-7) such as API5 at 11p12 (P = 8.8 × 10-8) and RBFOX1 at 16p13 (P = 5.4 × 10-7) were identified. Gene expression data from brain tissue demonstrate association of ALCAM, ARAP1, GPC6, and RBFOX1 with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, only APOE, ABCA7, TREM2, BIN1, CD2AP, FERMT2, and WWOX were implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration. Conclusions and relevance: While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.