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Patel D, Zhang X, Farrell JJ, Chung J, Stein TD, Lunetta KL, Farrer LA. Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue. Transl Psychiatry 2021; 11:250. [PMID: 33907181 PMCID: PMC8079392 DOI: 10.1038/s41398-021-01373-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 03/24/2021] [Accepted: 04/08/2021] [Indexed: 02/02/2023] Open
Abstract
Because regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1 Mb of genes was evaluated using linear regression models for unrelated subjects and linear-mixed models for related subjects. Cell-type-specific eQTL (ct-eQTL) models included an interaction term for the expression of "proxy" genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell types is supported by the observation that a large portion of GWS ct-eQTLs map within 1 Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type-specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type-specific analysis.
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Patel D, Zhang X, Farrell JJ, Lunetta KL, Farrer LA. Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants. Genes (Basel) 2021; 12:419. [PMID: 33804025 PMCID: PMC7999141 DOI: 10.3390/genes12030419] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/04/2021] [Accepted: 03/10/2021] [Indexed: 12/12/2022] Open
Abstract
Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer's Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.
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Sherva R, Zhu C, Wetherill L, Edenberg HJ, Johnson E, Degenhardt L, Agrawal A, Martin NG, Nelson E, Kranzler HR, Gelernter J, Farrer LA. Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes. EXPLORATION OF MEDICINE 2021. [DOI: 10.37349/emed.2020.00032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Aim: Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted.
Methods: Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts.
Results: In the discovery sample, three independent regions containing variants associated with time to dependence at P < 5 x 10-8 were identified, one (rs61835088 = 1.03 x 10-8) for cocaine in the combined EA-AA meta-analysis in the gene FAM78B on chromosome 1, and two for opioids in the AA portion of the sample in intergenic regions of chromosomes 4 (rs4860439, P = 1.37 x 10-8) and 9 (rs7032521, P = 3.30 x 10-8). After meta-analysis with data from the replication cohorts, the signal at rs61835088 improved (HR = 0.87, P = 3.71 x 10-9 and an intergenic SNP on chromosome 21 (rs2825295, HR = 1.14, P = 2.57 x 10-8) that missed the significance threshold in the AA discovery sample became genome-wide significant (GWS) for CD.
Conclusions: Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs.
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Sherva R, Zhu C, Wetherill L, Edenberg HJ, Johnson E, Degenhardt L, Agrawal A, Martin NG, Nelson E, Kranzler HR, Gelernter J, Farrer LA. Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes. EXPLORATION OF MEDICINE 2021; 2:60-73. [PMID: 34124712 DOI: 10.37349/emed.2021.00032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Aim Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted. Methods Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts. Results In the discovery sample, three independent regions containing variants associated with time to dependence at P < 5 x 10-8 were identified, one (rs61835088 = 1.03 x 10-8) for cocaine in the combined EA-AA meta-analysis in the gene FAM78B on chromosome 1, and two for opioids in the AA portion of the sample in intergenic regions of chromosomes 4 (rs4860439, P = 1.37 x 10-8) and 9 (rs7032521, P = 3.30 x 10-8). After meta-analysis with data from the replication cohorts, the signal at rs61835088 improved (HR = 0.87, P = 3.71 x 10-9 and an intergenic SNP on chromosome 21 (rs2825295, HR = 1.14, P = 2.57 x 10-8) that missed the significance threshold in the AA discovery sample became genome-wide significant (GWS) for CD. Conclusions Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs.
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Cox JW, Sherva RM, Lunetta KL, Saitz R, Kon M, Kranzler HR, Gelernter J, Farrer LA. Identifying factors associated with opioid cessation in a biracial sample using machine learning. EXPLORATION OF MEDICINE 2021; 1:27-41. [PMID: 33554217 PMCID: PMC7861053 DOI: 10.37349/emed.2020.00003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Aim Racial disparities in opioid use disorder (OUD) management exist, however, and there is limited research on factors that influence opioid cessation in different population groups. Methods We employed multiple machine learning prediction algorithms least absolute shrinkage and selection operator, random forest, deep neural network, and support vector machine to assess factors associated with ceasing opioid use in a sample of 1,192 African Americans (AAs) and 2,557 individuals of European ancestry (EAs) who met Diagnostic and Statistical Manual of Mental Disorders, 5th Edition criteria for OUD. Values for nearly 4,000 variables reflecting demographics, alcohol and other drug use, general health, non-drug use behaviors, and diagnoses for other psychiatric disorders, were obtained for each participant from the Semi-Structured Assessment for Drug Dependence and Alcoholism, a detailed semi-structured interview. Results Support vector machine models performed marginally better on average than other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression considered the 83 most highly ranked variables across all methods and models and identified less recent cocaine use (AAs: odds ratio (OR) = 1.82, P = 9.19 × 10-5; EAs: OR = 1.91, P = 3.30 × 10-15), shorter duration of opioid use (AAs: OR = 0.55, P = 5.78 × 10-6; EAs: OR = 0.69, P = 3.01 × 10-7), and older age (AAs: OR = 2.44, P = 1.41 × 10-12; EAs: OR = 2.00, P = 5.74 × 10-9) as the strongest independent predictors of opioid cessation in both AAs and EAs. Attending self-help groups for OUD was also an independent predictor (P < 0.05) in both population groups, while less gambling severity (OR = 0.80, P = 3.32 × 10-2) was specific to AAs and post-traumatic stress disorder recovery (OR = 1.93, P = 7.88 × 10-5), recent antisocial behaviors (OR = 0.64, P = 2.69 × 10-3), and atheism (OR = 1.45, P = 1.34 × 10-2) were specific to EAs. Factors related to drug use comprised about half of the significant independent predictors in both AAs and EAs, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics. Conclusions These proof-of-concept findings provide avenues for hypothesis-driven analysis, and will lead to further research on strategies to improve OUD management in EAs and AAs.
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Kunkle BW, Schmidt M, Klein HU, Naj AC, Hamilton-Nelson KL, Larson EB, Evans DA, De Jager PL, Crane PK, Buxbaum JD, Ertekin-Taner N, Barnes LL, Fallin MD, Manly JJ, Go RCP, Obisesan TO, Kamboh MI, Bennett DA, Hall KS, Goate AM, Foroud TM, Martin ER, Wang LS, Byrd GS, Farrer LA, Haines JL, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis. JAMA Neurol 2021; 78:102-113. [PMID: 33074286 PMCID: PMC7573798 DOI: 10.1001/jamaneurol.2020.3536] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/09/2020] [Indexed: 12/11/2022]
Abstract
Importance 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.
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Munn‐Chernoff MA, Johnson EC, Chou Y, Coleman JR, Thornton LM, Walters RK, Yilmaz Z, Baker JH, Hübel C, Gordon S, Medland SE, Watson HJ, Gaspar HA, Bryois J, Hinney A, Leppä VM, Mattheisen M, Ripke S, Yao S, Giusti‐Rodríguez P, Hanscombe KB, Adan RA, Alfredsson L, Ando T, Andreassen OA, Berrettini WH, Boehm I, Boni C, Boraska Perica V, Buehren K, Burghardt R, Cassina M, Cichon S, Clementi M, Cone RD, Courtet P, Crow S, Crowley JJ, Danner UN, Davis OS, Zwaan M, Dedoussis G, Degortes D, DeSocio JE, Dick DM, Dikeos D, Dina C, Dmitrzak‐Weglarz M, Docampo E, Duncan LE, Egberts K, Ehrlich S, Escaramís G, Esko T, Estivill X, Farmer A, Favaro A, Fernández‐Aranda F, Fichter MM, Fischer K, Föcker M, Foretova L, Forstner AJ, Forzan M, Franklin CS, Gallinger S, Giegling I, Giuranna J, Gonidakis F, Gorwood P, Gratacos Mayora M, Guillaume S, Guo Y, Hakonarson H, Hatzikotoulas K, Hauser J, Hebebrand J, Helder SG, Herms S, Herpertz‐Dahlmann B, Herzog W, Huckins LM, Hudson JI, Imgart H, Inoko H, Janout V, Jiménez‐Murcia S, Julià A, Kalsi G, Kaminská D, Karhunen L, Karwautz A, Kas MJ, Kennedy JL, Keski‐Rahkonen A, Kiezebrink K, Kim Y, Klump KL, Knudsen GPS, La Via MC, Le Hellard S, Levitan RD, Li D, Lilenfeld L, Lin BD, Lissowska J, Luykx J, Magistretti PJ, Maj M, Mannik K, Marsal S, Marshall CR, Mattingsdal M, McDevitt S, McGuffin P, Metspalu A, Meulenbelt I, Micali N, Mitchell K, Monteleone AM, Monteleone P, Nacmias B, Navratilova M, Ntalla I, O'Toole JK, Ophoff RA, Padyukov L, Palotie A, Pantel J, Papezova H, Pinto D, Rabionet R, Raevuori A, Ramoz N, Reichborn‐Kjennerud T, Ricca V, Ripatti S, Ritschel F, Roberts M, Rotondo A, Rujescu D, Rybakowski F, Santonastaso P, Scherag A, Scherer SW, Schmidt U, Schork NJ, Schosser A, Seitz J, Slachtova L, Slagboom PE, Slof‐Op't Landt MC, Slopien A, Sorbi S, Świątkowska B, Szatkiewicz JP, Tachmazidou I, Tenconi E, Tortorella A, Tozzi F, Treasure J, Tsitsika A, Tyszkiewicz‐Nwafor M, Tziouvas K, Elburg AA, Furth EF, Wagner G, Walton E, Widen E, Zeggini E, Zerwas S, Zipfel S, Bergen AW, Boden JM, Brandt H, Crawford S, Halmi KA, Horwood LJ, Johnson C, Kaplan AS, Kaye WH, Mitchell J, Olsen CM, Pearson JF, Pedersen NL, Strober M, Werge T, Whiteman DC, Woodside DB, Grove J, Henders AK, Larsen JT, Parker R, Petersen LV, Jordan J, Kennedy MA, Birgegård A, Lichtenstein P, Norring C, Landén M, Mortensen PB, Polimanti R, McClintick JN, Adkins AE, Aliev F, Bacanu S, Batzler A, Bertelsen S, Biernacka JM, Bigdeli TB, Chen L, Clarke T, Degenhardt F, Docherty AR, Edwards AC, Foo JC, Fox L, Frank J, Hack LM, Hartmann AM, Hartz SM, Heilmann‐Heimbach S, Hodgkinson C, Hoffmann P, Hottenga J, Konte B, Lahti J, Lahti‐Pulkkinen M, Lai D, Ligthart L, Loukola A, Maher BS, Mbarek H, McIntosh AM, McQueen MB, Meyers JL, Milaneschi Y, Palviainen T, Peterson RE, Ryu E, Saccone NL, Salvatore JE, Sanchez‐Roige S, Schwandt M, Sherva R, Streit F, Strohmaier J, Thomas N, Wang J, Webb BT, Wedow R, Wetherill L, Wills AG, Zhou H, Boardman JD, Chen D, Choi D, Copeland WE, Culverhouse RC, Dahmen N, Degenhardt L, Domingue BW, Frye MA, Gäebel W, Hayward C, Ising M, Keyes M, Kiefer F, Koller G, Kramer J, Kuperman S, Lucae S, Lynskey MT, Maier W, Mann K, Männistö S, Müller‐Myhsok B, Murray AD, Nurnberger JI, Preuss U, Räikkönen K, Reynolds MD, Ridinger M, Scherbaum N, Schuckit MA, Soyka M, Treutlein J, Witt SH, Wodarz N, Zill P, Adkins DE, Boomsma DI, Bierut LJ, Brown SA, Bucholz KK, Costello EJ, Wit H, Diazgranados N, Eriksson JG, Farrer LA, Foroud TM, Gillespie NA, Goate AM, Goldman D, Grucza RA, Hancock DB, Harris KM, Hesselbrock V, Hewitt JK, Hopfer CJ, Iacono WG, Johnson EO, Karpyak VM, Kendler KS, Kranzler HR, Krauter K, Lind PA, McGue M, MacKillop J, Madden PA, Maes HH, Magnusson PK, Nelson EC, Nöthen MM, Palmer AA, Penninx BW, Porjesz B, Rice JP, Rietschel M, Riley BP, Rose RJ, Shen P, Silberg J, Stallings MC, Tarter RE, Vanyukov MM, Vrieze S, Wall TL, Whitfield JB, Zhao H, Neale BM, Wade TD, Heath AC, Montgomery GW, Martin NG, Sullivan PF, Kaprio J, Breen G, Gelernter J, Edenberg HJ, Bulik CM, Agrawal A. Shared genetic risk between eating disorder‐ and substance‐use‐related phenotypes: Evidence from genome‐wide association studies. Addict Biol 2021; 26:e12880. [DOI: 10.1111/adb.12880] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 12/09/2019] [Accepted: 01/13/2020] [Indexed: 02/01/2023]
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Jun GR, Zhu C, Panitch R, Chung J, Hu J, Wang L, Lunetta KL, Haines JL, Mayeux R, Pericak‐Vance MA, Schellenberg GD, Stein TD, Farrer LA. Mechanism for the protective effect of
APOE
ε2 against Alzheimer disease is linked to tau and the classical complement pathway. Alzheimers Dement 2020. [DOI: 10.1002/alz.044881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Peloso GM, Wang Y, Lin H, Sarnowski C, Pitsillides AN, Lim EM, Beecham GW, Hamilton‐Nelson KL, Ramos J, Martin ER, Naj AC, Thornton TA, Wang L, Boerwinkle E, Farrer LA, Haines JL, Mayeux R, Pericak‐Vance MA, Seshadri S, Schellenberg GD, Wijsman E, Fornage M, Dupuis J, Destefano AL, Kunkle BW. Assessing whole genome sequencing variation for Alzheimer’s disease in 4707 individuals from the Alzheimer’s Disease Sequencing Project (ADSP). Alzheimers Dement 2020. [DOI: 10.1002/alz.045548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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You Y, Poon WW, Jun GR, Farrer LA, Ikezu T. Differential effects of apolipoprotein E on the molecular and cellular phenotypes associated with Alzheimer’s disease in isogenic human iPSC‐derived neurons. Alzheimers Dement 2020. [DOI: 10.1002/alz.044579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Atherton K, Khan MM, Shea C, Chung J, Nair E, Baucom ZH, Abdolmohammadi B, Uretsky M, Martin BM, Palmisano J, Farrell KW, Cherry JD, Alvarez VE, Huber BR, Alosco ML, Lunetta KL, Tripodis Y, Stein TD, Farrer LA, Crary JF, McKee AC, Mez J. Genome wide association study of chronic traumatic encephalopathy. Alzheimers Dement 2020. [DOI: 10.1002/alz.046505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Bagyinszky E, Farrer LA, Farrell J, Van Vo G, Shim K, An SS, Kim S. Alzheimer’s disease risk factor mutations in patients diagnosed with Creutzfelt‐Jakob disease. Alzheimers Dement 2020. [DOI: 10.1002/alz.045035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Moore MR, Chung J, Rosenthaler M, Uretsky M, Abdolmohammadi B, Raghavan NS, Farrell J, Bennett DA, Crane PK, Kamboh MI, Kukull WA, Larson EB, Haines JL, Pericak‐Vance MA, Schellenberg GD, Mayeux R, Lunetta KL, Farrer LA, Mez J. Genome‐wide interaction study of smoking in Alzheimer’s disease. Alzheimers Dement 2020. [DOI: 10.1002/alz.046149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Hu J, Chung J, Panitch R, Zhu C, Beecham GW, Mez J, Farrer LA, Stein TD, Crane PK, Jun GR. Defining Alzheimer’s disease subtypes using polygenic risk scores integrated with genomic and brain transcriptomic profiles. Alzheimers Dement 2020. [DOI: 10.1002/alz.046449] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Patel D, Zhang X, Farrer LA. Cell‐type specific eQTLs (ct‐eQTLs) associated with Alzheimer disease in blood and brain tissue. Alzheimers Dement 2020. [DOI: 10.1002/alz.044149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Whitehead PL, Rajabli F, Hamilton‐Nelson KL, Kunkle BW, Reitz C, Naj AC, Bush WS, Farrer LA, Schellenberg GD, Mayeux R, Martin ER, Byrd GS, Haines JL, Beecham GW, Pericak‐Vance MA. Mapping Alzheimer disease–associated regions in the African American population. Alzheimers Dement 2020. [DOI: 10.1002/alz.046072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Panitch R, Zhu C, Hu J, Chung J, Stein TD, Farrer LA, Jun GR. Novel mechanism underlying the APOE ε2 protective effect for Alzheimer disease implicated by integrative genome and transcriptome analysis. Alzheimers Dement 2020. [DOI: 10.1002/alz.040065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Johnson EC, Demontis D, Thorgeirsson TE, Walters RK, Polimanti R, Hatoum AS, Sanchez-Roige S, Paul SE, Wendt FR, Clarke TK, Lai D, Reginsson GW, Zhou H, He J, Baranger DAA, Gudbjartsson DF, Wedow R, Adkins DE, Adkins AE, Alexander J, Bacanu SA, Bigdeli TB, Boden J, Brown SA, Bucholz KK, Bybjerg-Grauholm J, Corley RP, Degenhardt L, Dick DM, Domingue BW, Fox L, Goate AM, Gordon SD, Hack LM, Hancock DB, Hartz SM, Hickie IB, Hougaard DM, Krauter K, Lind PA, McClintick JN, McQueen MB, Meyers JL, Montgomery GW, Mors O, Mortensen PB, Nordentoft M, Pearson JF, Peterson RE, Reynolds MD, Rice JP, Runarsdottir V, Saccone NL, Sherva R, Silberg JL, Tarter RE, Tyrfingsson T, Wall TL, Webb BT, Werge T, Wetherill L, Wright MJ, Zellers S, Adams MJ, Bierut LJ, Boardman JD, Copeland WE, Farrer LA, Foroud TM, Gillespie NA, Grucza RA, Harris KM, Heath AC, Hesselbrock V, Hewitt JK, Hopfer CJ, Horwood J, Iacono WG, Johnson EO, Kendler KS, Kennedy MA, Kranzler HR, Madden PAF, Maes HH, Maher BS, Martin NG, McGue M, McIntosh AM, Medland SE, Nelson EC, Porjesz B, Riley BP, Stallings MC, Vanyukov MM, Vrieze S, Davis LK, Bogdan R, Gelernter J, Edenberg HJ, Stefansson K, Børglum AD, Agrawal A. A large-scale genome-wide association study meta-analysis of cannabis use disorder. Lancet Psychiatry 2020; 7:1032-1045. [PMID: 33096046 PMCID: PMC7674631 DOI: 10.1016/s2215-0366(20)30339-4] [Citation(s) in RCA: 160] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 07/15/2020] [Accepted: 07/16/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. METHODS To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. FINDINGS We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. INTERPRETATION These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. FUNDING National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.
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Palmer EL, Moth C, Benchek P, Wheeler NR, Kunkle BW, Hamilton‐Nelson KL, Griswold AJ, Naj AC, Farrer LA, Martin ER, Pericak‐Vance MA, Haines JL, Sheehan JH, Capra JA, Bush WS. Structural characterization of rare missense variants within known neurodegenerative disease proteins. Alzheimers Dement 2020. [DOI: 10.1002/alz.046405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Zhang X, Tong T, Chang A, Ang TFA, Tao Q, Auerbach SH, Devine S, Qiu W, Mez J, Massaro J, Lunetta KL, Au R, Farrer LA. Early‐mid adulthood measures of HDL, triglycerides and fasting glucose are associated with late‐onset Alzheimer disease. Alzheimers Dement 2020. [DOI: 10.1002/alz.046125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Naj AC, Sha J, Zhao Y, Leonenko G, Jian X, Grenier‐Boley B, Dalmasso MC, van der Lee SJ, Sims R, Chouraki V, Bis JC, Kuzma AB, Kunkle BW, Karamujić‐Čomić H, Pitsillides AN, Xia R, Fulton‐Howard B, Holmans P, Dupuis J, Wang L, Farrer LA, van Duijn CM, Haines JL, Destefano AL, Pericak‐Vance MA, Ramirez A, Amouyel P, Lambert J, Seshadri S, Williams J, Schellenberg GD. Genome‐wide meta‐analysis of late‐onset Alzheimer’s disease using rare variant imputation in 65,602 subjects identifies risk loci with roles in memory, neurodevelopment, and cardiometabolic traits: The international genomics of Alzheimer’s project (IGAP). Alzheimers Dement 2020. [DOI: 10.1002/alz.044193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Quach BC, Bray MJ, Gaddis NC, Liu M, Palviainen T, Minica CC, Zellers S, Sherva R, Aliev F, Nothnagel M, Young KA, Marks JA, Young H, Carnes MU, Guo Y, Waldrop A, Sey NYA, Landi MT, McNeil DW, Drichel D, Farrer LA, Markunas CA, Vink JM, Hottenga JJ, Iacono WG, Kranzler HR, Saccone NL, Neale MC, Madden P, Rietschel M, Marazita ML, McGue M, Won H, Winterer G, Grucza R, Dick DM, Gelernter J, Caporaso NE, Baker TB, Boomsma DI, Kaprio J, Hokanson JE, Vrieze S, Bierut LJ, Johnson EO, Hancock DB. Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits. Nat Commun 2020; 11:5562. [PMID: 33144568 PMCID: PMC7642344 DOI: 10.1038/s41467-020-19265-z] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 09/24/2020] [Indexed: 12/31/2022] Open
Abstract
Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (rg = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking.
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Zhou H, Rentsch CT, Cheng Z, Kember RL, Nunez YZ, Sherva RM, Tate JP, Dao C, Xu K, Polimanti R, Farrer LA, Justice AC, Kranzler HR, Gelernter J. Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study. JAMA Psychiatry 2020; 77:1072-1080. [PMID: 32492095 PMCID: PMC7270886 DOI: 10.1001/jamapsychiatry.2020.1206] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
IMPORTANCE With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). OBJECTIVES To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. DESIGN, SETTING, AND PARTICIPANTS A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. MAIN OUTCOMES AND MEASURES Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). RESULTS A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (μ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: β = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. CONCLUSIONS AND RELEVANCE This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci.
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Lancour D, Dupuis J, Mayeux R, Haines JL, Pericak-Vance MA, Schellenberg GC, Crovella M, Farrer LA, Kasif S. Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease. Alzheimers Res Ther 2020; 12:103. [PMID: 32878640 PMCID: PMC7469336 DOI: 10.1186/s13195-020-00674-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 08/26/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration. METHODS A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD. RESULTS We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10-3) and HSPA2 (FDR p = 0.245). CONCLUSIONS Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach.
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Dumitrescu L, Mahoney ER, Mukherjee S, Lee ML, Bush WS, Engelman CD, Lu Q, Fardo DW, Trittschuh EH, Mez J, Kaczorowski C, Hernandez Saucedo H, Widaman KF, Buckley R, Properzi M, Mormino E, Yang HS, Harrison T, Hedden T, Nho K, Andrews SJ, Tommet D, Hadad N, Sanders RE, Ruderfer DM, Gifford KA, Moore AM, Cambronero F, Zhong X, Raghavan NS, Vardarajan B, Pericak-Vance MA, Farrer LA, Wang LS, Cruchaga C, Schellenberg G, Cox NJ, Haines JL, Keene CD, Saykin AJ, Larson EB, Sperling RA, Mayeux R, Bennett DA, Schneider JA, Crane PK, Jefferson AL, Hohman TJ. Genetic variants and functional pathways associated with resilience to Alzheimer's disease. Brain 2020; 143:2561-2575. [PMID: 32844198 PMCID: PMC7447518 DOI: 10.1093/brain/awaa209] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 04/22/2020] [Accepted: 05/08/2020] [Indexed: 12/23/2022] Open
Abstract
Approximately 30% of older adults exhibit the neuropathological features of Alzheimer's disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer's disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values < 2.5 × 10-20), and we observed novel correlations with neuropsychiatric conditions (P-values < 7.9 × 10-4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer's disease (P-values > 0.42) nor associated with APOE (P-values > 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer's disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.
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