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Browsing by Author "Polimanti, Renato"
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Item Ancestry May Confound Genetic Machine Learning: Candidate-Gene Prediction of Opioid Use Disorder as an Example(Elsevier, 2021) Hatoum, Alexander S.; Wendt, Frank R.; Galimberti, Marco; Polimanti, Renato; Neale, Benjamin; Kranzler, Henry R.; Gelernter, Joel; Edenberg, Howard J.; Agrawal, Arpana; Medical and Molecular Genetics, School of MedicineBackground: Machine learning (ML) models are beginning to proliferate in psychiatry, however machine learning models in psychiatric genetics have not always accounted for ancestry. Using an empirical example of a proposed genetic test for OUD, and exploring a similar test for tobacco dependence and a simulated binary phenotype, we show that genetic prediction using ML is vulnerable to ancestral confounding. Methods: We utilize five ML algorithms trained with 16 brain reward-derived "candidate" SNPs proposed for commercial use and examine their ability to predict OUD vs. ancestry in an out-of-sample test set (N = 1000, stratified into equal groups of n = 250 cases and controls each of European and African ancestry). We rerun analyses with 8 random sets of allele-frequency matched SNPs. We contrast findings with 11 genome-wide significant variants for tobacco smoking. To document generalizability, we generate and test a random phenotype. Results: None of the 5 ML algorithms predict OUD better than chance when ancestry was balanced but were confounded with ancestry in an out-of-sample test. In addition, the algorithms preferentially predicted admixed subpopulations. Random sets of variants matched to the candidate SNPs by allele frequency produced similar bias. Genome-wide significant tobacco smoking variants were also confounded by ancestry. Finally, random SNPs predicting a random simulated phenotype show that the bias attributable to ancestral confounding could impact any ML-based genetic prediction. Conclusions: Researchers and clinicians are encouraged to be skeptical of claims of high prediction accuracy from ML-derived genetic algorithms for polygenic traits like addiction, particularly when using candidate variants.Item APOL1 Risk Variants, Acute Kidney Injury, and Death in Participants With African Ancestry Hospitalized With COVID-19 From the Million Veteran Program(American Medical Association, 2022) Hung, Adriana M.; Shah, Shailja C.; Bick, Alexander G.; Yu, Zhihong; Chen, Hua-Chang; Hunt, Christine M.; Wendt, Frank; Wilson, Otis; Greevy, Robert A.; Chung, Cecilia P.; Suzuki, Ayako; Ho, Yuk-Lam; Akwo, Elvis; Polimanti, Renato; Zhou, Jin; Reaven, Peter; Tsao, Philip S.; Gaziano, J. Michael; Huffman, Jennifer E.; Joseph, Jacob; Luoh, Shiuh-Wen; Iyengar, Sudha; Chang, Kyong-Mi; Casas, Juan P.; Matheny, Michael E.; O'Donnell, Christopher J.; Cho, Kelly; Tao, Ran; Susztak, Katalin; Robinson-Cohen, Cassianne; Tuteja, Sony; Siew, Edward D.; VA Million Veteran Program COVID-19 Science Initiative; Medicine, School of MedicineImportance: Coronavirus disease 2019 (COVID-19) confers significant risk of acute kidney injury (AKI). Patients with COVID-19 with AKI have high mortality rates. Objective: Individuals with African ancestry with 2 copies of apolipoprotein L1 (APOL1) variants G1 or G2 (high-risk group) have significantly increased rates of kidney disease. We tested the hypothesis that the APOL1 high-risk group is associated with a higher-risk of COVID-19-associated AKI and death. Design, setting, and participants: This retrospective cohort study included 990 participants with African ancestry enrolled in the Million Veteran Program who were hospitalized with COVID-19 between March 2020 and January 2021 with available genetic information. Exposures: The primary exposure was having 2 APOL1 risk variants (RV) (APOL1 high-risk group), compared with having 1 or 0 risk variants (APOL1 low-risk group). Main outcomes and measures: The primary outcome was AKI. The secondary outcomes were stages of AKI severity and death. Multivariable logistic regression analyses adjusted for preexisting comorbidities, medications, and inpatient AKI risk factors; 10 principal components of ancestry were performed to study these associations. We performed a subgroup analysis in individuals with normal kidney function prior to hospitalization (estimated glomerular filtration rate ≥60 mL/min/1.73 m2). Results: Of the 990 participants with African ancestry, 905 (91.4%) were male with a median (IQR) age of 68 (60-73) years. Overall, 392 (39.6%) patients developed AKI, 141 (14%) developed stages 2 or 3 AKI, 28 (3%) required dialysis, and 122 (12.3%) died. One hundred twenty-five (12.6%) of the participants were in the APOL1 high-risk group. Patients categorized as APOL1 high-risk group had significantly higher odds of AKI (adjusted odds ratio [OR], 1.95; 95% CI, 1.27-3.02; P = .002), higher AKI severity stages (OR, 2.03; 95% CI, 1.37-2.99; P < .001), and death (OR, 2.15; 95% CI, 1.22-3.72; P = .007). The association with AKI persisted in the subgroup with normal kidney function (OR, 1.93; 95% CI, 1.15-3.26; P = .01). Data analysis was conducted between February 2021 and April 2021. Conclusions and relevance: In this cohort study of veterans with African ancestry hospitalized with COVID-19 infection, APOL1 kidney risk variants were associated with higher odds of AKI, AKI severity, and death, even among individuals with prior normal kidney function.Item Association of Kidney Comorbidities and Acute Kidney Failure With Unfavorable Outcomes After COVID-19 in Individuals With the Sickle Cell Trait(American Medical Association, 2022) Verma, Anurag; Huffman, Jennifer E.; Gao, Lina; Minnier, Jessica; Wu, Wen-Chih; Cho, Kelly; Ho, Yuk-Lam; Gorman, Bryan R.; Pyarajan, Saiju; Rajeevan, Nallakkandi; Garcon, Helene; Joseph, Jacob; McGeary, John E.; Suzuki, Ayako; Reaven, Peter D.; Wan, Emily S.; Lynch, Julie A.; Petersen, Jeffrey M.; Meigs, James B.; Freiberg, Matthew S.; Gatsby, Elise; Lynch, Kristine E.; Zekavat, Seyedeh Maryam; Natarajan, Pradeep; Dalal, Sharvari; Jhala, Darshana N.; Arjomandi, Mehrdad; Bonomo, Robert A.; Thompson, Trevor K.; Pathak, Gita A.; Zhou, Jin J.; Donskey, Curtis J.; Madduri, Ravi K.; Wells, Quinn S.; Gelernter, Joel; Huang, Rose D. L.; Polimanti, Renato; Chang, Kyong-Mi; Liao, Katherine P.; Tsao, Philip S.; Sun, Yan V.; Wilson, Peter W. F.; O'Donnell, Christopher J.; Hung, Adriana M.; Gaziano, J. Michael; Hauger, Richard L.; Iyengar, Sudha K.; Luoh, Shiuh-Wen; VA Million Veteran Program COVID-19 Science Initiative; Medicine, School of MedicineImportance: Sickle cell trait (SCT), defined as the presence of 1 hemoglobin beta sickle allele (rs334-T) and 1 normal beta allele, is prevalent in millions of people in the US, particularly in individuals of African and Hispanic ancestry. However, the association of SCT with COVID-19 is unclear. Objective: To assess the association of SCT with the prepandemic health conditions in participants of the Million Veteran Program (MVP) and to assess the severity and sequelae of COVID-19. Design, setting, and participants: COVID-19 clinical data include 2729 persons with SCT, of whom 353 had COVID-19, and 129 848 SCT-negative individuals, of whom 13 488 had COVID-19. Associations between SCT and COVID-19 outcomes were examined using firth regression. Analyses were performed by ancestry and adjusted for sex, age, age squared, and ancestral principal components to account for population stratification. Data for the study were collected between March 2020 and February 2021. Exposures: The hemoglobin beta S (HbS) allele (rs334-T). Main outcomes and measures: This study evaluated 4 COVID-19 outcomes derived from the World Health Organization severity scale and phenotypes derived from International Classification of Diseases codes in the electronic health records. Results: Of the 132 577 MVP participants with COVID-19 data, mean (SD) age at the index date was 64.8 (13.1) years. Sickle cell trait was present in 7.8% of individuals of African ancestry and associated with a history of chronic kidney disease, diabetic kidney disease, hypertensive kidney disease, pulmonary embolism, and cerebrovascular disease. Among the 4 clinical outcomes of COVID-19, SCT was associated with an increased COVID-19 mortality in individuals of African ancestry (n = 3749; odds ratio, 1.77; 95% CI, 1.13 to 2.77; P = .01). In the 60 days following COVID-19, SCT was associated with an increased incidence of acute kidney failure. A counterfactual mediation framework estimated that on average, 20.7% (95% CI, -3.8% to 56.0%) of the total effect of SCT on COVID-19 fatalities was due to acute kidney failure. Conclusions and relevance: In this genetic association study, SCT was associated with preexisting kidney comorbidities, increased COVID-19 mortality, and kidney morbidity.Item Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium(Cambridge University Press, 2019-05) Polimanti, Renato; Peterson, Roseann E.; Ong, Jue-Sheng; MacGregor, Stuart; Edwards, Alexis C.; Clarke, Toni-Kim; Frank, Josef; Gerring, Zachary; Gillespie, Nathan A.; Lind, Penelope A.; Maes, Hermine H.; Martin, Nicholas G.; Mbarek, Hamdi; Medland, Sarah E.; Streit, Fabian; Agrawal, Arpana; Edenberg, Howard J.; Kendler, Kenneth S.; Lewis, Cathryn M.; Sullivan, Patrick F.; Wray, Naomi R.; Gelernter, Joel; Derks, Eske M.; Biochemistry and Molecular Biology, School of MedicineBACKGROUND: Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS: Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS: Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation. CONCLUSION: This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.Item Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder(Springer Nature, 2024) Nievergelt, Caroline M.; Maihofer, Adam X.; Atkinson, Elizabeth G.; Chen, Chia-Yen; Choi, Karmel W.; Coleman, Jonathan R. I.; Daskalakis, Nikolaos P.; Duncan, Laramie E.; Polimanti, Renato; Aaronson, Cindy; Amstadter, Ananda B.; Andersen, Soren B.; Andreassen, Ole A.; Arbisi, Paul A.; Ashley-Koch, Allison E.; Austin, S. Bryn; Avdibegoviç, Esmina; Babić, Dragan; Bacanu, Silviu-Alin; Baker, Dewleen G.; Batzler, Anthony; Beckham, Jean C.; Belangero, Sintia; Benjet, Corina; Bergner, Carisa; Bierer, Linda M.; Biernacka, Joanna M.; Bierut, Laura J.; Bisson, Jonathan I.; Boks, Marco P.; Bolger, Elizabeth A.; Brandolino, Amber; Breen, Gerome; Bressan, Rodrigo Affonseca; Bryant, Richard A.; Bustamante, Angela C.; Bybjerg-Grauholm, Jonas; Bækvad-Hansen, Marie; Børglum, Anders D.; Børte, Sigrid; Cahn, Leah; Calabrese, Joseph R.; Caldas-de-Almeida, Jose Miguel; Chatzinakos, Chris; Cheema, Sheraz; Clouston, Sean A. P.; Colodro-Conde, Lucía; Coombes, Brandon J.; Cruz-Fuentes, Carlos S.; Dale, Anders M.; Dalvie, Shareefa; Davis, Lea K.; Deckert, Jürgen; Delahanty, Douglas L.; Dennis, Michelle F.; Desarnaud, Frank; DiPietro, Christopher P.; Disner, Seth G.; Docherty, Anna R.; Domschke, Katharina; Dyb, Grete; Džubur Kulenović, Alma; Edenberg, Howard J.; Evans, Alexandra; Fabbri, Chiara; Fani, Negar; Farrer, Lindsay A.; Feder, Adriana; Feeny, Norah C.; Flory, Janine D.; Forbes, David; Franz, Carol E.; Galea, Sandro; Garrett, Melanie E.; Gelaye, Bizu; Gelernter, Joel; Geuze, Elbert; Gillespie, Charles F.; Goleva, Slavina B.; Gordon, Scott D.; Goçi, Aferdita; Grasser, Lana Ruvolo; Guindalini, Camila; Haas, Magali; Hagenaars, Saskia; Hauser, Michael A.; Heath, Andrew C.; Hemmings, Sian M. J.; Hesselbrock, Victor; Hickie, Ian B.; Hogan, Kelleigh; Hougaard, David Michael; Huang, Hailiang; Huckins, Laura M.; Hveem, Kristian; Jakovljević, Miro; Javanbakht, Arash; Jenkins, Gregory D.; Johnson, Jessica; Jones, Ian; Jovanovic, Tanja; Karstoft, Karen-Inge; Kaufman, Milissa L.; Kennedy, James L.; Kessler, Ronald C.; Khan, Alaptagin; Kimbrel, Nathan A.; King, Anthony P.; Koen, Nastassja; Kotov, Roman; Kranzler, Henry R.; Krebs, Kristi; Kremen, William S.; Kuan, Pei-Fen; Lawford, Bruce R.; Lebois, Lauren A. M.; Lehto, Kelli; Levey, Daniel F.; Lewis, Catrin; Liberzon, Israel; Linnstaedt, Sarah D.; Logue, Mark W.; Lori, Adriana; Lu, Yi; Luft, Benjamin J.; Lupto, Michelle K.; Luykx, Jurjen J.; Makotkine, Iouri; Maples-Keller, Jessica L.; Marchese, Shelby; Marmar, Charles; Martin, Nicholas G.; Martínez-Levy, Gabriela A.; McAloney, Kerrie; McFarlane, Alexander; McLaughlin, Katie A.; McLean, Samuel A.; Medland, Sarah E.; Mehta, Divya; Meyers, Jacquelyn; Michopoulos, Vasiliki; Mikita, Elizabeth A.; Milani, Lili; Milberg, William; Miller, Mark W.; Morey, Rajendra A.; Morris, Charles Phillip; Mors, Ole; Mortensen, Preben Bo; Mufford, Mary S.; Nelson, Elliot C.; Nordentoft, Merete; Norman, Sonya B.; Nugent, Nicole R.; O'Donnell, Meaghan; Orcutt, Holly K.; Pan, Pedro M.; Panizzon, Matthew S.; Pathak, Gita A.; Peters, Edward S.; Peterson, Alan L.; Peverill, Matthew; Pietrzak, Robert H.; Polusny, Melissa A.; Porjesz, Bernice; Powers, Abigail; Qin, Xue-Jun; Ratanatharathorn, Andrew; Risbrough, Victoria B.; Roberts, Andrea L.; Rothbaum, Alex O.; Rothbaum, Barbara O.; Roy-Byrne, Peter; Ruggiero, Kenneth J.; Rung, Ariane; Runz, Heiko; Rutten, Bart P. F.; Saenz de Viteri, Stacey; Salum, Giovanni Abrahão; Sampson, Laura; Sanchez, Sixto E.; Santoro, Marcos; Seah, Carina; Seedat, Soraya; Seng, Julia S.; Shabalin, Andrey; Sheerin, Christina M.; Silove, Derrick; Smith, Alicia K.; Smoller, Jordan W.; Sponheim, Scott R.; Stein, Dan J.; Stensland, Synne; Stevens, Jennifer S.; Sumner, Jennifer A.; Teicher, Martin H.; Thompson, Wesley K.; Tiwari, Arun K.; Trapido, Edward; Uddin, Monica; Ursano, Robert J.; Valdimarsdóttir, Unnur; Van Hooff, Miranda; Vermetten, Eric; Vinkers, Christiaan H.; Voisey, Joanne; Wang, Yunpeng; Wang, Zhewu; Waszczuk, Monika; Weber, Heike; Wendt, Frank R.; Werge, Thomas; Williams, Michelle A.; Williamson, Douglas E.; Winsvold, Bendik S.; Winternitz, Sherry; Wolf, Christiane; Wolf, Erika J.; Xia, Yan; Xiong, Ying; Yehuda, Rachel; Young, Keith A.; Young, Ross McD.; Zai, Clement C.; Zai, Gwyneth C.; Zervas, Mark; Zhao, Hongyu; Zoellner, Lori A.; Zwart, John-Anker; deRoon-Cassini, Terri; van Rooij, Sanne J. H.; van den Heuvel, Leigh L.; AURORA Study; Estonian Biobank Research Team; FinnGen Investigators; HUNT All-In Psychiatry; Stein, Murray B.; Ressler, Kerry J.; Koenen, Karestan C.; Biochemistry and Molecular Biology, School of MedicinePost-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.Item Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci(Springer, 2022-10) Deak, Joseph D.; Zhou, Hang; Galimberti, Marco; Levey, Daniel F.; Wendt, Frank R.; Sanchez-Roige, Sandra; Hatoum, Alexander S.; Johnson, Emma C.; Nunez, Yaira Z.; Demontis, Ditte; Børglum, Anders D.; Rajagopal, Veera M.; Jennings, Mariela V.; Kember, Rachel L.; Justice, Amy C.; Edenberg, Howard J.; Agrawal, Arpana; Polimanti, Renato; Kranzler, Henry R.; Gelernter, Joel; Biochemistry and Molecular Biology, School of MedicineDespite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10−8) lead SNPs—one at FURIN (rs11372849; p = 9.54 × 10−10) and two OPRM1 variants (rs1799971, p = 4.92 × 10−09; rs79704991, p = 1.11 × 10−08; r2 = 0.02). Rs1799971 (p = 4.91 × 10−08) and another OPRM1 variant (rs9478500; p = 1.95 × 10−08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10−47) and AUD (rg = 0.77; p = 6.36 × 10−78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10−16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10−13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.Item Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits(Nature, 2020-07) Zhou, Hang; Sealock, Julia M.; Sanchez-Roige, Sandra; Clarke, Toni-Kim; Levey, Daniel F.; Cheng, Zhongshan; Li, Boyang; Polimanti, Renato; Kember, Rachel L.; Smith, Rachel Vickers; Thygesen, Johan H.; Morgan, Marsha Y.; Atkinson, Stephen R.; Thursz, Mark R.; Nyegaard, Mette; Mattheisen, Manuel; Børglum, Anders D.; Johnson, Emma C.; Justice, Amy C.; Palmer, Abraham A.; McQuillin, Andrew; Davis, Lea K.; Edenberg, Howard J.; Agrawal, Arpana; Kranzler, Henry R.; Gelernter, Joel; Medical and Molecular Genetics, School of MedicineProblematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.Item GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors(American Psychiatric Association, 2023) Docherty, Anna R.; Mullins, Niamh; Ashley-Koch, Allison E.; Qin, Xuejun; Coleman, Jonathan R. I.; Shabalin, Andrey; Kang, JooEun; Murnyak, Balasz; Wendt, Frank; Adams, Mark; Campos, Adrian I.; DiBlasi, Emily; Fullerton, Janice M.; Kranzler, Henry R.; Bakian, Amanda V.; Monson, Eric T.; Rentería, Miguel E.; Walss-Bass, Consuelo; Andreassen, Ole A.; Behera, Chittaranjan; Bulik, Cynthia M.; Edenberg, Howard J.; Kessler, Ronald C.; Mann, J. John; Nurnberger, John I., Jr.; Pistis, Giorgio; Streit, Fabian; Ursano, Robert J.; Polimanti, Renato; Dennis, Michelle; Garrett, Melanie; Hair, Lauren; Harvey, Philip; Hauser, Elizabeth R.; Hauser, Michael A.; Huffman, Jennifer; Jacobson, Daniel; Madduri, Ravi; McMahon, Benjamin; Oslin, David W.; Trafton, Jodie; Awasthi, Swapnil; Berrettini, Wade H.; Bohus, Martin; Chang, Xiao; Chen, Hsi-Chung; Chen, Wei J.; Christensen, Erik D.; Crow, Scott; Duriez, Philibert; Edwards, Alexis C.; Fernández-Aranda, Fernando; Galfalvy, Hanga; Gandal, Michael; Gorwood, Philip; Guo, Yiran; Hafferty, Jonathan D.; Hakonarson, Hakon; Halmi, Katherine A.; Hishimoto, Akitoyo; Jain, Sonia; Jamain, Stéphane; Jiménez-Murcia, Susana; Johnson, Craig; Kaplan, Allan S.; Kaye, Walter H.; Keel, Pamela K.; Kennedy, James L.; Kim, Minsoo; Klump, Kelly L.; Levey, Daniel F.; Li, Dong; Liao, Shih-Cheng; Lieb, Klaus; Lilenfeld, Lisa; Marshall, Christian R.; Mitchell, James E.; Okazaki, Satoshi; Otsuka, Ikuo; Pinto, Dalila; Powers, Abigail; Ramoz, Nicolas; Ripke, Stephan; Roepke, Stefan; Rozanov, Vsevolod; Scherer, Stephen W.; Schmahl, Christian; Sokolowski, Marcus; Starnawska, Anna; Strober, Michael; Su, Mei-Hsin; Thornton, Laura M.; Treasure, Janet; Ware, Erin B.; Watson, Hunna J.; Witt, Stephanie H.; Woodside, D. Blake; Yilmaz, Zeynep; Zillich, Lea; Adolfsson, Rolf; Agartz, Ingrid; Alda, Martin; Alfredsson, Lars; Appadurai, Vivek; Artigas, María Soler; Van der Auwera, Sandra; Azevedo, M. Helena; Bass, Nicholas; Bau, Claiton H. D.; Baune, Bernhard T.; Bellivier, Frank; Berger, Klaus; Biernacka, Joanna M.; Bigdeli, Tim B.; Binder, Elisabeth B.; Boehnke, Michael; Boks, Marco P.; Braff, David L.; Bryant, Richard; Budde, Monika; Byrne, Enda M.; Cahn, Wiepke; Castelao, Enrique; Cervilla, Jorge A.; Chaumette, Boris; Corvin, Aiden; Craddock, Nicholas; Djurovic, Srdjan; Foo, Jerome C.; Forstner, Andreas J.; Frye, Mark; Gatt, Justine M.; Giegling, Ina; Grabe, Hans J.; Green, Melissa J.; Grevet, Eugenio H.; Grigoroiu-Serbanescu, Maria; Gutierrez, Blanca; Guzman-Parra, Jose; Hamshere, Marian L.; Hartmann, Annette M.; Hauser, Joanna; Heilmann-Heimbach, Stefanie; Hoffmann, Per; Ising, Marcus; Jones, Ian; Jones, Lisa A.; Jonsson, Lina; Kahn, René S.; Kelsoe, John R.; Kendler, Kenneth S.; Kloiber, Stefan; Koenen, Karestan C.; Kogevinas, Manolis; Krebs, Marie-Odile; Landén, Mikael; Leboyer, Marion; Lee, Phil H.; Levinson, Douglas F.; Liao, Calwing; Lissowska, Jolanta; Mayoral, Fermin; McElroy, Susan L.; McGrath, Patrick; McGuffin, Peter; McQuillin, Andrew; Mehta, Divya; Melle, Ingrid; Mitchell, Philip B.; Molina, Esther; Morken, Gunnar; Nievergelt, Caroline; Nöthen, Markus M.; O'Donovan, Michael C.; Ophoff, Roel A.; Owen, Michael J.; Pato, Carlos; Pato, Michele T.; Penninx, Brenda W. J. H.; Potash, James B.; Power, Robert A.; Preisig, Martin; Quested, Digby; Ramos-Quiroga, Josep Antoni; Reif, Andreas; Ribasés, Marta; Richarte, Vanesa; Rietschel, Marcella; Rivera, Margarita; Roberts, Andrea; Roberts, Gloria; Rouleau, Guy A.; Rovaris, Diego L.; Sanders, Alan R.; Schofield, Peter R.; Schulze, Thomas G.; Scott, Laura J.; Serretti, Alessandro; Shi, Jianxin; Sirignano, Lea; Sklar, Pamela; Smeland, Olav B.; Smoller, Jordan W.; Sonuga-Barke, Edmund J. S.; Trzaskowski, Maciej; Tsuang, Ming T.; Turecki, Gustavo; Vilar-Ribó, Laura; Vincent, John B.; Völzke, Henry; Walters, James T. R.; Weickert, Cynthia Shannon; Weickert, Thomas W.; Weissman, Myrna M.; Williams, Leanne M.; Wray, Naomi R.; Zai, Clement C.; Agerbo, Esben; Børglum, Anders D.; Breen, Gerome; Demontis, Ditte; Erlangsen, Annette; Gelernter, Joel; Glatt, Stephen J.; Hougaard, David M.; Hwu, Hai-Gwo; Kuo, Po-Hsiu; Lewis, Cathryn M.; Li, Qingqin S.; Liu, Chih-Min; Martin, Nicholas G.; McIntosh, Andrew M.; Medland, Sarah E.; Mors, Ole; Nordentoft, Merete; Olsen, Catherine M.; Porteous, David; Smith, Daniel J.; Stahl, Eli A.; Stein, Murray B.; Wasserman, Danuta; Werge, Thomas; Whiteman, David C.; Willour, Virginia; VA Million Veteran Program (MVP); MVP Suicide Exemplar Workgroup; Suicide Working Group of the Psychiatric Genomics Consortium; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium; Bipolar Disorder Working Group of the Psychiatric Genomics Consortium; Schizophrenia Working Group of the Psychiatric Genomics Consortium; Eating Disorder Working Group of the Psychiatric Genomics Consortium; German Borderline Genomics Consortium; Coon, Hilary; Beckham, Jean C.; Kimbrel, Nathan A.; Ruderfer, Douglas M.; Psychiatry, School of MedicineObjective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.Item Integration of evidence across human and model organism studies: A meeting report(Wiley, 2021-04-23) Palmer, Rohan H.C.; Johnson, Emma C.; Won, Hyejung; Polimanti, Renato; Kapoor, Manav; Chitre, Apurva; Bogue, Molly A.; Benca-Bachman, Chelsie E.; Parker, Clarissa C.; Verm, Anurag; Reynolds, Timothy; Ernst, Jason; Bray, Michael; Kwon, Soo Bin; Lai, Dongbing; Quach, Bryan C.; Gaddis, Nathan C.; Saba, Laura; Chen, Hao; Hawrylycz, Michael; Zhang, Shan; Zhou, Yuan; Mahaffey, Spencer; Fischer, Christian; Sanchez-Roige, Sandra; Bandrowski, Anita; Lu, Qing; Shen, Li; Philip, Vivek; Gelernter, Joel; Bierut, Laura J.; Hancock, Dana B.; Edenberg, Howard J.; Johnson, Eric O.; Nestler, Eric J.; Barr, Peter B.; Prins, Pjotr; Smith, Desmond J.; Akbarian, Schahram; Thorgeirsson, Thorgeir; Walton, Dave; Baker, Erich; Jacobson, Daniel; Palmer, Abraham A.; Miles, Michael; Chesler, Elissa J.; Emerson, Jake; Agrawal, Arpana; Martone, Maryann; Williams, Robert W.; Medical and Molecular Genetics, School of MedicineThe National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.Item Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder(Cambridge University Press, 2023) Johnson, Emma C.; Kapoor, Manav; Hatoum, Alexander S.; Zhou, Hang; Polimanti, Renato; Wendt, Frank R.; Walters, Raymond K.; Lai, Dongbing; Kember, Rachel L.; Hartz, Sarah; Meyers, Jacquelyn L.; Peterson, Roseann E.; Ripke, Stephan; Bigdeli, Tim B.; Fanous, Ayman H.; Pato, Carlos N.; Pato, Michele T.; Goate, Alison M.; Kranzler, Henry R.; O’Donovan, Michael C.; Walters, James T. R.; Gelernter, Joel; Edenberg, Howard J.; Agrawal, Arpana; Medical and Molecular Genetics, School of MedicineBackground: Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders. Methods: We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific. Results: We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). Conclusions: Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.