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Browsing by Author "Chen, Chia-Yen"
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Item Explicit Modeling of Ancestry Improves Polygenic Risk Scores and BLUP Prediction(Wiley, 2015-09) Chen, Chia-Yen; Han, Jiali; Hunter, David J.; Kraft, Peter; Price, Alkes L.; Department of Epidemiology, Richard M. Fairbanks School of Public HealthPolygenic prediction using genome-wide SNPs can provide high prediction accuracy for complex traits. Here, we investigate the question of how to account for genetic ancestry when conducting polygenic prediction. We show that the accuracy of polygenic prediction in structured populations may be partly due to genetic ancestry. However, we hypothesized that explicitly modeling ancestry could improve polygenic prediction accuracy. We analyzed three GWAS of hair color (HC), tanning ability (TA), and basal cell carcinoma (BCC) in European Americans (sample size from 7,440 to 9,822) and considered two widely used polygenic prediction approaches: polygenic risk scores (PRSs) and best linear unbiased prediction (BLUP). We compared polygenic prediction without correction for ancestry to polygenic prediction with ancestry as a separate component in the model. In 10-fold cross-validation using the PRS approach, the R(2) for HC increased by 66% (0.0456-0.0755; P < 10(-16)), the R(2) for TA increased by 123% (0.0154 to 0.0344; P < 10(-16)), and the liability-scale R(2) for BCC increased by 68% (0.0138-0.0232; P < 10(-16)) when explicitly modeling ancestry, which prevents ancestry effects from entering into each SNP effect and being overweighted. Surprisingly, explicitly modeling ancestry produces a similar improvement when using the BLUP approach, which fits all SNPs simultaneously in a single variance component and causes ancestry to be underweighted. We validate our findings via simulations, which show that the differences in prediction accuracy will increase in magnitude as sample sizes increase. In summary, our results show that explicitly modeling ancestry can be important in both PRS and BLUP prediction.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 Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations(Elsevier, 2019-10-10) Peterson, Roseann E.; Kuchenbaecker, Karoline; Walters, Raymond K.; Chen, Chia-Yen; Popejoy, Alice B.; Periyasamy, Sathish; Lam, Max; Iyegbe, Conrad; Strawbridge, Rona J.; Brick, Leslie; Carey, Caitlin E.; Martin, Alicia R.; Meyers, Jacquelyn L.; Su, Jinni; Chen, Junfang; Edwards, Alexis C.; Kalungi, Allan; Koen, Nastassja; Majara, Lerato; Schwarz, Emanuel; Smoller, Jordan W.; Stahl, Eli A.; Sullivan, Patrick F.; Vassos, Evangelos; Mowry, Bryan; Prieto, Miguel L.; Cuellar-Barboza, Alfredo; Bigdeli, Tim B.; Edenberg, Howard J.; Huang, Hailiang; Duncan, Laramie E.; Biochemistry and Molecular Biology, School of MedicineGenome-wide association studies (GWAS) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.Item Sex-Dependent Shared and Non-Shared Genetic Architecture Across Mood and Psychotic Disorders(Elsevier, 2022) Blokland, Gabriëlla A. M.; Grove, Jakob; Chen, Chia-Yen; Cotsapas, Chris; Tobet, Stuart; Handa, Robert; Schizophrenia Working Group of the Psychiatric Genomics Consortium; St. Clair, David; Lencz, Todd; Mowry, Bryan J.; Periyasamy, Sathish; Cairns, Murray J.; Tooney, Paul A.; Wu, Jing Qin; Kelly, Brian; Kirov, George; Sullivan, Patrick F.; Corvin, Aiden; Riley, Brien P.; Esko, Tõnu; Milani, Lili; Jönsson, Erik G.; Palotie, Aarno; Ehrenreich, Hannelore; Begemann, Martin; Steixner-Kumar, Agnes; Sham, Pak C.; Iwata, Nakao; Weinberger, Daniel R.; Gejman, Pablo V.; Sanders, Alan R.; Buxbaum, Joseph D.; Rujescu, Dan; Giegling, Ina; Konte, Bettina; Hartmann, Annette M.; Bramon, Elvira; Murray, Robin M.; Pato, Michele T.; Lee, Jimmy; Melle, Ingrid; Molden, Espen; Ophoff, Roel A.; McQuillin, Andrew; Bass, Nicholas J.; Adolfsson, Rolf; Malhotra, Anil K.; Bipolar Disorder Working Group of the Psychiatric Genomics Consortium; Martin, Nicholas G.; Fullerton, Janice M.; Mitchell, Philip B.; Schofield, Peter R.; Forstner, Andreas J.; Degenhardt, Franziska; Schaupp, Sabrina; Comes, Ashley L.; Kogevinas, Manolis; Guzman-Parra, José; Reif, Andreas; Streit, Fabian; Sirignano, Lea; Cichon, Sven; Grigoroiu-Serbanescu, Maria; Hauser, Joanna; Lissowska, Jolanta; Mayoral, Fermin; Müller-Myhsok, Bertram; Świątkowska, Beata; Schulze, Thomas G.; Nöthen, Markus M.; Rietschel, Marcella; Kelsoe, John; Leboyer, Marion; Jamain, Stéphane; Etain, Bruno; Bellivier, Frank; Vincent, John B.; Alda, Martin; O'Donovan, Claire; Cervantes, Pablo; Biernacka, Joanna M.; Frye, Mark; McElroy, Susan L.; Scott, Laura J.; Stahl, Eli A.; Landén, Mikael; Hamshere, Marian L.; Smeland, Olav B.; Djurovic, Srdjan; Vaaler, Arne E.; Andreassen, Ole A.; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium; Baune, Bernhard T.; Air, Tracy; Preisig, Martin; Uher, Rudolf; Levinson, Douglas F.; Weissman, Myrna M.; Potash, James B.; Shi, Jianxin; Knowles, James A.; Perlis, Roy H.; Lucae, Susanne; Boomsma, Dorret I.; Penninx, Brenda W. J. H.; Hottenga, Jouke-Jan; de Geus, Eco J. C.; Willemsen, Gonneke; Milaneschi, Yuri; Tiemeier, Henning; Grabe, Hans J.; Teumer, Alexander; Van der Auwera, Sandra; Völker, Uwe; Hamilton, Steven P.; Magnusson, Patrik K. E.; Viktorin, Alexander; Mehta, Divya; Mullins, Niamh; Adams, Mark J.; Breen, Gerome; McIntosh, Andrew M.; Lewis, Cathryn M.; Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium; iPSYCH; Hougaard, David M.; Nordentoft, Merete; Mors, Ole; Mortensen, Preben B.; Werge, Thomas; Als, Thomas D.; Børglum, Anders D.; Petryshen, Tracey L.; Smoller, Jordan W.; Goldstein, Jill M.; Psychiatry, School of MedicineBackground: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10-7; rs73033497, p = 8.8 × 10-7; rs7914279, p = 6.4 × 10-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.