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1. Transcriptional profiling in microglia across physiological and pathological states identifies a transcriptional module associated with neurodegeneration

Author: Aysegul Guvenek, Neelroop Parikshak, Daria Zamolodchikov, Sahar Gelfman, Arden Moscati, Lee Dobbyn, Eli Stahl, Alan Shuldiner, and Giovanni Coppola
Subjects: Biology (General), QH301-705.5
Abstract: Abstract Microglia are the resident immune cells of the central nervous system and are involved in brain development, homeostasis, and disease. New imaging and genomics technologies are revealing microglial complexity across developmental and functional states, brain regions, and diseases. We curated a set of publicly available gene expression datasets from human microglia spanning disease and health to identify sets of genes reflecting physiological and pathological microglial states. We also integrated multiple human microglial single-cell RNA-seq datasets in Alzheimer’s disease (AD), multiple sclerosis (MS), and Parkinson’s disease, and identified a distinct microglial transcriptional signature shared across diseases. Analysis of germ-line DNA identified genes with variants associated with AD and MS that are overrepresented in microglial gene sets, including the disease-associated transcriptional signature. This work points to genes that are dysregulated in disease states and provides a resource for the analysis of diseases in which microglia are implicated by genetic evidence.
Published: 2024
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2. PMS2CL interference leading to erroneous identification of a pathogenic PMS2 variant in Black patients

Author: Jacqueline Cappadocia, Lisa B. Aiello, Michael J. Kelley, Bryson W. Katona, Kara N. Maxwell, Anurag Verma, Ph.D., Shefali S. Verma, Ph.D., Yuki Bradford, M.S., Ashlei Brock, Stephanie DerOhannessian, Scott Dudek, M.S., Joseph Dunn, Theodore Drivas, M.D., Ph.D., Ned Haubein, Khadijah Hu-Sain, Renae Judy, Ashley Kloter, Yi-An Ko, Meghan Livingstone, Linda Morrel, Colleen Morse, M.S., Afiya Poindexter, Marjorie Risman, M.S., Teo Tran, Fred Vadivieso, JoEllen Weaver, Daniel J. Rader, M.D., Marylyn D. Ritchie, Ph.D., Michael D. Feldman, M.D., Ph.D., Christina Beechert, Caitlin Forsythe, M.S., Erin D. Fuller, Zhenhua Gu, M.S., Michael Lattari, Alexander Lopez, M.S., John D. Overton, Ph.D., Maria Sotiropoulos Padilla, M.S., Manasi Pradhan, M.S., Kia Manoochehri, B.S., Thomas D. Schleicher, M.S., Louis Widom, Sarah E. Wolf, M.S., Ricardo H. Ulloa, B.S., Amelia Averitt, Ph.D., Nilanjana Banerjee, Ph.D., Michael Cantor, M.D., Dadong Li, Ph.D., Sameer Malhotra, M.D., Deepika Sharma, MHI, Jeffrey Staples, Ph.D., Xiaodong Bai, Ph.D., Suganthi Balasubramanian, Ph.D., Suying Bao, Ph.D., Boris Boutkov, Ph.D., Siying Chen, Ph.D., Gisu Eom, B.S., Lukas Habegger, Ph.D., Alicia Hawes, B.S., Shareef Khalid, Olga Krasheninina, M.S., Rouel Lanche, B.S., Adam J. Mansfield, B.A., Evan K. Maxwell, Ph.D., George Mitra, B.A., Mona Nafde, M.S., Sean O’Keeffe, Ph.D., Max Orelus, B.B.A., Razvan Panea, Ph.D., Tommy Polanco, B.A., Ayesha Rasool, M.S., Jeffrey G. Reid, Ph.D., William Salerno, Ph.D., Jeffrey C. Staples, Ph.D., Kathie Sun, Ph.D., Goncalo Abecasis, D.Phil., Joshua Backman, Ph.D., Amy Damask, Ph.D., Lee Dobbyn, Ph.D., Manuel Allen Revez Ferreira, Ph.D., Arkopravo Ghosh, M.S., Christopher Gillies, Ph.D., Lauren Gurski, B.S., Eric Jorgenson, Ph.D., Hyun Min Kang, Ph.D., Michael Kessler, Ph.D., Jack Kosmicki, Ph.D., Alexander Li, Ph.D., Nan Lin, Ph.D., Daren Liu, M.S., Adam Locke, Ph.D., Jonathan Marchini, Ph.D., Anthony Marcketta, M.S., Joelle Mbatchou, Ph.D., Arden Moscati, Ph.D., Charles Paulding, Ph.D., Carlo Sidore, Ph.D., Eli Stahl, Ph.D., Kyoko Watanabe, Ph.D., Bin Ye, Ph.D., Blair Zhang, Ph.D., Andrey Ziyatdinov, Ph.D., Ariane Ayer, B.S., Aysegul Guvenek, Ph.D., George Hindy, Ph.D., Giovanni Coppola, M.D., Jan Freudenberg, M.D., Jonas Bovijn, M.D., Katherine Siminovitch, M.D., Kavita Praveen, Ph.D., Luca A. Lotta, M.D., Manav Kapoor, Ph.D., Mary Haas, Ph.D., Moeen Riaz, Ph.D., Niek Verweij, Ph.D., Olukayode Sosina, Ph.D., Parsa Akbari, Ph.D., Priyanka Nakka, Ph.D., Sahar Gelfman, Ph.D., Sujit Gokhale, B.E., Tanima De, Ph.D., Veera Rajagopal, Ph.D., Alan Shuldiner, M.D., Gannie Tzoneva, Ph.D., Juan Rodriguez-Flores, Ph.D., Esteban Chen, M.S., Marcus B. Jones, Ph.D., Michelle G. LeBlanc, Ph.D., Jason Mighty, Ph.D., Lyndon J. Mitnaul, Ph.D., Nirupama Nishtala, Ph.D., Nadia Rana, Ph.D., Jaimee Hernandez, Goncalo Abecasis, PhD, Aris Baras, M.D., Andrew Deubler, Aris Economides, Ph.D., and Luca A. Lotta, M.D., Ph.D.
Subjects: PMS2, germline genetic testing, Lynch syndrome, PMS2CL, pseudogene interference, Genetics, QH426-470, Medicine
Abstract: This study investigates the frequency of a clinically reported variant in PMS2, NM_000535.7:c.2523G>A p.(W841∗), from next-generation sequencing studies in 2 racially diverse cohorts. We identified clinical reports of the PMS2 c.2523G>A p.(W841∗) variant in the National Precision Oncology Program’s somatic testing database (n = 25,168). We determined frequency of the variant in germline exome sequencing from the Penn Medicine BioBank (n = 44,256) and in gnomAD. The PMS2 c.2523G>A p.(W841∗) was identified as a homozygous variant on tumor testing in an adult patient of self-identified Black race/ethnicity with no evidence of constitutional mismatch repair deficiency. The variant was clinically reported on 35 total tumor and liquid biopsy tests (0.1%), and all individuals with the variant were of self-identified Black race/ethnicity (0.6% of n = 5787). In individuals of African genetic ancestry (AFR), the variant's germline frequency was reported to be 0.2% and 1.3% in the Penn Medicine BioBank (PMBB) and gnomAD, respectively. The variant cannot be found in any individuals of European genetic ancestry (EUR) from either of the databases. The variant is found in a region of PMS2 with 100% homology to the PMS2CL pseudogene. PMS2 c.2523G>A p.(W841∗), when identified, is typically an African-ancestry-specific PMS2CL pseudogene variant, which should be recognized to prevent misdiagnosis of Lynch syndrome in Blacks.
Published: 2024
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3. ANGPTL7, a therapeutic target for increased intraocular pressure and glaucoma

Author: Kavita Praveen, Gaurang C. Patel, Lauren Gurski, Ariane H. Ayer, Trikaladarshi Persaud, Matthew D. Still, Lawrence Miloscio, Tavé Van Zyl, Silvio Alessandro Di Gioia, Ben Brumpton, Kristi Krebs, Bjørn Olav Åsvold, Esteban Chen, Venkata R. M. Chavali, Wen Fury, Harini V. Gudiseva, Sarah Hyde, Eric Jorgenson, Stephanie Lefebvre, Dadong Li, Alexander Li, James Mclninch, Brijeshkumar Patel, Jeremy S. Rabinowitz, Rebecca Salowe, Claudia Schurmann, Anne-Sofie Seidelin, Eli Stahl, Dylan Sun, Tanya M. Teslovich, Anne Tybjærg-Hansen, Cristen Willer, Scott Waldron, Sabrina Walley, Hua Yang, Sarthak Zaveri, Regeneron Genetics Center, GHS-RGC DiscovEHR Collaboration, Estonian Biobank Research Team, Ying Hu, Kristian Hveem, Olle Melander, Lili Milani, Stefan Stender, Joan M. O’Brien, Marcus B. Jones, Gonçalo R. Abecasis, Michael N. Cantor, Jonathan Weyne, Katia Karalis, Aris Economides, Giusy Della Gatta, Manuel A. Ferreira, George D. Yancopoulos, Aris Baras, Carmelo Romano, and Giovanni Coppola
Subjects: Biology (General), QH301-705.5
Abstract: Rare variant association data from human genetics combined with in vitro and in vivo functional validation highlight ANGPTL7 as a promising therapeutic target for intraocular pressure reduction, and protection from glaucoma.
Published: 2022
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4. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Author: Solveig K. Sieberts, Fan Zhu, Javier García-García, Eli Stahl, Abhishek Pratap, Gaurav Pandey, Dimitrios Pappas, Daniel Aguilar, Bernat Anton, Jaume Bonet, Ridvan Eksi, Oriol Fornés, Emre Guney, Hongdong Li, Manuel Alejandro Marín, Bharat Panwar, Joan Planas-Iglesias, Daniel Poglayen, Jing Cui, Andre O. Falcao, Christine Suver, Bruce Hoff, Venkat S. K. Balagurusamy, Donna Dillenberger, Elias Chaibub Neto, Thea Norman, Tero Aittokallio, Muhammad Ammad-ud-din, Chloe-Agathe Azencott, Víctor Bellón, Valentina Boeva, Kerstin Bunte, Himanshu Chheda, Lu Cheng, Jukka Corander, Michel Dumontier, Anna Goldenberg, Peddinti Gopalacharyulu, Mohsen Hajiloo, Daniel Hidru, Alok Jaiswal, Samuel Kaski, Beyrem Khalfaoui, Suleiman Ali Khan, Eric R. Kramer, Pekka Marttinen, Aziz M. Mezlini, Bhuvan Molparia, Matti Pirinen, Janna Saarela, Matthias Samwald, Véronique Stoven, Hao Tang, Jing Tang, Ali Torkamani, Jean-Phillipe Vert, Bo Wang, Tao Wang, Krister Wennerberg, Nathan E. Wineinger, Guanghua Xiao, Yang Xie, Rae Yeung, Xiaowei Zhan, Cheng Zhao, Members of the Rheumatoid Arthritis Challenge Consortium, Jeff Greenberg, Joel Kremer, Kaleb Michaud, Anne Barton, Marieke Coenen, Xavier Mariette, Corinne Miceli, Nancy Shadick, Michael Weinblatt, Niek de Vries, Paul P. Tak, Danielle Gerlag, Tom W. J. Huizinga, Fina Kurreeman, Cornelia F. Allaart, S. Louis Bridges Jr., Lindsey Criswell, Larry Moreland, Lars Klareskog, Saedis Saevarsdottir, Leonid Padyukov, Peter K. Gregersen, Stephen Friend, Robert Plenge, Gustavo Stolovitzky, Baldo Oliva, Yuanfang Guan, and Lara M. Mangravite
Subjects: Science
Abstract: Rheumatoid arthritis patients respond differently to anti-TNF treatment. Using community-based challenge, the authors show that currently available data does not reveal meaningful genetic predictors of response to anti-TNF therapy, thus confirming clinical observations.
Published: 2016
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5. A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.

Author: Aaditya V Rangan, Caroline C McGrouther, John Kelsoe, Nicholas Schork, Eli Stahl, Qian Zhu, Arjun Krishnan, Vicky Yao, Olga Troyanskaya, Seda Bilaloglu, Preeti Raghavan, Sarah Bergen, Anders Jureus, Mikael Landen, and Bipolar Disorders Working Group of the Psychiatric Genomics Consortium
Subjects: Biology (General), QH301-705.5
Abstract: A common goal in data-analysis is to sift through a large data-matrix and detect any significant submatrices (i.e., biclusters) that have a low numerical rank. We present a simple algorithm for tackling this biclustering problem. Our algorithm accumulates information about 2-by-2 submatrices (i.e., 'loops') within the data-matrix, and focuses on rows and columns of the data-matrix that participate in an abundance of low-rank loops. We demonstrate, through analysis and numerical-experiments, that this loop-counting method performs well in a variety of scenarios, outperforming simple spectral methods in many situations of interest. Another important feature of our method is that it can easily be modified to account for aspects of experimental design which commonly arise in practice. For example, our algorithm can be modified to correct for controls, categorical- and continuous-covariates, as well as sparsity within the data. We demonstrate these practical features with two examples; the first drawn from gene-expression analysis and the second drawn from a much larger genome-wide-association-study (GWAS).
Published: 2018
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6. No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study.

Author: Emma C Johnson, Douglas W Bjelland, Daniel P Howrigan, Abdel Abdellaoui, Gerome Breen, Anders Borglum, Sven Cichon, Franziska Degenhardt, Andreas J Forstner, Josef Frank, Giulio Genovese, Stefanie Heilmann-Heimbach, Stefan Herms, Per Hoffman, Wolfgang Maier, Manuel Mattheisen, Derek Morris, Bryan Mowry, Betram Müller-Mhysok, Benjamin Neale, Igor Nenadic, Markus M Nöthen, Colm O'Dushlaine, Marcella Rietschel, Douglas M Ruderfer, Dan Rujescu, Thomas G Schulze, Matthew A Simonson, Eli Stahl, Jana Strohmaier, Stephanie H Witt, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Patrick F Sullivan, and Matthew C Keller
Subjects: Genetics, QH426-470
Abstract: It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest.
Published: 2016
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7. Disproportionate Contributions of Select Genomic Compartments and Cell Types to Genetic Risk for Coronary Artery Disease.

Author: Hong-Hee Won, Pradeep Natarajan, Amanda Dobbyn, Daniel M Jordan, Panos Roussos, Kasper Lage, Soumya Raychaudhuri, Eli Stahl, and Ron Do
Subjects: Genetics, QH426-470
Abstract: Large genome-wide association studies (GWAS) have identified many genetic loci associated with risk for myocardial infarction (MI) and coronary artery disease (CAD). Concurrently, efforts such as the National Institutes of Health (NIH) Roadmap Epigenomics Project and the Encyclopedia of DNA Elements (ENCODE) Consortium have provided unprecedented data on functional elements of the human genome. In the present study, we systematically investigate the biological link between genetic variants associated with this complex disease and their impacts on gene function. First, we examined the heritability of MI/CAD according to genomic compartments. We observed that single nucleotide polymorphisms (SNPs) residing within nearby regulatory regions show significant polygenicity and contribute between 59-71% of the heritability for MI/CAD. Second, we showed that the polygenicity and heritability explained by these SNPs are enriched in histone modification marks in specific cell types. Third, we found that a statistically higher number of 45 MI/CAD-associated SNPs that have been identified from large-scale GWAS studies reside within certain functional elements of the genome, particularly in active enhancer and promoter regions. Finally, we observed significant heterogeneity of this signal across cell types, with strong signals observed within adipose nuclei, as well as brain and spleen cell types. These results suggest that the genetic etiology of MI/CAD is largely explained by tissue-specific regulatory perturbation within the human genome.
Published: 2015
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8. Allele-specific methylation occurs at genetic variants associated with complex disease.

Author: John N Hutchinson, Towfique Raj, Jes Fagerness, Eli Stahl, Fernando T Viloria, Alexander Gimelbrant, Johanna Seddon, Mark Daly, Andrew Chess, and Robert Plenge
Subjects: Medicine, Science
Abstract: We hypothesize that the phenomenon of allele-specific methylation (ASM) may underlie the phenotypic effects of multiple variants identified by Genome-Wide Association studies (GWAS). We evaluate ASM in a human population and document its genome-wide patterns in an initial screen at up to 380,678 sites within the genome, or up to 5% of the total genomic CpGs. We show that while substantial inter-individual variation exists, 5% of assessed sites show evidence of ASM in at least six samples; the majority of these events (81%) are under genetic influence. Many of these cis-regulated ASM variants are also eQTLs in peripheral blood mononuclear cells and monocytes and/or in high linkage-disequilibrium with variants linked to complex disease. Finally, focusing on autoimmune phenotypes, we extend this initial screen to confirm the association of cis-regulated ASM with multiple complex disease-associated variants in an independent population using next-generation bisulfite sequencing. These four variants are implicated in complex phenotypes such as ulcerative colitis and AIDS progression disease (rs10491434), Celiac disease (rs2762051), Crohn's disease, IgA nephropathy and early-onset inflammatory bowel disease (rs713875) and height (rs6569648). Our results suggest cis-regulated ASM may provide a mechanistic link between the non-coding genetic changes and phenotypic variation observed in these diseases and further suggests a route to integrating DNA methylation status with GWAS results.
Published: 2014
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9. Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway.

Author: Gang Li, Dorothée Diogo, Di Wu, Jim Spoonamore, Vlado Dancik, Lude Franke, Fina Kurreeman, Elizabeth J Rossin, Grant Duclos, Cathy Hartland, Xuezhong Zhou, Kejie Li, Jun Liu, Philip L De Jager, Katherine A Siminovitch, Alexandra Zhernakova, Soumya Raychaudhuri, John Bowes, Steve Eyre, Leonid Padyukov, Peter K Gregersen, Jane Worthington, Rheumatoid Arthritis Consortium International (RACI), Namrata Gupta, Paul A Clemons, Eli Stahl, Nicola Tolliday, and Robert M Plenge
Subjects: Genetics, QH426-470
Abstract: Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P = 1.4×10(-9)). Second, we demonstrate that subjects homozygous for the RA risk allele have ∼33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P = 10(-9)), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-κB transcription factor. Finally, we develop a high-throughput NF-κB luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA-approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-κB signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.
Published: 2013
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10. Erratum: Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Author: Solveig K. Sieberts, Fan Zhu, Javier García-García, Eli Stahl, Abhishek Pratap, Gaurav Pandey, Dimitrios Pappas, Daniel Aguilar, Bernat Anton, Jaume Bonet, Ridvan Eksi, Oriol Fornés, Emre Guney, Hongdong Li, Manuel Alejandro Marín, Bharat Panwar, Joan Planas-Iglesias, Daniel Poglayen, Jing Cui, Andre O. Falcao, Christine Suver, Bruce Hoff, Venkat S. K. Balagurusamy, Donna Dillenberger, Elias Chaibub Neto, Thea Norman, Tero Aittokallio, Muhammad Ammad-ud-din, Chloe-Agathe Azencott, Víctor Bellón, Valentina Boeva, Kerstin Bunte, Himanshu Chheda, Lu Cheng, Jukka Corander, Michel Dumontier, Anna Goldenberg, Peddinti Gopalacharyulu, Mohsen Hajiloo, Daniel Hidru, Alok Jaiswal, Samuel Kaski, Beyrem Khalfaoui, Suleiman Ali Khan, Eric R. Kramer, Pekka Marttinen, Aziz M. Mezlini, Bhuvan Molparia, Matti Pirinen, Janna Saarela, Matthias Samwald, Véronique Stoven, Hao Tang, Jing Tang, Ali Torkamani, Jean-Phillipe Vert, Bo Wang, Tao Wang, Krister Wennerberg, Nathan E. Wineinger, Guanghua Xiao, Yang Xie, Rae Yeung, Xiaowei Zhan, Cheng Zhao, Members of the Rheumatoid Arthritis Challenge Consortium, Jeff Greenberg, Joel Kremer, Kaleb Michaud, Anne Barton, Marieke Coenen, Xavier Mariette, Corinne Miceli, Nancy Shadick, Michael Weinblatt, Niek de Vries, Paul P. Tak, Danielle Gerlag, Tom W. J. Huizinga, Fina Kurreeman, Cornelia F. Allaart, S. Louis Bridges Jr., Lindsey Criswell, Larry Moreland, Lars Klareskog, Saedis Saevarsdottir, Leonid Padyukov, Peter K. Gregersen, Stephen Friend, Robert Plenge, Gustavo Stolovitzky, Baldo Oliva, Yuanfang Guan, and Lara M. Mangravite
Subjects: Science
Abstract: Nature Communications 7: Article number: 12460 (2016); Published: 23 August 2016; Updated: 10 October 2016. The HTML version of this Article incorrectly duplicated the authors S. Louis Bridges, Lindsey Criswell, Larry Moreland, Lars Klareskog, Saedis Saevarsdottir, Leonid Padyukov, Peter K. Gregersen, Stephen Friend, Robert Plenge, Gustavo Stolovitzky, Baldo Oliva, Yuanfang Guan and Lara M.
Published: 2016
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11. Impact of schizophrenia GWAS loci converge onto distinct pathways in cortical interneurons vs glutamatergic neurons during development

Author: Dongxin Liu, Amy Zinski, Akanksha Mishra, Haneul Noh, Gun-Hoo Park, Yiren Qin, Oshoname Olorife, James M. Park, Chiderah P. Abani, Joy S. Park, Janice Fung, Farah Sawaqed, Joseph T. Coyle, Eli Stahl, Jaroslav Bendl, John F. Fullard, Panos Roussos, Xiaolei Zhang, Patric K. Stanton, Changhong Yin, Weihua Huang, Hae-Young Kim, Hyejung Won, Jun-Hyeong Cho, and Sangmi Chung
Subjects: Neurons, Mice, Cellular and Molecular Neuroscience, Psychiatry and Mental health, Interneurons, Schizophrenia, Animals, Humans, Brain, Genetic Predisposition to Disease, Molecular Biology, Genome-Wide Association Study
Abstract: Remarkable advances have been made in schizophrenia (SCZ) GWAS, but gleaning biological insight from these loci is challenging. Genetic influences on gene expression (e.g., eQTLs) are cell type-specific, but most studies that attempt to clarify GWAS loci's influence on gene expression have employed tissues with mixed cell compositions that can obscure cell-specific effects. Furthermore, enriched SCZ heritability in the fetal brain underscores the need to study the impact of SCZ risk loci in specific developing neurons. MGE-derived cortical interneurons (cINs) are consistently affected in SCZ brains and show enriched SCZ heritability in human fetal brains. We identified SCZ GWAS risk genes that are dysregulated in iPSC-derived homogeneous populations of developing SCZ cINs. These SCZ GWAS loci differential expression (DE) genes converge on the PKC pathway. Their disruption results in PKC hyperactivity in developing cINs, leading to arborization deficits. We show that the fine-mapped GWAS locus in the ATP2A2 gene of the PKC pathway harbors enhancer marks by ATACseq and ChIPseq, and regulates ATP2A2 expression. We also generated developing glutamatergic neurons (GNs), another population with enriched SCZ heritability, and confirmed their functionality after transplantation into the mouse brain. Then, we identified SCZ GWAS risk genes that are dysregulated in developing SCZ GNs. GN-specific SCZ GWAS loci DE genes converge on the ion transporter pathway, distinct from those for cINs. Disruption of the pathway gene CACNA1D resulted in deficits of Ca
Published: 2022
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12. Non-additive effects of schizophrenia risk genes reflect convergent downstream function

Author: PJ Michael Deans, Carina Seah, Jessica Johnson, Judit Garcia Gonzalez, Kayla Townsley, Evan Cao, Nadine Schrode, Eli Stahl, Paul O’Reilly, Laura M. Huckins, and Kristen J. Brennand
Subjects: Article
Abstract: Genetic studies of schizophrenia (SCZ) reveal a complex polygenic risk architecture comprised of hundreds of risk variants, the majority of which are common in the population at-large and confer only modest increases in disorder risk. Precisely how genetic variants with individually small predicted effects on gene expression combine to yield substantial clinical impacts in aggregate is unclear. Towards this, we previously reported that the combinatorial perturbation of four SCZ risk genes (“eGenes”, whose expression is regulated by common variants) resulted in gene expression changes that were not predicted by individual perturbations, being most non-additive among genes associated with synaptic function and SCZ risk. Now, across fifteen SCZ eGenes, we demonstrate that non-additive effects are greatest within groups of functionally similar eGenes. Individual eGene perturbations reveal common downstream transcriptomic effects (“convergence”), while combinatorial eGene perturbations result in changes that are smaller than predicted by summing individual eGene effects (“sub-additive effects”). Unexpectedly, these convergent and sub-additive downstream transcriptomic effects overlap and constitute a large proportion of the genome-wide polygenic risk score, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Single eGene perturbations likewise fail to predict the magnitude or directionality of cellular phenotypes resulting from combinatorial perturbations. Overall, our results indicate that polygenic risk cannot be extrapolated from experiments testing one risk gene at a time and must instead be empirically measured. By unravelling the interactions between complex risk variants, it may be possible to improve the clinical utility of polygenic risk scores through more powerful prediction of symptom onset, clinical trajectory, and treatment response, or to identify novel targets for therapeutic intervention.
Published: 2023
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13. The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

Author: Henry Kranzler, Sylvanus Toikumo, Rachel Vickers-Smith, Zeal Jinwala, Heng Xu, Divya Saini, Emily Hartwell, Mirko Pavicic, Kyle Sullivan, Ke Xu, Daniel Jacobson, Joel Gelernter, Christopher Rentscsh, Eli Stahl, Martin Cheatle, Hang Zhou, Stephen Waxman, Amy Justice, and Rachel Kember
Abstract: Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25–50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.
Published: 2023
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14. Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions

Author: Brenda Xiao, Digna R. Velez Edwards, Anastasia Lucas, Theodore Drivas, Kathryn Gray, Brendan Keating, Chunhua Weng, Gail P. Jarvik, Hakon Hakonarson, Leah Kottyan, Noemie Elhadad, Wei‐Qi Wei, Yuan Luo, Dokyoon Kim, Marylyn Ritchie, Shefali Setia Verma, Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Andrew Deubler, Aris Economides, Katia Karalis, Luca A. Lotta, John D. Overton, Jeffrey G. Reid, Katherine Siminovitch, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Maria Sotiropoulos Padilla, Manasi Pradhan, Kia Manoochehri, Thomas D. Schleicher, Louis Widom, Sarah E. Wolf, Ricardo H. Ulloa, Amelia Averitt, Nilanjana Banerjee, Dadong Li, Sameer Malhotra, Deepika Sharma, Jeffrey Staples, Xiaodong Bai, Suganthi Balasubramanian, Suying Bao, Boris Boutkov, Siying Chen, Gisu Eom, Lukas Habegger, Alicia Hawes, Shareef Khalid, Olga Krasheninina, Rouel Lanche, Adam J. Mansfield, Evan K. Maxwell, George Mitra, Mona Nafde, Sean O’Keeffe, Max Orelus, Razvan Panea, Tommy Polanco, Ayesha Rasool, William Salerno, Jeffrey C. Staples, Kathie Sun, Joshua Backman, Amy Damask, Lee Dobbyn, Manuel Allen Revez Ferreira, Arkopravo Ghosh, Christopher Gillies, Lauren Gurski, Eric Jorgenson, Hyun Min Kang, Michael Kessler, Jack Kosmicki, Alexander Li, Nan Lin, Daren Liu, Adam Locke, Jonathan Marchini, Anthony Marcketta, Joelle Mbatchou, Arden Moscati, Charles Paulding, Carlo Sidore, Eli Stahl, Kyoko Watanabe, Bin Ye, Blair Zhang, Andrey Ziyatdinov, Ariane Ayer, Aysegul Guvenek, George Hindy, Jan Freudenberg, Jonas Bovijn, Kavita Praveen, Manav Kapoor, Mary Haas, Moeen Riaz, Niek Verweij, Olukayode Sosina, Parsa Akbari, Priyanka Nakka, Sahar Gelfman, Sujit Gokhale, Tanima De, Veera Rajagopal, Gannie Tzoneva, Juan Rodriguez‐Flores, Shek Man Chim, Valerio Donato, Daniel Fernandez, Giusy Della Gatta, Alessandro Di Gioia, Kristen Howell, Lori Khrimian, Minhee Kim, Hector Martinez, Lawrence Miloscio, Sheilyn Nunez, Elias Pavlopoulos, Trikaldarshi Persaud, Esteban Chen, Marcus B. Jones, Michelle G. LeBlanc, Jason Mighty, Lyndon J. Mitnaul, Nirupama Nishtala, and Nadia Rana
Subjects: Cardiology and Cardiovascular Medicine
Abstract: Background Cardiometabolic diseases are highly comorbid, but their relationship with female‐specific or overwhelmingly female‐predominant health conditions (breast cancer, endometriosis, pregnancy complications) is understudied. This study aimed to estimate the cross‐trait genetic overlap and influence of genetic burden of cardiometabolic traits on health conditions unique to women. Methods and Results Using electronic health record data from 71 008 ancestrally diverse women, we examined relationships between 23 obstetrical/gynecological conditions and 4 cardiometabolic phenotypes (body mass index, coronary artery disease, type 2 diabetes, and hypertension) by performing 4 analyses: (1) cross‐trait genetic correlation analyses to compare genetic architecture, (2) polygenic risk score–based association tests to characterize shared genetic effects on disease risk, (3) Mendelian randomization for significant associations to assess cross‐trait causal relationships, and (4) chronology analyses to visualize the timeline of events unique to groups of women with high and low genetic burden for cardiometabolic traits and highlight the disease prevalence in risk groups by age. We observed 27 significant associations between cardiometabolic polygenic scores and obstetrical/gynecological conditions (body mass index and endometrial cancer, body mass index and polycystic ovarian syndrome, type 2 diabetes and gestational diabetes, type 2 diabetes and polycystic ovarian syndrome). Mendelian randomization analysis provided additional evidence of independent causal effects. We also identified an inverse association between coronary artery disease and breast cancer. High cardiometabolic polygenic scores were associated with early development of polycystic ovarian syndrome and gestational hypertension. Conclusions We conclude that polygenic susceptibility to cardiometabolic traits is associated with elevated risk of certain female‐specific health conditions.
Published: 2023
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15. Polygenic risk of Social-isolation and its influence on social behavior, psychosis, depression and autism spectrum disorder

Author: Adam Socrates, Niamh Mullins, Ruben Gur, Raquel Gur, Eli Stahl, Paul O’Reilly, Abraham Reichenberg, Hannah Jones, Stan Zammit, and Eva Velthorst
Abstract: Social-isolation has been linked to a range of psychiatric issues, but the behavioral component that drives it is not well understood. Here, a GWAS is carried out to identify genetic variants which contribute to Social-isolation behaviors in up to 449,609 participants from the UK Biobank. 17 loci were identified at genome-wide significance, contributing to a 4% SNP heritability estimate. Using the Social-isolation GWAS, polygenic risk scores (PRS) were derived in ALSPAC, an independent, developmental cohort, and used to test for association with friendship quality. At age 18, friendship scores were associated with the Social-isolation PRS, demonstrating that the genetic factors are able to predict related social traits. LD score regression using the GWAS demonstrated genetic correlation with autism spectrum disorder, schizophrenia, and major depressive disorder. However, no evidence of causality was found using a conservative Mendelian randomization approach other than that of autism spectrum disorder on Social-isolation. Our results show that Social-isolation has a small heritable component which may drive those behaviors which is associated genetically with other social traits such as friendship satisfaction as well as psychiatric disorders.
Published: 2023
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16. 37. CONVERGENT IMPACT OF SCHIZOPHRENIA RISK GENES

Author: Kayla Townsley, Aiqun Li, PJ Michael Deans, John F. Fullard, Alex Yu, Sam Cartwright, Minghui Wang, Georgios Voloudakis, Kiran Girdhar, Schahram Akbarian, Eli Stahl, Panos Roussos, Bin Zhang, Laura Huckins, and Kristen J. Brennand
Subjects: Pharmacology, Psychiatry and Mental health, Neurology, Pharmacology (medical), Neurology (clinical), Biological Psychiatry
Published: 2022
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17. Convergent impact of schizophrenia risk genes

Author: Kayla G. Townsley, Aiqun Li, PJ Michael Deans, John F. Fullard, Alex Yu, Sam Cartwright, Wen Zhang, Minghui Wang, Georgios Voloudakis, Kiran Girdhar, Eli Stahl, Schahram Akbarian, Bin Zhang, Panos Roussos, Laura M. Huckins, and Kristen J. Brennand
Abstract: Genetic liability associated with schizophrenia most frequently arises from common genetic variation that confers small individual effects and contributes to phenotypes only when considered in aggregate. These risk variants are typically non-coding and act by genetically regulating the expression of one or more gene targets (eGenes), but the mechanisms by which unlinked eGenes interact to contribute to complex genetic risk remains unclear. Here we apply a pooled CRISPR approach to evaluate in parallel ten schizophrenia eGenes in human glutamatergic neurons. Querying the shared neuronal impacts across eGenes reveals shared downstream transcriptomic impacts (“convergence”) concentrated on pathways of brain development and synaptic signaling. The composition and strength of convergent networks is influenced by both the similarity of eGene functional annotation and the strength of eGene co-expression in human postmortem brain tissue. Convergent networks resolve distinct patterns of eGene up-regulation associated with individual-level risk in the post-mortem dorsolateral prefrontal cortex that are broadly enriched for neuropsychiatric disorder risk genes and may represent molecular subtypes of schizophrenia. Convergent gene targets are druggable as novel points of therapeutic intervention. Overall, convergence suggests a model to explain how non-additive interactions arise between risk genes and may explain cross-disorder pleiotropy of genetic risk for psychiatric disorders.
Published: 2022
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18. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Author: Gabriëlla A.M. Blokland, Jakob Grove, Chia-Yen Chen, Chris Cotsapas, Stuart Tobet, Robert Handa, David St Clair, Todd Lencz, Bryan J. Mowry, Sathish Periyasamy, Murray J. Cairns, Paul A. Tooney, Jing Qin Wu, Brian Kelly, George Kirov, Patrick F. Sullivan, Aiden Corvin, Brien P. Riley, Tõnu Esko, Lili Milani, Erik G. Jönsson, Aarno Palotie, Hannelore Ehrenreich, Martin Begemann, Agnes Steixner-Kumar, Pak C. Sham, Nakao Iwata, Daniel R. Weinberger, Pablo V. Gejman, Alan R. Sanders, Joseph D. Buxbaum, Dan Rujescu, Ina Giegling, Bettina Konte, Annette M. Hartmann, Elvira Bramon, Robin M. Murray, Michele T. Pato, Jimmy Lee, Ingrid Melle, Espen Molden, Roel A. Ophoff, Andrew McQuillin, Nicholas J. Bass, Rolf Adolfsson, Anil K. Malhotra, Nicholas G. Martin, Janice M. Fullerton, Philip B. Mitchell, Peter R. Schofield, Andreas J. Forstner, Franziska Degenhardt, Sabrina Schaupp, Ashley L. Comes, Manolis Kogevinas, José Guzman-Parra, Andreas Reif, Fabian Streit, Lea Sirignano, Sven Cichon, Maria Grigoroiu-Serbanescu, Joanna Hauser, Jolanta Lissowska, Fermin Mayoral, Bertram Müller-Myhsok, Beata Świątkowska, Thomas G. Schulze, Markus M. Nöthen, Marcella Rietschel, John Kelsoe, Marion Leboyer, Stéphane Jamain, Bruno Etain, Frank Bellivier, John B. Vincent, Martin Alda, Claire O’Donovan, Pablo Cervantes, Joanna M. Biernacka, Mark Frye, Susan L. McElroy, Laura J. Scott, Eli A. Stahl, Mikael Landén, Marian L. Hamshere, Olav B. Smeland, Srdjan Djurovic, Arne E. Vaaler, Ole A. Andreassen, Bernhard T. Baune, Tracy Air, Martin Preisig, Rudolf Uher, Douglas F. Levinson, Myrna M. Weissman, James B. Potash, Jianxin Shi, James A. Knowles, Roy H. Perlis, Susanne Lucae, Dorret I. Boomsma, Brenda W.J.H. Penninx, Jouke-Jan Hottenga, Eco J.C. de Geus, Gonneke Willemsen, Yuri Milaneschi, Henning Tiemeier, Hans J. Grabe, Alexander Teumer, Sandra Van der Auwera, Uwe Völker, Steven P. Hamilton, Patrik K.E. Magnusson, Alexander Viktorin, Divya Mehta, Niamh Mullins, Mark J. Adams, Gerome Breen, Andrew M. McIntosh, Cathryn M. Lewis, David M. Hougaard, Merete Nordentoft, Ole Mors, Preben B. Mortensen, Thomas Werge, Thomas D. Als, Anders D. Børglum, Tracey L. Petryshen, Jordan W. Smoller, Jill M. Goldstein, Stephan Ripke, Benjamin M. Neale, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Sandra Meier, Carin J. Meijer, Bela Melegh, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Vihra Milanova, Younes Mokrab, Derek W. Morris, Kieran C. Murphy, Inez Myin-Germeys, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Ulrich Schall, Christian R. Schubert, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Peter M. Visscher, Douglas H.R. Blackwood, Ariel Darvasi, Enrico Domenici, Michael Gill, Hugh Gurling, Christina M. Hultman, Assen V. Jablensky, Kenneth S. Kendler, Jo Knight, Qingqin S. Li, Jianjun Liu, Steven A. McCarroll, Jennifer L. Moran, Michael J. Owen, Carlos N. Pato, Danielle Posthuma, Pamela Sklar, Jens R. Wendland, Mark J. Daly, Michael C. O’Donovan, Peter Donnelly, Ines Barroso, Jenefer M. Blackwell, Matthew A. Brown, Juan P. Casas, Panos Deloukas, Audrey Duncanson, Janusz Jankowski, Hugh S. Markus, Christopher G. Mathew, Colin N.A. Palmer, Robert Plomin, Anna Rautanen, Stephen J. Sawcer, Richard C. Trembath, Ananth C. Viswanathan, Nicholas W. Wood, Gavin Band, Céline Bellenguez, Colin Freeman, Eleni Giannoulatou, Garrett Hellenthal, Richard Pearson, Matti Pirinen, Amy Strange, Zhan Su, Damjan Vukcevic, Cordelia Langford, Hannah Blackburn, Suzannah J. Bumpstead, Serge Dronov, Sarah Edkins, Matthew Gillman, Emma Gray, Rhian Gwilliam, Naomi Hammond, Sarah E. Hunt, Alagurevathi Jayakumar, Jennifer Liddle, Owen T. McCann, Simon C. Potter, Radhi Ravindrarajah, Michelle Ricketts, Avazeh Tashakkori-Ghanbaria, Matthew Waller, Paul Weston, Pamela Whittaker, Sara Widaa, Mark I. McCarthy, Maria J. Arranz, Steven Bakker, Stephan Bender, Benedicto Crespo-Facorro, Jeremy Hall, Conrad Iyegbe, Stephen Lawrie, Kuang Lin, Don H. Linszen, Ignacio Mata, Muriel Walshe, Matthias Weisbrod, Durk Wiersma, Vassily Trubetskoy, Yunpeng Wang, Jonathan R.I. Coleman, Héléna A. Gaspar, Christiaan A. de Leeuw, Jennifer M. Whitehead Pavlides, Maciej Trzaskowski, Enda M. Byrne, Liam Abbott, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Carsten Bøcker Pedersen, Erlend Bøen, Marco P. Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, Miquel Casas, Felecia Cerrato, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W. Craig, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Simone de Jong, Jurgen Del-Favero, J. Raymond DePaulo, Amanda L. Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Chun Chieh Fan, Sascha B. Fischer, Matthew Flickinger, Tatiana M. Foroud, Liz Forty, Christine Fraser, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D. Gordon, Katherine Gordon-Smith, Elaine K. Green, Melissa J. Green, Tiffany A. Greenwood, Weihua Guan, Martin Hautzinger, Urs Heilbronner, Maria Hipolito, Dominic Holland, Laura Huckins, Jessica S. Johnson, Radhika Kandaswamy, Robert Karlsson, Sarah Kittel-Schneider, Anna C. Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B. Lawson, Markus Leber, Phil H. Lee, Shawn E. Levy, Jun Z. Li, Chunyu Liu, Anna Maaser, Donald J. MacIntyre, Pamela B. Mahon, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Fan Meng, Grant W. Montgomery, Thomas W. Mühleisen, Hoang Nguyen, Caroline M. Nievergelt, Annelie Nordin Adolfsson, Evaristus A. Nwulia, Claire O'Donovan, Loes M. Olde Loohuis, Anil P.S. Ori, Lilijana Oruc, Urban Ösby, Amy Perry, Andrea Pfennig, Eline J. Regeer, Céline S. Reinbold, John P. Rice, Fabio Rivas, Margarita Rivera, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Nicholas J. Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Christine Søholm Hansen, Anne T. Spijker, Michael Steffens, John S. Strauss, Szabolcs Szelinger, Robert C. Thompson, Thorgeir E. Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J. Watson, Thomas W. Weickert, Simon Xi, Wei Xu, Allan H. Young, Peter Zandi, Peng Zhang, Sebastian Zöllner, Abdel Abdellaoui, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Fernando S. Goes, Lynsey S. Hall, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Christel M. Middeldorp, Evelin Mihailov, Francis M. Mondimore, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O'Reilly, Hogni Oskarsson, Jodie N. Painter, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Katherine E. Tansey, Henning Teismann, Wesley Thompson, Pippa A. Thomson, Matthew Traylor, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Shantel Marie Weinsheimer, Jürgen Wellmann, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Klaus Berger, Udo Dannlowski, Katharina Domschke, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Pamela AF. Madden, Patrik K. Magnusson, Preben Bo Mortensen, Michael C. O'Donovan, Sara A. Paciga, Nancy L. Pedersen, David J. Porteous, Catherine Schaefer, Henry Völzke, Marco Bortolato, Janita Bralten, Cynthia M. Bulik, Christie L. Burton, Caitlin E. Carey, Lea K. Davis, Laramie E. Duncan, Howard J. Edenberg, Lauren Erdman, Stephen V. Faraone, Slavina B. Goleva, Wei Guo, Christopher Hübel, Laura M. Huckins, Ekaterina A. Khramtsova, Joanna Martin, Carol A. Mathews, Elise Robinson, Eli Stahl, Barbara E. Stranger, Michela Traglia, Raymond K. Walters, Lauren A. Weiss, Stacey J. Winham, Yin Yao, Kristjar Skajaa, Markus Nöthen, Michael Owen, Robert H. Yolken, Niels Plath, Jonathan Mill, Daniel Geschwind, Psychiatry 1, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Functional Genomics, Biological Psychology, APH - Mental Health, APH - Methodology, Sociology and Social Gerontology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Blokland, Gabriella AM, Grove, Jakob, Chen, Chia Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, Lee, Sang Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, iPSYCH, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, ANS - Complex Trait Genetics, and ANS - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: 0301 basic medicine, Male, Bipolar Disorder, Schizophrenia/genetics, LD SCORE REGRESSION, Genome-wide association study, 0302 clinical medicine, Receptors, SCHIZOPHRENIA, Psychotic Disorders/genetics, KYNURENINE PATHWAY METABOLISM, Genetics, RISK, Sex Characteristics, Vascular Endothelial Growth Factor, Bipolar Disorder/genetics, Major/genetics, Single Nucleotide, AFFECTIVE STIMULI IMPACT, Schizophrenia, Sulfurtransferases, Major depressive disorder, Female, Depressive Disorder, Major/genetics, Bipolar disorder, Locus (genetics), Genomics, Biology, Polymorphism, Single Nucleotide, Article, DYSPHORIC MOOD, 03 medical and health sciences, Sex differences, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Polymorphism, GENOME-WIDE ASSOCIATION, Genotype-by-sex interaction, Biological Psychiatry, Depressive Disorder, Major, Depressive Disorder, GENDER-DIFFERENCES, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], PARAVENTRICULAR NUCLEUS, 3112 Neurosciences, Endothelial Cells, MAJOR DEPRESSION, medicine.disease, Genetic architecture, 030104 developmental biology, Mood, Receptors, Vascular Endothelial Growth Factor, Psychotic Disorders, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: 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.
Published: 2022
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19. Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits

Author: Joanna Martin, Ekaterina A. Khramtsova, Slavina B. Goleva, Gabriëlla A.M. Blokland, Michela Traglia, Raymond K. Walters, Christopher Hübel, Jonathan R.I. Coleman, Gerome Breen, Anders D. Børglum, Ditte Demontis, Jakob Grove, Thomas Werge, Janita Bralten, Cynthia M. Bulik, Phil H. Lee, Carol A. Mathews, Roseann E. Peterson, Stacey J. Winham, Naomi Wray, Howard J. Edenberg, Wei Guo, Yin Yao, Benjamin M. Neale, Stephen V. Faraone, Tracey L. Petryshen, Lauren A. Weiss, Laramie E. Duncan, Jill M. Goldstein, Jordan W. Smoller, Barbara E. Stranger, Lea K. Davis, Martin Alda, Marco Bortolato, Christie L. Burton, Enda Byrne, Caitlin E. Carey, Lauren Erdman, Laura M. Huckins, Manuel Mattheisen, Elise Robinson, Eli Stahl, Psychiatrie & Neuropsychologie, and RS: MHeNs - R2 - Mental Health
Subjects: DISORDER, 0301 basic medicine, Male, Multifactorial Inheritance, Sex Differentiation, Evolution of sexual reproduction, Genome-wide association study, Medical and Health Sciences, Correlation, 0302 clinical medicine, GWAS, Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, RISK, Psychiatry, Sex Characteristics, 0303 health sciences, Single Nucleotide, Biological Sciences, OVERLAP, Archival Report, Phenotype, Mental Health, DISEASES, Trait, Female, Biotechnology, Genetic correlation, Biology, BIOBANK, Polymorphism, Single Nucleotide, MECHANISMS, Heritability, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, Sex differences, Genetics, Humans, SNP, GENOME-WIDE ASSOCIATION, Polymorphism, Gene, Biological Psychiatry, Behavioral, 030304 developmental biology, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Prevention, Human Genome, Psychology and Cognitive Sciences, Genetic architecture, 030104 developmental biology, Neurodevelopmental Disorders, Evolutionary biology, JACKKNIFE, Psychiatric, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: BackgroundThe origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits.MethodsUsing genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h2) and genetic correlation (rgResultsWith current sample sizes (and power), we found no significant, consistent sex differences in SNP-based h2. Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior).ConclusionsSex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large sample sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.
Published: 2021
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20. msBayes: Pipeline for testing comparative phylogeographic histories using hierarchical approximate Bayesian computation.

Author: Michael J. Hickerson, Eli Stahl, and Naoki Takebayashi
Published: 2007
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21. Global landscape and genetic regulation of RNA editing in cortical samples from individuals with schizophrenia

Author: Michael S, Breen, Amanda, Dobbyn, Qin, Li, Panos, Roussos, Gabriel E, Hoffman, Eli, Stahl, Andrew, Chess, Pamela, Sklar, Jin Billy, Li, Bernie, Devlin, Joseph D, Buxbaum, and Elizabeth, Zharovsky
Subjects: 0301 basic medicine, Schizophrenia (object-oriented programming), Quantitative Trait Loci, molecular mechanisms, RNA editing quantitative trait loci, Quantitative trait locus, Biology, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Eukaryotic translation, mental disorders, medicine, Humans, Gene, Anterior cingulate cortex, Cerebral Cortex, Genetics, neurodevelopment, General Neuroscience, disease risk, Dorsolateral prefrontal cortex, 030104 developmental biology, medicine.anatomical_structure, RNA editing, Schizophrenia, RNA Editing, Postsynaptic density, Neuroscience, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: RNA editing critically regulates neurodevelopment and normal neuronal function. The global landscape of RNA editing was surveyed across 364 schizophrenia cases and 383 control postmortem brain samples from the CommonMind Consortium, comprising two regions: dorsolateral prefrontal cortex and anterior cingulate cortex. In schizophrenia, RNA editing sites in genes encoding AMPA-type glutamate receptors and postsynaptic density proteins were less edited, whereas those encoding translation initiation machinery were edited more. These sites replicate between brain regions, map to 3′-untranslated regions and intronic regions, share common sequence motifs and overlap with binding sites for RNA-binding proteins crucial for neurodevelopment. These findings cross-validate in hundreds of non-overlapping dorsolateral prefrontal cortex samples. Furthermore, ~30% of RNA editing sites associate with cis-regulatory variants (editing quantitative trait loci or edQTLs). Fine-mapping edQTLs with schizophrenia risk loci revealed co-localization of eleven edQTLs with six loci. The findings demonstrate widespread altered RNA editing in schizophrenia and its genetic regulation, and suggest a causal and mechanistic role of RNA editing in schizophrenia neuropathology. Breen et al. map RNA editing profiles in cortical samples from individuals with schizophrenia and controls, and find links between altered RNA editing in glutamatergic and postsynaptic density genes and schizophrenia genetic risk architecture.
Published: 2019
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22. GENETICALLY PREDICTED GENE EXPRESSION IN THE BRAIN AND PERIPHERAL TISSUES ASSOCIATES WITH PTSD

Author: Laura Huckins, Kiran Girdhar, Amanda Dobbyn, Tanja Jovanovic, Caroline Nievergelt, Gabriel Hoffman, Adam Maihofer, Murray Stein, Pamela Sklar, Kerry Ressler, Joseph Buxbaum, Eli Stahl, Nikolaos Daskalakis, null The CommonMind Consortium (CMC), and null PGC PTSD Working Group
Subjects: Pharmacology, biology, Genetic heterogeneity, Genome-wide association study, Immune dysregulation, Bioinformatics, medicine.disease_cause, Psychiatry and Mental health, Histone, Neurology, Genotype, Expression quantitative trait loci, biology.protein, medicine, H3K4me3, Pharmacology (medical), Neurology (clinical), Gene, Biological Psychiatry
Abstract: Background Post-Traumatic Stress Disorder (PTSD) is a debilitating psychiatric disorder occurring in individuals exposed to trauma. To date, little is known about the genetic aetiology of the disorder, although the latest GWAS (carried out by the PGC-PTSD working group) demonstrates that genetic heritability is in line with other psychiatric disorders. PTSD development involves multi-systemic dysregulation in multiple brain regions and diverse peripheral tissues. Some peripheral systems are particularly interesting since epidemiologic evidence suggests that PTSD patients commonly have cardiovascular, metabolic and immune dysregulation. Methods Transcriptomic Imputation approaches use machine-learning methods to impute gene expression from large genotype data using curated eQTL reference panels. These offer an exciting opportunity to compare gene associations across neurological and peripheral tissues. Here, we apply CommonMind Consortium (CMC) and Genotype-Tissue Expression (GTEx) derived gene expression prediction models to the PGC-PTSD data (9,245 cases/ 24,285 controls). Models included 12 brain regions, five cardiovascular tissues, 2 endocrine tissues, the tibial nerve, adipose tissue and whole blood. Results We identified 24 significant gene-tissue associations, of which 5 were in peripheral tissues (adrenal gland, heart atrial appendage, tibial artery, tibial nerve). We stratified analyses according to trauma type (civilian vs. combat trauma), sex, and self-defined ancestry. Our three strongest associations were identified in military cohorts only, which supports the hypothesis that there is substantial genetic heterogeneity between civilian and combat PTSD risk. We used the PsychENCODE neuronal and non-neuronal reference map for two histone marks associated with transcription and open chromatin (3-trimethyl-lysine 4 (H3K4me3) and H3-acetyl-lysine 27 (H3K27ac) to understand patterns of histone modification among our PTSD-associated genes. Preliminary analyses indicate a significant correlation between PTSD-association statistics and the presence of both histone marks (correlation with neuronal H3K4me3, Pearson R=0.87, p=3.99×10-5). We intend to expand this analysis to include a wider range of histone modification marks. Discussion We will further expand these analyses to identify tissue specific gene clusters and enriched pathways across tissues or in specific tissues. Finally, we will use neuroimaging data and physiological cardiovascular data to functionally validate our results.
Published: 2019
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23. Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Author: Bjarni J. Vilhjálmsson, Jian Yang, Hilary K. Finucane, Alexander Gusev, Sara Lindström, Stephan Ripke, Giulio Genovese, Po-Ru Loh, Gaurav Bhatia, Ron Do, Tristan Hayeck, Hong-Hee Won, Sekar Kathiresan, Michele Pato, Carlos Pato, Rulla Tamimi, Eli Stahl, Noah Zaitlen, Bogdan Pasaniuc, Gillian Belbin, Eimear E. Kenny, Mikkel H. Schierup, Philip De Jager, Nikolaos A. Patsopoulos, Steve McCarroll, Mark Daly, Shaun Purcell, Daniel Chasman, Benjamin Neale, Michael Goddard, Peter M. Visscher, Peter Kraft, Nick Patterson, Alkes L. Price, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Lynn E. DeLisi, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Lyudmila Georgieva, Elliot S. Gershon, Ina Giegling, Paola Giusti-Rodrguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Jakob Grove, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julia, Rene S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, Brian J. Kelly, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kahler, Claudine Laurent, Jimmy Lee Chee Keong, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lnnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Preben B. Mortensen, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Mller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietilinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Sderman, Srinivas Thirumalai, Draga Toncheva, Paul A. Tooney, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Jing Qin Wu, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tonu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jonsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Bryan J. Mowry, Markus M. Nthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St. Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, David J. Hunter, Muriel Adank, Habibul Ahsan, Kristiina Aittomäki, Laura Baglietto, Sonja Berndt, Carl Blomquist, Federico Canzian, Jenny Chang-Claude, Stephen J. Chanock, Laura Crisponi, Kamila Czene, Norbert Dahmen, Isabel dos Santos Silva, Douglas Easton, A. Heather Eliassen, Jonine Figueroa, Olivia Fletcher, Montserrat Garcia-Closas, Mia M. Gaudet, Lorna Gibson, Christopher A. Haiman, Per Hall, Aditi Hazra, Rebecca Hein, Brian E. Henderson, Albert Hofman, John L. Hopper, Astrid Irwanto, Mattias Johansson, Rudolf Kaaks, Muhammad G. Kibriya, Peter Lichtner, Eiliv Lund, Enes Makalic, Alfons Meindl, Hanne Meijers-Heijboer, Bertram Müller-Myhsok, Taru A. Muranen, Heli Nevanlinna, Petra H. Peeters, Julian Peto, Ross L. Prentice, Nazneen Rahman, María José Sánchez, Daniel F. Schmidt, Rita K. Schmutzler, Melissa C. Southey, Ruth Travis, Clare Turnbull, Andre G. Uitterlinden, Rob B. van der Luijt, Quinten Waisfisz, Zhaoming Wang, Alice S. Whittemore, Rose Yang, Wei Zheng, ANS - Amsterdam Neuroscience, Adult Psychiatry, Other departments, CCA -Cancer Center Amsterdam, ARD - Amsterdam Reproduction and Development, Human Genetics, Grove, Jakob, Complex Trait Genetics, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Vilhjalmsson, Bjarni J, Yang, Jian, Finucane, Hilary K, Gusev, Alexander, Lee, SH, Price, Alkes L, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Study, Psychosis Endophenotype International Consortium, Wellcome Trust Case Control Consortium, Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON), Human genetics, NCA - Brain mechanisms in health and disease, CCA - Oncogenesis, CCA - Quality of life, CCA - Cancer biology and immunology, Psychiatry, Department of Technology and Operations Management, Department of Organisation and Personnel Management, Child and Adolescent Psychiatry / Psychology, Clinical Genetics, Cell biology, and Internal Medicine
Subjects: Multifactorial Inheritance, Linkage disequilibrium, Complex disease, heritability, Bioinformatics, Medical and Health Sciences, Linkage Disequilibrium, 0302 clinical medicine, Theoretical, External reference, Models, Statistics, GWAS, Genetics(clinical), Genetics (clinical), Mathematics, Genetics & Heredity, Schizophrenia Working Group of the Psychiatric Genomics Consortium, 0303 health sciences, Single Nucleotide, Biological Sciences, Serious Mental Illness, Prognosis, Thresholding, Regression, Mental Health, Phenotype, polygenic risk scores, Mixed model, Multiple Sclerosis, Genotype, Quantitative Trait Loci, polygenic risk score, schizophrenia, GWAS, Discovery, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Genetics, Humans, p-value, Pruning (decision trees), Polymorphism, Genome-Wide Association Study, Schizophrenia, Models, Theoretical, 030304 developmental biology, genome-wide association study, and Risk of Inherited Variants in Breast Cancer (DRIVE) study, Brain Disorders, Data set, schizophrenia, Sample size determination, polygenic risk score, Polygenic risk score, 030217 neurology & neurosurgery, linkage disequilibrium
Abstract: Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R-2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase. Refereed/Peer-reviewed
Published: 2015
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24. TRANSCRIPTOMIC IMPUTATION ANALYSIS IN ANOREXIA NERVOSA IDENTIFIES BOTH METABOLIC AND PSYCHIATRIC AETIOLOGIES

Author: Laura Huckins, Amanda Dobbyn, Laura Thornton, null Eating Disorders Working Group of the PGC, Bernie Devlin, Solveig Sieberts, Nancy Cox, Hae Kyung Im, Gerome Breen, Pamela Sklar, Cynthia Bulik, and Eli Stahl
Subjects: Pharmacology, medicine.medical_specialty, Locus (genetics), Genome-wide association study, Biology, Phenotype, Psychiatry and Mental health, Neurology, Expression quantitative trait loci, Genotype, medicine, Etiology, Pharmacology (medical), Neurology (clinical), Psychiatry, Biological Psychiatry, Chromosome 12, Imputation (genetics)
Abstract: Background Anorexia Nervosa (AN) is a complex and serious eating disorder, occurring in ~1% of individuals. Despite having the highest mortality rate of any psychiatric disorder, little is known about the aetiology of the AN, and few effective treatments exist. Global efforts to collect large samples from individuals with AN have been highly successful, and a recent study consequently identified the first genome-wide significant locus involved in AN, with significant genetic correlations with multiple metabolic indices. This result, coupled with other recent studies and epidemiological evidence, implies that previous characterizations of AN as a purely psychiatric disorder should be revisited. Rather, it seems that both psychiatric and metabolic systems may be involved. Methods In order to elucidate more of the system-specific aetiology of AN, we applied transcriptomic imputation methods to 3,495 cases and 10,982 controls, collected by the PGC-ED working group. Transcriptomic Imputation (TI) methods approaches use machine-learning methods to impute tissue-specific gene expression from large genotype data using curated eQTL reference panels. These offer an exciting opportunity to compare gene associations across neurological and metabolic tissues. Here, we applied CommonMind Consortium (CMC) and GTEx-derived gene expression prediction models for 12 brain tissues and 12 tissues with potential metabolic involvement (Adipose, Adrenal Gland, 2 Colon, 3 Esophagus, Liver, Pancreas, Small Intestine, Spleen, Stomach). In total, these analyses include 234,968 gene-tissue association tests. Results We identified 35 significant gene-tissue associations within the large chromosome 12 region described in the recent PGC-ED GWAS. We applied a forward-stepwise conditional analysis analogous to GCTA-CoJo in order to identify independent associations within this region and across tissues, and identified two independently associated genes, both in metabolic tissues; RPS26, in the Spleen (p=2.59e-08), and C12orf49, in the Thyroid (p=4.01e-06). We also identified two further regions with genome-wide significant gene-tissue associations, both in brain tissues; REEP5, in the DLPFC (p=8.52e-07), and CUL3, in the Caudate Basal Ganglia (p=1.8e-06). Discussion Our results support a model of AN risk influenced by both metabolic and psychiatric factors. We plan to follow these analyses with investigations of the overlap between AN and other psychiatric and metabolic phenotypes, as well as analysis of potentially implicated molecular pathways.
Published: 2019
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25. GENOME-WIDE ASSOCIATION STUDY IDENTIFIES TWENTY NEW LOCI ASSOCIATED WITH BIPOLAR DISORDER

Author: Eli Stahl and null Bipolar Working Group of the Psychiatric Genomics Consortium
Subjects: Pharmacology, Genetics, Single-nucleotide polymorphism, Genomics, Genome-wide association study, Biology, medicine.disease, Genetic correlation, 030227 psychiatry, 03 medical and health sciences, Psychiatry and Mental health, 0302 clinical medicine, Mood, Neurology, Schizophrenia, mental disorders, medicine, Pharmacology (medical), Neurology (clinical), ANK3, Bipolar disorder, 030217 neurology & neurosurgery, Biological Psychiatry
Abstract: Background Bipolar Disorder (BD) is a common, complex and severe mood disorder with high heritability. Genetic analyses of bipolar disorder continue to benefit from large international cohort collections amassed by members of the Psychiatric Genomics Consortium. Here we describe insights into disease risk from new and existing BD risk loci and from polygenic analyses of BD and related diseases and traits. Methods We performed GWAS meta-analysis of 32 cohorts from 14 countries in Europe and North America, totaling 20,352 cases and 31,358 controls of European descent, including 6,328 case and 7,963 control samples not previously reported. We tested suggestive SNPs (P Results Bipolar disorder GWAS identified 31 genome-wide significant (P BD2, P BD1, P Discussion The PGC2 Bipolar Disorder GWAS identified twenty novel risk loci. Single gene loci include the synaptic genes ANK3, GRIN2A, SHANK2 and RIMS1. Polygenic analyses reaffirm the striking polygenicity of bipolar disorder and close relationships with schizophrenia and other psychiatric disorders, and evince an affective-to-mood disorder gradient of genetic overlap from schizophrenia, to BDI, to BDII, to major depression. Bipolar disorder's positive genetic correlation with cognitive/education phenotypes stands in contrast to schizophrenia and major depression, suggesting an inroad to further dissection of genetic components specific to these major psychiatric disorders. Genetic overlaps of BD with lipid-, osteoarthritis- and immune-related traits, provide additional intriguing clinical and physiological implications.
Published: 2019
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26. Abstract 56: Fine-Mapping of Metabochip Lipid Regions in Global Populations Identifies Signals Unique to Hispanic Descent Populations and Refines Previously Identified Lipid Loci

Author: Niha Zubair, Mariaelisa Graff, Danyu Lin, Ani Manichaikul, Ida Chen, Eli Stahl, Kevin Lu, Iona Cheng, Christopher Haiman, Dana Crawford, Logan Dumitrescu, Petra Buzkova, Steven Buyske, Myriam Fornage, Kari North, Charles Kooperberg, and Cara Carty
Subjects: Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract: INTRODUCTION: Genome wide association studies (GWAS) have identified over 150 loci associated with lipids traits. The majority of these GWAS were performed in European Americans (EA); no large-scale studies exist for Hispanic descent populations. Additionally, in many cases, the genetic architecture of these trait-influencing loci remains largely unknown. To address these gaps in knowledge, we performed one of the most ethnically diverse fine-mapping genetic studies on HDL-C, LDL-C, and triglycerides (TG) to-date. HYPOTHESIS: Here we aimed to identify variants with the strongest association at each locus, detect population-specific signals, and refine previously identified EA GWAS loci. METHODS: We used Metabochip data from African American (AA, ~21,000), Hispanic American (HA, ~20,000), Asian (AS, ~2,000), and Native American (NA, ~550) participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study. We applied multiple linear regression models and assumed an additive mode of inheritance to test for association between genotypes and HDL-C, LDL-C, or log-transformed TG levels; lipid levels were corrected for lipid-lowering medication use. Model covariates included age, sex, and principal components of ancestry. We first conducted a meta-analysis within each ethnic group separately and then performed a combined trans-ethnic fixed effects meta-analysis. Significance was defined as p < 1 x 10 -6 ; equivalent to 0.05/ the mean number of variants at each Metabochip lipid locus. RESULTS: For HDL-C, 19 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 5 of these loci, APOB, LIPC, STARD3, LIPG, and APOC1, have not been reported in EA. We identified a signal unique to HA at APOA5. In addition, we refined the set of candidate functional variants at PPP1R3B, LPL, and PLTP. For LDL-C, 16 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 5 of these loci, PCSK9, APOB, APOA5, CLIP2, and APOC1, have not been reported in EA. We identified a signal unique to HA at SLC22A1. In addition, we refined the set of candidate functional variants at TIMD4 and LDLR. For TG, 15 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 3 of these loci, APOB, APOA5, and LIPC, have not been reported in EA. In addition, we refined the set of candidate functional variants at ANGPTL3, MLXIPL, PPP1R3B, and LPL. CONCLUSIONS: By taking advantage of the genetic architecture of ethnically diverse populations, we identified novel lipid-influencing variants in HA and refined the set of candidate functional variants at GWAS lipid loci. Anticipated conditional analyses will provide further insight into secondary and ethnic-specific signals. Our results can guide the creation of more informed risk models, which can then be used for targeted prevention efforts, especially for underrepresented populations.
Published: 2015
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27. Partitioning heritability by functional category using GWAS summary statistics

Author: Hilary Kiyo Finucane, Brendan Bulik-Sullivan, Alexander Gusev, Gosia Trynka, Yakir Reshef, Po-Ru Loh, Verneri Anttilla, Han Xu, Chongzhi Zang, Kyle Farh, Stephan Ripke, Felix Day, ReproGen Consortium, Schizophrenia Working Group of the Psychiatric Genetics Consortium, RACI Consortium, Shaun Purcell, Eli Stahl, Sara Lindstrom, John R.B. Perry, Yukinori Okada, Soumya Raychaudhuri, Mark Daly, Nick Patterson, Benjamin M. Neale, and Alkes L. Price
Subjects: Genetics, 0303 health sciences, Genome-wide association study, Computational biology, Heritability, Biology, Summary statistics, Genome, Genetic correlation, Smoking behavior, 03 medical and health sciences, 0302 clinical medicine, Missing heritability problem, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.
Published: 2015
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28. Regulatory variants explain much more heritability than coding variants across 11 common diseases

Author: Alexander Gusev, S Hong Lee, Benjamin M Neale, Gosia Trynka, Bjarni J Vilhjalmsson, Hilary Finucane, Han Xu, Chongzhi Zang, Stephan Ripke, Eli Stahl, n/a Schizophrenia Working Group of the PGC, n/a SWE-SCZ Consortium, Anna K Kahler, Christina M Hultman, Shaun M Purcell, Steven A McCarroll, Mark Daly, Bogdan Pasaniuc, Patrick F Sullivan, Naomi R Wray, Soumya Raychaudhuri, and Alkes L Price
Subjects: Genetics, 0303 health sciences, Linkage disequilibrium, Single-nucleotide polymorphism, Genome-wide association study, Heritability, Biology, Genome, 03 medical and health sciences, 0302 clinical medicine, Genotype, Exome, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: Common variants implicated by genome-wide association studies (GWAS) of complex diseases are known to be enriched for coding and regulatory variants. We applied methods to partition the heritability explained by genotyped SNPs (h2g) across functional categories (while accounting for shared variance due to linkage disequilibrium) to genotype and imputed data for 11 common diseases. DNaseI Hypersensitivity Sites (DHS) from 218 cell-types, spanning 16% of the genome, explained an average of 79% of h2g (5.1× enrichment; P < 10−20); further enrichment was observed at enhancer and cell-type specific DHS elements. The enrichments were much smaller in analyses that did not use imputed data or were restricted to GWAS- associated SNPs. In contrast, coding variants, spanning 1% of the genome, explained only 8% of h2g (13.8× enrichment; P = 5 × 10−4). We replicated these findings but found no significant contribution from rare coding variants in an independent schizophrenia cohort genotyped on GWAS and exome chips.
Published: 2014
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29. Exploring genetic and expression differences between physiologically extreme ecotypes: comparative genomic hybridization and gene expression studies of Kas-1 and Tsu-1 accessions of Arabidopsis thaliana

Author: Thomas E, Juenger, Saunak, Sen, Elizabeth, Bray, Eli, Stahl, Tierney, Wayne, John, McKay, and James H, Richards
Subjects: Comparative Genomic Hybridization, Soil, Phenotype, DNA, Plant, Gene Expression Regulation, Plant, Stress, Physiological, Gene Expression Profiling, Arabidopsis, Water, Adaptation, Physiological, Polymorphism, Single Nucleotide, Oligonucleotide Array Sequence Analysis
Abstract: Recent studies have documented remarkable genetic variation among Arabidopsis thaliana accessions collected from diverse habitats. Of particular interest are accessions with putatively locally adapted phenotypes - that is, accessions with attributes that are likely adaptive at their sites of origin. These genotypes may provide insight into the genetic basis of adaptive evolution as well as allow the discovery of genes of ecological importance. We studied the physiology, genome content and gene expression of two physiologically extreme accessions (Tsu-1 from Tsushima, Japan and Kas-1 from Kashmir, India). Our study was conducted under two levels of soil moisture and accompanied by physiological measurements to characterize early responses to soil drying. Genomic hybridizations identified 42,503 single feature polymorphisms (SFP) between accessions, providing an initial screen for genetic differences. Transcript profiling identified a large number (5996) of genes exhibiting constitutive differences in expression including genes involved in many biological pathways. Mild soil drying resulted in only subtle physiological responses but resulted in gene expression changes in hundreds of transcripts, including 352 genes exhibiting differential responses between accessions. Our results highlight the value of genomic studies of natural accessions as well as identify a number of candidate genes underlying physiological differences between Tsu-1 and Kas-1.
Published: 2010

30. Contribution of common and rare damaging variants in familial forms of bipolar disorder and phenotypic outcome

Author: Courtois, Elisa, Schmid, Mark, Wajsbrot, Orly, Barau, Caroline, Le Corvoisier, Philippe, Aouizerate, Bruno, Bellivier, Frank, Belzeaux, Raoul, Dubertret, Caroline, Kahn, Jean-Pierre, Leboyer, Marion, Olie, Emilie, Passerieux, Christine, Polosan, Mircea, Etain, Bruno, Jamain, Stéphane, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Université Paris-Est Créteil Val-de-Marne - Faculté de médecine (UPEC Médecine), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Fondation FondaMental [Créteil], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Hôpital Henri Mondor, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Centre d'Investigation Clinique Henri Mondor (CIC Henri Mondor), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Centre hospitalier Charles Perrens [Bordeaux], Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Paris Diderot, Sorbonne Paris Cité, Paris, France, Université Paris Diderot - Paris 7 (UPD7), Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Institut de psychiatrie et neurosciences (U894 / UMS 1266), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Psychiatrie et Neurologie personnalisées [AP-HP Hôpital Henri-Mondor] (DHU PePsy), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Laboratoire de recherches cliniques et en santé publique sur les handicaps psychique, cognitif et moteur (HANDIReSP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Hôpital Lariboisière-Fernand-Widal [APHP], Réseau de Recherche en Santé Buccodentaire et Osseuse, RSBO ANR-10-COHO-10-01 Institut National de la Santé et de la Recherche Médicale, Inserm Agence Nationale de la Recherche, ANR, This work was supported by the Investissements d’Avenir program managed by the Agence Nationale pour la Recherche (ANR) under references ANR-11-IDEX-0004-02 (Labex BioPsy) and ANR-10-COHO-10-01 (Cohorte PSY-COH). This work also received financial support from the ANR program on mental health and addiction under reference ANR-13-SAMENTA-0003-01 (ANTIDOCT), from the International Foundation (IF), the Institut National pour la Santé et la Recherche Médicale (Inserm) and the Réseau Thématique de Recherche et de Soins en Santé Mentale (Fondation FondaMental®, Prix Henry Rousset). The Jamain’s team is affiliated to the Paris School of Neuroscience (ENP) and the Bio-Psy Laboratory of Excellence. We are very grateful to patients with bipolar disorder, their family, and control subjects for their participation. The authors thank Dr. Eli Stahl and the Bipolar Disorder Group of the PGC for having provided PGC BD summary statistics excluding the French cohort. In addition, we thank the Clinical Investigation Centre and the Biological Resources Platform of Mondor Hospital for technical assistance FondaMental Advanced Centers of Expertise in Bipolar Disorders (FACE-BD)., ANR-11-IDEX-0004,SUPER,Sorbonne Universités à Paris pour l'Enseignement et la Recherche(2011), HAL UVSQ, Équipe, Sorbonne Universités à Paris pour l'Enseignement et la Recherche - - SUPER2011 - ANR-11-IDEX-0004 - IDEX - VALID, Hôpital Charles Perrens, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Centre de Psychiatrie et Neurosciences (U894)
Subjects: [SDV] Life Sciences [q-bio], Multifactorial Inheritance, Bipolar Disorder, Comparative genomics, [SDV]Life Sciences [q-bio], Schizophrenia, Humans, Genetic Predisposition to Disease, Clinical genetics, Polymorphism, Single Nucleotide, Article, Genome-Wide Association Study
Abstract: International audience; Genome-wide association studies on bipolar disorders (BD) have revealed an additive polygenic contribution of common single-nucleotide polymorphisms (SNPs). However, these SNPs explain only 25% of the overall genetic variance and suggest a role of rare variants in BD vulnerability. Here, we combined high-throughput genotyping data and whole-exome sequencing in cohorts of individuals with BD as well as in multiplex families with a high density of affected individuals in order to determine the contribution of both common and rare variants to BD genetic vulnerability. Using polygenic risk scores (PRS), we showed a strong contribution of common polymorphisms previously associated with BD and schizophrenia (SZ) and noticed that those specifically associated with SZ contributed more in familial forms of BD than in non-familial ones. The analysis of rare damaging variants shared by affected individuals in multiplex families with BD revealed a single interaction network enriched in neuronal and developmental biological pathways, as well as in the regulation of gene expression. We identified four genes with a higher mutation rate in individuals with BD than in the general population and showed that mutations in two of them were associated with specific clinical manifestations. In addition, we showed a significant negative correlation between PRS and the number of rare damaging variants specifically in unaffected individuals of multiplex families. Altogether, our results suggest that common and rare genetic variants both contribute to the familial aggregation of BD and this genetic architecture may explain the heterogeneity of clinical manifestations in multiplex families.
Published: 2020
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30 results on '"Eli Stahl"'

1. Transcriptional profiling in microglia across physiological and pathological states identifies a transcriptional module associated with neurodegeneration

2. PMS2CL interference leading to erroneous identification of a pathogenic PMS2 variant in Black patients

3. ANGPTL7, a therapeutic target for increased intraocular pressure and glaucoma

4. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

5. A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.

6. No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study.

7. Disproportionate Contributions of Select Genomic Compartments and Cell Types to Genetic Risk for Coronary Artery Disease.

8. Allele-specific methylation occurs at genetic variants associated with complex disease.

9. Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway.

10. Erratum: Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

11. Impact of schizophrenia GWAS loci converge onto distinct pathways in cortical interneurons vs glutamatergic neurons during development

12. Non-additive effects of schizophrenia risk genes reflect convergent downstream function

13. The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

14. Inference of Causal Relationships Between Genetic Risk Factors for Cardiometabolic Phenotypes and Female‐Specific Health Conditions

15. Polygenic risk of Social-isolation and its influence on social behavior, psychosis, depression and autism spectrum disorder

16. 37. CONVERGENT IMPACT OF SCHIZOPHRENIA RISK GENES

17. Convergent impact of schizophrenia risk genes

18. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

19. Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits

20. msBayes: Pipeline for testing comparative phylogeographic histories using hierarchical approximate Bayesian computation.

21. Global landscape and genetic regulation of RNA editing in cortical samples from individuals with schizophrenia

22. GENETICALLY PREDICTED GENE EXPRESSION IN THE BRAIN AND PERIPHERAL TISSUES ASSOCIATES WITH PTSD

23. Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

24. TRANSCRIPTOMIC IMPUTATION ANALYSIS IN ANOREXIA NERVOSA IDENTIFIES BOTH METABOLIC AND PSYCHIATRIC AETIOLOGIES

25. GENOME-WIDE ASSOCIATION STUDY IDENTIFIES TWENTY NEW LOCI ASSOCIATED WITH BIPOLAR DISORDER

26. Abstract 56: Fine-Mapping of Metabochip Lipid Regions in Global Populations Identifies Signals Unique to Hispanic Descent Populations and Refines Previously Identified Lipid Loci

27. Partitioning heritability by functional category using GWAS summary statistics

28. Regulatory variants explain much more heritability than coding variants across 11 common diseases

29. Exploring genetic and expression differences between physiologically extreme ecotypes: comparative genomic hybridization and gene expression studies of Kas-1 and Tsu-1 accessions of Arabidopsis thaliana

30. Contribution of common and rare damaging variants in familial forms of bipolar disorder and phenotypic outcome

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30 results on '"Eli Stahl"'

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