Browsing by Subject "Genome-wide association studies"

Now showing 1 - 10 of 29
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    Author Correction: Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations
    (Springer Nature, 2023-10-19) Feofanova, Elena V.; Brown, Michael R.; Alkis, Taryn; Manuel, Astrid M.; Li, Xihao; Tahir, Usman A.; Li, Zilin; Mendez, Kevin M.; Kelly, Rachel S.; Qi, Qibin; Chen, Han; Larson, Martin G.; Lemaitre, Rozenn N.; Morrison, Alanna C.; Grieser, Charles; Wong, Kari E.; Gerszten, Robert E.; Zhao, Zhongming; Lasky-Su, Jessica; NHLBI Trans-Omics for Precision Medicine (TOPMed); Yu, Bing; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Correction to: Nature Communications 10.1038/s41467-023-38800-2, published online 30 May2023 In this article, the author name Robert E. Gerszten was incorrectly written as Robert E. Gersztern. The original article has been corrected.
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    Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression
    (Nature Publishing Group, 2018-01) Culverhouse, Robert C.; Saccone, Nancy L.; Horton, Amy C.; Ma, Yinjiao; Anstey, Kaarin J.; Banaschewski, Tobias; Burmeister, Margit; Cohen-Woods, Sarah; Etain, Bruno; Fisher, Helen L.; Goldman, Noreen; Guillaume, Sébastien; Horwood, John; Juhasz, Gabriella; Lester, Kathryn J.; Mandelli, Laura; Middeldorp, Christel M.; Olié, Emilie; Villafuerte, Sandra; Air, Tracy M.; Araya, Ricardo; Bowes, Lucy; Burns, Richard; Byrne, Enda M.; Coffey, Carolyn; Coventry, William L.; Gawronski, Katerina; Glei, Dana; Hatzimanolis, Alex; Hottenga, Jouke-Jan; Jaussent, Isabelle; Jawahar, Catharine; Jennen-Steinmetz, Christine; Kramer, John R.; Lajnef, Mohamed; Little, Keriann; zu Schwabedissen, Henriette Meyer; Nauck, Matthias; Nederhof, Esther; Petschner, Peter; Peyrot, Wouter J.; Schwahn, Christian; Sinnamon, Grant; Stacey, David; Tian, Yan; Toben, Catherine; Auwera, Sandra Van der; Wainwright, Nick; Wang, Jen-Chyong; Willemsen, Gonneke; Anderson, Ian M.; Arolt, Volker; Åslund, Cecilia; Bagdy, Gyorgy; Baune, Bernhard T.; Bellivier, Frank; Boomsma, Dorret I.; Courtet, Philippe; Dannlowski, Udo; de Geus, Eco J.C.; Deakin, John F. W.; Easteal, Simon; Eley, Thalia; Fergusson, David M.; Goate, Alison M.; Gonda, Xenia; Grabe, Hans J.; Holzman, Claudia; Johnson, Eric O.; Kennedy, Martin; Laucht, Manfred; Martin, Nicholas G.; Munafò, Marcus; Nilsson, Kent W.; Oldehinkel, Albertine J.; Olsson, Craig; Ormel, Johan; Otte, Christian; Patton, George C.; Penninx, Brenda W.J.H.; Ritchie, Karen; Sarchiapone, Marco; Scheid, JM; Serretti, Alessandro; Smit, Johannes H.; Stefanis, Nicholas C.; Surtees, Paul G.; Völzke, Henry; Weinstein, Maxine; Whooley, Mary; Nurnberger, John I., Jr.; Breslau, Naomi; Bierut, Laura J.; Psychiatry, School of Medicine
    The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research, and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 datasets containing 38 802 European-ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analyzed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis1) with qualifying unpublished data were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction, and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalizable, but must be of modest effect size and only observable in limited situations.
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    Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease
    (Springer Nature, 2022-06-06) Cadby, Gemma; Giles, Corey; Melton, Phillip E.; Huynh, Kevin; Mellett, Natalie A.; Duong, Thy; Nguyen, Anh; Cinel, Michelle; Smith, Alex; Olshansky, Gavriel; Wang, Tingting; Brozynska, Marta; Inouye, Mike; McCarthy, Nina S.; Ariff, Amir; Hung, Joseph; Hui, Jennie; Beilby, John; Dubé, Marie-Pierre; Watts, Gerald F.; Shah, Sonia; Wray, Naomi R.; Lim, Wei Ling Florence; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Porter, Tenielle; Vacher, Michael; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Taddei, Kevin; Arnold, Matthias; Kastenmüller, Gabi; Nho, Kwangsik; Saykin, Andrew J.; Han, Xianlin; Kaddurah-Daouk, Rima; Martins, Ralph N.; Blangero, John; Meikle, Peter J.; Moses, Eric K.; Radiology and Imaging Sciences, School of Medicine
    We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
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    Deep learning-based identification of genetic variants: application to Alzheimer’s disease classification
    (Oxford University Press, 2022) Jo, Taeho; Nho, Kwangsik; Bice, Paula; Saykin, Andrew J.; Alzheimer’s Disease Neuroimaging Initiative
    Deep learning is a promising tool that uses nonlinear transformations to extract features from high-dimensional data. Deep learning is challenging in genome-wide association studies (GWAS) with high-dimensional genomic data. Here we propose a novel three-step approach (SWAT-CNN) for identification of genetic variants using deep learning to identify phenotype-related single nucleotide polymorphisms (SNPs) that can be applied to develop accurate disease classification models. In the first step, we divided the whole genome into nonoverlapping fragments of an optimal size and then ran convolutional neural network (CNN) on each fragment to select phenotype-associated fragments. In the second step, using a Sliding Window Association Test (SWAT), we ran CNN on the selected fragments to calculate phenotype influence scores (PIS) and identify phenotype-associated SNPs based on PIS. In the third step, we ran CNN on all identified SNPs to develop a classification model. We tested our approach using GWAS data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) including (N = 981; cognitively normal older adults (CN) = 650 and AD = 331). Our approach identified the well-known APOE region as the most significant genetic locus for AD. Our classification model achieved an area under the curve (AUC) of 0.82, which was compatible with traditional machine learning approaches, random forest and XGBoost. SWAT-CNN, a novel deep learning-based genome-wide approach, identified AD-associated SNPs and a classification model for AD and may hold promise for a range of biomedical applications.
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    Editorial: Deciphering Non-Coding Regulatory Variants: Computational and Functional Validation
    (Frontiers, 2021-11) Chen, Li; Li, Mulin Jun; Biostatistics, School of Public Health
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    Fine-mapping genomic loci refines bipolar disorder risk genes
    (medRxiv, 2024-02-13) Koromina, Maria; Ravi, Ashvin; Panagiotaropoulou, Georgia; Schilder, Brian M.; Humphrey, Jack; Braun, Alice; Bidgeli, Tim; Chatzinakos, Chris; Coombes, Brandon; Kim, Jaeyoung; Liu, Xiaoxi; Terao, Chikashi; O'Connell, Kevin S.; Adams, Mark; Adolfsson, Rolf; Alda, Martin; Alfredsson, Lars; Andlauer, Till F. M.; Andreassen, Ole A.; Antoniou, Anastasia; Baune, Bernhard T.; Bengesser, Susanne; Biernacka, Joanna; Boehnke, Michael; Bosch, Rosa; Cairns, Murray; Carr, Vaughan J.; Casas, Miquel; Catts, Stanley; Cichon, Sven; Corvin, Aiden; Craddock, Nicholas; Dafnas, Konstantinos; Dalkner, Nina; Dannlowski, Udo; Degenhardt, Franziska; Di Florio, Arianna; Dikeos, Dimitris; Fellendorf, Frederike Tabea; Ferentinos, Panagiotis; Forstner, Andreas J.; Forty, Liz; Frye, Mark; Fullerton, Janice M.; Gawlik, Micha; Gizer, Ian R.; Gordon-Smith, Katherine; Green, Melissa J.; Grigoroiu-Serbanescu, Maria; Guzman-Parra, José; Hahn, Tim; Henskens, Frans; Hillert, Jan; Jablensky, Assen V.; Jones, Lisa; Jones, Ian; Jonsson, Lina; Kelsoe, John R.; Kircher, Tilo; Kirov, George; Kittel-Schneider, Sarah; Kogevinas, Manolis; Landén, Mikael; Leboyer, Marion; Lenger, Melanie; Lissowska, Jolanta; Lochner, Christine; Loughland, Carmel; MacIntyre, Donald; Martin, Nicholas G.; Maratou, Eirini; Mathews, Carol A.; Mayoral, Fermin; McElroy, Susan L.; McGregor, Nathaniel W.; McIntosh, Andrew; McQuillin, Andrew; Michie, Patricia; Milanova, Vihra; Mitchell, Philip B.; Moutsatsou, Paraskevi; Mowry, Bryan; Müller-Myhsok, Bertram; Myers, Richard; Nenadić, Igor; Nöthen, Markus M.; O'Donovan, Claire; O'Donovan, Michael; Ophoff, Roel A.; Owen, Michael J.; Pantelis, Chris; Pato, Carlos; Pato, Michele T.; Patrinos, George P.; Pawlak, Joanna M.; Perlis, Roy H.; Porichi, Evgenia; Posthuma, Danielle; Ramos-Quiroga, Josep Antoni; Reif, Andreas; Reininghaus, Eva Z.; Ribasés, Marta; Rietschel, Marcella; Schall, Ulrich; Schulze, Thomas G.; Scott, Laura; Scott, Rodney J.; Serretti, Alessandro; Shannon Weickert, Cynthia; Smoller, Jordan W.; Soler Artigas, Maria; Stein, Dan J.; Streit, Fabian; Toma, Claudio; Tooney, Paul; Vieta, Eduard; Vincent, John B.; Waldman, Irwin D.; Weickert, Thomas; Witt, Stephanie H.; Hong, Kyung Sue; Ikeda, Masashi; Iwata, Nakao; Świątkowska, Beata; Won, Hong-Hee; Edenberg, Howard J.; Ripke, Stephan; Raj, Towfique; Coleman, Jonathan R. I.; Mullins, Niamh; Biochemistry and Molecular Biology, School of Medicine
    Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
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    Genes identified in rodent studies of alcohol intake are enriched for heritability of human substance use
    (Wiley, 2021) Huggett, Spencer B.; Johnson, Emma C.; Hatoum, Alexander S.; Lai, Dongbing; Srijeyanthan, Jenani; Bubier, Jason A.; Chesler, Elissa J.; Agrawal, Arpana; Palmer, Abraham A.; Edenberg, Howard J.; Palmer, Rohan H. C.; Medical and Molecular Genetics, School of Medicine
    Background: Rodent paradigms and human genome-wide association studies (GWAS) on drug use have the potential to provide biological insight into the pathophysiology of addiction. Methods: Using GeneWeaver, we created rodent alcohol and nicotine gene-sets derived from 19 gene expression studies on alcohol and nicotine outcomes. We partitioned the SNP heritability of these gene-sets using four large human GWAS: (1) alcoholic drinks per week, (2) problematic alcohol use, (3) cigarettes per day, and (4) smoking cessation. We benchmarked our findings with curated human alcohol and nicotine addiction gene-sets and performed specificity analyses using other rodent gene-sets (e.g., locomotor behavior) and other human GWAS (e.g., height). Results: The rodent alcohol gene-set was enriched for heritability of drinks per week, cigarettes per day, and smoking cessation, but not problematic alcohol use. However, the rodent nicotine gene-set was not significantly associated with any of these traits. Both rodent gene-sets showed enrichment for several non-substance-use GWAS, and the extent of this relationship tended to increase as a function of trait heritability. In general, larger gene-sets demonstrated more significant enrichment. Finally, when evaluating human traits with similar heritabilities, both rodent gene-sets showed greater enrichment for substance use traits. Conclusion: Our results suggest that rodent gene expression studies can help to identify genes that contribute to the heritability of some substance use traits in humans, yet there was less specificity than expected. We outline various limitations, interpretations, and considerations for future research.
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    Genome sequencing unveils a regulatory landscape of platelet reactivity
    (Springer Nature, 2021-06-15) Keramati, Ali R.; Chen, Ming-Huei; Rodriguez, Benjamin A. T.; Yanek, Lisa R.; Bhan, Arunoday; Gaynor, Brady J.; Ryan, Kathleen; Brody, Jennifer A.; Zhong, Xue; Wei, Qiang; NHLBI Trans-Omics for Precision (TOPMed) Consortium; Kammers, Kai; Kanchan, Kanika; Iyer, Kruthika; Kowalski, Madeline H.; Pitsillides, Achilleas N.; Cupples, L. Adrienne; Li, Bingshan; Schlaeger, Thorsten M.; Shuldiner, Alan R.; O’Connell, Jeffrey R.; Ruczinski, Ingo; Mitchell, Braxton D.; Faraday, Nauder; Taub, Margaret A.; Becker, Lewis C.; Lewis, Joshua P.; Mathias, Rasika A.; Johnson, Andrew D.; Medicine, School of Medicine
    Platelet aggregation at the site of atherosclerotic vascular injury is the underlying pathophysiology of myocardial infarction and stroke. To build upon prior GWAS, here we report on 16 loci identified through a whole genome sequencing (WGS) approach in 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) participants deeply phenotyped for platelet aggregation. We identify the RGS18 locus, which encodes a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with expression quantitative trait loci (eQTL) signatures for RGS18 expression in platelets. Gene-based approaches implicate the SVEP1 gene, a known contributor of coronary artery disease risk. Sentinel variants at RGS18 and PEAR1 are associated with thrombosis risk and increased gastrointestinal bleeding risk, respectively. Our WGS findings add to previously identified GWAS loci, provide insights regarding the mechanism(s) by which genetics may influence cardiovascular disease risk, and underscore the importance of rare variant and regulatory approaches to identifying loci contributing to complex phenotypes.
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    Genome-wide association analysis of hippocampal volume identifies enrichment of neurogenesis-related pathways
    (Nature Research, 2019-10-10) Horgusluoglu-Moloch, Emrin; Risacher, Shannon L.; Crane, Paul K.; Hibar, Derrek; Thompson, Paul M.; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Medical and Molecular Genetics, School of Medicine
    Adult neurogenesis occurs in the dentate gyrus of the hippocampus during adulthood and contributes to sustaining the hippocampal formation. To investigate whether neurogenesis-related pathways are associated with hippocampal volume, we performed gene-set enrichment analysis using summary statistics from a large-scale genome-wide association study (N = 13,163) of hippocampal volume from the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium and two year hippocampal volume changes from baseline in cognitively normal individuals from Alzheimer's Disease Neuroimaging Initiative Cohort (ADNI). Gene-set enrichment analysis of hippocampal volume identified 44 significantly enriched biological pathways (FDR corrected p-value < 0.05), of which 38 pathways were related to neurogenesis-related processes including neurogenesis, generation of new neurons, neuronal development, and neuronal migration and differentiation. For genes highly represented in the significantly enriched neurogenesis-related pathways, gene-based association analysis identified TESC, ACVR1, MSRB3, and DPP4 as significantly associated with hippocampal volume. Furthermore, co-expression network-based functional analysis of gene expression data in the hippocampal subfields, CA1 and CA3, from 32 normal controls showed that distinct co-expression modules were mostly enriched in neurogenesis related pathways. Our results suggest that neurogenesis-related pathways may be enriched for hippocampal volume and that hippocampal volume may serve as a potential phenotype for the investigation of human adult neurogenesis.
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    Genome-wide association meta-analysis identifies 29 new acne susceptibility loci
    (Springer Nature, 2022-02-07) Mitchell, Brittany L.; Saklatvala, Jake R.; Dand, Nick; Hagenbeek, Fiona A.; Li, Xin; Min, Josine L.; Thomas, Laurent; Bartels, Meike; Hottenga, Jouke Jan; Lupton, Michelle K.; Boomsma, Dorret I.; Dong, Xianjun; Hveem, Kristian; Løset, Mari; Martin, Nicholas G.; Barker, Jonathan N.; Han, Jiali; Smith, Catherine H.; Rentería, Miguel E.; Simpson, Michael A.; Epidemiology, Richard M. Fairbanks School of Public Health
    Acne vulgaris is a highly heritable skin disorder that primarily impacts facial skin. Severely inflamed lesions may leave permanent scars that have been associated with long-term psychosocial consequences. Here, we perform a GWAS meta-analysis comprising 20,165 individuals with acne from nine independent European ancestry cohorts. We identify 29 novel genome-wide significant loci and replicate 14 of the 17 previously identified risk loci, bringing the total number of reported acne risk loci to 46. Using fine-mapping and eQTL colocalisation approaches, we identify putative causal genes at several acne susceptibility loci that have previously been implicated in Mendelian hair and skin disorders, including pustular psoriasis. We identify shared genetic aetiology between acne, hormone levels, hormone-sensitive cancers and psychiatric traits. Finally, we show that a polygenic risk score calculated from our results explains up to 5.6% of the variance in acne liability in an independent cohort.