Browsing by Author "Liu, Chunyu"

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    Comparison of whole genome sequencing and targeted sequencing for mitochondrial DNA
    (Elsevier, 2021) Chen, Ruoying; Aldred, Micheala A.; Xu, Weiling; Zein, Joe; Bazeley, Peter; Comhai, Suzy A. A.; Meyers, Deborah A.; Bleecker, Eugene R.; Liu, Chunyu; Erzurum, Serpil C.; Hu, Bo; NHLBI Severe Asthma Research Program (SARP); Medicine, School of Medicine
    Mitochondrial dysfunction has emerged to be associated with a broad spectrum of diseases, and there is an increasing demand for accurate detection of mitochondrial DNA (mtDNA) variants. Whole genome sequencing (WGS) has been the dominant sequencing approach to identify genetic variants in recent decades, but most studies focus on variants on the nuclear genome. Whole genome sequencing is also costly and time consuming. Sequencing specifically targeted for mtDNA is commonly used in the diagnostic settings and has lower costs. However, there is a lack of pairwise comparisons between these two sequencing approaches for calling mtDNA variants on a population basis. In this study, we compared WGS and mtDNA-targeted sequencing (targeted-seq) in analyzing mitochondrial DNA from 1499 participants recruited into the Severe Asthma Research Program (SARP). Our study reveals that targeted-sequencing and WGS have comparable capacity to determine genotypes and to call haplogroups and homoplasmies on mtDNA. However, there exists a large variability in calling heteroplasmies, especially for low-frequency heteroplasmies, which indicates that investigators should be cautious about heteroplasmies acquired from different sequencing methods. Further research is highly desired to improve variant detection methods for mitochondrial DNA.
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    Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics
    (SpringerOpen, 2018-11-11) Breuer, René; Mattheisen, Manuel; Frank, Josef; Krumm, Bertram; Treutlein, Jens; Kassem, Layla; Strohmaier, Jana; Herms, Stefan; Mühleisen, Thomas W.; Degenhardt, Franziska; Cichon, Sven; Nöthen, Markus M.; Karypis, George; Kelsoe, John; Greenwood, Tiffany; Nievergelt, Caroline; Shilling, Paul; Shekhtman, Tatyana; Edenberg, Howard; Craig, David; Szelinger, Szabolcs; Nurnberger, John; Gershon, Elliot; Alliey‑Rodriguez, Ney; Zandi, Peter; Goes, Fernando; Schork, Nicholas; Smith, Erin; Koller, Daniel; Zhang, Peng; Badner, Judith; Berrettini, Wade; Bloss, Cinnamon; Byerley, William; Coryell, William; Foroud, Tatiana; Guo, Yirin; Hipolito, Maria; Keating, Brendan; Lawson, William; Liu, Chunyu; Mahon, Pamela; McInnis, Melvin; Murray, Sarah; Nwulia, Evaristus; Potash, James; Rice, John; Scheftner, William; Zöllner, Sebastian; McMahon, Francis J.; Rietschel, Marcella; Schulze, Thomas G.; Biochemistry and Molecular Biology, School of Medicine
    BACKGROUND: Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype-phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted. RESULTS: Two of these rules-one associated with eating disorder and the other with anxiety-remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings. CONCLUSION: Our approach detected novel specific genotype-phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype-phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.
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    Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder
    (Elsevier, 2019-01-01) Budde, Monika; Friedrichs, Stefanie; Alliey-Rodriguez, Ney; Ament, Seth; Badner, Judith A.; Berrettini, Wade H.; Bloss, Cinnamon S.; Byerley, William; Cichon, Sven; Comes, Ashley L.; Coryell, William; Craig, David W.; Degenhardt, Franziska; Edenberg, Howard J.; Foroud, Tatiana; Forstner, Andreas J.; Frank, Josef; Gershon, Elliot S.; Goes, Fernando S.; Greenwood, Tiffany A.; Guo, Yiran; Hipolito, Maria; Hood, Leroy; Keating, Brendan J.; Koller, Daniel L.; Lawson, William B.; Liu, Chunyu; Mahon, Pamela B.; McInnis, Melvin G.; McMahon, Francis J.; Meier, Sandra M.; Mühleisen, Thomas W.; Murray, Sarah S.; Nievergelt, Caroline M.; Nurnberger, John I.; Nwulia, Evaristus A.; Potash, James B.; Quarless, Danjuma; Rice, John; Roach, Jared C.; Scheftner, William A.; Schork, Nicholas J.; Shekhtman, Tatyana; Shilling, Paul D.; Smith, Erin N.; Streit, Fabian; Strohmaier, Jana; Szelinger, Szabolcs; Treutlein, Jens; Witt, Stephanie H.; Zandi, Peter P.; Zhang, Peng; Zöllner, Sebastian; Bickeböller, Heike; Falkai, Peter G.; Kelsoe, John R.; Nöthen, Markus M.; Rietschel, Marcella; Schulze, Thomas G.; Malzahn, Dörthe; Biochemistry and Molecular Biology, School of Medicine
    Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 – 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 – rs2086256 – rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.
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    Epigenetic age acceleration and cognitive resilience in the Framingham Heart Study
    (Wiley, 2025-01-03) Dacey, Ryan; Durape, Shruti; Wang, Mengyao; Hwang, Phillip H.; Gurnani, Ashita S.; Ang, Ting Fang Alvin; Devine, Sherral A.; Choi, Seo-Eun; Lee, Michael L.; Scollard, Phoebe; Gibbons, Laura E.; Mukherjee, Shubhabrata; Trittschuh, Emily H.; Sherva, Richard; Dumitrescu, Logan C.; Hohman, Timothy J.; Cuccaro, Michael L.; Saykin, Andrew J.; Crane, Paul K.; Li, Yi; Levy, Daniel; Ma, Jiantao; Liu, Chunyu; Lunetta, Kathryn L.; Au, Rhoda; Farrer, Lindsay A.; Mez, Jesse; Radiology and Imaging Sciences, School of Medicine
    Background: There is growing evidence that epigenetic age acceleration may predict late life cognitive decline and dementia, but it is unknown whether this is due to accelerated neurodegeneration or reduction in cognitive resilience. We examined the relationship between epigenetic clocks and domain specific neuropsychological (NP) factor scores, mild cognitive impairment (MCI), Alzheimer’s Disease (AD), and all‐cause dementia, before and after accounting for plasma total tau (t‐tau), a marker of neurodegeneration. Method: DNA methylation and plasma t‐tau (Simoa assay; Quanterix) data from 2091 Framingham Heart Study Offspring cohort participants were generated from blood at the same Exam 8 visit (2005‐2008). Three epigenetic clock measures: DunedinPACE, PC PhenoAge, and PC GrimAge were estimated from the DNA methylation data. Longitudinal NP factor scores were previously derived for memory, language, and executive function using confirmatory factor analysis. We tested the association of epigenetic age acceleration with cognitive trajectories using linear mixed effects models and with time to MCI, all‐cause dementia and AD using Cox‐proportional hazard models. Models were run with and without adjustment for plasma t‐tau. All models included APOE ε4‐carrier status, education, smoking, age, and sex as covariates. Epigenetic measures were standardized in all models. Result: At Exam 8, the sample was, on average, 66.3 (SD = 9.0) years of age, 54.8% female, and had 16.4 (SD = 2.7) years of education. DundeinPACE was significantly associated with faster decline in executive function (βtimeXepi_age = ‐0.005, 95% CI:[‐0.009,‐0.002], p = 0.0020), but not with baseline executive function. Older PhenoAge (βepi_age = ‐0.041, 95% CI:[‐0.067,‐0.014], p = 0.0028) and GrimAge (βepi_age = ‐0.042, 95% CI:[‐0.073,‐0.011], p = 0.0084) were significantly associated with worse baseline executive function, but not with rate of decline. Older PhenoAge also was significantly associated with worse baseline memory (βepi_age = ‐0.037, 95% CI:[‐0.061,‐0.012], p = 0.0036). DunedinPACE was significantly associated with time to MCI (HR = 1.20, 95% CI:[1.06,1.35], p = 0.0034), AD (HR = 1.30, 95% CI:[1.07,1.57], p = 0.0068) and all‐cause dementia (HR = 1.30, 95% CI:[1.10,1.53], p = 0.0017). Results remained similar after adjustment for plasma t‐tau. Conclusion: Epigenetic age acceleration may be a marker of cognitive resilience, particularly in executive function. Of the three epigenetic clocks examined, DundedinPACE showed the most robust associations with cognitive resilience, with lower DunedinPACE associated with greater cognitive resilience.
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    Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility
    (Nature Publishing Group, 2015-01-29) Wessel, Jennifer; Chu, Audrey Y.; Willems, Sara M.; Wang, Shuai; Yaghootkar, Hanieh; Brody, Jennifer A.; Dauriz, Marco; Hivert, Marie-France; Raghavan, Sridharan; Lipovich, Leonard; Hidalgo, Bertha; Fox, Keolu; Huffman, Jennifer E.; An, Ping; Lu, Yingchang; Rasmussen-Torvik, Laura J.; Grarup, Niels; Ehm, Margaret G.; Li, Li; Baldridge, Abigail S.; Stančáková, Alena; Abrol, Ravinder; Besse, Céline; Boland, Anne; Bork-Jensen, Jette; Fornage, Myriam; Freitag, Daniel F.; Garcia, Melissa E.; Guo, Xiuqing; Hara, Kazuo; Isaacs, Aaron; Jakobsdottir, Johanna; Lange, Leslie A.; Layton, Jill C.; Li, Man; Hua Zhao, Jing; Meidtner, Karina; Morrison, Alanna C.; Nalls, Mike A.; Peters, Marjolein J.; Sabater-Lleal, Maria; Schurmann, Claudia; Silveira, Angela; Smith, Albert V.; Southam, Lorraine; Stoiber, Marcus H.; Strawbridge, Rona J.; Taylor, Kent D.; Varga, Tibor V.; Allin, Kristine H.; Amin, Najaf; Aponte, Jennifer L.; Aung, Tin; Barbieri, Caterina; Bihlmeyer, Nathan A.; Boehnke, Michael; Bombieri, Cristina; Bowden, Donald W.; Burns, Sean M.; Chen, Yuning; Chen, Yii-DerI; Cheng, Ching-Yu; Correa, Adolfo; Czajkowski, Jacek; Dehghan, Abbas; Ehret, Georg B.; Eiriksdottir, Gudny; Escher, Stefan A.; Farmaki, Aliki-Eleni; Frånberg, Mattias; Gambaro, Giovanni; Giulianini, Franco; Goddard, William A.; Goel, Anuj; Gottesman, Omri; Grove, Megan L.; Gustafsson, Stefan; Hai, Yang; Hallmans, Göran; Heo, Jiyoung; Hoffmann, Per; Ikram, Mohammad K.; Jensen, Richard A.; Jørgensen, Marit E.; Jørgensen, Torben; Karaleftheri, Maria; Khor, Chiea C.; Kirkpatrick, Andrea; Kraja, Aldi T.; Kuusisto, Johanna; Lange, Ethan M.; Lee, I. T.; Lee, Wen-Jane; Leong, Aaron; Liao, Jiemin; Liu, Chunyu; Liu, Yongmei; Lindgren, Cecilia M.; Linneberg, Allan; Malerba, Giovanni; Mamakou, Vasiliki; Marouli, Eirini; Maruthur, Nisa M.; Matchan, Angela; McKean-Cowdin, Roberta; McLeod, Olga; Metcalf, Ginger A.; Mohlke, Karen L.; Muzny, Donna M.; Ntalla, Ioanna; Palmer, Nicholette D.; Pasko, Dorota; Peter, Andreas; Rayner, Nigel W.; Renström, Frida; Rice, Ken; Sala, Cinzia F.; Sennblad, Bengt; Serafetinidis, Ioannis; Smith, Jennifer A.; Soranzo, Nicole; Speliotes, Elizabeth K.; Stahl, Eli A.; Stirrups, Kathleen; Tentolouris, Nikos; Thanopoulou, Anastasia; Torres, Mina; Traglia, Michela; Tsafantakis, Emmanouil; Javad, Sundas; Yanek, Lisa R.; Zengini, Eleni; Becker, Diane M.; Bis, Joshua C.; Brown, James B.; Adrienne Cupples, L.; Hansen, Torben; Ingelsson, Erik; Karter, Andrew J.; Lorenzo, Carlos; Mathias, Rasika A.; Norris, Jill M.; Peloso, Gina M.; Sheu, Wayne H.-H.; Toniolo, Daniela; Vaidya, Dhananjay; Varma, Rohit; Wagenknecht, Lynne E.; Boeing, Heiner; Bottinger, Erwin P.; Dedoussis, George; Deloukas, Panos; Ferrannini, Ele; Franco, Oscar H.; Franks, Paul W.; Gibbs, Richard A.; Gudnason, Vilmundur; Hamsten, Anders; Harris, Tamara B.; Hattersley, Andrew T.; Hayward, Caroline; Hofman, Albert; Jansson, Jan-Håkan; Langenberg, Claudia; Launer, Lenore J.; Levy, Daniel; Oostra, Ben A.; O'Donnell, Christopher J.; O'Rahilly, Stephen; Padmanabhan, Sandosh; Pankow, James S.; Polasek, Ozren; Province, Michael A.; Rich, Stephen S.; Ridker, Paul M.; Rudan, Igor; Schulze, Matthias B.; Smith, Blair H.; Uitterlinden, André G.; Walker, Mark; Watkins, Hugh; Wong, Tien Y.; Zeggini, Eleftheria; Laakso, Markku; Borecki, Ingrid B.; Chasman, Daniel I.; Pedersen, Oluf; Psaty, Bruce M.; Shyong Tai, E.; van Duijn, Cornelia M.; Wareham, Nicholas J.; Waterworth, Dawn M.; Boerwinkle, Eric; Linda Kao, W. H.; Florez, Jose C.; Loos, Ruth J. F.; Wilson, James G.; Frayling, Timothy M.; Siscovick, David S.; Dupuis, Josée; Rotter, Jerome I.; Meigs, James B.; Scott, Robert A.; Goodarzi, Mark O.; Department of Epidemiology, Richard M. Fairbanks School of Public Health
    Fasting ​glucose and ​insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in ​GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=−0.09±0.01 mmol l−1, P=3.4 × 10−12), T2D risk (OR[95%CI]=0.86[0.76–0.96], P=0.010), early ​insulin secretion (β=−0.07±0.035 pmolinsulin mmolglucose−1, P=0.048), but higher 2-h ​glucose (β=0.16±0.05 mmol l−1, P=4.3 × 10−4). We identify a gene-based association with FG at ​G6PC2 (pSKAT=6.8 × 10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ​ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l−1, P=1.3 × 10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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    Mitochondrial DNA Copy Number Variation in Asthma Risk, Severity, and Exacerbations
    (medRxiv, 2023-12-05) Xu, Weiling; Hong, Yun Soo; Hu, Bo; Comhair, Suzy A. A.; Janocha, Allison J.; Zein, Joe G.; Chen, Ruoying; Meyers, Deborah A.; Mauger, David T.; Ortega, Victor E.; Bleecker, Eugene R.; Castro, Mario; Denlinger, Loren C.; Fahy, John V.; Israel, Elliot; Levy, Bruce D.; Jarjour, Nizar N.; Moore, Wendy C.; Wenzel, Sally E.; Gaston, Benjamin; Liu, Chunyu; Arking, Dan E.; Erzurum, Serpil C.; National Heart, Lung, and Blood Institute (NHLBI) Severe Asthma Research Program (SARP) and TOPMed mtDNA Working Group in NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Pediatrics, School of Medicine
    Rationale: Although airway oxidative stress and inflammation are central to asthma pathogenesis, there is limited knowledge of the relationship of asthma risk, severity, or exacerbations to mitochondrial dysfunction, which is pivotal to oxidant generation and inflammation. Objectives: We investigated whether mitochondrial DNA copy number (mtDNA-CN) as a measure of mitochondrial function is associated with asthma diagnosis, severity, oxidative stress, and exacerbations. Methods: We measured mtDNA-CN in blood in two cohorts. In the UK Biobank (UKB), we compared mtDNA-CN in mild and moderate-severe asthmatics to non-asthmatics. In the Severe Asthma Research Program (SARP), we evaluated mtDNA-CN in relation to asthma severity, biomarkers of oxidative stress and inflammation, and exacerbations. Measures and main results: In UK Biobank, asthmatics (n = 29,768) have lower mtDNA-CN compared to non-asthmatics (n = 239,158) (beta, -0.026 [95% CI, -0.038 to -0.014], P = 2.46×10-5). While lower mtDNA-CN is associated with asthma, mtDNA-CN did not differ by asthma severity in either UKB or SARP. Biomarkers of inflammation show that asthmatics have higher white blood cells (WBC), neutrophils, eosinophils, fraction exhaled nitric oxide (FENO), and lower superoxide dismutase (SOD) than non-asthmatics, confirming greater oxidative stress in asthma. In one year follow-up in SARP, higher mtDNA-CN is associated with reduced risk of three or more exacerbations in the subsequent year (OR 0.352 [95% CI, 0.164 to 0.753], P = 0.007). Conclusions: Asthma is characterized by mitochondrial dysfunction. Higher mtDNA-CN identifies an exacerbation-resistant asthma phenotype, suggesting mitochondrial function is important in exacerbation risk.
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    Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study
    (medRxiv, 2023-06-29) Wang, Yuxuan; Selvaraj, Margaret Sunitha; Li, Xihao; Li, Zilin; Holdcraft, Jacob A.; Arnett, Donna K.; Bis, Joshua C.; Blangero, John; Boerwinkle, Eric; Bowden, Donald W.; Cade, Brian E.; Carlson, Jenna C.; Carson, April P.; Chen, Yii-Der Ida; Curran, Joanne E.; de Vries, Paul S.; Dutcher, Susan K.; Ellinor, Patrick T.; Floyd, James S.; Fornage, Myriam; Freedman, Barry I.; Gabriel, Stacey; Germer, Soren; Gibbs, Richard A.; Guo, Xiuqing; He, Jiang; Heard-Costa, Nancy; Hildalgo, Bertha; Hou, Lifang; Irvin, Marguerite R.; Joehanes, Roby; Kaplan, Robert C.; Kardia, Sharon Lr.; Kelly, Tanika N.; Kim, Ryan; Kooperberg, Charles; Kral, Brian G.; Levy, Daniel; Li, Changwei; Liu, Chunyu; Lloyd-Jone, Don; Loos, Ruth Jf.; Mahaney, Michael C.; Martin, Lisa W.; Mathias, Rasika A.; Minster, Ryan L.; Mitchell, Braxton D.; Montasser, May E.; Morrison, Alanna C.; Murabito, Joanne M.; Naseri, Take; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Preuss, Michael H.; Psaty, Bruce M.; Raffield, Laura M.; Rao, Dabeeru C.; Redline, Susan; Reiner, Alexander P.; Rich, Stephen S.; Ruepena, Muagututi'a Sefuiva; Sheu, Wayne H-H; Smith, Jennifer A.; Smith, Albert; Tiwari, Hemant K.; Tsai, Michael Y.; Viaud-Martinez, Karine A.; Wang, Zhe; Yanek, Lisa R.; Zhao, Wei; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Rotter, Jerome I.; Lin, Xihong; Natarajan, Pradeep; Peloso, Gina M.; Biostatistics and Health Data Science, School of Medicine
    Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.
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    Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program
    (Springer Nature, 2021) Taliun, Daniel; Harris, Daniel N.; Kessler, Michael D.; Carlson, Jedidiah; Szpiech, Zachary A.; Torres, Raul; Gagliano Taliun, Sarah A.; Corvelo, André; Gogarten, Stephanie M.; Kang, Hyun Min; Pitsillides, Achilleas N.; LeFaive, Jonathon; Lee, Seung-Been; Tian, Xiaowen; Browning, Brian L.; Das, Sayantan; Emde, Anne-Katrin; Clarke, Wayne E.; Loesch, Douglas P.; Shetty, Amol C.; Blackwell, Thomas W.; Smith, Albert V.; Wong, Quenna; Liu, Xiaoming; Conomos, Matthew P.; Bobo, Dean M.; Aguet, François; Albert, Christine; Alonso, Alvaro; Ardlie, Kristin G.; Arking, Dan E.; Aslibekyan, Stella; Auer, Paul L.; Barnard, John; Barr, R. Graham; Barwick, Lucas; Becker, Lewis C.; Beer, Rebecca L.; Benjamin, Emelia J.; Bielak, Lawrence F.; Blangero, John; Boehnke, Michael; Bowden, Donald W.; Brody, Jennifer A.; Burchard, Esteban G.; Cade, Brian E.; Casella, James F.; Chalazan, Brandon; Chasman, Daniel I.; Chen, Yii-Der Ida; Cho, Michael H.; Choi, Seung Hoan; Chung, Mina K.; Clish, Clary B.; Correa, Adolfo; Curran, Joanne E.; Custer, Brian; Darbar, Dawood; Daya, Michelle; de Andrade, Mariza; DeMeo, Dawn L.; Dutcher, Susan K.; Ellinor, Patrick T.; Emery, Leslie S.; Eng, Celeste; Fatkin, Diane; Fingerlin, Tasha; Forer, Lukas; Fornage, Myriam; Franceschini, Nora; Fuchsberger, Christian; Fullerton, Stephanie M.; Germer, Soren; Gladwin, Mark T.; Gottlieb, Daniel J.; Guo, Xiuqing; Hall, Michael E.; He, Jiang; Heard-Costa, Nancy L.; Heckbert, Susan R.; Irvin, Marguerite R.; Johnsen, Jill M.; Johnson, Andrew D.; Kaplan, Robert; Kardia, Sharon L. R.; Kelly, Tanika; Kelly, Shannon; Kenny, Eimear E.; Kiel, Douglas P.; Klemmer, Robert; Konkle, Barbara A.; Kooperberg, Charles; Köttgen, Anna; Lange, Leslie A.; Lasky-Su, Jessica; Levy, Daniel; Lin, Xihong; Lin, Keng-Han; Liu, Chunyu; Loos, Ruth J. F.; Garman, Lori; Gerszten, Robert; Lubitz, Steven A.; Lunetta, Kathryn L.; Mak, Angel C. Y.; Manichaikul, Ani; Manning, Alisa K.; Mathias, Rasika A.; McManus, David D.; McGarvey, Stephen T.; Meigs, James B.; Meyers, Deborah A.; Mikulla, Julie L.; Minear, Mollie A.; Mitchell, Braxton D.; Mohanty, Sanghamitra; Montasser, May E.; Montgomery, Courtney; Morrison, Alanna C.; Murabito, Joanne M.; Natale, Andrea; Natarajan, Pradeep; Nelson, Sarah C.; North, Kari E.; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Pankratz, Nathan; Peloso, Gina M.; Peyser, Patricia A.; Pleiness, Jacob; Post, Wendy S.; Psaty, Bruce M.; Rao, D. C.; Redline, Susan; Reiner, Alexander P.; Roden, Dan; Rotter, Jerome I.; Ruczinski, Ingo; Sarnowski, Chloé; Schoenherr, Sebastian; Schwartz, David A.; Seo, Jeong-Sun; Seshadri, Sudha; Sheehan, Vivien A.; Sheu, Wayne H.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Smith, Jennifer A.; Sotoodehnia, Nona; Stilp, Adrienne M.; Tang, Weihong; Taylor, Kent D.; Telen, Marilyn; Thornton, Timothy A.; Tracy, Russell P.; Van Den Berg, David J.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Vrieze, Scott; Weeks, Daniel E.; Weir, Bruce S.; Weiss, Scott T.; Weng, Lu-Chen; Willer, Cristen J.; Zhang, Yingze; Zhao, Xutong; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Boerwinkle, Eric; Gabriel, Stacey; Gibbs, Richard; Rice, Kenneth M.; Rich, Stephen S.; Silverman, Edwin K.; Qasba, Pankaj; Gan, Weiniu; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Papanicolaou, George J.; Nickerson, Deborah A.; Browning, Sharon R.; Zody, Michael C.; Zöllner, Sebastian; Wilson, James G.; Cupples, L. Adrienne; Laurie, Cathy C.; Jaquish, Cashell E.; Hernandez, Ryan D.; O'Connor, Timothy D.; Abecasis, Gonçalo R.; Epidemiology, Richard M. Fairbanks School of Public Health
    The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.