1
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Yu H, Ou G. Genetic analyses unravel the causal association of cytokine levels on lichen simplex chronicus risk: insights from a mendelian randomization study. Arch Dermatol Res 2024; 316:241. [PMID: 38795165 DOI: 10.1007/s00403-024-02964-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 04/23/2024] [Accepted: 04/26/2024] [Indexed: 05/27/2024]
Abstract
Lichen simplex chronicus (LSC) presents a challenge in dermatology due to its elusive pathogenic mechanisms. While associations between circulating inflammatory cytokines and LSC were observed, the definitive causal dynamics remain to be elucidated. Our study used a two-sample Mendelian randomization (MR) approach to investigate causal relationships. We applied a suite of MR methodologies, including IVW, Weighted Median, MR-Egger, Weighted Mode, Simple Mode, MR-PRESSO, and the Steiger test, to ensure robust causal inference. Our analysis confirmed the causal impact of genetically determined cytokine levels on LSC risk, particularly MMP-10 (OR = 0.493, P = 0.004) and DNER (OR = 0.651, P = 0.043) in risk attenuation. We also found a positive causal correlation between GDNF levels (OR = 1.871, P = 0.007) and LSC prevalence. Notably, bidirectional causality was observed between DNER and LSC. Consistency across various MR analyses and sensitivity analyses confirmed the absence of horizontal pleiotropy, validating the causal estimates. This pioneering MR investigation unveils a novel genetically anchored causal relationship between the circulating levels of MMP-10, DNER, and GDNF and LSC risk. Although further validation is requisite, our findings augment the understanding of cytokine mediation in LSC and underscore prospective avenues for research.
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Affiliation(s)
- Haoyang Yu
- Department of Dermatology, Taizhou First People's Hospital, Taizhou, Zhejiang, 318020, P. R. China.
| | - Guanyong Ou
- School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, 518055, P. R. China
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2
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Igoshin AV, Yudin NS, Romashov GA, Larkin DM. A Multibreed Genome-Wide Association Study for Cattle Leukocyte Telomere Length. Genes (Basel) 2023; 14:1596. [PMID: 37628647 PMCID: PMC10454124 DOI: 10.3390/genes14081596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 07/26/2023] [Accepted: 08/02/2023] [Indexed: 08/27/2023] Open
Abstract
Telomeres are terminal DNA regions of chromosomes that prevent chromosomal fusion and degradation during cell division. In cattle, leukocyte telomere length (LTL) is associated with longevity, productive lifespan, and disease susceptibility. However, the genetic basis of LTL in this species is less studied than in humans. In this study, we utilized the whole-genome resequencing data of 239 animals from 17 cattle breeds for computational leukocyte telomere length estimation and subsequent genome-wide association study of LTL. As a result, we identified 42 significant SNPs, of which eight were found in seven genes (EXOC6B, PTPRD, RPS6KC1, NSL1, AGBL1, ENSBTAG00000052188, and GPC1) when using covariates for two major breed groups (Turano-Mongolian and European). Association analysis with covariates for breed effect detected 63 SNPs, including 13 in five genes (EXOC6B, PTPRD, RPS6KC1, ENSBTAG00000040318, and NELL1). The PTPRD gene, demonstrating the top signal in analysis with breed effect, was previously associated with leukocyte telomere length in cattle and likely is involved in the mechanism of alternative lengthening of telomeres. The single nucleotide variants found could be tested for marker-assisted selection to improve telomere-length-associated traits.
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Affiliation(s)
- Alexander V. Igoshin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090 Novosibirsk, Russia
| | - Nikolay S. Yudin
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090 Novosibirsk, Russia
| | - Grigorii A. Romashov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), 630090 Novosibirsk, Russia
| | - Denis M. Larkin
- Royal Veterinary College, University of London, London NW1 0TU, UK
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3
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Rozanova IV, Grigoriev YN, Efimov VM, Igoshin AV, Khlestkina EK. Genetic Dissection of Spike Productivity Traits in the Siberian Collection of Spring Barley. Biomolecules 2023; 13:909. [PMID: 37371489 DOI: 10.3390/biom13060909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/23/2023] [Accepted: 05/27/2023] [Indexed: 06/29/2023] Open
Abstract
Barley (Hordeum vulgare L.) is one of the most commonly cultivated cereals worldwide. Its local varieties can represent a valuable source of unique genetic variants useful for crop improvement. The aim of this study was to reveal loci contributing to spike productivity traits in Siberian spring barley and to develop diagnostic DNA markers for marker-assisted breeding programs. For this purpose we conducted a genome-wide association study using a panel of 94 barley varieties. In total, 64 SNPs significantly associated with productivity traits were revealed. Twenty-three SNP markers were validated by genotyping in an independent sample set using competitive allele-specific PCR (KASP). Finally, fourteen markers associated with spike productivity traits on chromosomes 2H, 4H and 5H can be suggested for use in breeding programs.
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Affiliation(s)
- Irina V Rozanova
- N.I. Vavilov All-Russian Research Institute of Plant Genetic Resources (VIR), 190000 St. Petersburg, Russia
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Lavrentjeva Ave. 10, 630090 Novosibirsk, Russia
| | - Yuriy N Grigoriev
- Siberian Research Institute of Plant Cultivation and Breeding-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Krasnoobsk, 630501 Novosibirsk, Russia
| | - Vadim M Efimov
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Lavrentjeva Ave. 10, 630090 Novosibirsk, Russia
| | - Alexander V Igoshin
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Lavrentjeva Ave. 10, 630090 Novosibirsk, Russia
| | - Elena K Khlestkina
- N.I. Vavilov All-Russian Research Institute of Plant Genetic Resources (VIR), 190000 St. Petersburg, Russia
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Lavrentjeva Ave. 10, 630090 Novosibirsk, Russia
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4
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Liu Y, Gusev A, Kraft P. Germline Cancer Gene Expression Quantitative Trait Loci Are Associated with Local and Global Tumor Mutations. Cancer Res 2023; 83:1191-1202. [PMID: 36745477 PMCID: PMC10106413 DOI: 10.1158/0008-5472.can-22-2624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 12/13/2022] [Accepted: 02/01/2023] [Indexed: 02/07/2023]
Abstract
Somatic mutations drive cancer development and are relevant to patient responses to treatment. Emerging evidence shows that variations in the somatic genome can be influenced by the germline genetic background. However, the mechanisms underlying these germline-somatic associations remain largely obscure. We hypothesized that germline variants can influence somatic mutations in a nearby cancer gene ("local impact") or a set of recurrently mutated cancer genes across the genome ("global impact") through their regulatory effect on gene expression. To test this hypothesis, tumor targeted sequencing data from 12,413 patients across 11 cancer types in the Dana-Farber Profile cohort were integrated with germline cancer gene expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression Project. Variants that upregulate ATM expression were associated with a decreased risk of somatic ATM mutations across 8 cancer types. GLI2, WRN, and CBFB eQTL were associated with global tumor mutational burden of cancer genes in ovarian cancer, glioma, and esophagogastric carcinoma, respectively. An EPHA5 eQTL was associated with mutations in cancer genes specific to colorectal cancer, and eQTL related to expression of APC, WRN, GLI1, FANCA, and TP53 were associated with mutations in genes specific to endometrial cancer. These findings provide evidence that germline-somatic associations are mediated through expression of specific cancer genes, opening new avenues for research on the underlying biological processes. SIGNIFICANCE Analysis of associations between the germline genetic background and somatic mutations in patients with cancer suggests that germline variants can influence local and global tumor mutations by altering expression of cancer-related genes. See related commentary by Kar, p. 1165.
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Affiliation(s)
- Yuxi Liu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, 02215, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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5
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Ciesielski TH, Zhang X, Tacconelli A, Lutsar I, de Cabre VM, Roilides E, Ciccacci C, Borgiani P, Scott WK, Williams SM, Sirugo G. Late-onset neonatal sepsis: genetic differences by sex and involvement of the NOTCH pathway. Pediatr Res 2023; 93:1085-1095. [PMID: 35835848 DOI: 10.1038/s41390-022-02114-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 02/10/2022] [Accepted: 04/27/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND Late-Onset Neonatal Sepsis (LOS) is a rare condition, involving widespread infection, immune disruption, organ dysfunction, and often death. Because exposure to pathogens is not completely preventable, identifying susceptibility factors is critical to characterizing the pathophysiology and developing interventions. Prior studies demonstrated both genetics and infant sex influence susceptibility. Our study was designed to identify LOS associated genetic variants. METHODS We performed an exploratory genome wide association study (GWAS) with 224 LOS cases and 273 controls from six European countries. LOS was defined as sepsis presenting from 3 to 90 days of age; diagnosis was established by clinical criteria consensus guidelines. We tested for association with both autosomal and X-chromosome variants in the total sample and in sex-stratified analyses. RESULTS In total, 71 SNPs associated with neonatal sepsis at p < 1 × 10-4 in at least one analysis. Most importantly, sex-stratified analyses revealed associations with multiple SNPs (28 in males and 16 in females), but no variants from single-sex analyses associated with sepsis in the other sex. Pathway analyses showed NOTCH signaling is over-represented among genes linked to these SNPS. CONCLUSION Our results indicate genetic susceptibility to LOS is sexually dimorphic and corroborate that NOTCH signaling plays a role in determining risk. IMPACT Genes associate with late onset neonatal sepsis. Notch pathway genes are overrepresented in associations with sepsis. Genes associating with sepsis do not overlap between males and females. Sexual dimorphism can lead to sex specific treatment of sepsis.
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Affiliation(s)
- Timothy H Ciesielski
- The Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Mary Ann Swetland Center for Environmental Health at Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Xueyi Zhang
- The Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | | | - Irja Lutsar
- Department of Microbiology, School of Medicine, University of Tartu, Tartu, Estonia
| | | | - Emmanuel Roilides
- Laboratory of Infectious Diseases, 3rd Department of Paediatrics, School of Medicine, Aristotle University, Thessaloniki, Greece
| | - Cinzia Ciccacci
- Dipartimento di Biomedicina e Prevenzione, Facolta' di Medicina e Chirurgia, Universita' di Tor Vergata, Rome, Italy
- Unicamillus, Saint Camillus International University of Health Sciences, Rome, Italy
| | - Paola Borgiani
- Dipartimento di Biomedicina e Prevenzione, Facolta' di Medicina e Chirurgia, Universita' di Tor Vergata, Rome, Italy
| | - William K Scott
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | | | - Scott M Williams
- The Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine, Cleveland, OH, USA.
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, USA.
- 10900 Euclid Ave, Cleveland Institute for Computational Biology, Cleveland, USA.
| | - Giorgio Sirugo
- Institute of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
- Division of Translational Medicine and Human Genetics, Perelman SPerelman School of Medicine, University of Pennsylvaniachool of Medicine, University of Pennsylvania, Philadelphia, USA.
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6
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McDonald MLN, Lakshman Kumar P, Srinivasasainagendra V, Nair A, Rocco AP, Wilson AC, Chiles JW, Richman JS, Pinson SA, Dennis RA, Jagadale V, Brown CJ, Pyarajan S, Tiwari HK, Bamman MM, Singh JA. Novel genetic loci associated with osteoarthritis in multi-ancestry analyses in the Million Veteran Program and UK Biobank. Nat Genet 2022; 54:1816-1826. [PMID: 36411363 DOI: 10.1038/s41588-022-01221-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 10/05/2022] [Indexed: 11/22/2022]
Abstract
Osteoarthritis is a common progressive joint disease. As no effective medical interventions are available, osteoarthritis often progresses to the end stage, in which only surgical options such as total joint replacement are available. A more thorough understanding of genetic influences of osteoarthritis is essential to develop targeted personalized approaches to treatment, ideally long before the end stage is reached. To date, there have been no large multiancestry genetic studies of osteoarthritis. Here, we leveraged the unique resources of 484,374 participants in the Million Veteran Program and UK Biobank to address this gap. Analyses included participants of European, African, Asian and Hispanic descent. We discovered osteoarthritis-associated genetic variation at 10 loci and replicated findings from previous osteoarthritis studies. We also present evidence that some osteoarthritis-associated regions are robust to population ancestry. Drug repurposing analyses revealed enrichment of targets of several medication classes and provide potential insight into the etiology of beneficial effects of antiepileptics on osteoarthritis pain.
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Affiliation(s)
- Merry-Lynn N McDonald
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA.
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA.
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA.
- Department of Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
| | - Preeti Lakshman Kumar
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Vinodh Srinivasasainagendra
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ashwathy Nair
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Alison P Rocco
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Ava C Wilson
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Joe W Chiles
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Joshua S Richman
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Department of Surgery, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sarah A Pinson
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA
| | - Richard A Dennis
- Central Arkansas Veterans Healthcare System (CAVHS), Little Rock, AR, USA
| | - Vivek Jagadale
- Central Arkansas Veterans Healthcare System (CAVHS), Little Rock, AR, USA
| | - Cynthia J Brown
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Department of Medicine, Louisiana State University Health Sciences Center, New Orleans, LA, USA
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), Veterans Affairs Boston Healthcare System (VABHS), Boston, MA, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Marcas M Bamman
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Department of Cell, Developmental, and Integrative Biology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
- Florida Institute for Human & Machine Cognition, Pensacola, FL, USA
| | - Jasvinder A Singh
- Birmingham Veterans Affairs Health Care System (BVAHCS), Birmingham, AL, USA
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
- Division of Rheumatology and Clinical Immunology, Department of Medicine at the School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
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7
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Nam K, Kim J, Lee S. Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits. CELL GENOMICS 2022; 2:100189. [PMID: 36777999 PMCID: PMC9903843 DOI: 10.1016/j.xgen.2022.100189] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 08/04/2022] [Accepted: 09/09/2022] [Indexed: 11/07/2022]
Abstract
Genome-wide association studies (GWAS) on diverse ancestry groups are lacking, resulting in deficits of genetic discoveries and polygenic scores. We conducted GWAS for 76 phenotypes in Korean biobank data, namely the Korean Genome and Epidemiology Study (KoGES) (n = 72,298). Our analysis discovered 2,242 associated loci, including 122 novel associations, many of which were replicated in Biobank Japan (BBJ) GWAS. We also applied several up-to-date methods for genetic association tests to increase the power, discovering additional associations that are not identified in simple case-control GWAS. We evaluated genetic pleiotropy to investigate genes associated with multiple traits. Following meta-analysis of 32 phenotypes between KoGES and BBJ, we further identified 379 novel associations and demonstrated the improved predictive performance of polygenic risk scores by using the meta-analysis results. The summary statistics of 76 KoGES GWAS phenotypes are publicly available, contributing to a better comprehension of the genetic architecture of the East Asian population.
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Affiliation(s)
- Kisung Nam
- Graduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea
| | - Jangho Kim
- Graduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea
- Corresponding author
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Galanti D, Ramos-Cruz D, Nunn A, Rodríguez-Arévalo I, Scheepens JF, Becker C, Bossdorf O. Genetic and environmental drivers of large-scale epigenetic variation in Thlaspi arvense. PLoS Genet 2022; 18:e1010452. [PMID: 36223399 PMCID: PMC9591053 DOI: 10.1371/journal.pgen.1010452] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 10/24/2022] [Accepted: 09/28/2022] [Indexed: 11/07/2022] Open
Abstract
Natural plant populations often harbour substantial heritable variation in DNA methylation. However, a thorough understanding of the genetic and environmental drivers of this epigenetic variation requires large-scale and high-resolution data, which currently exist only for a few model species. Here, we studied 207 lines of the annual weed Thlaspi arvense (field pennycress), collected across a large latitudinal gradient in Europe and propagated in a common environment. By screening for variation in DNA sequence and DNA methylation using whole-genome (bisulfite) sequencing, we found significant epigenetic population structure across Europe. Average levels of DNA methylation were strongly context-dependent, with highest DNA methylation in CG context, particularly in transposable elements and in intergenic regions. Residual DNA methylation variation within all contexts was associated with genetic variants, which often co-localized with annotated methylation machinery genes but also with new candidates. Variation in DNA methylation was also significantly associated with climate of origin, with methylation levels being lower in colder regions and in more variable climates. Finally, we used variance decomposition to assess genetic versus environmental associations with differentially methylated regions (DMRs). We found that while genetic variation was generally the strongest predictor of DMRs, the strength of environmental associations increased from CG to CHG and CHH, with climate-of-origin as the strongest predictor in about one third of the CHH DMRs. In summary, our data show that natural epigenetic variation in Thlaspi arvense is significantly associated with both DNA sequence and environment of origin, and that the relative importance of the two factors strongly depends on the sequence context of DNA methylation. T. arvense is an emerging biofuel and winter cover crop; our results may hence be relevant for breeding efforts and agricultural practices in the context of rapidly changing environmental conditions.
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Affiliation(s)
- Dario Galanti
- Plant Evolutionary Ecology, Institute of Evolution and Ecology, University of Tübingen, Tübingen, Germany
| | - Daniela Ramos-Cruz
- Gregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- LMU Biocenter, Faculty of Biology, Ludwig Maximilians University Munich, 82152 Martinsried, Germany
| | - Adam Nunn
- ecSeq Bioinformatics GmbH, Leipzig, Germany
- Institute for Computer Science, University of Leipzig, Leipzig, Germany
| | - Isaac Rodríguez-Arévalo
- Gregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- LMU Biocenter, Faculty of Biology, Ludwig Maximilians University Munich, 82152 Martinsried, Germany
| | - J. F. Scheepens
- Plant Evolutionary Ecology, Institute for Ecology, Evolution and Diversity, Faculty of Biological Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Claude Becker
- Gregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- LMU Biocenter, Faculty of Biology, Ludwig Maximilians University Munich, 82152 Martinsried, Germany
| | - Oliver Bossdorf
- Plant Evolutionary Ecology, Institute of Evolution and Ecology, University of Tübingen, Tübingen, Germany
- * E-mail:
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9
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Zhao P, Zhang J, Liu B, Tang Y, Wang L, Wang G, Wu H, Yang C, Li X, Li B. Causal Effects of Circulating Cytokines on the Risk of Psoriasis Vulgaris: A Mendelian Randomization Study. Front Genet 2022; 13:941961. [PMID: 35769988 PMCID: PMC9234291 DOI: 10.3389/fgene.2022.941961] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 05/24/2022] [Indexed: 11/24/2022] Open
Abstract
Background: Psoriasis vulgaris is an inflammatory skin disease. Observational studies have shown associations between circulating cytokine levels and psoriasis vulgaris. But the causal relationship between circulating cytokine and psoriasis vulgaris remains elusive. Methods: To assess the causal effects of cytokine levels on the risk of psoriasis vulgaris and vice versa, we performed a two-sample Mendelian randomization (MR) study by using the inverse-variance weighted (IVW), weighted median, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) in genome-wide association summary statistics of 41 circulating cytokines in up to 8,293 individuals and psoriasis vulgaris in 399,883 individuals. Results: We identified that increasing RANTES level induced an elevated risk of psoriasis vulgaris in IVW (β = 0.33, S.E. = 0.12, p = 0.006). This causal effect showed consistency across the weighted median (β = 0.35, S.E. = 0.15, p = 0.022) and MR-PRESSO method (β = 0.33, S.E. = 0.11, p = 0.028). Conclusions: Our results suggest a potential causal effect of elevated RANTES concentration on the increased risk of psoriasis vulgaris.
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Mahajan A, Spracklen CN, Zhang W, Ng MCY, Petty LE, Kitajima H, Yu GZ, Rüeger S, Speidel L, Kim YJ, Horikoshi M, Mercader JM, Taliun D, Moon S, Kwak SH, Robertson NR, Rayner NW, Loh M, Kim BJ, Chiou J, Miguel-Escalada I, Della Briotta Parolo P, Lin K, Bragg F, Preuss MH, Takeuchi F, Nano J, Guo X, Lamri A, Nakatochi M, Scott RA, Lee JJ, Huerta-Chagoya A, Graff M, Chai JF, Parra EJ, Yao J, Bielak LF, Tabara Y, Hai Y, Steinthorsdottir V, Cook JP, Kals M, Grarup N, Schmidt EM, Pan I, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Long J, Sun M, Tong L, Chen WM, Ahmad M, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Lecoeur C, Prins BP, Nicolas A, Yanek LR, Chen G, Jensen RA, Tajuddin S, Kabagambe EK, An P, Xiang AH, Choi HS, Cade BE, Tan J, Flanagan J, Abaitua F, Adair LS, Adeyemo A, Aguilar-Salinas CA, Akiyama M, Anand SS, Bertoni A, Bian Z, Bork-Jensen J, Brandslund I, Brody JA, Brummett CM, Buchanan TA, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt KU, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Fornage M, Franco OH, Frayling TM, Freedman BI, Fuchsberger C, Genter P, Gerstein HC, Giedraitis V, González-Villalpando C, González-Villalpando ME, Goodarzi MO, Gordon-Larsen P, Gorkin D, Gross M, Guo Y, Hackinger S, Han S, Hattersley AT, Herder C, Howard AG, Hsueh W, Huang M, Huang W, Hung YJ, Hwang MY, Hwu CM, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang HM, Jasmine F, Jiang G, Jonas JB, Jørgensen ME, Jørgensen T, Kamatani Y, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor CC, Kibriya MG, Kim DH, Kohara K, Kriebel J, Kronenberg F, Kuusisto J, Läll K, Lange LA, Lee MS, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Ligthart S, Lindgren CM, Linneberg A, Liu CT, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lyssenko V, Mamakou V, Mani KR, Meitinger T, Metspalu A, Morris AD, Nadkarni GN, Nadler JL, Nalls MA, Nayak U, Nongmaithem SS, Ntalla I, Okada Y, Orozco L, Patel SR, Pereira MA, Peters A, Pirie FJ, Porneala B, Prasad G, Preissl S, Rasmussen-Torvik LJ, Reiner AP, Roden M, Rohde R, Roll K, Sabanayagam C, Sander M, Sandow K, Sattar N, Schönherr S, Schurmann C, Shahriar M, Shi J, Shin DM, Shriner D, Smith JA, So WY, Stančáková A, Stilp AM, Strauch K, Suzuki K, Takahashi A, Taylor KD, Thorand B, Thorleifsson G, Thorsteinsdottir U, Tomlinson B, Torres JM, Tsai FJ, Tuomilehto J, Tusie-Luna T, Udler MS, Valladares-Salgado A, van Dam RM, van Klinken JB, Varma R, Vujkovic M, Wacher-Rodarte N, Wheeler E, Whitsel EA, Wickremasinghe AR, van Dijk KW, Witte DR, Yajnik CS, Yamamoto K, Yamauchi T, Yengo L, Yoon K, Yu C, Yuan JM, Yusuf S, Zhang L, Zheng W, Raffel LJ, Igase M, Ipp E, Redline S, Cho YS, Lind L, Province MA, Hanis CL, Peyser PA, Ingelsson E, Zonderman AB, Psaty BM, Wang YX, Rotimi CN, Becker DM, Matsuda F, Liu Y, Zeggini E, Yokota M, Rich SS, Kooperberg C, Pankow JS, Engert JC, Chen YDI, Froguel P, Wilson JG, Sheu WHH, Kardia SLR, Wu JY, Hayes MG, Ma RCW, Wong TY, Groop L, Mook-Kanamori DO, Chandak GR, Collins FS, Bharadwaj D, Paré G, Sale MM, Ahsan H, Motala AA, Shu XO, Park KS, Jukema JW, Cruz M, McKean-Cowdin R, Grallert H, Cheng CY, Bottinger EP, Dehghan A, Tai ES, Dupuis J, Kato N, Laakso M, Köttgen A, Koh WP, Palmer CNA, Liu S, Abecasis G, Kooner JS, Loos RJF, North KE, Haiman CA, Florez JC, Saleheen D, Hansen T, Pedersen O, Mägi R, Langenberg C, Wareham NJ, Maeda S, Kadowaki T, Lee J, Millwood IY, Walters RG, Stefansson K, Myers SR, Ferrer J, Gaulton KJ, Meigs JB, Mohlke KL, Gloyn AL, Bowden DW, Below JE, Chambers JC, Sim X, Boehnke M, Rotter JI, McCarthy MI, Morris AP. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat Genet 2022; 54:560-572. [PMID: 35551307 PMCID: PMC9179018 DOI: 10.1038/s41588-022-01058-3] [Citation(s) in RCA: 215] [Impact Index Per Article: 107.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 03/23/2022] [Indexed: 02/02/2023]
Abstract
We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
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Affiliation(s)
- Anubha Mahajan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Genentech, South San Francisco, CA, USA.
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Epidemiology and Biostatistics, University of Massachusetts Amherst, Amherst, MA, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, London, UK
| | - Maggie C Y Ng
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hidetoshi Kitajima
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Cancer Center, Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Grace Z Yu
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Sina Rüeger
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Leo Speidel
- Genetics Institute, University College London, London, UK
- Francis Crick Institute, London, UK
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Josep M Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Daniel Taliun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Sanghoon Moon
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Soo-Heon Kwak
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Neil R Robertson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nigel W Rayner
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) and National University of Singapore (NUS), Singapore, Singapore
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Joshua Chiou
- Biomedical Sciences Graduate Studies Program, University of California San Diego, La Jolla, CA, USA
- Internal Medicine Research Unit, Pfizer Worldwide Research, Cambridge, MA, USA
| | - Irene Miguel-Escalada
- Regulatory Genomics and Diabetes, Centre for Genomic Regulation, the Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas asociadas (CIBERDEM), Madrid, Spain
| | | | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Fiona Bragg
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jana Nano
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Jung-Jin Lee
- Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Alicia Huerta-Chagoya
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Departamento de Medicina Genómica y Toxicologí, a AmbientalInstituto de Investigaciones Biomédicas, UNAM, Ciudad de Mexico, Mexico, Mexico
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, Ontario, Canada
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ellen M Schmidt
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ian Pan
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
| | - Tamar Sofer
- Department of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard University, Boston, MA, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Chloe Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Human Genetics, and Environmental Sciences, the University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
| | - Christian Gieger
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Darryl Nousome
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Meng Sun
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lin Tong
- Institute for Population and Precision Health, the University of Chicago, Chicago, IL, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Meraj Ahmad
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Victor J Y Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, the Chinese University of Hong Kong, Hong Kong, China
| | - Yoonjung Yoonie Joo
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Institute of Data Science, Korea University, Seoul, South Korea
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Cécile Lecoeur
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
| | - Bram Peter Prins
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Richard A Jensen
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Salman Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Edmond K Kabagambe
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Academics, Ochsner Health, New Orleans, LA, USA
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Anny H Xiang
- Department of Research and Evaluation, Division of Biostatistics Research, Kaiser Permanente of Southern California, Pasadena, CA, USA
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Brian E Cade
- Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jack Flanagan
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Fernando Abaitua
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Vertex Pharmaceuticals Ltd, Oxford, UK
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adebowale Adeyemo
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carlos A Aguilar-Salinas
- Unidad de Investigación en Enfermedades Metabólicas and Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Masato Akiyama
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Sonia S Anand
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Zheng Bian
- Chinese Academy of Medical Sciences, Beijing, China
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Brandslund
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Chad M Brummett
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Thomas A Buchanan
- Department of Medicine, Division of Endocrinology and Diabetes, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Mickaël Canouil
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, the Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, the Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, the Chinese University of Hong Kong, Hong Kong, China
| | - Li-Ching Chang
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ji Chen
- Wellcome Sanger Institute, Hinxton, UK
- Exeter Centre of Excellence in Diabetes (ExCEeD), Exeter Medical School, University of Exeter, Exeter, UK
| | - Shyh-Huei Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lee-Ming Chuang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Mary Cushman
- Department of Medicine, University of Vermont, Colchester, VT, USA
| | - Swapan K Das
- Section on Endocrinology and Metabolism, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shufa Du
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Leslie S Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Barry I Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Christian Fuchsberger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
| | - Pauline Genter
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Maria Elena González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Mark O Goodarzi
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - David Gorkin
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing, China
| | - Sophie Hackinger
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | | | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Annie-Green Howard
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Willa Hsueh
- Department of Internal Medicine, Diabetes and Metabolism Research Center, the Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Mengna Huang
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | | | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Farzana Jasmine
- Institute for Population and Precision Health, the University of Chicago, Chicago, IL, USA
| | - Guozhi Jiang
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, the Chinese University of Hong Kong, Hong Kong, China
| | - Jost B Jonas
- Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
| | - Marit E Jørgensen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- National Institute of Public Health, Southern Denmark University, Copenhagen, Denmark
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Fouad R Kandeel
- Department of Clinical Diabetes, Endocrinology & Metabolism, Department of Translational Research and Cellular Therapeutics, City of Hope, Duarte, CA, USA
| | | | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Varinderpal Kaur
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Jacob M Keaton
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Abel N Kho
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Muhammad G Kibriya
- Institute for Population and Precision Health, the University of Chicago, Chicago, IL, USA
| | - Duk-Hwan Kim
- Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, South Korea
| | - Katsuhiko Kohara
- Department of Regional Resource Management, Ehime University Faculty of Collaborative Regional Innovation, Ehime, Japan
- Ibusuki Kozenkai Hospital, Ibusuki, Japan
| | - Jennifer Kriebel
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Myung-Shik Lee
- Severance Biomedical Science Institute and Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
| | - Aaron Leong
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, Peking University Health Science Centre, Peking University, Beijing, China
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Symen Ligthart
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Adam E Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St Louis, MO, USA
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Andrea O Luk
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, the Chinese University of Hong Kong, Hong Kong, China
| | - Xi Luo
- Department of Biostatistics and Data Science, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jun Lv
- Department of Epidemiology and Biostatistics, Peking University Health Science Centre, Peking University, Beijing, China
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway
| | - Vasiliki Mamakou
- Dromokaiteio Psychiatric Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - K Radha Mani
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technical University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andrew D Morris
- The Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Digital Health Center, Digital Engineering Faculty of Hasso Plattner Institue and University Potsdam, Potsdam, Germany
- The Division of Data Driven and Digital Medicine (D3M), Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jerry L Nadler
- Department of Medicine and Pharmacology, New York Medical College, Valhalla, NY, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Baltimore, MD, USA
| | - Uma Nayak
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Suraj S Nongmaithem
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Osaka, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Sanjay R Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark A Pereira
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Annette Peters
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Fraser J Pirie
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Centre Campus, Ghaziabad, India
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Michael Roden
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kathryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Maike Sander
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Digital Health Center, Digital Engineering Faculty of Hasso Plattner Institue and University Potsdam, Potsdam, Germany
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mohammad Shahriar
- Institute for Population and Precision Health, the University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, the University of Chicago, Chicago, IL, USA
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Dong Mun Shin
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wing Yee So
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, the Chinese University of Hong Kong, Hong Kong, China
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Konstantin Strauch
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Ken Suzuki
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Atsushi Takahashi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Genomic Medicine, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Barbara Thorand
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Unnur Thorsteinsdottir
- deCODE Genetics, Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Reykjavik, Reykjavik, Iceland
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Jason M Torres
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Fuu-Jen Tsai
- Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jaakko Tuomilehto
- Department of Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- National School of Public Health, Madrid, Spain
- Department of Neuroscience and Preventive Medicine, Danube University Krems, Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Teresa Tusie-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Departamento de Medicina Genómica y Toxiología, Ambiental Instituto de Investigaciones Biomédicas, UNAM, Mexico City, Mexico
| | - Miriam S Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, IMSS, Mexico City, Mexico
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jan B van Klinken
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Clinical Chemistry, Laboratory of Genetic Metabolic Disease, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA
| | - Marijana Vujkovic
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Niels Wacher-Rodarte
- Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, IMSS, Mexico City, Mexico
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Ko Willems van Dijk
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Chittaranjan S Yajnik
- Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Ken Yamamoto
- Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, Japan
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Loïc Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, Peking University Health Science Centre, Peking University, Beijing, China
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Leslie J Raffel
- Department of Pediatrics, Division of Genetic and Genomic Medicine, UCI Irvine School of Medicine, Irvine, CA, USA
| | - Michiya Igase
- Department of Anti-Aging Medicine, Ehime University Graduate School of Medicine, Ehime, Japan
| | - Eli Ipp
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Susan Redline
- Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Michael A Province
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Craig L Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Ophthalmology and Visual Sciences Key Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Diane M Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | - Eleftheria Zeggini
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | | | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - James C Engert
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Philippe Froguel
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes, Institut Pasteur de Lille, Lille, France
- University of Lille, Lille University Hospital, Lille, France
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Wayne H H Sheu
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - M Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Anthropology, Northwestern University, Evanston, IL, USA
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, the Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, the Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, the Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, the Chinese University of Hong Kong, Hong Kong, China
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Leif Groop
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Giriraj R Chandak
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Centre Campus, Ghaziabad, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Michèle M Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Habibul Ahsan
- Institute for Population and Precision Health, the University of Chicago, Chicago, IL, USA
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyong-Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, IMSS, Mexico City, Mexico
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Harald Grallert
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Digital Health Center, Digital Engineering Faculty of Hasso Plattner Institue and University Potsdam, Potsdam, Germany
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Woon-Puay Koh
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, University of Dundee, Dundee, UK
| | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
- Department of Medicine, Brown University Alpert School of Medicine, Providence, RI, USA
| | - Goncalo Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher A Haiman
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Danish Saleheen
- Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité Universitätsmedizin, Berlin, Germany
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Shiro Maeda
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Toranomon Hospital, Tokyo, Japan
| | - Juyoung Lee
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Republic of Korea
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kari Stefansson
- deCODE Genetics, Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Reykjavik, Reykjavik, Iceland
| | - Simon R Myers
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Jorge Ferrer
- Regulatory Genomics and Diabetes, Centre for Genomic Regulation, the Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas asociadas (CIBERDEM), Madrid, Spain
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Kyle J Gaulton
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - James B Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Division of Endocrinology, Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, the Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
- Genentech, South San Francisco, CA, USA.
| | - Andrew P Morris
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Department of Health Data Science, University of Liverpool, Liverpool, UK.
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK.
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK.
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11
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Choe EK, Shivakumar M, Verma A, Verma SS, Choi SH, Kim JS, Kim D. Leveraging deep phenotyping from health check-up cohort with 10,000 Korean individuals for phenome-wide association study of 136 traits. Sci Rep 2022; 12:1930. [PMID: 35121771 PMCID: PMC8817039 DOI: 10.1038/s41598-021-04580-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 12/17/2021] [Indexed: 11/09/2022] Open
Abstract
The expanding use of the phenome-wide association study (PheWAS) faces challenges in the context of using International Classification of Diseases billing codes for phenotype definition, imbalanced study population ethnicity, and constrained application of the results in research. We performed a PheWAS utilizing 136 deep phenotypes corroborated by comprehensive health check-ups in a Korean population, along with trans-ethnic comparisons through using the UK Biobank and Biobank Japan Project. Meta-analysis with Korean and Japanese population was done. The PheWAS associated 65 phenotypes with 14,101 significant variants (P < 4.92 × 10-10). Network analysis, visualization of cross-phenotype mapping, and causal inference mapping with Mendelian randomization were conducted. Among phenotype pairs from the genotype-driven cross-phenotype associations, we evaluated penetrance in correlation analysis using a clinical database. We focused on the application of PheWAS in order to make it robust and to aid the derivation of biological meaning post-PheWAS. This comprehensive analysis of PheWAS results based on a health check-up database will provide researchers and clinicians with a panoramic overview of the networks among multiple phenotypes and genetic variants, laying groundwork for the practical application of precision medicine.
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Affiliation(s)
- Eun Kyung Choe
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, B304 Richards Building, 3700 Hamilton Walk, Philadelphia, PA, 19104-6116, USA.,Department of Surgery, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, 06236, South Korea
| | - Manu Shivakumar
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, B304 Richards Building, 3700 Hamilton Walk, Philadelphia, PA, 19104-6116, USA
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Shefali Setia Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Seung Ho Choi
- Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, 06236, South Korea
| | - Joo Sung Kim
- Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, 06236, South Korea. .,Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, 03080, South Korea.
| | - Dokyoon Kim
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, B304 Richards Building, 3700 Hamilton Walk, Philadelphia, PA, 19104-6116, USA. .,Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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12
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Ortega VE, Daya M, Szefler SJ, Bleecker ER, Chinchilli VM, Phipatanakul W, Mauger D, Martinez FD, Herrera-Luis E, Pino-Yanes M, Hawkins GA, Ampleford EJ, Kunselman SJ, Cox C, Bacharier LB, Cabana MD, Cardet JC, Castro M, Denlinger LC, Eng C, Fitzpatrick AM, Holguin F, Hu D, Jackson DJ, Jarjour N, Kraft M, Krishnan JA, Lazarus SC, Lemanske RF, Lima JJ, Lugogo N, Mak A, Moore WC, Naureckas ET, Peters SP, Pongracic JA, Sajuthi SP, Seibold MA, Smith LJ, Solway J, Sorkness CA, Wenzel S, White SR, Burchard EG, Barnes K, Meyers DA, Israel E, Wechsler ME. Pharmacogenetic studies of long-acting beta agonist and inhaled corticosteroid responsiveness in randomised controlled trials of individuals of African descent with asthma. THE LANCET. CHILD & ADOLESCENT HEALTH 2021; 5:862-872. [PMID: 34762840 PMCID: PMC8787857 DOI: 10.1016/s2352-4642(21)00268-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Pharmacogenetic studies in asthma cohorts, primarily made up of White people of European descent, have identified loci associated with response to inhaled beta agonists and corticosteroids (ICSs). Differences exist in how individuals from different ancestral backgrounds respond to long-acting beta agonist (LABA) and ICSs. Therefore, we sought to understand the pharmacogenetic mechanisms regulating therapeutic responsiveness in individuals of African descent. METHODS We did ancestry-based pharmacogenetic studies of children (aged 5-11 years) and adolescents and adults (aged 12-69 years) from the Best African Response to Drug (BARD) trials, in which participants with asthma uncontrolled with low-dose ICS (fluticasone propionate 50 μg in children, 100 μg in adolescents and adults) received different step-up combination therapies. The hierarchal composite outcome of pairwise superior responsiveness in BARD was based on asthma exacerbations, a 31-day difference in annualised asthma-control days, or a 5% difference in percentage predicted FEV1. We did whole-genome admixture mapping of 15 159 ancestral segments within 312 independent regions, stratified by the two age groups. The two co-primary outcome comparisons were the step up from low-dose ICS to the quintuple dose of ICS (5 × ICS: 250 μg twice daily in children and 500 μg twice daily in adolescents and adults) versus double dose (2-2·5 × ICS: 100 μg twice daily in children, 250 μg twice daily in adolescents and adults), and 5 × ICS versus 100 μg fluticasone plus a LABA (salmeterol 50 μg twice daily). We used a genome-wide significance threshold of p<1·6 × 10-4, and tested for replication using independent cohorts of individuals of African descent with asthma. FINDINGS We included 249 unrelated children and 267 unrelated adolescents and adults in the BARD pharmacogenetic analysis. In children, we identified a significant admixture mapping peak for superior responsiveness to 5 × ICS versus 100 μg fluticasone plus salmeterol on chromosome 12 (odds ratio [ORlocal African] 3·95, 95% CI 2·02-7·72, p=6·1 × 10-5) fine mapped to a locus adjacent to RNFT2 and NOS1 (rs73399224, ORallele dose 0·17, 95% CI 0·07-0·42, p=8·4 × 10-5). In adolescents and adults, we identified a peak for superior responsiveness to 5 × ICS versus 2·5 × ICS on chromosome 22 (ORlocal African 3·35, 1·98-5·67, p=6·8 × 10-6) containing a locus adjacent to TPST2 (rs5752429, ORallele dose 0·21, 0·09-0·52, p=5·7 × 10-4). We replicated rs5752429 and nominally replicated rs73399224 in independent African American cohorts. INTERPRETATION BARD is the first genome-wide pharmacogenetic study of LABA and ICS response in clinical trials of individuals of African descent to detect and replicate genome-wide significant loci. Admixture mapping of the composite BARD trial outcome enabled the identification of novel pharmacogenetic variation accounting for differential therapeutic responses in people of African descent with asthma. FUNDING National Institutes of Health, National Heart, Lung, and Blood Institute.
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Affiliation(s)
- Victor E Ortega
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA.
| | - Michelle Daya
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Stanley J Szefler
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Eugene R Bleecker
- Department of Internal Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Vernon M Chinchilli
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Wanda Phipatanakul
- Division of Pediatric Allergy and Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Dave Mauger
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Fernando D Martinez
- Asthma and Airway Disease Research Center, University of Arizona Health Sciences, Tucson, AZ, USA
| | - Esther Herrera-Luis
- Department of Biochemistry, La Laguna, Tenerife, Spain; Microbiology, Cell Biology, and Genetics, La Laguna, Tenerife, Spain; Genomics and Health Group, La Laguna, Tenerife, Spain; Universidad de La Laguna, La Laguna, Tenerife, Spain
| | - Maria Pino-Yanes
- Department of Biochemistry, La Laguna, Tenerife, Spain; Microbiology, Cell Biology, and Genetics, La Laguna, Tenerife, Spain; Genomics and Health Group, La Laguna, Tenerife, Spain; Universidad de La Laguna, La Laguna, Tenerife, Spain; CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Gregory A Hawkins
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Elizabeth J Ampleford
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Susan J Kunselman
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Corey Cox
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Leonard B Bacharier
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Michael D Cabana
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Juan Carlos Cardet
- Department of Internal Medicine, Division of Allergy and Immunology, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Mario Castro
- Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Kansas Medical Center, Kansas City, KS, USA
| | - Loren C Denlinger
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | - Fernando Holguin
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Donglei Hu
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Daniel J Jackson
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - Nizar Jarjour
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Monica Kraft
- Department of Internal Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Jerry A Krishnan
- Breathe Chicago Center, Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois, Chicago, IL, USA
| | - Stephen C Lazarus
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Robert F Lemanske
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - John J Lima
- Center for Pharmacogenomics and Translational Research, Nemours Children's Health System, Jacksonville, FL, USA
| | - Njira Lugogo
- Department of Medicine, Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA
| | - Angel Mak
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Wendy C Moore
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Stephen P Peters
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jacqueline A Pongracic
- Department of Pediatrics, Ann & Robert H Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Satria P Sajuthi
- Center for Genes, Environment, and Health, Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Max A Seibold
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA; Center for Genes, Environment, and Health, Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Lewis J Smith
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Julian Solway
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Christine A Sorkness
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Sally Wenzel
- Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Steven R White
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Kathleen Barnes
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Deborah A Meyers
- Department of Internal Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Elliot Israel
- Department of Pulmonary and Critical Care Medicine and Allergy and Immunology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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13
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Lee CY, Zeng JH, Lee SY, Lu RB, Kuo PH. SNP Data Science for Classification of Bipolar Disorder I and Bipolar Disorder II. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021; 18:2862-2869. [PMID: 32324560 DOI: 10.1109/tcbb.2020.2988024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Bipolar disorder I (BD-I) and bipolar disorder II (BD-II) have specific characteristics and clear diagnostic criteria, but quite different treatment guidelines. In clinical practice, BD-II is commonly mistaken as a mild form of BD-I. This study uses data science technique to identify the important Single Nucleotide Polymorphisms (SNPs) significantly affecting the classifications of BD-I and BD-II, and develops a set of complementary diagnostic classifiers to enhance the diagnostic process. Screening assessments and SNP genotypes of 316 Han Chinese were performed with the Affymetrix Axiom Genome-Wide TWB Array Plate. The results show that the classifier constructed by 23 SNPs reached the area under curve of ROC (AUC) level of 0.939, while the classifier constructed by 42 SNPs reached the AUC level of 0.9574, which is a mere addition of 1.84 percent. The accuracy rate of classification increased by 3.46 percent. This study also uses Gene Ontology (GO) and Pathway to conduct a functional analysis and identify significant items, including calcium ion binding, GABA-A receptor activity, Rap1 signaling pathway, ECM proteoglycans, IL12-mediated signaling events, Nicotine addiction), and PI3K-Akt signaling pathway. The study can address time-consuming SNPs identification and also quantify the effect of SNP-SNP interactions.
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14
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Tekeu H, Ngonkeu ELM, Bélanger S, Djocgoué PF, Abed A, Torkamaneh D, Boyle B, Tsimi PM, Tadesse W, Jean M, Belzile F. GWAS identifies an ortholog of the rice D11 gene as a candidate gene for grain size in an international collection of hexaploid wheat. Sci Rep 2021; 11:19483. [PMID: 34593838 PMCID: PMC8484655 DOI: 10.1038/s41598-021-98626-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 08/09/2021] [Indexed: 12/26/2022] Open
Abstract
Grain size is a key agronomic trait that contributes to grain yield in hexaploid wheat. Grain length and width were evaluated in an international collection of 157 wheat accessions. These accessions were genetically characterized using a genotyping-by-sequencing (GBS) protocol that produced 73,784 single nucleotide polymorphism (SNP) markers. GBS-derived genotype calls obtained on Chinese Spring proved extremely accurate when compared to the reference (> 99.9%) and showed > 95% agreement with calls made at SNP loci shared with the 90 K SNP array on a subset of 71 Canadian wheat accessions for which both types of data were available. This indicates that GBS can yield a large amount of highly accurate SNP data in hexaploid wheat. The genetic diversity analysis performed using this set of SNP markers revealed the presence of six distinct groups within this collection. A GWAS was conducted to uncover genomic regions controlling variation for grain length and width. In total, seven SNPs were found to be associated with one or both traits, identifying three quantitative trait loci (QTLs) located on chromosomes 1D, 2D and 4A. In the vicinity of the peak SNP on chromosome 2D, we found a promising candidate gene (TraesCS2D01G331100), whose rice ortholog (D11) had previously been reported to be involved in the regulation of grain size. These markers will be useful in breeding for enhanced wheat productivity.
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Affiliation(s)
- Honoré Tekeu
- Département de Phytologie, Université Laval, Quebec City, QC, Canada.,Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada.,Department of Plant Biology, University of Yaoundé I, Yaoundé, Cameroon
| | - Eddy L M Ngonkeu
- Institute of Agricultural Research for Development, Yaoundé, Cameroon.,Department of Plant Biology, University of Yaoundé I, Yaoundé, Cameroon
| | - Sébastien Bélanger
- Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada.,Donald Danforth Plant Science Center, St. Louis, MO, USA
| | - Pierre F Djocgoué
- Department of Plant Biology, University of Yaoundé I, Yaoundé, Cameroon
| | - Amina Abed
- Département de Phytologie, Université Laval, Quebec City, QC, Canada.,Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Quebec City, QC, Canada.,Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada.,Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Brian Boyle
- Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada
| | - Patrick M Tsimi
- Department of Plant Biology, University of Yaoundé I, Yaoundé, Cameroon
| | - Wuletaw Tadesse
- International Center for Agricultural Research in the Dry Areas (ICARDA), Beirut, Lebanon
| | - Martine Jean
- Département de Phytologie, Université Laval, Quebec City, QC, Canada.,Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC, Canada. .,Institut de Biologie Intégrative et des Systèmes, Université Laval, Quebec City, QC, Canada.
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15
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A high-resolution genome-wide association study of the grain ionome and agronomic traits in rice Oryza sativa subsp. indica. Sci Rep 2021; 11:19230. [PMID: 34584121 PMCID: PMC8478900 DOI: 10.1038/s41598-021-98573-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/09/2021] [Indexed: 02/08/2023] Open
Abstract
This study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight. GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 linked to the locus that controls the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on multiple grain elements were elucidated through the likely involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.
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16
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Vergara C, Valencia A, Thio CL, Goedert JJ, Mangia A, Piazzolla V, Johnson E, Kral AH, O’Brien TR, Mehta SH, Kirk GD, Kim AY, Lauer GM, Chung RT, Cox AL, Peters MG, Khakoo SI, Alric L, Cramp ME, Donfield SM, Edlin BR, Busch MP, Alexander G, Rosen HR, Murphy EL, Wojcik GL, Taub MA, Thomas DL, Duggal P. A Multiancestry Sex-Stratified Genome-Wide Association Study of Spontaneous Clearance of Hepatitis C Virus. J Infect Dis 2021; 223:2090-2098. [PMID: 33119750 PMCID: PMC8205624 DOI: 10.1093/infdis/jiaa677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 10/28/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Spontaneous clearance of acute hepatitis C virus (HCV) infection is more common in women than in men, independent of known risk factors. METHODS To identify sex-specific genetic loci, we studied 4423 HCV-infected individuals (2903 male, 1520 female) of European, African, and Hispanic ancestry. We performed autosomal, and X chromosome sex-stratified and combined association analyses in each ancestry group. RESULTS A male-specific region near the adenosine diphosphate-ribosylation factor-like 5B (ARL5B) gene was identified. Individuals with the C allele of rs76398191 were about 30% more likely to have chronic HCV infection than individuals with the T allele (OR, 0.69; P = 1.98 × 10-07), and this was not seen in females. The ARL5B gene encodes an interferon-stimulated gene that inhibits immune response to double-stranded RNA viruses. We also identified suggestive associations near septin 6 and ribosomal protein L39 genes on the X chromosome. In box sexes, allele G of rs12852885 was associated with a 40% increase in HCV clearance compared with the A allele (OR, 1.4; P = 2.46 × 10-06). Septin 6 facilitates HCV replication via interaction with the HCV NS5b protein, and ribosomal protein L39 acts as an HCV core interactor. CONCLUSIONS These novel gene associations support differential mechanisms of HCV clearance between the sexes and provide biological targets for treatment or vaccine development.
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Affiliation(s)
- Candelaria Vergara
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Ana Valencia
- Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
- Universidad Pontificia Bolivariana, Medellín, Colombia
| | - Chloe L Thio
- Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
| | - James J Goedert
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Alessandra Mangia
- Liver Unit IRCCS “Casa Sollievo della Sofferenza,” San Giovanni Rotondo, Italy
| | - Valeria Piazzolla
- Liver Unit IRCCS “Casa Sollievo della Sofferenza,” San Giovanni Rotondo, Italy
| | - Eric Johnson
- RTI International, Research Triangle Park, North Carolina, USA
| | - Alex H Kral
- RTI International, Research Triangle Park, North Carolina, USA
| | - Thomas R O’Brien
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Shruti H Mehta
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Gregory D Kirk
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA
- Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
| | - Arthur Y Kim
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Georg M Lauer
- Liver Center and Gastrointestinal Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Raymond T Chung
- Liver Center and Gastrointestinal Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Andrea L Cox
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Marion G Peters
- Division of Gastroenterology, Department of Medicine, School of Medicine, University of California, San Francisco, California, USA
| | - Salim I Khakoo
- University of Southampton, Southampton General Hospital, Southampton, United Kingdom
| | - Laurent Alric
- Department of Internal Medicine and Digestive Diseases, CHU Rangueil, UMR 152 IRD, Toulouse 3 University, France
| | | | | | - Brian R Edlin
- SUNY Downstate College of Medicine, Brooklyn, New York, USA
| | - Michael P Busch
- University of California and Vitalant Research Institute, San Francisco, California, USA
| | - Graeme Alexander
- UCL Institute for Liver and Digestive Health, Royal Free Hospital, Hampstead, London, United Kingdom
| | | | - Edward L Murphy
- University of California and Vitalant Research Institute, San Francisco, California, USA
| | - Genevieve L Wojcik
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Margaret A Taub
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - David L Thomas
- Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
| | - Priya Duggal
- Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA
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17
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Goddard PC, Keys KL, Mak ACY, Lee EY, Liu AK, Samedy-Bates LA, Risse-Adams O, Contreras MG, Elhawary JR, Hu D, Huntsman S, Oh SS, Salazar S, Eng C, Himes BE, White MJ, Burchard EG. Integrative genomic analysis in African American children with asthma finds three novel loci associated with lung function. Genet Epidemiol 2021; 45:190-208. [PMID: 32989782 PMCID: PMC7902343 DOI: 10.1002/gepi.22365] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 08/21/2020] [Accepted: 09/14/2020] [Indexed: 11/06/2022]
Abstract
Bronchodilator (BD) drugs are commonly prescribed for treatment and management of obstructive lung function present with diseases such as asthma. Administration of BD medication can partially or fully restore lung function as measured by pulmonary function tests. The genetics of baseline lung function measures taken before BD medication have been extensively studied, and the genetics of the BD response itself have received some attention. However, few studies have focused on the genetics of post-BD lung function. To address this gap, we analyzed lung function phenotypes in 1103 subjects from the Study of African Americans, Asthma, Genes, and Environment, a pediatric asthma case-control cohort, using an integrative genomic analysis approach that combined genotype, locus-specific genetic ancestry, and functional annotation information. We integrated genome-wide association study (GWAS) results with an admixture mapping scan of three pulmonary function tests (forced expiratory volume in 1 s [FEV1 ], forced vital capacity [FVC], and FEV1 /FVC) taken before and after albuterol BD administration on the same subjects, yielding six traits. We identified 18 GWAS loci, and five additional loci from admixture mapping, spanning several known and novel lung function candidate genes. Most loci identified via admixture mapping exhibited wide variation in minor allele frequency across genotyped global populations. Functional fine-mapping revealed an enrichment of epigenetic annotations from peripheral blood mononuclear cells, fetal lung tissue, and lung fibroblasts. Our results point to three novel potential genetic drivers of pre- and post-BD lung function: ADAMTS1, RAD54B, and EGLN3.
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Affiliation(s)
- Pagé C. Goddard
- Department of Genetics, Stanford University, Stanford, California, USA
- Department of Medicine, University of California, San Francisco, California, USA
| | - Kevin L. Keys
- Department of Medicine, University of California, San Francisco, California, USA
- Berkeley Institute for Data Science, University of California, Berkeley, California, USA
| | - Angel C. Y. Mak
- Department of Medicine, University of California, San Francisco, California, USA
| | - Eunice Y. Lee
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
| | - Amy K. Liu
- Department of Neurology, University of California, San Francisco, California, USA
| | - Lesly-Anne Samedy-Bates
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
| | - Oona Risse-Adams
- Department of Medicine, University of California, San Francisco, California, USA
- Department of Biology, University of California, Santa Cruz, California, USA
| | - María G. Contreras
- Department of Medicine, University of California, San Francisco, California, USA
- Department of Biology, San Francisco State University, San Francisco, California, USA
| | - Jennifer R. Elhawary
- Department of Medicine, University of California, San Francisco, California, USA
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, California, USA
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, California, USA
| | - Sam S. Oh
- Department of Medicine, University of California, San Francisco, California, USA
| | - Sandra Salazar
- Department of Medicine, University of California, San Francisco, California, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, California, USA
| | - Blanca E. Himes
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Marquitta J. White
- Department of Medicine, University of California, San Francisco, California, USA
| | - Esteban G. Burchard
- Department of Medicine, University of California, San Francisco, California, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
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18
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Herrera-Luis E, Lorenzo-Diaz F, Samedy-Bates LA, Eng C, Villar J, Rodriguez-Santana JR, Burchard EG, Pino-Yanes M. A deoxyribonuclease 1-like 3 genetic variant associates with asthma exacerbations. J Allergy Clin Immunol 2021; 147:1095-1097.e10. [PMID: 33035569 PMCID: PMC7940549 DOI: 10.1016/j.jaci.2020.09.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 09/18/2020] [Accepted: 09/23/2020] [Indexed: 10/23/2022]
Abstract
The analysis of genetic variants from six genes whose expression is predictive of asthma exacerbations revealed a novel association of a regulatory polymorphism from DNASE1L3 in African-Americans and Latinos.
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Affiliation(s)
- Esther Herrera-Luis
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
| | - Fabian Lorenzo-Diaz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
| | - Lesly-Anne Samedy-Bates
- Department of Medicine, University of California San Francisco, San Francisco, Calif; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, Calif
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, Calif
| | - Jesús Villar
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain; Multidisciplinary Organ Dysfunction Evaluation Research Network, Research Unit, Hospital Universitario Dr Negrín, Las Palmas de Gran Canaria, Spain; Keenan Research Center for Biomedical Science at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | | | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, Calif; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, Calif
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain; Instituto de Tecnologías Biomédicas, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain.
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19
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Novel directions in data pre-processing and genome-wide association study (GWAS) methodologies to overcome ongoing challenges. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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20
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Spear ML, Diaz-Papkovich A, Ziv E, Yracheta JM, Gravel S, Torgerson DG, Hernandez RD. Recent shifts in the genomic ancestry of Mexican Americans may alter the genetic architecture of biomedical traits. eLife 2020; 9:e56029. [PMID: 33372659 PMCID: PMC7771964 DOI: 10.7554/elife.56029] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 12/13/2020] [Indexed: 11/13/2022] Open
Abstract
People in the Americas represent a diverse continuum of populations with varying degrees of admixture among African, European, and Amerindigenous ancestries. In the United States, populations with non-European ancestry remain understudied, and thus little is known about the genetic architecture of phenotypic variation in these populations. Using genotype data from the Hispanic Community Health Study/Study of Latinos, we find that Amerindigenous ancestry increased by an average of ~20% spanning 1940s-1990s in Mexican Americans. These patterns result from complex interactions between several population and cultural factors which shaped patterns of genetic variation and influenced the genetic architecture of complex traits in Mexican Americans. We show for height how polygenic risk scores based on summary statistics from a European-based genome-wide association study perform poorly in Mexican Americans. Our findings reveal temporal changes in population structure within Hispanics/Latinos that may influence biomedical traits, demonstrating a need to improve our understanding of admixed populations.
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Affiliation(s)
- Melissa L Spear
- Biomedical Sciences Graduate Program, University of California, San FranciscoSan FranciscoUnited States
- Department of Bioengineering and Therapeutic Sciences, University of California, San FranciscoSan FranciscoUnited States
- McGill Genome Centre, McGill UniversityMontrealCanada
- Department of Human Genetics, McGill UniversityMontrealCanada
| | - Alex Diaz-Papkovich
- McGill Genome Centre, McGill UniversityMontrealCanada
- Quantitative Life Sciences Program, McGill UniversityMontrealCanada
| | - Elad Ziv
- Division of General Internal Medicine, University of California, San FranciscoSan FranciscoUnited States
- Department of Medicine, University of California, San FranciscoSan FranciscoUnited States
- Institute of Human Genetics, University of California, San FranciscoSan FranciscoUnited States
- Helen Diller Family Comprehensive Cancer Center, University of California, San FranciscoSan FranciscoUnited States
| | - Joseph M Yracheta
- Native BioData ConsortiumEagle ButteUnited States
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | - Simon Gravel
- McGill Genome Centre, McGill UniversityMontrealCanada
- Department of Human Genetics, McGill UniversityMontrealCanada
| | - Dara G Torgerson
- McGill Genome Centre, McGill UniversityMontrealCanada
- Department of Human Genetics, McGill UniversityMontrealCanada
- Department of Epidemiology and Biostatistics University of California, San FranciscoSan FranciscoUnited States
| | - Ryan D Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California, San FranciscoSan FranciscoUnited States
- McGill Genome Centre, McGill UniversityMontrealCanada
- Department of Human Genetics, McGill UniversityMontrealCanada
- Institute of Human Genetics, University of California, San FranciscoSan FranciscoUnited States
- Bakar Computational Health Sciences Institute, University of California, San FranciscoSan FranciscoUnited States
- Quantitative Biosciences Institute, University of California, San FranciscoSan FranciscoUnited States
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21
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Multini LC, de Souza ALDS, Marrelli MT, Wilke ABB. The influence of anthropogenic habitat fragmentation on the genetic structure and diversity of the malaria vector Anopheles cruzii (Diptera: Culicidae). Sci Rep 2020; 10:18018. [PMID: 33093465 PMCID: PMC7581522 DOI: 10.1038/s41598-020-74152-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 09/10/2020] [Indexed: 12/27/2022] Open
Abstract
Fragmentation of natural environments as a result of human interference has been associated with a decrease in species richness and increase in abundance of a few species that have adapted to these environments. The Brazilian Atlantic Forest, which has been undergoing an intense process of fragmentation and deforestation caused by human-made changes to the environment, is an important hotspot for malaria transmission. The main vector of simian and human malaria in this biome is the mosquito Anopheles cruzii. Anthropogenic processes reduce the availability of natural resources at the tree canopies, An. cruzii primary habitat. As a consequence, An. cruzii moves to the border of the Atlantic Forest nearing urban areas seeking resources, increasing their contact with humans in the process. We hypothesized that different levels of anthropogenic changes to the environment can be an important factor in driving the genetic structure and diversity in An. cruzii populations. Five different hypotheses using a cross-sectional and a longitudinal design were tested to assess genetic structure in sympatric An. cruzii populations and microevolutionary processes driving these populations. Single nucleotide polymorphisms were used to assess microgeographic genetic structure in An. cruzii populations in a low-endemicity area in the city of São Paulo, Brazil. Our results show an overall weak genetic structure among the populations, indicating a high gene flow system. However, our results also pointed to the presence of significant genetic structure between sympatric An. cruzii populations collected at ground and tree-canopy habitats in the urban environment and higher genetic variation in the ground-level population. This indicates that anthropogenic modifications leading to habitat fragmentation and a higher genetic diversity and structure in ground-level populations could be driving the behavior of An. cruzii, ultimately increasing its contact with humans. Understanding how anthropogenic changes in natural areas affect An. cruzii is essential for the development of more effective mosquito control strategies and, on a broader scale, for malaria-elimination efforts in the Brazilian Atlantic Forest.
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Affiliation(s)
- Laura Cristina Multini
- Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, SP, Brazil
| | | | - Mauro Toledo Marrelli
- Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, SP, Brazil
- São Paulo Institute of Tropical Medicine, University of São Paulo, São Paulo, SP, Brazil
| | - André Barretto Bruno Wilke
- Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, SP, Brazil.
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, 1120 Northwest 14th Street, Miami, FL, 33136, USA.
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22
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Wang Z, Greenbaum J, Qiu C, Li K, Wang Q, Tang SY, Deng HW. Identification of pleiotropic genes between risk factors of stroke by multivariate metaCCA analysis. Mol Genet Genomics 2020; 295:1173-1185. [PMID: 32474671 DOI: 10.1007/s00438-020-01692-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Accepted: 05/25/2020] [Indexed: 12/11/2022]
Abstract
Genome-wide association studies (GWASs) have identified more than 20 genetic loci as risk predictors associated with stroke. However, these studies were generally performed for single-trait and failed to consider the pleiotropic effects of these risk genes among the multiple risk factors for stroke. In this study, we applied a novel metaCCA method followed by gene-based VEGAS2 analysis to identify the risk genes for stroke that may overlap between seven correlated risk factors (including atrial fibrillation, hypertension, coronary artery disease, heart failure, diabetes, body mass index, and total cholesterol level) by integrating seven corresponding GWAS data. We detected 20 potential pleiotropic genes that may be associated with multiple risk factors of stroke. Furthermore, using gene-to-trait pathway analysis, we suggested six potential risk genes (FUT8, GMIP, PLA2G6, PDE3A, SMARCA4, SKAPT) that may affect ischemic or hemorrhage stroke through multiple intermediate factors such as MAPK family. These findings provide novel insight into the genetic determinants contributing to the concurrent development of biological conditions that may influence stroke susceptibility, and also indicate some potential therapeutic targets that can be further studied for the prevention of cerebrovascular disease.
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Affiliation(s)
- Zun Wang
- Xiangya Nursing School, Central South University, Changsha, 410013, China.,Department of Global Biostatistics and Data Science, Tulane Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Jonathan Greenbaum
- Department of Global Biostatistics and Data Science, Tulane Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Chuan Qiu
- Department of Global Biostatistics and Data Science, Tulane Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Kelvin Li
- Department of Global Biostatistics and Data Science, Tulane Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Qian Wang
- Xiangya Nursing School, Central South University, Changsha, 410013, China
| | - Si-Yuan Tang
- Xiangya Nursing School, Central South University, Changsha, 410013, China.,Hunan Women's Research Association, Changsha, 410011, China
| | - Hong-Wen Deng
- Department of Global Biostatistics and Data Science, Tulane Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA. .,School of Basic Medical Science, Central South University, Changsha, 410013, China.
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23
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Wetherill L, Lai D, Johnson EC, Anokhin A, Bauer L, Bucholz KK, Dick DM, Hariri AR, Hesselbrock V, Kamarajan C, Kramer J, Kuperman S, Meyers JL, Nurnberger JI, Schuckit M, Scott DM, Taylor RE, Tischfield J, Porjesz B, Goate AM, Edenberg HJ, Foroud T, Bogdan R, Agrawal A. Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans. GENES, BRAIN, AND BEHAVIOR 2019; 18:e12580. [PMID: 31099175 PMCID: PMC6726116 DOI: 10.1111/gbb.12580] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/19/2019] [Accepted: 05/11/2019] [Indexed: 02/07/2023]
Abstract
Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P < 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk.
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Affiliation(s)
- Leah Wetherill
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
| | - Dongbing Lai
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
| | - Emma C. Johnson
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
| | - Andrey Anokhin
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
| | - Lance Bauer
- University of Connecticut. University of Connecticut School of Medicine, Department of Psychiatry. Farmington, CT
| | - Kathleen K. Bucholz
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
| | - Danielle M. Dick
- Virginia Commonwealth University. Department of Psychology & College Behavioral and Emotional Health Institute, Virginia Commonwealth University. Richmond, VA
| | - Ahmad R. Hariri
- Duke Institute for Brain Sciences, Dept. of Psychology, Duke University, Durham, NC
| | - Victor Hesselbrock
- University of Connecticut. University of Connecticut School of Medicine, Department of Psychiatry. Farmington, CT
| | - Chella Kamarajan
- SUNY. Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center. Brooklyn, NY
| | - John Kramer
- University of Iowa. University of Iowa Roy J and Lucille A Carver College of Medicine, Department of Psychiatry. Iowa City, IA
| | - Samuel Kuperman
- University of Iowa. University of Iowa Roy J and Lucille A Carver College of Medicine, Department of Psychiatry. Iowa City, IA
| | - Jacquelyn L. Meyers
- SUNY. Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center. Brooklyn, NY
| | - John I. Nurnberger
- Indiana University. Department of Psychiatry, Indiana University School of Medicine. Indianapolis, IN
| | - Marc Schuckit
- University of California San Diego. University of California San Diego, Department of Psychiatry. San Diego, CA
| | - Denise M. Scott
- Howard University, Departments of Pediatrics and Human Genetics, Washington, DC
| | | | | | - Bernice Porjesz
- SUNY. Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center. Brooklyn, NY
| | - Alison M. Goate
- Department of Neuroscience, Icahn School of Medicine at Mt. Sinai, New York, NY
| | - Howard J. Edenberg
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
- Indiana University. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine. Indianapolis, IN
| | - Tatiana Foroud
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
| | - Ryan Bogdan
- Washington University in Saint Louis, Department of Psychological and Brain Sciences, Saint Louis, MO, USA
| | - Arpana Agrawal
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
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24
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Vergara C, Thio CL, Johnson E, Kral AH, O'Brien TR, Goedert JJ, Mangia A, Piazzolla V, Mehta SH, Kirk GD, Kim AY, Lauer GM, Chung RT, Cox AL, Peters MG, Khakoo SI, Alric L, Cramp ME, Donfield SM, Edlin BR, Busch MP, Alexander G, Rosen HR, Murphy EL, Latanich R, Wojcik GL, Taub MA, Valencia A, Thomas DL, Duggal P. Multi-Ancestry Genome-Wide Association Study of Spontaneous Clearance of Hepatitis C Virus. Gastroenterology 2019; 156:1496-1507.e7. [PMID: 30593799 PMCID: PMC6788806 DOI: 10.1053/j.gastro.2018.12.014] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 12/05/2018] [Accepted: 12/19/2018] [Indexed: 02/08/2023]
Abstract
BACKGROUND & AIMS Spontaneous clearance of hepatitis C virus (HCV) occurs in approximately 30% of infected persons and less often in populations of African ancestry. Variants in major histocompatibility complex (MHC) and in interferon lambda genes are associated with spontaneous HCV clearance, but there have been few studies of these variants in persons of African ancestry. We performed a dense multi-ancestry genome-wide association study of spontaneous clearance of HCV, focusing on individuals of African ancestry. METHODS We performed genotype analyses of 4423 people from 3 ancestry groups: 2201 persons of African ancestry (445 with HCV clearance and 1756 with HCV persistence), 1739 persons of European ancestry (701 with HCV clearance and 1036 with HCV persistence), and 486 multi-ancestry Hispanic persons (173 with HCV clearance and 313 with HCV persistence). Samples were genotyped using Illumina (San Diego, CA) arrays and statistically imputed to the 1000 Genomes Project. For each ancestry group, the association of single-nucleotide polymorphisms with HCV clearance was tested by log-additive analysis, and then a meta-analysis was performed. RESULTS In the meta-analysis, significant associations with HCV clearance were confirmed at the interferon lambda gene locus IFNL4-IFNL3 (19q13.2) (P = 5.99 × 10-50) and the MHC locus 6p21.32 (P = 1.15 × 10-21). We also associated HCV clearance with polymorphisms in the G-protein-coupled receptor 158 gene (GPR158) at 10p12.1 (P = 1.80 × 10-07). These 3 loci had independent, additive effects of HCV clearance, and account for 6.8% and 5.9% of the variance of HCV clearance in persons of European and African ancestry, respectively. Persons of African or European ancestry carrying all 6 variants were 24-fold and 11-fold, respectively, more likely to clear HCV infection compared with individuals carrying none or 1 of the clearance-associated variants. CONCLUSIONS In a meta-analysis of data from 3 studies, we found variants in MHC genes, IFNL4-IFNL3, and GPR158 to increase odds of HCV clearance in patients of European and African ancestry. These findings could increase our understanding of immune response to and clearance of HCV infection.
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Affiliation(s)
| | - Chloe L Thio
- Johns Hopkins University, School of Medicine, Baltimore, Maryland
| | - Eric Johnson
- Research Triangle Institute International, Research Triangle Park, North Carolina; Atlanta, Georgia; San Francisco, California
| | - Alex H Kral
- Research Triangle Institute International, Research Triangle Park, North Carolina; Atlanta, Georgia; San Francisco, California
| | - Thomas R O'Brien
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - James J Goedert
- Liver Unit Istituto Di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Italy
| | - Alessandra Mangia
- Liver Unit Istituto Di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Italy
| | - Valeria Piazzolla
- Liver Unit Istituto Di Ricovero e Cura a Carattere Scientifico "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Italy
| | - Shruti H Mehta
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland
| | - Gregory D Kirk
- Johns Hopkins University, School of Medicine, Baltimore, Maryland; Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland
| | - Arthur Y Kim
- Liver Center and Gastrointestinal Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Georg M Lauer
- Liver Center and Gastrointestinal Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Raymond T Chung
- Liver Center and Gastrointestinal Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Andrea L Cox
- Johns Hopkins University, School of Medicine, Baltimore, Maryland
| | - Marion G Peters
- Division of Gastroenterology, Department of Medicine, School of Medicine, University of California, San Francisco, California
| | - Salim I Khakoo
- University of Southampton, Southampton General Hospital, Southampton, UK
| | - Laurent Alric
- Department of Internal Medicine and Digestive Diseases, Centre Hospitalier Universitaire Purpan, UMR 152, Institut de Recherche pour le Développement Toulouse 3 University, France
| | | | | | - Brian R Edlin
- State University of New York Downstate College of Medicine, Brooklyn, New York
| | - Michael P Busch
- University of California and Vitalant Research Institute, San Francisco, California
| | - Graeme Alexander
- University College London Institute for Liver and Digestive Health, The Royal Free Hospital, London, UK
| | | | - Edward L Murphy
- University of California and Vitalant Research Institute, San Francisco, California
| | - Rachel Latanich
- Johns Hopkins University, School of Medicine, Baltimore, Maryland
| | - Genevieve L Wojcik
- Department of Genetics, Stanford University School of Medicine, Stanford, California
| | - Margaret A Taub
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland
| | - Ana Valencia
- Johns Hopkins University, School of Medicine, Baltimore, Maryland; Universidad Pontificia Bolivariana, Medellin, Colombia
| | - David L Thomas
- Johns Hopkins University, School of Medicine, Baltimore, Maryland
| | - Priya Duggal
- Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland.
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25
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Lin DY. A simple and accurate method to determine genomewide significance for association tests in sequencing studies. Genet Epidemiol 2019; 43:365-372. [PMID: 30623491 DOI: 10.1002/gepi.22183] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 11/30/2018] [Accepted: 12/04/2018] [Indexed: 11/05/2022]
Abstract
Whole-exome sequencing (WES) and whole-genome sequencing (WGS) studies are underway to investigate the impact of genetic variants on complex diseases and traits. It is customary to perform single-variant association tests for common variants and region-based association tests for rare variants. The latter may target variants with similar or opposite effects, interrogate variants with different frequencies or different functional annotations, and examine a variety of regions. The large number of tests that are performed necessitates adjustment for multiple testing. The conventional Bonferroni correction is overly conservative as the test statistics are correlated. To address this challenge, we propose a simple and accurate method based on parametric bootstrap to assess genomewide significance. We show that the correlations of the test statistics are determined primarily by the genotypes, such that the same significance threshold can be used in different studies that share a common sequencing platform. We demonstrate the usefulness of the proposed method with WES data from the National Heart, Lung, and Blood Institute Exome Sequencing Project and WGS data from the 1000 Genomes Project. We recommend the p value of 5 × 1 0 - 9 as the genomewide significance threshold for testing all common and low-frequency variants (MAFs ≥ 0.1%) in the human genome.
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Affiliation(s)
- Dan-Yu Lin
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
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26
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Zaimi I, Pei D, Koestler DC, Marsit CJ, De Vivo I, Tworoger SS, Shields AE, Kelsey KT, Michaud DS. Variation in DNA methylation of human blood over a 1-year period using the Illumina MethylationEPIC array. Epigenetics 2018; 13:1056-1071. [PMID: 30270718 PMCID: PMC6342169 DOI: 10.1080/15592294.2018.1530008] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Revised: 08/02/2018] [Accepted: 09/22/2018] [Indexed: 12/29/2022] Open
Abstract
Assessing DNA methylation profiles in human blood has become a major focus of epidemiologic inquiry. Understanding variability in CpG-specific DNA methylation over moderate periods of time is a critical first step in identifying CpG sites that are candidates for DNA methylation-based etiologic, diagnostic and prognostic predictors of pathogenesis. Using the Illumina MethylationEPIC [850K] BeadArray, DNA methylation was profiled in paired whole blood samples collected approximately 1 year apart from 35 healthy women enrolled in the Nurses Study II cohort. The median intraclass correlation coefficient (ICC) across all CpG loci was 0.19 [Interquartile Range (IQR) 0.00-0.50]; 74.8% of ICCs were in the low range (0-0.5), 16.9% in the mid-range of ICCs (0.5-0.8), and 8.3% in the high-range of ICCs (0.8-1). ICCs were similar for CpG probes on the 450K Illumina array (median 0.17) and the new probes added to the 850K array (median 0.21). ICCs for CpG loci on the sex chromosomes and known metastable epialleles were high (median 0.71, 0.97, respectively), and ICCs among methylation quantitative trait loci (mQTL) CpGs were significantly higher as compared to non-mQTL CpGs (median 0.73, 0.16, respectively, P < 2 × 10-16). We observed wide variation in DNA methylation stability over a 1-year period. Probes considered non-stable, due to substantial variation over a moderate period of time and with minimal variability across individuals could be removed in large epidemiological studies. Moreover, adjusting for technical variation that arises from using high-dimensional arrays is critical.
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Affiliation(s)
- Ina Zaimi
- a Department of Public Health & Community Medicine, Tufts University School of Medicine , Tufts University , Boston , USA
| | - Dong Pei
- b Department of Biostatistics , University of Kansas Medical Center , Kansas City , USA
- c University of Kansas Cancer Center , The University of Kansas Medical Center , Kansas City , USA
| | - Devin C Koestler
- b Department of Biostatistics , University of Kansas Medical Center , Kansas City , USA
- c University of Kansas Cancer Center , The University of Kansas Medical Center , Kansas City , USA
| | - Carmen J Marsit
- d Department of Environmental Health and Department of Epidemiology, Rollins School of Public Health , Emory University , Atlanta , USA
| | - Immaculata De Vivo
- e Channing Division of Network Medicine, Department of Medicine , Brigham and Women's Hospital and Harvard Medical School , Boston , USA
| | - Shelley S Tworoger
- f Department of Cancer Epidemiology , Moffitt Cancer Center , Tampa , USA
- g Department of Epidemiology , Harvard T.H. Chan School of Public Health , Boston , USA
| | - Alexandra E Shields
- h Department of Medicine , Harvard Medical School , Boston , MA , USA
- k Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities , Massachusetts General Hospital , Boston , MA , USA
| | - Karl T Kelsey
- i Department of Epidemiology , Brown University , Providence , USA
- j Department of Pathology and Laboratory Medicine , Brown University , Providence , USA
| | - Dominique S Michaud
- a Department of Public Health & Community Medicine, Tufts University School of Medicine , Tufts University , Boston , USA
- i Department of Epidemiology , Brown University , Providence , USA
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27
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Spear ML, Hu D, Pino-Yanes M, Huntsman S, Eng C, Levin AM, Ortega VE, White MJ, McGarry ME, Thakur N, Galanter J, Mak ACY, Oh SS, Ampleford E, Peters SP, Davis A, Kumar R, Farber HJ, Meade K, Avila PC, Serebrisky D, Lenoir MA, Brigino-Buenaventura E, Cintron WR, Thyne SM, Rodriguez-Santana JR, Ford JG, Chapela R, Estrada AM, Sandoval K, Seibold MA, Winkler CA, Bleecker ER, Myers DA, Williams LK, Hernandez RD, Torgerson DG, Burchard EG. A genome-wide association and admixture mapping study of bronchodilator drug response in African Americans with asthma. THE PHARMACOGENOMICS JOURNAL 2018; 19:249-259. [PMID: 30206298 PMCID: PMC6414286 DOI: 10.1038/s41397-018-0042-4] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 06/08/2018] [Accepted: 06/19/2018] [Indexed: 01/15/2023]
Abstract
Short-acting β2-adrenergic receptor agonists (SABAs) are the most commonly prescribed asthma medications worldwide. Response to SABAs is measured as bronchodilator drug response (BDR), which varies among racial/ethnic groups in the U.S1, 2. However, the genetic variation that contributes to BDR is largely undefined in African Americans with asthma3. To identify genetic variants that may contribute to differences in BDR in African Americans with asthma, we performed a genome-wide association study (GWAS) of BDR in 949 African American children with asthma, genotyped with the Axiom World Array 4 (Affymetrix, Santa Clara, CA) followed by imputation using 1000 Genomes phase III genotypes. We used linear regression models adjusting for age, sex, body mass index (BMI) and genetic ancestry to test for an association between BDR and genotype at single nucleotide polymorphisms (SNPs). To increase power and distinguish between shared vs. population-specific associations with BDR in children with asthma, we performed a meta-analysis across 949 African Americans and 1,830 Latinos (Total=2,779). Lastly, we performed genome-wide admixture mapping to identify regions whereby local African or European ancestry is associated with BDR in African Americans. We identified a population-specific association with an intergenic SNP on chromosome 9q21 that was significantly associated with BDR (rs73650726, p=7.69×10−9). A trans-ethnic meta-analysis across African Americans and Latinos identified three additional SNPs within the intron of PRKG1 that were significantly associated with BDR (rs7903366, rs7070958, and rs7081864, p≤5×10−8). Our results failed to replicate in three additional populations of 416 Latinos and 1,615 African Americans. Our findings indicate that both population specific and shared genetic variation contributes to differences in BDR in minority children with asthma, and that the genetic underpinnings of BDR may differ between racial/ethnic groups.
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Affiliation(s)
- Melissa L Spear
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Pino-Yanes
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain.,Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, La Laguna, Tenerife, Spain
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Albert M Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Victor E Ortega
- Department of Internal Medicine, Wake Forest Baptist Medical Center, Winston Salem, NC, USA
| | - Marquitta J White
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Meghan E McGarry
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Neeta Thakur
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Joshua Galanter
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.,Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Angel C Y Mak
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Sam S Oh
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Elizabeth Ampleford
- Department of Internal Medicine, Wake Forest Baptist Medical Center, Winston Salem, NC, USA
| | - Stephen P Peters
- Department of Internal Medicine, Wake Forest Baptist Medical Center, Winston Salem, NC, USA
| | - Adam Davis
- UCSF Benioff Children's Hospital Oakland, Center for Community Health and Engagement, Oakland, CA, USA
| | - Rajesh Kumar
- Ann & Robert H. Lurie Children's Hospital of Chicago, Pediatrics, Chicago, IL, USA
| | - Harold J Farber
- Department of Pediatrics, Section of Pulmonology, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA
| | - Kelley Meade
- UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
| | - Pedro C Avila
- Division of Allergy-Immunology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Denise Serebrisky
- Pediatric Pulmonary Division, Jacobi Medical Center, Bronx, NY, USA.,Albert Einstein College of Medicine, Pediatrics, Bronx, NY, USA
| | | | | | | | - Shannon M Thyne
- Department of Pediatrics, David Geffen School of Medicine at ULCA, Olive View-UCLA Medical Center, Sylmar, CA, USA
| | | | | | - Rocio Chapela
- Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Andrés Moreno Estrada
- National Laboratory of Genomics for Biodiversity (LANGEBIO), CINVESTAV, Irapuato, Guanajuato, Mexico
| | - Karla Sandoval
- National Laboratory of Genomics for Biodiversity (LANGEBIO), CINVESTAV, Irapuato, Guanajuato, Mexico
| | - Max A Seibold
- Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Cheryl A Winkler
- Basic Research Laboratory, National Cancer Institute, Leidos Biomedical Research, Frederick National Laboratory, Frederick, MD, USA
| | | | - Deborah A Myers
- Department of Medicine, The University of Arizona, Tucson, AZ, USA
| | - L Keoki Williams
- Center for Health Policy and Health Services Research,, Henry Ford Health System, Detroit, MI, USA.,Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Ryan D Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.,California Institute for Quantitative Biosciences (QB3), University of California, San Francisco, CA, USA.,Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Dara G Torgerson
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Esteban G Burchard
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA. .,Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
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28
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Genetic Determinants of Telomere Length in African American Youth. Sci Rep 2018; 8:13265. [PMID: 30185882 PMCID: PMC6125592 DOI: 10.1038/s41598-018-31238-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 08/06/2018] [Indexed: 12/17/2022] Open
Abstract
Telomere length (TL) is associated with numerous disease states and is affected by genetic and environmental factors. However, TL has been mostly studied in adult populations of European or Asian ancestry. These studies have identified 34 TL-associated genetic variants recently used as genetic proxies for TL. The generalizability of these associations to pediatric populations and racially diverse populations, specifically of African ancestry, remains unclear. Furthermore, six novel variants associated with TL in a population of European children have been identified but not validated. We measured TL from whole blood samples of 492 healthy African American youth (children and adolescents between 8 and 20 years old) and performed the first genome-wide association study of TL in this population. We were unable to replicate neither the 34 reported genetic associations found in adults nor the six genetic associations found in European children. However, we discovered a novel genome-wide significant association between TL and rs1483898 on chromosome 14. Our results underscore the importance of examining genetic associations with TL in diverse pediatric populations such as African Americans.
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29
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Fine-mapping analysis of a chromosome 2 region linked to resistance to Mycobacterium tuberculosis infection in Uganda reveals potential regulatory variants. Genes Immun 2018; 20:473-483. [PMID: 30100616 PMCID: PMC6374218 DOI: 10.1038/s41435-018-0040-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 05/31/2018] [Accepted: 06/06/2018] [Indexed: 12/17/2022]
Abstract
Tuberculosis (TB) is a major public health burden worldwide, and more effective treatment is sorely needed. Consequently, uncovering causes of resistance to Mycobacterium tuberculosis (Mtb) infection is of special importance for vaccine design. Resistance to Mtb infection can be defined by a persistently negative tuberculin skin test (PTST-) despite living in close and sustained exposure to an active TB case. While susceptibility to Mtb is, in part, genetically determined, relatively little work has been done to uncover genetic factors underlying resistance to Mtb infection. We examined a region on chromosome 2q previously implicated in our genomewide linkage scan by a targeted, high-density association scan for genetic variants enhancing PTST- in two independent Ugandan TB household cohorts (n = 747 and 471). We found association with SNPs in neighboring genes ZEB2 and GTDC1 (peak meta p = 1.9 × 10-5) supported by both samples. Bioinformatic analysis suggests these variants may affect PTST- by regulating the histone deacetylase (HDAC) pathway, supporting previous results from transcriptomic analyses. An apparent protective effect of PTST- against body-mass wasting suggests a link between resistance to Mtb infection and healthy body composition. Our results provide insight into how humans may escape latent Mtb infection despite heavy exposure.
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30
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Mak ACY, White MJ, Eckalbar WL, Szpiech ZA, Oh SS, Pino-Yanes M, Hu D, Goddard P, Huntsman S, Galanter J, Wu AC, Himes BE, Germer S, Vogel JM, Bunting KL, Eng C, Salazar S, Keys KL, Liberto J, Nuckton TJ, Nguyen TA, Torgerson DG, Kwok PY, Levin AM, Celedón JC, Forno E, Hakonarson H, Sleiman PM, Dahlin A, Tantisira KG, Weiss ST, Serebrisky D, Brigino-Buenaventura E, Farber HJ, Meade K, Lenoir MA, Avila PC, Sen S, Thyne SM, Rodriguez-Cintron W, Winkler CA, Moreno-Estrada A, Sandoval K, Rodriguez-Santana JR, Kumar R, Williams LK, Ahituv N, Ziv E, Seibold MA, Darnell RB, Zaitlen N, Hernandez RD. Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma. Am J Respir Crit Care Med 2018; 197:1552-1564. [PMID: 29509491 PMCID: PMC6006403 DOI: 10.1164/rccm.201712-2529oc] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 03/05/2018] [Indexed: 12/25/2022] Open
Abstract
RATIONALE Albuterol, a bronchodilator medication, is the first-line therapy for asthma worldwide. There are significant racial/ethnic differences in albuterol drug response. OBJECTIVES To identify genetic variants important for bronchodilator drug response (BDR) in racially diverse children. METHODS We performed the first whole-genome sequencing pharmacogenetics study from 1,441 children with asthma from the tails of the BDR distribution to identify genetic association with BDR. MEASUREMENTS AND MAIN RESULTS We identified population-specific and shared genetic variants associated with BDR, including genome-wide significant (P < 3.53 × 10-7) and suggestive (P < 7.06 × 10-6) loci near genes previously associated with lung capacity (DNAH5), immunity (NFKB1 and PLCB1), and β-adrenergic signaling (ADAMTS3 and COX18). Functional analyses of the BDR-associated SNP in NFKB1 revealed potential regulatory function in bronchial smooth muscle cells. The SNP is also an expression quantitative trait locus for a neighboring gene, SLC39A8. The lack of other asthma study populations with BDR and whole-genome sequencing data on minority children makes it impossible to perform replication of our rare variant associations. Minority underrepresentation also poses significant challenges to identify age-matched and population-matched cohorts of sufficient sample size for replication of our common variant findings. CONCLUSIONS The lack of minority data, despite a collaboration of eight universities and 13 individual laboratories, highlights the urgent need for a dedicated national effort to prioritize diversity in research. Our study expands the understanding of pharmacogenetic analyses in racially/ethnically diverse populations and advances the foundation for precision medicine in at-risk and understudied minority populations.
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Affiliation(s)
| | | | | | | | | | - Maria Pino-Yanes
- Research Unit, Hospital Universitario N. S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | | | | | | | | | - Ann Chen Wu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Precision Medicine Translational Research (PRoMoTeR) Center, Department of Population Medicine, Harvard Medical School and Pilgrim Health Care Institute, Boston, Massachusetts
| | - Blanca E. Himes
- Department of Biostatistics, Epidemiology and Informatics and
| | | | | | | | | | | | | | | | | | | | | | - Pui-Yan Kwok
- Cardiovascular Research Institute
- Institute for Human Genetics, and
| | | | - Juan C. Celedón
- Division of Pediatric Pulmonary Medicine, Allergy and Immunology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Erick Forno
- Division of Pediatric Pulmonary Medicine, Allergy and Immunology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Hakon Hakonarson
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Center for Applied Genomics, The Children’s Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania
| | - Patrick M. Sleiman
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Center for Applied Genomics, The Children’s Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania
| | - Amber Dahlin
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Kelan G. Tantisira
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Denise Serebrisky
- Pediatric Pulmonary Division, Jacobi Medical Center, Bronx, New York
| | | | - Harold J. Farber
- Department of Pediatrics, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas
| | - Kelley Meade
- Children’s Hospital and Research Center, Oakland, California
| | | | - Pedro C. Avila
- Department of Medicine, Northwestern University, Chicago, Illinois
| | | | - Shannon M. Thyne
- Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | | | - Cheryl A. Winkler
- Basic Science Laboratory, Center for Cancer Research, National Cancer Institute, Leidos Biomedical Research, Frederick National Laboratory, Frederick, Maryland
| | - Andrés Moreno-Estrada
- National Laboratory of Genomics for Biodiversity (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato, Mexico
| | - Karla Sandoval
- National Laboratory of Genomics for Biodiversity (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato, Mexico
| | | | - Rajesh Kumar
- Division of Allergy and Immunology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois
| | - L. Keoki Williams
- Department of Internal Medicine, and
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, Michigan
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences
- Institute for Human Genetics, and
| | | | - Max A. Seibold
- Center for Genes, Environment and Health, Department of Pediatrics, National Jewish Health, Denver, Colorado; and
| | - Robert B. Darnell
- New York Genome Center, New York, New York
- Laboratory of Molecular Neuro-Oncology and
- Howard Hughes Medical Institute, The Rockefeller University, New York, New York
| | | | - Ryan D. Hernandez
- Department of Bioengineering and Therapeutic Sciences
- Cardiovascular Research Institute
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, California
| | - on behalf of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
- Department of Medicine
- Department of Bioengineering and Therapeutic Sciences
- Department of Pediatrics
- Cardiovascular Research Institute
- Institute for Human Genetics, and
- Quantitative Biosciences Institute, University of California San Francisco, San Francisco, California
- Research Unit, Hospital Universitario N. S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Precision Medicine Translational Research (PRoMoTeR) Center, Department of Population Medicine, Harvard Medical School and Pilgrim Health Care Institute, Boston, Massachusetts
- Department of Biostatistics, Epidemiology and Informatics and
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- New York Genome Center, New York, New York
- Department of Public Health Sciences
- Department of Internal Medicine, and
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, Michigan
- Division of Pediatric Pulmonary Medicine, Allergy and Immunology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Center for Applied Genomics, The Children’s Hospital of Philadelphia Research Institute, Philadelphia, Pennsylvania
- Pediatric Pulmonary Division, Jacobi Medical Center, Bronx, New York
- Department of Allergy and Immunology, Kaiser Permanente Vallejo Medical Center, Vallejo, California
- Department of Pediatrics, Baylor College of Medicine and Texas Children’s Hospital, Houston, Texas
- Children’s Hospital and Research Center, Oakland, California
- Bay Area Pediatrics, Oakland, California
- Department of Medicine, Northwestern University, Chicago, Illinois
- Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Veterans Caribbean Health Care System, San Juan, Puerto Rico
- Basic Science Laboratory, Center for Cancer Research, National Cancer Institute, Leidos Biomedical Research, Frederick National Laboratory, Frederick, Maryland
- National Laboratory of Genomics for Biodiversity (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato, Mexico
- Centro de Neumologia Pediatrica, San Juan, Puerto Rico
- Division of Allergy and Immunology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois
- Center for Genes, Environment and Health, Department of Pediatrics, National Jewish Health, Denver, Colorado; and
- Laboratory of Molecular Neuro-Oncology and
- Howard Hughes Medical Institute, The Rockefeller University, New York, New York
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31
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Verma A, Lucas A, Verma SS, Zhang Y, Josyula N, Khan A, Hartzel DN, Lavage DR, Leader J, Ritchie MD, Pendergrass SA. PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger. Am J Hum Genet 2018; 102:592-608. [PMID: 29606303 PMCID: PMC5985339 DOI: 10.1016/j.ajhg.2018.02.017] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Accepted: 02/20/2018] [Indexed: 01/23/2023] Open
Abstract
Most phenome-wide association studies (PheWASs) to date have used a small to moderate number of SNPs for association with phenotypic data. We performed a large-scale single-cohort PheWAS, using electronic health record (EHR)-derived case-control status for 541 diagnoses using International Classification of Disease version 9 (ICD-9) codes and 25 median clinical laboratory measures. We calculated associations between these diagnoses and traits with ∼630,000 common frequency SNPs with minor allele frequency > 0.01 for 38,662 individuals. In this landscape PheWAS, we explored results within diseases and traits, comparing results to those previously reported in genome-wide association studies (GWASs), as well as previously published PheWASs. We further leveraged the context of functional impact from protein-coding to regulatory regions, providing a deeper interpretation of these associations. The comprehensive nature of this PheWAS allows for novel hypothesis generation, the identification of phenotypes for further study for future phenotypic algorithm development, and identification of cross-phenotype associations.
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Affiliation(s)
- Anurag Verma
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Anastasia Lucas
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shefali S Verma
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Yu Zhang
- Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA
| | - Navya Josyula
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Anqa Khan
- Mount Holyoke College, South Hadley, MA 01075, USA
| | - Dustin N Hartzel
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Daniel R Lavage
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Joseph Leader
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA; Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sarah A Pendergrass
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA.
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Copley TR, Duceppe MO, O'Donoughue LS. Identification of novel loci associated with maturity and yield traits in early maturity soybean plant introduction lines. BMC Genomics 2018; 19:167. [PMID: 29490606 PMCID: PMC5831853 DOI: 10.1186/s12864-018-4558-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 02/20/2018] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND To continue to meet the increasing demands of soybean worldwide, it is crucial to identify key genes regulating flowering and maturity to expand the cultivated regions into short season areas. Although four soybean genes have been successfully utilized in early maturity breeding programs, new genes governing maturity are continuously being identified suggesting that there remains as yet undiscovered loci governing agronomic traits of interest. The objective of this study was to identify novel loci and genes involved in a diverse set of early soybean maturity using genome-wide association (GWA) analyses to identify loci governing days to maturity (DTM), flowering (DTF) and pod filling (DTPF), as well as yield and 100 seed weight in Canadian environments. To do so, soybean plant introduction lines varying significantly for maturity, but classified as early varieties, were used. Plants were phenotyped for the five agronomic traits for five site-years and GWA approaches used to identify candidate loci and genes affecting each trait. RESULTS Genotyping using genotyping-by-sequencing and microarray methods identified 67,594 single nucleotide polymorphisms, of which 31,283 had a linkage disequilibrium < 1 and minor allele frequency > 0.05 and were used for GWA analyses. A total of 9, 6, 4, 5 and 2 loci were detected for GWA analyses for DTM, DTF, DTPF, 100 seed weight and yield, respectively. Regions of interest, including a region surrounding the E1 gene for flowering and maturity, and several novel loci, were identified, with several loci having pleiotropic effects. Novel loci affecting maturity were identified on chromosomes five and 13 and reduced maturity by 7.2 and 3.3 days, respectively. Novel loci for maturity and flowering contained genes orthologous to known Arabidopsis flowering genes, while loci affecting yield and 100 seed weight contained genes known to cause dwarfism. CONCLUSIONS This study demonstrated substantial variation in soybean agronomic traits of interest, including maturity and flowering dates as well as yield, and the utility of GWA analyses in identifying novel genetic factors underlying important agronomic traits. The loci and candidate genes identified serve as promising targets for future studies examining the mechanisms underlying the related soybean traits.
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Affiliation(s)
- Tanya R Copley
- Centre de recherche sur les grains (CÉROM), Inc., 740 chemin Trudeau, St-Mathieu-de-Beloeil, Québec, J3G 0E2, Canada
| | - Marc-Olivier Duceppe
- Centre de recherche sur les grains (CÉROM), Inc., 740 chemin Trudeau, St-Mathieu-de-Beloeil, Québec, J3G 0E2, Canada
- Canadian Food Inspection Agency, 3851 Fallowfield Road, Nepean, ON, K2H 8P9, Canada
| | - Louise S O'Donoughue
- Centre de recherche sur les grains (CÉROM), Inc., 740 chemin Trudeau, St-Mathieu-de-Beloeil, Québec, J3G 0E2, Canada.
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33
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Shahin MH, Gong Y, Frye RF, Rotroff DM, Beitelshees AL, Baillie RA, Chapman AB, Gums JG, Turner ST, Boerwinkle E, Motsinger-Reif A, Fiehn O, Cooper-DeHoff RM, Han X, Kaddurah-Daouk R, Johnson JA. Sphingolipid Metabolic Pathway Impacts Thiazide Diuretics Blood Pressure Response: Insights From Genomics, Metabolomics, and Lipidomics. J Am Heart Assoc 2017; 7:e006656. [PMID: 29288159 PMCID: PMC5778957 DOI: 10.1161/jaha.117.006656] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Accepted: 11/01/2017] [Indexed: 01/04/2023]
Abstract
BACKGROUND Although hydrochlorothiazide (HCTZ) is a well-established first-line antihypertensive in the United States, <50% of HCTZ treated patients achieve blood pressure (BP) control. Thus, identifying biomarkers that could predict the BP response to HCTZ is critically important. In this study, we utilized metabolomics, genomics, and lipidomics to identify novel pathways and biomarkers associated with HCTZ BP response. METHODS AND RESULTS First, we conducted a pathway analysis for 13 metabolites we recently identified to be significantly associated with HCTZ BP response. From this analysis, we found the sphingolipid metabolic pathway as the most significant pathway (P=5.8E-05). Testing 78 variants, within 14 genes involved in the sphingolipid metabolic canonical pathway, with the BP response to HCTZ identified variant rs6078905, within the SPTLC3 gene, as a novel biomarker significantly associated with the BP response to HCTZ in whites (n=228). We found that rs6078905 C-allele carriers had a better BP response to HCTZ versus noncarriers (∆SBP/∆DBP: -11.4/-6.9 versus -6.8/-3.5 mm Hg; ∆SBP P=6.7E-04; ∆DBP P=4.8E-04). Additionally, in blacks (n=148), we found genetic signals in the SPTLC3 genomic region significantly associated with the BP response to HCTZ (P<0.05). Last, we observed that rs6078905 significantly affects the baseline level of 4 sphingomyelins (N24:2, N24:3, N16:1, and N22:1; false discovery rate <0.05), from which N24:2 sphingomyelin has a significant correlation with both HCTZ DBP-response (r=-0.42; P=7E-03) and SBP-response (r=-0.36; P=2E-02). CONCLUSIONS This study provides insight into potential pharmacometabolomic and genetic mechanisms underlying HCTZ BP response and suggests that SPTLC3 is a potential determinant of the BP response to HCTZ. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00246519.
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Affiliation(s)
- Mohamed H Shahin
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Reginald F Frye
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Daniel M Rotroff
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC
| | | | | | | | - John G Gums
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | | | - Eric Boerwinkle
- Human Genetics Center and Institute for Molecular Medicine, University of Texas Health Science Center, Houston, TX
| | | | - Oliver Fiehn
- Genome Center, University of California at Davis, CA
- Biochemistry Department, King Abdulaziz University, Jeddah, Saudi-Arabia
| | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
| | - Xianlin Han
- Sanford-Burnham Medical Research Institute, Orlando, FL
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioural Sciences and Department of Medicine, Duke University, Durham, NC
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL
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34
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Abstract
PURPOSE OF REVIEW Over many decades, researchers have been designing studies to investigate the relationship between genotypes and phenotypes to gain an understanding about the effect of genetics on disease. Recently, a high-throughput approach called phenome-wide associations studies (PheWAS) have been extensively used to identify associations between genetic variants and many diseases and traits simultaneously. In this review, we describe the value of PheWAS along with methodological issues and challenges in interpretation for current applications of PheWAS. RECENT FINDINGS PheWAS have uncovered a paradigm to identify new associations for genetic loci across many diseases. The application of PheWAS have been effective with phenotype data from electronic health records, epidemiological studies, and clinical trials data. SUMMARY The key strength of a PheWAS is to identify the association of one or more genetic variants with multiple phenotypes, which can showcase interconnections among the phenotypes due to shared genetic associations. While the PheWAS approach appears promising, there are a number of challenges that need to be addressed to provide additional robustness to PheWAS findings.
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Affiliation(s)
- Anurag Verma
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA
| | - Marylyn D Ritchie
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA
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35
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Jabot-Hanin F, Cobat A, Feinberg J, Orlova M, Niay J, Deswarte C, Poirier C, Theodorou I, Bustamante J, Boisson-Dupuis S, Casanova JL, Alcaïs A, Hoal EG, Delacourt C, Schurr E, Abel L. An eQTL variant of ZXDC is associated with IFN-γ production following Mycobacterium tuberculosis antigen-specific stimulation. Sci Rep 2017; 7:12800. [PMID: 28993696 PMCID: PMC5634485 DOI: 10.1038/s41598-017-13017-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Accepted: 09/12/2017] [Indexed: 12/26/2022] Open
Abstract
There is a large inter-individual variability in the response to Mycobacterium tuberculosis infection. In previous linkage analyses, we identified a major locus on chromosome region 8q controlling IFN-γ production after stimulation with live BCG (Bacillus Calmette-Guérin), and a second locus on chromosome region 3q affecting IFN-γ production triggered by the 6-kDa early secretory antigen target (ESAT-6), taking into account the IFN-γ production induced by BCG (IFNγ-ESAT6BCG). High-density genotyping and imputation identified ~100,000 variants within each linkage region, which we tested for association with the corresponding IFN-γ phenotype in families from a tuberculosis household contact study in France. Significant associations were replicated in a South African familial sample. The most convincing association observed was that between the IFNγ-ESAT6BCG phenotype and rs9828868 on chromosome 3q (p = 9.8 × 10−6 in the French sample). This variant made a significant contribution to the linkage signal (p < 0.001), and a trend towards the same association was observed in the South African sample. This variant was reported to be an eQTL of the ZXDC gene, biologically linked to monocyte IL-12 production through CCL2/MCP1. The identification of rs9828868 as a genetic driver of IFNγ production in response to mycobacterial antigens provides new insights into human anti-tuberculosis immunity.
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Affiliation(s)
- Fabienne Jabot-Hanin
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France
| | - Aurélie Cobat
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France
| | - Jacqueline Feinberg
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France
| | - Marianna Orlova
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada.,McGill International TB Centre, McGill University, Montreal, Canada.,Department of Human Genetics and Department of Medicine, McGill University, Montreal, Canada
| | - Jonathan Niay
- Université Pierre et Marie Curie, UF d'Histocompatibilité et Immunogénétique, Département d'Immunologie, Groupe Hospitalier Pitié Salpêtrière - Charles Foix, Paris, France
| | - Caroline Deswarte
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France
| | - Christine Poirier
- Centre de Lutte Anti-Tuberculeuse, Centre Hospitalier Intercommunal de Créteil, Créteil, France
| | - Ioannis Theodorou
- Université Pierre et Marie Curie, UF d'Histocompatibilité et Immunogénétique, Département d'Immunologie, Groupe Hospitalier Pitié Salpêtrière - Charles Foix, Paris, France
| | - Jacinta Bustamante
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France
| | - Stéphanie Boisson-Dupuis
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France.,St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, NY, USA
| | - Jean-Laurent Casanova
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France.,St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, NY, USA.,Howard Hughes Medical Institute, New York, NY, USA.,Pediatric Hematology-Immunology Unit, Necker Hospital for Sick Children, AP-HP, Paris, France
| | - Alexandre Alcaïs
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France.,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France
| | - Eileen G Hoal
- Molecular Biology and Human Genetics, MRC Centre for Molecular and Cellular Biology, DST/NRF Centre of Excellence for Biomedical TB Research, Faculty of Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Christophe Delacourt
- Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France.,Pediatric Pneumology Unit, Necker Hospital for Sick Children, AP-HP, Paris, France
| | - Erwin Schurr
- Program in Infectious Diseases and Immunity in Global Health, The Research Institute of the McGill University Health Centre, Montreal, Canada.,McGill International TB Centre, McGill University, Montreal, Canada.,Department of Human Genetics and Department of Medicine, McGill University, Montreal, Canada
| | - Laurent Abel
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France. .,Paris Descartes University, Sorbonne Paris Cité, Imagine Institute, Paris, France. .,St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, Rockefeller University, New York, NY, USA.
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Lee BD, Gonzalez S, Villa E, Camarillo C, Rodriguez M, Yao Y, Guo W, Flores D, Jerez A, Raventos H, Ontiveros A, Nicolini H, Escamilla M. A genome-wide quantitative trait locus (QTL) linkage scan of NEO personality factors in Latino families segregating bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2017; 174:683-690. [PMID: 28556497 PMCID: PMC5597458 DOI: 10.1002/ajmg.b.32551] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Revised: 03/20/2017] [Accepted: 04/25/2017] [Indexed: 12/24/2022]
Abstract
Personality traits have been suggested as potential endophenotypes for Bipolar Disorder (BP), as they can be quantitatively measured and show correlations with BP. The present study utilized data from 2,745 individuals from 686 extended pedigrees originally ascertained for having multiplex cases of BP (963 cases of BPI or schizoaffective BP). Subjects were assessed with the NEO Personality Inventory, Revised (NEO PI-R) and genotyped using the Illumina HumanLinkage-24 Bead Chip, with an average genetic coverage of 0.67 cM. Two point linkage scores were calculated for each trait as a quantitative variable using SOLAR (Sequential Oligogenic Linkage Analysis Routines). Suggestive evidence for linkage was found for neuroticism at 1q32.1 (LOD = 2.52), 6q23.3 (2.32), 16p12 (2.79), extraversion at 4p15.3 (2.33), agreeableness at 4q31.1 (2.37), 5q34 (2.80), 7q31.1 (2.56), 16q22 (2.52), and conscientiousness at 4q31.1 (2.50). Each of the above traits have been shown to be correlated with the broad BP phenotype in this same sample. In addition, for the trait of openness, we found significant evidence of linkage to chromosome 3p24.3 (rs336610, LOD = 4.75) and suggestive evidence at 1q43 (2.74), 5q35.1 (3.03), 11q14.3 (2.61), 11q21 (2.30), and 19q13.1 (2.52). These findings support previous linkage findings of the openness trait to chromosome 19q13 and the agreeableness trait to 4q31 and identify a number of new loci for personality endophenotypes related to bipolar disorder.
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Affiliation(s)
- Byung Dae Lee
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas,Department of Psychiatry, School of Medicine, Pusan National University, Busan, South Korea
| | - Suzanne Gonzalez
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas
| | - Erika Villa
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas
| | - Cynthia Camarillo
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas
| | - Marco Rodriguez
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas
| | - Yin Yao
- Unit on Statistical Genomics, National Institute of Mental Health, Bethesda, Maryland
| | - Wei Guo
- Unit on Statistical Genomics, National Institute of Mental Health, Bethesda, Maryland
| | - Deborah Flores
- Los Angeles Biomedical Research Center at Harbor, University of California Los Angeles Medical Center, Torrance, California
| | - Alvaro Jerez
- Centro Internacional de Trastornos Afectivos y de la Conducta Adictiva, Guatemala, Guatemala
| | - Henriette Raventos
- Centro de Investigacion en Biologia Celular y Molecular y Escuela de Biologia, Universidad de Costa Rica, San Jose, Costa Rica
| | - Alfonso Ontiveros
- Instituto de Informacion e InvestigaciónenSalud Mental AC, Monterrey, Nuevo Leon, Mexico
| | - Humberto Nicolini
- Grupo de Estudios Medicos y Familiares Carracci, S.C., Mexico, D.F., Mexico,Instituto Nacional de Medicina Genomica, Mexico, D.F., Mexico
| | - Michael Escamilla
- Center of Excellence for Neurosciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas,Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, Texas,Correspondence to: Michael Escamilla, MD, Department of Psychiatry Paul L. Foster School of Medicine Texas Tech University Health Science Center 4800 Alberta El Paso, TX 79905, USA,
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37
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Li R, Kim D, Ritchie MD. Methods to analyze big data in pharmacogenomics research. Pharmacogenomics 2017; 18:807-820. [PMID: 28612644 DOI: 10.2217/pgs-2016-0152] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
The scale and scope of pharmacogenomics research continues to expand as the cost and efficiency of molecular data generation techniques advance. These new technologies give rise to enormous opportunity for the identification of important genetic and genomic factors important for drug treatment response. With this opportunity come significant challenges. Most of these can be categorized as 'big data' issues, facing not only pharmacogenomics, but other fields in the life sciences as well. In this review, we describe some of the analysis techniques and tools being implemented for genetic/genomic discovery in pharmacogenomics.
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Affiliation(s)
- Ruowang Li
- Bioinformatics & Genomics Graduate Program, The Pennsylvania State University, University Park, PA 16802, USA
| | - Dokyoon Kim
- Biomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA 17821, USA
| | - Marylyn D Ritchie
- Bioinformatics & Genomics Graduate Program, The Pennsylvania State University, University Park, PA 16802, USA.,Biomedical & Translational Informatics Institute, Geisinger Health System, Danville, PA 17821, USA
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38
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Tragante V, Gho JMIH, Felix JF, Vasan RS, Smith NL, Voight BF, Palmer C, van der Harst P, Moore JH, Asselbergs FW. Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype. BioData Min 2017; 10:18. [PMID: 28559929 PMCID: PMC5446754 DOI: 10.1186/s13040-017-0137-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 05/09/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genetic studies for complex diseases have predominantly discovered main effects at individual loci, but have not focused on genomic and environmental contexts important for a phenotype. Gene Set Enrichment Analysis (GSEA) aims to address this by identifying sets of genes or biological pathways contributing to a phenotype, through gene-gene interactions or other mechanisms, which are not the focus of conventional association methods. RESULTS Approaches that utilize GSEA can now take input from array chips, either gene-centric or genome-wide, but are highly sensitive to study design, SNP selection and pruning strategies, SNP-to-gene mapping, and pathway definitions. Here, we present lessons learned from our experience with GSEA of heart failure, a particularly challenging phenotype due to its underlying heterogeneous etiology. CONCLUSIONS This case study shows that proper data handling is essential to avoid false-positive results. Well-defined pipelines for quality control are needed to avoid reporting spurious results using GSEA.
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Affiliation(s)
- Vinicius Tragante
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Johannes M. I. H. Gho
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Janine F. Felix
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ramachandran S. Vasan
- Departments of Medicine and Preventive Medicine, Boston University School of Medicine, Boston, MA USA
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, Seattle, WA USA
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - CHARGE Heart Failure Working Group
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Departments of Medicine and Preventive Medicine, Boston University School of Medicine, Boston, MA USA
- Department of Epidemiology, University of Washington, Seattle, WA USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Population Pharmacogenetics Group, University of Dundee, Dundee, UK
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Biostatistics and Epidemiology, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Durrer Center for Cardiovascular Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Farr Institute of Health Informatics Research and Institute of Health Informatics, University College London, London, UK
| | - Colin Palmer
- Population Pharmacogenetics Group, University of Dundee, Dundee, UK
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Jason H. Moore
- Department of Biostatistics and Epidemiology, Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Folkert W. Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Durrer Center for Cardiovascular Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Farr Institute of Health Informatics Research and Institute of Health Informatics, University College London, London, UK
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Kodaman N, Sobota RS, Asselbergs FW, Oetjens MT, Moore JH, Brown NJ, Aldrich MC, Williams SM. Genetic Effects on the Correlation Structure of CVD Risk Factors: Exome-Wide Data From a Ghanaian Population. Glob Heart 2017; 12:133-140. [PMID: 28408189 DOI: 10.1016/j.gheart.2017.01.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 01/17/2017] [Indexed: 01/11/2023] Open
Abstract
Plasma concentration of plasminogen activator inhibitor-1 (PAI-1) is highly correlated with several cardiovascular disease (CVD) risk factors. It also plays a direct role in CVD, including myocardial infarction and stroke, by impeding the dissolution of thrombi in the blood. Insofar as PAI-1 links CVD's risk factors to its endpoints, genetic variants modulating the relationship between PAI-1 and risk factors may be of particular clinical and biological interest. The high heritability of PAI-1, which has not been explained by genetic association studies, may also, in large part, be due to this relationship with CVD risk factors. Using exome-wide data from 1,032 Ghanaian study participants, we tested for heterogeneity of correlation by genotype between PAI-1 and 4 CVD risk factors (body mass index, triglycerides, mean arterial pressure, and fasting glucose) under the hypothesis that loci involved in the relationship between PAI-1 and other risk factors will also modify their correlational structure. We found more significant heterogeneities of correlation by genotype than we found marginal effects, with no evidence of type I inflation. The most significant result among all univariate and multivariate tests performed in this study was the heterogeneity of correlation between PAI-1 and mean arterial pressure at rs10738554, near SLC24A2, a gene previously associated with high blood pressure in African Americans.
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Affiliation(s)
- Nuri Kodaman
- Vanderbilt Genetics Institute, Vanderbilt University Medical School, Nashville, TN, USA; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA; Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Rafal S Sobota
- Vanderbilt Genetics Institute, Vanderbilt University Medical School, Nashville, TN, USA; Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, UMC (University Medical Center) Utrecht, Utrecht, the Netherlands; Durrer Center for Cardiogenetic Research, Netherlands Heart Institute, Utrecht, the Netherlands; Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | | | - Jason H Moore
- Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA; Department of Biostatistics and Epidemiology, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nancy J Brown
- Department of Medicine, Vanderbilt University Medical School, Nashville, TN, USA
| | - Melinda C Aldrich
- Department of Thoracic Surgery and Division of Epidemiology, Vanderbilt University Medical School, Nashville, TN, USA
| | - Scott M Williams
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA; Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
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40
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Böger CA, Gorski M, McMahon GM, Xu H, Chang YPC, van der Most PJ, Navis G, Nolte IM, de Borst MH, Zhang W, Lehne B, Loh M, Tan ST, Boerwinkle E, Grams ME, Sekula P, Li M, Wilmot B, Moon JG, Scheet P, Cucca F, Xiao X, Lyytikäinen LP, Delgado G, Grammer TB, Kleber ME, Sedaghat S, Rivadeneira F, Corre T, Kutalik Z, Bergmann S, Nielson CM, Srikanth P, Teumer A, Müller-Nurasyid M, Brockhaus AC, Pfeufer A, Rathmann W, Peters A, Matsumoto M, de Andrade M, Atkinson EJ, Robinson-Cohen C, de Boer IH, Hwang SJ, Heid IM, Gögele M, Concas MP, Tanaka T, Bandinelli S, Nalls MA, Singleton A, Tajuddin SM, Adeyemo A, Zhou J, Doumatey A, McWeeney S, Murabito J, Franceschini N, Flessner M, Shlipak M, Wilson JG, Chen G, Rotimi CN, Zonderman AB, Evans MK, Ferrucci L, Devuyst O, Pirastu M, Shuldiner A, Hicks AA, Pramstaller PP, Kestenbaum B, Kardia SLR, Turner ST, Study LC, Briske TE, Gieger C, Strauch K, Meisinger C, Meitinger T, Völker U, Nauck M, Völzke H, Vollenweider P, Bochud M, Waeber G, Kähönen M, Lehtimäki T, März W, Dehghan A, Franco OH, Uitterlinden AG, Hofman A, Taylor HA, Chambers JC, Kooner JS, Fox CS, Hitzemann R, Orwoll ES, Pattaro C, Schlessinger D, Köttgen A, Snieder H, Parsa A, Cohen DM. NFAT5 and SLC4A10 Loci Associate with Plasma Osmolality. J Am Soc Nephrol 2017; 28:2311-2321. [PMID: 28360221 DOI: 10.1681/asn.2016080892] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Accepted: 02/02/2017] [Indexed: 12/20/2022] Open
Abstract
Disorders of water balance, an excess or deficit of total body water relative to body electrolyte content, are common and ascertained by plasma hypo- or hypernatremia, respectively. We performed a two-stage genome-wide association study meta-analysis on plasma sodium concentration in 45,889 individuals of European descent (stage 1 discovery) and 17,637 additional individuals of European descent (stage 2 replication), and a transethnic meta-analysis of replicated single-nucleotide polymorphisms in 79,506 individuals (63,526 individuals of European descent, 8765 individuals of Asian Indian descent, and 7215 individuals of African descent). In stage 1, we identified eight loci associated with plasma sodium concentration at P<5.0 × 10-6 Of these, rs9980 at NFAT5 replicated in stage 2 meta-analysis (P=3.1 × 10-5), with combined stages 1 and 2 genome-wide significance of P=5.6 × 10-10 Transethnic meta-analysis further supported the association at rs9980 (P=5.9 × 10-12). Additionally, rs16846053 at SLC4A10 showed nominally, but not genome-wide, significant association in combined stages 1 and 2 meta-analysis (P=6.7 × 10-8). NFAT5 encodes a ubiquitously expressed transcription factor that coordinates the intracellular response to hypertonic stress but was not previously implicated in the regulation of systemic water balance. SLC4A10 encodes a sodium bicarbonate transporter with a brain-restricted expression pattern, and variant rs16846053 affects a putative intronic NFAT5 DNA binding motif. The lead variants for NFAT5 and SLC4A10 are cis expression quantitative trait loci in tissues of the central nervous system and relevant to transcriptional regulation. Thus, genetic variation in NFAT5 and SLC4A10 expression and function in the central nervous system may affect the regulation of systemic water balance.
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Affiliation(s)
- Carsten A Böger
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Mathias Gorski
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Gearoid M McMahon
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Huichun Xu
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Yen-Pei C Chang
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Peter J van der Most
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Gerjan Navis
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Ilja M Nolte
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Martin H de Borst
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Weihua Zhang
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Benjamin Lehne
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Marie Loh
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Sian-Tsung Tan
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Eric Boerwinkle
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Morgan E Grams
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Peggy Sekula
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Man Li
- Due to the number of contributing authors, the affiliations are listed in the supplemental material.
| | - Beth Wilmot
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - James G Moon
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Paul Scheet
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Francesco Cucca
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Xiangjun Xiao
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Leo-Pekka Lyytikäinen
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Graciela Delgado
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Tanja B Grammer
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Marcus E Kleber
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Sanaz Sedaghat
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Fernando Rivadeneira
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Tanguy Corre
- Due to the number of contributing authors, the affiliations are listed in the supplemental material.
| | - Zoltan Kutalik
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Sven Bergmann
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Carrie M Nielson
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Priya Srikanth
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Alexander Teumer
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Martina Müller-Nurasyid
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Anne Catharina Brockhaus
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Arne Pfeufer
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Wolfgang Rathmann
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Annette Peters
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Martha Matsumoto
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Mariza de Andrade
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Elizabeth J Atkinson
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Cassianne Robinson-Cohen
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Ian H de Boer
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Shih-Jen Hwang
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Iris M Heid
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Martin Gögele
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Maria Pina Concas
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Toshiko Tanaka
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Stefania Bandinelli
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Mike A Nalls
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Andrew Singleton
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Salman M Tajuddin
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Adebowale Adeyemo
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Jie Zhou
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Ayo Doumatey
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Shannon McWeeney
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Joanne Murabito
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Nora Franceschini
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Michael Flessner
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Michael Shlipak
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - James G Wilson
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Guanjie Chen
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Charles N Rotimi
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Alan B Zonderman
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Michele K Evans
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Luigi Ferrucci
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Olivier Devuyst
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Mario Pirastu
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Alan Shuldiner
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Andrew A Hicks
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Peter Paul Pramstaller
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Bryan Kestenbaum
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Sharon L R Kardia
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Stephen T Turner
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - LifeLines Cohort Study
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Tamara Ellefson Briske
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Christian Gieger
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Konstantin Strauch
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Christa Meisinger
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Thomas Meitinger
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Uwe Völker
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Matthias Nauck
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Henry Völzke
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Peter Vollenweider
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Murielle Bochud
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Gerard Waeber
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Mika Kähönen
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Terho Lehtimäki
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Winfried März
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Abbas Dehghan
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Oscar H Franco
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Andre G Uitterlinden
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Albert Hofman
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Herman A Taylor
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - John C Chambers
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Jaspal S Kooner
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Caroline S Fox
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Robert Hitzemann
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Eric S Orwoll
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Cristian Pattaro
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - David Schlessinger
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Anna Köttgen
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Harold Snieder
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - Afshin Parsa
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
| | - David M Cohen
- Due to the number of contributing authors, the affiliations are listed in the supplemental material
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41
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Genetic architecture differences between pediatric and adult-onset inflammatory bowel diseases in the Polish population. Sci Rep 2016; 6:39831. [PMID: 28008999 PMCID: PMC5180213 DOI: 10.1038/srep39831] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Accepted: 11/29/2016] [Indexed: 12/15/2022] Open
Abstract
Most inflammatory bowel diseases (IBDs) are classic complex disorders represented by common alleles. Here we aimed to define the genetic architecture of pediatric and adult-onset IBDs for the Polish population. A total of 1495 patients were recruited, including 761 patients with Crohn’s disease (CD; 424 pediatric), 734 patients with ulcerative colitis (UC; 390 pediatric), and 934 healthy controls. Allelotyping employed a pooled-DNA genome-wide association study (GWAS) and was validated by individual genotyping. Whole exome sequencing (WES) was performed on 44 IBD patients diagnosed before 6 years of age, 45 patients diagnosed after 40 years of age, and 18 healthy controls. Altogether, out of 88 selected SNPs, 31 SNPs were replicated for association with IBD. A novel BRD2 (rs1049526) association reached significance of P = 5.2 × 10−11 and odds ratio (OR) = 2.43. Twenty SNPs were shared between pediatric and adult patients; 1 and 7 were unique to adult-onset and pediatric-onset IBD, respectively. WES identified numerous rare and potentially deleterious variants in IBD-associated or innate immunity-associated genes. Deleterious alleles in both groups were over-represented among rare variants in affected children. Our GWAS revealed differences in the polygenic architecture of pediatric- and adult-onset IBD. A significant accumulation of rare and deleterious variants in affected children suggests a contribution by yet unexplained genetic components.
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42
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Pulit SL, de With SAJ, de Bakker PIW. Resetting the bar: Statistical significance in whole-genome sequencing-based association studies of global populations. Genet Epidemiol 2016; 41:145-151. [PMID: 27990689 DOI: 10.1002/gepi.22032] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Revised: 10/31/2016] [Accepted: 10/31/2016] [Indexed: 12/29/2022]
Abstract
Genome-wide association studies (GWAS) of common disease have been hugely successful in implicating loci that modify disease risk. The bulk of these associations have proven robust and reproducible, in part due to community adoption of statistical criteria for claiming significant genotype-phenotype associations. As the cost of sequencing continues to drop, assembling large samples in global populations is becoming increasingly feasible. Sequencing studies interrogate not only common variants, as was true for genotyping-based GWAS, but variation across the full allele frequency spectrum, yielding many more (independent) statistical tests. We sought to empirically determine genome-wide significance thresholds for various analysis scenarios. Using whole-genome sequence data, we simulated sequencing-based disease studies of varying sample size and ancestry. We determined that future sequencing efforts in >2,000 samples of European, Asian, or admixed ancestry should set genome-wide significance at approximately P = 5 × 10-9 , and studies of African samples should apply a more stringent genome-wide significance threshold of P = 1 × 10-9 . Adoption of a revised multiple test correction will be crucial in avoiding irreproducible claims of association.
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Affiliation(s)
- Sara L Pulit
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Sera A J de With
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Paul I W de Bakker
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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43
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Phenome-Wide Association Study to Explore Relationships between Immune System Related Genetic Loci and Complex Traits and Diseases. PLoS One 2016; 11:e0160573. [PMID: 27508393 PMCID: PMC4980020 DOI: 10.1371/journal.pone.0160573] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 07/16/2016] [Indexed: 12/21/2022] Open
Abstract
We performed a Phenome-Wide Association Study (PheWAS) to identify interrelationships between the immune system genetic architecture and a wide array of phenotypes from two de-identified electronic health record (EHR) biorepositories. We selected variants within genes encoding critical factors in the immune system and variants with known associations with autoimmunity. To define case/control status for EHR diagnoses, we used International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes from 3,024 Geisinger Clinic MyCode® subjects (470 diagnoses) and 2,899 Vanderbilt University Medical Center BioVU biorepository subjects (380 diagnoses). A pooled-analysis was also carried out for the replicating results of the two data sets. We identified new associations with potential biological relevance including SNPs in tumor necrosis factor (TNF) and ankyrin-related genes associated with acute and chronic sinusitis and acute respiratory tract infection. The two most significant associations identified were for the C6orf10 SNP rs6910071 and “rheumatoid arthritis” (ICD-9 code category 714) (pMETAL = 2.58 x 10−9) and the ATN1 SNP rs2239167 and “diabetes mellitus, type 2” (ICD-9 code category 250) (pMETAL = 6.39 x 10−9). This study highlights the utility of using PheWAS in conjunction with EHRs to discover new genotypic-phenotypic associations for immune-system related genetic loci.
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44
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Kanai M, Tanaka T, Okada Y. Empirical estimation of genome-wide significance thresholds based on the 1000 Genomes Project data set. J Hum Genet 2016; 61:861-866. [PMID: 27305981 PMCID: PMC5090169 DOI: 10.1038/jhg.2016.72] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Revised: 04/18/2016] [Accepted: 05/16/2016] [Indexed: 01/22/2023]
Abstract
To assess the statistical significance of associations between variants and traits, genome-wide association studies (GWAS) should employ an appropriate threshold that accounts for the massive burden of multiple testing in the study. Although most studies in the current literature commonly set a genome-wide significance threshold at the level of P=5.0 × 10-8, the adequacy of this value for respective populations has not been fully investigated. To empirically estimate thresholds for different ancestral populations, we conducted GWAS simulations using the 1000 Genomes Phase 3 data set for Africans (AFR), Europeans (EUR), Admixed Americans (AMR), East Asians (EAS) and South Asians (SAS). The estimated empirical genome-wide significance thresholds were Psig=3.24 × 10-8 (AFR), 9.26 × 10-8 (EUR), 1.83 × 10-7 (AMR), 1.61 × 10-7 (EAS) and 9.46 × 10-8 (SAS). We additionally conducted trans-ethnic meta-analyses across all populations (ALL) and all populations except for AFR (ΔAFR), which yielded Psig=3.25 × 10-8 (ALL) and 4.20 × 10-8 (ΔAFR). Our results indicate that the current threshold (P=5.0 × 10-8) is overly stringent for all ancestral populations except for Africans; however, we should employ a more stringent threshold when conducting a meta-analysis, regardless of the presence of African samples.
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Affiliation(s)
- Masahiro Kanai
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Toshihiro Tanaka
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.,Bioresource Research Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yukinori Okada
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.,Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.,Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
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45
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White MJ, Risse-Adams O, Goddard P, Contreras MG, Adams J, Hu D, Eng C, Oh SS, Davis A, Meade K, Brigino-Buenaventura E, LeNoir MA, Bibbins-Domingo K, Pino-Yanes M, Burchard EG. Novel genetic risk factors for asthma in African American children: Precision Medicine and the SAGE II Study. Immunogenetics 2016; 68:391-400. [PMID: 27142222 DOI: 10.1007/s00251-016-0914-1] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Accepted: 04/25/2016] [Indexed: 01/06/2023]
Abstract
Asthma, an inflammatory disorder of the airways, is the most common chronic disease of children worldwide. There are significant racial/ethnic disparities in asthma prevalence, morbidity, and mortality among US children. This trend is mirrored in obesity, which may share genetic and environmental risk factors with asthma. The majority of asthma biomedical research has been performed in populations of European decent. We sought to identify genetic risk factors for asthma in African American children. We also assessed the generalizability of genetic variants associated with asthma in European and Asian populations to African American children. Our study population consisted of 1227 (812 asthma cases, 415 controls) African American children with genome-wide single nucleotide polymorphism (SNP) data. Logistic regression was used to identify associations between SNP genotype and asthma status. We identified a novel variant in the PTCHD3 gene that is significantly associated with asthma (rs660498, p = 2.2 × 10(-7)) independent of obesity status. Approximately 5 % of previously reported asthma genetic associations identified in European populations replicated in African Americans. Our identification of novel variants associated with asthma in African American children, coupled with our inability to replicate the majority of findings reported in European Americans, underscores the necessity for including diverse populations in biomedical studies of asthma.
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Affiliation(s)
- Marquitta J White
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA.
| | - O Risse-Adams
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
- Lowell Science Research Program, Lowell High School, San Francisco, CA, USA
| | - P Goddard
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
| | - M G Contreras
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
- SF BUILD, San Francisco State University, San Francisco, CA, USA
| | - J Adams
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
| | - D Hu
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
| | - C Eng
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
| | - S S Oh
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
| | - A Davis
- Children's Hospital and Research Center Oakland, Oakland, CA, USA
| | - K Meade
- Children's Hospital and Research Center Oakland, Oakland, CA, USA
| | - E Brigino-Buenaventura
- Department of Allergy and Immunology, Kaiser Permanente Vallejo Medical Center, Vallejo, CA, USA
| | | | - K Bibbins-Domingo
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
| | - M Pino-Yanes
- Research Unit, Hospital Universitario N.S. de Candelaria, Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - E G Burchard
- Department of Medicine, University of California, San Francisco, UCSF Box 2911, San Francisco, CA, 94143-2911, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
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Sobota RS, Stein CM, Kodaman N, Scheinfeldt LB, Maro I, Wieland-Alter W, Igo RP, Magohe A, Malone LL, Chervenak K, Hall NB, Modongo C, Zetola N, Matee M, Joloba M, Froment A, Nyambo TB, Moore JH, Scott WK, Lahey T, Boom WH, von Reyn CF, Tishkoff SA, Sirugo G, Williams SM. A Locus at 5q33.3 Confers Resistance to Tuberculosis in Highly Susceptible Individuals. Am J Hum Genet 2016; 98:514-524. [PMID: 26942285 PMCID: PMC4800052 DOI: 10.1016/j.ajhg.2016.01.015] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 01/26/2016] [Indexed: 12/22/2022] Open
Abstract
Immunosuppression resulting from HIV infection increases the risk of progression to active tuberculosis (TB) both in individuals newly exposed to Mycobacterium tuberculosis (MTB) and in those with latent infections. We hypothesized that HIV-positive individuals who do not develop TB, despite living in areas where it is hyperendemic, provide a model of natural resistance. We performed a genome-wide association study of TB resistance by using 581 HIV-positive Ugandans and Tanzanians enrolled in prospective cohort studies of TB; 267 of these individuals developed active TB, and 314 did not. A common variant, rs4921437 at 5q33.3, was significantly associated with TB (odds ratio = 0.37, p = 2.11 × 10(-8)). This variant lies within a genomic region that includes IL12B and is embedded in an H3K27Ac histone mark. The locus also displays consistent patterns of linkage disequilibrium across African populations and has signals of strong selection in populations from equatorial Africa. Along with prior studies demonstrating that therapy with IL-12 (the cytokine encoded in part by IL12B, associated with longer survival following MTB infection in mice deficient in CD4 T cells), our results suggest that this pathway might be an excellent target for the development of new modalities for treating TB, especially for HIV-positive individuals. Our results also indicate that studying extreme disease resistance in the face of extensive exposure can increase the power to detect associations in complex infectious disease.
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Affiliation(s)
- Rafal S Sobota
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA; Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
| | - Catherine M Stein
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA; Tuberculosis Research Unit, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Nuri Kodaman
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA; Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Laura B Scheinfeldt
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; Coriell Institute for Medical Research, Camden, NJ 08103, USA
| | - Isaac Maro
- Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
| | | | - Robert P Igo
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Albert Magohe
- Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - LaShaunda L Malone
- Tuberculosis Research Unit, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Keith Chervenak
- Tuberculosis Research Unit, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Noemi B Hall
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Chawangwa Modongo
- Division of Infectious Diseases, University of Pennsylvania, Philadelphia, PA 19104, USA; Botswana-UPenn Partnership, 214 Independence Avenue, Gaborone, Botswana; Department of Medicine, University of Botswana, Gaborone, Botswana
| | - Nicola Zetola
- Division of Infectious Diseases, University of Pennsylvania, Philadelphia, PA 19104, USA; Botswana-UPenn Partnership, 214 Independence Avenue, Gaborone, Botswana; Department of Medicine, University of Botswana, Gaborone, Botswana
| | - Mecky Matee
- Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Moses Joloba
- Uganda-CWRU Research Collaboration, Kampala, Uganda; College of Health Sciences Makerere University and Mulago Hospital, Kampala, Uganda
| | - Alain Froment
- UMR 208, Institut de Recherche pour le Développement and Musée de l'Homme, Muséum National d'Histoire Naturelle, 75116 Paris, France
| | - Thomas B Nyambo
- Department of Biochemistry, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Jason H Moore
- Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William K Scott
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL 33136, USA
| | - Timothy Lahey
- Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
| | - W Henry Boom
- Tuberculosis Research Unit, Case Western Reserve University, Cleveland, OH 44106, USA; Uganda-CWRU Research Collaboration, Kampala, Uganda
| | | | - Sarah A Tishkoff
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Giorgio Sirugo
- Centro di Ricerca, Ospedale San Pietro Fatebenefratelli, 00189 Rome, Italy
| | - Scott M Williams
- Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA.
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Tsareva E, Kulakova O, Boyko A, Favorova O. Pharmacogenetics of multiple sclerosis. Pharmacogenet Genomics 2016; 26:103-15. [DOI: 10.1097/fpc.0000000000000194] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Verma A, Leader JB, Verma SS, Frase A, Wallace J, Dudek S, Lavage DR, Van Hout CV, Dewey FE, Penn J, Lopez A, Overton JD, Carey DJ, Ledbetter DH, Kirchner HL, Ritchie MD, Pendergrass SA. INTEGRATING CLINICAL LABORATORY MEASURES AND ICD-9 CODE DIAGNOSES IN PHENOME-WIDE ASSOCIATION STUDIES. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2016; 21:168-79. [PMID: 26776183 PMCID: PMC4718547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Electronic health records (EHR) provide a comprehensive resource for discovery, allowing unprecedented exploration of the impact of genetic architecture on health and disease. The data of EHRs also allow for exploration of the complex interactions between health measures across health and disease. The discoveries arising from EHR based research provide important information for the identification of genetic variation for clinical decision-making. Due to the breadth of information collected within the EHR, a challenge for discovery using EHR based data is the development of high-throughput tools that expose important areas of further research, from genetic variants to phenotypes. Phenome-Wide Association studies (PheWAS) provide a way to explore the association between genetic variants and comprehensive phenotypic measurements, generating new hypotheses and also exposing the complex relationships between genetic architecture and outcomes, including pleiotropy. EHR based PheWAS have mainly evaluated associations with case/control status from International Classification of Disease, Ninth Edition (ICD-9) codes. While these studies have highlighted discovery through PheWAS, the rich resource of clinical lab measures collected within the EHR can be better utilized for high-throughput PheWAS analyses and discovery. To better use these resources and enrich PheWAS association results we have developed a sound methodology for extracting a wide range of clinical lab measures from EHR data. We have extracted a first set of 21 clinical lab measures from the de-identified EHR of participants of the Geisinger MyCodeTM biorepository, and calculated the median of these lab measures for 12,039 subjects. Next we evaluated the association between these 21 clinical lab median values and 635,525 genetic variants, performing a genome-wide association study (GWAS) for each of 21 clinical lab measures. We then calculated the association between SNPs from these GWAS passing our Bonferroni defined p-value cutoff and 165 ICD-9 codes. Through the GWAS we found a series of results replicating known associations, and also some potentially novel associations with less studied clinical lab measures. We found the majority of the PheWAS ICD-9 diagnoses highly related to the clinical lab measures associated with same SNPs. Moving forward, we will be evaluating further phenotypes and expanding the methodology for successful extraction of clinical lab measurements for research and PheWAS use. These developments are important for expanding the PheWAS approach for improved EHR based discovery.
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Affiliation(s)
- Anurag Verma
- Biomedical and Translational Informatics, Geisinger Health System, Danville, PA, USA3Center for Systems Genomics, The Pennsylvania State University, University Park, PA, USA
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Pendergrass SA, Ritchie MD. Phenome-Wide Association Studies: Leveraging Comprehensive Phenotypic and Genotypic Data for Discovery. CURRENT GENETIC MEDICINE REPORTS 2015; 3:92-100. [PMID: 26146598 PMCID: PMC4489156 DOI: 10.1007/s40142-015-0067-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
With the large volume of clinical and epidemiological data being collected, increasingly linked to extensive genotypic data, coupled with expanding high-performance computational resources, there are considerable opportunities for comprehensively exploring the networks of connections that exist between the phenome and the genome. These networks can be identified through Phenome-Wide Association Studies (PheWAS) where the association between a collection of genetic variants, or in some cases a particular clinical lab variable, and a wide and diverse range of phenotypes, diagnoses, traits, and/or outcomes are evaluated. This is a departure from the more familiar genome-wide association study (GWAS) approach, which has been used to identify single nucleotide polymorphisms (SNPs) associated with one outcome or a very limited phenotypic domain. In addition to highlighting novel connections between multiple phenotypes and elucidating more of the phenotype-genotype landscape, PheWAS can generate new hypotheses for further exploration, and can also be used to narrow the search space for research using comprehensive data collections. The complex results of PheWAS also have the potential for uncovering new mechanistic insights. We review here how the PheWAS approach has been used with data from epidemiological studies, clinical trials, and de-identified electronic health record data. We also review methodologies for the analyses underlying PheWAS, and emerging methods developed for evaluating the comprehensive results of PheWAS including genotype-phenotype networks. This review also highlights PheWAS as an important tool for identifying new biomarkers, elucidating the genetic architecture of complex traits, and uncovering pleiotropy. There are many directions and new methodologies for the future of PheWAS analyses, from the phenotypic data to the genetic data, and herein we also discuss some of these important future PheWAS developments.
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