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Kim HR, Jin HS, Eom YB. Metabolite Genome-Wide Association Study for Indoleamine 2,3-Dioxygenase Activity Associated with Chronic Kidney Disease. Genes (Basel) 2021; 12:1905. [PMID: 34946851 PMCID: PMC8701662 DOI: 10.3390/genes12121905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 11/21/2022] Open
Abstract
Chronic kidney disease (CKD) causes progressive damage to kidney function with increased inflammation. This process contributes to complex amino acid changes. Indoleamine 2,3-dioxygenase (IDO) has been proposed as a new biomarker of CKD in previous studies. In our research, we performed a metabolite genome-wide association study (mGWAS) to identify common and rare variants associated with IDO activity in a Korean population. In addition, single-nucleotide polymorphisms (SNPs) selected through mGWAS were further analyzed for associations with the estimated glomerular filtration rate (eGFR) and CKD. A total of seven rare variants achieved the genome-wide significance threshold (p < 1 × 10-8). Among them, four genes (TNFRSF19, LOC105377444, LOC101928535, and FSTL5) associated with IDO activity showed statistically significant associations with eGFR and CKD. Most of these rare variants appeared specifically in an Asian geographic region. Furthermore, 15 common variants associated with IDO activity were detected in this study and five novel genes (RSU1, PDGFD, SNX25, LOC107984031, and UBASH3B) associated with CKD and eGFR were identified. This study discovered several loci for IDO activity via mGWAS and provided insight into the underlying mechanisms of CKD through association analysis with CKD. To the best of our knowledge, this is the first study to suggest a genetic link between IDO activity and CKD through comparative and integrated analysis.
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Affiliation(s)
- Hye-Rim Kim
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan 31538, Chungnam, Korea
| | - Hyun-Seok Jin
- Department of Biomedical Laboratory Science, College of Life and Health Sciences, Hoseo University, Asan 31499, Chungnam, Korea
| | - Yong-Bin Eom
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan 31538, Chungnam, Korea
- Department of Biomedical Laboratory Science, College of Medical Sciences, Soonchunhyang University, Asan 31538, Chungnam, Korea
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Feofanova EV, Chen H, Dai Y, Jia P, Grove ML, Morrison AC, Qi Q, Daviglus M, Cai J, North KE, Laurie CC, Kaplan RC, Boerwinkle E, Yu B. A Genome-wide Association Study Discovers 46 Loci of the Human Metabolome in the Hispanic Community Health Study/Study of Latinos. Am J Hum Genet 2020; 107:849-863. [PMID: 33031748 PMCID: PMC7675000 DOI: 10.1016/j.ajhg.2020.09.003] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 09/10/2020] [Indexed: 02/08/2023] Open
Abstract
Variation in levels of the human metabolome reflect changes in homeostasis, providing a window into health and disease. The genetic impact on circulating metabolites in Hispanics, a population with high cardiometabolic disease burden, is largely unknown. We conducted genome-wide association analyses on 640 circulating metabolites in 3,926 Hispanic Community Health Study/Study of Latinos participants. The estimated heritability for 640 metabolites ranged between 0%-54% with a median at 2.5%. We discovered 46 variant-metabolite pairs (p value < 1.2 × 10-10, minor allele frequency ≥ 1%, proportion of variance explained [PEV] mean = 3.4%, PEVrange = 1%-22%) with generalized effects in two population-based studies and confirmed 301 known locus-metabolite associations. Half of the identified variants with generalized effect were located in genes, including five nonsynonymous variants. We identified co-localization with the expression quantitative trait loci at 105 discovered and 151 known loci-metabolites sets. rs5855544, upstream of SLC51A, was associated with higher levels of three steroid sulfates and co-localized with expression levels of SLC51A in several tissues. Mendelian randomization (MR) analysis identified several metabolites associated with coronary heart disease (CHD) and type 2 diabetes. For example, two variants located in or near CYP4F2 (rs2108622 and rs79400241, respectively), involved in vitamin E metabolism, were associated with the levels of octadecanedioate and vitamin E metabolites (gamma-CEHC and gamma-CEHC glucuronide); MR analysis showed that genetically high levels of these metabolites were associated with lower odds of CHD. Our findings document the genetic architecture of circulating metabolites in an underrepresented Hispanic/Latino community, shedding light on disease etiology.
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Affiliation(s)
- Elena V Feofanova
- Human Genetics Center, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Han Chen
- Human Genetics Center, University of Texas Health Science Center, Houston, TX 77030, USA; Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Yulin Dai
- Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Peilin Jia
- Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Megan L Grove
- Human Genetics Center, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Alanna C Morrison
- Human Genetics Center, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois College of Medicine, Chicago, IL 60612, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina Gilling School of Global Public Health, Chapel Hill, NC 27599, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina Gilling School of Global Public Health, Chapel Hill, NC 27599, USA; Carolina Center of Genome Sciences, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Bing Yu
- Human Genetics Center, University of Texas Health Science Center, Houston, TX 77030, USA.
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Mass spectrometry-based metabolomics for an in-depth questioning of human health. Adv Clin Chem 2020; 99:147-191. [PMID: 32951636 DOI: 10.1016/bs.acc.2020.02.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.
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