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Narayanan B, Xia C, McAndrew R, Shen AL, Kim JJP. Structural basis for expanded substrate specificities of human long chain acyl-CoA dehydrogenase and related acyl-CoA dehydrogenases. Sci Rep 2024; 14:12976. [PMID: 38839792 PMCID: PMC11153573 DOI: 10.1038/s41598-024-63027-6] [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: 02/23/2024] [Accepted: 05/23/2024] [Indexed: 06/07/2024] Open
Abstract
Crystal structures of human long-chain acyl-CoA dehydrogenase (LCAD) and the catalytically inactive Glu291Gln mutant, have been determined. These structures suggest that LCAD harbors functions beyond its historically defined role in mitochondrial β-oxidation of long and medium-chain fatty acids. LCAD is a homotetramer containing one FAD per 43 kDa subunit with Glu291 as the catalytic base. The substrate binding cavity of LCAD reveals key differences which makes it specific for longer and branched chain substrates. The presence of Pro132 near the start of the E helix leads to helix unwinding that, together with adjacent smaller residues, permits binding of bulky substrates such as 3α, 7α, l2α-trihydroxy-5β-cholestan-26-oyl-CoA. This structural element is also utilized by ACAD11, a eucaryotic ACAD of unknown function, as well as bacterial ACADs known to metabolize sterol substrates. Sequence comparison suggests that ACAD10, another ACAD of unknown function, may also share this substrate specificity. These results suggest that LCAD, ACAD10, ACAD11 constitute a distinct class of eucaryotic acyl CoA dehydrogenases.
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Affiliation(s)
- Beena Narayanan
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Chuanwu Xia
- Department of Chemistry and Biochemistry, College of Arts and Sciences, University of North Florida, Jacksonville, FL, 32224, USA
| | - Ryan McAndrew
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94740, USA
| | - Anna L Shen
- McArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Jung-Ja P Kim
- Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
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Narayanan B, Xia C, McAndrew R, Shen AL, Kim JJP. Structural Basis for Expanded Substrate Speci ficities of Human Long Chain Acyl-CoA Dehydrogenase and Related Acyl- CoA Dehydrogenases. RESEARCH SQUARE 2024:rs.3.rs-3980524. [PMID: 38464032 PMCID: PMC10925408 DOI: 10.21203/rs.3.rs-3980524/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Crystal structures of human long-chain acyl-CoA dehydrogenase (LCAD) and the E291Q mutant, have been determined. These structures suggest that LCAD harbors functions beyond its historically defined role in mitochondrial β-oxidation of long and medium-chain fatty acids. LCAD is a homotetramer containing one FAD per 43kDa subunit with Glu291 as the catalytic base. The substrate binding cavity of LCAD reveals key differences which makes it specific for longer and branched chain substrates. The presence of Pro132 near the start of the E helix leads to helix unwinding that, together with adjacent smaller residues, permits binding of bulky substrates such as 3α, 7α, l2α-trihydroxy-5β-cholestan-26-oyl-CoA. This structural element is also utilized by ACAD11, a eucaryotic ACAD of unknown function, as well as bacterial ACADs known to metabolize sterol substrates. Sequence comparison suggests that ACAD10, another ACAD of unknown function, may also share this substrate specificity. These results suggest that LCAD, ACAD10, ACAD11 constitute a distinct class of eucaryotic acyl CoA dehydrogenases.
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3
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Rao L, Peng B, Li T. Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis. BMC Bioinformatics 2023; 24:196. [PMID: 37173646 PMCID: PMC10176911 DOI: 10.1186/s12859-023-05244-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/21/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Atherosclerosis is the common pathological basis for many cardiovascular and cerebrovascular diseases. The purpose of this study is to identify the diagnostic biomarkers related to atherosclerosis through machine learning algorithm. METHODS Clinicopathological parameters and transcriptomics data were obtained from 4 datasets (GSE21545, GSE20129, GSE43292, GSE100927). A nonnegative matrix factorization algorithm was used to classify arteriosclerosis patients in GSE21545 dataset. Then, we identified prognosis-related differentially expressed genes (DEGs) between the subtypes. Multiple machine learning methods to detect pivotal markers. Discrimination, calibration and clinical usefulness of the predicting model were assessed using area under curve, calibration plot and decision curve analysis respectively. The expression level of the feature genes was validated in GSE20129, GSE43292, GSE100927. RESULTS 2 molecular subtypes of atherosclerosis was identified, and 223 prognosis-related DEGs between the 2 subtypes were identified. These genes are not only related to epithelial cell proliferation, mitochondrial dysfunction, but also to immune related pathways. Least absolute shrinkage and selection operator, random forest, support vector machine- recursive feature elimination show that IL17C and ACOXL were identified as diagnostic markers of atherosclerosis. The prediction model displayed good discrimination and good calibration. Decision curve analysis showed that this model was clinically useful. Moreover, IL17C and ACOXL were verified in other 3 GEO datasets, and also have good predictive performance. CONCLUSION IL17C and ACOXL were diagnostic genes of atherosclerosis and associated with higher incidence of ischemic events.
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Affiliation(s)
- Li Rao
- Department of Geriatrics, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Bo Peng
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
- Cardiovascular Research Institute of Wuhan University, Wuhan, 430060, Hubei, China
- Hubei Key Laboratory of Cardiology, Wuhan, 430060, Hubei, China
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China
| | - Tao Li
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China.
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Gholami M, Zoughi M, Hasanzad M, Larijani B, Amoli MM. Haplotypic variants of COVID-19 related genes are associated with blood pressure and metabolites levels. J Med Virol 2023; 95:e28355. [PMID: 36443248 PMCID: PMC9877746 DOI: 10.1002/jmv.28355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Revised: 07/27/2022] [Accepted: 11/22/2022] [Indexed: 12/03/2022]
Abstract
The genetic association of coronavirus disease 2019 (COVID-19) with its complications has not been fully understood. This study aimed to identify variants and haplotypes of candidate genes implicated in COVID-19 related traits by combining the literature review and pathway analysis. To explore such genes, the protein-protein interactions and relevant pathways of COVID-19-associated genes were assessed. A number of variants on candidate genes were identified from Genome-wide association studies (GWASs) which were associated with COVID-19 related traits (p ˂ 10-6 ). Haplotypic blocks were assessed using haplotypic structures among the 1000 Genomes Project (r2 ≥ 0.8, D' ≥ 0.8). Further functional analyses were performed on the selected variants. The results demonstrated that a group of variants in ACE and AGT genes were significantly correlated with COVID-19 related traits. Three haplotypes were identified to be involved in the blood metabolites levels and the development of blood pressure. Functional analyses revealed that most GWAS index variants were expression quantitative trait loci and had transcription factor binding sites, exonic splicing enhancers or silencer activities. Furthermore, the proxy haplotype variants, rs4316, rs4353, rs4359, and three variants, namely rs2493133, rs2478543, and rs5051, were associated with blood metabolite and systolic blood pressure, respectively. These variants exerted more regulatory effects compared with other GWAS variants. The present study indicates that the genetic variants and candidate haplotypes of COVID-19 related genes are associated with blood pressure and blood metabolites. However, further observational studies are warranted to confirm these results.
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Affiliation(s)
- Morteza Gholami
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular‐Cellular Sciences InstituteTehran University of Medical SciencesTehranIran,Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences InstituteTehran University of Medical SciencesTehranIran
| | - Marziyeh Zoughi
- Metabolomics and genomics research center endocrinology and metabolism molecular‐cellular sciences instituteTehran University of medical sciencesTehranIran
| | - Mandana Hasanzad
- Personalized Medicine Research Center, Endocrinology and Metabolism Clinical Sciences InstituteTehran University of Medical SciencesTehranIran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences InstituteTehran University of Medical SciencesTehranIran
| | - Mahsa M. Amoli
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular‐Cellular Sciences InstituteTehran University of Medical SciencesTehranIran
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5
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Hoshi RA, Liu Y, Luttmann-Gibson H, Tiwari S, Giulianini F, Andres AM, Watrous JD, Cook NR, Costenbader KH, Okereke OI, Ridker PM, Manson JE, Lee IM, Vinayagamoorthy M, Cheng S, Copeland T, Jain M, Chasman DI, Demler OV, Mora S. Association of Physical Activity With Bioactive Lipids and Cardiovascular Events. Circ Res 2022; 131:e84-e99. [PMID: 35862024 PMCID: PMC9357171 DOI: 10.1161/circresaha.122.320952] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND To clarify the mechanisms underlying physical activity (PA)-related cardioprotection, we examined the association of PA with plasma bioactive lipids (BALs) and cardiovascular disease (CVD) events. We additionally performed genome-wide associations. METHODS PA-bioactive lipid associations were examined in VITAL (VITamin D and OmegA-3 TriaL)-clinical translational science center (REGISTRATION: URL: https://www. CLINICALTRIALS gov; Unique identifier: NCT01169259; N=1032) and validated in JUPITER (Justification for the Use of statins in Prevention: an Intervention Trial Evaluating Rosuvastatin)-NC (NCT00239681; N=589), using linear models adjusted for age, sex, race, low-density lipoprotein-cholesterol, total-C, and smoking. Significant BALs were carried over to examine associations with incident CVD in 2 nested CVD case-control studies: VITAL-CVD (741 case-control pairs) and JUPITER-CVD (415 case-control pairs; validation). RESULTS We detected 145 PA-bioactive lipid validated associations (false discovery rate <0.1). Annotations were found for 6 of these BALs: 12,13-diHOME, 9,10-diHOME, lysoPC(15:0), oxymorphone-3b-D-glucuronide, cortisone, and oleoyl-glycerol. Genetic analysis within JUPITER-NC showed associations of 32 PA-related BALs with 22 single-nucleotide polymorphisms. From PA-related BALs, 12 are associated with CVD. CONCLUSIONS We identified a PA-related bioactive lipidome profile out of which 12 BALs also had opposite associations with incident CVD events.
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Affiliation(s)
- Rosangela A Hoshi
- Center for Lipid Metabolomics, Division of Preventive Medicine, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., P.M.R., O.V.D., S.M.).,Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Yanyan Liu
- Center for Lipid Metabolomics, Division of Preventive Medicine, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., P.M.R., O.V.D., S.M.).,Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Heike Luttmann-Gibson
- Center for Lipid Metabolomics, Division of Preventive Medicine, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., P.M.R., O.V.D., S.M.).,Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.).,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (H.L.-G., O.I.O., J.E.M., I.-M.L., M.J.)
| | - Saumya Tiwari
- Department of Pharmacology, University of California San Diego, La Jolla (S.T., A.M.A., J.D.W.)
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Allen M Andres
- Department of Pharmacology, University of California San Diego, La Jolla (S.T., A.M.A., J.D.W.)
| | - Jeramie D Watrous
- Department of Pharmacology, University of California San Diego, La Jolla (S.T., A.M.A., J.D.W.)
| | - Nancy R Cook
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Karen H Costenbader
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (K.H.C.)
| | - Olivia I Okereke
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (H.L.-G., O.I.O., J.E.M., I.-M.L., M.J.).,Department of Psychiatry, Massachusetts General Hospital, Boston (O.I.O.)
| | - Paul M Ridker
- Center for Lipid Metabolomics, Division of Preventive Medicine, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., P.M.R., O.V.D., S.M.).,Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - JoAnn E Manson
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.).,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (H.L.-G., O.I.O., J.E.M., I.-M.L., M.J.)
| | - I-Min Lee
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.).,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (H.L.-G., O.I.O., J.E.M., I.-M.L., M.J.)
| | - Manickavasagar Vinayagamoorthy
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Susan Cheng
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA (S.C.)
| | - Trisha Copeland
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Mohit Jain
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (H.L.-G., O.I.O., J.E.M., I.-M.L., M.J.)
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
| | - Olga V Demler
- Center for Lipid Metabolomics, Division of Preventive Medicine, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., P.M.R., O.V.D., S.M.).,Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.).,Department of Computer Science, ETH Zurich, Switzerland (O.V.D.)
| | - Samia Mora
- Center for Lipid Metabolomics, Division of Preventive Medicine, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., P.M.R., O.V.D., S.M.).,Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. (R.A.H., Y.L., H.L.-G., F.G., N.R.C., P.M.R., J.E.M., I.-M.L., M.V., T.C., D.I.C., O.V.D., S.M.)
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6
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Resurreccion EP, Fong KW. The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer. Metabolites 2022; 12:metabo12060488. [PMID: 35736421 PMCID: PMC9230859 DOI: 10.3390/metabo12060488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/21/2022] [Accepted: 05/24/2022] [Indexed: 02/06/2023] Open
Abstract
Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.
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Affiliation(s)
- Eleazer P. Resurreccion
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY 40506, USA;
| | - Ka-wing Fong
- Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY 40506, USA;
- Markey Cancer Center, University of Kentucky, Lexington, KY 40506, USA
- Correspondence: ; Tel.: +1-859-562-3455
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7
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Van Bergen NJ, Hock DH, Spencer L, Massey S, Stait T, Stark Z, Lunke S, Roesley A, Peters H, Lee JY, Le Fevre A, Heath O, Mignone C, Yang JYM, Ryan MM, D’Arcy C, Nash M, Smith S, Caruana NJ, Thorburn DR, Stroud DA, White SM, Christodoulou J, Brown NJ. Biallelic Variants in PYROXD2 Cause a Severe Infantile Metabolic Disorder Affecting Mitochondrial Function. Int J Mol Sci 2022; 23:ijms23020986. [PMID: 35055180 PMCID: PMC8777681 DOI: 10.3390/ijms23020986] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/11/2022] [Accepted: 01/13/2022] [Indexed: 12/04/2022] Open
Abstract
Pyridine Nucleotide-Disulfide Oxidoreductase Domain 2 (PYROXD2; previously called YueF) is a mitochondrial inner membrane/matrix-residing protein and is reported to regulate mitochondrial function. The clinical importance of PYROXD2 has been unclear, and little is known of the protein’s precise biological function. In the present paper, we report biallelic variants in PYROXD2 identified by genome sequencing in a patient with suspected mitochondrial disease. The child presented with acute neurological deterioration, unresponsive episodes, and extreme metabolic acidosis, and received rapid genomic testing. He died shortly after. Magnetic resonance imaging (MRI) brain imaging showed changes resembling Leigh syndrome, one of the more common childhood mitochondrial neurological diseases. Functional studies in patient fibroblasts showed a heightened sensitivity to mitochondrial metabolic stress and increased mitochondrial superoxide levels. Quantitative proteomic analysis demonstrated decreased levels of subunits of the mitochondrial respiratory chain complex I, and both the small and large subunits of the mitochondrial ribosome, suggesting a mitoribosomal defect. Our findings support the critical role of PYROXD2 in human cells, and suggest that the biallelic PYROXD2 variants are associated with mitochondrial dysfunction, and can plausibly explain the child’s clinical presentation.
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Affiliation(s)
- Nicole J. Van Bergen
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Correspondence: (N.J.V.B.); (J.C.); (N.J.B.)
| | - Daniella H. Hock
- Department of Biochemistry and Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC 3010, Australia; (D.H.H.); (N.J.C.)
| | - Lucy Spencer
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
| | - Sean Massey
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
| | - Tegan Stait
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
| | - Zornitza Stark
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
- Australian Genomics Health Alliance, Parkville, VIC 3052, Australia
| | - Sebastian Lunke
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Department of Pathology, University of Melbourne, Parkville, VIC 3010, Australia
| | - Ain Roesley
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
| | - Heidi Peters
- Department of Metabolic Medicine, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (H.P.); (O.H.)
| | - Joy Yaplito Lee
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Department of Metabolic Medicine, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (H.P.); (O.H.)
| | - Anna Le Fevre
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
| | - Oliver Heath
- Department of Metabolic Medicine, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (H.P.); (O.H.)
| | - Cristina Mignone
- Medical Imaging Department, Royal Children’s Hospital, Parkville, VIC 3052, Australia;
| | - Joseph Yuan-Mou Yang
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children’s Hospital, Parkville, VIC 3052, Australia
- Developmental Imaging, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia
- Neuroscience Research, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia
| | - Monique M. Ryan
- Neurology Department, Royal Children’s Hospital, Parkville, VIC 3052, Australia;
| | - Colleen D’Arcy
- Anatomical Pathology Department, Royal Children’s Hospital, Parkville, VIC 3052, Australia;
| | - Margot Nash
- General Medicine, Royal Children’s Hospital, Parkville, VIC 3052, Australia;
| | - Sile Smith
- Paediatric Intensive Care Unit, Royal Children’s Hospital, Parkville, VIC 3052, Australia;
| | - Nikeisha J. Caruana
- Department of Biochemistry and Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC 3010, Australia; (D.H.H.); (N.J.C.)
- Institute for Health and Sport (iHeS), Victoria University, Footscray, VIC 3011, Australia
| | - David R. Thorburn
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
| | - David A. Stroud
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
- Department of Biochemistry and Pharmacology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC 3010, Australia; (D.H.H.); (N.J.C.)
| | - Susan M. White
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
| | - John Christodoulou
- Brain and Mitochondrial Research Group, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia; (L.S.); (S.M.); (T.S.); (D.R.T.); (D.A.S.)
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
- Discipline of Child and Adolescent Health, University of Sydney, Camperdown, NSW 2006, Australia
- Correspondence: (N.J.V.B.); (J.C.); (N.J.B.)
| | - Natasha J. Brown
- Department of Paediatrics, University of Melbourne, Parkville, VIC 3010, Australia; (Z.S.); (S.L.); (J.Y.L.); (J.Y.-M.Y.); (S.M.W.)
- Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Parkville, VIC 3052, Australia; (A.R.); (A.L.F.)
- Correspondence: (N.J.V.B.); (J.C.); (N.J.B.)
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8
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Sönmez Flitman R, Khalili B, Kutalik Z, Rueedi R, Brümmer A, Bergmann S. Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine. J Proteome Res 2021; 20:5103-5114. [PMID: 34699229 PMCID: PMC9286311 DOI: 10.1021/acs.jproteome.1c00585] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
![]()
Gene products can
affect the concentrations of small molecules
(aka “metabolites”), and conversely, some metabolites
can modulate the concentrations of gene transcripts. While many specific
instances of this interplay have been revealed, a global approach
to systematically uncover human gene-metabolite interactions is still
lacking. We performed a metabolome- and transcriptome-wide association
study to identify genes influencing the human metabolome using untargeted
metabolome features, extracted from 1H nuclear magnetic
resonance spectroscopy (NMR) of urine samples, and gene expression
levels, quantified from RNA-Seq of lymphoblastoid cell lines (LCL)
from 555 healthy individuals. We identified 20 study-wide significant
associations corresponding to 15 genes, of which 5 associations (with
2 genes) were confirmed with follow-up NMR data. Using metabomatching,
we identified the metabolites corresponding to metabolome features
associated with the genes, namely, N-acetylated compounds with ALMS1 and trimethylamine (TMA) with HPS1. Finally, Mendelian randomization analysis supported a potential
causal link between the expression of genes in both the ALMS1- and HPS1-loci and their associated metabolite
concentrations. In the case of HPS1, we additionally
observed that TMA concentration likely exhibits a reverse causal effect
on HPS1 expression levels, indicating a negative
feedback loop. Our study highlights how the integration of metabolomics,
gene expression, and genetic data can pinpoint causal genes modulating
metabolite concentrations.
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Affiliation(s)
- Reyhan Sönmez Flitman
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Bita Khalili
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Zoltan Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.,University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Anneke Brümmer
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.,Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town 7700, South Africa
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9
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Luo S, Feofanova EV, Tin A, Tung S, Rhee EP, Coresh J, Arking DE, Surapaneni A, Schlosser P, Li Y, Köttgen A, Yu B, Grams ME. Genome-wide association study of serum metabolites in the African American Study of Kidney Disease and Hypertension. Kidney Int 2021; 100:430-439. [PMID: 33838163 PMCID: PMC8583323 DOI: 10.1016/j.kint.2021.03.026] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 02/26/2021] [Accepted: 03/11/2021] [Indexed: 01/23/2023]
Abstract
The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. To date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73m2) in the African American Study of Kidney Disease and Hypertension, a clinical trial of blood pressure lowering and antihypertensive medication in African Americans with chronic kidney disease. We identified 42 significant variant metabolite associations. Twenty associations had been previously identified in published GWAS, and eleven novel associations were replicated in a separate cohort of 818 African Americans with genetic and metabolomic data from the Atherosclerosis Risk in Communities Study. The replicated novel variant-metabolite associations comprised eight metabolites and eleven distinct genomic loci. Nine of the replicated associations represented clear enzyme-metabolite interactions, with high expression in the kidneys as well as the liver. Three loci (ACY1, ACY3, and NAT8) were associated with a common pool of metabolites, acetylated amino acids, but with different individual affinities. Thus, extensive metabolite profiling in an African American population with chronic kidney disease aided identification of novel genome-wide metabolite associations, providing clues about substrate specificity and the key roles of enzymes in modulating systemic levels of metabolites.
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Affiliation(s)
- Shengyuan Luo
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA.
| | - Elena V Feofanova
- Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Sarah Tung
- Johns Hopkins Whiting School of Engineering, Baltimore, Maryland, USA
| | - Eugene P Rhee
- Division of Nephrology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Dan E Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Aditya Surapaneni
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Bing Yu
- Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA; Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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10
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Chu X, Jaeger M, Beumer J, Bakker OB, Aguirre-Gamboa R, Oosting M, Smeekens SP, Moorlag S, Mourits VP, Koeken VACM, de Bree C, Jansen T, Mathews IT, Dao K, Najhawan M, Watrous JD, Joosten I, Sharma S, Koenen HJPM, Withoff S, Jonkers IH, Netea-Maier RT, Xavier RJ, Franke L, Xu CJ, Joosten LAB, Sanna S, Jain M, Kumar V, Clevers H, Wijmenga C, Netea MG, Li Y. Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease. Genome Biol 2021; 22:198. [PMID: 34229738 PMCID: PMC8259168 DOI: 10.1186/s13059-021-02413-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 06/21/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Recent studies highlight the role of metabolites in immune diseases, but it remains unknown how much of this effect is driven by genetic and non-genetic host factors. RESULT We systematically investigate circulating metabolites in a cohort of 500 healthy subjects (500FG) in whom immune function and activity are deeply measured and whose genetics are profiled. Our data reveal that several major metabolic pathways, including the alanine/glutamate pathway and the arachidonic acid pathway, have a strong impact on cytokine production in response to ex vivo stimulation. We also examine the genetic regulation of metabolites associated with immune phenotypes through genome-wide association analysis and identify 29 significant loci, including eight novel independent loci. Of these, one locus (rs174584-FADS2) associated with arachidonic acid metabolism is causally associated with Crohn's disease, suggesting it is a potential therapeutic target. CONCLUSION This study provides a comprehensive map of the integration between the blood metabolome and immune phenotypes, reveals novel genetic factors that regulate blood metabolite concentrations, and proposes an integrative approach for identifying new disease treatment targets.
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Affiliation(s)
- Xiaojing Chu
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine, CiiM, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Martin Jaeger
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Joep Beumer
- Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, 3584, CT, Utrecht, the Netherlands
| | - Olivier B Bakker
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Raul Aguirre-Gamboa
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Marije Oosting
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Sanne P Smeekens
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Simone Moorlag
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Vera P Mourits
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Valerie A C M Koeken
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine, CiiM, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Charlotte de Bree
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Trees Jansen
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Ian T Mathews
- Departments of Medicine and Pharmacology, University of California, San Diego, CA, USA
- La Jolla Institute, La Jolla, CA, USA
| | - Khoi Dao
- Departments of Medicine and Pharmacology, University of California, San Diego, CA, USA
| | - Mahan Najhawan
- Departments of Medicine and Pharmacology, University of California, San Diego, CA, USA
| | - Jeramie D Watrous
- Departments of Medicine and Pharmacology, University of California, San Diego, CA, USA
| | - Irma Joosten
- Department of Laboratory Medicine, Laboratory for Medical Immunology, Radboud University Medical Center, 6525, GA, Nijmegen, the Netherlands
| | | | - Hans J P M Koenen
- Department of Laboratory Medicine, Laboratory for Medical Immunology, Radboud University Medical Center, 6525, GA, Nijmegen, the Netherlands
| | - Sebo Withoff
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Iris H Jonkers
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Romana T Netea-Maier
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Ramnik J Xavier
- Broad Institute of MIT and Harvard University, Cambridge, MA, 02142, USA
- Center for Computational and Integrative Biology and Gastrointestinal Unit, Massachusetts General Hospital, Harvard School of Medicine, Boston, MA, 02114, USA
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Cheng-Jian Xu
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine, CiiM, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Leo A B Joosten
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands
| | - Serena Sanna
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Mohit Jain
- Departments of Medicine and Pharmacology, University of California, San Diego, CA, USA
| | - Vinod Kumar
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands
| | - Hans Clevers
- Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht, 3584, CT, Utrecht, the Netherlands
- Oncode Institute, Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584, CS, Utrecht, the Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands.
- Department of Immunology, University of Oslo, Oslo University Hospital, Rikshospitalet, 0372, Oslo, Norway.
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands.
- Department for Genomics & Immunoregulation, Life and Medical Sciences Institute (LIMES), University of Bonn, 53115, Bonn, Germany.
| | - Yang Li
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700, RB, Groningen, the Netherlands.
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine, CiiM, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany.
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany.
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, 6525, HP, Nijmegen, the Netherlands.
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11
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Lu H, Zhang J, Chen YE, Garcia-Barrio MT. Integration of Transformative Platforms for the Discovery of Causative Genes in Cardiovascular Diseases. Cardiovasc Drugs Ther 2021; 35:637-654. [PMID: 33856594 DOI: 10.1007/s10557-021-07175-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/18/2021] [Indexed: 12/11/2022]
Abstract
Cardiovascular diseases are the leading cause of morbidity and mortality worldwide. Genome-wide association studies (GWAS) are powerful epidemiological tools to find genes and variants associated with cardiovascular diseases while follow-up biological studies allow to better understand the etiology and mechanisms of disease and assign causality. Improved methodologies and reduced costs have allowed wider use of bulk and single-cell RNA sequencing, human-induced pluripotent stem cells, organoids, metabolomics, epigenomics, and novel animal models in conjunction with GWAS. In this review, we feature recent advancements relevant to cardiovascular diseases arising from the integration of genetic findings with multiple enabling technologies within multidisciplinary teams to highlight the solidifying transformative potential of this approach. Well-designed workflows integrating different platforms are greatly improving and accelerating the unraveling and understanding of complex disease processes while promoting an effective way to find better drug targets, improve drug design and repurposing, and provide insight towards a more personalized clinical practice.
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Affiliation(s)
- Haocheng Lu
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA
| | - Jifeng Zhang
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA.,Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical Center, Ann Arbor, MI, 48109, USA
| | - Y Eugene Chen
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA. .,Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical Center, Ann Arbor, MI, 48109, USA.
| | - Minerva T Garcia-Barrio
- Department of Internal Medicine, University of Michigan Medical Center, 2800 Plymouth Rd, Ann Arbor, MI, 48109-2800, USA.
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12
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He S, Lyu F, Lou L, Liu L, Li S, Jakowitsch J, Ma Y. Anti-tumor activities of Panax quinquefolius saponins and potential biomarkers in prostate cancer. J Ginseng Res 2021; 45:273-286. [PMID: 33841008 PMCID: PMC8020356 DOI: 10.1016/j.jgr.2019.12.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 10/28/2019] [Accepted: 12/30/2019] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Prostate carcinoma is the second most common cancer among men worldwide. Developing new therapeutic approaches and diagnostic biomarkers for prostate cancer (PC) is a significant need. The Chinese herbal medicine Panax quinquefolius saponins (PQS) have been reported to show anti-tumor effects. We hypothesized that PQS exhibits anti-cancer activity in human PC cells and we aimed to search for novel biomarkers allowing early diagnosis of PC. METHODS We used the human PC cell line DU145 and the prostate epithelial cell line PNT2 to perform cell viability assays, flow cytometric analysis of the cell cycle, and FACS-based apoptosis assays. Microarray-based gene expression analysis was used to display specific gene expression patterns and to search for novel biomarkers. Western blot and quantitative real-time PCR were performed to demonstrate the expression levels of multiple cancer-related genes. RESULTS Our data showed that PQS inhibited the viability of DU145 cells and induced cell cycle arrest at the G1 phase. A significant decrease in DU145 cell invasion and migration were observed after 24 h treatment by PQS. PQS up-regulated the expression levels of p21, p53, TMEM79, ACOXL, ETV5, and SPINT1 while it down-regulated the expression levels of bcl2, STAT3, FANCD2, DRD2, and TMPRSS2. CONCLUSION PQS promoted cells apoptosis and inhibited the proliferation of DU145 cells, which suggests that PQS may be effective for treating PC. TMEM79 and ACOXL were expressed significantly higher in PNT2 than in DU145 cells and could be novel biomarker candidates for PC diagnosis.
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Key Words
- ACOXL, Acyl-CoA oxidase-like protein
- Chinese medicinal herbs
- DRD2, dopamine receptor D2
- ETV5, ETS variant 5
- FACS, fluorescence-activated cell sorting
- FANCD2, fanconi anemia group D2
- PC, prostate cancer
- PQS, Panax quinquefolius saponins
- Panax quinquefolius
- Potential biomarkers
- Prostate cancer cells
- SPINT1, serine peptidase inhibitor Kunitz type 1
- STAT3, signal transducer and activator of transcription 3
- TCM, Traditional Chinese Medicine
- TMEM79, transmembrane protein 79
- TMPRSS2, transmembrane protease serine 2
- bcl2, B-cell lymphoma 2
- p21, cyclin-dependent kinase inhibitor p21
- p53, tumor suppressor p53
- qRT-PCR, quantitative real-time PCR
- saponins
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Affiliation(s)
- Shan He
- Department of Pathophysiology and Allergy Research, Center of Pathophysiology, Infectiology & Immunology, Vienna General Hospital, Medical University of Vienna, Vienna, Austria
| | - Fangqiao Lyu
- Department of Cell Biology, School of Basic Medicine, Capital Medical University, Beijing, China
| | - Lixia Lou
- The Key Laboratory of Chinese Internal Medicine of Ministry of Education, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Lu Liu
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Songlin Li
- Department of Pharmaceutical Analysis and Metabolomics, Jiangsu Province Academy of Traditional Chinese Medicine and Jiangsu Branch of China Academy of Chinese Medical Sciences, Nanjing, China
| | - Johannes Jakowitsch
- Department of Internal Medicine, Vienna General Hospital, Medical University of Vienna, Vienna, Austria
| | - Yan Ma
- Department of Pathophysiology and Allergy Research, Center of Pathophysiology, Infectiology & Immunology, Vienna General Hospital, Medical University of Vienna, Vienna, Austria
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13
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ACAD10 protein expression and Neurobehavioral assessment of Acad10-deficient mice. PLoS One 2020; 15:e0242445. [PMID: 33301490 PMCID: PMC7728233 DOI: 10.1371/journal.pone.0242445] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 11/02/2020] [Indexed: 11/19/2022] Open
Abstract
Acyl-CoA dehydrogenase 10 (Acad10)-deficient mice develop impaired glucose tolerance, peripheral insulin resistance, and abnormal weight gain. In addition, they exhibit biochemical features of deficiencies of fatty acid oxidation, such as accumulation of metabolites consistent with abnormal mitochondrial energy metabolism and fasting induced rhabdomyolysis. ACAD10 has significant expression in mouse brain, unlike other acyl-CoA dehydrogenases (ACADs) involved in fatty acid oxidation. The presence of ACAD10 in human tissues was determined using immunohistochemical staining. To characterize the effect of ACAD10 deficiency on the brain, micro-MRI and neurobehavioral evaluations were performed. Acad10-deficient mouse behavior was examined using open field testing and DigiGait analysis for changes in general activity as well as indices of gait, respectively. ACAD10 protein was shown to colocalize to mitochondria and peroxisomes in lung, muscle, kidney, and pancreas human tissue. Acad10-deficient mice demonstrated subtle behavioral abnormalities, which included reduced activity and increased time in the arena perimeter in the open field test. Mutant animals exhibited brake and propulsion metrics similar to those of control animals, which indicates normal balance, stability of gait, and the absence of significant motor impairment. The lack of evidence for motor impairment combined with avoidance of the center of an open field arena and reduced vertical and horizontal exploration are consistent with a phenotype characterized by elevated anxiety. These results implicate ACAD10 function in normal mouse behavior, which suggests a novel role for ACAD10 in brain metabolism.
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14
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Iacobas DA. Powerful quantifiers for cancer transcriptomics. World J Clin Oncol 2020; 11:679-704. [PMID: 33033692 PMCID: PMC7522543 DOI: 10.5306/wjco.v11.i9.679] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 06/06/2020] [Accepted: 07/01/2020] [Indexed: 02/06/2023] Open
Abstract
Every day, investigators find a new link between a form of cancer and a particular alteration in the sequence or/and expression level of a key gene, awarding this gene the title of “biomarker”. The clinician may choose from numerous available panels to assess the type of cancer based on the mutation or expression regulation (“transcriptomic signature”) of “driver” genes. However, cancer is not a “one-gene show” and, together with the alleged biomarker, hundreds other genes are found as mutated or/and regulated in cancer samples. Regardless of the platform, a well-designed transcriptomic study produces three independent features for each gene: Average expression level, expression variability and coordination with expression of each other gene. While the average expression level is used in all studies to identify what genes were up-/down-regulated or turn on/off, the other two features are unfairly ignored. We use all three features to quantify the transcriptomic change during the progression of the disease and recovery in response to a treatment. Data from our published microarray experiments on cancer nodules and surrounding normal tissue from surgically removed tumors prove that the transcriptomic topologies are not only different in histopathologically distinct regions of a tumor but also dynamic and unique for each human being. We show also that the most influential genes in cancer nodules [the Gene Master Regulators (GMRs)] are significantly less influential in the normal tissue. As such, “smart” manipulation of the cancer GMRs expression may selectively kill cancer cells with little consequences on the normal ones. Therefore, we strongly recommend a really personalized approach of cancer medicine and present the experimental procedure and the mathematical algorithm to identify the most legitimate targets (GMRs) for gene therapy.
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Affiliation(s)
- Dumitru Andrei Iacobas
- Personalized Genomics Laboratory, CRI Center for Computational Systems Biology, Roy G Perry College of Engineering, Prairie View A&M University, Prairie View, TX 77446, United States
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15
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Beck ME, Zhang Y, Bharathi SS, Kosmider B, Bahmed K, Dahmer MK, Nogee LM, Goetzman ES. The common K333Q polymorphism in long-chain acyl-CoA dehydrogenase (LCAD) reduces enzyme stability and function. Mol Genet Metab 2020; 131:83-89. [PMID: 32389575 PMCID: PMC7606262 DOI: 10.1016/j.ymgme.2020.04.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 04/21/2020] [Accepted: 04/21/2020] [Indexed: 01/19/2023]
Abstract
The fatty acid oxidation enzyme long-chain acyl-CoA dehydrogenase (LCAD) is expressed at high levels in human alveolar type II (ATII) cells in the lung. A common polymorphism causing an amino acid substitution (K333Q) was previously linked to a loss of LCAD antigen in the lung tissue in sudden infant death syndrome. However, the effects of the polymorphism on LCAD function has not been tested. The present work evaluated recombinant LCAD K333Q. Compared to wild-type LCAD protein, LCAD K333Q exhibited significantly reduced enzymatic activity. Molecular modeling suggested that K333 is within interacting distance of the essential FAD cofactor, and the K333Q protein showed a propensity to lose FAD. Exogenous FAD only partially rescued the activity of LCAD K333Q. LCAD K333Q protein was less stable than wild-type when incubated at physiological temperatures, likely explaining the observation of dramatically reduced LCAD antigen in primary ATII cells isolated from individuals homozygous for K333Q. Despite the effect of K333Q on activity, stability, and antigen levels, the frequency of the polymorphism was not increased among infants and children with lung disease.
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Affiliation(s)
- Megan E Beck
- Department of Pediatrics, Division of Medical Genetics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States of America
| | - Yuxun Zhang
- Department of Pediatrics, Division of Medical Genetics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States of America
| | - Sivakama S Bharathi
- Department of Pediatrics, Division of Medical Genetics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States of America
| | - Beata Kosmider
- Department of Physiology, Temple University, Philadelphia, PA 19140, United States of America; Department of Thoracic Medicine and Surgery, Temple University, Philadelphia, PA 19140, United States of America; Center for Inflammation, Translational and Clinical Lung Research, Temple University, Philadelphia, PA 19140, United States of America; Department of Medicine, National Jewish Health, Denver, CO 80206, United States of America
| | - Karim Bahmed
- Department of Thoracic Medicine and Surgery, Temple University, Philadelphia, PA 19140, United States of America; Center for Inflammation, Translational and Clinical Lung Research, Temple University, Philadelphia, PA 19140, United States of America
| | - Mary K Dahmer
- Department of Pediatrics, Division of Critical Care, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Lawrence M Nogee
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States of America
| | - Eric S Goetzman
- Department of Pediatrics, Division of Medical Genetics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA 15224, United States of America.
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16
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Stevelink R, Pangilinan F, Jansen FE, Braun KPJ, Molloy AM, Brody LC, Koeleman BPC. Assessing the genetic association between vitamin B6 metabolism and genetic generalized epilepsy. Mol Genet Metab Rep 2019; 21:100518. [PMID: 31641590 PMCID: PMC6796782 DOI: 10.1016/j.ymgmr.2019.100518] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 09/07/2019] [Indexed: 01/23/2023] Open
Abstract
Altered vitamin B6 metabolism due to pathogenic variants in the gene PNPO causes early onset epileptic encephalopathy, which can be treated with high doses of vitamin B6. We recently reported that single nucleotide polymorphisms (SNPs) that influence PNPO expression in the brain are associated with genetic generalized epilepsy (GGE). However, it is not known whether any of these GGE-associated SNPs influence vitamin B6 metabolite levels. Such an influence would suggest that vitamin B6 could play a role in GGE therapy. Here, we performed genome-wide association studies (GWAS) to assess the influence of GGE associated genetic variants on measures of vitamin B6 metabolism in blood plasma in 2232 healthy individuals. We also asked if SNPs that influence vitamin B6 were associated with GGE in 3122 affected individuals and 20,244 controls. Our GWAS of vitamin B6 metabolites reproduced a previous association and found a novel genome-wide significant locus. The SNPs in these loci were not associated with GGE. We found that 84 GGE-associated SNPs influence expression levels of PNPO in the brain as well as in blood. However, these SNPs were not associated with vitamin B6 metabolism in plasma. By leveraging polygenic risk scoring (PRS), we found suggestive evidence of higher catabolism and lower levels of the active and transport forms of vitamin B6 in GGE, although these findings require further replication.
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Affiliation(s)
- Remi Stevelink
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, the Netherlands.,Department of Child Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Faith Pangilinan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Floor E Jansen
- Department of Child Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Kees P J Braun
- Department of Child Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - Anne M Molloy
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Lawrence C Brody
- National Human Genome Research Institute, National Institutes of Health, Bethesda, USA
| | - Bobby P C Koeleman
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
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17
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An acyl-CoA dehydrogenase microplate activity assay using recombinant porcine electron transfer flavoprotein. Anal Biochem 2019; 581:113332. [PMID: 31194945 DOI: 10.1016/j.ab.2019.06.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 06/03/2019] [Accepted: 06/03/2019] [Indexed: 12/12/2022]
Abstract
Acyl-CoA dehydrogenases (ACADs) play key roles in the mitochondrial catabolism of fatty acids and branched-chain amino acids. All nine characterized ACAD enzymes use electron transfer flavoprotein (ETF) as their redox partner. The gold standard for measuring ACAD activity is the anaerobic ETF fluorescence reduction assay, which follows the decrease of pig ETF fluorescence as it accepts electrons from an ACAD in vitro. Although first described 35 years ago, the assay has not been widely used due to the need to maintain an anaerobic assay environment and to purify ETF from pig liver mitochondria. Here, we present a method for expressing recombinant pig ETF in E coli and purifying it to homogeneity. The recombinant protein is virtually pure after one chromatography step, bears higher intrinsic fluorescence than the native enzyme, and provides enhanced activity in the ETF fluorescence reduction assay. Finally, we present a simplified protocol for removing molecular oxygen that allows adaption of the assay to a 96-well plate format. The availability of recombinant pig ETF and the microplate version of the ACAD activity assay will allow wide application of the assay for both basic research and clinical diagnostics.
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18
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Matejka K, Stückler F, Salomon M, Ensenauer R, Reischl E, Hoerburger L, Grallert H, Kastenmüller G, Peters A, Daniel H, Krumsiek J, Theis FJ, Hauner H, Laumen H. Dynamic modelling of an ACADS genotype in fatty acid oxidation - Application of cellular models for the analysis of common genetic variants. PLoS One 2019; 14:e0216110. [PMID: 31120904 PMCID: PMC6532850 DOI: 10.1371/journal.pone.0216110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Accepted: 04/15/2019] [Indexed: 11/19/2022] Open
Abstract
Background Genome-wide association studies of common diseases or metabolite quantitative traits often identify common variants of small effect size, which may contribute to phenotypes by modulation of gene expression. Thus, there is growing demand for cellular models enabling to assess the impact of gene regulatory variants with moderate effects on gene expression. Mitochondrial fatty acid oxidation is an important energy metabolism pathway. Common noncoding acyl-CoA dehydrogenase short chain (ACADS) gene variants are associated with plasma C4-acylcarnitine levels and allele-specific modulation of ACADS expression may contribute to the observed phenotype. Methods and findings We assessed ACADS expression and intracellular acylcarnitine levels in human lymphoblastoid cell lines (LCL) genotyped for a common ACADS variant associated with plasma C4-acylcarnitine and found a significant genotype-dependent decrease of ACADS mRNA and protein. Next, we modelled gradual decrease of ACADS expression using a tetracycline-regulated shRNA-knockdown of ACADS in Huh7 hepatocytes, a cell line with high fatty acid oxidation-(FAO)-capacity. Assessing acylcarnitine flux in both models, we found increased C4-acylcarnitine levels with decreased ACADS expression levels. Moreover, assessing time-dependent changes of acylcarnitine levels in shRNA-hepatocytes with altered ACADS expression levels revealed an unexpected effect on long- and medium-chain fatty acid intermediates. Conclusions Both, genotyped LCL and regulated shRNA-knockdown are valuable tools to model moderate, gradual gene-regulatory effects of common variants on cellular phenotypes. Decreasing ACADS expression levels modulate short and surprisingly also long/medium chain acylcarnitines, and may contribute to increased plasma acylcarnitine levels.
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Affiliation(s)
- Kerstin Matejka
- Chair of Nutritional Medicine, Else Kröner-Fresenius-Center for Nutritional Medicine, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- ZIEL-Research Center for Nutrition and Food Sciences, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Helmholtz Zentrum München, Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Technische Universität München, Freising-Weihenstephan, Germany
| | - Ferdinand Stückler
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | | | - Regina Ensenauer
- Research Center, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians-Universität München, München, Germany
- Experimental Pediatrics and Metabolism, Department of General Pediatrics, Neonatology and Pediatric Cardiology, University Children’s Hospital, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Child Nutrition, Max Rubner-Institut, Karlsruhe, Germany
| | - Eva Reischl
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Lena Hoerburger
- Paediatric Nutritional Medicine, Else Kröner-Fresenius-Centre for Nutritional Medicine, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
| | - Harald Grallert
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Helmholtz Zentrum München, Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Technische Universität München, Freising-Weihenstephan, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK-Munich partner site), Neuherberg, Germany
| | - Hannelore Daniel
- ZIEL-Research Center for Nutrition and Food Sciences, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- Chair of Physiology of Human Nutrition, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, United States of America
| | - Fabian J. Theis
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Mathematical Science, Technische Universität München, Garching, Germany
- * E-mail: (FJT); (HL)
| | - Hans Hauner
- Chair of Nutritional Medicine, Else Kröner-Fresenius-Center for Nutritional Medicine, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- ZIEL-Research Center for Nutrition and Food Sciences, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Helmholtz Zentrum München, Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Technische Universität München, Freising-Weihenstephan, Germany
- Else Kröner-Fresenius-Center for Nutritional Medicine, Klinikum rechts der Isar, Technische Universität München, München, Germany
| | - Helmut Laumen
- Chair of Nutritional Medicine, Else Kröner-Fresenius-Center for Nutritional Medicine, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- ZIEL-Research Center for Nutrition and Food Sciences, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Helmholtz Zentrum München, Neuherberg, Germany
- Clinical Cooperation Group Nutrigenomics and Type 2 Diabetes, Technische Universität München, Freising-Weihenstephan, Germany
- Paediatric Nutritional Medicine, Else Kröner-Fresenius-Centre for Nutritional Medicine, TUM School of Life Sciences Weihenstephan, Technische Universität München, Freising-Weihenstephan, Germany
- Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Research Unit Protein Science, Helmholtz Zentrum München, Neuherberg, Germany
- * E-mail: (FJT); (HL)
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19
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Köttgen A, Raffler J, Sekula P, Kastenmüller G. Genome-Wide Association Studies of Metabolite Concentrations (mGWAS): Relevance for Nephrology. Semin Nephrol 2019; 38:151-174. [PMID: 29602398 DOI: 10.1016/j.semnephrol.2018.01.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Metabolites are small molecules that are intermediates or products of metabolism, many of which are freely filtered by the kidneys. In addition, the kidneys have a central role in metabolite anabolism and catabolism, as well as in active metabolite reabsorption and/or secretion during tubular passage. This review article illustrates how the coupling of genomics and metabolomics in genome-wide association analyses of metabolites can be used to illuminate mechanisms underlying human metabolism, with a special focus on insights relevant to nephrology. First, genetic susceptibility loci for reduced kidney function and chronic kidney disease (CKD) were reviewed systematically for their associations with metabolite concentrations in metabolomics studies of blood and urine. Second, kidney function and CKD-associated metabolites reported from observational studies were interrogated for metabolite-associated genetic variants to generate and discuss complementary insights. Finally, insights originating from the simultaneous study of both blood and urine or by modeling intermetabolite relationships are summarized. We also discuss methodologic questions related to the study of metabolite concentrations in urine as well as among CKD patients. In summary, genome-wide association analyses of metabolites using metabolite concentrations quantified from blood and/or urine are a promising avenue of research to illuminate physiological and pathophysiological functions of the kidney.
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Affiliation(s)
- Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
| | - Johannes Raffler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
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20
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Peng L, Guo JC, Long L, Pan F, Zhao JM, Xu LY, Li EM. A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma. BIOMED RESEARCH INTERNATIONAL 2019; 2019:3869825. [PMID: 31815134 PMCID: PMC6878914 DOI: 10.1155/2019/3869825] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 08/23/2019] [Accepted: 10/04/2019] [Indexed: 02/05/2023]
Abstract
Flavoproteins and their interacting proteins play important roles in mitochondrial electron transport, fatty acid degradation, and redox regulation. However, their clinical significance and function in esophageal squamous cell carcinoma (ESCC) are little known. Here, using survival analysis and machine learning, we mined 179 patient expression profiles with ESCC in GSE53625 from the Gene Expression Omnibus (GEO) database and constructed a signature consisting of two flavoprotein genes (GPD2 and PYROXD2) and four flavoprotein interacting protein genes (CTTN, GGH, SRC, and SYNJ2BP). Kaplan-Meier analysis revealed the signature was significantly associated with the survival of ESCC patients (mean survival time: 26.77 months in the high-risk group vs. 54.97 months in the low-risk group, P < 0.001, n = 179), and time-dependent ROC analysis demonstrated that the six-gene signature had good predictive ability for six-year survival for ESCC (AUC = 0.86, 95% CI: 0.81-0.90). We then validated its prediction performance in an independent set by RT-PCR (mean survival: 15.73 months in the high-risk group vs. 21.1 months in the low-risk group, P=0.032, n = 121). Furthermore, RNAi-mediated knockdown of genes in the flavoprotein signature led to decreased proliferation and migration of ESCC cells. Taken together, CTTN, GGH, GPD2, PYROXD2, SRC, and SYNJ2BP have an important clinical significance for prognosis of ESCC patients, suggesting they are efficient prognostic markers and potential targets for ESCC therapy.
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Affiliation(s)
- Liu Peng
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, China
| | - Jin-Cheng Guo
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, China
| | - Lin Long
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, China
| | - Feng Pan
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, China
| | - Jian-Mei Zhao
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, China
| | - Li-Yan Xu
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Institute of Oncologic Pathology, Shantou University Medical College, Shantou 515041, Guangdong, China
| | - En-Min Li
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, Guangdong, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, Guangdong, China
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21
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Li MJ, Zhang J, Liang Q, Xuan C, Wu J, Jiang P, Li W, Zhu Y, Wang P, Fernandez D, Shen Y, Chen Y, Kocher JPA, Yu Y, Sham PC, Wang J, Liu JS, Liu XS. Exploring genetic associations with ceRNA regulation in the human genome. Nucleic Acids Res 2017; 45:5653-5665. [PMID: 28472449 PMCID: PMC5449616 DOI: 10.1093/nar/gkx331] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 04/26/2017] [Indexed: 01/01/2023] Open
Abstract
Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project. We call these loci competing endogenous RNA expression quantitative trait loci or 'cerQTL', and found that a large number of them were unexplored in conventional eQTL mapping. We identified many cerQTLs that have undergone recent positive selection in different human populations, and showed that single nucleotide polymorphisms in gene 3΄UTRs at the miRNA seed binding regions can simultaneously regulate gene expression changes in both cis and trans by the ceRNA mechanism. We also discovered that cerQTLs are significantly enriched in traits/diseases associated variants reported from genome-wide association studies in the miRNA binding sites, suggesting that disease susceptibilities could be attributed to ceRNA regulation. Further in vitro functional experiments demonstrated that a cerQTL rs11540855 can regulate ceRNA function. These results provide a comprehensive catalog of functional non-coding regulatory variants that may be responsible for ceRNA crosstalk at the post-transcriptional level.
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Affiliation(s)
- Mulin Jun Li
- Department of pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Statistics, Harvard University, Cambridge, MA 02138, USA.,Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Jian Zhang
- Department of pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Qian Liang
- Department of pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Chenghao Xuan
- Department of pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jiexing Wu
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - Peng Jiang
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
| | - Wei Li
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
| | - Yun Zhu
- Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China.,School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Panwen Wang
- Department of Health Sciences Research & Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ 85259, USA
| | - Daniel Fernandez
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - Yujun Shen
- Department of pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yiwen Chen
- Department of Bioinformatics and Computational Biology, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jean-Pierre A Kocher
- Department of Health Sciences Research & Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ 85259, USA
| | - Ying Yu
- Department of pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Pak Chung Sham
- Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China.,Department of Psychiatry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Junwen Wang
- Department of Health Sciences Research & Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ 85259, USA.,Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ 85259, USA
| | - Jun S Liu
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - X Shirley Liu
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
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22
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Rifkin SB, Shrubsole MJ, Cai Q, Smalley WE, Ness RM, Swift LL, Zheng W, Murff HJ. PUFA levels in erythrocyte membrane phospholipids are differentially associated with colorectal adenoma risk. Br J Nutr 2017; 117:1615-1622. [PMID: 28660850 PMCID: PMC5891121 DOI: 10.1017/s0007114517001490] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Dietary intake of PUFA has been associated with colorectal neoplasm risk; however, results from observational studies have been inconsistent. Most prior studies have utilised self-reported dietary measures to assess fatty acid exposure which might be more susceptible to measurement error and biases compared with biomarkers. The purpose of this study was to determine whether erythrocyte phospholipid membrane PUFA percentages are associated with colorectal adenoma risk. We included data from 904 adenoma cases and 835 polyp-free controls who participated in the Tennessee Colorectal Polyp Study, a large colonoscopy-based case-control study. Erythrocyte membrane PUFA percentages were measured using GC. Conditional logistic regression was used to calculate adjusted OR for risk of colorectal adenomas with erythrocyte membrane PUFA. Higher erythrocyte membrane percentages of arachidonic acid was associated with an increased risk of colorectal adenomas (adjusted OR 1·66; 95 % CI 1·05, 2·62, P trend=0·02) comparing the highest tertile to the lowest tertile. The effect size for arachidonic acid was more pronounced when restricting the analysis to advanced adenomas only. Higher erythrocyte membrane EPA percentages were associated with a trend towards a reduced risk of advanced colorectal adenomas (P trend=0·05). Erythrocyte membrane arachidonic acid percentages are associated with an increased risk of colorectal adenomas.
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Affiliation(s)
- Samara B Rifkin
- 1Division of Gastroenterology and Hepatology,Johns Hopkins University School of Medicine,1800 Orleans Street,Baltimore, MD 21287,USA
| | - Martha J Shrubsole
- 2Division of Epidemiology,Vanderbilt University Medical Center,2525 West End Avenue,Suite 800,Nashville, TN 37203,USA
| | - Qiuyin Cai
- 2Division of Epidemiology,Vanderbilt University Medical Center,2525 West End Avenue,Suite 800,Nashville, TN 37203,USA
| | - Walter E Smalley
- 4Department of Health Policy,Vanderbilt University Medical Center,2525 West End Avenue,Suite 1200, Nashville, TN 37203,USA
| | - Reid M Ness
- 5Division of Gastroenterology,Vanderbilt University Medical Center,1211 Medical Center Drive,Nashville, TN 37232,USA
| | - Larry L Swift
- 6Department of Pathology, Microbiology and Immunology,Vanderbilt University Medical Center,1211 Medical Center Drive,Nashville, TN 37232,USA
| | - Wei Zheng
- 2Division of Epidemiology,Vanderbilt University Medical Center,2525 West End Avenue,Suite 800,Nashville, TN 37203,USA
| | - Harvey J Murff
- 3Geriatric Research Education and Clinical Center (GRECC),Department of Veterans Affairs,Tennessee Valley Healthcare System,1310 24th Avenue S,Nashville, TN 37212,USA
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Krumsiek J, Bartel J, Theis FJ. Computational approaches for systems metabolomics. Curr Opin Biotechnol 2016; 39:198-206. [PMID: 27135552 DOI: 10.1016/j.copbio.2016.04.009] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Revised: 03/30/2016] [Accepted: 04/07/2016] [Indexed: 10/21/2022]
Abstract
Systems genetics is defined as the simultaneous assessment and analysis of multi-omics datasets. In the past few years, metabolomics has been established as a robust tool describing an important functional layer in this approach. The metabolome of a biological system represents an integrated state of genetic and environmental factors and has been referred to as a 'link between genotype and phenotype'. In this review, we summarize recent progresses in statistical analysis methods for metabolomics data in combination with other omics layers. We put a special focus on complex, multivariate statistical approaches as well as pathway-based and network-based analysis methods. Moreover, we outline current challenges and pitfalls of metabolomics-focused multi-omics analyses and discuss future steps for the field.
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Affiliation(s)
- Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; German Center for Diabetes Research (DZD e.V.), Germany
| | - Jörg Bartel
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; German Center for Diabetes Research (DZD e.V.), Germany
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; Department of Mathematics, Technische Universität München, Garching, Germany.
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Shah SH, Newgard CB. Integrated metabolomics and genomics: systems approaches to biomarkers and mechanisms of cardiovascular disease. ACTA ACUST UNITED AC 2016; 8:410-9. [PMID: 25901039 DOI: 10.1161/circgenetics.114.000223] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The genetic architecture underlying the heritability of cardiovascular disease is incompletely understood. Metabolomics is an emerging technology platform that has shown early success in identifying biomarkers and mechanisms of common chronic diseases. Integration of metabolomics, genetics, and other omics platforms in a systems biology approach holds potential for elucidating novel genetic markers and mechanisms for cardiovascular disease. We review important studies that have used metabolomic profiling in cardiometabolic diseases, approaches for integrating metabolomics with genetics and other molecular profiling platforms, and key studies showing the potential for such studies in deciphering cardiovascular disease genetics, biomarkers, and mechanisms.
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Affiliation(s)
- Svati H Shah
- From the Duke Molecular Physiology Institute (S.H.S., C.B.N.), Division of Cardiology, Department of Medicine (S.H.S., C.B.N.), Department of Pharmacology and Cancer Biology and Division of Endocrinology, Department of Medicine, and the Sarah W. Stedman Nutrition and Metabolism Center (C.B.N.), Duke University, Durham, NC.
| | - Christopher B Newgard
- From the Duke Molecular Physiology Institute (S.H.S., C.B.N.), Division of Cardiology, Department of Medicine (S.H.S., C.B.N.), Department of Pharmacology and Cancer Biology and Division of Endocrinology, Department of Medicine, and the Sarah W. Stedman Nutrition and Metabolism Center (C.B.N.), Duke University, Durham, NC
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Abstract
Systems biology represents an integrative research strategy that studies the interactions between DNA, mRNA, protein, and metabolite level in an organism, thereby including the interactions with the physical environment and other organisms. The application of metabonomics, or the quantitative study of metabolites in biological systems, in systems biology is currently an emerging area of research, which can contribute to the discovery of (disease) signatures, drug targeting and design, and the further elucidation of basic and more complex biochemical principles. This chapter covers the contribution of metabonomics in advancing our understanding in systems biology.
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Affiliation(s)
- Vicky De Preter
- Translational Research Center for Gastrointestinal Disorders (TARGID), KULeuven, Herestraat 49, 3000, Leuven, Belgium,
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Suhre K, Raffler J, Kastenmüller G. Biochemical insights from population studies with genetics and metabolomics. Arch Biochem Biophys 2015; 589:168-76. [PMID: 26432701 DOI: 10.1016/j.abb.2015.09.023] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 09/28/2015] [Accepted: 09/28/2015] [Indexed: 12/31/2022]
Abstract
Genome-wide association studies with concentrations of hundreds of small molecules in samples collected from thousands of individuals (mGWAS) access otherwise inaccessible natural genetic experiments and their influence on the metabolic capacities of the human body. By sampling the natural metabolic and genetic variability that is present in the general population, mGWAS identified over 150 associations between genetic variants and variation in the metabolic composition of human body fluids. Many of these genetic variants were found to be located in enzyme or transporter coding genes, whose functions match the biochemical nature of the associated metabolites. Associations identified by mGWAS can reveal novel biochemical knowledge, such as the function of uncharacterized genes, the biochemical identity of small molecules, and the structure of entire biochemical pathways. Here we review findings of recent mGWAS and discuss concrete examples of how their results can be interpreted in a biochemical context. We describe online resources that are available for mining mGWAS results. In this context, we present two concepts that also find more general applications in the field of metabolomics: strengthening of associations by looking at ratios between metabolite pairs and reconstruction of metabolic pathways by Gaussian graphical modeling.
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Affiliation(s)
- Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medical College - Qatar, Doha, Qatar; Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Johannes Raffler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
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27
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Burkhardt R, Kirsten H, Beutner F, Holdt LM, Gross A, Teren A, Tönjes A, Becker S, Krohn K, Kovacs P, Stumvoll M, Teupser D, Thiery J, Ceglarek U, Scholz M. Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood. PLoS Genet 2015; 11:e1005510. [PMID: 26401656 PMCID: PMC4581711 DOI: 10.1371/journal.pgen.1005510] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2015] [Accepted: 08/17/2015] [Indexed: 01/23/2023] Open
Abstract
Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.
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Affiliation(s)
- Ralph Burkhardt
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Holger Kirsten
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- Department for Cell Therapy, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Frank Beutner
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Heart Center Leipzig, Leipzig, Germany
| | - Lesca M. Holdt
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute for Laboratory Medicine, Ludwig-Maximilians University Munich, Munich, Germany
| | - Arnd Gross
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - Andrej Teren
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Heart Center Leipzig, Leipzig, Germany
| | - Anke Tönjes
- Medical Department, Clinic for Endocrinology and Nephrology, University of Leipzig, Leipzig, Germany
| | - Susen Becker
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Knut Krohn
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Interdisciplinary Centre for Clinical Research, University of Leipzig, Leipzig, Germany
| | - Peter Kovacs
- Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Leipzig Germany
| | - Michael Stumvoll
- Medical Department, Clinic for Endocrinology and Nephrology, University of Leipzig, Leipzig, Germany
- Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Leipzig Germany
| | - Daniel Teupser
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute for Laboratory Medicine, Ludwig-Maximilians University Munich, Munich, Germany
| | - Joachim Thiery
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Uta Ceglarek
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Markus Scholz
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig Germany
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- * E-mail:
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Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality. PLoS Genet 2015; 11:e1005487. [PMID: 26352407 PMCID: PMC4564198 DOI: 10.1371/journal.pgen.1005487] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 08/06/2015] [Indexed: 12/24/2022] Open
Abstract
Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases. Human metabolism is influenced by genetic and environmental factors defining a person’s metabolic individuality. This individuality is linked to personal differences in the ability to react on metabolic challenges and in the susceptibility to specific diseases. By investigating how common variants in genetic regions (loci) affect individual blood metabolite levels, the substantial contribution of genetic inheritance to metabolic individuality has been demonstrated previously. Meanwhile, more than 150 loci influencing metabolic homeostasis in blood are known. Here we shift the focus to genetic variants that modulate urinary metabolite excretion, for which only 11 loci were reported so far. In the largest genetic study on urinary metabolites to date, we identified 15 additional loci. Most of the 26 loci also affect blood metabolite levels. This shows that the metabolic individuality seen in blood is also reflected in urine, which is expected when urine is regarded as “diluted blood”. Nonetheless, we also found loci that appear to primarily influence metabolite excretion. For instance, we identified genetic variants near a gene of a transporter that change the capability for renal re-absorption of the transporter’s substrate. Thus, our findings could help to elucidate molecular mechanisms influencing kidney function and the body’s detoxification capabilities.
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Analysis of the Human Prostate-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling Identifies TMEM79 and ACOXL as Two Putative, Diagnostic Markers in Prostate Cancer. PLoS One 2015; 10:e0133449. [PMID: 26237329 PMCID: PMC4523174 DOI: 10.1371/journal.pone.0133449] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Accepted: 06/25/2015] [Indexed: 11/19/2022] Open
Abstract
To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL.
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Kastenmüller G, Raffler J, Gieger C, Suhre K. Genetics of human metabolism: an update. Hum Mol Genet 2015; 24:R93-R101. [PMID: 26160913 PMCID: PMC4572003 DOI: 10.1093/hmg/ddv263] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2015] [Accepted: 07/06/2015] [Indexed: 01/01/2023] Open
Abstract
Genome-wide association studies with metabolomics (mGWAS) identify genetically influenced metabotypes (GIMs), their ensemble defining the heritable part of every human's metabolic individuality. Knowledge of genetic variation in metabolism has many applications of biomedical and pharmaceutical interests, including the functional understanding of genetic associations with clinical end points, design of strategies to correct dysregulations in metabolic disorders and the identification of genetic effect modifiers of metabolic disease biomarkers. Furthermore, it has been shown that GIMs provide testable hypotheses for functional genomics and metabolomics and for the identification of novel gene functions and metabolite identities. mGWAS with growing sample sizes and increasingly complex metabolic trait panels are being conducted, allowing for more comprehensive and systems-based downstream analyses. The generated large datasets of genetic associations can now be mined by the biomedical research community and provide valuable resources for hypothesis-driven studies. In this review, we provide a brief summary of the key aspects of mGWAS, followed by an update of recently published mGWAS. We then discuss new approaches of integrating and exploring mGWAS results and finish by presenting selected applications of GIMs in recent studies.
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Affiliation(s)
- Gabi Kastenmüller
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, German Center for Diabetes Research, Neuherberg, Germany and
| | - Johannes Raffler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany and Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Karsten Suhre
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany, Department of Physiology and Biophysics, Weill Cornell Medical College-Qatar, Doha, Qatar
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31
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Translational regulation shapes the molecular landscape of complex disease phenotypes. Nat Commun 2015; 6:7200. [PMID: 26007203 PMCID: PMC4455061 DOI: 10.1038/ncomms8200] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2014] [Accepted: 04/17/2015] [Indexed: 01/05/2023] Open
Abstract
The extent of translational control of gene expression in mammalian tissues remains largely unknown. Here we perform genome-wide RNA sequencing and ribosome profiling in heart and liver tissues to investigate strain-specific translational regulation in the spontaneously hypertensive rat (SHR/Ola). For the most part, transcriptional variation is equally apparent at the translational level and there is limited evidence of translational buffering. Remarkably, we observe hundreds of strain-specific differences in translation, almost doubling the number of differentially expressed genes. The integration of genetic, transcriptional and translational data sets reveals distinct signatures in 3'UTR variation, RNA-binding protein motifs and miRNA expression associated with translational regulation of gene expression. We show that a large number of genes associated with heart and liver traits in human genome-wide association studies are primarily translationally regulated. Capturing interindividual differences in the translated genome will lead to new insights into the genes and regulatory pathways underlying disease phenotypes.
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32
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Demirkan A, Henneman P, Verhoeven A, Dharuri H, Amin N, van Klinken JB, Karssen LC, de Vries B, Meissner A, Göraler S, van den Maagdenberg AMJM, Deelder AM, C ’t Hoen PA, van Duijn CM, van Dijk KW. Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. PLoS Genet 2015; 11:e1004835. [PMID: 25569235 PMCID: PMC4287344 DOI: 10.1371/journal.pgen.1004835] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2014] [Accepted: 10/16/2014] [Indexed: 12/20/2022] Open
Abstract
Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value = 1.27×10−32), PRODH with proline (P-value = 1.11×10−19), SLC16A9 with carnitine level (P-value = 4.81×10−14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value = 1.65×10−19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value = 1.26×10−8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10−8) and 2p12 locus with valine (P-value = 3.49×10−8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits. Human metabolic individuality is under strict control of genetic and environmental factors. In our study, we aimed to find the genetic determinants of circulating molecules in sera of large set of individuals representing the general population. First, we performed a hypothesis-free genome wide screen in this population to identify genetic regions of interest. Our study confirmed four known gene metabolite connections, but also pointed to four novel ones. Genome-wide screens enriched for common intergenic variants may miss causal genetic variations directly changing the protein sequence. To investigate this further, we zoomed into regions of interest and tested whether the association signals obtained in the first stage were direct, or whether they represent causal variations, which were not captured in the initial panel. These subsequent tests showed that protein coding and regulatory variations are involved in metabolite levels. For two genomic regions we also found that genes harbour more than one causal variant influencing metabolite levels independent of each other. We also observed strong connection between markers of cardio-metabolic health and metabolites. Taken together, our novel loci are of interest for further research to investigate the causal relation to for instance type 2 diabetes and cardiovascular disease.
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Affiliation(s)
- Ayşe Demirkan
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Aswin Verhoeven
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands
| | - Harish Dharuri
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jan Bert van Klinken
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Lennart C. Karssen
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Boukje de Vries
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Axel Meissner
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands
| | - Sibel Göraler
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands
| | - Arn M. J. M. van den Maagdenberg
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - André M. Deelder
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands
| | - Peter A. C ’t Hoen
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands
- * E-mail:
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Murff HJ, Edwards TL. Endogenous Production of Long-Chain Polyunsaturated Fatty Acids and Metabolic Disease Risk. CURRENT CARDIOVASCULAR RISK REPORTS 2014; 8. [PMID: 26392837 DOI: 10.1007/s12170-014-0418-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Long chain polyunsaturated fatty acids (PUFAs) are important structural components of cellular membranes and are converted into eicosanoids which serve various biological roles. The most common dietary n-6 and n-3 PUFAs are linoleic acid and α-linoleic acid, respectively. These 18-carbon chain fatty acids undergo a series of desaturation and elongation steps to become the 20-carbon fatty acids arachidonic acid and eicosapentaenoic acid, respectively. Evidence from genome wide association studies has consistently demonstrated that plasma and tissue levels of the n-6 long-chain PUFA arachidonic acid and to a lesser extent the n-3 long-chain PUFA eicosapentaenoic acid, are strongly influenced by variation in fatty acid desaturase-1,-2, and elongation of very long chain fatty acid genes. Studies of functional variants in these genes, as well as studies in which desaturase activity has been indirectly estimated by fatty acid product-to -precursor ratios, have suggested that endogenous capacity to synthesize long-chain PUFAs may be associated with metabolic diseases such as diabetes mellitus. Interventional studies are starting to tease out the complicated relationship between dietary intakes of specific fatty acids, variation in desaturase and elongase genes and tissue levels of long chain PUFAs. Thus future studies of dietary PUFA interventions designed to reduce inflammatory and metabolic diseases will need to carefully consider how an individual's genetically-determined endogenous long-chain PUFA synthesis capacity might modify therapeutic response.
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Affiliation(s)
- Harvey J Murff
- Division of General Internal Medicine and Public Health, Vanderbilt University School of Medicine, Nashville TN ; GRECC, Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville TN
| | - Todd L Edwards
- Division of Epidemiology, Vanderbilt University School of Medicine
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Voros S, Maurovich-Horvat P, Marvasty IB, Bansal AT, Barnes MR, Vazquez G, Murray SS, Voros V, Merkely B, Brown BO, Warnick GR. Precision phenotyping, panomics, and system-level bioinformatics to delineate complex biologies of atherosclerosis: rationale and design of the "Genetic Loci and the Burden of Atherosclerotic Lesions" study. J Cardiovasc Comput Tomogr 2014; 8:442-51. [PMID: 25439791 DOI: 10.1016/j.jcct.2014.08.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Revised: 08/25/2014] [Accepted: 08/27/2014] [Indexed: 01/24/2023]
Abstract
BACKGROUND Complex biological networks of atherosclerosis are largely unknown. OBJECTIVE The main objective of the Genetic Loci and the Burden of Atherosclerotic Lesions study is to assemble comprehensive biological networks of atherosclerosis using advanced cardiovascular imaging for phenotyping, a panomic approach to identify underlying genomic, proteomic, metabolomic, and lipidomic underpinnings, analyzed by systems biology-driven bioinformatics. METHODS By design, this is a hypothesis-free unbiased discovery study collecting a large number of biologically related factors to examine biological associations between genomic, proteomic, metabolomic, lipidomic, and phenotypic factors of atherosclerosis. The Genetic Loci and the Burden of Atherosclerotic Lesions study (NCT01738828) is a prospective, multicenter, international observational study of atherosclerotic coronary artery disease. Approximately 7500 patients are enrolled and undergo non-contrast-enhanced coronary calcium scanning by CT for the detection and quantification of coronary artery calcium, as well as coronary artery CT angiography for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. In addition, patients undergo whole genome sequencing, DNA methylation, whole blood-based transcriptome sequencing, unbiased proteomics based on mass spectrometry, as well as metabolomics and lipidomics on a mass spectrometry platform. The study is analyzed in 3 subsequent phases, and each phase consists of a discovery cohort and an independent validation cohort. For the primary analysis, the primary phenotype will be the presence of any atherosclerotic plaque, as detected by cardiac CT. Additional phenotypic analyses will include per patient maximal luminal stenosis defined as 50% and 70% diameter stenosis. Single-omic and multi-omic associations will be examined for each phenotype; putative biomarkers will be assessed for association, calibration, discrimination, and reclassification.
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Affiliation(s)
- Szilard Voros
- Global Genomics Group, LLC, 737 N. 5th Street, Richmond, VA 23219, USA.
| | | | - Idean B Marvasty
- Global Genomics Group, LLC, 737 N. 5th Street, Richmond, VA 23219, USA
| | | | | | | | - Sarah S Murray
- University of California at San Diego, San Diego, CA, USA
| | - Viktor Voros
- Global Genomics Group, LLC, 737 N. 5th Street, Richmond, VA 23219, USA
| | | | - Bradley O Brown
- Global Genomics Group, LLC, 737 N. 5th Street, Richmond, VA 23219, USA
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Harris WS, Davidson MH. RE: Plasma phospholipid fatty acids and prostate cancer risk in the SELECT trial. J Natl Cancer Inst 2014; 106:dju019. [PMID: 24685928 DOI: 10.1093/jnci/dju019] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Affiliation(s)
- William S Harris
- Affiliations of authors: Department of Medicine, University of South Dakota School of Medicine, Sioux Falls, SD (WSH); University of Chicago School of Medicine, Chicago, IL (MHD)
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Wang X, Tang H, Teng M, Li Z, Li J, Fan J, Zhong L, Sun X, Xu J, Chen G, Chen D, Wang Z, Xing T, Zhang J, Huang L, Wang S, Peng X, Qin S, Shi Y, Peng Z. Mapping of hepatic expression quantitative trait loci (eQTLs) in a Han Chinese population. J Med Genet 2014; 51:319-26. [PMID: 24665059 PMCID: PMC3995251 DOI: 10.1136/jmedgenet-2013-102045] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Background Elucidating the genetic basis underlying hepatic gene expression variability is of importance to understand the aetiology of the disease and variation in drug metabolism. To date, no genome-wide expression quantitative trait loci (eQTLs) analysis has been conducted in the Han Chinese population, the largest ethnic group in the world. Methods We performed a genome-wide eQTL mapping in a set of Han Chinese liver tissue samples (n=64). The data were then compared with published eQTL data from a Caucasian population. We then performed correlations between these eQTLs with important pharmacogenes, and genome-wide association study (GWAS) identified single nucleotide polymorphisms (SNPs), in particular those identified in the Asian population. Results Our analyses identified 1669 significant eQTLs (false discovery rate (FDR) < 0.05). We found that 41% of Asian eQTLs were also eQTLs in Caucasians at the genome-wide significance level (p=10−8). Both cis- and trans-eQTLs in the Asian population were also more likely to be eQTLs in Caucasians (p<10−4). Enrichment analyses revealed that trait-associated GWAS-SNPs were enriched within the eQTLs identified in our data, so were the GWAS-SNPs specifically identified in Asian populations in a separate analysis (p<0.001 for both). We also found that hepatic expression of very important pharmacogenetic (VIP) genes (n=44) and a manually curated list of major genes involved in pharmacokinetics (n=341) were both more likely to be controlled by eQTLs (p<0.002 for both). Conclusions Our study provided, for the first time, a comprehensive hepatic eQTL analysis in a non-European population, further generating valuable data for characterising the genetic basis of human diseases and pharmacogenetic traits.
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Affiliation(s)
- Xiaoliang Wang
- Department of General Surgery, Shanghai First People's Hospital, Medical College, Shanghai Jiaotong University, Shanghai, China
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Goetzman ES, Alcorn JF, Bharathi SS, Uppala R, McHugh KJ, Kosmider B, Chen R, Zuo YY, Beck ME, McKinney RW, Skilling H, Suhrie KR, Karunanidhi A, Yeasted R, Otsubo C, Ellis B, Tyurina YY, Kagan VE, Mallampalli RK, Vockley J. Long-chain acyl-CoA dehydrogenase deficiency as a cause of pulmonary surfactant dysfunction. J Biol Chem 2014; 289:10668-10679. [PMID: 24591516 DOI: 10.1074/jbc.m113.540260] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Long-chain acyl-CoA dehydrogenase (LCAD) is a mitochondrial fatty acid oxidation enzyme whose expression in humans is low or absent in organs known to utilize fatty acids for energy such as heart, muscle, and liver. This study demonstrates localization of LCAD to human alveolar type II pneumocytes, which synthesize and secrete pulmonary surfactant. The physiological role of LCAD and the fatty acid oxidation pathway in lung was subsequently studied using LCAD knock-out mice. Lung fatty acid oxidation was reduced in LCAD(-/-) mice. LCAD(-/-) mice demonstrated reduced pulmonary compliance, but histological examination of lung tissue revealed no obvious signs of inflammation or pathology. The changes in lung mechanics were found to be due to pulmonary surfactant dysfunction. Large aggregate surfactant isolated from LCAD(-/-) mouse lavage fluid had significantly reduced phospholipid content as well as alterations in the acyl chain composition of phosphatidylcholine and phosphatidylglycerol. LCAD(-/-) surfactant demonstrated functional abnormalities when subjected to dynamic compression-expansion cycling on a constrained drop surfactometer. Serum albumin, which has been shown to degrade and inactivate pulmonary surfactant, was significantly increased in LCAD(-/-) lavage fluid, suggesting increased epithelial permeability. Finally, we identified two cases of sudden unexplained infant death where no lung LCAD antigen was detectable. Both infants were homozygous for an amino acid changing polymorphism (K333Q). These findings for the first time identify the fatty acid oxidation pathway and LCAD in particular as factors contributing to the pathophysiology of pulmonary disease.
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Affiliation(s)
- Eric S Goetzman
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15213.
| | - John F Alcorn
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Sivakama S Bharathi
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Radha Uppala
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Kevin J McHugh
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Beata Kosmider
- Department of Medicine, National Jewish Health, Denver, Colorado 80206
| | - Rimei Chen
- Department of Mechanical Engineering, University of Hawaii at Manoa, Honolulu, Hawaii 96822
| | - Yi Y Zuo
- Department of Mechanical Engineering, University of Hawaii at Manoa, Honolulu, Hawaii 96822
| | - Megan E Beck
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15213
| | - Richard W McKinney
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Helen Skilling
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Kristen R Suhrie
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Anuradha Karunanidhi
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Renita Yeasted
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Chikara Otsubo
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224
| | - Bryon Ellis
- Department of Medicine, Acute Lung Injury Center of Excellence, University of Pittsburgh, Pittsburgh, Pennsylvania 15213
| | - Yulia Y Tyurina
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15260; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Valerian E Kagan
- Center for Free Radical and Antioxidant Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15260; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
| | - Rama K Mallampalli
- Department of Medicine, Acute Lung Injury Center of Excellence, University of Pittsburgh, Pittsburgh, Pennsylvania 15213; Medical Specialty Service Line, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania 15213
| | - Jerry Vockley
- Department of Pediatrics, University of Pittsburgh School of Medicine, Children's Hospital of Pittsburgh of University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15224; Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15213
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Davidson MH. Omega-3 fatty acids: new insights into the pharmacology and biology of docosahexaenoic acid, docosapentaenoic acid, and eicosapentaenoic acid. Curr Opin Lipidol 2013; 24:467-74. [PMID: 24184945 DOI: 10.1097/mol.0000000000000019] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW Fish oil contains a complex mixture of omega-3 fatty acids, which are predominantly eicosapentaenoic acid (EPA), docosapentaenoic acid, and docosahexaenoic acid (DHA). Each of these omega-3 fatty acids has distinct biological effects that may have variable clinical effects. In addition, plasma levels of omega-3 fatty acids are affected not only by dietary intake, but also by the polymorphisms of coding genes fatty acid desaturase 1-3 for the desaturase enzymes that convert short-chain polyunsaturated fatty acids to long-chain polyunsaturated fatty acids. The clinical significance of this new understanding regarding the complexity of omega-3 fatty acid biology is the purpose of this review. RECENT FINDINGS FADS polymorphisms that result in either lower levels of long-chain omega-3 fatty acids or higher levels of long-chain omega-6 polyunsaturated fatty acids, such as arachidonic acid, are associated with dyslipidemia and other cardiovascular risk factors. EPA and DHA have differences in their effects on lipoprotein metabolism, in which EPA, with a more potent peroxisome proliferator-activated receptor-alpha effect, decreases hepatic lipogenesis, whereas DHA not only enhances VLDL lipolysis, resulting in greater conversion to LDL, but also increases HDL cholesterol and larger, more buoyant LDL particles. SUMMARY Overall, these results emphasize that blood concentrations of individual long-chain polyunsaturated fatty acids, which reflect both dietary intake and metabolic influences, may have independent, but also complementary- biological effects and reinforce the need to potentially provide a complex mixture of omega-3 fatty acids to maximize cardiovascular risk reduction.
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Affiliation(s)
- Michael H Davidson
- aPritzker School of Medicine, The University of Chicago, Chicago, Illinois bOmthera Pharmaceuticals, Princeton, New Jersey, USA
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