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Wu KCH, Liu L, Xu A, Chan YH, Cheung BMY. Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis. Endocrine 2024; 85:685-694. [PMID: 38460073 PMCID: PMC11291565 DOI: 10.1007/s12020-024-03766-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/27/2024] [Indexed: 03/11/2024]
Abstract
PURPOSE To investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association. METHODS Our study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c. RESULTS With this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10-13), HbA1c (rg = 0.182, p = 4.14 × 10-6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10-6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER. CONCLUSION Our research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.
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Affiliation(s)
- Kevin Chun Hei Wu
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Lin Liu
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Aimin Xu
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Yap Hang Chan
- Division of Cardiology, Queen Mary Hospital, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Bernard Man Yung Cheung
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
- Institute of Cardiovascular Science and Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
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2
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Hawes EM, Rahim M, Haratipour Z, Orun AR, O'Rourke ML, Oeser JK, Kim K, Claxton DP, Blind RD, Young JD, O'Brien RM. Biochemical and metabolic characterization of a G6PC2 inhibitor. Biochimie 2024; 222:109-122. [PMID: 38431189 DOI: 10.1016/j.biochi.2024.02.012] [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: 02/14/2024] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 03/05/2024]
Abstract
Three glucose-6-phosphatase catalytic subunits, that hydrolyze glucose-6-phosphate (G6P) to glucose and inorganic phosphate, have been identified, designated G6PC1-3, but only G6PC1 and G6PC2 have been implicated in the regulation of fasting blood glucose (FBG). Elevated FBG has been associated with multiple adverse clinical outcomes, including increased risk for type 2 diabetes and various cancers. Therefore, G6PC1 and G6PC2 inhibitors that lower FBG may be of prophylactic value for the prevention of multiple conditions. The studies described here characterize a G6PC2 inhibitor, designated VU0945627, previously identified as Compound 3. We show that VU0945627 preferentially inhibits human G6PC2 versus human G6PC1 but activates human G6PC3. VU0945627 is a mixed G6PC2 inhibitor, increasing the Km but reducing the Vmax for G6P hydrolysis. PyRx virtual docking to an AlphaFold2-derived G6PC2 structural model suggests VU0945627 binds two sites in human G6PC2. Mutation of residues in these sites reduces the inhibitory effect of VU0945627. VU0945627 does not inhibit mouse G6PC2 despite its 84% sequence identity with human G6PC2. Mutagenesis studies suggest this lack of inhibition of mouse G6PC2 is due, in part, to a change in residue 318 from histidine in human G6PC2 to proline in mouse G6PC2. Surprisingly, VU0945627 still inhibited glucose cycling in the mouse islet-derived βTC-3 cell line. Studies using intact mouse liver microsomes and PyRx docking suggest that this observation can be explained by an ability of VU0945627 to also inhibit the G6P transporter SLC37A4. These data will inform future computational modeling studies designed to identify G6PC isoform-specific inhibitors.
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Affiliation(s)
- Emily M Hawes
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Mohsin Rahim
- Department of Chemical and Biomolecular Engineering, Vanderbilt School of Engineering, Nashville, TN, 37232, USA
| | - Zeinab Haratipour
- Austin Peay State University, 601 College St, Clarksville, TN 37044, USA; Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Abigail R Orun
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Margaret L O'Rourke
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - James K Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Kwangho Kim
- Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, TN, 37232, USA
| | - Derek P Claxton
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Ray D Blind
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Jamey D Young
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA; Department of Chemical and Biomolecular Engineering, Vanderbilt School of Engineering, Nashville, TN, 37232, USA
| | - Richard M O'Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.
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3
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Hawes E, Claxton D, Oeser J, O’Brien R. Identification of structural motifs critical for human G6PC2 function informed by sequence analysis and an AlphaFold2-predicted model. Biosci Rep 2024; 44:BSR20231851. [PMID: 38095063 PMCID: PMC10776900 DOI: 10.1042/bsr20231851] [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: 10/26/2023] [Revised: 11/22/2023] [Accepted: 12/12/2023] [Indexed: 01/10/2024] Open
Abstract
G6PC2 encodes a glucose-6-phosphatase (G6Pase) catalytic subunit, primarily expressed in pancreatic islet β cells, which modulates the sensitivity of insulin secretion to glucose and thereby regulates fasting blood glucose (FBG). Mutational analyses were conducted to validate an AlphaFold2 (AF2)-predicted structure of human G6PC2 in conjunction with a novel method to solubilize and purify human G6PC2 from a heterologous expression system. These analyses show that residues forming a predicted intramolecular disulfide bond are essential for G6PC2 expression and that residues forming part of a type 2 phosphatidic acid phosphatase (PAP2) motif are critical for enzyme activity. Additional mutagenesis shows that residues forming a predicted substrate cavity modulate enzyme activity and substrate specificity and residues forming a putative cholesterol recognition amino acid consensus (CRAC) motif influence protein expression or enzyme activity. This CRAC motif begins at residue 219, the site of a common G6PC2 non-synonymous single-nucleotide polymorphism (SNP), rs492594 (Val219Leu), though the functional impact of this SNP is disputed. In microsomal membrane preparations, the L219 variant has greater activity than the V219 variant, but this difference disappears when G6PC2 is purified in detergent micelles. We hypothesize that this was due to a differential association of the two variants with cholesterol. This concept was supported by the observation that the addition of cholesteryl hemi-succinate to the purified enzymes decreased the Vmax of the V219 and L219 variants ∼8-fold and ∼3 fold, respectively. We anticipate that these observations should support the rational development of G6PC2 inhibitors designed to lower FBG.
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Affiliation(s)
- Emily M. Hawes
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, U.S.A
| | - Derek P. Claxton
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, U.S.A
| | - James K. Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, U.S.A
| | - Richard M. O’Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, U.S.A
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4
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Cheng YF, Yang CY, Tsai MC. Shared Genetics between Age at Menarche and Type 2 Diabetes Mellitus: Genome-Wide Genetic Correlation Study. Biomedicines 2024; 12:157. [PMID: 38255262 PMCID: PMC10813301 DOI: 10.3390/biomedicines12010157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/07/2024] [Accepted: 01/09/2024] [Indexed: 01/24/2024] Open
Abstract
Background: Age at menarche (AAM) has been associated with type 2 diabetes mellitus (T2DM). However, little is known about their shared heritability. Methods: Our data comes from the Taiwan Biobank. Genome-wide association studies (GWASs) were conducted to identify single-nucleotide polymorphisms (SNPs) related to AAM-, T2DM-, and T2DM-related phenotypes, such as body fat percentage (BFP), fasting blood glucose (FBG), and hemoglobin A1C (HbA1C). Further, the conditional false discovery rate (cFDR) method was applied to examine the shared genetic signals. Results: Conditioning on AAM, Quantile-quantile plots showed an earlier departure from the diagonal line among SNPs associated with BFP and FBG, indicating pleiotropic enrichments among AAM and these traits. Further, the cFDR analysis found 39 independent pleiotropic loci that may underlie the AAM-T2DM association. Among them, FN3KRP rs1046896 (cFDR = 6.84 × 10-49), CDKAL1 rs2206734 (cFDR = 6.48 × 10-10), B3GNTL1 rs58431774 (cFDR = 2.95 × 10-10), G6PC2 rs1402837 (cFDR = 1.82 × 10-8), and KCNQ1 rs60808706 (cFDR = 9.49 × 10-8) were highlighted for their significant genetic enrichment. The protein-protein interaction analysis revealed a significantly enriched network among novel discovered genes that were mostly found to be involved in the insulin and glucagon signaling pathways. Conclusions: Our study highlights potential pleiotropic effects across AAM and T2DM. This may shed light on identifying the genetic causes of T2DM.
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Affiliation(s)
- Yuan-Fang Cheng
- School of Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
| | - Cheng-Yi Yang
- Department of Statistics, College of Management, National Cheng Kung University, Tainan 70101, Taiwan
| | - Meng-Che Tsai
- Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, 138 Shengli Road, Tainan 70403, Taiwan
- Department of Genomic Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
- Department of Medical Humanities and Social Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan
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5
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Keller MP, Hawes EM, Schueler KL, Stapleton DS, Mitok KA, Simonett SP, Oeser JK, Sampson LL, Attie AD, Magnuson MA, O’Brien RM. An Enhancer Within Abcb11 Regulates G6pc2 in C57BL/6 Mouse Pancreatic Islets. Diabetes 2023; 72:1621-1628. [PMID: 37552875 PMCID: PMC10588275 DOI: 10.2337/db23-0215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 08/01/2023] [Indexed: 08/10/2023]
Abstract
G6PC2 is predominantly expressed in pancreatic islet β-cells where it encodes a glucose-6-phosphatase catalytic subunit that modulates the sensitivity of insulin secretion to glucose by opposing the action of glucokinase, thereby regulating fasting blood glucose (FBG). Prior studies have shown that the G6pc2 promoter alone is unable to confer sustained islet-specific gene expression in mice, suggesting the existence of distal enhancers that regulate G6pc2 expression. Using information from both mice and humans and knowledge that single nucleotide polymorphisms (SNPs) both within and near G6PC2 are associated with variations in FBG in humans, we identified several putative enhancers 3' of G6pc2. One region, herein referred to as enhancer I, resides in the 25th intron of Abcb11 and binds multiple islet-enriched transcription factors. CRISPR-mediated deletion of enhancer I in C57BL/6 mice had selective effects on the expression of genes near the G6pc2 locus. In isolated islets, G6pc2 and Spc25 expression were reduced ∼50%, and Gm13613 expression was abolished, whereas Cers6 and nostrin expression were unaffected. This partial reduction in G6pc2 expression enhanced islet insulin secretion at basal glucose concentrations but did not affect FBG or glucose tolerance in vivo, consistent with the absence of a phenotype in G6pc2 heterozygous C57BL/6 mice. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Mark P. Keller
- Department of Biochemistry, University of Wisconsin–Madison, Madison, WI
| | - Emily M. Hawes
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
| | | | | | - Kelly A. Mitok
- Department of Biochemistry, University of Wisconsin–Madison, Madison, WI
| | - Shane P. Simonett
- Department of Biochemistry, University of Wisconsin–Madison, Madison, WI
| | - James K. Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
| | - Leesa L. Sampson
- Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN
| | - Alan D. Attie
- Department of Biochemistry, University of Wisconsin–Madison, Madison, WI
- Department of Chemistry, University of Wisconsin–Madison, Madison, WI
- Department of Medicine, University of Wisconsin–Madison, Madison, WI
| | - Mark A. Magnuson
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
- Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN
| | - Richard M. O’Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN
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6
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Grenko CM, Bonnycastle LL, Taylor HJ, Yan T, Swift AJ, Robertson CC, Narisu N, Erdos MR, Collins FS, Taylor DL. Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 hours. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.06.543931. [PMID: 37333221 PMCID: PMC10274787 DOI: 10.1101/2023.06.06.543931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycemia, beta cell glucotoxicity, and ultimately type 2 diabetes (T2D). In this study, we sought to explore the effects of hyperglycemia on human pancreatic islet (HPI) gene expression by exposing HPIs from two donors to low (2.8mM) and high (15.0mM) glucose concentrations over 24 hours, assaying the transcriptome at seven time points using single-cell RNA sequencing (scRNA-seq). We modeled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Across all cell types, we identified 1,528 genes associated with time, 1,185 genes associated with glucose exposure, and 845 genes associated with interaction effects between time and glucose. We clustered differentially expressed genes across cell types and found 347 modules of genes with similar expression patterns across time and glucose conditions, including two beta cell modules enriched in genes associated with T2D. Finally, by integrating genomic features from this study and genetic summary statistics for T2D and related traits, we nominate 363 candidate effector genes that may underlie genetic associations for T2D and related traits.
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Affiliation(s)
- Caleb M. Grenko
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lori L. Bonnycastle
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Henry J. Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Tingfen Yan
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amy J. Swift
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Catherine C. Robertson
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael R. Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Francis S. Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - D. Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
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7
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Veiga-da-Cunha M, Wortmann SB, Grünert SC, Van Schaftingen E. Treatment of the Neutropenia Associated with GSD1b and G6PC3 Deficiency with SGLT2 Inhibitors. Diagnostics (Basel) 2023; 13:diagnostics13101803. [PMID: 37238286 DOI: 10.3390/diagnostics13101803] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/12/2023] [Accepted: 05/17/2023] [Indexed: 05/28/2023] Open
Abstract
Glycogen storage disease type Ib (GSD1b) is due to a defect in the glucose-6-phosphate transporter (G6PT) of the endoplasmic reticulum, which is encoded by the SLC37A4 gene. This transporter allows the glucose-6-phosphate that is made in the cytosol to cross the endoplasmic reticulum (ER) membrane and be hydrolyzed by glucose-6-phosphatase (G6PC1), a membrane enzyme whose catalytic site faces the lumen of the ER. Logically, G6PT deficiency causes the same metabolic symptoms (hepatorenal glycogenosis, lactic acidosis, hypoglycemia) as deficiency in G6PC1 (GSD1a). Unlike GSD1a, GSD1b is accompanied by low neutrophil counts and impaired neutrophil function, which is also observed, independently of any metabolic problem, in G6PC3 deficiency. Neutrophil dysfunction is, in both diseases, due to the accumulation of 1,5-anhydroglucitol-6-phosphate (1,5-AG6P), a potent inhibitor of hexokinases, which is slowly formed in the cells from 1,5-anhydroglucitol (1,5-AG), a glucose analog that is normally present in blood. Healthy neutrophils prevent the accumulation of 1,5-AG6P due to its hydrolysis by G6PC3 following transport into the ER by G6PT. An understanding of this mechanism has led to a treatment aimed at lowering the concentration of 1,5-AG in blood by treating patients with inhibitors of SGLT2, which inhibits renal glucose reabsorption. The enhanced urinary excretion of glucose inhibits the 1,5-AG transporter, SGLT5, causing a substantial decrease in the concentration of this polyol in blood, an increase in neutrophil counts and function and a remarkable improvement in neutropenia-associated clinical signs and symptoms.
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Affiliation(s)
- Maria Veiga-da-Cunha
- Metabolic Research Group, de Duve Institute and UCLouvain, B-1200 Brussels, Belgium
| | - Saskia B Wortmann
- University Children's Hospital, Paracelsus Medical University, 5020 Salzburg, Austria
- Amalia Children's Hospital, Radboudumc, 6525 Nijmegen, The Netherlands
| | - Sarah C Grünert
- Department of General Pediatrics, Adolescent Medicine and Neonatology, Medical Center, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany
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Qiao Z, Sidorenko J, Revez JA, Xue A, Lu X, Pärna K, Snieder H, Visscher PM, Wray NR, Yengo L. Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose. Nat Commun 2023; 14:451. [PMID: 36707517 PMCID: PMC9883484 DOI: 10.1038/s41467-023-36013-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 01/12/2023] [Indexed: 01/29/2023] Open
Abstract
The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal (h2 = 11%; standard error: 1%). The genetic correlation between different fasting times is > 0.77, suggesting that the genetic control of glucose is largely constant across fasting durations. Accounting for heritability differences between fasting times leads to a ~16% improvement in the discovery of genetic variants associated with glucose. Newly detected variants improve the prediction of fasting glucose and type 2 diabetes in independent samples. Finally, we meta-analysed summary statistics from genome-wide association studies of random and fasting glucose (N = 518,615) and identified 156 independent SNPs explaining 3% of fasting glucose variance. Altogether, our study demonstrates the utility of random glucose measures to improve the discovery of genetic variants associated with glucose homeostasis, even in fasting conditions.
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Affiliation(s)
- Zhen Qiao
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Julia Sidorenko
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Joana A Revez
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Angli Xue
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Xueling Lu
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Laboratory of Environmental Medicine and Developmental Toxicology, Shantou University Medical College, Guangdong, China
| | - Katri Pärna
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
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9
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Ansari N, Ramachandran V, Mohamad NA, Salim E, Ismail P, Hazmi M, Mat LNI. Association of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) Gene Polymorphisms with Type 2 Diabetes among Malay Ethnics. Glob Med Genet 2023; 10:12-18. [PMID: 36703777 PMCID: PMC9873477 DOI: 10.1055/s-0042-1760384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder, and the underlying causes remain unknown and have not been fully elucidated. Several candidate genes have been associated with T2DM in various populations with conflicting results. The variations found in glucokinase ( GCK ), glucokinase regulatory protein ( GCKR ), and glucose-6-phosphatase 2 ( G6PC2 ) genes were not well studied, particularly among Asians. Aims The main objective of this study was to determine the candidate genetic polymorphisms of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) genes in T2DM among Malay ethnics. Methods In this candidate gene association study, a total of 180 T2DM subjects and 180 control subjects were recruited to determine the genotypes using polymerase chain reaction-restriction fragment length polymorphism and Taqman probe assay methods. Genotype and allele frequencies in case and control samples were compared using the chi-squared test to determine a significant difference. Results The body mass index, fasting blood glucose, hemoglobin A1c, systolic and diastolic blood pressure, and total cholesterol were significantly different ( p < 0.05) between T2DM and control subjects. The genotypic and allelic frequencies of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) gene polymorphisms were significantly different between T2DM and controls ( p < 0.05). Conclusion Hence, rs1799884 of GCK gene and rs780094 of GCKR gene and rs560887 of the G6PC2 gene are possible genetic biomarkers in T2DM development among Malay ethnics in Malaysia.
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Affiliation(s)
- Neda Ansari
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
| | - Vasudevan Ramachandran
- Faculty of Health Sciences, University College MAIWP International, Taman Batu Muda, Kuala Lumpur, Malaysia,Vasudevan Ramachandran Faculty of Health Sciences, University College MAIWP InternationalTaman Batu Muda, 68100 Batu Caves, Kuala LumpurMalaysia
| | - Nur Afiqah Mohamad
- Centre for Foundation Studies, Lincoln University College, Selangor, DE, Malaysia
| | - Elnaz Salim
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
| | - Patimah Ismail
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Selangor, Malaysia
| | - Mohamad Hazmi
- Department of Surgery, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor DE, Malaysia
| | - Liyana Najwa Inchee Mat
- Department of Medicine, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor DE, Malaysia,Address for correspondence Liyana Najwa Inchee, Mat, MBBCh BAO, PhD Department of Medicine, Faculty of Medicine and Health Sciences, Universiti Putra MalaysiaSerdang 43400, Selangor DEMalaysia
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10
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Han H, McGivney BA, Allen L, Bai D, Corduff LR, Davaakhuu G, Davaasambuu J, Dorjgotov D, Hall TJ, Hemmings AJ, Holtby AR, Jambal T, Jargalsaikhan B, Jargalsaikhan U, Kadri NK, MacHugh DE, Pausch H, Readhead C, Warburton D, Dugarjaviin M, Hill EW. Common protein-coding variants influence the racing phenotype in galloping racehorse breeds. Commun Biol 2022; 5:1320. [PMID: 36513809 PMCID: PMC9748125 DOI: 10.1038/s42003-022-04206-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 11/01/2022] [Indexed: 12/14/2022] Open
Abstract
Selection for system-wide morphological, physiological, and metabolic adaptations has led to extreme athletic phenotypes among geographically diverse horse breeds. Here, we identify genes contributing to exercise adaptation in racehorses by applying genomics approaches for racing performance, an end-point athletic phenotype. Using an integrative genomics strategy to first combine population genomics results with skeletal muscle exercise and training transcriptomic data, followed by whole-genome resequencing of Asian horses, we identify protein-coding variants in genes of interest in galloping racehorse breeds (Arabian, Mongolian and Thoroughbred). A core set of genes, G6PC2, HDAC9, KTN1, MYLK2, NTM, SLC16A1 and SYNDIG1, with central roles in muscle, metabolism, and neurobiology, are key drivers of the racing phenotype. Although racing potential is a multifactorial trait, the genomic architecture shaping the common athletic phenotype in horse populations bred for racing provides evidence for the influence of protein-coding variants in fundamental exercise-relevant genes. Variation in these genes may therefore be exploited for genetic improvement of horse populations towards specific types of racing.
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Affiliation(s)
- Haige Han
- grid.411638.90000 0004 1756 9607Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, College of Animal Science, Equine Research Center, Inner Mongolia Agricultural University, Hohhot, 010018 China
| | - Beatrice A. McGivney
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland
| | - Lucy Allen
- grid.417905.e0000 0001 2186 5933Royal Agricultural University, Cirencester, Gloucestershire GL7 6JS UK
| | - Dongyi Bai
- grid.411638.90000 0004 1756 9607Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, College of Animal Science, Equine Research Center, Inner Mongolia Agricultural University, Hohhot, 010018 China
| | - Leanne R. Corduff
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland
| | - Gantulga Davaakhuu
- grid.425564.40000 0004 0587 3863Institute of Biology, Mongolian Academy of Sciences, Peace Avenue 54B, Ulaanbaatar, 13330 Mongolia
| | - Jargalsaikhan Davaasambuu
- Ajnai Sharga Horse Racing Team, Encanto Town 210-11, Ikh Mongol State Street, 26th Khoroo, Bayanzurkh district Ulaanbaatar, 13312 Mongolia
| | - Dulguun Dorjgotov
- grid.440461.30000 0001 2191 7895School of Industrial Technology, Mongolian University of Science and Technology, Ulaanbaatar, 661 Mongolia
| | - Thomas J. Hall
- grid.7886.10000 0001 0768 2743UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin D04 V1W8 Ireland
| | - Andrew J. Hemmings
- grid.417905.e0000 0001 2186 5933Royal Agricultural University, Cirencester, Gloucestershire GL7 6JS UK
| | - Amy R. Holtby
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland
| | - Tuyatsetseg Jambal
- grid.440461.30000 0001 2191 7895School of Industrial Technology, Mongolian University of Science and Technology, Ulaanbaatar, 661 Mongolia
| | - Badarch Jargalsaikhan
- grid.444534.60000 0000 8485 883XDepartment of Obstetrics and Gynecology, Mongolian National University of Medical Sciences, Ulaanbaatar, 14210 Mongolia
| | - Uyasakh Jargalsaikhan
- Ajnai Sharga Horse Racing Team, Encanto Town 210-11, Ikh Mongol State Street, 26th Khoroo, Bayanzurkh district Ulaanbaatar, 13312 Mongolia
| | - Naveen K. Kadri
- grid.5801.c0000 0001 2156 2780Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - David E. MacHugh
- grid.7886.10000 0001 0768 2743UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin D04 V1W8 Ireland ,grid.7886.10000 0001 0768 2743UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin D04 V1W8 Ireland
| | - Hubert Pausch
- grid.5801.c0000 0001 2156 2780Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Carol Readhead
- grid.20861.3d0000000107068890Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125 USA
| | - David Warburton
- grid.42505.360000 0001 2156 6853The Saban Research Institute, Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA 90027 USA
| | - Manglai Dugarjaviin
- grid.411638.90000 0004 1756 9607Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, College of Animal Science, Equine Research Center, Inner Mongolia Agricultural University, Hohhot, 010018 China
| | - Emmeline W. Hill
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland ,grid.7886.10000 0001 0768 2743UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin D04 V1W8 Ireland
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11
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Chen G, Shriner D, Zhang J, Zhou J, Adikaram P, Doumatey AP, Bentley AR, Adeyemo A, Rotimi CN. Additive genetic effect of GCKR, G6PC2, and SLC30A8 variants on fasting glucose levels and risk of type 2 diabetes. PLoS One 2022; 17:e0269378. [PMID: 35657990 PMCID: PMC9165855 DOI: 10.1371/journal.pone.0269378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 05/19/2022] [Indexed: 01/11/2023] Open
Abstract
Impaired glucose tolerance is a major risk factor for type 2 diabetes (T2D) and several cardiometabolic disorders. To identify genetic loci underlying fasting glucose levels, we conducted an analysis of 9,232 individuals of European ancestry who at enrollment were either nondiabetic or had untreated type 2 diabetes. Multivariable linear mixed models were used to test for associations between fasting glucose and 7.9 million SNPs, with adjustment for age, body mass index (BMI), sex, significant principal components of the genotypes, and cryptic relatedness. Three previously discovered loci were genome-wide significant, with the lead SNPs being rs1260326, a missense variant in GCKR (p = 1.06×10−8); rs560887, an intronic variant in G6PC2 (p = 3.39×10−11); and rs13266634, a missense variant in SLC30A8 (p = 4.28×10−10). Fine mapping, genome-wide conditional analysis, and functional annotation indicated that the three loci were independently associated with fasting glucose. Each copy of an alternate allele at any of these three SNPs was associated with a reduction of 0.012 mmol/L in fasting glucose levels (p = 8.0×10−28), and this association was replicated in trans-ethnic analysis of 14,303 individuals (p = 2.2×10−16). The three SNPs were jointly associated with significantly reduced T2D risk, with an odds ratio (95% CI) of 0.93 (0.88, 0.98) per protective allele. Our findings implicate additive effects across pathophysiological pathways involved in type 2 diabetes, including glycolysis, gluconeogenesis, and insulin secretion. Since none of the individuals homozygous for the alternate alleles at all three loci has T2D, it might be possible to use a genetic predictor of fasting glucose levels to identify individuals at low vs. high risk of developing type 2 diabetes.
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Affiliation(s)
- Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Jianhua Zhang
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States of America
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Poorni Adikaram
- Advanced BioScience Laboratories, Rockville, Maryland, United States of America
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
- * E-mail:
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12
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Sánchez-Maldonado JM, Collado R, Cabrera-Serrano AJ, Ter Horst R, Gálvez-Montosa F, Robles-Fernández I, Arenas-Rodríguez V, Cano-Gutiérrez B, Bakker O, Bravo-Fernández MI, García-Verdejo FJ, López JAL, Olivares-Ruiz J, López-Nevot MÁ, Fernández-Puerta L, Cózar-Olmo JM, Li Y, Netea MG, Jurado M, Lorente JA, Sánchez-Rovira P, Álvarez-Cubero MJ, Sainz J. Type 2 Diabetes-Related Variants Influence the Risk of Developing Prostate Cancer: A Population-Based Case-Control Study and Meta-Analysis. Cancers (Basel) 2022; 14:cancers14102376. [PMID: 35625981 PMCID: PMC9139180 DOI: 10.3390/cancers14102376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/26/2022] [Accepted: 04/29/2022] [Indexed: 02/06/2023] Open
Abstract
In this study, we have evaluated whether 57 genome-wide association studies (GWAS)-identified common variants for type 2 diabetes (T2D) influence the risk of developing prostate cancer (PCa) in a population of 304 Caucasian PCa patients and 686 controls. The association of selected single nucleotide polymorphisms (SNPs) with the risk of PCa was validated through meta-analysis of our data with those from the UKBiobank and FinnGen cohorts, but also previously published genetic studies. We also evaluated whether T2D SNPs associated with PCa risk could influence host immune responses by analysing their correlation with absolute numbers of 91 blood-derived cell populations and circulating levels of 103 immunological proteins and 7 steroid hormones. We also investigated the correlation of the most interesting SNPs with cytokine levels after in vitro stimulation of whole blood, peripheral mononuclear cells (PBMCs), and monocyte-derived macrophages with LPS, PHA, Pam3Cys, and Staphylococcus Aureus. The meta-analysis of our data with those from six large cohorts confirmed that each copy of the FTOrs9939609A, HNF1Brs7501939T, HNF1Brs757210T, HNF1Brs4430796G, and JAZF1rs10486567A alleles significantly decreased risk of developing PCa (p = 3.70 × 10-5, p = 9.39 × 10-54, p = 5.04 × 10-54, p = 1.19 × 10-71, and p = 1.66 × 10-18, respectively). Although it was not statistically significant after correction for multiple testing, we also found that the NOTCH2rs10923931T and RBMS1rs7593730 SNPs associated with the risk of developing PCa (p = 8.49 × 10-4 and 0.004). Interestingly, we found that the protective effect attributed to the HFN1B locus could be mediated by the SULT1A1 protein (p = 0.00030), an arylsulfotransferase that catalyzes the sulfate conjugation of many hormones, neurotransmitters, drugs, and xenobiotic compounds. In addition to these results, eQTL analysis revealed that the HNF1Brs7501939, HNF1Brs757210, HNF1Brs4430796, NOTCH2rs10923931, and RBMS1rs7593730 SNPs influence the risk of PCa through the modulation of mRNA levels of their respective genes in whole blood and/or liver. These results confirm that functional TD2-related variants influence the risk of developing PCa, but also highlight the need of additional experiments to validate our functional results in a tumoral tissue context.
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Affiliation(s)
- José Manuel Sánchez-Maldonado
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Hematology Department, Virgen de las Nieves University Hospital, 18012 Granada, Spain;
- Instituto de Investigación Biosanataria IBs. Granada, 18012 Granada, Spain
| | - Ricardo Collado
- Medical Oncology Department, Hospital de San Pedro Alcántara, 10003 Cáceres, Spain; (R.C.); (M.I.B.-F.); (J.O.-R.)
| | - Antonio José Cabrera-Serrano
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Hematology Department, Virgen de las Nieves University Hospital, 18012 Granada, Spain;
- Instituto de Investigación Biosanataria IBs. Granada, 18012 Granada, Spain
| | - Rob Ter Horst
- Department of Internal Medicine and Radboud Centre for Infectious Diseases, Radboud University Nijmegen Medical Center, 6525 GA Nijmegen, The Netherlands; (R.T.H.); (Y.L.); (M.G.N.)
| | - Fernando Gálvez-Montosa
- Department of Medical Oncology, Complejo Hospitalario de Jaén, 23007 Jaén, Spain; (F.G.-M.); (F.J.G.-V.); (J.A.L.L.); (P.S.-R.)
| | - Inmaculada Robles-Fernández
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
| | - Verónica Arenas-Rodríguez
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Department of Biochemistry and Molecular Biology III, Faculty of Medicine, University of Granada, 18016 Granada, Spain;
| | - Blanca Cano-Gutiérrez
- Department of Biochemistry and Molecular Biology III, Faculty of Medicine, University of Granada, 18016 Granada, Spain;
| | - Olivier Bakker
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands;
| | | | - Francisco José García-Verdejo
- Department of Medical Oncology, Complejo Hospitalario de Jaén, 23007 Jaén, Spain; (F.G.-M.); (F.J.G.-V.); (J.A.L.L.); (P.S.-R.)
| | - José Antonio López López
- Department of Medical Oncology, Complejo Hospitalario de Jaén, 23007 Jaén, Spain; (F.G.-M.); (F.J.G.-V.); (J.A.L.L.); (P.S.-R.)
| | - Jesús Olivares-Ruiz
- Medical Oncology Department, Hospital de San Pedro Alcántara, 10003 Cáceres, Spain; (R.C.); (M.I.B.-F.); (J.O.-R.)
| | | | | | | | - Yang Li
- Department of Internal Medicine and Radboud Centre for Infectious Diseases, Radboud University Nijmegen Medical Center, 6525 GA Nijmegen, The Netherlands; (R.T.H.); (Y.L.); (M.G.N.)
- Centre for Individualised Infection Medicine (CiiM) & TWINCORE, Joint Ventures between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medical School (MHH), 30625 Hannover, Germany
| | - Mihai G. Netea
- Department of Internal Medicine and Radboud Centre for Infectious Diseases, Radboud University Nijmegen Medical Center, 6525 GA Nijmegen, The Netherlands; (R.T.H.); (Y.L.); (M.G.N.)
- Department for Immunology & Metabolism, Life and Medical Sciences Institute (LIMES), University of Bonn, 53115 Bonn, Germany
| | - Manuel Jurado
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Hematology Department, Virgen de las Nieves University Hospital, 18012 Granada, Spain;
- Instituto de Investigación Biosanataria IBs. Granada, 18012 Granada, Spain
- Department of Medicine, Faculty of Medicine, University of Granada, 18016 Granada, Spain
| | - Jose Antonio Lorente
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Department of Legal Medicine, Faculty of Medicine, University of Granada, 18016 Granada, Spain
| | - Pedro Sánchez-Rovira
- Department of Medical Oncology, Complejo Hospitalario de Jaén, 23007 Jaén, Spain; (F.G.-M.); (F.J.G.-V.); (J.A.L.L.); (P.S.-R.)
| | - María Jesús Álvarez-Cubero
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Department of Biochemistry and Molecular Biology III, Faculty of Medicine, University of Granada, 18016 Granada, Spain;
| | - Juan Sainz
- Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain; (J.M.S.-M.); (A.J.C.-S.); (I.R.-F.); (V.A.-R.); (M.J.); (J.A.L.); (M.J.Á.-C.)
- Hematology Department, Virgen de las Nieves University Hospital, 18012 Granada, Spain;
- Instituto de Investigación Biosanataria IBs. Granada, 18012 Granada, Spain
- Department of Biochemistry and Molecular Biology I, Faculty of Sciences, University of Granada, 18071 Granada, Spain
- Correspondence: ; Tel.: +34-95871-5500 (ext. 126); Fax: +34-9-5863-7071
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13
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Udhaya Kumar S, Kamaraj B, Varghese RP, Preethi VA, Bithia R, George Priya Doss C. Mutations in G6PC2 gene with increased risk for development of type 2 diabetes: Understanding via computational approach. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 130:351-373. [PMID: 35534112 DOI: 10.1016/bs.apcsb.2022.02.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
An increase in the fast blood glucose (FBG) levels has been linked to an increased risk of developing a chronic condition, type 2 diabetes (T2D). The mutation in the G6PC2 gene was identified to have a lead role in the modulation of FBG levels. The abnormal regulation of this enzyme influences glucose-stimulated insulin secretion (GSIS), which controls the insulin levels corresponding to the system's glucose level. This study focuses on the mutations at the G6PC2 gene, which cause the variation from normal expression levels and increase the risk of T2D. We examined the non-synonymous single nucleotide polymorphisms (nsSNPs) present in the G6PC2 and subjected them to pathogenicity, stability, residue conservation, and membrane simulation. The individual representation of surrounding amino acids in the mutant (I63T) model showed the loss of hydrophobic interactions compared to the native G6PC2. In addition, the trajectory results from the membrane simulation exhibited reduced stability, and the least compactness was identified for the I63T mutant model. Our study shed light on the structural and conformational changes at the transmembrane region due to the I63T mutation in G6PC2. Additionally, the Gibbs free energy landscape analysis against the two principal components showed structural differences and decreased the conformational stability of the I63T mutant model compared to the native. Like those presented in this study, dynamical simulations may indeed be crucial to comprehending the structural insights of G6PC2 mutations in cardiovascular-associated mortality and T2D.
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Affiliation(s)
- S Udhaya Kumar
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Balu Kamaraj
- Department of Neuroscience Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia
| | - Rinku Polachirakkal Varghese
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - V Anu Preethi
- School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - R Bithia
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - C George Priya Doss
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
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14
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Glucose-6-phosphatase catalytic subunit 2 negatively regulates glucose oxidation and insulin secretion in pancreatic β-cells. J Biol Chem 2022; 298:101729. [PMID: 35176280 PMCID: PMC8941207 DOI: 10.1016/j.jbc.2022.101729] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 02/11/2022] [Accepted: 02/12/2022] [Indexed: 12/11/2022] Open
Abstract
Elevated fasting blood glucose (FBG) is associated with increased risks of developing type 2 diabetes (T2D) and cardiovascular-associated mortality. G6PC2 is predominantly expressed in islets, encodes a glucose-6-phosphatase catalytic subunit that converts glucose-6-phosphate (G6P) to glucose, and has been linked with variations in FBG in genome-wide association studies. Deletion of G6pc2 in mice has been shown to lower FBG without affecting fasting plasma insulin levels in vivo. At 5 mM glucose, pancreatic islets from G6pc2 knockout (KO) mice exhibit no glucose cycling, increased glycolytic flux, and enhanced glucose-stimulated insulin secretion (GSIS). However, the broader effects of G6pc2 KO on β-cell metabolism and redox regulation are unknown. Here we used CRISPR/Cas9 gene editing and metabolic flux analysis in βTC3 cells, a murine pancreatic β-cell line, to examine the role of G6pc2 in regulating glycolytic and mitochondrial fluxes. We found that deletion of G6pc2 led to ∼60% increases in glycolytic and citric acid cycle (CAC) fluxes at both 5 and 11 mM glucose concentrations. Furthermore, intracellular insulin content and GSIS were enhanced by approximately two-fold, along with increased cytosolic redox potential and reductive carboxylation flux. Normalization of fluxes relative to net glucose uptake revealed upregulation in two NADPH-producing pathways in the CAC. These results demonstrate that G6pc2 regulates GSIS by modulating not only glycolysis but also, independently, citric acid cycle activity in β-cells. Overall, our findings implicate G6PC2 as a potential therapeutic target for enhancing insulin secretion and lowering FBG, which could benefit individuals with prediabetes, T2D, and obesity.
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15
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Overway EM, Bosma KJ, Claxton DP, Oeser JK, Singh K, Breidenbach LB, Mchaourab HS, Davis LK, O'Brien RM. Nonsynonymous single-nucleotide polymorphisms in the G6PC2 gene affect protein expression, enzyme activity, and fasting blood glucose. J Biol Chem 2022; 298:101534. [PMID: 34954144 PMCID: PMC8800118 DOI: 10.1016/j.jbc.2021.101534] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 12/30/2022] Open
Abstract
G6PC2 encodes a glucose-6-phosphatase (G6Pase) catalytic subunit that modulates the sensitivity of insulin secretion to glucose and thereby regulates fasting blood glucose (FBG). A common single-nucleotide polymorphism (SNP) in G6PC2, rs560887 is an important determinant of human FBG variability. This SNP has a subtle effect on G6PC2 RNA splicing, which raises the question as to whether nonsynonymous SNPs with a major impact on G6PC2 stability or enzyme activity might have a broader disease/metabolic impact. Previous attempts to characterize such SNPs were limited by the very low inherent G6Pase activity and expression of G6PC2 protein in islet-derived cell lines. In this study, we describe the use of a plasmid vector that confers high G6PC2 protein expression in islet cells, allowing for a functional analysis of 22 nonsynonymous G6PC2 SNPs, 19 of which alter amino acids that are conserved in mouse G6PC2 and the human and mouse variants of the related G6PC1 isoform. We show that 16 of these SNPs markedly impair G6PC2 protein expression (>50% decrease). These SNPs have variable effects on the stability of human and mouse G6PC1, despite the high sequence homology between these isoforms. Four of the remaining six SNPs impaired G6PC2 enzyme activity. Electronic health record-derived phenotype analyses showed an association between high-impact SNPs and FBG, but not other diseases/metabolites. While homozygous G6pc2 deletion in mice increases the risk of hypoglycemia, these human data reveal no evidence that the beneficial use of partial G6PC2 inhibitors to lower FBG would be associated with unintended negative consequences.
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Affiliation(s)
- Emily M Overway
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Karin J Bosma
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Derek P Claxton
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - James K Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Kritika Singh
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Lindsay B Breidenbach
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Hassane S Mchaourab
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Lea K Davis
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA; Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Richard M O'Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
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16
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Zusi C, Rinaldi E, Bonetti S, Boselli ML, Trabetti E, Malerba G, Bonora E, Bonadonna RC, Trombetta M. Haplotypes of the genes (GCK and G6PC2) underlying the glucose/glucose-6-phosphate cycle are associated with pancreatic beta cell glucose sensitivity in patients with newly diagnosed type 2 diabetes from the VNDS study (VNDS 11). J Endocrinol Invest 2021; 44:2567-2574. [PMID: 34128214 DOI: 10.1007/s40618-020-01483-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 12/07/2020] [Indexed: 10/21/2022]
Abstract
BACKGROUND Elevated fasting plasma glucose has been associated with increased risk for development of type 2 diabetes (T2D). The balance between glucokinase (GCK) and glucose-6-phosphate catalytic subunit 2 (G6PC2) activity are involved in glucose homeostasis through glycolytic flux, and subsequent insulin secretion. AIM In this study, we evaluated the association between the genetic variability of G6PC2 and GCK genes and T2D-related quantitative traits. METHODS In 794 drug-naïve, GADA-negative, newly diagnosed T2D patients (VNDS; NTC01526720) we performed: genotyping of 6 independent tag-SNPs within GCK gene and 5 tag-SNPs within G6PC2 gene; euglycaemic insulin clamp to assess insulin sensitivity; OGTT to estimate beta-cell function (derivative and proportional control; DC, PC) by mathematical modeling. Genetic association analysis has been conducted using Plink software. RESULTS Two SNPs within GCK gene (rs882019 and rs1303722) were associated to DC in opposite way (both p < 0.004). Two G6PC2 variants (rs13387347 and rs560887) were associated to both parameters of insulin secretion (DC and PC) and to fasting C-peptide levels (all p < 0.038). Moreover, subjects carrying the A allele of rs560887 showed higher values of 2h-plasma glucose (2hPG) (p = 0.033). Haplotype analysis revealed that GCK (AACAAA) haplotype was associated to decreased fasting C-peptide levels, whereas, the most frequent haplotype of G6PC2 (GGAAG) was associated with higher fasting C-peptide levels (p = 0.001), higher PC (β = 6.87, p = 0.022) and the lower 2hPG (p = 0.012). CONCLUSION Our findings confirmed the role of GCK and G6PC2 in regulating the pulsatility in insulin secretion thereby influencing insulin-signaling and leading to a gradual modulation in glucose levels in Italian patients with newly diagnosed T2D.
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Affiliation(s)
- C Zusi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Hospital Trust of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - E Rinaldi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Hospital Trust of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - S Bonetti
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Hospital Trust of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - M L Boselli
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Hospital Trust of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - E Trabetti
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Biology and Genetics, University of Verona, Verona, Italy
| | - G Malerba
- Department of Neuroscience, Biomedicine and Movement Sciences, Section of Biology and Genetics, University of Verona, Verona, Italy
| | - E Bonora
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Hospital Trust of Verona, Piazzale Stefani 1, 37126, Verona, Italy
| | - R C Bonadonna
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Division of Endocrinology and Metabolic Diseases, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - M Trombetta
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Hospital Trust of Verona, Piazzale Stefani 1, 37126, Verona, Italy.
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17
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Buchanan VL, Wang Y, Blanco E, Graff M, Albala C, Burrows R, Santos JL, Angel B, Lozoff B, Voruganti VS, Guo X, Taylor KD, Chen YDI, Yao J, Tan J, Downie C, Highland HM, Justice AE, Gahagan S, North KE. Genome-wide association study identifying novel variant for fasting insulin and allelic heterogeneity in known glycemic loci in Chilean adolescents: The Santiago Longitudinal Study. Pediatr Obes 2021; 16:e12765. [PMID: 33381925 PMCID: PMC8711702 DOI: 10.1111/ijpo.12765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 11/25/2020] [Indexed: 12/01/2022]
Abstract
BACKGROUND The genetic underpinnings of glycemic traits have been understudied in adolescent and Hispanic/Latino (H/L) populations in comparison to adults and populations of European ancestry. OBJECTIVE To identify genetic factors underlying glycemic traits in an adolescent H/L population. METHODS We conducted a genome-wide association study (GWAS) of fasting glucose (FG) and fasting insulin (FI) in H/L adolescents from the Santiago Longitudinal Study. RESULTS We identified one novel variant positioned in the CSMD1 gene on chromosome 8 (rs77465890, effect allele frequency = 0.10) that was associated with FI (β = -0.299, SE = 0.054, p = 2.72×10-8 ) and was only slightly attenuated after adjusting for body mass index z-scores (β = -0.252, SE = 0.047, p = 1.03×10-7 ). We demonstrated directionally consistent, but not statistically significant results in African and Hispanic adults of the Population Architecture Using Genomics and Epidemiology Consortium. We also identified secondary signals for two FG loci after conditioning on known variants, which demonstrate allelic heterogeneity in well-known glucose loci. CONCLUSION Our results exemplify the importance of including populations with diverse ancestral origin and adolescent participants in GWAS of glycemic traits to uncover novel risk loci and expand our understanding of disease aetiology.
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Affiliation(s)
- Victoria L Buchanan
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Estela Blanco
- Division of Academic General Pediatrics, Child Development and Community Health, University of California at San Diego, San Diego, California, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cecilia Albala
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Raquel Burrows
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - José L Santos
- Department of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Bárbara Angel
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile
| | - Betsy Lozoff
- Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA
| | - Venkata Saroja Voruganti
- Department of Nutrition and UNC Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Carolina Downie
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Anne E Justice
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania, USA
| | - Sheila Gahagan
- Division of Academic General Pediatrics, Child Development and Community Health, University of California at San Diego, San Diego, California, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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18
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Sayed S, Nabi AHMN. Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1307:457-498. [PMID: 32314317 DOI: 10.1007/5584_2020_518] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.
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Affiliation(s)
- Shomoita Sayed
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh.
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19
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Li C, Yang Y, Liu X, Li Z, Liu H, Tan Q. Glucose metabolism-related gene polymorphisms as the risk predictors of type 2 diabetes. Diabetol Metab Syndr 2020; 12:97. [PMID: 33292424 PMCID: PMC7643457 DOI: 10.1186/s13098-020-00604-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 10/22/2020] [Accepted: 10/26/2020] [Indexed: 02/07/2023] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a complex polygenic metabolic disease characterized by elevated blood glucose. Multiple environmental and genetic factors can increase the risk of T2DM and its complications, and genetic polymorphisms are no exception. This review is mainly focused on the related genes involved in glucose metabolic, including G6PC2, GCK, GCKR and OCT3. In this review, we have summarized the results reported globally and found that the genetic variants of GCK and OCT3 genes is a risk factor for T2DM while G6PC2 and GCKR genes are controversial in different ethnic groups. Hopefully, this summary could possibly help researchers and physicians understand the mechanism of T2DM so as to diagnose and even prevent T2DM at early time.
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Affiliation(s)
- Cuilin Li
- Department of Pharmacy, The Affiliated Zhuzhou Hospital Xiangya Medical College CSU, Zhuzhou, 412007, Hunan, China.
| | - Yuping Yang
- Department of Pharmacy, The Affiliated Zhuzhou Hospital Xiangya Medical College CSU, Zhuzhou, 412007, Hunan, China
| | - Xin Liu
- Department of Pharmacy, The Affiliated Zhuzhou Hospital Xiangya Medical College CSU, Zhuzhou, 412007, Hunan, China
| | - Zhongyu Li
- Laboratory Medical Center, The Affiliated Zhuzhou Hospital Xiangya Medical College CSU, Zhuzhou, 412007, China
| | - Hong Liu
- Department of Metabolism and Endocrinology, The Affiliated Zhuzhou Hospital Xiangya Medical College CSU, Zhuzhou, 412007, China
| | - Qiuhong Tan
- Department of Pharmacy, The Affiliated Zhuzhou Hospital Xiangya Medical College CSU, Zhuzhou, 412007, Hunan, China
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20
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Jung SY, Papp JC, Sobel EM, Zhang ZF. Mendelian Randomization Study: The Association Between Metabolic Pathways and Colorectal Cancer Risk. Front Oncol 2020; 10:1005. [PMID: 32850306 PMCID: PMC7396568 DOI: 10.3389/fonc.2020.01005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 05/21/2020] [Indexed: 12/24/2022] Open
Abstract
Background: The roles of obesity-related biomarkers and their molecular pathways in the development of postmenopausal colorectal cancer (CRC) have been inconclusive. We examined insulin resistance (IR) as a major hormonal pathway mediating the association between obesity and CRC risk in a Mendelian randomization (MR) framework. Methods: We performed MR analysis using individual-level data of 11,078 non-Hispanic white postmenopausal women from our earlier genome-wide association study. We identified four independent single-nucleotide polymorphisms associated with fasting glucose (FG), three with fasting insulin (FI), and six with homeostatic model assessment–IR (HOMA-IR), which were not associated with obesity. We estimated hazard ratios (HRs) for CRC by adjusting for potential confounding factors plus genetic principal components. Results: Overall, we observed no direct association between combined 13 IR genetic instruments and CRC risk (HR = 0.96, 95% confidence interval [CI]: 0.78–1.17). In phenotypic analysis, genetically raised HOMA-IR exhibited its effects on the increased risk and FG and FI on the reduced risk for CRC, but with a lack of statistical power. Subgroup analyses by physical activity level and dietary fat intake with combined phenotypes showed that genetically determined IR was associated with reduced CRC risk in both physical activity-stratified (single contributor: MTRR rs722025; HR = 0.12, 95% CI: 0.02–0.62) and high-fat diet subgroups (main contributor: G6PC2 rs560887; HR = 0.59, 95% CI: 0.37–0.94). Conclusions: Complex evidence was observed for a potential causal association between IR and CRC risk. Our findings may provide an additional value of intervention trials to lower IR and reduce CRC risk.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jeanette C Papp
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Eric M Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.,Center for Human Nutrition, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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21
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Bosma KJ, Rahim M, Oeser JK, McGuinness OP, Young JD, O'Brien RM. G6PC2 confers protection against hypoglycemia upon ketogenic diet feeding and prolonged fasting. Mol Metab 2020; 41:101043. [PMID: 32569842 PMCID: PMC7369601 DOI: 10.1016/j.molmet.2020.101043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 05/26/2020] [Accepted: 06/16/2020] [Indexed: 12/14/2022] Open
Abstract
Objective G6PC2 is predominantly expressed in pancreatic islet beta cells. G6PC2 hydrolyzes glucose-6-phosphate to glucose and inorganic phosphate, thereby creating a futile substrate cycle that opposes the action of glucokinase. This substrate cycle determines the sensitivity of glucose-stimulated insulin secretion to glucose and hence regulates fasting blood glucose (FBG) but not fasting plasma insulin (FPI) levels. Our objective was to explore the physiological benefit this cycle confers. Methods We investigated the response of wild type (WT) and G6pc2 knockout (KO) mice to changes in nutrition. Results Pancreatic G6pc2 expression was little changed by ketogenic diet feeding but was inhibited by 24 hr fasting and strongly induced by high fat feeding. When challenged with either a ketogenic diet or 24 hr fasting, blood glucose fell to 70 mg/dl or less in G6pc2 KO but not WT mice, suggesting that G6PC2 may have evolved, in part, to prevent hypoglycemia. Prolonged ketogenic diet feeding reduced the effect of G6pc2 deletion on FBG. The hyperglycemia associated with high fat feeding was partially blunted in G6pc2 KO mice, suggesting that under these conditions the presence of G6PC2 is detrimental. As expected, FPI changed but did not differ between WT and KO mice in response to fasting, ketogenic and high fat feeding. Conclusions Since elevated FBG levels are associated with increased risk for cardiovascular-associated mortality (CAM), these studies suggest that, while G6PC2 inhibitors would be useful for lowering FBG and the risk of CAM, partial inhibition will be important to avoid the risk of hypoglycemia. G6pc2 deletion lowers fasting blood glucose (FBG) in chow and high fat fed mice. Elevated FBG increases the risk of cardiovascular-associated mortality (CAM). G6pc2 deletion results in hypoglycemia in mice on a ketogenic diet. G6pc2 deletion results in hypoglycemia in mice following prolonged fasting. G6PC2 inhibitors may prevent CAM but increase risk of hypoglycemia.
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Affiliation(s)
- Karin J Bosma
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Mohsin Rahim
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - James K Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Owen P McGuinness
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Jamey D Young
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Richard M O'Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
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22
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Bosma KJ, Rahim M, Singh K, Goleva SB, Wall ML, Xia J, Syring KE, Oeser JK, Poffenberger G, McGuinness OP, Means AL, Powers AC, Li WH, Davis LK, Young JD, O’Brien RM. Pancreatic islet beta cell-specific deletion of G6pc2 reduces fasting blood glucose. J Mol Endocrinol 2020; 64:235-248. [PMID: 32213654 PMCID: PMC7331801 DOI: 10.1530/jme-20-0031] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 03/13/2020] [Indexed: 12/25/2022]
Abstract
The G6PC1, G6PC2 and G6PC3 genes encode distinct glucose-6-phosphatase catalytic subunit (G6PC) isoforms. In mice, germline deletion of G6pc2 lowers fasting blood glucose (FBG) without affecting fasting plasma insulin (FPI) while, in isolated islets, glucose-6-phosphatase activity and glucose cycling are abolished and glucose-stimulated insulin secretion (GSIS) is enhanced at submaximal but not high glucose. These observations are all consistent with a model in which G6PC2 regulates the sensitivity of GSIS to glucose by opposing the action of glucokinase. G6PC2 is highly expressed in human and mouse islet beta cells however, various studies have shown trace G6PC2 expression in multiple tissues raising the possibility that G6PC2 also affects FBG through non-islet cell actions. Using real-time PCR we show here that expression of G6pc1 and/or G6pc3 are much greater than G6pc2 in peripheral tissues, whereas G6pc2 expression is much higher than G6pc3 in both pancreas and islets with G6pc1 expression not detected. In adult mice, beta cell-specific deletion of G6pc2 was sufficient to reduce FBG without changing FPI. In addition, electronic health record-derived phenotype analyses showed no association between G6PC2 expression and phenotypes clearly unrelated to islet function in humans. Finally, we show that germline G6pc2 deletion enhances glycolysis in mouse islets and that glucose cycling can also be detected in human islets. These observations are all consistent with a mechanism by which G6PC2 action in islets is sufficient to regulate the sensitivity of GSIS to glucose and hence influence FBG without affecting FPI.
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Affiliation(s)
- Karin J. Bosma
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Mohsin Rahim
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Kritika Singh
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Slavina B. Goleva
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Martha L. Wall
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Jing Xia
- Departments of Cell Biology and of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9039
| | - Kristen E. Syring
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - James K. Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Greg Poffenberger
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Owen P. McGuinness
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Anna L. Means
- Department of Surgery, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Alvin C. Powers
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
- VA Tennessee Valley Healthcare System, Nashville, TN 37232
| | - Wen-hong Li
- Departments of Cell Biology and of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390-9039
| | - Lea K. Davis
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Jamey D. Young
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Richard M. O’Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
- To whom correspondence should be addressed: Department of Molecular Physiology and Biophysics, 8415 MRB IV, 2213 Garland Ave, Vanderbilt University Medical School, Nashville, TN 37232-0615,
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23
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Momozawa Y, Merveille AC, Battaille G, Wiberg M, Koch J, Willesen JL, Proschowsky HF, Gouni V, Chetboul V, Tiret L, Fredholm M, Seppälä EH, Lohi H, Georges M, Lequarré AS. Genome wide association study of 40 clinical measurements in eight dog breeds. Sci Rep 2020; 10:6520. [PMID: 32300138 PMCID: PMC7162946 DOI: 10.1038/s41598-020-63457-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 03/26/2020] [Indexed: 12/29/2022] Open
Abstract
The domestic dog represents an ideal model for identifying susceptibility genes, many of which are shared with humans. In this study, we investigated the genetic contribution to individual differences in 40 clinically important measurements by a genome-wide association study (GWAS) in a multinational cohort of 472 healthy dogs from eight breeds. Meta-analysis using the binary effects model after breed-specific GWAS, identified 13 genome-wide significant associations, three of them showed experimental-wide significant associations. We detected a signal at chromosome 13 for the serum concentration of alanine aminotransferase (ALT) in which we detected four breed-specific signals. A large proportion of the variance of ALT (18.1–47.7%) was explained by this locus. Similarly, a single SNP was also responsible for a large proportion of the variance (6.8–78.4%) for other measurements such as fructosamine, stress during physical exam, glucose, and morphometric measurements. The genetic contribution of single variant was much larger than in humans. These findings illustrate the importance of performing meta-analysis after breed-specific GWAS to reveal the genetic contribution to individual differences in clinically important measurements, which would lead to improvement of veterinary medicine.
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Affiliation(s)
- Yukihide Momozawa
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège, Belgium. .,Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, 230-0045, Japan.
| | - Anne-Christine Merveille
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège, Belgium.,Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Géraldine Battaille
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège, Belgium.,Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Maria Wiberg
- Department of Equine and Small Animal Medicine, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
| | - Jørgen Koch
- Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg C, Denmark
| | - Jakob Lundgren Willesen
- Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg C, Denmark
| | | | - Vassiliki Gouni
- U955 - IMRB Inserm and Unité de Cardiologie d'Alfort (UCA), Université Paris-Est, École Nationale Vétérinaire d'Alfort, UPEC, 7 avenue du général de Gaulle, Maisons-Alfort, F-94700, France
| | - Valérie Chetboul
- U955 - IMRB Inserm and Unité de Cardiologie d'Alfort (UCA), Université Paris-Est, École Nationale Vétérinaire d'Alfort, UPEC, 7 avenue du général de Gaulle, Maisons-Alfort, F-94700, France
| | - Laurent Tiret
- U955 - IMRB, Biology of the neuromuscular system, Inserm, National Veterinary School of Alfort (ENVA), Maisons-Alfort, France
| | - Merete Fredholm
- Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg C, Denmark
| | - Eija H Seppälä
- Department of Veterinary Biosciences, Department of Medical and Clinical Genetics, University of Helsinki, Folkhälsan Research Center, Helsinki, Finland
| | - Hannes Lohi
- Department of Veterinary Biosciences, Department of Medical and Clinical Genetics, University of Helsinki, Folkhälsan Research Center, Helsinki, Finland
| | - Michel Georges
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège, Belgium.,Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Anne-Sophie Lequarré
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège, Belgium. .,Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium.
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24
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Prentki M, Peyot ML, Masiello P, Madiraju SRM. Nutrient-Induced Metabolic Stress, Adaptation, Detoxification, and Toxicity in the Pancreatic β-Cell. Diabetes 2020; 69:279-290. [PMID: 32079704 DOI: 10.2337/dbi19-0014] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 12/20/2019] [Indexed: 11/13/2022]
Abstract
Paraphrasing the Swiss physician and father of toxicology Paracelsus (1493-1541) on chemical agents used as therapeutics, "the dose makes the poison," it is now realized that this aptly applies to the calorigenic nutrients. The case here is the pancreatic islet β-cell presented with excessive levels of nutrients such as glucose, lipids, and amino acids. The short-term effects these nutrients exert on the β-cell are enhanced insulin biosynthesis and secretion and changes in glucose sensitivity. However, chronic fuel surfeit triggers additional compensatory and adaptive mechanisms by β-cells to cope with the increased insulin demand or to protect itself. When these mechanisms fail, toxicity due to the nutrient surplus ensues, leading to β-cell dysfunction, dedifferentiation, and apoptosis. The terms glucotoxicity, lipotoxicity, and glucolipotoxicity have been widely used, but there is some confusion as to what they mean precisely and which is most appropriate for a given situation. Here we address the gluco-, lipo-, and glucolipo-toxicities in β-cells by assessing the evidence both for and against each of them. We also discuss potential mechanisms and defend the view that many of the identified "toxic" effects of nutrient excess, which may also include amino acids, are in fact beneficial adaptive processes. In addition, candidate fuel-excess detoxification pathways are evaluated. Finally, we propose that a more general term should be used for the in vivo situation of overweight-associated type 2 diabetes reflecting both the adaptive and toxic processes to mixed calorigenic nutrients excess: "nutrient-induced metabolic stress" or, in brief, "nutri-stress."
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Affiliation(s)
- Marc Prentki
- Departments of Nutrition and Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Quebec, Canada
| | - Marie-Line Peyot
- Departments of Nutrition and Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Quebec, Canada
| | - Pellegrino Masiello
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - S R Murthy Madiraju
- Departments of Nutrition and Biochemistry and Molecular Medicine, University of Montreal, and Montreal Diabetes Research Center, Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Quebec, Canada
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25
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Gloaguen E, Dizier MH, Boissel M, Rocheleau G, Canouil M, Froguel P, Tichet J, Roussel R, Julier C, Balkau B, Mathieu F. General regression model: A "model-free" association test for quantitative traits allowing to test for the underlying genetic model. Ann Hum Genet 2019; 84:280-290. [PMID: 31834638 DOI: 10.1111/ahg.12372] [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: 07/20/2018] [Revised: 11/19/2019] [Accepted: 11/20/2019] [Indexed: 11/26/2022]
Abstract
Most genome-wide association studies used genetic-model-based tests assuming an additive mode of inheritance, leading to underpowered association tests in case of departure from additivity. The general regression model (GRM) association test proposed by Fisher and Wilson in 1980 makes no assumption on the genetic model. Interestingly, it also allows formal testing of the underlying genetic model. We conducted a simulation study of quantitative traits to compare the power of the GRM test to the classical linear regression tests, the maximum of the three statistics (MAX), and the allele-based (allelic) tests. Simulations were performed on two samples sizes, using a large panel of genetic models, varying genetic models, minor allele frequencies, and the percentage of explained variance. In case of departure from additivity, the GRM was more powerful than the additive regression tests (power gain reaching 80%) and had similar power when the true model is additive. GRM was also as or more powerful than the MAX or allelic tests. The true simulated model was mostly retained by the GRM test. Application of GRM to HbA1c illustrates its gain in power. To conclude, GRM increases power to detect association for quantitative traits, allows determining the genetic model and is easily applicable.
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Affiliation(s)
- Emilie Gloaguen
- Inserm UMRS-958, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Marie-Hélène Dizier
- Inserm UMR-946, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Mathilde Boissel
- Université de Lille, UMR 8199 - EGID, Lille, France.,CNRS, Paris, France.,Institut Pasteur de Lille, Lille, France
| | - Ghislain Rocheleau
- Université de Lille, UMR 8199 - EGID, Lille, France.,CNRS, Paris, France.,Institut Pasteur de Lille, Lille, France
| | - Mickaël Canouil
- Université de Lille, UMR 8199 - EGID, Lille, France.,CNRS, Paris, France.,Institut Pasteur de Lille, Lille, France
| | - Philippe Froguel
- Université de Lille, UMR 8199 - EGID, Lille, France.,CNRS, Paris, France.,Institut Pasteur de Lille, Lille, France.,Department of Genomics of Common Disease, Imperial College London, London, United Kingdom
| | | | - Ronan Roussel
- Inserm U1138, Centre de Recherche des Cordeliers, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Paris, France.,Diabetology, Endocrinology and Nutrition Department, DHU FIRE, Hôpital Bichat, AP-HP, Paris, France
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- Inserm UMRS-958, Paris, France
| | - Cécile Julier
- Inserm UMRS-958, Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | | | - Flavie Mathieu
- Mission Associations Recherche & Société - Inserm Siège, DISC, Paris, France.,Paris Diderot, Sorbonne Paris Cité, Paris, France
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26
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Jung SY, Mancuso N, Papp J, Sobel E, Zhang ZF. Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization. PLoS One 2019; 14:e0218917. [PMID: 31246991 PMCID: PMC6597082 DOI: 10.1371/journal.pone.0218917] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 06/13/2019] [Indexed: 12/18/2022] Open
Abstract
PURPOSE The role of insulin resistance (IR) in developing postmenopausal breast cancer has not been thoroughly resolved and may be confounded by lifestyle factors such as obesity. We examined whether genetically determined IR is causally associated with breast cancer risk. METHODS We conducted Mendelian randomization (MR) analyses using individual-level data from our previous meta-analysis of a genome-wide association study (GWAS) (n = 11,109 non-Hispanic white postmenopausal women). Four single-nucleotide polymorphisms were associated with fasting glucose (FG), 2 with fasting insulin (FI), and 6 with homeostatic model assessment-IR (HOMA-IR) but were not associated with obesity. We used this GWAS to employ hazard ratios (HRs) for breast cancer risk by adjusting for potential confounding factors. RESULTS No direct association was observed between comprising 12 IR genetic instruments and breast cancer risk (HR = 0.93, 95% CI: 0.76-1.14). In phenotype-specific analysis, genetically elevated FG was associated with reduced risk for breast cancer (main contributor of this MR-effect estimate: G6PC2 rs13431652; HR = 0.59, 95% CI: 0.35-0.99). Genetically driven FI and HOMA-IR were not significantly associated. Stratification analyses by body mass index, exercise, and dietary fat intake with combined phenotypes showed that genetically elevated IR was associated with greater breast cancer risk in overall obesity and inactive subgroups (single contributor: MTRR/LOC729506 rs13188458; HR = 2.21, 95% CI: 1.03-4.75). CONCLUSIONS We found complex evidence for causal association between IR and risk of breast cancer, which may support the potential value of intervention trials to lower IR and reduce breast cancer risk.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California, Los Angeles, Los Angeles, CA, United States of America
- * E-mail:
| | - Nicholas Mancuso
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Jeanette Papp
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Eric Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States of America
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Noncoding Variations in the Gene Encoding Ceramide Synthase 6 are Associated with Type 2 Diabetes in a Large Indigenous Australian Pedigree. Twin Res Hum Genet 2019; 22:79-87. [PMID: 31012404 DOI: 10.1017/thg.2019.13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Type 2 diabetes (T2D) is a chronic disease that disproportionately affects Indigenous Australians. We have previously reported the localization of a novel T2D locus by linkage analysis to chromosome 2q24 in a large admixed Indigenous Australian pedigree (Busfield et al. (2002). American Journal of Human Genetics, 70, 349-357). Here we describe fine mapping of this region in this pedigree, with the identification of SNPs showing strong association with T2D: rs3845724 (diabetes p = 7 × 10-4), rs4668106 (diabetes p = 9 × 10-4) and rs529002 (plasma glucose p = 3 × 10-4). These associations were successfully replicated in an independent collection of Indigenous Australian T2D cases and controls. These SNPs all lie within the gene encoding ceramide synthase 6 (CERS6) and thus may regulate ceramide synthesis.
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28
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Barroso I, McCarthy MI. The Genetic Basis of Metabolic Disease. Cell 2019; 177:146-161. [PMID: 30901536 PMCID: PMC6432945 DOI: 10.1016/j.cell.2019.02.024] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 02/11/2019] [Accepted: 02/14/2019] [Indexed: 02/06/2023]
Abstract
Recent developments in genetics and genomics are providing a detailed and systematic characterization of the genetic underpinnings of common metabolic diseases and traits, highlighting the inherent complexity within systems for homeostatic control and the many ways in which that control can fail. The genetic architecture underlying these common metabolic phenotypes is complex, with each trait influenced by hundreds of loci spanning a range of allele frequencies and effect sizes. Here, we review the growing appreciation of this complexity and how this has fostered the implementation of genome-scale approaches that deliver robust mechanistic inference and unveil new strategies for translational exploitation.
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Affiliation(s)
- Inês Barroso
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford OX3 7LJ, UK; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Old Road, Headington, Oxford OX3 7LJ, UK
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29
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Liu S, Li L, Meng J, Song K, Huang B, Wang W, Zhang G. Association and Functional Analyses Revealed That PPP1R3B Plays an Important Role in the Regulation of Glycogen Content in the Pacific Oyster Crassostrea gigas. Front Genet 2019; 10:106. [PMID: 30853975 PMCID: PMC6396720 DOI: 10.3389/fgene.2019.00106] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 01/30/2019] [Indexed: 12/15/2022] Open
Abstract
The Pacific oyster (Crassostrea gigas) is one of the most important aquaculture species worldwide. Glycogen contributes greatly to the special taste and creamy white color of oysters. Previous genome-wide association studies (GWAS) identified several single nucleotide polymorphism (SNP) sites that were strongly related to glycogen content. Genes within 100 kb upstream and downstream of the associated SNPs were screened. One gene annotated as protein phosphatase 1 regulatory subunit 3B (PPP1R3B), which can promote glycogen synthesis together with protein phosphatase 1 catalytic subunit (PPP1C) in mammals, was selected as a candidate gene in this study. First, full-length CgPPP1R3B was cloned and its function was characterized. The gene expression profiles of CgPPP1R3B in different tissues and seasons showed a close relationship to glycogen content. RNA interference (RNAi) experiments of this gene in vivo showed that decreased CgPPP1R3B levels resulted in lower glycogen contents in the experimental group than in the control group. Co-immunoprecipitation (Co-IP) and yeast two-hybrid (Y2H) assays indicated that CgPPP1R3B can interact with CgPPP1C, glycogen synthase (CgGS) and glycogen phosphorylase (CgGP), thus participating in glycogen metabolism. Co-sedimentation analysis in vitro demonstrated that the CgPPP1R3B protein can bind to glycogen molecules directly, and these results indicated the conserved function of the CgPPP1R3B protein compared to that of mammals. In addition, thirteen SNPs were precisely mapped in this gene. Ten of the thirteen SNPs were confirmed to be significantly (p < 0.05) related to glycogen content in an independent wild population (n = 288). The CgPPP1R3B levels in oysters with high glycogen content were significantly higher than those of oysters with low glycogen content, and gene expression levels were significantly associated with various genotypes of four associated SNPs (p < 0.05). The data indicated that the associated SNPs may control glycogen content by regulating CgPPP1R3B expression. These results suggest that CgPPP1R3B is an important gene for glycogen metabolic regulation and that the associated SNPs of this gene are potential markers for oyster molecular breeding for increased glycogen content.
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Affiliation(s)
- Sheng Liu
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Li Li
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China.,Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
| | - Jie Meng
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China.,Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
| | - Kai Song
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China.,Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
| | - Baoyu Huang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China.,Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
| | - Wei Wang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China.,Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
| | - Guofan Zhang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,National and Local Joint Engineering Laboratory of Ecological Mariculture, Qingdao, China.,Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
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30
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Caspers M, Blocquiaux S, Charlier R, Lefevre J, De Bock K, Thomis M. Metabolic fitness in relation to genetic variation and leukocyte DNA methylation. Physiol Genomics 2019; 51:12-26. [DOI: 10.1152/physiolgenomics.00077.2018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Metabolic syndrome (MetS) is a highly prevalent condition causing increased risk of several life-threatening diseases. MetS has a pronounced hereditary basis but is also influenced by environmental factors, partly through epigenetic mechanisms. In this study, the five phenotypes underlying MetS were incorporated into a continuous score for metabolic fitness (MF), and associations with both genotypic variation and leukocyte DNA methylation were investigated. Baseline MF phenotypes (waist circumference, blood pressure, blood glucose, serum triglycerides, and high-density lipoproteins) of 710 healthy Flemish adults were measured. After a 10 yr period, follow-up measures were derived from 618 of these subjects. Genotyping was performed for 65 preselected MF-related genetic variants. Next, full genetic predisposition scores (GPSs) were calculated, combining genotype scores of multiple genetic variants. Additionally, stepwise GPSs were constructed, including only the most predictive genetic variants for the different MF phenotypes. For a subset of 68 middle-aged men, global and gene-specific DNA methylation was investigated, and a biological pathway analysis was performed. The full GPSs were predictive for some baseline MF phenotypes, but not for changes over time. Only a limited number of genetic variants were significantly predictive individually. On the contrary, global and gene-specific DNA methylation was associated with changes in the MF phenotypes rather than with the baseline measures, indicating that effects of DNA methylation on MF are somewhat delayed. Furthermore, several biological pathways were associated with the MF phenotypes through gene promoter methylation. For CETP, G6PC2, MC4R, and TFAP2B both a genetic and epigenetic relationship was found with MF.
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Affiliation(s)
- M. Caspers
- Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - S. Blocquiaux
- Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - R. Charlier
- Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - J. Lefevre
- Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - K. De Bock
- Department of Health Sciences and Technology, ETH Zürich, Schwerzenbach, Switzerland
| | - M. Thomis
- Department of Movement Sciences, KU Leuven, Leuven, Belgium
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31
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Johnson MP, Keyho R, Blackburn NB, Laston S, Kumar S, Peralta J, Thapa SS, Towne B, Subedi J, Blangero J, Williams-Blangero S. Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors. J Diabetes Res 2019; 2019:2310235. [PMID: 31089471 PMCID: PMC6476113 DOI: 10.1155/2019/2310235] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 12/20/2018] [Accepted: 01/12/2019] [Indexed: 01/08/2023] Open
Abstract
Measurements of fasting glucose (FG) or glycated hemoglobin A1c (HbA1c) are two clinically approved approaches commonly used to determine glycemia, both of which are influenced by genetic factors. Obtaining accurate measurements of FG or HbA1c is not without its challenges, though. Measuring glycated serum protein (GSP) offers an alternative approach for assessing glycemia. The aim of this study was to estimate the heritability of GSP and GSP expressed as a percentage of total serum albumin (%GA) using a variance component approach and localize genomic regions (QTLs) that harbor genes likely to influence GSP and %GA trait variation in a large extended multigenerational pedigree from Jiri, Nepal (n = 1,800). We also performed quantitative bivariate analyses to assess the relationship between GSP or %GA and several cardiometabolic traits. Additive genetic effects significantly influence variation in GSP and %GA levels (p values: 1.15 × 10-5 and 3.39 × 10-5, respectively). We localized a significant (LOD score = 3.18) and novel GSP QTL on chromosome 11q, which has been previously linked to type 2 diabetes. Two common (MAF > 0.4) SNPs within the chromosome 11 QTL were associated with GSP (adjusted pvalue < 5.87 × 10-5): an intronic variant (rs10790184) in the DSCAML1 gene and a 3'UTR variant (rs8258) in the CEP164 gene. Significant positive correlations were observed between GSP or %GA and blood pressure, and lipid traits (p values: 0.0062 to 1.78 × 10-9). A significant negative correlation was observed between %GA and HDL cholesterol (p = 1.12 × 10-5). GSP is influenced by genetic factors and can be used to assess glycemia and diabetes risk. Thus, GSP measurements can facilitate glycemic studies when accurate FG and/or HbA1c measurements are difficult to obtain. GSP can also be measured from frozen blood (serum) samples, which allows the prospect of retrospective glycemic studies using archived samples.
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Affiliation(s)
- Matthew P. Johnson
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Ryan Keyho
- The University of Texas at Austin, Austin, Texas 78705, USA
| | - Nicholas B. Blackburn
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Sandra Laston
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Satish Kumar
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Juan Peralta
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Menzies Institute for Medical Research, University of Tasmania, Hobart 7000, Australia
| | - Suman S. Thapa
- Tilganga Institute of Ophthalmology, Gaushala, Bagmati Bridge, P.O. Box 561, Kathmandu, Nepal
| | - Bradford Towne
- Department of Population Health and Public Health Sciences, Boonshoft School of Medicine, Wright State University, Kettering, Ohio 45435, USA
| | - Janardan Subedi
- Department of Sociology and Gerontology, College of Arts and Science, Miami University, Oxford, Ohio 45056, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Sarah Williams-Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
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32
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Cheng L, Zhuang H, Yang S, Jiang H, Wang S, Zhang J. Exposing the Causal Effect of C-Reactive Protein on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study. Front Genet 2018; 9:657. [PMID: 30619477 PMCID: PMC6306438 DOI: 10.3389/fgene.2018.00657] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 12/03/2018] [Indexed: 12/21/2022] Open
Abstract
As a biomarker of inflammation, C-reactive protein (CRP) has attracted much attention due to its role in the incidence of type 2 diabetes mellitus (T2DM). Prospective studies have observed a positive correlation between the level of serum CRP and the incidence of T2DM. Recently, studies have reported that drugs for curing T2DM can also decrease the level of serum CRP. However, it is not yet clear whether high CRP levels cause T2DM. To evaluate this, we conducted a Mendelian randomization (MR) analysis using genetic variations as instrumental variables (IVs). Significantly associated single nucleotide polymorphisms (SNPs) of CRP were obtained from a genome-wide study and a replication study. Therein, 17,967 participants were utilized for the genome-wide association study (GWAS), and another 14,747 participants were utilized for the replication of identifying SNPs associated with CRP levels. The associations between SNPs and T2DM were from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium. After removing SNPs in linkage disequilibrium (LD) and T2DM-related SNPs, the four remaining CRP-related SNPs were deemed as IVs. To evaluate the pooled influence of these IVs on the risk of developing T2DM through CRP, the penalized robust inverse-variance weighted (IVW) method was carried out. The combined result (OR 1.114048; 95% CI 1.058656 to 1.172338; P = 0.024) showed that high levels of CRP significantly increase the risk of T2DM. In the subsequent analysis of the relationship between CRP and type 1 diabetes mellitus (T1DM), the pooled result (OR 1.017145; 95% CI 0.9066489 to 1.14225; P = 0.909) supported that CRP levels cannot determine the risk of developing T1DM.
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Affiliation(s)
- Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - He Zhuang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Shuo Yang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Huijie Jiang
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Song Wang
- Department of Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jun Zhang
- Heilongjiang Provincial Hospital, Harbin, China
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33
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Canouil M, Balkau B, Roussel R, Froguel P, Rocheleau G. Jointly Modelling Single Nucleotide Polymorphisms With Longitudinal and Time-to-Event Trait: An Application to Type 2 Diabetes and Fasting Plasma Glucose. Front Genet 2018; 9:210. [PMID: 29963075 PMCID: PMC6010582 DOI: 10.3389/fgene.2018.00210] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Accepted: 05/25/2018] [Indexed: 11/13/2022] Open
Abstract
In observational cohorts, longitudinal data are collected with repeated measurements at predetermined time points for many biomarkers, along with other variables measured at baseline. In these cohorts, time until a certain event of interest occurs is reported and very often, a relationship will be observed between some biomarker repeatedly measured over time and that event. Joint models were designed to efficiently estimate statistical parameters describing this relationship by combining a mixed model for the longitudinal biomarker trajectory and a survival model for the time until occurrence of the event, using a set of random effects to account for the relationship between the two types of data. In this paper, we discuss the implementation of joint models in genetic association studies. First, we check model consistency based on different simulation scenarios, by varying sample sizes, minor allele frequencies and number of repeated measurements. Second, using genotypes assayed with the Metabochip DNA arrays (Illumina) from about 4,500 individuals recruited in the French cohort D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome), we assess the feasibility of implementing the joint modelling approach in a real high-throughput genomic dataset. An alternative model approximating the joint model, called the Two-Step approach (TS), is also presented. Although the joint model shows more precise and less biased estimators than its alternative counterpart, the TS approach results in much reduced computational times, and could thus be used for testing millions of SNPs at the genome-wide scale.
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Affiliation(s)
- Mickaël Canouil
- Université de Lille, UMR 8199-EGID, Lille, France.,Centre National de la Recherche Scientifique, UMR 8199, Lille, France.,Institut Pasteur de Lille, Lille, France
| | - Beverley Balkau
- Centre for Research in Epidemiology and Population Health, Villejuif, France.,Université Paris-Saclay, Université Paris Sud, UVSQ, UMRS 1018, Villejuif, France.,Institut National de la Santé et de la Recherche Médicale U1018, Centre de Recherche en Épidémiologie et Santé des Populations, Renal and Cardiovascular Epidemiology, UVSQ-UPS, Villejuif, France
| | - Ronan Roussel
- Institut National de la Santé et de la Recherche Médicale U1138 (équipe 2: Pathophysiology and Therapeutics of Vascular and Renal Diseases Related to Diabetes, Centre de Recherches des Cordeliers), Paris, France.,Université Paris 7 Denis Diderot, Sorbonne Paris Cité, Paris, France.,AP-HP, DHU FIRE, Department of Endocrinology, Diabetology, Nutrition, and Metabolic Diseases, Bichat Claude Bernard Hospital, Paris, France
| | - Philippe Froguel
- Université de Lille, UMR 8199-EGID, Lille, France.,Centre National de la Recherche Scientifique, UMR 8199, Lille, France.,Institut Pasteur de Lille, Lille, France.,Department of Genomics of Common Disease, Imperial College London, London, United Kingdom
| | - Ghislain Rocheleau
- Université de Lille, UMR 8199-EGID, Lille, France.,Centre National de la Recherche Scientifique, UMR 8199, Lille, France.,Institut Pasteur de Lille, Lille, France
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Spracklen CN, Shi J, Vadlamudi S, Wu Y, Zou M, Raulerson CK, Davis JP, Zeynalzadeh M, Jackson K, Yuan W, Wang H, Shou W, Wang Y, Luo J, Lange LA, Lange EM, Popkin BM, Gordon-Larsen P, Du S, Huang W, Mohlke KL. Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey. PLoS Genet 2018; 14:e1007275. [PMID: 29621232 PMCID: PMC5886383 DOI: 10.1371/journal.pgen.1007275] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 02/23/2018] [Indexed: 12/17/2022] Open
Abstract
To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.
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Affiliation(s)
- Cassandra N. Spracklen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jinxiu Shi
- Department of Genetics, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute, Shanghai, China
| | - Swarooparani Vadlamudi
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ying Wu
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Meng Zou
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Chelsea K. Raulerson
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - James P. Davis
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Monica Zeynalzadeh
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kayla Jackson
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Wentao Yuan
- Department of Genetics, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute, Shanghai, China
| | - Haifeng Wang
- Department of Genetics, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute, Shanghai, China
| | - Weihua Shou
- Department of Genetics, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute, Shanghai, China
| | - Ying Wang
- Department of Genetics, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute, Shanghai, China
| | - Jingchun Luo
- Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Ethan M. Lange
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Barry M. Popkin
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Penny Gordon-Larsen
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Shufa Du
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Heath and Disease Genomics, Chinese National Human Genome Center and Shanghai Industrial Technology Institute, Shanghai, China
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- * E-mail:
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A common variant within the HNF1B gene is associated with overall survival of multiple myeloma patients: results from the IMMEnSE consortium and meta-analysis. Oncotarget 2018; 7:59029-59048. [PMID: 27437873 PMCID: PMC5312293 DOI: 10.18632/oncotarget.10665] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 05/19/2016] [Indexed: 01/01/2023] Open
Abstract
Diabetogenic single nucleotide polymorphisms (SNPs) have recently been associated with multiple myeloma (MM) risk but their impact on overall survival (OS) of MM patients has not been analysed yet. In order to investigate the impact of 58 GWAS-identified variants for type 2 diabetes (T2D) on OS of patients with MM, we analysed genotyping data of 936 MM patients collected by the International Multiple Myeloma rESEarch (IMMENSE) consortium and an independent set of 700 MM patients recruited by the University Clinic of Heidelberg. A meta-analysis of the cox regression results of the two sets showed that rs7501939 located in the HNF1B gene negatively impacted OS (HRRec= 1.44, 95% CI = 1.18-1.76, P = 0.0001). The meta-analysis also showed a noteworthy gender-specific association of the SLC30A8rs13266634 SNP with OS. The presence of each additional copy of the minor allele at rs13266634 was associated with poor OS in men whereas no association was seen in women (HRMen-Add = 1.32, 95% CI 1.13-1.54, P = 0.0003). In conclusion, these data suggest that the HNF1Brs7501939 SNP confers poor OS in patients with MM and that a SNP in SLC30A8 affect OS in men.
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Wheeler E, Marenne G, Barroso I. Genetic aetiology of glycaemic traits: approaches and insights. Hum Mol Genet 2017; 26:R172-R184. [PMID: 28977447 PMCID: PMC5886471 DOI: 10.1093/hmg/ddx293] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 07/18/2017] [Accepted: 07/21/2017] [Indexed: 12/17/2022] Open
Abstract
Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.
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Affiliation(s)
- Eleanor Wheeler
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Gaëlle Marenne
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Inês Barroso
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK
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Lakbakbi El Yaagoubi F, Charoute H, Morjane I, Sefri H, Rouba H, Ainahi A, Kandil M, Benrahma H, Barakat A. Association analysis of genetic variants with metabolic syndrome components in the Moroccan population. Curr Res Transl Med 2017; 65:121-125. [DOI: 10.1016/j.retram.2017.08.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 07/17/2017] [Accepted: 08/09/2017] [Indexed: 12/17/2022]
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Meta-analyses of the association of G6PC2 allele variants with elevated fasting glucose and type 2 diabetes. PLoS One 2017; 12:e0181232. [PMID: 28704540 PMCID: PMC5509327 DOI: 10.1371/journal.pone.0181232] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 06/28/2017] [Indexed: 12/19/2022] Open
Abstract
Objective To collectively evaluate the association of glucose-6-phosphatase catalytic unit 2 (G6PC2) allele variants with elevated fasting glucose (FG) and type 2 diabetes (T2D). Design Meta-analysis Data sources PubMed, Web of Knowledge and Embase databases. Study selection Full text articles of studies that identified an association of G6PC2 with T2D and elevated FG. Patient involvement There was no T2D patient involvement in the analyses on the association of FG with G6PC2, there were T2D patients and non-diabetes patient involvement in the analyses on the association of T2D with G6PC2. Statistical analysis Random-effects meta-analyses were used to calculate the pool effect sizes. I2 metric and H2 tests were used to calculate the heterogeneity. Begg's funnel plot and Egger’s linear regression test were done to assess publication bias. Results Of the 423 studies identified, 21 were eligible and included. Data on three loci (rs560887, rs16856187 and rs573225) were available. The G allele at rs560887 in three ethnicities, the C allele at rs16856187 and the A allele at rs573225 all had a positive association with elevated FG. Per increment of G allele at rs560887 and A allele at rs573225 resulted in a FG 0.070 mmol/l and 0.075 mmol/l higher (ß (95% CI) = 0.070 (0.060, 0.079), p = 4.635e-50 and 0.075 (0.065, 0.085), p = 5.856e-48, respectively). With regard to the relationship of rs16856187 and FG, an increase of 0.152 (95% CI: 0.034–0.270; p = 0.011) and 0.317 (95% CI: 0.193–0.442, p = 6.046e-07) was found in the standardized mean difference (SMD) of FG for the AC and CC genotypes, respectively, when compared with the AA reference genotype. However, the G-allele of rs560887 in Caucasians under the additive model and the C-allele of rs16856187 under the allele and dominant models were associated with a decreased risk of T2D (OR (95% CI) = 0.964 (0.947, 0.981), p = 0.570e-4; OR (95% CI) = 0.892 (0.832, 0.956), p = 0.001; and OR (95% CI) = 0.923(0.892, 0.955), p = 5.301e-6, respectively). Conclusions Our meta-analyses demonstrate that all three allele variants of G6PC2 (rs560887, rs16856187 and rs573225) are associated with elevated FG, with two variants (rs560887 in the Caucasians subgroup and rs16856187 under the allele and dominant model) being associated with T2D as well. Further studies utilizing larger sample sizes and different ethnic populations are needed to extend and confirm these findings.
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Ashcroft FM, Rohm M, Clark A, Brereton MF. Is Type 2 Diabetes a Glycogen Storage Disease of Pancreatic β Cells? Cell Metab 2017; 26:17-23. [PMID: 28683284 PMCID: PMC5890904 DOI: 10.1016/j.cmet.2017.05.014] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 04/24/2017] [Accepted: 05/24/2017] [Indexed: 11/17/2022]
Abstract
Elevated plasma glucose leads to pancreatic β cell dysfunction and death in type 2 diabetes. Glycogen accumulation, due to impaired metabolism, contributes to this "glucotoxicity" via dysregulated biochemical pathways promoting β cell dysfunction. Here, we review emerging data, and re-examine published findings, on the role of glycogen in β cells in normoglycemia and in diabetes.
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Affiliation(s)
- Frances M Ashcroft
- Department of Physiology, Anatomy, and Genetics and OXION, University of Oxford, Parks Road, Oxford OX1 3PT, UK.
| | - Maria Rohm
- Department of Physiology, Anatomy, and Genetics and OXION, University of Oxford, Parks Road, Oxford OX1 3PT, UK
| | - Anne Clark
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Melissa F Brereton
- Department of Physiology, Anatomy, and Genetics and OXION, University of Oxford, Parks Road, Oxford OX1 3PT, UK
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40
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Thomsen SK, Gloyn AL. Human genetics as a model for target validation: finding new therapies for diabetes. Diabetologia 2017; 60:960-970. [PMID: 28447115 PMCID: PMC5423999 DOI: 10.1007/s00125-017-4270-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 03/14/2017] [Indexed: 01/01/2023]
Abstract
Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are 'experiments of nature' that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck.
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Affiliation(s)
- Soren K Thomsen
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford, OX3 7LE, UK
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford, OX3 7LE, UK.
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
- National Institute of Health Research Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK.
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41
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Merino J, Leong A, Posner DC, Porneala B, Masana L, Dupuis J, Florez JC. Genetically Driven Hyperglycemia Increases Risk of Coronary Artery Disease Separately From Type 2 Diabetes. Diabetes Care 2017; 40:687-693. [PMID: 28298470 PMCID: PMC5399655 DOI: 10.2337/dc16-2625] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 02/13/2017] [Indexed: 02/03/2023]
Abstract
OBJECTIVE This study tested the hypothesis that genetically raised hyperglycemia increases coronary artery disease (CAD) risk separately from the risk conferred by type 2 diabetes as a whole. RESEARCH DESIGN AND METHODS We conducted a Mendelian randomization (MR) analysis using summary-level statistics from the largest published meta-analyses of genome-wide association studies (GWAS) for fasting glucose (FG) (n = 133,010 participants free of diabetes) and CAD (n = 63,746 case subjects and 130,681 control subjects) of predominantly European ancestry. FG-increasing variants associated with type 2 diabetes from the largest GWAS for type 2 diabetes were excluded. Variants with pleiotropic effects on other CAD risk factors (blood lipids, blood pressure, and obesity) were excluded using summary-level data from the largest published GWAS. Data from the Framingham Heart Study were used to validate the MR instrument and to build an FG genetic risk score (GRS). RESULTS In an instrumental variable analysis comprising 12 FG-raising variants, a 1 mmol/L increase in FG revealed an effect-size estimate of 1.43 CAD odds (95% CI 1.14-1.79). The association was preserved after excluding variants for heterogeneity and pleiotropic effects on other CAD risk factors (odds ratio [OR] 1.33 [95% CI 1.02-1.73]). The 12 FG-increasing variants did not significantly increase type 2 diabetes risk (OR 1.05 [95% CI 0.91-1.23]), and its prevalence was constant across FG GRS quintiles (P = 0.72). CONCLUSIONS Our data support that genetic predisposition to hyperglycemia raises the odds of CAD separately from type 2 diabetes and other CAD risk factors. These findings suggest that modulating glycemia may provide cardiovascular benefit.
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Affiliation(s)
- Jordi Merino
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA.,Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA.,Vascular Medicine and Metabolism Unit, Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Institut Investigació Sanitaria Pere VirgiliI, Rovira i Virgili University, CIBERDEM, Reus, Spain
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA.,Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Daniel C Posner
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Lluís Masana
- Vascular Medicine and Metabolism Unit, Research Unit on Lipids and Atherosclerosis, Sant Joan University Hospital, Institut Investigació Sanitaria Pere VirgiliI, Rovira i Virgili University, CIBERDEM, Reus, Spain
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA.,National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA
| | - Jose C Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA .,Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA.,Department of Medicine, Harvard Medical School, Boston, MA
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Boortz KA, Syring KE, Pound LD, Mo H, Bastarache L, Oeser JK, McGuinness OP, Denny JC, O’Brien RM. Effects of G6pc2 deletion on body weight and cholesterol in mice. J Mol Endocrinol 2017; 58:127-139. [PMID: 28122818 PMCID: PMC5380368 DOI: 10.1530/jme-16-0202] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 01/24/2017] [Indexed: 11/08/2022]
Abstract
Genome-wide association study (GWAS) data have linked the G6PC2 gene to variations in fasting blood glucose (FBG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit that forms a substrate cycle with the beta cell glucose sensor glucokinase. This cycle modulates the glucose sensitivity of insulin secretion and hence FBG. GWAS data have not linked G6PC2 to variations in body weight but we previously reported that female C57BL/6J G6pc2-knockout (KO) mice were lighter than wild-type littermates on both a chow and high-fat diet. The purpose of this study was to compare the effects of G6pc2 deletion on FBG and body weight in both chow-fed and high-fat-fed mice on two other genetic backgrounds. FBG was reduced in G6pc2 KO mice largely independent of gender, genetic background or diet. In contrast, the effect of G6pc2 deletion on body weight was markedly influenced by these variables. Deletion of G6pc2 conferred a marked protection against diet-induced obesity in male mixed genetic background mice, whereas in 129SvEv mice deletion of G6pc2 had no effect on body weight. G6pc2 deletion also reduced plasma cholesterol levels in a manner dependent on gender, genetic background and diet. An association between G6PC2 and plasma cholesterol was also observed in humans through electronic health record-derived phenotype analyses. These observations suggest that the action of G6PC2 on FBG is largely independent of the influences of environment, modifier genes or epigenetic events, whereas the action of G6PC2 on body weight and cholesterol are influenced by unknown variables.
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Affiliation(s)
- Kayla A. Boortz
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Kristen E. Syring
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Lynley D. Pound
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Huan Mo
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - James K. Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Owen P. McGuinness
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Joshua C. Denny
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Richard M. O’Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
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Al-Daghri NM, Pontremoli C, Cagliani R, Forni D, Alokail MS, Al-Attas OS, Sabico S, Riva S, Clerici M, Sironi M. Susceptibility to type 2 diabetes may be modulated by haplotypes in G6PC2, a target of positive selection. BMC Evol Biol 2017; 17:43. [PMID: 28173748 PMCID: PMC5297017 DOI: 10.1186/s12862-017-0897-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 01/26/2017] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The endoplasmic reticulum enzyme glucose-6-phosphatase catalyzes the common terminal reaction in the gluconeogenic/glycogenolytic pathways and plays a central role in glucose homeostasis. In most mammals, different G6PC subunits are encoded by three paralogous genes (G6PC, G6PC2, and G6PC3). Mutations in G6PC and G6PC3 are responsible for human mendelian diseases, whereas variants in G6PC2 are associated with fasting glucose (FG) levels. RESULTS We analyzed the evolutionary history of G6Pase genes. Results indicated that the three paralogs originated during early vertebrate evolution and that negative selection was the major force shaping diversity at these genes in mammals. Nonetheless, site-wise estimation of evolutionary rates at corresponding sites revealed weak correlations, suggesting that mammalian G6Pases have evolved different structural features over time. We also detected pervasive positive selection at mammalian G6PC2. Most selected residues localize in the C-terminal protein region, where several human variants associated with FG levels also map. This region was re-sequenced in ~560 subjects from Saudi Arabia, 185 of whom suffering from type 2 diabetes (T2D). The frequency of rare missense and nonsense variants was not significantly different in T2D and controls. Association analysis with two common missense variants (V219L and S342C) revealed a weak but significant association for both SNPs when analyses were conditioned on rs560887, previously identified in a GWAS for FG. Two haplotypes were significantly associated with T2D with an opposite effect direction. CONCLUSIONS We detected pervasive positive selection at mammalian G6PC2 genes and we suggest that distinct haplotypes at the G6PC2 locus modulate susceptibility to T2D.
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Affiliation(s)
- Nasser M Al-Daghri
- Biomarker research program, Biochemistry Department, College of Science, King Saud Universiy, Riyadh, 11451, Kingdom of Saudi Arabia.,Prince Mutaib Chair for Biomarkers of Osteoporosis Research, King Saud University, Riyadh, 11451, Kingdom of Saudi Arabia
| | | | - Rachele Cagliani
- Scientific Institute IRCCS E.MEDEA, Bosisio Parini, 23842, Italy
| | - Diego Forni
- Scientific Institute IRCCS E.MEDEA, Bosisio Parini, 23842, Italy
| | - Majed S Alokail
- Biomarker research program, Biochemistry Department, College of Science, King Saud Universiy, Riyadh, 11451, Kingdom of Saudi Arabia.,Prince Mutaib Chair for Biomarkers of Osteoporosis Research, King Saud University, Riyadh, 11451, Kingdom of Saudi Arabia
| | - Omar S Al-Attas
- Biomarker research program, Biochemistry Department, College of Science, King Saud Universiy, Riyadh, 11451, Kingdom of Saudi Arabia.,Prince Mutaib Chair for Biomarkers of Osteoporosis Research, King Saud University, Riyadh, 11451, Kingdom of Saudi Arabia
| | - Shaun Sabico
- Biomarker research program, Biochemistry Department, College of Science, King Saud Universiy, Riyadh, 11451, Kingdom of Saudi Arabia.,Prince Mutaib Chair for Biomarkers of Osteoporosis Research, King Saud University, Riyadh, 11451, Kingdom of Saudi Arabia
| | - Stefania Riva
- Scientific Institute IRCCS E.MEDEA, Bosisio Parini, 23842, Italy
| | - Mario Clerici
- Department of Physiopathology and Transplantation, University of Milan, via F.lli Cervi 93, Segrate, 20090, Milan, Italy. .,Don Gnocchi Foundation, ONLUS, Milan, 20148, Italy.
| | - Manuela Sironi
- Scientific Institute IRCCS E.MEDEA, Bosisio Parini, 23842, Italy
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Andersson LE, Nicholas LM, Filipsson K, Sun J, Medina A, Al-Majdoub M, Fex M, Mulder H, Spégel P. Glycogen metabolism in the glucose-sensing and supply-driven β-cell. FEBS Lett 2016; 590:4242-4251. [PMID: 27943300 DOI: 10.1002/1873-3468.12460] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Revised: 07/25/2016] [Accepted: 09/29/2016] [Indexed: 12/24/2022]
Abstract
Glycogen metabolism in β-cells may affect downstream metabolic pathways controlling insulin release. We examined glycogen metabolism in human islets and in the rodent-derived INS-1 832/13 β-cells and found them to express the same isoforms of key enzymes required for glycogen metabolism. Our findings indicate that glycogenesis is insulin-independent but influenced by extracellular glucose concentrations. Levels of glycogen synthase decrease with increasing glucose concentrations, paralleling accumulation of glycogen. We did not find cAMP-elicited glycogenolysis and insulin secretion to be causally related. In conclusion, our results reveal regulated glycogen metabolism in human islets and insulin-secreting cells. Whether glycogen metabolism affects insulin secretion under physiological conditions remains to be determined.
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Affiliation(s)
- Lotta E Andersson
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Lisa M Nicholas
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Karin Filipsson
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Jiangming Sun
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Anya Medina
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Mahmoud Al-Majdoub
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Malin Fex
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Hindrik Mulder
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden
| | - Peter Spégel
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University Diabetes Centre, CRC, Malmö, Sweden.,Department of Chemistry, Centre for Analysis and Synthesis, Lund University, Sweden
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45
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Boortz KA, Syring KE, Lee RA, Dai C, Oeser JK, McGuinness OP, Wang JC, O'Brien RM. G6PC2 Modulates the Effects of Dexamethasone on Fasting Blood Glucose and Glucose Tolerance. Endocrinology 2016; 157:4133-4145. [PMID: 27653037 PMCID: PMC5086534 DOI: 10.1210/en.2016-1678] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
The glucose-6-phosphatase catalytic subunit 2 (G6PC2) gene encodes an islet-specific glucose-6-phosphatase catalytic subunit. G6PC2 forms a substrate cycle with glucokinase that determines the glucose sensitivity of insulin secretion. Consequently, deletion of G6pc2 lowers fasting blood glucose (FBG) without affecting fasting plasma insulin. Although chronic elevation of FBG is detrimental to health, glucocorticoids induce G6PC2 expression, suggesting that G6PC2 evolved to transiently modulate FBG under conditions of glucocorticoid-related stress. We show, using competition and mutagenesis experiments, that the synthetic glucocorticoid dexamethasone (Dex) induces G6PC2 promoter activity through a mechanism involving displacement of the islet-enriched transcription factor MafA by the glucocorticoid receptor. The induction of G6PC2 promoter activity by Dex is modulated by a single nucleotide polymorphism, previously linked to altered FBG in humans, that affects FOXA2 binding. A 5-day repeated injection paradigm was used to examine the chronic effect of Dex on FBG and glucose tolerance in wild-type (WT) and G6pc2 knockout mice. Acute Dex treatment only induces G6pc2 expression in 129SvEv but not C57BL/6J mice, but this chronic treatment induced G6pc2 expression in both. In 6-hour fasted C57BL/6J WT mice, Dex treatment lowered FBG and improved glucose tolerance, with G6pc2 deletion exacerbating the decrease in FBG and enhancing the improvement in glucose tolerance. In contrast, in 24-hour fasted C57BL/6J WT mice, Dex treatment raised FBG but still improved glucose tolerance, with G6pc2 deletion limiting the increase in FBG and enhancing the improvement in glucose tolerance. These observations demonstrate that G6pc2 modulates the complex effects of Dex on both FBG and glucose tolerance.
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Affiliation(s)
- Kayla A Boortz
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Kristen E Syring
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Rebecca A Lee
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Chunhua Dai
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - James K Oeser
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Owen P McGuinness
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Jen-Chywan Wang
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Richard M O'Brien
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
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46
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Langlois C, Abadi A, Peralta-Romero J, Alyass A, Suarez F, Gomez-Zamudio J, Burguete-Garcia AI, Yazdi FT, Cruz M, Meyre D. Evaluating the transferability of 15 European-derived fasting plasma glucose SNPs in Mexican children and adolescents. Sci Rep 2016; 6:36202. [PMID: 27782183 PMCID: PMC5080582 DOI: 10.1038/srep36202] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 10/12/2016] [Indexed: 12/15/2022] Open
Abstract
Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population.
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Affiliation(s)
- Christine Langlois
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Arkan Abadi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Jesus Peralta-Romero
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Akram Alyass
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Fernando Suarez
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Jaime Gomez-Zamudio
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Ana I. Burguete-Garcia
- Centro de investigación sobre enfermedades infecciosas. Instituto Nacional de Salud Pública. Cuernavaca, Morelos, Mexico
| | - Fereshteh T. Yazdi
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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47
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Functional Analysis of Mouse G6pc1 Mutations Using a Novel In Situ Assay for Glucose-6-Phosphatase Activity and the Effect of Mutations in Conserved Human G6PC1/G6PC2 Amino Acids on G6PC2 Protein Expression. PLoS One 2016; 11:e0162439. [PMID: 27611587 PMCID: PMC5017610 DOI: 10.1371/journal.pone.0162439] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2016] [Accepted: 08/23/2016] [Indexed: 11/19/2022] Open
Abstract
Elevated fasting blood glucose (FBG) has been associated with increased risk for development of type 2 diabetes. Single nucleotide polymorphisms (SNPs) in G6PC2 are the most important common determinants of variations in FBG in humans. Studies using G6pc2 knockout mice suggest that G6pc2 regulates the glucose sensitivity of insulin secretion. G6PC2 and the related G6PC1 and G6PC3 genes encode glucose-6-phosphatase catalytic subunits. This study describes a functional analysis of 22 non-synonymous G6PC2 SNPs, that alter amino acids that are conserved in human G6PC1, mouse G6pc1 and mouse G6pc2, with the goal of identifying variants that potentially affect G6PC2 activity/expression. Published data suggest strong conservation of catalytically important amino acids between all four proteins and the related G6PC3 isoform. Because human G6PC2 has very low glucose-6-phosphatase activity we used an indirect approach, examining the effect of these SNPs on mouse G6pc1 activity. Using a novel in situ functional assay for glucose-6-phosphatase activity we demonstrate that the amino acid changes associated with the human G6PC2 rs144254880 (Arg79Gln), rs149663725 (Gly114Arg) and rs2232326 (Ser324Pro) SNPs reduce mouse G6pc1 enzyme activity without affecting protein expression. The Arg79Gln variant alters an amino acid mutation of which, in G6PC1, has previously been shown to cause glycogen storage disease type 1a. We also demonstrate that the rs368382511 (Gly8Glu), rs138726309 (His177Tyr), rs2232323 (Tyr207Ser) rs374055555 (Arg293Trp), rs2232326 (Ser324Pro), rs137857125 (Pro313Leu) and rs2232327 (Pro340Leu) SNPs confer decreased G6PC2 protein expression. In summary, these studies identify multiple G6PC2 variants that have the potential to be associated with altered FBG in humans.
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48
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Boortz KA, Syring KE, Dai C, Pound LD, Oeser JK, Jacobson DA, Wang JC, McGuinness OP, Powers AC, O'Brien RM. G6PC2 Modulates Fasting Blood Glucose In Male Mice in Response to Stress. Endocrinology 2016; 157:3002-8. [PMID: 27300767 PMCID: PMC4967123 DOI: 10.1210/en.2016-1245] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The glucose-6-phosphatase catalytic 2 (G6PC2) gene is expressed specifically in pancreatic islet beta cells. Genome-wide association studies have shown that single nucleotide polymorphisms in the G6PC2 gene are associated with variations in fasting blood glucose (FBG) but not fasting plasma insulin. Molecular analyses examining the functional effects of these single nucleotide polymorphisms demonstrate that elevated G6PC2 expression is associated with elevated FBG. Studies in mice complement these genome-wide association data and show that deletion of the G6pc2 gene lowers FBG without affecting fasting plasma insulin. This suggests that, together with glucokinase, G6PC2 forms a substrate cycle that determines the glucose sensitivity of insulin secretion. Because genome-wide association studies and mouse studies demonstrate that elevated G6PC2 expression raises FBG and because chronically elevated FBG is detrimental to human health, increasing the risk of type 2 diabetes, it is unclear why G6PC2 evolved. We show here that the synthetic glucocorticoid dexamethasone strongly induces human G6PC2 promoter activity and endogenous G6PC2 expression in isolated human islets. Acute treatment with dexamethasone selectively induces endogenous G6pc2 expression in 129SvEv but not C57BL/6J mouse pancreas and isolated islets. The difference is due to a single nucleotide polymorphism in the C57BL/6J G6pc2 promoter that abolishes glucocorticoid receptor binding. In 6-hour fasted, nonstressed 129SvEv mice, deletion of G6pc2 lowers FBG. In response to the stress of repeated physical restraint, which is associated with elevated plasma glucocorticoid levels, G6pc2 gene expression is induced and the difference in FBG between wild-type and knockout mice is enhanced. These data suggest that G6PC2 may have evolved to modulate FBG in response to stress.
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Affiliation(s)
- Kayla A Boortz
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Kristen E Syring
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Chunhua Dai
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Lynley D Pound
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - James K Oeser
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - David A Jacobson
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Jen-Chywan Wang
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Owen P McGuinness
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Alvin C Powers
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
| | - Richard M O'Brien
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., L.D.P., J.K.O., D.A.J., O.P.M., R.M.O.) and Medicine (C.D., A.C.P.), Vanderbilt University School of Medicine, and VA Tennessee Valley Healthcare System (A.C.P.), Nashville, Tennessee 37232-0615; and Department of Nutritional Sciences and Toxicology (J.-C.W.), University of California, Berkeley, Berkeley, California 94720-3104
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49
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Palmer ND, Wagenknecht LE, Langefeld CD, Wang N, Buchanan TA, Xiang AH, Allayee H, Bergman RN, Raffel LJ, Chen YDI, Haritunians T, Fingerlin T, Goodarzi MO, Taylor KD, Rotter JI, Watanabe RM, Bowden DW. Improved Performance of Dynamic Measures of Insulin Response Over Surrogate Indices to Identify Genetic Contributors of Type 2 Diabetes: The GUARDIAN Consortium. Diabetes 2016; 65:2072-80. [PMID: 27207554 PMCID: PMC4915581 DOI: 10.2337/db15-1543] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 04/09/2016] [Indexed: 01/24/2023]
Abstract
Type 2 diabetes (T2D) is a heterogeneous disorder with contributions from peripheral insulin resistance and β-cell dysfunction. For minimization of phenotypic heterogeneity, quantitative intermediate phenotypes characterizing basal glucose homeostasis (insulin resistance and HOMA of insulin resistance [HOMAIR] and of β-cell function [HOMAB]) have shown promise in relatively large samples. We investigated the utility of dynamic measures of glucose homeostasis (insulin sensitivity [SI] and acute insulin response [AIRg]) evaluating T2D-susceptibility variants (n = 57) in Hispanic Americans from the GUARDIAN Consortium (n = 2,560). Basal and dynamic measures were genetically correlated (HOMAB-AIRg: ρG = 0.28-0.73; HOMAIR-SI: ρG = -0.73 to -0.83) with increased heritability for the dynamic measure AIRg Significant association of variants with dynamic measures (P < 8.77 × 10(-4)) was observed. A pattern of superior performance of AIRg was observed for well-established loci including MTNR1B (P = 9.46 × 10(-12)), KCNQ1 (P = 1.35 × 10(-4)), and TCF7L2 (P = 5.10 × 10(-4)) with study-wise statistical significance. Notably, significant association of MTNR1B with AIRg (P < 1.38 × 10(-9)) was observed in a population one-fourteenth the size of the initial discovery cohort. These observations suggest that basal and dynamic measures provide different views and levels of sensitivity to discrete elements of glucose homeostasis. Although more costly to obtain, dynamic measures yield significant results that could be considered physiologically "closer" to causal pathways and provide insight into the discrete mechanisms of action.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Nan Wang
- Department of Preventative Medicine, Keck School of Medicine of USC, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA
| | - Thomas A Buchanan
- Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA Department of Medicine, Keck School of Medicine of USC, Los Angeles, CA
| | - Anny H Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA
| | - Hooman Allayee
- Department of Preventative Medicine, Keck School of Medicine of USC, Los Angeles, CA
| | - Richard N Bergman
- Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA
| | - Leslie J Raffel
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Talin Haritunians
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Tasha Fingerlin
- Department of Epidemiology, University of Colorado Denver, Aurora, CO Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, CO
| | - Mark O Goodarzi
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Kent D Taylor
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Richard M Watanabe
- Department of Preventative Medicine, Keck School of Medicine of USC, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
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50
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Wang T, Huang T, Zheng Y, Rood J, Bray GA, Sacks FM, Qi L. Genetic variation of fasting glucose and changes in glycemia in response to 2-year weight-loss diet intervention: the POUNDS LOST trial. Int J Obes (Lond) 2016; 40:1164-9. [PMID: 27113490 PMCID: PMC4935586 DOI: 10.1038/ijo.2016.41] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2015] [Revised: 01/14/2016] [Accepted: 01/28/2016] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Weight-loss intervention through diet modification has been widely used to improve obesity-related hyperglycemia; however, little is known about whether genetic variation modifies the intervention effect. We examined the interaction between weight-loss diets and genetic variation of fasting glucose on changes in glycemic traits in a dietary intervention trial. RESEARCH DESIGN AND METHODS The Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial is a randomized, controlled 2-year weight-loss trial. We assessed overall genetic variation of fasting glucose by calculating a genetic risk score (GRS) based on 14 fasting glucose-associated single nucleotide polymorphisms, and examined the progression in fasting glucose and insulin levels, and insulin resistance and insulin sensitivity in 733 adults from this trial. RESULTS The GRS was associated with 6-month changes in fasting glucose (P<0.001), fasting insulin (P=0.042), homeostasis model assessment of insulin resistance (HOMA-IR, P=0.009) and insulin sensitivity (HOMA-S, P=0.043). We observed significant interaction between the GRS and dietary fat on 6-month changes in fasting glucose, HOMA-IR and HOMA-S after multivariable adjustment (P-interaction=0.007, 0.045 and 0.028, respectively). After further adjustment for weight loss, the interaction remained significant on change in fasting glucose (P=0.015). In the high-fat diet group, participants in the highest GRS tertile showed increased fasting glucose, whereas participants in the lowest tertile showed decreased fasting glucose (P-trend <0.001); in contrast, the genetic association was not significant in the low-fat diet group (P-trend=0.087). CONCLUSIONS Our data suggest that participants with a higher genetic risk may benefit more by eating a low-fat diet to improve glucose metabolism.
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Affiliation(s)
- Tiange Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Shanghai Clinical Center for Endocrine and Metabolic Diseases, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tao Huang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yan Zheng
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jennifer Rood
- Pennington Biomedical Research Center of the Louisiana State University System, Baton Rouge, LA, USA
| | - George A. Bray
- Pennington Biomedical Research Center of the Louisiana State University System, Baton Rouge, LA, USA
| | - Frank M. Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Lu Qi
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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