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Hua R, Shi M, Chow E, Yang A, Cheung YT. Genetic evidence for the effects of glucokinase activation on frailty-related outcomes: A Mendelian randomisation study. Diabetes Obes Metab 2025; 27:3072-3083. [PMID: 40035195 PMCID: PMC12046474 DOI: 10.1111/dom.16312] [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: 12/02/2024] [Revised: 02/19/2025] [Accepted: 02/23/2025] [Indexed: 03/05/2025]
Abstract
AIMS We aimed to use the Mendelian randomisation (MR) design to investigate the potential causal effects of glucokinase (GK) activation on frailty-related outcomes and to explore the potential mediating effects of metabolic and inflammatory biomarkers. MATERIALS AND METHODS Seventeen independent single-nucleotide polymorphisms (SNPs) located within the GCK gene and significantly correlated with the glycated haemoglobin (HbA1c) level were used as genetic proxies for the effect of GK activation. We employed two-sample MR analysis to assess the relationship between genetically proxied GK activation and multifactorial frailty-related outcomes (frailty index, grip strength, walking pace, appendicular lean mass [ALM] and telomere length) We also explored the potential mediating effects using two-step MR. RESULTS Genetically proxied GK activation was significantly associated with a lower frailty index (beta: -0.161 per 1% decrease in HbA1c level due to GK activation, 95% confidence interval: -0.282 to -0.040, false discovery rate-adjusted p = 0.011). Additionally, GK activation showed significant associations with increased grip strength, higher ALM, faster walking pace and longer telomere length. GK activation also demonstrated a significant indirect effect on total grip strength and telomere length by reducing C-reactive protein levels (proportion of mediation: 6.79% to 8.21%). CONCLUSION Our study provides genetic evidence supporting the causal effects of GK activation on lowering the risk of frailty. These findings suggest that GK activators (GKAs) may aid in the management of frailty and sarcopaenia in people with diabetes; however, future randomized controlled trials are necessary to validate these results and establish their clinical applicability.
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Affiliation(s)
- Rong Hua
- School of Pharmacy, Faculty of MedicineThe Chinese University of Hong KongHong KongChina
| | - Mai Shi
- Department of Medicine and TherapeuticsThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
- Hong Kong Institute of Diabetes and ObesityThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
| | - Elaine Chow
- Department of Medicine and TherapeuticsThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
- Hong Kong Institute of Diabetes and ObesityThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
- Phase 1 Clinical Trial CentreThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
| | - Aimin Yang
- Department of Medicine and TherapeuticsThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
- Hong Kong Institute of Diabetes and ObesityThe Chinese University of Hong Kong, Prince of Wales HospitalHong KongChina
| | - Yin Ting Cheung
- School of Pharmacy, Faculty of MedicineThe Chinese University of Hong KongHong KongChina
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Langer S, Jagdhuhn D, Waterstradt R, Gromoll J, Müller M, Rees MG, Gloyn AL, Baltrusch S. Effects of coding variants in the glucokinase regulatory protein gene on hepatic glucose and triglyceride metabolism suggest a gene regulatory function of glucokinase. Metabolism 2025; 166:156150. [PMID: 39894388 DOI: 10.1016/j.metabol.2025.156150] [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: 11/21/2024] [Revised: 01/17/2025] [Accepted: 01/28/2025] [Indexed: 02/04/2025]
Abstract
BACKGROUND Regulation of glucose metabolism after a meal is the major task of hepatic glucokinase (GCK). Inhibition and nuclear retention of glucokinase during fasting is achieved by glucokinase regulatory protein (GKRP). Compounds disrupting the GCK-GKRP interaction alter glucose but not triglyceride levels, whilst GKRP coding alleles lower glucose but elevate triglycerides. The aim of this study was to identify yet unknown functions of GKRP by examining human variants both rare (p.Q234P, p.H438Y) and common (p.P446L). METHODS Fluorescently labelled human GKRP variant and GCK proteins were expressed in hepatoma cells or primary mouse hepatocytes to investigate the subcellular localization of both proteins, cellular glucose uptake, and triglyceride levels. Mutational effects on GKRP protein structure were analyzed with PyMOL. Nuclear-to-cytoplasmic distribution of the GCK-GKRP complex was modeled in MATLAB. RESULTS Nuclear localization of the GKRP variants was decreased compared to wild-type. Only H438Y-GKRP still evoked WT-like GCK nuclear accumulation. Nuclear localization of Q234P-GKRP was most impaired and depended on the presence of GCK, which, supported by structural analyses, could stabilize its conformation. Nonetheless, inhibition of glucose uptake was least impaired with Q234P-GKRP. Triglyceride contents related to the glucose uptake of hepatoma cells were disproportionately high for cells expressing wild-type or H438Y-GKRP, the two variants that induced higher nuclear sequestration of GCK. CONCLUSIONS Our results, supported by a modeling approach, suggest that GKRP-mediated nuclear localization of GCK has a function in liver metabolism beyond GCK inhibition and sequestration. This needs further elucidation given that GKRP disruptors have been proposed for antihyperglycemic therapy.
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Affiliation(s)
- Sara Langer
- Institute of Medical Biochemistry and Molecular Biology, University Medicine Rostock, Rostock, Germany
| | - David Jagdhuhn
- Institute of Medical Biochemistry and Molecular Biology, University Medicine Rostock, Rostock, Germany
| | - Rica Waterstradt
- Institute of Medical Biochemistry and Molecular Biology, University Medicine Rostock, Rostock, Germany
| | - Jessica Gromoll
- Institute of Medical Biochemistry and Molecular Biology, University Medicine Rostock, Rostock, Germany
| | - Michael Müller
- Institute for Acoustics and Dynamics, Technical University of Braunschweig, Braunschweig, Germany
| | - Matthew G Rees
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK; Department of Pediatrics & Genetics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Simone Baltrusch
- Institute of Medical Biochemistry and Molecular Biology, University Medicine Rostock, Rostock, Germany.
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Liang TT, Cao MJ, Wang Q, Zou JS, Yang XM, Gu LF, Shi FH. Evaluating the Overall Safety of Glucokinase Activators in Patients with Type 2 Diabetes Mellitus. Diabetes Metab Syndr Obes 2024; 17:4539-4552. [PMID: 39629068 PMCID: PMC11612564 DOI: 10.2147/dmso.s474280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 11/13/2024] [Indexed: 12/06/2024] Open
Abstract
Purpose This study aimed to assess the overall clinical adverse events (AEs) associated with glucokinase activators (GKAs) in patients with type 2 diabetes mellitus (T2DM). Methods We searched MEDLINE, EMBASE, Cochrane Library, and ClinicalTrials.gov databases from their dates of inception to June 6, 2023, for randomized controlled trials (RCTs) that reported safety data for GKAs in patients with T2DM. A random-effects model was used to obtain a summary odds ratio (OR) with associated 95% Confidence Intervals (CIs). Pre-specified subgroup analyses were conducted according to individual GKAs (dorzagliatin and all other GKAs), various controls, follow-up duration, mean duration of diabetes, and the location of clinical research. Results 17 RCTs enrolling 4,918 patients (3,196 patients received GKAs and 1,722 patients received placebo or other hypoglycemic drugs) were identified. Among the 17 RCTs, dorzagliatin, AZD1656 and MK-0941 in three trials (1,541 patients), five trials (885 patients), and three trials (798 patients), respectively. GKA treatment was associated with a higher risk of any AEs (OR 1.220, 95% CI 1.072-1.389), mild AEs (OR 1.373, 95% CI 1.085-1.738), hyperlipidemia (OR 1.532, 95% CI 1.071-2.189), and hyperuricemia (OR 2.768, 95% CI 1.562-4.903) compared to patients in the control groups. The higher risks of any AEs were mainly attributed to dorzagliatin and MK-0941 and mild AEs mainly attributed to dorzagliatin. Notably, dorzagliatin had significant effects on the occurrence of hyperlipidemia (OR 1.476, 95% CI 1.025-2.126) and hyperuricemia (OR 2.727, 95% CI 1.523-4.883) in the subgroup analyses. No significant effects were detected from other GKAs when regarding hyperlipidemia and hyperuricemia. Conclusion The results of our meta-analysis indicated that GKAs were associated with a higher risk of any AEs, mild AEs, hyperlipidemia, and hyperuricemia. Further subgroup analyses revealed that the increased occurrence of hyperlipidemia, and hyperuricemia mainly originated from dorzagliatin treatment.
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Affiliation(s)
- Ting-Ting Liang
- Department of Pharmacy, Changshu Affiliated Hospital of Nanjing University of Chinese Medicine, Suzhou, Jiangsu, People’s Republic of China
| | - Min-Jia Cao
- Department of Pharmacy, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
| | - Qian Wang
- Department of Pharmacy, Changshu Affiliated Hospital of Nanjing University of Chinese Medicine, Suzhou, Jiangsu, People’s Republic of China
| | - Jia-Shuang Zou
- Department of Pharmacy, Changshu Affiliated Hospital of Nanjing University of Chinese Medicine, Suzhou, Jiangsu, People’s Republic of China
| | - Xiao-Ming Yang
- Department of Pharmacy, Changshu Affiliated Hospital of Nanjing University of Chinese Medicine, Suzhou, Jiangsu, People’s Republic of China
| | - Li-Fang Gu
- Department of Pharmacy, Changshu Affiliated Hospital of Nanjing University of Chinese Medicine, Suzhou, Jiangsu, People’s Republic of China
| | - Fang-Hong Shi
- Department of Pharmacy, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
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Ford BE, Chachra SS, Alshawi A, Oakley F, Fairclough RJ, Smith DM, Tiniakos D, Agius L. Compromised chronic efficacy of a glucokinase activator AZD1656 in mouse models for common human GCKR variants. Biochem Pharmacol 2024; 229:116499. [PMID: 39173844 DOI: 10.1016/j.bcp.2024.116499] [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: 05/15/2024] [Revised: 07/23/2024] [Accepted: 08/19/2024] [Indexed: 08/24/2024]
Abstract
Glucokinase activators (GKAs) have been developed as blood glucose lowering drugs for type 2 diabetes. Despite good short-term efficacy, several GKAs showed a decline in efficacy chronically during clinical trials. The underlying mechanisms remain incompletely understood. We tested the hypothesis that deficiency in the liver glucokinase regulatory protein (GKRP) as occurs with common human GCKR variants affects chronic GKA efficacy. We used a Gckr-P446L mouse model for the GCKR exonic rs1260326 (P446L) variant and the Gckr-del/wt mouse to model transcriptional deficiency to test for chronic efficacy of the GKA, AZD1656 in GKRP-deficient states. In the Gckr-P446L mouse, the blood glucose lowering efficacy of AZD1656 (3 mg/kg body wt) after 2 weeks was independent of genotype. However after 19 weeks, efficacy was maintained in wild-type but declined in the LL genotype, in conjunction with raised hepatic glucokinase activity and without raised liver lipids. Sustained blood glucose lowering efficacy in wild-type mice was associated with qualitatively similar but more modest changes in the liver transcriptome compared with the P446L genotype, consistent with GKA therapy representing a more modest glucokinase excess than the P446L genotype. Chronic treatment with AZD1656 in the Gckr-del/wt mouse was associated with raised liver triglyceride and hepatocyte microvesicular steatosis. The results show that in mouse models of liver GKRP deficiency in conjunction with functional liver glucokinase excess as occurs in association with common human GCKR variants, GKRP-deficiency predisposes to declining efficacy of the GKA in lowering blood glucose and to GKA induced elevation in liver lipids.
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Affiliation(s)
- Brian E Ford
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Shruti S Chachra
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Ahmed Alshawi
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; Medical Laboratory Technique Department, Kufa Institute, Al-Furat Al-Awsat Technical University, Kufa, Iraq
| | - Fiona Oakley
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
| | - Rebecca J Fairclough
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David M Smith
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dina Tiniakos
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK; Dept of Pathology, Aretaieion Hospital Medical School, National and Kapodistrian University of Athens, Greece
| | - Loranne Agius
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, UK.
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Moqaddam MA, Nemati M, Dara MM, Hoteit M, Sadek Z, Ramezani A, Rand MK, Abbassi-Daloii A, Pashaei Z, Almaqhawi A, Razi O, Escobar KA, Supriya R, Saeidi A, Zouhal H. Exploring the Impact of Astaxanthin Supplementation in Conjunction with a 12-Week CrossFit Training Regimen on Selected Adipo-Myokines Levels in Obese Males. Nutrients 2024; 16:2857. [PMID: 39275173 PMCID: PMC11397083 DOI: 10.3390/nu16172857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 07/22/2024] [Accepted: 08/14/2024] [Indexed: 09/16/2024] Open
Abstract
OBJECTIVE Obesity is associated with an exacerbated metabolic condition that is mediated through impairing balance in the secretion of some adipo-myokines. Therefore, the objective of the present study was to explore the impact of astaxanthin supplementation in conjunction with a 12-week CrossFit training regimen on some selected adipo-myokines, insulin insensitivity, and serum lipid levels in obese males. MATERIAL AND METHODS This study is a randomized control trial design; 60 obese males were randomly divided into four groups of 15, including the control group (CG), supplement group (SG), training group (TG), and combined training and supplement group (TSG). The participants were subjected to 12 weeks of astaxanthin (AST) supplementation [20 mg/d capsule, once/d] or CrossFit training or a combination of both interventions. The training regimen comprised 36 sessions of CrossFit, each lasting 60 min, conducted three times per week. The metabolic indices, body composition, anthropometrical, cardio-respiratory, and also some plasma adipo-myokine factors, including decorin (DCN), activin A, myostatin (MST), transforming growth factor (TGF)-β1, and follistatin (FST), were examined 12 and 72 h before the initiation of the main interventional protocols, and then 72 h after the final session of the training protocol. RESULTS There was no significant difference in the baseline data between the groups (p > 0.05). There were significant interactions between group x time for DCN (η2 = 0.82), activin A (η2 = 0.50), FST (η2 = 0.92), MST (η2 = 0.75), and TGFB-1 (η2 = 0.67) (p < 0.001 for all the variables). Significantly changes showed for DCN in TSG compared to TG and SG and also TG compared to SG (p = 0.0001); for activin A in SG compared to TG (p = 0.01) and TSG (p = 0.002); for FST in SG compared to TG and TSG (p = 0.0001), also in TSG compared to TG (p = 0.0001); for MST in SG, TG, and TSG compared to CG (p = 0.0001) and also in TSG compared to SG (p = 0.0001) and TG (p = 0.001); for TGFB-1 in SG, TG, and TSG compared to CG (p = 0.0001) and also TSG compared to SG (p = 0.0001) and TG (p = 0.001). CONCLUSIONS The 12-week CrossFit training concurrent with AST supplementation reduced anthropometric and metabolic factors and also serum lipid levels while producing positive changes in body composition and cardiovascular factors. Increased FST and DCN and reduced activin A, MST, and TGF-β1 were other affirmative responses to both interventions.
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Affiliation(s)
- Mohammad Ahmadi Moqaddam
- Department of Physical Education and Sport Science, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran; (M.A.M.); (M.M.D.)
| | - Morteza Nemati
- Department of Biomechanics and Sports Injuries, Faculty of Physical Education and Sports Sciences, Kharazmi University, Tehran 1571914911, Iran;
| | - Marjan Mansouri Dara
- Department of Physical Education and Sport Science, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran; (M.A.M.); (M.M.D.)
| | - Maha Hoteit
- Food Science Unit, National Council for Scientific Research of Lebanon (CNRS-L), Beirut 11-8281, Lebanon;
- Section 1, Faculty of Public Health, Lebanese University, Beirut 6573, Lebanon;
| | - Zahra Sadek
- Section 1, Faculty of Public Health, Lebanese University, Beirut 6573, Lebanon;
- Laboratory of Motor System, Handicap and Rehabilitation (MOHAR), Faculty of Public Health, Lebanese University, Beirut 6573, Lebanon
| | - Akbar Ramezani
- Ayatollah Amoli Branch, Department of Exercise Physiology, Islamic Azad University, Amol 6134937333, Iran; (A.R.); (M.K.R.); (A.A.-D.)
| | - Mahboubeh Khak Rand
- Ayatollah Amoli Branch, Department of Exercise Physiology, Islamic Azad University, Amol 6134937333, Iran; (A.R.); (M.K.R.); (A.A.-D.)
| | - Asieh Abbassi-Daloii
- Ayatollah Amoli Branch, Department of Exercise Physiology, Islamic Azad University, Amol 6134937333, Iran; (A.R.); (M.K.R.); (A.A.-D.)
| | - Zhaleh Pashaei
- Department of Exercise Physiology, Faculty of Physical Education and Sport Sciences, University of Tabriz, Tabriz 5166616471, Iran;
| | - Abdullah Almaqhawi
- Department of Family Medicine and Community, College of Medicine, King Faisal University, Al Ahsa 31982, Saudi Arabia;
| | - Omid Razi
- Department of Exercise Physiology, Faculty of Physical Education and Sports Science, Razi University, Kermanshah 6714414971, Iran;
| | - Kurt A. Escobar
- Department of Kinesiology, California State University, Long Beach, CA 90840, USA;
| | - Rashmi Supriya
- Centre for Health and Exercise Science Research, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
- Academy of Wellness and Human Development, Faculty of Arts and Social Sciences, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
| | - Ayoub Saeidi
- Department of Physical Education and Sport Sciences, Faculty of Humanities and Social Sciences, University of Kurdistan, Sanandaj 1517566177, Iran
| | - Hassane Zouhal
- M2S (Laboratoire Mouvement, Sport, Santé)—EA 1274, Université Rennes, 35044 Rennes, France;
- Institut International des Sciences du Sport (2I2S), 35850 Irodouer, France
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Chang R, Xiang S, Jin Y, Xu X, Qian S, Chen L, Hu C, Shi Y, Ding X. Hormone and reproductive factors and risk of systemic lupus erythematosus: a Mendelian randomized study. Immunol Res 2024; 72:665-674. [PMID: 38581614 DOI: 10.1007/s12026-024-09470-z] [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: 12/18/2023] [Accepted: 02/22/2024] [Indexed: 04/08/2024]
Abstract
Systemic lupus erythematosus (SLE) is an autoimmune and inflammatory disease with a risk associated with hormonal and reproductive factors. However, the potential causal effects between these factors and SLE remain unclear. A two-sample Mendelian randomization study was conducted using the published summary data from the genome-wide association study database. Five independent genetic variants associated with hormonal and reproductive factors were selected as instrumental variables: age at menarche, age at natural menopause, estradiol, testosterone, and follistatin. To estimate the causal relationship between these exposure factors and disease outcome, we employed the inverse-variance weighted, weighted median, and MR-Egger methods. In addition, we carried out multiple sensitivity analyses to validate model assumptions. Inverse variance weighted showed that there was a causal association between circulating follistatin and SLE risk (OR = 1.38, 95% CI 1.03 to 1.86, P = 0.033). However, no evidence was found that correlation between AAM (OR = 1.04, 95% CI 0.77 to 1.40, P = 0.798), ANM (OR = 0.99, 95% CI 0.92 to 1.06, P = 0.721), E2 (OR = 1.40, 95% CI 0.14 to 13.56, P = 0.772), T (OR = 1.25, 95% CI 0.70 to 2.28, P = 0.459), and SLE risk. Our study revealed that elevated circulating follistatin associates with an increased risk of SLE. This finding suggests that the regulatory signals mediated by circulating follistatin may provide a potential mechanism relevant to the treatment of SLE.
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Affiliation(s)
- Runyu Chang
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Shate Xiang
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yibo Jin
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Xiaofen Xu
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Suhai Qian
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Lingfeng Chen
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Chao Hu
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yufeng Shi
- The First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
| | - Xinghong Ding
- Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
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7
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Wang K, Shi M, Luk AOY, Kong APS, Ma RCW, Li C, Chen L, Chow E, Chan JCN. Impaired GK-GKRP interaction rather than direct GK activation worsens lipid profiles and contributes to long-term complications: a Mendelian randomization study. Cardiovasc Diabetol 2024; 23:228. [PMID: 38951793 PMCID: PMC11218184 DOI: 10.1186/s12933-024-02321-z] [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: 05/07/2024] [Accepted: 06/16/2024] [Indexed: 07/03/2024] Open
Abstract
BACKGROUND Glucokinase (GK) plays a key role in glucose metabolism. In the liver, GK is regulated by GK regulatory protein (GKRP) with nuclear sequestration at low plasma glucose level. Some GK activators (GKAs) disrupt GK-GKRP interaction which increases hepatic cytoplasmic GK level. Excess hepatic GK activity may exceed the capacity of glycogen synthesis with excess triglyceride formation. It remains uncertain whether hypertriglyceridemia associated with some GKAs in previous clinical trials was due to direct GK activation or impaired GK-GKRP interaction. METHODS Using publicly available genome-wide association study summary statistics, we selected independent genetic variants of GCKR and GCK associated with fasting plasma glucose (FPG) as instrumental variables, to mimic the effects of impaired GK-GKRP interaction and direct GK activation, respectively. We applied two-sample Mendelian Randomization (MR) framework to assess their causal associations with lipid-related traits, risks of metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular diseases. We verified these findings in one-sample MR analysis using individual-level statistics from the Hong Kong Diabetes Register (HKDR). RESULTS Genetically-proxied impaired GK-GKRP interaction increased plasma triglycerides, low-density lipoprotein cholesterol and apolipoprotein B levels with increased odds ratio (OR) of 14.6 (95% CI 4.57-46.4) per 1 mmol/L lower FPG for MASLD and OR of 2.92 (95% CI 1.78-4.81) for coronary artery disease (CAD). Genetically-proxied GK activation was associated with decreased risk of CAD (OR 0.69, 95% CI 0.54-0.88) and not with dyslipidemia. One-sample MR validation in HKDR showed consistent results. CONCLUSIONS Impaired GK-GKRP interaction, rather than direct GK activation, may worsen lipid profiles and increase risks of MASLD and CAD. Development of future GKAs should avoid interfering with GK-GKRP interaction.
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Affiliation(s)
- Ke Wang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Hua Medicine (Shanghai) Co., Ltd., Shanghai, China
| | - Mai Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Phase 1 Clinical Trial Centre, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Changhong Li
- Hua Medicine (Shanghai) Co., Ltd., Shanghai, China
| | - Li Chen
- Hua Medicine (Shanghai) Co., Ltd., Shanghai, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
- Phase 1 Clinical Trial Centre, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
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8
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Lee K, Kuang A, Bain JR, Hayes MG, Muehlbauer MJ, Ilkayeva OR, Newgard CB, Powe CE, Hivert MF, Scholtens DM, Lowe WL. Metabolomic and genetic architecture of gestational diabetes subtypes. Diabetologia 2024; 67:895-907. [PMID: 38367033 DOI: 10.1007/s00125-024-06110-x] [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: 08/14/2023] [Accepted: 01/12/2024] [Indexed: 02/19/2024]
Abstract
AIMS/HYPOTHESIS Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes. METHODS This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM). RESULTS Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM. CONCLUSIONS/INTERPRETATION This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.
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Affiliation(s)
- Kristen Lee
- Department of Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Alan Kuang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - James R Bain
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - M Geoffrey Hayes
- Department of Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Olga R Ilkayeva
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - Christopher B Newgard
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC, USA
| | - Camille E Powe
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Marie-France Hivert
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Denise M Scholtens
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
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9
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Oliveri A, Rebernick RJ, Kuppa A, Pant A, Chen Y, Du X, Cushing KC, Bell HN, Raut C, Prabhu P, Chen VL, Halligan BD, Speliotes EK. Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank. Nat Genet 2024; 56:212-221. [PMID: 38200128 PMCID: PMC10923176 DOI: 10.1038/s41588-023-01625-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 11/28/2023] [Indexed: 01/12/2024]
Abstract
Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.
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Affiliation(s)
- Antonino Oliveri
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ryan J Rebernick
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Annapurna Kuppa
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Asmita Pant
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Yanhua Chen
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Xiaomeng Du
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Kelly C Cushing
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Hannah N Bell
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Chinmay Raut
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Ponnandy Prabhu
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Vincent L Chen
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Brian D Halligan
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA
| | - Elizabeth K Speliotes
- Division of Gastroenterology and Hepatology, University of Michigan Health System, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
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10
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Yan P, Zhang L, Yang C, Zhang W, Wang Y, Zhang M, Cui H, Tang M, Chen L, Wu X, Zhao X, Zou Y, Xiao J, Liu Y, Xiao C, Yang Y, Zhang L, Yao Y, Li J, Liu Z, Yang C, Jiang X, Zhang B. Observational and genetic analyses clarify the relationship between type 2 diabetes mellitus and gallstone disease. Front Endocrinol (Lausanne) 2024; 14:1337071. [PMID: 38356679 PMCID: PMC10864641 DOI: 10.3389/fendo.2023.1337071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 12/26/2023] [Indexed: 02/16/2024] Open
Abstract
Background The relationship between type 2 diabetes mellitus (T2DM) and gallstone disease (GSD) have been incompletely understood. We aimed to investigate their phenotypic and genetic associations and evaluate the biological mechanisms underlying these associations. Methods We first evaluated the phenotypic association between T2DM and GSD using data from the UK Biobank (n>450,000) using a prospective observational design. We then conducted genetic analyses using summary statistics from a meta-analysis of genome-wide association studies of T2DM, with and without adjusting for body mass index (BMI) (Ncase=74,124, Ncontrol=824,006; T2DMadjBMI: Ncase=50,409, Ncontrol=523,897) and GSD (Ncase=43,639, Ncontrol=506,798). Results A unidirectional phenotypic association was observed, where individuals with T2DM exhibited a higher GSD risk (hazard ratio (HR)=1.39, P<0.001), but not in the reverse direction (GSD→T2DM: HR=1.00, P=0.912). The positive T2DM-GSD genetic correlation (rg=0.35, P=7.71×10-23) remained even after adjusting for BMI (T2DMadjBMI: rg=0.22, P=4.48×10-10). Mendelian randomization analyses provided evidence of a unidirectional causal relationship (T2DM→GSD: odds ratio (OR)=1.08, P=4.6×10-8; GSD→T2DM: OR=1.02, P=0.48), even after adjusting for important metabolic confounders (OR=1.02, P=0.02). This association was further corroborated through a comprehensive functional analysis reflected by 23 pleiotropic single nucleotide polymorphisms, as well as multiple neural and motor-enriched tissues. Conclusion Through comprehensive observational and genetic analyses, our study clarified the causal relationship between T2DM and GSD, but not in the reverse direction. These findings might provide new insights into prevention and treatment strategies for T2DM and GSD.
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Affiliation(s)
- Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- School of Public Health, Southwest Medical University, Luzhou, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Min Zhang
- Clinical Research Center, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinyu Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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11
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Shen M, Jiang L, Liu H, Dai H, Jiang H, Qian Y, Wang Z, Zheng S, Chen H, Yang T, Fu Q, Xu K. Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-β and ISI Matusda in the middle-aged T2D individuals. J Hum Genet 2023; 68:835-842. [PMID: 37648893 DOI: 10.1038/s10038-023-01191-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/13/2023] [Accepted: 08/22/2023] [Indexed: 09/01/2023]
Abstract
This study aims to investigate the correlations between islet function/ insulin resistance and serum lipid levels, as well as to assess whether the strength of such correlations is affected by the GCKR rs1260326 variant in healthy and T2D individuals. We performed an oral glucose tolerance test (OGTT) on 4889 middle-aged adults, including 3135 healthy and 1754 T2D individuals from the REACTION population study in the Nanjing region. We also measured their serum lipid levels and genotyped for rs1260326. We found that serum high-density lipoprotein (HDL) cholesterol and triglyceride (TG) levels were independently correlated with indexes of islet function (HOMA-β and IGI [insulinogenic index]) and insulin resistance (HOMO-IR and ISIMatsuda) in both healthy and T2D individuals. The correlations were significantly decreased in T2D individuals, with significant heterogeneities compared to healthy controls (I2 > 75%, Phet < 0.05). Although no correlation was observed between serum total cholesterol (TC) level and islet function/ insulin resistance in healthy controls, significant correlations were found in T2D individuals, with significant heterogeneity to healthy controls in the correlation with ISIMatsuda(I2 = 85.3%, Phet = 0.009). Furthermore, we found significant interactions of the GCKR rs1260326 variant for the correlations between serum HDL cholesterol and HOMA-β/ISIMatsuda in T2D subjects (P = 0.015 and 0.038, respectively). These findings illustrate that distinct correlations between serum lipid levels and islet function/ insulin resistance occurred in T2D subjects compared to healthy individuals. Common gene variants, such as rs1260326, might interact substantially when studied in specific populations, especially T2D disease status.
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Affiliation(s)
- Min Shen
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Liying Jiang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Hechun Liu
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Hao Dai
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Hemin Jiang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Yu Qian
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Zhixiao Wang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Shuai Zheng
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Heng Chen
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Tao Yang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Qi Fu
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
| | - Kuanfeng Xu
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
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12
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Zhu M, Lv Y, Peng Y, Wu Y, Feng Y, Jia T, Xu S, Li S, Wang W, Tian J, Sun L. GCKR and ADIPOQ gene polymorphisms in women with gestational diabetes mellitus. Acta Diabetol 2023; 60:1709-1718. [PMID: 37524927 PMCID: PMC10587232 DOI: 10.1007/s00592-023-02165-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 07/18/2023] [Indexed: 08/02/2023]
Abstract
AIMS To investigate the associations of GCKR and ADIPOQ variants with the risk of gestational diabetes mellitus (GDM) in Chinese women. METHODS GCKR rs1260326, ADIPOQ rs266729, and rs1501299 were selected and genotyped in 519 GDM patients and 498 controls. Candidate SNPs were genotyped using multiplex polymerase chain reaction (PCR) combined with next-generation sequencing methods, and the association of these SNPs with GDM was analyzed. RESULTS We found that GCKR rs1260326 was significantly associated with an increased risk of GDM in the allele model, the codominant model (CC vs. TT), the dominant model, the recessive model, and the genotypic model distributions (p = 0.0029, p = 0.0022, p = 0.0402, p = 0.0038, and p = 0.0028, respectively). The rs1260326 polymorphism was shown to be associated with 1 h-OGTT level and gravidity in GDM patients (CC vs. TT: p = 0.0475 and p = 0.0220, respectively). Diastolic blood pressure (DBP) was significantly higher in the GDM patients with the rs266729 GG genotype compared to those with the CC or CG genotype (p = 0.0444 and p = 0.0339, respectively). The DBP of the GDM patients with the rs1501299 GT genotype was lower than that of those with the GG genotype (p = 0.0197). There was a weak linkage disequilibrium value between the GCKR and ADIPOQ SNPs. CONCLUSIONS The genes GCKR and ADIPOQ may be involved in the pathophysiology of GDM.
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Affiliation(s)
- Manning Zhu
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yaer Lv
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yanqing Peng
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yingnan Wu
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yanan Feng
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
| | - Tianshuang Jia
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Songcheng Xu
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Songxue Li
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Wei Wang
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jiawei Tian
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China.
| | - Litao Sun
- Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital(Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
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13
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Xu H, Sun Y, Francis M, Cheng CF, Modulla NT, Brenna JT, Chiang CWK, Ye K. Shared genetic basis informs the roles of polyunsaturated fatty acids in brain disorders. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.03.23296500. [PMID: 37873425 PMCID: PMC10593041 DOI: 10.1101/2023.10.03.23296500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The neural tissue is rich in polyunsaturated fatty acids (PUFAs), components that are indispensable for the proper functioning of neurons, such as neurotransmission. PUFA nutritional deficiency and imbalance have been linked to a variety of chronic brain disorders, including major depressive disorder (MDD), anxiety, and anorexia. However, the effects of PUFAs on brain disorders remain inconclusive, and the extent of their shared genetic determinants is largely unknown. Here, we used genome-wide association summary statistics to systematically examine the shared genetic basis between six phenotypes of circulating PUFAs (N = 114,999) and 20 brain disorders (N = 9,725-762,917), infer their potential causal relationships, identify colocalized regions, and pinpoint shared genetic variants. Genetic correlation and polygenic overlap analyses revealed a widespread shared genetic basis for 77 trait pairs between six PUFA phenotypes and 16 brain disorders. Two-sample Mendelian randomization analysis indicated potential causal relationships for 16 pairs of PUFAs and brain disorders, including alcohol consumption, bipolar disorder (BIP), and MDD. Colocalization analysis identified 40 shared loci (13 unique) among six PUFAs and ten brain disorders. Twenty-two unique variants were statistically inferred as candidate shared causal variants, including rs1260326 (GCKR), rs174564 (FADS2) and rs4818766 (ADARB1). These findings reveal a widespread shared genetic basis between PUFAs and brain disorders, pinpoint specific shared variants, and provide support for the potential effects of PUFAs on certain brain disorders, especially MDD, BIP, and alcohol consumption.
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Affiliation(s)
- Huifang Xu
- Department of Genetics, University of Georgia, Athens, Georgia
| | - Yitang Sun
- Department of Genetics, University of Georgia, Athens, Georgia
| | - Michael Francis
- Institute of Bioinformatics, University of Georgia, Athens, Georgia
| | - Claire F. Cheng
- Department of Genetics, University of Georgia, Athens, Georgia
| | | | - J. Thomas Brenna
- Dell Pediatric Research Institute and Department of Pediatrics, The University of Texas at Austin, Texas
- Dell Pediatric Research Institute and Department of Chemistry, The University of Texas at Austin, Texas
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Texas
| | - Charleston W. K. Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California
| | - Kaixiong Ye
- Department of Genetics, University of Georgia, Athens, Georgia
- Institute of Bioinformatics, University of Georgia, Athens, Georgia
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14
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Hu C, Zhou Y, Wu X, Jia X, Zhu Y, Zheng R, Wang S, Lin L, Qi H, Lin H, Li M, Wang T, Zhao Z, Xu M, Xu Y, Chen Y, Ning G, Borges MC, Wang W, Zheng J, Bi Y, Lu J. Evaluating the distinct pleiotropic effects of omega-3 fatty acids on type 2 diabetes mellitus: a mendelian randomization study. J Transl Med 2023; 21:370. [PMID: 37286992 DOI: 10.1186/s12967-023-04202-7] [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: 03/16/2023] [Accepted: 05/14/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND Observational studies and conventional Mendelian randomization (MR) studies showed inconclusive evidence to support the association between omega-3 fatty acids and type 2 diabetes. We aim to evaluate the causal effect of omega-3 fatty acids on type 2 diabetes mellitus (T2DM), and the distinct intermediate phenotypes linking the two. METHODS Two-sample MR was performed using genetic instruments derived from a recent genome-wide association study (GWAS) of omega-3 fatty acids (N = 114,999) from UK Biobank and outcome data obtained from a large-scale T2DM GWAS (62,892 cases and 596,424 controls) in European ancestry. MR-Clust was applied to determine clustered genetic instruments of omega-3 fatty acids that influences T2DM. Two-step MR analysis was used to identify potential intermediate phenotypes (e.g. glycemic traits) that linking omega-3 fatty acids with T2DM. RESULTS Univariate MR showed heterogenous effect of omega-3 fatty acids on T2DM. At least two pleiotropic effects between omega-3 fatty acids and T2DM were identified using MR-Clust. For cluster 1 with seven instruments, increasing omega-3 fatty acids reduced T2DM risk (OR: 0.52, 95%CI 0.45-0.59), and decreased HOMA-IR (β = - 0.13, SE = 0.05, P = 0.02). On the contrary, MR analysis using 10 instruments in cluster 2 showed that increasing omega-3 fatty acids increased T2DM risk (OR:1.10; 95%CI 1.06-1.15), and decreased HOMA-B (β = - 0.04, SE = 0.01, P = 4.52 × 10-5). Two-step MR indicated that increasing omega-3 fatty acid levels decreased T2DM risk via decreasing HOMA-IR in cluster 1, while increased T2DM risk via decreasing HOMA-B in cluster 2. CONCLUSIONS This study provides evidence to support two distinct pleiotropic effects of omega-3 fatty acids on T2DM risk influenced by different gene clusters, which could be partially explained by distinct effects of omega-3 fatty acids on insulin resistance and beta cell dysfunction. The pleiotropic feature of omega-3 fatty acids variants and its complex relationships with T2DM need to be carefully considered in future genetic and clinical studies.
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Affiliation(s)
- Chunyan Hu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yulin Zhou
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xueyan Wu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaojing Jia
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuanyue Zhu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruizhi Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lin Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongyan Qi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Maria-Carolina Borges
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Rui Jin 2nd Road, Shanghai, 200025, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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15
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Ford BE, Chachra SS, Rodgers K, Moonira T, Al-Oanzi ZH, Anstee QM, Reeves HL, Schattenberg JM, Fairclough RJ, Smith DM, Tiniakos D, Agius L. The GCKR-P446L gene variant predisposes to raised blood cholesterol and lower blood glucose in the P446L mouse-a model for GCKR rs1260326. Mol Metab 2023; 72:101722. [PMID: 37031802 PMCID: PMC10182400 DOI: 10.1016/j.molmet.2023.101722] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/28/2023] [Accepted: 04/04/2023] [Indexed: 04/11/2023] Open
Abstract
OBJECTIVES The Glucokinase Regulatory Protein GKRP, encoded by GCKR, enables acute regulation of liver glucokinase to support metabolic demand. The common human GCKR rs1260326:Pro446 > Leu variant within a large linkage disequilibrium region associates with pleiotropic traits including lower Type 2 diabetes risk and raised blood triglycerides and cholesterol. Whether the GCKR-P446 > L substitution is causal to the raised lipids is unknown. We determined whether mouse GKRP phenocopies the human GKRP:P446 > L substitution and studied a GKRP:P446L knockin mouse to identify physiological consequences to P446 > L. METHODS GKRP-deficient hepatocytes were transfected with adenoviral vectors for human or mouse GKRP:446 P or 446 L for cellular comprehensive analysis including transcriptomics consequent to P446 > L. Physiological traits in the diet-challenged P446L mouse were compared with pleiotropic associations at the human rs1260326 locus. Transcriptomics was compared in P446L mouse liver with hepatocytes overexpressing glucokinase or GKRP:446 P/L. RESULTS 1. P446 > L substitution in mouse or human GKRP similarly compromises protein expressivity of GKRP:446 L, nuclear sequestration of glucokinase and counter-regulation of gene expression. 2. The P446L knockin mouse has lower liver glucokinase and GKRP protein similar to human liver homozygous for rs1260326-446 L. 3. The diet-challenged P446L mouse has lower blood glucose, raised blood cholesterol and altered hepatic cholesterol homeostasis consistent with relative glucokinase-to-GKRP excess, but not raised blood triglycerides. CONCLUSIONS Mouse GKRP phenocopies the human GKRP:P446 > L substitution despite the higher affinity for glucokinase of human GKRP. The diet-challenged P446L mouse replicates several traits found in association with the rs1260326 locus on chromosome 2 including raised blood cholesterol, lower blood glucose and lower liver glucokinase and GKRP protein but not raised blood triglycerides.
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Affiliation(s)
- Brian E Ford
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Shruti S Chachra
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Katrina Rodgers
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Tabassum Moonira
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK
| | - Ziad H Al-Oanzi
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK; Jouf University, Clinical Laboratory Science, Sakaka, Saudi Arabia
| | - Quentin M Anstee
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Center, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Helen L Reeves
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Center, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Jörn M Schattenberg
- Metabolic Liver Research Programm, Department of Medicine, University Hospital Mainz, Mainz, Germany
| | - Rebecca J Fairclough
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David M Smith
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dina Tiniakos
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK; Newcastle NIHR Biomedical Research Center, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK; Dept of Pathology, Aretaieion Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Loranne Agius
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK.
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16
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Yang W, Wu H, Cai X, Lin C, Jiao R, Ji L. Evaluation of efficacy and safety of glucokinase activators-a systematic review and meta-analysis. Front Endocrinol (Lausanne) 2023; 14:1175198. [PMID: 37223016 PMCID: PMC10200948 DOI: 10.3389/fendo.2023.1175198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 04/17/2023] [Indexed: 05/25/2023] Open
Abstract
Aims Glucokinase activators (GKAs) promote the activity of glucokinase (GK) and is under development for the treatment of diabetes. The efficacy and safety of GKAs require evaluation. Methods This meta-analysis included randomized controlled trials (RCTs) with a duration of at least 12 weeks conducted in patients with diabetes. The primary objective of this meta-analysis was the difference of hemoglobin A1c (HbA1c) change from baseline to study end between GKA groups and placebo groups. Risk of hypoglycemia and laboratory indicators were also evaluated. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were calculated for the continuous outcomes, and odds ratios (ORs) and 95% CI were calculated for the risk of hypoglycemia. Results Data from 13 RCTs with 2,748 participants treated with GKAs and 2,681 control participants were analyzed. In type 2 diabetes, the level of HbA1c decreased greater in patients with GKA treatment compared with placebo (WMD = -0.339%, 95% CI -0.524 to -0.154%, P < 0.001). The OR comparing GKA versus placebo was 1.448 for risk of hypoglycemia (95% CI 0.808 to 2.596, P = 0.214). The WMD comparing GKA versus placebo was 0.322 mmol/L for triglyceride (TG) levels (95% CI 0.136 to 0.508 mmol/L, P = 0.001). When stratified by drug type, selectivity, and study duration, a significant difference was found between groups. In type 1 diabetes, the result of HbA1c change and lipid indicators showed no significant difference between the TPP399 group and the placebo group. Conclusions In patients with type 2 diabetes, GKA treatment was associated with a better glycemic control but a significant elevation in TG concentration in general. The efficacy and safety varied with drug type and selectivity. Systematic review registration International Prospective Register of Systematic Reviews, identifier CRD42022378342.
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Affiliation(s)
| | | | | | | | | | - Linong Ji
- *Correspondence: Xiaoling Cai, ; Linong Ji,
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17
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Dutta D, Khandelwal D, Kumar M, Sharma M. Efficacy and safety of novel dual glucokinase activator dorzagliatin in type-2 diabetes A meta-analysis. Diabetes Metab Syndr 2023; 17:102695. [PMID: 36566614 DOI: 10.1016/j.dsx.2022.102695] [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: 11/14/2022] [Revised: 12/03/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND & AIMS Glucokinase has a critical role in regulating glucose homeostasis in humans, and has been a target for diabetes drug development since 1990s. Dorzagliatin is a novel allosteric dual glucokinase activator targeting both pancreatic and hepatic glucokinase. No meta-analysis has analysed the efficacy and safety of dorzagliatin in type-2 diabetes (T2DM). We undertook this meta-analysis to address this knowledge-gap. METHODS Electronic databases were searched for RCTs involving T2DM patients receiving dorzagliatin in intervention arm, and placebo/active comparator in control arm. Primary outcome was to evaluate changes in HbA1c. Secondary outcomes were to evaluate alterations in blood glucose parameters, lipids, insulin-resistance and adverse events. RESULTS From initially screened 17 articles, data from 3 RCTs (1333 patients) was analysed. Over 12-24 weeks use, dorzagliatin had significantly higher lowering of HbA1c [MD -0.66% (95%CI: -0.74 to -0.59); P < 0.01; I2 = 99%], fasting glucose [MD -32.03 mg/dl (95%CI: 45.12 to -18.94); P < 0.01; I2 = 100%], 2-h post-prandial glucose [MD -43.49 mg/dl (95%CI: -46.26 to -40.72); P < 0.01; I2 = 90%] along with greater number of patients achieving HbA1c<7% [OR 6.01 (95% CI: 2.50-14.46); P < 0.01; I2 = 83%], as compared to placebo. Dorzagliatin was associated with significant elevation of triglycerides [MD 0.43 mmol/L (95%CI:0.30-0.56); P < 0.01; I2 = 0%], greater occurrence of hyperlipidaemia [RR 1.52 (95% CI:1.05-2.18); P = 0.03; I2 = 0%], and increase in body-weight [MD 0.40 kg (95%CI:0.06-0.75); P = 0.03; I2 = 0%], compared to placebo. The occurrence of total-adverse-events [RR 1.43 (95%CI:1.11-1.83); P < 0.01; I2 = 0%] but not severe adverse-events [RR 0.92 (95%CI:0.54-1.57); P = 0.76; I2 = 0%] was significantly higher with dorzagliatin. CONCLUSION Dorzagliatin has good glycaemic efficacy and well tolerated over 6-months use. Mild increase in body-weight, serum triglycerides and overall adverse events remain issues of concern warranting further evaluation in longer clinical trials with active controls.
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Affiliation(s)
- Deep Dutta
- Department of Endocrinology, Center for Endocrinology Diabetes Arthritis & Rheumatism (CEDAR) Super-speciality Healthcare, Dwarka, New Delhi, India.
| | - Deepak Khandelwal
- Department of Endocrinology, Khandelwal Diabetes, Thyroid & Endocrinology Clinic, Paschim Vihar, New Delhi, India
| | - Manoj Kumar
- Department of Endocrinology, CEDAR Super-speciality Healthcare, Panchkula, Haryana, India
| | - Meha Sharma
- Department of Rheumatology, CEDAR Super-speciality Healthcare, Dwarka, New Delhi, India
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18
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Holmer M, Ekstedt M, Nasr P, Zenlander R, Wester A, Tavaglione F, Romeo S, Kechagias S, Stål P, Hagström H. Effect of common genetic variants on the risk of cirrhosis in non-alcoholic fatty liver disease during 20 years of follow-up. Liver Int 2022; 42:2769-2780. [PMID: 36166317 PMCID: PMC9828463 DOI: 10.1111/liv.15438] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 09/11/2022] [Accepted: 09/25/2022] [Indexed: 01/20/2023]
Abstract
BACKGROUND AND AIMS Several genotypes associate with a worse histopathological profile in patients with non-alcoholic fatty liver disease (NAFLD). Whether genotypes impact long-term outcomes is unclear. We investigated the importance of PNPLA3, TM6SF2, MBOAT7 and GCKR genotype for the development of severe outcomes in NAFLD. METHOD DNA samples were collected from 546 patients with NAFLD. Advanced fibrosis was diagnosed by liver biopsy or elastography. Non-alcoholic steatohepatitis (NASH) was histologically defined. Additionally, 5396 controls matched for age, sex and municipality were identified from population-based registers. Events of severe liver disease and all-cause mortality were collected from national registries. Hazard ratios (HRs) adjusted for age, sex, body mass index and type 2 diabetes were estimated with Cox regression. RESULTS In NAFLD, the G/G genotype of PNPLA3 was associated with a higher prevalence of NASH at baseline (odds ratio [OR] 3.67, 95% CI = 1.66-8.08), but not with advanced fibrosis (OR 1.81, 95% CI = 0.79-4.14). After up to 40 years of follow-up, the PNPLA3 G/G genotype was associated with a higher rate of severe liver disease (adjusted hazard ratio [aHR] 2.27, 95% CI = 1.15-4.47) compared with the C/C variant. NAFLD patients developed cirrhosis at a higher rate than controls (aHR 9.00, 95% CI = 6.85-11.83). The PNPLA3 G/G genotype accentuated this rate (aHR 23.32, 95% = CI 9.14-59.47). Overall mortality was not affected by any genetic variant. CONCLUSION The PNPLA3 G/G genotype is associated with an increased rate of cirrhosis in NAFLD. Our results suggest that assessment of the PNPLA3 genotype is of clinical relevance in patients with NAFLD to individualize monitoring and therapeutic strategies.
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Affiliation(s)
- Magnus Holmer
- Division of Liver and Pancreatic disease, Department of Upper GIKarolinska University HospitalStockholmSweden,Department of Medicine, HuddingeKarolinska InstitutetStockholmSweden
| | - Mattias Ekstedt
- Department of Gastroenterology and Hepatology, Department of Health, Medicine, and Caring SciencesLinköping UniversityLinköpingSweden
| | - Patrik Nasr
- Department of Medicine, HuddingeKarolinska InstitutetStockholmSweden,Department of Gastroenterology and Hepatology, Department of Health, Medicine, and Caring SciencesLinköping UniversityLinköpingSweden
| | - Robin Zenlander
- Department of Medicine, HuddingeKarolinska InstitutetStockholmSweden
| | - Axel Wester
- Department of Medicine, HuddingeKarolinska InstitutetStockholmSweden
| | - Federica Tavaglione
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg LaboratoryUniversity of GothenburgGothenburgSweden
| | - Stefano Romeo
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Wallenberg LaboratoryUniversity of GothenburgGothenburgSweden,Department of CardiologySahlgrenska University HospitalGothenburgSweden
| | - Stergios Kechagias
- Department of Gastroenterology and Hepatology, Department of Health, Medicine, and Caring SciencesLinköping UniversityLinköpingSweden
| | - Per Stål
- Division of Liver and Pancreatic disease, Department of Upper GIKarolinska University HospitalStockholmSweden,Department of Medicine, HuddingeKarolinska InstitutetStockholmSweden
| | - Hannes Hagström
- Division of Liver and Pancreatic disease, Department of Upper GIKarolinska University HospitalStockholmSweden,Department of Medicine, HuddingeKarolinska InstitutetStockholmSweden,Clinical Epidemiology Unit, Department of Medicine, SolnaKarolinska InstitutetStockholmSweden
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19
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Simons PIHG, Valkenburg O, Stehouwer CDA, Brouwers MCGJ. Association between de novo lipogenesis susceptibility genes and coronary artery disease. Nutr Metab Cardiovasc Dis 2022; 32:2883-2889. [PMID: 36182335 DOI: 10.1016/j.numecd.2022.09.003] [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: 02/21/2022] [Revised: 08/18/2022] [Accepted: 09/08/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND AND AIMS Coronary artery disease (CAD) is the principal cause of death in individuals with non-alcoholic fatty liver disease (NAFLD). The aim of this study was to use genetic epidemiology to study the association between de novo lipogenesis (DNL), one of the major pathways leading to NAFLD, and CAD risk. METHODS AND RESULTS DNL susceptibility genes were used as instruments and selected using three approaches: 1) genes that are associated with both high serum triglycerides and low sex hormone-binding globulin, both downstream consequences of DNL (unbiased approach), 2) genes that have a known role in DNL (biased approach), and 3) genes that have been associated with serum fatty acids, used as a proxy of DNL. Gene-CAD effect estimates were retrieved from the meta-analysis of CARDIoGRAM and the UK Biobank (∼76014 cases and ∼264785 controls). Effect estimates were clustered using a fixed-effects meta-analysis. Twenty-two DNL susceptibility genes were identified by the unbiased approach, nine genes by the biased approach and seven genes were associated with plasma fatty acids. Clustering of genes selected in the unbiased and biased approach showed a statistically significant association with CAD (OR:1.016, 95%CI:1.012; 1.020 and OR:1.013, 95%CI:1.007; 1.020, respectively), while clustering of fatty acid genes did not (OR:1.004, 95%CI:0.996-1.011). Subsequent exclusion of potential influential outliers did reveal a statistically significant association (OR:1.009, 95%CI:1.000; 1.018). CONCLUSIONS DNL susceptibility genes are associated with an increased risk of CAD. These findings suggest that DNL may be involved in the pathogenesis of CAD and favor further development of strategies that target NAFLD through DNL.
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Affiliation(s)
- Pomme I H G Simons
- Department of Internal Medicine, Division of Endocrinology and Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands; Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - Olivier Valkenburg
- Department of Reproductive Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Coen D A Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands; Department of Internal Medicine, Division of General Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Martijn C G J Brouwers
- Department of Internal Medicine, Division of Endocrinology and Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands.
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20
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Kroon T, Hagstedt T, Alexandersson I, Ferm A, Petersson M, Maurer S, Zarrouki B, Wallenius K, Oakes ND, Boucher J. Chronotherapy with a glucokinase activator profoundly improves metabolism in obese Zucker rats. Sci Transl Med 2022; 14:eabh1316. [DOI: 10.1126/scitranslmed.abh1316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Circadian rhythms play a critical role in regulating metabolism, including daily cycles of feeding/fasting. Glucokinase (GCK) is central for whole-body glucose homeostasis and oscillates according to a circadian clock. GCK activators (GKAs) effectively reduce hyperglycemia, but their use is also associated with hypoglycemia, hyperlipidemia, and hepatic steatosis. Given the circadian rhythmicity and natural postprandial activation of GCK, we hypothesized that GKA treatment would benefit from being timed specifically during feeding periods. Acute treatment of obese Zucker rats with the GKA AZD1656 robustly increased flux into all major metabolic pathways of glucose disposal, enhancing glucose elimination. Four weeks of continuous AZD1656 treatment of obese Zucker rats improved glycemic control; however, hepatic steatosis and inflammation manifested. In contrast, timing AZD1656 to feeding periods robustly reduced hepatic steatosis and inflammation in addition to improving glycemia, whereas treatment timed to fasting periods caused overall detrimental metabolic effects. Mechanistically, timing AZD1656 to feeding periods diverted newly synthesized lipid toward direct VLDL secretion rather than intrahepatic storage. In line with increased hepatic insulin signaling, timing AZD1656 to feeding resulted in robust activation of AKT, mTOR, and SREBP-1C after glucose loading, pathways known to regulate VLDL secretion and hepatic de novo lipogenesis. In conclusion, intermittent AZD1656 treatment timed to feeding periods promotes glucose disposal when needed the most, restores metabolic flexibility and hepatic insulin sensitivity, and thereby avoids hepatic steatosis. Thus, chronotherapeutic approaches may benefit the development of GKAs and other drugs acting on metabolic targets.
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Affiliation(s)
- Tobias Kroon
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
- Lundberg Laboratory for Diabetes Research, University of Gothenburg, Gothernburg 41345, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothernburg 40530 Sweden
| | - Therese Hagstedt
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Ida Alexandersson
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Annett Ferm
- Animal Sciences and Technologies, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Marie Petersson
- Animal Sciences and Technologies, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Stefanie Maurer
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Bader Zarrouki
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Kristina Wallenius
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Nicholas D. Oakes
- Functional and Mechanistic Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gothenburg 43183, Sweden
| | - Jeremie Boucher
- Bioscience Metabolism, Research and Early Development, Cardiovascular, Renal, and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg 43183, Sweden
- Lundberg Laboratory for Diabetes Research, University of Gothenburg, Gothernburg 41345, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothernburg 40530 Sweden
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21
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Brouwers MCGJ. Fructose 1-phosphate, an evolutionary signaling molecule of abundancy. Trends Endocrinol Metab 2022; 33:680-689. [PMID: 35995682 DOI: 10.1016/j.tem.2022.07.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 07/27/2022] [Accepted: 07/27/2022] [Indexed: 11/18/2022]
Abstract
Evidence is accumulating that specifically fructose exerts adverse cardiometabolic effects in humans. Recent experimental studies have shown that fructose not only serves as a substrate for, among others, intrahepatic lipid formation, but also has a signaling function. It is postulated that fructose 1-phosphate (F1-P) has evolved as a signaling molecule of abundancy that stimulates nutrient absorption, lipid storage, and reproduction. Such a role would provide an explanation for why fructose contributes to the pathogenesis of evolutionary mismatch diseases, including nonalcoholic fatty liver disease (NAFLD), cardiovascular disease, polycystic ovary syndrome (PCOS), and colorectal cancer, in the current era of nutritional abundance. It is anticipated that reducing F1-P, by either pharmacological inhibition of ketohexokinase (KHK) or societal measures, will mitigate the risk of these diseases.
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Affiliation(s)
- Martijn C G J Brouwers
- Department of Internal Medicine, Division of Endocrinology and Metabolic Disease, Maastricht University Medical Centre, Maastricht, The Netherlands; CARIM School for Cardiovascular Disease, Maastricht University, Maastricht, The Netherlands.
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22
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Wang K, Shi M, Huang C, Fan B, Luk AOY, Kong APS, Ma RCW, Chan JCN, Chow E. Evaluating the impact of glucokinase activation on risk of cardiovascular disease: a Mendelian randomisation analysis. Cardiovasc Diabetol 2022; 21:192. [PMID: 36151532 PMCID: PMC9503210 DOI: 10.1186/s12933-022-01613-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 08/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Glucokinase activators (GKAs) are an emerging class of glucose lowering drugs that activate the glucose-sensing enzyme glucokinase (GK). Pending formal cardiovascular outcome trials, we applied two-sample Mendelian randomisation (MR) to investigate the impact of GK activation on risk of cardiovascular diseases. METHODS We used independent genetic variants in or around the glucokinase gene meanwhile associated with HbA1c at genome-wide significance (P < 5 × 10-8) in the Meta-Analyses of Glucose and Insulin-related traits Consortium study (N = 146,806; European ancestry) as instrumental variables (IVs) to mimic the effects of GK activation. We assessed the association between genetically proxied GK activation and the risk of coronary artery disease (CAD; 122,733 cases and 424,528 controls), peripheral arterial disease (PAD; 7098 cases and 206,541 controls), stroke (40,585 cases and 406,111 controls) and heart failure (HF; 47,309 cases and 930,014 controls), using genome-wide association study summary statistics of these outcomes in Europeans. We compared the effect estimates of genetically proxied GK activation with estimates of genetically proxied lower HbA1c on the same outcomes. We repeated our MR analyses in East Asians as validation. RESULTS Genetically proxied GK activation was associated with reduced risk of CAD (OR 0.38 per 1% lower HbA1c, 95% CI 0.29-0.51, P = 8.77 × 10-11) and HF (OR 0.54 per 1% lower HbA1c, 95% CI 0.41-0.73, P = 3.55 × 10-5). The genetically proxied protective effects of GKA on CAD and HF exceeded those due to non-targeted HbA1c lowering. There was no causal relationship between genetically proxied GK activation and risk of PAD or stroke. The estimates in sensitivity analyses and in East Asians were generally consistent. CONCLUSIONS GKAs may protect against CAD and HF which needs confirmation by long-term clinical trials.
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Affiliation(s)
- Ke Wang
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Mai Shi
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Phase 1 Clinical Trial Centre, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China. .,Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China. .,Phase 1 Clinical Trial Centre, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.
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23
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Koene E, Schrauwen-Hinderling VB, Schrauwen P, Brouwers MCGJ. Novel insights in intestinal and hepatic fructose metabolism: from mice to men. Curr Opin Clin Nutr Metab Care 2022; 25:354-359. [PMID: 35838297 DOI: 10.1097/mco.0000000000000853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW The rise in fructose consumption in parallel with the current epidemic of obesity and related cardiometabolic disease requires a better understanding of the pathophysiological pathways that are involved. RECENT FINDINGS Animal studies have shown that fructose has various effects on the intestines that subsequently affect intrahepatic lipid accumulation and inflammation. Fructose adversely affects the gut microbiome - as a producer of endotoxins and intermediates of de novo lipogenesis - and intestinal barrier function. Furthermore, intestinal fructose metabolism shields fructose away from the liver. Finally, fructose 1-phosphate (F1-P) serves as a signal molecule that promotes intestinal cell survival and, consequently, intestinal absorption capacity. Intervention and epidemiological studies have convincingly shown that fructose, particularly derived from sugar-sweetened beverages, stimulates de novo lipogenesis and intrahepatic lipid accumulation in humans. Of interest, individuals with aldolase B deficiency, who accumulate F1-P, are characterized by a greater intrahepatic lipid content. First phase II clinical trials have recently shown that reduction of F1-P, by inhibition of ketohexokinase, reduces intrahepatic lipid content. SUMMARY Experimental evidence supports current measures to reduce fructose intake, for example by the implementation of a tax on sugar-sweetened beverages, and pharmacological inhibition of fructose metabolism to reduce the global burden of cardiometabolic disease.
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Affiliation(s)
- Evi Koene
- Department of Nutrition and Movement Sciences
- School of Nutrition and Translational Research in Metabolism (NUTRIM)
| | - Vera B Schrauwen-Hinderling
- Department of Nutrition and Movement Sciences
- School of Nutrition and Translational Research in Metabolism (NUTRIM)
- Department of Radiology and Nuclear Medicine, Maastricht University
| | - Patrick Schrauwen
- Department of Nutrition and Movement Sciences
- School of Nutrition and Translational Research in Metabolism (NUTRIM)
| | - Martijn C G J Brouwers
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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24
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Chew NW, Chong B, Ng CH, Kong G, Chin YH, Xiao W, Lee M, Dan YY, Muthiah MD, Foo R. The genetic interactions between non-alcoholic fatty liver disease and cardiovascular diseases. Front Genet 2022; 13:971484. [PMID: 36035124 PMCID: PMC9399730 DOI: 10.3389/fgene.2022.971484] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 07/19/2022] [Indexed: 12/03/2022] Open
Abstract
The ongoing debate on whether non-alcoholic fatty liver disease (NAFLD) is an active contributor or an innocent bystander in the development of cardiovascular disease (CVD) has sparked interests in understanding the common mediators between the two biologically distinct entities. This comprehensive review identifies and curates genetic studies of NAFLD overlapping with CVD, and describes the colinear as well as opposing correlations between genetic associations for the two diseases. Here, CVD described in relation to NAFLD are coronary artery disease, cardiomyopathy and atrial fibrillation. Unique findings of this review included certain NAFLD susceptibility genes that possessed cardioprotective properties. Moreover, the complex interactions of genetic and environmental risk factors shed light on the disparity in genetic influence on NAFLD and its incident CVD. This serves to unravel NAFLD-mediated pathways in order to reduce CVD events, and helps identify targeted treatment strategies, develop polygenic risk scores to improve risk prediction and personalise disease prevention.
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Affiliation(s)
- Nicholas W.S. Chew
- Department of Cardiology, National University Heart Centre, Singapore, Singapore
- *Correspondence: Nicholas W.S. Chew, ; Roger Foo,
| | - Bryan Chong
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Cheng Han Ng
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Gwyneth Kong
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Yip Han Chin
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Wang Xiao
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cardiovascular Disease Translational Research Programme, National University Health Systems, Singapore, Singapore
- Genome Institute of Singapore, Agency of Science Technology and Research, Bipolis way, Singapore
| | - Mick Lee
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cardiovascular Disease Translational Research Programme, National University Health Systems, Singapore, Singapore
- Genome Institute of Singapore, Agency of Science Technology and Research, Bipolis way, Singapore
| | - Yock Young Dan
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore, Singapore
- National University Centre for Organ Transplantation, National University Health System, Singapore, Singapore
| | - Mark D. Muthiah
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore, Singapore
- National University Centre for Organ Transplantation, National University Health System, Singapore, Singapore
| | - Roger Foo
- Department of Cardiology, National University Heart Centre, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
- Cardiovascular Research Institute, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cardiovascular Disease Translational Research Programme, National University Health Systems, Singapore, Singapore
- Genome Institute of Singapore, Agency of Science Technology and Research, Bipolis way, Singapore
- *Correspondence: Nicholas W.S. Chew, ; Roger Foo,
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25
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Simons PIHG, Valkenburg O, Telgenkamp I, van der Waaij KM, de Groot DM, Veeraiah P, Bons JAP, Derks TGJ, Schalkwijk CG, Schrauwen-Hinderling VB, Stehouwer CDA, Brouwers MCGJ. Serum sex hormone-binding globulin levels are reduced and inversely associated with intrahepatic lipid content and saturated fatty acid fraction in adult patients with glycogen storage disease type 1a. J Endocrinol Invest 2022; 45:1227-1234. [PMID: 35132570 PMCID: PMC9098618 DOI: 10.1007/s40618-022-01753-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 01/22/2022] [Indexed: 11/28/2022]
Abstract
PURPOSE De novo lipogenesis has been inversely associated with serum sex hormone-binding globulin (SHBG) levels. However, the directionality of this association has remained uncertain. We, therefore, studied individuals with glycogen storage disease type 1a (GSD1a), who are characterized by a genetic defect in glucose-6-phosphatase resulting in increased rates of de novo lipogenesis, to assess the downstream effect on serum SHBG levels. METHODS A case-control study comparing serum SHBG levels in patients with GSD1a (n = 10) and controls matched for age, sex, and BMI (n = 10). Intrahepatic lipid content and saturated fatty acid fraction were quantified by proton magnetic resonance spectroscopy. RESULTS Serum SHBG levels were statistically significantly lower in patients with GSD1a compared to the controls (p = 0.041), while intrahepatic lipid content and intrahepatic saturated fatty acid fraction-a marker of de novo lipogenesis-were significantly higher in patients with GSD1a (p = 0.001 and p = 0.019, respectively). In addition, there was a statistically significant, inverse association of intrahepatic lipid content and saturated fatty acid fraction with serum SHBG levels in patients and controls combined (β: - 0.28, 95% CI: - 0.47;- 0.09 and β: - 0.02, 95% CI: - 0.04;- 0.01, respectively). CONCLUSION Patients with GSD1a, who are characterized by genetically determined higher rates of de novo lipogenesis, have lower serum SHBG levels than controls.
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Affiliation(s)
- P I H G Simons
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Centre, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - O Valkenburg
- Department of Reproductive Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - I Telgenkamp
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Centre, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
| | - K M van der Waaij
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Centre, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
| | - D M de Groot
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Centre, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - P Veeraiah
- Department of Nutrition and Movement Sciences, Maastricht University, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University, Maastricht, The Netherlands
| | - J A P Bons
- Central Diagnostic Laboratory, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - T G J Derks
- Section of Metabolic Diseases, Beatrix Children's Hospital, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - C G Schalkwijk
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - V B Schrauwen-Hinderling
- Department of Nutrition and Movement Sciences, Maastricht University, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University, Maastricht, The Netherlands
| | - C D A Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - M C G J Brouwers
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Centre, PO Box 5800, 6202 AZ, Maastricht, The Netherlands.
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.
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26
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Vujkovic M, Ramdas S, Lorenz KM, Guo X, Darlay R, Cordell HJ, He J, Gindin Y, Chung C, Myers RP, Schneider CV, Park J, Lee KM, Serper M, Carr RM, Kaplan DE, Haas ME, MacLean MT, Witschey WR, Zhu X, Tcheandjieu C, Kember RL, Kranzler HR, Verma A, Giri A, Klarin DM, Sun YV, Huang J, Huffman JE, Creasy KT, Hand NJ, Liu CT, Long MT, Yao J, Budoff M, Tan J, Li X, Lin HJ, Chen YDI, Taylor KD, Chang RK, Krauss RM, Vilarinho S, Brancale J, Nielsen JB, Locke AE, Jones MB, Verweij N, Baras A, Reddy KR, Neuschwander-Tetri BA, Schwimmer JB, Sanyal AJ, Chalasani N, Ryan KA, Mitchell BD, Gill D, Wells AD, Manduchi E, Saiman Y, Mahmud N, Miller DR, Reaven PD, Phillips LS, Muralidhar S, DuVall SL, Lee JS, Assimes TL, Pyarajan S, Cho K, Edwards TL, Damrauer SM, Wilson PW, Gaziano JM, O'Donnell CJ, Khera AV, Grant SFA, Brown CD, Tsao PS, Saleheen D, Lotta LA, Bastarache L, Anstee QM, Daly AK, Meigs JB, Rotter JI, Lynch JA, Rader DJ, Voight BF, Chang KM. A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation. Nat Genet 2022; 54:761-771. [PMID: 35654975 PMCID: PMC10024253 DOI: 10.1038/s41588-022-01078-z] [Citation(s) in RCA: 113] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 04/18/2022] [Indexed: 02/05/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.
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Affiliation(s)
- Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Shweta Ramdas
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kim M Lorenz
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Rebecca Darlay
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Heather J Cordell
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Robert P Myers
- Gilead Sciences, Inc., Foster City, CA, USA
- The Liver Company, Palo Alto, CA, USA
| | - Carolin V Schneider
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joseph Park
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Marina Serper
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rotonya M Carr
- Division of Gastroenterology, University of Washington, Seattle, WA, USA
| | - David E Kaplan
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mary E Haas
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew T MacLean
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Walter R Witschey
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Rachel L Kember
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Henry R Kranzler
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ayush Giri
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Derek M Klarin
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Division of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yan V Sun
- Atlanta VA Medical Center, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jie Huang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | | | - Kate Townsend Creasy
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nicholas J Hand
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michelle T Long
- Department of Medicine, Section of Gastroenterology, Boston University School of Medicine, Boston, MA, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Matthew Budoff
- Department of Cardiology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ruey-Kang Chang
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ronald M Krauss
- Departments of Pediatrics and Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Silvia Vilarinho
- Section of Digestive Diseases, Department of Internal Medicine, and Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Joseph Brancale
- Section of Digestive Diseases, Department of Internal Medicine, and Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | | | | | | | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - K Rajender Reddy
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Jeffrey B Schwimmer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Arun J Sanyal
- Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Naga Chalasani
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathleen A Ryan
- Program for Personalized and Genomic Medicine, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Program for Personalized and Genomic Medicine, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Andrew D Wells
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elisabetta Manduchi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yedidya Saiman
- Department of Medicine, Section of Hepatology, Lewis Katz School of Medicine at Temple University, Temple University Hospital, Philadelphia, PA, USA
| | - Nadim Mahmud
- Department of Medicine, Division of Gastroenterology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA
- Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
- College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Lawrence S Phillips
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology, Emory University School of Medicine, Atlanta, GA, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Scott L DuVall
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Todd L Edwards
- Nashville VA Medical Center, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter W Wilson
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Struan F A Grant
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Christopher D Brown
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | | | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quentin M Anstee
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Ann K Daly
- Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- College of Nursing and Health Sciences, University of Massachusetts, Lowell, MA, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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27
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Targeting human Glucokinase for the treatment of type 2 diabetes: an overview of allosteric Glucokinase activators. J Diabetes Metab Disord 2022; 21:1129-1137. [PMID: 35673438 PMCID: PMC9167346 DOI: 10.1007/s40200-022-01019-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 02/28/2022] [Indexed: 10/18/2022]
Abstract
Diabetes mellitus is a worldwide impacting disorder and the ratio through which the number of diabetic patients had increased worldwide, puts medical professionals to serious stress for its effective management. Due to its polygenic origin and involvement of multiple genes to its pathophysiology, leads to understanding of this ailment more complex. It seems that current interventions, such as dietary changes, life style changes and drug therapy such as oral hypoglycaemics and insulin, are unable to halt the trend. There are various novel and emerging targets on which the researchers are paying attention to combat with this ailment successfully. Human glucokinase (GK) enzyme is one of these novel and emerging targets for management of diabetes. Its availability in the pancreas and liver cells makes this target more lucrative. GK's presence in the pancreatic and hepatic cells plays a very important function for the management of glucose homoeostasis. Small molecules that activate GK allosterically provide an alternative strategy for restoring/improving glycaemic regulation, especially in type 2 diabetic patients. Although after enduring many setbacks in the development of the GK activators, interest has been renewed especially due to introduction of novel dual acting GK activator dorzagliatin, and a novel hepato-selective GK activator, TTP399. This review article has been formulated to discuss importance of GK in glucose homeostasis, recent updates on small molecules of GK activators, clinical status of GK activators and challenges in development of GK activators.
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28
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DiCorpo D, LeClair J, Cole JB, Sarnowski C, Ahmadizar F, Bielak LF, Blokstra A, Bottinger EP, Chaker L, Chen YDI, Chen Y, de Vries PS, Faquih T, Ghanbari M, Gudmundsdottir V, Guo X, Hasbani NR, Ibi D, Ikram MA, Kavousi M, Leonard HL, Leong A, Mercader JM, Morrison AC, Nadkarni GN, Nalls MA, Noordam R, Preuss M, Smith JA, Trompet S, Vissink P, Yao J, Zhao W, Boerwinkle E, Goodarzi MO, Gudnason V, Jukema JW, Kardia SL, Loos RJ, Liu CT, Manning AK, Mook-Kanamori D, Pankow JS, Picavet HSJ, Sattar N, Simonsick EM, Verschuren WM, Willems van Dijk K, Florez JC, Rotter JI, Meigs JB, Dupuis J, Udler MS. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts. Diabetes Care 2022; 45:674-683. [PMID: 35085396 PMCID: PMC8918228 DOI: 10.2337/dc21-1395] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/15/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.
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Affiliation(s)
- Daniel DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jessica LeClair
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Joanne B. Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Division of Endocrinology, Boston Children’s Hospital, Boston, MA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Julius Global Health, University Utrecht Medical Center, Utrecht, the Netherlands
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Anneke Blokstra
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Erwin P. Bottinger
- Hasso Plattner Institute Digital Health, Potsdam, Germany
- Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Layal Chaker
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yii-Der I. Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Ye Chen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Tariq Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Dorina Ibi
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Hampton L. Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josep M. Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Alanna C. Morrison
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Petra Vissink
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Ruth J.F. Loos
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Dennis Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - H. Susan J. Picavet
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, U.K
| | - Eleanor M. Simonsick
- Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - W.M. Monique Verschuren
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Miriam S. Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
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29
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Wu C, Borné Y, Gao R, López Rodriguez M, Roell WC, Wilson JM, Regmi A, Luan C, Aly DM, Peter A, Machann J, Staiger H, Fritsche A, Birkenfeld AL, Tao R, Wagner R, Canouil M, Hong MG, Schwenk JM, Ahlqvist E, Kaikkonen MU, Nilsson P, Shore AC, Khan F, Natali A, Melander O, Orho-Melander M, Nilsson J, Häring HU, Renström E, Wollheim CB, Engström G, Weng J, Pearson ER, Franks PW, White MF, Duffin KL, Vaag AA, Laakso M, Stefan N, Groop L, De Marinis Y. Elevated circulating follistatin associates with an increased risk of type 2 diabetes. Nat Commun 2021; 12:6486. [PMID: 34759311 PMCID: PMC8580990 DOI: 10.1038/s41467-021-26536-w] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 10/05/2021] [Indexed: 12/23/2022] Open
Abstract
The hepatokine follistatin is elevated in patients with type 2 diabetes (T2D) and promotes hyperglycemia in mice. Here we explore the relationship of plasma follistatin levels with incident T2D and mechanisms involved. Adjusted hazard ratio (HR) per standard deviation (SD) increase in follistatin levels for T2D is 1.24 (CI: 1.04–1.47, p < 0.05) during 19-year follow-up (n = 4060, Sweden); and 1.31 (CI: 1.09–1.58, p < 0.01) during 4-year follow-up (n = 883, Finland). High circulating follistatin associates with adipose tissue insulin resistance and non-alcoholic fatty liver disease (n = 210, Germany). In human adipocytes, follistatin dose-dependently increases free fatty acid release. In genome-wide association study (GWAS), variation in the glucokinase regulatory protein gene (GCKR) associates with plasma follistatin levels (n = 4239, Sweden; n = 885, UK, Italy and Sweden) and GCKR regulates follistatin secretion in hepatocytes in vitro. Our findings suggest that GCKR regulates follistatin secretion and that elevated circulating follistatin associates with an increased risk of T2D by inducing adipose tissue insulin resistance. Follistatin promotes in type 2 diabetes (T2D) pathogenesis in model animals and is elevated in patients with T2D. Here the authors report that plasma follistatin associates with increased risk of incident T2D in two longitudinal cohorts, and show that follistatin regulates insulin-induced suppression lipolysis in cultured human adipocytes.
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Affiliation(s)
- Chuanyan Wu
- Department of Clinical Sciences, Lund University, Malmö, Sweden.,School of Control Science and Engineering, Shandong University, Jinan, Shandong, China.,School of Intelligent Engineering, Shandong Management University, Jinan, Shandong, China
| | - Yan Borné
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Rui Gao
- School of Control Science and Engineering, Shandong University, Jinan, Shandong, China
| | - Maykel López Rodriguez
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.,A.I. Virtanen Institute for Molecular Sciences, Department of Biotechnology and Molecular Medicine, University of Eastern Finland, Kuopio, Finland
| | - William C Roell
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Jonathan M Wilson
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Ajit Regmi
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Cheng Luan
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Andreas Peter
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Jürgen Machann
- Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany.,Section of Experimental Radiology, Department of Radiology, University of Tübingen, Tübingen, Germany
| | - Harald Staiger
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Andreas Fritsche
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Andreas L Birkenfeld
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Rongya Tao
- Division of Endocrinology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert Wagner
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Mickaël Canouil
- Inserm U1283 / CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille; University of Lille, Lille University Hospital, Lille, France
| | - Mun-Gwan Hong
- Affinity Proteomics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Jochen M Schwenk
- Affinity Proteomics, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Emma Ahlqvist
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Minna U Kaikkonen
- A.I. Virtanen Institute for Molecular Sciences, Department of Biotechnology and Molecular Medicine, University of Eastern Finland, Kuopio, Finland
| | - Peter Nilsson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Angela C Shore
- NIHR Exeter Clinical Research Facility, Royal Devon and Exeter Hospital and University of Exeter Medical School, Exeter, Devon, UK
| | - Faisel Khan
- Division of Systems Medicine, University of Dundee, Ninewells Hospital & Medical School, Dundee, UK
| | - Andrea Natali
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Jan Nilsson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Hans-Ulrich Häring
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Erik Renström
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Claes B Wollheim
- Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Cell Physiology and Metabolism, University Medical Centre, Geneva, Switzerland
| | - Gunnar Engström
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Jianping Weng
- Department of Endocrinology and Metabolism, Division of Life Sciences of Medicine, University of Science and Technology of China, Hefei, China
| | - Ewan R Pearson
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, DD1 9SY, UK
| | - Paul W Franks
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Morris F White
- Division of Endocrinology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kevin L Duffin
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.,Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Norbert Stefan
- Department of Internal Medicine IV, Division of Endocrinology, Diabetology and Nephrology; and Department for Diagnostic Laboratory Medicine, Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.,Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich, Tübingen, Germany.,German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Leif Groop
- Department of Clinical Sciences, Lund University, Malmö, Sweden.,Finnish Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland
| | - Yang De Marinis
- Department of Clinical Sciences, Lund University, Malmö, Sweden. .,School of Control Science and Engineering, Shandong University, Jinan, Shandong, China. .,Department of Endocrinology and Metabolism, Division of Life Sciences of Medicine, University of Science and Technology of China, Hefei, China.
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Simons PIHG, Valkenburg O, Stehouwer CDA, Brouwers MCGJ. Sex hormone-binding globulin: biomarker and hepatokine? Trends Endocrinol Metab 2021; 32:544-553. [PMID: 34052096 DOI: 10.1016/j.tem.2021.05.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/19/2021] [Accepted: 05/04/2021] [Indexed: 12/18/2022]
Abstract
Over the past decade, there have been important breakthroughs in our understanding of the regulation and function of sex hormone-binding globulin (SHBG). A recent genome-wide association and Mendelian randomization study has provided new insights at the population level. Thorough study of genetic variants affecting serum SHBG has identified de novo lipogenesis as one of the mechanistic links between the metabolic syndrome and reduced serum SHBG levels in humans. Furthermore, careful deduction of the Mendelian randomization results suggests a direct, causal role for SHBG in the pathogenesis of type 2 diabetes, as a hepatokine, in women. These findings prompt the development of SHBG-raising therapies as a means to prevent or treat disorders such as type 2 diabetes and polycystic ovary syndrome.
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Affiliation(s)
- Pomme I H G Simons
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands; Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Olivier Valkenburg
- Department of Reproductive Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Coen D A Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Maastricht University, Maastricht, The Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands; Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Martijn C G J Brouwers
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands; CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.
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31
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Dong M, Liu S, Wang M, Wang Y, Xin Y, Xuan S. Relationship between AGT rs2493132 polymorphism and the risk of coronary artery disease in patients with NAFLD in the Chinese Han population. J Int Med Res 2021; 49:3000605211019263. [PMID: 34275374 PMCID: PMC8293844 DOI: 10.1177/03000605211019263] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Objective To investigate the relationship between angiotensin (AGT) rs2493132 gene polymorphism and the risk of developing non-alcoholic fatty liver disease (NAFLD) and coronary artery disease (CAD) in the Chinese Han population. Methods Polymerase chain reaction was performed to determine AGT genotypes. Anthropometric and clinical data were investigated and statistically analyzed in the clinical laboratory department of Qingdao Municipal Hospital. Results The AGT rs2493132 CT + TT genotype was an important risk factor for CAD in patients with NAFLD and NAFLD + CAD in healthy controls. The AGT rs2493132 T allele increased the risk of NAFLD + CAD in healthy controls. The AGT rs2493132 CT + TT genotype and T allele also significantly increased the risk of CAD in patients with NAFLD after adjustments for age, sex, and body mass index. In addition, AGT rs2493132 T allele carriers showed higher total cholesterol (TC) and low-density lipoprotein (LDL) levels compared with non-carriers. Conclusions The AGT rs2493132 CT + TT genotype and T allele significantly increased the risk of developing CAD in patients with NAFLD in the Chinese Han population. The AGT rs2493132 T allele was associated with increased serum TC and LDL levels.
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Affiliation(s)
- Mengzhen Dong
- Department of Infectious Disease, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Shousheng Liu
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.,Digestive Disease Key Laboratory of Qingdao, Qingdao, China
| | - Mengke Wang
- Department of Infectious Disease, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yifen Wang
- Department of Infectious Disease, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yongning Xin
- Department of Infectious Disease, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.,Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.,Digestive Disease Key Laboratory of Qingdao, Qingdao, China.,Department of Gastroenterology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Shiying Xuan
- Department of Infectious Disease, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.,Digestive Disease Key Laboratory of Qingdao, Qingdao, China
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32
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Zhou F, Zhang L, Zhu K, Bai M, Zhang Y, Zhu Q, Wang S, Sheng C, Yuan M, Liu Y, Lu J, Shao L, Wang X, Zhou L. SIRT2 ablation inhibits glucose-stimulated insulin secretion through decreasing glycolytic flux. Am J Cancer Res 2021; 11:4825-4838. [PMID: 33754030 PMCID: PMC7978320 DOI: 10.7150/thno.55330] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 02/06/2021] [Indexed: 11/30/2022] Open
Abstract
Rationale: Sirtuins are NAD+-dependent protein deacylases known to have protective effects against age-related diseases such as diabetes, cancer, and neurodegenerative disease. SIRT2 is the only primarily cytoplasmic isoform and its overall role in glucose homeostasis remains uncertain. Methods: SIRT2-knockout (KO) rats were constructed to evaluate the role of SIRT2 in glucose homeostasis. The effect of SIRT2 on β-cell function was detected by investigating the morphology, insulin secretion, and metabolomic state of islets. The deacetylation and stabilization of GKRP in β-cells by SIRT2 were determined by western blot, adenoviral infection, and immunoprecipitation. Results: SIRT2-KO rats exhibited impaired glucose tolerance and glucose-stimulated insulin secretion (GSIS), without change in insulin sensitivity. SIRT2 deficiency or inhibition by AGK2 decreased GSIS in isolated rat islets, with lowered oxygen consumption rate. Adenovirus-mediated overexpression of SIRT2 enhanced insulin secretion from rat islets. Metabolomics analysis revealed a decrease in metabolites of glycolysis and tricarboxylic acid cycle in SIRT2-KO islets compared with control islets. Our study further demonstrated that glucokinase regulatory protein (GKRP), an endogenous inhibitor of glucokinase (GCK), was expressed in rat islets. SIRT2 overexpression deacetylated GKRP in INS-1 β-cells. SIRT2 knockout or inhibition elevated GKRP protein stability in islet β-cells, leading to an increase in the interaction of GKRP and GCK. On the contrary, SIRT2 inhibition promoted the protein degradation of ALDOA, a glycolytic enzyme. Conclusions: SIRT2 ablation inhibits GSIS through blocking GKRP protein degradation and promoting ALDOA protein degradation, resulting in a decrease in glycolytic flux.
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33
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Targher G, Corey KE, Byrne CD. NAFLD, and cardiovascular and cardiac diseases: Factors influencing risk, prediction and treatment. DIABETES & METABOLISM 2020; 47:101215. [PMID: 33296704 DOI: 10.1016/j.diabet.2020.101215] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 11/11/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND AND AIM Non-alcoholic fatty liver disease (NAFLD), affecting up to around 30% of the world's adult population, causes considerable liver-related and extrahepatic morbidity and mortality. Strong evidence indicates that NAFLD (especially its more severe forms) is associated with a greater risk of all-cause mortality, and the predominant cause of mortality in this patient population is cardiovascular disease (CVD). This narrative review aims to discuss the strong association between NAFLD and increased risk of cardiovascular, cardiac and arrhythmic complications. Also discussed are the putative mechanisms linking NAFLD to CVD and other cardiac/arrhythmic complications, with a brief summary of CVD risk prediction/stratification and management of the increased CVD risk observed in patients with NAFLD. RESULTS NAFLD is associated with an increased risk of CVD events and other cardiac complications (left ventricular hypertrophy, valvular calcification, certain arrhythmias) independently of traditional CVD risk factors. The magnitude of risk of CVD and other cardiac/arrhythmic complications parallels the severity of NAFLD (especially liver fibrosis severity). There are most likely multiple underlying mechanisms through which NAFLD may increase risk of CVD and cardiac/arrhythmic complications. Indeed, NAFLD exacerbates hepatic and systemic insulin resistance, promotes atherogenic dyslipidaemia, induces hypertension, and triggers synthesis of proatherogenic, procoagulant and proinflammatory mediators that may contribute to the development of CVD and other cardiac/arrhythmic complications. CONCLUSION Careful assessment of CVD risk is mandatory in patients with NAFLD for primary prevention of CVD, together with pharmacological treatment for coexisting CVD risk factors.
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Affiliation(s)
- Giovanni Targher
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy.
| | - Kathleen E Corey
- Liver Center, Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christopher D Byrne
- Nutrition and Metabolism, Faculty of Medicine, University of Southampton, UK; National Institute for Health Research Southampton Biomedical Research Centre, University Hospital Southampton, Southampton General Hospital, Tremona Road, Southampton, UK
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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: 1.8] [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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Ford BE, Chachra SS, Alshawi A, Brennan A, Harnor S, Cano C, Baker DJ, Smith DM, Fairclough RJ, Agius L. Chronic glucokinase activator treatment activates liver Carbohydrate response element binding protein and improves hepatocyte ATP homeostasis during substrate challenge. Diabetes Obes Metab 2020; 22:1985-1994. [PMID: 32519798 DOI: 10.1111/dom.14111] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 06/01/2020] [Accepted: 06/07/2020] [Indexed: 01/16/2023]
Abstract
AIM To test the hypothesis that glucokinase activators (GKAs) induce hepatic adaptations that alter intra-hepatocyte metabolite homeostasis. METHODS C57BL/6 mice on a standard rodent diet were treated with a GKA (AZD1656) acutely or chronically. Hepatocytes were isolated from the mice after 4 or 8 weeks of treatment for analysis of cellular metabolites and gene expression in response to substrate challenge. RESULTS Acute exposure of mice to AZD1656 or a liver-selective GKA (PF-04991532), before a glucose tolerance test, or challenge of mouse hepatocytes with GKAs ex vivo induced various Carbohydrate response element binding protein (ChREBP) target genes, including Carbohydrate response element binding protein beta isoform (ChREBP-β), Gckr and G6pc. Both glucokinase activation and ChREBP target gene induction by PF-04991532 were dependent on the chirality of the molecule, confirming a mechanism linked to glucokinase activation. Hepatocytes from mice treated with AZD1656 for 4 or 8 weeks had lower basal glucose 6-phosphate levels and improved ATP homeostasis during high substrate challenge. They also had raised basal ChREBP-β mRNA and AMPK-α mRNA (Prkaa1, Prkaa2) and progressively attenuated substrate induction of some ChREBP target genes and Prkaa1 and Prkaa2. CONCLUSIONS Chronic GKA treatment of C57BL/6 mice for 8 weeks activates liver ChREBP and improves the resilience of hepatocytes to compromised ATP homeostasis during high-substrate challenge. These changes are associated with raised mRNA levels of ChREBP-β and both catalytic subunits of AMP-activated protein kinase.
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Affiliation(s)
- Brian E Ford
- Biosciences Institute, Newcastle University, Medical School, Newcastle upon Tyne, UK
| | - Shruti S Chachra
- Biosciences Institute, Newcastle University, Medical School, Newcastle upon Tyne, UK
| | - Ahmed Alshawi
- Biosciences Institute, Newcastle University, Medical School, Newcastle upon Tyne, UK
| | - Alfie Brennan
- Newcastle Drug Discovery, Newcastle Centre for Cancer, School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - Suzannah Harnor
- Newcastle Drug Discovery, Newcastle Centre for Cancer, School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - Celine Cano
- Newcastle Drug Discovery, Newcastle Centre for Cancer, School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - David J Baker
- Bioscience, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - David M Smith
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Rebecca J Fairclough
- Emerging Innovations Unit, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Loranne Agius
- Biosciences Institute, Newcastle University, Medical School, Newcastle upon Tyne, UK
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Genome-wide association study of non-alcoholic fatty liver and steatohepatitis in a histologically characterised cohort ☆. J Hepatol 2020; 73:505-515. [PMID: 32298765 DOI: 10.1016/j.jhep.2020.04.003] [Citation(s) in RCA: 331] [Impact Index Per Article: 66.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 03/20/2020] [Accepted: 04/02/2020] [Indexed: 02/08/2023]
Abstract
BACKGROUND & AIMS Genetic factors associated with non-alcoholic fatty liver disease (NAFLD) remain incompletely understood. To date, most genome-wide association studies (GWASs) have adopted radiologically assessed hepatic triglyceride content as the reference phenotype and so cannot address steatohepatitis or fibrosis. We describe a GWAS encompassing the full spectrum of histologically characterised NAFLD. METHODS The GWAS involved 1,483 European NAFLD cases and 17,781 genetically matched controls. A replication cohort of 559 NAFLD cases and 945 controls was genotyped to confirm signals showing genome-wide or close to genome-wide significance. RESULTS Case-control analysis identified signals showing p values ≤5 × 10-8 at 4 locations (chromosome [chr] 2 GCKR/C2ORF16; chr4 HSD17B13; chr19 TM6SF2; chr22 PNPLA3) together with 2 other signals with p <1 × 10-7 (chr1 near LEPR and chr8 near IDO2/TC1). Case-only analysis of quantitative traits showed that the PNPLA3 signal (rs738409) had genome-wide significance for steatosis, fibrosis and NAFLD activity score and a new signal (PYGO1 rs62021874) had close to genome-wide significance for steatosis (p = 8.2 × 10-8). Subgroup case-control analysis for NASH confirmed the PNPLA3 signal. The chr1 LEPR single nucleotide polymorphism also showed genome-wide significance for this phenotype. Considering the subgroup with advanced fibrosis (≥F3), the signals on chr2, chr19 and chr22 maintained their genome-wide significance. Except for GCKR/C2ORF16, the genome-wide significance signals were replicated. CONCLUSIONS This study confirms PNPLA3 as a risk factor for the full histological spectrum of NAFLD at genome-wide significance levels, with important contributions from TM6SF2 and HSD17B13. PYGO1 is a novel steatosis modifier, suggesting that Wnt signalling pathways may be relevant in NAFLD pathogenesis. LAY SUMMARY Non-alcoholic fatty liver disease is a common disease where excessive fat accumulates in the liver and may result in cirrhosis. To understand who is at risk of developing this disease and suffering liver damage, we undertook a genetic study to compare the genetic profiles of people suffering from fatty liver disease with genetic profiles seen in the general population. We found that particular sequences in 4 different areas of the human genome were seen at different frequencies in the fatty liver disease cases. These sequences may help predict an individual's risk of developing advanced disease. Some genes where these sequences are located may also be good targets for future drug treatments.
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Liu Y, Kuang A, Talbot O, Bain JR, Muehlbauer MJ, Hayes MG, Ilkayeva OR, Lowe LP, Metzger BE, Newgard CB, Scholtens DM, Lowe WL. Metabolomic and genetic associations with insulin resistance in pregnancy. Diabetologia 2020; 63:1783-1795. [PMID: 32556615 PMCID: PMC7416451 DOI: 10.1007/s00125-020-05198-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 05/01/2020] [Indexed: 12/13/2022]
Abstract
AIMS/HYPOTHESIS Our study aimed to integrate maternal metabolic and genetic data related to insulin sensitivity during pregnancy to provide novel insights into mechanisms underlying pregnancy-induced insulin resistance. METHODS Fasting and 1 h serum samples were collected from women in the Hyperglycemia and Adverse Pregnancy Outcome study who underwent an OGTT at ∼28 weeks' gestation. We obtained targeted and non-targeted metabolomics and genome-wide association data from 1600 and 4528 mothers, respectively, in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai); 1412 of the women had both metabolomics and genome-wide association data. Insulin sensitivity was calculated using a modified insulin sensitivity index that included fasting and 1 h glucose and C-peptide levels after a 75 g glucose load. RESULTS Per-metabolite and network analyses across the four ancestries identified numerous metabolites associated with maternal insulin sensitivity before and 1 h after a glucose load, ranging from amino acids and carbohydrates to fatty acids and lipids. Genome-wide association analyses identified 12 genetic variants in the glucokinase regulatory protein gene locus that were significantly associated with maternal insulin sensitivity, including a common functional missense mutation, rs1260326 (β = -0.2004, p = 4.67 × 10-12 in a meta-analysis across the four ancestries). This SNP was also significantly associated with multiple fasting and 1 h metabolites during pregnancy, including fasting and 1 h triacylglycerols and 2-hydroxybutyrate and 1 h lactate, 2-ketoleucine/ketoisoleucine and palmitoleic acid. Mediation analysis suggested that 1 h palmitoleic acid contributes, in part, to the association of rs1260326 with maternal insulin sensitivity, explaining 13.7% (95% CI 4.0%, 23.3%) of the total effect. CONCLUSIONS/INTERPRETATION The present study demonstrates commonalities between metabolites and genetic variants associated with insulin sensitivity in the gravid and non-gravid states and provides insights into mechanisms underlying pregnancy-induced insulin resistance. Graphical abstract.
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Affiliation(s)
- Yu Liu
- Department of Medicine, Northwestern University Feinberg School of Medicine, Rubloff 12, 420 E. Superior St, Chicago, IL, 60611, USA
- Department of Endocrinology, South Campus, Renji Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Alan Kuang
- Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA
| | - Octavious Talbot
- Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA
| | - James R Bain
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Michael J Muehlbauer
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Durham, NC, USA
| | - M Geoffrey Hayes
- Department of Medicine, Northwestern University Feinberg School of Medicine, Rubloff 12, 420 E. Superior St, Chicago, IL, 60611, USA
| | - Olga R Ilkayeva
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Durham, NC, USA
| | - Lynn P Lowe
- Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA
| | - Boyd E Metzger
- Department of Medicine, Northwestern University Feinberg School of Medicine, Rubloff 12, 420 E. Superior St, Chicago, IL, 60611, USA
| | - Christopher B Newgard
- Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC, USA
- Duke Molecular Physiology Institute, Durham, NC, USA
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Denise M Scholtens
- Department of Preventive Medicine (Biostatistics), Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA.
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Rubloff 12, 420 E. Superior St, Chicago, IL, 60611, USA.
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Hannon BA, Edwards CG, Thompson SV, Reeser GE, Burd NA, Holscher HD, Teran-Garcia M, Khan NA. Single Nucleotide Polymorphisms Related to Lipoprotein Metabolism Are Associated with Blood Lipid Changes following Regular Avocado Intake in a Randomized Control Trial among Adults with Overweight and Obesity. J Nutr 2020; 150:1379-1387. [PMID: 32195538 DOI: 10.1093/jn/nxaa054] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 11/05/2019] [Accepted: 02/17/2020] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Avocados are rich in unsaturated fat and fiber; clinical trials have investigated their effects on metabolic disease. There is high variability in individual changes following avocado consumption, which may be in part due to individual genetic differences. OBJECTIVE Secondary analyses of the Persea americana for Total Health (PATH) Study were used to examine how single nucleotide polymorphisms (SNPs) impact blood lipid changes following a daily meal containing avocado compared with control. METHODS Adults (n = 115, 37% male) aged 25-45 y with overweight and obesity were randomly assigned to receive a daily isocaloric meal with (intervention) or without (control) a standardized amount (males: 175 g; females: 140 g) of avocado for 12 wk. Control meals were higher in saturated fat (17% of energy compared with 7%) and lower in fiber (4 g compared with 16 g) than intervention meals. Whole venous blood was taken at baseline and 12 wk to determine total cholesterol (TC), high-density lipoprotein (HDL) cholesterol, and triglyceride (TG) concentrations. Seventeen SNPs in 10 genes related to lipoprotein metabolism were genotyped. Effects of SNP, diet, and SNP-diet interactions were determined using general linear models. RESULTS No group-by-time effects were detected for changes in TC (P = 0.96), HDL cholesterol (P = 0.28), or TG (P = 0.06) over 12 wk. Three SNP-diet interactions were associated with final TC concentrations: ANGPTL3-rs10889337 (P = 0.01), ANGPTL4-rs2278236 (P = 0.02), and CD36-rs10499859 (P = 0.01). SNPs in GCKR and LPL were associated with TC changes (P = 0.01). The interaction between GCKR-rs1260326 and diet was such that C-homozygotes receiving avocado (n = 23) had final TC concentrations that were significantly lower than the C-homozygotes in the control group (n = 20) (P = 0.02). CONCLUSIONS Results from these exploratory analyses indicate that avocado consumption may help manage dyslipidemia in adults with overweight and obesity; however, effectiveness may differ by genetic profile. Understanding the role of genetic variation in variability following dietary intervention can potentially inform personalized nutrition recommendations.
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Affiliation(s)
- Bridget A Hannon
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Caitlyn G Edwards
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Sharon V Thompson
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ginger E Reeser
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Nicholas A Burd
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Hannah D Holscher
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Margarita Teran-Garcia
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Department of Human Development and Family Studies, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Naiman A Khan
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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39
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Abstract
Nonalcoholic fatty liver disease (NAFLD) is the most prevalent liver diseases and can progress to advanced fibrosis and end-stage liver disease. Thus, intensive research has been performed to develop noninvasive methods for the diagnosis of nonalcoholic steatohepatitis (NASH) and fibrosis. Currently, no single noninvasive tool covers all of the stages of pathologies and conditions of NAFLD, and the cost and feasibility of known techniques are also important issues. Blood biomarkers for NAFLD may be useful to select subjects who need ultrasonography (US) screening for NAFLD, and noninvasive tools for assessing fibrosis may be helpful to exclude the probability of significant fibrosis and to predict advanced fibrosis, thus guiding the decision of whether to perform liver biopsy in patients with NAFLD. Among various methods, magnetic resonance-based methods have been shown to perform better than other methods in assessing steatosis as well as in detecting hepatic fibrosis. Many genetic markers are associated with the development and progression of NAFLD. Further well-designed studies are needed to determine which biomarker panels, imaging studies, genetic marker panels, or combinations thereof perform well for diagnosing NAFLD, differentiating NASH and fibrosis, and following-up NAFLD, respectively.
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Affiliation(s)
- Dae Ho Lee
- Department of Internal Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
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Buziau AM, Schalkwijk CG, Stehouwer CDA, Tolan DR, Brouwers MCGJ. Recent advances in the pathogenesis of hereditary fructose intolerance: implications for its treatment and the understanding of fructose-induced non-alcoholic fatty liver disease. Cell Mol Life Sci 2020; 77:1709-1719. [PMID: 31713637 PMCID: PMC11105038 DOI: 10.1007/s00018-019-03348-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 10/02/2019] [Accepted: 10/16/2019] [Indexed: 12/31/2022]
Abstract
Hereditary fructose intolerance (HFI) is a rare inborn disease characterized by a deficiency in aldolase B, which catalyzes the cleavage of fructose 1,6-bisphosphate and fructose 1-phosphate (Fru 1P) to triose molecules. In patients with HFI, ingestion of fructose results in accumulation of Fru 1P and depletion of ATP, which are believed to cause symptoms, such as nausea, vomiting, hypoglycemia, and liver and kidney failure. These sequelae can be prevented by a fructose-restricted diet. Recent studies in aldolase B-deficient mice and HFI patients have provided more insight into the pathogenesis of HFI, in particular the liver phenotype. Both aldolase B-deficient mice (fed a very low fructose diet) and HFI patients (treated with a fructose-restricted diet) displayed greater intrahepatic fat content when compared to controls. The liver phenotype in aldolase B-deficient mice was prevented by reduction in intrahepatic Fru 1P concentrations by crossing these mice with mice deficient for ketohexokinase, the enzyme that catalyzes the synthesis of Fru 1P. These new findings not only provide a potential novel treatment for HFI, but lend insight into the pathogenesis of fructose-induced non-alcoholic fatty liver disease (NAFLD), which has raised to epidemic proportions in Western society. This narrative review summarizes the most recent advances in the pathogenesis of HFI and discusses the implications for the understanding and treatment of fructose-induced NAFLD.
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Affiliation(s)
- Amée M Buziau
- Division of Endocrinology, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Laboratory for Metabolism and Vascular Medicine, Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht, The Netherlands
| | - Casper G Schalkwijk
- Laboratory for Metabolism and Vascular Medicine, Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht, The Netherlands
| | - Coen D A Stehouwer
- Laboratory for Metabolism and Vascular Medicine, Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht, The Netherlands
- Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Dean R Tolan
- Department of Biology, Boston University, Boston, MA, USA.
| | - Martijn C G J Brouwers
- Division of Endocrinology, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.
- Laboratory for Metabolism and Vascular Medicine, Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht, The Netherlands.
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41
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Abstract
Hepatic glycogen synthesis plays a critical role in maintaining normal glucose homeostasis; however, the rate-controlling step regulating this process is unknown. Applying metabolic control analysis in vivo, we show that the regulation of insulin-stimulated hepatic glycogen synthesis under both normal and pathophysiological conditions of fatty liver-associated hepatic insulin resistance is controlled at the glucokinase (GCK) step through GCK translocation. Multiple insulin-regulated enzymes participate in hepatic glycogen synthesis, and the rate-controlling step responsible for insulin stimulation of glycogen synthesis is unknown. We demonstrate that glucokinase (GCK)-mediated glucose phosphorylation is the rate-controlling step in insulin-stimulated hepatic glycogen synthesis in vivo, by use of the somatostatin pancreatic clamp technique using [13C6]glucose with metabolic control analysis (MCA) in three rat models: 1) regular chow (RC)-fed male rats (control), 2) high fat diet (HFD)-fed rats, and 3) RC-fed rats with portal vein glucose delivery at a glucose infusion rate matched to the control. During hyperinsulinemia, hyperglycemia dose-dependently increased hepatic glycogen synthesis. At similar levels of hyperinsulinemia and hyperglycemia, HFD-fed rats exhibited a decrease and portal delivery rats exhibited an increase in hepatic glycogen synthesis via the direct pathway compared with controls. However, the strong correlation between liver glucose-6-phosphate concentration and net hepatic glycogen synthetic rate was nearly identical in these three groups, suggesting that the main difference between models is the activation of GCK. MCA yielded a high control coefficient for GCK in all three groups. We confirmed these findings in studies of hepatic GCK knockdown using an antisense oligonucleotide. Reduced liver glycogen synthesis in lipid-induced hepatic insulin resistance and increased glycogen synthesis during portal glucose infusion were explained by concordant changes in translocation of GCK. Taken together, these data indicate that the rate of insulin-stimulated hepatic glycogen synthesis is controlled chiefly through GCK translocation.
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Brouwers MCGJ, Simons N, Stehouwer CDA, Isaacs A. Non-alcoholic fatty liver disease and cardiovascular disease: assessing the evidence for causality. Diabetologia 2020; 63:253-260. [PMID: 31713012 PMCID: PMC6946734 DOI: 10.1007/s00125-019-05024-3] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 07/29/2019] [Indexed: 02/06/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is highly prevalent among individuals with type 2 diabetes. Although epidemiological studies have shown that NAFLD is associated with cardiovascular disease (CVD), it remains unknown whether NAFLD is an active contributor or an innocent bystander. Plasma lipids, low-grade inflammation, impaired fibrinolysis and hepatokines are potential mediators of the relationship between NAFLD and CVD. The Mendelian randomisation approach can help to make causal inferences. Studies that used common variants in PNPLA3, TM6SF2 and GCKR as instruments to investigate the relationship between NAFLD and coronary artery disease (CAD) have reported contrasting results. Variants in PNPLA3 and TM6SF2 were found to protect against CAD, whereas variants in GCKR were positively associated with CAD. Since all three genes have been associated with non-alcoholic steatohepatitis, the second stage of NAFLD, the question of whether low-grade inflammation is an important mediator of the relationship between NAFLD and CAD arises. In contrast, the differential effects of these genes on plasma lipids (i.e. lipid-lowering for PNPLA3 and TM6SF2, and lipid-raising for GCKR) strongly suggest that plasma lipids account for their differential effects on CAD risk. This concept has recently been confirmed in an extended set of 12 NAFLD susceptibility genes. From these studies it appears that plasma lipids are an important mediator between NAFLD and CVD risk. These findings have important clinical implications, particularly for the design of anti-NAFLD drugs that also affect lipid metabolism.
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Affiliation(s)
- Martijn C G J Brouwers
- Division of Endocrinology and Metabolic Disease, Department of Internal Medicine, Maastricht University Medical Centre, P. Debyelaan 25, 6229 HX, Maastricht, the Netherlands.
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands.
| | - Nynke Simons
- Division of Endocrinology and Metabolic Disease, Department of Internal Medicine, Maastricht University Medical Centre, P. Debyelaan 25, 6229 HX, Maastricht, the Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Laboratory for Metabolism and Vascular Medicine, Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Coen D A Stehouwer
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Division of General Internal Medicine, Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Aaron Isaacs
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
- Department of Biochemistry, Maastricht University, Maastricht, the Netherlands
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44
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Association between lncRNA and GCKR gene in type 2 diabetes mellitus. Clin Chim Acta 2019; 501:66-71. [PMID: 31756311 DOI: 10.1016/j.cca.2019.10.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 10/02/2019] [Accepted: 10/06/2019] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To screen long non-coding RNA (lncRNA) related to glucokinase regulatory protein gene (GCKR), its differential expression was analyzed in patients with Type 2 diabetes mellitus (T2DM) and control samples. The correlation of lncRNA with GCKR was verified and its potential value as a molecular marker of T2DM was assessed. METHODS Lymphocyte RNA was extracted from five patients with T2DM and five patients with non-T2DM. The expression profiles of circulating lncRNAs and mRNAs were obtained by microarray. Bioinformatics analysis was used to screen lncRNAs associated with the GCKR gene in 127 patients with T2DM and 130 patients with non-T2DM were selected. The expression levels of the GCKR gene and lncRNA (ENST00000588707.1 and TCONS_00004187) in the T2DM group and control group were verified by real-time PCR. Additionally, a correlation analysis was conducted. The value of circulating ENST00000588707.1 and TCONS_00004187 as biomarkers for the diagnosis of T2DM was performed by receiver operating characteristic curve analysis. RESULTS We identified 68 lncRNAs and 74 mRNAs differentially expressed from the expression profile. Compared with the control group, the expression levels of the GCKR gene and lncRNA ENST00000588707.1 and TCONS_00004187 in the T2DM group were significantly lower (P < 0.05). The correlation analysis revealed that ENST00000588707.1 and TCONS_00004187 were correlated with GCKR gene expression and glycolipid metabolism (P < 0.05). ROC analysis showed that the area under the curve value of ENST00000588707.1 between T2DM patients and non-T2DM patients was 0.816 (95% CI: 0.764-0.869, sensitivity 72.0%, specificity 80.3%) and the AUC value of TCONS_00004187 was 0.826 (95% CI: 0.774-0.879, sensitivity 81.6%, specificity 61.3%). CONCLUSION lncRNA ENST0000588707.1 and TCONS_00004187 could serve as potential biomarkers for T2DM, which could involve in glycolipid metabolism by regulating the GCKR gene.
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45
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Bloomgarden Z. Glucokinase and the potential of glucokinase activation in type 2 diabetes. J Diabetes 2019; 11:626-627. [PMID: 31013387 DOI: 10.1111/1753-0407.12937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Affiliation(s)
- Zachary Bloomgarden
- Department of Medicine, Division of Endocrinology, Diabetes, and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, New York
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46
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Sanghera DK, Hopkins R, Malone-Perez MW, Bejar C, Tan C, Mussa H, Whitby P, Fowler B, Rao CV, Fung KA, Lightfoot S, Frazer JK. Targeted sequencing of candidate genes of dyslipidemia in Punjabi Sikhs: Population-specific rare variants in GCKR promote ectopic fat deposition. PLoS One 2019; 14:e0211661. [PMID: 31369557 PMCID: PMC6675050 DOI: 10.1371/journal.pone.0211661] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 05/28/2019] [Indexed: 12/18/2022] Open
Abstract
Dyslipidemia is a well-established risk factor for cardiovascular diseases. Although, advances in genome-wide technologies have enabled the discovery of hundreds of genes associated with blood lipid phenotypes, most of the heritability remains unexplained. Here we performed targeted resequencing of 13 bona fide candidate genes of dyslipidemia to identify the underlying biological functions. We sequenced 940 Sikh subjects with extreme serum levels of hypertriglyceridemia (HTG) and 2,355 subjects were used for replication studies; all 3,295 participants were part of the Asian Indians Diabetic Heart Study. Gene-centric analysis revealed burden of variants for increasing HTG risk in GCKR (p = 2.1x10-5), LPL (p = 1.6x10-3) and MLXIPL (p = 1.6x10-2) genes. Of these, three missense and damaging variants within GCKR were further examined for functional consequences in vivo using a transgenic zebrafish model. All three mutations were South Asian population-specific and were largely absent in other multiethnic populations of Exome Aggregation Consortium. We built different transgenic models of human GCKR with and without mutations and analyzed the effects of dietary changes in vivo. Despite the short-term of feeding, profound phenotypic changes were apparent in hepatocyte histology and fat deposition associated with increased expression of GCKR in response to a high fat diet (HFD). Liver histology of the GCKRmut showed severe fatty metamorphosis which correlated with ~7 fold increase in the mRNA expression in the GCKRmut fish even in the absence of a high fat diet. These findings suggest that functionally disruptive GCKR variants not only increase the risk of HTG but may enhance ectopic lipid/fat storage defects in absence of obesity and HFD. To our knowledge, this is the first transgenic zebrafish model of a putative human disease gene built to accurately assess the influence of genetic changes and their phenotypic consequences in vivo.
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Affiliation(s)
- Dharambir K. Sanghera
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- Oklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
- Harold Hamm Diabetes Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Ruth Hopkins
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Megan W. Malone-Perez
- Department of Pediatrics, Section of Pediatric Hematology-Oncology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Cynthia Bejar
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Chengcheng Tan
- Department of Pediatrics, Section of Genetics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Huda Mussa
- Department of Pediatrics, Section of Infectious Diseases, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Paul Whitby
- Department of Pediatrics, Section of Infectious Diseases, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Ben Fowler
- Oklahoma Medical Research Foundation, Imaging Core Facility, Oklahoma City, Oklahoma, United States of America
| | - Chinthapally V. Rao
- Center for Cancer Prevention and Drug Development, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - KarMing A. Fung
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, Oklahoma, United States of America
| | - Stan Lightfoot
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, Oklahoma, United States of America
| | - J. Kimble Frazer
- Department of Pediatrics, Section of Pediatric Hematology-Oncology, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
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Fernandes Silva L, Vangipurapu J, Kuulasmaa T, Laakso M. An intronic variant in the GCKR gene is associated with multiple lipids. Sci Rep 2019; 9:10240. [PMID: 31308433 PMCID: PMC6629684 DOI: 10.1038/s41598-019-46750-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 07/02/2019] [Indexed: 12/25/2022] Open
Abstract
Previous studies have shown that an intronic variant rs780094 of the GCKR gene (glucokinase regulatory protein) is significantly associated with several metabolites, but the associations of this genetic variant with different lipids is largely unknown. Therefore, we applied metabolomics approach to measure metabolites in a large Finnish population sample (METSIM study) to investigate their associations with rs780094 of GCKR. We measured metabolites by mass spectrometry from 5,181 participants. P < 5.8 × 10-5 was considered as statistically significant given 857 metabolites included in statistical analyses. We found novel negative associations of the T allele of GCKR rs780094 with serine and threonine, and positive associations with two metabolites of tryptophan, indolelactate and N-acetyltryptophan. Additionally, we found novel significant positive associations of this genetic variant with 12 glycerolipids and 19 glycerophospholipids. Significant negative associations were found for three glycerophospholipids (all plasmalogen-cholines), and two sphingolipids. Significant novel associations were also found with gamma-glutamylthreonine, taurocholenate sulfate, and retinol. Our study adds new information about the pleiotropy of the GCKR gene, and shows the associations of the T allele of GCKR rs780094 with lipids.
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Affiliation(s)
- Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Teemu Kuulasmaa
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland.
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Chen H, Cai X, Xu A, Zhu L, Lu Y, Chen X, Liu S. Characterization of Glucokinase Catalysis from a Pseudo-Dimeric View. Appl Biochem Biotechnol 2019; 189:345-358. [PMID: 31011989 DOI: 10.1007/s12010-019-02998-z] [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] [Received: 12/13/2018] [Accepted: 03/27/2019] [Indexed: 11/30/2022]
Abstract
Glucose phosphorylation by glucokinase exhibits a sigmoidal dependency on substrate concentration regardless of its simple structure. Dimorph mechanism suggested the existence of two enzymatic states with different catalytic properties, which has been shown to be plausible by structural analysis. However, the dimorph mechanism gives rise to a complicated or non-explicit non-closed mathematical form. It is neither feasible to apply the dimorph mechanism in effector characterizations. To improve the area of glucokinase study with stronger theoretical support and less complication in computation, we proposed the investigation of the enzyme from a pseudo-dimeric angle. The proposed mechanism started from the idealization of two monomeric glucokinase as a dimeric complex, which significantly simplified the glucose phosphorylation kinetics, while the differences in enzyme reconfiguration caused by variable substrates and effectors have been successfully characterized. The study presented a simpler and more reliable way in studying the properties of glucokinase and its effectors, providing guidelines of effector developments for hyperglycemia and hypoglycemia treatment.
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Affiliation(s)
- Hanchi Chen
- Institution of Fermentation Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China.,Department of Paper and Bioprocess Engineering, State University of New York College of Environmental Science and Forestry, Syracuse, NY, 13210, USA
| | - Xiaoqing Cai
- Institution of Fermentation Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China
| | - Anjie Xu
- Institution of Fermentation Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China
| | - Linjiang Zhu
- Institution of Fermentation Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China
| | - Yuele Lu
- Institution of Fermentation Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China
| | - Xiaolong Chen
- Institution of Fermentation Engineering, Zhejiang University of Technology, Hangzhou, 310014, Zhejiang, China.
| | - Shijie Liu
- Department of Paper and Bioprocess Engineering, State University of New York College of Environmental Science and Forestry, Syracuse, NY, 13210, USA.
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López Rodríguez M, Fernandes Silva L, Vangipurapu J, Modi S, Kuusisto J, Kaikkonen MU, Laakso M. Functional Variant in the GCKR Gene Affects Lactate Levels Differentially in the Fasting State and During Hyperglycemia. Sci Rep 2018; 8:15989. [PMID: 30375486 PMCID: PMC6207693 DOI: 10.1038/s41598-018-34501-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 10/06/2018] [Indexed: 12/31/2022] Open
Abstract
The rs780094 single nucleotide polymorphism (SNP; C/T) of glucokinase regulatory protein gene (GCKR) is a regulatory genetic variant that has been associated with lactate levels in the fasting state. However, the association of this locus with lactate during hyperglycemia, and the mechanisms underlying these associations remain unknown. We investigated the association of rs780094 with lactate levels in a frequently sampled oral glucose tolerance test in humans and evaluated the effect of increasing GCKR expression on lactate production in liver cells. The C allele of rs780094 was associated with lower lactate levels in fasting but increased lactate level during hyperglycemia independently of insulin levels. Increased expression of GKRP induced higher lactate level in HepG2 cells and in human primary hepatocytes (HPH) upon glucose stimulation by increasing the amount of GCK. Glucagon induced the expression of GCKR in HepG2 and HPH cells. Our results suggest that the association of rs780094 with lactate levels may involve differential GCKR expression between the carriers of the C and T alleles.
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Affiliation(s)
- Maykel López Rodríguez
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Shalem Modi
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Kuopio University Hospital, P.O. Box 100 FI 70029 KYS, Kuopio, Finland
| | - Minna U Kaikkonen
- A.I. Virtanen Institute for Molecular Sciences, Department of Biotechnology and Molecular Medicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.
- Department of Medicine, Kuopio University Hospital, P.O. Box 100 FI 70029 KYS, Kuopio, Finland.
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50
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Association of common gene variants in glucokinase regulatory protein with cardiorenal disease: A systematic review and meta-analysis. PLoS One 2018; 13:e0206174. [PMID: 30352097 PMCID: PMC6198948 DOI: 10.1371/journal.pone.0206174] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 10/08/2018] [Indexed: 12/22/2022] Open
Abstract
Background Small-molecules that disrupt the binding between glucokinase and glucokinase regulatory protein (GKRP) in the liver represent a potential new class of glucose-lowering drugs. It will, however, take years before their effects on clinically relevant cardiovascular endpoints are known. The purpose of this study was to estimate the effects of these drugs on cardiorenal outcomes by studying variants in the GKRP gene (GCKR) that mimic glucokinase-GKRP disruptors. Methods The MEDLINE and EMBASE databases were searched for studies reporting on the association between GCKR variants (rs1260326, rs780094, and rs780093) and coronary artery disease (CAD), estimated glomerular filtration rate (eGFR), and chronic kidney disease (CKD). Results In total 5 CAD studies (n = 274,625 individuals), 7 eGFR studies (n = 195,195 individuals), and 4 CKD studies (n = 31,642 cases and n = 408,432 controls) were included. Meta-analysis revealed a significant association between GCKR variants and CAD (OR:1.02 per risk allele, 95%CI:1.00–1.04, p = 0.01). Sensitivity analyses showed that replacement of one large, influential CAD study by two other, partly overlapping studies resulted in similar point estimates, albeit less precise (OR:1.02; 95%CI:0.98–1.06 and OR: 1.02; 95%CI: 0.99–1.04). GCKR was associated with an improved eGFR (+0.49 ml/min, 95%CI:0.10–0.89, p = 0.01) and a trend towards protection from CKD (OR:0.98, 95%CI:0.95–1.01, p = 0.13). Conclusion This study suggests that increased glucokinase-GKRP disruption has beneficial effects on eGFR, but these may be offset by a disadvantageous effect on coronary artery disease risk. Further studies are warranted to elucidate the mechanistic link between hepatic glucose metabolism and eGFR.
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