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Taurbekova B, Mukhtarova K, Salpynov Z, Atageldiyeva K, Sarria-Santamera A. The impact of PPARγ and ApoE gene polymorphisms on susceptibility to diabetic kidney disease in type 2 diabetes mellitus: a meta-analysis. BMC Nephrol 2024; 25:436. [PMID: 39614174 PMCID: PMC11607899 DOI: 10.1186/s12882-024-03859-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2024] [Accepted: 11/14/2024] [Indexed: 12/01/2024] Open
Abstract
BACKGROUND Globally, diabetic kidney disease (DKD) has become the leading cause of end-stage renal disease, imposing substantial social and economic costs. This meta-analysis was designed to provide valuable insights into gene-disease interactions by investigating the potential association between lipid metabolism gene polymorphisms and the risk of DKD. METHODS An electronic literature search was conducted on MEDLINE Complete, Web of Science, Embase, and PubMed. A total of 18 studies on the peroxisome proliferator-activated receptor γ (PPARγ) Pro12Ala variant and 20 publications concerning apolipoprotein E (ApoE) gene polymorphism were included in the meta-analysis. RESULTS Overall, the PPARγ Pro12Ala polymorphism was found to be significantly associated with a decreased DKD risk (OR = 0.74, 95% CI: 0.62-0.88). In subgroup analysis, Ala carriers were less susceptible to DKD than Pro homozygotes among Asian (OR = 0.73, 95% CI: 0.56-0.95) and Caucasian populations (OR = 0.74, 95% CI: 0.59-0.93). Subgroup analysis stratified by albuminuria categories showed that the PPARγ Pro12Ala polymorphism reduced the risk of both microalbuminuria and macroalbuminuria with corresponding ORs of 0.58 (95% CI: 0.43-0.78) and 0.68 (95% CI: 0.53-0.86). Sensitivity analysis confirmed the robustness of the meta-analysis results. However, publication bias was identified in the subgroup analysis of the Caucasian population. The primary analysis of the ApoE gene polymorphism yielded significant findings, indicating that ApoE ε2/ε2, ApoE ε2/ε3, and ApoE ε2/ε4 genotypes increase the risk of DKD (ε2/ε2 vs. ε3/ε3: OR = 1.93, 95% CI: 1.03-3.61; ε2/ε3 vs. ε3/ε3: OR = 1.63, 95% CI: 1.19-2.25; ε2/ε4 vs. ε3/ε3: OR = 1.87, 95% CI: 1.37-2.55). However, sensitivity analysis suggested that influential and Hardy-Weinberg equilibrium (HWE)-violating studies may impact the overall effect estimates. CONCLUSIONS A meta-analysis showed that PPARγ gene polymorphism may be a protective factor for DKD, whereas the ApoE ε2/ε2, ApoE ε2/ε3, and ApoE ε2/ε4 genotypes are associated with an increased risk of DKD. However, the role of ApoE gene polymorphism in susceptibility to DKD is less certain and requires further evaluation.
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Affiliation(s)
- Binura Taurbekova
- Department of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, Kazakhstan.
- School of Medicine, Nazarbayev University, 5/1 Kerey and Zhanibek Khandar Str, Astana city, Republic of Kazakhstan.
| | - Kymbat Mukhtarova
- Department of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, Kazakhstan
| | - Zhandos Salpynov
- Department of Surgery, School of Medicine, Nazarbayev University, Astana, Kazakhstan
| | - Kuralay Atageldiyeva
- Department of Medicine, School of Medicine, Nazarbayev University, Astana, Kazakhstan
| | - Antonio Sarria-Santamera
- Department of Biomedical Sciences, School of Medicine, Nazarbayev University, Astana, Kazakhstan
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Lu J, Wang H, Chen X, Zhang K, Zhao X, Xiao Y, Yang F, Han M, Yuan W, Guo Y, Zhang Y. Exploration of potential antidiabetic and antioxidant components from the branches of Mitragyna diversifolia and possible mechanism. Biomed Pharmacother 2024; 180:117450. [PMID: 39312881 DOI: 10.1016/j.biopha.2024.117450] [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: 07/24/2024] [Revised: 09/07/2024] [Accepted: 09/19/2024] [Indexed: 09/25/2024] Open
Abstract
In this study, sixteen compounds were isolated from the branches of Mitragyna diversifolia, including twelve triterpenes (1-12), a phenolic compound (13), and three flavonoids (14-16). Among them, compounds 1-7, and 10-16 were reported for the first time from this plant. Compounds 7, 14, and 15 exhibited significant inhibitory activities against α-glucosidase, with IC50 values of 18.48 ± 2.74, 12.14 ± 1.58 and 35.77 ± 4.52 µM, respectively. Furthermore, the inhibitory kinetics of α-glucosidase revealed that all fractions, active compounds 7, 14, and 15 belong to the mix inhibition type. In molecular docking, the analysis showed that compounds 13, 14, 15, and 16 possessed superior binding capacities with α-glucosidase (-8.3, -9.6, -9.9, and -9.2 kcal/mol, respectively). The results of the glucose uptake experiment indicated that only compound 14 showed a significant promotion effect on the glucose uptake rate of 3T3-L1 adipocytes (P < 0.05). Meanwhile, compounds 13, 14, 15, and 16 possessed potent antioxidant abilities with DPPH, ABTS, and FRAP. In DNA and protein oxidative damage assays, compound 15 had a stronger effect than the positive control Vc. The network-based pharmacological analysis platform was used to predict the diabetes-related target proteins of active compounds 7, 13, 14, 15, and 16, and two candidate targets (ALB and PPARG) related to their therapeutic effects on diabetes were identified.
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Affiliation(s)
- Jing Lu
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hanlei Wang
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xuelin Chen
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
| | - Kun Zhang
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xia Zhao
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
| | - Yunxue Xiao
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
| | - Fengxian Yang
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
| | - Mei Han
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
| | - Wenyi Yuan
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuling Guo
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
| | - Yumei Zhang
- Key Laboratory of Tropical Plant Resource and Sustainable Use, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Zhao YK, Zhu XD, Liu R, Yang X, Liang YL, Wang Y. The Role of PPARγ Gene Polymorphisms, Gut Microbiota in Type 2 Diabetes: Current Progress and Future Prospects. Diabetes Metab Syndr Obes 2023; 16:3557-3566. [PMID: 37954888 PMCID: PMC10638901 DOI: 10.2147/dmso.s429825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023] Open
Abstract
Over the past decade, there has been a significant increase in studies investigating the relationship between the polymorphisms of the Peroxisome Proliferator-Activated Receptor gamma (PPARγ) gene and Type 2 Diabetes (T2D). PPARγ, a critical transcription factor, plays a central role in lipid metabolism, insulin resistance, and inflammatory response. Concurrently, the influence of gut microbiota on the development of T2D has gained increasing attention, especially their role in affecting host metabolism, such as lipid metabolism and the PPARγ signaling pathway. This review provides a comprehensive analysis of recent studies on PPARγ gene polymorphisms and their association with T2D, with a specific emphasis on the implications of gut microbiota and their interaction with PPARγ pathways. We also discuss the potential of manipulating gut microbiota and targeting PPARγ gene polymorphisms in T2D management. By deepening our understanding of these relationships, we aim to pave the way for novel preventative and therapeutic strategies for T2D.
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Affiliation(s)
- Yi-Kun Zhao
- Department of Basic Medical College, Gansu University of Chinese Medicine, Lanzhou City, People’s Republic of China
| | - Xiang-Dong Zhu
- Department of Traditional Chinese Medicine College, Ningxia Medical University, Yinchuan city, People’s Republic of China
| | - Rong Liu
- Department of Basic Medical College, Gansu University of Chinese Medicine, Lanzhou City, People’s Republic of China
| | - Xia Yang
- Department of Basic Medical College, Gansu University of Chinese Medicine, Lanzhou City, People’s Republic of China
| | - Yong-Lin Liang
- Department of Basic Medical College, Gansu University of Chinese Medicine, Lanzhou City, People’s Republic of China
| | - Yan Wang
- Department of Traditional Chinese Medicine College, Ningxia Medical University, Yinchuan city, People’s Republic of China
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Jang EJ, Lee DH, Im SS, Yee J, Gwak HS. Correlation between PPARG Pro12Ala Polymorphism and Therapeutic Responses to Thiazolidinediones in Patients with Type 2 Diabetes: A Meta-Analysis. Pharmaceutics 2023; 15:1778. [PMID: 37376225 PMCID: PMC10303709 DOI: 10.3390/pharmaceutics15061778] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/09/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
Background: Thiazolidinediones (TZDs) are a type of oral drug that are utilized for the treatment of type 2 diabetes mellitus (T2DM). They function by acting as agonists for a nuclear transcription factor known as peroxisome proliferator-activated receptor-gamma (PPAR-γ). TZDs, such as pioglitazone and rosiglitazone, help enhance the regulation of metabolism in individuals with T2DM by improving their sensitivity to insulin. Previous studies have suggested a relationship between the therapeutic efficacy of TZDs and the PPARG Pro12Ala polymorphism (C > G, rs1801282). However, the small sample sizes of these studies may limit their applicability in clinical settings. To address this limitation, we conducted a meta-analysis assessing the influence of the PPARG Pro12Ala polymorphism on the responsiveness of TZDs. Method: We registered our study protocol with PROSPERO, number CRD42022354577. We conducted a comprehensive search of the PubMed, Web of Science, and Embase databases, including studies published up to August 2022. We examined studies investigating the association between the PPARG Pro12Ala polymorphism and metabolic parameters such as hemoglobin A1C (HbA1C), fasting plasma glucose (FPG), triglyceride (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and total cholesterol (TC). The mean difference (MD) and 95% confidence intervals (CIs) between pre- and post-drug administration were evaluated. The quality of the studies included in the meta-analysis was assessed by using the Newcastle-Ottawa Scale (NOS) tool for cohort studies. Heterogeneity across studies was assessed by using the I2 value. An I2 value greater than 50% indicated substantial heterogeneity, and a random-effects model was used for meta-analysis. If the I2 value was below 50%, a fixed-effects model was employed instead. Both Begg's rank correlation test and Egger's regression test were performed to detect publication bias, using R Studio software. Results: Our meta-analysis incorporated 6 studies with 777 patients for blood glucose levels and 5 studies with 747 patients for lipid levels. The included studies were published between 2003 and 2016, with the majority involving Asian populations. Five of the six studies utilized pioglitazone, while the remaining study employed rosiglitazone. The quality scores, as assessed with the NOS, ranged from 8 to 9. Patients carrying the G allele exhibited a significantly greater reduction in HbA1C (MD = -0.3; 95% CI = -0.55 to -0.05; p = 0.02) and FPG (MD = -10.91; 95% CI = -19.82 to -2.01; p = 0.02) levels compared to those with the CC genotype. Furthermore, individuals with the G allele experienced a significantly larger decrease in TG levels than those with the CC genotype (MD = -26.88; 95% CI = -41.30 to -12.46; p = 0.0003). No statistically significant differences were observed in LDL (MD = 6.69; 95% CI = -0.90 to 14.29; p = 0.08), HDL (MD = 0.31; 95% CI = -1.62 to 2.23; p = 0.75), and TC (MD = 6.4; 95% CI = -0.05 to 12.84; p = 0.05) levels. No evidence of publication bias was detected based on Begg's test and Egger's test results. Conclusions: This meta-analysis reveals that patients with the Ala12 variant in the PPARG Pro12Ala polymorphism are more likely to exhibit positive responses to TZD treatment in terms of HbA1C, FPG, and TG levels compared to those with the Pro12/Pro12 genotype. These findings suggest that genotyping the PPARG Pro12Ala in diabetic patients may be advantageous for devising personalized treatment strategies, particularly for identifying individuals who are likely to respond favorably to TZDs.
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Affiliation(s)
- Eun Jeong Jang
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Republic of Korea; (E.J.J.); (D.H.L.); (J.Y.)
| | - Da Hoon Lee
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Republic of Korea; (E.J.J.); (D.H.L.); (J.Y.)
| | - Sae-Seul Im
- Graduate School of Clinical Biohealth, Ewha Womans University, Seoul 03760, Republic of Korea;
| | - Jeong Yee
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Republic of Korea; (E.J.J.); (D.H.L.); (J.Y.)
| | - Hye Sun Gwak
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Republic of Korea; (E.J.J.); (D.H.L.); (J.Y.)
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Yang AM, Lai TS, Lin YL, Wang C, Lin CY. Urinary di-(2-ethylhexyl) phthalate metabolites are independently related to serum neurofilament light chain, a biomarker of neurological diseases, in adults: results from NHANES 2013-2014. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:66417-66425. [PMID: 37097562 DOI: 10.1007/s11356-023-26943-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/07/2023] [Indexed: 05/17/2023]
Abstract
Di (2-ethylhexyl) phthalate (DEHP) is a chemical commonly used in the manufacturing of plastics and can pose human health risks, including endocrine disruption, reproductive toxicity, and potential carcinogenic effects. Children may be particularly vulnerable to the harmful effects of DEHP. Early exposure to DEHP has been linked to potential behavioral and learning problems. However, there are no reports to date on whether DEHP exposure in adulthood has neurotoxic effects. Serum neurofilament light chain (NfL), a protein released into the blood after neuroaxonal damage, has been shown to be a reliable biomarker for many neurological diseases. To date, no study has examined the relationship between DEHP exposure and NfL. For the present study, we selected 619 adults (aged ≥ 20 years) from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) to examine the association between urinary DEHP metabolites and serum NfL. We reported higher urinary levels of ln-mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), ln-mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), and ln-mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), and ln-ΣDEHP levels were associated with higher serum levels of ln-NfL (ΣDEHP: β-coefficient = 0. 075; S.E. = 0.026; P = 0.011). When we divided ΣDEHP into quartiles, mean NfL concentrations increased with quartiles of MEHHP (P for trend = 0.023). The association was more pronounced in males, non-Hispanic white race, higher income, and BMI < 25. In conclusion, higher DEHP exposure was positively associated with higher serum NfL in adults from NHANES 2013-2014. If this finding is causal, it is possible that DEHP exposure in adulthood may also induce neurological damage. Although the causality of this observation and the clinical significance are uncertain, our findings suggest that additional research is needed on DEHP exposure, serum NfL, and neurological disease in adults.
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Affiliation(s)
- An-Ming Yang
- Department of Internal Medicine, En Chu Kong Hospital, No. 399, Fuxing Rd., Sanxia Dist., New Taipei City, 237, Taiwan
- Department of Healthcare Management, Yuanpei University of Medical Technology, Hsinchu, 300, Taiwan
| | - Tai-Shuan Lai
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, 100, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, 100, Taiwan
| | - Yu-Ling Lin
- Department of Healthcare Management, Yuanpei University of Medical Technology, Hsinchu, 300, Taiwan
- Department of Nephrology, Hsinchu Cathay General Hospital, Hsinchu, 300, Taiwan
| | - ChiKang Wang
- Department of Environmental Engineering and Health, Yuanpei University of Medical Technology, Hsinchu, 300, Taiwan
| | - Chien-Yu Lin
- Department of Internal Medicine, En Chu Kong Hospital, No. 399, Fuxing Rd., Sanxia Dist., New Taipei City, 237, Taiwan.
- Department of Environmental Engineering and Health, Yuanpei University of Medical Technology, Hsinchu, 300, Taiwan.
- School of Medicine, Fu Jen Catholic University, New Taipei City, 242, Taiwan.
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The frequency of cytochrome 4F2 rs2108622 genetic variant and its effects on the lipid profile and complications of type II diabetes among a sample of patients in Jordan: A pilot study. Prostaglandins Other Lipid Mediat 2023; 165:106715. [PMID: 36758722 DOI: 10.1016/j.prostaglandins.2023.106715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 02/10/2023]
Abstract
BACKGROUND Cytochrome 4F2 (CYP4F2) is a major arachidonic acid-metabolizing enzyme which produces 20-Hydroxyeicosatetraenoic acid (20-HETE). It is found that 20-HETE is involved in the pathophysiology of many diseases, including diabetes mellitus. The genetic variants of CYP4F2 can affect its enzymatic activity as well as the 20-HETE production. AIMS Our aim with this paper was to find out the genotype frequency of CYP4F2 rs2108622 C>T, the major functional variant in the CYP4F2 gene, among a sample of type II diabetes (TIIDM) and its effects on diabetes complications and lipid profile. METHODS The CYP4F2 rs2108622 variant was genotyped among 90 healthy volunteers and 90 TIIDM patients that attending the University of Jordan Hospital, using the DNA Sanger sequencing method. The data of lipid profile and diabetes complications were obtained from the electronic records available in the hospital. RESULTS We found that the frequency of CYP4F2 rs2108622C>T variant is significantly (P = 0.02) lower among TIIDM patients in comparison to healthy subjects using both co-dominant and dominant genotyping models. In addition, the CYP4F2 rs2108622 T/T genotype was significantly (P = 0.02) more frequent among TIIDM patients with retinopathy complications (OR=4.36, CI: 1.32-14.37). Lastly, the CYP4F2 rs2108622C>T variant was not associated (P > 0.05) with the glycaemic and lipid profile of patients. CONCLUSIONS It can be concluded from this study that the frequency of CYP4F2 rs2108622 T/T genotype is lower among TIIDM, but this genotype is associated with an increased risk of retinopathy complications in patients of Jordanian origin. Further studies with a larger sample size are needed to validate the findings of this study.
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Vourdoumpa A, Paltoglou G, Charmandari E. The Genetic Basis of Childhood Obesity: A Systematic Review. Nutrients 2023; 15:1416. [PMID: 36986146 PMCID: PMC10058966 DOI: 10.3390/nu15061416] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/05/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Overweight and obesity in childhood and adolescence represents one of the most challenging public health problems of our century owing to its epidemic proportions and the associated significant morbidity, mortality, and increase in public health costs. The pathogenesis of polygenic obesity is multifactorial and is due to the interaction among genetic, epigenetic, and environmental factors. More than 1100 independent genetic loci associated with obesity traits have been currently identified, and there is great interest in the decoding of their biological functions and the gene-environment interaction. The present study aimed to systematically review the scientific evidence and to explore the relation of single-nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with changes in body mass index (BMI) and other measures of body composition in children and adolescents with obesity, as well as their response to lifestyle interventions. Twenty-seven studies were included in the qualitative synthesis, which consisted of 7928 overweight/obese children and adolescents at different stages of pubertal development who underwent multidisciplinary management. The effect of polymorphisms in 92 different genes was assessed and revealed SNPs in 24 genetic loci significantly associated with BMI and/or body composition change, which contribute to the complex metabolic imbalance of obesity, including the regulation of appetite and energy balance, the homeostasis of glucose, lipid, and adipose tissue, as well as their interactions. The decoding of the genetic and molecular/cellular pathophysiology of obesity and the gene-environment interactions, alongside with the individual genotype, will enable us to design targeted and personalized preventive and management interventions for obesity early in life.
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Affiliation(s)
- Aikaterini Vourdoumpa
- Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, ‘Aghia Sophia’ Children’s Hospital, 11527 Athens, Greece
| | - George Paltoglou
- Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, ‘Aghia Sophia’ Children’s Hospital, 11527 Athens, Greece
| | - Evangelia Charmandari
- Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens Medical School, ‘Aghia Sophia’ Children’s Hospital, 11527 Athens, Greece
- Division of Endocrinology and Metabolism, Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece
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Jan A, Ali S, Muhammad B, Arshad A, Shah Y, Bahadur H, Khan H, Khuda F, Akbar R, Ijaz K. Decoding type 2 diabetes mellitus genetic risk variants in Pakistani Pashtun ethnic population using the nascent whole exome sequencing and MassARRAY genotyping: A case-control association study. PLoS One 2023; 18:e0281070. [PMID: 36730981 PMCID: PMC9882913 DOI: 10.1371/journal.pone.0281070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 01/14/2023] [Indexed: 02/04/2023] Open
Abstract
Genome-wide association studies have greatly increased the number of T2DM associated risk variants but most of them have focused on populations of European origin. There is scarcity of such studies in developing countries including Pakistan. High prevalence of T2DM in Pakistani population prompted us to design this study. We have devised a two stage (the discovery stage and validation stage) case-control study in Pashtun ethnic population in which 500 T2DM cases and controls each have been recruited to investigate T2DM genetic risk variants. In discovery stage Whole Exome Sequencing (WES) was used to identify and suggest T2DM pathogenic SNPs, based on SIFT and Polyphen scores; whereas in validation stage the selected variants were confirmed for T2DM association using MassARRAY genotyping and appropriate statistical tests. Results of the study showed the target positive association of rs1801282/PPARG (OR = 1.24, 95%Cl = 1.20-1.46, P = 0.010), rs745975/HNF4A (OR = 1.30, 95%Cl = 1.06-1.38, P = 0.004), rs806052/GLIS3 (OR = 1.32, 95%Cl = 1.07-1.66, P = 0.016), rs8192552/MTNR1B (OR = 1.53, 95%Cl = 0.56-1.95, P = 0.012) and rs1805097/IRS-2 (OR = 1.27, 95%Cl = 1.36-1.92, P = 0.045), with T2DM; whereas rs6415788/GLIS3, rs61788900/NOTCH2, rs61788901/NOTCH2 and rs11810554/NOTCH2 (P>0.05) showed no significant association. Identification of genetic risk factors/variants can be used in defining high risk subjects assessment, and disease prevention.
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Affiliation(s)
- Asif Jan
- Department of Pharmacy, University of Peshawar, Peshawar, Pakistan
- * E-mail: (ZU); (AJ)
| | - Sajid Ali
- Department of Biotechnology, Abdul Wali Khan University, Mardan, Pakistan
| | - Basir Muhammad
- Atomic Energy Cancer Hospital, Swat Institute of Nuclear Medicine, Oncology & Radiotherapy, Swat, Pakistan
| | - Amina Arshad
- Rashid Latif College of Pharmacy, Lahore, Pakistan
| | - Yasar Shah
- Department of Pharmacy, Abdul Wali Khan University, Mardan, Pakistan
| | - Haji Bahadur
- Institute of Pharmaceutical Sciences, Khyber Medical University, Peshawar, Pakistan
| | - Hamayun Khan
- Department of Pharmacy, University of Peshawar, Peshawar, Pakistan
| | - Fazli Khuda
- Department of Pharmacy, University of Peshawar, Peshawar, Pakistan
| | - Rani Akbar
- Department of Pharmacy, Abdul Wali Khan University, Mardan, Pakistan
| | - Kiran Ijaz
- Institute of Pharmaceutical Sciences, Khyber Medical University, Peshawar, Pakistan
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Wong SK, Ramli FF, Ali A, Ibrahim N‘I. Genetics of Cholesterol-Related Genes in Metabolic Syndrome: A Review of Current Evidence. Biomedicines 2022; 10:biomedicines10123239. [PMID: 36551995 PMCID: PMC9775320 DOI: 10.3390/biomedicines10123239] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 12/15/2022] Open
Abstract
Metabolic syndrome (MetS) refers to a cluster of metabolic dysregulations, which include insulin resistance, obesity, atherogenic dyslipidemia and hypertension. The complex pathogenesis of MetS encompasses the interplay between environmental and genetic factors. Environmental factors such as excessive nutrients and sedentary lifestyle are modifiable and could be improved by lifestyle modification. However, genetic susceptibility to MetS, a non-modifiable factor, has attracted the attention of researchers, which could act as the basis for future diagnosis, prognosis, and therapy for MetS. Several cholesterol-related genes associated with each characteristic of MetS have been identified, such as apolipoprotein, lipoprotein lipase (LPL), cholesteryl ester transfer protein (CETP) and adiponectin. This review aims to summarize the genetic information of cholesterol-related genes in MetS, which may potentially serve as biomarkers for early prevention and management of MetS.
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Affiliation(s)
- Sok Kuan Wong
- Department of Pharmacology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras 56000, Kuala Lumpur, Malaysia
| | - Fitri Fareez Ramli
- Department of Pharmacology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras 56000, Kuala Lumpur, Malaysia
- Clinical Psychopharmacology Research Unit, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Adli Ali
- Department of Pediatrics, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras 56000, Kuala Lumpur, Malaysia
| | - Nurul ‘Izzah Ibrahim
- Department of Pharmacology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras 56000, Kuala Lumpur, Malaysia
- Correspondence: ; Tel.: +60-39145-9545
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Bai J, Ma Y, Zhao Y, Yang D, Mubarik S, Yu C. Mixed exposure to phenol, parabens, pesticides, and phthalates and insulin resistance in NHANES: A mixture approach. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158218. [PMID: 36028038 DOI: 10.1016/j.scitotenv.2022.158218] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/01/2022] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
PURPOSE The effects of environmental chemicals on insulin resistance have attracted extensive attention. Previous studies typically focused on the single chemical effects. This study adopted three different models to analyze the mixed effects of nine common chemicals (one phenol, two parabens, two chlorophenols and four phthalates) on insulin resistance. METHODS Urinary concentrations of chemicals were extracted from National Health and Nutrition Examination Survey (NHANES) 2009-2016. Insulin resistance was assessed using homeostatic model assessment (HOMA) and defined as HOMA-IR >2.6. The generalized linear regression (GLM), weighted quantile sum regression (WQS) and Bayesian kernel machine regression models (BKMR) were applied to assess the relationship between chemical mixture and HOMA-IR or insulin resistance. RESULTS Of the 2067 participants included, 872 (42.19 %) were identified as insulin resistant. In single-chemical GLM model, di-2-ethylhexyl phthalate (DEHP) had the highest parameter (β/OR, 95 % CIs) of 0.21 (quartile 4, 0.12- 0.29) and 1.95 (quartile 4, 1.39- 2.74). Similar results were observed in the multi-chemical models, with DEHP (quartile 4) showing the positive relationship with HOMA-IR (0.18, 0.08- 0.28) and insulin resistance (1.76, 1.17- 2.64). According to WQS models, the WQS indices were significantly positively correlated with both HOMA-IR (β: 0.07, 95 % CI: 0.03- 0.12) and insulin resistance (OR: 1.25, 95 % CI: 1.03- 1.53). DEHP was the top-weighted chemical positively correlated with both HOMA-IR and insulin resistance. In the BKMR model, the joint effect was also positively correlated with both outcomes. DEHP remained the main contributor to the joint effect, consistent with WQS analysis. CONCLUSION Our findings suggested that these chemical mixtures had the positive joint effects on both HOMA-IR and insulin resistance, with DEHP being the potentially predominant driver. The inter-validation of the three models may indicate that reducing the DEHP concentration could improve glucose homeostasis and reduce the risk of insulin resistance. However, further studies are recommended to deepen our findings and elucidate the mechanisms of insulin resistance and chemical mixture.
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Affiliation(s)
- Jianjun Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China
| | - Yudiyang Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China
| | - Yudi Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China
| | - Donghui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China
| | - Sumaira Mubarik
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China
| | - Chuanhua Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, 185# Donghu Road, Wuhan 430072, China; Global Health Institute, Wuhan University, 185# Donghu Road, Wuhan 430072, China.
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11
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Xie R, Tang S, Yang Y. Associations of peroxisome proliferator-activated receptor-γ Pro12Ala polymorphism with non-alcoholic fatty liver disease: A meta-analysis. J Diabetes Complications 2022; 36:108261. [PMID: 36055011 DOI: 10.1016/j.jdiacomp.2022.108261] [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: 05/19/2022] [Revised: 06/30/2022] [Accepted: 07/07/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Polymorphisms in peroxisome proliferator-activated receptor-γ pro12Ala (PPAR-γ Pro12Ala) have been associated with Non-alcoholic Fatty Liver Disease (NAFLD) in several studies. However, the results of these studies are not entirely consistent. Thus, we performed a meta-analysis to investigate the association between the PPAR-γ Pro12Ala polymorphisms and NAFLD. METHODS Studies were identified by searching PubMed database and manual assessment of the cited references in the retrieved articles. Study-specific relative risks (RRs) and 95 % confidence intervals (CIs) were estimated using a random-effect model. Study quality was assessed using the Newcastle-Ottawa scale. RESULTS Relevant medical researches show that 11 studies have been conducted on the analysis of NAFLD for meta-analysis, with a total of 2404 cases and 3959 participating controls. Meta-analysis results show that PPAR-γ Pro12Ala polymorphism and NALAD Ala alleles[no association between dominance model (OR = 0.968, 95%CI: 0.734-1.276, P = 0.815); Pro/Ala vs. Pro/Pro (OR = 0.930, 95 % CI: 0.701-1.233, P = 0.612); Ala/Ala vs. Pro/Pro (OR = 1.220, 95 % CI: 0.668-2.230, P = 0.518); recessive model (OR = 0.907, 95 % CI: 0.516-1.596, P = 0.736)]. Moreover, stratification by ethnicity also revealed that no matter it is in Caucasian populations or in Asian populations, NAFLD has no association with the PPAR-γ Pro12Ala polymorphism. CONCLUSIONS According to the meta-analysis, both in Asians and Caucasian populations, the PPAR-γ Pro12Ala polymorphism can't be demonstrated to have any link with susceptibility to NAFLD.
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Affiliation(s)
- Rong Xie
- The Gastroenterology Department of the First Hospital of Nanning, Nanning, Guangxi Province 530022, PR China
| | - Shaobo Tang
- The Gastroenterology Department of the First Hospital of Nanning, Nanning, Guangxi Province 530022, PR China.
| | - Yanna Yang
- The Ultrasonography of Maternal and Children Health Hospital of Guangxi, Guangxi Province 530022, PR China
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12
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Prasad M, Rajagopal P, Devarajan N, Veeraraghavan VP, Palanisamy CP, Cui B, Patil S, Jayaraman S. A comprehensive review on high fat diet-induced diabetes mellitus: An epigenetic view. J Nutr Biochem 2022; 107:109037. [PMID: 35533900 DOI: 10.1016/j.jnutbio.2022.109037] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 01/08/2022] [Accepted: 03/21/2022] [Indexed: 12/12/2022]
Abstract
Modern lifestyle, genetics, nutritional overload through high-fat diet attributed prevalence and diabetes outcomes with various complications primarily due to obesity in which energy-dense diets frequently affect metabolic health. One possible issue usually associated with elevated chronic fat intake is insulin resistance, and hyperglycaemia constitutes an important function in altering the carbohydrates and lipids metabolism. Similarly, in assessing human susceptibility to weight gain and obesity, genetic variations play a central role, contributing to keen interest in identifying the possible role of epigenetics as a mediator of gene-environmental interactions influencing the production of type 2 diabetes mellitus and its related concerns. Epigenetic modifications associated with the acceptance of a sedentary lifestyle and environmental stress factors in response to energy intake and expenditure imbalances complement genetic alterations and lead to the production and advancement of metabolic disorders such as diabetes and obesity. Methylation of DNA, histone modifications and increases in the expression of non-coding RNAs can result in reduced transcriptional activity of key β-cell genes thus creating insulin resistance. Epigenetics contribute to changes in the expression of the underlying insulin resistance and insufficiency gene networks, along with low-grade obesity-related inflammation, increased ROS generation and DNA damage in multi organs. This review focused on epigenetic mechanisms and metabolic regulations associated with high fat diet (HFD)-induced diabetes mellitus.
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Affiliation(s)
- Monisha Prasad
- Centre for Molecular Medicine and diagnostic (CoMManD), Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600 077, India
| | - Ponnulakshmi Rajagopal
- Central Research Laboratory, Meenakhsi Ammal Dental College and Hospitals, Academy of Higher Education and Research, Chennai, 600 095, India
| | - Nalini Devarajan
- Central Research Laboratory, Meenakhsi Academy of Higher Education and Research, West K.K. Nagar, Chennai, 600 078, India
| | - Vishnu Priya Veeraraghavan
- State Key Laboratory of Biobased Materials and Green Papermaking, College of Food Science and Engineering, Qilu University of Technology, Shandong Academy of Science, Jinan, 250353, China
| | - Chella Perumal Palanisamy
- State Key Laboratory of Biobased Materials and Green Papermaking, College of Food Science and Engineering, Qilu University of Technology, Shandong Academy of Science, Jinan, 250353, China
| | - Bo Cui
- State Key Laboratory of Biobased Materials and Green Papermaking, College of Food Science and Engineering, Qilu University of Technology, Shandong Academy of Science, Jinan, 250353, China
| | - Shankargouda Patil
- Department of Maxillofacial Surgery and Diagnostic Sciences, Division of Oral Pathology, College of Dentistry, Jazan University, Saudi Arabia
| | - Selvaraj Jayaraman
- Centre for Molecular Medicine and diagnostic (CoMManD), Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600 077, India.
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13
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Marcos-Pasero H, Aguilar-Aguilar E, de la Iglesia R, Espinosa-Salinas I, Molina S, Colmenarejo G, Martínez JA, Ramírez de Molina A, Reglero G, Loria-Kohen V. "GENYAL" Study to Childhood Obesity Prevention: Methodology and Preliminary Results. Front Nutr 2022; 9:777384. [PMID: 35350411 PMCID: PMC8957940 DOI: 10.3389/fnut.2022.777384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 02/04/2022] [Indexed: 11/13/2022] Open
Abstract
Objective This article describes the methodology and summarizes some preliminary results of the GENYAL study aiming to design and validate a predictive model, considering both environmental and genetic factors, that identifies children who would benefit most from actions aimed at reducing the risk of obesity and its complications. Design The study is a cluster randomized clinical trial with 5-year follow-up. The initial evaluation was carried out in 2017. The schools were randomly split into intervention (nutritional education) and control schools. Anthropometric measurements, social and health as well as dietary and physical activity data of schoolchildren and their families are annually collected. A total of 26 single nucleotide polymorphisms (SNPs) were assessed. Machine Learning models are being designed to predict obesity phenotypes after the 5-year follow-up. Settings Six schools in Madrid. Participants A total of 221 schoolchildren (6-8 years old). Results Collected results show that the prevalence of excess weight was 19.0, 25.4, and 32.2% (according to World Health Organization, International Obesity Task Force and Orbegozo Foundation criteria, respectively). Associations between the nutritional state of children with mother BMI [β = 0.21 (0.13-0.3), p (adjusted) <0.001], geographical location of the school [OR = 2.74 (1.24-6.22), p (adjusted) = 0.06], dairy servings per day [OR = 0.48 (0.29-0.75), p (adjusted) = 0.05] and 8 SNPs [rs1260326, rs780094, rs10913469, rs328, rs7647305, rs3101336, rs2568958, rs925946; p (not adjusted) <0.05] were found. Conclusions These baseline data support the evidence that environmental and genetic factors play a role in the development of childhood obesity. After 5-year follow-up, the GENYAL study pretends to validate the predictive model as a new strategy to fight against obesity. Clinical Trial Registration This study has been registered in ClinicalTrials.gov with the identifier NCT03419520, https://clinicaltrials.gov/ct2/show/NCT03419520.
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Affiliation(s)
- Helena Marcos-Pasero
- Nutrition and Clinical Trials Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
- Faculty of Health Sciences, Valencian International University (VIU), Valencia, Spain
| | - Elena Aguilar-Aguilar
- Nutrition and Clinical Trials Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Rocío de la Iglesia
- Departamento de Ciencias Farmaceúticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Isabel Espinosa-Salinas
- Nutritional Genomics and Health Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Susana Molina
- GenyalLab, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Gonzalo Colmenarejo
- Biostatistics and Bioinformatics Unit, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - J. Alfredo Martínez
- Precision Nutrition and Cardiometabolic Health, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
- IdisNA, Navarra Institute for Health Research, Pamplona, Spain
- Center of Biomedical Research in Physiopathology of Obesity and Nutrition, Institute of Health Carlos III, Madrid, Spain
| | - Ana Ramírez de Molina
- Molecular Oncology and Nutritional Genomics of Cancer, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Guillermo Reglero
- Production and Development of Foods for Health, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
- Department of Production and Characterization of Novel Foods, Institute of Food Science Research (CIAL), CEI UAM+CSIC, Madrid, Spain
| | - Viviana Loria-Kohen
- Nutrition and Clinical Trials Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
- Departamento de Nutrición y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, Grupo de Investigación VALORNUT-UCM, Madrid, Spain
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Vales-Villamarín C, de Dios O, Pérez-Nadador I, Gavela-Pérez T, Soriano-Guillén L, Garcés C. PPARγ2 Pro12Ala Polymorphism is Associated in Children With Traits Related to Susceptibility to Type 2 Diabetes. Front Pharmacol 2021; 12:763853. [PMID: 34887761 PMCID: PMC8650059 DOI: 10.3389/fphar.2021.763853] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 11/10/2021] [Indexed: 12/16/2022] Open
Abstract
Peroxisome proliferator-activated receptor gamma (PPARγ) is a ligand-activated nuclear receptor that regulates glucose and lipid metabolism. Pharmacological activators of PPARγ are being used as a treatment of obesity related disorders such as dyslipidaemia and type 2 diabetes, but questions remain open regarding the effects of PPARγ on traits related to the development of type 2 diabetes. In our study, we have analyzed the relationship of the common variant Pro12Ala in the human PPARγ2 gene with the presence of obesity and with insulin, HOMA and lipid profile in a representative sample of 6-to 8-year-old children free from the confounding factors associated with adults. We found that Ala12Ala genotype was significantly more frequent in females with obesity than in those without obesity, with Ala12Ala carriers having significantly higher weight and body mass index (BMI), however the association disappeared when adjusting by leptin concentrations. The Ala12Ala genotype was associated with significantly higher HDL-cholesterol and apoA-I levels in males but not in females, independently of BMI. In a recessive model, in females, leptin levels appeared higher in Ala12Ala carriers. Although no apparent differences were observed in any sex when analyzing insulin levels and HOMA among genotypes without adjusting, lower insulin levels and lower HOMA appeared associated with Ala12Ala carriers when adjusting for BMI and leptin levels. In summary, our data showed that leptin seems to be having an effect on the association between the PPARγ2 Pro12Ala and BMI. Besides, after controlling for BMI and leptin, a protective effect of the Ala12Ala variant of the PPARγ2 Pro12Ala polymorphism on insulin sensitivity is evident already in prepubertal children.
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Affiliation(s)
| | - Olaya de Dios
- Lipid Research Laboratory, IIS-Fundación Jiménez Díaz UAM, Madrid, Spain
| | - Iris Pérez-Nadador
- Lipid Research Laboratory, IIS-Fundación Jiménez Díaz UAM, Madrid, Spain
| | | | | | - Carmen Garcés
- Lipid Research Laboratory, IIS-Fundación Jiménez Díaz UAM, Madrid, Spain
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15
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Ahluwalia MK. Nutrigenetics and nutrigenomics-A personalized approach to nutrition. ADVANCES IN GENETICS 2021; 108:277-340. [PMID: 34844714 DOI: 10.1016/bs.adgen.2021.08.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The prevalence of non-communicable diseases has been on an upward trajectory for some time and this puts an enormous burden on the healthcare expenditure. Lifestyle modifications including dietary interventions hold an immense promise to manage and prevent these diseases. Recent advances in genomic research provide evidence that focussing these efforts on individual variations in abilities to metabolize nutrients (nutrigenetics) and exploring the role of dietary compounds on gene expression (nutrigenomics and nutri-epigenomics) can lead to more meaningful personalized dietary strategies to promote optimal health. This chapter aims to provide examples on these gene-diet interactions at multiple levels to support the need of embedding targeted dietary interventions as a way forward to prevent, avoid and manage diseases.
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Peroxisome Proliferator-Activated Receptor Gamma Pro12Ala/C161T Genotypes and Risky Haplotype Altering Risk of Breast Cancer: A Turkish Case-Control Study. Biochem Genet 2021; 59:1413-1426. [PMID: 33893920 DOI: 10.1007/s10528-021-10068-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 04/06/2021] [Indexed: 01/26/2023]
Abstract
Breast cancer (BC) has a high incidence rate among women worldwide, and the mechanisms and etiology of this disease are not yet fully understood. The peroxisome proliferator-activated receptor gamma (PPARgamma), a nuclear hormone receptor that plays important roles in energy metabolism and cellular differentiation, is also suggested to be effective in cancer development. However, the results of studies investigating the cancer association with PPARgamma are inconsistent, creating a need for further investigation of the effects of this transcription factor on BC risk. We have examined the Pro12Ala-(rs1801282) and C161T-(rs3856806) polymorphisms of the PPARgamma gene in Turkish patients with BC in this case-control study. A total of 95 women diagnosed with BC as cases and 119 controls were genotyped for PPARgamma polymorphisms by polymerase chain reaction and restriction fragment length polymorphism techniques. The ProPro genotype and T161 allele were associated with an increased risk of BC comparing with the Ala12 allele and CC161 genotype, respectively (p < 0.001). The multivariate regression analysis confirmed that the ProPro genotype (p < 0.011), T161 allele (p < 0.001), smoking (p = 0.019), and advanced age (> 60 years) (p = 0.007) are risk factors for breast cancer. We also found that the PPARgamma Pro12Ala and C161T polymorphisms were in linkage disequilibrium (D':0.511, r2:0.099). It was determined that carrying ProPro-T161 risky PPARgamma haplotype was associated with a higher risk of BC compared to protective Ala12-CC161 haplotype (p < 0.01, OR:7.797, 95% CI:3.521-17.263). We concluded that PPARgamma Pro12Ala and C161T polymorphisms are associated with increased BC risk, and ProPro-T161 risky haplotype, which is in linkage disequilibrium, increases this effect.
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Cataldi S, Costa V, Ciccodicola A, Aprile M. PPARγ and Diabetes: Beyond the Genome and Towards Personalized Medicine. Curr Diab Rep 2021; 21:18. [PMID: 33866450 DOI: 10.1007/s11892-021-01385-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/25/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE OF REVIEW Full and partial synthetic agonists targeting the transcription factor PPARγ are contained in FDA-approved insulin-sensitizing drugs and used for the treatment of metabolic syndrome-related dysfunctions. Here, we discuss the association between PPARG genetic variants and drug efficacy, as well as the role of alternative splicing and post-translational modifications as contributors to the complexity of PPARγ signaling and to the effects of synthetic PPARγ ligands. RECENT FINDINGS PPARγ regulates the transcription of several target genes governing adipocyte differentiation and glucose and lipid metabolism, as well as insulin sensitivity and inflammatory pathways. These pleiotropic functions confer great relevance to PPARγ in physiological regulation of whole-body metabolism, as well as in the etiology of metabolic disorders. Accordingly, PPARG gene mutations, nucleotide variations, and post-translational modifications have been associated with adipose tissue disorders and the related risk of insulin resistance and type 2 diabetes (T2D). Moreover, PPARγ alternative splicing isoforms-generating dominant-negative isoforms mainly expressed in human adipose tissue-have been related to impaired PPARγ activity and adipose tissue dysfunctions. Thus, multiple regulatory levels that contribute to PPARγ signaling complexity may account for the beneficial as well as adverse effects of PPARγ agonists. Further targeted analyses, taking into account all these aspects, are needed for better deciphering the role of PPARγ in human pathophysiology, especially in insulin resistance and T2D. The therapeutic potential of full and partial PPARγ synthetic agonists underlines the clinical significance of this nuclear receptor. PPARG mutations, polymorphisms, alternative splicing isoforms, and post-translational modifications may contribute to the pathogenesis of metabolic disorders, also influencing the responsiveness of pharmacological therapy. Therefore, in the context of the current evidence-based trend to personalized diabetes management, we highlight the need to decipher the intricate regulation of PPARγ signaling to pave the way to tailored therapies in patients with insulin resistance and T2D.
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Affiliation(s)
- Simona Cataldi
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", CNR, Via P. Castellino 111, 80131, Naples, Italy
| | - Valerio Costa
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", CNR, Via P. Castellino 111, 80131, Naples, Italy
| | - Alfredo Ciccodicola
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", CNR, Via P. Castellino 111, 80131, Naples, Italy.
- Department of Science and Technology, University of Naples "Parthenope", 80131, Naples, Italy.
| | - Marianna Aprile
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", CNR, Via P. Castellino 111, 80131, Naples, Italy
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Cardiolipin-mediated PPARγ S112 phosphorylation impairs IL-10 production and inflammation resolution during bacterial pneumonia. Cell Rep 2021; 34:108736. [PMID: 33567272 PMCID: PMC7947928 DOI: 10.1016/j.celrep.2021.108736] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 12/17/2020] [Accepted: 01/20/2021] [Indexed: 12/20/2022] Open
Abstract
Bacterial pneumonia is a global healthcare burden, and unwarranted inflammation is suggested as an important cause of mortality. Optimum levels of the anti-inflammatory cytokine IL-10 are essential to reduce inflammation and improve survival in pneumonia. Elevated levels of the mitochondrial-DAMP cardiolipin (CL), reported in tracheal aspirates of pneumonia patients, have been shown to block IL-10 production from lung MDSCs. Although CL-mediated K107 SUMOylation of PPARγ has been suggested to impair this IL-10 production, the mechanism remains elusive. We identify PIAS2 to be the specific E3-SUMOligase responsible for this SUMOylation. Moreover, we identify a concomitant CL-mediated PPARγ S112 phosphorylation, mediated by JNK-MAPK, to be essential for PIAS2 recruitment. Furthermore, using a clinically tested peptide inhibitor targeting JNK-MAPK, we blocked these post-translational modifications (PTMs) of PPARγ and rescued IL-10 expression, improving survival in murine pneumonia models. Thus, we explore the mechanism of mito-DAMP-mediated impaired lung inflammation resolution and propose a therapeutic strategy targeting PPARγ PTMs.
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Matsunaga T, Naito M, Yin G, Hishida A, Okada R, Kawai S, Sasakabe T, Kadomatsu Y, Tsukamoto M, Kubo Y, Tamura T, Takeuchi K, Mori A, Hamajima N, Wakai K. Associations between peroxisome proliferator-activated receptor γ (PPAR-γ) polymorphisms and serum lipids: Two cross-sectional studies of community-dwelling adults. Gene 2020; 762:145019. [PMID: 32755657 DOI: 10.1016/j.gene.2020.145019] [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: 04/16/2020] [Revised: 07/07/2020] [Accepted: 07/30/2020] [Indexed: 12/11/2022]
Abstract
Dyslipidemia is a well-established risk factor for cardiovascular disease. Experimental studies have reported that peroxisome proliferator-activated receptor γ (PPAR-γ) regulates adipocyte differentiation, lipid storage, and glucose metabolism. Therefore, we examined the associations between PPAR-γ polymorphisms (rs1801282, rs3856806, rs12497191, rs1151999, and rs1152003) and serum lipids in two cross-sectional studies. In the Shizuoka area of the Japan Multi-Institutional Collaborative Cohort Study, we examined 4,952 participants (3,356 men and 1,596 women) in a baseline survey and 2,245 participants (1,550 men and 695 women) in a second survey 5 years later. Outcome measures were the prevalence of dyslipidemia (low-density lipoprotein-cholesterol [LDL-C] ≥ 140 mg/dl, high-density lipoprotein-cholesterol < 40 mg/dl, triglycerides ≥ 150 mg/dl, and/or use of cholesterol-lowering drugs) and the prevalence of high LDL-C (LDL-C ≥ 140 mg/dl and/or use of cholesterol-lowering drugs). Multivariate odds ratios (ORs) were estimated by using unconditional logistic regression models. A total of 2,114 and 1,431 individuals (42.7% and 28.9%) had dyslipidemia and high LDL-C in the baseline survey, respectively, as did 933 and 716 (41.6% and 31.9%), respectively, in the second survey. In the baseline study, compared with major allele homozygotes, minor allele homozygotes of rs3856806 and rs12497191 had a 42% (OR, 0.58; 95% confidence interval (CI), 0.39-0.85) and 23% (OR, 0.77; 95% CI, 0.60-0.99) lower risk of dyslipidemia, respectively, after adjustment for potential confounding factors. In addition, minor allele homozygotes of rs3856806 had a 45% (OR, 0.55; 95% CI, 0.35-0.86) lower risk of high LDL-C. Similar risk reductions were found in the second survey. In conclusion, rs3856806 and rs12497191 polymorphisms may be related to a lower risk of dyslipidemia and high LDL-C.
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Affiliation(s)
- Takashi Matsunaga
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan; Department of Oral Epidemiology, Hiroshima University Graduate School of Biomedical and Health Sciences, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8553, Japan
| | - Guang Yin
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan; Department of Nutritional Sciences, Faculty of Health and Welfare, Seinan Jo Gakuin University, 1-3-5 Ibori, Kokura Kita-ku, Kitakyushu, Fukuoka 803-0835, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan; Department of Public Health, Aichi Medical University, Nagakute 480-1195, Japan
| | - Tae Sasakabe
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan; Department of Public Health, Aichi Medical University, Nagakute 480-1195, Japan
| | - Yuka Kadomatsu
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Mineko Tsukamoto
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Yoko Kubo
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Takashi Tamura
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kenji Takeuchi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Atsuyoshi Mori
- Seirei Preventive Health Care Center, 3453-1 Mikatahara-cho, Kita-ku, Hamamatsu 433-8558, Japan
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan
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20
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García-Ricobaraza M, García-Bermúdez M, Torres-Espinola FJ, Segura Moreno MT, Bleyere MN, Díaz-Prieto LE, Nova E, Marcos A, Campoy C. Association study of rs1801282 PPARG gene polymorphism and immune cells and cytokine levels in a Spanish pregnant women cohort and their offspring. J Biomed Sci 2020; 27:101. [PMID: 33250050 PMCID: PMC7702670 DOI: 10.1186/s12929-020-00694-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 11/12/2020] [Indexed: 12/20/2022] Open
Abstract
Background Peroxisome proliferator activated receptor gamma (PPARG) belongs to the nuclear receptor superfamily functioning as transcription factors to regulate cellular differentiation, development and metabolism. Moreover, it has been implicated in the regulation of lipid metabolism, as well as the maturation of monocytes/macrophages and the control of inflammatory reactions. The aim of this study was to evaluate the relationship between the Pro12Ala (rs1808212) PPARG gene polymorphism on immune molecular and cellular components in mothers and their offspring participating in the PREOBE study. Methods DNA from maternal venous blood samples at 24, 34 and 40 gestational weeks, plus cord blood samples was extracted. Pro12Ala PPARG polymorphism genotyping was performed, and immune system markers were analyzed by flow cytometry. Results Study findings revealed no effect of rs1808212 PPARG genotypes on innate immune parameters in mothers and their offspring; however, CD4 + /CD8 + ratio were decreased at 24 and 34 weeks in pregnant women carrying the CG (Pro12Ala) rs1808212 polymorphism, (p = 0,012 and p = 0,030; respectively). Only CD19 levels in peripheral blood were significantly higher at delivery in pregnant women carrying the CC (Pro12Pro) genotype (p ≤ 0.001). Moreover, there were statistically significant differences in leukocytes and neutrophils maternal levels at 34 weeks of gestation, being lower in carriers of Pro12Ala genotype (p = 0.028 and p = 0.031, respectively). Conclusions Results suggest that Pro12Ala PPARG polymorphism may have an effect on some cell and immune parameters in pregnant women during pregnancy and at time of delivery. However, newborn innate immune system does not seems to be influenced by PPARG Pro12Ala polymorphism in cord blood.
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Affiliation(s)
- Maria García-Ricobaraza
- Department of Paediatrics, School of Medicine, Universidad de Granada, Granada, Spain.,Instituto de Investigación Biosanitaria ibsGRANADA, Health Sciences Technological Park, Granada, Spain
| | - Mercedes García-Bermúdez
- Department of Paediatrics, School of Medicine, Universidad de Granada, Granada, Spain. .,Instituto de Investigación Biosanitaria ibsGRANADA, Health Sciences Technological Park, Granada, Spain.
| | - Francisco J Torres-Espinola
- Department of Paediatrics, School of Medicine, Universidad de Granada, Granada, Spain.,EURISTIKOS Excellence Centre for Paediatric Research, Universidad de Granada, Granada, Spain
| | - M Teresa Segura Moreno
- Department of Paediatrics, School of Medicine, Universidad de Granada, Granada, Spain.,Instituto de Investigación Biosanitaria ibsGRANADA, Health Sciences Technological Park, Granada, Spain
| | - Mathieu N Bleyere
- Department of Physiology, Haematology and Immunology, Nangui Abrogoua University, Abidjan, Côte d'Ivoire
| | - Ligia E Díaz-Prieto
- Institute of Food Science, Technology and Nutrition (ICTAN), CSIC, Madrid, Spain
| | - Esther Nova
- Institute of Food Science, Technology and Nutrition (ICTAN), CSIC, Madrid, Spain
| | - Ascensión Marcos
- Institute of Food Science, Technology and Nutrition (ICTAN), CSIC, Madrid, Spain
| | - Cristina Campoy
- Department of Paediatrics, School of Medicine, Universidad de Granada, Granada, Spain. .,Instituto de Investigación Biosanitaria ibsGRANADA, Health Sciences Technological Park, Granada, Spain. .,EURISTIKOS Excellence Centre for Paediatric Research, Universidad de Granada, Granada, Spain.
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21
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Hall JA, Ramachandran D, Roh HC, DiSpirito JR, Belchior T, Zushin PJH, Palmer C, Hong S, Mina AI, Liu B, Deng Z, Aryal P, Jacobs C, Tenen D, Brown CW, Charles JF, Shulman GI, Kahn BB, Tsai LTY, Rosen ED, Spiegelman BM, Banks AS. Obesity-Linked PPARγ S273 Phosphorylation Promotes Insulin Resistance through Growth Differentiation Factor 3. Cell Metab 2020; 32:665-675.e6. [PMID: 32941798 PMCID: PMC7543662 DOI: 10.1016/j.cmet.2020.08.016] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 06/05/2020] [Accepted: 08/26/2020] [Indexed: 12/13/2022]
Abstract
The thiazolidinediones (TZDs) are ligands of PPARγ that improve insulin sensitivity, but their use is limited by significant side effects. Recently, we demonstrated a mechanism wherein TZDs improve insulin sensitivity distinct from receptor agonism and adipogenesis: reversal of obesity-linked phosphorylation of PPARγ at serine 273. However, the role of this modification hasn't been tested genetically. Here we demonstrate that mice encoding an allele of PPARγ that cannot be phosphorylated at S273 are protected from insulin resistance, without exhibiting differences in body weight or TZD-associated side effects. Indeed, hyperinsulinemic-euglycemic clamp experiments confirm insulin sensitivity. RNA-seq in these mice reveals reduced expression of Gdf3, a BMP family member. Ectopic expression of Gdf3 is sufficient to induce insulin resistance in lean, healthy mice. We find Gdf3 inhibits BMP signaling and insulin signaling in vitro. Together, these results highlight the diabetogenic role of PPARγ S273 phosphorylation and focus attention on a putative target, Gdf3.
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Affiliation(s)
- Jessica A Hall
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Deepti Ramachandran
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Hyun C Roh
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | | | - Thiago Belchior
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Peter-James H Zushin
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Colin Palmer
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Shangyu Hong
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Amir I Mina
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Bingyang Liu
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Zhaoming Deng
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Pratik Aryal
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Christopher Jacobs
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Danielle Tenen
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Chester W Brown
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Memphis, TN 38103, USA
| | - Julia F Charles
- Department of Orthopedics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Gerald I Shulman
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Barbara B Kahn
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Linus T Y Tsai
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Evan D Rosen
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA
| | - Bruce M Spiegelman
- Department of Cancer Biology, Dana-Farber Cancer Institute and Department of Cell Biology, Harvard Medical School, Boston, MA 02215, USA
| | - Alexander S Banks
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA.
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22
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Sarhangi N, Sharifi F, Hashemian L, Hassani Doabsari M, Heshmatzad K, Rahbaran M, Jamaldini SH, Aghaei Meybodi HR, Hasanzad M. PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis. Sci Rep 2020; 10:12764. [PMID: 32728045 PMCID: PMC7391673 DOI: 10.1038/s41598-020-69363-7] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 07/06/2020] [Indexed: 12/11/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a complex disease caused by the interaction between genetic and environmental factors. A growing number of evidence suggests that the peroxisome proliferator-activated receptor gamma (PPARG) gene plays a major role in T2DM development. Meta-analysis of genetic association studies is an efficient tool to gain a better understanding of multifactorial diseases and potentially to provide valuable insights into gene-disease interactions. The present study was focused on assessing the association between Pro12Ala variation in the PPARG and T2DM risk through a comprehensive meta-analysis. We searched PubMed, WoS, Embase, Scopus and ProQuest from 1990 to 2017. The fixed-effect or random-effect model was used to evaluate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) depending on the heterogeneity among studies. The sources of heterogeneity and publication bias among the included studies were assessed using I2 statistics and Egger's tests. A total of 73 studies, involving 62,250 cases and 69,613 controls were included. The results showed that the minor allele (G) of the rs1801282 variant was associated with the decreased risk of T2DM under different genetic models. Moreover, the protective effect of minor allele was detected to be significantly more in some ethnicities including the European (18%), East Asian (20%), and South East Asian (18%). And the reduction of T2DM risk in Ala12 carriers was stronger in individuals from North Europe rather than Central and South Europe. Our findings indicated that the rs1801282 variant may contribute to decrease of T2DM susceptibility in different ancestries.
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Affiliation(s)
- Negar Sarhangi
- Personalized Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, 1411413137, Tehran, Iran
| | - Farshad Sharifi
- Elderly Health Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, 1411413137, Tehran, Iran
| | - Leila Hashemian
- Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, 1916893813, Tehran, Iran
| | - Maryam Hassani Doabsari
- Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, 1916893813, Tehran, Iran
| | - Katayoun Heshmatzad
- Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, 1916893813, Tehran, Iran
| | - Marzieh Rahbaran
- Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, 1916893813, Tehran, Iran
| | - Seyed Hamid Jamaldini
- Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, 1916893813, Tehran, Iran
| | - Hamid Reza Aghaei Meybodi
- Personalized Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, 1411413137, Tehran, Iran.,Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, 1411413137, Tehran, Iran
| | - Mandana Hasanzad
- Personalized Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, 1411413137, Tehran, Iran. .,Medical Genomics Research Center, Tehran Medical Sciences, Islamic Azad University, 1916893813, Tehran, Iran.
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Carrillo-Venzor MA, Erives-Anchondo NR, Moreno-González JG, Moreno-Brito V, Licón-Trillo A, González-Rodríguez E, Hernández-Rodríguez PDC, Reza-López SA, Loera-Castañeda V, Leal-Berumen I. Pro12Ala PPAR-γ2 and +294T/C PPAR-δ Polymorphisms and Association with Metabolic Traits in Teenagers from Northern Mexico. Genes (Basel) 2020; 11:genes11070776. [PMID: 32664384 PMCID: PMC7397260 DOI: 10.3390/genes11070776] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 07/01/2020] [Accepted: 07/07/2020] [Indexed: 11/20/2022] Open
Abstract
Peroxisome proliferator-activated receptors (PPARs) play roles in glucose and lipid metabolism regulation. Pro12Ala PPAR-γ2 and +294T/C PPAR-δ have been associated with dyslipidemia, hyperglycemia and high body mass index (BMI). We compared metabolic traits and determined associations with Pro12Ala PPAR-γ2 or +294T/C PPAR-δ polymorphism among teenagers from different ethnicity. Four hundred and twelve samples with previous biochemical and biometric measurements were used. Genomic DNA from peripheral blood was extracted and analyzed by end-point PCR for Pro12Ala PPAR-γ2. The +294T/C PPAR-δ PCR product was also digested with Bsl I. Two genotype groups were formed: major allele homozygous and minor allele carriers. Pro12Ala PPAR-γ2 G minor allele frequencies were: 10% in Mestizo-1, 19% in Mestizo-2, 23% in Tarahumara, 12% in Mennonite, and 17% in the total studied population. The +294T/C PPAR-δ C minor allele frequencies were: 18% in Mestizo-1, 20% in Mestizo-2, 6% in Tarahumara, 13% in Mennonite, and 12% in the total studied population. Teenagers with PPAR-γ2 G allele showed a greater risk for either high waist/height ratio or low high-density lipoprotein; and, also had lower total cholesterol. Whereas, PPAR-γ2 G allele showed lower overweight/obesity phenotype (BMI Z-score) frequency, PPAR-δ C allele was a risk factor for it. Metabolic traits were associated with both PPAR polymorphisms.
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Affiliation(s)
- Martín A. Carrillo-Venzor
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | - Nancy R. Erives-Anchondo
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | - Janette G. Moreno-González
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | - Verónica Moreno-Brito
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | - Angel Licón-Trillo
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | - Everardo González-Rodríguez
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | | | - Sandra A. Reza-López
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
| | | | - Irene Leal-Berumen
- Faculty of Medicine and Biomedical Sciences, Autonomous University of Chihuahua, Circuito Universitario, Campus II, Chihuahua 31109, Mexico; (M.A.C.-V.); (N.R.E.-A.); (J.G.M.-G.); (V.M.-B.); (A.L.T.); (E.G.-R.); (S.A.R.-L.)
- Correspondence:
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PPARG Polymorphisms Are Associated with Unexplained Mild Vision Loss in Patients with Type 2 Diabetes Mellitus. J Ophthalmol 2019; 2019:5284867. [PMID: 31915541 PMCID: PMC6930731 DOI: 10.1155/2019/5284867] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 11/11/2019] [Accepted: 11/20/2019] [Indexed: 01/17/2023] Open
Abstract
Objectives To investigate whether the presence of peroxisome proliferator-activated receptor gamma (PPARG) gene polymorphisms is associated with unexplained mild visual impairment (UMVI) in patients with type 2 diabetes mellitus (T2DM). Methods A total of 135 T2DM residents with UMVI and 133 with normal vision (NV; best-corrected visual acuity ≥ 20/25 in both eyes) were enrolled. UMVI was defined as best-corrected visual acuity (BCVA) < 20/25 and ≥ 20/63 in both eyes, with no visual impairment-causing diseases found. Four PPARG gene single-nucleotide polymorphisms (SNPs) (rs3856806, rs1801282, rs709158, and rs10865710) were assessed with the HAPLOVIEW 4.0 software to examine the statistical association of PPARG polymorphisms and UMVI in patients with T2DM. Results Four SNPs qualified the Hardy-Weinberg equilibrium (p > 0.05). The frequency of genotype GC at SNP rs10865710 was significantly higher in the UMVI group than in the NV group (p < 0.001; GG + GC versus CC) (OR = 8.94, 95% CI: 4.90-16.31), whereas genotype CC decreased the risk (OR = 0.07, 95% CI: 0.03-0.14). Genotype TT at SNP rs3856806 was strongly associated with UMVI (p < 0.0001, TT + TC versus CC) (OR = 4.74, 95% CI: 2.68-8.54), whereas genotype CC appeared to be protective for UMVI (OR = 0.55, 95% CI: 0.37-0.82). Conclusions Susceptibilities of PPARG variants may lead to differences in PPARG transcription, result in early function loss of retinal photoreceptor cells, and eventually cause UMVI.
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25
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Investigating the Systems-Level Effect of Pueraria lobata for Menopause-Related Metabolic Diseases Using an Ovariectomized Rat Model and Network Pharmacological Analysis. Biomolecules 2019; 9:biom9110747. [PMID: 31752216 PMCID: PMC6921005 DOI: 10.3390/biom9110747] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 11/05/2019] [Accepted: 11/14/2019] [Indexed: 12/29/2022] Open
Abstract
This study was conducted to evaluate the biological activities of Pueraria lobata (PL) on menopause-related metabolic diseases and to explore the underlying mechanism of PL by network pharmacological analyses. We used ovariectomized (OVX) rats as a postmenopausal model and administered PL at different doses (50, 100, and 200 mg/kg). In OVX rats, decreased uterine weights and PPAR-γ (peroxisome proliferator-activated receptor-gamma) mRNA expression in the thigh muscle were significantly recovered after PL administration. PL also significantly alleviated OVX-induced increases in total cholesterol, triglyceride, alanine aminotransferase (ALT/GPT), and aspartate aminotransferase (AST/GOT) levels. To identify the systems-level mechanism of PL, we performed network pharmacological analyses by predicting the targets of the potential bioactive compounds and their associated pathways. We identified 61 targets from four potential active compounds of PL: formononetin, beta-sitosterol, 3’-methoxydaidzein, and daidzein-4,7-diglucoside. Pathway enrichment analysis revealed that among female sex hormone-related pathways, the estrogen signaling pathways, progesterone-mediated oocyte maturation, oxytocin signaling pathways, and prolactin signaling pathways were associated with multiple targets of PL. In conclusion, we found that PL improved various indicators associated with lipid metabolism in the postmenopausal animal model, and we also identified that its therapeutic effects are exerted via multiple female sex hormone-related pathways.
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Abstract
Lipodystrophies are the result of a range of inherited and acquired causes, but all are characterized by perturbations in white adipose tissue function and, in many instances, its mass or distribution. Though patients are often nonobese, they typically manifest a severe form of the metabolic syndrome, highlighting the importance of white fat in the "safe" storage of surplus energy. Understanding the molecular pathophysiology of congenital lipodystrophies has yielded useful insights into the biology of adipocytes and informed therapeutic strategies. More recently, genome-wide association studies focused on insulin resistance have linked common variants to genes implicated in adipose biology and suggested that subtle forms of lipodystrophy contribute to cardiometabolic disease risk at a population level. These observations underpin the use of aligned treatment strategies in insulin-resistant obese and lipodystrophic patients, the major goal being to alleviate the energetic burden on adipose tissue.
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Duan Y, Sun H, Han L, Chen L. Association between phthalate exposure and glycosylated hemoglobin, fasting glucose, and type 2 diabetes mellitus: A case-control study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 670:41-49. [PMID: 30901574 DOI: 10.1016/j.scitotenv.2019.03.192] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 02/18/2019] [Accepted: 03/13/2019] [Indexed: 06/09/2023]
Abstract
Epidemiological studies have shown that exposure to phthalates (PAEs) is associated with type 2 diabetes mellitus (T2DM) and related markers, but limited evidence has been found in Chinese people. Given that China has the highest number of people with DM and Chinese people show relatively higher exposure levels of PAEs, a case-control study was conducted in China to explore the associations of PAE exposure with T2DM and two glycemic indicators, including fasting glucose and glycosylated hemoglobin (HbA1c). Two hundred fifty people with T2DM and 250 controls were recruited in this study. Multivariable logistic regression analyses showed significant positive associations between urinary concentrations of most studied PAE metabolites (mPAEs) and T2DM, with odd ratios comparing extreme mPAEs quartiles ranging from 2.09 to 40.53, whereas two secondary metabolites, mono (2-ethyl-5-carboxypentyl) phthalate and mono [(2-carboxymethyl) hexyl] phthalate showed significant inverse relationships with T2DM. In addition, multivariable linear regression analyses showed that urinary concentrations of mono (2-ethyl-5-hydroxyhexyl) phthalate were positively associated with HbA1c levels in controls (β = 0.013; 95% CI: 0.003, 0.023). A significant positive association was also observed for urinary mono (2-ethylhexyl) phthalate and fasting glucose (β = 0.009; 95% CI: 0.002, 0.016). In the stratified analyses, the significant associations of mPAEs with T2DM were more likely to be observed in the younger people, compared to the older people. The significant positive associations between urinary mPAEs and HbA1c levels were more likely to be found in the lower body mass index (BMI) subgroup. Additionally, urinary specific mPAEs were found to be significantly positively related to fasting glucose in males and the older people. The findings suggest that exposure to PAEs is associated with T2DM, fasting glucose, and HbA1c levels in Chinese people and the associations of exposure to PAEs with T2DM, fasting glucose, and HbA1c may differ between sexes, BMIs, or ages.
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Affiliation(s)
- Yishuang Duan
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin, China
| | - Hongwen Sun
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin, China.
| | - Liping Han
- Metabolic Disease Hospital, Tianjin Medical University, Tianjin, China
| | - Liming Chen
- Metabolic Disease Hospital, Tianjin Medical University, Tianjin, China
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28
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Mannino GC, Andreozzi F, Sesti G. Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine. Diabetes Metab Res Rev 2019; 35:e3109. [PMID: 30515958 PMCID: PMC6590177 DOI: 10.1002/dmrr.3109] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 11/27/2018] [Accepted: 11/30/2018] [Indexed: 12/11/2022]
Abstract
Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.
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Affiliation(s)
- Gaia Chiara Mannino
- Department of Medical and Surgical SciencesUniversity Magna Graecia of CatanzaroCatanzaroItaly
| | - Francesco Andreozzi
- Department of Medical and Surgical SciencesUniversity Magna Graecia of CatanzaroCatanzaroItaly
| | - Giorgio Sesti
- Department of Medical and Surgical SciencesUniversity Magna Graecia of CatanzaroCatanzaroItaly
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Li J, Niu X, Li J, Wang Q. Association of PPARG Gene Polymorphisms Pro12Ala with Type 2 Diabetes Mellitus: A Meta-analysis. Curr Diabetes Rev 2019; 15:277-283. [PMID: 30207237 DOI: 10.2174/1573399814666180912130401] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 08/15/2018] [Accepted: 09/04/2018] [Indexed: 12/25/2022]
Abstract
BACKGROUND Previous studies suggested that the single nucleotide polymorphisms of Pro12Ala located within the PPARG gene were significantly associated with the T2DM. Recently, the genetic studies on Pro12Ala were conducted in the different ethnic groups and the results of each study were shown to be inconsistent. Moreover, the systematic review has not been updated since 2000. OBJECTIVE To further validate the risk of Pro12Ala for T2DM disease based on the genetic data. METHODS The genetic studies on the Pro12Ala in the T2DM were searched in the PubMed and PMC database from January 2000 to October 2017. The meta-analysis was conducted with the CMA software. RESULTS The meta-analysis collected 14 studies including 20702 cases and 36227 controls. The combined analysis of all studies found that Pro12Ala was shown to be significantly associated with T2DM and the Ala allele played the increasing risks for the disease. Nevertheless, publication bias was detected in the combined analysis. The subgroup analysis indicated that Pro12Ala was found to be significant in the Caucasian and Chinese population. There was no heterogeneity and publication bias in these two groups. CONCLUSION The meta-analysis confirmed the evidence that the Pro12Ala was the susceptible variant for the decreasing risks for the T2DM.
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Affiliation(s)
- Junyan Li
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Changzhi Medical College Affiliated Heji Hospital, Endocrinology and Metabolism. No. 271, East Taihang Road Changzhi, China
| | - Xiaohong Niu
- Changzhi Medical College Affiliated Heji Hospital, Endocrinology and Metabolism. No. 271, East Taihang Road Changzhi, China
| | - JianBo Li
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qingzhong Wang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
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Wan R, Ding Z, Xia S, Zheng L, Lu J. Effects Of PPARγ2 Pro12Ala Variant On Adipocyte Phenotype Dependent Of DHA. Diabetes Metab Syndr Obes 2019; 12:2273-2279. [PMID: 31802926 PMCID: PMC6830383 DOI: 10.2147/dmso.s214526] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 10/03/2019] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Peroxisome proliferator-activated receptor γ2 (PPARγ2) plays a critical role in the regulation of adipocyte differentiation and adipocytokine production. The Pro12Ala variant is the most common mutation in the PPARγ2 gene. Its effect appears to be sensitive to dietary factors, such as docosahexaenoic acid (DHA) level. The purpose of this study was to investigate the interaction effect between PPARγ2 Pro12Ala variant and DHA on the phenotypes of adipocytes. METHODS We generated stable 3T3-L1 cell lines expressing wild-type PPARγ2 or PPARγ2 Pro12Ala variant. These two cell lines were cultured with different concentrations of DHA (0, 50, 200 umol/L). Then Oil red O staining was used to observe cell differentiation and the degree of lipid accumulation, TUNNEL assay was used to detect cell apoptosis, and ELISA assays were used to detect the changes of TNF-α, resistin and adiponectin levels in cell culture supernatant. RESULTS PPARγ2 Pro12Ala variant reduced lipid droplet accumulation in 3T3-L1 preadipocytes treated with or without 50 μmol/L DHA, but not with 200 μmol/L DHA, compared to that of wild-type PPARγ2. PPARγ2 reduced resistin production and increased adiponectin production in 3T3-L1 adipocytes, whereas PPARγ2 Pro12Ala variant diminished these effects. However, the absence of DHA blocked PPARγ2 Ala12 variant-induced effects on adiponectin production. There was no significant difference in TNF-α secretion between wild-type PPARγ2 and PPARγ2 Pro12Ala cells whether with or without DHA. CONCLUSION These results indicated that the effects of PPARγ2 Pro12Ala variant were dependent on DHA concentration.
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Affiliation(s)
- Renhui Wan
- Department of Endocrinology, Changhai Hospital, Second Military Medical University, Shanghai200433, People’s Republic of China
| | - Zhengping Ding
- Department of Endocrinology, Changhai Hospital, Second Military Medical University, Shanghai200433, People’s Republic of China
| | - Sheng Xia
- Department of Endocrinology, Changhai Hospital, Second Military Medical University, Shanghai200433, People’s Republic of China
| | - Longyi Zheng
- Department of Endocrinology, Changhai Hospital, Second Military Medical University, Shanghai200433, People’s Republic of China
| | - Jin Lu
- Department of Endocrinology, Changhai Hospital, Second Military Medical University, Shanghai200433, People’s Republic of China
- Correspondence: Jin Lu; Longyi Zheng Department of Endocrinology, Changhai Hospital, Second Military Medical University, No.168, Changhai Road, Shanghai200433, People’s Republic of China Email ;
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Koohdani F, Sotoudeh G, Kalantar Z, Mansoori A. PPARγ Pro12Ala Polymorphism Influences the Relationship between Dietary Fat Intake, Adiposity and Lipid Profile in Patients with Type 2 Diabetes. INT J VITAM NUTR RES 2018; 88:263-269. [DOI: 10.1024/0300-9831/a000595] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Abstract. Background: Peroxisome proliferator-activated receptor γ (PPARγ) Pro12Ala polymorphism (rs1801282) has been associated with metabolic syndrome components in some studies. Moreover, the PPARγ gene may mediate the physiological response to dietary fat intake in a ligand-dependent manner. Methods: Metabolic syndrome components (body mass index, waist circumference, and lipid profile) were determined in 290 type 2 diabetes mellitus patients in a cross-sectional study. DNA genotyping for determining PPARγ Pro12Ala polymorphism was conducted using the polymerase chain reaction-restriction length polymorphism method. A semi-quantitative food frequency questionnaire was used to assess the participants’ dietary intakes in the previous year. Results: There were significant differences between the two genotype groups of PPARγ Pro12Ala polymorphism, Ala carriers (Pro/Ala + Ala/Ala) versus non-Ala carriers (Pro/Pro), in terms of mean body mass index (p = 0.04) and waist circumference (p = 0.02). Below the median percentage of energy from monounsaturated and polyunsaturated fatty acids, Ala carriers had a higher body mass index (p = 0.01) compared to non-Ala carriers. Furthermore, a significant interaction between this single-nucleotide polymorphism and polyunsaturated fatty acids intake on serum triglyceride levels (p = 0.01) was seen, and in higher polyunsaturated fatty acids intake (≥ median) Ala carriers had lower triglyceride levels than non-Ala carriers (p = 0.007). Conclusions: The findings of the current study support a significant association between PPARγ Pro12Ala polymorphism and metabolic syndrome components, and they suggest that this polymorphism can modulate the biological response of dietary fat intake on body mass index and triglyceride levels.
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Affiliation(s)
- Fariba Koohdani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, Iran
- Cellular and Molecular Nutrition Department, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Gity Sotoudeh
- Community Nutrition Department, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Kalantar
- Cellular and Molecular Nutrition Department, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Anahita Mansoori
- Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Iran
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Abstract
PURPOSE OF REVIEW The leading cause of death in both chronic kidney disease (CKD) and renal transplant patients is cardiovascular events. Post-transplant diabetes mellitus (PTx-DM), which is a major cardiovascular risk factor, is a metabolic disorder that affects 5.5-60.2% of renal allograft recipients by 1-year posttransplant (PTx). PTx-DM has been associated with a negative impact on patient and graft outcomes and survival. RECENT FINDINGS Individuals who develop PTx-DM are usually prone to this condition prior to and/or after developing CKD. Genetic factors, obesity, inflammation, medications and CKD all are risk factors for PTx-diabetes mellitus. The path to development of disease continues PTx frequently augmented by the use of diabetogenic maintenance immunosuppressive and some nonimmunosuppressive medications. These risk factors are usually associated with an increase in insulin resistance, a decrease in insulin gene expression and/or β-cell dysfunction and apoptosis. SUMMARY Some new anti-diabetes mellitus medications may help to improve the overall outcome; however, there is a real need for developing a preventive strategy. Identifying and targeting PTx-DM risk factors may help to guide the development of an effective programme. This could include the adoption of nondiabetogenic immunosuppressive protocols for high-risk patients.
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Lin PC, Chou PL, Wung SF. Geographic diversity in genotype frequencies and meta-analysis of the association between rs1801282 polymorphisms and gestational diabetes mellitus. Diabetes Res Clin Pract 2018; 143:15-23. [PMID: 29885389 DOI: 10.1016/j.diabres.2018.05.050] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 05/10/2018] [Accepted: 05/30/2018] [Indexed: 01/27/2023]
Abstract
AIMS To derive a better understanding of the association between peroxisome proliferator-activated receptor gamma (PPAR-γ) rs1801282 polymorphisms and gestational diabetes mellitus (GDM) in general and in racial and ethnic subgroups and to illustrate geographic distribution of the protective of G allele of rs1801282 in women with and without GDM. METHODS ProQuest, PubMed, Medline, Web of Science, and Wanfang Data were systematically searched. Case-control studies on association between rs1801282 polymorphisms and GDM were selected. Comprehensive Meta-Analysis 2.0 statistical software was used to determine the relationship between GDM and rs1801282 polymorphism. Race/ethnicity-based and country-based stratified analysis was conducted. RESULTS Sixteen studies involving 3129 cases and 7168 controls were included. Significant associations were observed between rs1801282 polymorphisms and GDM under the dominant, heterozygote, and allele models. The G allele of rs1801282 polymorphism was associated with a reduced risk of GDM in Asian, especially Chinese, populations. Data revealed significant geographic diversity in frequency of the protective G allele in women with and without GDM. CONCLUSIONS The rs1801282 polymorphism may not be associated with genetic susceptibility to GDM in whites. The G allele of rs1801282 polymorphism was associated with reduced risk of GDM in Asians, especially Chinese, but not South Koreans.
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Affiliation(s)
- Pei-Chao Lin
- School of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Nursing, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Pi-Ling Chou
- School of Nursing, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Nursing, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Shu-Fen Wung
- College of Nursing, The University of Arizona, Tucson, AZ, United States.
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Functional Regulation of PPARs through Post-Translational Modifications. Int J Mol Sci 2018; 19:ijms19061738. [PMID: 29895749 PMCID: PMC6032173 DOI: 10.3390/ijms19061738] [Citation(s) in RCA: 165] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 06/05/2018] [Accepted: 06/07/2018] [Indexed: 12/11/2022] Open
Abstract
Peroxisome proliferator-activated receptors (PPARs) belong to the nuclear receptor superfamily and they are essential regulators of cell differentiation, tissue development, and energy metabolism. Given their central roles in sensing the cellular metabolic state and controlling metabolic homeostasis, PPARs became important targets of drug development for the management of metabolic disorders. The function of PPARs is mainly regulated through ligand binding, which induces structural changes, further affecting the interactions with co-activators or co-repressors to stimulate or inhibit their functions. In addition, PPAR functions are also regulated by various Post-translational modifications (PTMs). These PTMs include phosphorylation, SUMOylation, ubiquitination, acetylation, and O-GlcNAcylation, which are found at numerous modification sites. The addition of these PTMs has a wide spectrum of consequences on protein stability, transactivation function, and co-factor interaction. Moreover, certain PTMs in PPAR proteins have been associated with the status of metabolic diseases. In this review, we summarize the PTMs found on the three PPAR isoforms PPARα, PPARβ/δ, and PPARγ, and their corresponding modifying enzymes. We also discuss the functional roles of these PTMs in regulating metabolic homeostasis and provide a perspective for future research in this intriguing field.
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Zhang X, Men T, Liu H, Li X, Wang J, Lv J. Genetic risk factors for post-transplantation diabetes mellitus in Chinese Han renal allograft recipients treated with tacrolimus. Transpl Immunol 2018; 49:39-42. [PMID: 29665413 DOI: 10.1016/j.trim.2018.04.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 03/31/2018] [Accepted: 04/04/2018] [Indexed: 12/31/2022]
Abstract
BACKGROUND Post-transplantation diabetes mellitus (PTDM) is a serious metabolic complication after kidney transplantation. The aim of this study was to explore the association of clinical variables and five selected single nucleotide polymorphisms (SNPs) with PTDM in Chinese Han renal allograft recipients taking tacrolimus (TAC). METHODS A total of 129 non-diabetic, primary, Chinese Han renal allograft recipients treated with TAC were enrolled. Five SNPs (CYP3A5 rs776741, rs776746, rs15524, CYP24A1 rs2296241, and PPARG rs1801282) were genotyped and analyzed. RESULTS Among 129 recipients, 17 (13.2%) developed PTDM. Both univariate and multivariate analysis demonstrated that age over 50 years old and CYP24A1 rs2296241 A allele were independently correlated with the development of PTDM, while no significant differences was observed in TAC pharmacokinetics and CYP3A5, PPARG polymorphisms between two groups. CONCLUSIONS Patients with advanced age and CYP24A1 rs2296241 A allele had an increased risk of PTDM after kidney transplantation.
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Affiliation(s)
- Xiaoming Zhang
- Department of Urology, Qianfoshan Hospital Affiliated to Shandong University, 16766 Jingshi Road, Jinan 250014, China
| | - Tongyi Men
- Department of Urology, Qianfoshan Hospital Affiliated to Shandong University, 16766 Jingshi Road, Jinan 250014, China
| | - Haitao Liu
- Department of Urology, Qianfoshan Hospital Affiliated to Shandong University, 16766 Jingshi Road, Jinan 250014, China
| | - Xianduo Li
- Department of Urology, Qianfoshan Hospital Affiliated to Shandong University, 16766 Jingshi Road, Jinan 250014, China
| | - Jianning Wang
- Department of Urology, Qianfoshan Hospital Affiliated to Shandong University, 16766 Jingshi Road, Jinan 250014, China
| | - Jiaju Lv
- Department of Urology, Shandong Provincial Hospital, Shandong University, 324 Jingwuweiqi Road, Jinan 250021, China.
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Sikhayeva N, Talzhanov Y, Iskakova A, Dzharmukhanov J, Nugmanova R, Zholdybaeva E, Ramanculov E. Type 2 diabetes mellitus: distribution of genetic markers in Kazakh population. Clin Interv Aging 2018; 13:377-388. [PMID: 29551892 PMCID: PMC5842777 DOI: 10.2147/cia.s156044] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background Ethnic differences exist in the frequencies of genetic variations that contribute to the risk of common disease. This study aimed to analyse the distribution of several genes, previously associated with susceptibility to type 2 diabetes and obesity-related phenotypes, in a Kazakh population. Methods A total of 966 individuals belonging to the Kazakh ethnicity were recruited from an outpatient clinic. We genotyped 41 common single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes in other ethnic groups and 31 of these were in Hardy–Weinberg equilibrium. The obtained allele frequencies were further compared to publicly available data from other ethnic populations. Allele frequencies for other (compared) populations were pooled from the haplotype map (HapMap) database. Principal component analysis (PCA), cluster analysis, and multidimensional scaling (MDS) were used for the analysis of genetic relationship between the populations. Results Comparative analysis of allele frequencies of the studied SNPs showed significant differentiation among the studied populations. The Kazakh population was grouped with Asian populations according to the cluster analysis and with the Caucasian populations according to PCA. According to MDS, results of the current study show that the Kazakh population holds an intermediate position between Caucasian and Asian populations. Conclusion A high percentage of population differentiation was observed between Kazakh and world populations. The Kazakh population was clustered with Caucasian populations, and this result may indicate a significant Caucasian component in the Kazakh gene pool.
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Affiliation(s)
- Nurgul Sikhayeva
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan.,Faculty of Natural Sciences, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
| | - Yerkebulan Talzhanov
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan
| | - Aisha Iskakova
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan
| | - Jarkyn Dzharmukhanov
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan
| | - Raushan Nugmanova
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan
| | - Elena Zholdybaeva
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan
| | - Erlan Ramanculov
- National Scientific Laboratory of Biotechnology, National Center for Biotechnology, Astana, Kazakhstan.,Faculty of Natural Sciences, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan.,School of Science and Technology, Nazarbayev University, Astana, Kazakhstan
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Al-Naemi AH, Ahmad AJ. Is the rs1801282 (G/C) Polymorphism of PPAR - Gamma Gene Associated with T2DM in Iraqi People? Open Access Maced J Med Sci 2018; 6:447-455. [PMID: 29610599 PMCID: PMC5874364 DOI: 10.3889/oamjms.2018.156] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2014] [Revised: 05/12/2014] [Accepted: 05/14/2014] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Pro12Ala (rs1801282) is a common polymorphism of the human PPAR-γ gene. Studies have demonstrated conflicting results about its association with T2DM worldwide. There are no reports about such possible association among Iraqi people. OBJECTIVES This study aims at finding out whether having the mutant allele (Ala12) might be associated with T2DM among Iraqi people. METHODS One hundred and ninety-two Arabic Iraqi adult subjects (97 with T2DM and 95 controls) were genotyped using PCR- RFLP. Clinical, anthropometrical and biochemical variables were compared regarding the Pro12Ala genotypes. RESULTS About 5.67% of people with diabetes were carriers of the (Ala12) allele versus 9.47% of controls. Allelic and genotypic frequencies were not statistically different among diabetics and controls [(χ2= 1.99, p= 0.16) and (χ2= 2.17, p= 0.14)]. Age, BMI and smoking- but not Pro12Ala - were independent risk factors for T2DM in our subjects. Pro12Ala was not associated with T2DM (Odd's ratio 0.55, 95% CI 0.23- 1.32, p= 0.14). CONCLUSIONS Our study revealed a relatively high frequency of the Ala12 allele among Arabic Iraqis. These frequencies did not significantly differ between diabetics and controls indicating the absence of association of Pro12Ala with T2DM among Iraqis.
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Affiliation(s)
- Amjad Hazim Al-Naemi
- Department of Biochemistry, Mosul Medical College, University of Mosul, Mosul, Iraq
| | - Akram Jarjees Ahmad
- Department of Biochemistry, Mosul Medical College, University of Mosul, Mosul, Iraq
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Duggan C, Baumgartner RN, Baumgartner KB, Bernstein L, George S, Ballard R, Neuhouser ML, McTiernan A. Genetic variation in TNFα, PPARγ, and IRS-1 genes, and their association with breast-cancer survival in the HEAL cohort. Breast Cancer Res Treat 2017; 168:567-576. [PMID: 29256014 DOI: 10.1007/s10549-017-4621-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 12/08/2017] [Indexed: 12/20/2022]
Abstract
PURPOSE Tumor necrosis factor-α (TNF-α), peroxisome proliferator-activated receptor-γ (PPARγ), and insulin receptor substrate-1 (IRS-1) are associated with obesity, insulin resistance, and inflammation. Few data exist on associations between polymorphisms in these genes and mortality in breast cancer survivors. METHODS We investigated associations between TNF-α -308G > A (rs1800629); PPARγ Pro12Ala (rs1801282); and IRS-1 Gly972Arg (rs1801278) polymorphisms and anthropometric variables, circulating levels of previously measured biomarkers, and tumor characteristics in 553 women enrolled in the Health, Eating, Activity, and Lifestyle Study, a multiethnic, prospective cohort study of women diagnosed with stage I-IIIA breast cancer between 1995 and 1999 (median follow-up 14.7 years). Using Cox proportional hazards models adjusted for possible confounders, we evaluated associations between these polymorphisms and mortality. RESULTS Carriers of the PPARγ variant allele had statistically significantly lower rates of type 2 diabetes (P = 0.04), lower BMI (P = 0.01), and HOMA scores [P = 0.004; non-Hispanic White (NHWs) only]; carriers of the TNF-α variant A allele had higher serum glucose (P = 0.004, NHW only); and the IRS-1 variant was associated with higher leptin levels (P = 0.003, Hispanics only). There were no associations between any of the polymorphisms and tumor characteristics. Among 141 deaths, 62 were due to breast cancer. Carriers of the TNF-α-variant A allele had a decreased risk of breast-cancer-specific mortality [hazard ratio (HR) 0.30; 95% confidence interval (CI) 0.10-0.83] and all-cause mortality (HR 0.51; 95% CI 0.28-0.91). CONCLUSIONS Neither the PPARγ nor the IRS-1 polymorphism was associated with mortality outcome. The TNF-α -308 G > A polymorphism was associated with reduced breast-cancer-specific and all-cause mortality.
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Affiliation(s)
- Catherine Duggan
- Epidemiology Program, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Richard N Baumgartner
- Department of Epidemiology & Population Health, University of Louisville, Louisville, KY, USA
| | - Kathy B Baumgartner
- Department of Epidemiology & Population Health, University of Louisville, Louisville, KY, USA
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Stephanie George
- Office of Disease Prevention, National Institutes of Health, Rockville, MD, USA
| | - Rachel Ballard
- Office of Disease Prevention, National Institutes of Health, Rockville, MD, USA
| | - Marian L Neuhouser
- Epidemiology Program, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Anne McTiernan
- Epidemiology Program, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
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Liu Y, Wan W, Fang F, Guo L, Zhao Y, Zhang X, Huang F. Clinical relevance of peroxisome proliferator-activated receptor-γ gene polymorphisms with sepsis. J Clin Lab Anal 2017; 32:e22340. [PMID: 29055064 DOI: 10.1002/jcla.22340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Accepted: 09/10/2017] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Peroxisome proliferator-activated receptor-γ (PPARγ) is a regulator of inflammation. This study aimed to explore associations between PPARγ gene single-nucleotide polymorphisms (SNPs) and susceptibility to and clinical outcome of sepsis in the North China Han population. METHODS This study included 303 patients with sepsis and 303 controls. We conducted genetic typing for 13 common PPARγ gene SNPs (improved multiplex ligation detection reaction), linkage disequilibrium mapping, and haplotype inference. Associations between SNP genotypes/haplotypes and sepsis susceptibility and outcome (septic shock, organ dysfunction, or death) were assessed using unconditional logistic regression analysis. RESULTS For rs2972164, patients with genotypes CT/CT+TT had higher risk of sepsis than genotype CC (odds ratio [95% CI]: 1.74 [1.05-2.86], P = .03 and 1.72 [1.06-2.80], P = .026, respectively); the T allele was associated with increased sepsis risk compared with the C allele (1.64 [1.04-2.58], P = .033). For rs1801282, genotypes CG/CG+GG had lower risk of sepsis than genotype CC (0.55 [0.33-0.92], P = .024 and 0.57 [0.35-0.95], P = .03, respectively); the G allele was associated with decreased sepsis risk compared with the C allele (0.62 [0.39-1.01], P = .055). For rs4135275, genotypes AG/AG+GG had higher risk of severe organ dysfunction (multiple organ dysfunction syndrome score >8) than genotype AA (2.66 [1.16-6.09], P = .038 and 2.21 [1.00-4.85], P = .042, respectively). Haplotype TAT (rs2972164, rs4684846, and rs17036188) was associated with increased sepsis risk (1.66 [1.03-2.67], P = .038). CONCLUSIONS No mutation was correlated with septic shock or death. PPARγ gene polymorphisms may play a role in the occurrence and progression of sepsis in the North China Han population.
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Affiliation(s)
- Yu Liu
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Wenhui Wan
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Fang Fang
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Lei Guo
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Yusheng Zhao
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Xinghu Zhang
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Fang Huang
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
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Elk N, Iwuchukwu OF. Using Personalized Medicine in the Management of Diabetes Mellitus. Pharmacotherapy 2017; 37:1131-1149. [PMID: 28654165 DOI: 10.1002/phar.1976] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Diabetes mellitus is a worldwide problem with an immense pharmacoeconomic burden. The multifactorial and complex nature of the disease lends itself to personalized pharmacotherapeutic approaches to treatment. Variability in individual risk and subsequent development of diabetes has been reported in addition to differences in response to the many oral glucose lowering therapies currently available for diabetes pharmacotherapy. Pharmacogenomic studies have attempted to uncover the heritable components of individual variability in risk susceptibility and response to pharmacotherapy. We review the current pharmacogenomics evidence as it relates to common oral glucose lowering therapies and how they can be utilized in the management of polygenic and monogenic forms of diabetes. Evidence supports the use of genetic testing and personalized approaches to the treatment of monogenic diabetes of the young. The data are not as robust for the current application of pharmacogenetic approaches to the treatment of polygenic type 2 diabetes mellitus, but there are suggestions as to future applications in this regard. We reviewed pertinent primary literature sources as well as current evidence-based guidelines on diabetes management.
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Affiliation(s)
- Nina Elk
- Division of Pharmacy Practice, Fairleigh Dickinson University School of Pharmacy, Florham Park, New Jersey
| | - Otito F Iwuchukwu
- Division of Pharmaceutical Sciences, Fairleigh Dickinson University School of Pharmacy, Florham Park, New Jersey
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Kawai VK, Levinson RT, Adefurin A, Kurnik D, Collier SP, Conway D, Stein CM. A genetic risk score that includes common type 2 diabetes risk variants is associated with gestational diabetes. Clin Endocrinol (Oxf) 2017; 87:149-155. [PMID: 28429832 PMCID: PMC5533106 DOI: 10.1111/cen.13356] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 03/15/2017] [Accepted: 04/17/2017] [Indexed: 12/26/2022]
Abstract
OBJECTIVE Gestational diabetes (GDM) is characterized by maternal glucose intolerance that manifests during pregnancy. Because GDM resembles type 2 diabetes (T2DM), shared genetic predisposition is likely but has not been established. We tested the hypothesis that a genetic risk score (GRS) that included variants known to be associated with T2DM is associated with GDM. STUDY DESIGN We conducted a case-control study using the Vanderbilt Medical Center biobank (BioVU) and calculated a simple-count GRS using 34 variants previously associated with T2DM or fasting glucose in the general population, or with GDM or glucose intolerance in pregnancy. We assessed the association of the GRS with GDM adjusting for maternal age, parity, and body mass index (BMI) and calculated the area under the curve for the receiver-operating characteristic curve (c-statistic). STUDY POPULATION Among Caucasian women, we identified 458 cases of GDM and 1538 pregnant controls with normal glucose tolerance. RESULTS Cases of GDM had a higher number of risk alleles compared to controls (38.9±4.0 vs 37.4±4.0 risk alleles, P=1.6×10-11 ). The GRS was significantly associated with GDM; the adjusted odds ratio associated with each additional risk allele was 1.10 (95% CI: 1.07-1.13, P=6×10-11 ). Clinical variables predicted the risk of GDM (c-statistic 0.67, 95% CI: 0.64-0.70), and adding the GRS modestly improved prediction (0.70, 95% CI: 0.67-0.73). CONCLUSIONS Among Caucasian women, a GRS that included common T2DM genetic risk variants was associated with increased risk of GDM but showed limited utility in the identification of GDM cases.
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Affiliation(s)
- Vivian K. Kawai
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt
University Medical Center, Nashville, TN, USA
| | - Rebecca T. Levinson
- Vanderbilt Genetics Institute, Vanderbilt University School of
Medicine, Nashville, TN, USA
| | - Abiodun Adefurin
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt
University Medical Center, Nashville, TN, USA
- Department of Internal Medicine, Meharry Medical College, Nashville,
TN, USA
| | - Daniel Kurnik
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt
University Medical Center, Nashville, TN, USA
- Clinical Pharmacology Unit, Rambam Health Care Campus, Haifa,
Israel
- Rappaport Faculty of Medicine, Technion – Israel Institute
of Technology, Haifa, Israel
| | - Sarah P. Collier
- Vanderbilt Institute for Clinical and Translational Research,
Vanderbilt University Medical Center, Nashville, TN, USA
| | - Douglas Conway
- Vanderbilt Institute for Clinical and Translational Research,
Vanderbilt University Medical Center, Nashville, TN, USA
| | - C. Michael Stein
- Division of Clinical Pharmacology, Department of Medicine Vanderbilt
University Medical Center, Nashville, TN, USA
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Gene-Diet Interactions in Type 2 Diabetes: The Chicken and Egg Debate. Int J Mol Sci 2017; 18:ijms18061188. [PMID: 28574454 PMCID: PMC5486011 DOI: 10.3390/ijms18061188] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 05/23/2017] [Accepted: 05/26/2017] [Indexed: 02/07/2023] Open
Abstract
Consistent evidence from both experimental and human studies indicates that Type 2 diabetes mellitus (T2DM) is a complex disease resulting from the interaction of genetic, epigenetic, environmental, and lifestyle factors. Nutrients and dietary patterns are important environmental factors to consider in the prevention, development and treatment of this disease. Nutritional genomics focuses on the interaction between bioactive food components and the genome and includes studies of nutrigenetics, nutrigenomics and epigenetic modifications caused by nutrients. There is evidence supporting the existence of nutrient-gene and T2DM interactions coming from animal studies and family-based intervention studies. Moreover, many case-control, cohort, cross-sectional cohort studies and clinical trials have identified relationships between individual genetic load, diet and T2DM. Some of these studies were on a large scale. In addition, studies with animal models and human observational studies, in different countries over periods of time, support a causative relationship between adverse nutritional conditions during in utero development, persistent epigenetic changes and T2DM. This review provides comprehensive information on the current state of nutrient-gene interactions and their role in T2DM pathogenesis, the relationship between individual genetic load and diet, and the importance of epigenetic factors in influencing gene expression and defining the individual risk of T2DM.
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Scudiero O, Nigro E, Elce A, Izzo V, Monaco ML, Sangiorgio D, Buono P, Villone G, Daniele A. PPARγ and ADRB3 polymorphisms analysis and Irisin expression in professional water polo players. SPORT SCIENCES FOR HEALTH 2017. [DOI: 10.1007/s11332-017-0371-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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44
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Achermann JC, Schwabe J, Fairall L, Chatterjee K. Genetic disorders of nuclear receptors. J Clin Invest 2017; 127:1181-1192. [PMID: 28368288 DOI: 10.1172/jci88892] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Following the first isolation of nuclear receptor (NR) genes, genetic disorders caused by NR gene mutations were initially discovered by a candidate gene approach based on their known roles in endocrine pathways and physiologic processes. Subsequently, the identification of disorders has been informed by phenotypes associated with gene disruption in animal models or by genetic linkage studies. More recently, whole exome sequencing has associated pathogenic genetic variants with unexpected, often multisystem, human phenotypes. To date, defects in 20 of 48 human NR genes have been associated with human disorders, with different mutations mediating phenotypes of varying severity or several distinct conditions being associated with different changes in the same gene. Studies of individuals with deleterious genetic variants can elucidate novel roles of human NRs, validating them as targets for drug development or providing new insights into structure-function relationships. Importantly, human genetic discoveries enable definitive disease diagnosis and can provide opportunities to therapeutically manage affected individuals. Here we review germline changes in human NR genes associated with "monogenic" conditions, including a discussion of the structural basis of mutations that cause distinctive changes in NR function and the molecular mechanisms mediating pathogenesis.
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Takahashi E, Unoki-Kubota H, Shimizu Y, Okamura T, Iwata W, Kajio H, Yamamoto-Honda R, Shiga T, Yamashita S, Tobe K, Okumura A, Matsumoto M, Yasuda K, Noda M, Kaburagi Y. Proteomic analysis of serum biomarkers for prediabetes using the Long-Evans Agouti rat, a spontaneous animal model of type 2 diabetes mellitus. J Diabetes Investig 2017; 8:661-671. [PMID: 28150914 PMCID: PMC5583949 DOI: 10.1111/jdi.12638] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Revised: 01/04/2017] [Accepted: 01/23/2017] [Indexed: 01/20/2023] Open
Abstract
AIMS/INTRODUCTION To identify candidate serum molecules associated with the progression of type 2 diabetes mellitus, differential serum proteomic analysis was carried out on a spontaneous animal model of type 2 diabetes mellitus without obesity, the Long-Evans Agouti (LEA) rat. MATERIALS AND METHODS We carried out quantitative proteomic analysis using serum samples from 8- and 16-week-old LEA and control Brown Norway (BN) rats (n = 4/group). Differentially expressed proteins were validated by multiple reaction monitoring analysis using the sera collected from 8-, 16-, and 24-week-old LEA (n = 4/each group) and BN rats (n = 5/each group). Among the validated proteins, we also examined the possible relevance of the human homolog of serine protease inhibitor A3 (SERPINA3) to type 2 diabetes mellitus. RESULTS The use of 2-D fluorescence difference gel electrophoresis analysis and the following liquid chromatography-multiple reaction monitoring analysis showed that the serum levels of five proteins were differentially changed between LEA rats and BN rats at all three time-points examined. Among the five proteins, SERPINA3N was increased significantly in the sera of LEA rats compared with age-matched BN rats. The serum level of SERPINA3 was also found to be significantly higher in type 2 diabetes mellitus patients than in healthy control participants. Furthermore, glycated hemoglobin, fasting insulin and estimated glomerular filtration rate were independently associated with the SERPINA3 levels. CONCLUSIONS These findings suggest a possible role for SERPINA3 in the development of the early stages of type 2 diabetes mellitus, although further replication studies and functional investigations regarding their role are required.
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Affiliation(s)
- Eri Takahashi
- Department of Diabetic Complications, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hiroyuki Unoki-Kubota
- Department of Diabetic Complications, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Yukiko Shimizu
- Department of Laboratory Animal Medicine, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Tadashi Okamura
- Department of Laboratory Animal Medicine, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan.,Section of Animal Models, Department of Infectious Diseases, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Wakiko Iwata
- Department of Diabetic Complications, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hiroshi Kajio
- Department of Diabetes, Endocrinology and Metabolism, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan
| | - Ritsuko Yamamoto-Honda
- Department of Diabetes, Endocrinology and Metabolism, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan
| | - Tomoko Shiga
- Department of Complete Medical Checkup, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan
| | - Shigeo Yamashita
- Department of Diabetes and Endocrinology, JR Tokyo General Hospital, Tokyo, Japan
| | - Kazuyuki Tobe
- The First Department of Internal Medicine, Faculty of Medicine, University of Toyama, Toyama, Japan
| | - Akinori Okumura
- Department of Diabetic Complications, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Michihiro Matsumoto
- Department of Molecular Metabolic Regulation, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Kazuki Yasuda
- Department of Metabolic Disorder, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Mitsuhiko Noda
- Department of Endocrinology and Diabetes, Saitama Medical University, Saitama, Japan
| | - Yasushi Kaburagi
- Department of Diabetic Complications, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
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Improvement of cardiometabolic markers after fish oil intervention in young Mexican adults and the role of PPARα L162V and PPARγ2 P12A. J Nutr Biochem 2017; 43:98-106. [PMID: 28282585 DOI: 10.1016/j.jnutbio.2017.02.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 12/03/2016] [Accepted: 02/07/2017] [Indexed: 11/20/2022]
Abstract
Polyunsaturated fatty acids (PUFA) contained in fish oil (FO) are ligands for peroxisome proliferator-activated receptors (PPAR) that may induce changes in cardiometabolic markers. Variation in PPAR genes may influence the beneficial responses linked to FO supplementation in young adults. The study aimed to analyze the effect of FO supplementation on glucose metabolism, circulating lipids and inflammation according to PPARα L162V and PPARγ2 P12A genotypes in young Mexican adults. 191 young, non-smoking subjects between 18 and 40 years were included in a one-arm study. Participants were supplemented with 2.7 g/day of EPA+DHA, during six weeks. Dietary analysis, body composition measurements and indicators for glucose metabolism, circulating lipids, and markers for inflammation were analyzed before and after intervention. An overall decrease in triglycerides (TG) and an increase in HS-ω3 index were observed in all subjects [-4.1 mg/dL, (SD:±51.7), P=.02 and 2.6%, (SD:±1.2), P<.001 respectively]. Mean fasting insulin and glycated hemoglobin (HbA1c%) were significantly decreased in all subjects [-0.547mlU/L, (SD:±10.29), P=.034 and-0.07%, (SD:±0.3), P<.001 respectively], whereas there was no change in body composition, fasting glucose, adiponectin and inflammatory markers. Subjects carrying the minor alleles of PPARα L162V and PPARγ2 P12A had higher responses in reduction of TG and fasting insulin respectively. Interestingly, doses below 2.7 g/day (1.8 g/day) were sufficient to induce a significant reduction in fasting insulin and HbA1c% from baseline (P=.019 and P<.001). The observed responses in triglycerides and fasting insulin in the Mexican population give further evidence of the importance of FO supplementation in young people as an early step towards the prevention of cardiometabolic disease.
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47
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Association of Pro12Ala Polymorphism of Peroxisome Proliferator-Activated Receptor gamma 2 (PPARγ2) Gene with Type 2 Diabetes Mellitus in Ethnic Kashmiri Population. Biochem Genet 2016; 55:10-21. [PMID: 27567620 DOI: 10.1007/s10528-016-9765-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2016] [Accepted: 07/30/2016] [Indexed: 10/21/2022]
Abstract
Type 2 diabetes mellitus (T2DM) is characterized by chronic hyperglycemia associated with insulin resistance and relative insulin deficiency. T2DM is believed to be attributable to the combined effect of genetic and environmental factors. Peroxisome proliferator-activated receptor gamma 2 (PPARγ2) is one of the main candidate genes that are implicated in T2DM. A common proline 12 alanine (Pro12Ala) polymorphism in PPARγ2 has been shown to be associated with T2DM. The aim of this work was to investigate the possible role of PPARγ2 gene polymorphism, as a genetic risk factor for T2DM. The study comprised 200 ethnic unrelated subjects (100 T2DM patients and 100 controls). PCR-RFLP technique was used for genotyping analysis. The frequency of the Pro allele was 79 and 91.5 % for controls and cases, respectively (P < 0.05; OR 3.2; 95 % CI 1.64-6.3). The Pro12Ala polymorphism was in Hardy-Weinberg equilibrium in both patients and controls (χ 2 = 0.13, P > 0.05). We found a significant association of Pro12Ala polymorphism of PPARγ2 gene with T2DM, however the genotypes showed statistically significant association only with few clinical parameters including body mass index, total cholesterol, and low-density lipoprotein (P < 0.05). The study signifies that Pro allele in PPARγ2 may be a genotypic risk factor that confers susceptibility to T2DM in ethnic Kashmiri population.
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48
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Avzaletdinova DS, Sharipova LF, Kochetova OV, Morugova TV, Erdman VV, Mustafina OE. Association of variable rs1801282 locus of PPARG2 gene with diabetic nephropathy. RUSS J GENET+ 2016. [DOI: 10.1134/s1022795416080032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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49
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Is the Mouse a Good Model of Human PPARγ-Related Metabolic Diseases? Int J Mol Sci 2016; 17:ijms17081236. [PMID: 27483259 PMCID: PMC5000634 DOI: 10.3390/ijms17081236] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Revised: 07/19/2016] [Accepted: 07/21/2016] [Indexed: 12/21/2022] Open
Abstract
With the increasing number of patients affected with metabolic diseases such as type 2 diabetes, obesity, atherosclerosis and insulin resistance, academic researchers and pharmaceutical companies are eager to better understand metabolic syndrome and develop new drugs for its treatment. Many studies have focused on the nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ), which plays a crucial role in adipogenesis and lipid metabolism. These studies have been able to connect this transcription factor to several human metabolic diseases. Due to obvious limitations concerning experimentation in humans, animal models—mainly mouse models—have been generated to investigate the role of PPARγ in different tissues. This review focuses on the metabolic features of human and mouse PPARγ-related diseases and the utility of the mouse as a model.
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50
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Liu CT, Raghavan S, Maruthur N, Kabagambe EK, Hong J, Ng MCY, Hivert MF, Lu Y, An P, Bentley AR, Drolet AM, Gaulton KJ, Guo X, Armstrong LL, Irvin MR, Li M, Lipovich L, Rybin DV, Taylor KD, Agyemang C, Palmer ND, Cade BE, Chen WM, Dauriz M, Delaney JAC, Edwards TL, Evans DS, Evans MK, Lange LA, Leong A, Liu J, Liu Y, Nayak U, Patel SR, Porneala BC, Rasmussen-Torvik LJ, Snijder MB, Stallings SC, Tanaka T, Yanek LR, Zhao W, Becker DM, Bielak LF, Biggs ML, Bottinger EP, Bowden DW, Chen G, Correa A, Couper DJ, Crawford DC, Cushman M, Eicher JD, Fornage M, Franceschini N, Fu YP, Goodarzi MO, Gottesman O, Hara K, Harris TB, Jensen RA, Johnson AD, Jhun MA, Karter AJ, Keller MF, Kho AN, Kizer JR, Krauss RM, Langefeld CD, Li X, Liang J, Liu S, Lowe WL, Mosley TH, North KE, Pacheco JA, Peyser PA, Patrick AL, Rice KM, Selvin E, Sims M, Smith JA, Tajuddin SM, Vaidya D, Wren MP, Yao J, Zhu X, Ziegler JT, Zmuda JM, Zonderman AB, Zwinderman AH, Adeyemo A, Boerwinkle E, Ferrucci L, Hayes MG, Kardia SLR, Miljkovic I, Pankow JS, Rotimi CN, Sale MM, Wagenknecht LE, et alLiu CT, Raghavan S, Maruthur N, Kabagambe EK, Hong J, Ng MCY, Hivert MF, Lu Y, An P, Bentley AR, Drolet AM, Gaulton KJ, Guo X, Armstrong LL, Irvin MR, Li M, Lipovich L, Rybin DV, Taylor KD, Agyemang C, Palmer ND, Cade BE, Chen WM, Dauriz M, Delaney JAC, Edwards TL, Evans DS, Evans MK, Lange LA, Leong A, Liu J, Liu Y, Nayak U, Patel SR, Porneala BC, Rasmussen-Torvik LJ, Snijder MB, Stallings SC, Tanaka T, Yanek LR, Zhao W, Becker DM, Bielak LF, Biggs ML, Bottinger EP, Bowden DW, Chen G, Correa A, Couper DJ, Crawford DC, Cushman M, Eicher JD, Fornage M, Franceschini N, Fu YP, Goodarzi MO, Gottesman O, Hara K, Harris TB, Jensen RA, Johnson AD, Jhun MA, Karter AJ, Keller MF, Kho AN, Kizer JR, Krauss RM, Langefeld CD, Li X, Liang J, Liu S, Lowe WL, Mosley TH, North KE, Pacheco JA, Peyser PA, Patrick AL, Rice KM, Selvin E, Sims M, Smith JA, Tajuddin SM, Vaidya D, Wren MP, Yao J, Zhu X, Ziegler JT, Zmuda JM, Zonderman AB, Zwinderman AH, Adeyemo A, Boerwinkle E, Ferrucci L, Hayes MG, Kardia SLR, Miljkovic I, Pankow JS, Rotimi CN, Sale MM, Wagenknecht LE, Arnett DK, Chen YDI, Nalls MA, Province MA, Kao WHL, Siscovick DS, Psaty BM, Wilson JG, Loos RJF, Dupuis J, Rich SS, Florez JC, Rotter JI, Morris AP, Meigs JB. Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin. Am J Hum Genet 2016; 99:56-75. [PMID: 27321945 PMCID: PMC5005440 DOI: 10.1016/j.ajhg.2016.05.006] [Show More Authors] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 05/02/2016] [Indexed: 12/11/2022] Open
Abstract
Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.
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Affiliation(s)
- Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
| | - Sridharan Raghavan
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Department of Veterans Affairs Medical Center, Eastern Colorado Health Care System, Denver, CO 80220, USA; Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Denver, CO 80220, USA
| | - Nisa Maruthur
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Edmond Kato Kabagambe
- Division of Epidemiology, Department of Medicine, School of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Jaeyoung Hong
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA 02215, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Universite de Sherbrooke, Sherbrooke, QC J1G 0A2, Canada
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ping An
- Division of Statistical Genomics, Department of Genetics, School of Medicine, Washington University, St Louis, MO 63108, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Anne M Drolet
- Center for Molecular Medicine and Genetics, School of Medicine, Wayne State University, Detroit, MI 48201, USA
| | - Kyle J Gaulton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Loren L Armstrong
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama - Birmingham, Birmingham, AL 35294, USA
| | - Man Li
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Leonard Lipovich
- Center for Molecular Medicine and Genetics, School of Medicine, Wayne State University, Detroit, MI 48201, USA; Department of Neurology, School of Medicine, Wayne State University, Detroit, MI 48201, USA
| | - Denis V Rybin
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Charles Agyemang
- Department of Public Health, Academic Medical Center Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, the Netherlands
| | - Nicholette D Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Marco Dauriz
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, University of Verona, 37126 Verona, Italy
| | - Joseph A C Delaney
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, School of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Michele K Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27607, USA
| | - Aaron Leong
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Jingmin Liu
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Yongmei Liu
- Center for Human Genetics, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Uma Nayak
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Sanjay R Patel
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Bianca C Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Marieke B Snijder
- Department of Public Health, Academic Medical Center Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, the Netherlands
| | - Sarah C Stallings
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute of Aging at Harbor Hospital, Baltimore, MD 21225, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Diane M Becker
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Mary L Biggs
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - David J Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Dana C Crawford
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Mary Cushman
- Department of Medicine and Pathology, University of Vermont, College of Medicine, Burlington, VT 05405, USA
| | - John D Eicher
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Framingham, MA 01702, USA
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Yi-Ping Fu
- Cardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung, and Blood Institute, NIH, Framingham, MA 01702, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes & Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kazuo Hara
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan; Department of Diabetes, Endocrinology, and Metabolism, Tokyo Medical University, Tokyo 163-0023, Japan
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, NIH, Bethesda, MD 20892, USA
| | - Richard A Jensen
- Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Framingham, MA 01702, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Andrew J Karter
- Division of Research, Kaiser Permanente, Northern California Region, Oakland, CA 94612, USA
| | - Margaux F Keller
- Department of Genetics and Pharmacogenomics, Merck Research Laboratories, 33 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Abel N Kho
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Jorge R Kizer
- Department of Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY 10461, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Ronald M Krauss
- Children's Hospital Oakland Research Institute, Oakland, CA 94609, USA
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Xiaohui Li
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jingling Liang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI 02912, USA; Department of Medicine, Brown University, Providence, RI 02903, USA
| | - William L Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Thomas H Mosley
- Division of Geriatrics/Gerontology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Jennifer A Pacheco
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Alan L Patrick
- Tobago Health Studies Office, Scarborough, Tobago, Trinidad and Tobago
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Salman M Tajuddin
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Dhananjay Vaidya
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA; GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Mary P Wren
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Julie T Ziegler
- Center for Public Health Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Joseph M Zmuda
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Alan B Zonderman
- Behavioral Epidemiology Section, Laboratory of Epidemiology & Population Science, Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD 21224, US
| | - Aeilko H Zwinderman
- Department of Public Health, Academic Medical Center Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, the Netherlands
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Eric Boerwinkle
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute of Aging at Harbor Hospital, Baltimore, MD 21225, USA
| | - M Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Iva Miljkovic
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Michele M Sale
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Donna K Arnett
- University of Kentucky College of Public Health, Lexington, KY 40563, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, School of Medicine, Washington University, St Louis, MO 63108, USA
| | - W H Linda Kao
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - David S Siscovick
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA; The New York Academy of Medicine, New York, NY 10029, USA
| | - Bruce M Psaty
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA; Department of Health Services, University of Washington, Seattle, WA 98195, USA; Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Josée Dupuis
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA; National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Jose C Florez
- Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Andrew P Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Institute of Translational Medicine, Department of Biostatistics, University of Liverpool, Liverpool L69 3BX, UK
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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