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Rajab SAS, Andersen LK, Kenter LW, Berlinsky DL, Borski RJ, McGinty AS, Ashwell CM, Ferket PR, Daniels HV, Reading BJ. Combinatorial metabolomic and transcriptomic analysis of muscle growth in hybrid striped bass (female white bass Morone chrysops x male striped bass M. saxatilis). BMC Genomics 2024; 25:580. [PMID: 38858615 PMCID: PMC11165755 DOI: 10.1186/s12864-024-10325-y] [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: 08/30/2023] [Accepted: 04/19/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Understanding growth regulatory pathways is important in aquaculture, fisheries, and vertebrate physiology generally. Machine learning pattern recognition and sensitivity analysis were employed to examine metabolomic small molecule profiles and transcriptomic gene expression data generated from liver and white skeletal muscle of hybrid striped bass (white bass Morone chrysops x striped bass M. saxatilis) representative of the top and bottom 10 % by body size of a production cohort. RESULTS Larger fish (good-growth) had significantly greater weight, total length, hepatosomatic index, and specific growth rate compared to smaller fish (poor-growth) and also had significantly more muscle fibers of smaller diameter (≤ 20 µm diameter), indicating active hyperplasia. Differences in metabolomic pathways included enhanced energetics (glycolysis, citric acid cycle) and amino acid metabolism in good-growth fish, and enhanced stress, muscle inflammation (cortisol, eicosanoids) and dysfunctional liver cholesterol metabolism in poor-growth fish. The majority of gene transcripts identified as differentially expressed between groups were down-regulated in good-growth fish. Several molecules associated with important growth-regulatory pathways were up-regulated in muscle of fish that grew poorly: growth factors including agt and agtr2 (angiotensins), nicotinic acid (which stimulates growth hormone production), gadd45b, rgl1, zfp36, cebpb, and hmgb1; insulin-like growth factor signaling (igfbp1 and igf1); cytokine signaling (socs3, cxcr4); cell signaling (rgs13, rundc3a), and differentiation (rhou, mmp17, cd22, msi1); mitochondrial uncoupling proteins (ucp3, ucp2); and regulators of lipid metabolism (apoa1, ldlr). Growth factors pttg1, egfr, myc, notch1, and sirt1 were notably up-regulated in muscle of good-growing fish. CONCLUSION A combinatorial pathway analysis using metabolomic and transcriptomic data collectively suggested promotion of cell signaling, proliferation, and differentiation in muscle of good-growth fish, whereas muscle inflammation and apoptosis was observed in poor-growth fish, along with elevated cortisol (an anti-inflammatory hormone), perhaps related to muscle wasting, hypertrophy, and inferior growth. These findings provide important biomarkers and mechanisms by which growth is regulated in fishes and other vertebrates as well.
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Affiliation(s)
- Sarah A S Rajab
- Department of Applied Ecology, North Carolina State University, 100 Eugene Brooks Avenue, Box 7617, Raleigh, NC, 27695, USA
| | - Linnea K Andersen
- Department of Applied Ecology, North Carolina State University, 100 Eugene Brooks Avenue, Box 7617, Raleigh, NC, 27695, USA
| | - Linas W Kenter
- Department of Agriculture, Nutrition, and Food Systems, University of New Hampshire, Durham, NH, USA
| | - David L Berlinsky
- Department of Agriculture, Nutrition, and Food Systems, University of New Hampshire, Durham, NH, USA
| | - Russell J Borski
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Andrew S McGinty
- North Carolina State University, Pamlico Aquaculture Field Laboratory, Aurora, NC, USA
| | - Christopher M Ashwell
- Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC, USA
| | - Peter R Ferket
- Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC, USA
| | - Harry V Daniels
- Department of Applied Ecology, North Carolina State University, 100 Eugene Brooks Avenue, Box 7617, Raleigh, NC, 27695, USA
| | - Benjamin J Reading
- Department of Applied Ecology, North Carolina State University, 100 Eugene Brooks Avenue, Box 7617, Raleigh, NC, 27695, USA.
- North Carolina State University, Pamlico Aquaculture Field Laboratory, Aurora, NC, USA.
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Venkatachalapathy P, Padhilahouse S, Sellappan M, Subramanian T, Kurian SJ, Miraj SS, Rao M, Raut AA, Kanwar RK, Singh J, Khadanga S, Mondithoka S, Munisamy M. Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice. Pharmgenomics Pers Med 2021; 14:1441-1455. [PMID: 34803393 PMCID: PMC8598203 DOI: 10.2147/pgpm.s329787] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 10/04/2021] [Indexed: 12/20/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient's genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and "multiomics" studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.
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Affiliation(s)
| | - Sruthi Padhilahouse
- Department of Pharmacy Practice, Karpagam College of Pharmacy, Coimbatore, Tamilnadu, India
| | - Mohan Sellappan
- Department of Pharmacy Practice, Karpagam College of Pharmacy, Coimbatore, Tamilnadu, India
| | | | - Shilia Jacob Kurian
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Sonal Sekhar Miraj
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Mahadev Rao
- Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Ashwin Ashok Raut
- Translational Medicine Centre, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Rupinder Kaur Kanwar
- Translational Medicine Centre, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Jitendra Singh
- Translational Medicine Centre, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Sagar Khadanga
- Department of General Medicine, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Sukumar Mondithoka
- Department of General Medicine, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
| | - Murali Munisamy
- Translational Medicine Centre, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
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3
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Alsulami S, Bodhini D, Sudha V, Shanthi Rani CS, Pradeepa R, Anjana RM, Radha V, Lovegrove JA, Gayathri R, Mohan V, Vimaleswaran KS. Lower Dietary Intake of Plant Protein Is Associated with Genetic Risk of Diabetes-Related Traits in Urban Asian Indian Adults. Nutrients 2021; 13:3064. [PMID: 34578944 PMCID: PMC8466015 DOI: 10.3390/nu13093064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 01/19/2023] Open
Abstract
The increasing prevalence of type 2 diabetes among South Asians is caused by a complex interplay between environmental and genetic factors. We aimed to examine the impact of dietary and genetic factors on metabolic traits in 1062 Asian Indians. Dietary assessment was performed using a validated semi-quantitative food frequency questionnaire. Seven single nucleotide polymorphisms (SNPs) from the Transcription factor 7-like 2 and fat mass and obesity-associated genes were used to construct two metabolic genetic risk scores (GRS): 7-SNP and 3-SNP GRSs. Both 7-SNP GRS and 3-SNP GRS were associated with a higher risk of T2D (p = 0.0000134 and 0.008, respectively). The 3-SNP GRS was associated with higher waist circumference (p = 0.010), fasting plasma glucose (FPG) (p = 0.002) and glycated haemoglobin (HbA1c) (p = 0.000066). There were significant interactions between 3-SNP GRS and protein intake (% of total energy intake) on FPG (Pinteraction = 0.011) and HbA1c (Pinteraction = 0.007), where among individuals with lower plant protein intake (<39 g/day) and those with >1 risk allele had higher FPG (p = 0.001) and HbA1c (p = 0.00006) than individuals with ≤1 risk allele. Our findings suggest that lower plant protein intake may be a contributor to the increased ethnic susceptibility to diabetes described in Asian Indians. Randomised clinical trials with increased plant protein in the diets of this population are needed to see whether the reduction of diabetes risk occurs in individuals with prediabetes.
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Affiliation(s)
- Sooad Alsulami
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6DZ, UK; (S.A.); (J.A.L.)
- Department of Clinical Nutrition, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai 603103, India; (D.B.); (V.R.)
| | - Vasudevan Sudha
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai 600086, India; (V.S.); (R.G.)
| | | | - Rajendra Pradeepa
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.P.); (R.M.A.); (V.M.)
| | - Ranjit Mohan Anjana
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.P.); (R.M.A.); (V.M.)
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai 603103, India; (D.B.); (V.R.)
| | - Julie A. Lovegrove
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6DZ, UK; (S.A.); (J.A.L.)
| | - Rajagopal Gayathri
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai 600086, India; (V.S.); (R.G.)
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan’s Diabetes Specialities Centre, WHO Collaborating Centre for Non-Communicable Diseases Prevention and Control, ICMR Centre for Advanced Research on Diabetes, Gopalapuram, Chennai 600086, India; (R.P.); (R.M.A.); (V.M.)
| | - Karani Santhanakrishnan Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading RG6 6DZ, UK; (S.A.); (J.A.L.)
- The Institute for Food, Nutrition, and Health (IFNH), University of Reading, Reading RG6 6AP, UK
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SAINI SIMMI, WALIA GAGANDEEPKAUR, SACHDEVA MOHINDERPAL, GUPTA VIPIN. Genomics of body fat distribution. J Genet 2021. [DOI: 10.1007/s12041-021-01281-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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5
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Walia GK, Saini S, Vimal P, Bhatia K, Kumar A, Singh R, Prabhakaran D, Gupta V. Association of MC4R (rs17782313) gene polymorphism with obesity measures in Western India. Diabetes Metab Syndr 2021; 15:661-665. [PMID: 33813238 DOI: 10.1016/j.dsx.2021.03.013] [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: 07/07/2020] [Revised: 03/08/2021] [Accepted: 03/15/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND AIMS The association of melanocortin receptor 4 (MC4R) gene with adiposity measures is widely studied in European populations. Only six studies have investigated the role of MC4R gene with adiposity measures among Indian populations. We have evaluated the role of MC4R (rs17782313) gene polymorphism in influencing adiposity measures in India among children and adults. MATERIALS AND METHODS The present population based cross sectional study was conducted among 303 individuals (208 children and 95 adults) of age group 10-30 years, belonging to Rajasthan. Somatometric measurements (standing height, weight, and waist and hip girths) and blood samples were taken after obtaining written informed consent. Genotyping of MC4R rs17782313 single nucleotide polymorphism was done using restriction fragment length polymorphism method for polymerase chain reaction amplified fragments. We examined association between rs17782313 and different adiposity measures (height, weight, BMI, WHR, and waist and hip girths) using linear regression models. RESULTS The MC4R variant (rs17782313) predicted increased body weight (0.15 kg, S.E ± 0.076, P = 0.043) among children. In combined population, the rs17782313 variant was moderately associated with body weight (0.13 kg, S.E ± 0.070, P = 0.057). This variant was not found to be associated with any other adiposity measure. CONCLUSION Further studies are needed to evaluate the association of MC4R variants through sequencing and functional genomics with different adiposity measures in Indian populations for understanding the genetic underpinnings of adiposity in India.
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Affiliation(s)
| | - Simmi Saini
- Department of Anthropology, University of Delhi, India.
| | - Pradeep Vimal
- Indian Institute of Public Health- Delhi, Public Health Foundation of India, Gurugram, India.
| | | | - Arun Kumar
- Department of Anthropology, University of Delhi, India.
| | - Ranjana Singh
- Indian Institute of Public Health- Delhi, Public Health Foundation of India, Gurugram, India.
| | | | - Vipin Gupta
- Department of Anthropology, University of Delhi, India.
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Wang L, Sinnott-Armstrong N, Wagschal A, Wark AR, Camporez JP, Perry RJ, Ji F, Sohn Y, Oh J, Wu S, Chery J, Moud BN, Saadat A, Dankel SN, Mellgren G, Tallapragada DSP, Strobel SM, Lee MJ, Tewhey R, Sabeti PC, Schaefer A, Petri A, Kauppinen S, Chung RT, Soukas A, Avruch J, Fried SK, Hauner H, Sadreyev RI, Shulman GI, Claussnitzer M, Näär AM. A MicroRNA Linking Human Positive Selection and Metabolic Disorders. Cell 2020; 183:684-701.e14. [PMID: 33058756 PMCID: PMC8092355 DOI: 10.1016/j.cell.2020.09.017] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 05/08/2020] [Accepted: 09/03/2020] [Indexed: 01/09/2023]
Abstract
Positive selection in Europeans at the 2q21.3 locus harboring the lactase gene has been attributed to selection for the ability of adults to digest milk to survive famine in ancient times. However, the 2q21.3 locus is also associated with obesity and type 2 diabetes in humans, raising the possibility that additional genetic elements in the locus may have contributed to evolutionary adaptation to famine by promoting energy storage, but which now confer susceptibility to metabolic diseases. We show here that the miR-128-1 microRNA, located at the center of the positively selected locus, represents a crucial metabolic regulator in mammals. Antisense targeting and genetic ablation of miR-128-1 in mouse metabolic disease models result in increased energy expenditure and amelioration of high-fat-diet-induced obesity and markedly improved glucose tolerance. A thrifty phenotype connected to miR-128-1-dependent energy storage may link ancient adaptation to famine and modern metabolic maladaptation associated with nutritional overabundance.
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Affiliation(s)
- Lifeng Wang
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,These authors contributed equally,Present address: Cardiovascular & Metabolism, Janssen Pharmaceutical Companies of Johnson & Johnson, Spring House, PA 19477, USA
| | - Nasa Sinnott-Armstrong
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA,These authors contributed equally
| | - Alexandre Wagschal
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,Present address: Vertex Pharmaceuticals, Watertown, MA 02472, USA
| | - Abigail R. Wark
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Joao-Paulo Camporez
- Departments of Internal Medicine and Cellular & Molecular Physiology, Yale School of Medicine, New Haven, CT 06510, USA,Present address: Ribeirao Preto School of Medicine, University of Sao Paulo, Sao Paulo 14049-90, Brazil
| | - Rachel J. Perry
- Departments of Internal Medicine and Cellular & Molecular Physiology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Fei Ji
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Yoojin Sohn
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,Present address: Vanderbilt University, Nashville, TN 37235, USA
| | - Justin Oh
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,Present address: Vertex Pharmaceuticals, Watertown, MA 02472, USA
| | - Su Wu
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,Present address: Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
| | - Jessica Chery
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,Present address: Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Bahareh Nemati Moud
- Else Kroener-Fresenius-Center of Nutritional Medicine, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Alham Saadat
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Simon N. Dankel
- Mohn Nutrition Research Laboratory, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway,Hormone Laboratory, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, 5020 Bergen, Norway
| | - Gunnar Mellgren
- Mohn Nutrition Research Laboratory, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway,Hormone Laboratory, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, 5020 Bergen, Norway
| | - Divya Sri Priyanka Tallapragada
- Mohn Nutrition Research Laboratory, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway,Hormone Laboratory, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, 5020 Bergen, Norway
| | - Sophie Madlen Strobel
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, 80992 Munich, Germany
| | - Mi-Jeong Lee
- Obesity Center, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA,Present address: Department of Human Nutrition, Food and Animal Sciences, University of Hawaii, Honolulu, HI 96822, USA
| | - Ryan Tewhey
- Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA,Present address: The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Anne Schaefer
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School ofMedicine atMount Sinai, New York, New York 10029, USA
| | - Andreas Petri
- Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, 2450 Copenhagen, Denmark
| | - Sakari Kauppinen
- Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, 2450 Copenhagen, Denmark
| | - Raymond T. Chung
- Liver Center, Gastrointestinal Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Alexander Soukas
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Department of Medicine, Center for Genomic Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, Boston, MA 02114, USA
| | - Joseph Avruch
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA,Department of Medicine, Harvard Medical School, Boston, MA 02114, USA,Diabetes unit, Medical Services, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Susan K. Fried
- Obesity Center, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA,Present address: Diabetes, Obesity and Metabolism Institute, Mt. Sinai School of Medicine, New York, NY 10029, USA
| | - Hans Hauner
- Else Kroener-Fresenius-Center of Nutritional Medicine, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany,Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, 80992 Munich, Germany
| | - Ruslan I. Sadreyev
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gerald I. Shulman
- Departments of Internal Medicine and Cellular & Molecular Physiology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Anders M. Näär
- Massachusetts General Hospital Cancer Center, Charlestown, MA 02129, USA,Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA,Present address: Department of Nutritional Sciences & Toxicology, University of California, Berkeley, Berkeley, CA 94720, USA,Lead Contact,Correspondence: https://doi.org/10.1016/j.cell.2020.09.017
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7
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Saini S, Walia GK, Sachdeva MP, Gupta V. Genetics of obesity and its measures in India. J Genet 2018; 97:1047-1071. [PMID: 30262717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Obesity is one of the largest global health problems associated with increased morbidity and mortality mediated by its association with several other metabolic disorders. The interaction between the genes and environment plays an important role in the manifestation of obesity. Despite a high heritability (40-70%) of obesity, the search for genetic variants associated with obesity susceptibility has been a challenging task. To date, limited studies have been conducted in India, restricted to the validation of few genetic variants identified by genomewide association studies. In this critical review, we sought to examine the current knowledge of genetic basis of obesity and its measures in the Indian population. A comprehensive literature search was performed using 'PubMed', 'Medline' and 'IndMed' databases to search for citations published until 31st May 2017, using the key terms as 'Genetics' AND 'obesity' AND 'India'. We identified 48 potential studies which fulfilled the eligibility criteria. The findings indicated that FTO, MC4R, TNF-α, PPAR-γ , UCP1, UCP2, LPL, LEPR, AMD1, IL6, APOE, ADIPOQ, DOK5, INSIG2, PBEF1, IL6R, Myostatin, CXCR4, HHEX, IRX3, POMC, NGN3, FOXA2, MTR, TCN and CHDH are some of the important genes studied among the Indian population. Importantly, the role of sexual dimorphism in the genetic regulation of obesity and body fat distribution was also reported in a few studies. Further, seven biological pathways have been identified that contribute to obesity pathogenesis in India. In conclusion, further exploration of pathway-based research on genetics of obesity can be useful for better understanding the pathophysiology of obesity in India.
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Affiliation(s)
- Simmi Saini
- Department of Anthropology, University of Delhi, Delhi 110 007, India.
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8
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Saini S, Walia GK, Sachdeva MP, Gupta V. Genetics of obesity and its measures in India. J Genet 2018. [DOI: 10.1007/s12041-018-0987-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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9
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Moraru A, Cakan-Akdogan G, Strassburger K, Males M, Mueller S, Jabs M, Muelleder M, Frejno M, Braeckman BP, Ralser M, Teleman AA. THADA Regulates the Organismal Balance between Energy Storage and Heat Production. Dev Cell 2017; 41:72-81.e6. [PMID: 28399403 PMCID: PMC5392496 DOI: 10.1016/j.devcel.2017.03.016] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 02/22/2017] [Accepted: 03/15/2017] [Indexed: 11/25/2022]
Abstract
Human susceptibility to obesity is mainly genetic, yet the underlying evolutionary drivers causing variation from person to person are not clear. One theory rationalizes that populations that have adapted to warmer climates have reduced their metabolic rates, thereby increasing their propensity to store energy. We uncover here the function of a gene that supports this theory. THADA is one of the genes most strongly selected during evolution as humans settled in different climates. We report here that THADA knockout flies are obese, hyperphagic, have reduced energy production, and are sensitive to the cold. THADA binds the sarco/ER Ca2+ ATPase (SERCA) and acts on it as an uncoupler. Reducing SERCA activity in THADA mutant flies rescues their obesity, pinpointing SERCA as a key effector of THADA function. In sum, this identifies THADA as a regulator of the balance between energy consumption and energy storage, which was selected during human evolution. Drosophila knockouts of the conserved gene THADA are obese and hyperphagic THADA knockouts produce less heat and are cold sensitive THADA binds SERCA and uncouples its ATP hydrolysis from Ca2+ pumping Reducing SERCA activity rescues the THADA loss-of-function phenotypes
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Affiliation(s)
| | | | | | - Matilda Males
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Sandra Mueller
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Markus Jabs
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Michael Muelleder
- Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK; Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - Martin Frejno
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | | | - Markus Ralser
- Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK; Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
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Corella D, Coltell O, Sorlí JV, Estruch R, Quiles L, Martínez-González MÁ, Salas-Salvadó J, Castañer O, Arós F, Ortega-Calvo M, Serra-Majem L, Gómez-Gracia E, Portolés O, Fiol M, Díez Espino J, Basora J, Fitó M, Ros E, Ordovás JM. Polymorphism of the Transcription Factor 7-Like 2 Gene (TCF7L2) Interacts with Obesity on Type-2 Diabetes in the PREDIMED Study Emphasizing the Heterogeneity of Genetic Variants in Type-2 Diabetes Risk Prediction: Time for Obesity-Specific Genetic Risk Scores. Nutrients 2016; 8:E793. [PMID: 27929407 PMCID: PMC5188448 DOI: 10.3390/nu8120793] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 11/17/2016] [Accepted: 11/17/2016] [Indexed: 11/24/2022] Open
Abstract
Nutrigenetic studies analyzing gene-diet interactions of the TCF7L2-rs7903146 C > T polymorphism on type-2 diabetes (T2D) have shown controversial results. A reason contributing to this may be the additional modulation by obesity. Moreover, TCF7L2-rs7903146 is one of the most influential variants in T2D-genetic risk scores (GRS). Therefore, to increase the predictive value (PV) of GRS it is necessary to first see whether the included polymorphisms have heterogeneous effects. We comprehensively investigated gene-obesity interactions between the TCF7L2-rs7903146 C > T polymorphism on T2D (prevalence and incidence) and analyzed other T2D-polymorphisms in a sub-sample. We studied 7018 PREDIMED participants at baseline and longitudinally (8.7 years maximum follow-up). Obesity significantly interacted with the TCF7L2-rs7903146 on T2D prevalence, associations being greater in non-obese subjects. Accordingly, we prospectively observed in non-T2D subjects (n = 3607) that its association with T2D incidence was stronger in non-obese (HR: 1.81; 95% CI: 1.13-2.92, p = 0.013 for TT versus CC) than in obese subjects (HR: 1.01; 95% CI: 0.61-1.66; p = 0.979; p-interaction = 0.048). Accordingly, TCF7L2-PV was higher in non-obese subjects. Additionally, we created obesity-specific GRS with ten T2D-polymorphisms and demonstrated for the first time their higher strata-specific PV. In conclusion, we provide strong evidence supporting the need for considering obesity when analyzing the TCF7L2 effects and propose the use of obesity-specific GRS for T2D.
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Affiliation(s)
- Dolores Corella
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Oscar Coltell
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Computer Languages and Systems, School of Technology and Experimental Sciences, Universitat Jaume I, 12071 Castellón, Spain.
| | - Jose V Sorlí
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Ramón Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Internal Medicine, Hospital Clinic, IDIBAPS, 08036 Barcelona, Spain.
| | - Laura Quiles
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Miguel Ángel Martínez-González
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, University of Navarra-Navarra Institute for Health Research (IdisNa), 31009 Pamplona, Spain.
| | - Jordi Salas-Salvadó
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Human Nutrition Unit, Biochemistry and Biotechnology Department, IISPV, University Rovira i Virgili, 43003 Reus, Spain.
| | - Olga Castañer
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain.
| | - Fernando Arós
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Cardiology, Hospital Txagorritxu, 01009 Vitoria, Spain.
| | - Manuel Ortega-Calvo
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Family Medicine, Distrito Sanitario Atención Primaria Sevilla, Centro de Salud Las Palmeritas, 41003 Sevilla, Spain.
| | - Lluís Serra-Majem
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, 35001 Las Palmas de Gran Canaria, Spain.
| | - Enrique Gómez-Gracia
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Epidemiology, School of Medicine, University of Malaga, 29071 Malaga, Spain.
| | - Olga Portolés
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, 46010 Valencia, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - Miquel Fiol
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Palma Institute of Health Research (IdISPa), Hospital Son Espases, 07014 Palma de Mallorca, Spain.
| | - Javier Díez Espino
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Department of Preventive Medicine and Public Health, University of Navarra-Navarra Institute for Health Research (IdisNA)-Servicio Navarro de Salud-Osasunbidea, 31009 Pamplona, Spain.
| | - Josep Basora
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Human Nutrition Unit, Biochemistry and Biotechnology Department, IISPV, University Rovira i Virgili, 43003 Reus, Spain.
| | - Montserrat Fitó
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain.
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Lipid Clinic, Endocrinology and Nutrition Service, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, 08036 Barcelona, Spain.
| | - José M Ordovás
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain.
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA.
- Department of Cardiovascular Epidemiology and Population Genetics, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid 28029-IMDEA Alimentación, 28049 Madrid, Spain.
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11
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Tarnowski M, Malinowski D, Safranow K, Dziedziejko V, Czerewaty M, Pawlik A. Hematopoietically expressed homeobox (HHEX) gene polymorphism (rs5015480) is associated with increased risk of gestational diabetes mellitus. Clin Genet 2016; 91:843-848. [PMID: 27684496 DOI: 10.1111/cge.12875] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 09/21/2016] [Accepted: 09/25/2016] [Indexed: 01/01/2023]
Abstract
Gestational diabetes mellitus (GDM) is a metabolic disorder that occurs during pregnancy. HHEX and PROX1 are genetic loci associated with diabetes mellitus type 2. HHEX and PROX1 play significant roles in carbohydrate intolerance and diabetes because these transcription factors may be involved in the regulation of insulin secretion and in glucose and lipid metabolism. The aim of this study was to examine the association between HHEX (rs5015480) and PROX1 (rs340874) gene polymorphisms and GDM. This study included 204 pregnant women with GDM and 207 pregnant women with the normal glucose tolerance (NGT). The diagnosis of GDM was based on a 75-g oral glucose tolerance test at 24-28 weeks' gestation. There was a statistically significant prevalence of the HHEX rs5015480 CC genotype and C allele among women with GDM (C vs T allele, p = 0.021, odds ratio OR = 1.40, 95% CI: 1.05-1.87). Statistically significant higher increase of body mass and BMI during pregnancy was found in women with the HHEX rs5015480 CC genotype. The results of our study suggest an association between the HHEX gene rs5015480 polymorphism and risk of GDM. The HHEX gene rs5015480 C allele may be a risk allele of GDM that is associated with increased BMI during pregnancy.
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Affiliation(s)
- M Tarnowski
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
| | - D Malinowski
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
| | - K Safranow
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, Szczecin, Poland
| | - V Dziedziejko
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, Szczecin, Poland
| | - M Czerewaty
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
| | - A Pawlik
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
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Casarini L, Simoni M, Brigante G. Is polycystic ovary syndrome a sexual conflict? A review. Reprod Biomed Online 2016; 32:350-61. [DOI: 10.1016/j.rbmo.2016.01.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 01/20/2016] [Accepted: 01/21/2016] [Indexed: 12/23/2022]
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13
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Yako YY, Guewo-Fokeng M, Balti EV, Bouatia-Naji N, Matsha TE, Sobngwi E, Erasmus RT, Echouffo-Tcheugui JB, Kengne AP. Genetic risk of type 2 diabetes in populations of the African continent: A systematic review and meta-analyses. Diabetes Res Clin Pract 2016; 114:136-50. [PMID: 26830076 DOI: 10.1016/j.diabres.2016.01.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Revised: 11/27/2015] [Accepted: 01/03/2016] [Indexed: 12/11/2022]
Abstract
BACKGROUND Type 2 diabetes (T2D) is growing faster in Africa than anywhere else, driven by the dual effects of genetic and environmental factors. We conducted a systematic review and meta-analyses of published studies on genetic markers of T2D in populations within Africa. METHODS Multiple databases were searched for studies of genetic variants associated with T2D in populations living in Africa. Studies reporting on the association of a genetic marker with T2D or indicators of glycaemia were included. Data were extracted on study design and characteristics, genetic determinants, effect estimates of associations with T2D. FINDINGS Overall, 100 polymorphisms in 57 genes have been investigated in relation with T2D in populations within Africa, in 60 studies. Almost all studies used the candidate gene approach, with >88% published during 2006-2014 and 70% (42/60) originating from Tunisia and Egypt. Polymorphisms in ACE, AGRP, eNOS, GSTP1, HSP70-2, MC4R, MTHFR, PHLPP, POL1, TCF7L2, and TNF-α gene were found to be associated with T2D, with overlapping effect on various cardiometabolic traits. The polymorphisms investigated in multiple studies mostly had consistent effects across studies, with only modest or no statistical heterogeneity. Effect sizes were modestly significant [e.g., odd ratio 1.49 (95%CI 1.33-1.66) for TCF7L2 (rs7903146)]. Underpowered genome-wide studies revealed no diabetes risk loci specific to African populations. INTERPRETATION Current evidence on the genetic markers of T2D in African populations mostly originate from North African countries, is overall scanty and largely insufficient to reliably inform the genetic architecture of T2D across Africa.
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Affiliation(s)
- Yandiswa Y Yako
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa; Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
| | - Magellan Guewo-Fokeng
- Department of Biochemistry, Faculty of Science, University of Yaounde I, Yaounde, Cameroon
| | - Eric V Balti
- Diabetes Research Center, Faculty of Medicine and Pharmacy, Brussels Free University, Brussels, Belgium
| | - Nabila Bouatia-Naji
- INSERM UMR970 Paris Cardiovascular Research Center, 56 rue Leblanc F-75015 Paris, France; Paris Descartes University, PRES Paris Sorbonne, 12 rue de l'école de medecine F75006 Paris, France
| | - Tandi E Matsha
- Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
| | - Eugene Sobngwi
- Department of Internal Medicine, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaounde, Cameroon
| | - Rajiv T Erasmus
- Division of Chemical Pathology, Faculty of Medicine and Health Sciences, National Health Laboratory Service (NHLS), University of Stellenbosch, Cape Town, South Africa
| | - Justin B Echouffo-Tcheugui
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Medicine, MedStar Health System, Baltimore, MD, USA
| | - Andre P Kengne
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa; Department of Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa; The George Institute for Global Health, The University of Sydney, Sydney, NSW, Australia.
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14
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15
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Srivastava A, Srivastava N, Mittal B. Genetics of Obesity. Indian J Clin Biochem 2015; 31:361-71. [PMID: 27605733 DOI: 10.1007/s12291-015-0541-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2015] [Accepted: 12/08/2015] [Indexed: 12/29/2022]
Abstract
Numerous classical genetic studies have proved that genes are contributory factors for obesity. Genes are directly responsible for obesity associated disorders such as Bardet-Biedl and Prader-Willi syndromes. However, both genes as well as environment are associated with obesity in the general population. Genetic epidemiological approaches, particularly genome-wide association studies, have unraveled many genes which play important roles in human obesity. Elucidation of their biological functions can be very useful for understanding pathobiology of obesity. In the near future, further exploration of obesity genetics may help to develop useful diagnostic and predictive tests for obesity treatment.
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Affiliation(s)
- Apurva Srivastava
- Department of Medical Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh 226014 India ; Department of Physiology, King George's Medical University, Chowk, Lucknow, Uttar Pradesh 226003 India
| | - Neena Srivastava
- Department of Physiology, King George's Medical University, Chowk, Lucknow, Uttar Pradesh 226003 India
| | - Balraj Mittal
- Department of Medical Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh 226014 India
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16
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A case-control association study of K121Q (rs 1044498) and G/T (rs 1225572) variants in ENPP1 and TCF7L2 genes with type 2 diabetes mellitus in north Indian Punjabi population. Int J Diabetes Dev Ctries 2015. [DOI: 10.1007/s13410-015-0337-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/06/2022] Open
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17
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Amisten S, Neville M, Hawkes R, Persaud SJ, Karpe F, Salehi A. An atlas of G-protein coupled receptor expression and function in human subcutaneous adipose tissue. Pharmacol Ther 2015; 146:61-93. [PMID: 25242198 DOI: 10.1016/j.pharmthera.2014.09.007] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Accepted: 09/09/2014] [Indexed: 12/17/2022]
Abstract
G-protein coupled receptors (GPCRs) are involved in the regulation of adipose tissue function, but the total number of GPCRs expressed by human subcutaneous adipose tissue, as well as their function and interactions with drugs, is poorly understood. We have constructed an atlas of all GPCRs expressed by human subcutaneous adipose tissue: the 'adipose tissue GPCRome', to support the exploration of novel control nodes in metabolic and endocrine functions. This atlas describes how adipose tissue GPCRs regulate lipolysis, insulin resistance and adiponectin and leptin secretion. We also discuss how adipose tissue GPCRs interact with their endogenous ligands and with GPCR-targeting drugs, with a focus on how drug/receptor interactions may affect lipolysis, and present a model predicting how GPCRs with unknown effects on lipolysis might modulate cAMP-regulated lipolysis. Subcutaneous adipose tissue expresses 163 GPCRs, a majority of which have unknown effects on lipolysis, insulin resistance and adiponectin and leptin secretion. These GPCRs are activated by 180 different endogenous ligands, and are the targets of a large number of clinically used drugs. We identified 119 drugs, acting on 23 GPCRs, that are predicted to stimulate lipolysis and 173 drugs, acting on 25 GPCRs, that are predicted to inhibit lipolysis. This atlas highlights knowledge gaps in the current understanding of adipose tissue GPCR function, and identifies GPCR/ligand/drug interactions that might affect lipolysis, which is important for understanding and predicting metabolic side effects of drugs. This approach may aid in the design of new, safer therapeutic agents, with fewer undesired effects on lipid homeostasis.
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Affiliation(s)
- Stefan Amisten
- Diabetes Research Group, Division of Diabetes & Nutritional Sciences, King's College London, Faculty of Life Sciences & Medicine, London, UK; Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK.
| | - Matt Neville
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LE, UK
| | - Ross Hawkes
- Diabetes Research Group, Division of Diabetes & Nutritional Sciences, King's College London, Faculty of Life Sciences & Medicine, London, UK
| | - Shanta J Persaud
- Diabetes Research Group, Division of Diabetes & Nutritional Sciences, King's College London, Faculty of Life Sciences & Medicine, London, UK
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LE, UK.
| | - Albert Salehi
- Department of Clinical Science, UMAS, Clinical Research Center, University of Lund, Sweden
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Abstract
Proneural genes encode evolutionarily conserved basic-helix-loop-helix transcription factors. In Drosophila, proneural genes are required and sufficient to confer a neural identity onto naïve ectodermal cells, inducing delamination and subsequent neuronal differentiation. In vertebrates, proneural genes are expressed in cells that already have a neural identity, but they are still required and sufficient to initiate neurogenesis. In all organisms, proneural genes control neurogenesis by regulating Notch-mediated lateral inhibition and initiating the expression of downstream differentiation genes. The general mode of proneural gene function has thus been elucidated. However, the regulatory mechanisms that spatially and temporally control proneural gene function are only beginning to be deciphered. Understanding how proneural gene function is regulated is essential, as aberrant proneural gene expression has recently been linked to a variety of human diseases-ranging from cancer to neuropsychiatric illnesses and diabetes. Recent insights into proneural gene function in development and disease are highlighted herein.
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Affiliation(s)
- Carol Huang
- Department of Pediatrics, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Jennifer A Chan
- Department of Pathology & Laboratory Medicine, Southern Alberta Cancer Research Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Carol Schuurmans
- Department of Biochemistry and Molecular Biology, Alberta Children's Hospital Research Institute, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
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