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Pérez-Pérez A, Sánchez-Jiménez F, Vilariño-García T, Sánchez-Margalet V. Role of Leptin in Inflammation and Vice Versa. Int J Mol Sci 2020; 21:E5887. [PMID: 32824322 PMCID: PMC7460646 DOI: 10.3390/ijms21165887] [Citation(s) in RCA: 140] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 08/07/2020] [Accepted: 08/14/2020] [Indexed: 12/15/2022] Open
Abstract
Inflammation is an essential immune response for the maintenance of tissue homeostasis. In a general sense, acute and chronic inflammation are different types of adaptive response that are called into action when other homeostatic mechanisms are insufficient. Although considerable progress has been made in understanding the cellular and molecular events that are involved in the acute inflammatory response to infection and tissue injury, the causes and mechanisms of systemic chronic inflammation are much less known. The pathogenic capacity of this type of inflammation is puzzling and represents a common link of the multifactorial diseases, such as cardiovascular diseases and type 2 diabetes. In recent years, interest has been raised by the discovery of novel mediators of inflammation, such as microRNAs and adipokines, with different effects on target tissues. In the present review, we discuss the data emerged from research of leptin in obesity as an inflammatory mediator sustaining multifactorial diseases and how this knowledge could be instrumental in the design of leptin-based manipulation strategies to help restoration of abnormal immune responses. On the other direction, chronic inflammation, either from autoimmune or infectious diseases, or impaired microbiota (dysbiosis) may impair the leptin response inducing resistance to the weight control, and therefore it may be a cause of obesity. Thus, we are reviewing the published data regarding the role of leptin in inflammation, and the other way around, the role of inflammation on the development of leptin resistance and obesity.
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Affiliation(s)
- Antonio Pérez-Pérez
- Department of Medical Biochemistry and Molecular Biology, and Immunology, Virgen Macarena University Hospital, University of Seville, 41009 Seville, Spain; (F.S.-J.); (T.V.-G.)
| | | | | | - Víctor Sánchez-Margalet
- Department of Medical Biochemistry and Molecular Biology, and Immunology, Virgen Macarena University Hospital, University of Seville, 41009 Seville, Spain; (F.S.-J.); (T.V.-G.)
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Micro(RNA) Management and Mismanagement of the Islet. J Mol Biol 2020; 432:1419-1428. [DOI: 10.1016/j.jmb.2019.09.017] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 09/10/2019] [Accepted: 09/15/2019] [Indexed: 02/08/2023]
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Romeo S, Sanyal A, Valenti L. Leveraging Human Genetics to Identify Potential New Treatments for Fatty Liver Disease. Cell Metab 2020; 31:35-45. [PMID: 31914377 DOI: 10.1016/j.cmet.2019.12.002] [Citation(s) in RCA: 144] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 10/07/2019] [Accepted: 12/06/2019] [Indexed: 02/08/2023]
Abstract
Fatty liver disease (FLD), including its more severe pathologies, namely steatohepatitis, hepatocarcinoma, and cirrhosis, is the most common cause of chronic liver disease worldwide and is projected to become the leading cause of hepatocellular carcinoma and end-stage liver disease. FLD is heterogeneous with multiple etiologies and diverse histological phenotypes, so therapies will ultimately need to be individualized for relevant targets. Inherited factors contribute to FLD, and most of the genetic variation influencing liver disease development and progression is derived from genes involved in lipid biology, including PNPLA3, TM6SF2, GCKR, MBOAT7, and HSD17B13. From this point of view, we focus in this perspective on how human molecular genetics of FLD have highlighted defects in hepatic lipid handling as a major common mechanism of its pathology and how this insight could be leveraged to treat and prevent its more serious complications.
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Affiliation(s)
- Stefano Romeo
- Department of Molecular and Clinical Medicine, University of Gothenburg, Gothenburg, Sweden; Clinical Nutrition Unit, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy; Cardiology Department, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Arun Sanyal
- Division of Gastroenterology and Hepatology, Department of Medicine, Virginia Commonwealth University, Richmond, VA, USA.
| | - Luca Valenti
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Translational Medicine, Department of Transfusion Medicine and Hematology, Fondazione IRCCS Ca' Granda, Pad Marangoni, Milan, Italy.
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Meta-analyses of the association of G6PC2 allele variants with elevated fasting glucose and type 2 diabetes. PLoS One 2017; 12:e0181232. [PMID: 28704540 PMCID: PMC5509327 DOI: 10.1371/journal.pone.0181232] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 06/28/2017] [Indexed: 12/19/2022] Open
Abstract
Objective To collectively evaluate the association of glucose-6-phosphatase catalytic unit 2 (G6PC2) allele variants with elevated fasting glucose (FG) and type 2 diabetes (T2D). Design Meta-analysis Data sources PubMed, Web of Knowledge and Embase databases. Study selection Full text articles of studies that identified an association of G6PC2 with T2D and elevated FG. Patient involvement There was no T2D patient involvement in the analyses on the association of FG with G6PC2, there were T2D patients and non-diabetes patient involvement in the analyses on the association of T2D with G6PC2. Statistical analysis Random-effects meta-analyses were used to calculate the pool effect sizes. I2 metric and H2 tests were used to calculate the heterogeneity. Begg's funnel plot and Egger’s linear regression test were done to assess publication bias. Results Of the 423 studies identified, 21 were eligible and included. Data on three loci (rs560887, rs16856187 and rs573225) were available. The G allele at rs560887 in three ethnicities, the C allele at rs16856187 and the A allele at rs573225 all had a positive association with elevated FG. Per increment of G allele at rs560887 and A allele at rs573225 resulted in a FG 0.070 mmol/l and 0.075 mmol/l higher (ß (95% CI) = 0.070 (0.060, 0.079), p = 4.635e-50 and 0.075 (0.065, 0.085), p = 5.856e-48, respectively). With regard to the relationship of rs16856187 and FG, an increase of 0.152 (95% CI: 0.034–0.270; p = 0.011) and 0.317 (95% CI: 0.193–0.442, p = 6.046e-07) was found in the standardized mean difference (SMD) of FG for the AC and CC genotypes, respectively, when compared with the AA reference genotype. However, the G-allele of rs560887 in Caucasians under the additive model and the C-allele of rs16856187 under the allele and dominant models were associated with a decreased risk of T2D (OR (95% CI) = 0.964 (0.947, 0.981), p = 0.570e-4; OR (95% CI) = 0.892 (0.832, 0.956), p = 0.001; and OR (95% CI) = 0.923(0.892, 0.955), p = 5.301e-6, respectively). Conclusions Our meta-analyses demonstrate that all three allele variants of G6PC2 (rs560887, rs16856187 and rs573225) are associated with elevated FG, with two variants (rs560887 in the Caucasians subgroup and rs16856187 under the allele and dominant model) being associated with T2D as well. Further studies utilizing larger sample sizes and different ethnic populations are needed to extend and confirm these findings.
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Santoro N, Caprio S, Pierpont B, Van Name M, Savoye M, Parks EJ. Hepatic De Novo Lipogenesis in Obese Youth Is Modulated by a Common Variant in the GCKR Gene. J Clin Endocrinol Metab 2015; 100:E1125-32. [PMID: 26043229 PMCID: PMC4524990 DOI: 10.1210/jc.2015-1587] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
OBJECTIVE This study's aim was to evaluate whether the GCKR rs1260326 variant increases hepatic de novo lipogenesis (DNL). SETTING AND DESIGN To test this hypothesis, 14 adolescents, seven homozygous for the common allele (CC) and seven homozygous for the risk allele (TT), underwent measurement of hepatic DNL during the fasting state and after consumption of a carbohydrate (CHO) drink (75 g glucose and 25 g fructose). DNL was assessed through incorporation of deuterium in the palmitate contained in the very low-density lipoprotein. RESULTS Subjects with TT demonstrated higher fasting fractional DNL (P = .036) and a lower increase in fractional DNL after the CHO challenge (P = .016). With regard to absolute lipogenesis, TT subjects had both higher fasting rates (P = .015) and 44% greater area under the curve of absolute lipogenesis during the study (P = .016), compared to CC subjects. Furthermore, subjects carrying the TT genotype showed higher basal rates of glucose oxidation (P = .0028) and a lower ability than CC subjects to increase the rates of glucose oxidation after the CHO load (P = .054). CONCLUSIONS This study reports for the first time rates of DNL in obese adolescents and suggests that the GCKR rs1260326 gene variant, which is associated with greater glycolysis, increases hepatic DNL. These data highlight the role of glycolytic carbon flux in liver lipid synthesis and hypertriglyceridemia in these youngsters.
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Affiliation(s)
- Nicola Santoro
- Department of Pediatrics (N.S., S.C., B.P., M.V.N., M.S.), Yale University School of Medicine, New Haven, Connecticut 06520; and Department of Medicine (E.J.P.), University of Missouri, Colombia, Missouri 65211
| | - Sonia Caprio
- Department of Pediatrics (N.S., S.C., B.P., M.V.N., M.S.), Yale University School of Medicine, New Haven, Connecticut 06520; and Department of Medicine (E.J.P.), University of Missouri, Colombia, Missouri 65211
| | - Bridget Pierpont
- Department of Pediatrics (N.S., S.C., B.P., M.V.N., M.S.), Yale University School of Medicine, New Haven, Connecticut 06520; and Department of Medicine (E.J.P.), University of Missouri, Colombia, Missouri 65211
| | - Michelle Van Name
- Department of Pediatrics (N.S., S.C., B.P., M.V.N., M.S.), Yale University School of Medicine, New Haven, Connecticut 06520; and Department of Medicine (E.J.P.), University of Missouri, Colombia, Missouri 65211
| | - Mary Savoye
- Department of Pediatrics (N.S., S.C., B.P., M.V.N., M.S.), Yale University School of Medicine, New Haven, Connecticut 06520; and Department of Medicine (E.J.P.), University of Missouri, Colombia, Missouri 65211
| | - Elizabeth J Parks
- Department of Pediatrics (N.S., S.C., B.P., M.V.N., M.S.), Yale University School of Medicine, New Haven, Connecticut 06520; and Department of Medicine (E.J.P.), University of Missouri, Colombia, Missouri 65211
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Yue JK, Pronger AM, Ferguson AR, Temkin NR, Sharma S, Rosand J, Sorani MD, McAllister TW, Barber J, Winkler EA, Burchard EG, Hu D, Lingsma HF, Cooper SR, Puccio AM, Okonkwo DO, Diaz-Arrastia R, Manley GT. Association of a common genetic variant within ANKK1 with six-month cognitive performance after traumatic brain injury. Neurogenetics 2015; 16:169-80. [PMID: 25633559 DOI: 10.1007/s10048-015-0437-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2014] [Accepted: 01/02/2015] [Indexed: 01/18/2023]
Abstract
Genetic association analyses suggest that certain common single nucleotide polymorphisms (SNPs) may adversely impact recovery from traumatic brain injury (TBI). Delineating their causal relationship may aid in development of novel interventions and in identifying patients likely to respond to targeted therapies. We examined the influence of the (C/T) SNP rs1800497 of ANKK1 on post-TBI outcome using data from two prospective multicenter studies: the Citicoline Brain Injury Treatment (COBRIT) trial and Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot). We included patients with ANKK1 genotyping results and cognitive outcomes at six months post-TBI (n = 492: COBRIT n = 272, TRACK-TBI Pilot n = 220). Using the California Verbal Learning Test Second Edition (CVLT-II) Trial 1-5 Standard Score, we found a dose-dependent effect for the T allele, with T/T homozygotes scoring lowest on the CVLT-II Trial 1-5 Standard Score (T/T 45.1, C/T 51.1, C/C 52.1, ANOVA, p = 0.008). Post hoc testing with multiple comparison-correction indicated that T/T patients performed significantly worse than C/T and C/C patients. Similar effects were observed in a test of non-verbal processing (Wechsler Adult Intelligence Scale, Processing Speed Index). Our findings extend those of previous studies reporting a negative relationship of the ANKK1 T allele with cognitive performance after TBI. In this study, we demonstrate the value of pooling shared clinical, biomarker, and outcome variables from two large datasets applying the NIH TBI Common Data Elements. The results have implications for future multicenter investigations to further elucidate the role of ANKK1 in post-TBI outcome.
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Affiliation(s)
- John K Yue
- Brain and Spinal Injury Center, San Francisco General Hospital, San Francisco, CA, USA
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Kuivenhoven JA, Groen AK. Beyond the genetics of HDL: why is HDL cholesterol inversely related to cardiovascular disease? Handb Exp Pharmacol 2015; 224:285-300. [PMID: 25522992 DOI: 10.1007/978-3-319-09665-0_8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
There is unequivocal evidence that high-density lipoprotein (HDL) cholesterol levels in plasma are inversely associated with the risk of cardiovascular disease (CVD). Studies of families with inherited HDL disorders and genetic association studies in general (and patient) population samples have identified a large number of factors that control HDL cholesterol levels. However, they have not resolved why HDL cholesterol and CVD are inversely related. A growing body of evidence from nongenetic studies shows that HDL in patients at increased risk of CVD has lost its protective properties and that increasing the cholesterol content of HDL does not result in the desired effects. Hopefully, these insights can help improve strategies to successfully intervene in HDL metabolism. It is clear that there is a need to revisit the HDL hypothesis in an unbiased manner. True insights into the molecular mechanisms that regulate plasma HDL cholesterol and triglycerides or control HDL function could provide the handholds that are needed to develop treatment for, e.g., type 2 diabetes and the metabolic syndrome. Especially genome-wide association studies have provided many candidate genes for such studies. In this review we have tried to cover the main molecular studies that have been produced over the past few years. It is clear that we are only at the very start of understanding how the newly identified factors may control HDL metabolism. In addition, the most recent findings underscore the intricate relations between HDL, triglyceride, and glucose metabolism indicating that these parameters need to be studied simultaneously.
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Affiliation(s)
- J A Kuivenhoven
- Department of Pediatrics, Section Molecular Genetics, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713GZ, Groningen, The Netherlands,
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Flannick J, Thorleifsson G, Beer NL, Jacobs SBR, Grarup N, Burtt NP, Mahajan A, Fuchsberger C, Atzmon G, Benediktsson R, Blangero J, Bowden DW, Brandslund I, Brosnan J, Burslem F, Chambers J, Cho YS, Christensen C, Douglas DA, Duggirala R, Dymek Z, Farjoun Y, Fennell T, Fontanillas P, Forsén T, Gabriel S, Glaser B, Gudbjartsson DF, Hanis C, Hansen T, Hreidarsson AB, Hveem K, Ingelsson E, Isomaa B, Johansson S, Jørgensen T, Jørgensen ME, Kathiresan S, Kong A, Kooner J, Kravic J, Laakso M, Lee JY, Lind L, Lindgren CM, Linneberg A, Masson G, Meitinger T, Mohlke KL, Molven A, Morris AP, Potluri S, Rauramaa R, Ribel-Madsen R, Richard AM, Rolph T, Salomaa V, Segrè AV, Skärstrand H, Steinthorsdottir V, Stringham HM, Sulem P, Tai ES, Teo YY, Teslovich T, Thorsteinsdottir U, Trimmer JK, Tuomi T, Tuomilehto J, Vaziri-Sani F, Voight BF, Wilson JG, Boehnke M, McCarthy MI, Njølstad PR, Pedersen O, Groop L, Cox DR, Stefansson K, Altshuler D. Loss-of-function mutations in SLC30A8 protect against type 2 diabetes. Nat Genet 2014; 46:357-63. [PMID: 24584071 DOI: 10.1038/ng.2915] [Citation(s) in RCA: 361] [Impact Index Per Article: 32.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2013] [Accepted: 02/10/2014] [Indexed: 02/07/2023]
Abstract
Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ~150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10(-6)), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (-0.17 s.d., P = 4.6 × 10(-4)). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.
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Affiliation(s)
- Jason Flannick
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Nicola L Beer
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Suzanne B R Jacobs
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Noël P Burtt
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Christian Fuchsberger
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Gil Atzmon
- 1] Department of Medicine, Albert Einstein College of Medicine, Bronx, New York, USA. [2] Department of Genetics, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Rafn Benediktsson
- Department of Endocrinology and Metabolism, Landspitali University Hospital, Reykjavik, Iceland
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Don W Bowden
- 1] Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. [2] Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. [3] Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. [4] Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Ivan Brandslund
- 1] Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark. [2] Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Julia Brosnan
- Cardiovascular & Metabolic Diseases Research Unit, Pfizer, Inc., Cambridge, Massachusetts, USA
| | - Frank Burslem
- Cardiovascular and Metabolic Diseases Practice, Prescient Life Sciences, London, UK
| | - John Chambers
- 1] Department of Epidemiology and Biostatistics, Imperial College London, London, UK. [2] Imperial College Healthcare National Health Service (NHS) Trust, London, UK. [3] Ealing Hospital NHS Trust, Middlesex, UK
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, Korea
| | - Cramer Christensen
- Department of Internal Medicine and Endocrinology, Vejle Hospital, Vejle, Denmark
| | - Desirée A Douglas
- Unit of Diabetes and Celiac Diseases, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Zachary Dymek
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Yossi Farjoun
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Timothy Fennell
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Pierre Fontanillas
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Tom Forsén
- 1] Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland. [2] Diabetes Care Unit, Vaasa Health Care Centre, Vaasa, Finland
| | - Stacey Gabriel
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Benjamin Glaser
- 1] Endocrinology and Metabolism Service, Hadassah-Hebrew University Medical Center, Jerusalem, Israel. [2] Israel Diabetes Research Group (IDRG), Holon, Israel
| | | | - Craig Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Torben Hansen
- 1] Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. [2] Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Astradur B Hreidarsson
- Department of Endocrinology and Metabolism, Landspitali University Hospital, Reykjavik, Iceland
| | - Kristian Hveem
- Department of Public Health, Faculty of Medicine, Norwegian University of Science and Technology, Levanger, Norway
| | - Erik Ingelsson
- 1] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. [2] Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Bo Isomaa
- 1] Folkhalsan Research Centre, Helsinki, Finland. [2] Department of Social Services and Health Care, Jakobstad, Finland
| | - Stefan Johansson
- 1] KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway. [2] Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway. [3] Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Torben Jørgensen
- 1] Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark. [2] Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. [3] Faculty of Medicine, University of Aalborg, Aalborg, Denmark
| | | | - Sekar Kathiresan
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA. [4] Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Jaspal Kooner
- 1] Imperial College Healthcare National Health Service (NHS) Trust, London, UK. [2] Ealing Hospital NHS Trust, Middlesex, UK. [3] National Heart and Lung Institute (NHLI), Imperial College London, Hammersmith Hospital, London, UK
| | - Jasmina Kravic
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland, Kuopio Campus and Kuopio University Hospital, Kuopio, Finland
| | - Jong-Young Lee
- Center for Genome Science, Korea National Institute of Health, Osong Health Technology, Chungcheongbuk-do, Korea
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Cecilia M Lindgren
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Allan Linneberg
- 1] Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark. [2] Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. [3] Department of Clinical Experimental Research, Glostrup University Hospital, Glostrup, Denmark
| | | | - Thomas Meitinger
- Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Anders Molven
- 1] KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway. [2] Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Bergen, Norway. [3] Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Andrew P Morris
- 1] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. [2] Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Shobha Potluri
- Applied Quantitative Genotherapeutics, Pfizer, Inc., South San Francisco, California, USA
| | - Rainer Rauramaa
- 1] Kuopio Research Institute of Exercise Medicine, Kuopio, Finland. [2] Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Rasmus Ribel-Madsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ann-Marie Richard
- Cardiovascular & Metabolic Diseases Research Unit, Pfizer, Inc., Cambridge, Massachusetts, USA
| | - Tim Rolph
- Cardiovascular & Metabolic Diseases Research Unit, Pfizer, Inc., Cambridge, Massachusetts, USA
| | - Veikko Salomaa
- National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Ayellet V Segrè
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Hanna Skärstrand
- Unit of Diabetes and Celiac Diseases, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Heather M Stringham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | | | - E Shyong Tai
- 1] Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore. [2] Department of Medicine, National University of Singapore, National University Health System, Singapore. [3] Duke-National University of Singapore Graduate Medical School, Singapore
| | - Yik Ying Teo
- 1] Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore. [2] Centre for Molecular Epidemiology, National University of Singapore, Singapore. [3] Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore. [4] Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore. [5] Department of Statistics and Applied Probability, National University of Singapore, Singapore
| | - Tanya Teslovich
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Unnur Thorsteinsdottir
- 1] deCODE Genetics/Amgen, Inc., Reykjavik, Iceland. [2] Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Jeff K Trimmer
- Cardiovascular & Metabolic Diseases Research Unit, Pfizer, Inc., Cambridge, Massachusetts, USA
| | - Tiinamaija Tuomi
- 1] Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland. [2] Folkhalsan Research Centre, Helsinki, Finland
| | - Jaakko Tuomilehto
- 1] Centre for Vascular Prevention, Danube-University Krems, Krems, Austria. [2] Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland. [3] Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Fariba Vaziri-Sani
- Unit of Diabetes and Celiac Diseases, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Benjamin F Voight
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Department of Pharmacology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA. [3] Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Mark I McCarthy
- 1] Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK. [2] Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. [3] Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Pål R Njølstad
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway. [3] Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Leif Groop
- 1] Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden. [2] Finnish Institute for Molecular Medicine (FIMM), Helsinki University, Helsinki, Finland
| | - David R Cox
- Applied Quantitative Genotherapeutics, Pfizer, Inc., South San Francisco, California, USA
| | - Kari Stefansson
- 1] deCODE Genetics/Amgen, Inc., Reykjavik, Iceland. [2] Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - David Altshuler
- 1] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [2] Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, USA. [3] Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA. [4] Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA. [5] Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA. [6] Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA. [7] Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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9
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Wang B, Chandrasekera PC, Pippin JJ. Leptin- and leptin receptor-deficient rodent models: relevance for human type 2 diabetes. Curr Diabetes Rev 2014; 10:131-45. [PMID: 24809394 PMCID: PMC4082168 DOI: 10.2174/1573399810666140508121012] [Citation(s) in RCA: 363] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2014] [Revised: 05/06/2014] [Accepted: 05/07/2014] [Indexed: 12/11/2022]
Abstract
Among the most widely used animal models in obesity-induced type 2 diabetes mellitus (T2DM) research are the congenital leptin- and leptin receptor-deficient rodent models. These include the leptin-deficient ob/ob mice and the leptin receptor-deficient db/db mice, Zucker fatty rats, Zucker diabetic fatty rats, SHR/N-cp rats, and JCR:LA-cp rats. After decades of mechanistic and therapeutic research schemes with these animal models, many species differences have been uncovered, but researchers continue to overlook these differences, leading to untranslatable research. The purpose of this review is to analyze and comprehensively recapitulate the most common leptin/leptin receptor-based animal models with respect to their relevance and translatability to human T2DM. Our analysis revealed that, although these rodents develop obesity due to hyperphagia caused by abnormal leptin/leptin receptor signaling with the subsequent appearance of T2DM-like manifestations, these are in fact secondary to genetic mutations that do not reflect disease etiology in humans, for whom leptin or leptin receptor deficiency is not an important contributor to T2DM. A detailed comparison of the roles of genetic susceptibility, obesity, hyperglycemia, hyperinsulinemia, insulin resistance, and diabetic complications as well as leptin expression, signaling, and other factors that confound translation are presented here. There are substantial differences between these animal models and human T2DM that limit reliable, reproducible, and translatable insight into human T2DM. Therefore, it is imperative that researchers recognize and acknowledge the limitations of the leptin/leptin receptor- based rodent models and invest in research methods that would be directly and reliably applicable to humans in order to advance T2DM management.
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Affiliation(s)
| | | | - John J Pippin
- Physicians Committee for Responsible Medicine, 5100 Wisconsin Avenue NW, Suite 400, Washington, DC 20016, USA.
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10
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O'Brien RM. Moving on from GWAS: functional studies on the G6PC2 gene implicated in the regulation of fasting blood glucose. Curr Diab Rep 2013; 13:768-77. [PMID: 24142592 PMCID: PMC4041587 DOI: 10.1007/s11892-013-0422-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Genome-wide association studies (GWAS) have shown that single-nucleotide polymorphisms (SNPs) in G6PC2 are the most important common determinants of variations in fasting blood glucose (FBG) levels. Molecular studies examining the functional impact of these SNPs on G6PC2 gene transcription and splicing suggest that they affect FBG by directly modulating G6PC2 expression. This conclusion is supported by studies on G6pc2 knockout (KO) mice showing that G6pc2 represents a negative regulator of basal glucose-stimulated insulin secretion that acts by hydrolyzing glucose-6-phosphate, thereby reducing glycolytic flux and opposing the action of glucokinase. Suppression of G6PC2 activity might, therefore, represent a novel therapy for lowering FBG and the risk of cardiovascular-associated mortality. GWAS and G6pc2 KO mouse studies also suggest that G6PC2 affects other aspects of beta cell function. The evolutionary benefit conferred by G6PC2 remains unclear, but it is unlikely to be related to its ability to modulate FBG.
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Affiliation(s)
- Richard M O'Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA,
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11
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Almawi WY, Nemr R, Keleshian SH, Echtay A, Saldanha FL, AlDoseri FA, Racoubian E. A replication study of 19 GWAS-validated type 2 diabetes at-risk variants in the Lebanese population. Diabetes Res Clin Pract 2013; 102:117-22. [PMID: 24145053 DOI: 10.1016/j.diabres.2013.09.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 07/25/2013] [Accepted: 09/05/2013] [Indexed: 12/20/2022]
Abstract
AIM Recent genome-wide association scans (GWAS) and replication studies have expanded the list of validated type 2 diabetes (T2DM) susceptibility loci. We replicated T2DM association of 19 SNPs from 15 candidate loci in Lebanese Arabs. METHODS Case-control association study, comprising 995 T2DM patients and 1076 control participants. We genotyped by the allelic discrimination method 19 SNPs in/near ADAM30, NOTCH2, THADA, TMEFF2, COL8A1, ADAMTS9-AS2, WFS1, JAZF1, SLC30A8, KCNQ1, LOC387761, ALX4, TSPAN8, FTO, and HNF1. RESULTS Allele frequencies of the tested SNPs were comparable with those of Caucasians. COL8A1 rs792837 (P=2.9 × 10(-9)), KCNQ1 rs2237892 (P=1.8 × 10(-18)) and rs2237895 (P=0.002), ALX4 rs729287 (Pc=7.5 × 10(-5)), and HNF1 rs4430796 (P=0.003) were significantly associated with T2DM, with similar effect sizes to those of Europeans. While FTO rs8050136 and rs17817449, ADAMTS9 rs4607103, and WFS1 rs10010131 were initially associated with T2DM, this was lost upon multiple testing correction. The remaining variants were not associated with T2DM, possibly resulting from insufficient power to detect smaller allele effects. CONCLUSION In addition to previous findings on the association of IGF2BP2, CDKAL1, TCF7L2 variants with T2DM among Lebanese, here we extend these by validating the association of five additional loci with T2DM in Lebanese Arabs.
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Affiliation(s)
- Wassim Y Almawi
- Department of Medical Biochemistry, Arabian Gulf University, Manama, Bahrain.
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12
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van de Bunt M, Gaulton KJ, Parts L, Moran I, Johnson PR, Lindgren CM, Ferrer J, Gloyn AL, McCarthy MI. The miRNA profile of human pancreatic islets and beta-cells and relationship to type 2 diabetes pathogenesis. PLoS One 2013; 8:e55272. [PMID: 23372846 PMCID: PMC3555946 DOI: 10.1371/journal.pone.0055272] [Citation(s) in RCA: 144] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2012] [Accepted: 12/22/2012] [Indexed: 12/21/2022] Open
Abstract
Recent advances in the understanding of the genetics of type 2 diabetes (T2D) susceptibility have focused attention on the regulation of transcriptional activity within the pancreatic beta-cell. MicroRNAs (miRNAs) represent an important component of regulatory control, and have proven roles in the development of human disease and control of glucose homeostasis. We set out to establish the miRNA profile of human pancreatic islets and of enriched beta-cell populations, and to explore their potential involvement in T2D susceptibility. We used Illumina small RNA sequencing to profile the miRNA fraction in three preparations each of primary human islets and of enriched beta-cells generated by fluorescence-activated cell sorting. In total, 366 miRNAs were found to be expressed (i.e. >100 cumulative reads) in islets and 346 in beta-cells; of the total of 384 unique miRNAs, 328 were shared. A comparison of the islet-cell miRNA profile with those of 15 other human tissues identified 40 miRNAs predominantly expressed (i.e. >50% of all reads seen across the tissues) in islets. Several highly-expressed islet miRNAs, such as miR-375, have established roles in the regulation of islet function, but others (e.g. miR-27b-3p, miR-192-5p) have not previously been described in the context of islet biology. As a first step towards exploring the role of islet-expressed miRNAs and their predicted mRNA targets in T2D pathogenesis, we looked at published T2D association signals across these sites. We found evidence that predicted mRNA targets of islet-expressed miRNAs were globally enriched for signals of T2D association (p-values <0.01, q-values <0.1). At six loci with genome-wide evidence for T2D association (AP3S2, KCNK16, NOTCH2, SCL30A8, VPS26A, and WFS1) predicted mRNA target sites for islet-expressed miRNAs overlapped potentially causal variants. In conclusion, we have described the miRNA profile of human islets and beta-cells and provide evidence linking islet miRNAs to T2D pathogenesis.
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Affiliation(s)
- Martijn van de Bunt
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kyle J. Gaulton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Leopold Parts
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Donnelly Centre for Cellular and Biomolecular Research, Toronto, Canada
| | - Ignasi Moran
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Paul R. Johnson
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Surgery, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Jorge Ferrer
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Anna L. Gloyn
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
- * E-mail:
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13
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Abstract
A new generation of genetic studies of diabetes is underway. Following from initial genome-wide association (GWA) studies, more recent approaches have used genotyping arrays of more densely spaced markers, imputation of ungenotyped variants based on improved reference haplotype panels, and sequencing of protein-coding exomes and whole genomes. Experimental and statistical advances make possible the identification of novel variants and loci contributing to trait variation and disease risk. Integration of sequence variants with functional analysis is critical to interpreting the consequences of identified variants. We briefly review these methods and technologies and describe how they will continue to expand our understanding of the genetic risk factors and underlying biology of diabetes.
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Affiliation(s)
- Karen L. Mohlke
- 5096 Genetic Medicine, 120 Mason Farm Drive, University of North Carolina, Chapel Hill, NC 27599-7264, USA, Tel: 919-966-2913, Fax: 919-843-0291
| | - Laura J. Scott
- M4134 SPH II, 1415 Washington Heights, University of Michigan, Ann Arbor, MI 48109-2029, USA, Tel: 734-763-0006, Fax: 734-763-2215
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14
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Morán I, Akerman İ, van de Bunt M, Xie R, Benazra M, Nammo T, Arnes L, Nakić N, García-Hurtado J, Rodríguez-Seguí S, Pasquali L, Sauty-Colace C, Beucher A, Scharfmann R, van Arensbergen J, Johnson PR, Berry A, Lee C, Harkins T, Gmyr V, Pattou F, Kerr-Conte J, Piemonti L, Berney T, Hanley NA, Gloyn AL, Sussel L, Langman L, Brayman KL, Sander M, McCarthy MI, Ravassard P, Ferrer J. Human β cell transcriptome analysis uncovers lncRNAs that are tissue-specific, dynamically regulated, and abnormally expressed in type 2 diabetes. Cell Metab 2012; 16:435-48. [PMID: 23040067 PMCID: PMC3475176 DOI: 10.1016/j.cmet.2012.08.010] [Citation(s) in RCA: 339] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2012] [Revised: 07/30/2012] [Accepted: 08/31/2012] [Indexed: 02/08/2023]
Abstract
A significant portion of the genome is transcribed as long noncoding RNAs (lncRNAs), several of which are known to control gene expression. The repertoire and regulation of lncRNAs in disease-relevant tissues, however, has not been systematically explored. We report a comprehensive strand-specific transcriptome map of human pancreatic islets and β cells, and uncover >1100 intergenic and antisense islet-cell lncRNA genes. We find islet lncRNAs that are dynamically regulated and show that they are an integral component of the β cell differentiation and maturation program. We sequenced the mouse islet transcriptome and identify lncRNA orthologs that are regulated like their human counterparts. Depletion of HI-LNC25, a β cell-specific lncRNA, downregulated GLIS3 mRNA, thus exemplifying a gene regulatory function of islet lncRNAs. Finally, selected islet lncRNAs were dysregulated in type 2 diabetes or mapped to genetic loci underlying diabetes susceptibility. These findings reveal a new class of islet-cell genes relevant to β cell programming and diabetes pathophysiology.
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Affiliation(s)
- Ignasi Morán
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - İldem Akerman
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Martijn van de Bunt
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK
| | - Ruiyu Xie
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, California, USA
| | - Marion Benazra
- Centre de recherche de l’institut du cerveau et de la moelle, Biotechnology & Biotherapy team, CNRS UMR7225; INSERM U975; University Pierre et Marie Curie, Paris, France
| | - Takao Nammo
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- Department of Metabolic Disorders, Diabetes Research Center, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Luis Arnes
- Department of Genetics and Development, Russ Berrie Medical Pavilion, Columbia University, New York, USA
| | - Nikolina Nakić
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Javier García-Hurtado
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Santiago Rodríguez-Seguí
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Lorenzo Pasquali
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Claire Sauty-Colace
- Centre de recherche de l’institut du cerveau et de la moelle, Biotechnology & Biotherapy team, CNRS UMR7225; INSERM U975; University Pierre et Marie Curie, Paris, France
| | - Anthony Beucher
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Raphael Scharfmann
- Institut National de la Santé et de la Recherche Médicale (INSERM) U845, Research Center Growth and Signalling, Paris Descartes University, Sorbonne Paris Cité, Necker Hospital, Paris, France
| | - Joris van Arensbergen
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Paul R Johnson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK
- Oxford Islet Transplant Programme, Nuffield Department of Surgical Sciences, John Radcliffe Hospital, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Andrew Berry
- Developmental Biomedicine Research Group, School of Biomedicine, Manchester Academic Health Sciences Centre, University of Manchester and Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Clarence Lee
- Genome Sequencing Collaborations Group, Life Technologies, Beverly, Massachusetts USA
| | - Timothy Harkins
- Genome Sequencing Collaborations Group, Life Technologies, Beverly, Massachusetts USA
| | - Valery Gmyr
- University of Lille Nord de France, INSERM U859 Biotherapies of Diabete, Lille, France
| | - François Pattou
- University of Lille Nord de France, INSERM U859 Biotherapies of Diabete, Lille, France
| | - Julie Kerr-Conte
- University of Lille Nord de France, INSERM U859 Biotherapies of Diabete, Lille, France
| | - Lorenzo Piemonti
- Diabetes research institute (HSR-DRI), San Raffaele Scientific Institute, Milano, Italy
| | - Thierry Berney
- Cell Isolation and Transplantation Center, Geneva, Switzerland
| | - Neil A Hanley
- Developmental Biomedicine Research Group, School of Biomedicine, Manchester Academic Health Sciences Centre, University of Manchester and Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Lori Sussel
- Department of Genetics and Development, Russ Berrie Medical Pavilion, Columbia University, New York, USA
| | - Linda Langman
- Division of Transplantation, Department of Surgery, Center for Cellular Therapy and Biotherapeutics, University of Virginia, USA
| | - Kenneth L Brayman
- Division of Transplantation, Department of Surgery, Center for Cellular Therapy and Biotherapeutics, University of Virginia, USA
| | - Maike Sander
- Department of Cellular and Molecular Medicine, University of California at San Diego, La Jolla, California, USA
| | - Mark I. McCarthy
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK
- Diabetes research institute (HSR-DRI), San Raffaele Scientific Institute, Milano, Italy
| | - Philippe Ravassard
- Centre de recherche de l’institut du cerveau et de la moelle, Biotechnology & Biotherapy team, CNRS UMR7225; INSERM U975; University Pierre et Marie Curie, Paris, France
| | - Jorge Ferrer
- Genomic Programming of Beta-cells Laboratory, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- Department of Endocrinology and Nutrition, Hospital Clínic de Barcelona, Barcelona, Spain
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15
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Solberg Woods LC, Holl KL, Oreper D, Xie Y, Tsaih SW, Valdar W. Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats. Physiol Genomics 2012; 44:1013-26. [PMID: 22947656 DOI: 10.1152/physiolgenomics.00040.2012] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Type 2 diabetes (T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate <3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D.
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Affiliation(s)
- Leah C Solberg Woods
- Department of Pediatrics, Human and Molecular Genetics Center and Children's Research Institute, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA.
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16
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Odgerel Z, Lee HS, Erdenebileg N, Gandbold S, Luvsanjamba M, Sambuughin N, Sonomtseren S, Sharavdorj P, Jodov E, Altaisaikhan K, Goldfarb LG. Genetic variants in potassium channels are associated with type 2 diabetes in a Mongolian population. J Diabetes 2012; 4:238-42. [PMID: 22151254 PMCID: PMC3309067 DOI: 10.1111/j.1753-0407.2011.00177.x] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Recent genome-wide association studies (GWAS) have identified more than 40 common sequence variants associated with type 2 diabetes (T2D). However, the results are not always the same in populations with differing genetic backgrounds. In the present study, we evaluated a hypothesis that a North Asian population living in a geographic area with unusually harsh environmental conditions would develop unique genetic risks. METHODS A population-based association study was performed with 21 single-nucleotide polymorphisms (SNPs) in nine genes selected according to the results of GWAS conducted in other populations. The study participants included 393 full-heritage Mongolian individuals (177 diagnosed with T2D and 216 matched controls). Genotyping was performed by TaqMan methodology. RESULTS The strongest association was detected with SNPs located within the potassium channel-coding genes KCNQ1 (highest odds ratio [OR] = 1.92; P = 3.4 × 10(-5) ) and ABCC8 (OR = 1.79; P = 5 × 10(-4) ). Genetic variants identified as strongly influencing the risk of T2D in other populations (e.g. KCNJ11 or TCF7L2) did not show significant association in Mongolia. CONCLUSIONS The strongest T2D risk-associated SNPs in Mongolians are located within two of three tested potassium channel-coding genes. Accumulated variations in these genes may be related to the exposure to harsh environmental conditions.
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Affiliation(s)
- Zagaa Odgerel
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Hee S Lee
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Narnygerel Erdenebileg
- Infectious Diseases and Immunogenetics Section, Department of Transfusion Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA
| | - Suren Gandbold
- National Institute of Forensic Science, Ulaanbaatar, Mongolia
| | | | | | | | | | - Erdenezul Jodov
- Health Sciences University of Mongolia, Ulaanbaatar, Mongolia
| | | | - Lev G Goldfarb
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
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17
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Song Y, Yeung E, Liu A, Vanderweele TJ, Chen L, Lu C, Liu C, Schisterman EF, Ning Y, Zhang C. Pancreatic beta-cell function and type 2 diabetes risk: quantify the causal effect using a Mendelian randomization approach based on meta-analyses. Hum Mol Genet 2012; 21:5010-8. [PMID: 22936689 DOI: 10.1093/hmg/dds339] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The objective of the study is to quantify the causal effect of β-cell function on type 2 diabetes by minimizing residual confounding and reverse causation. We employed a Mendelian randomization (MR) approach using TCF7L2 variant rs7903146 as an instrument for lifelong levels of β-cell function. We first conducted two sets of meta-analyses to quantify the association of the TCF7L2 variant with the risk of type 2 diabetes among 55 436 cases and 106 020 controls from 66 studies by calculating pooled odds ratio (OR) and to quantify the associations with multiple direct or indirect measures of β-cell function among 35 052 non-diabetic individuals from 31 studies by calculating pooled mean difference. We further applied the method of MR to obtain the causal estimates for the effect of β-cell function on type 2 diabetes risk based on findings from the meta-analyses. The OR [95% confidence interval (CI)] was 0.87 (0.81-0.93) for each five unit increment in homeostasis model assessment of insulin secretion (HOMA-%B) (P = 3.0 × 10(-5)). In addition, for measures based on intravenous glucose tolerance test, ORs (95% CI) associated with type 2 diabetes risk were 0.24 (0.08-0.74) (P = 0.01) and 0.14 (0.04-0.48) (P = 0.002) for per 1 standard deviation increment in insulin sensitivity index and disposition index, respectively. Findings from the present study lend support to a causal role of pancreatic β-cell function itself in the etiology of type 2 diabetes.
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Affiliation(s)
- Yiqing Song
- Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
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Pound LD, Sarkar SA, Ustione A, Dadi PK, Shadoan MK, Lee CE, Walters JA, Shiota M, McGuinness OP, Jacobson DA, Piston DW, Hutton JC, Powell DR, O’Brien RM. The physiological effects of deleting the mouse SLC30A8 gene encoding zinc transporter-8 are influenced by gender and genetic background. PLoS One 2012; 7:e40972. [PMID: 22829903 PMCID: PMC3400647 DOI: 10.1371/journal.pone.0040972] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2011] [Accepted: 06/18/2012] [Indexed: 11/18/2022] Open
Abstract
Objective The SLC30A8 gene encodes the islet-specific transporter ZnT-8, which is hypothesized to provide zinc for insulin-crystal formation. A polymorphic variant in SLC30A8 is associated with altered susceptibility to type 2 diabetes. Several groups have examined the effect of global Slc30a8 gene deletion but the results have been highly variable, perhaps due to the mixed 129SvEv/C57BL/6J genetic background of the mice studied. We therefore sought to remove the conflicting effect of 129SvEv-specific modifier genes. Methods The impact of Slc30a8 deletion was examined in the context of the pure C57BL/6J genetic background. Results Male C57BL/6J Slc30a8 knockout (KO) mice had normal fasting insulin levels and no change in glucose-stimulated insulin secretion (GSIS) from isolated islets in marked contrast to the ∼50% and ∼35% decrease, respectively, in both parameters observed in male mixed genetic background Slc30a8 KO mice. This observation suggests that 129SvEv-specific modifier genes modulate the impact of Slc30a8 deletion. In contrast, female C57BL/6J Slc30a8 KO mice had reduced (∼20%) fasting insulin levels, though this was not associated with a change in fasting blood glucose (FBG), or GSIS from isolated islets. This observation indicates that gender also modulates the impact of Slc30a8 deletion, though the physiological explanation as to why impaired insulin secretion is not accompanied by elevated FBG is unclear. Neither male nor female C57BL/6J Slc30a8 KO mice showed impaired glucose tolerance. Conclusions Our data suggest that, despite a marked reduction in islet zinc content, the absence of ZnT-8 does not have a substantial impact on mouse physiology.
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Affiliation(s)
- Lynley D. Pound
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - Suparna A. Sarkar
- Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, Colorado, United States of America
| | - Alessandro Ustione
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - Prasanna K. Dadi
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - Melanie K. Shadoan
- Lexicon Pharmaceuticals Incorporated, The Woodlands, Texas, United States of America
| | - Catherine E. Lee
- Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, Colorado, United States of America
| | - Jay A. Walters
- Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, Colorado, United States of America
| | - Masakazu Shiota
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - Owen P. McGuinness
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - David A. Jacobson
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - David W. Piston
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
| | - John C. Hutton
- Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, Colorado, United States of America
| | - David R. Powell
- Lexicon Pharmaceuticals Incorporated, The Woodlands, Texas, United States of America
| | - Richard M. O’Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, Tennessee, United States of America
- * E-mail:
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Rees MG, Wincovitch S, Schultz J, Waterstradt R, Beer NL, Baltrusch S, Collins FS, Gloyn AL. Cellular characterisation of the GCKR P446L variant associated with type 2 diabetes risk. Diabetologia 2012; 55:114-22. [PMID: 22038520 PMCID: PMC3276843 DOI: 10.1007/s00125-011-2348-5] [Citation(s) in RCA: 84] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2011] [Accepted: 09/28/2011] [Indexed: 11/25/2022]
Abstract
AIMS/HYPOTHESIS Translation of genetic association signals into molecular mechanisms for diabetes has been slow. The glucokinase regulatory protein (GKRP; gene symbol GCKR) P446L variant, associated with inverse modulation of glucose- and lipid-related traits, has been shown to alter the kinetics of glucokinase (GCK) inhibition. As GCK inhibition is associated with nuclear sequestration, we aimed to determine whether this variant also alters the direct interaction between GKRP and GCK and their intracellular localisation. METHODS Fluorescently tagged rat and human wild-type (WT)- or P446L-GCKR and GCK were transiently transfected into HeLa cells and mouse primary hepatocytes. Whole-cell and nuclear fluorescence was quantified in individual cells exposed to low- or high-glucose conditions (5.5 or 25 mmol/l glucose, respectively). Interaction between GCK and GKRP was measured by sensitised emission-based fluorescence resonance energy transfer (FRET) efficiency. RESULTS P446L-GKRP had a decreased degree of nuclear localisation, ability to sequester GCK and direct interaction with GCK as measured by FRET compared with WT-GKRP. Decreased interaction was observed between WT-GKRP and GCK at high compared with low glucose, but not between P446L-GKRP and GCK. Rat WT-GKRP and P446L-GKRP behaved quite differently: both variants responded to high glucose by diminished sequestration of GCK but showed no effect of the P446L variant on nuclear localisation or GCK sequestration. CONCLUSIONS/INTERPRETATION Our study suggests the common human P446L-GKRP variant protein results in elevated hepatic glucose uptake and disposal by increasing active cytosolic GCK. This would increase hepatic lipid biosynthesis but decrease fasting plasma glucose concentrations and provides a potential mechanism for the protective effect of this allele on type 2 diabetes risk.
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Affiliation(s)
- M. G. Rees
- Oxford Centre for Diabetes Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, OX3 7LJ UK
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - S. Wincovitch
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - J. Schultz
- Institute for Medical Biochemistry & Molecular Biology, University of Rostock, Rostock, Germany
| | - R. Waterstradt
- Institute for Medical Biochemistry & Molecular Biology, University of Rostock, Rostock, Germany
| | - N. L. Beer
- Oxford Centre for Diabetes Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, OX3 7LJ UK
| | - S. Baltrusch
- Institute for Medical Biochemistry & Molecular Biology, University of Rostock, Rostock, Germany
| | - F. S. Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD USA
| | - A. L. Gloyn
- Oxford Centre for Diabetes Endocrinology & Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, OX3 7LJ UK
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Cabeza-Arvelaiz Y, Fleming SM, Richter F, Masliah E, Chesselet MF, Schiestl RH. Analysis of striatal transcriptome in mice overexpressing human wild-type alpha-synuclein supports synaptic dysfunction and suggests mechanisms of neuroprotection for striatal neurons. Mol Neurodegener 2011; 6:83. [PMID: 22165993 PMCID: PMC3271045 DOI: 10.1186/1750-1326-6-83] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2011] [Accepted: 12/13/2011] [Indexed: 01/08/2023] Open
Abstract
Background Alpha synuclein (SNCA) has been linked to neurodegenerative diseases (synucleinopathies) that include Parkinson's disease (PD). Although the primary neurodegeneration in PD involves nigrostriatal dopaminergic neurons, more extensive yet regionally selective neurodegeneration is observed in other synucleinopathies. Furthermore, SNCA is ubiquitously expressed in neurons and numerous neuronal systems are dysfunctional in PD. Therefore it is of interest to understand how overexpression of SNCA affects neuronal function in regions not directly targeted for neurodegeneration in PD. Results The present study investigated the consequences of SNCA overexpression on cellular processes and functions in the striatum of mice overexpressing wild-type, human SNCA under the Thy1 promoter (Thy1-aSyn mice) by transcriptome analysis. The analysis revealed alterations in multiple biological processes in the striatum of Thy1-aSyn mice, including synaptic plasticity, signaling, transcription, apoptosis, and neurogenesis. Conclusion The results support a key role for SNCA in synaptic function and revealed an apoptotic signature in Thy1-aSyn mice, which together with specific alterations of neuroprotective genes suggest the activation of adaptive compensatory mechanisms that may protect striatal neurons in conditions of neuronal overexpression of SNCA.
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Affiliation(s)
- Yofre Cabeza-Arvelaiz
- Department of Pathology and Environmental Health Sciences, The Geffen School of Medicine and School of Public Health, University of California, Los Angeles, 650 Charles E, Young Dr. S, CHS 71-295, Los Angeles, CA 90095, USA.
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Sousa AG, Selvatici L, Krieger JE, Pereira AC. Association between genetics of diabetes, coronary artery disease, and macrovascular complications: exploring a common ground hypothesis. Rev Diabet Stud 2011; 8:230-44. [PMID: 22189546 DOI: 10.1900/rds.2011.8.230] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Type 2 diabetes and coronary artery disease (CAD) are conditions that cause a substantial public health burden. Since both conditions often coexist in the same individual, it has been hypothesized that they have a common effector. Insulin and hyperglycemia are assumed to play critical roles in this scenario. In recent years, many genetic risk factors for both diabetes and CAD have been discovered, mainly through genome-wide association studies. Genetic aspects of diabetes, diabetic macrovascular complications, and CAD are assumed to have intersections leading to the common effector hypothesis. However, only a few genetic risk factors could be identified that modulate the risk for both conditions. Polymorphisms in TCF7L2 and near the CDKN2A/B genes seem to be of great importance in this regard since they appear to modulate both conditions, and they are not necessarily related to insulinism, or hyperglycemia, for CAD development. Other issues related to this hypothesis, such as the problems of phenotype heterogeneity, are also of interest. Recent studies have contributed to a better understanding of the complex genetics of diabetic macrovascular complications. Much effort is still needed to clarify the associations in the genetics of diabetes, and cardiovascular disease. At present, there is little genetic evidence to support a common effector hypothesis, other than insulin or hyperglycemia, for the association between these conditions.
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Affiliation(s)
- André G Sousa
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, Brazil
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Rees SD, Hydrie MZI, Shera AS, Kumar S, O'Hare JP, Barnett AH, Basit A, Kelly MA. Replication of 13 genome-wide association (GWA)-validated risk variants for type 2 diabetes in Pakistani populations. Diabetologia 2011; 54:1368-74. [PMID: 21350842 DOI: 10.1007/s00125-011-2063-2] [Citation(s) in RCA: 79] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2010] [Accepted: 01/05/2011] [Indexed: 12/29/2022]
Abstract
AIMS/HYPOTHESIS Recent genome-wide association (GWA) studies and subsequent replication studies have greatly increased the number of validated type 2 diabetes susceptibility variants, but most of these have been conducted in European populations. Despite the high prevalence of the disease in South Asians, studies investigating GWA-validated type 2 diabetes risk variants in this ethnic group are limited. We investigated 30 single nucleotide polymorphisms (SNPs), predominantly derived from recent GWA studies, to determine if and to what extent these variants affect type 2 diabetes risk in two Punjabi populations, originating predominantly from the District of Mirpur, Pakistan. METHODS Thirty SNPs were genotyped in 1,678 participants with type 2 diabetes and 1,584 normoglycaemic control participants from two populations; one resident in the UK and one indigenous to the District of Mirpur. RESULTS SNPs in or near PPARG, TCF7L2, FTO, CDKN2A/2B, HHEX/IDE, IGF2BP2, SLC30A8, KCNQ1, JAZF1, IRS1, KLF14, CHCHD9 and DUSP9 displayed significant (p < 0.05) associations with type 2 diabetes, with similar effect sizes to those seen in European populations. A constructed genetic risk score was associated with type 2 diabetes (p = 5.46 × 10(-12)), BMI (p = 2.25 × 10(-4)) and age at onset of diabetes (p = 0.002). CONCLUSIONS/INTERPRETATION We have demonstrated that 13 variants confer an increased risk of type 2 diabetes in our Pakistani populations; to our knowledge this is the first time that SNPs in or near KCNQ1, JAZF1, IRS1, KLF14, CHCHD9 and DUSP9 have been significantly associated with the disease in South Asians. Large-scale studies and meta-analyses of South Asian populations are needed to further confirm the effect of these variants in this ethnic group.
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Affiliation(s)
- S D Rees
- Diabetes Research Laboratory, School of Clinical and Experimental Medicine, College of Medical and Dental Sciences, The Medical School, University of Birmingham, Vincent Drive, Edgbaston, Birmingham B15 2TT, UK.
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Koelsch B, Winzen-Reichert B, Fischer C, Kutritz A, van den Berg L, Kindler-Röhrborn A. Sex-biased suppression of chemically induced neural carcinogenesis in congenic BDIX.BDIV-Mss4a rats. Physiol Genomics 2011; 43:631-9. [PMID: 21427360 DOI: 10.1152/physiolgenomics.00246.2010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
We previously mapped several gene loci influencing cancer risk of inbred BDIV and BDIX rats, resistant and susceptible, respectively, to N-ethyl-N-nitrosourea (ENU)-induced malignant peripheral nerve sheath tumors (MPNSTs). On the basis of a genomewide association analysis using a (BDIV × BDIX) F(2) generation the Mss4 locus on rat chromosome 6 was predicted to mediate resistance to MPNST development in the trigeminal nerves, preferentially in females. F(2) females homozygous for D6Mit1 proved almost exclusively resistant to peripheral neurooncogenesis, with no effect detectable in males. To functionally verify Mss4, a congenic BDIX rat strain was generated carrying a corresponding BDIV genomic fragment. On treatment with ENU, congenic BDIX.BDIV-Mss4a rats showed a 2.4-fold lower MPNST rate and a 55-day-longer survival time compared with BDIX animals. The sex-specific effect observed in F(2) rats was less pronounced in BDIX.BDIV-Mss4a congenics, with males, too, being protected against MPNST but to a lesser extent than females. Transcription profiling using trigeminal nerve tissue of BDIX, BDIV, and BDIX.BDIV-Mss4a congenics of both sexes revealed 61 genes located in the Mss4a fragment differentially expressed between BDIV and BDIX rats. In congenic rats each gene either displayed trans-regulated BDIX-like expression strength or cis-regulated BDIV-like transcript levels or intermediate expression without marked sex differences. Genomewide a number of genes exhibiting male-biased expression in the BDIX rat strain displayed a reversal of the sexual dimorphism in congenic rats similar to the BDIV expression pattern, which might be the basis of preferential protection of females against MPNST development.
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Affiliation(s)
- Bernd Koelsch
- Institute of Pathology and Neuropathology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
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