Richard N Bergman

The University of Warwick, Coventry, England, United Kingdom

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Publications (353)2799.38 Total impact

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    ABSTRACT: Context: Metabolomic profiling of amino acids and acylcarnitines has revealed consistent patterns associated with metabolic disease. Objective: Use metabolomic profiling to identify analytes associated with insulin sensitivity (SI) and conversion to type 2 diabetes (T2D). Design: Insulin Resistance Atherosclerosis Study. Setting: Community-based. Patients: A total of 196 subjects (European American, Hispanic, and African American) were selected to represent extremes of the SI distribution and conversion to T2D between baseline and follow-up exams. Main Outcome: Mass spectrometry-based profiling of 69 metabolites. Subjects participated in a frequently sampled intravenous glucose tolerance test to measure SI and acute insulin response (AIR). T2D status was determined by a 2-hour oral glucose tolerance test. Results: Logistic regression analysis from 72 high and 75 low SI subjects, revealed significantly decreased glycine and increased valine, leucine, phenylalanine, and combined glutamine and glutamate (P=0.0079-7.7×10(-6)) in insulin resistant subjects. Ethnic-stratified results were strongest in European Americans. Comparing amino acid profiles between subjects that converted to T2D (76 converters; 70 non-converters) yielded a similar pattern of associations: decreased glycine and increased valine, leucine, and combined glutamine and glutamate (P=0.016-0.00010). Importantly, beta-cell function as a covariate revealed a similar pattern of association. Conclusions: A distinct pattern of differences in amino acids were observed when comparing subjects with high and low levels of SI. This pattern was associated with conversion to T2D, remaining significant when accounting for beta-cell function, emphasizing a link between this metabolic profile and insulin resistance. These results demonstrate a consistent metabolic signature associated with insulin resistance and conversion to T2D, providing potential insight into underlying mechanisms of disease pathogenesis.
    Journal of Clinical Endocrinology &amp Metabolism 11/2014; · 6.31 Impact Factor
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    ABSTRACT: Insulin injected directly into skeletal muscle diffuses rapidly through the interstitial space to cause glucose uptake, but this is blocked in insulin resistance. As glucotoxicity is associated with endothelial dysfunction, the observed hyperglycemia in diet-induced obese dogs may inhibit insulin access to muscle cells, and exacerbate insulin resistance. Here we asked whether interstitial insulin diffusion is reduced in modest hyperglycemia, similar to that induced by a high fat diet.Methods During normoglycemic (100 mg/dl) and moderately hyperglycemic (120 mg/dl) clamps in anesthetized canines, sequential doses of insulin were injected into the vastus medialis of one hindlimb; the contra-lateral limb served as a control. Plasma samples were collected and analyzed for insulin content. Lymph vessels of the hind leg were also catheterized, and lymph samples were analyzed as an indicator of interstitial insulin concentration.ResultsInsulin injection increased lymph insulin in normoglycemic animals, but not in hyperglycemic animals. Muscle glucose uptake was elevated in response to hyperglycemia, however the insulin-mediated glucose uptake in normoglycemic controls was not observed in hyperglycemia. Modest hyperglycemia prevented intra-muscularly injected insulin from diffusing through the interstitial space reduced insulin-mediated glucose uptake.Conclusion Hyperglycemia prevents the appearance of injected insulin in the interstitial space, thus reducing insulin action on skeletal muscle cells.
    Metabolism 11/2014; · 3.61 Impact Factor
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    ABSTRACT: Previous human studies reported inconsistent effects of dietary protein and branched-chain amino acids (BCAAs) on insulin action and glucose metabolism. Similarly, it is unclear whether saturated fat (SF) intake influences these metabolic variables.
    Journal of Nutrition 11/2014; 144(11):1753-9. · 4.23 Impact Factor
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    ABSTRACT: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated approximately 2,000, approximately 3,700 and approximately 9,500 SNPs explained approximately 21%, approximately 24% and approximately 29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
    Nature Genetics 10/2014; · 29.65 Impact Factor
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    ABSTRACT: Objectives To determine whether a selective increase of visceral adipose tissue content will result in insulin resistance.Methods Sympathetic denervation of the omental fat was performed under general inhalant anesthesia by injecting 6-hydroxydopamine in the omental fat of lean mongrel dogs (n = 11). In the conscious animal, whole-body insulin sensitivity was assessed by the minimal model (SI) and the euglycemic hyperinsulinemic clamp (SICLAMP). Changes in abdominal fat were monitored by magnetic resonance. All assessments were determined before (Wk0) and 2 weeks (Wk2) after denervation. Data are medians (upper and lower interquartile).ResultsDenervation of omental fat resulted in increased percentage (and content) of visceral fat [Wk0: 10.2% (8.5-11.4); Wk2: 12.4% (10.4-13.6); P < 0.01]. Abdominal subcutaneous fat remained unchanged. However, no changes were found in SI [Wk0: 4.7 (mU/l)−1 min−1 (3.1-8.8); Wk2: 5.3 (mU/l)−1 min−1 (4.5-7.2); P = 0.59] or SICLAMP [Wk0: 42.0 × 10−4 dl kg−1 min−1 (mU/l)−1 (41.0-51.0); Wk2: 40.0 × 10−4 dl kg−1 min−1 (mU/l) −1 (34.0-52.0); P = 0.67].Conclusions Despite a selective increase in visceral adiposity in dogs, insulin sensitivity in vivo did not change, which argues against the concept that accumulation of visceral adipose tissue contributes to insulin resistance.
    Obesity 10/2014; · 4.39 Impact Factor
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    ABSTRACT: The hepato-portal area is an important glucohomeostatic metabolic sensor, sensing hypoglycemia, hyperglycemia, and hormones such as glucagon- like peptide-1 (GLP-1). We have previously reported that activation of hepato-portal sensors by intraportal infusion of glucose and GLP-1, or by subcutaneous administration of GLP-1-receptor activator exenatide and of intraportal glucose, improved glycemia independent of corresponding changes in pancreatic hormones. It is not clear if this effect is mediated via the portal vein (PV) or by direct action on the liver itself. To test whether receptors in the PV mediate exenatide's beneficial effect on glucose tolerance, we performed a) paired oral glucose tolerance tests (OGTT) with and without exenatide and b) intravenous glucose tolerance tests before and after PV denervation in canines. Denervation of the portal vein affected oral glucose tolerance: post-denervation OGTT glucose and insulin AUC were 50% higher than before denervation (p=0.01). However, portal denervation did not impair exenatide's effect to improve oral glucose tolerance (exenatide effect: 48±12 mmol/l*min before vs. 64±26 mmol/l*min after, p=0.67). There were no changes in insulin sensitivity or secretion during IVGTTs. Portal vein sensing might play a role in controlling oral glucose tolerance during physiological conditions, but not in pharmacological activation of GLP-1 receptors by exenatide.
    AJP Endocrinology and Metabolism 08/2014; · 4.09 Impact Factor
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    ABSTRACT: Overall excess of fat, usually defined by the body mass index, is associated with metabolic (e.g. glucose intolerance, type 2 diabetes mellitus (T2DM), dyslipidemia) and non-metabolic disorders (e.g. neoplasias, polycystic ovary syndrome, non-alcoholic fat liver disease, glomerulopathy, bone fragility etc.). However, more than its total amount, the distribution of adipose tissue throughout the body is a better predictor of the risk to the development of those disorders. Fat accumulation in the abdominal area and in non-adipose tissue (ectopic fat), for example, is associated with increased risk to develop metabolic and non-metabolic derangements. On the other hand, observations suggest that individuals who present peripheral adiposity, characterized by large hip and thigh circumferences, have better glucose tolerance, reduced incidence of T2DM and of metabolic syndrome. Insulin resistance (IR) is one of the main culprits in the association between obesity, particularly visceral, and metabolic as well as non-metabolic diseases. In this review we will highlight the current pathophysiological and molecular mechanisms possibly involved in the link between increased VAT, ectopic fat, IR and comorbidities. We will also provide some insights in the identification of these abnormalities. Arq Bras Endocrinol Metab. 2014;58(6):600-9.
    Arquivos Brasileiros de Endocrinologia & Metabologia 08/2014; 58(6):600-609. · 0.68 Impact Factor
  • Richard N Bergman, Darko Stefanovski, Stella P Kim
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    ABSTRACT: Prevalence of Type 2 diabetes has increased at an alarming rate, highlighting the need to correctly predict the development of this disease in order to allow intervention and thus, slow progression of the disease and resulting metabolic derangement. There have been many recent 'advances' geared toward the detection of pre-diabetes, including genome wide association studies and metabolomics. Although these approaches generate a large amount of data with a single blood sample, studies have indicated limited success using genetic and metabolomics information alone for identification of disease risk. Clinical assessment of the disposition index (DI), based on the hyperbolic law of glucose tolerance, is a powerful predictor of Type 2 diabetes, but is not easily assessed in the clinical setting. Thus, it is evident that combining genetic or metabolomic approaches for a more simple assessment of DI may provide a useful tool to identify those at highest risk for Type 2 diabetes, allowing for intervention and prevention.
    Current Opinion in Biotechnology 06/2014; 28C:165-170. · 8.04 Impact Factor
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    ABSTRACT: Objective To determine whether geographical elevation is inversely associated with diabetes, while adjusting for multiple risk factors.Methods This is a cross-sectional analysis of publicly available online data from the Behavioral Risk Factor Surveillance System, 2009. Final dataset included 285,196 US adult subjects. Odds ratios were obtained from multilevel mixed-effects logistic regression analysis.ResultsAmong US adults (≥20 years old), the odds ratio for diabetes was 1.00 between 0 and 499 m of altitude (reference), 0.95 (95% confidence interval, 0.90-1.01) between 500 and 1,499 m, and 0.88 (0.81-0.96) between 1,500 and 3,500 m, adjusting for age, sex, body mass index, ethnicity, self-reported fruit and vegetable consumption, self-reported physical activity, current smoking status, level of education, income, health status, employment status, and county-level information on migration rate, urbanization, and latitude. The inverse association between altitude and diabetes in the US was found among men [0.84 (0.76-0.94)], but not women [1.09 (0.97-1.22)].Conclusions Among US adults, living at high altitude (1,500-3,500 m) is associated with lower odds of having diabetes than living between 0 and 499 m, while adjusting for multiple risk factors. Our findings suggest that geographical elevation may be an important factor linked to diabetes.
    Obesity 05/2014; · 4.39 Impact Factor
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    ABSTRACT: Risk alleles within a gene desert at the 9p21 locus constitute the most prevalent genetic determinant of cardiovascular disease. Previous research has demonstrated that 9p21 risk variants influence gene expression in vascular tissues, yet the biological mechanisms by which this would mediate atherosclerosis merits further investigation. To investigate possible influences of this locus on other tissues, we explored expression patterns of 9p21-regulated genes in a panel of multiple human tissues and found that the tumor suppressor CDKN2B was highly expressed in subcutaneous adipose tissue (SAT). CDKN2B expression was regulated by obesity status, and this effect was stronger in carriers of 9p21 risk alleles. Covariation between expression of CDKN2B and genes implemented in adipogenesis was consistent with an inhibitory effect of CDKN2B on SAT proliferation. Moreover, studies of postprandial triacylglycerol clearance indicated that CDKN2B is involved in down-regulation of SAT fatty acid trafficking. CDKN2B expression in SAT correlated with indicators of ectopic fat accumulation, including markers of hepatic steatosis. Among genes regulated by 9p21 risk variants, CDKN2B appears to play a significant role in the regulation of SAT expandability, which is a strong determinant of lipotoxicity and therefore might contribute to the development of atherosclerosis.
    Biochemical and Biophysical Research Communications 04/2014; · 2.28 Impact Factor
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    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.
    Nature Genetics 03/2014; · 29.65 Impact Factor
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    ABSTRACT: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
    Nature Genetics 03/2014; 46(3):234-244. · 29.65 Impact Factor
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    ABSTRACT: A major issue of in the treatment of diabetes is the risk of hypoglycemia. Hypoglycemia is detected both centrally and peripherally in the porto-hepatic area. The portal locus for hypoglycemic detection was originally described using the "local irrigation of the liver" approach in a canine model. Further work using portal vein denervation in a rodent model characterized portal hypoglycemic sensing in detail. However, recent controversy about the relevance of rodent findings to large animals and humans prompted us to investigate the effect of portal denervation on the hypoglycemic response in the canine, a species with multiple similarities to human glucose homeostasis. Hypoglycemic hyperinsulinemic clamps were performed in male canines, before and after portal vein denervation (DEN) or sham surgery (CON). Insulin (30 pmol/kg/min) and glucose (variable) were infused to slowly decrease systemic glycemia to 50 mg/dl over 160 min. The average plasma glucose during clamp steady state was: 2.9±0.1 mmol DEN-PRE; 2.9 ±0.2 mmol DEN-POST; 2.9±0.1 mmol CON-PRE and 2.8±0.0 mmol CON-POST. There were no significant differences in plasma insulin between DEN and CON, PRE and POST experiments. The epinephrine response to hypoglycemia was reduced by 62% in DEN but not in CON. Steady state cortisol was 46% lower post DEN but not post CON. Our study shows, in a large animal model, that surgical disconnection of the portal vein from the afferent pathway of the hypoglycemic counterregulatory circuitry results in a substantial suppression of the epinephrine response and a significant impact on cortisol response. These findings directly demonstrate an essential role for the portal vein in sensing hypoglycemia and relating glycemic information to the central nervous system.
    Endocrinology 01/2014; · 4.72 Impact Factor
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    ABSTRACT: Accurate quantification of insulin resistance is essential for determining efficacy of treatments to reduce diabetes risk. Gold standard methods to assess resistance are available (e.g. hyperinsulinemic clamp or minimal model), but surrogate indices based solely on fasting values have attractive simplicity. One such surrogate, the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), is widely applied despite known inaccuracies in characterizing resistance across groups. Of greater significance is whether HOMA-IR can detect changes in insulin sensitivity induced by an intervention. We tested the ability of HOMA-IR to detect high fat diet-induced insulin resistance in 36 healthy canines, using clamp and minimal model analysis of the intravenous glucose tolerance test (IVGTT) to document progression of resistance. The influence of pancreatic function on HOMA-IR accuracy was assessed using the acute insulin response during the IVGTT (AIRG). Diet-induced resistance was confirmed by both clamp and minimal model (p<0.0001), and measures were correlated with each other (p=0.001). In striking contrast, HOMA-IR ([fasting insulin (μU/ml) x fasting glucose (mM)] / 22.5) did not detect reduced sensitivity induced by fat feeding (p=0.22). In fact, 13 of 36 animals showed an artifactual decrease in HOMA-IR (i.e. increased sensitivity). The ability of HOMA-IR to detect diet-induced resistance was particularly limited under conditions when insulin secretory function (AIRG) is less than robust. In conclusion, HOMA-IR is of limited utility for detecting diet-induced deterioration of insulin sensitivity quantified by glucose clamp or minimal model. Caution should be exercised when using HOMA-IR to detect insulin resistance when pancreatic function is compromised.
    Diabetes 12/2013; · 7.90 Impact Factor
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    ABSTRACT: Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci and indices of proinsulin processing, insulin secretion and insulin sensitivity. We included data from up to 58,614 non-diabetic subjects with basal measures, and 17,327 with dynamic measures. We employed additive genetic models with adjustment for sex, age and BMI, followed by fixed-effects inverse variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (including TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without detectable change in fasting glucose. The final group contained twenty risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.
    Diabetes 12/2013; · 7.90 Impact Factor
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    ABSTRACT: Objective: We describe the GUARDIAN (Genetics UndeRlying DIAbetes in HispaNics) consortium, along with heritability estimates and genetic and environmental correlations of insulin sensitivity and metabolic clearance rate of insulin (MCRI). Design and Methods: GUARDIAN is comprised of seven cohorts, consisting of 4336 Mexican-American individuals in 1346 pedigrees. Insulin sensitivity (SI ), MCRI, and acute insulin response (AIRg) were measured by frequently sampled intravenous glucose tolerance test in four cohorts. Insulin sensitivity (M, M/I) and MCRI were measured by hyperinsulinemic-euglycemic clamp in three cohorts. Heritability and genetic and environmental correlations were estimated within the family cohorts (totaling 3925 individuals) using variance components. Results: Across studies, age and gender-adjusted heritability of insulin sensitivity (SI , M, M/I) ranged from 0.23-0.48 and of MCRI from 0.35-0.73. The ranges for the genetic correlations were 0.91 to 0.93 between SI and MCRI; and -0.57 to 0.59 for AIRg and MCRI (all P<0.0001). The ranges for the environmental correlations were 0.54 to 0.74 for SI and MCRI (all P<0.0001); and -0.16 to -0.36 for AIRg and MCRI (P <0.0001-0.06). Conclusions: These data support a strong familial basis for insulin sensitivity and MCRI in Mexican Americans. The strong genetic correlations between MCRI and SI suggest common genetic determinants.
    Obesity 10/2013; · 4.39 Impact Factor
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    ABSTRACT: Insulin-independent glucose disposal (referred to as glucose effectiveness [GE]) is crucial for glucose homeostasis and, until recently, was thought to be invariable. However, GE is reduced in type 2 diabetes and markedly decreased in leptin-deficient ob/ob mice. Strategies aimed at increasing GE should therefore be capable of improving glucose tolerance in these animals. The gut-derived hormone FGF19 has previously been shown to exert potent antidiabetic effects in ob/ob mice. In ob/ob mice, we found that systemic FGF19 administration improved glucose tolerance through its action in the brain and that a single, low-dose i.c.v. injection of FGF19 dramatically improved glucose intolerance within 2 hours. Minimal model analysis of glucose and insulin data obtained during a frequently sampled i.v. glucose tolerance test showed that the antidiabetic effect of i.c.v. FGF19 was solely due to increased GE and not to changes of either insulin secretion or insulin sensitivity. The mechanism underlying this effect appears to involve increased metabolism of glucose to lactate. Together, these findings implicate the brain in the antidiabetic action of systemic FGF19 and establish the brain's capacity to rapidly, potently, and selectively increase insulin-independent glucose disposal.
    The Journal of clinical investigation 10/2013; · 15.39 Impact Factor
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    ABSTRACT: Insulin resistance is a powerful risk factor for Type 2 diabetes and a constellation of chronic diseases, and is most commonly associated with obesity. We examined if factors other than obesity are more substantial predictors of insulin sensitivity under baseline, non-stimulated conditions. Metabolic assessment was performed in healthy dogs (n=90). Whole-body sensitivity from euglycemic clamps (SICLAMP ) was the primary outcome variable, and was measured independently by IVGTT (n=36). Adiposity was measured by MRI (n=90), and glucose-stimulated insulin response was measured from hyperglycemic clamp or IVGTT (n=86 and 36, respectively). SICLAMP was highly variable (5.9 to 75.9 dl/min per kg per μU/ml). Despite narrow range of body weight (mean, 28.7±0.3 kg), adiposity varied ~8-fold and was inversely correlated with SICLAMP (p<0.025). SICLAMP was negatively associated with fasting insulin, but most strongly associated with insulin clearance. Clearance was the dominant factor associated with sensitivity (r=0.53, p<0.00001), whether calculated from clamp or IVGTT. These data suggest that insulin clearance contributes substantially to insulin sensitivity, and may be pivotal in understanding the pathogenesis of insulin resistance. We propose that hyperinsulinemia due to reduction in insulin clearance is responsible for insulin resistance secondary to changes in body weight.
    Obesity 09/2013; · 4.39 Impact Factor

Publication Stats

26k Citations
2,799.38 Total Impact Points


  • 2014
    • The University of Warwick
      • Division of Metabolic and Vascular Health
      Coventry, England, United Kingdom
  • 2012–2014
    • Cedars-Sinai Medical Center
      • Cedars Sinai Medical Center
      Los Angeles, California, United States
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
    • University of Oxford
      • Wellcome Trust Centre for Human Genetics
      Oxford, ENG, United Kingdom
  • 1979–2012
    • University of Southern California
      • • Department of Physiology and Biophysics
      • • Department of Biomedical Engineering
      Los Angeles, California, United States
    • Northwestern University
      Evanston, Illinois, United States
  • 2009–2011
    • University of Toronto
      • Department of Nutritional Sciences
      Toronto, Ontario, Canada
  • 2010
    • Broad Institute of MIT and Harvard
      • Program in Medical and Population Genetics
      Cambridge, Massachusetts, United States
  • 1999–2010
    • University of Michigan
      • Department of Biostatistics
      Ann Arbor, MI, United States
  • 1990–2010
    • University of Texas Health Science Center at San Antonio
      • • Division of Clinical Epidemiology
      • • Division of Hospital Medicine
      San Antonio, TX, United States
    • University of Illinois at Chicago
      • Section of Endocrinology, Diabetes and Metabolism
      Chicago, IL, United States
  • 1989–2010
    • University of California, Los Angeles
      • • Department of Physiology
      • • Department of Medicine
      Los Angeles, California, United States
  • 2008–2009
    • University of Virginia
      • • Center for Public Health Genomics (CPHG)
      • • Department of Public Health Sciences
      Charlottesville, Virginia, United States
  • 2003–2008
    • Wake Forest School of Medicine
      • • Department of Biochemistry
      • • Division of Public Health Sciences
      Winston-Salem, NC, United States
  • 2002–2007
    • Keck School of Medicine USC
      Los Angeles, California, United States
  • 2006
    • Harbor-UCLA Medical Center
      Torrance, California, United States
  • 1999–2006
    • National Human Genome Research Institute
      Maryland, United States
  • 2005
    • Kaiser Permanente
      Oakland, California, United States
    • Laval University
      • Département de Kinésiologie
      Québec, Quebec, Canada
    • University of North Carolina at Chapel Hill
      • Department of Genetics
      Chapel Hill, NC, United States
  • 2004–2005
    • Pennington Biomedical Research Center
      • Human Genomics Laboratory
      Baton Rouge, Louisiana, United States
    • University of Maryland, Baltimore
      • Division of Endocrinology, Diabetes and Nutrition
      Baltimore, MD, United States
    • University of Houston
      • Department of Chemistry
      Houston, TX, United States
  • 2003–2005
    • University of Pennsylvania
      • School of Veterinary Medicine
      Philadelphia, PA, United States
  • 2001
    • University of Alabama at Birmingham
      Birmingham, Alabama, United States
    • Novo Nordisk
      København, Capital Region, Denmark
  • 1998
    • Joslin Diabetes Center
      Boston, Massachusetts, United States
    • Texas Tech University Health Sciences Center
      • Department of Medicine
      Lubbock, TX, United States
    • University of South Carolina
      • Department of Epidemiology & Biostatistics
      Columbia, SC, United States
    • National Public Health Institute
      Helsinki, Southern Finland Province, Finland
  • 1996
    • University of Melbourne
      Melbourne, Victoria, Australia
    • Wake Forest University
      • Department of Public Health Sciences
      Winston-Salem, North Carolina, United States
  • 1989–1994
    • University of Washington Seattle
      • Department of Medicine
      Seattle, WA, United States