Richard N Bergman

The University of Warwick, Coventry, England, United Kingdom

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Publications (352)2789.57 Total impact

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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.
    American journal of physiology. Endocrinology and metabolism. 08/2014;
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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 e metabologia. 08/2014; 58(6):600-609.
  • 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.
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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; · 3.92 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; · 35.21 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. · 35.21 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: 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 01/2014; · 2.41 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; · 3.92 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; · 3.92 Impact Factor
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    ABSTRACT: Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes but its causal role remains controversial. We used a Mendelian randomisation approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics based genetic risk scores to test the associations with gold standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 cases and 64,731 controls). In conventional regression analyses a 1 SD decrease in adiponectin levels was correlated with a 0.31 SD (95%CIs: 0.26-0.35) increase in fasting insulin, a 0.34 SD (0.30-0.38) decrease in insulin sensitivity and a type 2 diabetes odds ratio of 1.75 (95%CIs: 1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD, 95%CI: -0.07, 0.11, N=29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95%CIs: -0.38, -0.02; N=1,860) and no evidence of a relationship with type 2 diabetes (odds ratio 0.94; 95%CIs: 0.75, 1.19; N= 2,777 cases and 13,011 controls). Using the ADIPOQ summary statistics genetic risk scores we found no evidence of an association between adiponectin lowering alleles and insulin sensitivity (effect per weighted adiponectin lowering allele: -0.03 SD, 95%CIs: -0.07, 0.01; N=2,969) or type 2 diabetes (odds ratio per weighted adiponectin lowering allele: 0.99; 95%CIs: 0.95, 1.04; 15,960 cases vs. 64,731 controls). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
    Diabetes 07/2013; · 7.90 Impact Factor
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    ABSTRACT: Obesity continues to be a major public health problem in the United States and worldwide. While recent statistics have demonstrated that obesity rates have begun to plateau, more severe classes of obesity are accelerating at a faster pace with important implications in regards to treatment. Bariatric surgery has a profound and durable effect on weight loss, being to date one of the most successful interventions for obesity. Objective: To provide updates to the possible role of gut hormones in post bariatric surgery weight loss and weight loss maintenance. Methods: The current review examines the changes in gastro-intestinal hormones with bariatric surgery and the potential mechanisms by which these changes could result in decreased weight and adiposity. Results and conclusion: The mechanism by which bariatric surgery results in body weight changes is incompletely elucidated, but it clearly goes beyond caloric restriction and malabsorption. Changes in gastro-intestinal hormones, including increases in GLP-1, PYY and oxyntomodulin, decreases in GIP and ghrelin, or the combined action of all these hormones might play a role in induction and long-term maintenance of weight loss.
    Obesity 03/2013; · 3.92 Impact Factor
  • Cathryn M Kolka, Richard N Bergman
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    ABSTRACT: The vascular endothelium has been identified as an important component in diabetes-associated complications, which include many cardiovascular disorders such as atherosclerosis, hypertension and peripheral neuropathy. Additionally, insulin's actions on the endothelium are now seen as a major factor in the metabolic effects of the hormone by increasing access to insulin sensitive tissues. Endothelial function is impaired in diabetes, obesity, and the metabolic syndrome, which could reduce insulin access to the tissue, and thus reduce insulin sensitivity independently of direct effects at the muscle cell. As such, the endothelium is a valid target for treatment of both the impaired glucose metabolism in diabetes, as well as the vascular based complications of diabetes. Here we review the basics of the endothelium in insulin action, with a focus on the skeletal muscle as insulin's major metabolic organ, and how this is affected by diabetes. We will focus on the most recent developments in the field, including current treatment possibilities.
    Reviews in Endocrine and Metabolic Disorders 01/2013; · 4.58 Impact Factor
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    ABSTRACT: OBJECTIVES We aimed to identify factors that are independently associated with the metabolic clearance rate of insulin (MCRI) and to examine the association of MCRI with incident type 2 diabetes in nondiabetic Hispanics and African Americans.RESEARCH DESIGN AND METHODS We investigated 1,116 participants in the Insulin Resistance Atherosclerosis Study (IRAS) Family Study with baseline examinations from 2000 to 2002 and follow-up examinations from 2005 to 2006. Insulin sensitivity (S(I)), acute insulin response (AIR), and MCRI were determined at baseline from frequently sampled intravenous glucose tolerance tests. MCRI was calculated as the ratio of the insulin dose over the incremental area under the curve of insulin. Incident diabetes was defined as fasting glucose ≥126 mg/dL or antidiabetic medication use by self-report.RESULTSWe observed that S(I) and HDL cholesterol were independent positive correlates of MCRI, whereas fasting insulin, fasting glucose, subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and AIR were independent negative correlates (all P < 0.05) at baseline. After 5 years of follow-up, 71 (6.4%) participants developed type 2 diabetes. Lower MCRI was associated with a higher risk of incident diabetes after adjusting for demographics, lifestyle factors, HDL cholesterol, indexes of obesity and adiposity, and insulin secretion (odds ratio 2.01 [95% CI 1.30-3.10], P = 0.0064, per one-SD decrease in log(e)-transformed MCRI).CONCLUSIONS Our data showed that lower MCRI predicts the incidence of type 2 diabetes.
    Diabetes care 12/2012; · 7.74 Impact Factor
  • Darko Stefanovski, Richard N Bergman
    Diabetes care 12/2012; 35(12):e91. · 7.74 Impact Factor

Publication Stats

24k Citations
2,789.57 Total Impact Points

Institutions

  • 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
    • University of Oxford
      • Wellcome Trust Centre for Human Genetics
      Oxford, ENG, United Kingdom
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
  • 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
    • University Hospital Regensburg
      Ratisbon, Bavaria, Germany
  • 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
    • National Public Health Institute
      Helsinki, Southern Finland Province, Finland
    • University of South Carolina
      • Department of Epidemiology & Biostatistics
      Columbia, SC, United States
  • 1994–1997
    • University of Kuopio
      • Department of Medicine
      Kuopio, Eastern 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