Showing papers by "Jose C. Florez published in 2014"

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

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.

Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico

Abstract: Performing genetic studies in multiple human populations can identify disease risk alleles that are common in one population but rare in others, with the potential to illuminate pathophysiology, health disparities, and the population genetic origins of disease alleles. Here we analysed 9.2 million single nucleotide polymorphisms (SNPs) in each of 8,214 Mexicans and other Latin Americans: 3,848 with type 2 diabetes and 4,366 non-diabetic controls. In addition to replicating previous findings, we identified a novel locus associated with type 2 diabetes at genome-wide significance spanning the solute carriers SLC16A11 and SLC16A13 (P = 3.9 × 10(-13); odds ratio (OR) = 1.29). The association was stronger in younger, leaner people with type 2 diabetes, and replicated in independent samples (P = 1.1 × 10(-4); OR = 1.20). The risk haplotype carries four amino acid substitutions, all in SLC16A11; it is present at ~50% frequency in Native American samples and ~10% in east Asian, but is rare in European and African samples. Analysis of an archaic genome sequence indicated that the risk haplotype introgressed into modern humans via admixture with Neanderthals. The SLC16A11 messenger RNA is expressed in liver, and V5-tagged SLC16A11 protein localizes to the endoplasmic reticulum. Expression of SLC16A11 in heterologous cells alters lipid metabolism, most notably causing an increase in intracellular triacylglycerol levels. Despite type 2 diabetes having been well studied by genome-wide association studies in other populations, analysis in Mexican and Latin American individuals identified SLC16A11 as a novel candidate gene for type 2 diabetes with a possible role in triacylglycerol metabolism.

Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity

Abstract: Patients with established type 2 diabetes display both β-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 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used 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 cluster (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 (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 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.

Association of a low-frequency variant in HNF1A with type 2 diabetes in a Latino population.

Abstract: Importance Latino populations have one of the highest prevalences of type 2 diabetes worldwide. Objectives To investigate the association between rare protein-coding genetic variants and prevalence of type 2 diabetes in a large Latino population and to explore potential molecular and physiological mechanisms for the observed relationships. Design, Setting, and Participants Whole-exome sequencing was performed on DNA samples from 3756 Mexican and US Latino individuals (1794 with type 2 diabetes and 1962 without diabetes) recruited from 1993 to 2013. One variant was further tested for allele frequency and association with type 2 diabetes in large multiethnic data sets of 14 276 participants and characterized in experimental assays. Main Outcome and Measures Prevalence of type 2 diabetes. Secondary outcomes included age of onset, body mass index, and effect on protein function. Results A single rare missense variant (c.1522G>A [p.E508K]) was associated with type 2 diabetes prevalence (odds ratio [OR], 5.48; 95% CI, 2.83-10.61; P = 4.4 × 10 −7 ) in hepatocyte nuclear factor 1-α ( HNF1A ), the gene responsible for maturity onset diabetes of the young type 3 (MODY3). This variant was observed in 0.36% of participants without type 2 diabetes and 2.1% of participants with it. In multiethnic replication data sets, the p.E508K variant was seen only in Latino patients (n = 1443 with type 2 diabetes and 1673 without it) and was associated with type 2 diabetes (OR, 4.16; 95% CI, 1.75-9.92; P = .0013). In experimental assays, HNF-1A protein encoding the p.E508K mutant demonstrated reduced transactivation activity of its target promoter compared with a wild-type protein. In our data, carriers and noncarriers of the p.E508K mutation with type 2 diabetes had no significant differences in compared clinical characteristics, including age at onset. The mean (SD) age for carriers was 45.3 years (11.2) vs 47.5 years (11.5) for noncarriers ( P = .49) and the mean (SD) BMI for carriers was 28.2 (5.5) vs 29.3 (5.3) for noncarriers ( P = .19). Conclusions and Relevance Using whole-exome sequencing, we identified a single low-frequency variant in the MODY3-causing gene HNF1A that is associated with type 2 diabetes in Latino populations and may affect protein function. This finding may have implications for screening and therapeutic modification in this population, but additional studies are required.

Polygenic Type 2 Diabetes Prediction at the Limit of Common Variant Detection

Abstract: Genome-wide association studies (GWAS) may have reached their limit of detecting common type 2 diabetes (T2D)–associated genetic variation. We evaluated the performance of current polygenic T2D prediction. Using data from the Framingham Offspring (FOS) and the Coronary Artery Risk Development in Young Adults (CARDIA) studies, we tested three hypotheses: 1) a 62-locus genotype risk score (GRSt) improves T2D prediction compared with previous less inclusive GRSt; 2) separate GRS for β-cell (GRSβ) and insulin resistance (GRSIR) independently predict T2D; and 3) the relationships between T2D and GRSt, GRSβ, or GRSIR do not differ between blacks and whites. Among 1,650 young white adults in CARDIA, 820 young black adults in CARDIA, and 3,471 white middle-aged adults in FOS, cumulative T2D incidence was 5.9%, 14.4%, and 12.9%, respectively, over 25 years. The 62-locus GRSt was significantly associated with incident T2D in all three groups. In FOS but not CARDIA, the 62-locus GRSt improved the model C statistic (0.698 and 0.726 for models without and with GRSt, respectively; P < 0.001) but did not materially improve risk reclassification in either study. Results were similar among blacks compared with whites. The GRSβ but not GRSIR predicted incident T2D among FOS and CARDIA whites. At the end of the era of common variant discovery for T2D, polygenic scores can predict T2D in whites and blacks but do not outperform clinical models. Further optimization of polygenic prediction may require novel analytic methods, including less common as well as functional variants.

Metformin Pharmacogenomics: Current Status and Future Directions

Abstract: The incidence of type 2 diabetes (T2D) and its costs to the health care system continue to rise. Despite the availability of at least 10 drug classes for the treatment of T2D, metformin remains the most widely used first-line pharmacotherapy for its treatment; however, marked interindividual variability in response and few clinical or biomarker predictors of response reduce its optimal use. As clinical care moves toward precision medicine, a variety of broad discovery-based “omics” approaches will be required. Technical innovation, decreasing sequencing cost, and routine sample storage and processing has made pharmacogenomics the most widely applied discovery-based approach to date. This opens up the opportunity to understand the genetics underlying the interindividual variation in metformin responses in order for clinicians to prescribe specific treatments to given individuals for better efficacy and safety: metformin for those predicted to respond and alternative therapies for those predicted to be nonresponders or who are at increased risk for adverse side effects. Furthermore, understanding of the genetic determinants of metformin response may lead to the identification of novel targets and development of more effective agents for diabetes treatment. The goals of this workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases were to review the state of research on metformin pharmacogenomics, discuss the scientific and clinical hurdles to furthering our knowledge of the variability in patient responses to metformin, and consider how to effectively use this increased understanding to improve patient outcomes.

Effects of Weight Loss, Weight Cycling, and Weight Loss Maintenance on Diabetes Incidence and Change in Cardiometabolic Traits in the Diabetes Prevention Program

Abstract: OBJECTIVE This study examined specific measures of weight loss in relation to incident diabetes and improvement in cardiometabolic risk factors. RESEARCH DESIGN AND METHODS This prospective, observational study analyzed nine weight measures, characterizing baseline weight, short- versus long-term weight loss, short- versus long-term weight regain, and weight cycling, within the Diabetes Prevention Program (DPP) lifestyle intervention arm ( n = 1,000) for predictors of incident diabetes and improvement in cardiometabolic risk factors over 2 years. RESULTS Although weight loss in the first 6 months was protective of diabetes (hazard ratio [HR] 0.94 per kg, 95% CI 0.90, 0.98; P P P P P P = 0.02), HOMA-IR (β = 0.25 units per cycle; P = 0.04), and systolic blood pressure (β = 0.94 mmHg per cycle; P = 0.01). After adjustment for baseline weight, the effect of weight cycling remained statistically significant for diabetes risk (HR 1.22, 95% CI 1.02, 1.47; P = 0.03) but not for cardiometabolic traits. CONCLUSIONS Two-year weight loss was the strongest predictor of reduced diabetes risk and improvements in cardiometabolic traits.

Metabolite Traits and Genetic Risk Provide Complementary Information for the Prediction of Future Type 2 Diabetes

Abstract: OBJECTIVE A genetic risk score (GRS) comprised of single nucleotide polymorphisms (SNPs) and metabolite biomarkers have each been shown, separately, to predict incident type 2 diabetes. We tested whether genetic and metabolite markers provide complementary information for type 2 diabetes prediction and, together, improve the accuracy of prediction models containing clinical traits. RESEARCH DESIGN AND METHODS Diabetes risk was modeled with a 62-SNP GRS, nine metabolites, and clinical traits. We fit age- and sex-adjusted logistic regression models to test the association of these sources of information, separately and jointly, with incident type 2 diabetes among 1,622 initially nondiabetic participants from the Framingham Offspring Study. The predictive capacity of each model was assessed by area under the curve (AUC). RESULTS Two hundred and six new diabetes cases were observed during 13.5 years of follow-up. The AUC was greater for the model containing the GRS and metabolite measurements together versus GRS or metabolites alone (0.820 vs. 0.641, P P = 0.01, respectively). Odds ratios for association of GRS or metabolites with type 2 diabetes were not attenuated in the combined model. The AUC was greater for the model containing the GRS, metabolites, and clinical traits versus clinical traits only (0.880 vs. 0.856, P = 0.002). CONCLUSIONS Metabolite and genetic traits provide complementary information to each other for the prediction of future type 2 diabetes. These novel markers of diabetes risk modestly improve the predictive accuracy of incident type 2 diabetes based only on traditional clinical risk factors.

Differences in pancreatic volume, fat content, and fat density measured by multidetector-row computed tomography according to the duration of diabetes.

Abstract: Pancreatic volume and fat content might be associated with β-cell function or insulin resistance (IR). We investigated the difference in pancreatic volume and fat content between age- and body mass index (BMI)-matched normal subjects and patients with having different durations of type 2 diabetes (T2D). We compared pancreatic volume and fat parameters between 50 age- and BMI-matched normal subjects, 51 subjects with newly diagnosed type 2 diabetes (T2D-new), 53 subjects with T2D 5Y groups. Pancreatic volume and fat and HUp–s values were associated with HbA1c and triglyceride levels. Pancreatic volume was correlated with IGI while pancreatic fat and HUp–s values were correlated with HOMA-IR. The current study suggests that pancreatic volume and fat deposition might be associated with the development and progression of T2D in Korean subjects.

HbA1c as a predictor of diabetes and as an outcome in the diabetes prevention program: A randomized clinical trial

Abstract: OBJECTIVE Glycated hemoglobin (HbA 1c ), a standard measure of chronic glycemia for managing diabetes, has been proposed to diagnose diabetes and identify people at risk. The Diabetes Prevention Program (DPP) was a 3.2-year randomized clinical trial of preventing type 2 diabetes with a 10-year follow-up study, the DPP Outcomes Study (DPPOS). We evaluated baseline HbA 1c as a predictor of diabetes and determined the effects of treatments on diabetes defined by an HbA 1c ≥6.5% (48 mmol/mol). RESEARCH DESIGN AND METHODS We randomized 3,234 nondiabetic adults at high risk of diabetes to placebo, metformin, or intensive lifestyle intervention and followed them for the development of diabetes as diagnosed by fasting plasma glucose (FPG) and 2-h postload glucose (2hPG) concentrations (1997 American Diabetes Association [ADA] criteria). HbA 1c was measured but not used for study eligibility or outcomes. We now evaluate treatment effects in the 2,765 participants who did not have diabetes at baseline according to FPG, 2hPG, or HbA 1c (2010 ADA criteria). RESULTS Baseline HbA 1c predicted incident diabetes in all treatment groups. Diabetes incidence defined by HbA 1c ≥6.5% was reduced by 44% by metformin and 49% by lifestyle during the DPP and by 38% by metformin and 29% by lifestyle throughout follow-up. Unlike the primary DPP and DPPOS findings based on glucose criteria, metformin and lifestyle were similarly effective in preventing diabetes defined by HbA 1c. CONCLUSIONS HbA 1c predicted incident diabetes. In contrast to the superiority of the lifestyle intervention on glucose-defined diabetes, metformin and lifestyle interventions had similar effects in preventing HbA 1c -defined diabetes. The long-term implications for other health outcomes remain to be determined.

An update on the pharmacogenomics of metformin: progress, problems and potential

Abstract: The increasing prevalence of Type 2 diabetes has emphasized the need to optimize treatment regimens. Metformin, the most widely used oral agent, is recommended as first-line drug therapy by multiple professional organizations. Response to metformin varies significantly at the individual level; this heterogeneity may be explained in part by genetic factors. Understanding these underlying factors may aid with tailoring treatment for individual patients as well as with designing improved Type 2 diabetes therapies. The past 10 years have seen substantial progress in the understanding of the pharmacogenetics of metformin response. The majority of this work has focused on genes involved in the pharmacokinetics of metformin. Owing to the uncertainty surrounding its mechanism of action, studies of pharmacodynamic genetics have been relatively few; genome-wide approaches have the potential to illuminate the molecular details of metformin response. In this review we summarize current knowledge about metformin pharmacogenetics and suggest directions for future investigation.

Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

Abstract: Patients with established type 2 diabetes display both β-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 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used 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 cluster (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 (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 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.

Effect of Phosphodiesterase Inhibition on Insulin Resistance in Obese Individuals

Abstract: Methods and Results-—We conducted a randomized, double-blinded, placebo-controlled trial of adults age 18 to 50 years with obesity and elevated fasting insulin levels (≥10 lU/mL). Participants were randomized to tadalafil 20 mg daily or placebo for 3 months. Oral glucose tolerance tests were performed, and the effect of tadalafil on IR was examined. A total of 53 participants (mean age, 33 years; body mass index [BMI], 38 kg/m 2 ) were analyzed, 25 randomized to tadalafil and 28 to placebo. In the overall sample, measures of IR did not differ between tadalafil and placebo groups at 3 months. However, in individuals with severe obesity (BMI ≥36.2 kg/m 2 ), tadalafil use was associated with improved IR (homeostatic model assessment for IR), compared to placebo (P=0.02, respectively). Furthermore, one measure of b-cell compensation for IR (oral disposition index) improved with tadalafil in the overall sample (P=0.009) and in the subgroup with severe obesity (P=0.01).

Common variation at PPARGC1A/B and change in body composition and metabolic traits following preventive interventions: the Diabetes Prevention Program.

Abstract: Aims/hypothesis PPARGC1A and PPARGCB encode transcriptional coactivators that regulate numerous metabolic processes. We tested associations and treatment (i.e. metformin or lifestyle modification) interactions with metabolic traits in the Diabetes Prevention Program, a randomised controlled trial in persons at high risk of type 2 diabetes.

Genetic risk of progression to type 2 diabetes and response to intensive lifestyle or metformin in prediabetic women with and without a history of gestational diabetes mellitus

Abstract: OBJECTIVE The Diabetes Prevention Program (DPP) trial investigated rates of progression to diabetes among adults with prediabetes randomized to treatment with placebo, metformin, or intensive lifes ...

The Influence of Rare Genetic Variation in SLC30A8 on Diabetes Incidence and β-Cell Function

Abstract: Context/Objective: The variant rs13266634 in SLC30A8, encoding a β-cell–specific zinc transporter, is associated with type 2 diabetes. We aimed to identify other variants in SLC30A8 that increase diabetes risk and impair β-cell function, and test whether zinc intake modifies this risk. Design/Outcome: We sequenced exons in SLC30A8 in 380 Diabetes Prevention Program (DPP) participants and identified 44 novel variants, which were genotyped in 3445 DPP participants and tested for association with diabetes incidence and measures of insulin secretion and processing. We examined individual common variants and used gene burden tests to test 39 rare variants in aggregate. Results: We detected a near-nominal association between a rare-variant genotype risk score and diabetes risk. Five common variants were associated with the oral disposition index. Various methods aggregating rare variants demonstrated associations with changes in oral disposition index and insulinogenic index during year 1 of follow-up. We did n...

Association of African genetic ancestry with fasting glucose and HbA1c levels in non-diabetic individuals: the Boston Area Community Health (BACH) Prediabetes Study.

Abstract: To test among diabetes-free urban community-dwelling adults the hypothesis that the proportion of African genetic ancestry is positively associated with glycaemia, after accounting for other continental ancestry proportions, BMI and socioeconomic status (SES). The Boston Area Community Health cohort is a multi-stage 1:1:1 stratified random sample of self-identified African-American, Hispanic and white adults from three Boston inner city areas. We measured 62 ancestry informative markers, fasting glucose (FG), HbA1c, BMI and SES (income, education, occupation and insurance status) and analysed 1,387 eligible individuals (379 African-American, 411 Hispanic, 597 white) without clinical or biochemical evidence of diabetes. We used three-heritage multinomial linear regression models to test the association of FG or HbA1c with genetic ancestry proportion adjusted for: (1) age and sex; (2) age, sex and BMI; and (3) age, sex, BMI and SES. Mean age- and sex-adjusted FG levels were 5.73 and 5.54 mmol/l among those with 100% African or European ancestry, respectively. Using per cent European ancestry as the referent, each 1% increase in African ancestry proportion was associated with an age- and sex-adjusted FG increase of 0.0019 mmol/l (p = 0.01). In the BMI- and SES-adjusted model the slope was 0.0019 (p = 0.02). Analysis of HbA1c gave similar results. A greater proportion of African genetic ancestry is independently associated with higher FG levels in a non-diabetic community-based cohort, even accounting for other ancestry proportions, obesity and SES. The results suggest that differences between African-Americans and whites in type 2 diabetes risk may include genetically mediated differences in glucose homeostasis.

Circulating natriuretic peptide concentrations reflect changes in insulin sensitivity over time in the Diabetes Prevention Program

Abstract: Aims/hypothesis We aimed to study the relationship between measures of adiposity, insulin sensitivity and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in the Diabetes Prevention Program (DPP).

Circulating natriuretic peptide concentrations reflect changes in insulin sensitivity over time in the Diabetes Prevention Program

Abstract: Aims/hypothesis We aimed to study the relationship between measures of adiposity, insulin sensitivity and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in the Diabetes Prevention Program (DPP).

Association of levels of fasting glucose and insulin with rare variants at the chromosome 11p11.2-MADD locus: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.

Abstract: Background—Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3, and SPI1, has been associated in genome-wide association studies with fasting glucose and insulin (FI). In ...

It's not black and white: individualizing metformin treatment in type 2 diabetes.

Abstract: The treatment of type 2 diabetes is algorithmic. Given a new diagnosis of type 2 diabetes, professional organizations offer a series of competing guidelines which share, as a common denominator, suggestions for both the initiation of therapy and subsequent escalation, depending on the ability of the prescribed regimen to achieve prespecified treatment goals (1, 2). At the top of all algorithms stands the generic drug metformin, which is safe, cheap, and effective; therefore, it is universally prescribed as the first-line agent in the treatment of type 2 diabetes, barring unusual contraindications. More recent recommendations have attempted to individualize treatment based on personal characteristics (3), but metformin remains in a pre-eminent position, and the prescriber’s assessment of suitability is necessarily subjective. This practice persists despite emerging evidence that metformin is not equally effective in everyone (4, 5). Thus, there is an urgent need to increase our granularity in type 2 diabetes therapeutics, so that precision medicine can guide the right prescription for the right patient at the right time. The paper by Williams et al (6) in this issue of the JCEM represents one step in that direction. Williams et al (6) examined whether response to metformin differs in European American or African American patients with type 2 diabetes by comparing change in glycated hemoglobin (HbA1C) in enrollees in the Henry Ford HealthSystem in southernMichigan.Theymadeuseof the electronic health records to identify 19 672 patients with diabetes taking metformin, among whom 7429 individuals self-identified as being African American and 8783 identified themselves as being European American. Participants had to have at least two HbA1C measurements while on metformin. The authors calculated the total daily dose of metformin exposure based on prescription information, normalized it to the allowed maximal dose (850 mg thrice daily, or 2550 mg), and derived 120-day windows to reflect the average lifespan of a red blood cell. They then used a variety of statistical models based on generalized estimating equations with repeated measures to examine the impact of metformin exposure on the outcome HbA1C, before and after adjustment for several relevant covariates such as patient age, sex, race/ethnicity, duration of time on treatment, baseline HbA1C level, and concomitant use of other diabetes medications (ie, similarly obtained exposure measures for meglitinides, sulfonylureas, thiazolidinediones, fast-acting insulin, and slow-acting insulin). They included interaction terms for self-reported ethnicity and conducted additional stratified analyses to confirm the observed effects. The authors found that African American patients were younger and had a higher HbA1C at baseline; a greater proportion of African American patients were women. They were also less likely to receive dipeptidyl peptidase-4 inhibitors and more likely to receive insulin. In every statistical model, African Americans were shown to be more responsive to metformin in terms of a change in HbA1C, even after adjusting for all relevant covariates. This provocative finding, if confirmed, would define African Americans as more likely metformin responders when compared to European Americans. Given the retrospective and uncontrolled nature of this exploration, however, great caution must be exercised to ensure that the observed differences are not the result of unmeasured confounders, and the authors take this valid concern to heart.

Insights From Monogenic Diabetes and Glycemic Treatment Goals for Common Types of Diabetes

Abstract: The “glucose hypothesis,” which held that bringing ambient glucose levels into the near-normal range would help prevent the onset of diabetic complications, was first supported by findings from the Diabetes Control and Complications Trial.1 Intensive glucose control resulting in a mean glycated hemoglobin (HbA1c) level near 7% had discernible and sustained effects on both microvascular2- 4 and macrovascular5 end points. An appeal of type 1 diabetes as a model for studying hyperglycemic effects is its clear-cut phenotype, in which autoimmune destruction of pancreatic beta cells causes hyperglycemia as the main triggering vascular insult at disease onset, typically unconfounded by other potential or established cardiovascular risk factors such as hyperinsulinemia, hyperlipidemia, and hypertension.

Genetics of Drug Response in Diabetes

Abstract: Patients with diabetes differ in how their diabetes responds to treatment. Some individuals can have a marked glycaemic response; others have a poor response. Some have adverse drug reactions (e.g. hy

Genome-Wide Association Studies of Glycaemic Traits: A MAGICal Journey

Abstract: Genome-wide association studies (GWAS) of patients with type 2 diabetes (T2D) and unaffected controls (case-control studies) have been hugely successful in identifying T2D risk loci. In the first 2 ye