Response to comment on Vassy et al. polygenic type 2 diabetes prediction at the limit of common variant detection. Diabetes 2014;63:2172-2182.

Abbasi et al. (1) raise excellent points about the current and future states of type 2 diabetes risk prediction. Two issues in particular are worth consideration. First, our clinical and polygenic prediction models do not include time-varying assessments of known risk factors such as BMI and fasting glucose (2). Abbasi et al. are correct that doing so would likely improve the models\u2019 predictive accuracy. Instead, we patterned our models on what is more common in clinical practice. In many ways, the Framingham Heart Study cardiovascular disease risk score defines the paradigm of using a \u201csnapshot in time\u201d approach to risk assessment. That is, what can the characteristics of a patient sitting in front of the clinician tell him or her about that patient\u2019s risk of an outcome 10 years from now? The dynamic risk factors Abbasi et al. propose will be especially salient if clinicians increasingly incorporate risk factor trajectories into their clinical decision making. Second, their tiered approach to risk stratification (i.e., obtaining more resource-intensive information only among those individuals whose history suggests higher risk) places an appropriate emphasis on the risks, benefits, and costs of screening. We agree with their call for an evaluation of such screening strategies, although we would argue that anthropometry and basic laboratory analyses are already routinely measured in the many clinical settings. An interesting question, then, is whether collection of genome-wide data will be increasingly routine in the clinical setting or even brought by the patients themselves after consulting genotyping services outside of the standard clinical setting. We think our analyses show that even if each individual had his or her genotype for common genetic variation stored in the electronic medical record, its marginal value in diabetes risk prediction would be small. Whether more sophisticated genetic information available soon from high-throughput whole-genome sequencing with detailed functional annotation will improve type 2 diabetes risk prediction, drug targeting, or patient care overall remains an important question for the future

Polygenic type 2 diabetes prediction at the limit of common variant detection.

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 \u3b2-cell (GRS\u3b2) and insulin resistance (GRSIR) independently predict T2D; and 3) the relationships between T2D and GRSt, GRS\u3b2, 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 GRS\u3b2 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

Genetic evidence for a normal-weight "metabolically obese" phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes

PublishedJournal ArticleResearch Support, Non-U.S. Gov'tThe mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin-based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (β = 0.018; P = 4 × 10(-29)), lower HDL cholesterol (β = -0.020; P = 7 × 10(-37)), greater hepatic steatosis (β = 0.021; P = 3 × 10(-4)), higher alanine transaminase (β = 0.002; P = 3 × 10(-5)), lower sex-hormone-binding globulin (β = -0.010; P = 9 × 10(-13)), and lower adiponectin (β = -0.015; P = 2 × 10(-26)). The same risk alleles were associated with lower BMI (per-allele β = -0.008; P = 7 × 10(-8)) and increased visceral-to-subcutaneous adipose tissue ratio (β = -0.015; P = 6 × 10(-7)). Individuals carrying ≥17 fasting insulin-raising alleles (5.5% population) were slimmer (0.30 kg/m(2)) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5 × 10(-13)), CAD (OR 1.12; per-allele P = 1 × 10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg [per-allele P = 2 × 10(-5)] and 0.67 mmHg [per-allele P = 2 × 10(-4)], respectively) compared with individuals carrying ≤9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism

Documentation of body mass index and control of associated risk factors in a large primary care network

<p>Abstract</p> <p>Background</p> <p>Body mass index (BMI) will be a reportable health measure in the United States (US) through implementation of Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. We evaluated current documentation of BMI, and documentation and control of associated risk factors by BMI category, based on electronic health records from a 12-clinic primary care network.</p> <p>Methods</p> <p>We conducted a cross-sectional analysis of 79,947 active network patients greater than 18 years of age seen between 7/05 - 12/06. We defined BMI category as normal weight (NW, 18-24.9 kg/m²), overweight (OW, 25-29.9), and obese (OB, ≥ 30). We measured documentation (yes/no) and control (above/below) of the following three risk factors: blood pressure (BP) ≤130/≤85 mmHg, low-density lipoprotein (LDL) ≤130 mg/dL (3.367 mmol/L), and fasting glucose <100 mg/dL (5.55 mmol/L) or casual glucose <200 mg/dL (11.1 mmol/L).</p> <p>Results</p> <p>BMI was documented in 48,376 patients (61%, range 34-94%), distributed as 30% OB, 34% OW, and 36% NW. Documentation of all three risk factors was higher in obesity (OB = 58%, OW = 54%, NW = 41%, p for trend <0.0001), but control of all three was lower (OB = 44%, OW = 49%, NW = 62%, p = 0.0001). The presence of cardiovascular disease (CVD) or diabetes modified some associations with obesity, and OB patients with CVD or diabetes had low rates of control of all three risk factors (CVD: OB = 49%, OW = 50%, NW = 56%; diabetes: OB = 42%, OW = 47%, NW = 48%, p < 0.0001 for adiposity-CVD or diabetes interaction).</p> <p>Conclusions</p> <p>In a large primary care network BMI documentation has been incomplete and for patients with BMI measured, risk factor control has been poorer in obese patients compared with NW, even in those with obesity and CVD or diabetes. Better knowledge of BMI could provide an opportunity for improved quality in obesity care.</p

Preventing weight gain: the baseline weight related behaviors and delivery of a randomized controlled intervention in community based women

<p>Abstract</p> <p>Background</p> <p>Women aged 25–45 years represent a high risk group for weight gain and those with children are at increased risk because of weight gain associated with pregnancy and subsequent lifestyle change. Average self-reported weight gain is approximately 0.60 kg per year, and weight gain is associated with increased risk of chronic disease. There are barriers to reaching, engaging and delivering lifestyle interventions to prevent weight gain in this population.</p> <p>Methods</p> <p>This study investigated the baseline weight related behaviors and feasibility of recruiting and delivering a low intensity self-management lifestyle intervention to community based women with children in order to prevent weight gain, compared to standard education. The recruitment and delivery of the cluster-randomized controlled intervention was in conjunction with 12 primary (elementary) schools. Baseline data collection included demographic, anthropometric, behavioral and biological measures.</p> <p>Results</p> <p>Two hundred and fifty community based women were randomized as clusters to intervention (n = 127) or control (n = 123). Mean age was 40.4 years (SD 4.7) and mean BMI 27.8 kg/m²(SD 5.6). All components of this intervention were successfully delivered and retention rates were excellent, 97% at 4 months.</p> <p>Nearly all women (90%) reported being dissatisfied with their weight and 72% attempted to self-manage their weight. Women were more confident of changing their diet (mean score 3.2) than physical activity (mean score 2.7). This population perceived they were engaging in prevention behaviors, with 71% reporting actively trying to prevent weight gain, yet they consumed a mean of 68 g fat/day (SD30 g) and 27 g saturated fat/day (SD12 g) representing 32% and 13% of energy respectively. The women had a high rate of dyslipidemia (33%) and engaged in an average of 9187 steps/day (SD 3671).</p> <p>Conclusion</p> <p>Delivery of this low intensity intervention to a broad cross-section of community based women with children is feasible. Women with children are engaging in lifestyle behaviours which do not confer adequate health benefits. They appear to be motivated to attend prevention programs by their interest in weight management. Interventions are required to strengthen and sustain current attempts at achieving healthy lifestyle behaviours in women to prevent weight gain.</p> <p>Trial Registration Number</p> <p>ACTRN 12608000110381</p

Lean Body Mass, Interleukin 18, and Metabolic Syndrome in Apparently Healthy Chinese

OBJECTIVE: We aimed to investigate how lean body mass is related to circulating Interleukin 18 (IL-18) and its association with metabolic syndrome (MetS) among apparently healthy Chinese. METHODS: A population-based sample of 1059 Chinese men and women aged 35-54 years was used to measure plasma IL-18, glucose, insulin, lipid profile, inflammatory markers and high-molecular-weight (HMW)-adiponectin. Fat mass index (FMI) and lean mass index (LMI) were measured by dual-energy X-ray absorptiometry. MetS was defined by the updated National Cholesterol Education Program Adult Treatment Panel III criteria for Asian-Americans. RESULTS: Circulating IL-18 was positively correlated with LMI after adjustment for FMI (correlation coefficient = 0.11, P<0.001). The association with the MetS (odds ratio 3.43, 95% confidence interval 2.01-5.85) was substantially higher in the highest than the lowest quartile of IL-18 after multiple adjustments including body mass index. In the stratified multivariable regression analyses, the positive association between IL-18 and MetS was independent of tertiles of FMI, inflammatory markers and HMW-adiponectin, but significantly interacted with tertile of LMI (P for interaction = 0.010). CONCLUSION: Elevated plasma IL-18 was associated with higher MetS prevalence in apparently healthy Chinese, independent of traditional risk factors, FMI, inflammatory markers and HMW-adiponectin. More studies are needed to clarify the role of lean mass in IL-18 secretion and its associated cardio-metabolic disorders

A Methodological Perspective on Genetic Risk Prediction Studies in Type 2 Diabetes: Recommendations for Future Research

Fueled by the successes of genome-wide association studies, numerous studies have investigated the predictive ability of genetic risk models in type 2 diabetes. In this paper, we review these studies from a methodological perspective, focusing on the variables included in the risk models as well as the study designs and populations investigated. We argue and show that differences in study design and characteristics of the study population have an impact on the observed predictive ability of risk models. This observation emphasizes that genetic risk prediction studies should be conducted in those populations in which the prediction models will ultimately be applied, if proven useful. Of all genetic risk prediction studies to date, only a few were conducted in populations that might be relevant for targeting preventive interventions