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OBJECTIVE To determine glycemic and nonglycemic risk factors that contribute to the presence of diabetic retinopathy (DR) before and after the onset of type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS During the Diabetes Prevention Program (DPP) and DPP Outcome Study (DPPOS), we performed fundus photography over time in adults at high risk for developing T2D, including after they developed diabetes. Fundus photographs were graded using the Early Treatment Diabetic Retinopathy Study (ETDRS) grading system, with DR defined as typical lesions of DR (microaneurysms, exudates, hemorrhage, or worse) in either eye. RESULTS By DPPOS year 16 (∼20 years after random assignment into DPP), 24% of 1,614 participants who had developed T2D and 14% of 885 who remained without diabetes had DR. In univariate analyses, using results from across the entire duration of follow-up, American Indian race was associated with less frequent DR compared with non-Hispanic White (NHW) race, and higher HbA1c, fasting and 2-h plasma glucose levels during an oral glucose tolerance test, weight, and history of hypertension, dyslipidemia, and smoking, but not treatment group assignment, were associated with more frequent DR. On multivariate analysis, American Indian race was associated with less DR compared with NHW (odds ratio [OR] 0.36, 95% CI 0.20–0.66), and average HbA1c was associated with more DR (OR 1.92, 95% CI 1.46–1.74 per SD [0.7%] increase in HbA1c). CONCLUSIONS DR may occur in adults with prediabetes and early in the course of T2D. HbA1c was an important risk factor for the development of DR across the entire glycemic range from prediabetes to T2D.

OBJECTIVE Regression from prediabetes to normal glucose regulation (NGR) was associated with reduced incidence of diabetes by 56% over 10 years in participants in the Diabetes Prevention Program Outcomes Study (DPPOS). In an observational analysis, we examined whether regression to NGR also reduced risk for microvascular disease (MVD). RESEARCH DESIGN AND METHODS Generalized estimating equations were used to examine the prevalence of aggregate MVD at DPPOS year 11 in people who regressed to NGR at least once (vs. never) during the Diabetes Prevention Program (DPP). Logistic regression assessed the relationship of NGR with retinopathy, nephropathy, and neuropathy, individually. Generalized additive models fit smoothing splines to describe the relationship between average A1C during follow-up and MVD (and its subtypes) at the end of follow-up. RESULTS Regression to NGR was associated with lower prevalence of aggregate MVD in models adjusted for age, sex, race/ethnicity, baseline A1C, and treatment arm (odds ratio [OR] 0.78, 95% CI 0.65–0.78, P = 0.011). However, this association was lost in models that included average A1C during follow-up (OR 0.95, 95% CI 0.78–1.16, P = 0.63) or diabetes status at the end of follow-up (OR 0.92, 95% CI 0.75–1.12, P = 0.40). Similar results were observed in examination of the association between regression to NGR and prevalence of nephropathy and retinopathy, individually. Risk for aggregate MVD, nephropathy, and retinopathy increased across the A1C range. CONCLUSIONS Regression to NGR is associated with a lower prevalence of aggregate MVD, nephropathy, and retinopathy, primarily due to lower glycemic exposure over time. Differential risk for the MVD subtypes begins in the prediabetes A1C range.

OBJECTIVE Both lifestyle and metformin interventions can delay or prevent progression to type 2 diabetes mellitus (DM) in people with impaired glucose regulation, but there is considerable interindividual variation in the likelihood of receiving benefit. Understanding an individual’s 3-year risk of progressing to DM and regressing to normal glucose regulation (NGR) might facilitate benefit-based tailored treatment. RESEARCH DESIGN AND METHODS We used the values of 19 clinical variables measured at the Diabetes Prevention Program (DPP) baseline evaluation and Cox proportional hazards models to assess the 3-year risk of progression to DM and regression to NGR separately for DPP lifestyle, metformin, and placebo participants who were adherent to the interventions. Lifestyle participants who lost ≥5% of their initial body weight at 6 months and metformin and placebo participants who reported taking ≥80% of their prescribed medication at the 6-month follow-up were defined as adherent. RESULTS Eleven of 19 clinical variables measured at baseline predicted progression to DM, and 6 of 19 predicted regression to NGR. Compared with adherent placebo participants at lowest risk of developing diabetes, participants at lowest risk of developing diabetes who adhered to a lifestyle intervention had an 8% absolute risk reduction (ARR) of developing diabetes and a 35% greater absolute likelihood of reverting to NGR. Participants at lowest risk of developing diabetes who adhered to a metformin intervention had no reduction in their risk of developing diabetes and a 17% greater absolute likelihood of reverting to NGR. Participants at highest risk of developing DM who adhered to a lifestyle intervention had a 39% ARR of developing diabetes and a 24% greater absolute likelihood of reverting to NGR, whereas those who adhered to the metformin intervention had a 25% ARR of developing diabetes and an 11% greater absolute likelihood of reverting to NGR. CONCLUSIONS Unlike our previous analyses that sought to explain population risk, these analyses evaluate individual risk. The models can be used by overweight and obese adults with fasting hyperglycemia and impaired glucose tolerance to facilitate personalized decision-making by allowing them to explicitly weigh the benefits and feasibility of the lifestyle and metformin interventions.

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 < 0.01) and cardiometabolic risk factors (P < 0.01), weight loss from 0 to 2 years was the strongest predictor of reduced diabetes incidence (HR 0.90 per kg, 95% CI 0.87, 0.93; P < 0.01) and cardiometabolic risk factor improvement (e.g., fasting glucose: β = −0.57 mg/dL per kg, 95% CI −0.66, −0.48; P < 0.01). Weight cycling (defined as number of 5-lb [2.25-kg] weight cycles) ranged 0–6 times per participant and was positively associated with incident diabetes (HR 1.33, 95% CI 1.12, 1.58; P < 0.01), fasting glucose (β = 0.91 mg/dL per cycle; 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.

OBJECTIVE We tested genetic associations with weight loss and weight regain in the Diabetes Prevention Program, a randomized controlled trial of weight loss–inducing interventions (lifestyle and metformin) versus placebo. RESEARCH DESIGN AND METHODS Sixteen obesity-predisposing single nucleotide polymorphisms (SNPs) were tested for association with short-term (baseline to 6 months) and long-term (baseline to 2 years) weight loss and weight regain (6 months to study end). RESULTS Irrespective of treatment, the Ala12 allele at PPARG associated with short- and long-term weight loss (−0.63 and −0.93 kg/allele, P ≤ 0.005, respectively). Gene–treatment interactions were observed for short-term (LYPLAL1 rs2605100, Plifestyle*SNP = 0.032; GNPDA2 rs10938397, Plifestyle*SNP = 0.016; MTCH2 rs10838738, Plifestyle*SNP = 0.022) and long-term (NEGR1 rs2815752, Pmetformin*SNP = 0.028; FTO rs9939609, Plifestyle*SNP = 0.044) weight loss. Three of 16 SNPs were associated with weight regain (NEGR1 rs2815752, BDNF rs6265, PPARG rs1801282), irrespective of treatment. TMEM18 rs6548238 and KTCD15 rs29941 showed treatment-specific effects (Plifestyle*SNP < 0.05). CONCLUSIONS Genetic information may help identify people who require additional support to maintain reduced weight after clinical intervention.

In the article cited above, Fig. 3 was updated: the number 5 in the x -axis of panels A and B were deleted. Also, …