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Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with waist circumference and waist-to-hip ratio adjusted for body mass index (WCadjBMI, WHRadjBMI), but it remains unclear whether these SNPs relate to change in WCadjBMI or WHRadjBMI with lifestyle intervention. We hypothesized that polygenic scores (PS) comprised of 59 SNPs previously associated with central adiposity would predict less of a reduction in WCadjBMI or WHRadjBMI at eight-to-ten weeks in two lifestyle intervention trials, NUGENOB and DiOGenes, and at one year in 5 lifestyle intervention trials, Look AHEAD, Diabetes Prevention Program, Diabetes Prevention Study, DIETFITS, and PREDIMED-Plus. One standard deviation higher PS related to smaller one-year change in WCadjBMI in the lifestyle intervention arms at year 1, and thus predicted poorer response (beta=0.007, SE=0.003, p=0.03) among White participants overall and in White men (beta=0.01, SE=0.004, p=0.01). At average weight loss, this amounted to 0.20-0.28 cm per standard deviation. No significant findings emerged in White women, African American men, for the 8-10 week outcomes or for WHRadjBMI. Findings were heterogeneous in African American women. These results indicate that polygenic risk relates to change in WCadjBMI with lifestyle intervention but the effects are small and not of sufficient magnitude to be clinically significant.

Lifestyle intervention, combining calorie restriction and physical activity to induce weight loss, is the frontline treatment for overweight or obesity and well-known to reduce waist circumference (WC). Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with WC adjusted for body mass index (WCadjBMI), but it remains unclear whether these SNPs relate to the change in WCadjBMI with lifestyle intervention. Here, we examined whether 59 SNPs previously associated with WCadjBMI in GWAS predicted change in WCadjBMI at one year in 5 lifestyle intervention trials and at 8-10 weeks in two lifestyle intervention trials. Look AHEAD, Diabetes Prevention Program, Diabetes Prevention Study, DIETFITS, and PrediMed Plus contributed one-year data, and NUGENOB and DiOGenes contributed 8-10 week data. Genetic risk scores (GRS) combined associated alleles for each SNP weighted by association with WCadjBMI from Shungin et al, 2015 and meta-analyses with random effects for each trial were used to pool results. Among White participants, higher GRS related to smaller year one change in WCadjBMI in the lifestyle intervention arms, and thus predicted poorer response (p=0.009). With a point estimate of 0.002 (SE=0.001) across trials, for a person with an initial BMI of 34 and a year 1 reduction in BMI of 2.5, each weighted risk allele in the GRS contributed to a 0.06 cm (SE=0.03) higher WC at year 1. With a 25th%ile, median, and 75th%ile GRS of 42.77, 46.75, and 50.48, this translates to 0.46 cm less change in WC between the 25th%ile and 75th%ile. No significant findings emerged in men and women separately, in the African-American subset, for the 8-10 week outcomes, or for the individuals SNPs after correcting for multiple comparisons. These results may help to define the molecular pathways through which lifestyle intervention impacts central adiposity. Disclosure J. Mccaffery: None. T. Hansen: None. T. O. Kilpelainen: None. D. Corella: None. W. H. M. Saris: Advisory Panel; Self; Friesland Campina International, Consultant; Self; Nutrition et sante. T. I. A. Sørensen: None. J. Tuomilehto: None. R. R. Wing: None. T. Agurs-collins: None. K. A. Jablonski: None. Q. Pan: None. A. Astrup: Consultant; Self; Groupe Éthique et Santé, France, Employee; Self; Novo Nordisk Foundation, Other Relationship; Self; Flaxslim ApS, Denmark, Gelesis, Personalized Weight Management Research Consortium ApS (Gluco-Diet. dk). M. R. Christiansen: None. L. M. Corso: None. J. C. Florez: Consultant; Self; Goldfinch Bio, Inc., Other Relationship; Self; Novo Nordisk. P. W. Franks: Advisory Panel; Self; Zoe Global Limited, Consultant; Self; Eli Lilly and Company, Novo Nordisk. C. D. Gardner: None. Funding WESTAT/National Cancer Institute

Randomization to lifestyle intervention (ILS) or metformin (MET) in the Diabetes Prevention Program (DPP) resulted in weight loss and reduced progression to diabetes. The long term effects of these interventions on bone mineral density (BMD) and falls, both associated with weight loss, are not known. We determined if ILS or MET was associated with prevalence of osteoporosis, osteopenia or history of falls in the DPP Outcome Study (DPPOS). During DPP, 3234 participants at high risk for diabetes were randomized to ILS, MET or PLB; 2779 continued in DPPOS and were offered modified group ILS. During DPPOS, ILS was offered additional lifestyle reinforcement semi-annually and MET received unmasked metformin. This analysis includes 1384 DPPOS participants who had dual-energy X-ray absorptiometry hip scans at year 12 (Y12). Osteoporosis was defined as femoral neck BMD T-score ≤-2.5 and osteopenia as -2.5 Mean age at Y12 was 66.5 (±9.5) years. Mean time since DPP baseline was 15.6 (±0.7) years. Weight loss (DPP baseline to DPPOS Y12) did not differ across treatment groups (-4.4 kg ILS; -3.5 kg MET; -3.1 kg PLB; p=0.114). There were no differences across groups in the prevalence of osteoporosis in men (1.4% ILS, 1.3% MET, 0.7% PLB; p=0.836) or women (2.9% ILS, 2.9% MET, 3.1% PLB; p=0.983). Prevalence of osteopenia was also similar across groups. Prevalence of history of falls was similar across groups in men (16.0% ILS, 16.4% MET, 16.0% PLB; p=0.995) and women (25.7% ILS, 21.3% MET, 21.6% PLB; p=0.342). Prevalence of osteoporosis, osteopenia or history of falls did not differ between ILS or MET and PLB in men or women. In a cohort at high risk of diabetes, lifestyle intervention or metformin did not have long-term effects on bone density or falls. Disclosure A.V. Schwartz: None. Q. Pan: None. V. Aroda: Consultant; Self; Novo Nordisk Inc.. Research Support; Self; Novo Nordisk Inc., AstraZeneca, Calibra Medical, Eisai Inc., Sanofi. Consultant; Self; Sanofi. Research Support; Self; Theracos, Inc.. Employee; Spouse/Partner; Merck & Co., Inc.. Other Relationship; Self; American Diabetes Association. Consultant; Self; ADOCIA. J.P. Crandall: None. A. Kriska: None. C.S. Piromalli: None. M. Temprosa: Other Relationship; Self; Merck KGaA. H. Florez: Advisory Panel; Self; Sanofi. D. Research Group: None.

Weight loss prevents progression to diabetes but long term effects on lean mass are unknown. We determined if intensive lifestyle modification (ILS), metformin (MET) or placebo (PLB) treatment in the Diabetes Prevention Program (DPP) had differential effects on appendicular lean mass (ALM) and sarcopenic-obesity (SO) ∼16 years after DPP randomization in the DPP Outcome Study (DPPOS). During DPP, 3234 participants at high risk for diabetes were randomized to ILS, MET or PLB; 2779 continued in DPPOS and were offered modified group ILS. During DPPOS, ILS was offered additional lifestyle reinforcement semi-annually and MET received unmasked metformin. This analysis includes 1374 DPPOS participants who had dual-energy X-ray absorptiometry scans at year 12 for ALM (sum of lean mass in arms and legs). Low ALM was defined as ALM/BMI 30. Prevalence of low ALM and SO was compared across the 3 groups using Pearson’s chi-squared test. Logistic regression models determined the associations between treatment and low ALM or SO and between weight loss and low ALM or SO. Mean age at Y12 was 66.5 (±9.5) years. Mean time since DPP baseline was 15.6 (±0.7) years. Weight loss (DPP baseline to DPPOS Y12) did not differ by group (-4.4 kg ILS; -3.5 kg MET; -3.1 kg PLB; p=0.114). Prevalence of low ALM differed by group in men (35.7% ILS, 28.3% MET, 22.5% PLB; p=0.049) but not women (20.9% ILS, 24.8% MET, 24.1% PLB; p=0.482). In men, low ALM prevalence was higher in ILS compared with PLB (P=0.024) but not in MET vs. PLB. Prevalence of SO did not differ across groups in men (23.1% ISL, 22.0% MET, 14.1% PLB; p=0.112) or women (17.3% ILS, 20.9% MET, 20.3% PLB; p=0.492). SO prevalence was not different in ILS vs. PLB or in MET vs. PLB in men or women. More weight loss was associated with higher risk of low ALM and SO in women and men (p Disclosure A.V. Schwartz: None. Q. Pan: None. H.P. Hazuda: None. E. Horton: Advisory Panel; Self; PTS Diagnostics, Merck & Co., Inc., Theracos, Inc.. M.A. Hoskin: None. R. Rastogi Kalyani: None. W.C. Knowler: None. A. Kriska: None. M. Schlögl: None. H. Florez: Advisory Panel; Self; Sanofi. D. Research Group: None.

Objective: To examine whether odds of frailty differ by DPP intervention arms (intensive lifestyle intervention [ILS], metformin [MET], placebo [PLB] after long-term follow-up in the DPPOS. Methods: DPP, a randomized trial of individuals at high risk of diabetes, lasted 2.8 years, after which there was a 13-month bridge period in which 16 sessions of group ILS was offered to all participants. During DPPOS, ILS was offered lifestyle reinforcement semi-annually and MET received unmasked metformin. Frailty was measured initially in DPPOS Year 8 in 2385 participants and repeated in 2264 of these in Year 10 (12 and 14 years after randomization). Using Fried criteria, presence of 3 of 5 characteristics (slow walking speed, weak grip strength, unintentional weight loss, low physical activity, and exhaustion) was classified as frail, 1 or 2 pre-frail, and 0 non-frail.: GEE models adjusting for visit year were employed with repeated measures pooled from Years 8 and 10 to estimate pairwise odds ratios between ILS, MET and PLB for the outcomes of frail and pre-frail vs. non-frail. Results: Odds of frailty vs. non-frailty were 37% lower in ILS compared to PLB (Table) and MET (OR=0.629, CI= 0.420-0.942, p=0.024). There were no significant treatment group differences in odds of pre-frailty. Conclusion: ILS intervention in persons at high risk of diabetes may reduce frailty in later life.12 years Post-randomization14 years post-randomizationOdds of Frailty vs. Non-Frailty Pooled over both examsTreatment GroupPrevalencePrevalence OR (95% CI) compared with placeboP-valuePre-FrailtyFrailtyPre-FrailtyFrailtyPlacebo42.8%5.7%43.7%5.4%1 (referent)n/aMetformin45.8%5.4%42.5%5.3%0.994 (0.694-1.424)0.976Lifestyle46.8%3.0%46.3%3.6%0.625 (0.419-0.934)0.022 Disclosure H.P. Hazuda: None. Q. Pan: None. J.P. Crandall: None. H. Florez: Advisory Panel; Self; Sanofi. J.A. Luchsinger: None. E.M. Venditti: None. A. Kriska: None. S. Golden: None. G. Bray: Advisory Panel; Self; Herbalife International of America, Inc., Novo Nordisk A/S. D. Research Group: None.

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: To assess associations and genotype x treatment interactions for melanocortin 4 receptor (MC4R) locus variants and obesity-related traits. Design and Methods: Diabetes prevention program (DPP) participants (N = 3,819, of whom 3,356 were genotyped for baseline and 3,234 for longitudinal analyses) were randomized into intensive lifestyle modification (diet, exercise, weight loss), metformin or placebo control. Adiposity was assessed in a subgroup (n = 909) using computed tomography. All analyses were adjusted for age, sex, ethnicity and treatment. Results: The rs1943218 minor allele was nominally associated with short-term (6 month; P = 0.032) and long-term (2 year; P = 0.038) weight change. Eight SNPs modified response to treatment on short-term (rs17066856, rs9966412, rs17066859, rs8091237, rs17066866, rs7240064) or long-term (rs12970134, rs17066866) reduction in body weight, or diabetes incidence (rs17066829) (all P-interaction < 0.05). Conclusion: This is the first study to comprehensively assess the role of MC4R variants and weight regulation in a weight loss intervention trial. One MC4R variant was directly associated with obesity-related traits or diabetes; numerous other variants appear to influence body weight and diabetes risk by modifying the protective effects of the DPP interventions. (Less)

Adults at high risk for diabetes may have reduced health-related quality of life (HRQoL).To assess changes in HRQoL after interventions aimed at diabetes risk reduction.A randomized clinical trial, the Diabetes Prevention Program, was conducted in 27 centers in the United States, in 3,234 non-diabetic persons with elevated fasting and post-load plasma glucose, mean age 51 years, mean BMI 34 Kg/m(2); 68 % women, and 45 % members of minority groups.Intensive lifestyle (ILS) program with the goals of at least 7 % weight loss and 150 min of physical activity per week, metformin (MET) 850 mg twice daily, or placebo (PLB).HRQoL using the 36-Item Short-Form (SF-36) health survey to evaluate health utility index (SF-6D), physical component summaries (PCS) and mental component summaries (MCS). A minimally important difference (MID) was met when the mean of HRQoL scores between groups differed by at least 3 %.After a mean follow-up of 3.2 years, there were significant improvements in the SF-6D (+0.008, p=0.04) and PCS (+1.57, p0.0001) scores in ILS but not in MET participants (+0.002 and +0.15, respectively, p=0.6) compared to the PLB group. ILS participants showed improvements in general health (+3.2, p0.001), physical function (+3.6, p0.001), bodily pain (+1.9, p=0.01), and vitality (+2.1, p=0.01) domain scores. Treatment effects remained significant after adjusting sequentially for baseline demographic factors, and for medical and psychological comorbidities. Increased physical activity and weight reduction mediated these ILS treatment effects. Participants who experienced weight gain had significant worsening on the same HRQoL specific domains when compared to those that had treatment-related (ILS or MET) weight loss. No benefits with ILS or MET were observed in the MCS score.Overweight/obese adults at high risk for diabetes show small improvement in most physical HRQoL and vitality scores through the weight loss and increased physical activity achieved with an ILS intervention.

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.

Objective To assess associations and genotype × treatment interactions for melanocortin 4 receptor (MC4R) locus variants and obesity-related traits. Design and Methods Diabetes Prevention Program (DPP) participants (N=3,819, of whom 3,356 were genotyped for baseline and 3,234 for longitudinal analyses) were randomized into intensive lifestyle modification (diet, exercise, weight loss), metformin or placebo control. Adiposity was assessed in a subgroup (n=909) using computed tomography. All analyses were adjusted for age, sex, ethnicity and treatment. Results The rs1943218 minor allele was nominally associated with short-term (6 month; P=0.032) and long-term (2 year; P=0.038) weight change. Eight SNPs modified response to treatment on short-term (rs17066856, rs9966412, rs17066859, rs8091237, rs17066866, rs7240064) or long-term (rs12970134, rs17066866) reduction in body weight, or diabetes incidence (rs17066829) (all Pinteraction

Our objective was to quantify and predict diabetes risk reduction during the Diabetes Prevention Program Outcomes Study (DPPOS) in participants who returned to normal glucose regulation at least once during the Diabetes Prevention Program (DPP) compared with those who consistently met criteria for prediabetes.DPPOS is an ongoing observational study of participants from the DPP randomised trial. For this analysis, diabetes cumulative incidence in DPPOS was calculated for participants with normal glucose regulation or prediabetes status during DPP with and without stratification by previous randomised treatment group. Cox proportional hazards modelling and generalised linear mixed models were used to quantify the effect of previous (DPP) glycaemic status on risk of later (DPPOS) diabetes and normal glucose regulation status, respectively, per SD in change. Included in this analysis were 1990 participants of DPPOS who had been randomly assigned to treatment groups during DPP (736 intensive lifestyle intervention, 647 metformin, 607 placebo). These studies are registered at ClinicalTrials.gov, NCT00004992 (DPP) and NCT00038727 (DPPOS).Diabetes risk during DPPOS was 56% lower for participants who had returned to normal glucose regulation versus those who consistently had prediabetes (hazard ratio [HR] 0·44, 95% CI 0·37-0·55, p0·0001) and was unaffected by previous group assignment (interaction test for normal glucose regulation and lifestyle intervention, p=0·1722; normal glucose regulation and metformin, p=0·3304). Many, but not all, of the variables that increased diabetes risk were inversely associated with the chance of a participant reaching normal glucose regulation status in DPPOS. Specifically, previous achievement of normal glucose regulation (odds ratio [OR] 3·18, 95% CI 2·71-3·72, p0·0001), increased β-cell function (OR 1·28; 95% CI 1·18-1·39, p0·0001), and insulin sensitivity (OR 1·16, 95% CI 1·08-1·25, p0·0001) were associated with normal glucose regulation in DPPOS, whereas the opposite was true for prediction of diabetes, with increased β-cell function (HR 0·80, 95% CI 0·71-0·89, p0·0001) and insulin sensitivity (HR 0·83, 95% CI 0·74-0·94, p=0·0001) having a protective effect. Among participants who did not return to normal glucose regulation in DPP, those assigned to the intensive lifestyle intervention had a higher diabetes risk (HR 1·31, 95% CI 1·03-1·68, p=0·0304) and lower chance of normal glucose regulation (OR 0·59, 95% CI 0·42-0·82, p=0·0014) than did the placebo group in DPPOS.We conclude that prediabetes is a high-risk state for diabetes, especially in patients who remain with prediabetes despite intensive lifestyle intervention. Reversion to normal glucose regulation, even if transient, is associated with a significantly reduced risk of future diabetes independent of previous treatment group.US National Institutes of Health.

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, P interaction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; P interaction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, P interaction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; P interaction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss., Author Summary The study included 2,993 participants from the Diabetes Prevention Program, a randomized clinical trial of intensive lifestyle intervention, metformin treatment, and placebo control. We examined associations between 32 gene variants that have been reproducibly associated with dyslipidemia and concentrations of lipids and NMR lipoprotein particle sizes and numbers. We also examined whether genetic background influences a person's response to cardioprotective interventions on lipid levels. Our analysis, which focused on determining whether common genetic variants impact the effects of cardioprotective interventions on lipid and lipoprotein particle size, shows that in persons with a high genetic risk score the benefit of intensive lifestyle intervention on LDL and small LDL particle levels is substantially diminished; this information may be informative for the targeted prevention of dyslipidemia, as it suggests that genetics might help identify persons in whom lifestyle intervention is likely to be an effective treatment for elevated lipids and lipoproteins. The NMR subfraction analyses provide novel insight into the biology of dyslipidemia by illustrating how numerous genetic variants that have previously been associated with lipid levels also modulate NMR lipoprotein particle sizes and number. This information may be informative for the targeted prevention of cardiovascular disease.