In an effort to improve risk assessments for ozone (O3) we compared the incorporation of inhaled oxygen-18-labeled O3 (18O3) into the lungs of humans and laboratory rats. Cells and fluids obtainable through bronchoalveolar lavage (BAL) were examined after exposure to 18O3 to determine whether excess 18O concentrations (presumed to be reaction products of 18O3) could be detected and equated to the O3 dose to the lung. Three O3 effect measurements (increased BAL protein and neutrophils and decreased BAL macrophages) were also made in subjects or animals exposed in parallel to determine whether there was a correspondence between dose and effect measurements. Eight human male volunteers 18 to 35 yr of age were exposed to 18O3 (0.4 ppm for 2 h) with 15-min alternating periods of heavy treadmill exercise and rest. Rats (F344) were exposed identically, except without exercise. 18O3 was generated directly from pure 18O2. BAL cells and centrifugally separable surfactant material were freeze-dried and analyzed by mass spectrometer for excess 18O. Results showed that the exercising humans had four- to fivefold higher 18O concentrations in all of their BAL constituents than did the rats. The humans also had significant increases in all of the effects markers after 0.4 ppm O3, whereas the rats did not. Rats that were exposed to higher concentrations of 18O3 (2.0 ppm) had levels of 18O in BAL that were more comparable to but still lower than those of exercising humans. Changes in all of the effects markers in these rats were comparable or higher than in exercising humans.(ABSTRACT TRUNCATED AT 250 WORDS)
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.
Across the Diabetes Prevention Program (DPP) follow-up, cumulative diabetes incidence remained lower in the lifestyle compared with the placebo and metformin randomized groups and could not be explained by weight. Collection of self-reported physical activity (PA) (yearly) with cross-sectional objective PA (in follow-up) allowed for examination of PA and its long-term impact on diabetes prevention. RESEARCH DESIGN AND METHODS Yearly self-reported PA and diabetes assessment and oral glucose tolerance test results (fasting glucose semiannually) were collected for 3,232 participants with one accelerometry assessment 11-13 years after randomization (n 5 1,793). Mixed models determined PA differences across treatment groups. The association between PA and diabetes incidence was examined using Cox proportional hazards models. RESULTS There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight). The effect of PA was greater (12% decrease) among participants less active at baseline (<7.5 MET-h/week) (n 5 1,338) (0.88 [0.83, 0.93]; P < 0.0001), with stronger findings for lifestyle participants. Lifestyle had higher cumulative PA compared with metformin or placebo (P < 0.0001) and higher accelerometry total minutes per day measured during follow-up (P 5 0.001 and 0.047). All associations remained significant with the addition of weight in the models. CONCLUSIONS PA was inversely related to incident diabetes in the entire cohort across the study, with cross-sectional accelerometry results supporting these findings. This highlights the importance of PA within lifestyle intervention efforts designed to prevent diabetes and urges health care providers to consider both PA and weight when counseling high-risk patients.
ImportanceAge-related macular degeneration (AMD) is a leading cause of blindness with no treatment available for early stages. Retrospective studies have shown an association between metformin and reduced risk of AMD.ObjectiveTo investigate the association between metformin use and age-related macular degeneration (AMD).Design, Setting, and ParticipantsThe Diabetes Prevention Program Outcomes Study is a cross-sectional follow-up phase of a large multicenter randomized clinical trial, Diabetes Prevention Program (1996-2001), to investigate the association of treatment with metformin or an intensive lifestyle modification vs placebo with preventing the onset of type 2 diabetes in a population at high risk for developing diabetes. Participants with retinal imaging at a follow-up visit 16 years posttrial (2017-2019) were included. Analysis took place between October 2019 and May 2022.InterventionsParticipants were randomly distributed between 3 interventional arms: lifestyle, metformin, and placebo.Main Outcomes and MeasuresPrevalence of AMD in the treatment arms.ResultsOf 1592 participants, 514 (32.3%) were in the lifestyle arm, 549 (34.5%) were in the metformin arm, and 529 (33.2%) were in the placebo arm. All 3 arms were balanced for baseline characteristics including age (mean [SD] age at randomization, 49 [9] years), sex (1128 [71%] male), race and ethnicity (784 [49%] White), smoking habits, body mass index, and education level. AMD was identified in 479 participants (30.1%); 229 (14.4%) had early AMD, 218 (13.7%) had intermediate AMD, and 32 (2.0%) had advanced AMD. There was no significant difference in the presence of AMD between the 3 groups: 152 (29.6%) in the lifestyle arm, 165 (30.2%) in the metformin arm, and 162 (30.7%) in the placebo arm. There was also no difference in the distribution of early, intermediate, and advanced AMD between the intervention groups. Mean duration of metformin use was similar for those with and without AMD (mean [SD], 8.0 [9.3] vs 8.5 [9.3] years; P = .69). In the multivariate models, history of smoking was associated with increased risks of AMD (odds ratio, 1.30; 95% CI, 1.05-1.61; P = .02).Conclusions and RelevanceThese data suggest neither metformin nor lifestyle changes initiated for diabetes prevention were associated with the risk of any AMD, with similar results for AMD severity. Duration of metformin use was also not associated with AMD. This analysis does not address the association of metformin with incidence or progression of AMD.
OBJECTIVE To determine whether interventions that slow or prevent the development of type 2 diabetes in those at risk reduce the subsequent prevalence of diabetic retinopathy. RESEARCH DESIGN AND METHODS The Diabetes Prevention Program (DPP) randomized subjects at risk for developing type 2 diabetes because of overweight/obesity and dysglycemia to metformin (MET), intensive lifestyle intervention (ILS), or placebo (PLB) to assess the prevention of diabetes. During the DPP and DPP Outcome Study (DPPOS), we performed fundus photography over time on study participants, regardless of their diabetes status. Fundus photographs were graded using the Early Treatment Diabetic Retinopathy Study grading system, with diabetic retinopathy defined as typical lesions of diabetic retinopathy (microaneurysms, exudates, or hemorrhage, or worse) in either eye. RESULTS Despite reduced progression to diabetes in the ILS and MET groups compared with PLB, there was no difference in the prevalence of diabetic retinopathy between treatment groups after 1, 5, 11, or 16 years of follow-up. No treatment group differences in retinopathy were found within prespecified subgroups (baseline age, sex, race/ethnicity, baseline BMI). In addition, there was no difference in the prevalence of diabetic retinopathy between those exposed to metformin and those not exposed to metformin, regardless of treatment group assignment. CONCLUSION Interventions that delay or prevent the onset of type 2 diabetes in overweight/obese subjects with dysglycemia who are at risk for diabetes do not reduce the development of diabetic retinopathy for up to 20 years.
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