Leigh Perreault

Impact of insufficient sleep on total daily energy expenditure, food intake, and weight gain

Insufficient sleep is associated with obesity, yet little is known about how repeated nights of insufficient sleep influence energy expenditure and balance. We studied 16 adults in a 14- to 15-d-long inpatient study and quantified effects of 5 d of insufficient sleep, equivalent to a work week, on energy expenditure and energy intake compared with adequate sleep. We found that insufficient sleep increased total daily energy expenditure by ∼5%; however, energy intake—especially at night after dinner—was in excess of energy needed to maintain energy balance. Insufficient sleep led to 0.82 ± 0.47 kg (±SD) weight gain despite changes in hunger and satiety hormones ghrelin and leptin, and peptide YY, which signaled excess energy stores. Insufficient sleep delayed circadian melatonin phase and also led to an earlier circadian phase of wake time. Sex differences showed women, not men, maintained weight during adequate sleep, whereas insufficient sleep reduced dietary restraint and led to weight gain in women. Our findings suggest that increased food intake during insufficient sleep is a physiological adaptation to provide energy needed to sustain additional wakefulness; yet when food is easily accessible, intake surpasses that needed. We also found that transitioning from an insufficient to adequate/recovery sleep schedule decreased energy intake, especially of fats and carbohydrates, and led to −0.03 ± 0.50 kg weight loss. These findings provide evidence that sleep plays a key role in energy metabolism. Importantly, they demonstrate physiological and behavioral mechanisms by which insufficient sleep may contribute to overweight and obesity.

Effect of regression from prediabetes to normal glucose regulation on long-term reduction in diabetes risk: results from the Diabetes Prevention Program Outcomes Study.

BACKGROUND 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. METHODS 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). FINDINGS 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, p<0·0001) 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, p<0·0001), increased β-cell function (OR 1·28; 95% CI 1·18-1·39, p<0·0001), and insulin sensitivity (OR 1·16, 95% CI 1·08-1·25, p<0·0001) 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, p<0·0001) 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. INTERPRETATION 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. FUNDING US National Institutes of Health.

Energy expenditure during sleep, sleep deprivation and sleep following sleep deprivation in adult humans

One of the proposed functions of sleep is to conserve energy. We determined the amount of energy conserved by sleep in humans, how much more energy is expended when missing a night of sleep, and how much energy is conserved during recovery sleep. Findings support the hypothesis that a function of sleep is to conserve energy in humans. Sleep deprivation increased energy expenditure indicating that maintaining wakefulness under bed‐rest conditions is energetically costly. Recovery sleep after sleep deprivation reduced energy use compared to baseline sleep suggesting that human metabolic physiology has the capacity to make adjustments to respond to the energetic cost of sleep deprivation. The finding that sleep deprivation increases energy expenditure should not be interpreted that sleep deprivation is a safe or effective strategy for weight loss as other studies have shown that chronic sleep deprivation is associated with impaired cognition and weight gain.

Updated Genetic Score Based on 34 Confirmed Type 2 Diabetes Loci Is Associated With Diabetes Incidence and Regression to Normoglycemia in the Diabetes Prevention Program

OBJECTIVE Over 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes–associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP). RESEARCH DESIGN AND METHODS We genotyped 34 type 2 diabetes–associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment. RESULTS In multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00–1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93–0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in β-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001). CONCLUSIONS A high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk.

Regression From Pre-Diabetes to Normal Glucose Regulation in the Diabetes Prevention Program

OBJECTIVE Participants in the Diabetes Prevention Program (DPP) randomized to intensive lifestyle modification (ILS) or metformin had a significantly reduced incidence of diabetes compared with those randomized to placebo, yet most were still at risk because they had pre-diabetes. We explored the effect of baseline characteristics, weight change, ILS, and metformin on regression from pre-diabetes to the lowest-risk state of normal glucose regulation (NGR) defined by American Diabetes Association criteria. RESEARCH DESIGN AND METHODS The DPP was a prospective randomized trial. Cox proportional hazards modeling was used to identify predictors of regression from pre-diabetes to NGR over 3 years of follow-up. RESULTS Lower baseline fasting (hazard ratio 1.52, P < 0.01) and 2-h (1.24, P < 0.01) glucose predicted regression to NGR, as did younger age (1.07, P < 0.01) and greater insulin secretion (1.09, P = 0.04). ILS (2.05, P < 0.01) and weight loss (1.34, P < 0.01) had significant and independent effects on regression. A nonsignificant trend for regression was also observed for metformin (1.25, P = 0.06), male sex (1.17, P = 0.08), and insulin sensitivity (1.07, P = 0.09). In those entering the study with both impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), male sex and insulin sensitivity predicted regression to isolated IFG, whereas ILS, metformin, female sex, and greater insulin secretion predicted regression to isolated IGT. CONCLUSIONS Insulin secretion, and other biologic processes retained with younger age, are key in restoring NGR in people with pre-diabetes. However, NGR may also be attained through weight loss and additional aspects of ILS.

Sex differences in diabetes risk and the effect of intensive lifestyle modification in the Diabetes Prevention Program

OBJECTIVE—In participants of the Diabetes Prevention Program (DPP) randomized to intensive lifestyle modification (ILS), meeting ILS goals strongly correlated with prevention of diabetes in the group as a whole. Men met significantly more ILS goals than women but had a similar incidence of diabetes. Therefore, we explored sex differences in risk factors for diabetes and the effect of ILS on risk factors. RESEARCH DESIGN AND METHODS—Baseline risk factors for diabetes and percent change in risk factors over the first year in men versus women were compared using Wilcoxons rank-sum tests. RESULTS—At baseline, men were older and had a larger waist circumference; higher fasting plasma glucose concentration, caloric intake, and blood pressure; and lower HDL cholesterol and corrected insulin response than women, who were less physically active and had a higher BMI (P < 0.01 for all comparisons). Over the first year of the DPP, no sex difference in risk factors for diabetes was observed for those who lost <3% body weight. Weight loss of 3–7% body weight yielded greater decreases in 2-h glucose (P < 0.01), insulin concentration (P < 0.04), and insulin resistance (P < 0.03) in men than in women. Weight loss of >7% body weight resulted in greater decreases in 2-h glucose (P < 0.01), triglyceride level (P < 0.01), and A1C (P < 0.03) in men than in women. CONCLUSIONS—Weight loss >3% body weight yielded greater reduction in risk factors for diabetes in men than in women. Despite the more favorable effects of ILS in men, baseline risk factors were more numerous in men and likely obscured any sex difference in incident diabetes.

Increased intramuscular lipid synthesis and low saturation relate to insulin sensitivity in endurance-trained athletes.

Intramuscular triglyceride (IMTG) has received considerable attention as a potential mechanism promoting insulin resistance. Endurance-trained athletes have high amounts of IMTG but are insulin sensitive, suggesting IMTG content alone does not change insulin action. Recent data suggest increased muscle lipid synthesis protects against fat-induced insulin resistance. We hypothesized that rates of IMTG synthesis at rest would be increased in athletes compared with controls. Eleven sedentary men and 11 endurance-trained male cyclists participated in this study. An intravenous glucose tolerance test was performed to assess insulin action. After 3 days of dietary control and an overnight fast, [13C16]palmitate was infused at 0.0174 micromol.kg(-1).min(-1) for 4 h, followed by a muscle biopsy to measure isotope incorporation into IMTG and diacylglycerol. Compared with controls, athletes were twice as insulin sensitive (P=0.004) and had a significantly greater resting IMTG concentration (athletes: 20.4+/-1.6 microg IMTG/mg dry wt, controls: 14.5+/-1.8 microg IMTG/mg dry wt, P=0.04) and IMTG fractional synthesis rate (athletes: 1.56+/-0.37%/h, controls: 0.61+/-0.15%/h, P=0.03). Stearoyl-CoA desaturase 1 mRNA expression (P=0.02) and protein content (P=0.03) were also significantly greater in athletes. Diacylglycerol, but not IMTG, saturation was significantly less in athletes compared with controls (P=0.002). These data indicate endurance-trained athletes have increased synthesis rates of skeletal muscle IMTG and decreased saturation of skeletal muscle diacylglycerol. Increased synthesis rates are not due to recovery from exercise and are likely adaptations to chronic endurance exercise training.

Trajectories of cardiometabolic risk factors before diagnosis of three subtypes of type 2 diabetes: a post-hoc analysis of the longitudinal Whitehall II cohort study

BACKGROUND Most clinicians acknowledge that type 2 diabetes is multifactorial and has heterogeneous characteristics, but neither prevention nor treatment is systematically stratified. To address the heterogeneity of the disease, we examined whether patients diagnosed on the basis of fasting glucose concentrations, those diagnosed on the basis of 2 h concentrations, and those diagnosed on the basis of both criteria differed in terms of pathogenesis or cardiovascular risks. METHODS Retrospectively, we analysed trajectories of cardiometabolic risk factors and 10 year cardiovascular risks in the prospective Whitehall II study cohort by use of multilevel longitudinal modelling. Participants were diagnosed by 75 g oral glucose-tolerance tests. We classified those diagnosed with type 2 diabetes into three subgroups: diagnosed on the basis of fasting glucose concentrations, diagnosed on the basis of 2 h glucose concentrations, and diagnosed on the basis of both concentrations. We also developed a classification tree for identification of individuals who are likely to have high fasting and 2 h glucose concentrations, but for whom only fasting concentrations are available. RESULTS Median follow-up was 14·2 years with 15,826 person-examinations (1991-2009). Of 10,308 individuals, 6843 were included and 6569 remained diabetes free. 274 cases of type 2 diabetes were identified: 55 had high fasting glucose concentrations only, 148 had high 2 h concentrations only, and 71 had high fasting and 2 h concentrations. At diagnosis, participants with high fasting and 2 h glucose concentrations had higher mean body-mass indices (30·9 kg/m(2) [SD 5·7]) than did those with high fasting concentrations (28·4 kg/m(2) [4·4]; p=0·0009) or 2 h concentrations (27·9 kg/m(2) [4·9]; <0·0001). Mean glycated haemoglobin A1c concentrations were also higher in the fasting and 2 h subgroup (7·4% [1·6]) than in the fasting (5·9% [0·5]; <0·0001) or 2 h (5·9% [0·6]; <0·0001) sugroups. Additionally, the fasting and 2 h subgroup had a higher proportion of individuals with moderate or high risk of cardiovascular disease than did the fasting subgroup (p=0·02). A classic pattern of β-cell decompensation before diagnosis was noted only in the fasting and 2 h subgroup. Additionally, glucose concentrations and insulin resistance accelerated more substantially before diagnosis in the fasting and 2 h subgroup than in the fasting subgroup or the 2 h subgroup. INTERPRETATION Patients with type 2 diabetes diagnosed on the basis of increased fasting glucose concentrations or 2 h glucose concentrations, or both, have distinct cardiometabolic risk development before diagnosis. FUNDING UK Medical Research Council, UK Economic and Social Research Council, British Heart Foundation, UK Health and Safety Executive, UK Department of Health, US National Heart Lung and Blood Institute, US National Institute on Aging, US Agency for Health Care Policy Research, and John D and Catherine T MacArthur Foundation.

Features of hepatic and skeletal muscle insulin resistance unique to type 1 diabetes.

CONTEXT Type 1 diabetes is known to be a state of insulin resistance; however, the tissues involved in whole-body insulin resistance are less well known. It is unclear whether insulin resistance is due to glucose toxicity in the post-Diabetes Control and Complications Trial era of tighter glucose control. OBJECTIVE We performed this study to determine muscle and liver insulin sensitivity individuals with type 1 diabetes after overnight insulin infusion to lower fasting glucose concentration. DESIGN, PATIENTS, AND METHODS Fifty subjects [25 controls without and 25 individuals with type 1 diabetes (diabetes duration 22.9 ± 1.7 yr, without known end organ damage] were frequency matched on age and body mass index by group and studied. After 3 d of dietary control and overnight insulin infusion to normalize glucose, we performed a three-stage hyperinsulinemic/euglycemic clamp infusing insulin at 4, 8, and 40 mU/m(2) · min. Glucose metabolism was quantified using an infusion of [6,6-(2)H(2)]glucose. Hepatic insulin sensitivity was measured using the insulin IC(50) for glucose rate of appearance (Ra), whereas muscle insulin sensitivity was measured using the glucose rate of disappearance during the highest insulin dose. RESULTS Throughout the study, glucose Ra was significantly greater in individuals compared with those without type 1 diabetes. The concentration of insulin required for 50% suppression of glucose Ra was 2-fold higher in subjects with type 1 diabetes. Glucose rate of disappearance was significantly lower in individuals with type 1 diabetes during the 8- and 40-mU/m(2) · min stages. CONCLUSION Insulin resistance in liver and skeletal muscle was a significant feature in type 1 diabetes. Nevertheless, the etiology of insulin resistance was not explained by body mass index, percentage fat, plasma lipids, visceral fat, and physical activity and was also not fully explained by hyperglycemia.

Novel and Reversible Mechanisms of Smoking-Induced Insulin Resistance in Humans

Smoking is the most common cause of preventable morbidity and mortality in the United States, in part because it is an independent risk factor for the development of insulin resistance and type 2 diabetes. However, mechanisms responsible for smoking-induced insulin resistance are unclear. In this study, we found smokers were less insulin sensitive compared with controls, which increased after either 1 or 2 weeks of smoking cessation. Improvements in insulin sensitivity after smoking cessation occurred with normalization of IRS-1ser636 phosphorylation. In muscle cell culture, nicotine exposure significantly increased IRS-1ser636 phosphorylation and decreased insulin sensitivity, recapitulating the phenotype of smoking-induced insulin resistance in humans. The two pathways known to stimulate IRS-1ser636 phosphorylation (p44/42 mitogen-activated protein kinase [MAPK] and mammalian target of rapamycin [mTOR]) were both stimulated by nicotine in culture. Inhibition of mTOR, but not p44/42 MAPK, during nicotine exposure prevented IRS-1ser636 phosphorylation and normalized insulin sensitivity. These data indicate nicotine induces insulin resistance in skeletal muscle by activating mTOR. Therapeutic agents designed to oppose skeletal muscle mTOR activation may prevent insulin resistance in humans who are unable to stop smoking or are chronically exposed to secondhand smoke.