Use of a High-Density Protein Microarray to Identify Autoantibodies in Subjects with Type 2 Diabetes Mellitus and an HLA Background Associated with Reduced Insulin Secretion

New biomarkers for type 2 diabetes mellitus (T2DM) may aid diagnosis, drug development or clinical treatment. Evidence is increasing for the adaptive immune system's role in T2DM and suggests the presence of unidentified autoantibodies. While high-density protein microarrays have emerged as a useful technology to identify possible novel autoantigens in autoimmune diseases, its application in T2DM has lagged. In Pima Indians, the HLA haplotype (HLA-DRB1*02) is protective against T2DM and, when studied when they have normal glucose tolerance, subjects with this HLA haplotype have higher insulin secretion compared to those without the protective haplotype. Possible autoantibody biomarkers were identified using microarrays containing 9480 proteins in plasma from Pima Indians with T2DM without the protective haplotype (n = 7) compared with those with normal glucose regulation (NGR) with the protective haplotype (n = 11). A subsequent validation phase involving 45 cases and 45 controls, matched by age, sex and specimen storage time, evaluated 77 proteins. Eleven autoantigens had higher antibody signals among T2DM subjects with the lower insulin-secretion HLA background compared with NGR subjects with the higher insulin-secretion HLA background (p<0.05, adjusted for multiple comparisons). PPARG2 and UBE2M had lowest p-values (adjusted p = 0.023) while PPARG2 and RGS17 had highest case-to-control antibody signal ratios (1.7). A multi-protein classifier involving the 11 autoantigens had sensitivity, specificity, and area under the receiver operating characteristics curve of 0.73, 0.80, and 0.83 (95% CI 0.74-0.91, p = 3.4x10-8), respectively. This study identified 11 novel autoantigens which were associated with T2DM and an HLA background associated with reduced insulin secretion. While further studies are needed to distinguish whether these antibodies are associated with insulin secretion via the HLA background, T2DM more broadly, or a combination of the two, this study may aid the search for autoantibody biomarkers by narrowing the list of protein targets

A Genome-Wide Association Study Using a Custom Genotyping Array Identifies Variants in GPR158 Associated with Reduced Energy Expenditure in American Indians

Pima Indians living in Arizona have a high prevalence of obesity, and we have previously shown that a relatively lower energy expenditure (EE) predicts weight and fat mass gain in this population. EE is a familial trait (heritability = 0.52); therefore, in the current study, we aimed to identify genetic variants that affect EE and thereby influence BMI and body fatness in Pima Indians. Genotypic data from 491,265 variants were analyzed for association with resting metabolic rate (RMR) and 24-h EE assessed in a whole-room calorimeter in 507 and 419 Pima Indians, respectively. Variants associated with both measures of EE were analyzed for association with maximum BMI and percent body fat (PFAT) in 5,870 and 912 Pima Indians, respectively. rs11014566 nominally associated with both measures of EE and both measures of adiposity in Pima Indians, where the G allele (frequency: Pima Indians = 0.60, Europeans <0.01) associated with lower 24-h EE ( = -33 kcal/day per copy), lower RMR ( = -31 kcal/day), higher BMI ( = +0.6 kg/m(2)), and higher PFAT ( = +0.9%). However, the association of rs11014566 with BMI did not directionally replicate when assessed in other ethnic groups. rs11014566 tags rs144895904, which affected promoter function in an in vitro luciferase assay. These variants map to GPR158, which is highly expressed in the brain and interacts with two other genes (RGS7 and CACNA1B) known to affect obesity in knockout mice. Our results suggest that common ethnic-specific variation in GPR158 may influence EE; however, its role in weight gain remains controversial, as it either had no association with BMI or associated with BMI but in the opposite direction in other ethnic groups

Preventing type 2 diabetes mellitus in Qatar by reducing obesity, smoking, and physical inactivity: mathematical modeling analyses.

BACKGROUND: The aim of this study was to estimate the impact of reducing the prevalence of obesity, smoking, and physical inactivity, and introducing physical activity as an explicit intervention, on the burden of type 2 diabetes mellitus (T2DM), using Qatar as an example. METHODS: A population-level mathematical model was adapted and expanded. The model was stratified by sex, age group, risk factor status, T2DM status, and intervention status, and parameterized by nationally representative data. Modeled interventions were introduced in 2016, reached targeted level by 2031, and then maintained up to 2050. Diverse intervention scenarios were assessed and compared with a counter-factual no intervention baseline scenario. RESULTS: T2DM prevalence increased from 16.7% in 2016 to 24.0% in 2050 in the baseline scenario. By 2050, through halting the rise or reducing obesity prevalence by 10-50%, T2DM prevalence was reduced by 7.8-33.7%, incidence by 8.4-38.9%, and related deaths by 2.1-13.2%. For smoking, through halting the rise or reducing smoking prevalence by 10-50%, T2DM prevalence was reduced by 0.5-2.8%, incidence by 0.5-3.2%, and related deaths by 0.1-0.7%. For physical inactivity, through halting the rise or reducing physical inactivity prevalence by 10-50%, T2DM prevalence was reduced by 0.5-6.9%, incidence by 0.5-7.9%, and related deaths by 0.2-2.8%. Introduction of physical activity with varying intensity at 25% coverage reduced T2DM prevalence by 3.3-9.2%, incidence by 4.2-11.5%, and related deaths by 1.9-5.2%. CONCLUSIONS: Major reductions in T2DM incidence could be accomplished by reducing obesity, while modest reductions could be accomplished by reducing smoking and physical inactivity, or by introducing physical activity as an intervention

Evaluating Active U: an Internet-mediated physical activity program.

Background: Engaging in regular physical activity can be challenging, particularly during the winter months. To promote physical activity at the University of Michigan during the winter months, an eight-week Internet-mediated program (Active U) was developed providing participants with an online physical activity log, goal setting, motivational emails, and optional team participation and competition. Methods: This study is a program evaluation of Active U. Approximately 47,000 faculty, staff, and graduate students were invited to participate in the online Active U intervention in the winter of 2007. Participants were assigned a physical activity goal and were asked to record each physical activity episode into the activity log for eight weeks. Statistics for program reach, effectiveness, adoption, and implementation were calculated using the Re-Aim framework. Multilevel regression analyses were used to assess the decline in rates of data entry and goal attainment during the program, to assess the likelihood of joining a team by demographic characteristics, to test the association between various predictors and the number of weeks an individual met his or her goal, and to analyze server load. Results: Overall, 7,483 individuals registered with the Active U website (≈16% of eligible), and 79% participated in the program by logging valid data at least once. Staff members, older participants, and those with a BMI < 25 were more likely to meet their weekly physical activity goals, and average rate of meeting goals was higher among participants who joined a competitive team compared to those who participated individually (IRR = 1.28, P < .001). Conclusion: Internet-mediated physical activity interventions that focus on physical activity logging and goal setting while incorporating team competition may help a significant percentage of the target population maintain their physical activity during the winter months

Effects of lifestyle intervention in persons at risk for type 2 diabetes mellitus - results from a randomised, controlled trial

Background: Lifestyle change is probably the most important single action to prevent type 2 diabetes mellitus. The purpose of this study was to assess the effects of a low-intensity individual lifestyle intervention by a physician and compare this to the same physician intervention combined with an interdisciplinary, group-based approach in a real-life setting. Methods: The “Finnish Diabetes Risk score” (FINDRISC) was used by GPs to identify individuals at high risk. A randomised, controlled design and an 18 month follow-up was used to assess the effect of individual lifestyle counselling by a physician (individual physician group, (IG)) every six months, with emphasis on diet and exercise, and compare this to the same individual lifestyle counselling combined with a group-based interdisciplinary program (individual and interdisciplinary group, (IIG)) provided over 16 weeks. Primary outcomes were changes in lifestyle indicated by weight reduction ≥ 5%, improvement in exercise capacity as assessed by VO2 max and diet improvements according to the Smart Diet Score (SDS). Results: 213 participants (104 in the IG and 109 in the IIG group, 50% women), with a mean age of 46 and mean body mass index 37, were included (inclusion rate > 91%) of whom 182 returned at follow-up (drop-out rate 15%). There were no significant differences in changes in lifestyle behaviours between the two groups. At baseline 57% (IG) and 53% (IIG) of participants had poor aerobic capacity and after intervention 35% and 33%, respectively, improved their aerobic capacity at least one metabolic equivalent. Unhealthy diets according to SDS were common in both groups at baseline, 61% (IG) and 60% (IIG), but uncommon at follow-up, 17% and 10%, respectively. At least 5% weight loss was achieved by 35% (IG) and 28% (IIG). In the combined IG and IIG group, at least one primary outcome was achieved by 93% while all primary outcomes were achieved by 6%. Most successful was the 78% reduction in the proportion of participants with unhealthy diet (almost 50% absolute reduction). Conclusion: It is possible to achieve important lifestyle changes in persons at risk for type 2 diabetes with modest clinical efforts. Group intervention yields no additional effects. The design of the study, with high inclusion and low dropout rates, should make the results applicable to ordinary clinical settings

Incidence of Diabetes in the Working Population in Spain: Results from the ICARIA Cohort

INTRODUCTION: Our objective was to evaluate the incidence of type 2 diabetes mellitus (T2DM) in a working population in Spain and to assess associations between its development and several risk factors. METHODS: The ICARIA (Ibermutuamur CArdiovascular RIsk Assessment) cohort (n = 627,523) includes ~3% of Spanish workers. This analysis was undertaken in individuals whose glycaemic status during the index period (May 2004-December 2007) was determined to be normal or indicative of prediabetes [fasting plasma glucose (FPG) 100-125 mg/dl] and who had at least one FPG measurement taken 9 months after a first measurement during follow-up (May 2004-June 2014) (n = 380,366). T2DM patients were defined as those with an FPG ? 126 mg/day and those who had already been diagnosed with T2DM or were taking antihyperglycaemic medications. RESULTS: The incidence rate of T2DM was 5.0 [95% confidence interval (CI) 4.9-5.1] cases per 1000 person-years. Under multivariate logistic regression analysis, the factor showing the strongest association with the occurrence of T2DM was the baseline FPG level, with the likelihood of T2DM almost doubling for every 5 mg/dl increase in baseline FPG between 100 and < 126 mg/dl. The presence of other cardiometabolic risk factors and being a blue-collar worker were also significantly associated with the occurrence of T2DM. CONCLUSIONS: The incidence of T2DM in the working population was within the range encountered in the general population and prediabetes was found to be the strongest risk factor for the development of diabetes. The workplace is an appropriate and feasible setting for the assessment of easily measurable risk factors, such as the presence of prediabetes and other cardiometabolic factors, to facilitate the early detection of individuals at higher risk of diabetes and the implementation of diabetes prevention programmes

Informing patients of familial diabetes mellitus risk: How do they respond? A cross-sectional survey

<p>Abstract</p> <p>Background</p> <p>A strong family history of type 2 diabetes mellitus (DM) confers increased DM risk. This survey analysis determined whether patients who were informed by their doctors of familial DM risk acknowledged that risk and took steps to reduce it.</p> <p>Methods</p> <p>We conducted an analysis of the National <it>Health Styles 2004 </it>mail survey. All non-diabetic participants who responded to the question of whether their doctor had or had not informed them of their familial DM risk (<it>n </it>= 3,323) were compared for their risk-reducing behaviour and attitude to DM risk.</p> <p>Results</p> <p>Forty-one percent (<it>n </it>= 616) of the question responders that had DM family histories were informed by their doctors of their familial risk; the chance of being informed increased with the number of relatives that had the disease. Members of the informed group were more likely than those in the non-informed group to report lifestyle changes to prevent DM (odds ratio [OR] 4.3, 95% confidence interval [CI] 3.5–5.2) and being tested for DM (OR 2.9, 95% CI 2.4–3.6), although no significant improvement occurred in their U.S.-recommended exercise activity (OR 0.9, 95% CI 0.7–1.1). Overall, informed responders recognised both their familial and personal DM risk; most discussed diabetes with their family (69%), though less so with friends (42%); however, 44% of them still did not consider themselves to be at risk.</p> <p>Conclusion</p> <p>Responders who were informed by their doctors of being at familial DM risk reported greater incidences of lifestyle changes, DM screening, and awareness of risk than non-informed responders. Doctors were more likely to inform patients with stronger DM family histories. Identifying this higher risk group, either in isolation or in combination with other recognised risk factors, offers doctors the opportunity to target limited health promotion resources efficiently for primary DM prevention.</p

Determinants of physical activity participation following traumatic brain injury

Aims The objective of the study described in this article was to establish the environmental, social, or personal determinants associated with physical activity participation in people with traumatic brain injury (TBI). Methods A multi-centre cross-sectional questionnaire survey using a convenience sample was used at eight community day centres for brain injured populations. The participants were 63 individuals with traumatic brain injury (51 male, 12 female). Physical activity participation was based on the proportion of participants achieving the level of physical activity recommended for health (30 mins moderate activity, most days of the week). Standardized measures were used to assess activities of daily living (Extended Activities of Daily Living Scale), self-efficacy (Self-Efficacy for Exercise Scale), social support (Social Support for Exercise Scale) and mood (General Health Questionnaire-12). Findings Over half the participants were not active enough for health benefit. Active participants were more independent in activities of daily living (t = -2.21, P < 0.05), had greater self-efficacy for exercise (t = -3.02, P < 0.05) and were more educated (χ2=5.61, P<0.05) than inactive participants. Logistic Regression showed self-efficacy for exercise to be the only significant predictor of physical activity participation (β = 0.32, OR 1.03, P < 0.05). Conclusions Self-efficacy predicted physical activity participation. Efforts to increase self-efficacy among brain injured participants may encourage activity participation in those who are able and this warrants further investigation

Application of the speed-duration relationship to normalize the intensity of high-intensity interval training

The tolerable duration of continuous high-intensity exercise is determined by the hyperbolic Speed-tolerable duration (S-tLIM) relationship. However, application of the S-tLIM relationship to normalize the intensity of High-Intensity Interval Training (HIIT) has yet to be considered, with this the aim of present study. Subjects completed a ramp-incremental test, and series of 4 constant-speed tests to determine the S-tLIM relationship. A sub-group of subjects (n = 8) then repeated 4 min bouts of exercise at the speeds predicted to induce intolerance at 4 min (WR4), 6 min (WR6) and 8 min (WR8), interspersed with bouts of 4 min recovery, to the point of exercise intolerance (fixed WR HIIT) on different days, with the aim of establishing the work rate that could be sustained for 960 s (i.e. 4×4 min). A sub-group of subjects (n = 6) also completed 4 bouts of exercise interspersed with 4 min recovery, with each bout continued to the point of exercise intolerance (maximal HIIT) to determine the appropriate protocol for maximizing the amount of high-intensity work that can be completed during 4×4 min HIIT. For fixed WR HIIT tLIM of HIIT sessions was 399±81 s for WR4, 892±181 s for WR6 and 1517±346 s for WR8, with total exercise durations all significantly different from each other (P&#60;0.050). For maximal HIIT, there was no difference in tLIM of each of the 4 bouts (Bout 1: 229±27 s; Bout 2: 262±37 s; Bout 3: 235±49 s; Bout 4: 235±53 s; P&#62;0.050). However, there was significantly less high-intensity work completed during bouts 2 (153.5±40. 9 m), 3 (136.9±38.9 m), and 4 (136.7±39.3 m), compared with bout 1 (264.9±58.7 m; P&#62;0.050). These data establish that WR6 provides the appropriate work rate to normalize the intensity of HIIT between subjects. Maximal HIIT provides a protocol which allows the relative contribution of the work rate profile to physiological adaptations to be considered during alternative intensity-matched HIIT protocols