The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study.

CONTEXT: The role of glucagon-like peptide-1 (GLP-1) in type 2 diabetes (T2D) and obesity is not fully understood. OBJECTIVE: We investigate the association of cardiometabolic, diet, and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. METHODS: We analyzed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1 (n = 2127) individuals at risk of diabetes; cohort 2 (n = 789) individuals with new-onset T2D. RESULTS: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin-resistant phenotype and observe a strong independent relationship with male sex, increased adiposity, and liver fat, particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycemia, higher adiposity, liver fat, male sex, and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit, and vegetables in people with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. CONCLUSION: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake, and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

Estimating the Direct Effect between Dietary Macronutrients and Cardiometabolic Disease, Accounting for Mediation by Adiposity and Physical Activity.

Assessing the causal effects of individual dietary macronutrients and cardiometabolic disease is challenging because distinguish direct effects from those mediated or confounded by other factors is difficult. To estimate these effects, intake of protein, carbohydrate, sugar, fat, and its subtypes were obtained using food frequency data derived from a Swedish population-based cohort (n~60,000). Data on clinical outcomes (i.e., type 2 diabetes (T2D) and cardiovascular disease (CVD) incidence) were obtained by linking health registry data. We assessed the magnitude of direct and mediated effects of diet, adiposity and physical activity on T2D and CVD using structural equation modelling (SEM). To strengthen causal inference, we used Mendelian randomization (MR) to model macronutrient intake exposures against clinical outcomes. We identified likely causal effects of genetically predicted carbohydrate intake (including sugar intake) and T2D, independent of adiposity and physical activity. Pairwise, serial- and parallel-mediational configurations yielded similar results. In the integrative genomic analyses, the candidate causal variant localized to the established T2D gene TCF7L2. These findings may be informative when considering which dietary modifications included in nutritional guidelines are most likely to elicit health-promoting effects.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one. CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community. TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.

Trust, happiness and mortality: Findings from a prospective US population-based survey.

There has been an abundance of research discussing the health implications of generalised trust and happiness over the past two decades. Both attitudes have been touted as independent predictors of morbidity and mortality, with strikingly similar trajectories and biological pathways being hypothesised. To date, however, neither trust nor happiness have been considered simultaneously as predictors of mortality. This study, therefore, aims to investigate the effects of generalised trust and happiness on all-cause and cause-specific mortality. The distinction between different causes of death (i.e. cardiovascular vs. cancer-related mortality) allowed us to assess if psychosocial mechanisms could account for associations between generalised trust, happiness and mortality. The study sample was derived from US General Social Survey data from 1978 to 2010 (response rates ranged from 70 to 82 per cent), and combined with death records from the National Death Index. The analytical sample comprised 23,933 individuals with 5382 validated deaths from all-cause mortality by 2014. Analyses were performed with Cox regression models and competing-risk models. In final models, generalised trust, but not happiness, showed robust and independent associations with all-cause mortality. Regarding cause-specific mortality, trust only showed a significant relationship with cardiovascular mortality. The distinct patterns of association between generalised trust and all-cause/cause-specific mortality suggest that their relationship could be being driven by cardiovascular mortality. In turn, this supports the feasibility of psychosocial pathways as possible biological mechanisms from distrust to mortality.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium.

AIMS/HYPOTHESIS: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). METHODS: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. RESULTS: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants' clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. CONCLUSIONS/INTERPRETATION: The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes.

Changes in Social Capital and Cigarette Smoking Behavior Over Time: A Population-Based Panel Study of Temporal Relationships.

INTRODUCTION: Identifying factors that influence individuals' smoking behavior remains a huge public health concern. This study aimed to investigate changes in individuals' cigarette smoking while considering well-known smoking determinants, including social capital, its presence being postulated to reduce smoking. METHODS: From British Household Panel Survey data, two baseline smoking cohorts were created ("smoking" and "not smoking"). The same individuals from this nationally representative sample (NT = 8114, aged 16-91 years) were interviewed on four occasions between years 2000 and 2007 to investigate changes in cigarette smoking behavior. Logistic regression models with random effects compensated for within-individual behavior over time. Temporal pathways were investigated by lagging independent variables (t - 1) in relation to our cigarette-use outcome at time (t). RESULTS: Active social participation at (t - 1) was positively associated with smoking cessation at (t) (odds ratio [OR] = 1.39; 95% confidence interval [CI] [1.07-1.82]). Separating from one's spouse at (t - 1) increased risk for smoking relapse/initiation at (t) (OR = 6.63; 95% CI [1.70-28.89]). Conversely, being married protected against smoking cigarettes (OR = 1.87; 95% CI [1.15-3.04]). These associations held in our robustness checks. CONCLUSIONS: Initial marital breakdown predicted a high risk of smoking relapse/initiation. The timing of this life event provides a critical window where adverse smoking behavior might occur. Conversely, the positive effects of active social participation on cigarette cessation remained consistent, its absence further predicting smoking relapse/initiation. Robustness of results confirms the important role that active participation has on cigarette smoking behavior. Group smoking cessation interventions could harness participatory elements to better achieve their goals. IMPLICATIONS: By investigating temporal relationships between well-known smoking determinants and cigarette smoking outcomes, we identified that being "separated" (not "divorced") at time (t) predicted a higher risk of smoking relapse/initiation at (t). Tailored health messages could be employed to highlight the increased risk of cigarette smoking relapse/initiation during this stressful life event. Conversely, active social participation (a common social capital proxy) consistently predicted smoking cessation over time. Future group smoking cessation interventions could be designed explicitly to harness participatory elements to better achieve their goals.

Unexpected adverse childhood experiences and subsequent drug use disorder: a Swedish population study (1995-2011).

AIMS: Exposure to extraordinary traumatic experience is one acknowledged risk factor for drug use. We aim to analyse the influence of potentially life-changing childhood stressors, experienced second-hand, on later drug use disorder in a national population of Swedish adolescent and young adults (aged 15-26 years). DESIGN: We performed Cox proportional hazard regression analyses, complemented with co-relative pair comparisons. SETTING: Sweden. PARTICIPANTS: All individuals in the Swedish population born 1984-95, who were registered in Sweden at the end of the calendar year that they turned 14 years of age. Our follow-up time (mean 6.2 years; range 11 years) started at the year they turned 15 and continued to December 2011 (n = 1,409,218). MEASUREMENTS: Our outcome variable was drug use disorder, identified from medical, legal and pharmacy registry records. Childhood stressors, as per DSM-IV stressor criteria, include death of an immediate family member and second-hand experience of diagnoses of malignant cancer, serious accidental injury and victim of assault. Other covariates include parental divorce, familial psychological wellbeing and familial drug and alcohol use disorders. FINDINGS: After adjustment for all considered confounders, individuals exposed to childhood stressors 'parental death' or 'parental assault' had more than twice the risk of drug use disorder than those who were not [hazard ratio (HR) = 2.63 (2.23-3.09) and 2.39 (2.06-2.79), respectively]. CONCLUSIONS: Children aged under 15 years who experience second-hand an extraordinary traumatic event (such as a parent or sibling being assaulted, diagnosed with cancer or dying) appear to have approximately twice the risk of developing a drug use disorder than those who do not.

The impact of social capital on changes in smoking behaviour: a longitudinal cohort study.

BACKGROUND: Smoking prevalence across high-income countries such as the United Kingdom has significantly decreased over the past few decades; this decrease, however, has not occurred uniformly across social strata. The highest concentrations of smokers are currently found in lower-income groups. Lack of access to material resources and differing social norms have been cited as possible causes of this imbalance in smoking behaviour. Social capital, measured by trust and levels of community participation, has also been postulated to influence health behaviour. METHODS: Data from the British Household Panel Survey were used to identify smoking and non-smoking cohorts at baseline (N = 10,512); from these, individuals whose smoking behaviour had changed (the dependent variable) were identified. Measures of social capital, income, employment and marital status, and considered confounders were tested for associations with changes in smoking behaviour over a 2-year period. Both bivariate and multivariate models were utilized to elicit associations. RESULTS: Only marital and employment status, along with social capital measures, remained significantly associated with changes in smoking behaviour. Individual/household income, baseline social class and general/psychological health failed to demonstrate any significant association with changes in smoking status. CONCLUSION: Support mechanisms (via marriage and employment) and elements social capital (measured by 'trust' and 'social participation') are independently and positively associated with smoking cessation; continual lack of active social participation and remaining single are associated with smoking initiation. Smoking interventions should consider increased participation as an intrinsic part of their design.

The impact of changes in different aspects of social capital and material conditions on self-rated health over time: a longitudinal cohort study.

Individual aspects of social capital have been shown to have significant associations with health outcomes. However, research has seldom tested different elements of social capital simultaneously, whilst also adjusting for other well-known health determinants over time. This longitudinal individual-level study investigates how temporal changes in social capital, together with changes in material conditions and other health determinants affect associations with self-rated health over a six year period. We use data from the British Household Panel Survey, a randomly selected cohort which is considered representative of the United Kingdom's population, with the same individuals (N=9303) providing responses to identical questions in 1999 and 2005. Four measures of social capital were used: interpersonal trust, social participation, civic participation and informal social networks. Material conditions were measured by total income (both individual and weighted household income), net of taxation. Other health determinants included age, gender, smoking, marital status and social class. After the baseline sample was stratified by health status, associations were examined between changes in health status and changes in all other considered variables. Simultaneous adjustment revealed that inability to trust demonstrated a significant association with deteriorating self-rated health, whereas increased levels of social participation were significantly associated with improved health status over time. Low levels of household and individual income also demonstrated significant associations with deteriorating self-rated health. In conclusion, it seems that interpersonal trust and social participation, considered valid indicators of social capital, appear to be independent predictors of self-rated health, even after adjusting for other well-known health determinants. Understandably, how trust and social participation influence health outcomes may help resolve the debate surrounding the role of social capital within the field of public health.