Supplement_r_(1) – Supplemental material for A network approach to the analysis of psychosocial risk factors and their association with health

<p>Supplemental material, Supplement_r_(1) for A network approach to the analysis of psychosocial risk factors and their association with health by Marko Elovainio, Christian Hakulinen, Laura Pulkki-Råback, Markus Juonala and Olli T Raitakari in Journal of Health Psychology</p

Vascular ultrasound measures before pregnancy and pregnancy complications: A prospective cohort study

<p><i>Objectives</i>: To examine the relationship between pre-pregnancy indicators of cardiovascular risk and pregnancy complications and outcomes. <i>Study design</i>: Data from 359 female participants in the Cardiovascular Risk in Young Finns Study were linked with the national birth registry. Flow-mediated dilatation (FMD; maximum change in the left brachial artery diameter after rest and hyperemia); carotid intima-media thickness (IMT); Young’s elastic modulus (YEM); and carotid artery distensibility (Cdist) at the visit prior to the pregnancy were examined as predictors of hypertensive disorders, birthweight, and gestational age using multivariable linear regression with adjustment for confounders (age, BMI, smoking, and socioeconomic status). <i>Results</i>: No relations were seen between FMD, IMT, or the stiffness indices, and hypertensive disorders. Higher pre-pregnancy FMD was associated with lower gestational age, while increased Cdist was associated with reduced birthweight-for-gestational-age. <i>Conclusions</i>: Some cardiovascular ultrasound measures of pre-pregnancy may predict pregnancy complications, but the association is likely to be small.</p

El Diario de Pontevedra : periódico liberal: Ano XXIV Número 7068 - 1907 novembro 9

Results of mixed models with age as a categorical predictor and log-insulin as a continuous predictor: LS means contrasts (No adult T2DM vs. adult T2DM) and significance at each age averaged over- (Table S1.) or adjusted for the levels of sex (Table S2.) and pairwise comparisons of Least-square means of BMI and 95% CIs at each age in each T2DM status group averaged over levels of sex (Figure S1.) at each age in each T2DM status group and sex group combination (M = males, F-females, 1 = No adult T2DM, 2 = adult T2DM) (Figure S2.) and adjusted for log(insulin). (DOCX 549 kb

DataSheet_1_Identification of gene networks jointly associated with depressive symptoms and cardiovascular health metrics using whole blood transcriptome in the Young Finns Study.pdf

BackgroundStudies have shown that cardiovascular health (CVH) is related to depression. We aimed to identify gene networks jointly associated with depressive symptoms and cardiovascular health metrics using the whole blood transcriptome.Materials and methodsWe analyzed human blood transcriptomic data to identify gene co-expression networks, termed gene modules, shared by Beck’s depression inventory (BDI-II) scores and cardiovascular health (CVH) metrics as markers of depression and cardiovascular health, respectively. The BDI-II scores were derived from Beck’s Depression Inventory, a 21-item self-report inventory that measures the characteristics and symptoms of depression. CVH metrics were defined according to the American Heart Association criteria using seven indices: smoking, diet, physical activity, body mass index (BMI), blood pressure, total cholesterol, and fasting glucose. Joint association of the modules, identified with weighted co-expression analysis, as well as the member genes of the modules with the markers of depression and CVH were tested with multivariate analysis of variance (MANOVA).ResultsWe identified a gene module with 256 genes that were significantly correlated with both the BDI-II score and CVH metrics. Based on the MANOVA test results adjusted for age and sex, the module was associated with both depression and CVH markers. The three most significant member genes in the module were YOD1, RBX1, and LEPR. Genes in the module were enriched with biological pathways involved in brain diseases such as Alzheimer’s, Parkinson’s, and Huntington’s.ConclusionsThe identified gene module and its members can provide new joint biomarkers for depression and CVH.</p

Table_1_Identification of gene networks jointly associated with depressive symptoms and cardiovascular health metrics using whole blood transcriptome in the Young Finns Study.xlsx

BackgroundStudies have shown that cardiovascular health (CVH) is related to depression. We aimed to identify gene networks jointly associated with depressive symptoms and cardiovascular health metrics using the whole blood transcriptome.Materials and methodsWe analyzed human blood transcriptomic data to identify gene co-expression networks, termed gene modules, shared by Beck’s depression inventory (BDI-II) scores and cardiovascular health (CVH) metrics as markers of depression and cardiovascular health, respectively. The BDI-II scores were derived from Beck’s Depression Inventory, a 21-item self-report inventory that measures the characteristics and symptoms of depression. CVH metrics were defined according to the American Heart Association criteria using seven indices: smoking, diet, physical activity, body mass index (BMI), blood pressure, total cholesterol, and fasting glucose. Joint association of the modules, identified with weighted co-expression analysis, as well as the member genes of the modules with the markers of depression and CVH were tested with multivariate analysis of variance (MANOVA).ResultsWe identified a gene module with 256 genes that were significantly correlated with both the BDI-II score and CVH metrics. Based on the MANOVA test results adjusted for age and sex, the module was associated with both depression and CVH markers. The three most significant member genes in the module were YOD1, RBX1, and LEPR. Genes in the module were enriched with biological pathways involved in brain diseases such as Alzheimer’s, Parkinson’s, and Huntington’s.ConclusionsThe identified gene module and its members can provide new joint biomarkers for depression and CVH.</p

Factors associated with six-year weight change in young and middle-aged adults in the Young Finns Study

<div><p></p><p><b><i>Objective.</i></b> To examine factors associated with weight change and obesity risk in young and middle-aged adults. <b><i>Subjects/methods.</i></b> The Young Finns Study with its 923 women and 792 men aged 24–39 years at baseline were followed for six years. Variables associated with the weight change were investigated with regression models. <b><i>Results.</i></b> The average weight change was 0.45 kg/year in women and 0.58 kg/year in men. In women, weight change was steady across all ages. In men, weight changes were more pronounced in younger age groups. In women (weight gain > 2 kg, <i>n</i> = 490), medication for anxiety, low occupational status, high baseline BMI (body mass index), high intake of sweet beverages, high childhood BMI, high salt (NaCl and/or KCl) use, low number of children, low childhood family income, high stature and low level of dependence (a temperament subscale) were associated with increased weight gain (in the order of importance). In men (weight gain > 2 kg, <i>n</i> = 455), high stature, high intake of french fries, low intake of sweet cookies, young age, recent divorce, low intake of cereals, high intake of milk, depressive symptoms, rural childhood origin, high baseline BMI and unemployment were associated with more pronounced weight gain. Sedentarity (screen-time) was associated with weight gain only in young men. Physical activity and genetic risk for high BMI (score of 31 known variants) were not consistently associated with weight change. <b><i>Conclusions.</i></b> Socio-economic factors, temperamental and physical characteristics, and some dietary factors are related with weight change in young/middle-aged adults. The weight change occurring in adulthood is also determined by childhood factors, such as high BMI and low family income.</p></div

Scatterplot of serum lipoprotein longitudinal profiles of participants according to their sex and wGRSs status (High and Low wGRS*) (N = 2435, N = 2308 and N = 2435 for LDL-C-, HDL-C- and triglyceride profiles respectively).

<p>Solid and dotted lines represent estimated sex-specific average age-related lipid trajectories for participants in High and Low genetic risk score, respectively (i.e. prototypical growth curves); grey bands around the growth curves represent approximated 95% prediction CI. Overlaid with the prototypical lipid trajectories are the age-specific cut points for lipoprotein status (normal vs. high risk) as defined by the NCEP adolescent and childhood classification [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146081#pone.0146081.ref036" target="_blank">36</a>] and NCEP adult-treatment panel guidelines [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146081#pone.0146081.ref037" target="_blank">37</a>]). The cut points are represented in grey/white blocks, used to identify those at significantly increased risk of developing atherosclerotic CVD in adulthood. * Mid wGRS risk group are not presented on the figure for the purpose of readability.</p

Age- and sex- stratified estimated effects of LDL-C wGRS (upper panel), HDL-C wGRS (middle panel) and TG wGRS (lower panel) on LDL-C, HDL-C and triglycerides levels respectively with color coded significance levels and studentized bootstrapped non-parametric 95% CI.

<p>For each age, the continuous error bars correspond to males and the dashed error bars directly next to them correspond to female models. Effect sizes are in mmol/L change per 1-sd change in wGRS for LDL-C and HDL-C and in odds ratio lipoprotein level change per 1-sd change in wGRS for triglycerides. Point sizes of the beta estimates reflect sample size (number of participants included in each age- and sex-specific regression analysis) Parameter estimates significance: Lightgrey, 0.05-3-6; Black, p-val≤1.X10^-6. Black lines: smooth trend curves fitted by LOESS (Locally weighted non-parametric regression) to help visualise trends in the cross-sectional associations.</p

Sex-specific marginal effect* and 95% CI of (A) combined continuous HDL-C wGRS on HDL-C levels (effect size expressed in mmol/L lipoprotein level change per 1-sd change in wGRSs); and (B) combined continuous TG wGRS on fasting triglyceride levels (effect size expressed in odds ratio lipoprotein level change per 1-sd change in wGRSs).

<p>Colour code: dark grey; females, light grey; males. (*Plotted marginal effect includes the significant linear slope, quadratic and quartic rates of change (cubic trajectory parameter not significant in the final model); Horizontal black dashed line shows where the slopes are not significantly different from zero).</p

Evidence for Protein Leverage in Children and Adolescents with Obesity

Objective: The aim of this study was to test the protein leverage hypothesis in a cohort of youth with obesity. Methods: A retrospective study was conducted in a cohort of youth with obesity attending a tertiary weight management service. Validated food questionnaires revealed total energy intake (TEI) and percentage of energy intake from carbohydrates (ì), fats (ï), and proteins (%EP). Individuals with a Goldberg cutoff ≥ 1.2 of the ratio of reported TEI to basal metabolic rate from fat-free mass were included. A subgroup had accelerometer data. Statistics included modeling of percentage of energy from macronutrients and TEI, compositional data analysis to predict TEI from macronutrient ratios, and mixture models for sensitivity testing. Results: A total of 137 of 203 participants were included (mean [SD] age 11.3 [2.7] years, 68 females, BMI z score 2.47 [0.27]). Mean TEI was 10,330 (2,728) kJ, mean ì was 50.6% (6.1%), mean ï was 31.6% (4.9%), and mean %EP was 18.4% (3.1%). The relationship between %EP and TEI followed a power function (L coefficient −0.48; P < 0.001). TEI was inversely associated with increasing %EP. In the subgroup with < 60 min/d of moderate to vigorous physical activity (n = 48), lower BMI z scores were associated with higher %EP and moderate ì. Conclusions: In youth with obesity, protein dilution by either carbohydrates or fats increases TEI. Assessment of dietary protein may be useful to assist in reducing TEI and BMI in youth with obesity