Genetic Predisposition Score Research Articles

Puberty Status Modifies the Effects of Genetic Variants, Lifestyle Factors and Their Interactions on Adiponectin: The BCAMS Study.

BackgroundHypoadiponectinemia has been associated with various cardiometabolic disease states. Previous studies in adults have shown that adiponectin levels were regulated by specific genetic and behavioral or lifestyle factors. However, little is known about the influence of these factors on adiponectin levels in children, particularly as mitigated by pubertal development.MethodsWe performed a cross-sectional analysis of data from 3,402 children aged 6-18 years from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study. Pubertal progress was classified as prepubertal, midpuberty, and postpuberty. Six relevant single nucleotide polymorphisms (SNPs) were selected from previous genome-wide association studies of adiponectin in East Asians. Individual SNPs and two weighted genetic predisposition scores, as well as their interactions with 14 lifestyle factors, were analyzed to investigate their influence on adiponectin levels across puberty. The effect of these factors on adiponectin was analyzed using general linear models adjusted for age, sex, and BMI.ResultsAfter adjustment for age, sex, and BMI, the associations between adiponectin levels and diet items, and diet score were significant at prepuberty or postpuberty, while the effect of exercise on adiponectin levels was more prominent at mid- and postpuberty. Walking to school was found to be associated with increased adiponectin levels throughout puberty. Meanwhile, the effect of WDR11-FGFR2-rs3943077 was stronger at midpuberty (P = 0.002), and ADIPOQ-rs6773957 was more effective at postpuberty (P = 0.005), while CDH13-rs4783244 showed the strongest association with adiponectin levels at all pubertal stages (all P < 3.24 × 10-15). We further found that effects of diet score (P interaction = 0.022) and exercise (P interaction = 0.049) were stronger in children with higher genetic risk of hypoadiponectinemia, while higher diet score and exercise frequency attenuated the differences in adiponectin levels among children with different genetic risks.ConclusionsOur study confirmed puberty modulates the associations between adiponectin, and genetic variants, lifestyle factors, and gene-by-lifestyle interactions. These findings provide new insight into puberty-specific lifestyle suggestions, especially in genetically susceptible individuals.

Association between Single Nucleotide Polymorphisms and Weight Reduction in Behavioural Interventions-A Pooled Analysis.

Knowledge of the association between single nucleotide polymorphisms (SNPs) and weight loss is limited. The aim was to analyse whether selected obesity-associated SNPs within the fat mass and obesity-associated (FTO), transmembrane protein 18 (TMEM18), melanocortin-4 receptor (MC4R), SEC16 homolog B (SEC16B), and brain-derived neurotrophic factor (BDNF) gene are associated with anthropometric changes during behavioural intervention for weight loss. genetic and anthropometric data from 576 individuals with overweight and obesity from four lifestyle interventions were obtained. A genetic predisposition score (GPS) was calculated. Our results show that study participants had a mean age of 48.2 ± 12.6 years and a mean baseline body mass index of 33.9 ± 6.4 kg/m2. Mean weight reduction after 12 months was −7.7 ± 10.9 kg. After 12 months of intervention, the MC4R SNPs rs571312 and rs17782313 were significantly associated with a greater decrease in body weight and BMI (p = 0.012, p = 0.011, respectively). The investigated SNPs within the other four genetic loci showed no statistically significant association with changes in anthropometric parameters. The GPS showed no statistically significant association with weight reduction. In conclusion there was no consistent evidence for statistically significant associations of SNPs with anthropometric changes during a behavioural intervention. It seems that other factors play a more significant in weight management than the investigated SNPs.

Associations of combined genetic and epigenetic scores with muscle size and muscle strength: a pilot study in older women.

BackgroundInter‐individual variance in skeletal muscle is closely related to genetic architecture and epigenetic regulation. Studies have examined genetic and epigenetic relationships with characteristics of ageing muscle separately, while no study has combined both genetic and epigenetic profiles in ageing muscle research. The aim of this study was to evaluate the association between combined genetic and methylation scores and skeletal muscle phenotypes in older women.MethodsForty‐eight older Caucasian women (aged 65–79 years) were included in this study. Biceps brachii thickness and vastus lateralis anatomical cross‐sectional area (ACSAVL) were measured by ultrasonography. Maximum isometric elbow flexion (MVCEF) and knee extension (MVCKE) torques were measured by a customized dynamometer. The muscle‐driven genetic predisposition score (GPSSNP) was calculated based on seven muscle‐related single nucleotide polymorphisms (SNPs). DNA methylation levels of whole blood samples were analysed using Infinium MethylationEPIC BeadChip arrays. The DNA methylation score was calculated as a weighted sum of methylation levels of sarcopenia‐driven CpG sites (MSSAR) or an overall gene‐wise methylation score (MSSNP, the mean methylation level of CpG sites located in muscle‐related genes). Linear regression models were built to study genetic and epigenetic associations with muscle size and strength. Three models were built with both genetic and methylation scores: (1) MSSAR + GPSSNP, (2) MSSNP + GPSSNP, and (3) gene‐wise combined scores which were calculated as the ratio of the SNP score to the mean methylation level of promoters in the corresponding gene. Additional models with only a genetic or methylation score were also built. All models were adjusted for age and BMI.ResultsMSSAR was negatively associated with ACSAVL, MVCEF, and MVCKE and explained 10.1%, 35.5%, and 40.1% of the variance, respectively. MSSAR explained more variance in these muscular phenotypes than GPSSNP, MSSNP, and models including both genetic and methylation scores. MSSNP and GPSSNP accounted for less than 8% and 5% of the variance in all muscular phenotypes, respectively. The genotype and methylation level of CNTF was positively related to MVCKE (P = 0.03) and explained 12.2% of the variance. The adjusted R 2 and Akaike information criterion showed that models with only a MSSAR performed the best in explaining inter‐individual variance in muscular phenotypes.ConclusionsOur results improve the understanding of inter‐individual variance in muscular characteristics of older women and suggest a possible application of a sarcopenia‐driven methylation score to muscle strength estimation in older women while the combination with a genetic score still needs to be further studied.

The Genetic Effect on Muscular Changes in an Older Population: A Follow-Up Study after One-Year Cessation of Structured Training.

Older adults lose muscle mass and strength at different speeds after the cessation of physical exercise, which might be genotype related. This study aimed to explore the genetic association with changes in muscle mass and strength one year after the cessation of structured training in an older population. Participants (n = 113, aged between 61 and 81 years) who performed one-year of combined fitness (n = 44) or whole-body vibration (n = 69) training were assessed one year after the cessation of the training. Whole-body skeletal muscle mass and knee strength were measured. Data-driven genetic predisposition scores (GPSs) were calculated and analysed in a general linear model with sex, age, body mass index and post-training values of skeletal muscle mass or muscle strength as covariates. Forty-six single nucleotide polymorphisms (SNPs) from an initial 170 muscle-related SNPs were identified as being significantly linked to muscular changes after cessation. Data-driven GPSs and over time muscular changes were significantly related (p < 0.01). Participants with higher GPSs had less muscular declines during the cessation period while data-driven GPSs accounted for 26–37% of the phenotypic variances. Our findings indicate that the loss of training benefits in older adults is partially genotype related.

Childhood sleep duration modifies the polygenic risk for obesity in youth through leptin pathway: the Beijing Child and Adolescent Metabolic Syndrome cohort study

Background/objectivesShort sleep is an obesity risk factor, however, little is known about its interplay with genetic predisposition and pathways involved in obesity pathogenesis, especially in the longitudinal setting. We aimed to investigate a possible sleep-gene interaction for childhood obesity risk, and whether the interaction in childhood longitudinally contributes to obesity risk at a 10-year follow-up and further to test if there is any mediation through the leptin pathway.Subjects/methodsA total of 3211 children from China (6–18 years) at baseline and 848 participants at 10-year follow-up from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) cohort study were analyzed. Baseline leptin concentrations and 12 established adult body mass index (BMI) loci were examined for the associations with habitual sleep duration.ResultsAfter adjusting for covariates, including pubertal stages and behavioral factors, short sleep duration at baseline was significantly associated with increased overweight/obesity risk at both baseline and follow-up. Genetic predisposition scores (GPS), particularly consisting of leptin-related SNPs (GPSleptin), were robustly associated with baseline overweight/obesity in children who slept ≤8 h/day (P < 0.001), whereas the association was ablated in those who slept ≥10 h/day (P > 0.05). Comparable observations were made at follow-up. Mediation analysis revealed a modest direct effect of the GPSleptin-sleep interaction on BMI at baseline, while a significant indirect effect of this interaction was found to be mediated principally through elevated leptin (proportion: 52.6%); moreover, the mediation effect via leptin remained stable over 10 years.ConclusionsThis study suggests that shorter sleep duration in children from China (< 8h/day), compared to longer sleep duration (≥10 h/day), has a long-term impact on the association of polygenic risk for obesity from childhood to young adulthood and leptin pathway explains a key mechanism via a modification effect. Therefore, adequate sleep duration during childhood is important for the early prevention of obesity, especially if there is a genetic predisposition to this trait.

Development of a Genetic Score to Predict an Increase in HDL Cholesterol Concentration After a Dietary Intervention in Adults with Metabolic Syndrome

Dietary intervention (DI) is a primary strategy to attenuate some of the metabolic abnormalities associated with metabolic syndrome (MetS), including low HDL cholesterol. There is no biomarker that can identify individuals who respond to DI by increasing HDL cholesterol. The aim of this study was to assess the predictive power of a genetic predisposition score (GPS) in Mexican adults with MetS to identify HDL cholesterol responders to DI. This study followed a prospective cohort design. Sixty-seven Mexican adults aged 20-60 y (21% men) with BMI ≥25 and ≤39.9 kg/m², who had at least 3 of 5 positive criteria for MetS, were included. Participants consumed a low saturated fat diet for 2.5 mo (<7% energy as saturated fat, <200 mg of cholesterol/d) and reduced their usual diet by ∼440 kcal/d, a reduction in total energy intake of about 25%. Anthropometry and serum biochemical markers, including HDL cholesterol, were measured before and after DI. A multilocus GPS was constructed using previously reported genetic variants associated with response to diet in subjects with MetS. GPS values, designed to predict the response of HDL cholesterol to the DI, were computed for each individual as the sum of the number of effect alleles across 14 SNPs. Individuals were dichotomized as high and low GPS according to median GPS (-2.12) and we observed a difference in HDL cholesterol changes on DI of +3 mg/dL (6.3%) in subjects with low GPS, whereas those with high GPS had HDL cholesterol decreases of -3 mg/dL (-7.9%) (P=0.04). Individuals with low GPS showed greater increases in their HDL cholesterol than those with high GPS. Therefore, the GPS can be useful for predicting the HDL cholesterol response to diet.

Metabolic fitness in relation to genetic variation and leukocyte DNA methylation.

Metabolic syndrome (MetS) is a highly prevalent condition causing increased risk of several life-threatening diseases. MetS has a pronounced hereditary basis but is also influenced by environmental factors, partly through epigenetic mechanisms. In this study, the five phenotypes underlying MetS were incorporated into a continuous score for metabolic fitness (MF), and associations with both genotypic variation and leukocyte DNA methylation were investigated. Baseline MF phenotypes (waist circumference, blood pressure, blood glucose, serum triglycerides, and high-density lipoproteins) of 710 healthy Flemish adults were measured. After a 10 yr period, follow-up measures were derived from 618 of these subjects. Genotyping was performed for 65 preselected MF-related genetic variants. Next, full genetic predisposition scores (GPSs) were calculated, combining genotype scores of multiple genetic variants. Additionally, stepwise GPSs were constructed, including only the most predictive genetic variants for the different MF phenotypes. For a subset of 68 middle-aged men, global and gene-specific DNA methylation was investigated, and a biological pathway analysis was performed. The full GPSs were predictive for some baseline MF phenotypes, but not for changes over time. Only a limited number of genetic variants were significantly predictive individually. On the contrary, global and gene-specific DNA methylation was associated with changes in the MF phenotypes rather than with the baseline measures, indicating that effects of DNA methylation on MF are somewhat delayed. Furthermore, several biological pathways were associated with the MF phenotypes through gene promoter methylation. For CETP, G6PC2, MC4R, and TFAP2B both a genetic and epigenetic relationship was found with MF.

Improving adherence to healthy dietary patterns, genetic risk, and long term weight gain: gene-diet interaction analysis in two prospective cohort studies

Abstract Objective To investigate whether improving adherence to healthy dietary patterns interacts with the genetic predisposition to obesity in relation to long term changes in body mass index and body weight. Design Prospective cohort study. Setting Health professionals in the United States. Participants 8828 women from the Nurses’ Health Study and 5218 men from the Health Professionals Follow-up Study. Exposure Genetic predisposition score was calculated on the basis of 77 variants associated with body mass index. Dietary patterns were assessed by the Alternate Healthy Eating Index 2010 (AHEI-2010), Dietary Approach to Stop Hypertension (DASH), and Alternate Mediterranean Diet (AMED). Main outcome measures Five repeated measurements of four year changes in body mass index and body weight over follow-up (1986 to 2006). Results During a 20 year follow-up, genetic association with change in body mass index was significantly attenuated with increasing adherence to the AHEI-2010 in the Nurses’ Health Study (P=0.001 for interaction) and Health Professionals Follow-up Study (P=0.005 for interaction). In the combined cohorts, four year changes in body mass index per 10 risk allele increment were 0.07 (SE 0.02) among participants with decreased AHEI-2010 score and −0.01 (0.02) among those with increased AHEI-2010 score, corresponding to 0.16 (0.05) kg versus −0.02 (0.05) kg weight change every four years (P Conclusions These data indicate that improving adherence to healthy dietary patterns could attenuate the genetic association with weight gain. Moreover, the beneficial effect of improved diet quality on weight management was particularly pronounced in people at high genetic risk for obesity.

Genetic predisposition score predicts the increases of knee strength and muscle mass after one-year exercise in healthy elderly.

This study aims to identify a genetic predisposition score from a set of candidate gene variants that predicts the response to a one-year exercise intervention. 200 participants (aged 60-83 years) were randomly assigned to a fitness (FIT), whole-body vibration (WBV) and control group. Participants in the exercise (FIT and WBV) groups performed a one-year intervention program. Whole-body skeletal muscle mass (SMM) and isometric knee extension strength (PTIM60) were measured before and after the intervention. A set of 170 muscle-related single nucleotide polymorphisms (SNPs) were genotyped. Stepwise regression analysis was applied to select significantly contributing SNPs for baseline and relative change parameters. A data-driven genetic predisposition score (GPS) was calculated by adding up predisposing alleles for each of the phenotypes. GPS was calculated based on 4 to 8 SNPs which were significantly related to the corresponding phenotypes. These SNPs belong to genes that are involved in myoblast differentiation, muscle and bone growth, myofiber contraction, cytokines and DNA methylation. GPS was related to baseline PTIM60 and relative changes of SMM and PTIM60 in the exercise groups, explaining the variance of the corresponding parameter by 3.2%, 14% and 27%, respectively. Adding one increasing allele in the GPS increased baseline PTIM60 by 4.73 Nm, and exercise-induced relative changes of SMM and PTIM60 by 1.78% and 3.86% respectively. The identified genetic predisposition scores were positively related to baseline knee extension strength and muscle adaptations to exercise in healthy elderly. These findings provide supportive genetic explanations for high and low responders in exercise-induced muscle adaptations.

Childhood Habitual Sleep Duration Modifies the Polygenic Risk for Obesity through Leptin Pathway—A Longitudinal Study

Sleep disruption is known to be an obesity risk factor, however, little is known about its interplay with genetic predisposition and pathways involved in obesity pathogenesis, especially in the longitudinal setting. Leveraging a large cohort from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study, we aimed to examine a possible sleep-gene interaction for childhood obesity risk, including longitudinal assessment in a 10-year follow-up and further test if there is any mediation through the leptin pathway. A total of 3,211 children (6-18 years) were recruited from this cohort study. Baseline leptin levels and twelve established adult BMI loci were examined for the associations with habitual sleep duration. After adjusting for pubertal stages, diet score and activity, short sleep duration at baseline was significantly associated with increased overweight/obesity risk at both baseline and follow-up. Genetic predisposition scores, particularly consisting of the central nervous system (CNS) gene variation (GPSCNS), were robustly correlated with baseline overweight/obesity in children who slept ≤8h/day (P&amp;lt;0.001), whereas the association was ablated in those who slept ≥10h/day (P&amp;gt;0.05). Comparable observations were made at follow-up. Mediation analysis revealed a modest direct effect of the GPSCNS-sleep interaction on BMI at baseline, while an indirect effect of this interaction was found to be mediated principally through elevated leptin (52.6%); moreover, the mediation effect via leptin remained stable over 10 years. This study provides longitudinal evidence that short sleep duration in children has a long-term impact on the association of polygenic risk for obesity from childhood to young adulthood and leptin pathway explains a key mechanism via a modification effect. Therefore, adequate sleep duration during childhood is important for the early prevention of obesity, especially if there is a genetic predisposition to this trait. Disclosure M. Li: None. J. Fu: None. L. Han: None. G. Li: None. S. Gao: None. S.F. Grant: None.

Alcohol consumption and its interaction with adiposity-associated genetic variants in relation to subsequent changes in waist circumference and body weight

BackgroundStudies have suggested a link between alcohol intake and adiposity. However, results from longitudinal studies have been inconsistent, and a possible interaction with genetic predisposition to adiposity measures has often not been taken into account.ObjectiveTo examine the association between alcohol intake recorded at baseline and subsequent annual changes in body weight (∆BW), waist circumference (ΔWC) and WC adjusted for BMI (ΔWCBMI), and to test for interaction with genetic predisposition scores based on single nucleotide polymorphisms (SNPs) associated with various forms of adiposity.MethodThis study included a total of 7028 adult men and women from MONICA, the Diet, Cancer and Health cohort (DCH), and the Inter99 studies. We combined 50 adiposity-associated SNPs into four scores indicating genetic predisposition to BMI, WC, WHRBMI and all three traits combined. Linear regression was used to examine the association of alcohol intake (drinks of 12 g (g) alcohol/day) with ΔBW, ΔWC, and ΔWCBMI, and to examine possible interactions with SNP-scores. Results from the analyses of the individual cohorts were combined in meta-analyses.ResultsEach additional drink/day was associated with a ΔBW/year of −18.0 g (95% confidence interval (CI): −33.4, −2.6, P = 0.02) and a ΔWC of −0.3 mm/year (−0.5, −0.0, P = 0.03). In analyses of women only, alcohol intake was associated with a higher ΔWCBMI of 0.5 mm/year (0.2, 0.9, P = 0.002) per drink/day. Overall, we found no statistically significant interactions between the four SNP-scores and alcohol intake in relation to changes in adiposity measures. However in analyses of women separately, we found interaction between the complete score of all 50 SNPs and alcohol intake in relation to ΔBW (P for interaction = 0.03). No significant interaction was observed among the men.ConclusionAlcohol intake was associated with a decrease in BW and WC among men and women, and an increase in WCBMI among women only. We found no strong indication that these associations depend on a genetic predisposition to adiposity.Trial registrationRegistry: ClinicalTrials.gov Trial number: CT00289237, Registered: 19 September 2005 retrospectively registered.

Genome-wide association analysis identifies common variants influencing infant brain volumes

Genome-wide association studies (GWAS) of adolescents and adults are transforming our understanding of how genetic variants impact brain structure and psychiatric risk, but cannot address the reality that psychiatric disorders are unfolding developmental processes with origins in fetal life. To investigate how genetic variation impacts prenatal brain development, we conducted a GWAS of global brain tissue volumes in 561 infants. An intronic single-nucleotide polymorphism (SNP) in IGFBP7 (rs114518130) achieved genome-wide significance for gray matter volume (P=4.15 × 10−10). An intronic SNP in WWOX (rs10514437) neared genome-wide significance for white matter volume (P=1.56 × 10−8). Additional loci with small P-values included psychiatric GWAS associations and transcription factors expressed in developing brain. Genetic predisposition scores for schizophrenia and ASD, and the number of genes impacted by rare copy number variants (CNV burden) did not predict global brain tissue volumes. Integration of these results with large-scale neuroimaging GWAS in adolescents (PNC) and adults (ENIGMA2) suggests minimal overlap between common variants impacting brain volumes at different ages. Ultimately, by identifying genes contributing to adverse developmental phenotypes, it may be possible to adjust adverse trajectories, preventing or ameliorating psychiatric and developmental disorders.

Limited potential of genetic predisposition scores to predict muscle mass and strength performance in Flemish Caucasians between 19 and 73 years of age.

Since both muscle mass and strength performance are polygenic in nature, the current study compared four genetic predisposition scores (GPS) in their ability to predict these phenotypes. Data were gathered within the framework of the first-generation Flemish Policy Research Centre "Sport, Physical Activity and Health" (2002-2004). Results are based on muscle characteristics data of 565 Flemish Caucasians (19-73 yr, 365 men). Skeletal muscle mass was determined from bioelectrical impedance. The Biodex dynamometer was used to measure isometric (PTstatic120°) and isokinetic strength (PTdynamic60° and PTdynamic240°), ballistic movement speed (S20%), and muscular endurance (Work) of the knee extensors. Genotyping was done for 153 gene variants, selected on the basis of a literature search and the expression quantitative trait loci of selected genes. Four GPS were designed: a total GPS (based on the sum of all 153 variants, each favorable allele = score 1), a data-driven and weighted GPS [respectively, the sum of favorable alleles of those variants with significant b-coefficients in stepwise regression (GPSdd), and the sum of these variants weighted with their respective partial r2 (GPSw)], and an elastic net GPS (based on the variants that were selected by an elastic net regularization; GPSen). It was found that four different models for a GPS were able to significantly predict up to ~7% of the variance in strength performance. GPSen made the best prediction of SMM and Work. However, this was not the case for the remaining strength performance parameters, where best predictions were made by GPSdd and GPSw.

Interactions between genetic variants associated with adiposity traits and soft drinks in relation to longitudinal changes in body weight and waist circumference

Background: Intake of sugar-sweetened beverages is associated with obesity, and this association may be modified by a genetic predisposition to obesity.Objective: We examined the interactions between a molecular genetic predisposition to various aspects of obesity and the consumption of soft drinks, which are a major part of sugar-sweetened beverages, in relation to changes in adiposity measures.Design: A total of 4765 individuals were included in the study. On the basis of 50 obesity-associated single nucleotide polymorphisms that are associated with body mass index (BMI), waist circumference (WC), or the waist-to-hip ratio adjusted for BMI (WHRBMI), the following 4 genetic predisposition scores (GRSs) were constructed: a complete genetic predisposition score including all 50 single nucleotide polymorphisms (GRSComplete), a genetic predisposition score including BMI-associated single nucleotide polymorphisms (GRSBMI), a genetic predisposition score including waist circumference–associated single nucleotide polymorphisms (GRSWC), and a genetic predisposition score including the waist-to-hip ratio adjusted for BMI–associated single nucleotide polymorphisms (GRSWHR). Associations between soft drink intake and the annual change (Δ) in body weight (BW), WC, or waist circumference adjusted for BMI (WCBMI) and possible interactions with the GRSs were examined with the use of linear regression analyses and meta-analyses.Results: For each soft drink serving per day, soft drink consumption was significantly associated with a higher ΔBW of 0.07 kg/y (95% CI: 0.01, 0.13 kg/y; P = 0.020) but not with the ΔWC or ΔWCBMI. In analyses of the ΔBW, we showed an interaction only with the GRSWC (per risk allele for each soft drink serving per day: −0.06 kg/y; 95% CI: −0.10, −0.02 kg/y; P = 0.006). In analyses of the ΔWC, we showed interactions only with the GRSBMI and GRSComplete [per risk allele for each soft drink serving per day: 0.05 cm/y (95% CI: 0.02, 0.09 cm/y; P = 0.001) and 0.05 cm/y (95% CI: 0.02, 0.07 cm/y; P = 0.001), respectively]. Nearly identical results were observed in analyses of the ΔWCBMI.Conclusions: A genetic predisposition to a high WC may attenuate the association between soft drink intake and BW gain. A genetic predisposition to high BMI as well as a genetic predisposition to high BMI, WC, and WHRBMI combined may strengthen the association between soft drink intake and WC gain. However, the public health impact may be limited.

The Genetic Predisposition Score of Seven Obesity-Related Single Nucleotide Polymorphisms Is Associated with Better Metabolic Outcomes after Roux-en-Y Gastric Bypass

Background/Aims: Genetic variants associated with obesity have cumulative effects on obesity risk and related phenotypes. This study aimed to estimate the contribution of a genetic predisposition score (GPS) calculated from 7 obesity-related polymorphisms to the improvement of biochemical parameters 1 year after Roux-en-Y gastric bypass (RYGB). Methods: Obese patients (n = 150; aged 47.2 ± 10.5 years) were enrolled and weight, body mass index (BMI), and biochemical parameters (glycemia and lipid profile) were evaluated preoperatively and 1 year after RYGB. A GPS was calculated with the polymorphisms rs1801282 of PPARG2, rs4994 of ADRB3, rs1800592 of UCP1, rs659366 and rs669339 of UCP2, rs7121 of GNAS1, and rs5443 of GNB3. We observed that 66.3% of the patients has a GPS >5. Results: During the preoperative period, the GPS showed a significant association with weight (β = -0.163; p = 0.020), BMI (β = -0.169; p = 0.038), and glucose concentrations (β = -0.177; p = 0.036). After sex and age adjustment, a higher GPS was associated with a greater reduction in glycemia (β = -0.158; p = 0.048), triglycerides (β = -0.256; p = 0.002), and total cholesterol (β = -0.172; p = 0.038) concentrations 1 year after surgery. Conclusion: Our data elucidated that a higher GPS provides a greater metabolic benefit of RYGB.

Use of different genetic predisposition score techniques to predict muscle mass and muscle function over the adult life span in Flemish Caucasians

Since the Belgian elderly population is expanding at a very high rate, it is important for public health care systems to better understand ageing-related syndromes and diseases, such as sarcopenia. This condition is characterized by a progressive loss of skeletal muscle mass and its action generating capacity (also termed muscle function). Therefore it also implies risk of adverse outcomes like fall-related injury and impaired quality of life. Furthermore, it is well known that both muscle mass and muscle function are under strong genetic determination. However, most previous studies only considered individual associations of one specific gene variant with muscular phenotypes, whereas it is likely several related polymorphisms that combine to influence muscular characteristics. The data of the current study were assessed within the framework of the first (2002-2004) and third (2012-2015) generation Flemish Policy Research Centre Sport. A total of 579 healthy, Flemish Caucasian adults (19-73, 64.4% men) were measured during a follow-up period of ten years. Genomic DNA was extracted and 384 gene variants were genotyped. Force and velocity characteristics of the knee extensors were measured using the Biodex Medical System 3® dynamometer. Furthermore, four genetic predisposition score (GPS) models were designed: a total GPS (based on the sum of all variants, each favorable allele = score 1), a data-driven GPS (sum of favorable alleles of those variants with significant b-coefficients in stepwise regression), a weighted GPS (weighting is done based on the proportion of the variance explained by those variants with significant b-coefficients in stepwise regression) and an elastic-net GPS (sum of favorable alleles included by elastic-net regularization). Afterwards, these GPS models will be compared and used to predict genetic predisposition towards muscle mass and muscle function and its loss by ageing via linear regression analysis.

(Epi)genetic variation in ageing of metabolic fitness

Ageing-related diseases are an important cause of mortality. Although the susceptibility to these diseases is partially genetically determined, a person's physical activity level can influence the development of harmful alterations in the body through epigenetic pathways. Therefore, it is important to investigate both genetic and epigenetic aspects of ageing-related diseases. In this study, the focus lies on variables related to metabolic fitness: obesity, blood pressure, plasma glucose, serum triglycerides and high-density lipoproteins. In the genetic part, a Genetic Predisposition Score (GPS) is calculated for metabolic fitness. This GPS is based on 28 selected single nucleotide polymorphisms (SNPs) and 54 expression quantitative trait loci (eQTLs) related to the metabolic fitness variables. In this context, DNA from blood samples of 842 adults of all age categories, measured within the framework of the Flemish Policy Research Centre Sport, was genotyped using the Illumina GoldenGate Genotyping Assay. The aim of the GPS is to determine the role of sequence variation in the interindividual variation in ageing regarding the metabolic fitness variables. Also the physical activity level of the subjects, assessed using the Flemish Physical Activity Computerized Questionnaire (FPACQ), will be included as covariate. In the epigenetic part, about 70 men (born in 1954-1957), whose DNA is also genotyped, will be included in a longitudinal DNA methylation study. To determine the plasticity of DNA methylation over a 10-year period (2002-2012), the Illumina Infinium HumanMethylation450 BeadChip Assay will be used. The hypothesis regarding a first exploration is that less physically active people are subjected to more overall DNA demethylation during ageing, resulting in a stronger deterioration of metabolic fitness. By combining information about sequence variation, DNA methylation plasticity and physical (in)activity, new insights can be acquired about the influence of both genetic factors and an (in)active lifestyle on metabolic fitness.

Modelling the Interplay between Lifestyle Factors and Genetic Predisposition on Markers of Type 2 Diabetes Mellitus Risk.

The risk of developing type 2 diabetes mellitus (T2DM) is determined by a complex interplay involving lifestyle factors and genetic predisposition. Despite this, many studies do not consider the relative contributions of this complex array of factors to identify relationships which are important in progression or prevention of complex diseases. We aimed to describe the integrated effect of a number of lifestyle changes (weight, diet and physical activity) in the context of genetic susceptibility, on changes in glycaemic traits in overweight or obese participants following 12-months of a weight management programme. A sample of 353 participants from a behavioural weight management intervention were included in this study. A graphical Markov model was used to describe the impact of the intervention, by dividing the effects into various pathways comprising changes in proportion of dietary saturated fat, physical activity and weight loss, and a genetic predisposition score (T2DM-GPS), on changes in insulin sensitivity (HOMA-IR), insulin secretion (HOMA-B) and short and long term glycaemia (glucose and HbA1c). We demonstrated the use of graphical Markov modelling to identify the importance and interrelationships of a number of possible variables changed as a result of a lifestyle intervention, whilst considering fixed factors such as genetic predisposition, on changes in traits. Paths which led to weight loss and change in dietary saturated fat were important factors in the change of all glycaemic traits, whereas the T2DM-GPS only made a significant direct contribution to changes in HOMA-IR and plasma glucose after considering the effects of lifestyle factors. This analysis shows that modifiable factors relating to body weight, diet, and physical activity are more likely to impact on glycaemic traits than genetic predisposition during a behavioural intervention.

Applying data envelopment analysis to preventive medicine: a novel method for constructing a personalized risk model of obesity.

Data envelopment analysis (DEA) is a method of operations research that has not yet been applied in the field of obesity research. However, DEA might be used to evaluate individuals’ susceptibility to obesity, which could help establish effective risk models for the onset of obesity. Therefore, we conducted this study to evaluate the feasibility of applying DEA to predict obesity, by calculating efficiency scores and evaluating the usefulness of risk models. In this study, we evaluated data from the Takahata study, which was a population-based cohort study (with a follow-up study) of Japanese people who are >40 years old. For our analysis, we used the input-oriented Charnes-Cooper-Rhodes model of DEA, and defined the decision-making units (DMUs) as individual subjects. The inputs were defined as (1) exercise (measured as calories expended) and (2) the inverse of food intake (measured as calories ingested). The output was defined as the inverse of body mass index (BMI). Using the β coefficients for the participants’ single nucleotide polymorphisms, we then calculated their genetic predisposition score (GPS). Both efficiency scores and GPS were available for 1,620 participants from the baseline survey, and for 708 participants from the follow-up survey. To compare the strengths of the associations, we used models of multiple linear regressions. To evaluate the effects of genetic factors and efficiency score on body mass index (BMI), we used multiple linear regression analysis, with BMI as the dependent variable, GPS and efficiency scores as the explanatory variables, and several demographic controls, including age and sex. Our results indicated that all factors were statistically significant (p < 0.05), with an adjusted R2 value of 0.66. Therefore, it is possible to use DEA to predict environmentally driven obesity, and thus to establish a well-fitted model for risk of obesity.

An anatomy of the way composite scores work.

Recently, epidemiologists tend to focus on the association of health outcomes with combinations of exposures (composites), defined a-priori or a-posteriori. Such composites appear often in nutritional (dietary patterns) and genetic (genetic scores) epidemiology. The estimated associations, however, have not been linked to those of the components of the composite, at least in a systematic way. We considered composites (X) which are linear combinations of more than one exposures (components of the composite) and explored the association of X with a linear heath outcome (Y) in terms of the associations of its individual components with Y. We showed that: (1) the association of X with Y is a weighted average of the associations of the components of X with Y; (2) the weights depend on the estimated covariance matrix of the components, and on the scalar used for the linear combination, and; (3) when components are binary variables and X is a simple sum of its components, the weights depend solely on the proportion of "1"s that are present in each component and are common with the others. Using data from a cohort study in Greece we illustrated these properties for: (1) the a-priori Mediterranean diet score; (2) an a-priori genetic predisposition score, and; (3) an a-posteriori dietary pattern. Our findings may be important in interpreting estimated associations of composites with health outcomes, or, in designing composites that are expected to capture most of the associations of their components with health outcomes (new genetic scores, or composites of biomarkers).