Alaitz Poveda

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.

Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.

Quantitative genetics of human morphology and obesity-related phenotypes in nuclear families from the Greater Bilbao (Spain): Comparison with other populations

Background: It is well established that variation of soft-tissue traits is less influenced by the genetic component than skeletal traits. However, it is still unclear whether heritabilities (h2) of obesity-related phenotypes present a common pattern across populations. Aim: To estimate familial resemblance and heritability of body size, shape and composition phenotypes and to compare these results with those from other populations. Subjects and methods: The subject group consisted of 533 nuclear families living in Greater Bilbao and included 1702 individuals aged 2–61 years. Familial correlations and h2 were estimated for 29 anthropometric phenotypes (19 simple measures, three derived factors, four obesity indices and the three Heath-Carter somatotype components) using MAN and SOLAR programmes. Results: All phenotypes were influenced by additive genetic factors with narrow sense heritabilities ranging from 0.28–0.69. In general, skeletal traits exhibited the highest h2, whereas phenotypes defining the amount of adipose tissue, particularly central fat, were less determined by genetic factors. Conclusions: Familial correlations and heritability estimates of body morphology and composition from the Greater Bilbao sample were within the range observed in other studies. The lower heritability detected for central fat has also been found in some other populations, but further investigations in different populations using the same anthropometric traits and estimation methods are needed in order to obtain more robust conclusions.

Common variants in BDNF, FAIM2, FTO, MC4R, NEGR1, and SH2B1 show association with obesity-related variables in Spanish Roma population.

The objective of this study is to investigate the association between previously GWAS identified genetic variants predisposing to obesity in Europeans and obesity‐related phenotypes in Roma population.

Lifestyle and precision diabetes medicine: will genomics help optimise the prediction, prevention and treatment of type 2 diabetes through lifestyle therapy?

Precision diabetes medicine, the optimisation of therapy using patient-level biomarker data, has stimulated enormous interest throughout society as it provides hope of more effective, less costly and safer ways of preventing, treating, and perhaps even curing the disease. While precision diabetes medicine is often framed in the context of pharmacotherapy, using biomarkers to personalise lifestyle recommendations, intended to lower type 2 diabetes risk or to slow progression, is also conceivable. There are at least four ways in which this might work: (1) by helping to predict a person’s susceptibility to adverse lifestyle exposures; (2) by facilitating the stratification of type 2 diabetes into subclasses, some of which may be prevented or treated optimally with specific lifestyle interventions; (3) by aiding the discovery of prognostic biomarkers that help guide timing and intensity of lifestyle interventions; (4) by predicting treatment response. In this review we overview the rationale for precision diabetes medicine, specifically as it relates to lifestyle; we also scrutinise existing evidence, discuss the barriers germane to research in this field and consider how this work is likely to proceed.

Contribution of genetics and environment to craniofacial anthropometric phenotypes in Belgian nuclear families.

Abstract In this study we estimate relative genetic and environmental influences on head-related anthropometric phenotypes. The subject group consisted of 119 nuclear families living in Brussels, Belgium, and included 238 males and 236 females, ages 17 to 72 years. Two factor analyses with vari-max rotation (the first one related to facial measurements and the second one to overall head morphology) were used to analyze 14 craniofacial size traits. The resulting four synthetic traits [HFCF, VFCF, HDF1, and HDF2—horizontal (breadth) and vertical (height) facial factors and two head horizontal (breadth) factors, respectively] were used as summary variables. Maximum heritabilities (H2) were estimated for all studied traits, and variance components analysis was applied to determine the contribution of genetics and environment on the four craniofacial factors. In addition, we examined the covariations between the face (HFCF and VFCF) and head-related factors (HDF1 and HDF2), separately. Quantitative genetic analysis showed that HFCF, VFCF, HDF1, and HDF2 variation was appreciably attributable to additive genetic effects, with heritability (h2) estimates of 67.62%, 54.97%, 70.76%, and 65.05%, respectively. The three variance components reflecting a shared familial environment were nonsignificant for these four phenotypes. Bivariate analysis revealed significant additive and residual correlations for both pair of traits. The results confirm the existence of a significant genetic component determining the four craniofacial synthetic traits, and common genetic and environmental effects shared by the two face-related phenotypes and by the head-related ones.

Established BMI-associated genetic variants and their prospective associations with BMI and other cardiometabolic traits: the GLACIER Study

Background:Recent cross-sectional genome-wide scans have reported associations of 97 independent loci with body mass index (BMI). In 3541 middle-aged adult participants from the GLACIER Study, we tested whether these loci are associated with 10-year changes in BMI and other cardiometabolic traits (fasting and 2-h glucose, triglycerides, total cholesterol, and systolic and diastolic blood pressures).Methods:A BMI-specific genetic risk score (GRS) was calculated by summing the BMI-associated effect alleles at each locus. Trait-specific cardiometabolic GRSs comprised only the loci that show nominal association (P⩽0.10) with the respective trait in the original cross-sectional study. In longitudinal genetic association analyses, the second visit trait measure (assessed ~10 years after baseline) was used as the dependent variable and the models were adjusted for the baseline measure of the outcome trait, age, age2, fasting time (for glucose and lipid traits), sex, follow-up time and population substructure.Results:The BMI-specific GRS was associated with increased BMI at follow-up (β=0.014 kg m−2 per allele per 10-year follow-up, s.e.=0.006, P=0.019) as were three loci (PARK2 rs13191362, P=0.005; C6orf106 rs205262, P=0.043; and C9orf93 rs4740619, P=0.01). Although not withstanding Bonferroni correction, a handful of single-nucleotide polymorphisms was nominally associated with changes in blood pressure, glucose and lipid levels.Conclusions:Collectively, established BMI-associated loci convey modest but statistically significant time-dependent associations with long-term changes in BMI, suggesting a role for effect modification by factors that change with time in this population.

Gene-lifestyle and gene-pharmacotherpy interactions in obesity and its cardiovascular consequences

Obesity is a highly prevalent complex trait that raises the risk of other chronic diseases such as type 2 diabetes, certain cancers, sleep apnea, and cardiovascular disease, and shortens lifespan. Clinical intervention studies focused on weight loss and epidemiological studies of obesity indicate that genetic variation may modify the relationship between lifestyle behaviors and weight loss or weight gain. Similar observations have also emerged from pharmacogenetic studies. The literature includes several reports from these studies, but few examples of interactions have been adequately replicated. In this review we introduce the topics of population genetics and gene x environment interaction research. We also provide a systematic review of the published literature on gene x lifestyle (physical activity and dietary factors) and gene x drug interactions in relation to obesity. Finally, we overview the scope and findings from these studies and discuss some of their strengths and limitations.

Heritability and genetic correlations of obesity-related phenotypes among Roma people

Background: The Roma people are particularly vulnerable to developing obesity and related diseases, due to their social and ethnic backgrounds. However, little is known about the genetic and/or environmental factors affecting the variability of obesity-related traits among the Roma population. Aim: The aim of the present study was to estimate heritabilities and common genetic and environmental influences of obesity-related phenotypes in a sample of Roma people living in the Greater Bilbao region (Basque Country; Spain). Subjects and methods: Three hundred and seventy-two individuals from 50 large, extended and highly consanguineous pedigrees were phenotyped for anthropometric traits related to obesity. Heritability estimates were assessed for all quantitative traits and bivariate analyses were conducted to assess the phenotypic, genetic and environmental correlations among these traits. Results: Significant heritable components (p < 0.01) ranging from 0.25–0.68 exist for the studied phenotypes. Heritability for WHR (h2 = 0.60) considerably surpasses the usual heritability estimates on family-based studies ( < 0.30). Measures of overall fatness (BMI, CF and SF) show stronger correlations with each other than body fat distribution traits (WHR, CI and TER). Conclusions: The study concluded that the Greater Bilbao Roma population is genetically predisposed to abdominal fat distribution. Variation in body mass is highly associated with variation in adiposity. However, overall fatness and adiposity distribution does not seem to share major common genetic factors, although common environmental factors operate between them.

Obesity and body size perceptions in a Spanish Roma population

Abstract Background: Roma people are particularly vulnerable to developing overweight and obesity. Self-perception of body image may influence the prevalence of obesity in this ethnic minority. Aim: The objectives of this study are to estimate the prevalence of obesity, to analyse body size perceptions and preferences and to assess the relationship between body size perceptions and obesity in the Roma population. Subjects and methods: The analyses were carried out on 372 men, women and children from the Roma population residing in the Greater Bilbao region (Basque Country, Spain). In adults, a standard figural scale was used to analyse body size perceptions and preferences in this ethnic minority. Results: Overall 51.7% of adult and 24.4% of minor Roma individuals were obese. Both Roma men and women had inaccurate self-perceptions of their body size. Significant differences on body size perceptions were detected based on age, sex, nutritional status and socioeconomic characteristics. Conclusion: This Roma population presents one of the highest rates of obesity worldwide. Although a certain awareness of the correct weight status was appreciated, the inability of Roma individuals to see themselves as overweight or obese may be a significant factor on the high prevalence of obesity in this population.

A statistical investigation into the sharing of common genetic factors between blood pressure and obesity phenotypes in nuclear families from the Greater Bilbao (Spain).

Objectives Several obesity phenotypes (e.g. body mass and fat, fat distribution) have been suggested to be a risk for elevated blood pressure. This study was undertaken to determine the heritability of four blood pressure phenotypes: SBP, DBP, pulse pressure (PP) and mean arterial pressure (MAP) and to assess the strength of genetic and environmental correlations among these phenotypes, and also between blood pressure and the different obesity-related traits. Methods The studied sample consisted of 429 nuclear families living in the Greater Bilbao (Spain) and included 1302 individuals aged 4–61 years. Univariate and bivariate quantitative genetic analyses were performed using a variance components procedure implemented in Sequential Oligogenic Linkage Analysis Routines software. Results SBP, DBP, PP and MAP were significantly influenced by genetic factors with heritability estimates of 0.25, 0.28, 0.14 and 0.31, respectively, and presented high genetic and environmental correlations between them (except DBP–PP). On the contrary, whereas SBP, DBP and MAP showed common environmental factors with almost all body mass and fat-related traits, pleiotropic effects were only detected for some pairs, especially for those phenotypes that included skinfolds. In contrast, PP did not exhibit common genetic or environmental factors with obesity phenotypes in the studied population Conclusion Blood pressure and obesity phenotypes do not share, in general, a substantial influence of common genetic and environmental effects. Finally, the results obtained revealed the importance of the amount of adipose tissue in the genetic correlations with SBP, DBP and MAP, at least, during the growth period.