Gene-by-age effects on BMI from birth to adulthood: the Fels Longitudinal Study

Genotype-by-Environment Interactions in Nonalcoholic Fatty Liver Disease and Chronic Illness among Mexican Americans: The Role of Acculturation Stress

This study examines the complex interplay of genetic and environmental interactions that shape chronic illness risk. Evidence is mounting for the role of genetic expression and the immune response in the pathogenesis of chronic disease. In the Rio Grande Valley of south Texas, where 90% of the population is Mexican American, chronic illnesses (including obesity, diabetes, nonalcoholic liver disease, and depression) are reaching epidemic proportions. This study leverages an ongoing family study of the genetic determinants of risk for obesity, diabetes, hypertension, hyperlipidemia, and depression in a Mexican American population. Data collected included blood pressure, BMI, hepatic transaminases, HbA1c, depression (BDI-II), acculturation/marginalization (ARSMA-II), and liver health as assessed by elastography. Heritability and genotype-by-environment (G×E) interactions were analyzed, focusing on the marginalization/separation measure of the ARSMA-II. Significant heritabilities were found for traits such as HbA1c (h2 = 0.52), marginalization (h2 = 0.30), AST (h2 = 0.25), ALT (h2 = 0.41), and BMI (h2 = 0.55). Genotype-by-environment interactions were significant for HbA1c, AST/ALT ratio, BDI-II, and CAP, indicating that genetic factors interact with marginalization to influence these traits. This study found that acculturation stress exacerbates the genetic response to chronic illness. These findings underscore the importance of considering G×E interactions in understanding disease susceptibility and may inform targeted interventions for at-risk populations. Further research is warranted to elucidate the underlying molecular pathways and replicate these findings in diverse populations.

Risk factors affecting polygenic score performance across diverse cohorts

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

The associations of maternal and paternal obesity with latent patterns of offspring BMI development between 7 and 17 years of age: pooled analyses of cohorts born in 1958 and 2001 in the United Kingdom

OBJECTIVE

We aimed to 1) describe how the UK obesity epidemic reflects a change over time in the proportion of the population demonstrating adverse latent patterns of BMI development and 2) investigate the potential roles of maternal and paternal BMI in this secular process.

METHODS

We used serial BMI data between 7 and 17 years of age from 13220 boys and 12711 girls. Half the sample was born in 1958 and half in 2001. Sex-specific growth mixture models were developed. The relationships of maternal and paternal BMI and weight status with class membership were estimated using the 3-step BCH approach, with covariate adjustment.

RESULTS

The selected models had five classes. For each sex, in addition to the two largest normal weight classes, there were "normal weight increasing to overweight" (17% of boys and 20% of girls), "overweight increasing to obesity" (8% and 6%), and "overweight decreasing to normal weight" (3% and 6%) classes. More than 1-in-10 children from the 2001 birth cohort were in the "overweight increasing to obesity" class, compared to less than 1-in-30 from the 1958 birth cohort. Approximately 75% of the mothers and fathers of this class had overweight or obesity. When considered together, both maternal and paternal BMI were associated with latent class membership, with evidence of negative departure from additivity (i.e., the combined effect of maternal and paternal BMI was smaller than the sum of the individual effects). The odds of a girl belonging to the "overweight increasing to obesity" class (compared to the largest normal weight class) was 13.11 (8.74, 19.66) times higher if both parents had overweight or obesity (compared to both parents having normal weight); the equivalent estimate for boys was 9.01 (6.37, 12.75).

CONCLUSIONS

The increase in obesity rates in the UK over more than 40 years has been partly driven by the growth of a sub-population demonstrating excess BMI gain during adolescence. Our results implicate both maternal and paternal BMI as correlates of this secular process.

Quantifying factors that affect polygenic risk score performance across diverse ancestries and age groups for body mass index

Polygenic risk scores (PRS) have led to enthusiasm for precision medicine. However, it is well documented that PRS do not generalize across groups differing in ancestry or sample characteristics e.g., age. Quantifying performance of PRS across different groups of study participants, using genome-wide association study (GWAS) summary statistics from multiple ancestry groups and sample sizes, and using different linkage disequilibrium (LD) reference panels may clarify which factors are limiting PRS transferability. To evaluate these factors in the PRS generation process, we generated body mass index (BMI) PRS (PRSBMI) in the Electronic Medical Records and Genomics (eMERGE) network (N=75,661). Analyses were conducted in two ancestry groups (European and African) and three age ranges (adult, teenagers, and children). For PRSBMI calculations, we evaluated five LD reference panels and three sets of GWAS summary statistics of varying sample size and ancestry. PRSBMI performance increased for both African and European ancestry individuals using cross-ancestry GWAS summary statistics compared to European-only summary statistics (6.3% and 3.7% relative R2 increase, respectively, pAfrican=0.038, pEuropean=6.26x10-4). The effects of LD reference panels were more pronounced in African ancestry study datasets. PRSBMI performance degraded in children; R2 was less than half of teenagers or adults. The effect of GWAS summary statistics sample size was small when modeled with the other factors. Additionally, the potential of using a PRS generated for one trait to predict risk for comorbid diseases is not well understood especially in the context of cross-ancestry analyses - we explored clinical comorbidities from the electronic health record associated with PRSBMI and identified significant associations with type 2 diabetes and coronary atherosclerosis. In summary, this study quantifies the effects that ancestry, GWAS summary statistic sample size, and LD reference panel have on PRS performance, especially in cross-ancestry and age-specific analyses.

Identification of five genetic variants with differential effects on obesity-related traits based on age

Obesity is a major public health concern, and its prevalence generally increases with age. As the number of elderly people is increasing in the aging population, the age-dependent increase in obesity has raised interest in the underlying mechanism. To understand the genetic basis of age-related increase in obesity, we identified genetic variants showing age-dependent differential effects on obesity. We conducted stratified analyses between young and old groups using genome-wide association studies of 355,335 United Kingom Biobank participants for five obesity-related phenotypes, including body mass index, body fat percentage, waist-hip ratio, waist circumference, and hip circumference. Using t-statistic, we identified five significant lead single nucleotide polymorphisms: rs2258461 with body mass index, rs9861311 and rs429358 with body fat percentage, rs2870099 with waist-hip ratio, and rs145500243 with waist circumference. Among these single nucleotide polymorphisms, rs429358, located in APOE gene was associated with diverse age-related diseases, such as Alzheimer’s disease, coronary artery disease, age-related degenerative macular diseases, and cognitive decline. The C allele of rs429358 gradually decreases body fat percentage as one grows older in the range of 40–69 years. In conclusion, we identified five genetic variants with differential effects on obesity-related phenotypes based on age using a stratified analysis between young and old groups, which may help to elucidate the mechanisms by which age influences the development of obesity.

The heritability of BMI varies across the range of BMI-a heritability curve analysis in a twin cohort

BACKGROUND

The heritability of traits such as body mass index (BMI), a measure of obesity, is generally estimated using family and twin studies, and increasingly by molecular genetic approaches. These studies generally assume that genetic effects are uniform across all trait values, yet there is emerging evidence that this may not always be the case.

METHOD/SUBJECTS

This paper analyzes twin data using a recently developed measure of heritability called the heritability curve. Under the assumption that trait values in twin pairs are governed by a flexible Gaussian mixture distribution, heritability curves may vary across trait values. The data consist of repeated measures of BMI on 1506 monozygotic (MZ) and 2843 like-sexed dizygotic (DZ) adult twin pairs, gathered from multiple surveys in older Finnish Twin Cohorts.

RESULTS

The heritability curve and BMI value-specific MZ and DZ pairwise correlations were estimated, and these varied across the range of BMI. MZ correlations were highest at BMI values from 21 to 24, with a stronger decrease for women than for men at higher values. Models with additive and dominance effects fit best at low and high BMI values, while models with additive genetic and common environmental effects fit best in the normal range of BMI.

CONCLUSIONS

We demonstrate that twin and molecular genetic studies need to consider how genetic effects vary across trait values. Such variation may reconcile findings of traits with high heritability and major differences in mean values between countries or over time.

Evaluation of the Predictive Ability, Environmental Regulation and Pharmacogenetics Utility of a BMI-Predisposing Genetic Risk Score during Childhood and Puberty

Polygenetic risk scores (pGRSs) consisting of adult body mass index (BMI) genetic variants have been widely associated with obesity in children populations. The implication of such obesity pGRSs in the development of cardio-metabolic alterations during childhood as well as their utility for the clinical prediction of pubertal obesity outcomes has been barely investigated otherwise. In the present study, we evaluated the utility of an adult BMI predisposing pGRS for the prediction and pharmacological management of obesity in Spanish children, further investigating its implication in the appearance of cardio-metabolic alterations. For that purpose, we counted on genetics data from three well-characterized children populations (composed of 574, 96 and 124 individuals), following both cross-sectional and longitudinal designs, expanding childhood and puberty. As a result, we demonstrated that the pGRS is strongly associated with childhood BMI Z-Score (B = 1.56, SE = 0.27 and p-value = 1.90 × 10⁻⁸), and that could be used as a good predictor of obesity longitudinal trajectories during puberty. On the other hand, we showed that the pGRS is not associated with cardio-metabolic comorbidities in children and that certain environmental factors interact with the genetic predisposition to the disease. Finally, according to the results derived from a weight-reduction metformin intervention in children with obesity, we discarded the utility of the pGRS as a pharmacogenetics marker of metformin response.

Genetic insights into fetal growth and measures of glycaemic regulation and adiposity in adulthood: a family-based study

Background

The genetics of fetal insulin release and/or action have been suggested to affect fetal growth, adult insulin resistance and adult body composition. The genetic correlation between body composition at birth versus glycaemic regulation and body composition in adulthood have, however, not been well studied. We therefore aimed to investigate these genetic correlations in a family-based cohort.

Methods

A Danish family cohort of 434 individuals underwent an oral glucose tolerance test with subsequent calculation of surrogate measures of serum insulin response and insulin sensitivity. Measures of fetal growth were retrieved from midwife journals. Heritability and genetic correlations were estimated using a variance component model.

Results

A high heritability of 0.80 was found for birth weight, whereas ponderal index had a heritability of 0.46. Adult insulin sensitivity measured as Matsuda index was genetically correlated with both birth weight and ponderal index (ρG = 0.36 (95% CI: 0.03; 0.69) and ρG = 0.52 (95% CI, 0.15; 0.89), respectively). Only birth weight showed a significant genetic correlation with adult weight (ρG = 0.38 (95% CI: 0.09; 0.67)) whereas only ponderal index was genetically inversely correlated with fasting insulin (ρG = - 0.47 (95% CI: - 0.86; - 0.08) and area under the curve for insulin release during the oral glucose tolerance test (ρG = - 0.66 (95% CI: - 1.13; - 0.19)).

Individual as well as combined adjustment for 45 selected birth weight, obesity and type 2 diabetes susceptibility gene variants did not affect the correlations.

Conclusions

The genetics of both birth weight and ponderal index appear to be under the same genetic influence as adult insulin resistance. Furthermore, ponderal index and adult insulin release seem to be partly shared, as well as the genetics of birth weight and adult weight.

Word count abstract: 281.

Electronic supplementary material

The online version of this article (10.1186/s12881-018-0718-2) contains supplementary material, which is available to authorized users.

Longitudinal Analysis of Genetic Susceptibility and BMI Throughout Adult Life

Little is known about the genetic influence on BMI trajectory throughout adulthood. We created a genetic risk score (GRS) comprising 97 adult BMI-associated variants among 9,971 women and 6,405 men of European ancestry. Serial measures of BMI were assessed from 18 (women) or 21 (men) years to 85 years of age. We also examined BMI change in early (from 18 or 21 to 45 years of age), middle (from 45 to 65 years of age), and late adulthood (from 65 to 80 years of age). GRS was positively associated with BMI across all ages, with stronger associations in women than in men. The associations increased from early to middle adulthood, peaked at 45 years of age in men and at 60 years of age in women (0.91 and 1.35 kg/m² per 10-allele increment, respectively) and subsequently declined in late adulthood. For women, each 10-allele increment in the GRS was associated with an average BMI gain of 0.54 kg/m² in early adulthood, whereas no statistically significant association was found for BMI change in middle or late adulthood or for BMI change in any life period in men. Our findings indicate that genetic predisposition exerts a persistent effect on adiposity throughout adult life and increases early adulthood weight gain in women.

Body mass index associations between mother and offspring from birth to age 18: the Fels Longitudinal Study

BACKGROUND

Parental obesity is a known determinant of childhood obesity. Previous research has shown a strong maternal influence on body mass index (BMI) during infancy and early childhood.

OBJECTIVES

The purpose of this research was to investigate the BMI associations between mother and offspring from birth to age 18 years.

METHODS

Participants were selected from the Fels Longitudinal Study. The current study sample includes 427 (215 mother/son and 212 mother/daughter) mother/child pairs. These pairs are repeatedly measured at multiple age groups in children, resulting in a total of 6,263 (3,215 mother/son, 3,048 mother/daughter) observations for data analysis. Inclusion criteria were children with measured height and weight for BMI collected at ages 0 to 18 years and their mother with BMI data. Maternal influences of BMI on offspring BMI from birth to early adulthood were analyzed by Spearman correlations and linear regression analyses.

RESULTS

Mother/son BMI correlations became statistically significant (p ≤ 0.05) at age 5-6 years and were significant through puberty and into early adulthood at age 18 years. Mother/daughter correlations became significant at age 1.5 years and also continued through adolescence, puberty and early adulthood at age 18 years. Associations persisted after the study sample was grouped into life stages and adjusted for decade of birth and parity.

CONCLUSIONS

The mother/daughter relationship was more strongly correlated than the mother/son relationship and also became statistically significant at an earlier age than boys.

GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling

Improving the accuracy of phenotyping through the use of advanced psychometric tools will increase the power to find significant associations with genetic variants and expand the range of possible hypotheses that can be tested on a genome-wide scale. Multivariate methods, such as structural equation modeling (SEM), are valuable in the phenotypic analysis of psychiatric and substance use phenotypes, but these methods have not been integrated into standard genome-wide association analyses because fitting a SEM at each single nucleotide polymorphism (SNP) along the genome was hitherto considered to be too computationally demanding. By developing a method that can efficiently fit SEMs, it is possible to expand the set of models that can be tested. This is particularly necessary in psychiatric and behavioral genetics, where the statistical methods are often handicapped by phenotypes with large components of stochastic variance. Due to the enormous amount of data that genome-wide scans produce, the statistical methods used to analyze the data are relatively elementary and do not directly correspond with the rich theoretical development, and lack the potential to test more complex hypotheses about the measurement of, and interaction between, comorbid traits. In this paper, we present a method to test the association of a SNP with multiple phenotypes or a latent construct on a genome-wide basis using a diagonally weighted least squares (DWLS) estimator for four common SEMs: a one-factor model, a one-factor residuals model, a two-factor model, and a latent growth model. We demonstrate that the DWLS parameters and p-values strongly correspond with the more traditional full information maximum likelihood parameters and p-values. We also present the timing of simulations and power analyses and a comparison with and existing multivariate GWAS software package.

Causal Effect of Genetic Variants Associated With Body Mass Index on Multiple Sclerosis Susceptibility

Multiple sclerosis (MS) is an autoimmune disease with both genetic and environmental risk factors. Recent studies indicate that childhood and adolescent obesity double the risk of MS, but this association may reflect unmeasured confounders rather than causal effects of obesity. We used separate-sample Mendelian randomization to estimate the causal effect of body mass index (BMI) on susceptibility to MS. Using data from non-Hispanic white members of the Kaiser Permanente Medical Care Plan of Northern California (KPNC) (2006-2014; 1,104 cases of MS and 10,536 controls) and a replication data set from Sweden (the Epidemiological Investigation of MS (EIMS) and the Genes and Environment in MS (GEMS) studies, 2005-2013; 5,133 MS cases and 4,718 controls), we constructed a weighted genetic risk score using 97 variants previously established to predict BMI. Results were adjusted for birth year, sex, education, smoking status, ancestry, and genetic predictors of MS. Estimates in KPNC and Swedish data sets suggested that higher genetically induced BMI predicted greater susceptibility to MS (odds ratio = 1.13, 95% confidence interval: 1.04, 1.22 for the KPNC sample; odds ratio = 1.09, 95% confidence interval: 1.03, 1.15 for the Swedish sample). Although the mechanism remains unclear, to our knowledge, these findings support a causal effect of increased BMI on susceptibility to MS for the first time, and they suggest a role for inflammatory pathways that characterize both obesity and the MS disease process.

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact.

Dopamine D4 receptor polymorphism and sex interact to predict children's affective knowledge

Affective knowledge, the ability to understand others' emotional states, is considered to be a fundamental part in efficient social interaction. Affective knowledge can be seen as related to cognitive empathy, and in the framework of theory of mind (ToM) as affective ToM. Previous studies found that cognitive empathy and ToM are heritable, yet little is known regarding the specific genes involved in individual variability in affective knowledge. Investigating the genetic basis of affective knowledge is important for understanding brain mechanisms underlying socio-cognitive abilities. The 7-repeat (7R) allele within the third exon of the dopamine D4 receptor gene (DRD4-III) has been a focus of interest, due to accumulated knowledge regarding its relevance to individual differences in social behavior. A recent study suggests that an interaction between the DRD4-III polymorphism and sex is associated with cognitive empathy among adults. We aimed to examine the same association in two childhood age groups. Children (N = 280, age 3.5 years, N = 283, age 5 years) participated as part of the Longitudinal Israel Study of Twins. Affective knowledge was assessed through children's responses to an illustrated story describing different emotional situations, told in a laboratory setting. The findings suggest a significant interaction between sex and the DRD4-III polymorphism, replicated in both age groups. Boy carriers of the 7R allele had higher affective knowledge scores than girls, whereas in the absence of the 7R there was no significant sex effect on affective knowledge. The results support the importance of DRD4-III polymorphism and sex differences to social development. Possible explanations for differences from adult findings are discussed, as are pathways for future studies.

A genome-wide association study of body mass index across early life and childhood

Background: Several studies have investigated the effect of known adult body mass index (BMI) associated single nucleotide polymorphisms (SNPs) on BMI in childhood. There has been no genome-wide association study (GWAS) of BMI trajectories over childhood.

Methods: We conducted a GWAS meta-analysis of BMI trajectories from 1 to 17 years of age in 9377 children (77 967 measurements) from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Western Australian Pregnancy Cohort (Raine) Study. Genome-wide significant loci were examined in a further 3918 individuals (48 530 measurements) from Northern Finland. Linear mixed effects models with smoothing splines were used in each cohort for longitudinal modelling of BMI.

Results: A novel SNP, downstream from the FAM120AOS gene on chromosome 9, was detected in the meta-analysis of ALSPAC and Raine. This association was driven by a difference in BMI at 8 years (T allele of rs944990 increased BMI; P_SNP = 1.52 × 10⁻⁸), with a modest association with change in BMI over time (P_Wald(Change) = 0.006). Three known adult BMI-associated loci (FTO, MC4R and ADCY3) and one childhood obesity locus (OLFM4) reached genome-wide significance (P_Wald < 1.13 × 10⁻⁸) with BMI at 8 years and/or change over time.

Conclusions: This GWAS of BMI trajectories over childhood identified a novel locus that warrants further investigation. We also observed genome-wide significance with previously established obesity loci, making the novel observation that these loci affected both the level and the rate of change in BMI. We have demonstrated that the use of repeated measures data can increase power to allow detection of genetic loci with smaller sample sizes.

Progressive influence of body mass index-associated genetic markers in rural Gambians

Background

In populations of European ancestry, the genetic contribution to body mass index (BMI) increases with age during childhood but then declines during adulthood, possibly due to the cumulative effects of environmental factors. How the effects of genetic factors on BMI change with age in other populations is unknown.

Subjects and methods

In a rural Gambian population (N=2535), we used a combined allele risk score, comprising genotypes at 28 ‘Caucasian adult BMI-associated’ single nucleotide polymorphisms (SNPs), as a marker of the genetic influence on body composition, and related this to internally-standardised z-scores for birthweight (zBW), weight-for-height (zWT-HT), weight-for-age (zWT), height-for-age (zHT), and zBMI cross-sectionally and longitudinally.

Results

Cross-sectionally, the genetic score was positively associated with adult zWT (0.018±0.009 per allele, p=0.034, N=1426) and zWT-HT (0.025±0.009, p=0.006), but not with size at birth or childhood zWT-HT (0.008±0.005, p=0.11, N=2211). The effect of the genetic score on zWT-HT strengthened linearly with age from birth through to late adulthood (age interaction term: 0.0083 z-scores/allele/year; 95% CI 0.0048 to 0.0118, p=0.0000032).

Conclusions

Genetic variants for obesity in populations of European ancestry have direct relevance to bodyweight in nutritionally deprived African settings. In such settings, genetic obesity susceptibility appears to regulate change in weight status throughout the life course, which provides insight into its potential physiological role.

The genetics of obesity in transition

Recent advances in human genetics have revealed a number of genes influencing the susceptibility to obesity and related conditions, but it is likely that their contribution to disease is contingent on numerous environmental factors. As the obesity epidemic has occurred over a relatively short period of recent history, use of gene-by-year of birth analysis may be a useful approach for quantifying, in aggregate, the interaction between genetic susceptibility to obesity and the numerous known and unknown environmental factors that have changed during nutrition and health transitions globally during this recent increase in obesity rates. Evidence from one family-based longitudinal study set in the United States is showcased, which points to significant increases in the effect of common genetic variants on childhood and adulthood BMI over an 80 year period spanning from 1929 to the present. First, common genetic variants previously known to be associated with age at menarche through genome-wide association analysis were examined in aggregate using a genetic risk score approach. The menarche genetic risk score, composed of 42 single-nucleotide polymorphisms (SNPs) was significantly associated with peri-pubertal BMI in both boys and girls, but the magnitude of the association was strongly dependent on year of birth, with greater effect as birth year increased. Second, a similar approach was taken using instead a BMI genetic risk score composed of 32 common variants previously found to be associated with BMI. This score was strongly associated with adulthood BMI, waist circumference, and skinfold thickness, as expected, but the magnitude of the association increased with later year of birth. Such gene-environment interactions call for greater focus on the mechanisms by which environmental factors impact the functional output of the human genome, including how epigenetic mechanisms may be altered during social, technological, nutritional, and ecological transitions.