Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank

Obesity risk in young adults from the Jerusalem Perinatal Study (JPS): the contribution of polygenic risk and early life exposure

BACKGROUND/OBJECTIVES

The effects of early life exposures on offspring life-course health are well established. This study assessed whether adding early socio-demographic and perinatal variables to a model based on polygenic risk score (PRS) improves prediction of obesity risk.

METHODS

We used the Jerusalem Perinatal study (JPS) with data at birth and body mass index (BMI) and waist circumference (WC) measured at age 32. The PRS was constructed using over 2.1M common SNPs identified in genome-wide association study (GWAS) for BMI. Linear and logistic models were applied in a stepwise approach. We first examined the associations between genetic variables and obesity-related phenotypes (e.g., BMI and WC). Secondly, socio-demographic variables were added and finally perinatal exposures, such as maternal pre-pregnancy BMI (mppBMI) and gestational weight gain (GWG) were added to the model. Improvement in prediction of each step was assessed using measures of model discrimination (area under the curve, AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

One standard deviation (SD) change in PRS was associated with a significant increase in BMI (β = 1.40) and WC (β = 2.45). These associations were slightly attenuated (13.7-14.2%) with the addition of early life exposures to the model. Also, higher mppBMI was associated with increased offspring BMI (β = 0.39) and WC (β = 0.79) (p < 0.001). For obesity (BMI ≥ 30) prediction, the addition of early socio-demographic and perinatal exposures to the PRS model significantly increased AUC from 0.69 to 0.73. At an obesity risk threshold of 15%, the addition of early socio-demographic and perinatal exposures to the PRS model provided a significant improvement in reclassification of obesity (NRI, 0.147; 95% CI 0.068-0.225).

CONCLUSIONS

Inclusion of early life exposures, such as mppBMI and maternal smoking, to a model based on PRS improves obesity risk prediction in an Israeli population-sample.

Plant-based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort

OBJECTIVE

The study's objective was to examine whether adherence to three plant-based dietary indices (PDIs) mediated or moderated genetic susceptibility to obesity.

METHODS

Baseline participants were 7037 adults (57% women, aged 55.6 ± 7.7 years) from the CARTaGENE cohort of Quebec adults. Two polygenic risk scores for BMI (PRS-BMI), 92 single-nucleotide polymorphisms and 2 million single-nucleotide polymorphisms, and three plant-based scores were calculated (overall, healthy, and unhealthy). Follow-up participants were 2258 adults with data on obesity outcomes, measured 6 years later. General linear models were used to examine the relationships between PRSs and PDI scores on obesity outcomes. Causal mediation analyses were conducted to assess mediation and interaction models.

RESULTS

The overall- and healthy-PDIs and PRSs were significantly associated with obesity outcomes. Adherence to PDIs did not mediate or moderate genetic susceptibility to obesity. Associations between PRSs and obesity outcomes were partly mediated by meat intake cross-sectionally and whole grains intake among males both cross-sectionally and longitudinally. Higher meat intake had a positive association with obesity outcomes, whereas higher whole grains intake had an inverse association.

CONCLUSIONS

These findings suggest that components of a plant-based diet and a shift away from animal products, specifically meat, might be beneficial for nutrition interventions, particularly among individuals with higher genetic risk of obesity.

New Insights into Polygenic Score-Lifestyle Interactions for Cardiometabolic Risk Factors from Genome-Wide Interaction Analyses

The relationship between lifestyles and cardiometabolic outcomes varies between individuals. In 382,275 UK Biobank Europeans, we investigate how lifestyles interact with polygenic scores (PGS) of cardiometabolic risk factors. We identify six interactions (PGS for body mass index with meat diet, physical activity, sedentary behaviour and insomnia; PGS for high-density lipoprotein cholesterol with sedentary behaviour; PGS for triglycerides with meat diet) in multivariable linear regression models including an interaction term and show stronger associations between lifestyles and cardiometabolic risk factors among individuals with high PGSs than those with low PGSs. Genome-wide interaction analyses pinpoint three genetic variants (FTO rs72805613 for BMI; CETP rs56228609 for high-density lipoprotein cholesterol; TRIB2 rs4336630 for triglycerides; PInteraction < 5 × 10-8). The associations between lifestyles and cardiometabolic risk factors differ between individuals grouped by the genotype of these variants, with the degree of differences being similar to that between individuals with high and low values for the corresponding PGSs. This study demonstrates that associations between lifestyles and cardiometabolic risk factors can differ between individuals based upon their genetic profiles. It further suggests that genetic variants with interaction effects contribute more to such differences compared to those without interaction effects, which has potential implications for developing PGSs for personalised intervention.

Association of GLP-1 Receptor Agonists with Chronic Obstructive Pulmonary Disease Exacerbations among Patients with Type 2 Diabetes

Rationale: Patients with chronic obstructive pulmonary disease (COPD) and type 2 diabetes (T2D) have worse clinical outcomes compared with patients without metabolic dysregulation. GLP-1 (glucagon-like peptide 1) receptor agonists (GLP-1RAs) reduce asthma exacerbation risk and improve FVC in patients with COPD. Objectives: To determine whether GLP-1RA use is associated with reduced COPD exacerbation rates, and severe and moderate exacerbation risk, compared with other T2D therapies. Methods: A retrospective, observational, electronic health records-based study was conducted using an active comparator, new-user design of 1,642 patients with COPD in a U.S. health system from 2012 to 2022. The COPD cohort was identified using a previously validated machine learning algorithm that includes a natural language processing tool. Exposures were defined as prescriptions for GLP-1RAs (reference group), DPP-4 (dipeptidyl peptidase 4) inhibitors (DPP-4is), SGLT2 (sodium-glucose cotransporter 2) inhibitors, or sulfonylureas. Measurements and Main Results: Unadjusted COPD exacerbation counts were lower in GLP-1RA users. Adjusted exacerbation rates were significantly higher in DPP-4i (incidence rate ratio, 1.48 [95% confidence interval, 1.08-2.04]; P = 0.02) and sulfonylurea (incidence rate ratio, 2.09 [95% confidence interval, 1.62-2.69]; P < 0.0001) users compared with GLP-1RA users. GLP-1RA use was also associated with significantly reduced risk of severe exacerbations compared with DPP-4i and sulfonylurea use, and of moderate exacerbations compared with sulfonylurea use. After adjustment for clinical covariates, moderate exacerbation risk was also lower in GLP-1RA users compared with DPP-4i users. No statistically significant difference in exacerbation outcomes was seen between GLP-1RA and SGLT2 inhibitor users. Conclusions: Prospective studies of COPD exacerbations in patients with comorbid T2D are warranted. Additional research may elucidate the mechanisms underlying these observed associations with T2D medications.

Polygenic Risk Scores and the Risk of Childhood Overweight/Obesity in Association With the Consumption of Sweetened Beverages: A Population-Based Cohort Study

Background: Sugar-sweetened beverage (SSB) and non-nutritive sweetened beverage (NNSB) consumption is associated with obesity and are targets for population-level dietary interventions. In children (<16 years), we evaluate whether SSB or NNSB consumption is associated with subsequent (2 years later) overweight and/or obesity, and the effect of consumption on subsequent overweight/obesity differs by BMI polygenic risk score (BMI-PRS). Methods: The nationally representative Longitudinal-Study-of-Australian-Children had biennial data collection from birth (n = 5107) until age 14/15 years (n = 3127). At age 11/12 years, a comprehensive biomedical assessment, including PRS assessment, was undertaken (n = 1422). Parent- or self-reported beverage consumption (SSBs: soft drinks, energy drinks, and/or juice; NNSBs: diet drinks) was measured as any/none over previous 24 hours. BMI-PRS was derived using published results (high PRS ≥75th percentile). At ages 4/5-14/15 children were classified as having obesity, overweight/obesity, or not having overweight/obesity using BMI z-score (CDC cut points). Results: SSB consumption had limited association with subsequent overweight/obesity. NNSB consumption was associated with ∼8% more children with subsequent overweight/obesity at most ages. In older children with high BMI-PRS, associations between NNSB consumption and subsequent overweight/obesity strengthened with age [at age 14-15 for high BMI-PRS, difference in proportion with overweight/obesity among NNSB consumers vs. nonconsumers = 0.38 (95% confidence interval: 0.22 to 0.55, p ≤ 0.001)]. There was limited association between SSB consumption and BMI-PRS. Conclusion: NNSB consumption was associated with increased risk of overweight/obesity for children with greater genetic risk at older ages (12-15 years). Focused intervention among children with high genetic risk could target NNSB consumption; however, reverse causality (children with genetic risk and/or high BMI consume more NNSBs) cannot be excluded.

Rare Variants of Obesity-Associated Genes in Young Adults with Abdominal Obesity

The increase in the prevalence of overweight, obesity and associated diseases is a serious problem. The aim of the study was to identify rare variants in obesity-associated genes in young adults with abdominal obesity in our population and to analyze information about these variants in other populations. Targeted high-throughput sequencing of obesity-associated genes was performed (203 young adults with an abdominal obesity phenotype). In our study, all of the 203 young adults with abdominal obesity had some rare variant in the genes associated with obesity. The widest range of rare and common variants was presented in ADIPOQ, FTO, GLP1R, GHRL, and INS genes. The use of targeted sequencing and clinical criteria makes it possible to identify carriers of rare clinically significant variants in a wide range of obesity-associated genes and to investigate their influence on phenotypic manifestations of abdominal obesity.

Genetics: A Starting Point for the Prevention and the Treatment of Obesity

Obesity is a common, serious, and costly disease. More than 1 billion people worldwide are obese-650 million adults, 340 million adolescents, and 39 million children. The WHO estimates that, by 2025, approximately 167 million people-adults and children-will become less healthy because they are overweight or obese. Obesity-related conditions include heart disease, stroke, type 2 diabetes, and certain types of cancer. These are among the leading causes of preventable, premature death. The estimated annual medical cost of obesity in the United States was nearly $173 billion in 2019 dollars. Obesity is considered the result of a complex interaction between genes and the environment. Both genes and the environment change in different populations. In fact, the prevalence changes as the result of eating habits, lifestyle, and expression of genes coding for factors involved in the regulation of body weight, food intake, and satiety. Expression of these genes involves different epigenetic processes, such as DNA methylation, histone modification, or non-coding micro-RNA synthesis, as well as variations in the gene sequence, which results in functional alterations. Evolutionary and non-evolutionary (i.e., genetic drift, migration, and founder's effect) factors have shaped the genetic predisposition or protection from obesity in modern human populations. Understanding and knowing the pathogenesis of obesity will lead to prevention and treatment strategies not only for obesity, but also for other related diseases.

Genetic and Environmental Factors Underlying Parallel Changes in Body Mass Index and Alcohol Consumption: A 36-Year Longitudinal Study of Adult Twins

INTRODUCTION

While the genetic and environmental underpinnings of body weight and alcohol use are fairly well-known, determinants of simultaneous changes in these traits are still poorly known. We sought to quantify the environmental and genetic components underlying parallel changes in weight and alcohol consumption and to investigate potential covariation between them.

METHODS

The analysis comprised 4,461 adult participants (58% women) from the Finnish Twin Cohort with four measures of alcohol consumption and body mass index (BMI) over a 36-year follow-up. Trajectories of each trait were described by growth factors, defined as intercepts (i.e., baseline) and slopes (i.e., change over follow-up), using latent growth curve modeling. Growth values were used for male (190 monozygotic pairs, 293 dizygotic pairs) and female (316 monozygotic pairs, 487 dizygotic pairs) same-sex complete twin pairs in multivariate twin modeling. The variances and covariances of growth factors were then decomposed into genetic and environmental components.

RESULTS

The baseline heritabilities were similar in men (BMI: h2 = 79% [95% confidence interval: 74, 83]; alcohol consumption: h2 = 49% [32, 67]) and women (h2 = 77% [73, 81]; h2 = 45% [29, 61]). Heritabilities of BMI change were similar in men (h2 = 52% [42, 61]) and women (h2 = 57% [50, 63]), but the heritability of change in alcohol consumption was significantly higher (p = 0.03) in men (h2 = 45% [34, 54]) than in women (h2 = 31% [22, 38]). Significant additive genetic correlations between BMI at baseline and change in alcohol consumption were observed in both men (rA = -0.17 [-0.29, -0.04]) and women (rA = -0.18 [-0.31, -0.06]). Non-shared environmental factors affecting changes in alcohol consumption and BMI were correlated in men (rE = 0.18 [0.06, 0.30]). Among women, non-shared environmental factors affecting baseline alcohol consumption and the change in BMI were inversely correlated (rE = -0.11 [-0.20, -0.01]).

CONCLUSIONS

Based on genetic correlations, genetic variation underlying BMI may affect changes in alcohol consumption. Independent of genetic effects, change in BMI correlates with change in alcohol consumption in men, suggesting direct effects between them.

Robust Bioinformatics Approaches Result in the First Polygenic Risk Score for BMI in Greek Adults

Quantifying the role of genetics via construction of polygenic risk scores (PRSs) is deemed a resourceful tool to enable and promote effective obesity prevention strategies. The present paper proposes a novel methodology for PRS extraction and presents the first PRS for body mass index (BMI) in a Greek population. A novel pipeline for PRS derivation was used to analyze genetic data from a unified database of three cohorts of Greek adults. The pipeline spans various steps of the process, from iterative dataset splitting to training and test partitions, calculation of summary statistics and PRS extraction, up to PRS aggregation and stabilization, achieving higher evaluation metrics. Using data from 2185 participants, implementation of the pipeline enabled consecutive repetitions in splitting training and testing samples and resulted in a 343-single nucleotide polymorphism PRS yielding an R² = 0.3241 (beta = 1.011, p-value = 4 × 10^-193) for BMI. PRS-included variants displayed a variety of associations with known traits (i.e., blood cell count, gut microbiome, lifestyle parameters). The proposed methodology led to creation of the first-ever PRS for BMI in Greek adults and aims at promoting a facilitating approach to reliable PRS development and integration in healthcare practice.

Patient Characteristics Associated With Reactions to Mrgprx2-Activating Drugs in an Electronic Health Record-Linked Biobank

BACKGROUND

Mas-related G protein-couple receptor x2 (Mrgprx2) activation underlies many common non-IgE-mediated adverse drug reactions (ADRs), yet the features of patients with reactions to Mrgprx2-activating drugs are unknown.

OBJECTIVE

To characterize the patient-specific comorbidities and laboratory characteristics associated with listed reactions to Mrgprx2-activating drugs, including fluoroquinolones, morphine, neuromuscular blockade agents, vancomycin, and leuprolide.

METHODS

We used a retrospective, observational cohort study design using electronic health record data from adults with an Mrgprx2-activating drug exposure recorded within a hospital system clinical Biobank. Odds ratios (ORs) and incidence rate ratios for clinical characteristics associated with ADRs, including immediate hypersensitivity reactions, were calculated using multivariable logistic regression.

RESULTS

Among 59,763 patients exposed to Mrgprx2-activating drugs, 4846 had a listed ADR. Female sex, White race, asthma (OR: 1.81, 95% confidence interval [CI]: 1.68-1.94), chronic urticaria (OR: 1.73, 95% CI: 1.46-2.05), and mastocytosis (OR: 12.79, 95% CI: 5.98-27.02) were associated with increased odds of a reaction. Overall, patients with allergic disease had 1.21 times the rate of an ADR compared with patients without allergic disease. Elevated absolute eosinophil count was inversely associated with reactions, and there was no association with elevated total IgE. Observed associations were similar in a patient subgroup with immediate-type hypersensitivity reactions.

CONCLUSION

Specific allergic diseases and common allergic biomarkers are differentially associated with ADRs to Mrgprx2-activating drugs. These findings from a large, "real world" drug-exposed population highlight clinical factors that may contribute to non-IgE-mediated drug allergy.

Lifestyle and Health-Related Quality of Life Relationships Concerning Metabolic Disease Phenotypes on the Nutrimdea Online Cohort

Obesity, diabetes and cardiovascular events are non-communicable diseases (NCDs) directly related to lifestyle and life quality. Rises on NCDs rates are leading to increases in early deaths concerning metabolic morbidities. Health-related quality of life (HRQoL) has been described as a subjective perception about the influence of health and personal features on human well-being. This study aimed to characterize phenotypic and lifestyle roles on the occurrence of metabolic diseases and determine the potential mutual interactions and with HRQoL. Data from an online adult population (NUTRiMDEA study, n = 17,332) were used to estimate an adapted Obesogenic Score (ObS), while logistic regression analyses were fitted in order to examine relevant factors related to the prevalence of different metabolic diseases including HRQoL. Sex and age showed significant differences depending on lifestyle and metabolic health (p < 0.05). Adherence to the Mediterranean diet and physical activity showed a mutual interaction concerning ObS (p < 0.001), as well with metabolic health (p = 0.044). Furthermore, metabolic diseases showed own features related to sociodemographic and lifestyle characteristics in this population. Metabolic syndrome components may be differently influenced by diverse lifestyle or socioeconomic factors which in turn affect the perceived HRQoL. These outcomes should be taken into account individually for a precision medicine and public health purposes.

Healthy beverages may reduce the genetic risk of abdominal obesity and related metabolic comorbidities: a gene-diet interaction study in Iranian women

BACKGROUND & AIMS

The nutrition transition in developing countries like Iran causes the increasing rise of obesity and abdominal obesity rates. However, it is not yet well proven that environmental modifications like improving the quality of beverage intake can be effective in people who have a genetic predisposition to obesity. So, in the present study, we examine the interaction between genetic predisposition and healthy beverage index (HBI) with abdominal obesity and obesity-related metabolic risk factors in overweight and obese women.

METHOD

Based on inclusion and exclusion criteria, 202 overweight or obese females were chosen for this cross-sectional study. Body composition, anthropometric measures, physical activity, and beverage intake data were collected and analyzed using recognized and trustworthy methodologies. Biochemical tests were performed on serum samples. A genetic risk score (GRS) was calculated based on the results of genetic tests. The predetermined HBI was calculated based on previous studies. A generalized linear model was used to estimate the interactions between GRS and HBI (GLM).

RESULTS

We found significant interactions between GRS and HBI on WHR (β = - 0.39, CI: -0.07 to 0.001, P = 0.05) and WC (β = - 6.18, CI: - 13.41 to 1.05, P = 0.09). Also, there were significant gene-diet interactions for HBI and GRS on HDL (β = 7.09, CI: - 0.73 to 14.92, P = 0.07) and FBS (β = - 9.07, CI: - 18.63 to 0.47, P = 0.06).

CONCLUSIONS

These findings emphasize the HBI considering genetics appears to protect against the risks of abdominal obesity and metabolic associated obesity markers.

Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study

BACKGROUND

Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank.

METHODS

We constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population.

FINDINGS

We found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10-5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31-1·55, p≤7·7 × 10-16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9-3·3, for stable weight; 4·1%, 1·4-6·8, for weight gain; 5·5%, 2·8-8·2, for weight loss; and 4·7%, 2·3-7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07-1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05).

INTERPRETATION

Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression.

FUNDING

Klarman Family Foundation, US National Institute of Mental Health (NIMH).

Study of the Combined Effect of Maternal Tobacco Smoking and Polygenic Risk Scores on Birth Weight and Body Mass Index in Childhood

Background: Maternal smoking during pregnancy has adverse health effects on the offspring, including lower birth weight and increased risk for obesity. These outcomes are also influenced by common genetic polymorphisms. We aimed to investigate the combined effect of maternal smoking during pregnancy and genetic predisposition on birth weight and body mass index (BMI)-related traits in 1,086 children of the Human Early Life Exposome (HELIX) project.

Methods: Maternal smoking during pregnancy was self-reported. Phenotypic traits were assessed at birth or at the age of 8 years. Ten polygenic risk scores (PRSs) per trait were calculated using the PRSice v2 program. For birth weight, we estimated two sets of PRSs based on two different base GWAS summary statistics: PRS-EGG, which includes HELIX children, and PRS-PanUK, which is completely independent. The best PRS per trait (highest R2) was selected for downstream analyses, and it was treated in continuous or categorized into three groups. Multivariate linear regression models were applied to evaluate the association of the explanatory variables with the traits of interest. The combined effect was evaluated by including an interaction term in the regression models and then running models stratified by the PRS group.

Results: BMI-related traits were correlated among them but not with birth weight. A similar pattern was observed for their PRSs. On average, the PRSs explained ∼4% of the phenotypic variation, with higher PRS values related to higher trait values (p-value &lt;5.55E-08). Sustained maternal smoking was associated with lower birth weight and higher BMI and related traits (p-value &lt;2.99E-02). We identified a gene by environment (GxE) interaction for birth weight between sustained maternal smoking and the PRS-EGG in three groups (p-value interaction = 0.01), which was not replicated with the PRS-PanUK (p-value interaction = 0.341). Finally, we did not find any statistically significant GxE interaction for BMI-related traits (p-value interaction &gt;0.237).

Conclusion: Sustained maternal smoking and the PRSs were independently associated with birth weight and childhood BMI-related traits. There was low evidence of GxE interactions.