Body Mass Index Polygenic Scores Research Articles

Dietary eggs, egg nutrients, polygenic score for body mass index, “Western pattern” diet, and weight change, a prospective analysis in the Women's health initiative

Background & AimsEggs contain nutrients which could help enrich the diets of postmenopausal women. Egg consumption and elevated body weight have been associated with elevated risk of serious chronic disease. It is possible that elevated body weight mediates between egg consumption and serious chronic disease. However, few studies exist on the link between egg consumption and body weight in post-menopausal women, and none of them accounted for genetic weight gain predispositions. Our objective was to examine associations between egg consumption, body weight, and genetic predisposition for an elevated Body Mass Index (BMI), in postmenopausal women. MethodsWe analyzed data from 4,439 healthy Women’s Health Initiative participants of European descent during a 6-year follow up using multivariable generalized linear mixed models to prospectively evaluate egg and egg-nutrient intake (measured by a food frequency questionnaire) against body weight and a BMI polygenic score (PGS-BMI) derived from GWAS meta-analysis effect-allele frequencies. ResultsWe found a positive prospective association between change in egg intake and body weight during the 6-year follow up. For instance, at year 3, women whose intake had increased by 2.0 eggs/week had gained 0.70 kg (95%CI: 0.34, 1.07, p=.0002) more than women whose intake had decreased by 2.4 eggs/week, p-linear <.0001. Cholesterol-intake and choline-intake, but not betaine-intake, showed similar significant associations. Exploratory analysis revealed that: 1) women only demonstrated these significant associations if they exhibited higher intakes of “Western-pattern” foods including processed and red meats, French fries, sweets and deserts, sugar-sweetened beverages, fried foods, and dietary fat, and energy; and 2) there was a significant positive prospective association between PGS-BMI and body-weight change, but only in the top quintile of egg-intake change. ConclusionsWe found significant positive prospective associations between weight change and changes in egg intake, cholesterol intake, and choline intake among healthy postmenopausal women of European ancestry in the Women’s Health Initiative. Exploratory analyses revealed that: 1) these significant associations only obtained among women who ate large amounts of “Western-pattern” foods; and 2) women with a higher genetic susceptibility for an elevated BMI gained more weight only if they increased their egg intake considerably. Our results require confirmation.

Polygenic Scores and Networks of Psychopathology Symptoms

Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology. To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms. Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included. Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS. Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041). Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.

Genetically Predicted Body Mass Index and Mortality in Chronic Obstructive Pulmonary Disease.

Rationale: Body mass index (BMI) is associated with chronic obstructive pulmonary disease (COPD) mortality, but the underlying mechanisms are unclear. The effect of genetic variants aggregated into a polygenic score may elucidate the causal mechanisms and predict risk. Objectives: To examine the associations of genetically predicted BMI with all-cause and cause-specific mortality in COPD. Methods: We developed a polygenic score (PGS) for BMI (PGSBMI) and tested for associations of the PGSBMI with all-cause, respiratory, and cardiovascular mortality in participants with COPD from the COPDGene (Genetic Epidemiology of COPD), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), and Framingham Heart studies. We calculated the difference between measured BMI and PGS-predicted BMI (BMIdiff) and categorized participants into groups of discordantly low (BMIdiff <20th percentile), concordant (BMIdiff between the 20th and 80th percentiles), and discordantly high (BMIdiff >80th percentile) BMI. We applied Cox models, examined potential nonlinear associations of the PGSBMI and BMIdiff with mortality, and summarized results with meta-analysis. Measurements and Main Results: We observed significant nonlinear associations of measured BMI and BMIdiff, but not PGSBMI, with all-cause mortality. In meta-analyses, a one-standard deviation increase in the PGSBMI was associated with an increased hazard for cardiovascular mortality (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.12-1.49), but not for respiratory or all-cause mortality. Compared with participants with concordant measured and genetically predicted BMI, those with discordantly low BMI had higher risks for all-cause mortality (HR, 1.57; 95% CI, 1.41-1.74) and respiratory death (HR, 2.01; 95% CI, 1.61-2.51). Conclusions: In people with COPD, a higher genetically predicted BMI is associated with higher cardiovascular mortality but not respiratory mortality. Individuals with a discordantly low BMI have higher all-cause and respiratory mortality rates than those with a concordant BMI.

Lifestyle factors, genetic susceptibility to obesity and their interactions on coronary artery disease risk: A cohort study in the UK Biobank

ObjectiveWe aimed to evaluate potential modifying effects of genetic susceptibility to obesity on the association of lifestyle factors with coronary artery disease (CAD) risk. MethodsA total of 328,606 participants (54% women) were included using data from the UK Biobank. We evaluated the risk of developing CAD associated with obesity-related polygenic scores (PGSs) and healthy lifestyle scores (HLSs). HLSs were constructed using six lifestyle factors. Obesity PGSs were created using genetic variants identified by genome-wide association studies, including 941 variants for body mass index (BMI) and 457 for waist-to-hip ratio (WHR). Both HLSs and PGSs were categorized into three groups. ResultsDuring a 9-year median follow-up, 14,541 participants developed CAD. An unhealthy lifestyle was significantly associated with an increased CAD risk (hazard ratio [HR] = 2.24, 95% confidence interval [CI] = 2.09–2.40). High BMI and WHR PGSs were each significantly associated with an increased CAD risk (HRBMI = 1.23, 1.17–1.29; HRWHR = 1.15, 1.09–1.21). Lifestyle factors explained 41% (95% CI = 38%–45%) of CAD, while genetic variants for BMI explained only 10% (7%–14%). Risks of CAD were increased with poorer HLS independent of obesity-related PGSs. Individuals with the most unhealthy lifestyle and highest BMI PGS had the highest risk of CAD risk (HR = 2.59, 95% CI = 2.26–2.97), compared with participants with the healthiest lifestyle and lowest BMI PGS. ConclusionsWhile the observational nature of the study precludes the establishment of causality, our study provides supports for a causal association between obesity and CAD risk and the importance of lifestyle modification in the prevention of CAD.

Gene-Environment Interplay in the Development of Overweight

PurposeOverweight in youth is influenced by genes and environment. Gene-environment interaction (G×E) has been demonstrated in twin studies and recent developments in genetics allow for studying G×E using individual genetic predispositions for overweight. We examine genetic influence on trajectories of overweight during adolescence and early adulthood and determine whether genetic predisposition is attenuated by higher socioeconomic status and having physically active parents. MethodsLatent class growth models of overweight were fitted using data from the TRacking Adolescents’ Individual Lives Survey (n = 2720). A polygenic score for body mass index (BMI) was derived using summary statistics from a genome-wide association study of adult BMI (N = ∼700,000) and tested as predictor of developmental pathways of overweight. Multinomial logistic regression models were used to examine effects of interactions of genetic predisposition with socioeconomic status and parental physical activity (n = 1675). ResultsA three-class model of developmental pathways of overweight fitted the data best (“non-overweight”, “adolescent-onset overweight”, and “persistent overweight”). The polygenic score for BMI and socioeconomic status distinguished the persistent overweight and adolescent-onset overweight trajectories from the non-overweight trajectory. Only genetic predisposition differentiated the adolescent-onset from the persistent overweight trajectory. There was no evidence for G×E. DiscussionHigher genetic predisposition increased the risk of developing overweight during adolescence and young adulthood and was associated with an earlier age at onset. We did not find that genetic predisposition was offset by higher socioeconomic status or having physically active parents. Instead, lower socioeconomic status and higher genetic predisposition acted as additive risk factors for developing overweight.

Polygenicity of Comorbid Depression in Multiple Sclerosis.

Depression is common in multiple sclerosis (MS); and is associated with faster disability progression. The etiology of comorbid depression in MS remains poorly understood. Identification of individuals with a high risk for depression, via polygenic scores (PGS), may facilitate earlier identification. Previous genetic studies of depression considered depression as a primary disorder, not a comorbidity, and thus findings may not generalize to MS. Body mass index (BMI) is a risk factor for both MS and depression and its association may highlight differences in depression in MS. To improve the understanding of comorbid depression in MS, we will investigate PGS in people with MS, with the hypothesis that higher depression PGS is associated with increased odds for comorbid depression in MS. Samples from three sources (Canada, UK Biobank, and the United States) were used. Individuals were grouped into cases (MS/comorbid depression) and compared to three control groups: MS/no depression, depression/no immune disease, and healthy persons. We employed three depression definitions: lifetime clinical diagnoses, self-reported diagnoses, and depressive symptoms. The PGS were tested in association with depression using regression. 106,682 individuals of European genetic ancestry were used: Canada (n=370; 213 with MS), UK Biobank (n=105,734; 1,390 MS), and USA (n=578 MS). Meta-analyses revealed individuals with MS and depression had a higher depression PGS compared to both MS without depression (odds ratio range per standard deviation [SD]: 1.29-1.38, P<0.05) and healthy controls (odds ratio range per SD: 1.49-1.53, P<0.025), regardless of the definition applied and when sex-stratified. The BMI PGS was associated with depressive symptoms (P≤.001). The depression PGS did not differ between depression occurring as a comorbid condition with MS or as the primary condition (odds ratio range per SD: 1.03-1.13, all P>0.05). Higher depression genetic burden was associated with ∼30-40% increased odds of depression in European genetic ancestry participants with MS compared to those without depression and was no different compared to those with depression and no comorbid immune disease. This study paves the way for further investigations into the possible use of PGS for assessing psychiatric disorder risk in MS and its application to non-European genetic ancestries.

Abstract 6504: Germline genetically predicted body mass index is associated with endometrial cancer somatic transcriptomic, immune, and mutational signatures in The Cancer Genome Atlas

Abstract High body mass index (BMI) is a causal risk factor for endometrial cancer but the molecular mechanisms underlying this association remain elusive. Here we sought to characterize the tumor genomic landscape of endometrial cancers that have developed on a germline genetic background of predisposition to elevated BMI. We built a polygenic score (PGS) for adult BMI in women using effect size estimates and allele information on 242 independent (r2&amp;lt;0.05) variants associated with BMI at genome-wide significance (P&amp;lt;5x10-9) in 379,501 women of European ancestry. We performed sample and germline (blood) genotype quality control and imputation into the 1000 Genomes reference panel on data from 354 endometrial cancer cases of genetically inferred European ancestry from The Cancer Genome Atlas (TCGA). We assigned each woman in this TCGA cohort her genetically predicted life-course BMI based on the BMI PGS and found this to be modestly correlated with BMI at the point of diagnosis (r2=0.23; P=2.1x10-5). Multivariable linear (default) and quasi-Poisson (for zero-inflated counts) regression models were used to test for associations between the BMI germline PGS and endometrial cancer tumor genomic, transcriptomic, proteomic, and immune traits in TCGA. All analyses were adjusted for age, stage, microsatellite status and 10 genetic principal components. Mutational signature models were also adjusted for signature accuracy. We ranked 18,458 genes based on the association between their tumor expression and the BMI PGS and performed gene set enrichment analysis to identify associations between the BMI PGS and upregulation of genes in the IL6-JAK-STAT3 signaling (false discovery rate (FDR)=8.50x10-7), inflammatory response (FDR=7.03x10-6), interferon gamma response (FDR=5.49x10-5) and glycolysis (FDR=3.28x10-4) pathways. High BMI PGS had an inverse association with endometrial tumor EGFR (FDR=0.07) protein levels of the 131 tumor proteins profiled by reverse phase protein array. Endometrial tumors that had developed on a germline background predictive of high BMI were also associated with increased infiltration of activated mast cells (FDR=9.55x10-3) in our evaluation of 22 tumor immune cell infiltrates quantified by the CIBERSORT algorithm, as well as the mitotic and aging clock-like single base substitution (SBS) signatures 1 (FDR=0.01) and 5 (FDR=0.04). The two SBS signature associations and the activated mast cell association with the BMI PGS were substantially more pronounced in the subgroup of endometrial cancers with microsatellite instability. Thus, we combined germline and somatic data using a novel approach to identify endometrial cancer tumor molecular features associated with genetically predicted higher BMI, providing precision multi-omic portraits of endometrial cancers that develop on a background of adiposity. Citation Format: George Richenberg, Victoria Gray, Carina Owen, Tom Gaunt, Caroline Relton, Emma Vincent, Siddhartha Kar. Germline genetically predicted body mass index is associated with endometrial cancer somatic transcriptomic, immune, and mutational signatures in The Cancer Genome Atlas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6504.

Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study

Evidence indicates that the adverse health effects of obesity differ between genetically and environmentally influenced obesity. We examined differences in the association between obesity and cardiovascular disease (CVD) between individuals with a genetically predicted low, medium, or high body mass index (BMI). We used cohort data from Swedish twins born before 1959 who had BMI measured between the ages of 40-64 years (midlife) or at the age of 65 years or later (late-life), or both, and prospective CVD information from nationwide register linkage through 2016. A polygenic score for BMI (PGSBMI) was used to define genetically predicted BMI. Individuals missing BMI or covariate data, or diagnosed with CVD at first BMI measure, were excluded, leaving an analysis sample of 17,988 individuals. We applied Cox proportional hazard models to examine the association between BMI category and incident CVD, stratified by the PGSBMI. Co-twin control models were applied to adjust for genetic influences not captured by the PGSBMI. Between 1984 and 2010, the 17,988 participants were enrolled in sub-studies of the Swedish Twin Registry. Midlife obesity was associated with a higher risk of CVD across all PGSBMI categories, but the association was stronger with genetically predicted lower BMI (hazard ratio from 1.55 to 2.08 for those with high and low PGSBMI, respectively). Within monozygotic twin pairs, the association did not differ by genetically predicted BMI, indicating genetic confounding not captured by the PGSBMI. Results were similar when obesity was measured in late-life, but suffered from low power. Obesity was associated with CVD regardless of PGSBMI category, but obesity influenced by genetic predisposition (genetically predicted high BMI) was less harmful than obesity influenced by environmental factors (obesity despite genetically predicted low BMI). However, additional genetic factors, not captured by the PGSBMI, still influence the associations. The Strategic Research Program in Epidemiology at Karolinska Institutet; Loo and Hans Osterman's Foundation; Foundation for Geriatric Diseases at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare; the Swedish Research Council; and the National Institutes of Health.

Abstract 12: Associations Between Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes: Million Veteran Program Study

Objective: Body mass index (BMI) is a commonly used estimate of obesity that is a complex multifactorial trait resulting from genetic and lifestyle factors. Weight gain and loss could correlate with adverse biological processes. Prior studies have reported that increased BMI variability predicts future adverse cardiovascular events. However, there have been no prior studies that have investigated this association in patients without cancer or preexisting cardiovascular disease among multiple ethnicities. Using the Million Veteran Program (MVP), a mega-biobank with longitudinal health record data from a large US healthcare system, we evaluated the association between BMI variability and incident cardiovascular events in an ethnically diverse longitudinal cohort (2011-2019). Methods: We studied 92,363 adults free of cardiovascular disease and cancer at baseline. BMI was longitudinally assessed from the baseline visit. BMI variability was assessed using the standard deviation (SD) and coefficient of variation (CV) of each participant. Cardiovascular disease (CVD) risk factors including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking status, diabetes status and statin use were assessed as covariates. We followed patients for the composite CVD events of incident non-fatal myocardial infarction, acute ischemic stroke, and cardiovascular death. Cox proportional hazards modeling was used to examine the association between BMI variability and incident CVD events after adjustment for dichotomous and continuous measures. We also assessed if results were affected sensitive to adjustment for the BMI polygenic score. Results: The cohort (88% men) included 60,180 non-Hispanic White (NHW), 22,488 non-Hispanic Black (NHB), and 9,695 Hispanic (HIS) participants with mean age 56.8 years. Patients were followed from 2011 to 2019. We observed 4,855 composite CVD events. The CV of BMI was associated with incident composite CVD across all groups, but to a stronger degree for Hispanic participants. Among the NHW, each SD increase of CV (indicative of greater BMI variability) was associated with a 15% rise in the risk of CVD events (i.e HR 1.15, 95%CI, 1.11-1.19 after adjustment of covariates. Among the NHB and HIS, results were similar: HR, 1.16 (95%CI, 1.09 - 1.22) and HR, 1.24 (95%CI, 1.12-1.38), respectively. In sensitivity analyses, we found that BMI variability is similarly predictive of the composite outcome after adjustment for BMI polygenic score. Conclusions and Relevance: Increased BMI variability is an independent risk factor for future CVD events.

Multivariate analyses of molecular genetic associations between childhood psychopathology and adult mood disorders and related traits.

Ubiquitous associations have been detected between different types of childhood psychopathology and polygenic risk scores based on adult psychiatric disorders and related adult outcomes, indicating that genetic factors partly explain the association between childhood psychopathology and adult outcomes. However, these analyses in general do not take into account the correlations between the adult trait and disorder polygenic risk scores. This study aimed to further clarify the influence of genetic factors on associations between childhood psychopathology and adult outcomes by accounting for these correlations. Using a multivariate multivariable regression, we analyzed associations of childhood attention-deficit/hyperactivity disorder (ADHD), internalizing, and social problems, with polygenic scores (PGS) of adult disorders and traits including major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI), derived for 20,539 children aged 8.5-10.5 years. After correcting for correlations between the adult phenotypes, major depression PGS were associated with all three childhood traits, that is, ADHD, internalizing, and social problems. In addition, BMI PGS were associated with ADHD symptoms and social problems, while neuroticism PGS were only associated with internalizing problems and educational attainment PGS were only associated with ADHD symptoms. PGS of bipolar disorder, subjective well-being, and insomnia were not associated with any childhood traits. Our findings suggest that associations between childhood psychopathology and adult traits like insomnia and subjective well-being may be primarily driven by genetic factors that influence adult major depression. Additionally, specific childhood phenotypes are genetically associated with educational attainment, BMI and neuroticism.

The impact of anorexia nervosa and BMI polygenic risk on childhood growth: A 20-year longitudinal population-based study

SummaryGrowth deviating from the norm during childhood has been associated with anorexia nervosa (AN) and obesity later in life. In this study, we examined whether polygenic scores (PGSs) for AN and BMI are associated with growth trajectories spanning the first two decades of life. AN PGSs and BMI PGSs were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 8,654). Using generalized (mixed) linear models, we associated PGSs with trajectories of weight, height, body mass index (BMI), fat mass index (FMI), lean mass index (LMI), and bone mineral density (BMD). Female participants with AN PGSs one standard deviation (SD) higher had, on average, 0.004% slower growth in BMI between the ages 6.5 and 24 years and a 0.4% slower gain in BMD between the ages 10 and 24 years. Higher BMI PGSs were associated with faster growth for BMI, FMI, LMI, BMD, and weight trajectories in both sexes throughout childhood. Female participants with both a high AN PGS and a low BMI PGS showed slower growth compared to those with both a low AN PGS and a low BMI PGS. We conclude that AN PGSs and BMI PGSs have detectable sex-specific effects on growth trajectories. Female participants with a high AN PGS and low BMI PGS likely constitute a high-risk group for AN, as their growth was slower compared to their peers with high PGSs on both traits. Further research is needed to better understand how the AN PGS and the BMI PGS co-influence growth during childhood and whether a high BMI PGS can mitigate the effects of a high AN PGS.

Can adult polygenic scores improve prediction of body mass index in childhood?

Modelling genetic pre-disposition may identify children at risk of obesity. However, most polygenic scores (PGSs) have been derived in adults, and lack validation during childhood. This study compared the utility of existing large-scale adult-derived PGSs to predict common anthropometric traits (body mass index (BMI), waist circumference, and body fat) in children and adults, and examined whether childhood BMI prediction could be improved by combining PGSs and non-genetic factors (maternal and earlier child BMI). Participants (n = 1365 children, and n = 2094 adults made up of their parents) were drawn from the Longitudinal Study of Australian Children. Children were weighed and measured every two years from 0-1 to 12-13 years, and adults were measured or self-reported measurements were obtained concurrently (average analysed). Participants were genotyped from blood or oral samples, and PGSs were derived based on published genome-wide association studies. We used linear regression to compare the relative utility of these PGSs to predict their respective traits at different ages. BMI PGSs explained up to 12% of child BMI z-score variance in 10-13 year olds, compared with up to 15% in adults. PGSs for waist circumference and body fat explained less variance (up to 8%). An interaction between BMI PGSs and puberty (p = 0.001-0.002) suggests the effect of some variants may differ across the life course. Individual BMI measures across childhood predicted 10-60% of the variance in BMI at 12-13 years, and maternal BMI and BMI PGS each added 1-9% above this. Adult-derived PGSs for BMI, particularly those derived by modelling between-variant interactions, may be useful for predicting BMI during adolescence with similar accuracy to that obtained in adulthood. The level of precision presented here to predict BMI during childhood may be relevant to public health, but is likely to be less useful for individual clinical purposes.

Polygenic association with severity and long-term outcome in eating disorder cases

About 20% of individuals with anorexia nervosa (AN) remain chronically ill. Therefore, early identification of poor outcome could improve care. Genetic research has identified regions of the genome associated with AN. Patients with anorexia nervosa were identified via the Swedish eating disorder quality registers Stepwise and Riksät and invited to participate in the Anorexia Nervosa Genetics Initiative. First, we associated genetic information longitudinally with eating disorder severity indexed by scores on the Clinical Impairment Assessment (CIA) in 2843 patients with lifetime AN with or without diagnostic migration to other forms of eating disorders followed for up to 16 years (mean = 5.3 years). Second, we indexed the development of a severe and enduring eating disorder (SEED) by a high CIA score plus a follow-up time ≥5 years. We associated individual polygenic scores (PGSs) indexing polygenic liability for AN, schizophrenia, and body mass index (BMI) with severity and SEED. After multiple testing correction, only the BMI PGS when calculated with traditional clumping and p value thresholding was robustly associated with disorder severity (βPGS = 1.30; 95% CI: 0.72, 1.88; p = 1.2 × 10–5) across all p value thresholds at which we generated the PGS. However, using the alternative PGS calculation method PRS-CS yielded inconsistent results for all PGS. The positive association stands in contrast to the negative genetic correlation between BMI and AN. Larger discovery GWASs to calculate PGS will increase power, and it is essential to increase sample sizes of the AN GWASs to generate clinically meaningful PGS as adjunct risk prediction variables. Nevertheless, this study provides the first evidence of potential clinical utility of PGSs for eating disorders.

The dynamic association between body mass index and cognition from midlife through late-life, and the effect of sex and genetic influences

Body mass index (BMI) is associated with cognitive abilities, but the nature of the relationship remains largely unexplored. We aimed to investigate the bidirectional relationship from midlife through late-life, while considering sex differences and genetic predisposition to higher BMI. We used data from 23,892 individuals of European ancestry from the Health and Retirement Study, with longitudinal data on BMI and three established cognitive indices: mental status, episodic memory, and their sum, called total cognition. To investigate the dynamic relationship between BMI and cognitive abilities, we applied dual change score models of change from age 50 through 89, with a breakpoint at age 65 or 70. Models were further stratified by sex and genetic predisposition to higher BMI using tertiles of a polygenic score for BMI (PGSBMI). We demonstrated bidirectional effects between BMI and all three cognitive indices, with higher BMI contributing to steeper decline in cognitive abilities in both midlife and late-life, and higher cognitive abilities contributing to less decline in BMI in late-life. The effects of BMI on change in cognitive abilities were more evident in men compared to women, and among those in the lowest tertile of the PGSBMI compared to those in the highest tertile, while the effects of cognition on BMI were similar across groups. In conclusion, these findings highlight a reciprocal relationship between BMI and cognitive abilities, indicating that the negative effects of a higher BMI persist from midlife through late-life, and that weight-loss in late-life may be driven by cognitive decline.

What your genes can (and can’t) tell you about BMI and diabetes

ABSTRACT Body mass index (BMI) is commonly used as a proxy for adiposity in epidemiological and public health studies. However, BMI may suffer from issues of misreporting and, because it fluctuates over the life course, its association with morbidities such as diabetes is difficult to measure. We examined the associations between actual BMI, genetic propensity for high BMI, and diabetes to better understand whether a BMI polygenic score (PGS) explained more variation in diabetes than self-reported BMI. We used a sample of non-Hispanic white adults from the longitudinal Health and Retirement Study (1992–2016). Structural equation models were used to determine how much variation in BMI could be explained by a BMI PGS. Then, we used logistic regression models (n = 12,086) to study prevalent diabetes at baseline and Cox regression models (n = 11,129) to examine incident diabetes with up to 24 years of follow-up. We observed that while both actual BMI and the BMI PGS were significantly associated with diabetes, actual BMI had a stronger association than its genetic counterpart and resulted in better model performance. Moreover, actual BMI explained more variation in baseline and incident diabetes than its genetic counterpart which may suggest that actual BMI captures more than just adiposity as intended.

Are there causal relationships between attention-deficit/hyperactivity disorder and body mass index? Evidence from multiple genetically informed designs.

Attention-deficit/hyperactivity disorder (ADHD) and body mass index (BMI) are associated. However, it remains unclear whether this association reflects causal relationships in either direction or confounding. Here, we implemented genetically informed methods to examine bidirectional causality and potential confounding. Three genetically informed methods were employed: (i) cross-lagged twin-differences analyses to assess bidirectional effects of ADHD symptoms and BMI at ages 8, 12, 14 and 16 years in 2386 pairs of monozygotic twins from the Twins Early Development Study (TEDS); (ii) within- and between-family ADHD and BMI polygenic score (PS) analyses in 3320 pairs of dizygotic TEDS twins; and (iii) two-sample bidirectional Mendelian randomization (MR) using summary statistics from genome-wide association studies (GWAS) on ADHD (N = 55,374) and BMI (N = 806,834). Mixed results were obtained across the three methods. Twin-difference analyses provided little support for cross-lagged associations between ADHD symptoms and BMI over time. PS analyses were consistent with bidirectional relationships between ADHD and BMI, with plausible time-varying effects from childhood to adolescence. MR findings also suggested bidirectional causal effects between ADHD and BMI. Multivariable MR indicated the presence of substantial confounding in bidirectional relationships. The three methods converged to highlight multiple sources of confounding in the association between ADHD and BMI. PS and MR analyses suggested plausible causal relationships in both directions. Possible explanations for mixed causal findings across methods are discussed.

Age-dependent effects of body mass index across the adult life span on the risk of dementia: a cohort study with a genetic approach

BackgroundWhile a high body mass index (BMI) in midlife is associated with higher risk of dementia, high BMI in late-life may be associated with lower risk. This study combined genetic designs with longitudinal data to achieve a better understanding of this paradox.MethodsWe used longitudinal data from 22,156 individuals in the Swedish Twin Registry (STR) and 25,698 from the Health and Retirement Study (HRS). The STR sample had information about BMI from early adulthood through late-life, and the HRS sample from age 50 through late-life. Survival analysis was applied to investigate age-specific associations between BMI and dementia risk. To examine if the associations are influenced by genetic susceptibility to higher BMI, an interaction between BMI and a polygenic score for BMI (PGSBMI) was included in the models and results stratified into those with genetic predisposition to low, medium, and higher BMI. In the STR, co-twin control models were applied to adjust for familial factors beyond those captured by the PGSBMI.ResultsAt age 35–49, 5 units higher BMI was associated with 15% (95% CI 7–24%) higher risk of dementia in the STR. There was a significant interaction (p = 0.04) between BMI and the PGSBMI, and the association present only among those with genetic predisposition to low BMI (HR 1.38, 95% CI 1.08–1.78). Co-twin control analyses indicated genetic influences. After age 80, 5 units higher BMI was associated with 10–11% lower risk of dementia in both samples. There was a significant interaction between late-life BMI and the PGSBMI in the STR (p = 0.01), but not the HRS, with the inverse association present only among those with a high PGSBMI (HR 0.70, 95% CI 0.52–0.94). No genetic influences were evident from co-twin control models of late-life BMI.ConclusionsNot only does the association between BMI and dementia differ depending on age at BMI measurement, but also the effect of genetic influences. In STR, the associations were only present among those with a BMI in opposite direction of their genetic predisposition, indicating that the association between BMI and dementia across the life course might be driven by environmental factors and hence likely modifiable.

Polygenic Score for Body Mass Index Is Associated with Disordered Eating in a General Population Cohort.

Background: Disordered eating (DE) is common and is associated with body mass index (BMI). We investigated whether genetic variants for BMI were associated with DE. Methods: BMI polygenic scores (PGS) were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8654) and their association with DE tested. Data on DE behaviors (e.g., binge eating and compensatory behaviors) were collected at ages 14, 16, 18 years, and DE cognitions (e.g., body dissatisfaction) at 14 years. Mediation analyses determined whether BMI mediated the association between the BMI-PGS and DE. Results: The BMI-PGS was positively associated with fasting (OR = 1.42, 95% CI = 1.25, 1.61), binge eating (OR = 1.28, 95% CI = 1.12, 1.46), purging (OR = 1.20, 95% CI = 1.02, 1.42), body dissatisfaction (Beta = 0.99, 95% CI = 0.77, 1.22), restrained eating (Beta = 0.14, 95% CI = 0.10, 1.17), emotional eating (Beta = 0.21, 95% CI = 0.052, 0.38), and negatively associated with thin ideal internalization (Beta = −0.15, 95% CI = −0.23, −0.07) and external eating (Beta = −0.19, 95% CI = −0.30, −0.09). These associations were mainly mediated by BMI. Conclusions: Genetic variants associated with BMI are also associated with DE. This association was mediated through BMI suggesting that weight potentially sits on the pathway from genetic liability to DE.

Genetic Associations Between Childhood Psychopathology and Adult Depression and Associated Traits in 42 998 Individuals

Adult mood disorders are often preceded by behavioral and emotional problems in childhood. It is yet unclear what explains the associations between childhood psychopathology and adult traits. To investigate whether genetic risk for adult mood disorders and associated traits is associated with childhood disorders. This meta-analysis examined data from 7 ongoing longitudinal birth and childhood cohorts from the UK, the Netherlands, Sweden, Norway, and Finland. Starting points of data collection ranged from July 1985 to April 2002. Participants were repeatedly assessed for childhood psychopathology from ages 6 to 17 years. Data analysis occurred from September 2017 to May 2019. Individual polygenic scores (PGS) were constructed in children based on genome-wide association studies of adult major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI). Regression meta-analyses were used to test associations between PGS and attention-deficit/hyperactivity disorder (ADHD) symptoms and internalizing and social problems measured repeatedly across childhood and adolescence and whether these associations depended on childhood phenotype, age, and rater. The sample included 42 998 participants aged 6 to 17 years. Male participants varied from 43.0% (1040 of 2417 participants) to 53.1% (2434 of 4583 participants) by age and across all cohorts. The PGS of adult major depression, neuroticism, BMI, and insomnia were positively associated with childhood psychopathology (β estimate range, 0.023-0.042 [95% CI, 0.017-0.049]), while associations with PGS of subjective well-being and educational attainment were negative (β, -0.026 to -0.046 [95% CI, -0.020 to -0.057]). There was no moderation of age, type of childhood phenotype, or rater with the associations. The exceptions were stronger associations between educational attainment PGS and ADHD compared with internalizing problems (Δβ, 0.0561 [Δ95% CI, 0.0318-0.0804]; ΔSE, 0.0124) and social problems (Δβ, 0.0528 [Δ95% CI, 0.0282-0.0775]; ΔSE, 0.0126), and between BMI PGS and ADHD and social problems (Δβ, -0.0001 [Δ95% CI, -0.0102 to 0.0100]; ΔSE, 0.0052), compared with internalizing problems (Δβ, -0.0310 [Δ95% CI, -0.0456 to -0.0164]; ΔSE, 0.0074). Furthermore, the association between educational attainment PGS and ADHD increased with age (Δβ, -0.0032 [Δ 95% CI, -0.0048 to -0.0017]; ΔSE, 0.0008). Results from this study suggest the existence of a set of genetic factors influencing a range of traits across the life span with stable associations present throughout childhood. Knowledge of underlying mechanisms may affect treatment and long-term outcomes of individuals with psychopathology.

A polygenic score for body mass index is associated with depressive symptoms via early life stress: Evidence for gene-environment correlation

Increasing childhood obesity rates are associated with not only adverse physical, but also mental health outcomes, including depression. These negative outcomes may be caused and/or exacerbated by the bullying and shaming overweight individuals experience. As body mass index (BMI) can be highly heritable, we hypothesized that a genetic risk for higher BMI, will predict higher early life stress (ELS), which in turn will predict higher depressive symptoms in adulthood. Such a process will reflect an evocative gene-environment correlation (rGE) wherein an individual's genetically influenced phenotype evokes a reaction from the environment that subsequently shapes the individual's health. We modeled genetic risk using a polygenic score of BMI derived from a recent large GWAS meta-analysis. Self-reports were used for the assessment of ELS and depressive symptoms in adulthood. The discovery sample consisted of 524 non-Hispanic Caucasian university students from the Duke Neurogenetics Study (DNS; 278 women, mean age 19.78 ± 1.23 years) and the independent replication sample consisted of 5930 white British individuals from the UK biobank (UKB; 3128 women, mean age 62.66 ± 7.38 years). A significant mediation effect was found in the DNS (indirect effect = 0.207, bootstrapped SE = .10, bootstrapped 95% CI: 0.014 to 0.421), and then replicated in the UKB (indirect effect = 0.04, bootstrapped SE = .01, bootstrapped 95% CI: 0.018 to 0.066). Higher BMI polygenic scores predicted higher ELS, which in turn predicted higher depressive symptoms. Our findings suggest that evocative rGE may contribute to weight-related mental health problems and stress the need for interventions that aim to reduce weight bias, specifically during childhood.