BMI-associated Variants Research Articles

Genetic modifiers of body mass index in individuals with cystic fibrosis

To identify modifier loci underlying variation in body mass index (BMI) in persons with cystic fibrosis (pwCF), we performed a genome-wide association study (GWAS). Utilizing longitudinal height and weight data, along with demographic information and covariates from 4,393 pwCF, we calculated AvgBMIz representing the average of per-quarter BMI Z scores. The GWAS incorporated 9.8M single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF)>0.005 extracted from whole-genome sequencing (WGS) of each study subject. We observed genome-wide significant association with a variant in FTO (FaT mass and Obesity-associated gene; rs28567725; p value= 1.21e-08; MAF= 0.41, β= 0.106; n= 4,393 individuals) and a variant within ADAMTS5 (A Disintegrin And Metalloproteinase with ThromboSpondin motifs 5; rs162500; p value= 2.11e-10; MAF= 0.005, β= -0.768; n= 4,085 pancreatic-insufficient individuals). Notably, BMI-associated variants in ADAMTS5 occur on a haplotype that is much more common in African (AFR, MAF= 0.183) than European (EUR, MAF= 0.006) populations (1000 Genomes project). A polygenic risk score (PRS) calculated using 924 SNPs (excluding 17 in FTO) showed significant association with AvgBMIz (p value= 2.2e-16; r2= 0.03). Association between variants in FTO and the PRS correlation reveals similarities in the genetic architecture of BMI in CF and the general population. Inclusion of Black individuals in whom the single-gene disorder CF is much less common but genomic diversity is greater facilitated detection of association with variants that are in LD with functional SNPs in ADAMTS5. Our results illustrate the importance of population diversity, particularly when attempting to identify variants that manifest only under certain physiologic conditions.

SORBS1 expression as a biomarker for obesity and breast cancer prognosis: Insights from genomic analysis and survival outcomes.

e13050 Background: Obesity is a known risk factor for breast cancer development and poorer survival. Correlation between the expression of the adaptor protein SORBS1 (Sorbin and SH3 domain-containing protein 1) and body mass index (BMI). Methods: Bioinformatics analysis. Results: We analyzed published datasets and plotted SORBS1 expression against patient BMI. Our findings show a negative correlation between SORBS1 expression and BMI in both datasets (R = -0.42, p = 0.00087, and R = -0.45 p = 0.00083, respectively). We also observed a negative correlation between SORBS1 expression and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) (R = -0.43, p = 0.00016). Additionally, we examined BMI-associated variants of the SORBS1 gene in the Qatar Biobank cohort of 15k individuals. We identified a total of 26 variants that were associated with an elevated risk for BMI in this population at a nominal significance. The top risk variant associated with the BMI is a missense variant (rs35480352; beta=0.058, p-value = 3.3e-03) with a frequency of 9.1% for the risk allele in our population. These results suggest that SORBS1 expression decreases with obesity and diabetes. This is significant because obesity is a known risk factor for breast cancer development and poorer survival. We also examined the SORBS1 gene expression in breast adenocarcinoma using UCSC TOIL RNA-seq recompute and TCGA-BRCA genomic and methylation data. Out of the 963 patients analyzed, only 12 (1.2%) showed any SORBS1 gene alteration, such as mutation (0.7%), amplification (0.2%), or deep deletion (0.3%), indicating a low occurrence of genomic alterations. Furthermore, our findings revealed no significant difference in SORBS1 methylation levels between the tumor and matched normal samples, indicating that the SORBS1 gene is not hypermethylated in breast carcinoma. Interestingly, our comparison of SORBS1 expression values between tumor and normal samples indicated significant under-expression in BRCA (log2FC = -2.7, p = 1.07E-127). SORBS1 expression was found to vary across various clinical stages (p = 0.0082, Kruskal-Wallis rank test), exhibiting a decline in advanced cancer stages. Moreover, we detected a significant difference in SORBS1 expression among different molecular subtypes (p < 2E-16, Kruskal-Wallis rank test), with a lower expression level in more aggressive subtypes like HER2. Patients were classified into two groups according to their SORBS1 expression levels, using the median expression as a threshold: high and low. Conclusions: Our findings showed that the SORBS1 low group had substantially lower overall survival (log-rank p = 0.0024) and progression-free survival rates (log-rank p = 0.028). Silencing of SORBS1 in MCF-7 and MDA-MB-231 cells increased cell proliferation, migration, and invasion, underscoring its importance in breast cancer prognosis and as a target for intervention.

Genetic Effect on Body Mass Index and Cardiovascular Disease Across Generations.

Whether genetics contribute to the rising prevalence of obesity or its cardiovascular consequences in today's obesogenic environment remains unclear. We sought to determine whether the effects of a higher aggregate genetic burden of obesity risk on body mass index (BMI) or cardiovascular disease (CVD) differed by birth year. We split the FHS (Framingham Heart Study) into 4 equally sized birth cohorts (birth year before 1932, 1932 to 1946, 1947 to 1959, and after 1960). We modeled a genetic predisposition to obesity using an additive genetic risk score (GRS) of 941 BMI-associated variants and tested for GRS-birth year interaction on log-BMI (outcome) when participants were around 50 years old (N=7693). We repeated the analysis using a GRS of 109 BMI-associated variants that increased CVD risk factors (type 2 diabetes, blood pressure, total cholesterol, and high-density lipoprotein) in addition to BMI. We then evaluated whether the effects of the BMI GRSs on CVD risk differed by birth cohort when participants were around 60 years old (N=5493). Compared with participants born before 1932 (mean age, 50.8 yrs [2.4]), those born after 1960 (mean age, 43.3 years [4.5]) had higher BMI (median, 25.4 [23.3-28.0] kg/m2 versus 26.9 [interquartile range, 23.7-30.6] kg/m2). The effect of the 941-variant BMI GRS on BMI and CVD risk was stronger in people who were born in later years (GRS-birth year interaction: P=0.0007 and P=0.04 respectively). The significant GRS-birth year interactions indicate that common genetic variants have larger effects on middle-age BMI and CVD risk in people born more recently. These findings suggest that the increasingly obesogenic environment may amplify the impact of genetics on the risk of obesity and possibly its cardiovascular consequences.

Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes

Body mass index (BMI) is a complex disease risk factor known to be influenced by genes acting via both metabolic pathways and appetite regulation. In this study, we aimed to gain insight into the phenotypic consequences of BMI-associated genetic variants, which may be mediated by their expression in different tissues. First, we harnessed meta-analyzed gene expression datasets derived from subcutaneous adipose (n = 1257) and brain (n = 1194) tissue to identify 86 and 140 loci, respectively, which provided evidence of genetic colocalization with BMI. These two sets of tissue-partitioned loci had differential effects with respect to waist-to-hip ratio, suggesting that the way they influence fat distribution might vary despite their having very similar average magnitudes of effect on BMI itself (adipose = 0.0148 and brain = 0.0149 standard deviation change in BMI per effect allele). For instance, BMI-associated variants colocalized with TBX15 expression in adipose tissue (posterior probability [PPA] = 0.97), but not when we used TBX15 expression data derived from brain tissue (PPA = 0.04) This gene putatively influences BMI via its role in skeletal development. Conversely, there were loci where BMI-associated variants provided evidence of colocalization with gene expression in brain tissue (e.g., NEGR1, PPA = 0.93), but not when we used data derived from adipose tissue, suggesting that these genes might be more likely to influence BMI via energy balance. Leveraging these tissue-partitioned variant sets through a multivariable Mendelian randomization framework provided strong evidence that the brain-tissue-derived variants are predominantly responsible for driving the genetically predicted effects of BMI on cardiovascular-disease endpoints (e.g., coronary artery disease: odds ratio = 1.05, 95% confidence interval = 1.04-1.07, p= 4.67× 10-14). In contrast, our analyses suggested that the adipose tissue variants might predominantly be responsible for the underlying relationship between BMI and measures of cardiac function, such as left ventricular stroke volume (beta = 0.21, 95% confidence interval = 0.09-0.32, p = 6.43× 10-4).

Non-linear interaction between physical activity and polygenic risk score of body mass index in Danish and Russian populations

Body mass index (BMI) is a highly heritable polygenic trait. It is also affected by various environmental and behavioral risk factors. We used a BMI polygenic risk score (PRS) to study the interplay between the genetic and environmental factors defining BMI. First, we generated a BMI PRS that explained more variance than a BMI genetic risk score (GRS), which was using only genome-wide significant BMI-associated variants (R2 = 13.1% compared to 6.1%). Second, we analyzed interactions between BMI PRS and seven environmental factors. We found a significant interaction between physical activity and BMI PRS, even when the well-known effect of the FTO region was excluded from the PRS, using a small dataset of 6,179 samples. Third, we stratified the study population into two risk groups using BMI PRS. The top 22% of the studied populations were included in a high PRS risk group. Engagement in self-reported physical activity was associated with a 1.66 kg/m2 decrease in BMI in this group, compared to a 0.84 kg/m2 decrease in BMI in the rest of the population. Our results (i) confirm that genetic background strongly affects adult BMI in the general population, (ii) show a non-linear interaction between BMI genetics and physical activity, and (iii) provide a standardized framework for future gene-environment interaction analyses.

Genetic Interactions with Intrauterine Diabetes Exposure in Relation to Obesity: The EPOCH and Project Viva Studies.

To examine whether BMI-associated genetic risk variants modify the association of intrauterine diabetes exposure with childhood BMI z-scores, we assessed the interaction between 95 BMI-associated genetic variants and in utero exposure to maternal diabetes among 459 children in the Exploring Perinatal Outcomes among Children historical prospective cohort study (n = 86 exposed; 373 unexposed) in relation to age- and sex-standardized childhood BMI z-scores (mean age = 10.3 years, standard deviation = 1.5 years). For the genetic variants showing a nominally significant interaction, we assessed the relationship in an additional 621 children in Project Viva, which is an independent longitudinal cohort study, and used meta-analysis to combine the results for the two studies. Seven of the ninety-five genetic variants tested exhibited a nominally significant interaction with in utero exposure to maternal diabetes in relation to the offspring BMI z-score in EPOCH. Five of the seven variants exhibited a consistent direction of interaction effect across both EPOCH and Project Viva. While none achieved statistical significance in the meta-analysis after accounting for multiple testing, three variants exhibited a nominally significant interaction with in utero exposure to maternal diabetes in relation to offspring BMI z-score: rs10733682 near LMX1B (interaction β = 0.39; standard error (SE) = 0.17), rs17001654 near SCARB2 (β = 0.53; SE = 0.22), and rs16951275 near MAP2K5 (β = 0.37; SE = 0.17). BMI-associated genetic variants may enhance the association between exposure to in utero diabetes and higher childhood BMI, but larger studies of in utero exposures are necessary to confirm the observed nominally significant relationships.

A Mendelian randomization study identified obesity as a causal risk factor of uterine endometrial cancer in Japanese.

Causal inference is one of the challenges in epidemiologic studies. Gynecologic diseases have been reported to have association with obesity, however the causality remained controversial except for uterine endometrial cancer. We conducted two‐sample Mendelian randomization (MR) analysis using the large‐scale genome‐wide association study (GWAS) results of gynecologic diseases and body mass index (BMI) in the Japanese population to assess causal effect of BMI on gynecologic diseases. We first conducted GWAS of ovarian cancer, uterine endometrial cancer, uterine cervical cancer, endometriosis, and uterine fibroid (n = 647, 909, 538, 5236, and 645 cases, respectively, and 39 556 shared female controls), and BMI (81 610 males and non‐overlapping 23 924 females). We then applied two‐sample MR using 74 BMI‐associated variants as instrumental variables. We observed significant causal effect of increased BMI on uterine endometrial cancer (β = 0.735, P = .0010 in inverse variance‐weighted analysis), which is concordant with results of European studies. Causal effect of obesity was not apparent in the other gynecologic diseases tested. Our MR analyses provided strong evidence of the causal role of obesity in gynecologic diseases etiology, and suggested a possible preventive effect of intervention for obesity.

Discovery and Mediation Analysis of Cross-Phenotype Associations Between Asthma and Body Mass Index in 12q13.2

Twin studies suggest that shared genetics contributes to the comorbidity of asthma and obesity, but candidate-gene studies provide limited evidence of pleiotropy. We conducted genome-wide association analyses of asthma and body mass index (BMI; weight (kg)/height (m)2)) among 305,945 White British subjects recruited into the UK Biobank in 2006-2010. We searched for overlapping signals and conducted mediation analyses on genome-wide-significant cross-phenotype associations, assessing moderation by sex and age at asthma diagnosis, and adjusting for confounders of the asthma-BMI relationship. We identified a genome-wide-significant cross-phenotype association at rs705708 (asthma odds ratio=1.05, 95% confidence interval: 1.03, 1.07; P=7.20× 10-9; and BMI β =-0.065, 95% confidence interval: -0.087, -0.042; P=1.30× 10-8). rs705708 resides on 12q13.2, which harbors 9 other asthma- and BMI-associated variants (all P<5× 10-5 for asthma; all but one P<5× 10-5 for BMI). Follow-up analyses of rs705708 show that most of the BMI association occurred independently of asthma, with consistent magnitude between men and women and persons with and without asthma, irrespective of age at diagnosis; the asthma association was stronger for childhood versus adult asthma; and both associations remained after confounder adjustment. This suggests that 12q13.2 displays pleiotropy for asthma and BMI. Upon further characterization, 12q13.2 might provide a target for interventions that simultaneously prevent or treat asthma and obesity.

Mendelian randomisation study of height and body mass index as modifiers of ovarian cancer risk in 22,588 BRCA1 and BRCA2 mutation carriers

BackgroundHeight and body mass index (BMI) are associated with higher ovarian cancer risk in the general population, but whether such associations exist among BRCA1/2 mutation carriers is unknown.MethodsWe applied a Mendelian randomisation approach to examine height/BMI with ovarian cancer risk using the Consortium of Investigators for the Modifiers of BRCA1/2 (CIMBA) data set, comprising 14,676 BRCA1 and 7912 BRCA2 mutation carriers, with 2923 ovarian cancer cases. We created a height genetic score (height-GS) using 586 height-associated variants and a BMI genetic score (BMI-GS) using 93 BMI-associated variants. Associations were assessed using weighted Cox models.ResultsObserved height was not associated with ovarian cancer risk (hazard ratio [HR]: 1.07 per 10-cm increase in height, 95% confidence interval [CI]: 0.94–1.23). Height-GS showed similar results (HR = 1.02, 95% CI: 0.85–1.23). Higher BMI was significantly associated with increased risk in premenopausal women with HR = 1.25 (95% CI: 1.06–1.48) and HR = 1.59 (95% CI: 1.08–2.33) per 5-kg/m2 increase in observed and genetically determined BMI, respectively. No association was found for postmenopausal women. Interaction between menopausal status and BMI was significant (Pinteraction < 0.05).ConclusionOur observation of a positive association between BMI and ovarian cancer risk in premenopausal BRCA1/2 mutation carriers is consistent with findings in the general population.

Variants in BMI-Associated Genes and Adrenergic Genes are not Associated with Gestational Weight Trajectory.

The aim of this study is to define the association between a genetic risk score (GRS) that combined the effect of multiple BMI-associated variants and gestational weight trajectory. Because pregnancy is a state of sympathetic activation, the association between gestational weight trajectory and variants in adrenergic pathways previously associated with weight was examined. In a previously defined cohort of pregnant women with (n = 1,504) and without gestational diabetes (GDM) (n = 435), weight trajectory was calculated using all weights during pregnancy. A GRS for BMI (GRSBMI ) was calculated using 31 common variants associated with BMI, and 10 variants in the adrenergic pathways were genotyped. Clinical and genetic factors were studied using generalized linear models. Prepregnancy BMI was associated with the GRSBMI (P = 9.3 × 10-11 ) and parity (P = 4.54 × 10-17 ). The GRSBMI was associated with gestational weight trajectory in women with and without GDM (P = 0.041 and P < 0.0001, respectively); however, when prepregnancy BMI was included in the models, the associations disappeared (P > 0.05). Variants in adrenergic genes were not associated with gestational weight trajectory. A GRS for BMI was associated with prepregnancy BMI but was not independently associated with gestational weight trajectory in women with and without GDM. Selected variants in adrenergic genes were not associated with gestational weight trajectory.

Diet quality and genetic association with body mass index: results from 3 observational studies

It is unknown whether dietary quality modifies genetic association with body mass index (BMI). This study examined whether dietary quality modifies genetic association with BMI. We calculated 3 diet quality scores including the Alternative Healthy Eating Index 2010 (AHEI-2010), the Alternative Mediterranean Diet score (AMED), and the Dietary Approach to Stop Hypertension (DASH) diet score. We examined the interactions of a genetic risk score (GRS) based on 97 BMI-associated variants with the 3 diet quality scores on BMI in 30,904 participants from 3 large cohorts. We found significant interactions between total GRS and all 3 diet scores on BMI assessed after 2-3 y, with an attenuated genetic effect observed in individuals with healthier diets (AHEI: P-interaction=0.003; AMED: P=0.001; DASH: P=0.004). For example, the difference in BMI (kg/m2) per 10-unit increment of the GRS was smaller among participants in the highest tertile of AHEI score compared with those in the lowest tertile (0.84; 95% CI: 0.72, 0.96 compared with 1.14; 95% CI: 0.99, 1.29). Results were consistent across the 3 cohorts with no significant heterogeneity. The interactions with diet scores on BMI appeared more significant for central nervous system GRSs (P<0.01 for 3 diet scores) than for non-central nervous system GRSs (P>0.05 for 3 diet scores). A higher diet quality attenuated genetic predisposition to obesity. These findings underscore the importance of maintaining a healthful diet for the prevention of obesity, particularly for those individuals with a strong genetic predisposition to obesity. This trial was registered with the Clinical Trial Registry as NCT03577639.

Evidence for gene-environment correlation in child feeding: Links between common genetic variation for BMI in children and parental feeding practices.

The parental feeding practices (PFPs) of excessive restriction of food intake (‘restriction’) and pressure to increase food consumption (‘pressure’) have been argued to causally influence child weight in opposite directions (high restriction causing overweight; high pressure causing underweight). However child weight could also ‘elicit’ PFPs. A novel approach is to investigate gene-environment correlation between child genetic influences on BMI and PFPs. Genome-wide polygenic scores (GPS) combining BMI-associated variants were created for 10,346 children (including 3,320 DZ twin pairs) from the Twins Early Development Study using results from an independent genome-wide association study meta-analysis. Parental ‘restriction’ and ‘pressure’ were assessed using the Child Feeding Questionnaire. Child BMI standard deviation scores (BMI-SDS) were calculated from children’s height and weight at age 10. Linear regression and fixed family effect models were used to test between- (n = 4,445 individuals) and within-family (n = 2,164 DZ pairs) associations between the GPS and PFPs. In addition, we performed multivariate twin analyses (n = 4,375 twin pairs) to estimate the heritabilities of PFPs and the genetic correlations between BMI-SDS and PFPs. The GPS was correlated with BMI-SDS (β = 0.20, p = 2.41x10-38). Consistent with the gene-environment correlation hypothesis, child BMI GPS was positively associated with ‘restriction’ (β = 0.05, p = 4.19x10-4), and negatively associated with ‘pressure’ (β = -0.08, p = 2.70x10-7). These results remained consistent after controlling for parental BMI, and after controlling for overall family contributions (within-family analyses). Heritabilities for ‘restriction’ (43% [40–47%]) and ‘pressure’ (54% [50–59%]) were moderate-to-high. Twin-based genetic correlations were moderate and positive between BMI-SDS and ‘restriction’ (rA = 0.28 [0.23–0.32]), and substantial and negative between BMI-SDS and ‘pressure’ (rA = -0.48 [-0.52 - -0.44]. Results suggest that the degree to which parents limit or encourage children’s food intake is partly influenced by children’s genetic predispositions to higher or lower BMI. These findings point to an evocative gene-environment correlation in which heritable characteristics in the child elicit parental feeding behaviour.

Height and Body Mass Index as Modifiers of Breast Cancer Risk in BRCA1/2 Mutation Carriers: A Mendelian Randomization Study.

BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear. We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided. Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer. Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.

A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci.

Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.

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.

Abstract P095: Diet Quality and Genetic Association With Body Mass Index

Background: Whether dietary quality modifies genetic association with body mass index (BMI) is unknown. Methods: We examined the interactions prospectively of a genetic risk score (GRS) based on 97 BMI-associated variants with three diet quality scores (alternative healthy eating index 2010 (AHEI-2010), Alternative Mediterranean Diet score (AMED) and Dietary Approach to Stop Hypertension (DASH) diet score) on BMI in 30,904 participants from three large US cohorts. According to the enrichment of genes near the BMI-associated loci in the central nervous system (CNS), we further created two subsets of GRSs: CNS GRS based on 54 variants and non-CNS GRS based on 43 variants. Findings: We found significant interactions between total GRS and all three diet scores on BMI assessed after 2 to 3 years, with an attenuated genetic effect observed in individuals with healthier diets (AHEI: P for interaction = 0.003; AMED: P = 0.001; DASH: P = 0.004). For example, the difference in BMI per 10 unit increment of the GRS was smaller among participants in the highest tertile of AHEI score compared to those in the lowest tertile (0.84 [95% CI: 0.72, 0.96] vs. 1.14 [0.99, 1.29] kg/m 2 ). Results were consistent across the three cohorts with no significant heterogeneity. The interactions with diet scores on BMI appeared more significant for CNS GRS (AHEI: P = 0.009; AMED and DASH: P &lt; 0.001) than for non-CNS GRS (AHEI: P = 0.10; AMED: P = 0.50; DASH: P = 0.68). Among individual components of diet scores, higher consumption of red/processed meat, sugar-sweetened beverages, and trans fat accentuated genetic associations with BMI (P &lt;0.01), while higher consumption of fruit and moderate alcohol attenuated genetic associations with BMI (P &lt; 0.01). Interpretation: A higher diet quality may mitigate genetic predisposition to obesity. These findings provide insights into complex interplays between diet and genetic influences and underscore the importance of adopting a healthful diet for the prevention of obesity, particularly those individuals with a strong genetic predisposition to obesity.

Molecular Profiling of Human Induced Pluripotent Stem Cell-Derived Hypothalamic Neurones Provides Developmental Insights into Genetic Loci for Body Weight Regulation.

Recent data suggest that common genetic risks for metabolic disorders such as obesity may be human-specific and exert effects via the central nervous system. To overcome the limitation of human tissue access for study, we have generated induced human pluripotent stem cell (hiPSC)-derived neuronal cultures that recapture many features of hypothalamic neurones within the arcuate nucleus. In the present study, we have comprehensively characterised this model across development, benchmarked these neurones to invivo events, and demonstrate a link between obesity risk variants and hypothalamic development. The dynamic transcriptome across neuronal maturation was examined using microarray and RNA sequencing methods at nine time points. K-means clustering of the longitudinal data was conducted to identify co-regulation and microRNA control of biological processes. The transcriptomes were compared with those of 103 samples from 13 brain regions reported in the Genotype-Tissue Expression database (GTEx) using principal components analysis. Genes with proximity to body mass index (BMI)-associated genetic variants were mapped to the developmentally expressed genesets, and enrichment significance was assessed with Fisher's exact test. The human neuronal cultures have a transcriptional and physiological profile of neuropeptide Y/agouti-related peptide arcuate nucleus neurones. The neuronal transcriptomes were highly correlated with adult hypothalamus compared to any other brain region from the GTEx. Also, approximately 25% of the transcripts showed substantial changes in expression across neuronal development and potential co-regulation of biological processes that mirror neuronal development invivo. These developmentally expressed genes were significantly enriched for genes in proximity to BMI-associated variants. We confirmed the utility of this invitro human model for studying the development of key hypothalamic neurones involved in energy balance and show that genes at loci associated with body weight regulation may share a pattern of developmental regulation. These data support the need to investigate early development to elucidate the human-specific central nervous system pathophysiology underlying obesity susceptibility.

Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.

We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing (WGS) data. We demonstrate using simulations based on WGS data that ~97% and ~68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ~17M imputed variants explain 56% (s.e. = 2.3%) of variance for height and 27% (s.e. = 2.5%) for body mass index (BMI), and find evidence that height- and BMI-associated variants have been under natural selection. Considering imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60–70% for height and 30–40% for BMI. Therefore, missing heritability is small for both traits. For further gene discovery of complex traits, a design with SNP arrays followed by imputation is more cost-effective than WGS at current prices.

Association of genetic predisposition to obesity with type 2 diabetes risk in Han Chinese individuals.

Obesity is a major risk factor for type 2 diabetes, but little is known about the contribution of BMI-associated loci to type 2 diabetes risk in East Asian populations. In this study, 30 known BMI-associated variants and a genetic risk score (GRS) calculated by summing the BMI-increasing alleles of these variants were tested for associations with type 2 diabetes and related glycaemic traits in 1,873 cases of type 2 diabetes and 1,839 controls in Han Chinese individuals. Logistic and linear regression analyses were performed to determine the association with type 2 diabetes risk or related glycaemic traits, respectively, under an additive model with or without adjustment for BMI. The GRS was significantly associated with increased BMI (β [SE] 0.070 [0.016]; p = 1.33 × 0(-5)) in the overall population. Each additional BMI-increasing allele in the GRS increased type 2 diabetes risk by 1.029-fold (95% CI 1.008, 1.050; p = 0.0056) without adjustment for BMI, and the association was slightly attenuated after adjustment for BMI (OR 1.022; 95% CI 1.002, 1.043; p = 0.035). In non-diabetic controls, the GRS was also associated with HOMA of beta cell function (HOMA-B) with adjustment for BMI (β [SE] -0.876 [0.345]; p = 0.011). Notably, the association of GRS with type 2 diabetes was abolished after adjusting for HOMA-B (OR 1.012; 95% CI 0.986, 1.039; p = 0.380). Our results suggested that genetic predisposition to obesity leads to increased risk of type 2 diabetes, independent of BMI and partly through impaired beta cell function.

Abstract 04: Fried Food Consumption and Genetic Predisposition to Obesity

Background: Fried food consumption has been associated with obesity; little is known about whether genetic background modifies this association. Methods: We analyzed interactions between a genetic risk score (GRS) based on 32 BMI-associated variants and fried food consumption on body mass index (BMI) and obesity in 9623 women from the Nurses’ Health Study (NHS) and 6379 men from the Health Professionals Follow-up Study (HPFS) and in a replication cohort of 21426 women from the Women’s Genome Health Study (WGHS). Results: An interaction between fried food consumption and the GRS on BMI was identified in both NHS and HPFS (P for interaction≤0.001). Among participants in the highest tertile of the GRS, the differences in BMI between individuals who consumed fried foods ≥4times/week and those consumed &lt;1time/week amounted to 1.0 in women and 0.7 kg/m2 in men, whereas the corresponding differences were 0.5 and 0.4 kg/m2 in the lowest tertile of the GRS. The gene-diet interaction was replicated in the WGHS (P for interaction&lt;0.001). Viewed differently, the genetic association with adiposity was strengthened with higher consumption of fried foods. In the combined three cohorts, the differences in BMI per 10 risk alleles were 1.2, 1.6, and 2.4 kg/m2 for fried food consumption&lt;1, 1-3 and ≥4times/week (P for interaction&lt;0.001) (Figure); and the odds ratios (95% CI) for obesity per 10 risk alleles were 1.60 (1.38-1.84), 2.13 (1.74-2.60) and 2.65 (2.08-3.39) across the three categories of consumption (P for interaction=0.002). In addition, we found that the individual variants in genes highly expressed or known to act in the central nervous system showed significant interactions, with the FTO variant showing the strongest result (P for interaction&lt;0.001). Conclusion: Fried food consumption may interact with genetic background in relation to obesity, highlighting the particular importance of reducing fried food consumption in individuals genetically predisposed to obesity.