Publications

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA<PSNP & PMETA<PBMI) results for YPEL3 in nucleus accumbens and NT5C2, SNAPC3, TMEM245, YPEL3, and ZNF646 in liver. The identified genes help link the genetic variation at obesity risk loci to biological mechanisms and health outcomes, thus translating GWAS findings to function.

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Obesity is a major risk factor for a myriad of diseases, affecting >600 million people worldwide. Genome-wide association studies (GWASs) have identified hundreds of genetic variants that influence body mass index (BMI), a commonly used metric to assess obesity risk. Most variants are non-coding and likely act through regulating genes nearby. Here, we apply multiple computational methods to prioritize the likely causal gene(s) within each of the 536 previously reported GWAS-identified BMI-associated loci. We performed summary-data-based Mendelian randomization (SMR), FINEMAP, DEPICT, MAGMA, transcriptome-wide association studies (TWASs), mutation significance cutoff (MSC), polygenic priority score (PoPS), and the nearest gene strategy. Results of each method were weighted based on their success in identifying genes known to be implicated in obesity, ranking all prioritized genes according to a confidence score (minimum: 0; max: 28). We identified 292 high-scoring genes (≥11) in 264 loci, including genes known to play a role in body weight regulation (e.g., DGKI, ANKRD26, MC4R, LEPR, BDNF, GIPR, AKT3, KAT8, MTOR) and genes related to comorbidities (e.g., FGFR1, ISL1, TFAP2B, PARK2, TCF7L2, GSK3B). For most of the high-scoring genes, however, we found limited or no evidence for a role in obesity, including the top-scoring gene BPTF. Many of the top-scoring genes seem to act through a neuronal regulation of body weight, whereas others affect peripheral pathways, including circadian rhythm, insulin secretion, and glucose and carbohydrate homeostasis. The characterization of these likely causal genes can increase our understanding of the underlying biology and offer avenues to develop therapeutics for weight loss.

Thinness and anorexia nervosa are both characterised by persistent low weight. Individuals with anorexia nervosa concurrently report distorted perceptions of their body and engage in weight-loss behaviours, whereas individuals with thinness often wish to gain weight. Both conditions are heritable and share genomics with BMI, but are not genetically correlated with each other. Based on their pattern of genetic associations with other traits, we explored differences between thinness and anorexia nervosa on a genomic level. In Part 1, using publicly available data, we compared genetic correlations of persistent thinness/anorexia nervosa with eleven psychiatric disorders. In Part 2, we identified individuals with adolescent persistent thinness in the Avon Longitudinal Study of Parents and Children (ALSPAC) by latent class growth analysis of measured BMI from 10 to 24 years (n = 6594) and evaluated associations with psychiatric and anthropometric polygenic scores. In Part 1, in contrast to the positive genetic correlations of anorexia nervosa with various psychiatric disorders, persistent thinness showed negative genetic correlations with attention deficit hyperactivity disorder (rgAN = 0.08 vs. rgPT = -0.30), alcohol dependence (rgAN = 0.07 vs. rgPT = -0.44), major depressive disorder (rgAN = 0.27 vs. rgPT = -0.18) and post-traumatic stress disorder (rgAN = 0.26 vs. rgPT = -0.20). In Part 2, individuals with adolescent persistent thinness in the ALSPAC had lower borderline personality disorder polygenic scores (OR = 0.77; Q = 0.01). Overall, results suggest that genetic variants associated with thinness are negatively associated with psychiatric disorders and therefore thinness may be differentiable from anorexia nervosa on a genomic level.

BACKGROUND/OBJECTIVES: Obesity polygenic risk scores (PRS) explain substantial variation in body mass index (BMI), yet associations between PRSs and appetitive traits in children remain unclear. To better understand pathways leading to pediatric obesity, this study aimed to assess the association of obesity PRSs and appetitive traits.

SUBJECTS/METHODS: This study included 248 unrelated children aged 9-12 years. DNA from the children was genotyped (236 met quality control thresholds) and four weighted polygenic risk scores from previous studies were computed and standardized: a 97 SNP PRS, 266 SNP pediatric-specific PRS, 466 SNP adult-specific PRS, and  2 million SNP PRS. Appetitive traits were assessed using a parent-completed Child Eating Behavior Questionnaire, which evaluated food approach/avoidance traits and a composite obesogenic appetite score. BMI was directly measured and standardized by age and sex. Three associations were evaluated with linear regression: (1) appetitive traits and BMI, (2) PRSs and BMI, and (3) PRSs and appetitive traits, the primary association of interest.

RESULTS: Expected positive associations were observed between obesogenic appetitive traits and BMI and all four PRSs and BMI. Examining the association between PRSs and appetitive traits, all PRSs except for the 466 SNP adult PRS were significantly associated with the obesogenic appetite score. Each standard deviation increase in the 266 SNP pediatric PRS was associated with an adjusted 2.1% increase in obesogenic appetite score (95% CI: 0.6%, 3.7%, p = 0.006). Significant partial mediation of the PRS-BMI association by obesogenic appetite score was found for these PRSs; for example, 21.3% of the association between the 266 SNP pediatric PRS and BMI was explained by the obesogenic appetite score.

CONCLUSIONS: Genetic obesity risk significantly predicted appetitive traits, which partially mediated the association between genetic obesity risk and BMI in children. These findings build a clearer picture of pathways leading to pediatric obesity.

AIMS/HYPOTHESIS: Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.

METHODS: Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.

RESULTS: We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development.

CONCLUSIONS/INTERPRETATION: Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations.

DATA AVAILABILITY: The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https://github.com/Arthur1021/MESA-1K-PWAS ).

OBJECTIVE: To test associations of candidate obesity-related single nucleotide polymorphisms (SNPs) and obesity polygenic risk scores (PRS) with neural reward reactivity to food cues.

METHODS: After consuming a pre-load meal, 9-12-year-old children completed a functional magnetic resonance imaging (fMRI) paradigm with exposure to food and non-food commercials. Genetic exposures included FTO rs9939609, MC4R rs571312, and a pediatric-specific obesity PRS. A targeted region-of-interest (ROI) analysis for 7 bilateral reward regions and a whole-brain analysis were conducted. Independent associations between each genetic factor and reward responsivity to food cues in each ROI were evaluated using linear models.

RESULTS: Analyses included 151 children (M = 10.9 years). Each FTO rs9939609 obesity risk allele was related to a higher food-cue-related response in the right lateral hypothalamus after controlling for covariates including the current BMI Z-score (p < 0.01), however, the association did not remain significant after applying the multiple testing correction. MC4R rs571312 and the PRS were not related to heightened food-cue-related reward responsivity in any examined regions. The whole-brain analysis did not identify additional regions of food-cue-related response related to the examined genetic factors.

CONCLUSION: Children genetically at risk for obesity, as indicated by the FTO genotype, may be predisposed to higher food-cue-related reward responsivity in the lateral hypothalamus in the sated state, which, in turn, could contribute to overconsumption.

CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT03766191, identifier NCT03766191.

The discovery of exercise-regulated circulatory factors has fueled interest in organ crosstalk, especially between skeletal muscle and adipose tissue, and the role in mediating beneficial effects of exercise. We studied the adipose tissue transcriptome in men and women with normal glucose tolerance or type 2 diabetes following an acute exercise bout, revealing substantial exercise- and time-dependent changes, with sustained increase in inflammatory genes in type 2 diabetes. We identify oncostatin-M as one of the most upregulated adipose-tissue-secreted factors post-exercise. In cultured human adipocytes, oncostatin-M enhances MAPK signaling and regulates lipolysis. Oncostatin-M expression arises predominantly from adipose tissue immune cell fractions, while the corresponding receptors are expressed in adipocytes. Oncostatin-M expression increases in cultured human Thp1 macrophages following exercise-like stimuli. Our results suggest that immune cells, via secreted factors such as oncostatin-M, mediate a crosstalk between skeletal muscle and adipose tissue during exercise to regulate adipocyte metabolism and adaptation.

Diet is a key lifestyle component that influences metabolic health through several factors, including total energy intake and macronutrient composition. While the impact of caloric intake on gene expression and physiological phenomena in various tissues is well described, the influence of dietary macronutrient composition on these parameters is less well studied. Here, we use the Nutritional Geometry framework to investigate the role of macronutrient composition on metabolic function and gene regulation in adipose tissue. Using ten isocaloric diets that vary systematically in their proportion of energy from fat, protein, and carbohydrates, we find that gene expression and splicing are highly responsive to macronutrient composition, with distinct sets of genes regulated by different macronutrient interactions. Specifically, the expression of many genes associated with Bardet-Biedl syndrome is responsive to dietary fat content. Splicing and expression changes occur in largely separate gene sets, highlighting distinct mechanisms by which dietary composition influences the transcriptome and emphasizing the importance of considering splicing changes to more fully capture the gene regulation response to environmental changes such as diet. Our study provides insight into the gene regulation plasticity of adipose tissue in response to macronutrient composition, beyond the already well-characterized response to caloric intake.

Nutrient composition in obesogenic diets may influence the severity of disorders associated with obesity such as insulin-resistance and chronic inflammation. Here we hypothesized that obesogenic diets rich in fat and varying in fatty acid composition, particularly in omega 6 (ω6) to omega 3 (ω3) ratio, have various effects on energy metabolism, neuroinflammation and behavior. Mice were fed either a control diet or a high fat diet (HFD) containing either low (LO), medium (ME) or high (HI) ω6/ω3 ratio. Mice from the HFD-LO group consumed less calories and exhibited less body weight gain compared to other HFD groups. Both HFD-ME and HFD-HI impaired glucose metabolism while HFD-LO partly prevented insulin intolerance and was associated with normal leptin levels despite higher subcutaneous and perigonadal adiposity. Only HFD-HI increased anxiety and impaired spatial memory, together with increased inflammation in the hypothalamus and hippocampus. Our results show that impaired glucose metabolism and neuroinflammation are uncoupled, and support that diets with a high ω6/ω3 ratio are associated with neuroinflammation and the behavioral deterioration coupled with the consumption of diets rich in fat.