Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

GLP-1-directed NMDA receptor antagonism for obesity treatment

The N-methyl-D-aspartate (NMDA) receptor is a glutamate-activated cation channel that is critical to many processes in the brain. Genome-wide association studies suggest that glutamatergic neurotransmission and NMDA receptor-mediated synaptic plasticity are important for body weight homeostasis1. Here we report the engineering and preclinical development of a bimodal molecule that integrates NMDA receptor antagonism with glucagon-like peptide-1 (GLP-1) receptor agonism to effectively reverse obesity, hyperglycaemia and dyslipidaemia in rodent models of metabolic disease. GLP-1-directed delivery of the NMDA receptor antagonist MK-801 affects neuroplasticity in the hypothalamus and brainstem. Importantly, targeting of MK-801 to GLP-1 receptor-expressing brain regions circumvents adverse physiological and behavioural effects associated with MK-801 monotherapy. In summary, our approach demonstrates the feasibility of using peptide-mediated targeting to achieve cell-specific ionotropic receptor modulation and highlights the therapeutic potential of unimolecular mixed GLP-1 receptor agonism and NMDA receptor antagonism for safe and effective obesity treatment.

Socio-economic differences in body mass index: the contribution of genetic factors

BACKGROUND

Higher mean body mass index (BMI) among lower socioeconomic position (SEP) groups is well established in Western societies, but the influence of genetic factors on these differences is not well characterized.

METHODS

We analyzed these associations using Finnish health surveys conducted between 1992 and 2017 (N = 33 523; 53% women) with information on measured weight and height, polygenic risk scores of BMI (PGS-BMI) and linked data from administrative registers to measure educational attainment, occupation-based social class and personal income.

RESULTS

In linear regressions, largest adjusted BMI differences were found between basic and tertiary educated men (1.4 kg/m2, 95% confidence interval [CI] 1.2; 1.6) and women (2.5 kg/m2, 95% CI 2.3; 2.8), and inverse BMI gradients were also found for social class and income. These SEP differences arose partly because mean PGS-BMI was higher and partly because PGS-BMI predicted BMI more strongly in lower SEP groups. The inverse SEP gradients of BMI were steeper in women than in men, but sex differences were not found in the genetic contributions to these differences.

CONCLUSIONS

Better understanding of the interplay between genes and environment provides insight into the mechanisms explaining SEP differences in BMI.

GIP-derived GIP receptor antagonists - a review of their role in GIP receptor pharmacology

Surprisingly, agonists, as well as antagonists of the glucose-dependent insulinotropic polypeptide receptor (GIPR), are currently being used or investigated as treatment options for type 2 diabetes and obesity - and both, when combined with glucagon-like peptide 1 receptor (GLP-1R) agonism, enhance GLP-1-induced glycemia and weight loss further. This paradox raises several questions regarding not only the mechanisms of actions of GIP but also the processes engaged during the activation of both the GIP and GLP-1 receptors. Here, we provide an overview of studies of the properties and actions of peptide-derived GIPR antagonists, focusing on GIP(3-30)NH2, a naturally occurring N- and C-terminal truncation of GIP(1-42). GIP(3-30)NH2 was the first GIPR antagonist administered to humans. GIP(3-30)NH2 and a few additional antagonists, like Pro3-GIP, have been used in both in vitro and in vivo studies to elucidate the molecular and cellular consequences of GIPR inhibition, desensitization, and internalization and, at a larger scale, the role of the GIP system in health and disease. We provide an overview of these studies combined with recent knowledge regarding the effects of naturally occurring variants of the GIPR system and species differences within the GIP system to enhance our understanding of the GIPR as a drug target.

Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data

OBJECTIVE

This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data.

METHODS

We conducted a meta-analysis to leverage information from a genome-wide association study (n = 339 224), a transcriptome-wide association study (n = 5619), and an epigenome-wide association study (n = 3743). We prioritized the significant genes with a machine learning-based method, netWAS, which borrows information from adipose tissue-specific interaction networks. We also used the brain-specific network in netWAS to investigate genes potentially involved in brain-adipose interaction.

RESULTS

We identified 195 genes that were significantly associated with BMI through meta-analysis. The netWAS analysis narrowed down the list to 21 genes in adipose tissue. Among these 21 genes, six genes, including FUS, STX4, CCNT2, FUBP1, NDUFS3, and RAPSN, were not reported to be BMI-associated in PubMed or GWAS Catalog. We also identified 11 genes that were significantly associated with BMI in both adipose and whole brain tissues.

CONCLUSION

This study integrated three types of omics data and identified a group of genes that have not previously been reported to be associated with BMI. This strategy could provide new insights for future studies to identify molecular mechanisms contributing to BMI regulation.

Maternal dietary fat during lactation shapes single nucleus transcriptomic profile of postnatal offspring hypothalamus in a sexually dimorphic manner in mice

Maternal overnutrition during lactation predisposes offspring to develop metabolic diseases and exacerbates the relevant syndromes in males more than females in later life. The hypothalamus is a heterogenous brain region that regulates energy balance. Here we combined metabolic trait quantification of mother and offspring mice under low and high fat diet (HFD) feeding during lactation, with single nucleus transcriptomic profiling of their offspring hypothalamus at peak lacation to understand the cellular and molecular alterations in response to maternal dietary pertubation. We found significant expansion in neuronal subpopulations including histaminergic (Hdc), arginine vasopressin/retinoic acid receptor-related orphan receptor β (Avp/Rorb) and agouti-related peptide/neuropeptide Y (AgRP/Npy) in male offspring when their mothers were fed HFD, and increased Npy-astrocyte interactions in offspring responding to maternal overnutrition. Our study provides a comprehensive offspring hypothalamus map at the peak lactation and reveals how the cellular subpopulations respond to maternal dietary fat in a sex-specific manner during development.

GFRAL Is Widely Distributed in the Brain and Peripheral Tissues of Mice

In 2017, four independent publications described the glial cell-derived neurotrophic factor (GDNF) receptor alpha-like (GFRAL) as receptor for the growth differentiation factor 15 (GDF15, also MIC-1, NAG-1) with an expression exclusively in the mice brainstem area postrema (AP) and nucleus tractus solitarii (NTS) where it mediates effects of GDF15 on reduction of food intake and body weight. GDF15 is a cell stress cytokine with a widespread expression and pleiotropic effects, which both seem to be in contrast to the reported highly specialized localization of its receptor. This discrepancy prompts us to re-evaluate the expression pattern of GFRAL in the brain and peripheral tissues of mice. In this detailed immunohistochemical study, we provide evidence for a more widespread distribution of this receptor. Apart from the AP/NTS region, GFRAL-immunoreactivity was found in the prefrontal cortex, hippocampus, nucleus arcuatus and peripheral tissues including liver, small intestine, fat, kidney and muscle tissues. This widespread receptor expression, not taken into consideration so far, may explain the multiple effects of GDF-15 that are not yet assigned to GFRAL. Furthermore, our results could be relevant for the development of novel pharmacological therapies for physical and mental disorders related to body image and food intake, such as eating disorders, cachexia and obesity.

Neurodevelopmental Programming of Adiposity: Contributions to Obesity Risk

This review analyzes the published evidence regarding maternal factors that influence the developmental programming of long-term adiposity in humans and animals via the central nervous system (CNS). We describe the physiological outcomes of perinatal underfeeding and overfeeding and explore potential mechanisms that may mediate the impact of such exposures on the development of feeding circuits within the CNS-including the influences of metabolic hormones and epigenetic changes. The perinatal environment, reflective of maternal nutritional status, contributes to the programming of offspring adiposity. The in utero and early postnatal periods represent critically sensitive developmental windows during which the hormonal and metabolic milieu affects the maturation of the hypothalamus. Maternal hyperglycemia is associated with increased transfer of glucose to the fetus driving fetal hyperinsulinemia. Elevated fetal insulin causes increased adiposity and consequently higher fetal circulating leptin concentration. Mechanistic studies in animal models indicate important roles of leptin and insulin in central and peripheral programming of adiposity, and suggest that optimal concentrations of these hormones are critical during early life. Additionally, the environmental milieu during development may be conveyed to progeny through epigenetic marks and these can potentially be vertically transmitted to subsequent generations. Thus, nutritional and metabolic/endocrine signals during perinatal development can have lifelong (and possibly multigenerational) impacts on offspring body weight regulation.

Targeting postsynaptic glutamate receptor scaffolding proteins PSD-95 and PICK1 for obesity treatment

Human genome-wide association studies (GWAS) suggest a functional role for central glutamate receptor signaling and plasticity in body weight regulation. Here, we use UK Biobank GWAS summary statistics of body mass index (BMI) and body fat percentage (BF%) to identify genes encoding proteins known to interact with postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate (NMDA) receptors. Loci in/near discs large homolog 4 (DLG4) and protein interacting with C kinase 1 (PICK1) reached genome-wide significance (P < 5 × 10-8) for BF% and/or BMI. To further evaluate the functional role of postsynaptic density protein-95 (PSD-95; gene name: DLG4) and PICK1 in energy homeostasis, we used dimeric PSD-95/disc large/ZO-1 (PDZ) domain-targeting peptides of PSD-95 and PICK1 to demonstrate that pharmacological inhibition of PSD-95 and PICK1 induces prolonged weight-lowering effects in obese mice. Collectively, these data demonstrate that the glutamate receptor scaffolding proteins, PICK1 and PSD-95, are genetically linked to obesity and that pharmacological targeting of their PDZ domains represents a promising therapeutic avenue for sustained weight loss.

Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction

BACKGROUND

Genetic variants can contribute differently to trait heritability by their functional categories, and recent studies have shown that incorporating functional annotation can improve the predictive performance of polygenic risk scores (PRSs). In addition, when only a small proportion of variants are causal variants, PRS methods that employ a Bayesian framework with shrinkage can account for such sparsity. It is possible that the annotation group level effect is also sparse. However, the number of PRS methods that incorporate both annotation information and shrinkage on effect sizes is limited. We propose a PRS method, PRSbils, which utilizes the functional annotation information with a bilevel continuous shrinkage prior to accommodate the varying genetic architectures both on the variant-specific level and on the functional annotation level.

RESULTS

We conducted simulation studies and investigated the predictive performance in settings with different genetic architectures. Results indicated that when there was a relatively large variability of group-wise heritability contribution, the gain in prediction performance from the proposed method was on average 8.0% higher AUC compared to the benchmark method PRS-CS. The proposed method also yielded higher predictive performance compared to PRS-CS in settings with different overlapping patterns of annotation groups and obtained on average 6.4% higher AUC. We applied PRSbils to binary and quantitative traits in three real world data sources (the UK Biobank, the Michigan Genomics Initiative (MGI), and the Korean Genome and Epidemiology Study (KoGES)), and two sources of annotations: ANNOVAR, and pathway information from the Kyoto Encyclopedia of Genes and Genomes (KEGG), and demonstrated that the proposed method holds the potential for improving predictive performance by incorporating functional annotations.

CONCLUSIONS

By utilizing a bilevel shrinkage framework, PRSbils enables the incorporation of both overlapping and non-overlapping annotations into PRS construction to improve the performance of genetic risk prediction. The software is available at https://github.com/styvon/PRSbils .

3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity

The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes.

EPAC1 enhances brown fat growth and beige adipogenesis

Brown adipose tissue (BAT) is a central thermogenic organ that enhances energy expenditure and cardiometabolic health. However, regulators that specifically increase the number of thermogenic adipocytes are still an unmet need. Here, we show that the cAMP-binding protein EPAC1 is a central regulator of adaptive BAT growth. In vivo, selective pharmacological activation of EPAC1 increases BAT mass and browning of white fat, leading to higher energy expenditure and reduced diet-induced obesity. Mechanistically, EPAC1 coordinates a network of regulators for proliferation specifically in thermogenic adipocytes, but not in white adipocytes. We pinpoint the effects of EPAC1 to PDGFRα-positive preadipocytes, and the loss of EPAC1 in these cells impedes BAT growth and worsens diet-induced obesity. Importantly, EPAC1 activation enhances the proliferation and differentiation of human brown adipocytes and human brown fat organoids. Notably, a coding variant of RAPGEF3 (encoding EPAC1) that is positively correlated with body mass index abolishes noradrenaline-induced proliferation of brown adipocytes. Thus, EPAC1 might be an attractive target to enhance thermogenic adipocyte number and energy expenditure to combat metabolic diseases.

G protein-coupled receptors and obesity

G protein-coupled receptors (GPCRs) have emerged as important drug targets for various chronic diseases, including obesity and diabetes. Obesity is a complex chronic disease that requires long term management predisposing to type 2 diabetes, heart disease, and some cancers. The therapeutic landscape for GPCR as targets of anti-obesity medications has undergone significant changes with the approval of semaglutide, the first peptide glucagon like peptide 1 receptor agonist (GLP-1RA) achieving double digit weight loss (≥10%) and cardiovascular benefits. The enhanced weight loss, with the expected beneficial effect on obesity-related complications and reduction of major adverse cardiovascular events (MACE), has propelled the commercial opportunity for the obesity market leading to new players entering the space. Significant progress has been made on approaches targeting GPCRs such as single peptides that simultaneously activate GIP and/or GCGR in addition to GLP1, oral tablet formulation of GLP-1, small molecules nonpeptidic oral GLP1R and fixed-dose combination as well as add-on therapy for patients already treated with a GLP-1 agonist.

A scan of all coding region variants of the human genome, identifies 13q12.2-rs9579139 and 15q24.1-rs2277598 as novel risk loci for pancreatic ductal adenocarcinoma

Coding sequence variants comprise a small fraction of the germline genetic variability of the human genome. However, they often cause deleterious change in protein function and are therefore associated with pathogenic phenotypes. To identify novel pancreatic ductal adenocarcinoma (PDAC) risk loci, we carried out a complete scan of all common missense and synonymous SNPs and analysed them in a case-control study comprising four different populations, for a total of 14 538 PDAC cases and 190 657 controls. We observed a statistically significant association between 13q12.2-rs9581957-T and PDAC risk (P = 2.46 × 10-9), that is in linkage disequilibrium (LD) with a deleterious missense variant (rs9579139) of the URAD gene. Recent findings suggest that this gene is active in peroxisomes. Considering that peroxisomes have a key role as molecular scavengers, especially in eliminating reactive oxygen species, a malfunctioning URAD protein might expose the cell to a higher load of potentially DNA damaging molecules and therefore increase PDAC risk. The association was observed in individuals of European and Asian ethnicity. We also observed the association of the missense variant 15q24.1-rs2277598-T, that belongs to BBS4 gene, with increased PDAC risk (P = 1.53 × 10-6). rs2277598 is associated with body mass index and is in LD with diabetes susceptibility loci. In conclusion, we identified two missense variants associated with the risk of developing PDAC independently from the ethnicity highlighting the importance of conducting reanalysis of genome-wide association studies (GWASs) in light of functional data.

Understanding the consequences of leisure sedentary behavior on periodontitis: A two-step, multivariate Mendelian randomization study

Background

The relationship between leisure sedentary behavior (LSB) and periodontitis risk remains unclear in terms of causality and the potential mediating effects of intermediate factors.

Materials and methods

Using the aggregate data of several large-scale genetic association studies from participants of European descent, we conducted a univariate, two-step, and multivariate Mendelian random (MR) analysis to infer the overall effect of LSB on periodontitis, and quantified the intermediary proportion of intermediary traits such as smoking.

Results

Our findings indicated that per 1-SD increase (1.87 h) in leisure screen time (LST), there was a 23 % increase in the risk of periodontitis. [odds ratios (95 % CI) = 1.23 (1.04-1.44), p = 0.013]. Smoking was found to partially mediate the overall causal effect of LST on periodontitis, with a mediation rate of 20.7 % (95 % CI: 4.9%-35.5 %). Multivariate MR analysis demonstrated that the causal effect of LST on periodontitis was weakened when adjusting for smoking, resulting in an odds ratio of 1.19 (95 % CI: 1.01-1.39, p = 0.049) for each 1 standard deviation increase in exposure.

Conclusion

The study provides evidence of a potential causal relationship between LSB characterized by LST and periodontitis, thereby further supporting the notion that reducing LSB is beneficial for health. Furthermore, it confirms the role of smoking as a mediator in this process, suggesting that inhibiting smoking behavior among individuals with long-term LSB may serve as a strategy to mitigate the risk of periodontitis.

Spatiotemporal regulation of GIPR signaling impacts glucose homeostasis as revealed in studies of a common GIPR variant

OBJECTIVE

Glucose-dependent insulinotropic polypeptide (GIP) has a role in controlling postprandial metabolic tone. In humans, a GIP receptor (GIPR) variant (Q354, rs1800437) is associated with a lower body mass index (BMI) and increased risk for Type 2 Diabetes. To better understand the impacts of GIPR-Q354 on metabolism, it is necessary to study it in an isogeneic background to the predominant GIPR isoform, E354. To accomplish this objective, we used CRISPR-CAS9 editing to generate mouse models of GIPR-Q354 and GIPR-E354. Here we characterize the metabolic effects of GIPR-Q354 variant in a mouse model (GIPR-Q350).

METHODS

We generated the GIPR-Q350 mice for in vivo studies of metabolic impact of the variant. We isolated pancreatic islets from GIPR-Q350 mice to study insulin secretion ex vivo. We used a β-cell cell line to understand the impact of the GIPR-Q354 variant on the receptor traffic.

RESULTS

We found that female GIPR-Q350 mice are leaner than littermate controls, and male GIPR-Q350 mice are resistant to diet-induced obesity, in line with the association of the variant with reduced BMI in humans. GIPR-Q350 mice of both sexes are more glucose tolerant and exhibit an increased sensitivity to GIP. Postprandial GIP levels are reduced in GIPR-Q350 mice, revealing feedback regulation that balances the increased sensitivity of GIP target tissues to secretion of GIP from intestinal endocrine cells. The increased GIP sensitivity is recapitulated ex vivo during glucose stimulated insulin secretion assays in islets. Generation of cAMP in islets downstream of GIPR activation is not affected by the Q354 substitution. However, post-activation traffic of GIPR-Q354 variant in β-cells is altered, characterized by enhanced intracellular dwell time and increased localization to the Trans-Golgi Network (TGN).

CONCLUSIONS

Our data link altered intracellular traffic of the GIPR-Q354 variant with GIP control of metabolism. We propose that this change in spatiotemporal signaling underlies the physiologic effects of GIPR-Q350/4 and GIPR-E350/4 in mice and humans. These findings contribute to a more complete understanding of the impact of GIPR-Q354 variant on glucose homeostasis that could perhaps be leveraged to enhance pharmacologic targeting of GIPR for the treatment of metabolic disease.

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Characterizing the Shared Genetic Underpinnings of Schizophrenia and Cardiovascular Disease Risk Factors

OBJECTIVE

Schizophrenia is associated with increased risk of cardiovascular disease (CVD), although there is variation in risk among individuals. There are indications of shared genetic etiology between schizophrenia and CVD, but the nature of the overlap remains unclear. The aim of this study was to fill this gap in knowledge.

METHODS

Overlapping genetic architectures between schizophrenia and CVD risk factors were assessed by analyzing recent genome-wide association study (GWAS) results. The bivariate causal mixture model (MiXeR) was applied to estimate the number of shared variants and the conjunctional false discovery rate (conjFDR) approach was used to pinpoint specific shared loci.

RESULTS

Extensive genetic overlap was found between schizophrenia and CVD risk factors, particularly smoking initiation (N=8.6K variants) and body mass index (BMI) (N=8.1K variants). Several specific shared loci were detected between schizophrenia and BMI (N=304), waist-to-hip ratio (N=193), smoking initiation (N=293), systolic (N=294) and diastolic (N=259) blood pressure, type 2 diabetes (N=147), lipids (N=471), and coronary artery disease (N=35). The schizophrenia risk loci shared with smoking initiation had mainly concordant effect directions, and the risk loci shared with BMI had mainly opposite effect directions. The overlapping loci with lipids, blood pressure, waist-to-hip ratio, type 2 diabetes, and coronary artery disease had mixed effect directions. Functional analyses implicated mapped genes that are expressed in brain tissue and immune cells.

CONCLUSIONS

These findings indicate a genetic propensity to smoking and a reduced genetic risk of obesity among individuals with schizophrenia. The bidirectional effects of the shared loci with the other CVD risk factors may imply differences in genetic liability to CVD across schizophrenia subgroups, possibly underlying the variation in CVD comorbidity.

Genetics and epigenetics in the obesity phenotyping scenario

Obesity is a common complex trait that elevates the risk for various diseases, including type 2 diabetes and cardiovascular disease. A combination of environmental and genetic factors influences the pathogenesis of obesity. Advances in genomic technologies have driven the identification of multiple genetic loci associated with this disease, ranging from studying severe onset cases to investigating common multifactorial polygenic forms. Additionally, findings from epigenetic analyses of modifications to the genome that do not involve changes to the underlying DNA sequence have emerged as key signatures in the development of obesity. Such modifications can mediate the effects of environmental factors, including diet and lifestyle, on gene expression and clinical presentation. This review outlines what is known about the genetic and epigenetic contributors to obesity susceptibility, along with the albeit limited therapeutic options currently available. Furthermore, we delineate the potential mechanisms of actions through which epigenetic changes can mediate environmental influences and the related opportunities they present for future interventions in the management of obesity.

Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults

Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m2, with only 6% being obese (i.e. BMI ≥ 30 kg/m2). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m2). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.

A missense mutation in zinc finger homeobox-3 (ZFHX3) impedes growth and alters metabolism and hypothalamic gene expression in mice

A protein altering variant in the gene encoding zinc finger homeobox-3 (ZFHX3) has recently been associated with lower BMI in a human genome-wide association study. We investigated metabolic parameters in mice harboring a missense mutation in Zfhx3 (Zfhx3Sci/+ ) and looked for altered in situ expression of transcripts that are associated with energy balance in the hypothalamus to understand how ZFHX3 may influence growth and metabolic effects. One-year-old male and female Zfhx3Sci/+ mice weighed less, had shorter body length, lower fat mass, smaller mesenteric fat depots, and lower circulating insulin, leptin, and insulin-like growth factor-1 (IGF1) concentrations than Zfhx3+/+ littermates. In a second cohort of 9-20-week-old males and females, Zfhx3Sci/+ mice ate less than wildtype controls, in proportion to body weight. In a third cohort of female-only Zfhx3Sci/+ and Zfhx3+/+ mice that underwent metabolic phenotyping from 6 to 14 weeks old, Zfhx3Sci/+ mice weighed less and had lower lean mass and energy expenditure, but fat mass did not differ. We detected increased expression of somatostatin and decreased expression of growth hormone-releasing hormone and growth hormone-receptor mRNAs in the arcuate nucleus (ARC). Similarly, ARC expression of orexigenic neuropeptide Y was decreased and ventricular ependymal expression of orphan G protein-coupled receptor Gpr50 was decreased. We demonstrate for the first time an energy balance effect of the Zfhx3Sci mutation, likely by altering expression of key ARC neuropeptides to alter growth, food intake, and energy expenditure.

A transcriptomic and proteomic atlas of obesity and type 2 diabetes in cynomolgus monkeys

Obesity and type 2 diabetes (T2D) remain major global healthcare challenges, and developing therapeutics necessitates using nonhuman primate models. Here, we present a transcriptomic and proteomic atlas of all the major organs of cynomolgus monkeys with spontaneous obesity or T2D in comparison to healthy controls. Molecular changes occur predominantly in the adipose tissues of individuals with obesity, while extensive expression perturbations among T2D individuals are observed in many tissues such as the liver and kidney. Immune-response-related pathways are upregulated in obesity and T2D, whereas metabolism and mitochondrial pathways are downregulated. Moreover, we highlight some potential therapeutic targets, including SLC2A1 and PCSK1 in obesity as well as SLC30A8 and SLC2A2 in T2D. Our study provides a resource for exploring the complex molecular mechanism of obesity and T2D and developing therapies for these diseases, with limitations including lack of hypothalamus, isolated islets of Langerhans, longitudinal data, and body fat percentage.

WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E-7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E-14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women's Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.

Interactions Between Genetic Risk Score and Healthy Plant Diet Index on Cardiometabolic Risk Factors Among Obese and Overweight Women

People with higher genetic predisposition to obesity are more susceptible to cardiovascular diseases (CVDs) and healthy plant-based foods may be associated with reduced risks of obesity and other metabolic markers. We investigated whether healthy plant-foods-rich dietary patterns might have inverse associations with cardiometabolic risk factors in participants at genetically elevated risk of obesity. For this cross-sectional study, 377 obese and overweight women were chosen from health centers in Tehran, Iran. We calculated a healthy plant-based diet index (h-PDI) in which healthy plant foods received positive scores, and unhealthy plant and animal foods received reversed scores. A genetic risk score (GRS) was developed based on 3 polymorphisms. The interaction between GRS and h-PDI on cardiometabolic traits was analyzed using a generalized linear model (GLM). We found significant interactions between GRS and h-PDI on body mass index (BMI) (p = 0.02), body fat mass (p = 0.04), and waist circumference (p = 0.056). There were significant gene-diet interactions for healthful plant-derived diets and BMI-GRS on high-sensitivity C-reactive protein (p = 0.03), aspartate aminotransferase (p = 0.04), alanine transaminase (p = 0.05), insulin (p = 0.04), and plasminogen activator inhibitor 1 (p = 0.002). Adherence to h-PDI was more strongly related to decreased levels of the aforementioned markers among participants in the second or top tertile of GRS than those with low GRS. These results highlight that following a plant-based dietary pattern considering genetics appears to be a protective factor against the risks of cardiometabolic abnormalities.

Causes of obesity: a review

Obesity research is advancing swiftly, but the increase in obesity prevalence is faster. Over the past three decades, researchers have found that biopsychosocial factors determine weight gain much more than personal choices and responsibility. Various genes have found to predispose people to obesity by interacting with our obesogenic environment. In this review, we discuss the impact of physical inactivity, excessive caloric intake, intrauterine environment, postnatal influences, insufficient sleep, drugs, medical conditions, socioeconomic status, ethnicity, psychosocial stress, endocrine disrupting chemicals and the gastrointestinal microbiome, on the occurrence of obesity.

Identifying important gene signatures of BMI using network structure-aided nonparametric quantile regression

We focus on identifying genomics risk factors of higher body mass index (BMI) incorporating a priori information, such as biological pathways. However, the commonly used methods to incorporate prior information provide a model for the mean function of the outcome and rely on unmet assumptions. To address these concerns, we propose a method for nonparametric additive quantile regression with network regularization to incorporate the information encoded by known networks. To account for nonlinear associations, we approximate the unknown additive functional effect of each predictor with the expansion of a B-spline basis. We implement the group Lasso penalty to obtain a sparse model. We define the network-constrained penalty by the totalℓ 2 $$ {\ell}_2 $$ norm of the difference between the effect functions of any two linked genes in the known network. We further propose an efficient computation procedure to solve the optimization problem that arises in our model. Simulation studies show that our proposed method performs well in identifying more truly associated genes and less falsely associated genes than alternative approaches. We apply the proposed method to analyze the microarray gene-expression dataset in the Framingham Heart Study and identify several 75 percentile BMI associated genes. In conclusion, our proposed approach efficiently identifies the outcome-associated variables in a nonparametric additive quantile regression framework by leveraging known network information.

Longitudinal associations between specific types of emotional reactivity and psychological, physical health, and school adjustment

Using a multimethod, multiinformant longitudinal design, we examined associations between specific forms of positive and negative emotional reactivity at age 5, children's effortful control (EC), emotion regulation, and social skills at age 7, and adolescent functioning across psychological, academic, and physical health domains at ages 15/16 (N = 383). We examined how distinct components of childhood emotional reactivity directly and indirectly predict domain-specific forms of adolescent adjustment, thereby identifying developmental pathways between specific types of emotional reactivity and adjustment above and beyond the propensity to express other forms of emotional reactivity. Age 5 high-intensity positivity was associated with lower age 7 EC and more adolescent risk-taking; age 5 low-intensity positivity was associated with better age 7 EC and adolescent cardiovascular health, providing evidence for the heterogeneity of positive emotional reactivity. Indirect effects indicated that children's age 7 social skills partially explain several associations between age 5 fear and anger reactivity and adolescent adjustment. Moreover, age 5 anger reactivity, low-, and high-intensity positivity were associated with adolescent adjustment via age 7 EC. The findings from this interdisciplinary, long-term longitudinal study have significant implications for prevention and intervention work aiming to understand the role of emotional reactivity in the etiology of adjustment and psychopathology.

Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction

Background

Genetic variants can contribute differently to trait heritability by their functional categories, and recent studies have shown that incorporating functional annotation can improve the predictive performance of polygenic risk scores (PRSs). In addition, when only a small proportion of variants are causal variants, PRS methods that employ a Bayesian framework with shrinkage can account for such sparsity. It is possible that the annotation group level effect is also sparse. However, the number of PRS methods that incorporate both annotation information and shrinkage on effect sizes is limited. We propose a PRS method, PRSbils, which utilizes the functional annotation information with a bilevel continuous shrinkage prior to accommodate the varying genetic architectures both on the variant-specific level and on the functional annotation level.

Results

We conducted simulation studies and investigated the predictive performance in settings with different genetic architectures. Results indicated that when there was a relatively large variability of group-wise heritability contribution, the gain in prediction performance from the proposed method was on average 8.0% higher AUC compared to the benchmark method PRS-CS. The proposed method also yielded higher predictive performance compared to PRS-CS in settings with different overlapping patterns of annotation groups and obtained on average 6.4% higher AUC. We applied PRSbils to binary and quantitative traits in three real world data sources (the UK Biobank, the Michigan Genomics Initiative (MGI), and the Korean Genome and Epidemiology Study (KoGES)), and two sources of annotations: ANNOVAR, and pathway information from the Kyoto Encyclopedia of Genes and Genomes (KEGG), and demonstrated that the proposed method holds the potential for improving predictive performance by incorporating functional annotations.

Conclusions

By utilizing a bilevel shrinkage framework, PRSbils enables the incorporation of both overlapping and non-overlapping annotations into PRS construction to improve the performance of genetic risk prediction. The software is available at https://github.com/styvon/PRSbils.

Dominant neoantigen verification in hepatocellular carcinoma by a single-plasmid system coexpressing patient HLA and antigen

BACKGROUND

Previous studies confirmed that most neoantigens predicted by algorithms do not work in clinical practice, and experimental validations remain indispensable for confirming immunogenic neoantigens. In this study, we identified the potential neoantigens with tetramer staining, and established the Co-HA system, a single-plasmid system coexpressing patient human leukocyte antigen (HLA) and antigen, to detect the immunogenicity of neoantigens and verify new dominant hepatocellular carcinoma (HCC) neoantigens.

METHODS

First, we enrolled 14 patients with HCC for next-generation sequencing for variation calling and predicting potential neoantigens. Then, the Co-HA system was established. To test the feasibility of the system, we constructed target cells coexpressing HLA-A*11:01 and the reported KRAS G12D neoantigen as well as specific T-cell receptor (TCR)-T cells. The specific cytotoxicity generated by this neoantigen was shown using the Co-HA system. Moreover, potential HCC-dominant neoantigens were screened out by tetramer staining and validated by the Co-HA system using methods including flow cytometry, enzyme-linked immunospot assay and ELISA. Finally, antitumor test in mouse mode and TCR sequencing were performed to further evaluate the dominant neoantigen.

RESULTS

First, 2875 somatic mutations in 14 patients with HCC were identified. The main base substitutions were C>T/G>A transitions, and the main mutational signatures were 4, 1 and 16. The high-frequency mutated genes included HMCN1, TTN and TP53. Then, 541 potential neoantigens were predicted. Importantly, 19 of the 23 potential neoantigens in tumor tissues also existed in portal vein tumor thrombi. Moreover, 37 predicted neoantigens restricted by HLA-A*11:01, HLA-A*24:02 or HLA-A*02:01 were performed by tetramer staining to screen out potential HCC-dominant neoantigens. HLA-A*24:02-restricted epitope 5'-FYAFSCYYDL-3' and HLA-A*02:01-restricted epitope 5'-WVWCMSPTI-3' demonstrated strong immunogenicity in HCC, as verified by the Co-HA system. Finally, the antitumor efficacy of 5'-FYAFSCYYDL-3'-specific T cells was verified in the B-NDG-B2m^tm1Fcrn^tm1(mB2m) mouse and their specific TCRs were successfully identified.

CONCLUSION

We found the dominant neoantigens with high immunogenicity in HCC, which were verified with the Co-HA system.

Phenome-wide Mendelian randomization study evaluating the association of circulating vitamin D with complex diseases

Background

Circulating vitamin D has been associated with multiple clinical diseases in observational studies, but the association was inconsistent due to the presence of confounders. We conducted a bidirectional Mendelian randomization (MR) study to explore the healthy atlas of vitamin D in many clinical traits and evaluate their causal association.

Methods

Based on a large-scale genome-wide association study (GWAS), the single nucleotide polymorphism (SNPs) instruments of circulating 25-hydroxyvitamin D (25OHD) from 443,734 Europeans and the corresponding effects of 10 clinical diseases and 42 clinical traits in the European population were recruited to conduct a bidirectional two-sample Mendelian randomization study. Under the network of Mendelian randomization analysis, inverse-variance weighting (IVW), weighted median, weighted mode, and Mendelian randomization (MR)–Egger regression were performed to explore the causal effects and pleiotropy. Mendelian randomization pleiotropy RESidual Sum and Outlier (MR-PRESSO) was conducted to uncover and exclude pleiotropic SNPs.

Results

The results revealed that genetically decreased vitamin D was inversely related to the estimated BMD (β = −0.029 g/cm2, p = 0.027), TC (β = −0.269 mmol/L, p = 0.006), TG (β = −0.208 mmol/L, p = 0.002), and pulse pressure (β = −0.241 mmHg, p = 0.043), while positively associated with lymphocyte count (β = 0.037%, p = 0.015). The results did not reveal any causal association of vitamin D with clinical diseases. On the contrary, genetically protected CKD was significantly associated with increased vitamin D (β = 0.056, p = 2.361 × 10−26).

Conclusion

The putative causal effects of circulating vitamin D on estimated bone mass, plasma triglyceride, and total cholesterol were uncovered, but not on clinical diseases. Vitamin D may be linked to clinical disease by affecting health-related metabolic markers.

GWAS-Identified Variants for Obesity Do Not Influence the Risk of Developing Multiple Myeloma: A Population-Based Study and Meta-Analysis

Multiple myeloma (MM) is an incurable disease characterized by the presence of malignant plasma cells in the bone marrow that secrete specific monoclonal immunoglobulins into the blood. Obesity has been associated with the risk of developing solid and hematological cancers, but its role as a risk factor for MM needs to be further explored. Here, we evaluated whether 32 genome-wide association study (GWAS)-identified variants for obesity were associated with the risk of MM in 4189 German subjects from the German Multiple Myeloma Group (GMMG) cohort (2121 MM cases and 2068 controls) and 1293 Spanish subjects (206 MM cases and 1087 controls). Results were then validated through meta-analysis with data from the UKBiobank (554 MM cases and 402,714 controls) and FinnGen cohorts (914 MM cases and 248,695 controls). Finally, we evaluated the correlation of these single nucleotide polymorphisms (SNPs) with cQTL data, serum inflammatory proteins, steroid hormones, and absolute numbers of blood-derived cell populations (n = 520). The meta-analysis of the four European cohorts showed no effect of obesity-related variants on the risk of developing MM. We only found a very modest association of the POC5_rs2112347G and ADCY3_rs11676272G alleles with MM risk that did not remain significant after correction for multiple testing (per-allele OR = 1.08, p = 0.0083 and per-allele OR = 1.06, p = 0.046). No correlation between these SNPs and functional data was found, which confirms that obesity-related variants do not influence MM risk.

A unifying statistical framework to discover disease genes from GWASs

Genome-wide association studies (GWASs) identify genomic loci associated with complex traits, but it remains a challenge to identify the genes affected by causal genetic variants in these loci. Attempts to solve this challenge are frustrated by a number of compounding problems. Here, we show how to combine solutions to these problems into a unified mathematical framework. From this synthesis, it becomes possible to compute the probability that each gene in the genome is affected by a causal variant, given a particular trait, without making assumptions about the relevant cell types or tissues. We validate each component of the framework individually and in combination. When applied to large GWASs of human disease, the resulting paradigm can rediscover the majority of well-known disease genes. Moreover, it establishes human genetics support for many genes previously implicated only by clinical or preclinical evidence, and it uncovers a plethora of novel disease genes with compelling biological rationale.

Genetic regulation of body size and morphology in children: a twin study of 22 anthropometric traits

BACKGROUND

Anthropometric measures show high heritability, and genetic correlations have been found between obesity-related traits. However, we lack a comprehensive analysis of the genetic background of human body morphology using detailed anthropometric measures.

METHODS

Height, weight, 7 skinfold thicknesses, 7 body circumferences and 4 body diameters (skeletal breaths) were measured in 214 pairs of twin children aged 3-18 years (87 monozygotic pairs) in the Autonomous Region of Madeira, Portugal. Factor analysis (Varimax rotation) was used to analyze the underlying structure of body physique. Genetic twin modeling was used to estimate genetic and environmental contributions to the variation and co-variation of the anthropometric traits.

RESULTS

Together, two factors explained 80% of the variation of all 22 anthropometric traits in boys and 73% in girls. Obesity measures (body mass index, skinfold thickness measures, as well as waist and hip circumferences) and limb circumferences loaded most strongly on the first factor, whereas height and body diameters loaded especially on the second factor. These factors as well as all anthropometric measures showed high heritability (80% or more for most of the traits), whereas the rest of the variation was explained by environmental factors not shared by co-twins. Obesity measures showed high genetic correlations (0.75-0.98). Height showed the highest genetic correlations with body diameter measures (0.58-0.76). Correlations between environmental factors not shared by co-twins were weaker than the genetic correlations but still substantial. The correlation patterns were roughly similar in boys and girls.

CONCLUSIONS

Our results show high genetic correlations underlying the human body physique, suggesting that there are sets of genes widely affecting anthropometric traits. Better knowledge of these genetic variants can help to understand the development of obesity and other features of the human physique.

The metabolic profile of waist to hip ratio-A multi-cohort study

BACKGROUND

The genetic background of general obesity and fat distribution is different, pointing to separate underlying physiology. Here, we searched for metabolites and lipoprotein particles associated with fat distribution, measured as waist/hip ratio adjusted for fat mass (WHRadjfatmass), and general adiposity measured as percentage fat mass.

METHOD

The sex-stratified association of 791 metabolites detected by liquid chromatography-mass spectrometry (LC-MS) and 91 lipoprotein particles measured by nuclear magnetic spectroscopy (NMR) with WHRadjfatmass and fat mass were assessed using three population-based cohorts: EpiHealth (n = 2350) as discovery cohort, with PIVUS (n = 603) and POEM (n = 502) as replication cohorts.

RESULTS

Of the 193 LC-MS-metabolites being associated with WHRadjfatmass in EpiHealth (false discovery rate (FDR) <5%), 52 were replicated in a meta-analysis of PIVUS and POEM. Nine metabolites, including ceramides, sphingomyelins or glycerophosphatidylcholines, were inversely associated with WHRadjfatmass in both sexes. Two of the sphingomyelins (d18:2/24:1, d18:1/24:2 and d18:2/24:2) were not associated with fat mass (p>0.50). Out of 91, 82 lipoprotein particles were associated with WHRadjfatmass in EpiHealth and 42 were replicated. Fourteen of those were associated in both sexes and belonged to very-large or large HDL particles, all being inversely associated with both WHRadjfatmass and fat mass.

CONCLUSION

Two sphingomyelins were inversely linked to body fat distribution in both men and women without being associated with fat mass, while very-large and large HDL particles were inversely associated with both fat distribution and fat mass. If these metabolites represent a link between an impaired fat distribution and cardiometabolic diseases remains to be established.

2,4-Di-tert-butylphenol Induces Adipogenesis in Human Mesenchymal Stem Cells by Activating Retinoid X Receptors

2,4-Di-tert-butylphenol (2,4-DTBP) is an important commercial antioxidant and a toxic natural secondary metabolite that has been detected in humans. However, there is scant information regarding its toxicological effects. We asked whether 2,4-DTBP is a potential obesogen. Using a human mesenchymal stem cell adipogenesis assay, we found that exposure to 2,4-DTBP led to increased lipid accumulation and expression of adipogenic marker genes. Antagonist assays revealed that 2,4-DTBP increased lipid accumulation by activating the peroxisome proliferator-activated receptor (PPAR) γ-retinoid X receptor (RXR) heterodimer. 2,4-DTBP likely activated the PPARγ/RXRα heterodimer by activating RXRα but not directly binding to PPARγ. We confirmed that 2,4-DTBP directly bound to RXRα by solving the crystal structure of this complex, then predicted and demonstrated that related compounds could also activate RXRα. Our study demonstrated that 2,4-DTBP and related chemicals could act as obesogens and endocrine disruptors via RXRs. These data showed that 2,4-DTBP belongs to a family of compounds whose endocrine-disrupting and obesogenic effects can be strongly modulated by their chemical composition. Structure-activity studies such as the present one could help guide the rational development of safer antioxidants that do not interact with important nuclear receptors having broad effects on human development and physiology.

Gene expression associations with body mass index in the Multi-Ethnic Study of Atherosclerosis

BACKGROUND/OBJECTIVES

Obesity, defined as excessive fat accumulation that represents a health risk, is increasing in adults and children, reaching global epidemic proportions. Body mass index (BMI) correlates with body fat and future health risk, yet differs in prediction by fat distribution, across populations and by age. Nonetheless, few genetic studies of BMI have been conducted in ancestrally diverse populations. Gene expression association with BMI was assessed in the Multi-Ethnic Study of Atherosclerosis (MESA) in four self-identified race and ethnicity (SIRE) groups to identify genes associated with obesity.

SUBJECTS/METHODS

RNA-sequencing was performed on 1096 MESA participants (37.8% white, 24.3% Hispanic, 28.4% African American, and 9.5% Chinese American) and linear models were used to assess the association of expression from each gene for its effect on BMI, adjusting for age, sex, sequencing center, study site, five expression and four genetic principal components in each self-identified race group. Sample-size-weighted meta-analysis was performed to identify genes with BMI-associated expression across ancestry groups.

RESULTS

Within individual SIRE groups, there were zero to three genes whose expression is significantly (p < 1.97 × 10^-6) associated with BMI. Across all groups, 45 genes were identified by meta-analysis whose expression was significantly associated with BMI, explaining 29.7% of BMI variation. The 45 genes are expressed in a variety of tissues and cell types and are enriched for obesity-related processes including erythrocyte function, oxygen binding and transport, and JAK-STAT signaling.

CONCLUSIONS

We have identified genes whose expression is significantly associated with obesity in a multi-ethnic cohort. We have identified novel genes associated with BMI as well as confirmed previously identified genes from earlier genetic analyses. These novel genes and their biological pathways represent new targets for understanding the biology of obesity as well as new therapeutic intervention to reduce obesity and improve global public health.

Structural basis for transcription factor ZBTB7A recognition of DNA and effects of ZBTB7A somatic mutations that occur in human acute myeloid leukemia

ZBTB7A belongs to a small family of transcription factors having three members in humans (7A, 7B, and 7C). They share a BTB/POZ protein interaction domain at the amino end and a zinc-finger DNA-binding domain at the carboxyl end. They control the transcription of a wide range of genes, having varied functions in hematopoiesis, oncogenesis, and metabolism (in particular glycolysis). ZBTB7A-binding profiles at gene promoters contain a consensus G(a/c)CCC motif, followed by a CCCC sequence in some instances. Structural and mutational investigations suggest that DNA-specific contacts with the four-finger tandem array of ZBTB7A are formed sequentially, initiated from ZF1-ZF2 binding to G(a/c)CCC before spreading to ZF3-ZF4, which bind the DNA backbone and the 3' CCCC sequence, respectively. Here, we studied some mutations found in t(8;21)-positive acute myeloid leukemia patients that occur within the ZBTB7A DNA-binding domain. We determined that these mutations generally impair ZBTB7A DNA binding, with the most severe disruptions resulting from mutations in ZF1 and ZF2, and the least from a frameshift mutation in ZF3 that results in partial mislocalization. Information provided here on ZBTB7A-DNA interactions is likely applicable to ZBTB7B/C, which have overlapping functions with ZBTB7A in controlling primary metabolism.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Opposing effects of genetic variation in MTCH2 for obesity versus heart failure

Genetic variation in genes regulating metabolism may be advantageous in some settings but not others. The non-failing adult heart relies heavily on fatty acids as a fuel substrate and source of ATP. In contrast, the failing heart favors glucose as a fuel source. A bootstrap analysis for genes with deviant allele frequencies in cardiomyopathy cases versus controls identified the MTCH2 gene as having unusual variation. MTCH2 encodes an outer mitochondrial membrane protein, and prior genome-wide studies associated MTCH2 variants with body mass index, consistent with its role in metabolism. We identified the referent allele of rs1064608 (p.Pro290) as being overrepresented in cardiomyopathy cases compared to controls, and linkage disequilibrium analysis associated this variant with the MTCH2 cis eQTL rs10838738 and lower MTCH2 expression. To evaluate MTCH2, we knocked down Mtch in Drosophila heart tubes which produced a dilated and poorly functioning heart tube, reduced adiposity and shortened life span. Cardiac Mtch mutants generated more lactate at baseline, and they displayed impaired oxygen consumption in the presence of glucose but not palmitate. Treatment of cardiac Mtch mutants with dichloroacetate, a pyruvate dehydrogenase kinase inhibitor, reduced lactate and rescued lifespan. Deletion of MTCH2 in human cells similarly impaired oxygen consumption in the presence of glucose but not fatty acids. These data support a model in which MTCH2 reduction may be favorable when fatty acids are the major fuel source, favoring lean body mass. However, in settings like heart failure, where the heart shifts toward using more glucose, reduction of MTCH2 is maladaptive.

Plasma Protein Biomarkers of Healthy Dietary Patterns: Results from the Atherosclerosis Risk in Communities Study and the Framingham Heart Study

BACKGROUND

Molecular mechanisms underlying the benefits of healthy dietary patterns are poorly understood. Identifying protein biomarkers of dietary patterns can contribute to characterizing biological pathways influenced by food intake.

OBJECTIVES

This study aimed to identify protein biomarkers associated with four indexes of healthy dietary patterns: Healthy Eating Index-2015 (HEI-2015); Alternative Healthy Eating Index-2010 (AHEI-2010); DASH diet; and alternate Mediterranean Diet (aMED).

METHODS

Analyses were conducted on 10,490 Black and White men and women aged 49-73 y from the ARIC study at visit 3 (1993-1995). Dietary intake data were collected using a food frequency questionnaire, and plasma proteins were quantified using an aptamer-based proteomics assay. Multivariable linear regression models were used to examine the association between 4955 proteins and dietary patterns. We performed pathway overrepresentation analysis for diet-related proteins. An independent study population from the Framingham Heart Study was used for replication analyses.

RESULTS

In the multivariable-adjusted models, 282 out of 4955 proteins (5.7%) were significantly associated with at least one dietary pattern (HEI-2015: 137; AHEI-2010: 72; DASH: 254; aMED: 35; P value < 0.05/4955 = 1.01 × 10-5). There were 148 proteins that were associated with only one dietary pattern (HEI-2015: 22; AHEI-2010: 5; DASH: 121; aMED: 0), and 20 proteins were associated with all four dietary patterns. Five unique biological pathways were significantly enriched by diet-related proteins. Seven out of 20 proteins associated with all dietary patterns in the ARIC study were available for replication analyses, and 6 out of these 7 proteins were consistent in direction and significantly associated with at least 1 dietary pattern in the Framingham Heart Study (HEI-2015: 2; AHEI-2010: 4; DASH: 6; aMED: 4; P value < 0.05/7 = 7.14 × 10-3).

CONCLUSIONS

A large-scale proteomic analysis identified plasma protein biomarkers that are representative of healthy dietary patterns among middle-aged and older US adult population. These protein biomarkers may be useful objective indicators of healthy dietary patterns.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Beneficial effect of the short-chain fatty acid propionate on vascular calcification through intestinal microbiota remodelling

BACKGROUND

Vascular calcification is a major cause of the high morbidity and mortality of cardiovascular diseases and is closely associated with the intestinal microbiota. Short-chain fatty acids (SCFAs) are derived from the intestinal microbiota and can also regulate intestinal microbiota homeostasis. However, it remains unclear whether exogenous supplementation with propionate, a SCFA, can ameliorate vascular calcification by regulating the intestinal microbiota. This study was conducted to explore the roles of propionate and the intestinal microbiota in the process of vascular calcification.

METHODS

In total, 92 patients were enrolled consecutively as the observational cohort to analyse the relationship between SCFAs and vascular calcification in both blood and faecal samples. A rat model of vascular calcification was induced by vitamin D3 and nicotine (VDN) to validate the effect of propionate. Differences in the intestinal microbiota were analysed by 16S ribosomal RNA gene sequencing. Faecal microbiota transplantation and Akkermansia muciniphila transplantation experiments were performed to evaluate the functions of the intestinal microbiota.

RESULTS

The results of the observational cohort study revealed that the levels of SCFAs (particularly propionate) in both blood and faecal samples independently correlated negatively with calcification scores (P < 0.01). To verify the activities of propionate, it was provided to VDN-treated rats, and oral or rectal propionate delivery reshaped the intestinal microbiota, resulted in elevated SCFA production, improved intestinal barrier function and alleviated inflammation, ultimately ameliorating vascular calcification. Furthermore, we demonstrated that transplantation of the propionate-modulated intestinal microbiota induced beneficial outcomes similar to those with oral or rectal propionate administration. Interestingly, linear discriminant analysis (LDA) effect size (LEfSe) revealed that oral or rectal propionate administration and propionate-modulated intestinal microbiota transplantation both enriched primarily Akkermansia. Subsequently, we demonstrated that Akkermansia supplementation could ameliorate VDN-induced vascular calcification in rats.

CONCLUSIONS

Propionate can significantly ameliorate vascular calcification in VDN-treated rats, and this effect is mediated by intestinal microbiota remodelling. The findings in our study indicate that the intestinal tract-vessel axis is a promising target for alleviating vascular calcification. Video Abstract.

The relationship of genetic risk score with cardiometabolic risk factors: a cross-sectional study

Background & aims

For more than eight decades, cardiovascular disease (CVD) has remained the leading cause of death in the world. CVD risk factors are multifaceted, with genetics and lifestyle both playing a role. The aim of this study was to investigate the association between a genetic profile risk score for obesity GRS and cardio-metabolic risk factors in overweight and obese women.

Methods

The current cross-sectional study was conducted on 391 overweight and obese women. The genetic risk score was created by combining three single nucleotide polymorphisms [MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1 (rs2287161)]. Anthropometric measurements, blood pressure, and some blood parameters were measured by standard protocols.

Results

A significant association between the GRS and some of cardiometabolic risk factors variables such as body mass index (β = 0. 49, 95%CI = 0.22 to 0.76, p < 0.001), waist circumference (β = 0. 86, 95%CI = 0.18 to 1.54, p = 0.01), body fat mass (β = 0. 82, 95%CI = 0.25 to 1.39, p = 0.005), %body fat (β = 0. 44, 95%CI = 0.06 to 0.82, p = 0.02), and hs-CRP (β = 0.46, 95% CI = 0.14 to 0.78, p = 0.005) was observed in crude model. After adjustment for confounding factors (age, BMI, and physical activity), a significant positive association was observed between BMI (p = 0.004), WC (p = 0.02), body fat mass (p = 0.01), %BF (p = 0.01), hs-CRP (p = 0.009), and GRS. In addition, we discovered a significant negative association between the GRS and BMC (= -0.02, 95%CI = -0.05 to -0.001, p = 0.04). But other variables did not show any significant association with GRS among obese and overweight women.

Conclusion

We found a significant positive association between GRS, including MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1 (rs2287161) and cardiometabolic risk factors among overweight and obese Iranian women.

Obesity caused by an OVOL2 mutation reveals dual roles of OVOL2 in promoting thermogenesis and limiting white adipogenesis

Using random germline mutagenesis in mice, we identified a viable hypomorphic allele (boh) of the transcription-factor-encoding gene Ovol2 that resulted in obesity, which initially developed with normal food intake and physical activity but decreased energy expenditure. Fat weight was dramatically increased, while lean weight was reduced in 12-week-old boh homozygous mice, culminating by 24 weeks in massive obesity, hepatosteatosis, insulin resistance, and diabetes. The Ovol2boh/boh genotype augmented obesity in Lepob/ob mice, and pair-feeding failed to normalize obesity in Ovol2boh/boh mice. OVOL2-deficient mice were extremely cold intolerant. OVOL2 is essential for brown/beige adipose tissue-mediated thermogenesis. In white adipose tissues, OVOL2 limited adipogenesis by blocking C/EBPα engagement of its transcriptional targets. Overexpression of OVOL2 in adipocytes of mice fed with a high-fat diet reduced total body and liver fat and improved insulin sensitivity. Our data reveal that OVOL2 plays dual functions in thermogenesis and adipogenesis to maintain energy balance.