Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

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.

Mendelian randomization on the association of obesity with vitamin D: Guangzhou Biobank Cohort Study

BACKGROUND

Mendelian randomization (MR) analyses from the West provide evidence that obesity causes lower 25-hydroxyvitamin D [25(OH)D]. As Asian populations are prone to metabolic disorders at a lower body mass index (BMI), whether the association remains in Asian is unclear. We studied whether obesity causes vitamin D deficiency using MR analysis in Chinese.

METHODS

We used data from the Guangzhou Biobank Cohort Study. A genetic score including seven BMI-related single-nucleotide polymorphisms (n = 15,249) was used as the instrumental variable (IV) for BMI. Two-stage least square regression and conventional multivariable linear regression in 2,036 participants with vitamin D data were used to analyze association of BMI with vitamin D.

RESULTS

Proportion of variation explained by the genetic score was 0.7% and the first stage F-statistic for MR analysis was 103. MR analyses showed that each 1 kg/m² higher BMI was associated with lower 25(OH)D by -2.35 (95% confidence interval (CI) -4.68 to -0.02) nmol/L. In conventional multivariable linear regression, higher BMI was also associated with lower 25(OH)D (β = -0.26 nmol/L per 1 kg/m² increase in BMI, 95% CI -0.46 to -0.06). Sensitivity analyses using two-sample IV analysis and leave-one-out method showed similar results.

CONCLUSION

We have first shown by MR and conventional multivariable linear regression that higher BMI causes vitamin D deficiency in Chinese. Our findings highlight the importance of weight control and suggest that vitamin D supplementation may be needed in individuals with overweight or obesity.

Inversions maintain differences between migratory phenotypes of a songbird

Structural rearrangements have been shown to be important in local adaptation and speciation, but have been difficult to reliably identify and characterize in non-model species. Here we combine long reads, linked reads and optical mapping to characterize three divergent chromosome regions in the willow warbler Phylloscopus trochilus, of which two are associated with differences in migration and one with an environmental gradient. We show that there are inversions (0.4-13 Mb) in each of the regions and that the divergence times between inverted and non-inverted haplotypes are similar across the regions (~1.2 Myrs), which is compatible with a scenario where inversions arose in either of two allopatric populations that subsequently hybridized. The improved genomes allow us to detect additional functional differences in the divergent regions, providing candidate genes for migration and adaptations to environmental gradients.

Association of common genetic variants with body mass index in Russian population

BACKGROUND

Overweight is the scourge of modern society and a major risk factor for many diseases. For this reason, understanding the genetic component predisposing to high body mass index (BMI) seems to be an important task along with preventive measures aimed at improving eating behavior and increasing physical activity.

METHODS

We analyzed genetic data of a European cohort (n = 21,080, 47.25% women, East Slavs ancestry >80%) for 5 frequently found genes in the context of association with obesity: IPX3 (rs3751723), MC4R (rs17782313), TMEM18 (rs6548238), PPARG (rs1801282) and FTO (rs9939609).

RESULTS

Our study revealed significant associations of FTO (rs9939609) (β = 0.37 (kg/m²)/allele, p = <2 × 10^-16), MC4R (rs17782313) (β = 0.28 (kg/m²)/allele, p = 5.79 × 10^-9), TMEM18 (rs6548238) (β = 0.29 (kg/m²)/allele, p = 2.43 × 10^-8) with BMI and risk of obesity.

CONCLUSIONS

The results confirm the contribution of FTO, M4CR, and TMEM18 genes to the mechanism of body weight regulation and control.

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.

Genetic heterogeneity in cardiovascular disease across ancestries: Insights for mechanisms and therapeutic intervention

Cardiovascular diseases (CVDs) are complex in their aetiology, arising due to a combination of genetics, lifestyle and environmental factors. By nature of this complexity, different CVDs vary in their molecular mechanisms, clinical presentation and progression. Although extensive efforts are being made to develop novel therapeutics for CVDs, genetic heterogeneity is often overlooked in the development process. By considering molecular mechanisms at an individual and ancestral level, a richer understanding of the influence of environmental and lifestyle factors can be gained and more refined therapeutic interventions can be developed. It is therefore expedient to understand the molecular and clinical heterogeneity in CVDs that exists across different populations. In this review, we highlight how the mechanisms underlying CVDs vary across diverse population ancestry groups due to genetic heterogeneity. We then discuss how such genetic heterogeneity is being leveraged to inform therapeutic interventions and personalised medicine, highlighting examples across the CVD spectrum. Finally, we present an overview of how polygenic risk scores and Mendelian randomisation can foster more robust insight into disease mechanisms and therapeutic intervention in diverse populations. Fulfilment of the vision of precision medicine requires more exhaustive leveraging of the genetic variability across diverse ancestry populations to improve our understanding of disease onset, progression and response to therapeutic intervention.

Genetic Val66Met BDNF Variant Increases Hyperphagia on Fat-rich Diets in Mice

High prevalence of obesity is attributable in part to consumption of highly palatable, fat-rich foods. However, the mechanism controlling dietary fat intake is largely unknown. In this study we investigated the role of brain-derived neurotrophic factor (BDNF) in the control of dietary fat intake in a mouse model that mimics the common human Val-to-Met (Val66Met) polymorphism that impairs BDNF release via the regulated secretory pathway. BdnfMet/Met mice gained weight much faster than wild-type (WT) mice and developed severe obesity due to marked hyperphagia when they were fed HFD. Hyperphagia in these mice worsened when the fat content in their diet was increased. Conversely, mice lacking leptin exhibited similar hyperphagia on chow and HFD. When 2 diets were provided simultaneously, WT and BdnfMet/Met mice showed a comparable preference for the more palatable diet rich in either fat or sucrose, indicating that increased hyperphagia on fat-rich diets in BdnfMet/Met mice is not due to enhanced hedonic drive. In support of this interpretation, WT and BdnfMet/Met mice increased calorie intake to a similar extent during the first day after chow was switched to HFD; however, WT mice decreased HFD intake faster than BdnfMet/Met mice in subsequent days. Furthermore, we found that refeeding after fasting or nocturnal feeding with HFD activated TrkB more strongly than with chow in the hypothalamus of WT mice, whereas TrkB activation under these 2 conditions was greatly attenuated in BdnfMet/Met mice. These results indicate that satiety factors generated during HFD feeding induce BDNF release to suppress excess dietary fat intake.

Drinking Habits and Physical Activity Interact and Attenuate Obesity Predisposition of TMEM18 Polymorphisms Carriers

The transmembrane protein 18 (TMEM18) gene plays a central and peripheral role in weight regulation. TMEM18 genetic polymorphisms have been identified as an important risk factor for obesity, depending on ethnic population and age. This research aimed to study the association of common TMEM18 polymorphisms with obesity and their interactions with modifiable factors, namely drinking habits (sugar-sweetened beverages (SSBs), flavored water and wine) and physical activity (PA) in the Israeli population. Adults (n = 3089) were analyzed for common TMEM18 polymorphisms and lifestyle and nutrition habits were obtained from questionnaires using adjusted (age, sex) binary logistic regression models. TMEM18 rs939583 and rs1879523 were significantly associated with increased obesity risk (OR = 1.35, 95% CI (1.17−1.57) and OR = 1.66, 95% CI (1.29−2.15), respectively). TMEM18 rs939583 interacted with consumption of 1−3 weekly glasses of wine and PA to attenuate obesity risk (OR = 0.82 95% CI (0.74−0.9; p < 0.001) and OR = 0.74 95% CI (0.68−0.8), respectively), while physical inactivity, SSBs and flavored water consumption significantly enhanced obesity risk (OR = 1.54 95% CI (1.41−1.67), OR = 1.31 95% CI (1.14−1.51) and OR = 1.35 95% CI (1.13−1.62), respectively). PA duration was significantly associated with a lower BMI for rs939583 risk carriers, with a PA cutoff of >30 min/week (p = 0.005) and >90 min/week (p = 0.01). Common TMEM18 SNPs were significantly linked with adult obesity risk and interacted with modifiable lifestyle factors.

Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats

Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.

Constructing a polygenic risk score for childhood obesity using functional data analysis

Obesity is a highly heritable condition that affects increasing numbers of adults and, concerningly, of children. However, only a small fraction of its heritability has been attributed to specific genetic variants. These variants are traditionally ascertained from genome-wide association studies (GWAS), which utilize samples with tens or hundreds of thousands of individuals for whom a single summary measurement (e.g., BMI) is collected. An alternative approach is to focus on a smaller, more deeply characterized sample in conjunction with advanced statistical models that leverage longitudinal phenotypes. Novel functional data analysis (FDA) techniques are used to capitalize on longitudinal growth information from a cohort of children between birth and three years of age. In an ultra-high dimensional setting, hundreds of thousands of single nucleotide polymorphisms (SNPs) are screened, and selected SNPs are used to construct two polygenic risk scores (PRS) for childhood obesity using a weighting approach that incorporates the dynamic and joint nature of SNP effects. These scores are significantly higher in children with (vs. without) rapid infant weight gain-a predictor of obesity later in life. Using two independent cohorts, it is shown that the genetic variants identified in very young children are also informative in older children and in adults, consistent with early childhood obesity being predictive of obesity later in life. In contrast, PRSs based on SNPs identified by adult obesity GWAS are not predictive of weight gain in the cohort of young children. This provides an example of a successful application of FDA to GWAS. This application is complemented with simulations establishing that a deeply characterized sample can be just as, if not more, effective than a comparable study with a cross-sectional response. Overall, it is demonstrated that a deep, statistically sophisticated characterization of a longitudinal phenotype can provide increased statistical power to studies with relatively small sample sizes; and shows how FDA approaches can be used as an alternative to the traditional GWAS.

Statistical Methods for Disease Risk Prediction with Genotype Data

Single-nucleotide polymorphism (SNP) is the basic unit to understand the heritability of complex traits. One attractive application of the susceptible SNPs is to construct prediction models for assessing disease risk. Here, we introduce prediction methods for human traits using SNPs data, including the polygenic risk score (PRS), linear mixed models (LMMs), penalized regressions, and methods for controlling population stratification.

dSec16 Acting in Insulin-like Peptide Producing Cells Controls Energy Homeostasis in Drosophila

Many studies show that genetics play a major contribution to the onset of obesity. Human genome-wide association studies (GWASs) have identified hundreds of genes that are associated with obesity. However, the majority of them have not been functionally validated. SEC16B has been identified in multiple obesity GWASs but its physiological role in energy homeostasis remains unknown. Here, we use Drosophila to determine the physiological functions of dSec16 in energy metabolism. Our results showed that global RNAi of dSec16 increased food intake and triglyceride (TAG) levels. Furthermore, this TAG increase was observed in flies with a specific RNAi of dSec16 in insulin-like peptide producing cells (IPCs) with an alteration of endocrine peptides. Together, our study demonstrates that dSec16 acting in IPCs controls energy balance and advances the molecular understanding of obesity.

Testing the Utility of Polygenic Risk Scores for Type 2 Diabetes and Obesity in Predicting Metabolic Changes in a Prediabetic Population: An Observational Study

Prediabetes is an intermediate state of hyperglycemia during which glycemic parameters are above normal levels but below the T2D threshold. T2D and its precursor prediabetes affect 6.28% and 7.3% of the world’s population, respectively. The main objective of this paper was to create and compare two polygenic risk scores (PRSs) versus changes over time (Δ) in metabolic parameters related to prediabetes and metabolic complications. The genetics of 446 prediabetic patients from the Polish Registry of Diabetes cohort were investigated. Seventeen metabolic parameters were measured and compared at baseline and after five years using statistical analysis. Subsequently, genetic polymorphisms present in patients were determined to build a T2D PRS (68 SNPs) and an obesity PRS (21 SNPs). Finally, the association among the two PRSs and the Δ of the metabolic traits was assessed. After a multiple linear regression with adjustment for age, sex, and BMI at a nominal significance of (p < 0.05) and adjustment for multiple testing, the T2D PRS was found to be positively associated with Δ fat mass (FM) (p = 0.025). The obesity PRS was positively associated with Δ FM (p = 0.023) and Δ 2 h glucose (p = 0.034). The comparison of genotype frequencies showed that AA genotype carriers of rs10838738 were significantly higher in Δ 2 h glucose and in Δ 2 h insulin. Our findings suggest that prediabetic individuals with a higher risk of developing T2D experience increased Δ FM, and those with a higher risk of obesity experience increased Δ FM and Δ two-hour postprandial glucose. The associations found in this research could be a powerful tool for identifying prediabetic individuals with an increased risk of developing T2D and obesity.

Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity

Asthma is a complex disease that varies widely in prevalence across populations. The extent to which genetic variation contributes to these disparities is unclear, as the genetics underlying asthma have been investigated primarily in populations of European descent. As part of the Global Biobank Meta-analysis Initiative, we conducted a large-scale genome-wide association study of asthma (153,763 cases and 1,647,022 controls) via meta-analysis across 22 biobanks spanning multiple ancestries. We discovered 179 asthma-associated loci, 49 of which were not previously reported. Despite the wide range in asthma prevalence among biobanks, we found largely consistent genetic effects across biobanks and ancestries. The meta-analysis also improved polygenic risk prediction in non-European populations compared with previous studies. Additionally, we found considerable genetic overlap between age-of-onset subtypes and between asthma and comorbid diseases. Our work underscores the multi-factorial nature of asthma development and offers insight into its shared genetic architecture.

Depression-Associated Negr1 Gene-Deficiency Induces Alterations in the Monoaminergic Neurotransmission Enhancing Time-Dependent Sensitization to Amphetamine in Male Mice

In GWAS studies, the neural adhesion molecule encoding the neuronal growth regulator 1 (NEGR1) gene has been consistently linked with both depression and obesity. Although the linkage between NEGR1 and depression is the strongest, evidence also suggests the involvement of NEGR1 in a wide spectrum of psychiatric conditions. Here we show the expression of NEGR1 both in tyrosine- and tryptophan hydroxylase-positive cells. Negr1-/- mice show a time-dependent increase in behavioral sensitization to amphetamine associated with increased dopamine release in both the dorsal and ventral striatum. Upregulation of transcripts encoding dopamine and serotonin transporters and higher levels of several monoamines and their metabolites was evident in distinct brain areas of Negr1-/- mice. Chronic (23 days) escitalopram-induced reduction of serotonin and dopamine turnover is enhanced in Negr1-/- mice, and escitalopram rescued reduced weight of hippocampi in Negr1-/- mice. The current study is the first to show alterations in the brain monoaminergic systems in Negr1-deficient mice, suggesting that monoaminergic neural circuits contribute to both depressive and obesity-related phenotypes linked to the human NEGR1 gene.

Bioactive dietary components-Anti-obesity effects related to energy metabolism and inflammation

Obesity is the result of the long-term energy imbalance between the excess calories consumed and the few calories expended. Reducing the intake of energy dense foods (fats, sugars), and strategies such as fasting and caloric restriction can promote body weight loss. Not only energy in terms of calories, but also the specific composition of the diet can affect the way the food is absorbed and how its energy is stored, used or dissipated. Recent research has shown that bioactive components of food, such as polyphenols and vitamins, can influence obesity and its pathologic complications such as insulin resistance, inflammation and metabolic syndrome. Individual micronutrients can influence lipid turnover but for long-term effects on weight stability, dietary patterns containing several micronutrients may be required. At the molecular level, these molecules modulate signaling and the expression of genes that are involved in the regulation of energy intake, lipid metabolism, adipogenesis into white, beige and brown adipose tissue, thermogenesis, lipotoxicity, adipo/cytokine synthesis, and inflammation. Higher concentrations of these molecules can be reached in the intestine, where they can modulate the composition and action of the microbiome. In this review, the molecular mechanisms by which bioactive compounds and vitamins modulate energy metabolism, inflammation and obesity are discussed.

Strategies to identify causal common genetic variants and corresponding effector genes for paediatric obesity

BACKGROUND

Childhood obesity rates are on the rise, but there are currently no effective therapies available to slow or halt their progression. Although environmental and lifestyle factors have been implicated in its pathogenesis, childhood obesity is considered a complex disorder with a clear genetic component. Intense genome-wide association study (GWAS) efforts through large-scale collaborations have enabled the discovery of genetic loci robustly associated with childhood obesity beyond the classic FTO locus. That said, GWAS itself does not pinpoint the actual underlying causal effector genes, but rather just yields association signals in the genome.

OBJECTIVE

This review aims to outline what has been elucidated thus far on the genetic aetiology of commong childhood obesity and to describe strategies to identify and validate both causal common genetic variants and their corresponding effector genes.

RESULTS

Relevant cell types for molecular studies can be identified by gene set enrichment analysis and considering known biology of obesity-related physiological processes. Putatively causal single nucleotide polymorphisms (SNPs) can be identified by several methods including statistical fine mapping and 'assay for transposase accessible chromatin sequencing' (ATAC-seq). Variant to gene mapping can then nominate effector genes likely regulated by cis-regulatory elements harbouring putatively causal SNPs. A SNP's cis-regulatory activity can be functionally validated by several in vitro methods including luciferase assay and CRISPR approaches. These CRISPR approaches can also be used to investigate how dysregulatn of effector genes may confer obesity risk.

CONCLUSION

Uncovering the causative genes related to GWAS signals and elucidating their functional contributions to paediatric obesity with these strategies will deepen our understanding of this disease and serve better treatment outcomes.

SH2B1 variants as potential causes of non-syndromic monogenic obesity in a Brazilian cohort

PURPOSE

SH2B1 gene encodes an important adaptor protein to receptor tyrosine kinases or cytokine receptors associated with Janus kinases. This gene has been associated with the structural and functional modulation of neurons and other cells, and impacts on energy and glucose homeostasis. Several studies suggested that alterations in this gene are strong candidates for the development of obesity. However, only a few studies have screened SH2B1 point variants in individuals with obesity. Therefore, the aim of this study was to investigate the prevalence of SH2B1 variants in a Brazilian cohort of patients with severe obesity and candidates to bariatric surgery.

METHODS

The cohort comprised 122 individuals with severe obesity, who developed this phenotype during childhood. As controls, 100 normal-weight individuals were included. The coding region of SH2B1 gene was screened by Sanger sequencing.

RESULTS

A total of eight variants were identified in SH2B1, of which p.(Val345Met) and p.(Arg630Gln) variants were rare and predicted as potentially pathogenic by the in the silico algorithms used in this study. The p.(Val345Met) was not found in either the control group or in publicly available databases. This variant was identified in a female patient with severe obesity, metabolic syndrome and hyperglycemia. The p.(Arg630Gln) was also absent in our control group, but it was reported in gnomAD with an extremely low frequency. This variant was observed in a female patient with morbid obesity, metabolic syndrome, hypertension and severe binge-eating disorder.

CONCLUSION

Our study reported for the first time two rare and potentially pathogenic variants in Brazilian patients with severe obesity. Further functional studies will be necessary to confirm and elucidate the impact of these variants on SH2B1 protein function and stability, and their impact on energetic metabolism.

LEVEL OF EVIDENCE

Level V, cross-sectional descriptive study.

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.

Reduced secretion of neuronal growth regulator 1 contributes to impaired adipose-neuronal crosstalk in obesity

While the endocrine function of white adipose tissue has been extensively explored, comparatively little is known about the secretory activity of less-investigated fat depots. Here, we use proteomics to compare the secretory profiles of male murine perivascular depots with those of canonical white and brown fat. Perivascular secretomes show enrichment for neuronal cell-adhesion molecules, reflecting a higher content of intra-parenchymal sympathetic projections compared to other adipose depots. The sympathetic innervation is reduced in the perivascular fat of obese (ob/ob) male mice, as well as in the epicardial fat of patients with obesity. Degeneration of sympathetic neurites is observed in presence of conditioned media of fat explants from ob/ob mice, that show reduced secretion of neuronal growth regulator 1. Supplementation of neuronal growth regulator 1 reverses this neurodegenerative effect, unveiling a neurotrophic role for this protein previously identified as a locus associated with human obesity. As sympathetic stimulation triggers energy-consuming processes in adipose tissue, an impaired adipose-neuronal crosstalk is likely to contribute to the disrupted metabolic homeostasis characterising obesity.

Architecture of the outbred brown fat proteome defines regulators of metabolic physiology

Brown adipose tissue (BAT) regulates metabolic physiology. However, nearly all mechanistic studies of BAT protein function occur in a single inbred mouse strain, which has limited the understanding of generalizable mechanisms of BAT regulation over physiology. Here, we perform deep quantitative proteomics of BAT across a cohort of 163 genetically defined diversity outbred mice, a model that parallels the genetic and phenotypic variation found in humans. We leverage this diversity to define the functional architecture of the outbred BAT proteome, comprising 10,479 proteins. We assign co-operative functions to 2,578 proteins, enabling systematic discovery of regulators of BAT. We also identify 638 proteins that correlate with protection from, or sensitivity to, at least one parameter of metabolic disease. We use these findings to uncover SFXN5, LETMD1, and ATP1A2 as modulators of BAT thermogenesis or adiposity, and provide OPABAT as a resource for understanding the conserved mechanisms of BAT regulation over metabolic physiology.

Identification of potentially common loci between childhood obesity and coronary artery disease using pleiotropic approaches

Childhood obesity remains one of the most important issues in global health, which is implicated in many chronic diseases. Converging evidence suggests that a higher body mass index during childhood (CBMI) is significantly associated with increased coronary artery disease (CAD) susceptibility in adulthood, which may partly arise from the shared genetic determination. Despite genome-wide association studies (GWASs) have successfully identified some loci associated with CBMI and CAD individually, the genetic overlap and common biological mechanism between them remains largely unexplored. Here, relying on the results from the two large-scale GWASs (n = 35,668 for CBMI and n = 547,261 for CAD), linkage disequilibrium score regression (LDSC) was used to estimate the genetic correlation of CBMI and CAD in the first step. Then, we applied different pleiotropy-informed methods including conditional false discovery rate ([Formula: see text]) and genetic analysis incorporating pleiotropy and annotation (GPA) to detect potentially common loci for childhood obesity and CAD. By integrating the genetic information from the existing GWASs summary statistics, we found a significant positive genetic correlation ([Formula: see text] = 0.127, p = 2E-4) and strong pleiotropic enrichment between CBMI and CAD (LRT = 79.352, p = 5.2E-19). Importantly, 28 loci were simultaneously discovered to be associated with CBMI, and 13 of them were identified as potentially pleiotropic loci by [Formula: see text] and GPA. Those corresponding pleiotropic genes were enriched in trait-associated gene ontology (GO) terms "amino sugar catabolic process", "regulation of fat cell differentiation" and "synaptic transmission". Overall, the findings of the pleiotropic loci will help to further elucidate the common molecular mechanisms underlying the association of childhood obesity and CAD, and provide a theoretical direction for early disease prevention and potential therapeutic targets.

Higher Waist Hip Ratio Genetic Risk Score Is Associated with Reduced Weight Loss in Patients with Severe Obesity Completing a Meal Replacement Programme

Background: A better understanding of the influence of genetic factors on the response to lifestyle interventions in people with obesity may allow the development of more personalised, effective and efficient therapeutic strategies. We sought to determine the influence of six obesity-related genetic risk scores on the magnitude of weight lost by patients with severe obesity who completed a dietary intervention. Methods: In this single-centre prospective cohort study, participants with severe and complicated obesity who completed a 24-week, milk-based meal replacement programme were genotyped to detect the frequency of common risk alleles for obesity and type 2 diabetes-related traits. Genetic risk scores (GRS) for six of these traits were derived. Participants with a potentially deleterious monogenic gene variant were excluded from the analysis. Results: In 93 patients completing the programme who were not carrying a known obesity-related gene mutation, 35.5% had diabetes, 53.8% were female, mean age was 51.4 ± 11 years, mean body mass index was 51.5 ± 8.7 and mean total weight loss percent at 24 weeks was 16 ± 6.3%. The waist-hip ratio (WHR) GRS was inversely associated with percentage total weight loss at 24 weeks (adjusted β for one standard deviation increase in WHR GRS -11.6 [-23.0, -0.3], p = 0.045), and patients in the lowest tertile of WHR GRS lost more weight. Conclusions: Patients with severe and complicated obesity with a genetic predisposition to central fat accumulation had less weight loss in a 24-week milk-based meal replacement programme, but there was no evidence for influence from the five other obesity-related genetic risk scores on the response to dietary restriction.

The effect of heteroscedasticity on the prediction efficiency of genome-wide polygenic score for body mass index

Globally, more than 1.9 billion adults are overweight. Thus, obesity is a serious public health issue. Moreover, obesity is a major risk factor for diabetes mellitus, coronary heart disease, and cardiovascular disease. Recently, GWAS examining obesity and body mass index (BMI) have increasingly unveiled many aspects of the genetic architecture of obesity and BMI. Information on genome-wide genetic variants has been used to estimate the genome-wide polygenic score (GPS) for a personalized prediction of obesity. However, the prediction power of GPS is affected by various factors, including the unequal variance in the distribution of a phenotype, known as heteroscedasticity. Here, we calculated a GPS for BMI using LDpred2, which was based on the BMI GWAS summary statistics from a European meta-analysis. Then, we tested the GPS in 354,761 European samples from the UK Biobank and found an effective prediction power of the GPS on BMI. To study a change in the variance of BMI, we investigated the heteroscedasticity of BMI across the GPS via graphical and statistical methods. We also studied the homoscedastic samples for BMI compared to the heteroscedastic sample, randomly selecting samples with various standard deviations of BMI residuals. Further, we examined the effect of the genetic interaction of GPS with environment (GPS×E) on the heteroscedasticity of BMI. We observed the changing variance (i.e., heteroscedasticity) of BMI along the GPS. The heteroscedasticity of BMI was confirmed by both the Breusch-Pagan test and the Score test. Compared to the heteroscedastic sample, the homoscedastic samples from small standard deviation of BMI residuals showed a decreased heteroscedasticity and an improved prediction accuracy, suggesting a quantitatively negative correlation between the phenotypic heteroscedasticity and the prediction accuracy of GPS. To further test the effects of the GPS×E on heteroscedasticity, first we tested the genetic interactions of the GPS with 21 environments and found 8 significant GPS×E interactions on BMI. However, the heteroscedasticity of BMI was not ameliorated after adjusting for the GPS×E interactions. Taken together, our findings suggest that the heteroscedasticity of BMI exists along the GPS and is not affected by the GPS×E interaction.

Population-based meta-analysis and gene-set enrichment identifies FXR/RXR pathway as common to fatty liver disease and serum lipids

Nonalcoholic fatty liver disease (NAFLD) is prevalent worldwide. NAFLD is associated with elevated serum triglycerides (TG), low-density lipoprotein cholesterol (LDL), and reduced high-density lipoprotein cholesterol (HDL). Both NAFLD and blood lipid levels are genetically influenced and may share a common genetic etiology. We used genome-wide association studies (GWAS)-ranked genes and gene-set enrichment analysis to identify pathways that affect serum lipids and NAFLD. We identified credible genes in these pathways and characterized missense variants in these for effects on serum traits. We used MAGENTA to identify 58 enriched pathways from publicly available TG, LDL, and HDL GWAS (n = 99,000). Three of these pathways were also enriched for associations with European-ancestry NAFLD GWAS (n = 7176). One pathway, farnesoid X receptor (FXR)/retinoid X receptor (RXR) activation, was replicated for association in an African-ancestry NAFLD GWAS (n = 3214) and plays a role in serum lipids and NAFLD. Credible genes (proteins) in FXR/RXR activation include those associated with cholesterol/bile/bilirubin transport/absorption (ABCC2 (MRP2) [ATP binding cassette subfamily C member (multidrug resistance-associated protein 2)], ABCG5, ABCG8 [ATP-binding cassette (ABC) transporters G5 and G8], APOB (APOB) [apolipoprotein B], FABP6 (ILBP) [fatty acid binding protein 6 (ileal lipid-binding protein)], MTTP (MTP) [microsomal triglyceride transfer protein], SLC4A2 (AE2) [solute carrier family 4 member 2 (anion exchange protein 2)]), nuclear hormone-mediated control of metabolism (NR0B2 (SHP) [nuclear receptor subfamily 0 group B member 2 (small heterodimer partner)], NR1H4 (FXR) [nuclear receptor subfamily 1 group H member 4 (FXR)], PPARA (PPAR) [peroxisome proliferator activated receptor alpha], FOXO1 (FOXO1A) [forkhead box O1]), or other pathways (FETUB (FETUB) [fetuin B]). Missense variants in ABCC2 (MRP2), ABCG5 (ABCG5), ABCG8 (ABCG8), APOB (APOB), MTTP (MTP), NR0B2 (SHP), NR1H4 (FXR), and PPARA (PPAR) that associate with serum LDL levels also associate with serum liver function tests in UK Biobank. Conclusion: Genetic variants in NR1H4 (FXR) that protect against liver steatosis increase serum LDL cholesterol while variants in other members of the family have congruent effects on these traits. Human genetic pathway enrichment analysis can help guide therapeutic development by identifying effective targets for NAFLD/serum lipid manipulation while minimizing side effects. In addition, missense variants could be used in companion diagnostics to determine their influence on drug effectiveness.

Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population

Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30-60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding.

Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior-posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = -0.02, SE = 0.004, P-value = 2.10 × 10-8). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10-4). In exome-array single-variant analysis (P-value threshold = 9 × 10-7), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10-5). In the gene-based analysis (P-value threshold = 1.85 × 10-6), PCSK5 showed an association with AAD (P-value = 8.03 × 10-7). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = -0.003, P-value = 0.02), triglycerides (beta = -0.16, P-value = 0.008) and height (beta = 0.03, P-value < 0.0001), known risk factors for AAA, consistent with a causal association with AAD. Our findings point to new biology as well as highlighting gene regions in mechanisms that have previously been implicated in the genetics of other vascular diseases.

Genome-wide association analysis of milk production, somatic cell score, and body conformation traits in Holstein cows

Milk production and body conformation traits are critical economic traits for dairy cows. To understand the basic genetic structure for those traits, a genome wide association study was performed on milk yield, milk fat yield, milk fat percentage, milk protein yield, milk protein percentage, somatic cell score, body form composite index, daily capacity composite index, feed, and leg conformation traits, based on the Illumina Bovine HD100k BeadChip. A total of 57, 12 and 26 SNPs were found to be related to the milk production, somatic cell score and body conformation traits in the Holstein cattle. Genes with pleiotropic effect were also found in this study. Seven significant SNPs were associated with multi-traits and were located on the PLEC, PLEKHA5, TONSL, PTGER4, and LCORL genes. In addition, some important candidate genes, like GPAT3, CEBPB, AGO2, SLC37A1, and FNDC3B, were found to participate in fat metabolism or mammary gland development. These results can be used as candidate genes for milk production, somatic cell score, and body conformation traits of Holstein cows, and are helpful for further gene function analysis to improve milk production and quality.

Syndromic and Nonsyndromic Obesity: Underlying Genetic Causes in Humans

Growing evidence supports syndromic and nonsyndromic causes of obesity, including genome-wide association studies, candidate gene analysis, advanced genetic technology using next-generation sequencing (NGS), and identification of copy number variants. Identification of susceptibility genes impacts mechanistic understanding and informs precision medicine. The cause of obesity is heterogeneous with complex biological processes playing a role by controlling peptides involved in regulating appetite and food intake, cellular energy, and metabolism. Evidence for heritability shows genetic components contributing to 40%-70% of obesity. Monogenic causes and obesity-related syndromes are discussed and illustrated as well as biological pathways, gene interactions, and factors contributing to the obesity phenotype. Over 550 obesity-related single genes have been identified and summarized in tabular form with approximately 20% of these genes have been added to obesity gene panels for testing by commercially available laboratories. Early studies show that about 10% of patients with severe obesity using NGS testing have a pathogenic gene variant. Discussion to help characterize gene-gene interactions and disease mechanisms for early diagnosis, treatment, and risk factors contributing to disease is incorporated in this review.

Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers

BACKGROUND

Knee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic, and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease. For the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors.

METHODS

Participants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, and TGFA; mtDNA haplogroups H, J, T, Uk, and others; and clusters HV, TJ, KU, and C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using tenfold cross-validation and an external cohort (TASOAC).

RESULTS

From 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, and FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models.

CONCLUSIONS

This study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of (i) age, BMI, TP63, DUS4L, GDF5, and FTO and (ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, and SUPT3H. Such a framework is translational and would benefit patients at risk of structural progressive knee osteoarthritis.

Dietary carbohydrates: Pathogenesis and potential therapeutic targets to obesity-associated metabolic syndrome

Metabolic syndrome (MetS) is a common feature in obesity, comprising a cluster of abnormalities including abdominal fat accumulation, hyperglycemia, hyperinsulinemia, dyslipidemia, and hypertension, leading to diabetes and cardiovascular diseases (CVD). Intake of carbohydrates (CHO), particularly a sugary diet that rapidly increases blood glucose, triglycerides, and blood pressure levels is the predominant determining factor of MetS. Complex CHO, on the other hand, are a stable source of energy taking a longer time to digest. In particular, resistant starch (RS) or soluble fiber is an excellent source of prebiotics, which alter the gut microbial composition, which in turn improves metabolic control. Altering maternal CHO intake during pregnancy may result in the child developing MetS. Furthermore, lifestyle factors such as physical inactivity in combination with dietary habits may synergistically influence gene expression by modulating genetic and epigenetic regulators transforming childhood obesity into adolescent metabolic disorders. This review summarizes the common pathophysiology of MetS in connection with the nature of CHO, intrauterine nutrition, genetic predisposition, lifestyle factors, and advanced treatment approaches; it also emphasizes how dietary CHO may act as a key element in the pathogenesis and future therapeutic targets of obesity and MetS.

The Link between Three Single Nucleotide Variants of the GIPR Gene and Metabolic Health

Single nucleotide variants (SNVs) of the GIPR gene have been associated with BMI and type 2 diabetes (T2D), suggesting the role of the variation in this gene in metabolic health. To increase our understanding of this relationship, we investigated the association of three GIPR SNVs, rs11672660, rs2334255 and rs10423928, with anthropometric measurements, selected metabolic parameters, and the risk of excessive body mass and metabolic syndrome (MS) in the Polish population. Normal-weight subjects (n = 340, control group) and subjects with excessive body mass (n = 600, study group) participated in this study. For all participants, anthropometric measurements and metabolic parameters were collected, and genotyping was performed using the high-resolution melting curve analysis. We did not find a significant association between rs11672660, rs2334255 and rs10423928 variants with the risk of being overweight. Differences in metabolic and anthropometric parameters were found for investigated subgroups. An association between rs11672660 and rs10423928 with MS was identified. Heterozygous CT genotype of rs11672660 and AT genotype of rs10423928 were significantly more frequent in the group with MS (OR = 1.38, 95%CI: 1.03–1.85; p = 0.0304 and OR = 1.4, 95%CI: 1.05–1.87; p = 0.0222, respectively). Moreover, TT genotype of rs10423928 was less frequent in the MS group (OR = 0.72, 95%CI: 0.54–0.95; p = 0.0221).

Genome-wide association study identifying genetic variants associated with carcass backfat thickness, lean percentage and fat percentage in a four-way crossbred pig population using SLAF-seq technology

Background

Carcass backfat thickness (BFT), carcass lean percentage (CLP) and carcass fat percentage (CFP) are important to the commercial pig industry. Nevertheless, the genetic architecture of BFT, CLP and CFP is still elusive. Here, we performed a genome-wide association study (GWAS) based on specific-locus amplified fragment sequencing (SLAF-seq) to analyze seven fatness-related traits, including five BFTs, CLP, and CFP on 223 four-way crossbred pigs.

Results

A total of 227, 921 highly consistent single nucleotide polymorphisms (SNPs) evenly distributed throughout the genome were used to perform GWAS. Using the mixed linear model (MLM), a total of 20 SNP loci significantly related to these traits were identified on ten Sus scrofa chromosomes (SSC), of which 10 SNPs were located in previously reported quantitative trait loci (QTL) regions. On SSC7, two SNPs (SSC7:29,503,670 and rs1112937671) for average backfat thickness (ABFT) exceeded 1% and 10% Bonferroni genome-wide significance levels, respectively. These two SNP loci were located within an intron region of the COL21A1 gene, which was a protein-coding gene that played an important role in the porcine backfat deposition by affecting extracellular matrix (ECM) remodeling. In addition, based on the other three significant SNPs on SSC7, five candidate genes, ZNF184, ZNF391, HMGA1, GRM4 and NUDT3 were proposed to influence BFT. On SSC9, two SNPs for backfat thickness at 6–7 ribs (67RBFT) and one SNP for CLP were in the same locus region (19 kb interval). These three SNPs were located in the PGM2L1 gene, which encoded a protein that played an indispensable role in glycogen metabolism, glycolysis and gluconeogenesis as a key enzyme. Finally, one significant SNP on SSC14 for CLP was located within the PLBD2 gene, which participated in the lipid catabolic process.

Conclusions

A total of two regions on SSC7 and SSC9 and eight potential candidate genes were found for fatness-related traits in pigs. The results of this GWAS based on SLAF-seq will greatly advance our understanding of the genetic architecture of BFT, CLP, and CFP traits. These identified SNP loci and candidate genes might serve as a biological basis for improving the important fatness-related traits of pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08827-8.

The weight of childhood adversity: evidence that childhood adversity moderates the impact of genetic risk on waist circumference in adulthood

OBJECTIVE

The present study tested the interactive effects of childhood adversity and polygenic risk scores for waist circumference (PRS-WC) on waist circumference (WC). Consistent with a diathesis-stress model, we hypothesize that the relationship between PRS-WC and WC will be magnified by increasing levels of childhood adversity.

METHODS

Observational study of 7976 adults (6347 European Americans and 1629 African Americans) in the Health and Retirement Study with genotyped data. PRS-WC were calculated by the HRS administrative core using the weighted sum of risk alleles based on a genome-wide association study conducted by the Genetic Investigation of Anthropometric Traits (GIANT) consortium. Childhood adversity was operationalized using a sum score of three traumatic events that occurred before the age of 18 years.

RESULTS

There was a statistically significant interaction between PRS-WC and childhood adversity for European Americans, whereby the magnitude of PRS-WC predicting WC increased as the number of adverse events increased.

CONCLUSIONS

This study supports the idea of the interactive effects of genetic risks and childhood adversity on obesity. More epidemiological studies, particularly with understudied populations, are needed to better understand the roles that genetics and childhood adversity play on the development and progression of obesity.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

Genome-wide Association Study of Liking for Several Types of Physical Activity in the UK Biobank and Two Replication Cohorts

INTRODUCTION

A lack of physical activity (PA) is one of the most pressing health issues today. Our individual propensity for PA is influenced by genetic factors. Stated liking of different PA types may help capture additional and informative dimensions of PA behavior genetics.

METHODS

In over 157,000 individuals from the UK Biobank, we performed genome-wide association studies of five items assessing the liking of different PA types, plus an additional derived trait of overall PA-liking. We attempted to replicate significant associations in the Netherlands Twin Register (NTR) and TwinsUK. Additionally, polygenic scores (PGS) were trained in the UK Biobank for each PA-liking item and for self-reported PA behavior, and tested for association with PA in the NTR.

RESULTS

We identified a total of 19 unique significant loci across all five PA-liking items and the overall PA-liking trait, and these showed strong directional consistency in the replication cohorts. Four of these loci were previously identified for PA behavior, including CADM2 , which was associated with three PA-liking items. The PA-liking items were genetically correlated with self-reported ( rg = 0.38-0.80) and accelerometer ( rg = 0.26-0.49) PA measures, and with a wide range of health-related traits. Each PA-liking PGS significantly predicted the same PA-liking item in NTR. The PGS of liking for going to the gym predicted PA behavior in the NTR ( r2 = 0.40%) nearly as well as a PGS based on self-reported PA behavior ( r2 = 0.42%). Combining the two PGS into a single model increased the r2 to 0.59%, suggesting that PA-liking captures distinct and relevant dimensions of PA behavior.

CONCLUSIONS

We have identified the first loci associated with PA-liking and extended our understanding of the genetic basis of PA behavior.

Determining the stability of genome-wide factors in BMI between ages 40 to 69 years

Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years. We then applied genomic structural equation modeling to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that molecular genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin genome-wide variation in BMI from middle to early old age in men and women alike.

Cross-fitted instrument: A blueprint for one-sample Mendelian randomization

Bias from weak instruments may undermine the ability to estimate causal effects in instrumental variable regression (IVR). We present here a new approach to handling weak instrument bias through the application of a new type of instrumental variable coined 'Cross-Fitted Instrument' (CFI). CFI splits the data at random and estimates the impact of the instrument on the exposure in each partition. These estimates are then used to perform an IVR on each partition. We adapt CFI to the Mendelian randomization (MR) setting and term this adaptation 'Cross-Fitting for Mendelian Randomization' (CFMR). We show that, even when using weak instruments, CFMR is, at worst, biased towards the null, which makes it a conservative one-sample MR approach. In particular, CFMR remains conservative even when the two samples used to perform the MR analysis completely overlap, whereas current state-of-the-art approaches (e.g., MR RAPS) display substantial bias in this setting. Another major advantage of CFMR lies in its use of all of the available data to select genetic instruments, which maximizes statistical power, as opposed to traditional two-sample MR where only part of the data is used to select the instrument. Consequently, CFMR is able to enhance statistical power in consortia-led meta-analyses by enabling a conservative one-sample MR to be performed in each cohort prior to a meta-analysis of the results across all the cohorts. In addition, CFMR enables a cross-ethnic MR analysis by accounting for ethnic heterogeneity, which is particularly important in meta-analyses where the participating cohorts may have different ethnicities. To our knowledge, none of the current MR approaches can account for such heterogeneity. Finally, CFMR enables the application of MR to exposures that are either rare or difficult to measure, which would normally preclude their analysis in the regular two-sample MR setting.

Novel Alzheimer risk factor IQ motif containing protein K is abundantly expressed in the brain and is markedly increased in patients with Alzheimer’s disease

Alzheimer’s disease (AD) is complex and highly heterogeneous. Less than 10% of AD cases are early-onset (EOAD) caused by autosomal dominantly inherited mutations in amyloid precursor protein (APP), presenilin 1 (PS1), or presenilin 2 (PS2), each of which can increase Aβ generation and, thus, amyloid plaques. The remaining 90% of cases of AD are late-onset (LOAD) or sporadic. Intense research efforts have led to identification of many genes that increase the risk of AD. An IQ motif containing protein K (IQCK) was recently identified by several investigators as an Alzheimer’s disease risk gene. However, how IQCK increases AD risk is completely unknown. Since IQCK is a novel gene, there is limited information on its physiological characterization. To understand its role in AD, it is first important to determine its subcellular localization, whether and where it is expressed in the brain, and what type of brain cells express the IQCK protein. Therefore, in this study, we show by immunocytochemical (ICC) staining that IQCK is expressed in both the nucleus and the cytoplasm of SH-SY5Y neuroblastoma cells as well as HeLa cells but not in either HMC3 microglial or CHO cells. By immunohistochemistry (IHC), we also show that IQCK is expressed in both mouse and human neurons, including neuronal processes in vivo in the mouse brain. IHC data also show that the IQCK protein is widely expressed throughout the mouse brain, although regional differences were noted. IQCK expression was highest in the brainstem (BS), followed by the cerebellum (CB) and the cortex (CX), and it was lowest in the hippocampus (HP). This finding was consistent with data from an immunoblot analysis of brain tissue homogenates. Interestingly, we found IQCK expression in neurons, astrocytes, and oligodendrocytes using cell-specific antibodies, but IQCK was not detected in microglial cells, consistent with negative in vitro results in HMC3 cells. Most importantly, we found that actin-normalized IQCK protein levels were increased by 2 folds in AD brains relative to normal control (NC) brains. Furthermore, the IQCK protein was found in amyloid plaques, suggesting that IQCK may play a pathogenic role in either Aβ generation or amyloid plaque deposition in AD.

Age and diet shape the genetic architecture of body weight in diversity outbred mice

Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds.

Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight.

Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week.

Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight.

The experiments highlight the importance of considering interactions between genetics, environment, and age in determining complex traits like body weight. The results and the approaches used by Wright et al. may help other scientists learn more about how the genetic predisposition to disease changes with environmental stimuli and age.

Sex Discrepancy Observed for Gestational Metabolic Syndrome Parameters and Polygenic Risk Associated With Preschoolers' BMI Growth Trajectory: The Ma'anshan Birth Cohort Study

Background

Few studies have investigated the associations of childhood growth trajectories with the prenatal metabolic risks of mothers and their interaction with children's genetic susceptibility.

Objective

To investigate the effects of gestational metabolic syndrome (GMS) risks and children's polygenic risk scores (PRSs), and their interaction effect on the BMI trajectory and obesity risk of offspring from birth to 6 years of age.

Methods

A total of 2,603 mother-child pairs were recruited from the Ma'anshan birth cohort (Anhui Province of China) study. Data on maternal prepregnancy obesity, gestational weight gain (GWG), gestational diabetes mellitus (GDM), and hypertensive disorders of pregnancy (HDP) were used to evaluate maternal GMS risk. In addition, 1,482 cord blood samples were used to genotype 11 candidate single-nucleotide polymorphisms (SNPs) to calculate children's PRSs. The latent class growth model using the longitudinal BMI-for-age z scores (BMIz) was applied to validly capture the BMIz growth trajectory.

Results

Maternal GMS status was associated with higher BMIz scores and with an increased risk of overweight/obesity. Positive relationships were revealed between PRS and the risk of overweight/obesity among girls. Additionally, maternal GMS significantly interacted with the child's PRS on BMIz scores and the risk of overweight/obesity among girls. Hierarchical BMI trajectory graphs by different exposure groups showed consistent findings, and both boys' and girls' BMIz trajectories were divided into three groups. Among girls, the higher the GMS risk or PRS they had, the higher the probability of being in the high BMIz trajectory group.

Conclusions

Maternal GMS status increased BMIz scores and the risk of obesity in both boys and girls and elevated the child's BMI trajectory from birth to 6 years of age among girls. PRSs were significantly associated with children's BMI trajectory and the risk of obesity and modified the associations between maternal GMS status and obesity biomarkers only among girls. Thus, regarding childhood obesity, steps should be taken to decrease maternal metabolic risks before and during pregnancy, and sex discrepancies should be noted to identify high-risk populations after birth to hierarchically manage them.

Divalent Metal Uptake and the Role of ZIP8 in Host Defense Against Pathogens

Manganese (Mn) and Zinc (Zn) are essential micronutrients whose concentration and location within cells are tightly regulated at the onset of infection. Two families of Zn transporters (ZIPs and ZnTs) are largely responsible for regulation of cytosolic Zn levels and to a certain extent, Mn levels, although much less is known regarding Mn. The capacity of pathogens to persevere also depends on access to micronutrients, yet a fundamental gap in knowledge remains regarding the importance of metal exchange at the host interface, often referred to as nutritional immunity. ZIP8, one of 14 ZIPs, is a pivotal importer of both Zn and Mn, yet much remains to be known. Dietary Zn deficiency is common and commonly occurring polymorphic variants of ZIP8 that decrease cellular metal uptake (Zn and Mn), are associated with increased susceptibility to infection. Strikingly, ZIP8 is the only Zn transporter that is highly induced following bacterial exposure in key immune cells involved with host defense against leading pathogens. We postulate that mobilization of Zn and Mn into key cells orchestrates the innate immune response through regulation of fundamental defense mechanisms that include phagocytosis, signal transduction, and production of soluble host defense factors including cytokines and chemokines. New evidence also suggests that host metal uptake may have long-term consequences by influencing the adaptive immune response. Given that activation of ZIP8 expression by pathogens has been shown to influence parenchymal, myeloid, and lymphoid cells, the impact applies to all mucosal surfaces and tissue compartments that are vulnerable to infection. We also predict that perturbations in metal homeostasis, either genetic- or dietary-induced, has the potential to impact bacterial communities in the host thereby adversely impacting microbiome composition. This review will focus on Zn and Mn transport via ZIP8, and how this vital metal transporter serves as a "go to" conductor of metal uptake that bolsters host defense against pathogens. We will also leverage past studies to underscore areas for future research to better understand the Zn-, Mn- and ZIP8-dependent host response to infection to foster new micronutrient-based intervention strategies to improve our ability to prevent or treat commonly occurring infectious disease.

Do adverse childhood experiences and genetic obesity risk interact in relation to body mass index in young adulthood? Findings from the National Longitudinal Study of Adolescent to Adult Health

BACKGROUND

Few studies have focused on the role of adverse childhood experiences (ACEs) in relation to genetic susceptibility to obesity.

OBJECTIVE

We aimed to examine the interaction between the presence of ACEs (i.e., physical, psychological and sexual abuse) before the age of 18 and BMI polygenic score.

METHODS

Data came from the National Longitudinal Study of Adolescent to Adult Health (Add Health) Wave IV (2007/2008) where saliva samples were collected for DNA genotyping and information on BMI and ACEs were obtained from 5854 European American (EA), 2073 African American (AA) and 1448 Hispanic American (HA) participants aged 24 to 32 years old. Polygenic scores were calculated as the sum of the number of risk alleles of BMI-related SNPs which were weighted by effect size. A race/ethnicity-stratified mixed-effects linear regression model was used to test for differential association between BMI polygenic score and BMI by the presence of ACEs.

RESULTS

We did not find any evidence of significant interaction between ACEs and polygenic score in relation to BMI among EA (p = 0.289), AA (p = 0.618) or HA (p = 0.870). In main effects models, polygenic score was positively associated with BMI in all race/ethnic groups, yet the presence of ACEs was associated with increased BMI only among EA.

CONCLUSION

We did not find any evidence that ACEs exacerbate genetic predisposition to increased BMI in early adulthood.

Effects of childhood obesity and related genetic factors on precocious puberty: protocol for a multi-center prospective cohort study

BACKGROUND

Childhood obesity has important effects on the onset and development of puberty. Although a number of studies have confirmed the relationship between obesity and precocious puberty, little is known about the pleiotropic genes of obesity and precocious puberty and the interaction between genes and environment. There are four objectives: (1) to analyze the incidence of precocious puberty in the general population in China; (2) to verify the direct effect of obesity on children's precocious puberty using a variety of methods; (3) to verify the effect of obesity and its risk gene polymorphism on precocious puberty in a prospective cohort study; and (4) to analyze the interaction effect of genes and environment on pubertal development.

METHODS

We will conduct a multi-center prospective cohort study in three cities, which are selected in southern, central, and northern China, respectively. Primary schools in these cities will be selected by a stratified cluster random sampling method. Primary school students from grade 1 to grade 3 (6 to 10 years old) will be selected for the cohort with extensive baseline data collection, including assessment of pubertal development, family demographic information, early development, sleep pattern, dietary pattern, and physical activity. Participants will be followed up for at least three years, and long-term follow-up will depend on future funding.

DISCUSSION

The findings of this multicenter prospective population-based cohort study may expand previous related puberty development research as well as provide important information on the mechanism of early puberty. Targeted interventions can also be developed to improve adolescent health problems related to puberty development based on the available evidence.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04113070 , prospectively registered on October 2, 2019.

Genetically Predicted Obesity Causally Increased the Risk of Hypertension Disorders in Pregnancy

Aims

This study aimed to evaluate the causal association between obesity and hypertension disorders in pregnancy.

Methods

Two-sample Mendelian randomization (MR) study was conducted based on the data obtained from the GIANT (n = 98,697 participants) consortium and FinnGen (n = 96,449 participants) consortium to determine the causal effect of obesity on the risk of hypertension disorders in pregnancy. Based on a genome-wide significance, 14 single-nucleotide polymorphisms (SNPs) associated with obesity-related databases were used as instrumental variables. The random-effects inverse-variance weighted (IVW) method was adopted as the main analysis with a supplemented sensitive analysis of the MR-Egger and weighted median approaches.

Results

All three MR methods showed that genetically predicted obesity causally increased the risk of hypertension disorders in pregnancy. IVW analysis provided obesity as a risk factor for hypertension disorders in pregnancy with an odds ratio (OR) of 1.39 [95% confidence interval (CI) 1.21–1.59; P = 2.46 × 10⁻⁶]. Weighted median and MR Egger regression also showed directionally similar results [weighted median OR = 1.49 (95% CI, 1.24–1.79), P = 2.45 × 10⁻⁵; MR-Egger OR = 1.95 (95% CI, 1.35–2.82), P = 3.84 × 10⁻³]. No directional pleiotropic effects were found between obesity and hypertension disorders in pregnancy with both MR-Egger intercepts and funnel plots.

Conclusions

Our findings provided directed evidence that obesity was causally associated with a higher risk of hypertension disorders in pregnancy. Taking measures to reduce the proportion of obesity may help reduce the incidence of hypertension disorders in pregnancy.

Dysfunction of the energy sensor NFE2L1 triggers uncontrollable AMPK signaling and glucose metabolism reprogramming

The antioxidant transcription factor NFE2L1 (also called Nrf1) acts as a core regulator of redox signaling and metabolism homeostasis, and thus, its dysfunction results in multiple systemic metabolic diseases. However, the molecular mechanism(s) by which NFE2L1 regulates glycose and lipid metabolism remains elusive. Here, we found that loss of NFE2L1 in human HepG2 cells led to a lethal phenotype upon glucose deprivation and NFE2L1 deficiency could affect the uptake of glucose. Further experiments revealed that glycosylation of NFE2L1 enabled it to sense the energy state. These results indicated that NFE2L1 can serve as a dual sensor and regulator of glucose homeostasis. The transcriptome, metabolome, and seahorse data further revealed that disruption of NFE2L1 could reprogram glucose metabolism to aggravate the Warburg effect in NFE2L1-silenced hepatoma cells, concomitant with mitochondrial damage. Co-expression and Co-immunoprecipitation experiments demonstrated that NFE2L1 could directly interact and inhibit AMPK. Collectively, NFE2L1 functioned as an energy sensor and negatively regulated AMPK signaling through directly interacting with AMPK. The novel NFE2L1/AMPK signaling pathway delineate the mechanism underlying of NFE2L1-related metabolic diseases and highlight the crosstalk between redox homeostasis and metabolism homeostasis.