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

Potential application of elastic nets for shared polygenicity detection with adapted threshold selection

Current research suggests that hundreds to thousands of single nucleotide polymorphisms (SNPs) with small to modest effect sizes contribute to the genetic basis of many disorders, a phenomenon labeled as polygenicity. Additionally, many such disorders demonstrate polygenic overlap, in which risk alleles are shared at associated genetic loci. A simple strategy to detect polygenic overlap between two phenotypes is based on rank-ordering the univariate p-values from two genome-wide association studies (GWASs). Although high-dimensional variable selection strategies such as Lasso and elastic nets have been utilized in other GWAS analysis settings, they are yet to be utilized for detecting shared polygenicity. In this paper, we illustrate how elastic nets, with polygenic scores as the dependent variable and with appropriate adaptation in selecting the penalty parameter, may be utilized for detecting a subset of SNPs involved in shared polygenicity. We provide theory to better understand our approaches, and illustrate their utility using synthetic datasets. Results from extensive simulations are presented comparing the elastic net approaches with the rank ordering approach, in various scenarios. Results from simulations studies exhibit one of the elastic net approaches to be superior when the correlations among the SNPs are high. Finally, we apply the methods on two real datasets to illustrate further the capabilities, limitations and differences among the methods.

The miR-668 binding site variant rs1046322 on WFS1 is associated with obesity in Southeast Asians

The Wolfram syndrome 1 gene (WFS1) is the main causative locus for Wolfram syndrome, an inherited condition characterized by childhood-onset diabetes mellitus, optic atrophy, and deafness. Global genome-wide association studies have listed at least 19 WFS1 variants that are associated with type 2 diabetes (T2D) and metabolic traits. It has been suggested that miRNA binding sites on WFS1 play a critical role in the regulation of the wolframin protein, and loss of WFS1 function may lead to the pathogenesis of diabetes. In the Hungarian population, it was observed that a 3' UTR variant from WFS1, namely rs1046322, influenced the affinity of miR-668 to WFS1 mRNA, and showed a strong association with T2D. In this study, we genotyped a large cohort of 2067 individuals of different ethnicities residing in Kuwait for the WFS1 rs1046322 polymorphism. The cohort included 362 Southeast Asians (SEA), 1045 Arabs, and 660 South Asians (SA). Upon performing genetic association tests, we observed significant associations between the rs1046322 SNP and obesity traits in the SEA population, but not in the Arab or SA populations. The associated traits in SEA cohort were body mass index, BMI (β=1.562, P-value=0.0035, Pemp=0.0072), waist circumference, WC (β=3.163, P-value=0.0197, Pemp=0.0388) and triglyceride, TGL (β=0.224, P-value=0.0340). The association with BMI remained statistically significant even after multiple testing correction. Among the SEA individuals, carriers of the effect allele at the SNP had significantly higher BMI [mean of 27.63 (3.6) Kg/m2], WC [mean of 89.9 (8.1) cm], and TGL levels [mean of 1.672 (0.8) mmol/l] than non-carriers of the effect allele. Our findings suggest a role for WFS1 in obesity, which is a risk factor for diabetes. The study also emphasizes the significant role the ethnic background may play in determining the effect of genetic variants on susceptibility to metabolic diseases.

Privacy-preserving federated genome-wide association studies via dynamic sampling

MOTIVATION

Genome-wide association studies (GWAS) benefit from the increasing availability of genomic data and cross-institution collaborations. However, sharing data across institutional boundaries jeopardizes medical data confidentiality and patient privacy. While modern cryptographic techniques provide formal secure guarantees, the substantial communication and computational overheads hinder the practical application of large-scale collaborative GWAS.

RESULTS

This work introduces an efficient framework for conducting collaborative GWAS on distributed datasets, maintaining data privacy without compromising the accuracy of the results. We propose a novel two-step strategy aimed at reducing communication and computational overheads, and we employ iterative and sampling techniques to ensure accurate results. We instantiate our approach using logistic regression, a commonly used statistical method for identifying associations between genetic markers and the phenotype of interest. We evaluate our proposed methods using two real genomic datasets and demonstrate their robustness in the presence of between-study heterogeneity and skewed phenotype distributions using a variety of experimental settings. The empirical results show the efficiency and applicability of the proposed method and the promise for its application for large-scale collaborative GWAS.

AVAILABILITY AND IMPLEMENTATION

The source code and data are available at https://github.com/amioamo/TDS.

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.

Genome wide association joint analysis reveals 99 risk loci for pain susceptibility and pleiotropic relationships with psychiatric, metabolic, and immunological traits

Chronic pain is at epidemic proportions in the United States, represents a significant burden on our public health system, and is coincident with a growing opioid crisis. While numerous genome-wide association studies have been reported for specific pain-related traits, many of these studies were underpowered, and the genetic relationship among these traits remains poorly understood. Here, we conducted a joint analysis of genome-wide association study summary statistics from seventeen pain susceptibility traits in the UK Biobank. This analysis revealed 99 genome-wide significant risk loci, 65 of which overlap loci identified in earlier studies. The remaining 34 loci are novel. We applied leave-one-trait-out meta-analyses to evaluate the influence of each trait on the joint analysis, which suggested that loci fall into four categories: loci associated with nearly all pain-related traits; loci primarily associated with a single trait; loci associated with multiple forms of skeletomuscular pain; and loci associated with headache-related pain. Overall, 664 genes were mapped to the 99 loci by genomic proximity, eQTLs, and chromatin interaction and ~15% of these genes showed differential expression in individuals with acute or chronic pain compared to healthy controls. Risk loci were enriched for genes involved in neurological and inflammatory pathways. Genetic correlation and two-sample Mendelian randomization indicated that psychiatric, metabolic, and immunological traits mediate some of these effects.

Phenotypic variance partitioning by transcriptomic gene expression levels and environmental variables for anthropometric traits using GTEx data

Phenotypic variation in human is the results of genetic variation and environmental influences. Understanding the contribution of genetic and environmental components to phenotypic variation is of great interest. The variance explained by genome-wide single nucleotide polymorphisms (SNPs) typically represents a small proportion of the phenotypic variance for complex traits, which may be because the genome is only a part of the whole biological process to shape the phenotypes. In this study, we propose to partition the phenotypic variance of three anthropometric traits, using gene expression levels and environmental variables from GTEx data. We use the gene expression of four tissues that are deemed relevant for the anthropometric traits (two adipose tissues, skeletal muscle tissue and blood tissue). Additionally, we estimate the transcriptome-environment correlation that partly underlies the phenotypes of the anthropometric traits. We found that genetic factors play a significant role in determining body mass index (BMI), with the proportion of phenotypic variance explained by gene expression levels of visceral adipose tissue being 0.68 (SE = 0.06). However, we also observed that environmental factors such as age, sex, ancestry, smoking status, and drinking alcohol status have a small but significant impact (0.005, SE = 0.001). Interestingly, we found a significant negative correlation between the transcriptomic and environmental effects on BMI (transcriptome-environment correlation = -0.54, SE = 0.14), suggesting an antagonistic relationship. This implies that individuals with lower genetic profiles may be more susceptible to the effects of environmental factors on BMI, while those with higher genetic profiles may be less susceptible. We also show that the estimated transcriptomic variance varies across tissues, e.g., the gene expression levels of whole blood tissue and environmental variables explain a lower proportion of BMI phenotypic variance (0.16, SE = 0.05 and 0.04, SE = 0.004 respectively). We observed a significant positive correlation between transcriptomic and environmental effects (1.21, SE = 0.23) for this tissue. In conclusion, phenotypic variance partitioning can be done using gene expression and environmental data even with a small sample size (n = 838 from GTEx data), which can provide insights into how the transcriptomic and environmental effects contribute to the phenotypes of the anthropometric traits.

Whole Exome Sequencing Reveals Rare Variants in Genes Associated with Metabolic Disorders in Women with PCOS

Background

Polycystic ovary syndrome (PCOS) is a complex genetic trait, the pathogenesis of which is governed by an interplay of genetic and epigenetic factors. However, the aetiology of PCOS is not fully understood.

Aims

The objective of this study was to investigate the genetic causes of PCOS by identifying rare variants in genes implicated in its pathophysiology.

Settings and Design

This was a hospital-based observational study.

Materials and Methods

We used whole-exome sequencing for 52 PCOS women to identify the rare variants in genes related to PCOS pathogenesis. Subsequently, we analysed these variants using in silico prediction software to determine their functional effects. We then assessed the relationship between these variants and the clinical outcomes of the patients.

Statistical Analysis Used

Student's t-test and Fisher's exact test were used to compare clinical parameters and frequency differences amongst PCOS patients with and without variants.

Results

A total of four rare exonic variants in obesity- and hyperinsulinaemia-related genes including UCP1 (p.Thr227Ile), UCP2 (p.Arg88Cys), IRS1 (p.Ser892Gly) and GHRL (p.Leu72Met) were identified in eight patients. Significant differences were observed between the patients carrying variants and those without variants. PCOS patients with identified variants exhibited significantly higher average body mass index and fasting insulin levels of PCOS subjects with identified variants compared to those without variants (P < 0.05). Additionally, there were significant differences in the variant frequencies of four variants when compared to the population database (P < 0.05).

Conclusion

This study shows a prevalence of rare variants in obesity and hyperinsulinaemia-related genes in a cohort of PCOS women, thereby underscoring the impact of the identified rare variants on the development of obesity and associated metabolic derangements in PCOS women.

Integrative neurocircuits that control metabolism and food intake

Systemic metabolism has to be constantly adjusted to the variance of food intake and even be prepared for anticipated changes in nutrient availability. Therefore, the brain integrates multiple homeostatic signals with numerous cues that predict future deviations in energy supply. Recently, our understanding of the neural pathways underlying these regulatory principles-as well as their convergence in the hypothalamus as the key coordinator of food intake, energy expenditure, and glucose metabolism-have been revealed. These advances have changed our view of brain-dependent control of metabolic physiology. In this Review, we discuss new concepts about how alterations in these pathways contribute to the development of prevalent metabolic diseases such as obesity and type 2 diabetes mellitus and how this emerging knowledge may provide new targets for their treatment.

Human microglial state dynamics in Alzheimer's disease progression

Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer's disease (AD) pathological phenotypes. We annotate 12 microglial transcriptional states, including AD-dysregulated homeostatic, inflammatory, and lipid-processing states. We identify 1,542 AD-differentially-expressed genes, including both microglia-state-specific and disease-stage-specific alterations. By integrating epigenomic, transcriptomic, and motif information, we infer upstream regulators of microglial cell states, gene-regulatory networks, enhancer-gene links, and transcription-factor-driven microglial state transitions. We demonstrate that ectopic expression of our predicted homeostatic-state activators induces homeostatic features in human iPSC-derived microglia-like cells, while inhibiting activators of inflammation can block inflammatory progression. Lastly, we pinpoint the expression of AD-risk genes in microglial states and differential expression of AD-risk genes and their regulators during AD progression. Overall, we provide insights underlying microglial states, including state-specific and AD-stage-specific microglial alterations at unprecedented resolution.

Uncovering structural variants associated with body weight and obesity risk in labrador retrievers: a genome-wide study

Although obesity in the domestic dog (Canis lupus familiaris) is known to decrease well-being and shorten lifespan, the genetic risk variants associated with canine obesity remain largely unknown. In our study, which focused on the obesity-prone Labrador Retriever breed, we conducted a genome-wide analysis to identify structural variants linked to body weight and obesity. Obesity status was based on a 5-point body condition score (BCS) and the obese dog group included all dogs with a BCS of 5, along with dogs with the highest body weight within the BCS 4 group. Data from whole-gene sequencing of fifty dogs, including 28 obese dogs, were bioinformatically analyzed to identify potential structural variants that varied in frequency between obese and healthy dogs. The seven most promising variants were further analyzed by droplet digital PCR in a group of 110 dogs, including 63 obese. Our statistical evidence suggests that common structural mutations in or near six genes, specifically ALPL, KCTD8, SGSM1, SLC12A6, RYR3, and VPS26C, may contribute to the variability observed in body weight and body condition scores among Labrador Retriever dogs. These findings emphasize the need for additional research to validate the associations and explore the specific functions of these genes in relation to canine obesity.

Interaction between genetic susceptibility to obesity and food intake on BMI in Finnish school-aged children

Diet modulates the genetic risk of obesity, but the modulation has been rarely studied using genetic risk scores (GRSs) in children. Our objectives were to identify single nucleotide polymorphisms (SNPs) that drive the interaction of specific foods with obesity and combine these into GRSs. Genetic and food frequency data from Finnish Health in Teens study was utilized. In total, 1142 11-year-old subjects were genotyped on the Metabochip array. BMI-GRS with 30 well-known SNPs was computed and the interaction of individual SNPs with food items and their summary dietary scores were examined in relation to age- and sex-specific BMI z-score (BMIz). The whole BMI-GRS interacted with several foods on BMIz. We identified 7-11 SNPs responsible for each interaction and these were combined into food-specific GRS. The most predominant interaction was witnessed for pizza (p < 0.001): the effect on BMIz was b - 0.130 (95% CI - 0.23; - 0.031) in those with low-risk, and 0.153 (95% CI 0.072; 0.234) in high-risk. Corresponding, but weaker interactions were verified for sweets and chocolate, sugary juice drink, and hamburger and hotdog. In total 5 SNPs close to genes NEGR1, SEC16B, TMEM18, GNPDA2, and FTO were shared between these interactions. Our results suggested that children genetically prone to obesity showed a stronger association of unhealthy foods with BMIz than those with lower genetic susceptibility. Shared SNPs of the interactions suggest common differences in metabolic gene-diet interactions, which warrants further investigation.

Obesity Prediction in Young Adults from the Jerusalem Perinatal Study: Contribution of Polygenic Risk and Early Life Exposures

We assessed whether adding early life exposures to a model based on polygenic risk score (PRS) improves prediction of obesity risk. We used a birth cohort with data at birth and BMI and waist circumference (WC) measured at age 32. The PRS was composed of SNPs identified in GWAS for BMI. Linear and logistic models were used to explore associations with obesity-related phenotypes. Improvement in prediction was assessed using measures of model discrimination (AUC), and net reclassification improvement (NRI). One SD change in PRS was associated with a significant increase in BMI and WC. These associations were slightly attenuated (13.7%-14.2%) with the addition of early life exposures to the model. Also, higher maternal pre-pregnancy BMI was associated with increase in offspring BMI and WC (p<0.001). For prediction obesity (BMI ≥ 30), the addition of early life exposures to the PRS model significantly increase the AUC from 0.69 to 0.73. At an obesity risk threshold of 15%, the addition of early life exposures to the PRS model provided a significant improvement in reclassification of obesity (NRI, 0.147; 95% CI 0.068-0.225). We conclude that inclusion of early life exposures to a model based on PRS improves obesity risk prediction in an Israeli population-sample.

Identification of Zip8-correlated hub genes in pulmonary hypertension by informatic analysis

Background

Pulmonary hypertension (PH) is a syndrome characterized by marked remodeling of the pulmonary vasculature and increased pulmonary vascular resistance, ultimately leading to right heart failure and even death. The localization of Zrt/Irt-like Protein 8 (ZIP8, a metal ion transporter, encoded by SLC39A8) was abundantly in microvasculature endothelium and its pivotal role in the lung has been demonstrated. However, the role of Zip8 in PH remains unclear.

Methods

Bioinformatics analysis was employed to identify SLC39A8 expression patterns and differentially expressed genes (DEGs) between PH patients and normal controls (NC), based on four datasets (GSE24988, GSE113439, GSE117261, and GSE15197) from the Biotechnology Gene Expression Omnibus (NCBI GEO) database. Gene set enrichment analysis (GSEA) was performed to analyze signaling pathways enriched for DEGs. Hub genes were identified by cytoHubba analysis in Cytoscape. Reverse transcriptase-polymerase chain reaction was used to validate SLC39A8 and its correlated metabolic DEGs expression in PH (SU5416/Hypoxia) mice.

Results

SLC39A8 expression was downregulated in PH patients, and this expression pattern was validated in PH (SU5416/Hypoxia) mouse lung tissue. SLC39A8-correlated genes were mainly enriched in the metabolic pathways. Within these SLC39A8-correlated genes, 202 SLC39A8-correlated metabolic genes were screened out, and seven genes were identified as SLC39A8-correlated metabolic hub genes. The expression patterns of hub genes were analyzed between PH patients and controls and further validated in PH mice. Finally, four genes (Fasn, Nsdhl, Acat2, and Acly) were downregulated in PH mice. However, there were no significant differences in the expression of the other three hub genes between PH mice and controls. Of the four genes, Fasn and Acly are key enzymes in fatty acids synthesis, Nsdhl is involved in cholesterol synthesis, and Acat2 is implicated in cholesterol metabolic transformation. Taken together, these results provide novel insight into the role of Zip8 in PH.

A multilocus genetic risk score for obesity: Association with BMI and metabolic alterations in a cohort with severe obesity

Genome wide association studies have identified numerous single nucleotide polymorphisms (SNPs) associated with obesity, yet effect sizes of individual SNPs are small. Therefore, the aim of our study was to investigate whether a genetic risk score (GRS) comprising risk alleles of SNPs identified in the GIANT consortium meta-analyses shows association with body mass index (BMI) and other BMI related metabolic alterations in a cohort with an extreme phenotype. Genotyping of 93 SNPs was performed in 314 obese individuals (mean BMI 40.5 ± 7.8 kg/m², aged 45 ± 12 years), participating in a standardized weight reduction program, and in 74 lean controls (mean BMI 24.6 ± 3.3 kg/m², aged 41.7 ± 13.4 years). Allele numbers of all 93 SNPs were added to a GRS. Anthropometric parameters, parameters of glucose/insulin and lipid metabolism were assessed standardized after a 12 hours fast. GRS was significantly different between controls and obese individuals (unweighted GRS: 86.6 vs 89.0, P = .002; weighted GRS: 84.9 vs 88.3, P = .005). Furthermore, linear regression analysis showed significant associations of GRS with BMI ( P < .0001), weight ( P = .0005), waist circumference ( P = .0039), fat mass ( P < .0001) and epicardial fat thickness ( P = .0032), yet with small effect sizes ( r ² < 0.06). In conclusion, in our study GRS could differentiate between extreme obese and lean individuals, and was associated with BMI and its related traits, yet with small effect sizes.

Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants

Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.

Genetic determinants of thyroid function in children

OBJECTIVE

Genome-wide association studies in adults have identified 42 loci associated with thyroid stimulating hormone (TSH) and 21 loci associated with free thyroxine (FT4) concentrations. While biologically plausible, age-dependent effects have not been assessed. We aimed to study the association of previously identified genetic determinants of TSH and FT4 with TSH and FT4 concentrations in newborns and (pre)school children.

METHODS

We selected participants from three population-based prospective cohorts with data on genetic variants and thyroid function: Generation R (N = 2169 children, mean age 6 years; N = 2388 neonates, the Netherlands), the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 3382, age 7.5 years, United Kingdom), and the Brisbane Longitudinal Twin Study (BLTS; N = 1680, age 12.1 years, Australia). The association of single nucleotide polymorphisms (SNPs) with TSH and FT4 concentrations was studied with multivariable linear regression models. Weighted polygenic risk scores (PRSs) were defined to combine SNP effects.

RESULTS

In childhood, 30/60 SNPs were associated with TSH and 11/31 SNPs with FT4 after multiple testing correction. The effect sizes for AADAT, GLIS3, TM4SF4, and VEGFA were notably larger than in adults. The TSH PRS explained 5.3%-8.4% of the variability in TSH concentrations; the FT4 PRS explained 1.5%-4.2% of the variability in FT4 concentrations. Five TSH SNPs and no FT4 SNPs were associated with thyroid function in neonates.

CONCLUSIONS

The effects of many known thyroid function SNPs are already apparent in childhood and some might be notably larger in children as compared to adults. These findings provide new knowledge about genetic regulation of thyroid function in early life.

The suppression of hyperlipid diet-induced ferroptosis of vascular smooth muscle cells protests against atherosclerosis independent of p53/SCL7A11/GPX4 axis

Ferroptosis as a novel programmed cell death that involves metabolic dysfunction due to iron-dependent excessive lipid peroxidation has been implicated in atherosclerosis (AS) development characterized by disrupted lipid metabolism, but the atherogenic role of ferroptosis in vascular smooth muscle cells (VSMCs), which are principal components of atherosclerotic plaque fibrous cap, remains unclear. The aim of this study was to determine the effects of ferroptosis on AS induced by lipid overload, and the effects of that on VSMCs ferroptosis. We found intraperitoneal injection of Fer-1, a ferroptosis inhibitor, ameliorated obviously high-fat diet-induced high plasma levels of triglycerides, total cholesterol, low-density lipoprotein, glucose and atherosclerotic lesions in ApoE-/- mice. Moreover, in vivo and in vitro, Fer-1 reduced the iron accumulation of atherosclerotic lesions through affecting the expression of TFR1, FTH, and FTL in VSMCs. Interestingly, Fer-1 did augment nuclear factor E2-related factor 2/ferroptosis suppressor protein 1 to enhance endogenous resistance to lipid peroxidation, but not classic p53/SCL7A11/GPX4. Those observations indicated inhibition of VSMCs ferroptosis can improve AS lesions independent of p53/SLC7A11/GPX4, which preliminarily revealed the potential mechanism of ferroptosis in aortic VSMCs on AS and provided new therapeutic strategies and targets for AS.

Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample

OBJECTIVE

Recent genome-wide association studies (GWASs) of alcohol-related phenotypes have uncovered key differences in the underlying genetic architectures of alcohol consumption and alcohol use disorder (AUD), with the two traits having opposite genetic correlations with psychiatric disorders. Understanding the genetic factors that underlie the transition from heavy drinking to AUD has important theoretical and clinical implications.

METHODS

The authors used longitudinal data from the cross-ancestry Million Veteran Program sample to identify 1) novel loci associated with AUD and alcohol consumption (measured by the score on the consumption subscale of the Alcohol Use Disorders Identification Test [AUDIT-C]), 2) the impact of phenotypic variation on genetic discovery, and 3) genetic variants with direct effects on AUD that are not mediated through alcohol consumption.

RESULTS

The authors identified 26 loci associated with AUD and 22 loci associated with AUDIT-C score, including ancestry-specific and novel loci. In secondary GWASs that excluded individuals who report abstinence, the authors identified seven additional loci for AUD and eight additional loci for AUDIT-C score. Although the heterogeneity of the abstinent group biases the GWAS findings, unique variance between alcohol consumption and disorder remained after the abstinent group was excluded. Finally, using mediation analysis, the authors identified a set of variants with effects on AUD that are not mediated through alcohol consumption.

CONCLUSIONS

Differences in genetic architecture between alcohol consumption and AUD are consistent with their having different biological contributions. Genetic variants with direct effects on AUD are potentially relevant to understanding the transition from heavy alcohol consumption to AUD and may be targets for translational prevention and treatment efforts.

Maternal Age at Menarche Gene Polymorphisms Are Associated with Offspring Birth Weight

In this study, the association between maternal age at menarche (AAM)-related polymorphisms and offspring birth weight (BW) was studied. The work was performed on a sample of 716 pregnant women and their newborns. All pregnant women underwent genotyping of 50 SNPs of AAM candidate genes. Regression methods (linear and Model-Based Multifactor Dimensionality Reduction (MB-MDR)) with permutation procedures (the indicator pperm was calculated) were used to identify the correlation between SNPs and newborn weight (transformed BW values were analyzed) and in silico bioinformatic examination was applied to assess the intended functionality of BW-associated loci. Four AAM-related genetic variants were BW-associated including genes such as POMC (rs7589318) (βadditive = 0.202/pperm = 0.015), KDM3B (rs757647) (βrecessive = 0.323/pperm = 0.005), INHBA (rs1079866) (βadditive = 0.110/pperm = 0.014) and NKX2-1 (rs999460) (βrecessive = -0.176/pperm = 0.015). Ten BW-significant models of interSNPs interactions (pperm ≤ 0.001) were identified for 20 polymorphisms. SNPs rs7538038 KISS1, rs713586 RBJ, rs12324955 FTO and rs713586 RBJ-rs12324955 FTO two-locus interaction were included in the largest number of BW-associated models (30% models each). BW-associated AAM-linked 22 SNPs and 350 proxy loci were functionally related to 49 genes relevant to pathways such as the hormone biosynthesis/process and female/male gonad development. In conclusion, maternal AMM-related genes polymorphism is associated with the offspring BW.

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.

Association of rs9939609 in FTO with BMI among Polynesian peoples living in Aotearoa New Zealand and other Pacific nations

The fat mass and obesity associated (FTO) locus consistently associates with higher body mass index (BMI) across diverse ancestral groups. However, previous small studies of people of Polynesian ancestries have failed to replicate the association. In this study, we used Bayesian meta-analysis to test rs9939609, the most replicated FTO variant, for association with BMI with a large sample (n = 6095) of Aotearoa New Zealanders of Polynesian (Māori and Pacific) ancestry and of Samoan people living in the Independent State of Samoa and in American Samoa. We did not observe statistically significant association within each separate Polynesian subgroup. Bayesian meta-analysis of the Aotearoa New Zealand Polynesian and Samoan samples resulted in a posterior mean effect size estimate of +0.21 kg/m2, with a 95% credible interval [+0.03 kg/m2, +0.39 kg/m2]. While the Bayes Factor (BF) of 0.77 weakly favors the null, the BF = 1.4 Bayesian support interval is [+0.04, +0.20]. These results suggest that rs9939609 in FTO may have a similar effect on mean BMI in people of Polynesian ancestries as previously observed in other ancestral groups.

A Mendelian randomization study on causal effects of 25(OH) vitamin D levels on diabetic nephropathy

BACKGROUND

Vitamin D supplementation is associated with a lower incidence of diabetic nephropathy (DN); however, whether this association is causative is uncertain.

METHODS

We used two-sample Mendelian randomization to examine the causal influence of vitamin D on diabetic nephropathy in 7,751 individuals with type I diabetes-related nephropathy (T1DN) and 9,933 individuals with type II diabetes-related nephropathy (T2DN). Meanwhile, we repeated some previous studies on the influence of KIM-1 (kidney injury molecule 1) and body mass index (BMI) on DN. Additionally, to test the validity of the instruments variable for vitamin D, we conducted two negative controls Mendelian randomization (MR) on breast and prostate cancer, and a positive control MR on multiple sclerosis.

RESULTS

Results of the MR analysis showed that there was no causal association between 25(OH)D with the early/later stage of T1DN (early: OR = 0.903, 95%CI: 0.229 to 3.555; later: OR = 1.213, 95%CI: 0.367 to 4.010) and T2DN (early: OR = 0.588, 95%CI: 0.182 to 1.904; later: OR = 0.904, 95%CI: 0.376 to 2.173), nor with the kidney function of patients with diabetes mellitus: eGFRcyea (creatinine-based estimated GFR) (Beta = 0.007, 95%CI: -0.355 to 0.369)) or UACR (urinary albumin creatinine ratio) (Beta = 0.186, 95%CI: -0.961 to 1.333)).

CONCLUSIONS

We found no evidence that Vitamin D was causally associated with DN or kidney function in diabetic patients.

Gut bacterial metabolism contributes to host global purine homeostasis

The microbes and microbial pathways that influence host inflammatory disease progression remain largely undefined. Here, we show that variation in atherosclerosis burden is partially driven by gut microbiota and is associated with circulating levels of uric acid (UA) in mice and humans. We identify gut bacterial taxa spanning multiple phyla, including Bacillota, Fusobacteriota, and Pseudomonadota, that use multiple purines, including UA as carbon and energy sources anaerobically. We identify a gene cluster that encodes key steps of anaerobic purine degradation and that is widely distributed among gut-dwelling bacteria. Furthermore, we show that colonization of gnotobiotic mice with purine-degrading bacteria modulates levels of UA and other purines in the gut and systemically. Thus, gut microbes are important drivers of host global purine homeostasis and serum UA levels, and gut bacterial catabolism of purines may represent a mechanism by which gut bacteria influence health.

Detection of trait-associated structural variations using short-read sequencing

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

Brain-based gene expression of putative risk genes for anorexia nervosa

The etiology of anorexia nervosa (AN) remains elusive. Recent genome-wide association studies identified the first genes liked to AN which reached genome-wide significance, although our understanding of how these genes confer risk remains preliminary. Here, we leverage the Allen Human Brain Atlas to characterize the spatially distributed gene expression patterns of genes linked to AN in the non-disordered human brain, developing whole-brain maps of AN gene expression. We found that genes associated with AN are most expressed in the brain, relative to all other body tissue types, and demonstrate gene-specific expression patterns which extend to cerebellar, temporal and basal ganglia structures in particular. fMRI meta-analyses reveal that AN gene expression maps correspond with functional brain activity involved in processing and anticipating appetitive and aversive cues. Findings offer novel insights around putative mechanisms through which genes associated with AN may confer risk.

What is Obesity?: Definition as a Disease, with Implications for Care

Advances in the understanding of weight regulation provide the framework for the recognition of obesity as a chronic disease. Lifestyle approaches are foundational in the prevention of obesity and should be continued while weight management interventions, including antiobesity medications and metabolic-bariatric procedures, are offered to eligible patients. Clinical challenges remain, however, including overcoming obesity stigma and bias within the medical community toward medical and surgical approaches, ensuring insurance coverage for obesity management (including medications and surgery), and promoting policies that reverse the upward worldwide trend in obesity and adiposity complications in populations.

Regulation of Satiety by Bdnf-e2-Expressing Neurons through TrkB Activation in Ventromedial Hypothalamus

The transcripts for Bdnf (brain-derived neurotrophic factor), driven by different promoters, are expressed in different brain regions to control different body functions. Specific promoter(s) that regulates energy balance remain unclear. We show that disruption of Bdnf promoters I and II but not IV and VI in mice (Bdnf-e1^-/-, Bdnf-e2^-/-) results in obesity. Whereas Bdnf-e1^-/- exhibited impaired thermogenesis, Bdnf-e2^-/- showed hyperphagia and reduced satiety before the onset of obesity. The Bdnf-e2 transcripts were primarily expressed in ventromedial hypothalamus (VMH), a nucleus known to regulate satiety. Re-expressing Bdnf-e2 transcript in VMH or chemogenetic activation of VMH neurons rescued the hyperphagia and obesity of Bdnf-e2^-/- mice. Deletion of BDNF receptor TrkB in VMH neurons in wildtype mice resulted in hyperphagia and obesity, and infusion of TrkB agonistic antibody into VMH of Bdnf-e2^-/- mice alleviated these phenotypes. Thus, Bdnf-e2-transcripts in VMH neurons play a key role in regulating energy intake and satiety through TrkB pathway.

Increased meso-striatal connectivity mediates trait impulsivity in FTO variant carriers

Objective

While variations in the first intron of the fat mass and obesity-associated gene (FTO, rs9939609 T/A variant) have long been identified as a major contributor to polygenic obesity, the mechanisms underlying weight gain in risk allele carriers still remain elusive. On a behavioral level, FTO variants have been robustly linked to trait impulsivity. The regulation of dopaminergic signaling in the meso-striatal neurocircuitry by these FTO variants might represent one mechanism for this behavioral alteration. Notably, recent evidence indicates that variants of FTO also modulate several genes involved in cell proliferation and neuronal development. Hence, FTO polymorphisms might establish a predisposition to heightened trait impulsivity during neurodevelopment by altering structural meso-striatal connectivity. We here explored whether the greater impulsivity of FTO variant carriers was mediated by structural differences in the connectivity between the dopaminergic midbrain and the ventral striatum.

Methods

Eighty-seven healthy normal-weight volunteers participated in the study; 42 FTO risk allele carriers (rs9939609 T/A variant, FTO ⁺ group: AT, AA) and 39 non-carriers (FTO ^- group: TT) were matched for age, sex and body mass index (BMI). Trait impulsivity was assessed via the Barratt Impulsiveness Scale (BIS-11) and structural connectivity between the ventral tegmental area/substantia nigra (VTA/SN) and the nucleus accumbens (NAc) was measured via diffusion weighted MRI and probabilistic tractography.

Results

We found that FTO risk allele carriers compared to non-carriers, demonstrated greater motor impulsivity (p = 0.04) and increased structural connectivity between VTA/SN and the NAc (p< 0.05). Increased connectivity partially mediated the effect of FTO genetic status on motor impulsivity.

Conclusion

We report altered structural connectivity as one mechanism by which FTO variants contribute to increased impulsivity, indicating that FTO variants may exert their effect on obesity-promoting behavioral traits at least partially through neuroplastic alterations in humans.

Fast and accurate Bayesian polygenic risk modeling with variational inference

The advent of large-scale genome-wide association studies (GWASs) has motivated the development of statistical methods for phenotype prediction with single-nucleotide polymorphism (SNP) array data. These polygenic risk score (PRS) methods use a multiple linear regression framework to infer joint effect sizes of all genetic variants on the trait. Among the subset of PRS methods that operate on GWAS summary statistics, sparse Bayesian methods have shown competitive predictive ability. However, most existing Bayesian approaches employ Markov chain Monte Carlo (MCMC) algorithms, which are computationally inefficient and do not scale favorably to higher dimensions, for posterior inference. Here, we introduce variational inference of polygenic risk scores (VIPRS), a Bayesian summary statistics-based PRS method that utilizes variational inference techniques to approximate the posterior distribution for the effect sizes. Our experiments with 36 simulation configurations and 12 real phenotypes from the UK Biobank dataset demonstrated that VIPRS is consistently competitive with the state-of-the-art in prediction accuracy while being more than twice as fast as popular MCMC-based approaches. This performance advantage is robust across a variety of genetic architectures, SNP heritabilities, and independent GWAS cohorts. In addition to its competitive accuracy on the "White British" samples, VIPRS showed improved transferability when applied to other ethnic groups, with up to 1.7-fold increase in R2 among individuals of Nigerian ancestry for low-density lipoprotein (LDL) cholesterol. To illustrate its scalability, we applied VIPRS to a dataset of 9.6 million genetic markers, which conferred further improvements in prediction accuracy for highly polygenic traits, such as height.

Association of SULT1A2 rs1059491 with obesity and dyslipidaemia in southern Chinese adults

In the sulfotransferase (SULT) superfamily, members of the SULT1 family mainly catalyse the sulfonation reaction of phenolic compounds, which is involved in the phase II metabolic detoxification process and plays a key role in endocrine homeostasis. A coding variant rs1059491 in the SULT1A2 gene has been reported to be associated with childhood obesity. This study aimed to investigate the association of rs1059491 with the risk of obesity and cardiometabolic abnormalities in adults. This case‒control study included 226 normal weight, 168 overweight and 72 obese adults who underwent a health examination in Taizhou, China. Genotyping of rs1059491 was performed by Sanger sequencing in exon 7 of the SULT1A2 coding region. Chi-squared tests, one-way ANOVA, and logistic regression models were applied. The minor allele frequencies of rs1059491 in the overweight combined with obesity and control groups were 0.0292 and 0.0686, respectively. No differences in weight and body mass index were detected between the TT genotype and GT + GG genotype under the dominant model, but the levels of serum triglycerides were significantly lower in G-allele carriers than in non-G-allele carriers (1.02 (0.74-1.32) vs. 1.35 (0.83-2.13) mmol/L, P = 0.011). The GT + GG genotype of rs1059491 versus the TT genotype reduced the risk of overweight and obesity by 54% (OR 0.46, 95% CI 0.22-0.96, P = 0.037) after adjusting for sex and age. Similar results were observed for hypertriglyceridaemia (OR 0.25, 95% CI 0.08-0.74, P = 0.013) and dyslipidaemia (OR 0.37, 95% CI 0.17-0.83, P = 0.015). However, these associations disappeared after correction for multiple tests. This study revealed that the coding variant rs1059491 is nominally associated with a decreased risk of obesity and dyslipidaemia in southern Chinese adults. The findings will be validated in larger studies including more detailed information on genetic background, lifestyle and weight change with age.

Loss of hepatic manganese transporter ZIP8 disrupts serum transferrin glycosylation and the glutamate-glutamine cycle

BACKGROUND

ZIP8, encoded by SLC39A8, is a membrane transporter that facilitates the cellular uptake of divalent biometals including zinc (Zn), manganese (Mn), and iron (Fe). The hepatic system has long been accepted as the central modulator for whole-body biometal distribution. Earlier investigations suggest the propensity of ZIP8 to prioritize Mn influx, as opposed to Fe or Zn, in hepatocytes. Hepatic ZIP8 Mn transport is crucial for maintaining homeostasis of various Mn-dependent metalloenzymes and their associated pathways. Herein, we hypothesize that a drastic decrease in systemic Mn, via the loss of hepatic ZIP8, disrupts two unique cellular pathways, post-translational glycosylation and the glutamate-glutamine cycle.

METHODS

ZIP8 liver-specific knockout (LSKO) mice were chosen in an attempt to substantially decrease whole-body Mn levels. To further elucidate the role of Mn in serum glycosylation, a Mn-deficient diet was adopted in conjunction with the LSKO mice to model a near-complete loss of systemic Mn. After the treatment course, transferrin sialylation profiles were determined using imaged capillary isoelectric focusing (icIEF). We also investigated the role of Mn in the glutamate-glutamine cycle; the conversion of glutamate to glutamine in F/F and LSKO mice was assessed by the glutamine/glutamate ratio in cerebrospinal fluid (CSF) via HPLC-MS. An open-field study was ultimately conducted to check if these mice displayed atypical behavior.

RESULTS

Two major biological pathways were found to be significantly altered due to the loss of hepatic ZIP8. We identified a disparity between F/F and LSKO transferrin sialylation profiles that were exacerbated under a Mn-deficient diet. Additionally, we discovered a neurotransmitter imbalance between the levels of glutamine and glutamate, exclusive to LSKO mice. This was characterized by the decreased glutamine/glutamate ratio in CSF. Secondary to the neurotransmitter alteration, LSKO mice exhibited an increase in locomotor activity in an open-field.

CONCLUSION

Our model successfully established a connection between the loss of hepatic ZIP8 and two Mn-dependent cellular pathways, namely, protein glycosylation and the glutamate-glutamine cycle.

Exercise training remodels inguinal white adipose tissue through adaptations in innervation, vascularization, and the extracellular matrix

Inguinal white adipose tissue (iWAT) is essential for the beneficial effects of exercise training on metabolic health. The underlying mechanisms for these effects are not fully understood, and here, we test the hypothesis that exercise training results in a more favorable iWAT structural phenotype. Using biochemical, imaging, and multi-omics analyses, we find that 11 days of wheel running in male mice causes profound iWAT remodeling including decreased extracellular matrix (ECM) deposition and increased vascularization and innervation. We identify adipose stem cells as one of the main contributors to training-induced ECM remodeling, show that the PRDM16 transcriptional complex is necessary for iWAT remodeling and beiging, and discover neuronal growth regulator 1 (NEGR1) as a link between PRDM16 and neuritogenesis. Moreover, we find that training causes a shift from hypertrophic to insulin-sensitive adipocyte subpopulations. Exercise training leads to remarkable adaptations to iWAT structure and cell-type composition that can confer beneficial changes in tissue metabolism.

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

Leveraging related health phenotypes for polygenic prediction of impulsive choice, impulsive action, and impulsive personality traits in 1534 European ancestry community adults

Impulsivity refers to a number of conceptually related phenotypes reflecting self-regulatory capacity that are considered promising endophenotypes for mental and physical health. Measures of impulsivity can be broadly grouped into three domains, namely, impulsive choice, impulsive action, and impulsive personality traits. In a community-based sample of ancestral Europeans (n = 1534), we conducted genome-wide association studies (GWASs) of impulsive choice (delay discounting), impulsive action (behavioral inhibition), and impulsive personality traits (UPPS-P), and evaluated 11 polygenic risk scores (PRSs) of phenotypes previously linked to self-regulation. Although there were no individual genome-wide significant hits, the neuroticism PRS was positively associated with negative urgency (adjusted R²  = 1.61%, p = 3.6 × 10^-7 ) and the educational attainment PRS was inversely associated with delay discounting (adjusted R²  = 1.68%, p = 2.2 × 10^-7 ). There was also evidence implicating PRSs of attention-deficit/hyperactivity disorder, externalizing, risk-taking, smoking cessation, smoking initiation, and body mass index with one or more impulsivity phenotypes (adjusted R² s: 0.35%-1.07%; FDR adjusted ps = 0.05-0.0006). These significant associations between PRSs and impulsivity phenotypes are consistent with established genetic correlations. The combined PRS explained 0.91%-2.46% of the phenotypic variance for individual impulsivity measures, corresponding to 8.7%-32.5% of their reported single-nucleotide polymorphism (SNP)-based heritability, suggesting a non-negligible portion of the SNP-based heritability can be recovered by PRSs. These results support the predictive validity and utility of PRSs, even derived from related phenotypes, to inform the genetics of impulsivity phenotypes.

Prebiotic and Probiotic Modulation of the Microbiota-Gut-Brain Axis in Depression

Emerging evidence demonstrates that alterations to the gut microbiota can affect mood, suggesting that the microbiota-gut-brain (MGB) axis contributes to the pathogenesis of depression. Many of these pathways overlap with the way in which the gut microbiota are thought to contribute to metabolic disease progression and obesity. In rodents, prebiotics and probiotics have been shown to modulate the composition and function of the gut microbiota. Together with germ-free rodent models, probiotics have provided compelling evidence for a causal relationship between microbes, microbial metabolites, and altered neurochemical signalling and inflammatory pathways in the brain. In humans, probiotic supplementation has demonstrated modest antidepressant effects in individuals with depressive symptoms, though more studies in clinically relevant populations are needed. This review critically discusses the role of the MGB axis in depression pathophysiology, integrating preclinical and clinical evidence, as well as the putative routes of communication between the microbiota-gut interface and the brain. A critical overview of the current approaches to investigating microbiome changes in depression is provided. To effectively translate preclinical breakthroughs in MGB axis research into novel therapies, rigorous placebo-controlled trials alongside a mechanistic and biochemical understanding of prebiotic and probiotic action are required from future research.

Variation in responses to incretin therapy: Modifiable and non-modifiable factors

Type 2 diabetes (T2D) and obesity have reached epidemic proportions. Incretin therapy is the second line of treatment for T2D, improving both blood glucose regulation and weight loss. Glucagon-like peptide-1 (GLP-1) and glucose-stimulated insulinotropic polypeptide (GIP) are the incretin hormones that provide the foundations for these drugs. While these therapies have been highly effective for some, the results are variable. Incretin therapies target the class B G protein-coupled receptors GLP-1R and GIPR, expressed mainly in the pancreas and the hypothalamus, while some therapeutical approaches include additional targeting of the related glucagon receptor (GCGR) in the liver. The proper functioning of these receptors is crucial for incretin therapy success and here we review several mechanisms at the cellular and molecular level that influence an individual's response to incretin therapy.

Genome-wide association study reveals a genomic region on SSC7 simultaneously associated with backfat thickness, skin thickness and carcass length in a Large White × Tongcheng advanced generation intercross resource population

In order to identify important genetic markers associated with backfat thickness, skin thickness and carcass length, we first constructed Large White × Tongcheng (Chinese local breed), an advanced generation intercross population, then performed a genome-wide association study (GWAS) to reveal the key genomic region associated with these traits through whole genome sequencing. The GWAS results of backfat thickness, skin thickness and carcass length showed that all the most significant SNPs associated with these three traits were located on SSC7, and that 14.9, 27.0 and 21.1% of phenotypic variances were explained by these three SNPs, respectively. Through linkage disequilibrium analysis, we found that a 66.9 kb (30.23-30.31 Mb) genetic region was overlapped among these three traits, and that NUDT3 and HMGA1 were identified as major candidate genes for backfat thickness and carcass length, and GRM4 as a potential candidate gene for skin thickness. In addition, 13 highly linked SNPs significantly associated with the three traits were also identified in overlapped region, and three completely linked SNPs formed two haplotypes Q and q. The backfat thickness of individuals with the qq genotype was significantly lower than that of individuals with the QQ genotype, but their carcass length and skin thickness were significantly higher than those with the QQ genotype. Our detected candidate genes and SNPs will provide the foundation for genetic improvement of these three traits.

Body composition and lung cancer-associated cachexia in TRACERx

Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC.

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.

Social isolation exacerbates diet-induced obesity and peripheral inflammation in young male mice under thermoneutrality

Social isolation (SI) is associated with an increased risk of mortality and various chronic diseases-including obesity-in humans. Murine studies probing SI metabolic outcomes remain inconsistent, due in part to a lack of consideration for housing temperature. Such experiments typically occur at room temperature, subjecting mice to chronic cold stress. Single housing prevents social thermoregulation, further exacerbating cold stress and obscuring psychosocial influences on metabolism at room temperature. In this study, C57BL/6 and BALB/c male mice were group- and single-housed under thermoneutral conditions to determine whether SI affects the development of high-fat diet-induced obesity. We report SI promotes weight gain, increases food intake, increases adiposity, worsens glycemic control, reduces insulin signaling, exacerbates systemic and adipose inflammatory responses, and induces a molecular signature within the hypothalamus. This study establishes a murine model that recapitulates the SI-induced propensity for obesity, which may further our understanding of SI's influence on health and disease.

The Genetic Basis of Childhood Obesity: A Systematic Review

Overweight and obesity in childhood and adolescence represents one of the most challenging public health problems of our century owing to its epidemic proportions and the associated significant morbidity, mortality, and increase in public health costs. The pathogenesis of polygenic obesity is multifactorial and is due to the interaction among genetic, epigenetic, and environmental factors. More than 1100 independent genetic loci associated with obesity traits have been currently identified, and there is great interest in the decoding of their biological functions and the gene-environment interaction. The present study aimed to systematically review the scientific evidence and to explore the relation of single-nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with changes in body mass index (BMI) and other measures of body composition in children and adolescents with obesity, as well as their response to lifestyle interventions. Twenty-seven studies were included in the qualitative synthesis, which consisted of 7928 overweight/obese children and adolescents at different stages of pubertal development who underwent multidisciplinary management. The effect of polymorphisms in 92 different genes was assessed and revealed SNPs in 24 genetic loci significantly associated with BMI and/or body composition change, which contribute to the complex metabolic imbalance of obesity, including the regulation of appetite and energy balance, the homeostasis of glucose, lipid, and adipose tissue, as well as their interactions. The decoding of the genetic and molecular/cellular pathophysiology of obesity and the gene-environment interactions, alongside with the individual genotype, will enable us to design targeted and personalized preventive and management interventions for obesity early in life.

Technologies, strategies, and cautions when deconvoluting genome-wide association signals: FTO in focus

Genome-wide association studies have revealed a plethora of genetic variants that correlate with polygenic conditions. However, causal molecular mechanisms have proven challenging to fully define. Without such information, the associations are not physiologically useful or clinically actionable. By reviewing studies of the FTO locus in the genetic etiology of obesity, we wish to highlight advances in the field fueled by the evolution of technical and analytic strategies in assessing the molecular bases for genetic associations. Particular attention is drawn to extrapolating experimental findings from animal models and cell types to humans, as well as technical aspects used to identify long-range DNA interactions and their biological relevance with regard to the associated trait. A unifying model is proposed by which independent obesogenic pathways regulated by multiple FTO variants and genes are integrated at the primary cilium, a cellular antenna where signaling molecules that control energy balance convene.

E26 transformation-specific transcription variant 5 in development and cancer: modification, regulation and function

E26 transformation-specific (ETS) transcription variant 5 (ETV5), also known as ETS-related molecule (ERM), exerts versatile functions in normal physiological processes, including branching morphogenesis, neural system development, fertility, embryonic development, immune regulation, and cell metabolism. In addition, ETV5 is repeatedly found to be overexpressed in multiple malignant tumors, where it is involved in cancer progression as an oncogenic transcription factor. Its roles in cancer metastasis, proliferation, oxidative stress response and drug resistance indicate that it is a potential prognostic biomarker, as well as a therapeutic target for cancer treatment. Post-translational modifications, gene fusion events, sophisticated cellular signaling crosstalk and non-coding RNAs contribute to the dysregulation and abnormal activities of ETV5. However, few studies to date systematically summarized the role and molecular mechanisms of ETV5 in benign diseases and in oncogenic progression. In this review, we specify the molecular structure and post-translational modifications of ETV5. In addition, its critical roles in benign and malignant diseases are summarized to draw a panorama for specialists and clinicians. The updated molecular mechanisms of ETV5 in cancer biology and tumor progression are delineated. Finally, we prospect the further direction of ETV5 research in oncology and its potential translational applications in the clinic.

The role of the brain-derived neurotrophic factor (BDNF) in anorexia nervosa

The brain-derived neurotrophic factor (BDNF) is a growth factor belonging to the neurotrophin family which plays a pivotal role in the differentiation, survival, and plasticity of neurons in the central nervous system. Evidence suggests that BDNF is an important signal molecule in the regulation of energy balance and thus implicated in body weight control. The discovery of BDNF-expressing neurons in the paraventricular hypothalamus which is important in the regulation of energy intake, physical activity, and thermogenesis gives more evidence to the suggested participation of BDNF in eating behavior. Until now it remains questionable whether BDNF can be used as a reliable biomarker for eating disorders such as anorexia nervosa (AN) as available findings on BDNF levels in patients with AN are ambiguous. AN is an eating disorder characterized by a pathological low body weight in combination with a body image disturbance typically developing during adolescence. A severe drive for thinness leads to restrictive eating behavior often accompanied by physical hyperactivity. During therapeutic weight restoration an increase of BDNF expression levels seems desirable as it might improve neuronal plasticity and survival which is essential for learning processes and thereby essential for the success of the psychotherapeutic treatment of patients. On the contrary, the well-known anorexigenic effect of BDNF might favor relapse in patients as soon as the BDNF levels significantly increase during weight rehabilitation. The present review summarizes the association between BDNF and general eating behavior and especially focuses on the eating disorder AN. In this regard findings from preclinical AN studies (activity-based anorexia model) are outlined as well.

The Effects of Food Advertisements on Food Intake and Neural Activity: A Systematic Review and Meta-Analysis of Recent Experimental Studies

Food advertisements are ubiquitous in our daily environment. However, the relationships between exposure to food advertising and outcomes related to ingestive behavior require further investigation. The objective was to conduct a systematic review and meta-analysis of behavioral and neural responses to food advertising in experimental studies. PubMed, Web of Science, and Scopus were searched for articles published from January 2014 to November 2021 using a search strategy following PRISMA guidelines. Experimental studies conducted with human participants were included. A random-effects inverse-variance meta-analysis was performed on standardized mean differences (SMD) of food intake (behavioral outcome) between the food advertisement and nonfood advertisement conditions of each study. Subgroup analyses were performed by age, BMI group, study design, and advertising media type. A seed-based d mapping meta-analysis of neuroimaging studies was performed to evaluate neural activity between experimental conditions. Nineteen articles were eligible for inclusion, 13 for food intake (n = 1303) and 6 for neural activity (n = 303). The pooled analysis of food intake revealed small, but statistically significant, effects of increased intake after viewing food advertising compared with the control condition among adults and children (adult SMD: 0.16; 95% CI: 0.03, 0.28; P = 0.01; I² = 0; 95% CI: 0, 95.0%; Children SMD: 0.25; 95% CI: 0.14, 0.37; P < 0.0001; I² = 60.4%; 95% CI: 25.6%, 79.0%). The neuroimaging studies involved children only, and the pooled analysis corrected for multiple comparisons identified one significant cluster, the middle occipital gyrus, with increased activity after food advertising exposure compared with the control condition (peak coordinates: 30, -86, 12; z-value: 6.301, size: 226 voxels; P < 0.001). These findings suggest that acute exposure to food advertising increases food intake among children and adults and that the middle occipital gyrus is an implicated brain region among children. (PROSPERO registration: CRD42022311357).

Glucocorticoids, stress and eating: The mediating role of appetite-regulating hormones

Disrupted hormonal appetite signaling plays a crucial role in obesity as it may lead to uncontrolled reward-related eating. Such disturbances can be induced not only by weight gain itself but also by glucocorticoid overexposure, for example, due to chronic stress, disease, or medication use. However, the exact pathways are just starting to be understood. Here, we present a conceptual framework of how glucocorticoid excess may impair hormonal appetite signaling and, consequently, eating control in the context of obesity. The evidence we present suggests that counteracting glucocorticoid excess can lead to improvements in appetite signaling and may therefore pose a crucial target for obesity prevention and treatment. In turn, targeting hormonal appetite signals may not only improve weight management and eating behavior but may also decrease detrimental effects of glucocorticoid excess on cardio-metabolic outcomes and mood. We conclude that gaining a better understanding of the relationship between glucocorticoid excess and circulating appetite signals will contribute greatly to improvements in personalized obesity prevention and treatment.

Risk prediction with imperfect survival outcome information from electronic health records

Readily available proxies for the time of disease onset such as the time of the first diagnostic code can lead to substantial risk prediction error if performing analyses based on poor proxies. Due to the lack of detailed documentation and labor intensiveness of manual annotation, it is often only feasible to ascertain for a small subset the current status of the disease by a follow-up time rather than the exact time. In this paper, we aim to develop risk prediction models for the onset time efficiently leveraging both a small number of labels on the current status and a large number of unlabeled observations on imperfect proxies. Under a semiparametric transformation model for onset and a highly flexible measurement error model for proxy onset time, we propose the semisupervised risk prediction method by combining information from proxies and limited labels efficiently. From an initially estimator solely based on the labeled subset, we perform a one-step correction with the full data augmenting against a mean zero rank correlation score derived from the proxies. We establish the consistency and asymptotic normality of the proposed semisupervised estimator and provide a resampling procedure for interval estimation. Simulation studies demonstrate that the proposed estimator performs well in a finite sample. We illustrate the proposed estimator by developing a genetic risk prediction model for obesity using data from Mass General Brigham Healthcare Biobank.

Understanding the contemporary high obesity rate from an evolutionary genetic perspective

The topic of obesity is gaining increasing popularity globally. From an evolutionary genetic perspective, it is believed that the main cause of the high obesity rate is the mismatch between environment and genes after people have shifted toward a modern high-calorie diet. However, it has been debated for over 60 years about how obesity-related genes become prevalent all over the world. Here, we review the three most influential hypotheses or viewpoints, i.e., the thrifty gene hypothesis, the drifty gene hypothesis, and the maladaptation viewpoint. In particular, genome-wide association studies in the recent 10 years have provided rich findings and evidence to be considered for a better understanding of the evolutionary genetic mechanisms of obesity. We anticipate this brief review to direct further studies and inspire the future application of precision medicine in obesity treatment.

Genetic risk score for common obesity and anthropometry in Spanish schoolchildren

IntroductionCommon or non-syndromic obesity is a complex polygenic trait conditioned by biallelic or single-base polymorphisms called SNPs (Single-Nucleotide Polymorphisms) that present an additive effect and act synergistically. Most genotype-obese phenotype association studies include body mass index (BMI) or waist-to-height ratio (WtHR), and very few introduce a broad anthropometric profile. ObjectiveTo verify whether a genetic risk score (GRS) developed from 10 SNPs is associated with the obesity phenotype assessed from anthropometric measures indicative of excess weight, adiposity and fat distribution. Material and methodsA series of 438 Spanish schoolchildren (6-16 years old) were evaluated anthropometrically (weight, height, waist circumference, skinfold thickness, BMI, WtHR, body fat percentage [%BF]). Ten SNPs were genotyped from saliva samples, generating a GRS for obesity, establishing genotype-phenotype association. ResultsSchoolchildren categorised as obese by BMI, ICT and %BF had higher GRS than their non-obese peers. The prevalence of overweight and adiposity was higher in subjects with a GRS above the median. Similarly, between 11 and 16 years of age, all anthropometric variables presented higher averages. ConclusionsGRS estimated from the 10 SNPs can be a diagnostic tool for the potential risk of obesity in Spanish schoolchildren and could be useful from the preventive perspective.