Variability in the heritability of body mass index: a systematic review and meta-regression

Alterations of DNA methylation profile in peripheral blood of children with simple obesity

Purpose

To investigate the association between DNA methylation and childhood simple obesity.

Methods

Genome-wide analysis of DNA methylation was conducted on peripheral blood samples from 41 children with simple obesity and 31 normal controls to identify differentially methylated sites (DMS). Subsequently, gene functional analysis of differentially methylated genes (DMGs) was carried out. After screening the characteristic DMGs based on specific conditions, the methylated levels of these DMS were evaluated and verified by pyrosequencing. Receiver operating characteristic (ROC) curve analysis assessed the predictive efficacy of corresponding DMGs. Finally, Pearson correlation analysis revealed the correlation between specific DMS and clinical data.

Results

The overall DNA methylation level in the obesity group was significantly lower than in normal. A total of 241 DMS were identified. Functional pathway analysis revealed that DMGs were primarily involved in lipid metabolism, carbohydrate metabolism, amino acid metabolism, human diseases, among other pathways. The characteristic DMS within the genes Transcription factor A mitochondrial (TFAM) and Piezo type mechanosensitive ion channel component 1(PIEZO1) were recognized as CpG-cg05831083 and CpG-cg14926485, respectively. Furthermore, the methylation level of CpG-cg05831083 significantly correlated with body mass index (BMI) and vitamin D.

Conclusions

Abnormal DNA methylation is closely related to childhood simple obesity. The altered methylation of CpG-cg05831083 and CpG-cg14926485 could potentially serve as biomarkers for childhood simple obesity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-024-00275-w.

Human brain proteome-wide association study provides insights into the genetic components of protein abundance in obesity

BACKGROUNDS

Genome-wide association studies have identified multiple genetic variants associated with obesity. However, most obesity-associated loci were waiting to be translated into new biological insights. Given the critical role of brain in obesity development, we sought to explore whether obesity-associated genetic variants could be mapped to brain protein abundances.

METHODS

We performed proteome-wide association studies (PWAS) and colocalization analyses to identify genes whose cis-regulated brain protein abundances were associated with obesity-related traits, including body fat percentage, trunk fat percentage, body mass index, visceral adipose tissue, waist circumference, and waist-to-hip ratio. We then assessed the druggability of the identified genes and conducted pathway enrichment analysis to explore their functional relevance. Finally, we evaluated the effects of the significant PWAS genes at the brain transcriptional level.

RESULTS

By integrating human brain proteomes from discovery (ROSMAP, N = 376) and validation datasets (BANNER, N = 198) with genome-wide summary statistics of obesity-related phenotypes (N ranged from 325,153 to 806,834), we identified 51 genes whose cis-regulated brain protein abundance was associated with obesity. These 51 genes were enriched in 11 metabolic processes, e.g., small molecule metabolic process and metabolic pathways. Fourteen of the 51 genes had high drug repurposing value. Ten of the 51 genes were also associated with obesity at the transcriptome level, suggesting that genetic variants likely confer risk of obesity by regulating mRNA expression and protein abundance of these genes.

CONCLUSIONS

Our study provides new insights into the genetic component of human brain protein abundance in obesity. The identified proteins represent promising therapeutic targets for future drug development.

Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.

Clinical phenotypes of adults with monogenic and syndromic genetic obesity

OBJECTIVE

Considering limited evidence on diagnostics of genetic obesity in adults, we evaluated phenotypes of adults with genetic obesity. Additionally, we assessed the applicability of Endocrine Society (ES) recommendations for genetic testing in pediatric obesity.

METHODS

We compared clinical features, including age of onset of obesity and appetite, between adults with non-syndromic monogenic obesity (MO), adults with syndromic obesity (SO), and adults with common obesity (CO) as control patients.

RESULTS

A total of 79 adults with genetic obesity (32 with MO, 47 with SO) were compared with 186 control patients with CO. Median BMI was similar among the groups: 41.2, 39.5, and 38.7 kg/m2 for patients with MO, SO, and CO, respectively. Median age of onset of obesity was 3 (IQR: 1-6) years in patients with MO, 9 (IQR: 4-13) years in patients with SO, and 21 (IQR: 13-33) years in patients with CO (p < 0.001). Patients with genetic obesity more often reported increased appetite: 65.6%, 68.1%, and 33.9% in patients with MO, SO, and CO, respectively (p < 0.001). Intellectual deficit and autism spectrum disorder were more prevalent in patients with SO (53.2% and 21.3%) compared with those with MO (3.1% and 6.3%) and CO (both 0.0%). The ES recommendations were fulfilled in 56.3%, 29.8%, and 2.7% of patients with MO, SO, and CO, respectively (p < 0.001).

CONCLUSIONS

We found distinct phenotypes in adult genetic obesity. Additionally, we demonstrated low sensitivity for detecting genetic obesity in adults using pediatric ES recommendations, necessitating specific genetic testing recommendations in adult obesity care.

The complex web of obesity: from genetics to precision medicine

INTRODUCTION

Obesity is a growing public health concern affecting both children and adults. Since it involves both genetic and environmental components, the management of obesity requires both, an understanding of the underlying genetics and changes in lifestyle. The knowledge of obesity genetics will enable the possibility of precision medicine in anti-obesity medications.

AREAS COVERED

Here, we explore health complications and the prevalence of obesity. We discuss disruptions in energy balance as a symptom of obesity, examining evolutionary theories, its multi-factorial origins, and heritability. Additionally, we discuss monogenic and polygenic obesity, the converging biological pathways, potential pharmacogenomics applications, and existing anti-obesity medications - specifically focussing on the leptin-melanocortin and incretin pathways. Comparisons between childhood and adult obesity genetics are made, along with insights into structural variants, epigenetic changes, and environmental influences on epigenetic signatures.

EXPERT OPINION

With recent advancements in anti-obesity drugs, genetic studies pinpoint new targets and allow for repurposing existing drugs. This creates opportunities for genotype-informed treatment options. Also, lifestyle interventions can help in the prevention and treatment of obesity by altering the epigenetic signatures. The comparison of genetic architecture in adults and children revealed a significant overlap. However, more robust studies with diverse ethnic representation is required in childhood obesity.

An integrative framework to prioritize genes in more than 500 loci associated with body mass index

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

Heritability of Body Mass Index Among Familial Generations

Importance

Studies on the familial effects of body mass index (BMI) status have yielded a wide range of data on its heritability.

Objective

To assess the heritability of obesity by measuring the association between the BMIs of fathers, mothers, and their offspring at the same age.

Design, Setting, and Participants

This cohort study used data from population-wide mandatory medical screening before compulsory military service in Israel. The study included participants examined between January 1, 1986, and December 31, 2018, whose both parents had their BMI measurement taken at their own prerecruitment evaluation in the past. Data analysis was performed from May to December 2023.

Main Outcomes and Measures

Spearman correlation coefficients were calculated for offsprings' BMI and their mothers', fathers', and midparental BMI percentile (the mean of the mothers' and fathers' BMI cohort- and sex-specific BMI percentile) to estimate heritability. Logistic regression models were applied to estimate the odds ratios (ORs) and 95% CIs of obesity compared with healthy BMI, according to parental BMI status.

Results

A total of 447 883 offspring (235 105 male [52.5%]; mean [SD] age, 17.09 [0.34] years) with both parents enrolled and measured for BMI at 17 years of age were enrolled in the study, yielding a total study population of 1 343 649 individuals. Overall, the correlation between midparental BMI percentile at 17 years of age and the offspring's BMI at 17 years of age was moderate (ρ = 0.386). Among female offspring, maternal-offspring BMI correlation (ρ = 0.329) was somewhat higher than the paternal-offspring BMI correlation (ρ = 0.266). Among trios in which both parents had a healthy BMI, the prevalence of overweight or obesity in offspring was 15.4%; this proportion increased to 76.6% when both parents had obesity and decreased to 3.3% when both parents had severe underweight. Compared with healthy weight, maternal (OR, 4.96; 95% CI, 4.63-5.32), paternal (OR, 4.48; 95% CI, 4.26-4.72), and parental (OR, 6.44; 95% CI, 6.22-6.67) obesity (midparent BMI in the ≥95th percentile) at 17 years of age were associated with increased odds of obesity among offspring.

Conclusions and Relevance

In this cohort study of military enrollees whose parents also underwent prerecruitment evaluations, the observed correlation between midparental and offspring BMI, coupled with a calculated narrow-sense heritability of 39%, suggested a substantive contribution of genetic factors to BMI variation at 17 years of age.

The Impact of Haplotypes of the FTO Gene, Lifestyle, and Dietary Patterns on BMI and Metabolic Syndrome in Polish Young Adult Men

BACKGROUND

Variants in fat mass and the obesity-associated protein (FTO) gene have long been recognized as the most significant genetic predictors of body fat mass and obesity. Nevertheless, despite the overall evidence, there are conflicting reports regarding the correlation between different polymorphisms of the FTO gene and body mass index (BMI). Additionally, it is unclear whether FTO influences metabolic syndrome (MetS) through mechanisms other than BMI's impact. In this work, we aimed to analyze the impact of the following FTO polymorphisms on the BMI as well as MetS components in a population of young adult men.

METHODS

The patient group consisted of 279 Polish young adult men aged 28.92 (4.28) recruited for the MAGNETIC trial. The single-nucleotide polymorphisms (SNPs), located in the first intron of the FTO gene, were genotyped, and the results were used to identify "protective" and "risk" haplotypes and diplotypes based on the literature data. Laboratory, as well as anthropometric measurements regarding MetS, were performed. Measured MetS components included those used in the definition in accordance with the current guidelines. Data regarding dietary patterns were also collected, and principal components of the dietary patterns were identified.

RESULTS

No statistically significant correlations were identified between the analyzed FTO diplotypes and BMI (p = 0.53) or other MetS components (waist circumference p = 0.55; triglycerides p = 0.72; HDL cholesterol p = 0.33; blood glucose p = 0.20; systolic blood pressure p = 0.06; diastolic blood pressure p = 0.21). Stratification by the level of physical activity or adherence to the dietary patterns also did not result in any statistically significant result.

CONCLUSIONS

Some studies have shown that FTO SNPs such as rs1421085, rs1121980, rs8050136, rs9939609, and rs9930506 have an impact on the BMI or other MetS components; nevertheless, this was not replicated in this study of Polish young adult males.

Genetic influence on within-person longitudinal change in anthropometric traits in the UK Biobank

The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2-5% for height, sitting height, body mass index (BMI) and weight (P ≤ 2.4 × 10-3). We also analysed longitudinal trait change and show a loss of both average height and weight beyond about 70 years of age. A variant tracking the Alzheimer's risk APOE- E 4 allele (rs429358) was significantly associated with weight loss ( β  = -0.047 kg per yr, s.e. 0.007, P = 2.2 × 10-11), and using 2-sample Mendelian Randomisation we detected a relationship consistent with causality between decreased lumbar spine bone mineral density and height loss (bxy = 0.011, s.e. 0.003, P = 3.5 × 10-4). Finally, population-level variance quantitative trait loci (vQTL) were consistent with within-person variability for several traits, indicating an overlap between trait variability assessed at the population or individual level. Our findings help elucidate the genetic influence on trait-change within an individual and highlight disease risks associated with these changes.

Impact of polygenic score for BMI on weight loss effectiveness and genome-wide association analysis

BACKGROUND

While environmental factors play an important role in weight loss effectiveness, genetics may also influence its success. We examined whether a genome-wide polygenic score for BMI was associated with weight loss effectiveness and aimed to identify common genetic variants associated with weight loss.

METHODS

Participants in the ONTIME study (n = 1210) followed a uniform, multimodal behavioral weight-loss intervention. We first tested associations between a genome-wide polygenic score for higher BMI and weight loss effectiveness (total weight loss, rate of weight loss, and attrition). We then conducted a genome-wide association study (GWAS) for weight loss in the ONTIME study and performed the largest weight loss meta-analysis with earlier studies (n = 3056). Lastly, we ran exploratory GWAS in the ONTIME study for other weight loss outcomes and related factors.

RESULTS

We found that each standard deviation increment in the polygenic score was associated with a decrease in the rate of weight loss (Beta (95% CI) = -0.04 kg per week (-0.06, -0.01); P = 3.7 × 10-03) and with higher attrition after adjusting by treatment duration. No associations reached genome-wide significance in meta-analysis with previous GWAS studies for weight loss. However, associations in the ONTIME study showed effects consistent with published studies for rs545936 (MIR486/NKX6.3/ANK1), a previously noted weight loss locus. In the meta-analysis, each copy of the minor A allele was associated with 0.12 (0.03) kg/m2 higher BMI at week five of treatment (P = 3.9 × 10-06). In the ONTIME study, we also identified two genome-wide significant (P < 5×10-08) loci for the rate of weight loss near genes implicated in lipolysis, body weight, and metabolic regulation: rs146905606 near NFIP1/SPRY4/FGF1; and rs151313458 near LSAMP.

CONCLUSION

Our findings are expected to help in developing personalized weight loss approaches based on genetics.

CLINICAL TRIAL REGISTRATION

Obesity, Nutrigenetics, Timing, and Mediterranean (ONTIME; clinicaltrials.gov: NCT02829619) study.

FTO genotype and body mass index reduction in childhood obesity interventions: A systematic review and meta-analysis

Numerous guidelines have called for personalized interventions to address childhood obesity. The role of fat mass and obesity-associated gene (FTO) in the risk of childhood obesity has been summarized. However, it remains unclear whether FTO could influence individual responses to obesity interventions, especially in children. To address this, we systematically reviewed 12,255 records across 10 databases/registers and included 13 lifestyle-based obesity interventions (3980 children with overweight/obesity) reporting changes in body mass index (BMI) Z-score, BMI, waist circumference, waist-to-hip ratio, and body fat percentage after interventions. These obesity-related outcomes were first compared between children carrying different FTO genotypes (rs9939609 or its proxy) and then synthesized by random-effect meta-analysis models. The results from single-group interventions showed no evidence of associations between FTO risk allele and changes in obesity-related outcomes after interventions (e.g., BMI Z-score: -0.01; 95% CI: -0.04, 0.01). The results from controlled trials showed that associations between the FTO risk allele and changes in obesity-related outcomes did not differ by intervention/control group. To conclude, the FTO risk allele might play a minor role in the response to obesity interventions among children. Future studies might pay more attention to the accumulation effect of multiple genes in the intervention process among children.

Identifying latent genetic interactions in genome-wide association studies using multiple traits

The "missing" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods. We then apply LIT to obesity-related traits in the UK Biobank and detect variants with interactive effects near known obesity-related genes (URL: https://CRAN.R-project.org/package=lit ).

Risk factors affecting polygenic score performance across diverse cohorts

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Genetic risk score based on obesity-related genes and progression in weight loss after bariatric surgery: a 60-month follow-up study

BACKGROUND

Obesity is a polygenic multifactorial disease. Recent genome-wide association studies have identified several common loci associated with obesity-related phenotypes. Bariatric surgery (BS) is the most effective long-term treatment for patients with severe obesity. The huge variability in BS outcomes between patients suggests a moderating effect of several factors, including the genetic architecture of the patients.

OBJECTIVE

To examine the role of a genetic risk score (GRS) based on 7 polymorphisms in 5 obesity-candidate genes (FTO, MC4R, SIRT1, LEP, and LEPR) on weight loss after BS.

SETTING

University hospital in Spain.

METHODS

We evaluated a cohort of 104 patients with severe obesity submitted to BS (Roux-en-Y gastric bypass or sleeve gastrectomy) followed up for >60 months (lost to follow-up, 19.23%). A GRS was calculated for each patient, considering the number of carried risk alleles for the analyzed genes. During the postoperative period, the percentage of excess weight loss total weight loss and changes in body mass index were evaluated. Generalized estimating equation models were used for the prospective analysis of the variation of these variables in relation to the GRS.

RESULTS

The longitudinal model showed a significant effect of the GRS on the percentage of excess weight loss (P = 1.5 × 10-5), percentage of total weight loss (P = 3.1 × 10-8), and change in body mass index (P = 7.8 × 10-16) over time. Individuals with a low GRS seemed to experience better outcomes at 24 and 60 months after surgery than those with a higher GRS.

CONCLUSION

The use of the GRS in considering the polygenic nature of obesity seems to be a useful tool to better understand the outcome of patients with obesity after BS.

Understanding risk and causal mechanisms for developing obesity in infants and young children: A National Institutes of Health workshop

Obesity in children remains a major public health problem, with the current prevalence in youth ages 2-19 years estimated to be 19.7%. Despite progress in identifying risk factors, current models do not accurately predict development of obesity in early childhood. There is also substantial individual variability in response to a given intervention that is not well understood. On April 29-30, 2021, the National Institutes of Health convened a virtual workshop on "Understanding Risk and Causal Mechanisms for Developing Obesity in Infants and Young Children." The workshop brought together scientists from diverse disciplines to discuss (1) what is known regarding epidemiology and underlying biological and behavioral mechanisms for rapid weight gain and development of obesity and (2) what new approaches can improve risk prediction and gain novel insights into causes of obesity in early life. Participants identified gaps and opportunities for future research to advance understanding of risk and underlying mechanisms for development of obesity in early life. It was emphasized that future studies will require multi-disciplinary efforts across basic, behavioral, and clinical sciences. An exposome framework is needed to elucidate how behavioral, biological, and environmental risk factors interact. Use of novel statistical methods may provide greater insights into causal mechanisms.

Determinants of obesity in Latin America

Obesity rates are increasing almost everywhere in the world, although the pace and timing for this increase differ when populations from developed and developing countries are compared. The sharp and more recent increase in obesity rates in many Latin American countries is an example of that and results from regional characteristics that emerge from interactions between multiple factors. Aware of the complexity of enumerating these factors, we highlight eight main determinants (the physical environment, food exposure, economic and political interest, social inequity, limited access to scientific knowledge, culture, contextual behaviour and genetics) and discuss how they impact obesity rates in Latin American countries. We propose that initiatives aimed at understanding obesity and hampering obesity growth in Latin America should involve multidisciplinary, global approaches that consider these determinants to build more effective public policy and strategies, accounting for regional differences and disease complexity at the individual and systemic levels.

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

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

Association Between rs217727 and rs2839698 H19 Polymorphisms and Obesity

Obesity is a worldwide health problem with an increasing trend. This condition has a significant genetic background. H19 lncRNA has been shown to protect from dietary obesity through decreasing levels of monoallelic genes in brown fat. In the current study, we aimed to find the association between two possibly functional H19 polymorphisms, namely rs217727 and rs2839698 and obesity in Iranian population. These polymorphisms have been shown to affect risk of some obesity-related conditions in different populations. The study included 414 obese cases and 392 controls. Notably, both rs2839698 and rs217727 were associated with obesity in the allelic model as well as all supposed inheritance models. In addition, after adjustment for gender, all P values remained significant. For rs2839698, the OR (95% CI) for T allele vs. C allele was 3.29 (2.67-4.05) (P-value < 0.0001). In the co-dominant model, both TT and CT genotypes were found to confer risk of obesity compared with CC genotype (OR (95% CI)= 14.02 (8.39-23.43) and 9.45 (6.36-14.04), respectively). Similarly, combination of TT and CT genotypes had an OR (95% CI) = 10.32 (7.03-15.17) when compared with CC genotype. For rs217727, the T allele was found to exert a protective effect (OR (95% CI) = 0.6 (0.48-0.75)). Moreover, in the co-dominant model, OR (95% CI) values for TT and TC genotypes vs. CC genotype were 0.23 (0.11-0.46) and 0.65 (0.49-0.87), respectively. Taken together, H19 polymorphisms may affect risk of obesity in Iranian population. It is necessary to conduct functional studies to confirm a causal relationship between the rs217727 and rs2839698 polymorphisms and obesity.

The relationship between weight-related indicators and depressive symptoms during adolescence and adulthood: results from two twin studies

BACKGROUND

The association between weight and depressive symptoms is well established, but the direction of effects remains unclear. Most studies rely on body mass index (BMI) as the sole weight indicator, with few examining the aetiology of the association between weight indicators and depressive symptoms.

METHODS

We analysed data from the Twins Early Development Study (TEDS) and UK Adult Twin Registry (TwinsUK) (7658 and 2775 twin pairs, respectively). A phenotypic cross-lagged panel model assessed the directionality between BMI and depressive symptoms at ages 12, 16, and 21 years in TEDS. Bivariate correlations tested the phenotypic association between a range of weight indicators and depressive symptoms in TwinsUK. In both samples, structural equation modelling of twin data investigated genetic and environmental influences between weight indicators and depression. Sensitivity analyses included two-wave phenotypic cross-lagged panel models and the exclusion of those with a BMI <18.5.

RESULTS

Within TEDS, the relationship between BMI and depression was bidirectional between ages 12 and 16 with a stronger influence of earlier BMI on later depression. The associations were unidirectional thereafter with depression at 16 influencing BMI at 21. Small genetic correlations were found between BMI and depression at ages 16 and 21, but not at 12. Within TwinsUK, depression was weakly correlated with weight indicators; therefore, it was not possible to generate precise estimates of genetic or environmental correlations.

CONCLUSIONS

The directionality of the relationship between BMI and depression appears to be developmentally sensitive. Further research with larger genetically informative samples is needed to estimate the aetiological influence on these associations.

Association between the FAAH C385A variant (rs324420) and obesity-related traits: a systematic review

BACKGROUND

Overweight and obesity are the consequence of a sustained positive energy balance. Twin studies show high heritability rates pointing to genetics as one of the principal risk factors. By 2022, genomic studies led to the identification of almost 300 obesity-associated variants that could help to fill the gap of the high heritability rates. The endocannabinoid system is a critical regulator of metabolism for its effects on the central nervous system and peripheral tissues. Fatty acid amide hydrolase (FAAH) is a key enzyme in the inactivation of one of the two endocannabinoids, anandamide, and of its congeners. The rs324420 variant within the FAAH gene is a nucleotide missense change at position 385 from cytosine to adenine, resulting in a non-synonymous amino acid substitution from proline to threonine in the FAAH enzyme. This change increases sensitivity to proteolytic degradation, leading to reduced FAAH levels and increased levels of anandamide, associated with obesity-related traits. However, association studies of this variant with metabolic parameters have found conflicting results. This work aims to perform a systematic review of the existing literature on the association of the rs324420 variant in the FAAH gene with obesity and its related traits.

METHODS

A literature search was conducted in PubMed, Web of Science, and Scopus. A total of 645 eligible studies were identified for the review.

RESULTS/CONCLUSIONS

After the identification, duplicate elimination, title and abstract screening, and full-text evaluation, 28 studies were included, involving 28 183 individuals. We show some evidence of associations between the presence of the variant allele and higher body mass index, waist circumference, fat mass, and waist-to-hip ratio levels and alterations in glucose and lipid homeostasis. However, this evidence should be taken with caution, as many included studies did not report a significant difference between genotypes. These discordant results could be explained mainly by the pleiotropy of the endocannabinoid system, the increase of other anandamide-like mediators metabolized by FAAH, and the influence of gene-environment interactions. More research is necessary to study the endocannabinoidomic profiles and their association with metabolic diseases.

Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance

Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.

Gene variants and the response to childhood obesity interventions: A systematic review and meta-analysis

BACKGROUND

Multiple lifestyle-based childhood obesity interventions have been conducted to address childhood obesity, but individual's response to the universal intervention approach varied greatly. Whether gene variants related to children and adolescents' varied responses to obesity interventions remained unclear.

AIMS

To determine the associations of gene variants with the changes in obesity- and metabolism-related indicators after obesity interventions in children and adolescents.

METHODS

Ten databases and registers (including grey literature) were searched. The lifestyle-based obesity interventions in children and adolescents (≤18 years) that reported the changes in obesity- (body mass index (BMI), BMI Z-score, waist circumference (WC), waist-to-hip ratio (WHR), etc) and metabolism-related (glucose, cholesterol, etc) indicators by genotype after interventions were included. Our primary outcome was the mean difference of the changes in BMI Z-score by genotype after interventions, and secondary outcomes were changes in the remaining obesity- and metabolism-related indicators after interventions. We used the random-effects model to synthesize the results.

RESULTS

This review included 50 studies (15,354 children and adolescents with overweight/obesity) covering 102 genes and 174 single nucleotide polymorphisms (SNPs). Approximately three-quarters of SNPs showed no evidence of association with the changes in obesity- or metabolic-related indicators after interventions. One quarter of SNPs were minorly associated with the changes in the BMI Z-score (median effect size: 0.001) with little clinical significance. Only 6 (12 %) studies focused on the accumulated effect of multiple gene variants.

CONCLUSIONS

Gene variants that have been explored appear to play a minor role in lifestyle-based obesity interventions in children and adolescents. More high-quality studies based on the design of randomized controlled trials are needed to examine the accumulated effect of multiple gene variants in childhood obesity interventions.

PROSPERO REGISTRY NUMBER

This systematic review and meta-analysis was registered at PROSPERO as CRD42022312177.

Mediation and moderation of genetic risk of obesity through eating behaviours in two UK cohorts

BACKGROUND

The mechanisms underlying genetic predisposition to higher body mass index (BMI) remain unclear.

METHODS

We hypothesized that the relationship between BMI-genetic risk score (BMI-GRS) and BMI was mediated via disinhibition, emotional eating and hunger, and moderated by flexible (but not rigid) restraint within two UK cohorts: the Genetics of Appetite Study (GATE) (n = 2101, 2010-16) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 1679, 2014-18). Eating behaviour was measured by the Adult Eating Behaviour Questionnaire and Three-Factor Eating Questionaire-51.

RESULTS

The association between BMI-GRS and BMI were partially mediated by habitual, emotional and situational disinhibition in the GATE/ALSPAC meta-mediation [standardized betaindirect 0.04, 95% confidence interval (CI) 0.02-0.06; 0.03, 0.01-0.04; 0.03, 0.01-0.04, respectively] external hunger and internal hunger in the GATE study (0.02, 0.01-0.03; 0.01, 0.001-0.02, respectively). There was evidence of mediation by emotional over/undereating and hunger in the ALSPAC study (0.02, 0.01-0.03; 0.01, 0.001-0.02; 0.01, 0.002-0.01, respectively). Rigid or flexible restraint did not moderate the direct association between BMI-GRS and BMI, but high flexible restraint moderated the effect of disinhibition subscales on BMI (reduction of the indirect mediation by -5% to -11% in GATE/ALSPAC) and external hunger (-5%) in GATE. High rigid restraint reduced the mediation via disinhibition subscales in GATE/ALSPAC (-4% to -11%) and external hunger (-3%) in GATE.

CONCLUSIONS

Genetic predisposition to a higher BMI was partly explained by disinhibition and hunger in two large cohorts. Flexible/rigid restraint may play an important role in moderating the impact of predisposition to higher BMI.

Association between the genetic variant in the vitamin D pathway (rs2282679), circulating 25-hydroxyvitamin D levels, insulin resistance and metabolic syndrome criteria

Introduction

Background and aims: some studies have reported links between 25-hydroxyvitamin D levels and the presence of metabolic syndrome. The aim of the present study was to evaluate whether an association exists among 25-hydroxyvitamin D, rs2282679 of the GC gene and metabolic syndrome (MS). Methods: the study involved a population of 134 postmenopausal obese females. Measurements of anthropometric parameters, blood pressure, bone turnover markers, fasting blood glucose, insulin resistance (HOMA-IR), lipid profile, C-reactive protein and prevalence of MS were recorded. Genotype of CG gene polymorphism (rs2282679) was evaluated. Results: insulin (delta: 4.6 ± 0.9 mUI/l; p = 0.02), triglycerides (delta: 21.6 ± 2.9 mg/dl; p = 0.04) and HOMA-IR (delta: 1.1 ± 0.9 unit; p = 0.02) were lower in TT subjects than TG + GG patients. The percentages of individuals who had MS (OR = 2.80, 95 % CI = 1.39-5.65; p = 0.02), hypertriglyceridemia (OR = 2.39, 95 % CI = 1.44-5.96; p = 0.01), and hyperglycemia (OR = 2.72, 95 % CI = 1.23-6.00; p = 0.43) were higher in G allele carriers. Logistic regression analysis showed an increased risk of MS in G allele carriers (OR = 2.36, 95 % CI = 1.11-5.91, p = 0.02) and an increased risk of 25-hydroxyvitamin D deficiency (< 20 ng/ml) (OR = 2.43, 95 % CI = 1.13-6.69, p = 0.02), too. Conclusions: a negative association among G allele and insulin resistance, hypertriglyceridemia, deficiency of 25 hydroxyvitamin D levels and MS was reported in this population.

The Polymorphism rs17300539 in the Adiponectin Promoter Gene Is Related to Metabolic Syndrome, Insulin Resistance, and Adiponectin Levels in Caucasian Patients with Obesity

Background and Aims: The present study was designed to investigate SNP rs17300539 in the ADIPOQ gene and its relationships with obesity, metabolic syndrome (MS), and serum circulating adiponectin. Methods: The present design involved a Caucasian population of 329 subjects with obesity. Anthropometric and adiposity parameters, blood pressure, biochemical parameters, and the percentage of patients with metabolic syndrome were recorded. The ADIPOQ gene variant (rs17300539) genotype was evaluated. Results: The percentage of patients with different genotypes of the rs17300539 polymorphism in this sample was 86.0% (n = 283) (GG), 11.2% (n = 37) (GA), and 2.7% (n = 9) (AA). The allele frequency was G (0.76) and A (0.24). Applying the dominant genetic model (GG vs. GA + AA), we reported differences between genotype GG and genotype GA + AA for serum adiponectin levels (Delta: 7.5 ± 1.4 ng/mL; p = 0.03), triglycerides (Delta: 41.1 ± 3.4 mg/dL; p = 0.01), fastingcirculating insulin (Delta: 4.9 ± 1.1 mUI/L; p = 0.02), and insulin resistance as HOMA-IR (Delta: 1.4 ± 0.1 units; p = 0.02). The remaining biochemical parameters were not related to the genotype of obese patients. The percentages of individuals with MS (OR = 2.07, 95% CI = 1.3-3.88; p = 0.01), hypertriglyceridaemia (OR = 2.66, 95% CI = 1.43-5.01; p = 0.01), and hyperglycaemia (OR = 3.31, 95% CI = 1.26-8.69; p = 0.02) were higher in GG subjects than patients with A allele. Logistic regression analysis reported an important risk of the presence of metabolic syndrome in GG subjects (OR = 1.99, 95% CI = 1.21-4.11; p = 0.02) after adjusting for adiponectin, dietary energy intakes, gender, weight, and age. Conclusions: The GG genotype of rs17300539 is associated with hypertriglyceridaemia, insulin resistance, low adiponectin levels, and a high risk of metabolic syndrome and its components.

Trends in the ability of socioeconomic position to predict individual body mass index: an analysis of repeated cross-sectional data, 1991-2019

BACKGROUND

The widening of group-level socioeconomic differences in body mass index (BMI) has received considerable research attention. However, the predictive power of socioeconomic position (SEP) indicators at the individual level remains uncertain, as does the potential temporal variation in their predictive value. Examining this is important given the increasing incorporation of SEP indicators into predictive algorithms and calls to reduce social inequality to tackle the obesity epidemic. We thus investigated SEP differences in BMI over three decades of the obesity epidemic in England, comparing population-wide (SEP group differences in mean BMI) and individual-level (out-of-sample prediction of individuals' BMI) approaches to understanding social inequalities.

METHODS

We used repeated cross-sectional data from the Health Survey for England, 1991-2019. BMI (kg/m2) was measured objectively, and SEP was measured via educational attainment, occupational class, and neighbourhood index of deprivation. We ran random forest models for each survey year and measure of SEP adjusting for age and sex.

RESULTS

The mean and variance of BMI increased within each SEP group over the study period. Mean differences in BMI by SEP group also increased: differences between lowest and highest education groups were 1.0 kg/m2 (0.4, 1.6) in 1991 and 1.3 kg/m2 (0.7, 1.8) in 2019. At the individual level, the predictive capacity of SEP was low, though increased in later years: including education in models improved predictive accuracy (mean absolute error) by 0.14% (- 0.9, 1.08) in 1991 and 1.05% (0.18, 1.82) in 2019. Similar patterns were obtained for occupational class and neighbourhood deprivation and when analysing obesity as an outcome.

CONCLUSIONS

SEP has become increasingly important at the population (group difference) and individual (prediction) levels. However, predictive ability remains low, suggesting limited utility of including SEP in prediction algorithms. Assuming links are causal, abolishing SEP differences in BMI could have a large effect on population health but would neither reverse the obesity epidemic nor reduce much of the variation in BMI.

Early ascending growth is associated with maternal lipoprotein profile during mid and late pregnancy and in cord blood

INTRODUCTION

Intrauterine conditions and accelerating early growth are associated with childhood obesity. It is unknown, whether fetal programming affects the early growth and could alterations in the maternal-fetal metabolome be the mediating mechanism. Therefore, we aimed to assess the associations between maternal and cord blood metabolite profile and offspring early growth.

METHODS

The RADIEL study recruited 724 women at high risk for gestational diabetes mellitus (GDM) BMI ≥ 30 kg/m2 and/or prior GDM) before or in early pregnancy. Blood samples were collected once in each trimester, and from cord. Metabolomics were analyzed by targeted nuclear magnetic resonance (NMR) technique. Following up on offsprings' first 2 years growth, we discovered 3 distinct growth profiles (ascending n = 80, intermediate n = 346, and descending n = 146) by using latent class mixed models (lcmm).

RESULTS

From the cohort of mother-child dyads with available growth profile data (n = 572), we have metabolomic data from 232 mothers from 1st trimester, 271 from 2nd trimester, 277 from 3rd trimester and 345 from cord blood. We have data on 220 metabolites in each trimester and 70 from cord blood. In each trimester of pregnancy, the mothers of the ascending group showed higher levels of VLDL and LDL particles, and lower levels of HDL particles (p < 0.05). When adjusted for gestational age, birth weight, sex, delivery mode, and maternal smoking, there was an association with ascending profile and 2nd trimester total cholesterol in HDL2, 3rd trimester total cholesterol in HDL2 and in HDL, VLDL size and ratio of triglycerides to phosphoglycerides (TG/PG ratio) in cord blood (p ≤ 0.002).

CONCLUSION

Ascending early growth was associated with lower maternal total cholesterol in HDL in 2nd and 3rd trimester, and higher VLDL size and more adverse TG/PG ratio in cord blood.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, http://www.

CLINICALTRIALS

com , NCT01698385.

Genetic architecture of adiposity measures among Asians: Findings from GWAS

Adiposity has gradually become a global public threat over the years with drastic increase in the attributable deaths and disability adjusted life years (DALYs). Given an increased metabolic risk among Asians as compared to Europeans for any given body mass index (BMI) and considering the differences in genetic architecture between them, the present review aims to summarize the findings from genome-wide scans for various adiposity indices and related anthropometric measures from Asian populations. The search for related studies, published till February 2022, were made on PubMed and GWAS Catalog using search strategy built with relevant keywords joined by Boolean operators. It was recorded that out of a total of 47 identified studies, maximum studies are from Korean population (n = 14), followed by Chinese (n = 7), and Japanese (n = 6). Nearly 200 loci have been identified for BMI, 660 for height, 16 for weight, 28 for circumferences (waist and hip), 32 for ratios (waist hip ratio [WHR] and thoracic hip ratio [THR]), 5 for body fat, 16 for obesity, and 28 for adiposity-related blood markers among Asians. It was observed that though, most of the loci were unique for each trait, there were 3 loci in common to BMI and WHR. Apart from validation of variants identified in European setting, there were many novel loci discovered in Asian populations. Notably, 125 novel loci form Asian studies have been reported for BMI, 47 for height, 5 for waist circumference, and 2 for adiponectin level to the existing knowledge of the genetic framework of adiposity and related measures. It is necessary to examine more advanced adiposity measures, specifically of relevance to abdominal adiposity, a major risk factor for cardiometabolic disorders among Asians. Moreover, in spite of being one continent, there is diversity among different ethnicities across Asia in terms of lifestyle, climate, geography, genetic structure and consequently the phenotypic manifestations. Hence, it is also important to consider ethnic specific studies for identifying and validating reliable genetic variants of adiposity measures among Asians.

Triangulating causality between childhood obesity and neurobehavior: Behavioral genetic and longitudinal evidence

Childhood obesity is a serious health concern that is not yet fully understood. Previous research has linked obesity with neurobehavioral factors such as behavior, cognition, and brain morphology. The causal directions of these relationships remain mostly untested. We filled this gap by using the Adolescent Brain Cognitive Development study cohort comprising 11,875 children aged 9-10. First, correlations between the age- and sex-specific 95th BMI percentile (%BMIp95) and neurobehavioral measures were cross-sectionally analyzed. Effects were then aggregated by neurobehavioral domain for causal analyses. Behavioral genetic Direction of Causation modeling was used to test the direction of each relationship. Findings were validated by longitudinal cross-lagged panel modeling. %BMIp95 correlated with impulsivity, motivation, psychopathology, eating behavior, and cognitive tests (executive functioning, language, memory, perception, working memory). Greater %BMIp95 was also associated with reduced cortical thickness in frontal and temporal brain areas but with increased thickness in parietal and occipital areas. Similar although weaker patterns emerged for cortical surface area and volume. Behavioral genetic modeling suggested causal effects of %BMIp95 on eating behavior (β = 0.26), cognition (β = 0.05), cortical thickness (β = 0.15), and cortical surface area (β = 0.07). Personality/psychopathology (β = 0.09) and eating behavior (β = 0.16) appeared to influence %BMIp95. Longitudinal evidence broadly supported these findings. Results regarding cortical volume were inconsistent. Results supported causal effects of obesity on brain functioning and morphology. The present study highlights the importance of physical health for brain development and may inform interventions aimed at preventing or reducing pediatric obesity. RESEARCH HIGHLIGHTS: A continuous measure related to obesity, %BMIp95, has correlations with various measures of brain functioning and structure Behavioral genetic and longitudinal modeling suggest causal links from personality, psychopathology, and eating behavior to %BMIp95 Results also indicate directional links from %BMIp95 to eating behavior, cognition, cortical thickness, and cortical surface area Obesity may play a role for healthy brain development during childhood.

Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future

Obesity is a complex and heterogeneous condition that leads to various metabolic complications, including type 2 diabetes. Unfortunately, for some, treatment options to date for obesity are insufficient, with many people not reaching sustained weight loss or having improvements in metabolic health. In this Review, we discuss advances in the genetics of obesity from the past decade-with emphasis on developments from the past 5 years-with a focus on metabolic consequences, and their potential implications for precision management of the disease. We also provide an overview of the potential role of genetics in guiding weight loss strategies. Finally, we propose a vision for the future of precision obesity management that includes developing an obesity-centred multidisease management algorithm that targets both obesity and its comorbidities. However, further collaborative efforts and research are necessary to fully realise its potential and improve metabolic health outcomes.

Heightened sensitivity to high-calorie foods in children at risk for obesity: insights from behavior, neuroimaging, and genetics

Pediatric obesity is a major public health concern. Genetic susceptibility and increased availability of energy-dense food are known risk factors for obesity. However, the extent to which these factors jointly bias behavior and neural circuitry towards increased adiposity in children remains unclear. While undergoing fMRI, 108 children (ages 5-11y) performed a food-specific go/no-go task. Participants were instructed to either respond ("go") or inhibit responding ("no-go") to images of food or toys. Half of the runs depicted high-calorie foods (e.g., pizza) whereas the other half depicted low-calorie foods (e.g., salad). Children were also genotyped for a DNA polymorphism associated with energy intake and obesity (FTO rs9939609) to examine the influence of obesity risk on behavioral and brain responses to food. Participants demonstrated differences in behavioral sensitivity to high- and low-calorie food images depending on task demands. Participants were slower but more accurate at detecting high- (relative to low-) calorie foods when responding to a neutral stimulus (i.e., toys) and worse at detecting toys when responding to high-calorie foods. Inhibition failures were accompanied by salience network activity (anterior insula, dorsal anterior cingulate cortex), which was driven by false alarms to food images. Children at a greater genetic risk for obesity (dose-dependent model of the FTO genotype) demonstrated pronounced brain and behavioral relationships such that genetic risk was associated with heightened sensitivity to high-calorie food images and increased anterior insula activity. These findings suggest that high-calorie foods may be particularly salient to children at risk for developing eating habits that promote obesity.

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

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

Identifying latent genetic interactions in genome-wide association studies using multiple traits

Genome-wide association studies of complex traits frequently find that SNP-based estimates of heritability are considerably smaller than estimates from classic family-based studies. This 'missing' heritability may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. To circumvent these challenges, we propose a new method to detect genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Our approach, Latent Interaction Testing (LIT), uses the observation that correlated traits with shared latent genetic interactions have trait variance and covariance patterns that differ by genotype. LIT examines the relationship between trait variance/covariance patterns and genotype using a flexible kernel-based framework that is computationally scalable for biobank-sized datasets with a large number of traits. We first use simulated data to demonstrate that LIT substantially increases power to detect latent genetic interactions compared to a trait-by-trait univariate method. We then apply LIT to four obesity-related traits in the UK Biobank and detect genetic variants with interactive effects near known obesity-related genes. Overall, we show that LIT, implemented in the R package lit, uses shared information across traits to improve detection of latent genetic interactions compared to standard approaches.

Gene-environment interactions and the effect on obesity risk in low and middle-income countries: a scoping review

Background

Obesity represents a major and preventable global health challenge as a complex disease and a modifiable risk factor for developing other non-communicable diseases. In recent years, obesity prevalence has risen more rapidly in low- and middle-income countries (LMICs) compared to high-income countries (HICs). Obesity traits are shown to be modulated by an interplay of genetic and environmental factors such as unhealthy diet and physical inactivity in studies from HICs focused on populations of European descent; however, genetic heterogeneity and environmental differences prevent the generalisation of study results to LMICs. Primary research investigating gene-environment interactions (GxE) on obesity in LMICs is limited but expanding. Synthesis of current research would provide an overview of the interactions between genetic variants and environmental factors that underlie the obesity epidemic and identify knowledge gaps for future studies.

Methods

Three databases were searched systematically using a combination of keywords such as "genes", "obesity", "LMIC", "diet", and "physical activity" to find all relevant observational studies published before November 2022.

Results

Eighteen of the 1,373 articles met the inclusion criteria, of which one was a genome-wide association study (GWAS), thirteen used a candidate gene approach, and five were assigned as genetic risk score studies. Statistically significant findings were reported for 12 individual SNPs; however, most studies were small-scale and without replication.

Conclusion

Although the results suggest significant GxE interactions on obesity in LMICs, updated robust statistical techniques with more precise and standardised exposure and outcome measurements are necessary for translatable results. Future research should focus on improved quality replication efforts, emphasising large-scale and long-term longitudinal study designs using multi-ethnic GWAS.

Adipose Tissue Hyperplasia and Hypertrophy in Common and Syndromic Obesity-The Case of BBS Obesity

Obesity is a metabolic state generated by the expansion of adipose tissue. Adipose tissue expansion depends on the interplay between hyperplasia and hypertrophy, and is mainly regulated by a complex interaction between genetics and excess energy intake. However, the genetic regulation of adipose tissue expansion is yet to be fully understood. Obesity can be divided into common multifactorial/polygenic obesity and monogenic obesity, non-syndromic and syndromic. Several genes related to obesity were found through studies of monogenic non-syndromic obesity models. However, syndromic obesity, characterized by additional features other than obesity, suggesting a more global role of the mutant genes related to the syndrome and, thus, an additional peripheral influence on the development of obesity, were hardly studied to date in this regard. This review summarizes present knowledge regarding the hyperplasia and hypertrophy of adipocytes in common obesity. Additionally, we highlight the scarce research on syndromic obesity as a model for studying adipocyte hyperplasia and hypertrophy, focusing on Bardet-Biedl syndrome (BBS). BBS obesity involves central and peripheral mechanisms, with molecular and mechanistic alternation in adipocyte hyperplasia and hypertrophy. Thus, we argue that using syndromic obesity models, such as BBS, can further advance our knowledge regarding peripheral adipocyte regulation in obesity.

Obesity and the risk of cardiometabolic diseases

The prevalence of obesity has reached pandemic proportions, and now approximately 25% of adults in Westernized countries have obesity. Recognized as a major health concern, obesity is associated with multiple comorbidities, particularly cardiometabolic disorders. In this Review, we present obesity as an evolutionarily novel condition, summarize the epidemiological evidence on its detrimental cardiometabolic consequences and discuss the major mechanisms involved in the association between obesity and the risk of cardiometabolic diseases. We also examine the role of potential moderators of this association, with evidence for and against the so-called 'metabolically healthy obesity phenotype', the 'fatness but fitness' paradox or the 'obesity paradox'. Although maintenance of optimal cardiometabolic status should be a primary goal in individuals with obesity, losing body weight and, particularly, excess visceral adiposity seems to be necessary to minimize the risk of cardiometabolic diseases.

The body mass index is associated with increased temporal variability of functional connectivity in brain reward system

The reward system has been proven to be contributed to the vulnerability of obesity. Previous fMRI studies have shown abnormal functional connectivity of the reward system in obesity. However, most studies were based on static index such as resting-state functional connectivity (FC), ignoring the dynamic changes over time. To investigate the dynamic neural correlates of obesity susceptibility, we used a large, demographically well-characterized sample from the Human Connectome Project (HCP) to determine the relationship of body mass index (BMI) with the temporal variability of FC from integrated multilevel perspectives, i.e., regional and within- and between-network levels. Linear regression analysis was used to investigate the association between BMI and temporal variability of FC, adjusting for covariates of no interest. We found that BMI was positively associated with regional FC variability in reward regions, such as the ventral orbitofrontal cortex and visual regions. At the intra-network level, BMI was positively related to the variability of FC within the limbic network (LN) and default mode network (DMN). At the inter-network level, variability of connectivity of LN with DMN, frontoparietal, sensorimotor, and ventral attention networks showed positive correlations with BMI. These findings provided novel evidence for abnormal dynamic functional interaction between the reward network and the rest of the brain in obesity, suggesting a more unstable state and over-frequent interaction of the reward network and other attention and cognitive networks. These findings, thus, provide novel insight into obesity interventions that need to decrease the dynamic interaction between reward networks and other brain networks through behavioral treatment and neural modulation.

Harnessing male germline epigenomics for the genetic improvement in cattle

Sperm is essential for successful artificial insemination in dairy cattle, and its quality can be influenced by both epigenetic modification and epigenetic inheritance. The bovine germline differentiation is characterized by epigenetic reprogramming, while intergenerational and transgenerational epigenetic inheritance can influence the offspring's development through the transmission of epigenetic features to the offspring via the germline. Therefore, the selection of bulls with superior sperm quality for the production and fertility traits requires a better understanding of the epigenetic mechanism and more accurate identifications of epigenetic biomarkers. We have comprehensively reviewed the current progress in the studies of bovine sperm epigenome in terms of both resources and biological discovery in order to provide perspectives on how to harness this valuable information for genetic improvement in the cattle breeding industry.

Parental imprisonment, delinquent behavior, and BMI gain in a U.S. nationally representative cohort study of adolescents and adults ages 12-32

Children who experience parental imprisonment report greater mental and physical health adversities in adolescence and adulthood relative to comparable individuals whose parents did not serve time in prison. Research has linked BMI gain with parental imprisonment among females, but other studies have shown null or negative associations between parental imprisonment and weight increases for their offspring. Using longitudinal data from the National Longitudinal Study of Adolescent to Adult Health, this study attempts to resolve these differential findings by examining the interrelationship between delinquent behavior and BMI associated with parental imprisonment as individuals progress from adolescence into adulthood (ages 12-32). We show that higher delinquency levels are associated with lower BMI among men and women. With the transition from adolescence to adulthood, parental imprisonment is linked with increased BMI gain and obesity among females who are not delinquent. These findings highlight the need to consider how the decline in delinquent behavior and increasing health disparities between adolescence and adulthood may intersect as individuals experiencing parental imprisonment transition from adolescence to adulthood.

Impact of parental lifestyle patterns in the preconception and pregnancy periods on childhood obesity

Introduction

High prevalence of overweight and obesity already observed in preschool children suggests the involvement of early-life risk factors. Preconception period and pregnancy are crucial windows for the implementation of child obesity prevention interventions with parental lifestyle factors as relevant targets. So far, most studies have evaluated their role separately, with only a few having investigated their potential synergistic effect on childhood obesity. Our objective was to investigate parental lifestyle patterns in the preconception and pregnancy periods and their association with the risk of child overweight after 5 years.

Materials and methods

We harmonized and interpreted results from four European mother-offspring cohorts participating in the EndObesity Consortium [EDEN, France; Elfe, France; Lifeways, Ireland; and Generation R, Netherlands] with data available for 1,900, 18,000, 1,100, and 9,500 families, respectively. Lifestyle factors were collected using questionnaires and included parental smoking, body mass index (BMI), gestational weight gain, diet, physical activity, and sedentary behavior. We applied principal component analyses to identify parental lifestyle patterns in preconception and pregnancy. Their association with risk of overweight (including obesity; OW-OB) and BMI z-scores between 5 and 12 years were assessed using cohort-specific multivariable logistic and linear and regression models (adjusted for potential confounders including parental age, education level, employment status, geographic origin, parity, and household income).

Results

Among the various lifestyle patterns derived in all cohorts, the two explaining the most variance were characterized by (1) "high parental smoking, low maternal diet quality (and high maternal sedentary behavior in some cohorts)" and, (2) "high parental BMI and low gestational weight gain." Patterns characterized by high parental BMI, smoking, low diet quality or high sedentary lifestyle before or during pregnancy were associated with higher risk of OW-OB in children, and BMI z-score at any age, with consistent strengths of associations in the main cohorts, except for lifeways.

Conclusion

This project provides insight into how combined parental lifestyle factors in the preconception and pregnancy periods are associated with the future risk of child obesity. These findings are valuable to inform family-based and multi-behavioural child obesity prevention strategies in early life.

Maximizing the value of twin studies in health and behaviour

In the classical twin design, researchers compare trait resemblance in cohorts of identical and non-identical twins to understand how genetic and environmental factors correlate with resemblance in behaviour and other phenotypes. The twin design is also a valuable tool for studying causality, intergenerational transmission, and gene-environment correlation and interaction. Here we review recent developments in twin studies, recent results from twin studies of new phenotypes and recent insights into twinning. We ask whether the results of existing twin studies are representative of the general population and of global diversity, and we conclude that stronger efforts to increase representativeness are needed. We provide an updated overview of twin concordance and discordance for major diseases and mental disorders, which conveys a crucial message: genetic influences are not as deterministic as many believe. This has important implications for public understanding of genetic risk prediction tools, as the accuracy of genetic predictions can never exceed identical twin concordance rates.

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.

Obesity-related parameters in carriers of some BDNF genetic variants may depend on daily dietary macronutrients intake

Some common single-nucleotide polymorphisms of the brain-derived neurotrophic factor (BDNF) gene have been associated not only with the neurodegenerative diseases but also with some eating disorders. The aim of this study was to assess the possible differences in the obesity-related and glucose metabolism parameters between some BDNF genotypes', that may depend on the daily energy and macronutrients intake. In 484 adult participants we performed the anthropometric measurements, body composition analysis, and body fat distribution. The daily dietary intake was assessed using the 3-day food intake diaries. Blood glucose and insulin concentrations were measured at fasting and during oral glucose tolerance tests. Moreover, the visceral adipose tissue/subcutaneous adipose tissue (VAT/SAT) ratio and homeostatic model assessment of insulin resistance were calculated. We noted that participants carrying the GG genotype had lower skeletal muscle mass and fat free mass (FFM) when carbohydrate intake was > 48%, whereas they presented higher fat-free mass (FFM), and surprisingly higher total cholesterol and LDL-C concentrations when daily fiber intake was > 18 g. Moreover, in these subjects we noted higher waist circumference, BMI, and fasting glucose and insulin concentrations, when > 18% of total daily energy intake was delivered from proteins, and higher VAT content and HDL-C concentrations when > 30% of energy intake was derived from dietary fat. Our results suggest that glucose homeostasis and obesity-related parameters in carriers of some common variants of BDNF gene, especially in the GG (rs10835211) genotype carriers, may differ dependently on daily energy, dietary macronutrients and fiber intake.

Proteome and genome integration analysis of obesity

ABSTRACT

The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.

Understanding drivers of micro-level disparities in childhood body mass index, overweight, and obesity within low-income, minority communities

The focus of childhood obesity disparities has been mainly on macro-level disparities, such as, between lower versus higher socioeconomic groups. But, less is known about micro-level disparities, that is disparities within minority and low-income populations. The present study examines individual and family level predictors of micro-level obesity disparities. We analyze data on 497 parent-child dyads living in public housing communities in Watts, Los Angeles. Cross-sectional multivariable linear and logistic regression models were estimated to examine whether individual and family level factors predict children's BMI z-scores, overweight, and obesity in the sample overall and separately by child's gender and age group. Child characteristics of our study sample included mean age 10.9 years, 74.3% Hispanic, 25.7% Non-Hispanic Black, 53.1% female, 47.5% with household income below $10,000, 53.3% with overweight or obesity, and 34.6% with obesity. Parental BMI was the strongest and most consistent predictor of child zBMI, overweight, and obesity, even after controlling for parent's diet and activity behaviors and home environment. The parenting practice of limiting children's screentime was also protective of unhealthy BMI in younger children and females. Home environment, parental diet and activity behaviors, and parenting practices related to food and bedtime routines were not significant predictors. Overall, our findings show that there is considerable heterogeneity in child BMI, overweight, and obesity even within low-income communities with similar socioeconomic and built environments in their neighborhoods. Parental factors play an important role in explaining micro-level disparities and should be an integral part of obesity prevention strategies in low-income minority communities.

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.

Genetic and Environmental Factors Underlying Parallel Changes in Body Mass Index and Alcohol Consumption: A 36-Year Longitudinal Study of Adult Twins

INTRODUCTION

While the genetic and environmental underpinnings of body weight and alcohol use are fairly well-known, determinants of simultaneous changes in these traits are still poorly known. We sought to quantify the environmental and genetic components underlying parallel changes in weight and alcohol consumption and to investigate potential covariation between them.

METHODS

The analysis comprised 4,461 adult participants (58% women) from the Finnish Twin Cohort with four measures of alcohol consumption and body mass index (BMI) over a 36-year follow-up. Trajectories of each trait were described by growth factors, defined as intercepts (i.e., baseline) and slopes (i.e., change over follow-up), using latent growth curve modeling. Growth values were used for male (190 monozygotic pairs, 293 dizygotic pairs) and female (316 monozygotic pairs, 487 dizygotic pairs) same-sex complete twin pairs in multivariate twin modeling. The variances and covariances of growth factors were then decomposed into genetic and environmental components.

RESULTS

The baseline heritabilities were similar in men (BMI: h2 = 79% [95% confidence interval: 74, 83]; alcohol consumption: h2 = 49% [32, 67]) and women (h2 = 77% [73, 81]; h2 = 45% [29, 61]). Heritabilities of BMI change were similar in men (h2 = 52% [42, 61]) and women (h2 = 57% [50, 63]), but the heritability of change in alcohol consumption was significantly higher (p = 0.03) in men (h2 = 45% [34, 54]) than in women (h2 = 31% [22, 38]). Significant additive genetic correlations between BMI at baseline and change in alcohol consumption were observed in both men (rA = -0.17 [-0.29, -0.04]) and women (rA = -0.18 [-0.31, -0.06]). Non-shared environmental factors affecting changes in alcohol consumption and BMI were correlated in men (rE = 0.18 [0.06, 0.30]). Among women, non-shared environmental factors affecting baseline alcohol consumption and the change in BMI were inversely correlated (rE = -0.11 [-0.20, -0.01]).

CONCLUSIONS

Based on genetic correlations, genetic variation underlying BMI may affect changes in alcohol consumption. Independent of genetic effects, change in BMI correlates with change in alcohol consumption in men, suggesting direct effects between them.

Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene

Obesity remains an unmet global health burden. Detrimental anatomical distribution of body fat is a major driver of obesity-mediated mortality risk and is demonstrably heritable. However, our understanding of the full genetic contribution to human adiposity is incomplete, as few studies measure adiposity directly. To address this, we impute whole-body imaging adiposity phenotypes in UK Biobank from the 4,366 directly measured participants onto the rest of the cohort, greatly increasing our discovery power. Using these imputed phenotypes in 392,535 participants yielded hundreds of genome-wide significant associations, six of which replicate in independent cohorts. The leading causal gene candidate, ADAMTS14, is further investigated in a mouse knockout model. Concordant with the human association data, the Adamts14-/- mice exhibit reduced adiposity and weight-gain under obesogenic conditions, alongside an improved metabolic rate and health. Thus, we show that phenotypic imputation at scale offers deeper biological insights into the genetics of human adiposity that could lead to therapeutic targets.

Identification and Association of Single Nucleotide Polymorphisms of the FTO Gene with Indicators of Overweight and Obesity in a Young Mexican Population

(1) Background: obesity is a global public health problem; various factors have been associated with this disease, and genetic factors play a very important role. Previous studies in multiple populations have associated a gene with fat mass and obesity (FTO). Thus, the present work aims to identify and determine associations between genetic variants of FTO with indicators of overweight and obesity in the Mexican population. (2) Methods: a total of 638 subjects were evaluated to compile data on body mass index (BMI), the percentage of body fat (%BF), the waist circumference (WC), the serum levels of triglycerides (TG), and food consumption. A total of 175 genetic variants in the FTO gene were sampled by a microarray in the evaluated population, followed by association statistical analyses and comparisons of means. (3) Results: a total of 34 genetic variants were associated with any of the 6 indicators of overweight and obesity, but only 15 showed mean differences using the recessive model after the Bonferroni correction. The present study shows a wide evaluation of FTO genetic variants associated with a classic indicator of overweight and obesity, which highlights the importance of genetic analyses in the study of obesity.