Common variants near MC4R are associated with fat mass, weight and risk of obesity

Insights into the molecular and genetic role of obesity in breast cancer pathogenesis

The epidemic of obesity is a growing concern and is one of the major risk factors for several chronic diseases, including several types of cancers. The correlation of breast cancer with obesity has been extensively studied and involves an interplay of hormonal, metabolic, and genetic factors explored in this review. Inflammation and hormone dysregulation play an important role in promoting a protumorigenic environment through adipose tissue, which is involved in energy storage and functions as an endocrine organ. As a result, various cytokines, primarily proinflammatory in nature, are released, resulting in low-grade inflammation promoting tumor growth. Additionally, obese conditions also induce imbalances in hormones, particularly estrogen and insulin, both of which drive carcinogenesis. Genetic components such as single nucleotide polymorphisms also play critical roles in modulating the correlation between obesity and breast cancer. This review provides a comprehensive overview of various mechanisms underlying obesity and breast cancer incidence and progression.

Impact of recognition of genetic information related to BMI on changes in physical activity, dietary intake, and blood cholesterol level: a randomized controlled trial

PURPOSE

Genes associated with body mass index (BMI), including FTO rs9939609,MC4R rs17782313, and BDNF rs6265, may influence BMI and regulate energy metabolism. While previous studies have explored health-related behavior changes, few have investigated both biochemical and behavior changes resulting from perceived genetic risk. This study investigated whether recognizing BMI-related genes affects health-related behaviors and alters blood metabolite levels.

METHODS

Normal and overweight adults aged 25-35 years (n = 100) were randomly assigned to an intervention group (n = 65) informed about BMI-related genetic information (FTO rs9939609, MC4R rs17782313, BDNF rs6265) and an uninformed group (n = 35, CON). The intervention group was further divided into Intervention-high risk (IHR, n = 36) and intervention-low risk (ILR, n = 29) subgroups. Dietary intake and physical activity (PA) were assessed using a 3-day dietary record and the IPAQ-short form. Blood metabolites were analyzed through multivariate analyses to identify significant differences among the groups, with measurements taken at baseline, 3 months, and 6 months.

RESULTS

The IHR group exhibited increased dietary fat and fast foods intake, along with enhanced vigorous and moderate PA. Six metabolites were selected as biomarkers that were distinguishable among groups, and the relative serum cholesterol levels significantly decreased in the IHR group at 3 months.

CONCLUSION

These results demonstrate that recognizing the BMI-associated genetic risk resulted in a short-term increase in PA but did not improve dietary intake. Increased PA was significantly associated with reduced cholesterol concentration, suggesting the clinical importance of physical activity in the genetically at-risk group.

CLINICAL TRIAL AND STUDY REGISTRATION

This study was reviewed and approved by the Seoul National University Institutional Review Board (IRB #1901/001-004) and registered on the Clinical Research Information Service (CRIS), KCT0004650 ( https://cris.nih.go.kr/cris/search/detailSearch.do /14091, 2020/01/28).

Genetic variants in the MC4R gene and risk of obesity/overweight: A systematic review and meta-analysis

AIM

Obesity is a significant health issue worldwide, progressing due to genetic factors and lifestyle. Melanocortin 4 receptor (MC4R) gene polymorphisms have been identified as a cause of overweight and obesity risk. The aim of this study was a comprehensive assessment of MC4R polymorphism effects on overweight/obesity risk.

METHODS

All retrieved literature from PubMed, Web of Science and Scopus according to PRISMA guidelines up to June 2022 was reviewed. Inclusion criteria are restricted to English-language, human case-control/cohort studies with genotype distributions of MC4R polymorphisms and their association with obesity and overweight in any geographic regions and age. The heterogeneity using the I-squared statistic (I2), the Q-test and Prediction Interval (PI) and publication bias using Begg's and Egger's tests were examined, and the pooled odds ratios in different genetic models were estimated using a random effect model. Subgroup analysis was performed by the geographic regions and age groups. Risk of bias for individual studies was not assessed. The review is limited by restricted racial diversity and exclusion of environmental factors, incomplete data and limited access to certain articles. This work received no specific funding, and the review was not prospectively registered.

RESULTS

In our study, 39 eligible studies with 43 697 overweight and obese cases and 52 272 normal weights were included. In mixed-age populations, rs17700633, rs17782313, rs11872992, rs12970134, rs2229616 and rs571312 were evaluated. The remarkable association was seen by rs17782313 and rs12970134 in the Homozygous model (OR = 1.73; 95% CI: 1.51, 1.98 and 1.74; 95% CI: 1.29; 2.35, respectively). In addition, rs17782313 and rs12970134 were found to be more strongly linked to overweight and obesity in Asian and European population groups, as determined by a subgroup analysis of the geographic regions.

CONCLUSION

The present study confirms the high association of rs17782313 and rs12970134 with obesity and overweight in all age groups and geographic regions. However, further functional studies and high-population research on other MC4R SNPs must validate their role.

Pitfalls in performing genome-wide association studies on ratio traits

Genome-wide association studies (GWASs) are often performed on ratios composed of a numerator trait divided by a denominator trait. Examples include body mass index (BMI) and the waist-to-hip ratio, among many others. Explicitly or implicitly, the goal of forming the ratio is typically to adjust for an association between the numerator and denominator. While forming ratios may be clinically expedient, there are several important issues with performing GWAS on ratios. Forming a ratio does not "adjust" for the denominator in the sense of conditioning on it, and it is unclear whether associations with ratios are attributable to the numerator, the denominator, or both. Here we demonstrate that associations arising in ratio GWAS can be entirely denominator driven, implying that at least some associations uncovered by ratio GWAS may be due solely to a putative adjustment variable. In a survey of 10 common ratio traits, we find that the ratio model disagrees with the adjusted model (performing GWAS on the numerator while conditioning on the denominator) at around 1/3 of loci. Using BMI as an example, we show that variants detected by only the ratio model are more strongly associated with the denominator (height), while variants detected by only the adjusted model are more strongly associated with the numerator (weight). Although the adjusted model provides effect sizes with a clearer interpretation, it is susceptible to collider bias. We propose and validate a simple method of correcting for the genetic component of collider bias via leave-one-chromosome-out polygenic scoring.

A gain-of-function variant in RICTOR predisposes to human obesity

mTORC1/2 play central roles as signaling hubs of cell growth and metabolism and are therapeutic targets for several diseases. However, the human genetic evidence linking mutations of mTORC1/2 to obesity remains elusive. Using whole-exome sequencing of 1944 cases with severe obesity and 2161 healthy lean controls, we identify a rare RICTOR p.I116V variant enriched in 9 unrelated cases. In Rictor null mouse embryonic fibroblasts, overexpression of the RICTOR p.I116V mutant increases phosphorylation of AKT, a canonical mTORC2 substrate, compared with wild-type RICTOR, indicating a gain-of-function change. Consistent with the human obesity phenotype, the knock-in mice carrying homogenous Rictor p.I116V variants gain more body weight under a high-fat diet. Additionally, the stromal vascular fraction cells derived from inguinal white adipose tissue of knock-in mice display an enhanced capacity for adipocyte differentiation via AKT activity. These findings demonstrate that the rare gain-of-function RICTOR p.I116V mutation activates AKT signaling, promotes adipogenesis, and contributes to obesity in humans.

Missense variants in FRS3 affect body mass index in populations of diverse ancestries

Obesity is associated with adverse effects on health and quality of life. Improved understanding of its underlying pathophysiology is essential for developing counteractive measures. To search for sequence variants with large effects on BMI, we perform a multi-ancestry meta-analysis of 13 genome-wide association studies on BMI, including data derived from 1,534,555 individuals of European ancestry, 339,657 of Asian ancestry, and 130,968 of African ancestry. We identify an intergenic 262,760 base pair deletion at the MC4R locus that associates with 4.11 kg/m2 higher BMI per allele, likely through downregulation of MC4R. Moreover, a rare FRS3 missense variant, p.Glu115Lys, only found in individuals from Finland, associates with 1.09 kg/m2 lower BMI per allele. We also detect three other low-frequency FRS3 missense variants that associate with BMI with smaller effects and are enriched in different ancestries. We characterize FRS3 as a BMI-associated gene, encoding an adaptor protein known to act downstream of BDNF and TrkB, which regulate appetite, food intake, and energy expenditure through unknown signaling pathways. The work presented here contributes to the biological foundation of obesity by providing a convincing downstream component of the BDNF-TrkB pathway, which could potentially be targeted for obesity treatment.

Integrative proteomic and lipidomic analysis of GNB1 and SCARB2 knockdown in human subcutaneous adipocytes

Obesity, a global public health concern, is influenced by various factors, including genetic predispositions. Although many obesity-associated genes have been identified through genome-wide association studies (GWAS), the molecular mechanisms linking these genes to adipose tissue function remain largely unexplored. This study integrates proteomic data on adipocyte fat accumulation with GWAS data on obesity to unravel the roles of the identified key candidate genes - G protein subunit beta 1 (GNB1) and scavenger receptor class B member 2 (SCARB2) - involved in fat accumulation. We utilized RNA interference to knock down GNB1 and SCARB2 in human subcutaneous adipocytes, followed by lipidome and proteome analyses using mass spectrometry. Knockdown of these genes resulted in a reduction in lipid droplet accumulation, indicating their role in adipocyte lipid storage. Digital PCR confirmed effective gene knockdown, with GNB1 and SCARB2 mRNA levels significantly reduced. In total, the lipidomic analysis identified 96 lipid species with significant alterations. GNB1 knockdown resulted in a decrease in cholesterol esters and an increase in phosphatidylcholines, phosphatidylinositols, and ceramides. SCARB2 knockdown also led to an increase in phosphatidylcholines, with a trend towards decreased triacylglycerols. Proteomic analysis revealed significant changes in proteins involved in lipid metabolism and adipocyte function, including PLPP1 and CDH13, which were upregulated following GNB1 knockdown, and HSPA8, which was downregulated. Conversely, SCARB2 knockdown resulted in the downregulation of PLPP1 and METTL7A, and the upregulation of PLIN2, HSPA8, NPC2, and SQSTM1. Our findings highlight the significant roles of GNB1 and SCARB2 in lipid metabolism and adipocyte function, providing insights that could inform therapeutic strategies targeting these regulatory genes in obesity.

The Microbiota and Evolution of Obesity

Obesity is a major global concern and is generally attributed to a combination of genetic and environmental factors. Several hypotheses have been proposed to explain the evolutionary origins of obesity epidemic, including thrifty and drifty genotypes, and changes in thermogenesis. Here, we put forward the hypothesis of metaflammation, which proposes that due to intense selection pressures exerted by environmental pathogens, specific genes that help develop a robust defense mechanism against infectious diseases have had evolutionary advantages and that this may contribute to obesity in modern times due to connections between the immune and energy storage systems. Indeed, incorporating the genetic variations of gut microbiota into the complex genetic framework of obesity makes it more polygenic than previously believed. Thus, uncovering the evolutionary origins of obesity requires a multifaceted approach that considers the complexity of human history, the unique genetic makeup of different populations, and the influence of gut microbiome on host genetics.

A cellular and molecular basis of leptin resistance

Similar to most humans with obesity, diet-induced obese (DIO) mice have high leptin levels and fail to respond to the exogenous hormone, suggesting that their obesity is caused by leptin resistance, the pathogenesis of which is unknown. We found that leptin treatment reduced plasma levels of leucine and methionine, mTOR-activating ligands, leading us to hypothesize that chronic mTOR activation might reduce leptin signaling. Rapamycin, an mTOR inhibitor, reduced fat mass and increased leptin sensitivity in DIO mice but not in mice with defects in leptin signaling. Rapamycin restored leptin's actions on POMC neurons and failed to reduce the weight of mice with defects in melanocortin signaling. mTOR activation in POMC neurons caused leptin resistance, whereas POMC-specific mutations in mTOR activators decreased weight gain of DIO mice. Thus, increased mTOR activity in POMC neurons is necessary and sufficient for the development of leptin resistance in DIO mice, establishing a key pathogenic mechanism leading to obesity.

The interaction between the Circadian Locomotor Output Cycles Kaput and Melanocortin-4-receptor gene variants on obesity and parameters related to obesity

INTRODUCTION

Obesity is a multifactorial disease caused by an interaction between genetic, environmental and behavioral factors. Polymorphisms of the two genes Circadian Locomotor Output Cycles Kaput (CLOCK) rs1801260 and Melanocortin-4-receptor (MC4R) rs17782313, are associated with obesity. Knowledge is limited on the interaction between CLOCK, MC4R and obesity. The aim was to explore the interactions between the CLOCK and MC4R gene variants on markers related to obesity.

METHODS

There were 423 subjects with information on two genetic variants of two genes (CLOCK and MC4R). Their interaction was evaluated with: chronotype, sleeping duration, emotional eating, food timing, stress, dietary intake, appetite, physical activity (assessed by questionnaires), anthropometric measures of obesity (assessed by physical measurements), and also hormonal factors (assessed by ELISA). Generalized Linear Models were applied.

RESULTS

Our results revealed that significant differences were observed between the genotypes of CLOCK rs1801260 for weight, Body Mass Index (BMI), Glucagon-like peptide-1 (GLP-1), cortisol, energy, fat, sleep duration, chronotype, appetite, depression, stress, emotional eating, physical activity, breakfast, lunch, and dinner time (p˂0.05). Also, significant differences were observed between the genotypes of MC4R rs17782313 for weight, BMI, Waist Circumference (WC), Waist to Hip Ratio (WHR), ghrelin, energy, carbohydrate, fat, appetite, depression, stress, breakfast time, and emotional eating (p˂0.05). Our findings also showed significant interactions between the CLOCK (CC)∗MC4R (CT) genotypes for higher appetite, stress and CLOCK (CT)∗ MC4R (CC) genotypes for higher fat and energy intake and CLOCK (CC)∗MC4R (CC) genotypes for higher weight, BMI, energy and fat intake, appetite, emotional eating, stress, ghrelin, cortisol and lower sleep duration and GLP-1 (p˂ 0.05).

CONCLUSION

Due to the non-significance of the interaction in CLOCK (CT)∗ MC4R (CT) genotypes, it seems that the presence of a healthy arm in the CLOCK and MC4R polymorphism is necessary for the proper function of the genes. Thus, these results highlight that gene variants and their interaction should be considered in obesity assessment.

GPTrans: A Biological Language Model-Based Approach for Predicting Disease-Associated Mutations in G Protein-Coupled Receptors

Accurately predicting mutations in G protein-coupled receptors (GPCRs) is critical for advancing disease diagnosis and drug discovery. In response to this imperative, GPTrans has emerged as a highly accurate predictor of disease-related mutations in GPCRs. The core innovation of GPTrans resides in the design of a novel feature extraction network, that is capable of integrating features from both wildtype and mutant protein variant sites, utilizing multifeature connections within a transformer framework to ensure comprehensive feature extraction. A key aspect of GPTrans's effectiveness is our introduction of an innovative deep feature integration strategy, which merges embeddings and class tokens from multiple protein language models, including evolutionary scale modeling and ProtTrans, thus shedding light on the biochemical properties of proteins. Leveraging transformer components and a self-attention mechanism, GPTrans captures higher-level representations of protein features. Employing both wildtype and mutation site information for feature fusion not only enriches the predictive feature set but also avoids the common issue of overestimation associated with sequence-based predictions. This approach distinguishes GPTrans, enabling it to significantly outperform existing methods. Our evaluations across diverse GPCR data sets, including ClinVar and MutHTP, demonstrate GPTrans's superior performance, with average AUC values of 0.874 and 0.590 in 10-fold cross-validation. Notably, compared to the AlphaMissense method, GPTrans exhibited a remarkable 38.03% improvement in accuracy when predicting disease-associated mutations in the MutHTP data set. A thorough analysis of the predicted results further validates the model's effectiveness. The source code, data sets, and prediction results for GPTrans are available for academic use at https://github.com/EduardWang/GPTrans.

Motivational dysregulation with melanocortin 4 receptor haploinsufficiency

Obesity, by any standard, is a global health crisis. Both genetic and dietary contributions to the development and maintenance of obesity were integral factors of our experimental design. As mutations of the melanocortin 4 receptors (MC4R) are the leading monogenetic cause of obesity, MC4R haploinsufficient rats were fed a range of dietary fat (0-12 %) in a longitudinal design. Physiological and motivational assessments were performed using a locomotor task, a 5-choice sucrose preference task, an operant task with fixed and progressive ratios, as well as a distraction operant task. Dendritic spine morphology of medium spiny neurons (MSNs) of the nucleus accumbens (NAc), cells with ample D1 and D2 receptors, was also assessed. The percentage of lipid deposits in the liver of each rat was also analyzed using the Area Fraction Fractionator probe for stereological measurements. MC4R haploinsufficiency resulted in a phenotypic resemblance for adult-onset obesity that was exacerbated by the consumption of a high-fat diet. Results from the operant tasks indicate that motivational deficits due to MC4R haploinsufficiency were apparent prior to the onset of obesity and exacerbated by dietary fat consumption after obesity was well established. Moreover, MSN morphology shifted to longer spines with smaller head diameters for the MC4R+/- animals under the high-fat diet, suggesting a potential mechanism for the dysregulation of motivation to work for food. Increasing our knowledge of the neural circuitry/mechanisms responsible for the rewarding properties of food has significant implications for understanding energy balance and the development of obesity.

Guidelines for in vivo models of developmental programming of cardiovascular disease risk

Research using animals depends on the generation of offspring for use in experiments or for the maintenance of animal colonies. Although not considered by all, several different factors preceding and during pregnancy, as well as during lactation, can program various characteristics in the offspring. Here, we present the most common models of developmental programming of cardiovascular outcomes, important considerations for study design, and provide guidelines for producing and reporting rigorous and reproducible cardiovascular studies in offspring exposed to normal conditions or developmental insult. These guidelines provide considerations for the selection of the appropriate animal model and factors that should be reported to increase rigor and reproducibility while ensuring transparent reporting of methods and results.

A molecularly defined orbitofrontal cortical neuron population controls compulsive-like behavior, but not inflexible choice or habit

Habits are familiar behaviors triggered by cues, not outcome predictability, and are insensitive to changes in the environment. They are adaptive under many circumstances but can be considered antecedent to compulsions and intrusive thoughts that drive persistent, potentially maladaptive behavior. Whether compulsive-like and habit-like behaviors share neural substrates is still being determined. Here, we investigated mice bred to display inflexible reward-seeking behaviors that are insensitive to action consequences. We found that these mice demonstrate habitual response biases and compulsive-like grooming behavior that was reversible by fluoxetine and ketamine. They also suffer dendritic spine attrition on excitatory neurons in the orbitofrontal cortex (OFC). Nevertheless, synaptic melanocortin 4 receptor (MC4R), a factor implicated in compulsive behavior, is preserved, leading to the hypothesis that Mc4r+ OFC neurons may drive aberrant behaviors. Repeated chemogenetic stimulation of Mc4r+ OFC neurons triggered compulsive and not inflexible or habitual response biases in otherwise typical mice. Thus, Mc4r+ neurons within the OFC appear to drive compulsive-like behavior that is dissociable from habitual behavior. Understanding which neuron populations trigger distinct behaviors may advance efforts to mitigate harmful compulsions.

The Association between Obesity Susceptibility and Polymorphisms of MC4R, SH2B1, and NEGR1 in Tibetans

Background: A high-altitude environment has inhibitory effects on obesity. Tibetans are not a high-risk population for obesity, but there are still obese individuals within that population. Obesity has become a worldwide health problem, and previous studies have found that obesity is closely associated with hereditary factors. Few studies have investigated obesity in Tibetans, and the association between gene polymorphisms and obesity in Tibetans remains unclear. Methods: Our study investigated the fat mass of 140 native Tibetan individuals (70 men and 70 women) from Lhasa and analyzed the associations between polymorphisms of melanocortin 4 receptor (MC4R), Src homology 2B adapter protein 1 (SH2B1), and neuronal growth regulator 1 (NEGR1) and obesity. Result: Among Tibetan individuals, there were differences in genotype and allele frequencies between those in the obesity group and those in the healthy group at MC4R (rs17782313) and SH2B1 (rs7359397). The polymorphisms of MC4R (rs17782313) were associated with fat mass and obesity in Tibetan men and women, and there was an association between SH2B1 (rs7359397) polymorphisms and fat mass and obesity in Tibetan men. However, polymorphisms of NEGR1 (rs3101336) were not associated with fat mass or obesity in Tibetan individuals. Conclusion: Among Tibetan individuals, polymorphisms of MC4R (rs17782313) and SH2B1 (rs7359397) were associated with obesity, but NEGR1 (rs3101336) polymorphisms were not associated with obesity.

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci

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

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Grants

• R01 HL143885 NHLBI NIH HHS
• R01 HL142302 NHLBI NIH HHS
• R01 HL151152 NHLBI NIH HHS
• HHSN268201500001I NHLBI NIH HHS
• R01 DK139598 NIDDK NIH HHS
• N01HC25195 NHLBI NIH HHS
• R01 HG010297 NHGRI NIH HHS
• HHSN268201500001C NHLBI NIH HHS
• R01 HL163262 NHLBI NIH HHS
• R01 HL092577 NHLBI NIH HHS
• P20 MD000170 NIMHD NIH HHS
• 75N92019D00031 NHLBI NIH HHS
• R01 HD057194 NICHD NIH HHS
• UL1 TR000371 NCATS NIH HHS
• R01 DK122503 NIDDK NIH HHS

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Affiliation(s)

Hanfei Xu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Shreyash Gupta Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ian Dinsmore Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Abbey Kollu Department of Psychology and Neuroscience, University of North Carolina, 235 E. Cameron Avenue, Chapel Hill, NC, 27599, USA
Anne Marie Cawley Marsico Lung Institute, University of North Carolina, 125 Mason Farm Rd, Chapel Hill, NC, 27599, USA
Mohammad Y. Anwar Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Hung-Hsin Chen Institute of Biomedical Sciences, Academia Sinica, No. 128, Section 2, Academia Rd., Taipei, Nangang District, 115201, Taiwan Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Lauren E. Petty Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Sudha Seshadri Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, 8300 Floyd Curl Drive, San Antonio, TX, 78229, USA
Misa Graff Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Piper Below Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, 1161 21st Ave S, Nashville, TN, 37232, USA
Jennifer A. Brody Department of Medicine, Cardiovascular Health Research Unit, University of Washington, 1730 Minor Ave, Seattle, WA, 98101, USA
Geetha Chittoor Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Susan P. Fisher-Hoch Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Nancy L. Heard-Costa Framingham Heart Study, 73 Mt Wayte Ave, Framingham, MA, 01702, USA Department of Neurology, Chobanian & Avedisian School of Medicine, Boston University, 72 E Concord St, Boston, MA, 02118, USA
Daniel Levy Population Sciences Branch, National Heart, Lung, and Blood Institute of the National Institutes of Health, 6701 Rockledge Drive, Bethesda, MD, 20892, USA
Honghuang Lin Department of Medicine, University of Massachusetts Chan Medical School, 55 N Lake Ave, Worcester, MA, 01655, USA
Ruth JF. Loos Charles Bronfman Institute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY, 10029, USA Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3A, 2200, Copenhagen, Denmark
Joseph B. Mccormick Department of Epidemiology, School of Public Health, UT Health Houston, Regional Academic Health Center, One West University Blvd, Brownsville, TX, 78520, USA
Jerome I. Rotter Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 West Carson Street, Torrance, CA, 90502, USA
Tooraj Mirshahi Department of Genomic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Christopher D. Still Center for Obesity and Metabolic Health, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Anita Destefano Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA Department of Neurology, School of Medicine, Boston University, 85 East Concord Street, Boston, MA, 02118, USA
L. Adrienne Cupples Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA
Karen L Mohlke Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC, 27599, USA
Kari E. North Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, Chapel Hill, NC, 27599, USA
Anne E. Justice Department of Population Health Sciences, Geisinger, 100 N. Academy Ave., Danville, PA, 17822, USA
Ching-Ti Liu Department of Biostatistics, School of Public Health, Boston University, 801 Massachusettes Ave, Boston, MA, 02118, USA

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Associations Between Obesity-Related Gene MC4R rs17782313 Locus Polymorphism and Components of Metabolic Syndrome: A Systematic Review and Meta-Analysis

Objective: It is well established that melanocortin-4 receptor (MC4R) rs17782313 locus polymorphism is associated with increased obesity risk and that obesity is strongly associated with an enhanced risk of all metabolic syndrome (MS) components. Thus, in this study, we examined the association between the MC4R rs17782313 locus polymorphism and the risk of the remaining MS components, namely, diabetes, hypertension, low high-density lipoprotein (HDL), and hypertriglyceridemia. Methods: We performed an extensive literature screening across six scientific databases, namely, PubMed, Embase, Web of Science, Medline, ScienceDirect, CNKI, and WanFang employing a specific search strategy. Eligible studies were selected for inclusion in our meta-analysis, and odds ratio (OR) values and 95% confidence interval (CI) were computed through fixed- or random-effects models to examine correlation strength. In addition, we performed subgroup analyses involving adjustment factors (unadjusted body mass index [BMI], adjusted BMI), race (Caucasian, Asian), and source of controls (population, hospital). Results: Twenty-two eligible studies were selected from 846 articles, involving 28,018 patients and 98,994 normal participants. Based on this meta-analysis, the MC4R rs17782313 locus polymorphism was associated with an augmented risk of diabetes (allele contrast model T vs. C: OR = 1.05, 95% CI = 1.03-1.08; dominant model TT vs. TC + CC: OR = 1.07, 95% CI = 1.03-1.11) and hypertension (dominant model TT vs. TC + CC: OR = 1.16, 95% CI = 1.03-1.31) risk. However, based on this analysis, the MC4R rs17782313 locus polymorphism was not associated with low HDL and hypertriglyceridemia risk. Conclusions: Based on this analysis, the MC4R rs17782313 locus polymorphism is associated with enhanced risks of diabetes and hypertension, while the associations with low HDL and hypertriglyceridemia require further exploration.

Mechanisms and risk factors of metabolic syndrome in children and adolescents

Metabolic syndrome (MetS) is a complex disorder characterized by abdominal obesity, elevated blood pressure, hyperlipidemia, and elevated fasting blood glucose levels. The diagnostic criteria for MetS in adults are well-established, but there is currently no consensus on the definition in children and adolescents. The etiology of MetS is believed to involve a complex interplay between genetic predisposition and environmental factors. While genetic predisposition explains only a small part of MetS pathogenesis, modifiable environmental risk factors play a significant role. Factors such as maternal weight during pregnancy, children's lifestyle, sedentariness, high-fat diet, fructose and branched-chain amino acid consumption, vitamin D deficiency, and sleep disturbances contribute to the development of MetS. Early identification and treatment of MetS in children and adolescents is crucial to prevent the development of chronic diseases later in life. In this review we discuss the latest research on factors contributing to the pathogenesis of MetS in children, focusing on non-modifiable and modifiable risk factors, including genetics, dysbiosis and chronic low-grade inflammation.

Melanocortin 3,5 receptors immunohistochemical expression in colonic mucosa of inflammatory bowel disease patients: A matter of disease activity?

BACKGROUND

Melanocortin 3 and 5 receptors (i.e., MC3R and MC5R) belong to the melanocortin family. However, data regarding their role in inflammatory bowel diseases (IBD) are currently unavailable.

AIM

This study aims to ascertain their expression profiles in the colonic mucosa of Crohn's disease (CD) and ulcerative colitis (UC), aligning them with IBD disease endoscopic and histologic activity.

METHODS

Colonic mucosal biopsies from CD/UC patients were sampled, and immunohistochemical analyses were conducted to evaluate the expression of MC3R and MC5R. Colonic sampling was performed on both traits with endoscopic scores (Mayo endoscopic score and CD endoscopic index of severity) consistent with inflamed mucosa and not consistent with disease activity (i.e., normal appearing mucosa).

RESULTS

In both CD and UC inflamed mucosa, MC3R (CD: + 7.7 fold vs normal mucosa, P < 0.01; UC: + 12 fold vs normal mucosa, P < 0.01) and MC5R (CD: + 5.5 fold vs normal mucosa, P < 0.01; UC: + 8.1 fold vs normal mucosa, P < 0.01) were significantly more expressed compared to normal mucosa.

CONCLUSION

MC3R and MC5R are expressed in the colon of IBD patients. Furthermore, expression may differ according to disease endoscopic activity, with a higher degree of expression in the traits affected by disease activity in both CD and UC, suggesting a potential use of these receptors in IBD pharmacology.

Combined transcriptome and metabolome analysis reveals breed-specific regulatory mechanisms in Dorper and Tan sheep

BACKGROUND

Dorper and Tan sheep are renowned for their rapid growth and exceptional meat quality, respectively. Previous research has provided evidence of the impact of gut microbiota on breed characteristics. The precise correlation between the gastrointestinal tract and peripheral organs in each breed is still unclear. Investigating the metabolic network of the intestinal organ has the potential to improve animal growth performance and enhance economic benefits through the regulation of intestinal metabolites.

RESULTS

In this study, we identified the growth advantage of Dorper sheep and the high fat content of Tan sheep. A transcriptome study of the brain, liver, skeletal muscle, and intestinal tissues of both breeds revealed 3,750 differentially expressed genes (DEGs). The genes PPARGC1A, LPL, and PHGDH were found to be highly expressed in Doper, resulting in the up-regulation of pathways related to lipid oxidation, glycerophospholipid metabolism, and amino acid anabolism. Tan sheep highly express the BSEP, LDLR, and ACHE genes, which up-regulate the pathways involved in bile transport and cholesterol homeostasis. Hindgut content analysis identified 200 differentially accumulated metabolites (DAMs). Purines, pyrimidines, bile acids, and fatty acid substances were more abundant in Dorper sheep. Based on combined gene and metabolite analyses, we have identified glycine, serine, and threonine metabolism, tryptophan metabolism, bile secretion, cholesterol metabolism, and neuroactive ligand-receptor interaction as key factors contributing to the differences among the breeds.

CONCLUSIONS

This study indicates that different breeds of sheep exhibit unique breed characteristics through various physiological regulatory methods. Dorper sheep upregulate metabolic signals related to glycine, serine, and threonine, resulting in an increase in purine and pyrimidine substances. This, in turn, promotes the synthesis of amino acids and facilitates body development, resulting in a faster rate of weight gain. Tan sheep accelerate bile transport, reduce bile accumulation in the intestine, and upregulate cholesterol homeostasis signals in skeletal muscles. This promotes the accumulation of peripheral and intramuscular fat, resulting in improved meat quality. This work adopts a joint analysis method of multi-tissue transcriptome and gut metabolome, providing a successful case for analyzing the mechanisms underlying the formation of various traits.

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

Introduction: Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Methods: Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. Results: We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. The clustering derived from netMUG achieved an adjusted Rand index of 1 with respect to the synthesized true labels. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these subgroups. Discussion: netMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

Gene-environment interactions that influence CVD, lipid traits, obesity, diabetes, and hypertension appear to be able to influence gene therapy

Most mind boggling diseases are accepted to be impacted by both genetic and environmental elements. As of late, there has been a flood in the improvement of different methodologies, concentrate on plans, and measurable and logical techniques to examine gene-environment cooperations (G × Es) in enormous scope studies including human populaces. The many-sided exchange between genetic elements and environmental openings has long charmed the consideration of clinicians and researchers looking to grasp the complicated starting points of diseases. While single variables can add to disease, the blend of genetic variations and environmental openings frequently decides disease risk. The fundamental point of this paper is to talk about the Gene-Environment Associations That Impact CVD, Lipid Characteristics, Obesity, Diabetes, and Hypertension Have all the earmarks of being Ready to Impact Gene Therapy. This survey paper investigates the meaning of gene-environment collaborations (G × E) in disease advancement. The intricacy of genetic and environmental communications in disease causation is explained, underlining the multifactorial idea of many circumstances. The job of gene-environment cooperations in cardiovascular disease, lipid digestion, diabetes, obesity, and hypertension is investigated. This audit fixates on Gene by Environment (G × E) collaborations, investigating their importance in disease etiology.

Development of genome-wide association studies on childhood obesity and its indicators: A scoping review and enrichment analysis

BACKGROUND

The progress of genome-wide association studies (GWAS) in childhood obesity and its indicators is challenging and there are differences in genetic studies in children and adults.

OBJECTIVE

To illustrate the history of the development of GWAS in childhood obesity and its indicators and summarize the GWAS loci.

METHODS

PubMed, Web of Science, Embase and GWAS Catalog databases were systematically searched from 1 January 2005 to 19 October 2022 for literature related to GWAS of childhood BMI, body fatness and obesity. The nearest genes were used as positional genes to perform gene set analyses including the enrichment of pathways, tissues and diseases.

RESULTS

Twenty articles published between 2007 and 2021 were included in this scoping review, which identified 116 SNPs reaching genome-wide significance with childhood BMI (n = 50), body fatness (n = 31) and obesity (n = 35). The study populations were European in 16 studies, non-European in three studies (1 East Asian; 1 American; 1 Mexican) and trans-ancestry in one study. Several enriched pathways, tissues and diseases were identified through enrichment analysis of genes associated with childhood obesity and its indicators.

CONCLUSIONS

The innovations in tools and methods enable GWAS to better explore the genetic characteristics of obesity in children and adolescents. However, the number of GWAS in American, Asian and African populations is limited compared to the European population.

Genetic variants associated with weight loss and metabolic outcomes after bariatric surgery: A systematic review

The extent to which genetic variations contribute to interindividual differences in weight loss and metabolic outcomes after bariatric surgery is unknown. Identifying genetic variants that impact surgery outcomes may contribute to clinical decision making. This review evaluates current evidence addressing the association of genetic variants with weight loss and changes in metabolic parameters after bariatric surgery. A search was conducted using Medline, Embase, Scopus, Web of Science, and Cochrane Library. Fifty-two eligible studies were identified. Single nucleotide polymorphisms (SNPs) at ADIPOQ (rs226729, rs1501299, rs3774261, and rs17300539) showed a positive association with postoperative change in measures of glucose homeostasis and lipid profiles (n = 4), but not with weight loss after surgery (n = 6). SNPs at FTO (rs11075986, rs16952482, rs8050136, rs9939609, rs9930506, and rs16945088) (n = 10) and MC4R (rs11152213, rs476828, rs2229616, rs9947255, rs17773430, rs5282087, and rs17782313) (n = 9) were inconsistently associated with weight loss and metabolic improvement. Four studies examining the UCP2 SNP rs660339 reported associations with postsurgical weight loss. In summary, there is limited evidence supporting a role for specific genetic variants in surgical outcomes after bariatric surgery. Most studies have adopted a candidate gene approach, limiting the scope for discovery, suggesting that the absence of compelling evidence is not evidence of absence.

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

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

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.

Predisposition of the Common MC4R rs17782313 Female Carriers to Elevated Obesity and Interaction with Eating Habits

The global rise in obesity is attributed to genetic predisposition interaction with an obesogenic environment. Melanocortin 4 receptor (MC4R) rs17782313 polymorphism has been linked to common obesity with varying influence across different populations. MC4R is a crucial player in the leptin proopiomelanocortin pathway that regulates weight hemostasis. We aimed to study MC4R rs17782313 and its interaction with eating behaviors on obesity predisposition in the Israeli population. Adults' (n = 5785, >18 y) genotype and anthropometric and demographic data were analyzed using logistic regression models adjusting for age, sex, T1DM, and T2DM. MC4R rs17782313 significantly predisposes to elevated obesity risk under the recessive and additive models (OR = 1.38, 95% CI: 1.1-1.72, p = 0.005 and OR = 1.1, 95% CI: 1.01-1.2, p = 0.03, respectively) adjusted for confounders (age, sex, T1DM, and T2DM). Stratification by sex demonstrated that carrying the common MC4R rs17782313 is significantly associated with an elevated predisposition to obesity under the recessive model among females only (OR = 1.41, 95% CI: 1.09-1.82, p = 0.01), with an average of 0.85 BMI increment compared with wild type and one risk allele carriers. MC4R rs17782313 significantly interacted with several eating behaviors to enhance the risk of obesity. Our findings demonstrate that MC4R rs17782313 homozygous female carriers are significantly predisposed to obesity amplified by eating behaviors.

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.

Targeting the central melanocortin system for the treatment of metabolic disorders

A large body of preclinical and clinical data shows that the central melanocortin system is a promising therapeutic target for treating various metabolic disorders such as obesity and cachexia, as well as anorexia nervosa. Setmelanotide, which functions by engaging the central melanocortin circuitry, was approved by the FDA in 2020 for use in certain forms of syndromic obesity. Furthermore, the FDA approvals in 2019 of two peptide drugs targeting melanocortin receptors for the treatment of generalized hypoactive sexual desire disorder (bremelanotide) and erythropoietic protoporphyria-associated phototoxicity (afamelanotide) demonstrate the safety of this class of peptides. These approvals have also renewed excitement in the development of therapeutics targeting the melanocortin system. Here, we review the anatomy and function of the melanocortin system, discuss progress and challenges in developing melanocortin receptor-based therapeutics, and outline potential metabolic and behavioural disorders that could be addressed using pharmacological agents targeting these receptors.

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.

The Melanocortin System in Inflammatory Bowel Diseases: Insights into Its Mechanisms and Therapeutic Potentials

The melanocortin system is a complex set of molecular mediators and receptors involved in many physiological and homeostatic processes. These include the regulation of melanogenesis, steroidogenesis, neuromodulation and the modulation of inflammatory processes. In the latter context, the system has assumed importance in conditions of chronic digestive inflammation, such as inflammatory bowel diseases (IBD), in which numerous experiences have been accumulated in mouse models of colitis. Indeed, information on how such a system can counteract colitis inflammation and intervene in the complex cytokine imbalance in the intestinal microenvironment affected by chronic inflammatory damage has emerged. This review summarises the evidence acquired so far and highlights that molecules interfering with the melanocortin system could represent new drugs for treating IBD.

Neurochemical Basis of Inter-Organ Crosstalk in Health and Obesity: Focus on the Hypothalamus and the Brainstem

Precise neural regulation is required for maintenance of energy homeostasis. Essential to this are the hypothalamic and brainstem nuclei which are located adjacent and supra-adjacent to the circumventricular organs. They comprise multiple distinct neuronal populations which receive inputs not only from other brain regions, but also from circulating signals such as hormones, nutrients, metabolites and postprandial signals. Hence, they are ideally placed to exert a multi-tier control over metabolism. The neuronal sub-populations present in these key metabolically relevant nuclei regulate various facets of energy balance which includes appetite/satiety control, substrate utilization by peripheral organs and glucose homeostasis. In situations of heightened energy demand or excess, they maintain energy homeostasis by restoring the balance between energy intake and expenditure. While research on the metabolic role of the central nervous system has progressed rapidly, the neural circuitry and molecular mechanisms involved in regulating distinct metabolic functions have only gained traction in the last few decades. The focus of this review is to provide an updated summary of the mechanisms by which the various neuronal subpopulations, mainly located in the hypothalamus and the brainstem, regulate key metabolic functions.

Plant-Derived Nutraceuticals Involved in Body Weight Control by Modulating Gene Expression

Obesity is the most prevalent health problem in the Western world, with pathological body weight gain associated with numerous co-morbidities that can be the main cause of death. There are several factors that can contribute to the development of obesity, such as diet, sedentary lifestyle, and genetic make-up. Genetic predispositions play an important role in obesity, but genetic variations alone cannot fully explain the explosion of obesity, which is why studies have turned to epigenetics. The latest scientific evidence suggests that both genetics and environmental factors contribute to the rise in obesity. Certain variables, such as diet and exercise, have the ability to alter gene expression without affecting the DNA sequence, a phenomenon known as epigenetics. Epigenetic changes are reversible, and reversibility makes these changes attractive targets for therapeutic interventions. While anti-obesity drugs have been proposed to this end in recent decades, their numerous side effects make them not very attractive. On the other hand, the use of nutraceuticals for weight loss is increasing, and studies have shown that some of these products, such as resveratrol, curcumin, epigallocatechin-3-gallate, ginger, capsaicin, and caffeine, can alter gene expression, restoring the normal epigenetic profile and aiding weight loss.

Insights from rare variants into the genetic architecture and biology of youth-onset type 2 diabetes

Youth-onset type 2 diabetes (T2D) is a growing public health concern. Its genetic basis and relationship to other forms of diabetes are largely unknown. To gain insight into the genetic architecture and biology of youth-onset T2D, we analyzed exome sequences of 3,005 youth-onset T2D cases and 9,777 ancestry matched adult controls. We identified (a) monogenic diabetes variants in 2.1% of individuals; (b) two exome-wide significant (P < 4.3×10-7) common coding variant associations (in WFS1 and SLC30A8); (c) three exome-wide significant (P < 2.5×10-6) rare variant gene-level associations (HNF1A, MC4R, ATX2NL); and (d) rare variant association enrichments within 25 gene sets broadly related to obesity, monogenic diabetes, and β-cell function. Many association signals were shared between youth-onset and adult-onset T2D but had larger effects for youth-onset T2D risk (1.18-fold increase for common variants and 2.86-fold increase for rare variants). Both common and rare variant associations contributed more to youth-onset T2D liability variance than they did to adult-onset T2D, but the relative increase was larger for rare variant associations (5.0-fold) than for common variant associations (3.4-fold). Youth-onset T2D cases showed phenotypic differences depending on whether their genetic risk was driven by common variants (primarily related to insulin resistance) or rare variants (primarily related to β-cell dysfunction). These data paint a picture of youth-onset T2D as a disease genetically similar to both monogenic diabetes and adult-onset T2D, in which genetic heterogeneity might be used to sub-classify patients for different treatment strategies.

netMUG: a novel network-guided multi-view clustering workflow for dissecting genetic and facial heterogeneity

Multi-view data offer advantages over single-view data for characterizing individuals, which is crucial in precision medicine toward personalized prevention, diagnosis, or treatment follow-up. Here, we develop a network-guided multi-view clustering framework named netMUG to identify actionable subgroups of individuals. This pipeline first adopts sparse multiple canonical correlation analysis to select multi-view features possibly informed by extraneous data, which are then used to construct individual-specific networks (ISNs). Finally, the individual subtypes are automatically derived by hierarchical clustering on these network representations. We applied netMUG to a dataset containing genomic data and facial images to obtain BMI-informed multi-view strata and showed how it could be used for a refined obesity characterization. Benchmark analysis of netMUG on synthetic data with known strata of individuals indicated its superior performance compared with both baseline and benchmark methods for multi-view clustering. In addition, the real-data analysis revealed subgroups strongly linked to BMI and genetic and facial determinants of these classes. NetMUG provides a powerful strategy, exploiting individual-specific networks to identify meaningful and actionable strata. Moreover, the implementation is easy to generalize to accommodate heterogeneous data sources or highlight data structures.

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.

Genetic association of the rs17782313 polymorphism with antipsychotic-induced weight gain

RATIONALE

Weight gain is a frequent side effect of treatment with SGAs (second-generation antipsychotics) and a leading cause for nonadherence. Several candidate genes have been identified that could influence the amount of AIWG (antipsychotic-induced weight gain). The polymorphism rs17782313 near the MC4R (human melanocortin 4 receptor gene) was strongly associated with obesity in a large scale GWAS (genome wide association study), yet previous studies investigating its impact on AIWG did not lead to a definite conclusion regarding its effect. In particular, they were all relatively short and had a naturalistic design.

OBJECTIVE

We therefore examined the influence of the rs17782313 polymorphism on SGA-related weight gain.

METHODS

Participants of a multicenter randomized, controlled, double-blind study comparing two treatment strategies in individuals with schizophrenia or schizoaffective disorder were genotyped using a rapid-cycle polymerase chain reaction. Up to 252 individuals completed the first 2 weeks (phase I), 212 the entire 8 weeks (hence 'completers'). Patients received either amisulpride or olanzapine or both consecutively. Thirty-seven had their first episode. Weight gain occurring in different genotypes was statistically compared and confounding factors were adjusted by stepwise multiple linear regression. A correction for multiple testing was included.

RESULTS

Within 212 'completers', carriers of the C allele had a higher absolute weight gain than those homozygous for the T allele (2.6 kg vs. 1.2 kg), though this observation was not significant (P = 0.063). In the amisulpride subpopulation, this association appeared stronger and reached significance (2.5 kg vs. 0.7 kg, P = 0.043), though failed to remain significant after correction for multiple testing. A stepwise multiple linear regression showed a significant association in both the whole study population (P < 0.001) and the amisulpride subpopulation (P < 0.001).

CONCLUSION

Our results indicate that the rs17782313 polymorphism might influence antipsychotic-induced weight gain and therefore confirm some of the earlier conclusions.

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.

Considerations of the Genetic Background of Obesity among Patients with Psoriasis

Psoriasis comorbidities may emerge from pleiotropic mechanisms, including common proinflammatory pathways, cellular mediators or genetic predisposition. Obesity is considered to be an independent risk factor of psoriasis, which may influence the severity of the disease and its early onset, decrease patients’ quality of life, alter response to psoriasis therapies and affect morbidity by reduced life expectancy due to cardiovascular events. Although novel approaches, including genetic techniques, have provided a wide range of new research, there are still scarce studies elaborating on the common genetic background of psoriasis and obesity. The aim of this study was to present and evaluate a possible common genetic background of psoriasis and concomitant increased body mass based on the review of the available literature.

MRAP2 regulates energy homeostasis by promoting primary cilia localization of MC4R

The G protein-coupled receptor melanocortin-4 receptor (MC4R) and its associated protein melanocortin receptor-associated protein 2 (MRAP2) are essential for the regulation of food intake and body weight in humans. MC4R localizes and functions at the neuronal primary cilium, a microtubule-based organelle that senses and relays extracellular signals. Here, we demonstrate that MRAP2 is critical for the weight-regulating function of MC4R neurons and the ciliary localization of MC4R. More generally, our study also reveals that GPCR localization to primary cilia can require specific accessory proteins that may not be present in heterologous cell culture systems. Our findings further demonstrate that targeting of MC4R to neuronal primary cilia is essential for the control of long-term energy homeostasis and suggest that genetic disruption of MC4R ciliary localization may frequently underlie inherited forms of obesity.

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

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

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

BACKGROUND

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

OBJECTIVE

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

RESULTS

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

CONCLUSION

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

The Role of Dietary Glycemic Index and Glycemic Load in Mediating Genetic Susceptibility via MC4R s17782313 Genotypes to Affect Cardiometabolic Risk Factors among Apparently Healthy Obese Individuals

Background

The association of genetic and dietary factors with occurrence and progression of chronic diseases such as metabolic syndrome (MetS) has long been addressed but there is a lack of evidence for complex interrelationships, including direct and indirect effects of these variables. Hence, this study is aimed at evaluating the mediating role of glycemic indices in the association of melanocortin-4 receptor (MC4R) rs17782313 polymorphism, sociodemographic, and psychological factors with the risk of MetS in obese adults using structural equation modeling.

Methods

We performed a cross-sectional analysis of data from 287 apparently healthy adults. Dietary glycemic index (GI) and glycemic load (GL) were calculated from a validated 147-item food frequency questionnaire (FFQ). MC4R s17782313 genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Structural equation modeling was used to explore direct and indirect effects of genetic and nongenetic factors on MetS.

Results

MC4R gene variant was directly associated with the risk of MetS (B = 0.010; P = 0.023). On the other hand, this variant was found to be indirectly and positively associated with LDL-C (B = 6.589; P = 0.042) through mediatory effects of GI and GL. Moreover, GI and GL also mediated indirect positive effects of sex and age on LDL-C (B = 3.970; P ≤ 0.01; B = 0.878; P ≤ 0.01, respectively) and HDL (B = 2.203; P ≤ 0.01; B = 0.129; P ≤ 0.01, respectively). MC4R rs17782313 polymorphism had positive effects on GI (B = 1.577; P ≤ 0.01) and GL (B = 1.235; P ≤ 0.01).

Conclusion

Our data may state a hypothesis of the mediating effect of quantity and quality of carbohydrates consumed in relationship between genetic susceptibility to obesity and cardiometabolic risk factors. Further analyses should be carried out in high-quality cohort studies in order to confirm the findings.

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

Background & aims

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

Methods

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

Results

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

Conclusion

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

The Legacy of Parental Obesity: Mechanisms of Non-Genetic Transmission and Reversibility

While a dramatic increase in obesity and related comorbidities is being witnessed, the underlying mechanisms of their spread remain unresolved. Epigenetic and other non-genetic mechanisms tend to be prominent candidates involved in the establishment and transmission of obesity and associated metabolic disorders to offspring. Here, we review recent findings addressing those candidates, in the context of maternal and paternal influences, and discuss the effectiveness of preventive measures.

Highlighting the Role of Obesity and Insulin Resistance in Type 1 Diabetes and Its Associated Cardiometabolic Complications

PURPOSE OF REVIEW

This narrative review appraises research data on the potentially harmful effect of obesity and insulin resistance (IR) co-existence with type 1 diabetes mellitus (T1DM)-related cardiovascular (CVD) complications and evaluates possible therapeutic options.

RECENT FINDINGS

Obesity and IR have increasingly been emerging in patients with T1DM. Genetic, epigenetic factors, and subcutaneous insulin administration are implicated in the pathogenesis of this coexistence. Accumulating evidence implies that the concomitant presence of obesity and IR is an independent predictor of worse CVD outcomes. The prevalence of obesity and IR has increased in patients with T1DM. This increase can be partly attributed to general population trends but, additionally, to iatrogenic weight gain caused by insulin treatment. This association might be the missing link explaining the excess CVD burden observed in patients with T1DM despite optimal glycemic control. Data on newer agents for type 2 diabetes mellitus (T2DM) treatment are unraveling novel ways to challenge this aggravating coexistence.

Distinct causal effects of body fat distribution on cardiometabolic traits among children: Findings from the BCAMS study

BACKGROUND AND AIMS

Observational studies reveal that different body fat measures are associated with cardiometabolic disease with different effects. However, causality is not reflected by such observations. To explore and compare the causal relationships of general obesity (measured by body mass index (BMI)), adipose obesity (measured by fat mass percentage (FMP)) and central obesity (measured by waist-to-height ratio (WHtR)) with cardiometabolic traits among children.

METHODS AND RESULTS

We conducted one sample Mendelian randomization (MR) analysis in 3266 children from Beijing Children and Adolescents Metabolic Syndrome Study. Genetic instruments based on 28 SNPs were performed to explore and compare the causal associations of genetically BMI, FMP and WHtR with cardiometabolic traits. The genetic instruments were robustly correlated with observed BMI, FMP and WHtR. Each genetically 1-SD increment in BMI, FMP and WHtR were causally associated with increment in systolic blood pressure (SBP), diastolic blood pressure (DBP), log-transformed fasting plasma glucose (FPG), log-transformed HOMA-β, and decrease in log-transformed high-density lipoprotein cholesterol (HDL), respectively (all P < 0.05 after Bonferroni correction). The receiver operating characteristic curve indicated that BMI and FMP showed stronger effects on SBP, DBP, HOMA-β and HDL than WHtR (all P < 0.05). We also observed causal associations of BMI and FMP with log-transformed fasting insulin and HOMA-IR.

CONCLUSIONS

The MR analysis based on population-based cohort indicated a causal relationship of adiposity and body fat distribution with cardiometabolic traits. When compared with central obesity, general obesity and adipose obesity might own stronger effects on blood pressure and blood lipids among children.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Mutations in melanocortin-4 receptor: From fish to men

Melanocortin-4 receptor (MC4R), expressed abundantly in the hypothalamus, is a critical regulator of energy homeostasis, including both food intake and energy expenditure. Shortly after the publication in 1997 of the Mc4r knockout phenotypes in mice, including increased food intake and severe obesity, the first mutations in MC4R were reported in humans in 1998. Studies in the subsequent two decades have established MC4R mutation as the most common monogenic form of obesity, especially in early-onset severe obesity. Studies in animals, from fish to mammals, have established the conserved physiological roles of MC4R in all vertebrates in regulating energy balance. Drug targeting MC4R has been recently approved for treating morbid genetic obesity. How the MC4R can be exploited for animal production is highly worthy of active investigation.