Predicting Polygenic Obesity Using Genetic Information

Impact of walnut consumption on glycemic control and anthropometric indices: a systematic review and meta-analysis of randomized controlled trials

Objectives

Previous studies have led to conflicting results regarding the effect of walnut consumption on glycemic control, and anthropometric indices. This study aimed to evaluate the efficacy of walnut consumption on serum levels of fasting blood sugar (FBS), fasting insulin, hemoglobin A1C (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR), weight and body mass index (BMI) through a systematic review and meta-analysis of randomized controlled trials (RCTs).

Methods

PubMed, Scopus, Web of Science, and the Cochrane databases were searched up to February 2023. Weighted mean difference (WMD) was analyzed using random effects models to assess the overall effect.

Results

A total of thirty-two RCTs were included in the systematic review and meta-analysis. Walnut supplementation was found to significantly reduce HOMA-IR (WMD = -0.29; 95% CI: -0.57, -0.01, P = 0.04), and body weight (WMD = -0.14 kg; 95% CI: -0.24, -0.04; P = 0.008). However, the meta-analysis showed that walnut supplementation did not have a significant effect on FBS (WMD = 0.62 mg/dL; 95% CI: -0.66, 1.91; P = 0.34), insulin levels (WMD = 1.27 mIU/ml; 95% CI: -0.59, 3.14; P = 0.18), HbA1C (WMD = 0.00%; 95% CI: -0.09, 0.10; P = 0.95), and BMI (WMD = -0.10 kg/m2; 95% CI: -0.40, 0.20; P = 0.50).

Conclusion

In conclusion, this study found a significant reduction in HOMA-IR levels and body weight with walnut supplementation, while other glycemic markers, and obesity-related indices did not change significantly. Future well-designed trials are needed to confirm these results.

Integrating Genetic Insights, Technological Advancements, Screening, and Personalized Pharmacological Interventions in Childhood Obesity

Childhood obesity is a significant global health challenge with rising prevalence over the past 50 years, affecting both immediate and long-term health outcomes. The increase in prevalence from 0.7% to 5.6% in girls and 0.9% to 7.8% in boys highlights the urgency of addressing this epidemic. By 2025, it is estimated that 206 million children and adolescents aged 5-19 years will be living with obesity. This review explores the complex interplay of genomics and genetics in pediatric obesity, transitioning from monogenic and polygenic obesity to epigenetics, and incorporating advancements in omics technologies. The evolutionary purpose of adiposity, systemic evaluation of hyperphagia, and the role of various genetic factors are discussed. Technological advancements in genotyping offer new insights and interventions. The integration of genetic screening into clinical practice for early identification and personalized treatment strategies is emphasized.

Experimental approaches for induction of diabetes mellitus and assessment of antidiabetic activity: An in vitro and in vivo methodological review

BACKGROUND

Diabetes mellitus poses a global health challenge, driving the need for innovative therapeutic solutions. Experimental methods play a crucial role in evaluating the efficacy of potential antidiabetic drugs, both in vitro and in vivo. Yet concerns about reproducibility persist, necessitating comprehensive reviews.

OBJECTIVES

This review aims to outline experimental approaches for inducing diabetes and evaluating antidiabetic activity, synthesizing data from authoritative sources and academic literature.

METHODS

We conducted a systematic search of prominent databases, including PubMed, ScienceDirect, and Scopus, to identify relevant articles spanning from 1943 to the present. A total of 132 articles were selected for inclusion in this review, focusing on in vitro and in vivo experimental validations of antidiabetic treatments.

RESULTS

Our review highlights the diverse array of experimental methods employed for inducing diabetes mellitus and evaluating antidiabetic interventions. From cell culture assays to animal models, researchers have employed various techniques to study the effectiveness of novel therapeutic agents.

CONCLUSION

This review provides a comprehensive guide to experimental approaches for assessing antidiabetic activity. By synthesizing data from a range of sources, we offer valuable insights into the current methodologies used in diabetes research. Standardizing protocols and enhancing reproducibility are critical for advancing effective antidiabetic treatments.

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

Sequencing methods, functional characterization, prevalence, and penetrance of rare coding mutations in panels of monogenic obesity genes from the leptin-melanocortin pathway: A systematic review

The recent development of next-generation sequencing (NGS) technologies has led to an increase of mutation screening reports of monogenic obesity genes in diverse experimental designs. However, no study to date has summarized their findings. Two reviewers independently conducted a systematic review of MEDLINE, Embase, and Web of Science Core Collection databases from inception to September 2022 to identify monogenic non-syndromic obesity gene screening studies. Of 1051 identified references, 31 were eligible after title and abstract screening and 28 after full-text reading and risk of bias and quality assessment. Most studies (82%) used NGS methods. The number of genes screened varied from 2 to 12 genes from the leptin-melanocortin pathway. While all the included studies used in silico tools to assess the functional status of mutations, only 2 performed in vitro tests. The prevalence of carriers of pathogenic/likely pathogenic monogenic mutations is 13.24% on average (heterozygous: 12.31%; homozygous/heterozygous composite: 0.93%). As no study reported the penetrance of pathogenic mutations on obesity, we estimated that homozygous carriers exhibited a complete penetrance (100%) and heterozygous carriers a variable penetrance (3-100%). The review provides an exhaustive description of sequencing methods, functional characterization, prevalence, and penetrance of rare coding mutations in monogenic non-syndromic obesity genes.

Deciphering the complex interplay of obesity, epithelial barrier dysfunction, and tight junction remodeling: Unraveling potential therapeutic avenues

Obesity stands as a formidable global health challenge, predisposing individuals to a plethora of chronic illnesses such as cardiovascular disease, diabetes, and cancer. A confluence of genetic polymorphisms, suboptimal dietary choices, and sedentary lifestyles significantly contribute to the elevated incidence of obesity. This multifaceted health issue profoundly disrupts homeostatic equilibrium at both organismal and cellular levels, with marked alterations in gut permeability as a salient consequence. The intricate mechanisms underlying these alterations have yet to be fully elucidated. Still, evidence suggests that heightened inflammatory cytokine levels and the remodeling of tight junction (TJ) proteins, particularly claudins, play a pivotal role in the manifestation of epithelial barrier dysfunction in obesity. Strategic targeting of proteins implicated in these pathways and metabolites such as short-chain fatty acids presents a promising intervention for restoring barrier functionality among individuals with obesity. Nonetheless, recognizing the heterogeneity among affected individuals is paramount; personalized medical interventions or dietary regimens tailored to specific genetic backgrounds and allergy profiles may prove indispensable. This comprehensive review delves into the nexus of obesity, tight junction remodeling, and barrier dysfunction, offering a critical appraisal of potential therapeutic interventions.

Molecular Mechanisms behind Obesity and Their Potential Exploitation in Current and Future Therapy

Obesity is a chronic disease caused primarily by the imbalance between the amount of calories supplied to the body and energy expenditure. Not only does it deteriorate the quality of life, but most importantly it increases the risk of cardiovascular diseases and the development of type 2 diabetes mellitus, leading to reduced life expectancy. In this review, we would like to present the molecular pathomechanisms underlying obesity, which constitute the target points for the action of anti-obesity medications. These include the central nervous system, brain-gut-microbiome axis, gastrointestinal motility, and energy expenditure. A significant part of this article is dedicated to incretin-based drugs such as GLP-1 receptor agonists (e.g., liraglutide and semaglutide), as well as the brand new dual GLP-1 and GIP receptor agonist tirzepatide, all of which have become "block-buster" drugs due to their effectiveness in reducing body weight and beneficial effects on the patient's metabolic profile. Finally, this review article highlights newly designed molecules with the potential for future obesity management that are the subject of ongoing clinical trials.

Obesity risk in young adults from the Jerusalem Perinatal Study (JPS): the contribution of polygenic risk and early life exposure

BACKGROUND/OBJECTIVES

The effects of early life exposures on offspring life-course health are well established. This study assessed whether adding early socio-demographic and perinatal variables to a model based on polygenic risk score (PRS) improves prediction of obesity risk.

METHODS

We used the Jerusalem Perinatal study (JPS) with data at birth and body mass index (BMI) and waist circumference (WC) measured at age 32. The PRS was constructed using over 2.1M common SNPs identified in genome-wide association study (GWAS) for BMI. Linear and logistic models were applied in a stepwise approach. We first examined the associations between genetic variables and obesity-related phenotypes (e.g., BMI and WC). Secondly, socio-demographic variables were added and finally perinatal exposures, such as maternal pre-pregnancy BMI (mppBMI) and gestational weight gain (GWG) were added to the model. Improvement in prediction of each step was assessed using measures of model discrimination (area under the curve, AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

One standard deviation (SD) change in PRS was associated with a significant increase in BMI (β = 1.40) and WC (β = 2.45). These associations were slightly attenuated (13.7-14.2%) with the addition of early life exposures to the model. Also, higher mppBMI was associated with increased offspring BMI (β = 0.39) and WC (β = 0.79) (p < 0.001). For obesity (BMI ≥ 30) prediction, the addition of early socio-demographic and perinatal exposures to the PRS model significantly increased AUC from 0.69 to 0.73. At an obesity risk threshold of 15%, the addition of early socio-demographic and perinatal exposures to the PRS model provided a significant improvement in reclassification of obesity (NRI, 0.147; 95% CI 0.068-0.225).

CONCLUSIONS

Inclusion of early life exposures, such as mppBMI and maternal smoking, to a model based on PRS improves obesity risk prediction in an Israeli population-sample.

Adiposity, type 2 diabetes and atherosclerotic cardiovascular disease risk: Use and abuse of the body mass index

The worldwide prevalence of individuals with an elevated body weight has increased steadily over the past five decades. Billions of research dollars have been invested to improve our understanding of the causes and consequences of having an elevated body weight. All this knowledge has, however, failed to influence populational body weight trajectories of most countries around the world. Research on the definition of "obesity" has also evolved. Body mass index (BMI), the most commonly used tool to make its diagnosis, has major limitations. In this review article, we will highlight evidence from observational studies, genetic association studies and randomized clinical trials that have shown the remarkable inter-individual differences in the way humans store energy as body fat. Increasing evidence also suggests that, as opposed to weight inclusive, lifestyle-based approaches, weight-centric approaches advising people to simply eat less and move more are not sustainable for most people for long-term weight loss and maintenance. It is time to recognize that this outdated approach may have produced more harm than good. On the basis of pathophysiological, genetic and clinical evidence presented in this review, we propose that it may be time to shift away from the traditional clinical approach, which is BMI-centric. Rather, emphasis should be placed on actionable lifestyle-related risk factors aiming at improving overall diet quality and increasing physical activity level in the general population.

The melanocortin-4 receptor pathway and the emergence of precision medicine in obesity management

Over the past few decades, there has been a global surge in the prevalence of obesity, rendering it a globally recognized epidemic. Contrary to simply being a medical condition, obesity is an intricate disease with a multifactorial aetiology. Understanding the precise cause of obesity remains a challenge; nevertheless, there seems to be a complex interplay among biological, psychosocial and behavioural factors. Studies on the genetic factors of obesity have revealed several pathways in the brain that play a crucial role in food intake regulation. The best characterized pathway, thus far, is the leptin-melanocortin pathway, from which disruptions are responsible for the majority of monogenic obesity disorders. The effectiveness of conservative lifestyle interventions in addressing monogenic obesity has been limited. Therefore, it is crucial to complement the management strategy with pharmacological and surgical options. Emphasis has been placed on developing drugs aimed at replacing the absent signals, with the goal of restoring the pathway. In both monogenic and polygenic forms of obesity, outcomes differ across various interventions, likely due to the multifaceted nature of the disease. This underscores the need to explore alternative therapeutic strategies that can mitigate this heterogeneity. Precision medicine can be regarded as a powerful tool that can address this concern, as it values the understanding of the underlying abnormality triggering the disease and provides a tailored treatment accordingly. This would assist in optimizing outcomes of the current therapeutic approaches and even aid in the development of novel treatments capable of more effectively managing the global obesity epidemic.

Neurodevelopmental Programming of Adiposity: Contributions to Obesity Risk

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

Unraveling Adipose Tissue Dysfunction: Molecular Mechanisms, Novel Biomarkers, and Therapeutic Targets for Liver Fat Deposition

Adipose tissue (AT), once considered a mere fat storage organ, is now recognized as a dynamic and complex entity crucial for regulating human physiology, including metabolic processes, energy balance, and immune responses. It comprises mainly two types: white adipose tissue (WAT) for energy storage and brown adipose tissue (BAT) for thermogenesis, with beige adipocytes demonstrating the plasticity of these cells. WAT, beyond lipid storage, is involved in various metabolic activities, notably lipogenesis and lipolysis, critical for maintaining energy homeostasis. It also functions as an endocrine organ, secreting adipokines that influence metabolic, inflammatory, and immune processes. However, dysfunction in WAT, especially related to obesity, leads to metabolic disturbances, including the inability to properly store excess lipids, resulting in ectopic fat deposition in organs like the liver, contributing to non-alcoholic fatty liver disease (NAFLD). This narrative review delves into the multifaceted roles of WAT, its composition, metabolic functions, and the pathophysiology of WAT dysfunction. It also explores diagnostic approaches for adipose-related disorders, emphasizing the importance of accurately assessing AT distribution and understanding the complex relationships between fat compartments and metabolic health. Furthermore, it discusses various therapeutic strategies, including innovative therapeutics like adipose-derived mesenchymal stem cells (ADMSCs)-based treatments and gene therapy, highlighting the potential of precision medicine in targeting obesity and its associated complications.

Rare predicted loss of function alleles in Bassoon (BSN) are associated with obesity

Bassoon (BSN) is a component of a hetero-dimeric presynaptic cytomatrix protein that orchestrates neurotransmitter release with Piccolo (PCLO) from glutamatergic neurons throughout the brain. Heterozygous missense variants in BSN have previously been associated with neurodegenerative disorders in humans. We performed an exome-wide association analysis of ultra-rare variants in about 140,000 unrelated individuals from the UK Biobank to search for new genes associated with obesity. We found that rare heterozygous predicted loss of function (pLoF) variants in BSN are associated with higher BMI with p-value of 3.6e-12 in the UK biobank cohort. Additionally, we identified two individuals (one of whom has a de novo variant) with a heterozygous pLoF variant in a cohort of early onset or extreme obesity and report the clinical histories of these individuals with non-syndromic obesity with no history of neurobehavioral or cognitive disability. The BMI association was replicated in the All of Us whole genome sequencing data. Heterozygous pLoF BSN variants constitute a new etiology for obesity.

Efficacy and Safety of Setmelanotide, a Melanocortin-4 Receptor Agonist, for Obese Patients: A Systematic Review and Meta-Analysis

BACKGROUND

A malfunction in the melanocortin-4 receptor (MC4R) is associated with obesity in rare genetic syndromes; setmelanotide is a new drug that activates this receptor and is being used to treat severe obesity. This meta-analysis evaluated the efficacy and safety of setmelanotide for weight loss in severe obesity linked to human MC4R deficiency.

METHODS

We searched PubMed, Embase, and Cochrane for randomized and nonrandomized clinical trials using setmelanotide. We considered a p-value ≤ 0.05 statistically significant.

RESULTS

We included 376 patients, of whom 328 (87.2%) received setmelanotide for a mean follow-up of 52 weeks. The mean age was 32.8 (14.67) years. Weight loss was significant (MD -3.52; 95% CI -3.98, -3.05; p = 0.01; I2 = 92%), with an average proportion of -6.91% weight loss during treatment. Changes in BMI showed an MD of -10.55 kg/m2 in patients > 18 years and -0.61 kg/m2 in patients < 18 years (BMI score). However, the drug was associated with a higher risk of skin hyperpigmentation (OR 0.69; 95% CI 0.55, 0.80; p = 0.08).

CONCLUSIONS

Our results support the use of setmelanotide in treating severe obesity.

Individualised prescription of medications for treatment of obesity in adults

Obesity continues to increase in prevalence globally, driven by changes in environmental factors which have accelerated the development of obesity in individuals with an underlying predisposition to weight gain. The adverse health effects and increased risk for chronic disease associated with obesity are ameliorated by weight loss, with greater benefits from larger amounts of weight reduction. Obesity is a heterogeneous condition, with the drivers, phenotype and complications differing substantially between individuals. This raises the question of whether treatments for obesity, specifically pharmacotherapy, can be targeted based on individual characteristics. This review examines the rationale and the clinical data evaluating this strategy in adults. Individualised prescribing of obesity medication has been successful in rare cases of monogenic obesity where medications have been developed to target dysfunctions in leptin/melanocortin signalling pathways but has been unsuccessful in polygenic obesity due to a lack of understanding of how the gene variants associated with body mass index affect phenotype. At present, the only factor consistently associated with longer-term efficacy of obesity pharmacotherapy is early weight loss outcome, which cannot inform choice of therapy at the time of medication initiation. The concept of matching a therapy for obesity to the characteristics of the individual is appealing but as yet unproven in randomised clinical trials. With increasing technology allowing deeper phenotyping of individuals, increased sophistication in the analysis of big data and the emergence of new treatments, it is possible that precision medicine for obesity will eventuate. For now, a personalised approach that takes into account the person's context, preferences, comorbidities and contraindications is recommended.

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

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

The DECON pilot project investigates predictive markers for successful bariatric surgery

Obesity is a chronic, multifactorial disease which is linked to a number of adverse endocrinological and metabolic conditions. Currently, bariatric surgery is one of the most effective treatments for individuals diagnosed with severe obesity. However, the current indications for bariatric surgery are based on inadequate metrics (i.e., BMI) which do not account for the complexity of the disease, nor the heterogeneity among the patient population. Moreover, there is a lack of understanding with respect to the biological underpinnings that influence successful and sustained weight loss post-bariatric surgery. Studies have implicated age and pre-surgery body weight as two factors that are associated with favorable patient outcomes. Still, there is an urgent medical need to identify other potential factors that could improve the specificity of candidate selection and better inform the treatment plan of patients with obesity. In this report, we present and describe the cohort of the DECON pilot project, a multicenter study which aims to identify predictive biomarkers of successful weight loss after bariatric surgery.

Genetics: A Starting Point for the Prevention and the Treatment of Obesity

Obesity is a common, serious, and costly disease. More than 1 billion people worldwide are obese-650 million adults, 340 million adolescents, and 39 million children. The WHO estimates that, by 2025, approximately 167 million people-adults and children-will become less healthy because they are overweight or obese. Obesity-related conditions include heart disease, stroke, type 2 diabetes, and certain types of cancer. These are among the leading causes of preventable, premature death. The estimated annual medical cost of obesity in the United States was nearly $173 billion in 2019 dollars. Obesity is considered the result of a complex interaction between genes and the environment. Both genes and the environment change in different populations. In fact, the prevalence changes as the result of eating habits, lifestyle, and expression of genes coding for factors involved in the regulation of body weight, food intake, and satiety. Expression of these genes involves different epigenetic processes, such as DNA methylation, histone modification, or non-coding micro-RNA synthesis, as well as variations in the gene sequence, which results in functional alterations. Evolutionary and non-evolutionary (i.e., genetic drift, migration, and founder's effect) factors have shaped the genetic predisposition or protection from obesity in modern human populations. Understanding and knowing the pathogenesis of obesity will lead to prevention and treatment strategies not only for obesity, but also for other related diseases.

Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study

Background

Evidence indicates that the adverse health effects of obesity differ between genetically and environmentally influenced obesity. We examined differences in the association between obesity and cardiovascular disease (CVD) between individuals with a genetically predicted low, medium, or high body mass index (BMI).

Methods

We used cohort data from Swedish twins born before 1959 who had BMI measured between the ages of 40-64 years (midlife) or at the age of 65 years or later (late-life), or both, and prospective CVD information from nationwide register linkage through 2016. A polygenic score for BMI (PGSBMI) was used to define genetically predicted BMI. Individuals missing BMI or covariate data, or diagnosed with CVD at first BMI measure, were excluded, leaving an analysis sample of 17,988 individuals. We applied Cox proportional hazard models to examine the association between BMI category and incident CVD, stratified by the PGSBMI. Co-twin control models were applied to adjust for genetic influences not captured by the PGSBMI.

Findings

Between 1984 and 2010, the 17,988 participants were enrolled in sub-studies of the Swedish Twin Registry. Midlife obesity was associated with a higher risk of CVD across all PGSBMI categories, but the association was stronger with genetically predicted lower BMI (hazard ratio from 1.55 to 2.08 for those with high and low PGSBMI, respectively). Within monozygotic twin pairs, the association did not differ by genetically predicted BMI, indicating genetic confounding not captured by the PGSBMI. Results were similar when obesity was measured in late-life, but suffered from low power.

Interpretation

Obesity was associated with CVD regardless of PGSBMI category, but obesity influenced by genetic predisposition (genetically predicted high BMI) was less harmful than obesity influenced by environmental factors (obesity despite genetically predicted low BMI). However, additional genetic factors, not captured by the PGSBMI, still influence the associations.

Funding

The Strategic Research Program in Epidemiology at Karolinska Institutet; Loo and Hans Osterman's Foundation; Foundation for Geriatric Diseases at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare; the Swedish Research Council; and the National Institutes of Health.

Gene-environment interaction explains a part of missing heritability in human body mass index

Gene-environment (G×E) interaction could partially explain missing heritability in traits; however, the magnitudes of G×E interaction effects remain unclear. Here, we estimate the heritability of G×E interaction for body mass index (BMI) by subjecting genome-wide interaction study data of 331,282 participants in the UK Biobank to linkage disequilibrium score regression (LDSC) and linkage disequilibrium adjusted kinships-software for estimating SNP heritability from summary statistics (LDAK-SumHer) analyses. Among 14 obesity-related lifestyle factors, MET score, pack years of smoking, and alcohol intake frequency significantly interact with genetic factors in both analyses, accounting for the partial variance of BMI. The G×E interaction heritability (%) and standard error of these factors by LDSC and LDAK-SumHer are as follows: MET score, 0.45% (0.12) and 0.65% (0.24); pack years of smoking, 0.52% (0.13) and 0.93% (0.26); and alcohol intake frequency, 0.32% (0.10) and 0.80% (0.17), respectively. Moreover, these three factors are partially validated for their interactions with genetic factors in other obesity-related traits, including waist circumference, hip circumference, waist-to-hip ratio adjusted with BMI, and body fat percentage. Our results suggest that G×E interaction may partly explain the missing heritability in BMI, and two G×E interaction loci identified could help in understanding the genetic architecture of obesity.

The effect of retirement on obesity in women: Evidence from China

Introduction

Retirement has been shown to impact individual health as an important life course, and we examined the impact of retirement on the prevalence of obesity in women based on a female perspective.

Methods

We use data from the five waves of the China Family Panel Study (CFPS) data from 2010 to 2018, with the body mass index (BMI) as the obesity measure. Fuzzy regression discontinuity design (FRDD) is used to overcome the endogeneity of retirement behavior and obesity.

Results

After retirement, the obesity rate among women increased 23.8%-27.4% (p < 0.05). The mechanism is that the activity consumption has not changed significantly, but the energy intake has increased significantly. In addition, we found that the effect of retirement on female obesity was strong heterogeneity.

Conclusions

The study found that retirement will increase the probability of obesity in women.

Predicted loss of function alleles in Bassoon (BSN) are associated with obesity

Bassoon ( BSN ) is a component of a hetero-dimeric presynaptic cytomatrix protein that orchestrates neurotransmitter release with Piccolo ( PCLO ) from glutamatergic neurons throughout the brain. Heterozygous missense variants in BSN have previously been associated with neurodegenerative disorders in humans. We performed an exome-wide association analysis of ultra-rare variants in about 140,000 unrelated individuals from the UK Biobank to search for new genes associated with obesity. We found that rare heterozygous predicted loss of function (pLoF) variants in BSN are associated with higher BMI with log10-p value of 11.78 in the UK biobank cohort. The association was replicated in the All of Us whole genome sequencing data. Additionally, we have identified two individuals (one of whom has a de novo variant) with a heterozygous pLoF variant in a cohort of early onset or extreme obesity at Columbia University. Like the individuals identified in the UKBB and All of us Cohorts, these individuals have no history of neurobehavioral or cognitive disability. Heterozygosity for pLoF BSN variants constitutes a new etiology for obesity.

Next-Generation Sequencing of a Large Gene Panel for Outcome Prediction of Bariatric Surgery in Patients with Severe Obesity

Obesity is a chronic disease in which abnormal deposition of fat threatens health, leading to diabetes, cardiovascular diseases, cancer, and other chronic illnesses. According to the WHO, 19.8% of the adult population in Italy is obese, and the prevalence is higher among men. It is important to know the predisposition of an individual to become obese and to respond to bariatric surgery, the most up-to-date treatment for severe obesity. To this purpose, we developed an NGS gene panel, comprising 72 diagnostic genes and 244 candidate genes, and we sequenced 247 adult obese Italian patients. Eleven deleterious variants in 9 diagnostic genes and 17 deleterious variants in 11 candidate genes were identified. Interestingly, mutations were found in several genes correlated to the Bardet-Biedl syndrome. Then, 25 patients were clinically followed to evaluate their response to bariatric surgery. After a 12-month follow-up, the patients that carried deleterious variants in diagnostic or candidate genes had a reduced weight loss, as compared to the other patients. The NGS-based panel, including diagnostic and candidate genes used in this study, could play a role in evaluating, diagnosing, and managing obese individuals, and may help in predicting the outcome of bariatric surgery.

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants that are reliably associated with human traits. Although GWASs are restricted to certain variant frequencies, they have improved our understanding of the genetic architecture of complex traits and diseases. The UK Biobank (UKBB) has brought substantial analytical opportunity and performance to association studies. The dramatic expansion of many GWAS sample sizes afforded by the inclusion of UKBB data has improved the power of estimation of effect sizes but, critically, has done so in a context where phenotypic depth and precision enable outcome dissection and the application of epidemiological approaches. However, at the same time, the availability of such a large, well-curated, and deeply measured population-based collection has the capacity to increase our exposure to the many complications and inferential complexities associated with GWASs and other analyses. In this review, we discuss the impact that UKBB has had in the GWAS era, some of the opportunities that it brings, and exemplar challenges that illustrate the reality of using data from this world-leading resource.

Epigenetics of type 2 diabetes mellitus and weight change - a tool for precision medicine?

Pioneering studies performed over the past few decades demonstrate links between epigenetics and type 2 diabetes mellitus (T2DM), the metabolic disorder with the most rapidly increasing prevalence in the world. Importantly, these studies identified epigenetic modifications, including altered DNA methylation, in pancreatic islets, adipose tissue, skeletal muscle and the liver from individuals with T2DM. As non-genetic factors that affect the risk of T2DM, such as obesity, unhealthy diet, physical inactivity, ageing and the intrauterine environment, have been associated with epigenetic modifications in healthy individuals, epigenetics probably also contributes to T2DM development. In addition, genetic factors associated with T2DM and obesity affect the epigenome in human tissues. Notably, causal mediation analyses found DNA methylation to be a potential mediator of genetic associations with metabolic traits and disease. In the past few years, translational studies have identified blood-based epigenetic markers that might be further developed and used for precision medicine to help patients with T2DM receive optimal therapy and to identify patients at risk of complications. This Review focuses on epigenetic mechanisms in the development of T2DM and the regulation of body weight in humans, with a special focus on precision medicine.

Dissecting the clinical relevance of polygenic risk score for obesity-a cross-sectional, longitudinal analysis

BACKGROUND

Obesity is a global pandemic disease whose prevalence is increasing worldwide. The clinical relevance of a polygenic risk score (PRS) for obesity has not been fully elucidated in Asian populations.

METHOD

We utilized a comprehensive health check-up database from the Korean population in conjunction with genotyping to generate PRS for BMI (PRS-BMI). We conducted a phenome-wide association (PheWAS) analysis and observed the longitudinal association of BMI with PRS-BMI.

RESULTS

PRS-BMI was generated by PRS-CS. Adding PRS-BMI to a model predicting ten-year BMI based on age, sex, and baseline BMI improved the model's accuracy (p = 0.003). In a linear mixed model of longitudinal change in BMI with aging, higher deciles of PRS were directly associated with changes in BMI. In the PheWAS, significant associations were observed for metabolic syndrome, bone density, and fatty liver. In the lean body population, those having the top 20% PRS-BMI had higher BMI and body fat mass along with better metabolic trait profiles compared to the bottom 20%. A bottom-20% PRS-BMI was a risk factor for metabolically unhealthy lean body (odds ratio 3.092, 95% confidence interval 1.707-6.018, p < 0.001), with adjustment for age, sex and BMI.

CONCLUSIONS

Genetic predisposition to obesity as defined by PRS-BMI was significantly associated with obesity-related disease or trajectory of obesity. Low PRS-BMI might be a risk factor associated with a metabolically unhealthy lean body. Better understanding the mechanisms of these relationships may allow tailored intervention in obesity or early selection of populations at risk of metabolic disease.

Low-frequency Coding Variants Associated With Body Mass Index Affect the Success of Bariatric Surgery

CONTEXT

A recent study identified 14 low-frequency coding variants associated with body mass index (BMI) in 718 734 individuals predominantly of European ancestry.

OBJECTIVE

We investigated the association of 2 genetic scores (GS) with i) the risk of severe/morbid obesity, ii) BMI variation before weight-loss intervention, iii) BMI change in response to an 18-month lifestyle/behavioral intervention program, and iv) BMI change up to 24 months after bariatric surgery.

METHODS

The 14 low-frequency coding variants were genotyped or sequenced in 342 French adults with severe/morbid obesity and 574 French adult controls from the general population. We built risk and protective GS based on 6 BMI-increasing and 5 BMI-decreasing low-frequency coding variants that were polymorphic in our study.

RESULTS

While the risk GS was not associated with severe/morbid obesity status, BMI-decreasing low-frequency coding variants were significantly less frequent in patients with severe/morbid obesity than in French adults from the general population. Neither the risk nor the protective GS was associated with BMI before intervention in patients with severe/morbid obesity, nor did they affect BMI change in response to a lifestyle/behavioral modification program. The protective GS was associated with a greater BMI decrease following bariatric surgery. The risk and protective GS were associated with a higher and lower risk of BMI regain after bariatric surgery.

CONCLUSION

Our data indicate that in populations of European descent, low-frequency coding variants associated with BMI in the general population also affect the outcomes of bariatric surgery in patients with severe/morbid obesity.

From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits

Decoding the genome confers the capability to predict characteristics of the organism (phenotype) from DNA (genotype). We describe the present status and future prospects of genomic prediction of complex traits in humans. Some highly heritable complex phenotypes such as height and other quantitative traits can already be predicted with reasonable accuracy from DNA alone. For many diseases, including important common conditions such as coronary artery disease, breast cancer, type I and II diabetes, individuals with outlier polygenic scores (e.g., top few percent) have been shown to have 5 or even 10 times higher risk than average. Several psychiatric conditions such as schizophrenia and autism also fall into this category. We discuss related topics such as the genetic architecture of complex traits, sibling validation of polygenic scores, and applications to adult health, in vitro fertilization (embryo selection), and genetic engineering.

Mice Lacking Gpr75 are Hypophagic and Thin

PURPOSE

Humans with haploinsufficiency of GPR75, an orphan GPCR, are thin. Gpr75 knockout (KO) mice are also thin with improved glucose homeostasis. We wanted to confirm these findings in Gpr75 KO mice and determine whether decreased energy intake and/or increased energy expenditure contributed to the thin phenotype.

METHODS

Gpr75 KO mice were generated by homologous recombination. All studies compared female and male Gpr75 KO mice to their wild type (WT) littermates. Body composition was measured by DXA and QMR technologies. Glucose homeostasis was evaluated by measuring glucose and insulin levels during oral glucose tolerance tests (OGTTs). Food intake was measured in group-housed mice. In singly housed mice, energy expenditure was measured in Oxymax indirect calorimetry chambers, and locomotor activity was measured in Oxymax and Photobeam Activity System chambers.

RESULTS

In all 12 cohorts of adult female or male mice, Gpr75 KO mice had less body fat; pooled data showed that, compared to WT littermates (n = 103), Gpr75 KO mice (n = 118) had 49% less body fat and 4% less LBM (P < 0.001 for each). KO mice also had 8% less body fat at weaning (P < 0.05), and during the month after weaning as the thin phenotype became more exaggerated, Gpr75 KO mice ate significantly less than, but had energy expenditure and activity levels comparable to, their WT littermates. During OGTTs, Gpr75 KO mice showed improved glucose tolerance (glucose AUC 23% lower in females, P < 0.05, and 26% lower in males, P < 0.001), accompanied by significantly decreased insulin levels and significantly increased insulin sensitivity indices.

CONCLUSION

Gpr75 KO mice are thin at weaning, are hypophagic as the thin phenotype becomes more exaggerated, and exhibit improved glucose tolerance and insulin sensitivity as healthy-appearing adults. These results suggest that inhibiting GPR75 in obese humans may safely decrease energy intake and body fat while improving glucose tolerance and insulin sensitivity.

Physical Activity and Subsequent Change in Body Weight, Composition and Shape: Effect Modification by Familial Overweight

BACKGROUND

Physical activity (PA) has been shown to attenuate the genetic risk of obesity as measured using polygenic risk scores. However, familial obesity history might be an easier predictor. We examined associations between PA and subsequent changes in BMI, body fat percentage (BF%) and waist circumference (WC) among participants with and without adiposity and a familial overweight.

METHODS

In total, 1971 participants from the Danish MONICA cohort were included. Mean differences for 6-year changes in BMI, BF% and WC across PA levels were estimated. Association between walking and biking and subsequent change in adiposity were analysed. Effect modification by familial obesity was assessed by adding product terms to the models.

RESULTS

We observed weak associations between leisure PA level and changes in WC [participants with low PA: 3.4 cm (95%CI: 2.8;4.0), participants with high PA: 2.4 cm (95%CI: 1.8;3.0)], with no evidence of effect modification by familial obesity. We found effect modification in analyses on walking and biking in relation to changes in BMI (P-interaction<0.01) and BF% (P-interaction=0.04), suggesting lower gain with more hours of activity among participants with adiposity and familial overweight.

CONCLUSIONS

The results were modest but suggested that PA, especially walking and biking, may prevent future adiposity.

Polygenic risk scores: An overview from bench to bedside for personalised medicine

Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.

Precision Medicine and Obesity

Obesity is a chronic, relapsing, and multifactorial disease, with a rising prevalence and an associated high economic burden. Achieving successful and sustained weight loss outcomes with current interventions is challenging. This is due, at least in part, to the disease's heterogenous pathophysiology that is yet to be completely understood. Technological advances and greater capabilities for the extraction and storage of information have facilitated the application of precision medicine. Several precision medicine initiatives have been proposed to improve obesity outcomes. Most of these initiatives are based on -omics technologies. Although the data generated from these technologies have led to developing hypotheses that may explain the underpinnings of obesity, their applicability to the clinical practice is yet to be determined. There are other initiatives that have identified quantitative or qualitative physiologic traits that can be targeted and that could have a more immediate clinical impact. This review aims to provide a perspective of current initiatives for precision medicine for obesity.

Non-linear interaction between physical activity and polygenic risk score of body mass index in Danish and Russian populations

Body mass index (BMI) is a highly heritable polygenic trait. It is also affected by various environmental and behavioral risk factors. We used a BMI polygenic risk score (PRS) to study the interplay between the genetic and environmental factors defining BMI. First, we generated a BMI PRS that explained more variance than a BMI genetic risk score (GRS), which was using only genome-wide significant BMI-associated variants (R² = 13.1% compared to 6.1%). Second, we analyzed interactions between BMI PRS and seven environmental factors. We found a significant interaction between physical activity and BMI PRS, even when the well-known effect of the FTO region was excluded from the PRS, using a small dataset of 6,179 samples. Third, we stratified the study population into two risk groups using BMI PRS. The top 22% of the studied populations were included in a high PRS risk group. Engagement in self-reported physical activity was associated with a 1.66 kg/m² decrease in BMI in this group, compared to a 0.84 kg/m² decrease in BMI in the rest of the population. Our results (i) confirm that genetic background strongly affects adult BMI in the general population, (ii) show a non-linear interaction between BMI genetics and physical activity, and (iii) provide a standardized framework for future gene-environment interaction analyses.

An Innovative Approach for Decision-Making on Designing Lifestyle Programs to Reduce Type 2 Diabetes on Dutch Population Level Using Dynamic Simulations

The number of individuals suffering from type 2 diabetes is dramatically increasing worldwide, resulting in an increasing burden on society and rising healthcare costs. With increasing evidence supporting lifestyle intervention programs to reduce type 2 diabetes, and the use of scenario simulations for policy support, there is an opportunity to improve population interventions based upon cost–benefit analysis of especially complex lifestyle intervention programs through dynamic simulations. In this article, we used the System Dynamics (SD) modeling methodology aiming to develop a simulation model for policy makers and health professionals to gain a clear understanding of the patient journey of type 2 diabetes mellitus and to assess the impact of lifestyle intervention programs on total cost for society associated with prevention and lifestyle treatment of pre-diabetes and type 2 diabetes in The Netherlands. System dynamics describes underlying structure in the form of causal relationships, stocks, flows, and delays to explore behavior and simulate scenarios, in order to prescribe intervention programs. The methodology has the opportunity to estimate and simulate the consequences of unforeseen interactions in order to prescribe intervention programs based on scenarios tested through “what-if” experiments. First, the extensive knowledge of diabetes, current available data on the type 2 diabetes population, lifestyle intervention programs, and associated cost in The Netherlands were captured in one simulation model. Next, the relationships between leverage points on the growth of type 2 diabetes population were based upon available data. Subsequently, the cost and benefits of future lifestyle intervention programs on reducing diabetes were simulated, identifying the need for an integrated adaptive design of lifestyle programs while collecting the appropriate data over time. The strengths and limitations of scenario simulations of complex lifestyle intervention programs to improve the (cost)effectiveness of these programs to reduce diabetes in a more sustainable way compared to usual care are discussed.

Identification of Genetic Variants in 65 Obesity Related Genes in a Cohort of Portuguese Obese Individuals

Obesity is a major public health problem, which has a strong genetic component that interplays with environmental factors. Several genes are known to be implicated in the regulation of body weight. The identification of alleles that can be associated with obesity is a key element to control this pandemic. On the basis of a Portuguese population, 65 obesity-related genes are sequenced using Next-Generation Sequencing (NGS) in 72 individuals with obesity, in order to identify variants associated with monogenic obesity and potential risk factors. A total of 429 variants are identified, 129 of which had already been associated with the phenotype. Comparing our results with the European and Global frequencies, from 1000 Genomes project, 23 potential risk variants are identified. Six new variants are discovered in heterozygous carriers: four missense (genes ALMS1-NM_015120.4:c.5552C>T; SORCS1-NM_001013031.2:c.1072A>G and NM_001013031.2: c.2491A>C; TMEM67-NM_153704.5:c.158A>G) and two synonymous (genes BBS1-NM_024649.4:c.1437C>T; TMEM67-NM_153704.5:c.2583T>C). Functional studies should be performed to validate these new findings and evaluate their penetrance and pathogenicity. Regardless of no cases of monogenic obesity being identified, this kind of investigational study is important when we are still trying to understand the aetiology and pathophysiology of obesity. This will allow the identification of rare variants associated with obesity and the study of their prevalence in specific populational groups.

Selection of Antiobesity Medications Based on Phenotypes Enhances Weight Loss: A Pragmatic Trial in an Obesity Clinic

OBJECTIVE

Little is known about the predictors of response to obesity interventions.

METHODS

In 450 participants with obesity, body composition, resting energy expenditure, satiety, satiation, eating behavior, affect, and physical activity were measured by validated studies and questionnaires. These variables were used to classify obesity phenotypes. Subsequently, in a 12-month, pragmatic, real-world trial performed in a weight management center, 312 patients were randomly assigned to phenotype-guided treatment or non-phenotype-guided treatment with antiobesity medications: phentermine, phentermine/topiramate, bupropion/naltrexone, lorcaserin, and liraglutide. The primary outcome was weight loss at 12 months.

RESULTS

Four phenotypes of obesity were identified in 383 of 450 participants (85%): hungry brain (abnormal satiation), emotional hunger (hedonic eating), hungry gut (abnormal satiety), and slow burn (decreased metabolic rate). In 15% of participants, no phenotype was identified. Two or more phenotypes were identified in 27% of patients. In the pragmatic clinical trial, the phenotype-guided approach was associated with 1.75-fold greater weight loss after 12 months with mean weight loss of 15.9% compared with 9.0% in the non-phenotype-guided group (difference -6.9% [95% CI -9.4% to -4.5%], P < 0.001), and the proportion of patients who lost >10% at 12 months was 79% in the phenotype-guided group compared with 34% with non-phenotype-guided treatment group.

CONCLUSIONS

Biological and behavioral phenotypes elucidate human obesity heterogeneity and can be targeted pharmacologically to enhance weight loss.

Evaluating Moderation of Parent-Teen Overweight/Obesity Relation by Household Socioeconomic Status

Evidence links parent-offspring weight status, but few studies have evaluated whether markers of socioeconomic status moderate this relation. The 2014 Family Life, Activity, Sun, Health, and Eating study was used to assess intergenerational weight status in a national sample of parent-teen dyads. Multivariable logistic regression models assessed the relation between parent-teen weight status, controlling for teen and parent dietary factors, physical activity, demographic factors, and socioeconomic factors. Models with interaction assessed moderation by household food security status and participation in federal assistance programs. In fully adjusted models, sons were 2.66 (95% CI: 1.56, 4.55) times more likely to have overweight/obesity if their mother had overweight/obesity, and daughters were 3.35 (95% CI: 1.91, 5.86) times more likely. This relation was stronger in mother-son pairs in households with lower food security. These findings provide important new information that can be used to inform nutritional counseling efforts and educational programs that support families with socioeconomic disadvantage.

Examining the effect of obesity-associated gene variants on breast cancer survivors in a randomized weight loss intervention

PURPOSE

Our study examined whether common variants of obesity-associated genes FTO, MC4R, BDNF, and CREB1 moderated the effects of a lifestyle intervention on weight change among breast cancer survivors.

METHODS

151 breast cancer survivors with a body mass index ≥ 25 kg/m² were randomly assigned to a 6-month weight loss intervention or usual care group. Genotyping of FTO rs9939609, MC4R rs6567160, BDNF rs11030104, CREB1 rs17203016 was performed. Linear mixed models were used including the main effects of genotype (assuming a dominant genetic model), treatment arm on weight and percent body fat changes, and genotype by treatment interaction variable. All statistical tests were evaluated against a Bonferroni-corrected alpha of 0.0125.

RESULTS

Women in the intervention group achieved significantly greater weight loss than the usual care group (5.9% vs 0.4%, p < 0.001), regardless of genotype. Changes in weight and percent body fat did not differ significantly between carriers of the FTO rs9939609, MC4R rs6567160, BDNF rs11030104, and CREB1 rs17203016 risk alleles compared to non-carriers (p-interaction > 0.0125 for each single-nucleotide polymorphisms).

CONCLUSIONS

Women who are genetically predisposed to obesity and recently diagnosed with breast cancer may achieve significant and clinically meaningful weight loss through healthy eating and exercise.

CLINICAL TRIAL REGISTRATION

NCT02863887 (Date of Registration: August 11, 2016); NCT02110641 (Date of Registration: April 10, 2014).

Utilizing genome wide data to highlight the social behavioral pathways to health: The case of obesity and cardiovascular health among older adults

We use genome-wide data from the 1992-2016 Health and Retirement Study (n = 12,090) to characterize obesity among older adults as genetically or socially oriented. To illustrate the significance of this approach for social epidemiological research, we deem those with the lowest genetic risk for obesity to be socially-behaviorally obese and obesity among those with the highest polygenic risk is characterized as genetically oriented. We then examine the association between obesity and four indicators of cardiovascular health (type-2 diabetes, hypertension, heart problems, and stroke) among those with low, average, and high genetic risk. Our results show that the association between obesity and cardiovascular health is significantly higher for those with the lowest genetic risk (e.g., social-behavioral obesity). We also demonstrate important sex differences such that this association is particularly strong for heart problems among men and hypertension and stroke among women. Our results further demonstrate the centrality of the social and behavioral determinants of health by utilizing detailed information across the human genome and add to both social and genetic epidemiology literatures.

Development of a Genetic Risk Score to predict the risk of overweight and obesity in European adolescents from the HELENA study

Obesity is the result of interactions between genes and environmental factors. Since monogenic etiology is only known in some obesity-related genes, a genetic risk score (GRS) could be useful to determine the genetic predisposition to obesity. Therefore, the aim of our study was to build a GRS able to predict genetic predisposition to overweight and obesity in European adolescents. A total of 1069 adolescents (51.3% female), aged 11-19 years participating in the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study were genotyped. The sample was divided in non-overweight (non-OW) and overweight/obesity (OW/OB). From 611 single nucleotide polymorphisms (SNP) available, a first screening of 104 SNPs univariately associated with obesity (p < 0.20) was established selecting 21 significant SNPs (p < 0.05) in the multivariate model. Unweighted GRS (uGRS) was calculated by summing the number of risk alleles and weighted GRS (wGRS) by multiplying the risk alleles to each estimated coefficient. The area under curve (AUC) was calculated in uGRS (0.723) and wGRS (0.734) using tenfold internal cross-validation. Both uGRS and wGRS were significantly associated with body mass index (BMI) (p < .001). Both GRSs could potentially be considered as useful genetic tools to evaluate individual's predisposition to overweight/obesity in European adolescents.

Do polyunsaturated fatty acids protect against bone loss in our aging and osteoporotic population?

Age-related bone loss is inevitable in both men and women and there will soon be more people of extreme old age than ever before. Osteoporosis is a common chronic disease and as the proportion of older people, rate of obesity and the length of life increases, a rise in age-related degenerating bone diseases, disability, and prolonged dependency is projected. Fragility fractures are one of the most severe complications associated with both primary and secondary osteoporosis and current treatment strategies target weight-bearing exercise and pharmacological intervention, both with limited long-term success. Obesity and osteoporosis are intimately interrelated, and diet is a variable that plays a significant role in bone regeneration and repair. The Western Diet is characterized by its unhealthy components, specifically excess amounts of saturated fat intake. This review examines the impact of saturated and polyunsaturated fatty acid consumption on chronic inflammation, osteogenesis, bone architecture, and strength and explores the hypothesis that dietary polyunsaturated fats have a beneficial effect on osteogenesis, reducing bone loss by decreasing chronic inflammation, and activating bone resorption through key cellular and molecular mechanisms in our aging population. We conclude that aging, obesity and a diet high in saturated fatty acids significantly impairs bone regeneration and repair and that consumption of ω-3 polyunsaturated fatty acids is associated with significantly increased bone regeneration, improved microarchitecture and structural strength. However, ω-6 polyunsaturated fatty acids were typically pro-inflammatory and have been associated with an increased fracture risk. This review suggests a potential role for ω-3 fatty acids as a non-pharmacological dietary method of reducing bone loss in our aging population. We also conclude that contemporary amendments to the formal nutritional recommendations made by the Food and Nutrition Board may be necessary such that our aging population is directly considered.

The Leptin System and Diet: A Mini Review of the Current Evidence

Leptin promotes satiety and modulates energy balance and weight. Diet-induced obesity leads to leptin resistance, exacerbating overeating. We reviewed the literature on the relationship between diet and leptin, which suggests that addressing leptin resistance through dietary interventions can contribute counteracting obesity. Albeit some limitations (e.g., limited rigor, small samples sizes), studies in animals and humans show that diets high in fat, carbohydrates, fructose, and sucrose, and low in protein are drivers of leptin resistance. Despite methodological heterogeneity pertaining to this body of literature, experimental studies show that energy-restricted diets can reduce leptinemia both in the short and long term and potentially reverse leptin resistance in humans. We also discuss limitations of this evidence, future lines of research, and implications for clinical and public health translations. Main limitations include the lack of a single universally-accepted definition of leptin resistance, and of adequate ways to accurately measure it in humans. The use of leptin sensitizers (drugs) and genetically individualized diets are alternatives against leptin resistance that should be further researched in humans. The tested very-low-energy intervention diets are challenging to translate into wide clinical or population recommendations. In conclusion, the link between nutritional components and leptin resistance, as well as research indicating that this condition is reversible, emphasizes the potential of diet to recover sensitivity to this hormone. A harmonized definition of leptin resistance, reliable methods to measure it, and large-scale, translational, clinical, and precision nutrition research involving rigorous methods are needed to benefit populations through these approaches.

Eating behaviour in contrasting adiposity phenotypes: Monogenic obesity and congenital generalized lipodystrophy

Most known types of nonsyndromic monogenic obesity are caused by rare mutations in genes of the leptin-melanocortin pathway controlling appetite and adiposity. In contrast, congenital generalized lipodystrophy represents the most extreme form of leanness in humans caused by recessive mutations in four genes involved in phospholipid/triglyceride synthesis and lipid droplet/caveolae structure. In this disease, the inability to store triglyceride in adipocytes results in hypoleptinemia and ectopic hepatic and muscle fat accumulation leading to fatty liver, hypertriglyceridemia and severe insulin resistance. As a result of hypoleptinemia, patients with lipodystrophy show alterations in eating behaviour characterized by constant increased energy intake. As it occurs in obesity caused by genetic leptin deficiency, exogenous leptin rapidly reduces hunger scores in patients with congenital generalized lipodystrophy, with additional beneficial effects on glucose homeostasis and metabolic profile normalization. The melanocortin-4 receptor agonist setmelanotide has been used in the treatment of monogenic obesities. There is only one report on the effect of setmelanotide in a patient with partial lipodystrophy resulting in mild reductions in hunger scores, with no improvements in metabolic status. The assessment of contrasting phenotypes of obesity/leanness represents an adequate strategy to understand the pathophysiology and altered eating behaviour associated with adipose tissue excessive accumulation/paucity.

Genetic Determinants of Childhood Obesity

Obesity represents a major health burden to both developed and developing countries. Furthermore, the incidence of obesity is increasing in children. Obesity contributes substantially to mortality in the United States by increasing the risk for type 2 diabetes, cardiovascular-related diseases, and other comorbidities. Despite environmental changes over past decades, including increases in high-calorie foods and sedentary lifestyles, there is very clear evidence of a genetic predisposition to obesity risk. Childhood obesity cases can be categorized in one of two ways: syndromic or non-syndromic. Syndromic obesity includes disorders such as Prader-Willi syndrome, Bardet-Biedl syndrome, and Alström syndrome. Non-syndromic cases of obesity can be further separated into rarer instances of monogenic obesity and much more common forms of polygenic obesity. The advent of genome-wide association studies (GWAS) and next-generation sequencing has driven significant advances in our understanding of the genetic contribution to childhood obesity. Many rare and common genetic variants have been shown to contribute to the heritability in obesity, although the molecular mechanisms underlying most of these variants remain unclear. An important caveat of GWAS efforts is that they do not strictly represent gene target discoveries, rather simply the uncovering of robust genetic signals. One clear example of this is with progress in understanding the key obesity signal harbored within an intronic region of the FTO gene. It has been shown that the non-coding region in which the variant actually resides in fact influences the expression of genes distal to FTO instead, specifically IRX3 and IRX5. Such discoveries suggest that associated non-coding variants can be embedded within or next to one gene, but commonly influence the expression of other, more distal effector genes. Advances in genetics and genomics are therefore contributing to a deeper understanding of childhood obesity, allowing for development of clinical tools and therapeutic agents.

An integrative machine learning approach to discovering multi-level molecular mechanisms of obesity using data from monozygotic twin pairs

We combined clinical, cytokine, genomic, methylation and dietary data from 43 young adult monozygotic twin pairs (aged 22-36 years, 53% female), where 25 of the twin pairs were substantially weight discordant (delta body mass index > 3 kg m^-2). These measurements were originally taken as part of the TwinFat study, a substudy of The Finnish Twin Cohort study. These five large multivariate datasets (comprising 42, 71, 1587, 1605 and 63 variables, respectively) were jointly analysed using an integrative machine learning method called group factor analysis (GFA) to offer new hypotheses into the multi-molecular-level interactions associated with the development of obesity. New potential links between cytokines and weight gain are identified, as well as associations between dietary, inflammatory and epigenetic factors. This encouraging case study aims to enthuse the research community to boldly attempt new machine learning approaches which have the potential to yield novel and unintuitive hypotheses. The source code of the GFA method is publically available as the R package GFA.

Omics Biomarkers in Obesity: Novel Etiological Insights and Targets for Precision Prevention

PURPOSE OF REVIEW

Omics-based technologies were suggested to provide an advanced understanding of obesity etiology and its metabolic consequences. This review highlights the recent developments in "omics"-based research aimed to identify obesity-related biomarkers.

RECENT FINDINGS

Recent advances in obesity and metabolism research increasingly rely on new technologies to identify mechanisms in the development of obesity using various "omics" platforms. Genetic and epigenetic biomarkers that translate into changes in transcriptome, proteome, and metabolome could serve as targets for obesity prevention. Despite a number of promising candidate biomarkers, there is an increased demand for larger prospective cohort studies to validate findings and determine biomarker reproducibility before they can find applications in primary care and public health. "Omics" biomarkers have advanced our knowledge on the etiology of obesity and its links with chronic diseases. They bring substantial promise in identifying effective public health strategies that pave the way towards patient stratification and precision prevention.

Environment and Gene Association With Obesity and Their Impact on Neurodegenerative and Neurodevelopmental Diseases

Obesity is a multifactorial disease in which environmental conditions and several genes play an important role in the development of this disease. Obesity is associated with neurodegenerative diseases (Alzheimer, Parkinson, and Huntington diseases) and with neurodevelopmental diseases (autism disorder, schizophrenia, and fragile X syndrome). Some of the environmental conditions that lead to obesity are physical activity, alcohol consumption, socioeconomic status, parent feeding behavior, and diet. Interestingly, some of these environmental conditions are shared with neurodegenerative and neurodevelopmental diseases. Obesity impairs neurodevelopment abilities as memory and fine-motor skills. Moreover, maternal obesity affects the cognitive function and mental health of the offspring. The common biological mechanisms involved in obesity and neurodegenerative/neurodevelopmental diseases are insulin resistance, pro-inflammatory cytokines, and oxidative damage, among others, leading to impaired brain development or cell death. Obesogenic environmental conditions are not the only factors that influence neurodegenerative and neurodevelopmental diseases. In fact, several genes implicated in the leptin-melanocortin pathway (LEP, LEPR, POMC, BDNF, MC4R, PCSK1, SIM1, BDNF, TrkB, etc.) are associated with obesity and neurodegenerative and neurodevelopmental diseases. Moreover, in the last decades, the discovery of new genes associated with obesity (FTO, NRXN3, NPC1, NEGR1, MTCH2, GNPDA2, among others) and with neurodegenerative or neurodevelopmental diseases (APOE, CD38, SIRT1, TNFα, PAI-1, TREM2, SYT4, FMR1, TET3, among others) had opened new pathways to comprehend the common mechanisms involved in these diseases. In conclusion, the obesogenic environmental conditions, the genes, and the interaction gene-environment would lead to a better understanding of the etiology of these diseases.

Preventive Cardiology and Risk Assessment: Beyond LDL

PURPOSE OF REVIEW

Risk assessment is the foundational cornerstone for cardiovascular prevention. The goal of this review is to apprise the reader of the latest evidence and guideline-based stepwise method for clinical risk assessment for future atherosclerotic events. We also discuss caveats to the current approach and review future directions including the promise of precision medicine.

RECENT FINDINGS

The most recent cholesterol and prevention guidelines improve upon the widely used pooled cohort equations by incorporating risk-enhancing factors to further personalize risk assessment. For those in whom uncertainty remains, there is mounting evidence for using the coronary calcium score to uncover subclinical disease to either up- or down-classify risk. Although still in its infancy, progress in high-throughput molecular analysis is edging the field closer to more precise risk stratification. Atherosclerosis is the leading cause of global morbidity and mortality. Emphasis on cardiovascular prevention is essential to mitigate the burden of disease. Here, we introduce a "4 + 2" paradigm for approaching preventive cardiology based on recent guidelines. Risk stratification is performed in four steps: qualitative risk approximation to initiate counseling and education, quantitative risk estimation based on a validated model, personalization with risk-enhancing factors, and measurement of coronary artery calcium score in select patients. The two foundational principles of preventive management are to promote a healthy lifestyle in all and to escalate preventive pharmacotherapy based on increasing risk. Shared decision-making remains central throughout this process.

Potential positive and negative consequences of ZnT8 inhibition

SLC30A8 encodes the zinc transporter ZnT8. SLC30A8 haploinsufficiency protects against type 2 diabetes (T2D), suggesting that ZnT8 inhibitors may prevent T2D. We show here that, while adult chow fed Slc30a8 haploinsufficient and knockout (KO) mice have normal glucose tolerance, they are protected against diet-induced obesity (DIO), resulting in improved glucose tolerance. We hypothesize that this protection against DIO may represent one mechanism whereby SLC30A8 haploinsufficiency protects against T2D in humans and that, while SLC30A8 is predominantly expressed in pancreatic islet beta cells, this may involve a role for ZnT8 in extra-pancreatic tissues. Consistent with this latter concept we show in humans, using electronic health record-derived phenotype analyses, that the 'C' allele of the non-synonymous rs13266634 SNP, which confers a gain of ZnT8 function, is associated not only with increased T2D risk and blood glucose, but also with increased risk for hemolytic anemia and decreased mean corpuscular hemoglobin (MCH). In Slc30a8 KO mice, MCH was unchanged but reticulocytes, platelets and lymphocytes were elevated. Both young and adult Slc30a8 KO mice exhibit a delayed rise in insulin after glucose injection, but only the former exhibit increased basal insulin clearance and impaired glucose tolerance. Young Slc30a8 KO mice also exhibit elevated pancreatic G6pc2 gene expression, potentially mediated by decreased islet zinc levels. These data indicate that the absence of ZnT8 results in a transient impairment in some aspects of metabolism during development. These observations in humans and mice suggest the potential for negative effects associated with T2D prevention using ZnT8 inhibitors.