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Nutrients Aug 2023Obesity is a metabolic state generated by the expansion of adipose tissue. Adipose tissue expansion depends on the interplay between hyperplasia and hypertrophy, and is... (Review)
Review
Obesity is a metabolic state generated by the expansion of adipose tissue. Adipose tissue expansion depends on the interplay between hyperplasia and hypertrophy, and is mainly regulated by a complex interaction between genetics and excess energy intake. However, the genetic regulation of adipose tissue expansion is yet to be fully understood. Obesity can be divided into common multifactorial/polygenic obesity and monogenic obesity, non-syndromic and syndromic. Several genes related to obesity were found through studies of monogenic non-syndromic obesity models. However, syndromic obesity, characterized by additional features other than obesity, suggesting a more global role of the mutant genes related to the syndrome and, thus, an additional peripheral influence on the development of obesity, were hardly studied to date in this regard. This review summarizes present knowledge regarding the hyperplasia and hypertrophy of adipocytes in common obesity. Additionally, we highlight the scarce research on syndromic obesity as a model for studying adipocyte hyperplasia and hypertrophy, focusing on Bardet-Biedl syndrome (BBS). BBS obesity involves central and peripheral mechanisms, with molecular and mechanistic alternation in adipocyte hyperplasia and hypertrophy. Thus, we argue that using syndromic obesity models, such as BBS, can further advance our knowledge regarding peripheral adipocyte regulation in obesity.
PubMed: 37571382
DOI: 10.3390/nu15153445 -
Genetics of Pulmonary Pressure and Right Ventricle Stress Identify Diabetes as a Causal Risk Factor.Journal of the American Heart... Aug 2023Background Epidemiologic studies have identified risk factors associated with pulmonary hypertension and right heart failure, but causative drivers of pulmonary...
Background Epidemiologic studies have identified risk factors associated with pulmonary hypertension and right heart failure, but causative drivers of pulmonary hypertension and right heart adaptation are not well known. We sought to leverage unbiased genetic approaches to determine clinical conditions that share genetic architecture with pulmonary pressure and right ventricular dysfunction. Methods and Results We leveraged Vanderbilt University's deidentified electronic health records and DNA biobank to identify 14 861 subjects of European ancestry who underwent at least 1 echocardiogram with available estimates of pulmonary pressure and right ventricular function. Analyses of the study were performed between 2020 and 2022. The final analytical sample included 14 861 participants (mean [SD] age, 63 [15] years and mean [SD] body mass index, 29 [7] kg/m). An unbiased phenome-wide association study identified diabetes as the most statistically significant clinical , () code associated with polygenic risk for increased pulmonary pressure. We validated this finding further by finding significant associations between genetic risk for diabetes and a related condition, obesity, with pulmonary pressure estimate. We then used 2-sample univariable Mendelian randomization and multivariable Mendelian randomization to show that diabetes, but not obesity, was independently associated with genetic risk for increased pulmonary pressure and decreased right ventricle load stress. Conclusions Our findings show that genetic risk for diabetes is the only significant independent causative driver of genetic risk for increased pulmonary pressure and decreased right ventricle load stress. These findings suggest that therapies targeting genetic risk for diabetes may also potentially be beneficial in treating pulmonary hypertension and right heart dysfunction.
Topics: Humans; Middle Aged; Diabetes Mellitus, Type 2; Genome-Wide Association Study; Heart Ventricles; Hypertension, Pulmonary; Obesity; Risk Factors; Aged
PubMed: 37522172
DOI: 10.1161/JAHA.122.029190 -
Reviews in Endocrine & Metabolic... Oct 2023Obesity continues to increase in prevalence globally, driven by changes in environmental factors which have accelerated the development of obesity in individuals with an... (Review)
Review
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.
Topics: Humans; Obesity; Comorbidity; Weight Loss
PubMed: 37202547
DOI: 10.1007/s11154-023-09808-2 -
Biomedicines Sep 2021Nonalcoholic fatty liver disease (NAFLD) is the commonest cause of chronic liver disease worldwide. It is closely related to obesity, insulin resistance (IR) and... (Review)
Review
Nonalcoholic fatty liver disease (NAFLD) is the commonest cause of chronic liver disease worldwide. It is closely related to obesity, insulin resistance (IR) and dyslipidemia so much so it is considered the hepatic manifestation of the Metabolic Syndrome. The NAFLD spectrum extends from simple steatosis to nonalcoholic steatohepatitis (NASH), a clinical condition which may progress up to fibrosis, cirrhosis and hepatocellular carcinoma (HCC). NAFLD is a complex disease whose pathogenesis is shaped by both environmental and genetic factors. In the last two decades, several heritable modifications in genes influencing hepatic lipid remodeling, and mitochondrial oxidative status have been emerged as predictors of progressive hepatic damage. Among them, the patatin-like phospholipase domain-containing 3 (PNPLA3) p.I148M, the Transmembrane 6 superfamily member 2 (TM6SF2) p.E167K and the rs641738 membrane bound-o-acyltransferase domain-containing 7 (MBOAT7) polymorphisms are considered the most robust modifiers of NAFLD. However, a forefront frontier in the study of NAFLD heritability is to postulate score-based strategy, building polygenic risk scores (PRS), which aggregate the most relevant genetic determinants of NAFLD and biochemical parameters, with the purpose to foresee patients with greater risk of severe NAFLD, guaranteeing the most highly predictive value, the best diagnostic accuracy and the more precise individualized therapy.
PubMed: 34680476
DOI: 10.3390/biomedicines9101359 -
International Journal of Molecular... Nov 2020Rare genetic obesity disorders are characterized by mutations of genes strongly involved in the central or peripheral regulation of energy balance. These mutations are... (Review)
Review
Rare genetic obesity disorders are characterized by mutations of genes strongly involved in the central or peripheral regulation of energy balance. These mutations are effective in causing the early onset of severe obesity and insatiable hunger (hyperphagia), suggesting that the genetic component can contribute to 40-70% of obesity. However, genes' roles in the processes leading to obesity are still unclear. This review is aimed to summarize the current knowledge of the genetic causes of obesity, especially monogenic obesity, describing the role of epigenetic mechanisms in obesity and metabolic diseases. A comprehensive understanding of the underlying genetic and epigenetic mechanisms, with the metabolic processes they control, will permit adequate management and prevention of obesity.
Topics: Body Weight; Epigenesis, Genetic; Genetic Predisposition to Disease; Genetic Variation; Humans; Obesity; Risk Factors
PubMed: 33261141
DOI: 10.3390/ijms21239035 -
Inflammation and Regeneration Jun 2021The prediction of disease risks is an essential part of personalized medicine, which includes early disease detection, prevention, and intervention. The polygenic risk... (Review)
Review
The prediction of disease risks is an essential part of personalized medicine, which includes early disease detection, prevention, and intervention. The polygenic risk score (PRS) has become the standard for quantifying genetic liability in predicting disease risks. PRS utilizes single-nucleotide polymorphisms (SNPs) with genetic risks elucidated by genome-wide association studies (GWASs) and is calculated as weighted sum scores of these SNPs with genetic risks using their effect sizes from GWASs as their weights. The utilities of PRS have been explored in many common diseases, such as cancer, coronary artery disease, obesity, and diabetes, and in various non-disease traits, such as clinical biomarkers. These applications demonstrated that PRS could identify a high-risk subgroup of these diseases as a predictive biomarker and provide information on modifiable risk factors driving health outcomes. On the other hand, there are several limitations to implementing PRSs in clinical practice, such as biased sensitivity for the ethnic background of PRS calculation and geographical differences even in the same population groups. Also, it remains unclear which method is the most suitable for the prediction with high accuracy among numerous PRS methods developed so far. Although further improvements of its comprehensiveness and generalizability will be needed for its clinical implementation in the future, PRS will be a powerful tool for therapeutic interventions and lifestyle recommendations in a wide range of diseases. Thus, it may ultimately improve the health of an entire population in the future.
PubMed: 34140035
DOI: 10.1186/s41232-021-00172-9 -
Diabetes Care May 2023Quantify the impact of genetic and socioeconomic factors on risk of type 2 diabetes (T2D) and obesity.
OBJECTIVE
Quantify the impact of genetic and socioeconomic factors on risk of type 2 diabetes (T2D) and obesity.
RESEARCH DESIGN AND METHODS
Among participants in the Mass General Brigham Biobank (MGBB) and UK Biobank (UKB), we used logistic regression models to calculate cross-sectional odds of T2D and obesity using 1) polygenic risk scores for T2D and BMI and 2) area-level socioeconomic risk (educational attainment) measures. The primary analysis included 26,737 participants of European genetic ancestry in MGBB with replication in UKB (N = 223,843), as well as in participants of non-European ancestry (MGBB N = 3,468; UKB N = 7,459).
RESULTS
The area-level socioeconomic measure most strongly associated with both T2D and obesity was percent without a college degree, and associations with disease prevalence were independent of genetic risk (P < 0.001 for each). Moving from lowest to highest quintiles of combined genetic and socioeconomic burden more than tripled T2D (3.1% to 22.2%) and obesity (20.9% to 69.0%) prevalence. Favorable socioeconomic risk was associated with lower disease prevalence, even in those with highest genetic risk (T2D 13.0% vs. 22.2%, obesity 53.6% vs. 69.0% in lowest vs. highest socioeconomic risk quintiles). Additive effects of genetic and socioeconomic factors accounted for 13.2% and 16.7% of T2D and obesity prevalence, respectively, explained by these models. Findings were replicated in independent European and non-European ancestral populations.
CONCLUSIONS
Genetic and socioeconomic factors significantly interact to increase risk of T2D and obesity. Favorable area-level socioeconomic status was associated with an almost 50% lower T2D prevalence in those with high genetic risk.
Topics: Humans; Diabetes Mellitus, Type 2; Prevalence; Cross-Sectional Studies; Genetic Predisposition to Disease; Obesity; Risk Factors; Socioeconomic Factors
PubMed: 36787958
DOI: 10.2337/dc22-1954 -
Frontiers in Pediatrics 2018Childhood obesity is occurring at alarming rates in both developed and developing countries. "Obesogenic" environmental factors must be associated with variants of... (Review)
Review
Childhood obesity is occurring at alarming rates in both developed and developing countries. "Obesogenic" environmental factors must be associated with variants of different risk alleles to determine polygenic or common obesity, and their impact depends on different developmental stages.The interaction between obesogenic environment and genetic susceptibility results in the so-called polygenic forms of obesity. In contrast, monogenic and syndromic obesity are not influenced by environmental events. Therefore, this review aimed to underline the roles of some of the most studied genes in the development of monogenic and polygenic obesity in children. Among the most common obesity related genes, we chose the fat mass and obesity-associated (FTO) gene, leptin gene and its receptor, tumor necrosis factor alpha (TNF-α), the melanocortin 4 receptor gene (MC4R), Ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1), and others, such as peroxisome proliferator-activated receptor gamma (PPARG), angiotensin-converting enzyme (ACE), glutathione S-transferase (GST), and interleukin-6 (IL-6) genes. The roles of these genes are complex and interdependent, being linked to different cornerstones in obesity development, such as appetite behavior, control of food intake and energy balance, insulin signaling, lipid and glucose metabolism, metabolic disorders, adipocyte differentiation, and so on. Genetic predisposition is mandatory, but not enough to trigger obesity.Dietary interventions and proper lifestyle changes can prevent obesity development in genetically predisposed children. Further studies are needed to identify the precise role of both genetic and obesogenic factors in the development of childhood obesity in order to design effective preventive methods.
PubMed: 30338250
DOI: 10.3389/fped.2018.00271 -
Annals of Pediatric Endocrinology &... Sep 2022Based on the genetic contribution, childhood obesity can be classified into 3 groups: common polygenic obesity, syndromic obesity, and monogenic obesity. More genetic...
Based on the genetic contribution, childhood obesity can be classified into 3 groups: common polygenic obesity, syndromic obesity, and monogenic obesity. More genetic causes of obesity are being identified along with the advances in the genetic testing. Genetic obesities including syndromic and monogenic obesity should be suspected and evaluated in children with early-onset morbid obesity and hyperphagia under 5 years of age. Patients with syndromic obesity have early-onset severe obesity associated specific genetic syndromes including Prader-Willi syndrome, Bardet-Biedle syndrome, and Alstrom syndrome. Syndromic obesity is often accompanied with neurodevelopmental delay or dysmorphic features. Nonsyndromic monogenic obesity is caused by variants in single gene which are usually involved in the regulation of hunger and satiety associated with the hypothalamic leptin-melanocortin pathway in central nervous system. Unlike syndromic obesity, patients with monogenic obesity usually show normal neurodevelopment. They would be presented with hyperphagia and early-onset severe obesity with additional clinical symptoms including short stature, red hair, adrenal insufficiency, hypothyroidism, hypogonadism, pituitary insufficiencies, diabetes insipidus, increased predisposition to infection or intractable recurrent diarrhea. Identifying patients with genetic obesity is critical as new innovative therapies including melanocortin 4 receptor agonist have become available. Early genetic evaluation enables to identify treatable obesity and provide timely intervention which may eventually achieve favorable outcome by establishing personalized management.
PubMed: 36203267
DOI: 10.6065/apem.2244188.094 -
Molecular Psychiatry Mar 2018Self-reported tiredness and low energy, often called fatigue, are associated with poorer physical and mental health. Twin studies have indicated that this has a...
Self-reported tiredness and low energy, often called fatigue, are associated with poorer physical and mental health. Twin studies have indicated that this has a heritability between 6 and 50%. In the UK Biobank sample (N=108 976), we carried out a genome-wide association study (GWAS) of responses to the question, 'Over the last two weeks, how often have you felt tired or had little energy?' Univariate GCTA-GREML found that the proportion of variance explained by all common single-nucleotide polymorphisms for this tiredness question was 8.4% (s.e.=0.6%). GWAS identified one genome-wide significant hit (Affymetrix id 1:64178756_C_T; P=1.36 × 10). Linkage disequilibrium score regression and polygenic profile score analyses were used to test for shared genetic aetiology between tiredness and up to 29 physical and mental health traits from GWAS consortia. Significant genetic correlations were identified between tiredness and body mass index (BMI), C-reactive protein, high-density lipoprotein (HDL) cholesterol, forced expiratory volume, grip strength, HbA1c, longevity, obesity, self-rated health, smoking status, triglycerides, type 2 diabetes, waist-hip ratio, attention deficit hyperactivity disorder, bipolar disorder, major depressive disorder, neuroticism, schizophrenia and verbal-numerical reasoning (absolute r effect sizes between 0.02 and 0.78). Significant associations were identified between tiredness phenotypic scores and polygenic profile scores for BMI, HDL cholesterol, low-density lipoprotein cholesterol, coronary artery disease, C-reactive protein, HbA1c, height, obesity, smoking status, triglycerides, type 2 diabetes, waist-hip ratio, childhood cognitive ability, neuroticism, bipolar disorder, major depressive disorder and schizophrenia (standardised β's had absolute values<0.03). These results suggest that tiredness is a partly heritable, heterogeneous and complex phenomenon that is phenotypically and genetically associated with affective, cognitive, personality and physiological processes.
Topics: Adult; Aged; Anoctamins; Body Mass Index; Fatigue; Female; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Linkage Disequilibrium; Male; Mental Disorders; Middle Aged; Multifactorial Inheritance; Obesity; Polymorphism, Single Nucleotide; Receptors, Dopamine D2; Risk Factors; Self Report; Statistics, Nonparametric; Transcription Factors; United Kingdom
PubMed: 28194004
DOI: 10.1038/mp.2017.5