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Current Obesity Reports Dec 2023Enormous progress has been made in understanding the genetic architecture of obesity and the correlation of epigenetic marks with obesity and related traits. This review... (Review)
Review
PURPOSE OF REVIEW
Enormous progress has been made in understanding the genetic architecture of obesity and the correlation of epigenetic marks with obesity and related traits. This review highlights current research and its challenges in genetics and epigenetics of obesity.
RECENT FINDINGS
Recent progress in genetics of polygenic traits, particularly represented by genome-wide association studies, led to the discovery of hundreds of genetic variants associated with obesity, which allows constructing polygenic risk scores (PGS). In addition, epigenome-wide association studies helped identifying novel targets and methylation sites being important in the pathophysiology of obesity and which are essential for the generation of methylation risk scores (MRS). Despite their great potential for predicting the individual risk for obesity, the use of PGS and MRS remains challenging. Future research will likely discover more loci being involved in obesity, which will contribute to better understanding of the complex etiology of human obesity. The ultimate goal from a clinical perspective will be generating highly robust and accurate prediction scores allowing clinicians to predict obesity as well as individual responses to body weight loss-specific life-style interventions.
Topics: Humans; DNA Methylation; Genome-Wide Association Study; Epigenesis, Genetic; Obesity; Phenotype; Genetic Risk Score
PubMed: 37819541
DOI: 10.1007/s13679-023-00526-z -
BMC Medicine Jun 2022Body mass index (BMI) has been found to be associated with a decreased risk of non-small cell lung cancer (NSCLC); however, the effect of BMI trajectories and potential... (Clinical Trial)
Clinical Trial
BACKGROUND
Body mass index (BMI) has been found to be associated with a decreased risk of non-small cell lung cancer (NSCLC); however, the effect of BMI trajectories and potential interactions with genetic variants on NSCLC risk remain unknown.
METHODS
Cox proportional hazards regression model was applied to assess the association between BMI trajectory and NSCLC risk in a cohort of 138,110 participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. One-sample Mendelian randomization (MR) analysis was further used to access the causality between BMI trajectories and NSCLC risk. Additionally, polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between BMI trajectories and genetic variants in NSCLC risk.
RESULTS
Compared with individuals maintaining a stable normal BMI (n = 47,982, 34.74%), BMI trajectories from normal to overweight (n = 64,498, 46.70%), from normal to obese (n = 21,259, 15.39%), and from overweight to obese (n = 4,371, 3.16%) were associated with a decreased risk of NSCLC (hazard ratio [HR] for trend = 0.78, P < 2×10). An MR study using BMI trajectory associated with genetic variants revealed no significant association between BMI trajectories and NSCLC risk. Further analysis of PRS showed that a higher GWAS-identified PRS (PRS) was associated with an increased risk of NSCLC, while the interaction between BMI trajectories and PRS with the NSCLC risk was not significant (P= 0.863 and P= 0.704). In GWIA analysis, four independent susceptibility loci (P < 1×10) were found to be associated with BMI trajectories on NSCLC risk, including rs79297227 (12q14.1, located in SLC16A7, P = 1.01×10), rs2336652 (3p22.3, near CLASP2, P = 3.92×10), rs16018 (19p13.2, in CACNA1A, P = 3.92×10), and rs4726760 (7q34, near BRAF, P = 9.19×10). Functional annotation demonstrated that these loci may be involved in the development of NSCLC by regulating cell growth, differentiation, and inflammation.
CONCLUSIONS
Our study has shown an association between BMI trajectories, genetic factors, and NSCLC risk. Interestingly, four novel genetic loci were identified to interact with BMI trajectories on NSCLC risk, providing more support for the aetiology research of NSCLC.
TRIAL REGISTRATION
http://www.
CLINICALTRIALS
gov , NCT01696968 .
Topics: Body Mass Index; Carcinoma, Non-Small-Cell Lung; Cohort Studies; Humans; Lung Neoplasms; Male; Obesity; Overweight; Risk Factors
PubMed: 35658861
DOI: 10.1186/s12916-022-02400-6 -
The Surgical Clinics of North America Apr 2021Childhood obesity can lead to comorbidities that cause significant decrease in health-related quality of life and early mortality. Recognition of obesity as a disease of... (Review)
Review
Childhood obesity can lead to comorbidities that cause significant decrease in health-related quality of life and early mortality. Recognition of obesity as a disease of polygenic etiology can help deter implicit bias. Current guidelines for treating severe obesity in children recommend referral to a multidisciplinary treatment center that offers metabolic and bariatric surgery at any age when a child develops a body mass index that is greater than 120% of the 95th percentile. Obesity medications and lifestyle counseling about diet and exercise are not adequate treatment for severe childhood obesity. Early referral can significantly improve quality and quantity of life.
Topics: Bariatric Surgery; Body Mass Index; Child; Humans; Laparoscopy; Pediatric Obesity; Quality of Life
PubMed: 33743964
DOI: 10.1016/j.suc.2020.12.007 -
The New England Journal of Medicine Dec 2016Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy...
BACKGROUND
Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy lifestyle is unknown.
METHODS
Using a polygenic score of DNA sequence polymorphisms, we quantified genetic risk for coronary artery disease in three prospective cohorts - 7814 participants in the Atherosclerosis Risk in Communities (ARIC) study, 21,222 in the Women's Genome Health Study (WGHS), and 22,389 in the Malmö Diet and Cancer Study (MDCS) - and in 4260 participants in the cross-sectional BioImage Study for whom genotype and covariate data were available. We also determined adherence to a healthy lifestyle among the participants using a scoring system consisting of four factors: no current smoking, no obesity, regular physical activity, and a healthy diet.
RESULTS
The relative risk of incident coronary events was 91% higher among participants at high genetic risk (top quintile of polygenic scores) than among those at low genetic risk (bottom quintile of polygenic scores) (hazard ratio, 1.91; 95% confidence interval [CI], 1.75 to 2.09). A favorable lifestyle (defined as at least three of the four healthy lifestyle factors) was associated with a substantially lower risk of coronary events than an unfavorable lifestyle (defined as no or only one healthy lifestyle factor), regardless of the genetic risk category. Among participants at high genetic risk, a favorable lifestyle was associated with a 46% lower relative risk of coronary events than an unfavorable lifestyle (hazard ratio, 0.54; 95% CI, 0.47 to 0.63). This finding corresponded to a reduction in the standardized 10-year incidence of coronary events from 10.7% for an unfavorable lifestyle to 5.1% for a favorable lifestyle in ARIC, from 4.6% to 2.0% in WGHS, and from 8.2% to 5.3% in MDCS. In the BioImage Study, a favorable lifestyle was associated with significantly less coronary-artery calcification within each genetic risk category.
CONCLUSIONS
Across four studies involving 55,685 participants, genetic and lifestyle factors were independently associated with susceptibility to coronary artery disease. Among participants at high genetic risk, a favorable lifestyle was associated with a nearly 50% lower relative risk of coronary artery disease than was an unfavorable lifestyle. (Funded by the National Institutes of Health and others.).
Topics: Aged; Cohort Studies; Coronary Disease; Cross-Sectional Studies; Female; Genetic Predisposition to Disease; Healthy Lifestyle; Humans; Incidence; Male; Middle Aged; Multifactorial Inheritance; Patient Compliance; Polymorphism, Genetic; Risk
PubMed: 27959714
DOI: 10.1056/NEJMoa1605086 -
Current Diabetes Reports Aug 2018This review aims to present current information on genes underlying severe obesity, with the main emphasis on the three genes LEP, LEPR and MC4R. (Review)
Review
PURPOSE OF REVIEW
This review aims to present current information on genes underlying severe obesity, with the main emphasis on the three genes LEP, LEPR and MC4R.
RECENT FINDINGS
There is a substantial amount of evidence that variants in at least ten different genes are the cause of severe monogenic obesity. The majority of these are involved in the leptin-melanocortin signalling pathway. Due to the frequency of some of the identified variants, it is clear that monogenic variants also make a significant contribution to common obesity. The artificial distinction between rare monogenic obesity and common polygenic obesity is now obsolete with the identification of MC4R variants of strong effect in the general population.
Topics: Body Mass Index; Genetic Predisposition to Disease; Humans; Leptin; Obesity; Receptor, Melanocortin, Type 4; Receptors, Leptin
PubMed: 30121879
DOI: 10.1007/s11892-018-1053-x -
Genes Feb 2024Sarcopenic obesity (SO) is a combination of obesity and sarcopenia, with diagnostic criteria defined as impaired skeletal muscle function and altered body composition... (Review)
Review
Sarcopenic obesity (SO) is a combination of obesity and sarcopenia, with diagnostic criteria defined as impaired skeletal muscle function and altered body composition (e.g., increased fat mass and reduced muscle mass). The mechanism of SO is not yet perfectly understood; however, the pathogenesis includes aging and its complications, chronic inflammation, insulin resistance (IR), and hormonal changes. Genetic background is apparent in the pathogenesis of isolated obesity, which is most often polygenic and is characterized by the additive effect of various genetic factors. The genetic etiology has not been strictly established in SO. Still, many data confirm the existence of pathogenic gene variants, e.g., Fat Mass and Obesity Associated Gene (), beta-2-adrenergic receptor () gene, melanocortin-4 receptor () and others with obesity. The literature on the role of these genes is scarce, and their role has not yet been thoroughly established. On the other hand, the involvement of systemic inflammation due to increased adipose tissue in SO plays a significant role in its pathophysiology through the synthesis of various cytokines such as monocyte chemoattractant protein-1 (MCP-1), IL-1Ra, IL-15, adiponectin or CRP. The lack of anti-inflammatory cytokine (e.g., IL-15) can increase SO risk, but further studies are needed to evaluate the exact mechanisms of implications of various cytokines in SO individuals. This manuscript analyses various immunogenetic and non-genetic factors and summarizes the recent findings on immunogenetics potentially impacting SO development.
Topics: Humans; Sarcopenia; Immunogenetics; Interleukin-15; Obesity; Inflammation; Alpha-Ketoglutarate-Dependent Dioxygenase FTO
PubMed: 38397196
DOI: 10.3390/genes15020206 -
JAMA Network Open Mar 2024Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by...
IMPORTANCE
Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes.
OBJECTIVE
To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts.
DESIGN, SETTING, AND PARTICIPANTS
This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023.
EXPOSURE
BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline.
MAIN OUTCOMES AND MEASURES
The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI.
RESULTS
Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11).
CONCLUSIONS AND RELEVANCE
This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.
Topics: Female; Male; Humans; Middle Aged; Body Mass Index; Ischemic Stroke; Cohort Studies; Retrospective Studies; Myocardial Infarction; Cholesterol, HDL
PubMed: 38512255
DOI: 10.1001/jamanetworkopen.2024.3062 -
Communications Biology Oct 2020Appendicular lean mass (ALM) is a heritable trait associated with loss of lean muscle mass and strength, or sarcopenia, but its genetic determinants are largely unknown....
Appendicular lean mass (ALM) is a heritable trait associated with loss of lean muscle mass and strength, or sarcopenia, but its genetic determinants are largely unknown. Here we conducted a genome-wide association study (GWAS) with 450,243 UK Biobank participants to uncover its genetic architecture. A total of 1059 conditionally independent variants from 799 loci were identified at the genome-wide significance level (p < 5 × 10), all of which were also significant at p < 5 × 10 in both sexes. These variants explained ~15.5% of the phenotypic variance, accounting for more than one quarter of the total ~50% GWAS-attributable heritability. There was no difference in genetic effect between sexes or among different age strata. Heritability was enriched in certain functional categories, such as conserved and coding regions, and in tissues related to the musculoskeletal system. Polygenic risk score prediction well distinguished participants with high and low ALM. The findings are important not only for lean mass but also for other complex diseases, such as type 2 diabetes, as ALM is shown to be a protective factor for type 2 diabetes.
Topics: Adult; Aged; Biological Specimen Banks; Diabetes Mellitus, Type 2; Female; Genetic Variation; Genome, Human; Genome-Wide Association Study; Humans; Male; Middle Aged; Muscle Strength; Muscle, Skeletal; Mutation; Obesity; Sarcopenia; United Kingdom
PubMed: 33097823
DOI: 10.1038/s42003-020-01334-0 -
Genes Jan 2024Hypertriglyceridemia is an exceptionally complex metabolic disorder characterized by elevated plasma triglycerides associated with an increased risk of acute... (Review)
Review
Hypertriglyceridemia is an exceptionally complex metabolic disorder characterized by elevated plasma triglycerides associated with an increased risk of acute pancreatitis and cardiovascular diseases such as coronary artery disease. Its phenotype expression is widely heterogeneous and heavily influenced by conditions as obesity, alcohol consumption, or metabolic syndromes. Looking into the genetic underpinnings of hypertriglyceridemia, this review focuses on the genetic variants in , , , and triglyceride-regulating genes reportedly associated with abnormal genetic transcription and the translation of proteins participating in triglyceride-rich lipoprotein metabolism. Hypertriglyceridemia resulting from such genetic abnormalities can be categorized as monogenic or polygenic. Monogenic hypertriglyceridemia, also known as familial chylomicronemia syndrome, is caused by homozygous or compound heterozygous pathogenic variants in the five canonical genes. Polygenic hypertriglyceridemia, also known as multifactorial chylomicronemia syndrome in extreme cases of hypertriglyceridemia, is caused by heterozygous pathogenic genetic variants with variable penetrance affecting the canonical genes, and a set of common non-pathogenic genetic variants (polymorphisms, using the former nomenclature) with well-established association with elevated triglyceride levels. We further address recent progress in triglyceride-lowering treatments. Understanding the genetic basis of hypertriglyceridemia opens new translational opportunities in the scope of genetic screening and the development of novel therapies.
Topics: Humans; Lipoprotein Lipase; Acute Disease; Pancreatitis; Hypertriglyceridemia; Triglycerides
PubMed: 38397180
DOI: 10.3390/genes15020190 -
Open Respiratory Archives 2023The circadian rhythm of sleep occurs in a cyclical 24-h pattern that is adjusted by the influence of several main synchronizers or "zeitgebers". The most powerful... (Review)
Review
The circadian rhythm of sleep occurs in a cyclical 24-h pattern that is adjusted by the influence of several main synchronizers or "zeitgebers". The most powerful synchronizer is the light-dark alternation, but also, socio-economic factors play a role, such as social and work relationships. Circadian rhythm regulation plays a crucial role in human health. This disruption of circadian rhythm can lead to increased incidence of diseases: diabetes, obesity, cancer, neurodegenerative diseases, increased risk of cardiovascular disease and stroke. Polygenic variations and environmental factors influence the circadian rhythm of each person. This is known as chronotype, which manifests itself as the degree of morning of evening preferences of each individual. There are indications to establish an association between individual chronotype preferences and the behavior of respiratory diseases.
PubMed: 37497245
DOI: 10.1016/j.opresp.2022.100228