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Lifestyle Genomics 2023Exposure to discrimination has emerged as a risk factor for obesity. It remains unclear, however, whether the genotype of the individual can modulate the sensitivity or... (Observational Study)
Observational Study
INTRODUCTION
Exposure to discrimination has emerged as a risk factor for obesity. It remains unclear, however, whether the genotype of the individual can modulate the sensitivity or response to discrimination exposure (gene × environment interaction) or increase the likelihood of experiencing discrimination (gene-environment correlation).
METHODS
This was an observational study of 4,102 white/European Americans in the Health and Retirement Study with self-reported, biological assessments, and genotyped data from 2006 to 2014. Discrimination was operationalized using the average of nine Everyday Discrimination Scale items. Polygenic risk scores (PRSs) for body mass index (BMI) and waist circumference (WC) were calculated using the weighted sum of risk alleles based on studies conducted by the Genetic Investigation of Anthropometric Traits (GIANT) consortium.
RESULTS
We found that greater PRS-BMI was significantly associated with more reports of discrimination (β = 0.04 ± 0.02; p = 0.037). Further analysis showed that measured BMI partially mediated the association between PRS-BMI and discrimination. There was no evidence that the association between discrimination and BMI, or the association between discrimination and WC, differed by PRS-BMI or PRS-WC, respectively.
CONCLUSION
Our findings suggest that individuals with genetic liability for obesity may experience greater discrimination in their lifetime, consistent with a gene-environment correlation hypothesis. There was no evidence of a gene-environment interaction. More genome-wide association studies in diverse populations are needed to improve generalizability of study findings. In the meantime, prevention and clinical intervention efforts that seek to reduce exposure to all forms of discrimination may help reduce obesity at the population level.
Topics: Humans; Gene-Environment Interaction; Genome-Wide Association Study; Genetic Predisposition to Disease; Obesity; Social Discrimination
PubMed: 36750036
DOI: 10.1159/000529527 -
JAMA Network Open Mar 2024Despite consistent public health recommendations, obesity rates in the US continue to increase. Physical activity recommendations do not account for individual genetic...
IMPORTANCE
Despite consistent public health recommendations, obesity rates in the US continue to increase. Physical activity recommendations do not account for individual genetic variability, increasing risk of obesity.
OBJECTIVE
To use activity, clinical, and genetic data from the All of Us Research Program (AoURP) to explore the association of genetic risk of higher body mass index (BMI) with the level of physical activity needed to reduce incident obesity.
DESIGN, SETTING, AND PARTICIPANTS
In this US population-based retrospective cohort study, participants were enrolled in the AoURP between May 1, 2018, and July 1, 2022. Enrollees in the AoURP who were of European ancestry, owned a personal activity tracking device, and did not have obesity up to 6 months into activity tracking were included in the analysis.
EXPOSURE
Physical activity expressed as daily step counts and a polygenic risk score (PRS) for BMI, calculated as weight in kilograms divided by height in meters squared.
MAIN OUTCOME AND MEASURES
Incident obesity (BMI ≥30).
RESULTS
A total of 3124 participants met inclusion criteria. Among 3051 participants with available data, 2216 (73%) were women, and the median age was 52.7 (IQR, 36.4-62.8) years. The total cohort of 3124 participants walked a median of 8326 (IQR, 6499-10 389) steps/d over a median of 5.4 (IQR, 3.4-7.0) years of personal activity tracking. The incidence of obesity over the study period increased from 13% (101 of 781) to 43% (335 of 781) in the lowest and highest PRS quartiles, respectively (P = 1.0 × 10-20). The BMI PRS demonstrated an 81% increase in obesity risk (P = 3.57 × 10-20) while mean step count demonstrated a 43% reduction (P = 5.30 × 10-12) when comparing the 75th and 25th percentiles, respectively. Individuals with a PRS in the 75th percentile would need to walk a mean of 2280 (95% CI, 1680-3310) more steps per day (11 020 total) than those at the 50th percentile to have a comparable risk of obesity. To have a comparable risk of obesity to individuals at the 25th percentile of PRS, those at the 75th percentile with a baseline BMI of 22 would need to walk an additional 3460 steps/d; with a baseline BMI of 24, an additional 4430 steps/d; with a baseline BMI of 26, an additional 5380 steps/d; and with a baseline BMI of 28, an additional 6350 steps/d.
CONCLUSIONS AND RELEVANCE
In this cohort study, the association between daily step count and obesity risk across genetic background and baseline BMI were quantified. Population-based recommendations may underestimate physical activity needed to prevent obesity among those at high genetic risk.
Topics: Female; Humans; Middle Aged; Male; Cohort Studies; Retrospective Studies; Population Health; Obesity; Exercise; Genetic Risk Score
PubMed: 38536175
DOI: 10.1001/jamanetworkopen.2024.3821 -
Advances in Nutrition (Bethesda, Md.) Mar 2018The increasing prevalence in polygenic diseases, such as obesity, cardiovascular disease, and type 2 diabetes, observed over the past few decades is more likely linked... (Review)
Review
The increasing prevalence in polygenic diseases, such as obesity, cardiovascular disease, and type 2 diabetes, observed over the past few decades is more likely linked to a rapid transition in lifestyle rather than to changes in the sequence of the nuclear genome. In the new era of precision medicine, nutritional genomics holds the promise to be translated into tailored nutritional strategies to prevent and manage polygenic diseases more effectively. Nutritional genomics aims to prevent, treat, and manage polygenic diseases through targeted therapies formulated from individuals' genetic makeup and dietary intake. Direct-to-consumer genetic testing (DTC-GT) has become commercially available to equip individuals with information on their genetic vulnerability to different diseases. This information may potentially prompt behavioral changes against adverse factors. However, scientific evidence behind the clinical recommendations is a matter of continuous debate, and behavioral modifications after disclosing genetic information remain inconclusive. In this review, we provide an overview of nutritional genomics and related nutritional DTC-GT services and discuss whether available data are sufficient to be translated into clinical recommendations and public health initiatives. Overall, the scientific evidence supporting the dissemination of genomic information for nutrigenomic purposes remains sparse. Therefore, additional knowledge needs to be generated, particularly for polygenic traits.
Topics: Cardiovascular Diseases; Diabetes Mellitus, Type 2; Direct-To-Consumer Screening and Testing; Genetic Testing; Genome, Human; Humans; Multifactorial Inheritance; Nutrigenomics; Obesity; Precision Medicine
PubMed: 29659694
DOI: 10.1093/advances/nmy001 -
Human Genetics Apr 2015Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although... (Review)
Review
Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.
Topics: Animals; Genetic Predisposition to Disease; Genome-Wide Association Study; Genomics; Genotype; Humans; Models, Genetic; Obesity
PubMed: 25687726
DOI: 10.1007/s00439-015-1533-x -
Progress in Molecular Biology and... 2016Obesity is a significant health problem in westernized societies, particularly in the United States where it has reached epidemic proportions in both adults and... (Review)
Review
Obesity is a significant health problem in westernized societies, particularly in the United States where it has reached epidemic proportions in both adults and children. The prevalence of childhood obesity has doubled in the past 30 years. The causation is complex with multiple sources, including an obesity promoting environment with plentiful highly dense food sources and overall decreased physical activity noted for much of the general population, but genetic factors clearly play a role. Advances in genetic technology using candidate gene approaches, genome-wide association studies, structural and expression microarrays, and next generation sequencing have led to the discovery of hundreds of genes recognized as contributing to obesity. Polygenic and monogenic causes of obesity are now recognized including dozens of examples of syndromic obesity with Prader-Willi syndrome, as a classical example and recognized as the most common known cause of life-threatening obesity. Genetic factors playing a role in the causation of obesity will be discussed along with the growing evidence of single genes and the continuum between monogenic and polygenic obesity. The clinical and genetic aspects of four classical but rare obesity-related syndromes (ie, Prader-Willi, Alström, fragile X, and Albright hereditary osteodystrophy) will be described and illustrated in this review of single gene and syndromic causes of obesity.
Topics: Adult; Genetic Diseases, Inborn; Genetic Diseases, X-Linked; Genome-Wide Association Study; High-Throughput Nucleotide Sequencing; Humans; Obesity; Prader-Willi Syndrome
PubMed: 27288824
DOI: 10.1016/bs.pmbts.2015.12.003 -
Abdominal obesity is a more important causal risk factor for pancreatic cancer than overall obesity.European Journal of Human Genetics :... Aug 2023Obesity and type 2 diabetes (T2D) are associated with increased risk of pancreatic cancer. Here we assessed the relationship between pancreatic cancer and two distinct...
Obesity and type 2 diabetes (T2D) are associated with increased risk of pancreatic cancer. Here we assessed the relationship between pancreatic cancer and two distinct measures of obesity, namely total adiposity, using BMI, versus abdominal adiposity, using BMI adjusted waist-to-hip ratio (WHRadjBMI) by utilising polygenic scores (PGS) and Mendelian randomisation (MR) analyses. We constructed z-score weighted PGS for BMI and WHRadjBMI using publicly available data and tested for their association with pancreatic cancer defined in UK biobank (UKBB). Using publicly available summary statistics, we then performed bi-directional MR analyses between the two obesity traits and pancreatic cancer. PGS was significantly (multiple testing-corrected) associated with pancreatic cancer (OR[95%CI] = 1.0804[1.025-1.14], P = 0.0037). The significance of association declined after T2D adjustment (OR[95%CI] = 1.073[1.018-1.13], P = 0.00904). PGS association with pancreatic cancer was at the margin of statistical significance (OR[95%CI] = 1.047[0.99-1.104], P = 0.086). T2D adjustment effectively lost any suggestive association of PGS with pancreatic cancer (OR[95%CI] = 1.039[0.99-1.097], P = 0.14). MR analyses showed a nominally significant causal effect of WHRadjBMI on pancreatic cancer (OR[95%CI] = 1.00095[1.00011-1.0018], P = 0.027) but not for BMI on pancreatic cancer. Overall, we show that abdominal adiposity measured using WHRadjBMI, may be a more important causal risk factor for pancreatic cancer compared to total adiposity, with T2D being a potential driver of this relationship.
Topics: Humans; Diabetes Mellitus, Type 2; Obesity, Abdominal; Body Mass Index; Obesity; Risk Factors; Adiposity; Pancreatic Neoplasms; Genome-Wide Association Study
PubMed: 37161092
DOI: 10.1038/s41431-023-01301-3 -
EBioMedicine Oct 2022Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations...
BACKGROUND
Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations between OSA and related phenotypes.
METHODS
In the Hispanic Community Healthy Study/Study of Latinos, we estimated genetic correlations ρ between the respiratory event index (REI) and 54 anthropometric, glycemic, cardiometabolic, and pulmonary phenotypes. We used summary statistics from published genome-wide association studies to construct Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated phenotype (ρ>0.2 and p-value<0.05), and of OSA. We studied the association of the PRSs of the correlated phenotypes with both REI and OSA (REI≥5), and the association of OSA PRS with the correlated phenotypes. Causal relationships were tested using Mendelian Randomization (MR) analysis.
FINDINGS
The dataset included 11,155 participants, 31.03% with OSA. 22 phenotypes were genetically correlated with REI. 10 PRSs covering obesity and fat distribution (BMI, WHR, WHRadjBMI), blood pressure (DBP, PP, MAP), glycaemic control (fasting insulin, HbA1c, HOMA-B) and insomnia were associated with REI and/or OSA. OSA PRS was associated with BMI, WHR, DBP and glycaemic traits (fasting insulin, HbA1c, HOMA-B and HOMA-IR). MR analysis identified robust causal effects of BMI and WHR on OSA, and probable causal effects of DBP, PP, and HbA1c on OSA/REI.
INTERPRETATION
There are shared genetic underpinnings of anthropometric, blood pressure, and glycaemic phenotypes with OSA, with evidence for causal relationships between some phenotypes.
FUNDING
Described in Acknowledgments.
Topics: Blood Glucose; Body Mass Index; Cardiovascular Diseases; Genome-Wide Association Study; Glycated Hemoglobin; Humans; Insulin; Phenotype; Sleep Apnea, Obstructive
PubMed: 36174398
DOI: 10.1016/j.ebiom.2022.104288 -
Annual Review of Nutrition Oct 2021Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and...
Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the involvement of the circadian clock in sleep and metabolism, few shared genes, including , were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring. Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. In addition, bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity,but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited.
Topics: Alpha-Ketoglutarate-Dependent Dioxygenase FTO; Body Mass Index; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Obesity; Sleep
PubMed: 34102077
DOI: 10.1146/annurev-nutr-082018-124258 -
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 -
Clinical Therapeutics Mar 2021The prevalence of nonalcoholic fatty liver disease (NAFLD) has been increasing over the years and is now as high in Asia as in the Western world, so much so that it... (Review)
Review
The prevalence of nonalcoholic fatty liver disease (NAFLD) has been increasing over the years and is now as high in Asia as in the Western world, so much so that it should no longer be considered a Western disease. In fact, China is expected to have the largest increase in the number of NAFLD cases in the coming years. The increase in prevalence of NAFLD in Asia lags behind that of the Western world; thus, there will be a lag in more severe liver disease in Asia despite a similar prevalence of the disease. NAFLD is more prevalent among patients with diabetes mellitus, which is also an important risk factor for more severe liver disease. Patients with diabetes mellitus thus represent an important target for screening for NAFLD and more severe liver disease. Although the PNPLA3 gene polymorphism is the most studied in NAFLD, it is increasingly clear that the cumulative effect of multiple genes likely predisposes to NAFLD and more severe liver disease in the different ethnic groups, and polygenic risk scores are emerging. Lean NAFLD has been largely reported in Asia but is increasingly recognized worldwide. Multiple risk factors have been identified for the disease that manifests in metabolically unhealthy normal weight individuals; however, it responds to lifestyle intervention, similar to the disease in obese individuals. Lastly, the newer term "metabolic dysfunction-associated fatty liver disease" provides a more accurate reflection of the disease, giving more focus to clinicians and researchers in tackling this increasingly common and challenging disease.
Topics: Diabetes Mellitus; Humans; Liver; Non-alcoholic Fatty Liver Disease; Obesity; Prevalence; Risk Factors
PubMed: 33526312
DOI: 10.1016/j.clinthera.2021.01.007