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Trends in Cognitive Sciences May 2017Recent work highlights the importance of genetic variants that influence brain structure and function in conferring risk for polygenic obesity. The neurotransmitter... (Review)
Review
Recent work highlights the importance of genetic variants that influence brain structure and function in conferring risk for polygenic obesity. The neurotransmitter dopamine (DA) has a pivotal role in energy balance by integrating metabolic signals with circuits supporting cognitive, perceptual, and appetitive functions that guide feeding. It has also been established that diet and obesity alter DA signaling, leading to compulsive-like feeding and neurocognitive impairments. This raises the possibility that genetic variants that influence DA signaling and adaptation confer risk for overeating and cognitive decline. Here, we consider the role of two common gene variants, FTO and TaqIA rs1800497 in driving gene × environment interactions promoting obesity, metabolic dysfunction, and cognitive change via their influence on DA receptor subtype 2 (DRD2) signaling.
Topics: Alpha-Ketoglutarate-Dependent Dioxygenase FTO; Dopamine; Gene-Environment Interaction; Genetic Predisposition to Disease; Humans; Obesity; Protein Serine-Threonine Kinases; Receptors, Dopamine D2
PubMed: 28372879
DOI: 10.1016/j.tics.2017.03.004 -
Molecular Psychiatry Mar 2021There is an extensive body of literature linking ADHD to overweight and obesity. Research indicates that impulsivity features of ADHD account for a degree of this...
There is an extensive body of literature linking ADHD to overweight and obesity. Research indicates that impulsivity features of ADHD account for a degree of this overlap. The neural and polygenic correlates of this association have not been thoroughly examined. In participants of the IMAGEN study, we found that impulsivity symptoms and body mass index (BMI) were associated (r = 0.10, n = 874, p = 0.014 FWE corrected), as were their respective polygenic risk scores (PRS) (r = 0.17, n = 874, p = 6.5 × 10 FWE corrected). We then examined whether the phenotypes of impulsivity and BMI, and the PRS scores of ADHD and BMI, shared common associations with whole-brain grey matter and the Monetary Incentive Delay fMRI task, which associates with reward-related impulsivity. A sparse partial least squared analysis (sPLS) revealed a shared neural substrate that associated with both the phenotypes and PRS scores. In a last step, we conducted a bias corrected bootstrapped mediation analysis with the neural substrate score from the sPLS as the mediator. The ADHD PRS associated with impulsivity symptoms (b = 0.006, 90% CIs = 0.001, 0.019) and BMI (b = 0.009, 90% CIs = 0.001, 0.025) via the neuroimaging substrate. The BMI PRS associated with BMI (b = 0.014, 95% CIs = 0.003, 0.033) and impulsivity symptoms (b = 0.009, 90% CIs = 0.001, 0.025) via the neuroimaging substrate. A common neural substrate may (in part) underpin shared genetic liability for ADHD and BMI and the manifestation of their (observable) phenotypic association.
Topics: Attention Deficit Disorder with Hyperactivity; Body Mass Index; Humans; Impulsive Behavior; Multifactorial Inheritance; Reward
PubMed: 31227801
DOI: 10.1038/s41380-019-0444-y -
Nutrients Jun 2023Obesity 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.... (Review)
Review
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.
Topics: Adult; Child; Adolescent; Humans; United States; Diabetes Mellitus, Type 2; Obesity; Overweight; Body Weight; Life Style
PubMed: 37375686
DOI: 10.3390/nu15122782 -
Current Cardiology Reports Oct 2020Obesity is a significant international public health epidemic with major downstream consequences on morbidity and mortality. While lifestyle factors contribute, there is... (Review)
Review
PURPOSE OF REVIEW
Obesity is a significant international public health epidemic with major downstream consequences on morbidity and mortality. While lifestyle factors contribute, there is an evolving understanding of genomic and metabolomic pathways involved with obesity and its relationship with cardiometabolic risk. This review will provide an overview of some of these important findings from both a biologic and clinical perspective.
RECENT FINDINGS
Recent studies have identified polygenic risk scores and metabolomic biomarkers of obesity and related outcomes, which have also highlighted biological pathways, such as the branched-chain amino acid (BCAA) pathway that is dysregulated in this disease. These biomarkers may help in personalizing obesity interventions and for mitigation of future cardiometabolic risk. A multifaceted approach is necessary to impact the growing epidemic of obesity and related diseases. This will likely include incorporating precision medicine approaches with genomic and metabolomic biomarkers to personalize interventions and improve risk prediction.
Topics: Amino Acids, Branched-Chain; Biomarkers; Cardiovascular Diseases; Genomics; Humans; Metabolomics; Obesity
PubMed: 33040225
DOI: 10.1007/s11886-020-01422-x -
Journal of Affective Disorders Sep 2022Bipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic... (Review)
Review
BACKGROUND
Bipolar disorder (BD) presents with high obesity and type 2 diabetes (T2D) and pathophysiological and phenomenological abnormalities shared with cardiometabolic disorders. Genomic studies may help define if they share genetic liability. This selective review of BD with obesity and T2D will focus on genomic studies, stress their current limitations and guide future steps in developing the field.
METHODS
We searched electronic databases (PubMed, Scopus) until December 2021 to identify genome-wide association studies, polygenic risk score analyses, and functional genomics of BD accounting for body mass index (BMI), obesity, or T2D.
RESULTS
The first genome-wide association studies (GWAS) of BD accounting for obesity found a promising genome-wide association in an intronic gene variant of TCF7L2 that was further replicated. Polygenic risk scores of obesity and T2D have also been associated with BD, yet, no genetic correlations have been demonstrated. Finally, human-induced stem cell studies of the intronic variant in TCF7L2 show a potential biological impact of the products of this genetic variant in BD risk.
LIMITATIONS
The narrative nature of this review.
CONCLUSIONS
Findings from BD GWAS accounting for obesity and their functional testing, have prompted potential biological insights. Yet, BD, obesity, and T2D display high phenotypic, genetic, and population-related heterogeneity, limiting our ability to detect genetic associations. Further studies should refine cardiometabolic phenotypes, test gene-environmental interactions and add population diversity.
Topics: Bipolar Disorder; Cardiovascular Diseases; Diabetes Mellitus, Type 2; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Obesity; Polymorphism, Single Nucleotide
PubMed: 35780966
DOI: 10.1016/j.jad.2022.06.084 -
MedRxiv : the Preprint Server For... Jun 2023Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse...
Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings.
PubMed: 37333246
DOI: 10.1101/2023.05.25.23290535 -
The Journals of Gerontology. Series B,... Jan 2021To examine the relationship between obesity and mortality as a function of polygenic risk for obesity among older U.S. adults.
OBJECTIVES
To examine the relationship between obesity and mortality as a function of polygenic risk for obesity among older U.S. adults.
METHOD
Using data from the 1994-2014 Health and Retirement Study in conjunction with genome-wide data, we evaluated the risk of mortality as a function of obesity classification, an individual's polygenic risk score (PGS) for obesity, and their interaction, stratified by sex. We conducted our analyses using cox proportional hazard models.
RESULTS
Among those with an average PGS for obesity (8,143 [68.8%]), obese I (hazard ratio [HR] = 0.79, p = .336) adults show no difference in their risk for mortality and obese II/III (HR = 3.17, p = .000) adults present higher risk of mortality relative to non-obese adults. The interaction of obesity classification and PGS suggests that obese II/III respondents with low PGS in the total sample (HR = 2.71, p = .006) and among women (HR = 3.02, p = .023) are at significantly higher risk of death when compared to obese II/III respondents with average or high PGS.
DISCUSSION
We posit that these findings suggest that the pathway to obesity, in this case, more socio-behavioral rather than genetic, may influence subsequent risk of death in older adults. We suggest that practitioners and population researchers be mindful of these pathways as to better identify and understand mortality risk.
Topics: Body Mass Index; Female; Humans; Life Style; Male; Middle Aged; Mortality; Multifactorial Inheritance; Obesity; Proportional Hazards Models; Psychology, Social; Risk Assessment; Risk Factors; Severity of Illness Index; Sex Factors; Social Factors; United States
PubMed: 31805181
DOI: 10.1093/geronb/gbz156 -
Biomedicines Jan 2023Nonalcoholic fatty liver disease (NAFLD) is a common chronic condition associated with genetic and environmental factors in which fat abnormally accumulates in the... (Review)
Review
Nonalcoholic fatty liver disease (NAFLD) is a common chronic condition associated with genetic and environmental factors in which fat abnormally accumulates in the liver. NAFLD is epidemiologically associated with obesity, type 2 diabetes, and dyslipidemia. Environmental factors, such as physical inactivity and an unbalanced diet, interact with genetic factors, such as epigenetic mechanisms and polymorphisms for the genesis and development of the condition. Different genetic polymorphisms seem to be involved in this context, including variants in PNPLA3, TM6SF2, PEMT, and CHDH genes, playing a role in the disease's susceptibility, development, and severity. From carbohydrate intake and weight loss to omega-3 supplementation and caloric restriction, different dietary and nutritional factors appear to be involved in controlling the onset and progression of NAFLD conditions influencing metabolism, gene, and protein expression. The polygenic risk score represents a sum of trait-associated alleles carried by an individual and seems to be associated with NAFLD outcomes depending on the dietary context. Understanding the exact extent to which lifestyle interventions and genetic predispositions can play a role in the prevention and management of NAFLD can be crucial for the establishment of a personalized and integrative approach to patients.
PubMed: 36830856
DOI: 10.3390/biomedicines11020319 -
JAMA Cardiology Jul 2022Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in young people. Although rare genetic variants are well-established contributors to HCM...
IMPORTANCE
Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in young people. Although rare genetic variants are well-established contributors to HCM risk, common genetic variants have recently been implicated in disease pathogenesis.
OBJECTIVE
To assess the contributions of rare and common genetic variation to risk of HCM in the general population.
DESIGN, SETTING, AND PARTICIPANTS
This cohort study of the UK Biobank (data from 2006-2010) and the Mass General Brigham Biobank (2010-2019) assessed the relative and joint contributions of rare genetic variants and a common variant (polygenic) score to risk of HCM. Both rare and common variant predictors were then evaluated in the context of relevant clinical risk factors. Data analysis was conducted from May 2021 to February 2022.
EXPOSURES
Pathogenic rare variants, common-variant (polygenic) score, and clinical risk factors.
MAIN OUTCOMES AND MEASURES
Risk of HCM.
RESULTS
The primary study population comprised 184 511 individuals from the UK Biobank. Mean (SD) age was 56 (8) years, 83 690 (45%) of participants were men, and 204 (0.1%) participants had HCM. Of 51 genes included in clinical genetic testing panels for HCM, pathogenic or likely pathogenic variants in 14 core genes (designated by the American College of Medical Genetics and Genomics [ACMG]) were associated with 55-fold higher odds (95% CI, 35-83) of HCM, while those in the remaining 37 non-ACMG genes were not significantly associated with HCM (OR, 1.8; 95% CI, 0.6-4.0). ClinVar pathogenic or likely pathogenic mutations in MYBPC3 (OR, 72; 95% CI, 39-124) and MYH7 (OR, 61; 95% CI, 26-121) were strongly associated with HCM, as were loss-of-function variants in ALPK3 (OR, 13; 95% CI, 4.4-28). A polygenic score was strongly associated with HCM (OR per SD increase in score, 1.6; 95% CI, 1.4-1.8), with concordant results in the Mass General Brigham Biobank. Genetic factors enhanced clinical risk prediction for HCM: addition of rare variant carrier status and the polygenic score to clinical risk factors (obesity, hypertension, atrial fibrillation, and coronary artery disease) improved the area under the receiver operator characteristic curve from 0.71 (95% CI, 0.65-0.77) to 0.82 (95% CI, 0.77-0.87).
CONCLUSIONS AND RELEVANCE
Both rare and common genetic variants contribute substantially to HCM susceptibility in the general population and improve HCM risk prediction beyond that achieved with clinical factors.
Topics: Adolescent; Biological Specimen Banks; Cardiomyopathy, Hypertrophic; Cohort Studies; Death, Sudden, Cardiac; Female; Humans; Male; Middle Aged; Mutation
PubMed: 35583889
DOI: 10.1001/jamacardio.2022.1061 -
Circulation. Genomic and Precision... Jun 2018Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance... (Review)
Review
Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.
Topics: Diabetes Mellitus, Type 2; Genetic Predisposition to Disease; Genetic Variation; Genome-Wide Association Study; Humans; Obesity; Risk Factors
PubMed: 29899044
DOI: 10.1161/CIRCGEN.118.002090