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Chest Jan 2021There is an unclear relationship of obesity to the pathogenesis and severity of pulmonary arterial hypertension (PAH) and pulmonary venous hypertension (PVH).
BACKGROUND
There is an unclear relationship of obesity to the pathogenesis and severity of pulmonary arterial hypertension (PAH) and pulmonary venous hypertension (PVH).
RESEARCH QUESTION
Is BMI casually associated with pulmonary artery pressure (PAP) and/or markers of pulmonary vascular remodeling?
STUDY DESIGN AND METHODS
The study design was a two-sample inverse-variance weighted Mendelian randomization. We constructed two BMI genetic risk scores from genome-wide association study summary data and deployed them in nonoverlapping cohorts of subjects referred for right heart catheterization (RHC) or echocardiography. A BMI highly polygenic risk score (hpGRS) optimally powered to detect shared genetic architecture of obesity with other traits was tested for association with RHC parameters including markers of pulmonary vascular remodeling. A BMI strict genetic risk score (sGRS) composed of high-confidence genetic variants was used for Mendelian randomization analyses to assess if higher BMI causes higher PAP.
RESULTS
Among all subjects, both directly measured BMI and hpGRS were positively associated with pulmonary arterial pressures but not markers of pulmonary vascular remodeling. Categorical analyses revealed BMI and hpGRS were associated with PVH but not PAH. Mendelian randomization of the sGRS supported that higher BMI is causal of higher systolic pulmonary artery pressure (sPAP). Sensitivity analyses showed sPAP-BMI sGRS relationship was preserved when either individuals with PAH or PVH were excluded. In the echocardiographic cohort, BMI and hpGRS were positively associated with estimated PAP and markers of left heart remodeling.
INTERPRETATION
BMI is a modifier of pulmonary hypertension severity in both PAH and PVH but is only involved in the pathogenesis of PVH.
Topics: Aged; Body Mass Index; Causality; Cohort Studies; Female; Genome-Wide Association Study; Humans; Male; Mendelian Randomization Analysis; Middle Aged; Obesity; Pulmonary Arterial Hypertension; Pulmonary Artery; Risk Factors; Vascular Remodeling
PubMed: 32712226
DOI: 10.1016/j.chest.2020.07.038 -
Frontiers in Oncology 2023Pancreatic ductal adenocarcinoma (PDAC) is lethal due to its late diagnosis and lack of successful treatments. A possible strategy to reduce its death burden is...
INTRODUCTION
Pancreatic ductal adenocarcinoma (PDAC) is lethal due to its late diagnosis and lack of successful treatments. A possible strategy to reduce its death burden is prevention. Intraductal papillary mucinous neoplasms (IPMNs) are precursors of PDAC. It is difficult to estimate the incidence of IPMNs because they are asymptomatic. Two recent studies reported pancreatic cysts in 3% and 13% of scanned subjects. The possibility of identifying a subgroup of IPMN patients with a higher probability of progression into cancer could be instrumental in increasing the survival rate. In this study, genetic and non-genetic PDAC risk factors were tested in a group of IPMN patients under surveillance.
METHODS
A retrospective study was conducted on 354 IPMN patients enrolled in two Italian centres with an average follow-up of 64 months. With the use of DNA extracted from blood, collected at IPMN diagnosis, all patients were genotyped for 30 known PDAC risk loci. The polymorphisms were analysed individually and grouped in an unweighted polygenic score (PGS) in relation to IPMN progression. The ABO blood group and non-genetic PDAC risk factors were also analysed. IPMN progression was defined based on the development of worrisome features and/or high-risk stigmata during follow-up.
RESULTS
Two genetic variants (rs1517037 and rs10094872) showed suggestive associations with an increment of IPMN progression. After correction for multiple testing, using the Bonferroni correction, none of the variants showed a statistically significant association. However, associations were observed for the non-genetic variables, such as smoking status, comparing heavy smokers with light smokers (HR = 3.81, 95% 1.43-10.09, = 0.007), and obesity (HR = 2.46, 95% CI 1.22-4.95, = 0.012).
CONCLUSION
In conclusion, this study is the first attempt to investigate the presence of shared genetic background between PDAC risk and IPMN progression; however, the results suggest that the 30 established PDAC susceptibility polymorphisms are not associated with clinical IPMN progression in a sample of 354 patients. However, we observed indications of cigarette smoking and body mass index (BMI) involvement in IPMN progression. The biological mechanism that could link these two risk factors to progression could be chronic inflammation, of which both smoking and obesity are strong promoters.
PubMed: 37346070
DOI: 10.3389/fonc.2023.1172606 -
International Journal of Obesity (2005) Jun 2021Childhood obesity is a complex multifaceted condition, which is influenced by genetics, environmental factors, and their interaction. However, these interactions have...
BACKGROUND
Childhood obesity is a complex multifaceted condition, which is influenced by genetics, environmental factors, and their interaction. However, these interactions have mainly been studied in twin studies and evidence from population-based cohorts is limited. Here, we analyze the interaction of an obesity-related genome-wide polygenic risk score (PRS) with sociodemographic and lifestyle factors for BMI and waist circumference (WC) in European children and adolescents.
METHODS
The analyses are based on 8609 repeated observations from 3098 participants aged 2-16 years from the IDEFICS/I.Family cohort. A genome-wide polygenic risk score (PRS) was calculated using summary statistics from independent genome-wide association studies of BMI. Associations were estimated using generalized linear mixed models adjusted for sex, age, region of residence, parental education, dietary intake, relatedness, and population stratification.
RESULTS
The PRS was associated with BMI (beta estimate [95% confidence interval (95%-CI)] = 0.33 [0.30, 0.37], r = 0.11, p value = 7.9 × 10) and WC (beta [95%-CI] = 0.36 [0.32, 0.40], r = 0.09, p value = 1.8 × 10). We observed significant interactions with demographic and lifestyle factors for BMI as well as WC. Children from Southern Europe showed increased genetic liability to obesity (BMI: beta [95%-CI] = 0.40 [0.34, 0.45]) in comparison to children from central Europe (beta [95%-CI] = 0.29 [0.23, 0.34]), p-interaction = 0.0066). Children of parents with a low level of education showed an increased genetic liability to obesity (BMI: beta [95%-CI] = 0.48 [0.38, 0.59]) in comparison to children of parents with a high level of education (beta [95%-CI] = 0.30 [0.26, 0.34]), p-interaction = 0.0012). Furthermore, the genetic liability to obesity was attenuated by a higher intake of fiber (BMI: beta [95%-CI] interaction = -0.02 [-0.04,-0.01]) and shorter screen times (beta [95%-CI] interaction = 0.02 [0.00, 0.03]).
CONCLUSIONS
Our results highlight that a healthy childhood environment might partly offset a genetic predisposition to obesity during childhood and adolescence.
Topics: Adolescent; Child; Child, Preschool; Cohort Studies; Europe; Female; Genome-Wide Association Study; Humans; Life Style; Male; Pediatric Obesity; Social Factors
PubMed: 33753884
DOI: 10.1038/s41366-021-00795-5 -
Methodist DeBakey Cardiovascular Journal 2021Familial hypercholesterolemia (FH) is a monogenic form of severe hypercholesterolemia that, if left untreated, is associated with early onset of atherosclerosis. FH... (Review)
Review
Familial hypercholesterolemia (FH) is a monogenic form of severe hypercholesterolemia that, if left untreated, is associated with early onset of atherosclerosis. FH derives from genetic variants that lead to inefficient hepatic clearance of low-density lipoprotein (LDL) particles from the circulation. The FH phenotype is encountered in approximately 1 of every 300 people. The risk of atherosclerotic cardiovascular disease (ASCVD) is higher in those with FH than in normolipidemic individuals and in those with polygenic hypercholesterolemia. FH is usually diagnosed by clinical scores that consider hypercholesterolemia, family history of early ASCVD and hypercholesterolemia, and cutaneous stigmata. Genetic diagnosis is important and should be offered to individuals suspected of FH. Family cascade screening is important to identify asymptomatic hypercholesterolemic individuals. Despite the high risk of ASCVD, this risk is heterogenous in heterozygous FH and depends not only on high LDL cholesterol (LDL-C) but also on other risk biomarkers. Risk can be evaluated by considering biomarkers such as male sex, late-onset therapy (> age 40), LDL-C > 310 mg/dL, low high-density lipoprotein cholesterol, elevated lipoprotein(a), obesity, diabetes, and hypertension by using specific risk equations and by detecting subclinical coronary atherosclerosis. Statins are the main therapy for FH and change the natural history of ASCVD; however, most individuals persist with elevated LDL-C. PCSK9 inhibitors provide robust and safe LDL-C lowering in FH, although elevated costs preclude their widespread use. Newer therapies such as ANGPTL3 inhibitors add intensive LDL-C lowering for refractory forms of FH. Finally, while it is possible to normalize LDL-C in people with FH, the disease unfortunately is still severely underdiagnosed and undertreated.
Topics: Adult; Angiopoietin-Like Protein 3; Angiopoietin-like Proteins; Cholesterol, LDL; Humans; Hyperlipoproteinemia Type II; Male; Proprotein Convertase 9; Risk Factors
PubMed: 34824679
DOI: 10.14797/mdcvj.887 -
The European Respiratory Journal Oct 2021Lung function is a heritable complex phenotype with obesity being one of its important risk factors. However, knowledge of their shared genetic basis is limited. Most...
BACKGROUND
Lung function is a heritable complex phenotype with obesity being one of its important risk factors. However, knowledge of their shared genetic basis is limited. Most genome-wide association studies (GWASs) for lung function have been based on European populations, limiting the generalisability across populations. Large-scale lung function GWASs in other populations are lacking.
METHODS
We included 100 285 subjects from the China Kadoorie Biobank (CKB). To identify novel loci for lung function, single-trait GWAS analyses were performed on forced expiratory volume in 1 s (FEV), forced vital capacity (FVC) and FEV/FVC in the CKB. We then performed genome-wide cross-trait analysis between lung function and obesity traits (body mass index (BMI), BMI-adjusted waist-to-hip ratio and BMI-adjusted waist circumference) to investigate the shared genetic effects in the CKB. Finally, polygenic risk scores (PRSs) of lung function were developed in the CKB and their interaction with BMI's association on lung function were examined. We also conducted cross-trait analysis in parallel with the CKB using up to 457 756 subjects from the UK Biobank (UKB) for replication and investigation of ancestry-specific effects.
RESULTS
We identified nine genome-wide significant novel loci for FEV, six for FVC and three for FEV/FVC in the CKB. FEV and FVC showed significant negative genetic correlation with obesity traits in both the CKB and UKB. Genetic loci shared between lung function and obesity traits highlighted important biological pathways, including cell proliferation, embryo, skeletal and tissue development, and regulation of gene expression. Mendelian randomisation analysis suggested significant negative causal effects of BMI on FEV and on FVC in both the CKB and UKB. Lung function PRSs significantly modified the effect of change in BMI on change in lung function during an average follow-up of 8 years.
CONCLUSION
This large-scale GWAS of lung function identified novel loci and shared genetic aetiology between lung function and obesity. Change in BMI might affect change in lung function differently according to a subject's polygenic background. These findings may open new avenues for the development of molecular-targeted therapies for obesity and lung function improvement.
Topics: Body Mass Index; China; Forced Expiratory Volume; Genome-Wide Association Study; Humans; Lung; Obesity; Polymorphism, Single Nucleotide
PubMed: 33766948
DOI: 10.1183/13993003.00199-2021 -
The Lancet. Global Health Mar 2023Across the life course, socioeconomic disadvantage disproportionately afflicts those with genetic predispositions to inflammatory diseases. We describe how socioeconomic...
BACKGROUND
Across the life course, socioeconomic disadvantage disproportionately afflicts those with genetic predispositions to inflammatory diseases. We describe how socioeconomic disadvantage and polygenic risk for high BMI magnify the risk of obesity across childhood, and using causal analyses, explore the hypothetical impact of intervening on socioeconomic disadvantage to reduce adolescent obesity.
METHODS
Data were drawn from a nationally representative Australian birth cohort, with biennial data collection between 2004 and 2018 (research and ethics committee approved). We generated a polygenic risk score for BMI using published genome-wide association studies. We measured early-childhood disadvantage (age 2-3 years) with a neighbourhood census-based measure and a family-level composite of parent income, occupation, and education. We used generalised linear regression (Poisson-log link) to estimate the risk of overweight or obesity (BMI ≥85th percentile) at age 14-15 years for children with early-childhood disadvantage (quintiles 4-5) versus average (quintile 3) and least disadvantage (quintiles 1-2), for those with high and low polygenic risk separately.
FINDINGS
For 1607 children (n=796 female, n=811 male; 31% of the original cohort [N=5107]), polygenic risk and disadvantage were both associated with overweight or obesity; effects of disadvantage were more marked as polygenic risk increased. Of children with polygenic risk higher than the median (n=805), 37% of children living in disadvantage at age 2-3 years had an overweight or obese BMI by adolescence, compared with 26% of those with least disadvantage. For genetically vulnerable children, causal analyses indicated that early neighbourhood intervention to lessen disadvantage (to quintile 1-2) would reduce risk of adolescent overweight or obesity by 23% (risk ratio 0·77; 95% CI 0·57-1·04); estimates for improving family environments were similar (0·59; 0·43-0·80).
INTERPRETATION
Actions addressing socioeconomic disadvantage could mitigate polygenic risk for developing obesity. This study benefits from population-representative longitudinal data but is limited by sample size.
FUNDING
Australian National Health and Medical Research Council.
Topics: Child; Adolescent; Female; Male; Humans; Child, Preschool; Overweight; Cohort Studies; Pediatric Obesity; Body Mass Index; Genome-Wide Association Study; Socioeconomic Disparities in Health; Australia
PubMed: 36866486
DOI: 10.1016/S2214-109X(23)00094-3 -
Diabetologia Sep 2023Low birthweight is a risk factor for type 2 diabetes but it is unknown whether low birthweight is associated with distinct clinical characteristics at disease onset. We...
AIMS/HYPOTHESIS
Low birthweight is a risk factor for type 2 diabetes but it is unknown whether low birthweight is associated with distinct clinical characteristics at disease onset. We examined whether a lower or higher birthweight in type 2 diabetes is associated with clinically relevant characteristics at disease onset.
METHODS
Midwife records were traced for 6866 individuals with type 2 diabetes in the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) cohort. Using a cross-sectional design, we assessed age at diagnosis, anthropomorphic measures, comorbidities, medications, metabolic variables and family history of type 2 diabetes in individuals with the lowest 25% of birthweight (<3000 g) and highest 25% of birthweight (>3700 g), compared with a birthweight of 3000-3700 g as reference, using log-binomial and Poisson regression. Continuous relationships across the entire birthweight spectrum were assessed with linear and restricted cubic spline regression. Weighted polygenic scores (PS) for type 2 diabetes and birthweight were calculated to assess the impact of genetic predispositions.
RESULTS
Each 1000 g decrease in birthweight was associated with a 3.3 year (95% CI 2.9, 3.8) younger age of diabetes onset, 1.5 kg/m (95% CI 1.2, 1.7) lower BMI and 3.9 cm (95% CI 3.3, 4.5) smaller waist circumference. Compared with the reference birthweight, a birthweight of <3000 g was associated with more overall comorbidity (prevalence ratio [PR] for Charlson Comorbidity Index Score ≥3 was 1.36 [95% CI 1.07, 1.73]), having a systolic BP ≥155 mmHg (PR 1.26 [95% CI 0.99, 1.59]), lower prevalence of diabetes-associated neurological disease, less likelihood of family history of type 2 diabetes, use of three or more glucose-lowering drugs (PR 1.33 [95% CI 1.06, 1.65]) and use of three or more antihypertensive drugs (PR 1.09 [95% CI 0.99, 1.20]). Clinically defined low birthweight (<2500 g) yielded stronger associations. Most associations between birthweight and clinical characteristics appeared linear, and a higher birthweight was associated with characteristics mirroring lower birthweight in opposite directions. Results were robust to adjustments for PS representing weighted genetic predisposition for type 2 diabetes and birthweight.
CONCLUSION/INTERPRETATION
Despite younger age at diagnosis, and fewer individuals with obesity and family history of type 2 diabetes, a birthweight <3000 g was associated with more comorbidities, including a higher systolic BP, as well as with greater use of glucose-lowering and antihypertensive medications, in individuals with recently diagnosed type 2 diabetes.
Topics: Humans; Diabetes Mellitus, Type 2; Birth Weight; Cross-Sectional Studies; Risk Factors; Genetic Predisposition to Disease; Glucose
PubMed: 37303007
DOI: 10.1007/s00125-023-05936-1 -
International Journal of Epidemiology Oct 2022We aimed to identify clinical, socio-demographic and genetic risk factors for severe COVID-19 (hospitalization, critical care admission or death) in the general... (Observational Study)
Observational Study
BACKGROUND
We aimed to identify clinical, socio-demographic and genetic risk factors for severe COVID-19 (hospitalization, critical care admission or death) in the general population.
METHODS
In this observational study, we identified 9560 UK Biobank participants diagnosed with COVID-19 during 2020. A polygenic risk score (PRS) for severe COVID-19 was derived and optimized using publicly available European and trans-ethnic COVID-19 genome-wide summary statistics. We estimated the risk of hospital or critical care admission within 28 days or death within 100 days following COVID-19 diagnosis, and assessed associations with socio-demographic factors, immunosuppressant use and morbidities reported at UK Biobank enrolment (2006-2010) and the PRS. To improve biological understanding, pathway analysis was performed using genetic variants comprising the PRS.
RESULTS
We included 9560 patients followed for a median of 61 (interquartile range = 34-88) days since COVID-19 diagnosis. The risk of severe COVID-19 increased with age and obesity, and was higher in men, current smokers, those living in socio-economically deprived areas, those with historic immunosuppressant use and individuals with morbidities and higher co-morbidity count. An optimized PRS, enriched for single-nucleotide polymorphisms in multiple immune-related pathways, including the 'oligoadenylate synthetase antiviral response' and 'interleukin-10 signalling' pathways, was associated with severe COVID-19 (adjusted odds ratio 1.32, 95% CI 1.11-1.58 for the highest compared with the lowest PRS quintile).
CONCLUSION
This study conducted in the pre-SARS-CoV-2-vaccination era, emphasizes the novel insights to be gained from using genetic data alongside commonly considered clinical and socio-demographic factors to develop greater biological understanding of severe COVID-19 outcomes.
Topics: Humans; Male; Antiviral Agents; COVID-19; COVID-19 Testing; Demography; Immunosuppressive Agents; Interleukin-10; Ligases; Risk Factors; SARS-CoV-2
PubMed: 35770811
DOI: 10.1093/ije/dyac137 -
The Journal of Adolescent Health :... Sep 2023Overweight in youth is influenced by genes and environment. Gene-environment interaction (G×E) has been demonstrated in twin studies and recent developments in genetics...
PURPOSE
Overweight in youth is influenced by genes and environment. Gene-environment interaction (G×E) has been demonstrated in twin studies and recent developments in genetics allow for studying G×E using individual genetic predispositions for overweight. We examine genetic influence on trajectories of overweight during adolescence and early adulthood and determine whether genetic predisposition is attenuated by higher socioeconomic status and having physically active parents.
METHODS
Latent class growth models of overweight were fitted using data from the TRacking Adolescents' Individual Lives Survey (n = 2720). A polygenic score for body mass index (BMI) was derived using summary statistics from a genome-wide association study of adult BMI (N = ∼700,000) and tested as predictor of developmental pathways of overweight. Multinomial logistic regression models were used to examine effects of interactions of genetic predisposition with socioeconomic status and parental physical activity (n = 1675).
RESULTS
A three-class model of developmental pathways of overweight fitted the data best ("non-overweight", "adolescent-onset overweight", and "persistent overweight"). The polygenic score for BMI and socioeconomic status distinguished the persistent overweight and adolescent-onset overweight trajectories from the non-overweight trajectory. Only genetic predisposition differentiated the adolescent-onset from the persistent overweight trajectory. There was no evidence for G×E.
DISCUSSION
Higher genetic predisposition increased the risk of developing overweight during adolescence and young adulthood and was associated with an earlier age at onset. We did not find that genetic predisposition was offset by higher socioeconomic status or having physically active parents. Instead, lower socioeconomic status and higher genetic predisposition acted as additive risk factors for developing overweight.
Topics: Adult; Adolescent; Humans; Young Adult; Longitudinal Studies; Genetic Predisposition to Disease; Genome-Wide Association Study; Overweight; Body Mass Index; Pediatric Obesity; Risk Factors; Seizures
PubMed: 37318409
DOI: 10.1016/j.jadohealth.2023.04.028 -
Diabetic Medicine : a Journal of the... Oct 2021Both lifestyle factors and genetic background contribute to the development of type 2 diabetes. Estimation of the lifetime risk of diabetes based on genetic information...
AIMS
Both lifestyle factors and genetic background contribute to the development of type 2 diabetes. Estimation of the lifetime risk of diabetes based on genetic information has not been presented, and the extent to which a normal body weight can offset a high lifetime genetic risk is unknown.
METHODS
We used data from 15,671 diabetes-free participants of European ancestry aged 45 years and older from the prospective population-based ARIC study and Rotterdam Study (RS). We quantified the remaining lifetime risk of diabetes stratified by genetic risk and quantified the effect of normal weight in terms of relative and lifetime risks in low, intermediate and high genetic risk.
RESULTS
At age 45 years, the lifetime risk of type 2 diabetes in ARIC in the low, intermediate and high genetic risk category was 33.2%, 41.3% and 47.2%, and in RS 22.8%, 30.6% and 35.5% respectively. The absolute lifetime risk for individuals with normal weight compared to individuals with obesity was 24% lower in ARIC and 8.6% lower in RS in the low genetic risk group, 36.3% lower in ARIC and 31.3% lower in RS in the intermediate genetic risk group, and 25.0% lower in ARIC and 29.4% lower in RS in the high genetic risk group.
CONCLUSIONS
Genetic variants for type 2 diabetes have value in estimating the lifetime risk of type 2 diabetes. Normal weight mitigates partly the deleterious effect of high genetic risk.
Topics: Aged; Diabetes Mellitus, Type 2; Female; Genetic Predisposition to Disease; Genetic Variation; Humans; Life Style; Male; Middle Aged; Multifactorial Inheritance; Obesity; Risk; White People
PubMed: 34245042
DOI: 10.1111/dme.14639