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International Journal of Epidemiology Jun 2023Genetic and lifestyle factors are associated with cancer risk. We investigated the benefits of adhering to lifestyle advice by the World Cancer Research Fund (WCRF) with...
BACKGROUND
Genetic and lifestyle factors are associated with cancer risk. We investigated the benefits of adhering to lifestyle advice by the World Cancer Research Fund (WCRF) with the risk of 13 types of cancer and whether these associations differ according to genetic risk using data from the UK Biobank.
METHODS
In 2006-2010, participants aged 37-73 years had their lifestyle assessed and were followed up for incident cancers until 2015-2019. Analyses were restricted to those of White European ancestry with no prior history of malignant cancer (n = 195 822). Polygenic risk scores (PRSs) were computed for 13 cancer types and these cancers combined ('overall cancer'), and a lifestyle index was calculated from WCRF recommendations. Associations with cancer incidence were estimated using Cox regression, adjusting for relevant confounders. Additive and multiplicative interactions between lifestyle index and PRSs were assessed.
RESULTS
There were 15 240 incident cancers during the 1 926 987 person-years of follow-up (median follow-up = 10.2 years). After adjusting for confounders, the lifestyle index was associated with a lower risk of overall cancer [hazard ratio per standard deviation increase (95% CI) = 0.89 (0.87, 0.90)] and of eight specific cancer types. There was no evidence of interactions on the multiplicative scale. There was evidence of additive interactions in risks for colorectal, breast, pancreatic, lung and bladder cancers, such that the recommended lifestyle was associated with greater change in absolute risk for persons at higher genetic risk (P < 0.0003 for all).
CONCLUSIONS
The recommended lifestyle has beneficial associations with most cancers. In terms of absolute risk, the protective association is greater for higher genetic risk groups for some cancers. These findings have important implications for persons most genetically predisposed to those cancers and for targeted strategies for cancer prevention.
Topics: Humans; Incidence; Prospective Studies; Risk Factors; Life Style; Neoplasms
PubMed: 36651198
DOI: 10.1093/ije/dyac238 -
Cell Metabolism Feb 2019Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a need for a more precise yet portable method of phenotyping and...
Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a need for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity. We find that obesity results in profound perturbation of the metabolome; nearly a third of the assayed metabolites associated with changes in BMI. A metabolome signature identifies the healthy obese and lean individuals with abnormal metabolomes-these groups differ in health outcomes and underlying genetic risk. Specifically, an abnormal metabolome associated with a 2- to 5-fold increase in cardiovascular events when comparing individuals who were matched for BMI but had opposing metabolome signatures. Because metabolome profiling identifies clinically meaningful heterogeneity in obesity, this approach could help select patients for clinical trials.
Topics: Adult; Aged; Aged, 80 and over; Body Mass Index; Cohort Studies; Female; Humans; Male; Metabolomics; Middle Aged; Obesity; Risk Factors; Twins; Whole Genome Sequencing
PubMed: 30318341
DOI: 10.1016/j.cmet.2018.09.022 -
Gastroenterology May 2023Non-alcoholic fatty liver disease (NAFLD) can progress to cirrhosis and hepatic decompensation, but whether genetic variants influence the rate of progression to...
BACKGROUND & AIMS
Non-alcoholic fatty liver disease (NAFLD) can progress to cirrhosis and hepatic decompensation, but whether genetic variants influence the rate of progression to cirrhosis or are useful in risk stratification among patients with NAFLD is uncertain.
METHODS
We included participants from 2 independent cohorts, they Michigan Genomics Initiative (MGI) and UK Biobank (UKBB), who had NAFLD defined by elevated alanine aminotransferase (ALT) levels in the absence of alternative chronic liver disease. The primary predictors were genetic variants and metabolic comorbidities associated with cirrhosis. We conducted time-to-event analyses using Fine-Gray competing risk models.
RESULTS
We included 7893 and 46,880 participants from MGI and UKBB, respectively. In univariable analysis, PNPLA3-rs738409-GG genotype, diabetes, obesity, and ALT of ≥2× upper limit of normal were associated with higher incidence rate of cirrhosis in both MGI and UKBB. PNPLA3-rs738409-GG had additive effects with clinical risk factors including diabetes, obesity, and ALT elevations. Among patients with indeterminate fibrosis-4 (FIB4) scores (1.3-2.67), those with diabetes and PNPLA3-rs738409-GG genotype had an incidence rate of cirrhosis comparable to that of patients with high-risk FIB4 scores (>2.67) and 2.9-4.8 times that of patients with diabetes but CC/CG genotypes. In contrast, FIB4 <1.3 was associated with an incidence rate of cirrhosis significantly lower than that of FIB4 of >2.67, even in the presence of clinical risk factors and high-risk PNPLA3 genotype.
CONCLUSIONS
PNPLA3-rs738409 genotype and diabetes identified patients with NAFLD currently considered indeterminate risk (FIB4 1.3-2.67) who had a similar risk of cirrhosis as those considered high-risk (FIB4 >2.67). PNPLA3 genotyping may improve prognostication and allow for prioritization of intensive intervention.
Topics: Humans; Diabetes Mellitus; Genetic Predisposition to Disease; Genotype; Liver Cirrhosis; Non-alcoholic Fatty Liver Disease; Obesity; Polymorphism, Single Nucleotide
PubMed: 36758837
DOI: 10.1053/j.gastro.2023.01.040 -
Circulation Mar 2023Calcific aortic stenosis (CAS) is the most common valvular heart disease in older adults and has no effective preventive therapies. Genome-wide association studies...
BACKGROUND
Calcific aortic stenosis (CAS) is the most common valvular heart disease in older adults and has no effective preventive therapies. Genome-wide association studies (GWAS) can identify genes influencing disease and may help prioritize therapeutic targets for CAS.
METHODS
We performed a GWAS and gene association study of 14 451 patients with CAS and 398 544 controls in the Million Veteran Program. Replication was performed in the Million Veteran Program, Penn Medicine Biobank, Mass General Brigham Biobank, BioVU, and BioMe, totaling 12 889 cases and 348 094 controls. Causal genes were prioritized from genome-wide significant variants using polygenic priority score gene localization, expression quantitative trait locus colocalization, and nearest gene methods. CAS genetic architecture was compared with that of atherosclerotic cardiovascular disease. Causal inference for cardiometabolic biomarkers in CAS was performed using Mendelian randomization and genome-wide significant loci were characterized further through phenome-wide association study.
RESULTS
We identified 23 genome-wide significant lead variants in our GWAS representing 17 unique genomic regions. Of the 23 lead variants, 14 were significant in replication, representing 11 unique genomic regions. Five replicated genomic regions were previously known risk loci for CAS () and 6 were novel (). Two novel lead variants were associated in non-White individuals (<0.05): rs12740374 () in Black and Hispanic individuals and rs1522387 () in Black individuals. Of the 14 replicated lead variants, only 2 (rs10455872 [], rs12740374 []) were also significant in atherosclerotic cardiovascular disease GWAS. In Mendelian randomization, lipoprotein(a) and low-density lipoprotein cholesterol were both associated with CAS, but the association between low-density lipoprotein cholesterol and CAS was attenuated when adjusting for lipoprotein(a). Phenome-wide association study highlighted varying degrees of pleiotropy, including between CAS and obesity at the locus. However, the locus remained associated with CAS after adjusting for body mass index and maintained a significant independent effect on CAS in mediation analysis.
CONCLUSIONS
We performed a multiancestry GWAS in CAS and identified 6 novel genomic regions in the disease. Secondary analyses highlighted the roles of lipid metabolism, inflammation, cellular senescence, and adiposity in the pathobiology of CAS and clarified the shared and differential genetic architectures of CAS with atherosclerotic cardiovascular diseases.
Topics: Humans; Aged; Genome-Wide Association Study; Veterans; Genetic Predisposition to Disease; Aortic Valve Stenosis; Obesity; Transcription Factors; Lipoprotein(a); Lipoproteins, LDL; Cholesterol; Polymorphism, Single Nucleotide; Glycoproteins; Nuclear Proteins
PubMed: 36802703
DOI: 10.1161/CIRCULATIONAHA.122.061451 -
Nature Communications Jun 2022For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not...
For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not fully understood. Here, we study up to 38,965 UK Biobank participants with MRI-derived visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes. Because these fat depot volumes are highly correlated with BMI, we additionally study six local adiposity traits: VAT adjusted for BMI and height (VATadj), ASATadj, GFATadj, VAT/ASAT, VAT/GFAT, and ASAT/GFAT. We identify 250 independent common variants (39 newly-identified) associated with at least one trait, with many associations more pronounced in female participants. Rare variant association studies extend prior evidence for PDE3B as an important modulator of fat distribution. Local adiposity traits (1) highlight depot-specific genetic architecture and (2) enable construction of depot-specific polygenic scores that have divergent associations with type 2 diabetes and coronary artery disease. These results - using MRI-derived, BMI-independent measures of local adiposity - confirm fat distribution as a highly heritable trait with important implications for cardiometabolic health outcomes.
Topics: Adipose Tissue; Adiposity; Body Mass Index; Diabetes Mellitus, Type 2; Female; Humans; Intra-Abdominal Fat; Obesity; Subcutaneous Fat
PubMed: 35773277
DOI: 10.1038/s41467-022-30931-2 -
The Lancet. Global Health Mar 2023Large adulthood body size was associated with increased risk of osteoarthritis. We aimed to examine the association between body size trajectories from childhood to...
Associations of childhood-to-adulthood body size trajectories and genetic susceptibility with the risks of osteoarthritis: a population-based cohort study of UK Biobank data.
BACKGROUND
Large adulthood body size was associated with increased risk of osteoarthritis. We aimed to examine the association between body size trajectories from childhood to adulthood and potential interactions with genetic susceptibility on osteoarthritis risk.
METHODS
We included participants from the UK Biobank aged 38-73 years in 2006-10. Childhood body size information was collected by questionnaire. Adulthood BMI was assessed and transformed into three categories (<25 kg/m for normal, 25-29·9 kg/m for overweight, and >30 kg/m for obesity). A Cox proportional hazards regression model was applied to assess the association between body size trajectories and osteoarthritis incidence. Osteoarthritis-related polygenic risk score (PRS) was constructed to evaluate its interactions with body size trajectories on osteoarthritis risk.
FINDINGS
For the 466 292 participants included, we identified nine body size trajectories [thinner to normal (11·6%), overweight (17·2%), or obesity (26·9%); average to normal (11·8%), overweight (16·2%), or obesity (23·7%); and plumper to normal (12·3%), overweight (16·2%), or obesity (23·6%)]. Compared with individuals in the average-to-normal group, all other trajectory groups had higher risks of osteoarthritis, after adjustment for demographic, social-economic and lifestyle covariates (hazard ratios [HRs] 1·05-2·41; all p<0·01). Among them, thinner-to-obesity (HR 2·41; 95% CI 2·23-2·49) had the most prominent association with increased osteoarthritis risk. A high PRS was significantly associated with an increased risk of osteoarthritis (1·14; 1·11-1·16), whereas no interaction between childhood-to-adulthood body size trajectories and PRS on osteoarthritis risks was observed. The population attributable fraction suggested that body size towards normal in adulthood could eliminate osteoarthritis cases by 18·67% for thinner-to-overweight to 38·74% for plumper-to-obesity.
INTERPRETATION
Average-to-normal body size seems to be the healthiest childhood-to-adulthood trajectory for osteoarthritis risk, whereas a trajectory of increased body size from thinner to obesity has the highest risk for osteoarthritis. These associations are independent of osteoarthritis genetic susceptibility.
FUNDING
The National Natural Science Foundation of China (32000925) and Guangzhou Science and Technology Program (202002030481).
Topics: Humans; Child; Adolescent; Young Adult; Overweight; Biological Specimen Banks; Cohort Studies; Genetic Predisposition to Disease; Obesity; Body Size; Osteoarthritis; United Kingdom
PubMed: 36866477
DOI: 10.1016/S2214-109X(23)00087-6 -
ELife Jul 2023Ossification of the posterior longitudinal ligament of the spine (OPLL) is an intractable disease leading to severe neurological deficits. Its etiology and pathogenesis... (Meta-Analysis)
Meta-Analysis
Ossification of the posterior longitudinal ligament of the spine (OPLL) is an intractable disease leading to severe neurological deficits. Its etiology and pathogenesis are primarily unknown. The relationship between OPLL and comorbidities, especially type 2 diabetes (T2D) and high body mass index (BMI), has been the focus of attention; however, no trait has been proven to have a causal relationship. We conducted a meta-analysis of genome-wide association studies (GWASs) using 22,016 Japanese individuals and identified 14 significant loci, 8 of which were previously unreported. We then conducted a gene-based association analysis and a transcriptome-wide Mendelian randomization approach and identified three candidate genes for each. Partitioning heritability enrichment analyses observed significant enrichment of the polygenic signals in the active enhancers of the connective/bone cell group, especially H3K27ac in chondrogenic differentiation cells, as well as the immune/hematopoietic cell group. Single-cell RNA sequencing of Achilles tendon cells from a mouse Achilles tendon ossification model confirmed the expression of genes in GWAS and post-GWAS analyses in mesenchymal and immune cells. Genetic correlations with 96 complex traits showed positive correlations with T2D and BMI and a negative correlation with cerebral aneurysm. Mendelian randomization analysis demonstrated a significant causal effect of increased BMI and high bone mineral density on OPLL. We evaluated the clinical images in detail and classified OPLL into cervical, thoracic, and the other types. GWAS subanalyses identified subtype-specific signals. A polygenic risk score for BMI demonstrated that the effect of BMI was particularly strong in thoracic OPLL. Our study provides genetic insight into the etiology and pathogenesis of OPLL and is expected to serve as a basis for future treatment development.
Topics: Animals; Mice; Osteogenesis; Genome-Wide Association Study; Diabetes Mellitus, Type 2; Spine; Ossification of Posterior Longitudinal Ligament
PubMed: 37461309
DOI: 10.7554/eLife.86514 -
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