CYP2A6 associates with respiratory disease risk and younger age of diagnosis: a phenome-wide association Mendelian Randomization study.

CYP2A6, a genetically variable enzyme, inactivates nicotine, activates carcinogens, and metabolizes many pharmaceuticals. Variation in CYP2A6 influences smoking behaviors and tobacco-related disease risk. This phenome-wide association study examined associations between a reconstructed version of our weighted genetic risk score (wGRS) for CYP2A6 activity with diseases in the UK Biobank (N = 395 887). Causal effects of phenotypic CYP2A6 activity (measured as the nicotine metabolite ratio: 3'-hydroxycotinine/cotinine) on the phenome-wide significant (PWS) signals were then estimated in two-sample Mendelian Randomization using the wGRS as the instrument. Time-to-diagnosis age was compared between faster versus slower CYP2A6 metabolizers for the PWS signals in survival analyses. In the total sample, six PWS signals were identified: two lung cancers and four obstructive respiratory diseases PheCodes, where faster CYP2A6 activity was associated with greater disease risk (Ps < 1 × 10-6). A significant CYP2A6-by-smoking status interaction was found (Psinteraction < 0.05); in current smokers, the same six PWS signals were found as identified in the total group, whereas no PWS signals were found in former or never smokers. In the total sample and current smokers, CYP2A6 activity causal estimates on the six PWS signals were significant in Mendelian Randomization (Ps < 5 × 10-5). Additionally, faster CYP2A6 metabolizer status was associated with younger age of disease diagnosis for the six PWS signals (Ps < 5 × 10-4, in current smokers). These findings support a role for faster CYP2A6 activity as a causal risk factor for lung cancers and obstructive respiratory diseases among current smokers, and a younger onset of these diseases. This research utilized the UK Biobank Resource.

Power of inclusion: Enhancing polygenic prediction with admixed individuals.

Admixed individuals offer unique opportunities for addressing limited transferability in polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many complex traits. However, they are rarely considered in PGS training, given the challenges in representing ancestry-matched linkage-disequilibrium reference panels for admixed individuals. Here we present inclusive PGS (iPGS), which captures ancestry-shared genetic effects by finding the exact solution for penalized regression on individual-level data and is thus naturally applicable to admixed individuals. We validate our approach in a simulation study across 33 configurations with varying heritability, polygenicity, and ancestry composition in the training set. When iPGS is applied to n = 237,055 ancestry-diverse individuals in the UK Biobank, it shows the greatest improvements in Africans by 48.9% on average across 60 quantitative traits and up to 50-fold improvements for some traits (neutrophil count, R2 = 0.058) over the baseline model trained on the same number of European individuals. When we allowed iPGS to use n = 284,661 individuals, we observed an average improvement of 60.8% for African, 11.6% for South Asian, 7.3% for non-British White, 4.8% for White British, and 17.8% for the other individuals. We further developed iPGS+refit to jointly model the ancestry-shared and -dependent genetic effects when heterogeneous genetic associations were present. For neutrophil count, for example, iPGS+refit showed the highest predictive performance in the African group (R2 = 0.115), which exceeds the best predictive performance for the White British group (R2 = 0.090 in the iPGS model), even though only 1.49% of individuals used in the iPGS training are of African ancestry. Our results indicate the power of including diverse individuals for developing more equitable PGS models.

Genetic distance and ancestry proportion modify the association between maternal genetic risk score of type 2 diabetes and fetal growth.

BACKGROUND: Maternal genetic risk of type 2 diabetes (T2D) has been associated with fetal growth, but the influence of genetic ancestry is not yet fully understood. We aimed to investigate the influence of genetic distance (GD) and genetic ancestry proportion (GAP) on the association of maternal genetic risk score of T2D (GRST2D) with fetal weight and birthweight. METHODS: Multi-ancestral pregnant women (n = 1,837) from the NICHD Fetal Growth Studies - Singletons cohort were included in the current analyses. Fetal weight (in grams, g) was estimated from ultrasound measurements of fetal biometry, and birthweight (g) was measured at delivery. GRST2D was calculated using T2D-associated variants identified in the latest trans-ancestral genome-wide association study and was categorized into quartiles. GD and GAP were estimated using genotype data of four reference populations. GD was categorized into closest, middle, and farthest tertiles, and GAP was categorized as highest, medium, and lowest. Linear regression analyses were performed to test the association of GRST2D with fetal weight and birthweight, adjusted for covariates, in each GD and GAP category. RESULTS: Among women with the closest GD from African and Amerindigenous ancestries, the fourth and third GRST2D quartile was significantly associated with 5.18 to 7.48 g (weeks 17-20) and 6.83 to 25.44 g (weeks 19-27) larger fetal weight compared to the first quartile, respectively. Among women with middle GD from European ancestry, the fourth GRST2D quartile was significantly associated with 5.73 to 21.21 g (weeks 18-26) larger fetal weight. Furthermore, among women with middle GD from European and African ancestries, the fourth and second GRST2D quartiles were significantly associated with 117.04 g (95% CI = 23.88-210.20, p = 0.014) and 95.05 g (95% CI = 4.73-185.36, p = 0.039) larger birthweight compared to the first quartile, respectively. The absence of significant association among women with the closest GD from East Asian ancestry was complemented by a positive significant association among women with the highest East Asian GAP. CONCLUSIONS: The association between maternal GRST2D and fetal growth began in early-second trimester and was influenced by GD and GAP. The results suggest the use of genetic GD and GAP could improve the generalizability of GRS.

Influence of Polygenic Background on the Clinical Presentation of Familial Hypercholesterolemia.

BACKGROUND: Heterozygous familial hypercholesterolemia (FH) is among the most common genetic conditions worldwide that affects ≈ 1 in 300 individuals. FH is characterized by increased levels of low-density lipoprotein cholesterol (LDL-C) and increased risk of coronary artery disease (CAD), but there is a wide spectrum of severity within the FH population. This variability in expression is incompletely explained by known risk factors. We hypothesized that genome-wide genetic influences, as represented by polygenic risk scores (PRSs) for cardiometabolic traits, would influence the phenotypic severity of FH. METHODS: We studied individuals with clinically diagnosed FH (n=1123) from the FH Canada National Registry, as well as individuals with genetically identified FH from the UK Biobank (n=723). For all individuals, we used genome-wide gene array data to calculate PRSs for CAD, LDL-C, lipoprotein(a), and other cardiometabolic traits. We compared the distribution of PRSs in individuals with clinically diagnosed FH, genetically diagnosed FH, and non-FH controls and examined the association of the PRSs with the risk of atherosclerotic cardiovascular disease. RESULTS: Individuals with clinically diagnosed FH had higher levels of LDL-C, and the incidence of atherosclerotic cardiovascular disease was higher in individuals with clinically diagnosed compared with genetically identified FH. Individuals with clinically diagnosed FH displayed enrichment for higher PRSs for CAD, LDL-C, and lipoprotein(a) but not for other cardiometabolic risk factors. The CAD PRS was associated with a risk of atherosclerotic cardiovascular disease among individuals with an FH-causing genetic variant. CONCLUSIONS: Genetic background, as expressed by genome-wide PRSs for CAD, LDL-C, and lipoprotein(a), influences the phenotypic severity of FH, expanding our understanding of the determinants that contribute to the variable expressivity of FH. A PRS for CAD may aid in risk prediction among individuals with FH.

Brugada syndrome in Japan and Europe: a genome-wide association study reveals shared genetic architecture and new risk loci.

BACKGROUND AND AIMS: Brugada syndrome (BrS) is an inherited arrhythmia with a higher disease prevalence and more lethal arrhythmic events in Asians than in Europeans. Genome-wide association studies (GWAS) have revealed its polygenic architecture mainly in European populations. The aim of this study was to identify novel BrS-associated loci and to compare allelic effects across ancestries. METHODS: A GWAS was conducted in Japanese participants, involving 940 cases and 1634 controls, followed by a cross-ancestry meta-analysis of Japanese and European GWAS (total of 3760 cases and 11 635 controls). The novel loci were characterized by fine-mapping, gene expression, and splicing quantitative trait associations in the human heart. RESULTS: The Japanese-specific GWAS identified one novel locus near ZSCAN20 (P = 1.0 × 10-8), and the cross-ancestry meta-analysis identified 17 association signals, including six novel loci. The effect directions of the 17 lead variants were consistent (94.1%; P for sign test = 2.7 × 10-4), and their allelic effects were highly correlated across ancestries (Pearson's R = .91; P = 2.9 × 10-7). The genetic risk score derived from the BrS GWAS of European ancestry was significantly associated with the risk of BrS in the Japanese population [odds ratio 2.12 (95% confidence interval 1.94-2.31); P = 1.2 × 10-61], suggesting a shared genetic architecture across ancestries. Functional characterization revealed that a lead variant in CAMK2D promotes alternative splicing, resulting in an isoform switch of calmodulin kinase II-δ, favouring a pro-inflammatory/pro-death pathway. CONCLUSIONS: This study demonstrates novel susceptibility loci implicating potentially novel pathogenesis underlying BrS. Despite differences in clinical expressivity and epidemiology, the polygenic architecture of BrS was substantially shared across ancestries.

Genetic susceptibility to prostate cancer in Taiwan: A genome-wide association study.

We conducted the first genome-wide association study (GWAS) of prostate cancer (PCa) in Taiwan with 1844 cases and 80,709 controls. Thirteen independent single-nucleotide polymorphisms (SNPs) reached genome-wide significance (p < 5 × 10-8 ). Among these, three were distinct from previously identified loci: rs76072851 in CORO2B gene (15q23), odds ratio (OR) = 1.54, 95% confidence interval (CI), 1.36-1.76, p = 5.30 × 10-11 ; rs7837051, near two long noncoding RNA (lncRNA) genes, PRNCR1 and PCAT2 (8q24.21), OR = 1.41 (95% CI, 1.31-1.51), p = 8.77 × 10-21 ; and rs56339048, near an lncRNA gene, CASC8 (8q24.21), OR = 1.25 (95% CI, 1.16-1.35), p = 2.14 × 10-8 . We refined the lead SNPs for two previously identified SNPs in Taiwanese: rs13255059 (near CASC8), p = 9.02 × 10-43 , and rs1456315 (inside PRNCR1), p = 4.33 × 10-42 . We confirmed 35 out of 49 GWAS-identified East Asian PCa susceptibility SNPs. In addition, we identified two SNPs more specific to Taiwanese than East Asians: rs34295433 in LAMC1 (1q25.3) and rs6853490 in PDLIM5 (4q22.3). A weighted genetic risk score (GRS) was developed using the 40 validated SNPs and the area under the receiver-operating characteristic curve for the GRS to predict PCa was 0.67 (95% CI, 0.63-0.71). These identified SNPs provide valuable insights into the molecular mechanisms of prostate carcinogenesis in Taiwan and underscore the significant role of genetic susceptibility in regional differences in PCa incidence.

Ultraprocessed food consumption, genetic predisposition, and the risk of gout: the UK Biobank study.

OBJECTIVE: This study aimed to examine the interactions between ultraprocessed food (UPF) consumption and genetic predisposition with the risk of gout. METHODS: This prospective cohort study analysed 181 559 individuals from the UK Biobank study who were free of gout at baseline. UPF was defined according to the NOVA classification. Assessment of genetic predisposition for gout was developed from a genetic risk score of 33 single nucleotide polymorphisms. Cox proportional hazards were used to estimate the associations between UPF consumption, genetic predisposition and the risk of gout. RESULTS: Among the 181 559 individuals in the study, 1558 patients developed gout over 1 648 167 person-years of follow-up. In the multivariable adjustment model, compared with the lowest quartile of UPF consumption, the hazard ratio (HR) and 95% CI of the highest UPF consumption was 1.16 (1.01, 1.33) for gout risk, and there was a non-linear correlation between UPF consumption and the development of gout. In substitution analyses, replacing 20% of the weight of UPF in the daily intake with an equal amount of unprocessed or minimally processed food resulted in a 13% lower risk of gout (HR: 0.87; 95% CI: 0.79, 0.95). In the joint-effect analysis, the HR (95% CI) for gout was 1.90 (1.39, 2.60) in participants with high genetic predisposition and high UPF consumption, compared with those with low genetic predisposition and low UPF consumption. CONCLUSION: In summary, UPF consumption was found to be associated with a higher risk of gout, particularly in those participants with genetic predisposition to gout. Our study indicated that reducing UPF consumption is crucial for gout prevention.

Development and Internal Validation of a Clinical and Genetic Risk Score for Rheumatoid Arthritis-Associated Interstitial Lung Disease.

OBJECTIVE: Although clinical and genetic risk factors have been identified for rheumatoid arthritis-associated interstitial lung disease (RA-ILD), there are no current tools allowing for risk stratification. We sought to develop and validate an ILD risk model in a large, multicentre, prospective RA cohort. METHODS: Participants in the Veterans Affairs RA (VARA) registry were genotyped for 12 single nucleotide polymorphisms (SNPs) associated with idiopathic pulmonary fibrosis. ILD was validated through systematic record review. A genetic risk score (GRS) was computed from minor alleles weighted by effect size with ILD, using backward selection. The GRS was combined with clinical risk factors within a logistic regression model. Internal validation was completed using bootstrapping, and model performance was assessed by the area under the receiver operating curve (AUC). RESULTS: Of 2,386 participants (89% male, mean age 69.5 years), 9.4% had ILD. Following backward selection, five SNPs contributed to the GRS. The GRS and clinical factors outperformed clinical factors alone in discriminating ILD (AUC 0.675 vs 0.635, p< 0.001). The shrinkage-corrected performance for combined and clinical-only models was 0.667 (95% CI 0.628, 0.712) and 0.623 (95% CI 0.584, 0.651), respectively. Twenty percent of the cohort had a combined risk score below a cut-point with >90% sensitivity. CONCLUSION: A clinical and genetic risk model discriminated ILD in a large, multicentre RA cohort better than a clinical-only model, excluding 20% of the cohort from low-yield testing. These results demonstrate the potential utility of a GRS in RA-ILD and support further investigation into individualized risk stratification and screening.

Genetic Risk Stratification of Primary Open-Angle Glaucoma in Japanese Individuals.

PURPOSE: To assess the impact of genetic risk estimation for primary open-angle glaucoma (POAG) in Japanese individuals. DESIGN: Cross-sectional analysis. PARTICIPANTS: Genetic risk scores (GRSs) were constructed based on a genome-wide association study (GWAS) of POAG in Japanese people. A total of 3625 Japanese individuals, including 1191 patients and 2434 controls (Japanese Tohoku), were used for the model selection. We also evaluated the discriminative accuracy of constructed GRSs in a dataset comprising 1034 patients and 1147 controls (the Japan Glaucoma Society Omics Group [JGS-OG] and the Genomic Research Committee of the Japanese Ophthalmological Society [GRC-JOS]) and 1900 participants from a population-based study (Hisayama Study). METHODS: We evaluated 2 types of GRSs: polygenic risk scores using the pruning and thresholding procedure and a GRS using variants associated with POAG in the GWAS of the International Glaucoma Genetics Consortium (IGGC). We selected the model with the highest areas under the receiver operating characteristic curve (AUC). In the population-based study, we evaluated the correlations between GRS and ocular measurements. MAIN OUTCOME MEASURE: Proportion of patients with POAG after stratification according to the GRS. RESULTS: We found that a GRS using 98 variants, which showed genome-wide significance in the IGGC, showed the best discriminative accuracy (AUC, 0.65). In the Japanese Tohoku, the proportion of patients with POAG in the top 10% individuals was significantly higher than that in the lowest 10% (odds ratio [OR], 6.15; 95% confidence interval [CI], 4.35-8.71). In the JGS-OG and GRC-JOS, we confirmed similar impact of POAG GRS (AUC, 0.64; OR [top vs. bottom decile], 5.81; 95% CI, 3.79-9.01). In the population-based study, POAG prevalence was significantly higher in the top 20% individuals of the GRS compared with the bottom 20% (9.2% vs. 5.0%). However, the discriminative accuracy was low (AUC, 0.56). The POAG GRS was correlated positively with intraocular pressure (r = 0.08: P = 4.0 × 10-4) and vertical cup-to-disc ratio (r = 0.11; P = 4.0 × 10-6). CONCLUSIONS: The GRS showed moderate discriminative accuracy for POAG in the Japanese population. However, risk stratification in the general population showed relatively weak discriminative performance. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The clinical utility of a glaucoma polygenic risk score in four population-based European-ancestry cohorts.

OBJECTIVE: We used a polygenic risk score (PRS) to identify high-risk groups for primary open-angle glaucoma (POAG) within population-based cohorts. DESIGN: Secondary analysis of four prospective population-based studies. PARTICIPANTS: We included four European-ancestry cohorts: the United States (US) based Nurses' Health Study (NHS), NHS2, and the Health Professionals Follow-up Study, and the Rotterdam Study (RS) in the Netherlands. The US cohorts included female nurses and male health professionals aged 55+ years. The RS included residents aged 45 years or older living in Rotterdam, the Netherlands. METHODS: PRS weights were estimated by applying the Lassosum method on imputed genotype and phenotype data from the UK-Biobank. This resulted in 144,020 variants, single nucleotide polymorphism (SNPs) and indels, with non-zero betas that we used to calculate a PRS in the target populations. Using multivariable Cox proportional hazard models, we estimated the relationship between the standardized PRS and relative risk for POAG. Additionally, POAG prediction was tested by calculating these models' concordance (Harrell's C-statistic). Finally, we assessed the association between PRS tertiles and glaucoma-related traits. MAIN OUTCOME MEASURES: The relative risk for POAG and Harrell's C-statistic (the equivalent of an area-under-the-curve for longitudinal models). RESULTS: Among 1,046 cases and 38,809‬ controls, the relative risk (95% confidence interval) for POAG for participants in the highest PRS quintile was 3.99 (3.08, 5.18) in the US cohorts, and 4.89 (2.93, 8.17) in the Rotterdam Study, compared with participants with median genetic risk (3rd quintile). In restricted cubic spline analyses, the relation between continuous PRS and POAG risk increased exponentially in the US and Rotterdam cohorts (Pspline<0.05). Combining age, sex, intraocular pressure >25 mmHg, and family history resulted in a meta-analyzed concordance of 0.75 (0.73, 0.75). Adding the PRS to this model improved the concordance to 0.82 (0.80, 0.84). In a meta-analysis of all cohorts, cases in the highest tertile had a larger cup-disc ratio at diagnosis, by 0.11 (0.07, 0.15), and a 2.07-fold increased risk of requiring glaucoma surgery (1.19, 3.60). CONCLUSIONS: Incorporating a PRS into a POAG predictive model improves identification concordance from 0.75 up to 0.82, supporting its potential for guiding more cost-effective screening strategies.

Outdoor walking, genetic predisposition, and the risk of incident osteoporosis among older adults: A prospective large population-based cohort study.

This large-scale prospective study showed that a significant association between longer duration of daily outdoor walking and reduced osteoporosis risk was found among older adults, particularly among those with a low genetic predisposition to osteoporosis, which highlighted the importance of outdoor walking as a simple, cost-effective adjunct for preventing osteoporosis. PURPOSE: The available cross-sectional data and small-scale studies indicate that outdoor walking benefits bone metabolism. Nevertheless, there is a scarcity of comprehensive prospective research investigating the enduring correlation between outdoor walking and osteoporosis. This study aims to conduct a prospective analysis of the correlation between outdoor walking and osteoporosis while also examining potential variations influenced by genetic susceptibility to osteoporosis. METHODS: 24,700 older adults without osteoporosis at baseline were enrolled. These individuals were followed up until December 31, 2021, during which data on outdoor walking was gathered. The genetic risk score for osteoporosis was comprised of 14 single-nucleotide polymorphisms. RESULTS: 4,586 cases of osteoporosis were identified throughout a median follow-up period of 37.3 months. Those who walked outside for > 30 but ≤ 60 min per day had a hazard ratio (HR) of 0.83 (95% confidence interval (CI): 0.72-0.95) for incident osteoporosis, whereas those who walked outside for > 60 min per day had an HR of 0.60 (95% CI: 0.39-0.92). We found that osteoporosis risk exhibited a declining trend in individuals with low genetic risk. Individuals walking outside for > 60 min per day tended to have the lowest overall osteoporosis risk among those with high genetic risk. CONCLUSIONS: A significant negative correlation exists between an extended period of daily outdoor walking and osteoporosis incidence risk. This correlation is particularly pronounced among individuals with low genetic risk. The results above underscore the significance of outdoor walking as a simple and economical adjunct to public health programs to prevent osteoporosis.

Diabetes Study of Children of Diverse Ethnicity and Race: Study design.

AIMS: Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth. MATERIALS AND METHODS: The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model. RESULTS: The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis. CONCLUSIONS: Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

Serum 25-Hydroxyvitamin D and Risk of Disability in Activities of Daily Living among the Oldest-Old: An Observational and Mendelian Randomization Study.

BACKGROUND: Vitamin D deficiency and disability are both prevalent among older adults. However, the association between them has rarely been investigated in the oldest-old subjects (aged ≥80 y), and the causality remains unclear. OBJECTIVE: This study aimed to elucidate the causal effect of vitamin D on the incident risk of disability in activities of daily living (ADL) among Chinese oldest-old based on the 2012-2018 Chinese Healthy Ageing and Biomarkers Cohort Study. METHODS: Serum 25-hydroxyvitamin D [25(OH)D] concentrations and ADL status at baseline and follow-up interviews were documented. Cox regression models were applied among 1427 oldest-old (mean age, 91.2 y) with normal baseline ADL status. One sample Mendelian randomization (MR) analyses were performed on a subset of 941 participants with qualified genetic data, using a 25(OH)D-associated genetic risk score as the genetic instrument. RESULTS: During a median follow-up of 3.4 y, 231 participants developed disability in ADL. Serum 25(OH)D concentration was inversely associated with the risk of disability in ADL [per 10 nmol/L increase hazard ratio (HR) 0.85; 95% CI: 0.75, 0.96]. Consistent results from MR analyses showed that a 10 nmol/L increment in genetically predicted 25(OH)D concentration corresponded to a 20% reduced risk of ADL disability (HR 0.80; 95% CI: 0.68, 0.94). Nonlinear MR demonstrated a monotonic declining curve, with the HRs exhibiting a more pronounced reduction among individuals with 25(OH)D concentrations below 50 nmol/L. Subgroup analyses showed that the associations were more distinct among females and those with poorer health conditions. CONCLUSIONS: Our study supports an inverse causal relationship between serum 25(OH)D concentration and the risk of disability in ADL among Chinese oldest-old. This protective effect was more distinct, especially for participants with vitamin D deficiency. Appropriate measures for improving vitamin D might help reduce the incidence of physical disability in this specific age group.

Prediction of esophageal cancer risk based on genetic variants and environmental risk factors in Chinese population.

BACKGROUND: Results regarding whether it is essential to incorporate genetic variants into risk prediction models for esophageal cancer (EC) are inconsistent due to the different genetic backgrounds of the populations studied. We aimed to identify single-nucleotide polymorphisms (SNPs) associated with EC among the Chinese population and to evaluate the performance of genetic and non-genetic factors in a risk model for developing EC. METHODS: A meta-analysis was performed to systematically identify potential SNPs, which were further verified by a case-control study. Three risk models were developed: a genetic model with weighted genetic risk score (wGRS) based on promising SNPs, a non-genetic model with environmental risk factors, and a combined model including both genetic and non-genetic factors. The discrimination ability of the models was compared using the area under the receiver operating characteristic curve (AUC) and the net reclassification index (NRI). The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to assess the goodness-of-fit of the models. RESULTS: Five promising SNPs were ultimately utilized to calculate the wGRS. Individuals in the highest quartile of the wGRS had a 4.93-fold (95% confidence interval [CI]: 2.59 to 9.38) increased risk of EC compared with those in the lowest quartile. The genetic or non-genetic model identified EC patients with AUCs ranging from 0.618 to 0.650. The combined model had an AUC of 0.707 (95% CI: 0.669 to 0.743) and was the best-fitting model (AIC = 750.55, BIC = 759.34). The NRI improved when the wGRS was added to the risk model with non-genetic factors only (NRI = 0.082, P = 0.037). CONCLUSIONS: Among the three risk models for EC, the combined model showed optimal predictive performance and can help to identify individuals at risk of EC for tailored preventive measures.

Islet autoantibody frequency in relatives of children with type 1 diabetes who have a type 2 diabetes diagnosis.

AIM: This study aimed to evaluate characteristics of autoimmunity in individuals who have a type 2 diagnosis and are relatives of children with type 1 diabetes. METHODS: Pre-diagnosis samples (median 17 months before onset) from relatives who were later diagnosed with type 2 diabetes were measured for autoantibodies to glutamate decarboxylase 65 (GADA), islet antigen-2 (IA-2A), zinc transporter 8 (ZnT8A) and insulin (IAA) as well as the type 1 diabetes genetic risk score (GRS2). Associations between islet autoantibodies, insulin treatment and GRS2 were analysed using Fisher's exact and t-tests. RESULTS: Among 226 relatives (64% men; mean age at sampling 41 years; mean age 54 years at diagnosis), 32 (14%) were islet autoantibody-positive for at least one autoantibody more than a decade before diagnosis. Approximately half of these (n = 15) were treated with insulin. GADA-positivity was higher in insulin-treated relatives than in non-insulin-treated relatives (12/18 [67%] vs. 6/18 [33%], p < 0.001). IAA-positivity was observed in 13/32 (41%) of relatives with autoantibodies. GRS2 scores were increased in autoantibody-positive relatives (p = 0.032), but there was no clear evidence for a difference according to treatment (p = 0.072). CONCLUSION: This study highlights the importance of measuring islet autoantibodies, including IAA, in relatives of people with type 1 diabetes to avoid misdiagnosis.

Metabolic syndrome, genetic susceptibility, and risk of chronic obstructive pulmonary disease: The UK Biobank Study.

AIM: To investigate the effect of metabolic syndrome (MetS), genetic predisposition, and their interactions, on the risk of developing chronic obstructive pulmonary disease (COPD). METHODS: Cohort analyses included 287 868 participants from the UK Biobank Study. A genetic risk score for COPD was created using 277 single nucleotide polymorphisms. Cox proportional hazard models were used to evaluate the hazard ratios (HRs) with 95% confidence intervals (CIs) for COPD in relation to exposure factors. RESULTS: During 2 658 936 person-years of follow-up, 5877 incident cases of COPD were documented. Compared with participants without MetS, those with MetS had a higher risk of COPD (HR 1.24, 95% CI 1.17-1.32). Compared to participants with low genetic predisposition, those with high genetic predisposition had a 17% increased risk of COPD. In the joint analysis, compared with participants without MetS and low genetic predisposition, the HR for COPD for those with MetS and high genetic predisposition was 1.50 (95% CI 1.36-1.65; P < 0.001). However, no significant interaction between MetS and genetic risk was found. CONCLUSIONS: Metabolic syndrome was found to be associated with an increased risk of COPD, regardless of genetic risk. It is crucial to conduct further randomized control trials to determine whether managing MetS and its individual components can potentially reduce the likelihood of developing COPD.

Combination of risk alleles of PNPLA3, TM6SF2, and HSD17B13 of donors can predict recurrence of steatotic liver disease after liver transplantation.

AIMS: This study aimed to identify the genetic risk factors from donors or recipients that contribute to postliver transplantation (LT) steatotic liver disease (SLD), focusing on the genetic risk score (GRS) based on single nucleotide polymorphisms (SNPs) in SLD patients. METHODS: This retrospective study included 55 Japanese SLD recipients and their respective donors. Genotyping of PNPLA3, TM6SF2, and HSD17B13 was undertaken, and the combined GRS was calculated. The relationship between the GRS and the incidence of posttransplant SLD was also evaluated. RESULTS: The SLD recipients had a high prevalence of post-LT graft steatosis/steatohepatitis (76.4% and 58.2%, respectively). Although the recipients had a high frequency of risk alleles, there was no relationship between the number of risk alleles for each SNP and the incidence of posttransplant SLD. In contrast, an increased number of risk alleles for any SNP in the donor was correlated with high incidence rates of both post-LT steatosis and steatohepatitis. A multivariable analysis showed that a high donor GRS was an independent risk factor for graft steatosis (odds ratio 8.77; 95% CI, 1.94-52.94; p = 0.009). Similarly, a high donor GRS was an independent risk factor (odds ratio 6.76; 95% CI, 1.84-30.78; p = 0.007) for post-LT graft steatohepatitis. CONCLUSIONS: Donor risk alleles of PNPLA3, TM6SF2, and HSD17B13, rather than recipient risk alleles, have been implicated in the development of posttransplant SLD. The combination of these donor risk alleles into a GRS could predict the development of posttransplant SLD.

Metabolic profiling of smoking, associations with type 2 diabetes and interaction with genetic susceptibility.

BACKGROUND: Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance. METHODS: In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI). FINDINGS: The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92). INTERPRETATION: The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.

Air pollutants, genetic susceptibility, and the risk of incident gastrointestinal diseases: A large prospective cohort study.

A comprehensive overview of the associations between air pollution and the risk of gastrointestinal (GI) diseases has been lacking. We aimed to examine the relationships of long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5 µm (PM2.5), 2.5-10 µm (PMcoarse), ≤10 µm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx), with the risk of incident GI diseases, and to explore the interplay between air pollution and genetic susceptibility. A total of 465,703 participants free of GI diseases in the UK Biobank were included at baseline. Land use regression models were employed to calculate the residential air pollutants concentrations. Cox proportional hazard models were used to evaluate the associations of air pollutants with the risk of GI diseases. The dose-response relationships of air pollutants with the risk of GI diseases were evaluated by restricted cubic spline curves. We found that long-term exposure to ambient air pollutants was positively associated with the risk of peptic ulcer (PM2.5 : Q4 vs. Q1: hazard ratio (HR) 1.272, 95% confidence interval (CI) 1.179-1.372, NO2: 1.220, 1.131-1.316, and NOx: 1.277, 1.184-1.376) and chronic gastritis (PM2.5: 1.454, 1.309-1.616, PM10 : 1.232, 1.112-1.366, NO2: 1.456, 1.311-1.617, and NOx: 1.419, 1.280-1.574) after Bonferroni correction. Participants with high genetic risk and high air pollution exposure had the highest risk of peptic ulcer, compared to those with low genetic risk and low air pollution exposure (PM2.5: HR 1.558, 95%CI 1.384-1.754, NO2: 1.762, 1.395-2.227, and NOx: 1.575, 1.403-1.769). However, no significant additive or multiplicative interaction between air pollution and genetic risk was found. In conclusion, long-term exposure to ambient air pollutants was associated with increased risk of peptic ulcer and chronic gastritis.

Genetic predisposition, lifestyle inflammation score, food-based dietary inflammatory index, and the risk for incident diabetes: Findings from the KoGES data.

BACKGROUND AND AIMS: We investigated whether genetic predisposition, the Lifestyle Inflammation Score (LIS), or the Food-based Dietary Inflammatory Index (FDII) were associated with diabetes incidence and whether these factors interact. METHODS AND RESULTS: The study was conducted using population-based cohort data derived from the Korean Genome and Epidemiology Study, which included 6568 people aged 40-69 years. Based on 25 genetic variants related to diabetes, genetic risk scores (GRSs) were determined and LISs and FDIIs were calculated and stratified into quartiles. We investigated the effects of gene-lifestyle interactions on the incident diabetes. The multivariate Cox proportional hazard model was used to generate hazard ratios with 95 % CIs. During the 16-year follow-up period, diabetes incidence was 13.6 per 1000 person-years. A dose-response association with diabetes was observed for both GRS and LIS quartiles but not for FDII quartiles. The GRS and LIS were also independently associated with diabetes incidence in a multivariate model. Compared to the bottom quartile, the top LIS quartile and the top GRS quartile had a 2.4-fold (95 % CI, 2.0-2.8) and a 1.4-fold (95 % CI, 1.2-1.7) higher diabetes risk, respectively. However, the FDII exhibited null association. When each genetic variant was evaluated, the top versus bottom LIS quartiles exhibited heterogeneous diabetes risks for rs560887 within G6PC2, rs7072268 within HK1, and rs837763 within CDT1; however, these differences were not statistically significant in multiple comparison. CONCLUSION: Both GRS and LIS factors independently affect the incident diabetes, but their interaction effect showed insignificant association. Therefore, regardless of genetic susceptibility, more effort is needed to lower the risk for diabetes by improving lifestyle behaviors.