Metabolic health and genetic predisposition in inflammatory bowel disease: Insights from a prospective cohort study.

BACKGROUND: Metabolic disorders exhibit strong inflammatory underpinnings and vice versa. This study aimed to investigate the association between metabolic health status, genetic predisposition, and the risk of inflammatory bowel disease (IBD), and to explore the potential benefits of maintaining ideal metabolic status for individuals with a predetermined genetic risk of IBD. METHOD: This population-based prospective study included 385,820 unrelated European descent participants from the UK Biobank. Using multivariable Cox regression, we assessed the relationship of metabolic phenotypes with risk of IBD and its subtypes. We also developed a polygenic risk score to examine how metabolic health status interacted with genetic risk in relation to IBD risk. RESULTS: During the follow-up period of 4,328,895 person-years, 2,044 newly-diagnosed IBD cases were identified. Higher genetic risk and an increasing number of abnormal metabolic phenotypes were associated with elevated IBD risk (p-trend <0.001). Individuals with high genetic risk and poor metabolic health had a significantly higher risk of IBD (HR=4.56, 95 % CI=3.27-6.36) compared to those with low genetic risk and ideal metabolic health. These results remained consistent for IBD subtypes. Maintaining ideal metabolic status reduced IBD risk within each genetic risk category and jointly decreased subsequent risk by 40 % in high genetic risk individuals. CONCLUSION: Our study reveals a combined impact of poor metabolic health and genetic risk on IBD incidence. Those with low genetic risk and optimal metabolic health exhibit the lowest IBD risk, offering insights into potential management strategies for individuals at predefined genetic risk.

Comparative analysis of genetic risk scores for predicting biochemical recurrence in prostate cancer patients after radical prostatectomy.

BACKGROUND: In recent years, Genome-Wide Association Studies (GWAS) has identified risk variants related to complex diseases, but most genetic variants have less impact on phenotypes. To solve the above problems, methods that can use variants with low genetic effects, such as genetic risk score (GRS), have been developed to predict disease risk. METHODS: As the GRS model with the most incredible prediction power for complex diseases has not been determined, our study used simulation data and prostate cancer data to explore the disease prediction power of three GRS models, including the simple count genetic risk score (SC-GRS), the direct logistic regression genetic risk score (DL-GRS), and the explained variance weighted GRS based on directed logistic regression (EVDL-GRS). RESULTS AND CONCLUSIONS: We used 26 SNPs to establish GRS models to predict the risk of biochemical recurrence (BCR) after radical prostatectomy. Combining clinical variables such as age at diagnosis, body mass index, prostate-specific antigen, Gleason score, pathologic T stage, and surgical margin and GRS models has better predictive power for BCR. The results of simulation data (statistical power = 0.707) and prostate cancer data (area under curve = 0.8462) show that DL-GRS has the best prediction performance. The rs455192 was the most relevant locus for BCR (p = 2.496 × 10-6) in our study.

Polygenic inheritance and its interplay with smoking history in predicting lung cancer diagnosis: a French-Canadian case-control cohort.

BACKGROUND: The most near-term clinical application of genome-wide association studies in lung cancer is a polygenic risk score (PRS). METHODS: A case-control dataset was generated consisting of 4002 lung cancer cases from the LORD project and 20,010 ethnically matched controls from CARTaGENE. A genome-wide PRS including >1.1 million genetic variants was derived and validated in UK Biobank (n = 5419 lung cancer cases). The predictive ability and diagnostic discrimination performance of the PRS was tested in LORD/CARTaGENE and benchmarked against previous PRSs from the literature. Stratified analyses were performed by smoking status and genetic risk groups defined as low (<20th percentile), intermediate (20-80th percentile) and high (>80th percentile) PRS. FINDINGS: The phenotypic variance explained and the effect size of the genome-wide PRS numerically outperformed previous PRSs. Individuals with high genetic risk had a 2-fold odds of lung cancer compared to low genetic risk. The PRS was an independent predictor of lung cancer beyond conventional clinical risk factors, but its diagnostic discrimination performance was incremental in an integrated risk model. Smoking increased the odds of lung cancer by 7.7-fold in low genetic risk and by 11.3-fold in high genetic risk. Smoking with high genetic risk was associated with a 17-fold increase in the odds of lung cancer compared to individuals who never smoked and with low genetic risk. INTERPRETATION: Individuals at low genetic risk are not protected against the smoking-related risk of lung cancer. The joint multiplicative effect of PRS and smoking increases the odds of lung cancer by nearly 20-fold. FUNDING: This work was supported by the CQDM and the IUCPQ Foundation owing to a generous donation from Mr. Normand Lord.

Association of genetic risk, lifestyle, and their interaction with obesity and obesity-related morbidities.

The extent to which modifiable lifestyle factors offset the determined genetic risk of obesity and obesity-related morbidities remains unknown. We explored how the interaction between genetic and lifestyle factors influences the risk of obesity and obesity-related morbidities. The polygenic score for body mass index was calculated to quantify inherited susceptibility to obesity in 338,645 UK Biobank European participants, and a composite lifestyle score was derived from five obesogenic factors (physical activity, diet, sedentary behavior, alcohol consumption, and sleep duration). We observed significant interaction between high genetic risk and poor lifestyles (pinteraction < 0.001). Absolute differences in obesity risk between those who adhere to healthy lifestyles and those who do not had gradually expanded with an increase in polygenic score. Despite a high genetic risk for obesity, individuals can prevent obesity-related morbidities by adhering to a healthy lifestyle and maintaining a normal body weight. Healthy lifestyles should be promoted irrespective of genetic background.

The impact of family-genetic risk scores on social functioning in individuals affected with six major psychiatric and substance use disorders in a Swedish National Sample.

To examine whether the level of genetic risk in psychiatric disorders impacts the social functioning of affected individuals, we examine the relationship between genetic risk factors for major depression (MD), anxiety disorders (AD), bipolar disorder (BD), non-affective psychosis (NAP), alcohol use disorder (AUD), and drug use disorder (DUD) in disordered individuals and five adverse social outcomes: unemployment, residence in areas of social deprivation, social welfare, early retirement, and divorce. We examine all cases with registration for these disorders from 1995 to 2015 in individuals born in Sweden. Genetic risk was assessed by the family genetic risk score (FGRS) and statistical estimates by Cox proportional hazard models. High genetic risk was significantly and modestly associated with poorer social outcomes in 23 of 30 analyses. Overall, genetic risk for MD, AD, AUD, and DUD impacted social functioning more strongly in affected individuals than did genetic risk for BD and NAP. Social welfare had the strongest associations with genetic risk, and residence in areas of high deprivation had the weakest. In individuals suffering from psychiatric and substance use disorders, high levels of genetic risk impact not only clinical features but also diverse measures of social functioning.

A novel SPAST gene splicing variant (c.1617-2A>C) in a heterozygous carrier with hereditary spastic paraplegia.

Hereditary spastic paraplegia (HSP) is a group of genetically heterogenous neurodegenerative disorders characterized by progressive spasticity and weakness of lower limbs. We report a novel splicing variant (c.1617-2A>C) of the SPAST gene in a heterozygous carrier from an Italian family with autosomal dominant HSP. The case study describes a pure form of spastic paraparesis with the cardinal clinical features of SPG4. The novel variant affects a canonical splice site and is likely to disrupt RNA splicing. We conclude that the c.1617-2A>C substitution is a null variant, which could be classified as pathogenic; its penetrance should be further investigated.

Characterizing the Relationship between Expression Quantitative Trait Loci (eQTLs), DNA Methylation Quantitative Trait Loci (mQTLs), and Breast Cancer Risk Variants.

PURPOSE: To assess the association of a polygenic risk score (PRS) for functional genetic variants with the risk of developing breast cancer. METHODS: Summary data-based Mendelian randomization (SMR) and heterogeneity in dependent instruments (HEIDI) were used to identify breast cancer risk variants associated with gene expression and DNA methylation levels. A new SMR-based PRS was computed from the identified variants (functional PRS) and compared to an established 313-variant breast cancer PRS (GWAS PRS). The two scores were evaluated in 3560 breast cancer cases and 3383 non-cancer controls and also in a prospective study (n = 10,213) comprising 418 cases. RESULTS: We identified 149 variants showing pleiotropic association with breast cancer risk (eQTLHEIDI > 0.05 = 9, mQTLHEIDI > 0.05 = 165). The discriminatory ability of the functional PRS (AUCcontinuous [95% CI]: 0.540 [0.526 to 0.553]) was found to be lower than that of the GWAS PRS (AUCcontinuous [95% CI]: 0.609 [0.596 to 0.622]). Even when utilizing 457 distinct variants from both the functional and GWAS PRS, the combined discriminatory performance remained below that of the GWAS PRS (AUCcontinuous, combined [95% CI]: 0.561 [0.548 to 0.575]). A binary high/low-risk classification based on the 80th centile PRS in controls revealed a 6% increase in cases using the GWAS PRS compared to the functional PRS. The functional PRS identified an additional 12% of high-risk cases but also led to a 13% increase in high-risk classification among controls. Similar findings were observed in the SCHS prospective cohort, where the GWAS PRS outperformed the functional PRS, and the highest-performing PRS, a combined model, did not significantly improve over the GWAS PRS. CONCLUSIONS: While this study identified potentially functional variants associated with breast cancer risk, their inclusion did not substantially enhance the predictive accuracy of the GWAS PRS.

Combined effects of genetic predisposition and sleep quality on acceleration of biological ageing: Findings from the UK biobank cohort.

OBJECTIVE: Genetic risks can accelerate ageing, yet better quality sleep may slow down it. We thus examined the interaction and combined effects of genetic predisposition and sleep quality on the risk of accelerate aging. METHODS: This study included 407,027 participants from the UK Biobank. Sleep index of each participant was retrieved from the following seven sleep behaviors: snoring, chronotype, daytime sleepiness, sleep duration, insomnia, nap and difficulties in getting up. The biological age (PhenoAge) were estimated by corresponding algorithms based on clinical traits, and their residual discrepancies with chronological age were defined as the age accelerations (PhenoAgeaccel). We explored the interaction and combined effects of genetic risk and sleep quality on accelerated ageing by constructing a linear model. RESULTS: Compared with participants in low sleep quality group, those in medium and high sleep quality group decreased 0.727 (95%CI, 0.653 to 0.801) and 1.056 (95%CI, 0.982 to 1.130) years of PhenoAgeaccel, respectively. Compared with participants in low genetic risk group, those in medium and high genetic risk group increased 0.833 (95%CI, 0.792 to 0.874) and 1.543 (95%CI, 1.494 to 1.592) years of PhenoAgeaccel, respectively. There was interaction between the genetic risk and sleep quality (P-interaction<0.001). For combined effect, compared to the group with high sleep quality and lower genetic risk, people with low sleep quality and high genetic risk had 2.747 (95%CI, 2.602 to 2.892) years higher PhenoAgeaccel. CONCLUSION: Our findings elucidate that better sleep quality could lessen accelerated biological ageing especially among population with high genetic risk.

The role of genetically-influenced phospholipid transfer protein activity in lipoprotein metabolism and coronary artery disease.

BACKGROUND: Phospholipid transfer protein (PLTP) transfers surface phospholipids between lipoproteins and as such plays a role in lipoprotein metabolism, but with unclear effects on coronary artery disease (CAD) risk. We aimed to investigate the associations of genetically-influenced PLTP activity with 1-H nuclear magnetic resonance (1H-NMR) metabolomic measures and with CAD. Furthermore, using factorial Mendelian randomization (MR), we examined the potential additional effect of genetically-influenced PLTP activity on CAD risk on top of genetically-influenced low-density lipoprotein-cholesterol (LDL-C) lowering. METHODS: Using data from UK Biobank, genetic scores for PLTP activity and LDL-C were calculated and dichotomised based on the median, generating four groups with combinations of high/low PLTP activity and high/low LDL-C levels for the factorial MR. Linear and logistic regressions were performed on 168 metabolomic measures (N = 58,514) and CAD (N = 318,734, N-cases=37,552), respectively, with results expressed as ß coefficients (in standard deviation units) or odds ratios (ORs) and 95% confidence interval (CI). RESULTS: Irrespective of the genetically-influenced LDL-C, genetically-influenced low PLTP activity was associated with a higher HDL particle concentration (ß [95% CI]: 0.03 [0.01, 0.05]), smaller HDL size (-0.14 [-0.15, -0.12]) and higher triglyceride (TG) concentration (0.04 [0.02, 0.05]), but not with CAD (OR 0.99 [0.97, 1.02]). In factorial MR analyses, genetically-influenced low PLTP activity and genetically-influenced low LDL-C had independent associations with metabolomic measures, and genetically-influenced low PLTP activity did not show an additional effect on CAD risk. CONCLUSIONS: Low PLTP activity associates with higher HDL particle concentration, smaller HDL particle size and higher TG concentration, but no association with CAD risk was observed.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning.

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (ß coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

T2DM/CKD genetic risk scores and the progression of diabetic kidney disease in T2DM subjects.

This study aimed at understanding the predictive potential of genetic risk scores (GRS) for diabetic kidney disease (DKD) progression in patients with type 2 diabetes mellitus (T2DM) and Major Cardiovascular Events (MCVE) and All-Cause Mortality (ACM) as secondary outcomes. We evaluated 30 T2DM and CKD GWAS-derived single nucleotide polymorphisms (SNPs) and their association with clinical outcomes in a central European cohort (n = 400 patients). Our univariate Cox analysis revealed significant associations of age, duration of diabetes, diastolic blood pressure, total cholesterol and eGFR with progression of DKD (all P < 0.05). However, no single SNP was conclusively associated with progression to DKD, with only CERS2 and SHROOM3 approaching statistical significance. While a single SNP was associated with MCVE - WSF1 (P = 0.029), several variants were associated with ACM - specifically CANCAS1, CERS2 and C9 (all P < 0.02). Our GRS did not outperform classical clinical factors in predicting progression to DKD, MCVE or ACM. More precisely, we observed an increase only in the area under the curve (AUC) in the model combining genetic and clinical factors compared to the clinical model alone, with values of 0.582 (95 % CI 0.487-0.676) and 0.645 (95 % CI 0.556-0.735), respectively. However, this difference did not reach statistical significance (P = 0.06). This study highlights the complexity of genetic predictors and their interplay with clinical factors in DKD progression. Despite the promise of personalised medicine through genetic markers, our findings suggest that current clinical factors remain paramount in the prediction of DKD. In conclusion, our results indicate that GWAS-derived GRSs for T2DM and CKD do not offer improved predictive ability over traditional clinical factors in the studied Czech T2DM population.

Addressing causal relationship between drinking behavior and metabolic syndrome: one-sample Mendelian randomization analysis.

AIMS: Alcohol drinking is associated with central obesity, hypertension, and hyperlipidemia, which further causes metabolic syndrome (MetS). However, prior epidemiological studies on such associations lack experimental evidence for a causal relationship. This study aims to explore the causal relationship between drinking behavior and MetS in Taiwan population by using Mendelian randomization (MR) analysis. METHODS: A cross-sectional study was conducted using the Taiwan Biobank database, which comprised 50 640 Han Chinese who were 30-70 years old without cancer from 2008 to 2020. In MR analysis, we constructed weighted and unweighted genetic risk scores by calculating SNP alleles significantly associated with alcohol drinking. We calculated odds ratios and 95% confidence interval (CI) by using a two-stage regression model. RESULTS: A total of 50 640 participants were included with a mean age of 49.5 years (SD: 1.67 years), 36.6% were men. The adjusted odds ratio (aOR) of MetS per 5% increase in the likelihood of genetic predisposition to drink based on weighted genetic risk score with adjustment was 1.11 (95% CI: 1.10, 1.12, P < .001). Analysis was also conducted by grouping the likelihood of genetic predisposition to drink based on quartiles with multivariate adjustment. Using Q1 as the reference group, the aORs of MetS for Q2, Q3, and Q4 were 1.19 (1.12, 1.27, p < .001), 1.31 (1.23, 1.40, p < .001), and 1.87 (1.75, 2.00, p < .001), respectively, for the weighted genetic risk score. CONCLUSIONS: This study shows a modest relationship between drinking behavior and MetS by using MR analysis.

Pulmonary function, genetic predisposition, and the risk of cirrhosis: A prospective cohort study.

OBJECTIVE: Pulmonary function is associated with the development of chronic liver disease. However, evidence of the association between pulmonary function and cirrhosis risk is still lacking. This study aimed to investigate the longitudinal associations of pulmonary function with the development of cirrhosis, and to explore whether genetic predisposition to cirrhosis could modify these associations. METHODS: Of 294,835 participants free of cirrhosis and had undergone spirometry at baseline from the UK Biobank were included. Cirrhosis diagnoses were ascertained through linked hospital records and death registries. Cox proportional hazard models were employed to investigate the longitudinal associations between pulmonary function, genetic predisposition, and cirrhosis risk. RESULTS: During a median follow-up of 12.0 years, 2598 incident cirrhosis cases were documented. Compared to individuals with normal spirometry findings, those with preserved ratio impaired spirometry (PRISm) findings (hazard ratio [HR] and 95% confidence interval [CI]: 1.32 [1.18, 1.48]) and airflow obstruction (HR [95%CI]: 1.19 [1.07, 1.31]) had a higher risk of developing cirrhosis after adjustments. These associations were consistent across all categories of genetic predisposition, with no observed modifying effect of genetic predisposition. In joint exposure analyses, the highest risk was observed in individuals with both a high genetic predisposition for cirrhosis and PRISm findings (HR [95% CI]: 1.74 [1.45, 2.08]). CONCLUSIONS: Our findings indicate that worse pulmonary function is a significant risk factor of cirrhosis, irrespective of genetic predisposition. Early identification and appropriate intervention for pulmonary function may lead to more effective healthcare resource utilization and reduce the burden associated with cirrhosis.

Dietary and genetic determinants of non-alcoholic fatty liver disease in coronary heart disease patients.

PURPOSE: A healthy diet reduces the risk of non-alcoholic fatty liver disease (NAFLD) in the general population, especially in individuals who are genetically predisposed to NAFLD. Little is known in patients who suffered from a myocardial infarction (MI). We examined the interaction between diet quality and genetic predisposition in relation to NAFLD in post-MI patients. METHODS: We included 3437 post-MI patients from the Alpha Omega Cohort. Diet quality was assessed with adherence to the Dutch Healthy Diet index 2015 (DHD15-index). A weighted genetic risk score (GRS) for NAFLD was computed using 39 genetic variants. NAFLD prevalence was predicted using the Fatty Liver Index. Prevalence ratios (PR) with 95% confidence intervals of DHD15-index and GRS in relation to NAFLD were obtained with multivariable Cox proportional hazards models. The interaction between DHD15-index and GRS in relation to NAFLD was assessed on an additive and multiplicative scale. RESULTS: Patients had a mean age of 69 (± 5.5) years, 77% was male and 20% had diabetes. The DHD15-index ranged from 28 to 120 with a mean of 73. Patients with higher diet quality were less likely to suffer from NAFLD, with a PR of 0.76 (0.62, 0.92) for the upper vs lower quintile of DHD15-index. No association between the GRS and NAFLD prevalence was found (PR of 0.92 [0.76, 1.11]). No statistically significant interaction between the DHD15-index and GRS was observed. CONCLUSION: In Dutch post-MI patients, adherence to the Dutch dietary guidelines was associated with a lower prevalence of NAFLD, as assessed by the FLI. This association was present regardless of genetic predisposition in this older aged cohort.

Associations of sleep behaviors and genetic risk with risk of incident osteoporosis: A prospective cohort study of 293,164 participants.

BACKGROUND: Unhealthy sleep behaviors are associated with higher risks of osteoporosis (OP), while prospective evidence is limited. This study aimed to prospectively investigate this association, quantify the attributable burden of OP incidence reduction due to unhealthy sleep behaviors, and explore potential modifications by genetic risk factors. METHODS: This longitudinal cohort study was conducted utilizing data from the UK Biobank, comprising 293,164 participants initially free of OP and with requisite sleep behaviors data at baseline. We followed the participants after recruitment until November 30, 2022, to ascertain incident OP. We assessed the associations of five sleep behaviors including sleep duration, chronotype, insomnia, daytime napping, and morning wake-up difficulties, as well as sleep behavior patterns identified based on the above sleep behaviors, with the risk of OP, using Cox models adjusted for multiple confounders. The analyses were then performed separately among individuals with different OP susceptibility, indexed by standard polygenetic risk scores(PRS) for OP. Our secondary outcome was OP with pathologic fracture. Subgroup and sensitivity analyses were performed. Additionally, attributable risk percent in the exposed population (AR%) and population attributable fraction (PAF) of sleep behaviors were calculated. RESULTS: Over a median follow-up of 13.7 years, 8253 new-onset OP cases were documented. Unhealthy sleep behaviors, such as long or short sleep duration, insomnia, daytime napping, morning wake-up difficulties, and unhealthy sleep patterns, were associated with elevated risks of OP (HRs ranging from 1.14 to 1.46, all P-value <0.001) compared to healthy sleep behaviors. Similar associations were observed for OP with pathologic fractures. Insomnia exhibited the largest AR% of 39.98 % (95%CI: 36.46, 43.31) and PAF of 33.25 % (95%CI: 30.00, 36.34) among healthy sleep patterns and components. A statistically significant multiplicative interaction was noted between sleep behaviors and OP PRS on OP risk (all P-interaction <0.001). CONCLUSIONS: Four unhealthy sleep behaviors and sleep behavior patterns were associated to increased OP risk, with insomnia contributing the most to OP incidence, while genetic risk for OP modified this association. These findings underscore the crucial role of adhering to healthy sleep behaviors for effective OP prevention.

Hospital-treated infectious diseases, genetic susceptibility and risk of type 2 diabetes: A population-based longitudinal study.

BACKGROUND: The longitudinal association between infectious diseases and the risk of type 2 diabetes (T2D) remains unclear. METHODS: Based on the UK Biobank, the prospective cohort study included a total of 396,080 participants without diabetes at baseline. We determined the types and sites of infectious diseases and incident T2D using the International Classification of Diseases 10th Revision codes (ICD-10). Time-varying Cox proportional hazard model was used to assess the association. Infection burden was defined as the number of infection episodes over time and the number of co-occurring infections. Genetic risk score (GRS) for T2D consisted of 424 single nucleotide polymorphisms. RESULTS: During a median of 9.04 [IQR, 8.3-9.7] years of follow-up, hospital-treated infectious diseases were associated with a greater risk of T2D (adjusted HR [aHR] 1.54 [95 % CI 1.46-1.61]), with risk difference per 10,000 individuals equal to 154.1 [95 % CI 140.7-168.2]. The heightened risk persisted after 5 years following the index infection. Bacterial infection with sepsis had the strongest risk of T2D (aHR 2.95 [95 % CI 2.53-3.44]) among different infection types. For site-specific analysis, bloodstream infections posed the greatest risk (3.01 [95 % CI 2.60-3.48]). A dose-response association was observed between infection burden and T2D risk within each GRS tertile (p-trend <0.001). High genetic risk and infection synergistically increased the T2D risk. CONCLUSION: Infectious diseases were associated with an increased risk of subsequent T2D. The risk showed specificity according to types, sites, severity of infection and the period since infection occurred. A potential accumulative effect of infection was revealed.

Genome-wide association study of BNT162b2 vaccine-related myocarditis identifies potential predisposing functional areas in Hong Kong adolescents.

Vaccine-related myocarditis associated with the BNT162b2 vaccine is a rare complication, with a higher risk observed in male adolescents. However, the contribution of genetic factors to this condition remains uncertain. In this study, we conducted a comprehensive genetic association analysis in a cohort of 43 Hong Kong Chinese adolescents who were diagnosed with myocarditis shortly after receiving the BNT162b2 mRNA COVID-19 vaccine. A comparison of whole-genome sequencing data was performed between the confirmed myocarditis cases and a control group of 481 healthy individuals. To narrow down potential genomic regions of interest, we employed a novel clustering approach called ClusterAnalyzer, which prioritised 2,182 genomic regions overlapping with 1,499 genes for further investigation. Our pathway analysis revealed significant enrichment of these genes in functions related to cardiac conduction, ion channel activity, plasma membrane adhesion, and axonogenesis. These findings suggest a potential genetic predisposition in these specific functional areas that may contribute to the observed side effect of the vaccine. Nevertheless, further validation through larger-scale studies is imperative to confirm these findings. Given the increasing prominence of mRNA vaccines as a promising strategy for disease prevention and treatment, understanding the genetic factors associated with vaccine-related myocarditis assumes paramount importance. Our study provides valuable insights that significantly advance our understanding in this regard and serve as a valuable foundation for future research endeavours in this field.

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.

Inflammatory bowel disease and rheumatoid arthritis share a common genetic structure.

Background: The comorbidity rate of inflammatory bowel disease (IBD) and rheumatoid arthritis (RA) is high; nevertheless, the reasons behind this high rate remain unclear. Their similar genetic makeup probably contributes to this comorbidity. Methods: Based on data obtained from the genome-wide association study of IBD and RA, we first assessed an overall genetic association by performing the linkage disequilibrium score regression (LDSC) analysis. Further, a local correlation analysis was performed by estimating the heritability in summary statistics. Next, the causality between the two diseases was analyzed by two-sample Mendelian randomization (MR). A genetic overlap was analyzed by the conditional/conjoint false discovery rate (cond/conjFDR) method.LDSC with specific expression of gene analysis was performed to identify related tissues between the two diseases. Finally, GWAS multi-trait analysis (MTAG) was also carried out. Results: IBD and RA are correlated at the genomic level, both overall and locally. The MR results suggested that IBD induced RA. We identified 20 shared loci between IBD and RA on the basis of a conjFDR of <0.01. Additionally, we identified two tissues, namely spleen and small intestine terminal ileum, which were commonly associated with both IBD and RA. Conclusion: Herein, we proved the presence of a polygenic overlap between the genetic makeup of IBD and RA and provided new insights into the genetic architecture and mechanisms underlying the high comorbidity between these two diseases.