Chronic obstructive pulmonary disease (COPD) remains a major public health burden, yet early risk prediction remains limited. Using Cox regression and multi-machine learning, we analyzed plasma proteomic data from 36,906 UK Biobank participants and identified nine proteins including GDF15, WFDC2, SCGB1A1, CXCL17, CA14, EDA2R, TNR, AGER, and ODAM. The 9-protein model achieved high accuracy for predicting COPD across different time frames (area under the curve [AUC] = 0.83 overall; 0.86 within 5 years; 0.84 within 10 years; 0.77 beyond 10 years) in a geographically defined UKB testing cohort (n = 15,607), and were further validated in the external EPIC-Norfolk cohort (n = 2,944) with similarly high AUCs. Consistent results were observed in the Southern China cohort (n = 100). Incorporating clinical factors further improved the predictive accuracy, achieving maximum AUCs of 0.89 overall, 0.91 for 5-year prediction, 0.89 for 10-year prediction and 0.83 for prediction beyond 10 years. Individuals with higher baseline protein levels had an 7.29-fold increased COPD risk, and proteomic alterations were detectable up to 16 years before diagnosis. All nine proteins showed significant positive genetic correlations with COPD and causal inference analyses further supported roles for CXCL17 and AGER. These findings demonstrate that plasma proteomics enables accurate long-term COPD risk prediction across diverse populations, provides new insights into disease mechanisms, and supports early identification of high-risk individuals for targeted prevention.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health challenge, yet preclinical identification remains difficult owing to a lack of reliable predictive tools. Here we show that a panel of five plasma proteins, FUOM, ACY1, KRT18, CDHR2 and GGT1, identified and validated across over 50,000 participants from the Southern UK, Northern UK, EPIC-Norfolk and Southern China cohorts, serves as a predictive signature for incident MASLD. Our five-protein model achieves predictive accuracy of 0.838 (5 year area under the curve (AUC)) and 0.756 (16.6 year AUC), with performance sustained longitudinally in the EPIC-Norfolk cohort (16.6 year AUC = 0.710) and confirmed in the Southern China Inception Cohort (AUC = 0.912). Integrating these biomarkers with routine clinical data further enhances performance (5 year AUC = 0.904; 16.6 year AUC = 0.822). These findings establish a scalable proteomic framework for ultra-early risk stratification and targeted intervention in MASLD up to 16 years before clinical onset.

BACKGROUND:Gastroesophageal reflux disease (GERD) and asthma are commonly co-occurring conditions, with shared genetic factors identified. However, the specific loci and the influence of common genetic architecture remain undefined. METHODS:We obtained genome-wide association study (GWAS) summary statistics for GERD (71 522 cases and 261 079 controls) and asthma (56 167 cases and 352 255 controls). Using linkage disequilibrium score regression (LDSC), we assessed genetic correlations between GERD and asthma. Bidirectional Mendelian randomization (MR) was performed to investigate potential causal relationships, followed by cross-trait GWAS meta-analysis and colocalization analysis to identify shared risk loci. Additionally, summary-data-based MR and transcriptome-wide association study were conducted to pinpoint common functional genes. Finally, we analyzed gene expression profiles in both healthy individuals and GERD patients using esophageal single-cell RNA sequencing (scRNA-seq) data. RESULTS:We identified a significant genetic correlation between GERD and asthma ( rg  = 0.37, P = 6.19 × 10 -38 ) and a significant causal effect of GERD on asthma [odds ratio (OR) = 1.22, P = 1.54 × 10 -5 ]. Cross-trait meta-analyses revealed 56 shared risk loci between GERD and asthma, including 51 loci that were newly identified. Three loci (rs61937247, rs7960225, and rs769670) exhibited evidence of colocalization. Gene-level analyses pinpointed three novel shared genes ( RBM6, SUOX , and MPHOSPH9 ) between GERD and asthma. scRNA-seq analysis uncovered heightened expression of these genes in immune cells of patients diagnosed with GERD. CONCLUSION:Our study has discovered novel shared genetic loci and candidate genes between GERD and asthma, providing further insights into the genetic susceptibility of comorbidity and potential mechanisms of the two diseases.

Early identification of metabolic dysfunction-associated steatotic liver disease (MASLD) is crucial for preventing disease progression, yet reliable predictive tools remain lacking. We analyzed proteomics data of 37,966 participants without baseline MASLD from southern United Kingdom, using multivariable Cox regression to conduct protein selection and model development. The top-ranking proteins were combined with clinical data and polygenic risk scores to develop models. The models were internally validated through 1,000 times bootstrap resampling within the Southern UK cohort, and externally validated in a preclinical Northern UK cohort (n = 14,986) and an inception Southern China cohort (n = 100). Cumulative MASLD incidences were compared across baseline protein concentration quintiles, and temporal trends in protein levels were assessed. Of the 2,737 proteins analyzed, five emerged as robust predictors for MASLD incidence within 5 years: CDHR2 (AUC = 0.812), GGT1 (AUC = 0.797), FUOM (AUC = 0.791), KRT18 (AUC = 0.789) and ACY1 (AUC = 0.777). Participants with higher baseline levels of these proteins faced markedly increased risks of MASLD (HRs = 7.05 - 9.81). In the Northern UK cohort, the combination of 5 proteins showed prominent validated predictive accuracy across different time frames: 5-year (AUC = 0.838), 10-year (AUC = 0.772), over 10-year (AUC = 0.742), all-time (AUC = 0.756). Combined with clinical predictors, the predictive performance is further enhanced: 5-year (AUC = 0.904), 10-year (AUC = 0.848), over 10-year (AUC = 0.799), all-time (AUC = 0.822). In the Southern China Inception cohort, the 5-Protein Panel also showed an outstanding performance (AUC = 0.912). Our study identified five key proteins, established and validated prominent predictive models of MASLD up to more than 16 years before onset, offering novel potential strategies for ultra-early prediction and intervention.

Reliable tools for early identification of Crohn's disease (CD) remain lacking. We analyzed 2736 plasma proteins in 39,634 UK Biobank (UKB) participants and identified 44 associated with incident CD. CD274, CHI3L1, REG1B, ITGAV, PRSS8, ITGA11, GDF15, DEFA1_DEFA1B, and IL6 ranked highest in protein importance ordering. A machine learning model based on these 9 proteins achieved high prediction for CD in a geographically distinct UKB testing cohort (n = 13,262, AUC 0.76), outperforming clinical risk models. It was externally validated in EPIC-Norfolk (n = 2944, AUC 0.73) and exhibited high discriminatory capacity for CD in the cross-sectional Southern China cohort (n = 74, AUC 0.79). In the UKB testing cohort, combining proteins with clinical data improved predictive performance (AUC 0.78) up to 16 years pre-diagnosis. In the same cohort, individuals at high risk stratified by the protein model were 4.23 times more likely to develop CD. Our findings highlight proteomics-based models as a promising approach to predict CD up to 16 years before diagnosis, offering opportunities for early screening and intervention.

Background: Inflammatory bowel disease (IBD) is a chronic condition affecting individuals across all age groups. However, the association between IBD and biological aging remains unclear. Methods: We utilized data from the UK Biobank and the diverse cohort of the All of Us (AoU) Research Programme to investigate the role of biological aging in the development of IBD and its subtypes. Biological age was assessed using the Klemera-Doubal method (KDMAge) and phenotypic biological age (PhenoAge), with KDMAgeAccel and PhenoAgeAccel defined as the residuals of chronological age minus KDMAge and PhenoAge, respectively. We assessed the impact of accelerated biological aging on life expectancy in patients with IBD through survival analysis. Additionally, we examined genetic susceptibility and its potential mediating effects on the association between biological aging and IBD. Findings: In the UK Biobank, accelerated biological aging was associated with an increased risk of IBD (KDMAgeAccel: HR 1.22, 95% CI 1.13-1.32; PhenoAgeAccel: HR 1.57, 95% CI 1.46-1.69). This association was further validated in the AoU cohort, where PhenoAgeAccel was also linked to an elevated risk of IBD (HR 1.57, 95% CI 1.18-2.09). An additive interaction was observed between accelerated biological aging and genetic risk for IBD. Individuals with both high genetic risk and accelerated aging exhibited the highest risk of developing IBD (KDMAgeAccel: HR 1.36, 95% CI 1.20-1.53; PhenoAgeAccel: HR 1.59, 95% CI 1.41-1.79). Life expectancy analysis indicated that IBD patients with accelerated biological aging experienced a significant reduction in life expectancy, with an average decrease of 1.36 years (KDMAgeAccel) and 1.95 years (PhenoAgeAccel). Mediation analyses suggested that accelerated biological aging partially mediated the protective effects of dried fruit and cooked vegetables on the risk of developing IBD. Results from multistate modelling showed that PhenoAgeAccel was also significantly associated with an increased risk of IBD occurrence to mortality (HR 1.44 [95% CI 1.17-1.77]). Interpretation: Biological aging is significantly associated with the risk of IBD and its subtypes, especially in individuals with high genetic susceptibility, and it reduces life expectancy in these patients. Identifying individuals with accelerated biological aging can serve as a marker for the effective prevention and management of IBD.

BACKGROUND:Digestive diseases affect patient health while highlighting challenges in socioeconomic development and health care system accessibility and efficiency. This analysis offers insights into digestive disease control by examining the burden, identifying risk factors, and forecasting trends to 2030. METHODS:Using the Global Burden of Disease (GBD) 2021 data to assess the burden of 17 digestive diseases, we analyzed incidence, prevalence, mortality, and disability-adjusted life years (DALYs). We analyzed the historical trends and their burden attributable to Level 1 and 2 risk factors. We conducted a Bayesian age-period-cohort (BAPC) analysis to forecast trends to 2030. RESULTS:In 2021, enteric infections were the primary contributors to age-standardized incidence, mortality, and DALYs rates within digestive diseases, while cirrhosis accounted for the highest prevalence rate. The DALYs attributable to risk factors were estimated at 4.01 million for males and 1.01 million for females. The leading Level 2 risk factor was poor sanitation. Alcohol use, tobacco, and high BMI are shared risk factors contributing to DALYs. We project a decline in incidence rate among females to 2030, accompanied by a rise in prevalence. CONCLUSIONS:Although mortality and DALYs will decrease, digestive diseases such as enteric infections and cirrhosis remain critical challenges, particularly in low- and middle-income countries. Governments must prioritize the management of risk factors and strengthen pandemic preparedness to alleviate future strain.

Frailty has become a major public health issue, but its association with Metabolic dysfunction-associated steatotic liver disease (MASLD) remains controversial. We conducted an observational study of frailty and MASLD using the frailty index (FI) and frailty phenotype (FP) in the UK Biobank. And the results were validated in the National Health and the All of Us Research Program (AoU) database. We explored the causal relationship and genetic correlation between frailty and MASLD. In the UK population, both pre-frail and frail individuals had increased risks of MASLD in the analyses of FI and FP. Notably, the odds ratios of FI to the occurrence of MASLD were even more significant in our study in the US population. The odds ratios were 2.75 ([95% CI 2.41-3.15]; P<0.001) for pre-frailty and 6.88 (95% CI 6.02-7.90; P<0.001) for frailty. There was significant causality (OR 2.00; [95% CI 1.40-2.86]; P<0.001) and positive genetic correlations (LDSC: rg =0.576, P<0.001; GNOVA: rg =0.777, P<0.001; ρ-HESS: rg =0.828) between FP and MASLD. Frailty greatly increases the risk of developing MASLD. There was a significant causal and positive genetic correlation between FP and MASLD.

Zhang, Lijun MD; Chen, Dong BS; Long, Yu MD; Li, Lingyi MD; Lyu, Yanlin MD; Meng, Meijun MD; Ma, Yuying MD; Wu, Yanjun MD; Leung, Felix W MD; Sha, Weihong MD; Chen, Hao PhD; Liu, Yufeng MD, PhD Author Information

Objective Cholelithiasis and gastroesophageal reflux disease (GERD) contribute to significant health concerns. We aimed to investigate the potential observational, causal, and genetic relationships between cholelithiasis and GERD.Design The observational correlations were assessed based on the prospective cohort study from UK Biobank. Then, by leveraging the genome-wide summary statistics of cholelithiasis (N = 334,277) and GERD (N = 332,601), the bidirectional causal associations were evaluated using Mendelian randomization (MR) analysis. Subsequently, a series of genetic analyses was used to assess the genetic correlation, shared loci, and genes between cholelithiasis and GERD.Results The prospective cohort analyses revealed a significantly increased risk of GERD in individuals with cholelithiasis (hazard ratio [HR] = 1.99; 95% confidence interval [CI], 1.89-2.10) and a higher risk of cholelithiasis among patients with GERD (HR = 2.30; 95% CI, 2.18-2.44). The MR study indicated the causal effect of genetic liability to cholelithiasis on the incidence of GERD (odds ratio [OR] = 1.08; 95% CI, 1.05-1.11) and the causal effect of genetic predicted GERD on cholelithiasis (OR = 1.15; 95% CI, 1.02-1.31). In addition, cholelithiasis and GERD exhibited a strong genetic association. Cross-trait meta-analyses identified 5 novel independent loci shared between cholelithiasis and GERD. Three shared genes, including SUN2, CBY1, and JOSD1, were further identified as novel risk genes.Conclusion The elucidation of the shared genetic basis underlying the phenotypic relationship of these 2 complex phenotypes offers new insights into the intrinsic linkage between cholelithiasis and GERD, providing a novel research direction for future therapeutic strategy and risk prediction.

Despite advances in research, studies on predictive models for Non-Alcoholic Fatty Liver Disease (NAFLD)-related fibrosis remain limited. Identifying new biomarkers to distinguish Non-Alcoholic Steatohepatitis (NASH) from NAFLD would aid in the treatment of NASH. Gene expression and clinical profiles of NAFL and NASH patients were collected from databases. Differentially expressed genes with prognostic value were used to construct predictive model. Validation of fibrosis stage-related pyroptosis-related genes (PRGs) was performed using Sprague-Dawley rats liver fibrosis models induced by CCl4 or PS. Immune cell infiltration assessment demonstrated that stromal score, immune score, and ESTIMATE score were higher in patients with NASH compared to those with NAFL. BAX, BAK1, PYCARD, and NLRP3 were identified as hub genes that exhibit a strong correlation with fibrosis stage. Additionally, the expression of these genes was increased in fibrotic liver tissues induced by CCl4 and PS. The pyroptosis-associated gene signature effectively predicts the degree of liver fibrosis in NASH patients. Our study indicates that BAX, BAK1, PYCARD, and NLRP3 might serve as biomarkers for NASH-associated fibrosis.

BACKGROUND:Early-life tobacco exposure exerts adverse effects significantly impacting long-term health; however, the comprehensive association with multiple digestive diseases and its implications for accelerated disease progression remain unclear. MATERIALS AND METHODS:Early-life tobacco exposure was measured based on in utero exposure to tobacco and age of smoking initiation among participants from the UK Biobank and LifeLines. Outcomes were 11 digestive diseases. To analyze the link between early-life tobacco exposure and digestive diseases, logistic regression and Cox proportional hazards models were applied. A multistate model was applied to examine the impact of early tobacco exposure on the progression in digestive disease status. Mediation effects of biological aging acceleration and Linkage Disequilibrium Score Regression between early-life tobacco exposure and digestive diseases were additionally analyzed. RESULTS:The hazard ratios and 95% confidence intervals for participants exposed to tobacco in utero or who began smoking during childhood were 1.10 (1.09-1.12) or 1.32 (1.28-1.35) for any digestive disease in the UK Biobank. Repeated analyses in the LifeLines cohort, and genetic correlation analysis confirmed these elevated risks. Accelerated biological aging plays a mediating role of 3% to 20% in these associations. The risks of digestive diseases were increased in all genetic risk categories, with a 17% to over fourfold increase in the high-risk group. Critically, childhood and adolescence smoking initiation increased the risk of transitioning from any digestive disease to death increased by 59% and 40%. CONCLUSION:Early-life tobacco exposure significantly increases risks of digestive diseases in two large cohorts, independent of genetic susceptibility and mediated by biological aging acceleration. It also accelerates progression from digestive disease to death, leading to severe outcomes and higher surgical need. Our findings help the identification of high-risk individuals and highlight the importance of preventing tobacco exposure during early life to mitigate digestive disease risk and mortality, and associated surgical burden.

Background:Irritable bowel syndrome (IBS) significantly impacts individuals due to its prevalence and negative effect on quality of life. Current genome-wide association studies (GWAS) have only identified a small number of crucial single nucleotide polymorphisms (SNPs), not fully elucidating IBS's pathogenesis.Objective:To identify genomic loci at which common genetic variation influences IBS susceptibility.Methods:Combining independent cohorts that in total comprise 65 840 cases of IBS and 788 652 controls, the authors performed a meta-analysis of genome-wide association studies (GWAS) of IBS. The authors also carried out gene mapping and pathway enrichment to gain insights into the underlying genes and pathways through which the associated loci contribute to disease susceptibility. Furthermore, the authors performed transcriptome analysis to deepen their understanding. IBS risk models were developed by combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. The authors detect the phenotype association for IBS utilizing PRS-based phenome-wide association (PheWAS) analyses, linkage disequilibrium score regression, and Mendelian randomization.Results:The GWAS meta-analysis identified 10 IBS risk loci, seven of which were novel (rs12755507, rs34209273, rs34365748, rs67427799, rs2587363, rs13321176, rs1546559). Multiple methods identified nine promising IBS candidate gene (PRRC2A, COP1, CADM2, LRP1B, SUGT1, MED12L, P2RY14, PHF2, SHISA6) at 10 GWAS loci. Transcriptome validation also revealed differential expression of these genes. Phenome-wide associations between PRS-IBS and nine traits (neuroticism, diaphragmatic hernia, asthma, diverticulosis, cholelithiasis, depression, insomnia, COPD, and BMI) were identified. The six diseases (asthma, diaphragmatic hernia, diverticulosis, insomnia major depressive disorder and neuroticism) were found to show genetic association with IBS and only major depressive disorder and neuroticism were found to show causality with IBS.Conclusion:The authors identified seven novel risk loci for IBS and highlighted the substantial influence on genetic risk harbored. The authors' findings offer novel insights into etiology and phenotypic association of IBS and lay the foundation for therapeutic targets and interventional strategies.

BACKGROUND:Emerging observational studies have indicated the association between autism spectrum disorder (ASD) and IBD, including Crohn's disease (CD) and ulcerative colitis (UC), whereas the causality remains unknown. METHODS:Summary-level data from large-scale genome-wide association (GWAS) studies of IBD and ASD were retrieved. Mendelian randomisation analyses were performed with a series of sensitivity tests. RESULTS:Genetic predisposition to ASD was not associated with the risk of IBD (odds ratio [OR] = 0.99, 95% confidence interval [CI = 0.91-1.06, p = 0.70; OR [95% CI]: 1.03 [0.93-1.13], p = 0.58 for CD; OR [95% CI]: 0.96 [0.87-1.05], p = 0.37 for UC) in the IIBDGC dataset. In the FinnGen dataset, their causal effects were unfounded (OR [95% CI]: 1.04 [0.94-1.15], p = 0.49 for IBD; OR [95% CI]: 1.08 [0.89-1.31], p = 0.42 for CD; OR [95% CI]: 1.00 [0.88-1.13], p = 0.95 for UC). In the meta-analysis of two datasets, the OR was 1.01 (95% CI 0.96-1.07, p = 0.45). For the risk of ASD under genetic liability to IBD, the OR from meta-analysis was 1.03 (95% CI 1.01-1.05, p = 0.01). CONCLUSION:Our findings indicate genetic predisposition to ASD might not increase the risk of IBD, whereas genetic liability to IBD is associated with an increased risk of ASD. Further investigations using more powerful datasets are warranted.