East Asian-specific and cross-ancestry genome-wide meta-analyses provide mechanistic insights into peptic ulcer disease

Abstract

Peptic ulcer disease (PUD) refers to acid-induced injury of the digestive tract, occurring mainly in the stomach (gastric ulcer; GU) or duodenum (duodenal ulcer; DU). We conducted a large-scale cross-ancestry meta-analysis of PUD combining genome-wide association studies with four Japanese and two European studies (52,032 cases and 905,344 controls), and discovered 25 novel loci highly concordant across ancestries. Based on these loci, an examination of similarities and differences in genetic architecture between GU and DU demonstrated that GU shared the same risk loci as DU, although with smaller genetic effect sizes and higher polygenicity than DU, indicating higher heterogeneity of GU. H. pylori (HP)-stratified analysis found an HP-related host genetic locus, marking its role in HP-mediated PUD etiology. Integrative analyses using bulk and single-cell transcriptome profiles highlighted the genetic factors of PUD to be enriched in the highly expressed genes in stomach tissues, especially in somatostatin-producing D cells. Our results provide genetic evidence that gastrointestinal cell differentiations and hormone regulations are critical in PUD etiology.

Recent Advances in Molecular Pathways and Therapeutic Implications for Peptic Ulcer Management: A Comprehensive Review

“…NSAIDs and peptic ulcer development, discontinuation or avoidance of NSAIDs is a crucial step in managing PUD. NSAIDs, including aspirin, elevate the risk of peptic ulcer disease and are linked to increased complications, making their cessation an integral component of initial management [68].…”

Proteogenomics in cerebrospinal fluid and plasma reveals new biological fingerprint of cerebral small vessel disease

“…To assess the causal association between serum protein levels of cSVD-associated proteins and stroke, in individuals of East-Asian ancestry, we conducted two-sample MR analyses in BioBank Japan (BBJ, rst cohort study 115 cardioembolic stroke (N=747), and small vessel stroke (N=4,876) were obtained in the BBJ rst cohort using REGENIE v3.2.9 (adjusted for age, sex, and the rst 10 genotype principal components), excluding the samples used for proteomic pro ling. Genotyping, quality control, and imputation for BBJ samples used in the stroke GWASs were conducted as previously described 119 , except that the imputation was performed using a reference panel combining the 1000 Genome Project phase 3 v5 reference panel and 3256 Japanese samples (JEWEL3k) samples 120 . Individuals without any type of stroke or cerebral aneurysm were used as controls.…”

TEMR: Trans-ethnic Mendelian Randomization Method using Large-scale GWAS Summary Datasets

“…However, a noteworthy challenge surfaces as the bulk of available large-scale datasets predominantly stem from European populations, such as the UK Biobank (UKB) [3][4][5][6][7] and FinnGen consortium [8] , while sample sizes for other ethnicities, notably Central/South Asian, East Asian, African, Hispanic, etc. remain comparatively limited [9][10][11][12] . Take the East Asian population as an example, despite the substantial data provided by the BioBank Japan (BBJ) [11][12] , Taiwan Biobank (TWB) [13] and China Kadoorie Biobank (CKB) [14] for the East Asian population (> 100,000 individuals), it falls short of the extensive dataset available from the UKB (> 500,000 individuals) or FinnGen consortium (> 620,000 individuals).…”

“…Take the East Asian population as an example, despite the substantial data provided by the BioBank Japan (BBJ) [11][12] , Taiwan Biobank (TWB) [13] and China Kadoorie Biobank (CKB) [14] for the East Asian population (> 100,000 individuals), it falls short of the extensive dataset available from the UKB (> 500,000 individuals) or FinnGen consortium (> 620,000 individuals). Moreover, the UKB incorporates a substantial amount of omics data, including imaging omics [4] , exomes [5] , proteomics [6] and metabolomics [7] -BBJ, TWB and CKB have significantly smaller sample sizes and may also lack some omics data [12] . Furthermore, omics databases dedicated to other ethnicities tend to exhibit relatively smaller sample sizes [15][16][17][18][19][20][21] .…”