As whole-genome sequencing (WGS) is increasingly used in clinical and public health contexts, clearer expectations regarding the amount of variation present in the “average” human genome are required to contextualise findings. We analysed WGS data from two large population cohorts: 490,541 individuals in UK Biobank (UKB) and 414,830 individuals in All of Us. Following variant and genotype QC, we aimed to assess the range of neutral and disease-associated variation across six genetically-inferred ancestry groups. The “average” genome contains 4.3–5.3 million variants, of which 1.5
Trans-ancestry polygenic risk scores (PRSs) have been proposed to address the limited transferability of European-specific PRSs to East Asian populations. However, their ability to improve risk prediction for coronary artery disease (CAD) in the Chinese population remains unclear. We aimed to develop and validate a trans-ancestry CAD PRS in the Chinese population by integrating European and East Asian genome-wide association studies (GWAS). Using summary statistics from large-scale CAD GWAS meta-analyses of East Asian and European populations, we constructed trans-ancestry PRSs via PRS-CSx in two configurations: PRS-meta, derived exclusively from GWAS results and linkage disequilibrium reference panels; and PRS-combine, optimized in a Chinese training set comprising 2,800 CAD cases and 2,055 controls. For comparison, we generated East Asian-specific PRSs using LDpred and pruning-and-thresholding methods, and additionally evaluated previously published CAD PRSs. The top-performing PRSs for each method in the training set were then externally validated in 72,782 individuals with genetic data from the China Kadoorie Biobank (CKB), a large-scale population-based cohort in China, with a mean follow-up of 12.1 years. In the training set, PRS-meta and PRS-combine exhibited comparable predictive performance, with odds ratios per standard deviation (SD) of 2.21 (95
Sonic hedgehog (SHH) medulloblastoma (MB) accounts for approximately one-third of all MB cases, the most common malignant brain tumor in children. Despite therapy, SHH MB relapse is frequent and has a dismal prognosis. New treatments for recurrent SHH MB are needed; however, the molecular drivers of relapse are poorly understood. We profiled 22 SHH MB specimens (16 primary and 6 recurrent), including four primary–recurrent patient pairs, using overlapping single-nucleus RNA sequencing (snRNA-seq; n = 16), single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq; n = 13), and spatial transcriptomic (n = 6) cohorts. We integrated these data with exome-derived variant calls from 25 specimens, including seven patients with primary and recurrent samples. Bulk RNA-seq data from 48 specimens representing 24 primary–recurrent pairs were used for validation. Our analyses show evidence of positive selection for nonsynonymous tumor mutations, including TP53 mutations involving its DNA-binding and tetramerization domains. TP53 mutations were associated with reduced base-excision repair (BER) gene expression and accessibility of linked cis-regulatory regions. Recurrent tumors showed increased tumor mutational burden (TMB) and an endoplasmic-reticulum (ER) stress expression program associated with poorer survival. Angiogenic gene expression and inferred immunosuppressive myeloid signaling were increased in recurrent disease. These data define recurrence-associated cellular and regulatory programs, nominate candidate therapeutic targets and prognostic markers, and provide a single-cell and spatial atlas of SHH MB.
Accurate germline variant classification requires correct application of ACMG/AMP evidence criteria and assignment of pathogenicity to a specific disease entity and mode of inheritance. Whether laboratories apply this disease-specific approach consistently to genes associated with multiple disorders remains insufficiently characterized. We conducted a national interlaboratory study of germline variant classification using a proficiency-testing dataset comprising 13 variants across five clinical scenarios from 128 Chinese clinical genetic laboratories. Overall concordance was achieved for 6 of 13 variants, whereas 7 showed clinically meaningful cross-category discordance. Residual disagreement was partly attributable to omission or inappropriate use of ACMG/AMP evidence criteria, inconsistent strength assignment, and disease-context-specific interpretation. A prominent pattern of discordance involved disease-specific interpretation of variants in genes associated with multiple disorders. For variants in APOB, LZTR1, MYH7, and EPCAM, laboratories frequently transferred pathogenic assertions across disorders without adequately considering disease mechanism, inheritance pattern, or disorder-specific validity. By contrast, two GJB2 variants showed substantially higher categorical concordance. These errors could alter downstream clinical interpretation and, in some cases, implied management recommendations. Disease-specific classification in multi-disease genes remains an important source of residual discordance despite improved criterion-level harmonization. Harmonization efforts should therefore extend beyond gene-level pathogenicity assessment toward mechanism-aware, disease-anchored classification frameworks and reporting practices. Not applicable.
Somatic mutations commonly accumulate in histologically normal tissues and contribute to cancer development. However, many mutations that are common in normal tissue are also found in cancers from the same organ, making their role in malignant progression unclear. To address this, we asked whether such mutations increase cell proliferation and survival to different degrees at different steps of esophageal tumor development, and whether they alter selection for other driver mutations. We used a quantitative evolutionary framework to distinguish underlying mutation rate from selection across two steps of esophageal development: from organogenesis to clonal histologically normal esophageal epithelium, and from that tissue to esophageal squamous-cell carcinoma. Analyzing sequence data from 2171 samples, we estimated step-specific selection on recurrent somatic mutations, corresponding to increased cellular division and survival, and tested whether mutations in one gene earlier in the trajectory changed selection for mutations on another. We additionally examined somatic copy-number alterations and single-cell transcriptomic profiles to contextualize these evolutionary patterns within broader genomic and cellular changes during progression. NOTCH1 mutations were strongly selected during the clonal expansion of histologically normal esophageal epithelium, explaining their high prevalence in that tissue. However, for the first time, we show that there is little to no positive selection for NOTCH1, NOTCH2, and FAT1 mutations during progression from clonal histologically normal esophageal tissue to esophageal squamous-cell carcinoma in humans, leading to a conclusion that these alterations promote clonal expansion in normal tissue, but do not drive malignant progression from established normal clones. Moreover, we provide a somatic genetic basis for this step-specific effect: we demonstrate for the first time that mutations in NOTCH1 exhibit antagonistic epistasis with mutations of TP53 and RB1, reducing selection for these key tumor suppressor alterations during tumor development. Consistent with this model, copy-number alterations associated with later ESCC progression were more strongly selected in TP53-mutant samples, supporting the idea that TP53 disruption promotes a genomic context more permissive for malignant evolution. Early somatic mutations can promote clonal expansion in normal tissue without promoting cancer, and in some cases may limit progression by reducing selection for later driver events. NOTCH1 and other genes can shape evolutionary trajectories in ways that ultimately constrain malignant progression. By separating mutation rate from selection, quantifying step-specific genetic interactions, and considering broader changes in genomic and cellular context, our study shows that the effects of recurrent mutations depend strongly on disease stage and mutational context—what promotes clonal expansion in normal tissue may later impede growth or survival in tumors. These insights underscore the need for precision strategies that account for the shifting fitness landscape across premalignant and malignant stages, informing early detection, prevention, and therapeutic prioritization.
