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Background The outbreak of coronavirus disease (COVID-19) was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), through its surface spike glycoprotein (S-protein) recognition on the receptor Angiotensin-converting enzyme 2 (ACE2) in humans. However, it remains unclear how genetic variations in ACE2 may affect its function and structure, and consequently alter the recognition by SARS-CoV-2. Methods We have systemically characterized missense variants in the gene ACE2 using data from the Genome Aggregation Database (gnomAD; N = 141,456). To investigate the putative deleterious role of missense variants, six existing functional prediction tools were applied to evaluate their impact. We further analyzed the structural flexibility of ACE2 and its protein–protein interface with the S-protein of SARS-CoV-2 using our developed Legion Interfaces Analysis (LiAn) program. Results Here, we characterized a total of 12 ACE2 putative deleterious missense variants. Of those 12 variants, we further showed that p.His378Arg could directly weaken the binding of catalytic metal atom to decrease ACE2 activity and p.Ser19Pro could distort the most important helix to the S-protein. Another seven missense variants may affect secondary structures (i.e. p.Gly211Arg; p.Asp206Gly; p.Arg219Cys; p.Arg219His, p.Lys341Arg, p.Ile468Val, and p.Ser547Cys), whereas p.Ile468Val with AF = 0.01 is only present in Asian. Conclusions We provide strong evidence of putative deleterious missense variants in ACE2 that are present in specific populations, which could disrupt the function and structure of ACE2. These findings provide novel insight into the genetic variation in ACE2 which may affect the SARS-CoV-2 recognition and infection, and COVID-19 susceptibility and treatment.

Identifying transcription factors (TFs) whose DNA bindings are altered by genetic variants that regulate susceptibility genes is imperative to understand transcriptional dysregulation in disease etiology. Here, we develop a statistical framework to analyze extensive ChIP-seq and GWAS data and identify 22 breast cancer risk-associated TFs. We find that, by analyzing genetic variations of TF-DNA bindings, the interaction of FOXA1 with co-factors such as ESR1 and E2F1, and the interaction of TFs with chromatin features (i.e., enhancers) play a key role in breast cancer susceptibility. Using genetic variants occupied by the 22 TFs, transcriptome-wide association analyses identify 52 previously unreported breast cancer susceptibility genes, including seven with evidence of essentiality from functional screens in breast relevant cell lines. We show that FOXA1 and co-factors form a core TF-transcriptional network regulating the susceptibility genes. Our findings provide additional insights into genetic variations of TF-DNA bindings (particularly for FOXA1) underlying breast cancer susceptibility. The identification of transcription factors (TFs) whose binding sites are affected by risk genetic variants remains crucial. Here, the authors develop a statistical framework to analyse ChIP-seq and GWAS data, identify 22 breast cancer risk-associated TFs and a core TF-transcriptional network for FOXA1 and co-factors.

Transcriptome-wide association studies (TWAS) have successfully discovered many putative disease susceptibility genes. However, TWAS may suffer from inaccuracy of gene expression predictions due to inclusion of non-regulatory variants. By integrating prior knowledge of susceptible transcription factor occupied elements, we develop sTF-TWAS and demonstrate that it outperforms existing TWAS approaches in both simulation and real data analyses. Under the sTF-TWAS framework, we build genetic models to predict alternative splicing and gene expression in normal breast, prostate and lung tissues from the Genotype-Tissue Expression project and apply these models to data from large genome-wide association studies (GWAS) conducted among European-ancestry populations. At Bonferroni-corrected P  < 0.05, we identify 354 putative susceptibility genes for these cancers, including 189 previously unreported in GWAS loci and 45 in loci unreported by GWAS. These findings provide additional insight into the genetic susceptibility of human cancers. Additionally, we show the generalizability of the sTF-TWAS on non-cancer diseases. Transcriptome-wide association studies can uncover genes involved in disease. Here, the authors extend the framework with a transcriptome-wide association study approach which incorporates transcription factor occupancy, adding tissue-specific mechanistic support to associations.

Hair production is fueled by stem cells (SCs), which transition between cyclical bouts of rest and activity. Here, we explore why hair growth wanes with age. We show that aged hair follicle SCs (HFSCs) in mice exhibit enhanced resting and abbreviated growth phases and are delayed in response to tissue-regenerating cues. Aged HFSCs are poor at initiating proliferation and show diminished self-renewing capacity upon extensive use. Only modestly restored by parabiosis, these features are rooted in elevated cell-intrinsic sensitivity and local elevation in bone morphogenic protein (BMP) signaling. Transcriptional profiling presents differences consistent with defects in aged HFSC activation. Notably, BMP-/calcium-regulated, nuclear factor of activated T-cell c1 (NFATc1) in HFSCs becomes recalcitrant to its normal down-regulating cues, and NFATc1 ChIP-sequencing analyses reveal a marked enrichment of NFATc1 target genes within the age-related signature. Moreover, aged HFSCs display more youthful levels of hair regeneration when BMP and/or NFATc1 are inhibited. These results provide unique insights into how skin SCs age.

ETV1: a factor in gastrointestinal cancer Gastroinestinal stromal tumours (GISTs) arise in the interstitial cells of Cajal, cells embedded in the musculature of the gastrointestinal tract where they generate electrical rhythmicity. Chi et al . now show that the transcription factor ETV1 is required for the development of these cells, and also promotes tumour development. The KIT gene, often activated by mutations in GIST, cooperates with ETV1 in the transformation of interstitial cells of Cajal, in part by promoting ETV1 stabilization. ETV1 seems to be present in high levels in all GISTs, making it a candidate diagnostic biomarker, and ETV1 blockers may prove useful against drug-resistant GIST. Gastrointestinal stromal tumours (GIST) are believed to arise in interstitial cells of Cajal (ICC). These authors show that the transcription factor ETV1 is required for ICC development and promotes the development of GIST. KIT, which is often activated by mutations in GIST, cooperates with ETV1 in the transformation of ICCs, in part by promoting ETV1 stabilization. Thus, a normal developmental lineage factor is switched into a tumour-promoting factor by a cooperating oncogene. Gastrointestinal stromal tumour (GIST) is the most common human sarcoma and is primarily defined by activating mutations in the KIT or PDGFRA receptor tyrosine kinases 1 , 2 . KIT is highly expressed in interstitial cells of Cajal (ICCs)—the presumed cell of origin for GIST—as well as in haematopoietic stem cells, melanocytes, mast cells and germ cells 2 , 3 . Yet, families harbouring germline activating KIT mutations and mice with knock-in Kit mutations almost exclusively develop ICC hyperplasia and GIST 4 , 5 , 6 , 7 , suggesting that the cellular context is important for KIT to mediate oncogenesis. Here we show that the ETS family member ETV1 is highly expressed in the subtypes of ICCs sensitive to oncogenic KIT mediated transformation 8 , and is required for their development. In addition, ETV1 is universally highly expressed in GISTs and is required for growth of imatinib-sensitive and resistant GIST cell lines. Transcriptome profiling and global analyses of ETV1-binding sites suggest that ETV1 is a master regulator of an ICC-GIST-specific transcription network mainly through enhancer binding. The ETV1 transcriptional program is further regulated by activated KIT, which prolongs ETV1 protein stability and cooperates with ETV1 to promote tumorigenesis. We propose that GIST arises from ICCs with high levels of endogenous ETV1 expression that, when coupled with an activating KIT mutation, drives an oncogenic ETS transcriptional program. This differs from other ETS -dependent tumours such as prostate cancer, melanoma and Ewing sarcoma where genomic translocation or amplification drives aberrant ETS expression 9 , 10 , 11 . It also represents a novel mechanism of oncogenic transcription factor activation.

The increasing incidence of early-onset colorectal cancer (age <50 years; EOCRC) shows a dramatic growing trend globally, while late-onset colorectal cancer (LOCRC) is gradually decreasing. We aimed to characterise the distinct mutational landscape of EOCRC in an effort to inform age-specific clinical management. In this observational study, we analysed whole-exome sequencing and clinical-grade targeted sequencing data from seven cohorts (the Memorial Sloan Kettering Cancer Center [MSKCC] cohort [the USA], the Leiden University Medical Center cohort [the Netherlands], the Nigerian African Research Group for Oncology [ARGO] cohort [Nigeria], the Genomics Evidence Neoplasia Information Exchange [GENIE] Project [Canada, France, Spain, and the USA], the Sun Yat-sen University Cancer Center (SYSUCC) cohort [China], the Asan Medical Center cohort [South Korea], and the Fudan University Shanghai Cancer Center–Colorectal Cancer [FUSCC-CRC] cohort [China]) across Canada, China, France, Nigeria, South Korea, Spain, the Netherlands, and the USA. Eligible patients were aged 18 years or older with a confirmed diagnosis of colorectal adenocarcinoma or mucinous adenocarcinoma. Samples were categorised into hypermutated (tumour mutational burden [TMB] >15 mutations per megabase) and non-hypermutated (TMB ≤15 mutations per megabase) groups. We evaluated the TMB difference between EOCRC and LOCRC using gamma regression and compared genomic mutation data between EOCRC and LOCRC using multiple logistic regression and pathway enrichment analysis. The primary study objective was to compare genomic mutational patterns between EOCRC and LOCRC, stratified by TMB groups. Between Jan 1 and Dec 31, 2024, 17 133 tumour samples from patients with colorectal cancer in eight countries were analysed (Canada [n=218], China [n=3009], France [n=62], Nigeria [n=64], South Korea [n=44], Spain [n=250], the Netherlands [n=281], and the USA [n=13 205]). Among 17 133 patients, 9452 (55·2%) were male, 7681 (44·8%) were female, 10 174 (59·4%) were White, 3904 (22·8%) were Asian or Pacific Islander, 983 (5·7%) were Black, and 4983 (29·1%) had EOCRC. In hypermutated colorectal cancer, EOCRC exhibited a significantly higher TMB compared with LOCRC (mean ratio 1·11 [95% CI 1·06–1·16]; p<0·0001). In non-hypermutated colorectal cancer, EOCRC showed a significantly lower TMB than LOCRC after adjusting for skewness (mean ratio 2·92 [95% CI 2·88–2·96]; p<0·0001). In hypermutated colorectal cancer, a total of 23 genes, including APC (EOCRC 464 [75·0%] of 619 vs LOCRC 891 [58·6%] of 1521; odds ratio [OR] 2·00 [95% CI 1·59–2·51]; adjusted p<0·0001), KRAS (EOCRC 331 [53·3%] of 621 vs LOCRC 488 [32·0%] of 1526; OR 2·35 [95% CI 1·91–2·89]; adjusted p<0·0001), and CTNNB1 (EOCRC 196 [31·6%] of 621 vs LOCRC 274 [18·0%] of 1526; OR 2·15 [95% CI 1·70–2·72]; adjusted p<0·0001), and TCF7L2 (EOCRC 294 [51·2%] of 574 vs LOCRC 489 [35·0%] of 1398; OR 2·01 [95% CI 1·62–2·50]; adjusted p<0·0001), displayed elevated mutation frequencies in EOCRC compared with LOCRC, whereas only BRAF (EOCRC 97 [15·6%] of 621 vs LOCRC 674 [44·2%] of 1526; OR 0·27 [95% CI 0·21–0·35]; adjusted p<0·0001) and RNF43 (EOCRC 225 [39·3%] of 573 vs LOCRC 778 [53·9%] of 1444; OR 0·61 [95% CI 0·49–0·76]; adjusted p=0·0015) were less frequently mutated in EOCRC than in LOCRC. In non-hypermutated colorectal cancer, only TP53 (EOCRC 3468 [79·5%] of 4362 vs LOCRC 7825 [73·7%] of 10 624; OR 1·37 [95% CI 1·25–1·50]; adjusted p<0·0001) showed a higher mutation frequency in EOCRC, while nine genes had lower mutation frequencies, including BRAF (EOCRC 274 [6·3%] of 4362 vs LOCRC 909 [8·6%] of 10 624; OR 0·70 [95% CI 0·60–0·81]; adjusted p=0·00024) and KRAS (EOCRC 1794 [41·1%] of 4362 vs LOCRC 4840 [45·6%] of 10624; OR 0·83 [95% CI 0·77–0·89]; adjusted p=0·00019). Within hypermutated colorectal cancer, younger patients exhibited a higher mutational burden than older patients. Our study reveals an abnormal accumulation of distinct somatic mutations in hypermutated EOCRC, the pattern of which might be contributing to the alarming rise in the incidence of EOCRC over the past decades. Our results support the need for EOCRC-specific molecular profiling to guide clinical practice. National Natural Science Foundation of China and the Shanghai Science and Technology Development Fund.

The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the Genotype-Tissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P  < 0.05, we identify 4248 CpGs that are significantly associated with cancer risk, of which 95.4% (4052) are specific to a particular cancer type. Notably, 92 CpGs within 55 putative novel loci retain significant associations with cancer risk after conditioning on proximal signals identified by genome-wide association studies. Integrative multi-omics analyses reveal 854 CpG-gene-cancer trios, suggesting that DNA methylation at 309 distinct CpGs might influence cancer risk through regulating the expression of 205 unique cis -genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology. The relationship between tissue-specific DNA methylation and cancer risk remains to be elucidated. Here, the authors predict DNA methylation at CpG sites for seven cancer types and investigate how these influence cancer risk.

Purpose Limited studies have been conducted to evaluate pathogenetic mutations in breast cancer predisposition genes among Chinese women. To fully characterize germline mutations of these genes in this population, we used the whole-exome sequencing data in a population-based case–control study conducted in Shanghai, China. Methods We evaluated exonic, splicing, and copy number variants in 11 established and 14 candidate breast cancer predisposition genes in 831 invasive breast cancer cases and 839 controls. We identified 55 pathogenic variants, including 15 newly identified in this study. Results Approximately 8% of the cases and 0.6% of the cancer-free controls carried these pathogenetic variants ( P  = 3.05 × 10 −15 ). Among cases, 3.7% had a BRCA 2 pathogenic variant and 1.6% had a BRCA1 pathogenic variant, while 2.5% had a pathogenic variant in other genes including ATM, CHEK2, NBN, NF1, CDH1, PALB2, PTEN, TP53 as well as BARD1, BRIP, and RAD51D . Patients with BRCA 1/2 pathogenic variants were more likely to have a family history of breast cancer and hormone receptor negative tumors compared with patients without pathogenic variants. Conclusions This study highlighted the importance of hereditary breast cancer genes in the breast cancer etiology in this understudied population. Together with previous studies in East Asian women, this study suggested a relatively more prominent role of BRCA2 compared to BRCA1 . This study also provides additional evidence to design cost-efficient genetic testing among Chinese women for risk assessment and early detection of breast cancer.

Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.