Biomedical subjects

Jianxin Shi

Publications and source records attributed to Jianxin Shi.

12 recordsLinked to original sources

PubMed2026

Circadian- and light-regulated oscillatory expression of CSA in rice leaves is required for pollen fertility.

The oscillatory expression of CSA in rice leaves is regulated by the circadian clock and red/far-red light signals, mediated through DOF5 and PIL11, and is required for normal pollen fertility. Photoperiod-sensitive male-sterile lines represent a pivotal innovation in the development of hybrid rice. However, the underlying mechanisms governing photoperiod-sensitive male reproductive development remain poorly understood. Our previous studies demonstrated that the carbon starved anther (csa) mutant exhibits male sterility under short-day (SD) conditions but partial fertility under long-day (LD) conditions. In this study, we report that CSA expression follows an oscillatory rhythm in rice leaves under both SD and LD conditions, a pattern regulated by both circadian clock and light signals. Tissue-specific RNA interference knockdown of CSA in leaves was associated with reduced pollen viability, suggesting that CSA expression in leaves contributes to normal male fertility. Promoter truncation assay results indicate that distinct regions of the CSA promoter contribute differentially to the regulation of CSA expression in leaves versus anthers, and that both the CSA expression level in anthers and the rhythmic expression pattern of CSA in leaves are associated with the restoration of male fertility. Using dual-luciferase, yeast one-hybrid, and electrophoretic mobility shift assays, we identified two proteins, PIL11 and DOF5, which directly bind to specific motifs (an E-box and T/AAAAG motif) within the CSA promoter truncation, thereby regulating its transcription. These findings elucidate novel mechanisms linking light sensing to the expression of circadian-controlled genes, thus connecting photoperiod with male reproductive development in rice.

Oryza↗

PubMed2026

Functional characterization of the 9q34.13 locus identifies RAPGEF1 as a candidate gene modulating risk for melanoma and nevi via RAS activation.

Genome-wide association studies identified a melanoma- and nevus count-associated locus on chromosome band 9q34.13. Fine-mapping and melanocyte expression data collectively suggest two potential risk genes with opposite associations with risk: higher levels of Rap guanine nucleotide exchange factor 1 (RAPGEF1) and lower levels of uridine-cytidine kinase 1 (UCK1). Colocalization analyses and conditional transcriptome-wide association studies (TWASs) suggest multiple causal cis-regulatory sequence variants in partial linkage disequilibrium (LD) to each other. Melanocyte capture-HiC and CRISPR inhibition demonstrated regulatory interactions between fine-mapped variants and the RAPGEF1 and UCK1 promoters. Focusing on RAPGEF1, we demonstrate that RAPGEF1 expression promotes melanocyte growth and drives colony formation of human immortalized melanocytes. Following treatment with human epidermal growth factor (EGF), RAPGEF1 overexpression activated both RAP1 and RAS. Further, we show that RAPGEF1 expression is significantly enriched in melanomas that lack strongly activating RAS-MAPK pathway mutations, which suggests that RAPGEF1 may promote oncogenic RAS-MAPK pathway signaling in melanomas. Furthermore, in these tumors, we provide preliminary evidence to support the prognostic relevance of RAPGEF1 expression in individuals whose melanomas lack RAS or BRAF mutations. Together with other recent studies, these data suggest that germline variation influencing RAS activation may play a key role in nevus development and melanoma risk.

GWAS↗

PubMed2026

Identification of immune cell type-specific susceptibility genes in multiple cancers using transcriptome-wide association studies.

BACKGROUND: Transcriptome-wide association studies (TWAS) integrate gene expression and genome-wide association studies (GWAS) to identify disease susceptibility genes. Because gene expression varies substantially across cell types within tissues, cell type-specific prediction models may enhance the power of TWAS. METHODS: We conducted cell type-specific TWAS leveraging single-cell RNA sequencing data from the OneK1K cohort (14 immune cell types, 1.27 million cells) and GWAS summary statistics for 7 cancers (>290 000 cases in total). To improve prediction accuracy, we developed a modeling framework that incorporates shared gene expression effects across cell types. RESULTS: At a false discovery rate of 5%, we identified 106 (Bonferroni 5%: 13) previously unreported loci for breast cancer, 51 (4) loci for prostate cancer, 11 (4) loci for lung cancer, 39 (5) loci for melanoma, 9 (1) loci for ovarian cancer, and 2 (1) loci for diffuse large B-cell lymphoma, with most genes exhibiting cell type specificity. Gene set analyses confirmed joint associations of unreported genes with breast and prostate cancer risk in UK Biobank data. Additional lung tissue single-cell RNA sequencing data with 113 individuals validated 18 of 32 (56.3%) statistically significant genes for lung cancer. Across cancers, 139 statistically significant genes were shared by at least 2 cancer types and were primarily enriched in specific immune cell types. CONCLUSION: Cell type-specific TWAS improve the identification of novel cancer susceptibility loci and provide insights into the immune landscape of cancer etiology.

Humans↗

PubMed2026

Large-scale low-coverage whole-genome sequencing reveals the genetic architecture of wool and growth traits in fine-wool sheep.

Breeding sheep with superior growth performance and wool quality is essential for the sustainability of the fine-wool sheep industry. In this study, we perform low-coverage whole-genome sequencing (lcWGS) on 3842 individuals from 5 sheep breeds (4 fine-wool and 1 semi-fine wool) and generate a large genomic dataset. By comparing these breeds with coarse-wool sheep, we characterize the genomic landscape and selection signatures of fine-wool sheep. We identify several known functional genes associated with hair follicle development and skin morphology, including EGFR, KRT74, EDAR, EREG, and GLI2. Furthermore, GWAS of 19 traits identifies 156 candidate genes significantly associated with growth and wool characteristics, including LCORL for body size, EGFR for clean wool yield, and PRDM1 for fiber diameter. Notably, EGFR is detected in both GWAS and selection signature analyses, indicating its important role in phenotype formation and historical selection. Overall, our findings reveal the genetic basis of growth and wool traits in fine-wool and semi-fine wool sheep, highlight EGFR, LCORL, and PRDM1 as candidate genes, and provide valuable genomic resources and candidate markers for future functional validation and molecular breeding.

Body size↗

PubMed2026

Fecal immunochemical tests from population-based colorectal cancer screening programs support prospective microbiome cohorts.

BACKGROUND: Large, prospective cohorts are needed to research the gut microbiome's role in colorectal cancer (CRC) risk. We evaluated the gut microbiome leveraging residual fecal immunochemical tests (FIT) from a CRC screening program in Turin, Italy, and conducted one of the largest population-based case-control studies across the adenoma-carcinoma sequence to date. METHODS: We extracted DNA from residual FIT stool, used whole-genome shotgun sequencing, and included those with CRC (N = 44), advanced adenomas (N = 269), early adenomas (N = 134), and FIT-negative controls (N = 478). Alpha diversity, beta diversity, and species, gene, and pathway relative abundances were estimated. Multivariable logistic regression models were used to estimate associations of these metrics with colorectal neoplasms. RESULTS: Alpha diversity was mostly inversely associated with colorectal neoplasms, particularly early adenomas (OR: 0.45, 95% CI: 0.25-0.80; P = 0.01). Presence of oral pathogens, including Parvimonas micra, was associated with higher odds of CRC. Furthermore, Escherichia coli and Bacteroides fragilis were strongly associated with higher odds of all colorectal neoplasms. Several genes and pathways were associated with colorectal neoplasms. CONCLUSIONS: Our findings align with smaller studies of the gut microbiome and colorectal neoplasms, supporting that CRC screening programs provide opportunities to prospectively study the gut microbiome's association with cancer risk in large populations.

Humans↗

PubMed2026

Functional characterization of the 9q34.13 locus identifies RAPGEF1 as modulating risk for melanoma and nevi via RAS activation.

Genome-wide association studies identified a melanoma- and nevus count-associated locus on chromosome band 9q34.13. Fine-mapping and melanocyte expression data collectively suggest two potential causal genes with opposite association with risk: higher levels of Rap guanine nucleotide exchange factor 1 (RAPGEF1) and lower levels of uridine-cytidine kinase 1 (UCK1). Colocalization analyses and conditional TWAS suggest multiple causal cis-regulatory sequence variants in partial linkage disequilibrium (LD) to each other. Melanocyte capture-HiC and CRISPR-inhibition demonstrated regulatory interactions between fine-mapped variants and the RAPGEF1 and UCK1 promoters. Focusing on RAPGEF1, we demonstrate RAPGEF1 expression promotes melanocyte growth and drives malignant transformation of human immortalized melanocytes. Following treatment with human EGF, RAPGEF1 overexpression activated both RAP1 and RAS. Further, we show RAPGEF1 expression is significantly enriched in melanomas lacking strongly activating RAS-MAPK mutations, suggesting that RAPGEF1 may promote oncogenic RAS-MAPK signaling in melanomas. Furthermore, in these tumors, we provide preliminary evidence to support the prognostic relevance of RAPGEF1 expression in patients lacking RAS or BRAF mutations. Together with other recent studies, these data suggest that germline variation influencing RAS activation may play a key role in nevus development and melanoma risk.

Journal Article↗

PubMed2026

Estimating the heritability of longitudinal rate-of-change: genetic insights into PSA velocity in prostate cancer-free individuals.

Serum prostate-specific antigen (PSA) is widely used for prostate cancer screening. While the genetics of PSA levels have been studied to enhance screening accuracy, the genetic basis of PSA velocity, the rate of PSA change over time, remains unclear. The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, a large, randomized study with longitudinal PSA data (15,260 cancer-free males, averaging 5.34 samples per subject) and genome-wide genotype data, provides a unique opportunity to estimate PSA velocity heritability. We developed a mixed model to jointly estimate the heritability of PSA levels at age 54 and PSA velocity. To accommodate the large dataset, we implemented 2 efficient computational approaches: a partitioning and meta-analysis strategy using average information restricted maximum likelihood (AI-REML) and a fast restricted Haseman-Elston (REHE) regression method. Simulations showed that both methods yield unbiased estimates of both heritability metrics, with AI-REML providing smaller variability in the estimation of velocity heritability than REHE. Applying AI-REML to PLCO data, we estimated heritability at 0.32 (s.e. = 0.07) for baseline PSA and 0.45 (s.e. = 0.18) for PSA velocity. These findings reveal a substantial genetic contribution to PSA velocity, supporting future genome-wide studies to identify variants affecting PSA dynamics and improve PSA-based screening.

Humans↗

PubMed2025

Panorama of Chromosomal Instability in Lung Cancer.

Lung cancer is a highly heterogeneous disease primarily driven by tobacco smoking. About 20% of lung cancers occur among patients who have never smoked (LCINS) with differences in patient ancestry, sex, tumor histology, and clinical features. Our understanding of chromosomal instability in lung cancer, especially LCINS, is still limited. Here, we perform a comprehensive study of 182,429 somatic structural variations (SVs) detected in 1,209 whole-genome sequenced lung cancers, of which 864 LCINS. SVs are more abundant in tumors from patients who have smoked (LCSS); however, they are more complex and play more important roles in tumorigenesis in LCINS. EGFR mutations and KRAS mutations profoundly and independently shape the SV landscape. EGFR-mutant tumors have higher SV burden and more cancer-driving SVs. In contrast, KRAS mutations are associated with lower SV burden and less driver SVs. We decompose 16 SV signatures for both complex and simple SVs that likely represent divergent molecular mechanisms. The SV breakpoints have distinct distributions across the genome depending on the signatures due to mutagenic mechanisms and positive selection. Many established cancer-driving genes are recurrently rearranged by multiple SV signatures suggesting functional convergence of these genome instability mechanisms.

Journal Article↗

PubMed2025

Stratifying Lung Adenocarcinoma Risk with Multi-ancestry Polygenic Risk Scores in East Asian Never-Smokers.

BACKGROUND: Lung adenocarcinoma (LUAD) in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve LUAD risk prediction. METHODS: PRSs were developed using genome-wide association study summary statistics from East Asian (8,002 cases; 20,782 controls) and European (2,058 cases; 5,575 controls) populations. Single-ancestry models included PRS-25, PRS-CT, and LDpred2; multi-ancestry models included LDpred2+PRS-EUR128, PRS-CSx, and CT-SLEB. Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium (FLCCA) and externally validated in the Nanjing Lung Cancer Cohort (NJLCC). We assessed predictive accuracy via AUC, with 10-year and (age 30-80) absolute risks estimates. RESULTS: The best multi-ancestry PRS, using East Asian and European data via CT-SLEB (clumping and thresholding, super learning, empirical Bayes), outperformed the best East Asian-only PRS (LDpred2; AUC=0.629, 95% CI:0.618,0.641), achieving an AUC of 0.640 (95% CI:0.629,0.653) and odds ratio of 1.71 (95% CI:1.61,1.82) per SD increase. NJLCC Validation confirmed robust performance (AUC =0.649, 95% CI: 0.623, 0.676). The top 20% PRS group had a 3.92-fold higher LUAD risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year LUAD risk at age 50 (0.42%) by age 41, nine years earlier. CONCLUSIONS: Multi-ancestry PRS approaches enhance LUAD risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

East Asian never smokers↗

PubMed2025

A prognostic signature for lung adenocarcinoma in people who have never smoked.

Knowledge of tumor cell dynamics can inform prognosis and treatment yet is largely lacking for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA-seq data from 684 NS-LUAD and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histological data further characterized the subtypes. 'Steady', marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver genes' alterations, is linked to prolonged survival and low immune evasion. 'Proliferative' shows high proliferation markers, TP53 mutations, and gene fusions. 'Chaotic', with high epithelial-to-mesenchymal transition markers, has the worst prognosis even within stage I tumors. Lacking known molecular or histological characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the overall classification and strongly predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving NS-LUAD prognostication in clinical settings.

Journal Article↗

PubMed2025

Animal farming and the oral microbiome in the Agricultural Health Study.

BACKGROUND: Raising farm animals imparts various exposures that may shape the human microbiome. The oral microbiome has been increasingly implicated in disease development. Animal farming has also been associated with certain chronic diseases such as cancer; however, underlying biological mechanisms are unclear. We investigated associations between raising farm animals and the oral microbiome in the Agricultural Health Study. METHODS: This analysis included 1,245 participants (865 farmers and 380 spouses) who provided oral wash specimens and information on types and numbers of specific animals raised on their farms within 2 years before sample collection. The oral microbiome was measured by sequencing the V4 region of the 16S ribosomal RNA gene. We evaluated associations of farm animal exposures with alpha and beta diversity metrics (within- and between-sample diversity, respectively), as well as presence and relative abundance of specific bacterial genera. All analyses adjusted for potential confounders (e.g., age, sex, smoking, alcohol consumption). RESULTS: Overall, 63 % of participants raised farm animals, most commonly cattle (46 %) and hogs (20 %). Those who raised a large number of hogs (≥2,000 vs. no hogs) had higher alpha diversity. Conversely, raising sheep/goats and raising larger numbers of poultry were associated with lower alpha diversity. Beta diversity was not significantly different between participants with and without any farm animals. Participants raising any farm animals had higher relative abundance of Porphyromonas and lower relative abundances of Prevotella and Ruminococcaceae UCG-014. Several genera were more likely to be absent with specific animal exposures (e.g., Capnocytophaga for cattle and sheep/goats; Corynebacterium, Dialister, Stomatobaculum, and Solobacterium for sheep/goats and poultry). CONCLUSIONS: This was the largest study of farm animal exposures and the human microbiome to date. Findings suggest that raising specific farm animals may influence the oral microbiome, supporting the need to further investigate the potential role of animal farming in disease etiology.

Microbiota↗

PubMed2021

Genetic Relationship Between Endometriosis and Melanoma.

Epidemiological studies have observed that risk of endometriosis is associated with history of cutaneous melanoma and vice versa. Evidence for shared biological mechanisms between the two traits is limited. The aim of this study was to investigate the genetic correlation and causal relationship between endometriosis and melanoma. Summary statistics from genome-wide association meta-analyses (GWAS) for endometriosis and melanoma were used to estimate the genetic correlation between the traits and Mendelian randomization was used to test for a causal association. When using summary statistics from separate female and male melanoma cohorts we identified a significant positive genetic correlation between melanoma in females and endometriosis (r g = 0.144, se = 0.065, p = 0.025). However, we find no evidence of a correlation between endometriosis and melanoma in males or a combined melanoma dataset. Endometriosis was not genetically correlated with skin color, red hair, childhood sunburn occasions, ease of skin tanning, or nevus count suggesting that the correlation between endometriosis and melanoma in females is unlikely to be influenced by pigmentary traits. Mendelian Randomization analyses also provided evidence for a relationship between the genetic risk of melanoma in females and endometriosis. Colocalization analysis identified 27 genomic loci jointly associated with the two diseases regions that contain different causal variants influencing each trait independently. This study provides evidence of a small genetic correlation and relationship between the genetic risk of melanoma in females and endometriosis. Genetic risk does not equate to disease occurrence and differences in the pathogenesis and age of onset of both diseases means it is unlikely that occurrence of melanoma causes endometriosis. This study instead provides evidence that having an increased genetic risk for melanoma in females is related to increased risk of endometriosis. Larger GWAS studies with increased power will be required to further investigate these associations.

endometriosis↗