Healthy dietary patterns, genetic risk, and gastrointestinal cancer incident risk: a large-scale prospective cohort study.

BACKGROUND: Dietary patterns have been associated with several cancers, especially gastrointestinal cancer (GIC). However, whether a healthy dietary pattern could modify the risk of GIC among people with different genetic backgrounds is not clear. OBJECTIVE: The objective of the study was to investigate how dietary patterns and genetic susceptibility contribute to the risk of GIC independently and jointly. METHODS: This large-scale prospective cohort study included 105,463 participants in UK Biobank who were aged 40-72 y and cancer-free at baseline. Dietary intake (Oxford WebQ) was used to calculate dietary pattern scores including dietary approach to stop hypertension (DASH) score and healthful plant-based diet index (hPDI). Genetic risk was quantified by a polygenic risk score (PRS) comprising 129 known GIC-associated loci. Cox proportional hazards regression was performed to estimate the associations of dietary patterns and PRS with GIC incidence after adjusting for potential confounders. RESULTS: Over a median follow-up of 11.70 y, 1,661 participants were diagnosed with GIC. DASH and hPDI were associated with 20% and 36% reductions, respectively, in GIC risk. Low PRS was associated with a 30 % decrease in GIC risk (HR: 0.70; 95% CI: 0.62, 0.79). Participants with healthy dietary scores at high-genetic risk had a lower GIC risk with HR of 0.77 (95% CI: 0.60, 0.98) for DASH and 0.66 (95% CI: 0.52, 0.84) for hPDI than those with unhealthy dietary score. Participants with both high-dietary score and low-genetic risk showed the lowest risk of GIC, with HR of 0.58 (95% CI: 0.45, 0.75) for DASH and 0.45 (95% CI: 0.34, 0.58) for hPDI. CONCLUSIONS: Adherence to DASH and hPDI were associated with a lower risk of some gastrointestinal cancers, and these 2 dietary patterns may partly compensate for genetic predispositions to cancer. Our results advance the development of precision medicine strategies that consider both dietary patterns and genetics to improve gastrointestinal health.

Genome-wide association analysis of left ventricular imaging-derived phenotypes identifies 72 risk loci and yields genetic insights into hypertrophic cardiomyopathy.

Left ventricular regional wall thickness (LVRWT) is an independent predictor of morbidity and mortality in cardiovascular diseases (CVDs). To identify specific genetic influences on individual LVRWT, we established a novel deep learning algorithm to calculate 12 LVRWTs accurately in 42,194 individuals from the UK Biobank with cardiac magnetic resonance (CMR) imaging. Genome-wide association studies of CMR-derived 12 LVRWTs identified 72 significant genetic loci associated with at least one LVRWT phenotype (P < 5 × 10-8), which were revealed to actively participate in heart development and contraction pathways. Significant causal relationships were observed between the LVRWT traits and hypertrophic cardiomyopathy (HCM) using genetic correlation and Mendelian randomization analyses (P < 0.01). The polygenic risk score of inferoseptal LVRWT at end systole exhibited a notable association with incident HCM, facilitating the identification of high-risk individuals. The findings yield insights into the genetic determinants of LVRWT phenotypes and shed light on the biological basis for HCM etiology.

Genetic Variants That Impact Alternative Polyadenylation in Cancer Represent Candidate Causal Risk Loci.

Alternative polyadenylation (APA) is emerging as a major mechanism of posttranscriptional regulation. APA can impact the development and progression of cancer, suggesting that the genetic determinants of APA might play an important role in regulating cancer risk. Here, we depicted a pan-cancer atlas of human APA quantitative trait loci (apaQTL), containing approximately 0.7 million apaQTLs across 32 cancer types. Systematic multiomics analyses indicated that cancer apaQTLs could contribute to APA regulation by altering poly(A) motifs, RNA-binding proteins (RBP), and chromatin regulatory elements and were preferentially enriched in genome-wide association studies (GWAS)-identified cancer susceptibility loci. Moreover, apaQTL-related genes (aGene) were broadly related to cancer signaling pathways, high mutational burden, immune infiltration, and drug response, implicating their potential as therapeutic targets. Furthermore, apaQTLs were mapped in Chinese colorectal cancer tumor tissues and then screened for functional apaQTLs associated with colorectal cancer risk in 17,789 cases and 19,951 controls using GWAS-ChIP data, with independent validation in a large-scale population consisting of 6,024 cases and 10,022 controls. A multi-ancestry-associated apaQTL variant rs1020670 with a C>G change in DNM1L was identified, and the G allele contributed to an increased risk of colorectal cancer. Mechanistically, the risk variant promoted aberrant APA and facilitated higher usage of DNM1L proximal poly(A) sites mediated by the RBP CSTF2T, which led to higher expression of DNM1L with a short 3'UTR. This stabilized DNM1L to upregulate its expression, provoking colorectal cancer cell proliferation. Collectively, these findings generate a resource for understanding APA regulation and the genetic basis of human cancers, providing insights into cancer etiology. SIGNIFICANCE: Cancer risk is mediated by alternative polyadenylation quantitative trait loci, including the rs1020670-G variant that promotes alternative polyadenylation of DNM1L and increases colorectal cancer risk.

Genome-wide enhancer-gene regulatory maps link causal variants to target genes underlying human cancer risk.

Genome-wide association studies have identified numerous variants associated with human complex traits, most of which reside in the non-coding regions, but biological mechanisms remain unclear. However, assigning function to the non-coding elements is still challenging. Here we apply Activity-by-Contact (ABC) model to evaluate enhancer-gene regulation effect by integrating multi-omics data and identified 544,849 connections across 20 cancer types. ABC model outperforms previous approaches in linking regulatory variants to target genes. Furthermore, we identify over 30,000 enhancer-gene connections in colorectal cancer (CRC) tissues. By integrating large-scale population cohorts (23,813 cases and 29,973 controls) and multipronged functional assays, we demonstrate an ABC regulatory variant rs4810856 associated with CRC risk (Odds Ratio = 1.11, 95%CI = 1.05-1.16, P = 4.02 × 10-5) by acting as an allele-specific enhancer to distally facilitate PREX1, CSE1L and STAU1 expression, which synergistically activate p-AKT signaling. Our study provides comprehensive regulation maps and illuminates a single variant regulating multiple genes, providing insights into cancer etiology.

Genetic Control of Alternative Splicing and its Distinct Role in Colorectal Cancer Mechanisms.

BACKGROUND & AIMS: Dysregulation of alternative splicing is implicated in many human diseases, and understanding the genetic variation underlying transcript splicing is essential to dissect the molecular mechanisms of cancers. We aimed to provide a comprehensive functional dissection of splicing quantitative trait loci (sQTLs) in cancer and focus on elucidating its distinct role in colorectal cancer (CRC) mechanisms. METHODS: We performed a comprehensive sQTL analysis to identify genetic variants that control messenger RNA splicing across 33 cancer types from The Cancer Genome Atlas and independently validated in our 154 CRC tissues. Then, large-scale, multicenter, multi-ethnic case-control studies (34,585 cases and 76,023 controls) were conducted to examine the association of these sQTLs with CRC risk. A series of biological experiments in vitro and in vivo were performed to investigate the potential mechanisms of the candidate sQTLs and target genes. RESULTS: The molecular characterization of sQTL revealed its distinct role in cancer susceptibility. Tumor-specific sQTL further showed better response to cancer development. In addition, functionally informed polygenic risk score highlighted the potentiality of sQTLs in the CRC prediction. Complemented by large-scale population studies, we identified that the risk allele (T) of a multi-ancestry-associated sQTL rs61746794 significantly increased the risk of CRC in Chinese (odds ratio, 1.20; 95% CI, 1.12-1.29; P = 8.82 × 10-7) and European (odds ratio, 1.11; 95% CI, 1.07-1.16; P = 1.13 × 10-7) populations. rs61746794-T facilitated PRMT7 exon 16 splicing mediated by the RNA-binding protein PRPF8, thus increasing the level of canonical PRMT7 isoform (PRMT7-V2). Overexpression of PRMT7-V2 significantly enhanced the growth of CRC cells and xenograft tumors compared with PRMT7-V1. Mechanistically, PRMT7-V2 functions as an epigenetic writer that catalyzes the arginine methylation of H4R3 and H3R2, subsequently regulating diverse biological processes, including YAP, AKT, and KRAS pathway. A selective PRMT7 inhibitor, SGC3027, exhibited antitumor effects on human CRC cells. CONCLUSIONS: Our study provides an informative sQTLs resource and insights into the regulatory mechanisms linking splicing variants to cancer risk and serving as biomarkers and therapeutic targets.

HSPA12A was identified as a key driver in colorectal cancer GWAS loci 10q26.12 and modulated by an enhancer-promoter interaction.

Although genome-wide association studies (GWASs) have identified over 100 colorectal cancer (CRC) risk loci, an understanding of causal genes or risk variants and their biological functions in these loci remain unclear. Recently, genomic loci 10q26.12 with lead SNP rs1665650 was identified as an essential CRC risk loci of Asian populations. However, the functional mechanism of this region has not been fully clarified. Here, we applied an RNA interfering-based on-chip approach to screen for the genes essential for cell proliferation in the CRC risk loci 10q26.12. Notably, HSPA12A had the most significant effect among the identified genes and functioned as a crucial oncogene facilitating cell proliferation. Moreover, we conducted an integrative fine-mapping analysis to identify putative casual variants and further explored their association with CRC risk in a large-scale Chinese population consisting of 4054 cases and 4054 controls and also independently validated in 5208 cases and 20,832 controls from the UK biobank cohort. We identified a risk SNP rs7093835 in the intron of HSPA12A that was significantly associated with an increased risk of CRC (OR 1.23, 95% CI 1.08-1.41, P = 1.92 × 10-3). Mechanistically, the risk variant could facilitate an enhancer-promoter interaction mediated by the transcriptional factor (TF) GRHL1 and ultimately upregulate HSPA12A expression, which provides functional evidence to support our population findings. Collectively, our study reveals the important role of HSPA12A in CRC development and illustrates a novel enhancer-promoter interaction module between HSPA12A and its regulatory elements rs7093835, providing new insights into the etiology of CRC.

Triclosan is associated with breast cancer via oxidative stress and relative telomere length.

Introduction: Triclosan (TCS), a widely prescribed broad-spectrum antibacterial agent, is an endocrine-disrupting chemical. The relationship and biological mechanisms between TCS exposure and breast cancer (BC) are disputed. We aimed to examine the correlation between urinary TCS exposure and BC risk and estimated the mediating effects of oxidative stress and relative telomere length (RTL) in the above association. Methods: This case-control study included 302 BC patients and 302 healthy individuals in Wuhan, China. We detected urinary TCS, three common oxidative stress biomarkers [8-hydroxy-2-deoxyguanosine (8-OHdG), 8-iso-prostaglandin F2α (8-isoPGF2α), 4-hydroxy-2-nonenal-mercapturic acid (HNE-MA)], and RTL in peripheral blood mononuclear cells. Results: Significant associations were observed between log-transformed urinary concentrations of TCS, 8-OHdG, HNE-MA, 8-isoPGF2α, RTL, and BC risk, with the odds ratios (95% confidence intervals) being 1.58 (1.32-1.91), 3.08 (1.55-6.23), 3.39 (2.45-4.77), 3.99 (2.48-6.54), and 1.67 (1.35-2.09), respectively. Continuous TCS exposure was significantly positively correlated with RTL, HNE-MA, and 8-isoPGF2α (all p<0.05) but not with 8-OHdG (p = 0.060) after adjusting for covariates. The mediated proportions of 8-isoPGF22α and RTL in the relationship between TCS and BC risk were 12.84% and 8.95%, respectively (all p<0.001). Discussion: In conclusion, our study provides epidemiological evidence to confirmed the deleterious effects of TCS on BC and indicated the mediating effect of oxidative stress and RTL on the correlation between TCS and BC risk. Moreover, exploring the contribution of TCS to BC can clarify the biological mechanisms of TCS exposure, provide new clues for the pathogenesis of BC, which is of great significance to improving public health systems.

Saturated fatty acid intake, genetic risk and colorectal cancer incidence: A large-scale prospective cohort study.

Previous investigations mainly focused on the associations of dietary fatty acids with colorectal cancer (CRC) risk, which ignored gene-environment interaction and mechanisms interpretation. We conducted a case-control study (751 cases and 3058 controls) and a prospective cohort study (125 021 participants) to explore the associations between dietary fatty acids, genetic risks, and CRC. Results showed that high intake of saturated fatty acid (SFA) was associated with a higher risk of CRC than low SFA intake (HR =1.22, 95% CI:1.02-1.46). Participants at high genetic risk had a greater risk of CRC with the HR of 2.48 (2.11-2.91) than those at low genetic risk. A multiplicative interaction of genetic risk and SFA intake with incident CRC risk was found (PInteraction = 7.59 × 10-20 ), demonstrating that participants with high genetic risk and high SFA intake had a 3.75-fold greater risk of CRC than those with low genetic risk and low SFA intake. Furthermore, incorporating PRS and SFA into traditional clinical risk factors improved the discriminatory accuracy for CRC risk stratification (AUC from 0.706 to 0.731). Multi-omics data showed that exposure to SFA-rich high-fat dietary (HFD) can responsively induce epigenome reprogramming of some oncogenes and pathological activation of fatty acid metabolism pathway, which may contribute to CRC development through changes in gut microbiomes, metabolites, and tumor-infiltrating immune cells. These findings suggest that individuals with high genetic risk of CRC may benefit from reducing SFA intake. The incorporation of SFA intake and PRS into traditional clinical risk factors will help improve high-risk sub-populations in individualized CRC prevention.

Identification of specific susceptibility loci for the early-onset colorectal cancer.

BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC; patients < 50 years old) has been rising rapidly, whereas the EOCRC genetic susceptibility remains incompletely investigated. Here, we aimed to systematically identify specific susceptible genetic variants for EOCRC. METHODS: Two parallel GWASs were conducted in 17,789 CRC cases (including 1490 EOCRC cases) and 19,951 healthy controls. A polygenic risk score (PRS) model was built based on identified EOCRC-specific susceptibility variants by using the UK Biobank cohort. We also interpreted the potential biological mechanisms of the prioritized risk variant. RESULTS: We identified 49 independent susceptibility loci that were significantly associated with the susceptibility to EOCRC and the diagnosed age of CRC (both P < 5.0×10-4), replicating 3 previous CRC GWAS loci. There are 88 assigned susceptibility genes involved in chromatin assembly and DNA replication pathways, mainly associating with precancerous polyps. Additionally, we assessed the genetic effect of the identified variants by developing a PRS model. Compared to the individuals in the low genetic risk group, the individuals in the high genetic risk group have increased EOCRC risk, and these results were replicated in the UKB cohort with a 1.63-fold risk (95% CI: 1.32-2.02, P = 7.67×10-6). The addition of the identified EOCRC risk loci significantly increased the prediction accuracy of the PRS model, compared to the PRS model derived from the previous GWAS-identified loci. Mechanistically, we also elucidated that rs12794623 may contribute to the early stage of CRC carcinogenesis via allele-specific regulating the expression of POLA2. CONCLUSIONS: These findings will broaden the understanding of the etiology of EOCRC and may facilitate the early screening and individualized prevention.

Pan-Cancer Analysis of Microbiome Quantitative Trait Loci.

Microorganisms are commonly detected in tumor tissues, and the species and abundance have been reported to affect cancer initiation, progression, and therapy. Host genetics have been associated with gut microbial abundances, while the relationships between genetic variants and the cancer microbiome still require systematic interrogation. Therefore, identification of cancer microbiome quantitative trait loci (mbQTL) across cancer types might elucidate the contributions of genetic variants to tumor development. Using genotype data from The Cancer Genome Atlas and microbial abundance levels from Kraken-derived data, we developed a computational pipeline to identify mbQTLs in 32 cancer types. This study systematically identified 38,660 mbQTLs across cancers, ranging 50 in endometrial carcinoma to 3,133 in thyroid carcinoma. Furthermore, a strong enrichment of mbQTLs was observed among transcription factor binding sites and chromatin regulatory elements, such as H3K27ac. Notably, mbQTLs were significantly enriched in cancer genome-wide association studies (GWAS) loci and explained an average of 2% for cancer heritability, indicating that mbQTLs could provide additional insights into cancer etiology. Correspondingly, 24,443 mbQTLs overlapping with GWAS linkage disequilibrium regions were identified. Survival analyses identified 318 mbQTLs associated with patient overall survival. Moreover, we uncovered 135,248 microbiome-immune infiltration associations and 166,603 microbiome-drug response associations that might provide clues for microbiome-based biomarkers. Finally, a user-friendly database, Cancer-mbQTL (http://canmbqtl.whu.edu.cn/#/), was constructed for users to browse, search, and download data of interest. This study provides a valuable resource for investigating the roles of genetics and microorganisms in human cancer. SIGNIFICANCE: This study provides insights into the host-microbiome interactions for multiple cancer types, which could help the research community understand the effects of inherited variants in tumorigenesis and development.

Aberrant RNA Splicing Is a Primary Link between Genetic Variation and Pancreatic Cancer Risk.

Understanding the genetic variation underlying transcript splicing is essential for fully dissecting the molecular mechanisms of common diseases. The available evidence from splicing quantitative trait locus (sQTL) studies using pancreatic ductal adenocarcinoma (PDAC) tissues have been limited to small sample sizes. Here we present a genome-wide sQTL analysis to identify SNP that control mRNA splicing in 176 PDAC samples from TCGA. From this analysis, 16,175 sQTLs were found to be significantly enriched in RNA-binding protein (RBP) binding sites and chromatin regulatory elements and overlapped with known loci from PDAC genome-wide association studies (GWAS). sQTLs and expression quantitative trait loci (eQTL) showed mostly nonoverlapping patterns, suggesting sQTLs provide additional insights into the etiology of disease. Target genes affected by sQTLs were closely related to cancer signaling pathways, high mutational burden, immune infiltration, and pharmaceutical targets, which will be helpful for clinical applications. Integration of a large-scale population consisting of 2,782 patients with PDAC and 7,983 healthy controls identified an sQTL variant rs1785932-T allele that promotes alternative splicing of ELP2 exon 6 and leads to a lower level of the ELP2 full-length isoform (ELP2_V1) and a higher level of a truncated ELP2 isoform (ELP2_V2), resulting in decreased risk of PDAC [OR = 0.83; 95% confidence interval (CI), 0.77-0.89; P = 1.16 × 10-6]. The ELP2_V2 isoform functioned as a potential tumor suppressor gene, inhibiting PDAC cell proliferation by exhibiting stronger binding affinity to JAK1/STAT3 than ELP2_V1 and subsequently blocking the pathologic activation of the phosphorylated STAT3 (pSTAT3) pathway. Collectively, these findings provide an informative sQTL resource and insights into the regulatory mechanisms linking splicing variants to PDAC risk. SIGNIFICANCE: In pancreatic cancer, splicing quantitative trait loci analysis identifies a rs1785932 variant that contributes to decreased risk of disease by influencing ELP2 mRNA splicing and blocking the STAT3 oncogenic pathway.

[Interaction between long noncoding RNA and environmental factors on coronary heart disease].

OBJECTIVE: To investigate the role of leukocyte long noncoding RNA(lncRNA) and environmental factors on coronary heart disease(CHD). METHODS: A case-control study was conducted in a hospital in Fuzhou City by using stratified random sampling method during March 2015 and December 2017. The related surveys included questionnaire investigation, physical examination and laboratory detection. And real-time fluorescence quantitative PCR was used to detect the expression of lncRNA(NR_027032, NR_047116 and NR_104181) in case group and control group. Multivariate Logistic regression models and crossover analysis were used to analyze the interaction and association of environmental factors and lncRNA on CHD. RESULTS: Wilcoxon rank sum test indicated that: The expression levels of NR_027032, NR_047116 and NR_104181 in CHD were lower than those in control group, the difference was statistically significant(P<0.05). Multivariate Logistic regression analysis showed that the low expression of NR_027032, NR_047116 and NR_104181 may increase the risk of CHD. Crossover analysis showed that the risk of CHD was 19.053 times(95% CI 5.159-70.361) in the presence of overweight and low expression of NR_047116 than that in the normal condition. And the additive model between the two groups was statistically significant(U=1.999, P=0.046). The evaluation indexes were S=0.598, AP=10.070 and RERI=0.629. CONCLUSION: CHD is the result of environmental factors and genetic factors. The association and additive effect of NR_047116 low expression and overweight may increase the risk of CHD.