Molecular epidemiology study on genetically regulated gene expression in the colonic mucosa and its role in disease susceptibility

[spa] La expresión genética es un proceso celular clave, que además está relacionado con la susceptibilidad genética a enfermedades y rasgos complejos. La mayoría de genes se someten a splicing alternativo (AS). Las variantes genéticas que regulan la expresión genética y el AS se llaman ¿quantitative trait loci¿ (e/sQTLs). Técnicas estadísticas permiten predecir in silico la expresión genética en un tejido concreto a partir de datos genéticos. Esta aproximación se lleva a cabo en los estudios de asociación de transcriptoma completo (TWAS). Esta Tesis se compone de tres objetivos principales y presenta tres artículos. 1) Generar perfiles de expresión genética de la mucosa colónica de individuos sanos, así como sus diferencias a lo largo del colon y sus e/sQTLs asociados; 2) Desarrollar una aplicación web que permita explorar los datos de expresión genética en el colon; 3) Llevar a cabo un TWAS para proponer genes de susceptibilidad a enfermedad inflamatoria intestinal (EII). Como resumen de los resultados, 1) se generaron catálogos de e/sQTLs a partir de nuevos datos de expresión genética en colon de 445 individuos, y se encontraron más de 4,000 genes que varían sus niveles de expresión a lo largo del colon; 2) se desarrolló el "Colon Transcriptome Explorer", disponible públicamente en https://barcuvaseq.org/cotrex/; 3) se propusieron más de doscientos genes de susceptibilidad genética a EII. En conclusión, nuestros estudios proporcionan nuevos datos y evidencias sobre los genes involucrados en mecanismos de susceptibilidad a enfermedades relacionadas con el colon, y servirán de guía a otros investigadores para proponer nuevas hipótesis en este campo

Oncogenic Features in Histologically Normal Mucosa: Novel Insights Into Field Effect From a Mega-Analysis of Colorectal Transcriptomes

Introduction: Colorectal cancer is a common malignancy that can be cured when detected early, but recurrence among survivors is a persistent risk. A field effect of cancer in the colon has been reported and could have implications for surveillance, but studies to date have been limited. A joint analysis of pooled transcriptomic data from all available bulk RNA-sequencing data sets of healthy, histologically normal tumor-adjacent, and tumor tissues was performed to provide an unbiased assessment of field effect. Methods: A novel bulk RNA-sequencing data set from biopsies of nondiseased colon from screening colonoscopy along with published data sets from the Genomic Data Commons and Sequence Read Archive were considered for inclusion. Analyses were limited to samples with a quantified read depth of at least 10 million reads. Transcript abundance was estimated with Salmon, and downstream analysis was performed in R. Results: A total of 1,139 samples were analyzed in 3 cohorts. The primary cohort consisted of 834 independent samples from 8 independent data sets, including 462 healthy, 61 tumor-adjacent, and 311 tumor samples. Tumor-adjacent gene expression was found to represent an intermediate state between healthy and tumor expression. Among differentially expressed genes in tumor-adjacent samples, 1,143 were expressed in patterns similar to tumor samples, and these genes were enriched for cancer-associated pathways. Discussion: Novel insights into the field effect in colorectal cancer were generated in this mega-analysis of the colorectal transcriptome. Oncogenic features that might help explain metachronous lesions in cancer survivors and could be used for surveillance and risk stratification were identified

Co‐occurrence of germline pathogenic variants for different hereditary cancer syndromes in patients with Lynch syndrome

Background: Lynch syndrome (LS) is a hereditary condition characterized by a high risk of colorectal cancer, endometrial cancer, and other neoplasia associated with germline alterations in DNA mismatch repair genes. The classical genetic diagnostic strategy for LS consists of the Sanger sequencing of genes associated with the suspected syndrome. Next‐generation sequencing (NGS) enables the simultaneous sequencing of a large number of hereditary cancer genes. Here, we aimed to study whether other germline pathogenic variants of hereditary cancer genes are present in patients with LS. Methods: A cohort of 84 probands with a previous genetic diagnosis of LS by Sanger sequencing was reanalyzed using NGS via a commercial panel of 94 hereditary cancer genes by hybrid capture. The American College of Medical Genetics and Genomics criteria were used to classify the clinical significance of the variants. The findings of NGS were confirmed by Sanger sequencing. When possible, genetic analyses of the new findings in the proband's relatives were also performed by Sanger sequencing. Results: We identified five families (6%), out of 84, with at least two germline pathogenic variants conferring to high or moderate risk in different dominant cancer‐predisposing genes: [MLH1‐BRCA2‐NBN], [MLH1‐BRCA1], [MSH2‐ATM], [MSH6‐NF1], and [MLH1‐FANCA]. Interestingly, only one out of these five families exhibited a clinical phenotype associated with the new pathogenic variants. The family with three pathogenic variants of the [MLH1‐BRCA2‐NBN] genes showed a high aggregation of tumors associated with LS and breast and ovarian cancer syndrome. Conclusions: Our results showed that the co‐occurrence of more than one pathogenic variant in cancer‐predisposing genes was remarkable among cases of LS. In most cases, no clinicial manifestations were associated with the secondary pathogenic variants. Further studies are needed to confirm these findings and elucidate their clinical impact. Reanalysis of LS families should be considered only in families with mixed clinical phenotypes.RFA is a recipient of a Fellowship from the Consellería Educación of the Valencian Community. The studies of ED and ACA are funded by the Acción Juvenil from Consellería Educación of the Valencian Community and the Spanish Ministry of Economy and Competitiveness, respectively. VDO is a recipient of a Fellowship from the Spanish Association Against Cancer (AECC). This work was supported by grants from the Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, FISABIO (Grants: UGP‐14‐192 and UGP‐16‐146), and the Carlos III Health Institute (Grant AES: PI17/01082)

Probing the diabetes and colorectal cancer relationship using gene – environment interaction analyses

BackgroundDiabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis.MethodsWe used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test).ResultsBased on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value(3-d.f.): 5.46 x 10(-11)) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value(2-d.f.): 7.84 x 10(-09)).DiscussionThese results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship

Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci

Background & aims: The association of genetic variation with tissue-specific gene expression and alternative splicing guides functional characterization of complex trait-associated loci and may suggest novel genes implicated in disease. Here, our aims were as follows: (1) to generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse, and descending), (2) to identify expression and splicing quantitative trait loci (QTLs), (3) to find traits for which identified QTLs contribute to single-nucleotide polymorphism (SNP)-based heritability, (4) to propose candidate effector genes, and (5) to provide a web-based visualization resource. Methods: We collected colonic mucosal biopsy specimens from 485 healthy adults and performed bulk RNA sequencing. We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses. Results: We provided a complete quantification of gene expression and alternative splicing across colon subsites and described their differences. We identified thousands of expression and splicing QTLs and defined their enrichment at genome-wide regulatory regions. We found that part of the SNP-based heritability of diseases affecting colon tissue, such as colorectal cancer and inflammatory bowel disease, but also of diseases affecting other tissues, such as psychiatric conditions, can be explained by the identified QTLs. We provided candidate effector genes for multiple phenotypes. Finally, we provided the Colon Transcriptome Explorer web application. Conclusions: We provide a large characterization of gene expression and splicing across colon subsites. Our findings provide greater etiologic insight into complex traits and diseases influenced by transcriptomic changes in colon tissue

Colorectal cancer, sun exposure and dietary vitamin D and calcium intake in the MCC-Spain study

Objectives: To explore the association of colorectal cancer with environmental solar radiation and sun exposure behavior, considering phenotypic variables (eye color, hair color and skin phenotype), dietary intake of vitamin D and calcium, and socio-demographic factors. Study design: Multicenter population-based frequency matched case-control study in Spain (MCC-Spain), with 2140 CRC cases and 3950 controls. Methods: Data were obtained through personal interviews using a structured epidemiological questionnaire that included socio-demographic data, residential history, environmental exposures, behavior, phenotypic and dietary information. An environmental-lifetime sun exposure score was constructed combining residential history and average daily solar radiation, direct and diffuse. Logistic regression was used to explore the association between different variables. A structural equation model was used to verify the associations of the conceptual model. Results: We found a lower risk of CRC in subjects frequently exposed to sunlight during the previous summer and skin burning due to sun exposure. No association was observed in relation to the residential solar radiation scores. Subjects with light eye or light hair colors had a lower risk of CRC that those with darker colors. Dietary calcium and vitamin D were also protective factors, but not in the multivariate model. The structural equation model analysis suggested that higher sun exposure was associated with a decreased risk of CRC, as well as dietary intake of calcium and vitamin D, and these factors are correlated among themselves and with environmental solar radiation and skin phenotypes. Conclusion: The results agree with previous observations that sun exposure, dietary vitamin D and calcium intake, and serum 25(OH)D concentration reduce the risk of CRC and indicate that these factors may be relevant for cancer prevention

Characterization of a novel POLD1 missense founder mutation in a Spanish population

Background: We identified a new and a recurrent POLD1 mutation associated with predisposition to colorectal cancer (CRC). We characterized the molecular and clinical nature of the potential POLD1 founder mutation in families from Valencia (Spain). Methods: Clinical and molecular data were collected from four independent families known to have a POLD1 Leu474Pro mutation. To establish its founder effect, haplotype construction was performed using 14 flanking POLD1 polymorphic markers. We calculated penetrance estimates and clinical expressivity, globally and stratified by age and sex. Results: We included 32 individuals from the four families: 20 carriers and 12 noncarriers. A common haplotype was identified in these families in a region comprising 2,995 Mb, confirming L474P as the first founder POLD1 mutation identified. Thirteen tumors diagnosed in 10 POLD1 carriers: eight CRC, three endometrial and two other tumors were considered. The median age of cancer onset for POLD1 mutation carriers was 48 years. The observed penetrance was 50% and the cumulative risk at age of 50 years was 30%. Conclusions: The findings of the present study contribute to a better understanding of CRC genetics in the Spanish population. The clinical phenotype for this mutation is similar to that in Lynch syndrome. Future studies using next generation sequencing with large gene panels for any hereditary cancer condition will offer the possibility of detecting POLE/POLD1 mutations in unsuspected clinical situations, demonstrating a more real and unbiased picture of the associated phenotype.This work was supported by the Institute for Health and Biomedical Research of Alicante (ISABIAL, UGP‐16‐146). RFA is recipient of a Fellowship from the Consellería Educación of the Valencian Community. ACA is funded by the Acción Juvenil from the Spanish Ministry of Economy and Competitiveness. VDO is recipient of a Fellowship from the Spanish Association Against Cancer (AECC). AC and MIC are funded by Health and Biomedical Research Foundation from the Valencian Region (FISABIO). EHI is recipient of a fellowship from the Fondo Investigación Sanitaria ISCIII (FI12/00233)

COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

Colonomics is a multi-omics dataset that includes 250 samples: 50 samples from healthy colon mucosa donors and 100 paired samples from colon cancer patients (tumor/adjacent). From these samples, Colonomics project includes data from genotyping, DNA methylation, gene expression, whole exome sequencing and micro-RNAs (miRNAs) expression. It also includes data from copy number variation (CNV) from tumoral samples. In addition, clinical data from all these samples is available. The aims of the project were to explore and integrate these datasets to describe colon cancer at molecular level and to compare normal and tumoral tissues. Also, to improve screening by finding biomarkers for the diagnosis and prognosis of colon cancer. This project has its own website including four browsers allowing users to explore Colonomics datasets. Since generated data could be reuse for the scientific community for exploratory or validation purposes, here we describe omics datasets included in the Colonomics project as well as results from multi-omics layers integration

Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

In the version of this article initially published, the author affiliations incorrectly listed “Candiolo Cancer Institute FPO-IRCCS, Candiolo (TO), Italy” as “Candiolo Cancer Institute, Candiolo, Italy.” The change has been made to the HTML and PDF versions of the article

Expression and splicing quantitative trait locus (e/sQTLs) summary statistics from normal colon tissue

We profiled gene expression and alternative splicing of non-neoplastic colon from biopsies of 445 healthy individuals. Here we provide summary statistics listings of BarcUVa-Seq eQTLs and sQTLs (from SUPPA2 and from LeafCutter), and of GTEx v8 transverse colon and sigmoid colon sQLTs (from SUPPA2). Filenames indicate the content of each file: {study}.{analysis}.{method}