To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.

The gut microbiome has a fundamental role in human health and disease. However, studying the complex structure and function of the gut microbiome using next generation sequencing is challenging and prone to reproducibility problems. Here, we obtained cross-sectional colon biopsies and faecal samples from nine participants in our COLSCREEN study and sequenced them in high coverage using Illumina pair-end shotgun (for faecal samples) and IonTorrent 16S (for paired feces and colon biopsies) technologies. The metagenomes consisted of between 47 and 92 million reads per sample and the targeted sequencing covered more than 300 k reads per sample across seven hypervariable regions of the 16S gene. Our data is freely available and coupled with code for the presented metagenomic analysis using up-to-date bioinformatics algorithms. These results will add up to the informed insights into designing comprehensive microbiome analysis and also provide data for further testing for unambiguous gut microbiome analysis.

Several studies have examined environmental factors and inflammatory bowel diseases (IBD) using traditional approaches; however, provided results are still conflicting. Our aim was to determine whether lifestyle and nutrient exposures, related to IBD in observational meta-analyses, influence IBD risk using a Mendelian randomization (MR) approach. A two-sample MR approach was applied on summary-level genome-wide association results. Genetic variants strongly associated with measures of tobacco smoking, obesity and fat distribution, physical activity, and blood levels of vitamins and fatty acids were evaluated on genetic data from international IBD consortia including a total of 25,042 IBD cases (12,194 cases of Crohn’s disease (CD) and 12,366 cases of ulcerative colitis (UC)) and 34,915 controls. Our results indicated that, among lifestyle exposures, being a smoker was positively associated with CD (OR 1.13, P = 0.02), but it was not associated with UC risk (OR 0.99, P = 0.88). Body-mass index (BMI) and body fat percentage were positively associated with CD (OR 1.11, P = 0.02, per standard deviation (SD) of 4.6 kg/m²; and OR 1.50, P = 3 × 10^–10, per SD of 6.6%; respectively); while for UC, BMI was inversely associated (OR 0.85, P = 5 × 10^–5; per SD) and body fat percentage showed a OR of 1.11 (P = 0.11; per SD). Additionally, among nutrient exposures, omega-3 fatty acids levels were inversely associated with CD (OR 0.67, P = 2 × 10^–6). Our MR results did not support a protective effect for being a smoker on UC risk; however, they are compatible with a risk effect for higher body fat proportion and a protective role for higher levels of omega-3 fatty acids on CD etiology.

Colorectal cancer (CRC) screening of the average risk population is only indicated according to age. We aim to elaborate a model to stratify the risk of CRC by incorporating environmental data and single nucleotide polymorphisms (SNP). The MCC-Spain case-control study included 1336 CRC cases and 2744 controls. Subjects were interviewed on lifestyle factors, family and medical history. Twenty-one CRC susceptibility SNPs were genotyped. The environmental risk model, which included alcohol consumption, obesity, physical activity, red meat and vegetable consumption, and nonsteroidal anti-inflammatory drug use, contributed to CRC with an average per factor OR of 1.36 (95% CI 1.27 to 1.45). Family history of CRC contributed an OR of 2.25 (95% CI 1.87 to 2.72), and each additional SNP contributed an OR of 1.07 (95% CI 1.04 to 1.10). The risk of subjects with more than 25 risk alleles (5^th quintile) was 82% higher (OR 1.82, 95% CI 1.11 to 2.98) than subjects with less than 19 alleles (1^st quintile). This risk model, with an AUROC curve of 0.63 (95% CI 0.60 to 0.66), could be useful to stratify individuals. Environmental factors had more weight than the genetic score, which should be considered to encourage patients to achieve a healthier lifestyle.

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, we aimed to 1) generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse and descending), 2) identify expression and splicing quantitative trait loci (QTLs), 3) find traits for which identified QTLs contribute to single nucleotide polymorphism (SNP)-based heritability, 4) propose candidate effector genes, and 5) provide a web-based visualization resource. We collected colonic mucosal biopsies from 485 healthy adults and performed bulk RNA sequencing (RNA-Seq). We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses. 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 (CoTrEx). We provided the largest characterization to date of gene expression and splicing across colon subsites. Our findings provide greater etiological insight into complex traits and diseases influenced by transcriptomic changes in colon tissue.