Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of ...CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening.
We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry.
In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62–0.64) for men and 0.62 (95% confidence interval, 0.61–0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk.
We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.
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Early-onset colorectal cancer diagnosed before the age of 50 years has been increasing. Likely reflecting the pathogenic role of the intestinal microbiome, which gradually changes across the entire ...colorectal length, the prevalence of certain tumor molecular characteristics gradually changes along colorectal subsites. Understanding how colorectal tumor molecular features differ by age and tumor location is important in personalized patient management.
Using 14,004 cases with colorectal cancer including 3,089 early-onset cases, we examined microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF mutations in carcinomas of the cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum and compared early-onset cases with later-onset cases.
The proportions of MSI-high, CIMP-high, and BRAF -mutated early-onset tumors were lowest in the rectum (8.8%, 3.4%, and 3.5%, respectively) and highest in the ascending colon (46% MSI-high; 15% CIMP-high) or transverse colon (8.6% BRAF -mutated) (all Ptrend <0.001 across the rectum to ascending colon). Compared with later-onset tumors, early-onset tumors showed a higher prevalence of MSI-high status and a lower prevalence of CIMP-high status and BRAF mutations in most subsites. KRAS mutation prevalence was higher in the cecum compared with that in the other subsites in both early-onset and later-onset tumors ( P < 0.001). Notably, later-onset MSI-high tumors showed a continuous decrease in KRAS mutation prevalence from the rectum (36%) to ascending colon (9%; Ptrend <0.001), followed by an increase in the cecum (14%), while early-onset MSI-high cancers showed no such trend.
Our findings support biogeographical and pathogenic heterogeneity of colorectal carcinomas in different colorectal subsites and age groups.
Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor ...mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87-100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10
and p = 6 × 10
, respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.
The role of the human gut microbiome in colorectal cancer (CRC) is unclear as most studies on the topic are unable to discern correlation from causation. We apply two-sample Mendelian randomization ...(MR) to estimate the causal relationship between the gut microbiome and CRC. We used summary-level data from independent genome-wide association studies to estimate the causal effect of 14 microbial traits (n = 3890 individuals) on overall CRC (55,168 cases, 65,160 controls) and site-specific CRC risk, conducting several sensitivity analyses to understand the nature of results. Initial MR analysis suggested that a higher abundance of Bifidobacterium and presence of an unclassified group of bacteria within the Bacteroidales order in the gut increased overall and site-specific CRC risk. However, sensitivity analyses suggested that instruments used to estimate relationships were likely complex and involved in many potential horizontal pleiotropic pathways, demonstrating that caution is needed when interpreting MR analyses with gut microbiome exposures. In assessing reverse causality, we did not find strong evidence that CRC causally affected these microbial traits. Whilst our study initially identified potential causal roles for two microbial traits in CRC, importantly, further exploration of these relationships highlighted that these were unlikely to reflect causality.
The etiology of colorectal cancer is not fully understood.
Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic ...prediction models for circulating metabolites. Models with prediction R2 > 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis.
Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk Benjamini-Hochberg FDR (BH-FDR) < 0.05 in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10-8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR < 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60-2.36, P = 2.6 × 10-11; OREUR: 1.01, 95% CI, 0.99-1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het < 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer.
This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data.
The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.
Colorectal cancer (CRC) is a heterogeneous disease with evidence of distinct tumor types that develop through different somatically altered pathways. To better understand the impact of the host ...genome on somatically mutated genes and pathways, we assessed associations of germline variations with somatic events via two complementary approaches. We first analyzed the association between individual germline genetic variants and the presence of non-silent somatic mutations in genes in 1375 CRC cases with genome-wide SNPs data and a tumor sequencing panel targeting 205 genes. In the second analysis, we tested if germline variants located within previously identified regions of somatic allelic imbalance were associated with overall CRC risk using summary statistics from a recent large scale GWAS (n≃125 k CRC cases and controls). The first analysis revealed that a variant (rs78963230) located within a CNA region associated with TLR3 was also associated with a non-silent mutation within gene FBXW7. In the secondary analysis, the variant rs2302274 located in CDX1/PDGFRB frequently gained/lost in colorectal tumors was associated with overall CRC risk (OR = 0.96, p = 7.50e-7). In summary, we demonstrate that an integrative analysis of somatic and germline variation can lead to new insights about CRC.
This study aims to evaluate the associations of vasomotor symptom (VMS) frequency, bother, and severity with equol producer status and dietary daidzein intake.
This is an observational study. This ...study included women aged 45 to 55 years, in postmenopause or in the menopausal transition, who had soy food intake of three or more servings per week. Exclusion criteria included severe concurrent disease, pregnancy or planned pregnancy, and current use of oral or transdermal hormones or selective estrogen receptor modulators. After screening, 375 participants completed a 3-day VMS diary and a 24-hour urine collection. Women with a urine daidzein or genistein concentration of 100 ng/mL or higher were included. We evaluated the association of VMS--dichotomized as lower than or equal to versus higher than the mean number of VMS per day (<2.33, ≥ 2.33)--with quartiles of daidzein intake.
Overall, 129 (35%) of 365 women were equol producers. The mean (SD) urinary equol excretion was 0.67 (1.57) mg/day (50th percentile, 0 mg/d; 95th percentile, 4.12 mg/d). Among equol producers, the mean (SD) urinary equol excretion was 1.91 (2.15) mg/day (50th percentile, 1.09 mg/d; 95th percentile, 6.27 mg/d). Among equol producers, compared with those in the lowest quartile of dietary daidzein intake (mean, 4.9 mg/d), those in the highest quartile (mean, 28.5 mg/d) were 76% less likely to have VMS higher than the mean number of VMS (odds ratio, 0.24; 95% CI, 0.07-0.83; trend test across all daidzein levels, P = 0.06). Among equol nonproducers, there were no associations between daidzein intake and VMS frequency. There were no differences in VMS bother or severity among equol producers or nonproducers by dietary daidzein level.
Among equol producers, higher equol availability attributable to higher soy consumption contributes to decreased VMS.
Over 50 loci associated with colorectal cancer (CRC) have been uncovered by genome-wide association studies (GWAS). Identifying additional loci has the potential to help elucidate aspects of the ...underlying biological processes leading to better understanding of the pathogenesis of the disease. We re-evaluated a GWAS by excluding controls that have family history of CRC or personal history of colorectal polyps, as we hypothesized that their inclusion reduces power to detect associations. This is supported empirically and through simulations. Two-phase GWAS analysis was performed in a total of 16,517 cases and 14,487 controls. We identified rs17094983, a SNP associated with risk of CRC
p
= 2.5 × 10
−10
; odds ratio estimated by re-including all controls (OR) = 0.87, 95 % confidence interval (CI) 0.83–0.91; minor allele frequency (MAF) = 13 %. Results were replicated in samples of African descent (1894 cases and 4703 controls;
p
= 0.01; OR = 0.86, 95 % CI 0.77–0.97; MAF = 16 %). Gene expression data in 195 colon adenocarcinomas and 59 normal colon tissues from two different studies revealed that this locus has genotypes that are associated with RTN1 (Reticulon 1) expression (
p
= 0.001), a protein-coding gene involved in survival and proliferation of cancer cells which is highly expressed in normal colon tissues but has significantly reduced expression in tumor cells (
p
= 1.3 × 10
−8
).
The evaluation of less frequent genetic variants and their effect on complex disease pose new challenges for genomic research. To investigate whether epigenetic data can be used to inform aggregate ...rare-variant association methods (RVAM), we assessed whether variants more significantly associated with colorectal cancer (CRC) were preferentially located in non-coding regulatory regions, and whether enrichment was specific to colorectal tissues.
Active regulatory elements (ARE) were mapped using data from 127 tissues and cell-types from NIH Roadmap Epigenomics and Encyclopedia of DNA Elements (ENCODE) projects. We investigated whether CRC association p-values were more significant for common variants inside versus outside AREs, or 2) inside colorectal (CR) AREs versus AREs of other tissues and cell-types. We employed an integrative epigenomic RVAM for variants with allele frequency <1%. Gene sets were defined as ARE variants within 200 kilobases of a transcription start site (TSS) using either CR ARE or ARE from non-digestive tissues. CRC-set association p-values were used to evaluate enrichment of less frequent variant associations in CR ARE versus non-digestive ARE.
ARE from 126/127 tissues and cell-types were significantly enriched for stronger CRC-variant associations. Strongest enrichment was observed for digestive tissues and immune cell types. CR-specific ARE were also enriched for stronger CRC-variant associations compared to ARE combined across non-digestive tissues (p-value = 9.6 × 10-4). Additionally, we found enrichment of stronger CRC association p-values for rare variant sets of CR ARE compared to non-digestive ARE (p-value = 0.029).
Integrative epigenomic RVAM may enable discovery of less frequent variants associated with CRC, and ARE of digestive and immune tissues are most informative. Although distance-based aggregation of less frequent variants in CR ARE surrounding TSS showed modest enrichment, future association studies would likely benefit from joint analysis of transcriptomes and epigenomes to better link regulatory variation with target genes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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