BACKGROUND: Some genetic polymorphisms (SNPs) have been proposed as predictors for different colorectal cancer (CRC) outcomes. This work aims to assess their performance in our cohort and find new SNPs associated with them. METHODS: A total of 833 CRC cases were analyzed for seven outcomes, including the use of chemotherapy, and stratified by tumor location and stage. The performance of 63 SNPs was assessed using a generalized linear model and area under the receiver operating characteristic curve, and local SNPs were detected using logistic regressions. RESULTS: In total 26 of the SNPs showed an AUC > 0.6 and a significant association (p < 0.05) with one or more outcomes. However, clinical variables outperformed some of them, and the combination of genetic and clinical data showed better performance. In addition, 49 suggestive (p < 5 × 10-6) SNPs associated with one or more CRC outcomes were detected, and those SNPs were located at or near genes involved in biological mechanisms associated with CRC. CONCLUSIONS: Some SNPs with clinical data can be used in our population as predictors of some CRC outcomes, and the local SNPs detected in our study could be feasible markers that need further validation as predictors.
The incidence of colorectal cancer (CRC) is increasing, and currently it is the third most common cancer. Early CRC diagnosis is still difficult and relies on an invasive colonoscopy and tissue biopsy. The globally observed tendency demands non-invasive, specific, and accurate diagnostic tools for early diagnosis and prognosis. In this work, the main aim was to evaluate for the first time the feasibility of using extracts from the non-invasive sample collection from faecal occult blood (FOB) kits for its use in metabolomics studies taking advantage in this way of the high sensitivity of this technology. Then, a cohort of 131 samples from control individuals (CTL), adenoma (AD) and CRC patients were analysed using a semitargeted approach by ultra-high-performance liquid chromatography-time-of-flight-mass spectrometry (UHPLC-ToF-MS). Multivariate and univariate statistical analysis revealed that cholesteryl esters (ChoE) with polyunsaturated fatty acids (PUFAs) together with FOB were relevant metabolites that could clearly separate CRC patients from AD and CTL individuals, whereas the metabolic profiles of CTL and AD were very similar. These results are in agreement with previous findings and reveal the advantage of using the same FOBT samples for several analyses, which would facilitate sample collection and improve direct connection between FOB measurements and metabolomics analysis. Although the sample size and the number of metabolites should be enhanced to cover a wider range of metabolites, alterations in lipid metabolism clearly point out for future perspectives.
Although the genetic contribution to colorectal cancer (CRC) has been studied in various populations, studies on the applicability of available genetic information in the Basque population are scarce. In total, 835 CRC cases and 940 controls from the Basque population were genotyped and genome-wide association studies were carried out. Mendelian Randomization analyses were used to discover the effect of modifiable risk factors and microbiota on CRC. In total, 25 polygenic risk score models were evaluated to assess their performance in CRC risk calculation. Moreover, 492 inflammatory bowel disease cases were used to assess whether that genetic information would not confuse both conditions. Five suggestive (p < 5 × 10−6) loci were associated with CRC risk, where genes previously associated with CRC were located (e.g., ABCA12, ATIC or ERBB4). Moreover, the analyses of CRC locations detected additional genes consistent with the biology of CRC. The possible contribution of cholesterol, BMI, Firmicutes and Cyanobacteria to CRC risk was detected by Mendelian Randomization. Finally, although polygenic risk score models showed variable performance, the best model performed correctly regardless of the location and did not misclassify inflammatory bowel disease cases. Our results are consistent with CRC biology and genetic risk models and could be applied to assess CRC risk in the Basque population.
BACKGROUND: Colorectal cancer (CRC), a major health concern, is developed depending on environmental, genetic and microbial factors. The microbiome and metabolome have been analyzed to study their role in CRC. However, the interplay of host genetics with those layers in CRC remains unclear. METHODS: 120 individuals were sequenced and association analyses were carried out for adenoma and CRC risk, and for selected components of the microbiome and metabolome. The epistasis between genes located in cholesterol pathways was analyzed; modifiable risk factors were studied using Mendelian randomization; and the three omic layers were used to integrate their data and to build risk prediction models. RESULTS: We detected genetic variants that were associated to components of metabolome or microbiome and adenoma or CRC risk (e.g., in LINC01605, PROKR2 and CCSER1 genes). In addition, we found interactions between genes of cholesterol metabolism, and HDL cholesterol levels affected adenoma (p = 0.0448) and CRC (p = 0.0148) risk. The combination of the three omic layers to build risk prediction models reached high AUC values (>0.91). CONCLUSIONS: The use of the three omic layers allowed for the finding of biological mechanisms related to the development of adenoma and CRC, and each layer provided complementary information to build risk prediction models.
OBJECTIVES: To examine the relationship between antibody status and cycle threshold (Ct) values, the prognostic value of the latter for COVID-19 patients, and the inter-assay comparability of SARS-CoV-2 Ct values. METHODS: In 347 COVID-19 inpatients, SARS-CoV-2 Ct values (via reverse transcription-quantitative polymerase chain reaction) on admission were compared between 2 assays and correlated with the antibody response (in the course of the disease), the clinical course and the time since onset of symptoms. RESULTS: Ct values for 2 of 3 target genes showed significant differences between the 2 assays used (P=0.012 and P<0.0001). Ct values were significantly higher for antibody positive patients (P<0.0001) and positively correlated with the amount of time since onset of symptoms (R: 0.332-0.363; P<0.001). Patients with fatal outcomes showed higher viral loads than survivors (P<0.0001). CONCLUSIONS: Ct values depend strongly on assay used and target gene examined and should not be used as quantitative values to guide therapeutic or diagnostic decisions. The inverse association between antibody status and viral load suggests that antibodies contribute to the elimination of the virus, independent of the outcome, which is influenced by the viral load on admission and might depend more strongly on other parts of the immune response.
COVID-19 , SARS-CoV-2 , Humans , Incidence , Reverse Transcriptase Polymerase Chain Reaction , Reverse Transcription , Viral Load
Laboratory testing for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consists of two pillars: the detection of viral RNA via rt-PCR as the diagnostic gold standard in acute cases, and the detection of antibodies against SARS-CoV-2. However, concerning the latter, questions remain about their diagnostic and prognostic value and it is not clear whether all patients develop detectable antibodies. We examined sera from 347 Spanish COVID-19 patients, collected during the peak of the epidemic outbreak in Spain, for the presence of IgA and IgG antibodies against SARS-CoV-2 and evaluated possible associations with age, sex and disease severity (as measured by duration of hospitalization, kind of respiratory support, treatment in ICU and death). The presence and to some degree the levels of anti-SARS-CoV-2 antibodies depended mainly on the amount of time between onset of symptoms and the collection of serum. A subgroup of patients did not develop antibodies at the time of sample collection. Compared to the patients that did, no differences were found. The presence and level of antibodies was not associated with age, sex, duration of hospitalization, treatment in the ICU or death. The case-fatality rate increased exponentially with older age. Neither the presence, nor the levels of anti-SARS-CoV-2 antibodies served as prognostic markers in our cohort. This is discussed as a possible consequence of the timing of the sample collection. Age is the most important risk factor for an adverse outcome in our cohort. Some patients appear not to develop antibodies within a reasonable time frame. It is unclear, however, why that is, as these patients differ in no respect examined by us from those who developed antibodies.
Antibodies, Viral/immunology , COVID-19/diagnosis , COVID-19/immunology , SARS-CoV-2/immunology , SARS-CoV-2/pathogenicity , Adult , Aged , Aged, 80 and over , COVID-19/virology , Cohort Studies , Female , Humans , Incidence , Male , Middle Aged , Spain
