Elisabet Guinó

SNPStats: a web tool for the analysis of association studies

SUMMARY A web-based application has been designed from a genetic epidemiology point of view to analyze association studies. Main capabilities include descriptive analysis, test for Hardy-Weinberg equilibrium and linkage disequilibrium. Analysis of association is based on linear or logistic regression according to the response variable (quantitative or binary disease status, respectively). Analysis of single SNPs: multiple inheritance models (co-dominant, dominant, recessive, over-dominant and log-additive), and analysis of interactions (gene-gene or gene-environment). Analysis of multiple SNPs: haplotype frequency estimation, analysis of association of haplotypes with the response, including analysis of interactions. AVAILABILITY http://bioinfo.iconcologia.net/SNPstats. Source code for local installation is available under GNU license.

SNPassoc: an R package to perform whole genome association studies

UNLABELLED The popularization of large-scale genotyping projects has led to the widespread adoption of genetic association studies as the tool of choice in the search for single nucleotide polymorphisms (SNPs) underlying susceptibility to complex diseases. Although the analysis of individual SNPs is a relatively trivial task, when the number is large and multiple genetic models need to be explored it becomes necessary a tool to automate the analyses. In order to address this issue, we developed SNPassoc, an R package to carry out most common analyses in whole genome association studies. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). AVAILABILITY Package SNPassoc is available at CRAN from http://cran.r-project.org. SUPPLEMENTARY INFORMATION A tutorial is available on Bioinformatics online and in http://davinci.crg.es/estivill_lab/snpassoc.

Polymorphisms in prostaglandin synthase 2/cyclooxygenase 2 (PTGS2/COX2) and risk of colorectal cancer

Inflammation plays a key role in the development of colorectal cancers. We have investigated the relationship between PTGS2 (COX2) polymorphisms and colorectal cancer risk in a hospital based case–control study. We recruited 292 patients with colorectal cancer and 274 controls from new patients admitted to Bellvitge Hospital, Barcelona, Spain, from 1996 to 1998. Subjects responded to a questionnaire on risk factors. Genotypes of the eight more frequent polymorphisms of PTGS2 were determined. Two polymorphisms are located in the promoter sequence, one in the untranslated region of exon 1, one in exon 3, one in intron 5, two in the untranslated region of exon 10, and one downstream of the last polyadenylation (poly-A) signal. Associations were analysed with logistic regression models assuming a dominant effect for rare variants to increase statistical power. An association was detected between colorectal cancer and a polymorphism in the untranslated region of exon 10 of PTGS2, with an odds ratio (OR) of 2.49, 95% confidence interval (CI) of 1.17–5.32, P=0.01. A nearby polymorphism downstream of the last poly-A signal also showed a nonsignificant increase in risk (OR 2.17, 95% CI 0.99–4.78, P=0.05). Analysis of haplotypes confirmed that individuals with these variants were at increased risk of colorectal cancer (OR compared to the most frequent haplotype: 2.17, 95% CI 0.97–4.84, P=0.06) Interactions between PTGS2 genotype and use of nonsteroidal anti-inflammatory drugs and risk of colorectal cancer were also explored.

Organochlorine Exposure and Colorectal Cancer Risk

Organochlorine compounds have been linked to increased risk of several cancers. Despite reductions in their use and fugitive release, they remain one of the most important groups of persistent pollutants to which humans are exposed, primarily through dietary intake. We designed a case–control study to assess the risk of colorectal cancer with exposure to these chemicals, and their potential interactions with genetic alterations in the tumors. A subsample of cases (n = 132) and hospital controls (n = 76) was selected from a larger case–control study in Barcelona, Catalonia, Spain. We measured concentrations in serum of several organochlorines by gas chromatography. We assessed point mutations in K-ras and p53 genes in tissue samples by polymerase chain reaction/single-strand conformation polymorphism and assessed expression of p53 protein by immunohistochemical methods. An elevated risk of colorectal cancer was associated with higher serum concentrations of mono-ortho polychlorinated biphenyl (PCB) congeners 28 and 118. The odds ratio for these mono-ortho PCBs for middle and higher tertile were, respectively, 1.82 [95% confidence interval (CI), 0.90–3.70] and 2.94 (95% CI, 1.39–6.20). α-Hexachlorocyclohexane, hexachlorobenzene, and p,p′-DDE (4,4′-dichlorodiphenyltrichloroethene) showed nonsignificant increases in risk. Risk associated with mono-ortho PCBs was slightly higher for tumors with mutations in the p53 gene but was not modified by mutations in K-ras. Mono-ortho PCBs were further associated with transversion-type mutations in both genes. These results generate the hypothesis that exposure to mono-ortho PCBs contributes to human colorectal cancer development. The trend and magnitude of the association, as well as the observation of a molecular fingerprint in tumors, raise the possibility that this finding may be causal.

Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.

Germline Mutations in FAN1 Cause Hereditary Colorectal Cancer by Impairing DNA Repair

Identification of genes associated with hereditary cancers facilitates management of patients with family histories of cancer. We performed exome sequencing of DNA from 3 individuals from a family with colorectal cancer who met the Amsterdam criteria for risk of hereditary nonpolyposis colorectal cancer. These individuals had mismatch repair-proficient tumors and each carried nonsense variant in the FANCD2/FANCI-associated nuclease 1 gene (FAN1), which encodes a nuclease involved in DNA inter-strand cross-link repair. We sequenced FAN1 in 176 additional families with histories of colorectal cancer and performed in vitro functional analyses of the mutant forms of FAN1 identified. We detected FAN1 mutations in approximately 3% of families who met the Amsterdam criteria and had mismatch repair-proficient cancers with no previously associated mutations. These findings link colorectal cancer predisposition to the Fanconi anemia DNA repair pathway, supporting the connection between genome integrity and cancer risk.

Polymorphisms within inflammatory genes and colorectal cancer

BackgroundChronic inflammation is a risk factor for colorectal cancer and polymorphisms in the inflammatory genes could modulate the levels of inflammation. We have investigated ten single nucleotide polymorphisms (SNPs) in the following inflammation-related genes: TLR4 (Asp299Gly), CD14 (-260 T>C), MCP1 (-2518 A>G), IL12A (+7506 A>T, +8707 A>G, +9177 T>A, +9508 G>A), NOS2A (+524T>C), TNF (-857C>T), and PTGS1 (V444I) in 377 colorectal (CRC) cancer cases and 326 controls from Barcelona (Spain).ResultsThere was no statistically significant association between the SNPs investigated and colorectal cancer risk.ConclusionThe lack of association may show that the inflammatory genes selected for this study are not involved in the carcinogenic process of colorectum. Alternatively, the negative results may derive from no particular biological effect of the analysed polymorphisms in relation to CRC. Otherwise, the eventual biological effect is so little to go undetected, unless analysing a much larger sample size.

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer

BackgroundA colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient’s gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response.MethodsA set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software).ResultsHere we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue.ConclusionsThe systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients.

Análisis estadístico de polimorfismos genéticos en estudios epidemiológicos

Analysis of genetic polymorphisms allows the genes that confer susceptibility to diseases to be analyzed. This paper presents the nomenclature used in genetic epidemiology literature and a basic strategy for statistical analysis of epidemiological studies that use genetic markers. First, a descriptive analysis of a single nucleotide polymorphism is presented, with assessment of Hardy-Weinberg equilibrium. Next, methods to assess the association with disease are presented. To do this, logistic regression models are used and alternative models of inheritance are explored. Finally, methods for the simultaneous analysis of multiple polymorphisms are presented: haplotype frequency estimation and analysis of disease association.

Variability in prescription drug expenditures explained by adjusted clinical groups (ACG) case-mix: A cross-sectional study of patient electronic records in primary care

BackgroundIn view of rapidly increasing prescription costs, case-mix adjustment should be considered for effective control of costs. We have estimated the variability in pharmacy costs explained by ACG in centers using patient electronic records, profiled centers and physicians and analyzed the correlation between cost and quality of prescription.MethodsWe analyzed 65,630 patient records attending five primary care centers in Spain during 2005. Variables explored were age, gender, registered diagnosed episodes of care during 2005, total cost of prescriptions, physician and center. One ACG was assigned to each patient with ACG case-mix software version 7.1. In a two-part model, logistic regression was used to explain the incurrence of drug expenditure at the first stage and a linear mixed model that considered the multilevel structure of data modeled the cost, conditional upon incurring any expense. Risk and efficiency indexes in pharmacy cost adjusted for ACG were obtained for centers and physicians. Spearman rank correlation between physician expenditure, adjusted for ACG, and a prescription quality index was also obtained. Pediatric and adult data were analyzed separately.ResultsNo prescription was recorded for 13% of adults and 39.6% of children. The proportion of variance of the incurrence of expenditure explained by ACGs was 0.29 in adults and 0.21 in children. For adults with prescriptions, the variance of cost explained by ACGs was 35.4%, by physician-center was 1.8% and age 10.5% (residual 52.3%). For children, ACGs explained 22.4% of cost and physician-center 10.9% (residual 66.7%). Center efficiency index for adults ranged 0.58 to 1.22 and for children 0.32 to 2.36.Spearman correlation between expenditure and prescription quality index was -0.36 in family physicians (p = 0.019, N = 41) and -0.52 in pediatricians (p = 0.08, N = 12).ConclusionIn our setting, ACG is the variable studied that explains more variability in pharmacy cost in adults compared to physician and center. In children there is greater variability among physicians and centers not related to case-mix. In our sites, ACG is useful to profile physicians and centers using electronic records in real practical conditions. Physicians with lower pharmaceutical expenditure have higher scores for a prescription quality index.