Genetic variants in the folate metabolic pathway genes predict cutaneous melanoma-specific survival.

BACKGROUND: Folate metabolism plays an important role in DNA methylation and nucleic acid synthesis and thus may function as a regulatory factor in cancer development. Genome-wide association studies (GWASs) have identified some single-nucleotide polymorphisms (SNPs) associated with cutaneous melanoma-specific survival (CMSS), but no SNPs were found in genes involved in the folate metabolic pathway. OBJECTIVES: To examine associations between SNPs in folate metabolic pathway genes and CMSS. METHODS: We comprehensively evaluated 2645 (422 genotyped and 2223 imputed) common SNPs in folate metabolic pathway genes from a published GWAS of 858 patients from The University of Texas MD Anderson Cancer Center and performed the validation in another GWAS of 409 patients from the Nurses' Health Study and Health Professionals Follow-up Study, in which 95/858 (11·1%) and 48/409 (11·7%) patients died of cutaneous melanoma, respectively. RESULTS: We identified two independent SNPs (MTHFD1 rs1950902 G>A and ALPL rs10917006 C>T) to be associated with CMSS in both datasets, and their meta-analysis yielded an allelic hazards ratio of 1·75 (95% confidence interval 1·32-2·32, P = 9·96 × 10-5 ) and 2·05 (1·39-3·01, P = 2·84 × 10-4 ), respectively. The genotype-phenotype correlation analyses provided additional support for the biological plausibility of these two variants' roles in tumour progression, suggesting that variation in SNP-related mRNA expression levels is likely to be the mechanism underlying the observed associations with CMSS. CONCLUSIONS: Two possibly functional genetic variants, MTHFD1 rs1950902 and ALPL rs10917006, were likely to be independently or jointly associated with CMSS, which may add to personalized treatment in the future, once further validated. What is already known about this topic? Existing data show that survival rates vary among patients with melanoma with similar clinical characteristics; therefore, it is necessary to identify additional complementary biomarkers for melanoma-specific prognosis. A hypothesis-driven approach, by pooling the effects of single-nucleotide polymorphisms (SNPs) in a specific biological pathway as genetic risk scores, may provide a prognostic utility, and genetic variants of genes in folate metabolism have been reported to be associated with cancer risk. What does this study add? Two genetic variants in the folate metabolic pathway genes, MTHFD1 rs1950902 and ALPL rs10917006, are significantly associated with cutaneous melanoma-specific survival (CMSS). What is the translational message? The identification of genetic variants will make a risk-prediction model possible for CMSS. The SNPs in the folate metabolic pathway genes, once validated in larger studies, may be useful in the personalized management and treatment of patients with cutaneous melanoma.

Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence.

Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency=44-77%) was associated with increased risk of nicotine dependence at P=3.7 × 10-8 (odds ratio (OR)=1.06 and 95% confidence interval (CI)=1.04-1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N=48,931) using heavy vs never smoking as a proxy phenotype (P=3.6 × 10-4, OR=1.05, and 95% CI=1.02-1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N=60,586, meta-analysis P=0.0095, OR=1.05, and 95% CI=1.01-1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N=166, P=2.3 × 10-26) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N=103, P=3.0 × 10-6) and the independent Brain eQTL Almanac (N=134, P=0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.

Genome-wide meta-analysis reveals common splice site acceptor variant in CHRNA4 associated with nicotine dependence.

We conducted a 1000 Genomes-imputed genome-wide association study (GWAS) meta-analysis for nicotine dependence, defined by the Fagerström Test for Nicotine Dependence in 17 074 ever smokers from five European-ancestry samples. We followed up novel variants in 7469 ever smokers from five independent European-ancestry samples. We identified genome-wide significant association in the alpha-4 nicotinic receptor subunit (CHRNA4) gene on chromosome 20q13: lowest P=8.0 × 10(-9) across all the samples for rs2273500-C (frequency=0.15; odds ratio=1.12 and 95% confidence interval=1.08-1.17 for severe vs mild dependence). rs2273500-C, a splice site acceptor variant resulting in an alternate CHRNA4 transcript predicted to be targeted for nonsense-mediated decay, was associated with decreased CHRNA4 expression in physiologically normal human brains (lowest P=7.3 × 10(-4)). Importantly, rs2273500-C was associated with increased lung cancer risk (N=28 998, odds ratio=1.06 and 95% confidence interval=1.00-1.12), likely through its effect on smoking, as rs2273500-C was no longer associated with lung cancer after adjustment for smoking. Using criteria for smoking behavior that encompass more than the single 'cigarettes per day' item, we identified a common CHRNA4 variant with important regulatory properties that contributes to nicotine dependence and smoking-related consequences.

Genome-wide association study identifies HLA 8.1 ancestral haplotype alleles as major genetic risk factors for myositis phenotypes.

Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis, 473 juvenile dermatomyositis, 532 polymyositis and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl-tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (P<5×10(-8)) in GWAS were identified in the major histocompatibility complex (MHC) region for all myositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1 comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations.

Changes in screening behaviors and attitudes toward screening from pre-test genetic counseling to post-disclosure in Lynch syndrome families.

The purpose of this study was to examine colonoscopy adherence and attitudes toward colorectal cancer (CRC) screening in individuals who underwent Lynch syndrome genetic counseling and testing. We evaluated changes in colonoscopy adherence and CRC screening attitudes in 78 cancer-unaffected relatives of Lynch syndrome mutation carriers before pre-test genetic counseling (baseline) and at 6 and 12 months post-disclosure of test results (52 mutation negative and 26 mutation positive). While both groups were similar at baseline, at 12 months post-disclosure, a greater number of mutation-positive individuals had had a colonoscopy compared with mutation-negative individuals. From baseline to 12 months post-disclosure, the mutation-positive group demonstrated an increase in mean scores on measures of colonoscopy commitment, self-efficacy, and perceived benefits of CRC screening, and a decrease in mean scores for perceived barriers to CRC screening. Mean scores on colonoscopy commitment decreased from baseline to 6 months in the mutation-negative group. To conclude, adherence to risk-appropriate guidelines for CRC surveillance improved after genetic counseling and testing for Lynch syndrome. Mutation-positive individuals reported increasingly positive attitudes toward CRC screening after receiving genetic test results, potentially reinforcing longer term colonoscopy adherence.

Pathway-based analysis of primary biliary cirrhosis genome-wide association studies.

Genome-wide association studies (GWAS) have successfully identified several loci associated with primary biliary cirrhosis (PBC) risk. Pathway analysis complements conventional GWAS analysis. We applied the recently developed linear combination test for pathways to datasets drawn from independent PBC GWAS in Italian and Canadian subjects. Of the Kyoto Encyclopedia of Genes and Genomes and BioCarta pathways tested, 25 pathways in the Italian dataset (449 cases, 940 controls) and 26 pathways in the Canadian dataset (530 cases, 398 controls) were associated with PBC susceptibility (P<0.05). After correcting for multiple comparisons, only the eight most significant pathways in the Italian dataset had FDR <0.25 with tumor necrosis factor/stress-related signaling emerging as the top pathway (P=7.38 × 10⁻4, FDR=0.18). Two pathways, phosphatidylinositol signaling and hedgehog signaling, were replicated in both datasets (P<0.05), and subjected to two additional complementary pathway tests. Both pathway signals remained significant in the Italian dataset on modified gene set enrichment analysis (P<0.05). In both GWAS, variants nominally associated with PBC were significantly overrepresented in the phosphatidylinositol pathway (Fisher exact P<0.05). These results point to established and novel pathway-level associations with inherited predisposition to PBC that, on further independent replication and functional validation, may provide fresh insights into PBC etiology.

Classical HLA-DRB1 and DPB1 alleles account for HLA associations with primary biliary cirrhosis.

Susceptibility to primary biliary cirrhosis (PBC) is strongly associated with human leukocyte antigen (HLA)-region polymorphisms. To determine if associations can be explained by classical HLA determinants, we studied Italian, 676 cases and 1440 controls, genotyped with dense single-nucleotide polymorphisms (SNPs) for which classical HLA alleles and amino acids were imputed. Although previous genome-wide association studies and our results show stronger SNP associations near DQB1, we demonstrate that the HLA signals can be attributed to classical DRB1 and DPB1 genes. Strong support for the predominant role of DRB1 is provided by our conditional analyses. We also demonstrate an independent association of DPB1. Specific HLA-DRB1 genes (*08, *11 and *14) account for most of the DRB1 association signal. Consistent with previous studies, DRB1*08 (P=1.59 × 10(-11)) was the strongest predisposing allele, whereas DRB1*11 (P=1.42 × 10(-10)) was protective. Additionally, DRB1*14 and the DPB1 association (DPB1*03:01; P=9.18 × 10(-7)) were predisposing risk alleles. No signal was observed in the HLA class 1 or class 3 regions. These findings better define the association of PBC with HLA and specifically support the role of classical HLA-DRB1 and DPB1 genes and alleles in susceptibility to PBC.

Association of primary biliary cirrhosis with variants in the CLEC16A, SOCS1, SPIB and SIAE immunomodulatory genes.

We fine mapped two primary biliary cirrhosis (PBC) risk loci, CLEC16A (C-type lectin domain family 16 member A)-suppressor of cytokine signaling 1 (SOCS1) and Spi-B protein (SPIB) and sequenced a locus, sialic acid acetylesterase (SIAE), proposed to harbor autoimmunity-associated mutations. In all, 1450 PBC cases and 2957 healthy controls were genotyped for 84 single-nucleotide polymorphisms (SNPs) across the CLEC16A-SOCS1 and SPIB loci. All 10 exons of the SIAE gene were resequenced in 381 cases and point substitutions of unknown significance assayed for activity and secretion. Fine mapping identified 26 SNPs across the CLEC16A-SOCS1 and 11 SNPs across the SPIB locus with significant association to PBC, the strongest signals at the CLEC16A-SOCS1 locus emanating from a SOCS1 intergenic SNP (rs243325; P=9.91 × 10(-9)) and at the SPIB locus from a SPIB intronic SNP (rs34944112; P=3.65 × 10(-9)). Among the associated SNPs at the CLEC16A-SOCS1 locus, two within the CLEC16A gene as well as one SOCS1 SNP (rs243325) remained significant after conditional logistic regression and contributed independently to risk. Sequencing of the SIAE gene and functional assays of newly identified variants revealed six patients with functional non-synonymous SIAE mutations (Fisher's P=9 × 10(-4) vs controls) We demonstrate independent effects on risk of PBC for CLEC16A, SOCS1 and SPIB variants, while identifying functionally defective SIAE variants as potential factors in risk for PBC.

Entropy-based information gain approaches to detect and to characterize gene-gene and gene-environment interactions/correlations of complex diseases.

For complex diseases, the relationship between genotypes, environment factors, and phenotype is usually complex and nonlinear. Our understanding of the genetic architecture of diseases has considerably increased over the last years. However, both conceptually and methodologically, detecting gene-gene and gene-environment interactions remains a challenge, despite the existence of a number of efficient methods. One method that offers great promises but has not yet been widely applied to genomic data is the entropy-based approach of information theory. In this article, we first develop entropy-based test statistics to identify two-way and higher order gene-gene and gene-environment interactions. We then apply these methods to a bladder cancer data set and thereby test their power and identify strengths and weaknesses. For two-way interactions, we propose an information gain (IG) approach based on mutual information. For three-ways and higher order interactions, an interaction IG approach is used. In both cases, we develop one-dimensional test statistics to analyze sparse data. Compared to the naive chi-square test, the test statistics we develop have similar or higher power and is robust. Applying it to the bladder cancer data set allowed to investigate the complex interactions between DNA repair gene single nucleotide polymorphisms, smoking status, and bladder cancer susceptibility. Although not yet widely applied, entropy-based approaches appear as a useful tool for detecting gene-gene and gene-environment interactions. The test statistics we develop add to a growing body methodologies that will gradually shed light on the complex architecture of common diseases.

Evolutionary evidence of the effect of rare variants on disease etiology.

The common disease/common variant hypothesis has been popular for describing the genetic architecture of common human diseases for several years. According to the originally stated hypothesis, one or a few common genetic variants with a large effect size control the risk of common diseases. A growing body of evidence, however, suggests that rare single-nucleotide polymorphisms (SNPs), i.e. those with a minor allele frequency of less than 5%, are also an important component of the genetic architecture of common human diseases. In this study, we analyzed the relevance of rare SNPs to the risk of common diseases from an evolutionary perspective and found that rare SNPs are more likely than common SNPs to be functional and tend to have a stronger effect size than do common SNPs. This observation, and the fact that most of the SNPs in the human genome are rare, suggests that rare SNPs are a crucial element of the genetic architecture of common human diseases. We propose that the next generation of genomic studies should focus on analyzing rare SNPs. Further, targeting patients with a family history of the disease, an extreme phenotype, or early disease onset may facilitate the detection of risk-associated rare SNPs.

Detecting haplotype effects in genomewide association studies.

The analysis of genomewide association studies requires methods that are both computationally feasible and statistically powerful. Given the large-scale collection of single nucleotide polymorphisms (SNPs), it is desirable to explore the information contained in their interrelationships. In particular, utilizing haplotypes rather than individual SNPs and accounting for correlations of polymorphisms in adjustment for multiple testing can lead to increased power. We present a statistically powerful and numerically efficient method based on sliding windows of adjacent SNPs to detect haplotype-disease association in genomewide studies. This method consists of an efficient algorithm to calculate a proper likelihood-ratio statistic for any given window of SNPs, along with an accurate and efficient Monte Carlo procedure to adjust for multiple testing. Simulation studies using the HapMap data showed that the proposed method performs well in realistic situations. We applied the new method to a case-control study on rheumatoid arthritis and identified several loci worthy of further investigations.

High-density SNP analysis of 642 Caucasian families with rheumatoid arthritis identifies two new linkage regions on 11p12 and 2q33.

We have completed a genome wide linkage scan using >5700 informative single-nucleotide polymorphism (SNP) markers (Illumina IV SNP linkage panel) in 642 Caucasian families containing affected sibling pairs with rheumatoid arthritis (RA), ascertained by the North American Rheumatoid Arthritis Consortium. The results show striking new evidence of linkage at chromosomes 2q33 and 11p12 with logarithm of odds (LOD) scores of 3.52 and 3.09, respectively. In addition to a strong and broad linkage interval surrounding the major histocompatibility complex (LOD>16), regions with LOD>2.5 were observed on chromosomes 5 and 10. Additional linkage evidence (LOD scores between 1.46 and 2.35) was also observed on chromosomes 4, 7, 12, 16 and 18. This new evidence for multiple regions of genetic linkage is partly explained by the significantly increased information content of the Illumina IV SNP linkage panel (75.6%) compared with a standard microsatellite linkage panel utilized previously (mean 52.6%). Stratified analyses according to whether or not the sibling pair members showed elevated anticyclic citrullinated peptide titers indicates significant variation in evidence for linkage among strata on chromosomes 4, 5, 6 and 7. Overall, these new linkage data should reinvigorate efforts to utilize positional information to identify susceptibility genes for RA.

A major lung cancer susceptibility locus maps to chromosome 6q23-25.

Lung cancer is a major cause of death in the United States and other countries. The risk of lung cancer is greatly increased by cigarette smoking and by certain occupational exposures, but familial factors also clearly play a major role. To identify susceptibility genes for familial lung cancer, we conducted a genomewide linkage analysis of 52 extended pedigrees ascertained through probands with lung cancer who had several first-degree relatives with the same disease. Multipoint linkage analysis, under a simple autosomal dominant model, of all 52 families with three or more individuals affected by lung, throat, or laryngeal cancer, yielded a maximum heterogeneity LOD score (HLOD) of 2.79 at 155 cM on chromosome 6q (marker D6S2436). A subset of 38 pedigrees with four or more affected individuals yielded a multipoint HLOD of 3.47 at 155 cM. Analysis of a further subset of 23 multigenerational pedigrees with five or more affected individuals yielded a multipoint HLOD score of 4.26 at the same position. The 14 families with only three affected relatives yielded negative LOD scores in this region. A predivided samples test for heterogeneity comparing the LOD scores from the 23 multigenerational families with those from the remaining families was significant (P=.007). The 1-HLOD multipoint support interval from the multigenerational families extends from C6S1848 at 146 cM to 164 cM near D6S1035, overlapping a genomic region that is deleted in sporadic lung cancers as well as numerous other cancer types. Parametric linkage and variance-components analysis that incorporated effects of age and personal smoking also supported linkage in this region, but with somewhat diminished support. These results localize a major susceptibility locus influencing lung cancer risk to 6q23-25.

Genotype-phenotype correlations in Peutz-Jeghers syndrome.

BACKGROUND AND AIMS: Peutz-Jeghers syndrome (PJS) is a dominantly inherited disorder often caused by mutations in STK11. Time to onset of symptoms was characterised for a large collection of individuals with PJS who had been tested for STK11 mutations and genotype-phenotype correlations were evaluated. METHODS: We characterised mutations in 42 independent probands and also used a historical cohort design to study 51 individuals with Peutz-Jeghers syndrome who had completed self-administered questionnaires. RESULTS: Mutations were detected in 22/32 (69%) probands with PJS and 0/10 probands referred to rule out PJS. Real-time PCR analysis to quantitate DNA failed to detect any large deletions in PJS participants without STK11 mutations. The median time to onset for gastrointestinal symptoms or polypectomy was 13 years of age but showed a wide variability. Gastric polyps were frequent in PJS participants, with a median age at onset of 16 years. Individuals with missense mutations had a significantly later time to onset of first polypectomy (p = 0.04) and of other symptoms compared with those participants either with truncating mutations or no detectable mutation. CONCLUSION: STK11 mutation analysis should be restricted to individuals who meet PJS criteria or their close relatives. Direct sequencing of STK11 yields a high rate of point mutations in individuals who meet phenotypic PJS criteria. Individuals with missense mutations of STK11 typically had a later time to onset for PJS symptoms. The common occurrence of gastric polyps may facilitate chemopreventive studies for this disorder.

Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci.

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests using the non-transformed, skewed phenotypes, from 7.5 to 20.1% after Winsorizing and from 12.6 to 33.2% after Box-Cox transformation. Likewise, power (adjusted for empirical type 1 error) using leptokurtic phenotypes at the 0.01 alpha level ranged from 4.4 to 12.5% across all tests with no transformation, from 7 to 19.2% after Winsorizing and from 4.5 to 13.8% after Box-Cox transformation. Thus the Box-Cox transformation apparently provided the best type 1 error control and maximal power among the procedures we considered for analyzing a non-normal, skewed distribution (chi2) while Winzorizing worked best for the non-normal, kurtic distribution (Laplace). We repeated the same simulations using a larger sample size (200 sib pairs) and found similar results.

Power of a simplified multivariate test for genetic linkage.

In this paper we compare the power of the multivariate Haseman-Elston (MHE) test proposed earlier by Amos et al. (1990) and a computationally rapid new version of the multivariate Haseman-Elston test (NMHE) (Elston et al. 2000). We show that the power of NMHE was, for different simulation setups, identical or higher than that of MHE. In the bivariate case, the power of the NMHE method was somewhat less than that of the computationally intensive maximum likelihood variance components method (Amos et al. 2001). We present comparisons of the empirical distributions of the NMHE test to its limiting distributions for a range of numbers of traits. The distribution of the NMHE test appeared to conform satisfactorily to its limiting asymptotic distribution in large samples. Otherwise, empirical critical values for NMHE are somewhat higher than predicted, i.e. the test proposed by Elston et al. (2000) is non-conservative. The use of empirical critical values is therefore recommended for limited sample sizes (less than several hundred families). We also present the results of a linkage analysis performed by the NMHE method on a set of 4 body size-related traits. The method identified meaningful combinations of traits that showed significant linkage on chromosome 2 and suggestive linkage to regions on chromosomes 16 and 17.

Contrasting molecular pathology of colorectal carcinoma in Egyptian and Western patients.

Colorectal carcinoma is uncommon in Egypt, but a high proportion of cases occurs before age 40 years and in the rectum. We compared the molecular pathology of 59 representative Egyptian patients aged 10-72 to Western patients with sporadic, young-onset, or hereditary non-polyposis colorectal cancer syndrome (HNPCC)-associated carcinoma and found significant differences. Most Egyptian cancers were rectal (51%) and poorly differentiated (58%). High levels of microsatellite instability (MSI-H) were frequent (37%) and attributable in some cases (36%) to methylation of the promoter of the hMLH1 mismatch repair gene, but no MSI-H cancer had loss of hMSH2 mismatch repair gene product of the type seen with germline hMSH2 mutation in HNPCC. K-ras mutation was uncommon (11%). In subset analyses, high frequencies of MSI-H in rectal carcinomas (36%) and p53 gene product overexpression in MSI-H cancers (50%) were found. MSI-H and K-ras mutation in Egyptians under age 40 were unusual (17% and 0%, respectively), and schistosomiasis was associated with MSI and K-ras mutation. Cluster analysis identified 2 groups: predominantly young men with poorly differentiated mucinous and signet-ring cell colorectal carcinoma lacking K-ras mutation; older patients who had well- or moderately differentiated adenocarcinoma often with MSI-H, K-ras mutation and schistosomiasis. Our findings show that the molecular pathology of colorectal cancer in older as well as younger Egyptians has unique differences from Western patients, and schistosomiasis influences the molecular pathogenesis of some tumours.