Genome scans and microarrays: converging on genes for schizophrenia?

Systematic genome-wide scans to date have shown that genes of major effect are not common causes of schizophrenia, but independent linkage studies looking for schizophrenia susceptibility genes are converging on a number of key chromosomal locations. Microarray expression analysis may identify new candidate genes and pathways, and a number of intriguing preliminary findings have already been reported.     

Analyzing the pathways enriched in genes associated with nicotine dependence in the context of human protein–protein interaction network

Nicotine dependence is the primary addictive stage of cigarette smoking. Although a lot of studies have been performed to explore the molecular mechanism underlying nicotine dependence, our understanding on this disorder is still far from complete. Over the past decades, an increasing number of candidate genes involved in nicotine dependence have been identified by different technical approaches, including the genetic association analysis. In this study, we performed a comprehensive collection of candidate genes reported to be genetically associated with nicotine dependence. Then, the biochemical pathways enriched in these genes were identified by considering the gene’s propensity to be related to nicotine dependence. One of the most widely used pathway enrichment analysis approach, over-representation analysis, ignores the function non-equivalence of genes in candidate gene set and may have low discriminative power in identifying some dysfunctional pathways. To overcome such drawbacks, we constructed a comprehensive human protein–protein interaction network, and then assigned a function weighting score to each candidate gene based on their network topological features. Evaluation indicated the function weighting score scheme was consistent with available evidence. Finally, the function weighting scores of the candidate genes were incorporated into pathway analysis to identify the dysfunctional pathways involved in nicotine dependence, and the interactions between pathways was detected by pathway crosstalk analysis. Compared to conventional over-representation-based pathway analysis tool, the modified method exhibited improved discriminative power and detected some novel pathways potentially underlying nicotine dependence. In summary, we conducted a comprehensive collection of genes associated with nicotine dependence and then detected the biochemical pathways enriched in these genes using a modified pathway enrichment analysis approach with function weighting score of candidate genes integrated. Our results may provide insight into the molecular mechanism underlying nicotine dependence.     

Schizophrenia Gene Networks and Pathways and Their Applications for Novel Candidate Gene Selection

Background

Schizophrenia (SZ) is a heritable, complex mental disorder. We have seen limited success in finding causal genes for schizophrenia from numerous conventional studies. Protein interaction network and pathway-based analysis may provide us an alternative and effective approach to investigating the molecular mechanisms of schizophrenia.

Methodology/Principal Findings

We selected a list of schizophrenia candidate genes (SZGenes) using a multi-dimensional evidence-based approach. The global network properties of proteins encoded by these SZGenes were explored in the context of the human protein interactome while local network properties were investigated by comparing SZ-specific and cancer-specific networks that were extracted from the human interactome. Relative to cancer genes, we observed that SZGenes tend to have an intermediate degree and an intermediate efficiency on a perturbation spreading throughout the human interactome. This suggested that schizophrenia might have different pathological mechanisms from cancer even though both are complex diseases. We conducted pathway analysis using Ingenuity System and constructed the first schizophrenia molecular network (SMN) based on protein interaction networks, pathways and literature survey. We identified 24 pathways overrepresented in SZGenes and examined their interactions and crosstalk. We observed that these pathways were related to neurodevelopment, immune system, and retinoic X receptor (RXR). Our examination of SMN revealed that schizophrenia is a dynamic process caused by dysregulation of the multiple pathways. Finally, we applied the network/pathway approach to identify novel candidate genes, some of which could be verified by experiments.

Conclusions/Significance

This study provides the first comprehensive review of the network and pathway characteristics of schizophrenia candidate genes. Our preliminary results suggest that this systems biology approach might prove promising for selection of candidate genes for complex diseases. Our findings have important implications for the molecular mechanisms for schizophrenia and, potentially, other psychiatric disorders.     

Gene Network Analysis of Candidate Loci for Human Anorectal Malformations

Anorectal malformations (ARMs) are birth defects that require surgery and carry significant chronic morbidity. Our earlier genome-wide copy number variation (CNV) study had provided a wealth of candidate loci. To find out whether these candidate loci are related to important developmental pathways, we have performed an extensive literature search coupled with the currently available bioinformatics tools. This has allowed us to assign both genic and non-genic CNVs to interrelated pathways known to govern the development of the anorectal region. We have linked 11 candidate genes to the WNT signalling pathway and 17 genes to the cytoskeletal network. Interestingly, candidate genes with similar functions are disrupted by the same type of CNV. The gene network we discovered provides evidence that rare mutations in different interrelated genes may lead to similar phenotypes, accounting for genetic heterogeneity in ARMs. Classification of patients according to the affected pathway and lesion type should eventually improve the diagnosis and the identification of common genes/molecules as therapeutic targets.     

Pathway analysis of a genome-wide association study in schizophrenia

Objective

The aim of this study was to identify the candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms that contribute to schizophrenia susceptibility and to generate a SNP to gene to pathway hypothesis using an analytical pathway-based approach.

Methods

We used schizophrenia GWAS data of the genotypes of 660,259 SNPs in 1378 controls and 1351 cases of European descent after quality control filtering. ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the schizophrenia GWAS dataset. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate SNPs using improved-gene set enrichment analysis.

Results

ICSNPathway analysis identified fifteen candidate SNPs, ten candidate pathways, and nine hypothetical biological mechanisms. The most strongly associated potential pathways were as follows. First, rs1644731 and rs1644730 to RDH8 to estrogen biosynthetic process (p < 0.001, FDR < 0.001). The genes involved in this pathway are RDH8 and HSD3B1 (p < 0.05). All-trans-retinol dehydrogenase (RDH8) is a visual cycle enzyme that reduces all-trans-retinal to all-trans-retinol in the presence of NADPH. The chemical reactions and pathways involved result in the formation of estrogens, which are C18 steroid hormones that can stimulate the development of female sexual characteristics. Second, rs1146031 to ACVR1 to mesoderm formation and activin binding (p < 0.001, FDR = 0.032, 0.034). Two of 15 candidate genes are known genes associated with schizophrenia: KCNQ2 and APOL2. One of the 10 candidate pathways, estrogen biosynthetic process, is known to be associated with schizophrenia (p < 0.001, FDR < 0.001). However, 13 of candidate genes (RDH8, ACVR1, PSMD9, KCNAB1, SLC17A3, ARCN1, COG7, STAB2, LRPAP1, STAB1, CXCL16, COL4A4, EXOSC3) and 9 of candidate pathways were novel.

Conclusion

By applying ICSNPathway analysis to schizophrenia GWAS data, we identified candidate SNPs, genes like KCNQ2 and APOL2 and pathways involving the estrogen biosynthetic process may contribute to schizophrenia susceptibility. Further analyses are needed to validate the results of this analysis.     

Association analysis of 94 candidate genes and schizophrenia-related endophenotypes

While it is clear that schizophrenia is highly heritable, the genetic basis of this heritability is complex. Human genetic, brain imaging, and model organism studies have met with only modest gains. A complementary research tactic is to evaluate the genetic substrates of quantitative endophenotypes with demonstrated deficits in schizophrenia patients. We used an Illumina custom 1,536-SNP array to interrogate 94 functionally relevant candidate genes for schizophrenia and evaluate association with both the qualitative diagnosis of schizophrenia and quantitative endophenotypes for schizophrenia. Subjects included 219 schizophrenia patients and normal comparison subjects of European ancestry and 76 schizophrenia patients and normal comparison subjects of African ancestry, all ascertained by the UCSD Schizophrenia Research Program. Six neurophysiological and neurocognitive endophenotype test paradigms were assessed: prepulse inhibition (PPI), P50 suppression, the antisaccade oculomotor task, the Letter-Number Span Test, the California Verbal Learning Test-II, and the Wisconsin Card Sorting Test-64 Card Version. These endophenotype test paradigms yielded six primary endophenotypes with prior evidence of heritability and demonstrated schizophrenia-related impairments, as well as eight secondary measures investigated as candidate endophenotypes. Schizophrenia patients showed significant deficits on ten of the endophenotypic measures, replicating prior studies and facilitating genetic analyses of these phenotypes. A total of 38 genes were found to be associated with at least one endophenotypic measure or schizophrenia with an empirical p-value<0.01. Many of these genes have been shown to interact on a molecular level, and eleven genes displayed evidence for pleiotropy, revealing associations with three or more endophenotypic measures. Among these genes were ERBB4 and NRG1, providing further support for a role of these genes in schizophrenia susceptibility. The observation of extensive pleiotropy for some genes and singular associations for others in our data may suggest both converging and independent genetic (and neural) pathways mediating schizophrenia risk and pathogenesis.     

利用果蝇模型研究人类心脏早期发育的分子机理(英文)

近年来 ,果蝇心脏特化的遗传机制已初步研究清楚 ,但控制人类心脏早期发育的基因尚待鉴定。因为调控果蝇和脊椎动物早期心脏细胞命运定型的途径具有保守性 ,果蝇是一种探讨人类心脏早期发育的分子机理的理想动物模式。为此目的 ,我们采用P转座子和EMS诱变技术建立了约 3 0 0 0个隐性致死基因平衡系。通过心脏前体细胞特异性抗体免疫组化筛选 ,我们检出 2 0 0余个表现心脏突变表型的平衡致死系。我们进一步利用RNAi技术对一些基因的功能进行了初步的研究 ,证明这些基因表现RNAi的突变表型 ,该类突变表型与基因突变时表现的表型相似 ,即心管呈缺陷型或无心脏前体细胞形成。利用果蝇和人类基因组计划获得的成果 ,我们从果蝇心脏侯选基因中初步克隆和鉴定了 5 0个人类同源基因 ,其中 2 0个是新基因。Northen印迹分析表明 ,一部分人类基因在心脏组织中有表达 ,从而为研究这些基因在人类心脏早期发育中的作用提供了信息。目前 ,我们正在建立转基因果蝇 ,以此为模型研究这些基因是否对心肌细胞发生或心肌功能起调控作用。产生心肌细胞突变类型的基因如果类似于人类心脏病综合症 ,则可以作为人类心脏疾病侯选基因作进一步的分析。     

Schizophrenia: genes at last?

Genetic epidemiological studies suggest that individual variation in susceptibility to schizophrenia is largely genetic, reflecting alleles of moderate to small effect in multiple genes. Molecular genetic studies have identified several potential regions of linkage and two associated chromosomal abnormalities, and evidence is accumulating in favour of several positional candidate genes. Currently, the positional candidate genes for which we consider the evidence to be strong are those encoding dysbindin (DTNBP1) and neuregulin 1 (NRG1). For other genes, disrupted in schizophrenia 1 (DISC1), D-amino-acid oxidase (DAO), D-amino-acid oxidase activator (DAOA, formerly known as G72) and regulator of G-protein signalling 4 (RGS4), the data are promising but not yet compelling. The identification of these, and other susceptibility genes, will open up new avenues for research aimed at understanding the pathogenesis of schizophrenia, and will catalyse a re-appraisal of the classification of psychiatric disorders.     

Reduce, reuse, and recycle: developmental evolution of trait diversification

A major focus of evolutionary developmental (evo-devo) studies is to determine the genetic basis of variation in organismal form and function, both of which are fundamental to biological diversification. Pioneering work on metazoan and flowering plant systems has revealed conserved sets of genes that underlie the bauplan of organisms derived from a common ancestor. However, the extent to which variation in the developmental genetic toolkit mirrors variation at the phenotypic level is an active area of research. Here we explore evidence from the angiosperm evo-devo literature supporting the frugal use of genes and genetic pathways in the evolution of developmental patterning. In particular, these examples highlight the importance of genetic pleiotropy in different developmental modules, thus reducing the number of genes required in growth and development, and the reuse of particular genes in the parallel evolution of ecologically important traits.     

Bipolar I disorder and schizophrenia: a 440-single-nucleotide polymorphism screen of 64 candidate genes among Ashkenazi Jewish case-parent trios

Bipolar, schizophrenia, and schizoaffective disorders are common, highly heritable psychiatric disorders, for which familial coaggregation, as well as epidemiological and genetic evidence, suggests overlapping etiologies. No definitive susceptibility genes have yet been identified for any of these disorders. Genetic heterogeneity, combined with phenotypic imprecision and poor marker coverage, has contributed to the difficulty in defining risk variants. We focused on families of Ashkenazi Jewish descent, to reduce genetic heterogeneity, and, as a precursor to genomewide association studies, we undertook a single-nucleotide polymorphism (SNP) genotyping screen of 64 candidate genes (440 SNPs) chosen on the basis of previous linkage or of association and/or biological relevance. We genotyped an average of 6.9 SNPs per gene, with an average density of 1 SNP per 11.9 kb in 323 bipolar I disorder and 274 schizophrenia or schizoaffective Ashkenazi case-parent trios. Using single-SNP and haplotype-based transmission/disequilibrium tests, we ranked genes on the basis of strength of association (P<.01). Six genes (DAO, GRM3, GRM4, GRIN2B, IL2RB, and TUBA8) met this criterion for bipolar I disorder; only DAO has been previously associated with bipolar disorder. Six genes (RGS4, SCA1, GRM4, DPYSL2, NOS1, and GRID1) met this criterion for schizophrenia or schizoaffective disorder; five replicate previous associations, and one, GRID1, shows a novel association with schizophrenia. In addition, six genes (DPYSL2, DTNBP1, G30/G72, GRID1, GRM4, and NOS1) showed overlapping suggestive evidence of association in both disorders. These results may help to prioritize candidate genes for future study from among the many suspected/proposed for schizophrenia and bipolar disorders. They provide further support for shared genetic susceptibility between these two disorders that involve glutamate-signaling pathways.     

Genes encoding longevity: from model organisms to humans

Ample evidence from model organisms has indicated that subtle variation in genes can dramatically influence lifespan. The key genes and molecular pathways that have been identified so far encode for metabolism, maintenance and repair mechanisms that minimize age-related accumulation of permanent damage. Here, we describe the evolutionary conserved genes that are involved in lifespan regulation of model organisms and humans, and explore the reasons of discrepancies that exist between the results found in the various species. In general, the accumulated data have revealed that when moving up the evolutionary ladder, together with an increase of genome complexity, the impact of candidate genes on lifespan becomes smaller. The presence of genetic networks makes it more likely to expect impact of variation in several interacting genes to affect lifespan in humans. Extrapolation of findings from experimental models to humans is further complicated as phenotypes are critically dependent on the setting in which genes are expressed, while laboratory conditions and modern environments are markedly dissimilar. Finally, currently used methodologies may have only little power and validity to reveal genetic variation in the population. In conclusion, although the study of model organisms has revealed potential candidate genetic mechanisms determining aging and lifespan, to what extent they explain variation in human populations is still uncertain.     

The relationship between membrane pathology and language disorder in schizophrenia

Receptive language disorder in schizophrenia has been hypothesized to involve a fundamental deficit in the temporal (time-based) dynamics of brain function that includes disruptions to patterns of activation and synchronization. In this paper, candidate mechanisms and pathways that could account for this basic deficit are discussed. Parallels are identified between the patterns of language dysfunction observed for schizophrenia and dyslexia, two separate clinical disorders that may share a common abnormality in cell membrane phospholipids. A heuristic is proposed which details a trajectory involving an interaction of brain fatty acids and second-messenger function that modulates synaptic efficacy, and, in turn, influences language processing in schizophrenia patients. It is additionally hypothesized that a primary deficit of functional excitation originating in the cerebellum, in combination with a compensatory decrease of functional inhibition in the prefrontal cortex, influences receptive language dysfunction in schizophrenia.     

Sequencing of DISC1 pathway genes reveals increased burden of rare missense variants in schizophrenia patients from a northern Swedish population

In recent years, DISC1 has emerged as one of the most credible and best supported candidate genes for schizophrenia and related neuropsychiatric disorders. Furthermore, increasing evidence--both genetic and functional--indicates that many of its protein interaction partners are also involved in the development of these diseases. In this study, we applied a pooled sample 454 sequencing strategy, to explore the contribution of genetic variation in DISC1 and 10 of its interaction partners (ATF5, Grb2, FEZ1, LIS-1, PDE4B, NDE1, NDEL1, TRAF3IP1, YWHAE, and ZNF365) to schizophrenia susceptibility in an isolated northern Swedish population. Mutation burden analysis of the identified variants in a population of 486 SZ patients and 514 control individuals, revealed that non-synonymous rare variants with a MAF<0.01 were significantly more present in patients compared to controls (8.64% versus 4.7%, P?=?0.018), providing further evidence for the involvement of DISC1 and some of its interaction partners in psychiatric disorders. This increased burden of rare missense variants was even more striking in a subgroup of early onset patients (12.9% versus 4.7%, P?=?0.0004), highlighting the importance of studying subgroups of patients and identifying endophenotypes. Upon investigation of the potential functional effects associated with the identified missense variants, we found that ～90% of these variants reside in intrinsically disordered protein regions. The observed increase in mutation burden in patients provides further support for the role of the DISC1 pathway in schizophrenia. Furthermore, this study presents the first evidence supporting the involvement of mutations within intrinsically disordered protein regions in the pathogenesis of psychiatric disorders. As many important biological functions depend directly on the disordered state, alteration of this disorder in key pathways may represent an intriguing new disease mechanism for schizophrenia and related neuropsychiatric diseases. Further research into this unexplored domain will be required to elucidate the role of the identified variants in schizophrenia etiology.     

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait''s genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function.     

Genetics of amyotrophic lateral sclerosis: an update

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder involving both upper motor neurons (UMN) and lower motor neurons (LMN). Enormous research has been done in the past few decades in unveiling the genetics of ALS, successfully identifying at least fifteen candidate genes associated with familial and sporadic ALS. Numerous studies attempting to define the pathogenesis of ALS have identified several plausible determinants and molecular pathways leading to motor neuron degeneration, which include oxidative stress, glutamate excitotoxicity, apoptosis, abnormal neurofilament function, protein misfolding and subsequent aggregation, impairment of RNA processing, defects in axonal transport, changes in endosomal trafficking, increased inflammation, and mitochondrial dysfunction. This review is to update the recent discoveries in genetics of ALS, which may provide insight information to help us better understanding of the disease neuropathogenesis.     

Building protein interaction maps for Down's syndrome.

Now that the complete sequences for human chromosome 21 and the orthologous mouse genomic regions are known, reasonably complete, conserved, protein-coding gene catalogues are also available. The central issue now facing Down's syndrome researchers is the correlation of increased expression of specific, normal, chromosome 21 genes with the development of specific deficits in learning and memory. Because of the number of candidate genes involved, the number of alternative splice variants of individual genes and the number of pathways in which these genes function, a pathway analysis approach will be critical to success. Here, three examples, both gene specific and pathway related, that would benefit from pathway analysis are discussed: (1) the potential roles of eight chromosome 21 proteins in RNA processing pathways; (2) the chromosome 21 protein intersectin 1 and its domain composition, alternative splicing, protein interactions and functions; and (3) the interactions of ten chromosome 21 proteins with components of the mitogen-activated protein kinase and the calcineurin signalling pathways. A productive approach to developing gene-phenotype correlations in Down's syndrome will make use of known and predicted functions and interactions of chromosome 21 genes to predict pathways that may be perturbed by their increased levels of expression. Investigations may then be targeted in animal models to specific interactions, intermediate steps or end-points of such pathways and the downstream - perhaps amplified - consequences of gene dosage directly assessed. Once pathway perturbations have been identified, the potential for rational design of therapeutics becomes practical.     

Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations

Recent studies have suggested that a significant fraction of the human genome is contained in blocks of strong linkage disequilibrium, ranging from ~5 to >100 kb in length, and that within these blocks a few common haplotypes may account for >90% of the observed haplotypes. Furthermore, previous studies have suggested that common haplotypes in candidate genes are generally shared across populations and represent the majority of chromosomes in each population. The conclusions drawn from these preliminary studies, however, are based on an incomplete knowledge of the variation in the regions examined. To bridge this gap in knowledge, we have completely resequenced 100 candidate genes in a population of African descent and one of European descent. Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described. We also report that the average number of inferred haplotypes per gene, when complete data is used, is higher than in previous reports and that the number and proportion of all haplotypes represented by common haplotypes per gene is variable. Furthermore, we demonstrate that haplotypes shared between the two populations constitute only a fraction of the total number of haplotypes observed and that these shared haplotypes represent fewer of the African-descent chromosomes than was expected from previous studies. Finally, we show that restricting variation discovery to coding regions does not adequately describe all common haplotypes or the true haplotype block structure observed when all common variation is used to infer haplotypes. These data, derived from complete knowledge of genetic variation in these genes, suggest that the haplotype architecture of candidate genes across the human genome is more complex than previously suggested, with important implications for candidate gene and genomewide association studies.     

A novel permutation testing method implicates sixteen nicotinic acetylcholine receptor genes as risk factors for smoking in schizophrenia families

Smoking is a common correlate of schizophrenia, which leads to medical morbidity. Although twin and adoption studies have consistently implicated genes in the etiology of both smoking and schizophrenia, finding genes has been difficult. Several authors have suggested that clinical or neurobiological features associated with schizophrenia, such as smoking, might improve the ability to detect schizophrenia susceptibility genes by identifying genes related to the etiology of that feature. The objective of this study is to assess evidence for linkage of sixteen nicotinic acetylcholine receptor genes and smoking in schizophrenia families, using data from the NIMH Genetics Initiative for schizophrenia. Sixteen nicotinic acetylcholine receptor genes were selected prior to analysis. We used a multipoint sibling pair linkage analysis program, SIBPAL2, with a smoking trait in schizophrenia families. The significance of the group of candidate genes, in addition to each individual candidate gene, was assessed using permutation testing, which adjusted for multiple comparisons. The group of genes showed significant linkage to the smoking trait after adjusting for multiple comparisons through permutation testing (p = 0.039). In addition, two of the individual candidate genes were significant (CHRNA2, p = 0.044) and (CHRNB2, p = 0.015) and two genes were marginally significant (CHRNA7, p = 0.095; CHRNA1, p = 0.076). The significance of the complex hypothesis, involving sixteen genes, implicates the nicotinic system in smoking for schizophrenic families. Individual gene analysis suggests that CHRNA2 and CHRNB2 may play a particular role in this involvement. Such findings help prioritize genes for future case control studies. In addition, we provide a novel permutation method that is useful in future analyses involving a single hypothesis, with multiple candidate genes.     

Genetic variation in RPS6KA1, RPS6KA2, RPS6KB1, RPS6KB2, and PDK1 and risk of colon or rectal cancer

RPS6KA1, RPS6KA2, RPS6KB1, RPS6KB2, and PDK1 are involved in several pathways central to the carcinogenic process, including regulation of cell growth, insulin, and inflammation. We evaluated genetic variation in their candidate genes to obtain a better understanding of their association with colon and rectal cancer. We used data from two population-based case-control studies of colon (n=1574 cases, 1940 controls) and rectal (n=791 cases, 999 controls) cancer. We observed genetic variation in RPS6KA1, RPS6KA2, and PRS6KB2 were associated with risk of developing colon cancer while only genetic variation in RPS6KA2 was associated with altering risk of rectal cancer. These genes also interacted significantly with other genes operating in similar mechanisms, including Akt1, FRAP1, NFκB1, and PIK3CA. Assessment of tumor markers indicated that these genes and this pathway may importantly contributed to CIMP+ tumors and tumors with KRAS2 mutations. Our findings implicate these candidate genes in the etiology of colon and rectal cancer and provide information on how these genes operate with other genes in the pathway. Our data further suggest that this pathway may lead to CIMP+ and KRAS2-mutated tumors.