Konstantin Shestopaloff

Association of host genome with intestinal microbial composition in a large healthy cohort

Intestinal microbiota is known to be important in health and disease. Its composition is influenced by both environmental and host factors. Few large-scale studies have evaluated the association between host genetic variation and the composition of microbiota. We recruited a cohort of 1,561 healthy individuals, of whom 270 belong in 123 families, and found that almost one-third of fecal bacterial taxa were heritable. In addition, we identified 58 SNPs associated with the relative abundance of 33 taxa in 1,098 discovery subjects. Among these, four loci were replicated in a second cohort of 463 subjects: rs62171178 (nearest gene UBR3) associated with Rikenellaceae, rs1394174 (CNTN6) associated with Faecalibacterium, rs59846192 (DMRTB1) associated with Lachnospira, and rs28473221 (SALL3) associated with Eubacterium. After correction for multiple testing, 6 of the 58 associations remained significant, one of which replicated. These results identify associations between specific genetic variants and the gut microbiome.

Determinants of Intestinal Permeability in Healthy First-Degree Relatives of Individuals with Crohnʼs Disease

Background:The Genetics, Environmental, Microbial Project is a multicenter study assessing etiological factors in Crohns disease by studying healthy first-degree relatives (FDRs) of individuals affected by Crohns disease. We aimed to evaluate the contribution of genetic, microbial, and environmental factors to the determination of intestinal permeability in healthy FDRs. Methods:IP was assessed using the lactulose-mannitol ratio (LacMan ratio). FDRs were genotyped for 167 inflammatory bowel disease-associated single nucleotide polymorphisms. Taxonomic profile of the fecal microbiota was determined by Illumina MiSeq pyrosequencing of 16S ribosomal RNA. The associations of LacMan ratio with demographic factors, inflammatory bowel disease-associated single nucleotide polymorphisms and the fecal microbiota were assessed. Results:One hundred ninety-six white FDRs were included. Eleven percent of FDRs had an elevated LacMan ratio (≥0.03). A multivariate analysis demonstrated that younger subjects and nonsmokers had higher LacMan ratios, P = 3.62 × 10−4 and P = 0.03, respectively. The LacMan ratio was not significantly heritable, H2r, 0.13, P = 0.13. There was no association between any of the 167 inflammatory bowel disease-associated risk variants and LacMan ratio nor was there a correlation between fecal microbial composition and the LacMan ratio. Conclusions:We did not find LacMan ratio to be significantly heritable suggesting that the contribution of genetic factors to the determination of intestinal permeability in healthy FDRs is modest. Environmental factors, such as smoking, are likely more important determinants. The effect of age on intestinal barrier function has been underappreciated.

FUT2 genotype and secretory status are not associated with fecal microbial composition and inferred function in healthy subjects

ABSTRACT Heritability analysis of the microbiota has demonstrated the importance of host genotype in defining the human microbiota. The alpha (1,2)-fucosyltransferase 2 encoded by FUT2 is involved in the formation of the H antigen and the SNP, rs601338 is associated with ABO histo-blood group antigen secretion in the intestinal mucosa. Previous studies have provided non replicated results for the association of this polymorphism with the composition and inferred function of intestinal microbiota. We aimed to assess this relationship in a large cohort of 1,190 healthy individuals. Genotyping was performed using the HumanCoreEXOME chip, microbial composition was addressed by 16S rRNA gene sequencing. Firmicutes, Bacteroidetes, and Actinobacteria were the dominant phyla in this cohort. Although we have sufficient power to detect significant associations of FUT2 genotype/ inferred phenotype with the microbiota, our data demonstrate that FUT2 genotype and secretor status is not associated with microbial alpha diversity, microbial composition or inferred microbial function after correction for multiple testing. Thus, FUT2 genotype and inferred phenotype are not associated with human fecal microbial composition and imputed function.

A model for estimating ovarian cancer risk: Application for preventive oophorectomy

OBJECTIVE It is important to identify women in the population who have a high risk of ovarian cancer and who might benefit from prophylactic bilateral salpingo-oophorectomy. The probability that a woman will develop ovarian cancer depends on her current age, her reproductive history and her genetic status. METHODS We simulated the distribution of ovarian cancer risk for the 2011 Ontario female population. We generated (at random) individual risks of ovarian cancer to age 80 for 6,301,340 women, based on the published risk factors, mutation frequencies and population age-specific incidence rates (SEER database). Risk factors included parity, breastfeeding, oral contraceptives, tubal ligation and family history. Genetic factors included 11 single nucleotide polymorphisms (SNPs) and BRCA1/2 mutations. RESULTS Of the 6,301,340 women simulated as the general population of Ontario, the (complete) model predicts that 65,805 women (1.0%) will develop ovarian cancer by age 80. There were 46,069 women (0.7%) with a risk of ovarian cancer above 5%. BRCA1/2 mutation carriers accounted for 67.4% of the women at greater than 5% risk (31,028 women). Among ovarian cancer patients at greater than 5% risk, a BRCA1/2 mutation was present in 89.2%. In contrast, SNPs contribute to a very small proportion of the ovarian cancer patients who were at greater than 5% risk. CONCLUSIONS Approximately 12.9% of all ovarian cancers in Ontario occur in the 0.7% of women in the general population who have a lifetime ovarian cancer risk in excess of 5%, the majority of whom carry a mutation in BRCA1 or BRCA2.

A genome wide association study on Newfoundland colorectal cancer patients' survival outcomes

BackgroundIn this study we performed genome-wide association studies to identify candidate SNPs that may predict the risk of disease outcome in colorectal cancer.MethodsPatient cohort consisted of 505 unrelated patients with Caucasian ancestry. Germline DNA samples were genotyped using the Illumina® human Omni-1quad SNP chip. Associations of SNPs with overall and disease free survivals were examined primarily for 431 patients with microsatellite instability-low (MSI-L) or stable (MSS) colorectal tumors using Cox proportional hazards method adjusting for clinical covariates. Bootstrap method was applied for internal validation of results. As exploratory analyses, association analyses for the colon (n = 334) and rectal (n = 171) cancer patients were also performed.ResultsAs a result, there was no SNP that reached the genomewide significance levels (p < 5x10−8) in any of the analyses. A small number of genetic markers (n = 10) showed nominal associations (p <10−6) for MSS/MSI-L, colon, or rectal cancer patient groups. These markers were located in two non-coding RNA genes or intergenic regions and none were amino acid substituting polymorphisms. Bootstrap analysis for the MSS/MSI-L cohort data suggested the robustness of the observed nominal associations.ConclusionsLikely due to small number of patients, our study did not identify an acceptable level of association of SNPs with outcome in MSS/MSI-L, colon, or rectal cancer patients. A number of SNPs with sub-optimal p-values were, however, identified; these loci may be promising and examined in other larger-sized patient cohorts.

A Survival Association Study of 102 Polymorphisms Previously Associated with Survival Outcomes in Colorectal Cancer

Several published studies identified associations of a number of polymorphisms with a variety of survival outcomes in colorectal cancer. In this study, we aimed to explore 102 previously reported common genetic polymorphisms and their associations with overall survival (OS) and disease-free survival (DFS) in a colorectal cancer patient cohort from Newfoundland (n = 505). Genotypes were obtained using a genomewide SNP genotyping platform. For each polymorphism, the best possible genetic model was estimated for both overall survival and disease-free survival using a previously published approach. These SNPs were then analyzed under their genetic models by Cox regression method. Correction for multiple comparisons was performed by the False Discovery Rate (FDR) method. Univariate analysis results showed that RRM1-rs12806698, IFNGR1-rs1327474, DDX20-rs197412, and PTGS2-rs5275 polymorphisms were nominally associated with OS or DFS (p < 0.01). In stage-adjusted analysis, the nominal associations of DDX20-rs197412, PTGS2-rs5275, and HSPA5-rs391957 with DFS were detected. However, after FDR correction none of these polymorphisms remained significantly associated with the survival outcomes. We conclude that polymorphisms investigated in this study are not associated with OS or DFS in our colorectal cancer patient cohort.

Germline INDELs and CNVs in a cohort of colorectal cancer patients: their characteristics, associations with relapse-free survival time, and potential time-varying effects on the risk of relapse

INDELs and CNVs are structural variations that may play roles in cancer susceptibility and patient outcomes. Our objectives were a) to computationally detect and examine the genome‐wide INDEL/CNV profiles in a cohort of colorectal cancer patients, and b) to examine the associations of frequent INDELs/CNVs with relapse‐free survival time. We also identified unique variants in 13 Familial Colorectal Cancer Type X (FCCX) cases. The study cohort consisted of 495 colorectal cancer patients. QuantiSNP and PennCNV algorithms were utilized to predict the INDELs/CNVs using genome‐wide signal intensity data. Duplex PCR was used to validate predictions for 10 variants. Multivariable Cox regression models were used to test the associations of 106 common variants with relapse‐free survival time. Score test and the multivariable Cox proportional hazards models with time‐varying coefficients were applied to identify the variants with time‐varying effects on the relapse‐free survival time. A total of 3486 distinct INDELs/CNVs were identified in the patient cohort. The majority of these variants were rare (83%) and deletion variants (81%). The results of the computational predictions and duplex PCR results were highly concordant (93–100%). We identified four promising variants significantly associated with relapse‐free survival time (P < 0.05) in the multivariable Cox proportional hazards regression models after adjustment for clinical factors. More importantly, two additional variants were identified to have time‐varying effects on the risk of relapse. Finally, 58 rare variants were identified unique to the FCCX cases; none of them were detected in more than one patient. This is one of the first genome‐wide analyses that identified the germline INDEL/CNV profiles in colorectal cancer patients. Our analyses identified novel variants and genes that can biologically affect the risk of relapse in colorectal cancer patients. Additionally, for the first time, we identified germline variants that can potentially be early‐relapse markers in colorectal cancer.

No associations of a set of SNPs in the Vascular Endothelial Growth Factor (VEGF) and Matrix Metalloproteinase (MMP) genes with survival of colorectal cancer patients

In this study, we aimed to investigate the associations of genetic variations within select genes functioning in angiogenesis, lymph‐angiogenesis, and metastasis pathways and the risk of outcome in colorectal cancer patients. We followed a two‐stage analysis: First, 381 polymorphisms from 30 genes (eight Vascular Endothelial Growth Factor (VEGF) and 22 Matrix Metalloproteinase [MMP] genes) were investigated in the discovery cohort (n = 505). Then, 16 polymorphisms with the lowest P‐value in this analysis were investigated in a separate replication cohort (n = 247). Genotypes were obtained using the Illumina® HumanOmni‐1‐Quad (discovery cohort) and Sequenom MassArray® (replication cohort) platforms. The primary outcome measure was overall survival (OS). Kaplan–Meier, univariate and multivariable Cox regression methods were used to test the associations between genotypes and OS. Four SNPs (rs12365082, rs11225389, rs11225388, and rs2846707) had the univariate analysis P < 0.05 in both the discovery and replication cohorts. These SNPs are in linkage disequilibrium with each other to varying extent and are located in the MMP8 and MMP27 genes. In the multivariable analysis adjusting for age, stage, and microsatellite instability status, three of these SNPs (rs12365082, rs11225389, rs11225388) were independent predictors of OS (P < 0.05) in the discovery cohort. However, the same analysis in the replication cohort did not yield statistically significant results. Overall, while the genetic variations in the VEGF and MMP genes are attractive candidates as prognostic markers, our study showed no evidence of associations of a large set of SNPs in these genes and overall survival of colorectal cancer patients in our study.

Analyzing differences between microbiome communities using mixture distributions: Analyzing Differences Between Microbiome Communities

In this paper, we present a method to assess differences between microbiome communities that effectively models sparse count data and accounts for presence-absence bias frequently encountered when zeros are present. We assume that the observed data for each operational taxonomic unit is Poisson generated with the rate for each sample originating from an underlying rate distribution. We propose to model this distribution using a mixture model, specifying the components based on the posterior rate distribution of a count and estimating the optimal weights using a least squares objective function. The distribution incorporates varying resolutions of samples, a point mass for differentiating structural and nonstructural zeros, and a truncation point mass to account for high values that are too sparse to model. As mixture component specification is not always straightforward, a method to estimate a joint model from several mixture distributions using minimum distances of bootstrap iterates is proposed. Once the population rate distribution is approximated, we obtain sample-specific distributions by conditioning on the observed operational taxonomic unit count, resolution, and estimated mixture distribution and then use these to estimate pairwise distances for a permutation test. The method gives an accurate estimate of the true proportion of zeros for presence-absence, effectively models the distribution of low counts using the mixture distribution, and achieves good power for detecting differences in a variety of scenarios. The method is tested using a simulation study and applied to two microbiome datasets. In each case, the results are compared with a number of existing methods.

744 Genome-Wide Association of Composition and Diversity of the Intestinal Bacterial Phyla in Healthy First Degree Relatives (FDR) of Crohn's Disease (CD) Subjects

Figure 1: Sepp1-/enteroids display an increase in stem cell characteristics and increased ROS production, proliferation, and decreased survival in response to hydrogen peroxide administration. (A) Relative Sepp1 mRNA expression. (B) Enteroid growth properties