22 research outputs found
Performance of risk prediction for inflammatory bowel disease based on genotyping platform and genomic risk score method
Background: Predicting risk of disease from genotypes is being increasingly proposed for a variety of diagnostic and prognostic purposes. Genome-wide association studies (GWAS) have identified a large number of genome-wide significant susceptibility loci for Crohn's disease (CD) and ulcerative colitis (UC), two subtypes of inflammatory bowel disease (IBD). Recent studies have demonstrated that including only loci that are significantly associated with disease in the prediction model has low predictive power and that power can substantially be improved using a polygenic approach. Methods: We performed a comprehensive analysis of risk prediction models using large case-control cohorts genotyped for 909,763 GWAS SNPs or 123,437 SNPs on the custom designed Immunochip using four prediction methods (polygenic score, best linear genomic prediction, elastic-net regularization and a Bayesian mixture model). We used the area under the curve (AUC) to assess prediction performance for discovery populations with different sample sizes and number of SNPs within cross-validation. Results: On average, the Bayesian mixture approach had the best prediction performance. Using cross-validation we found little differences in prediction performance between GWAS and Immunochip, despite the GWAS array providing a 10 times larger effective genome-wide coverage. The prediction performance using Immunochip is largely due to the power of the initial GWAS for its marker selection and its low cost that enabled larger sample sizes. The predictive ability of the genomic risk score based on Immunochip was replicated in external data, with AUC of 0.75 for CD and 0.70 for UC. CD patients with higher risk scores demonstrated clinical characteristics typically associated with a more severe disease course including ileal location and earlier age at diagnosis. Conclusions: Our analyses demonstrate that the power of genomic risk prediction for IBD is mainly due to strongly associated SNPs with considerable effect sizes. Additional SNPs that are only tagged by high-density GWAS arrays and low or rare-variants over-represented in the high-density region on the Immunochip contribute little to prediction accuracy. Although a quantitative assessment of IBD risk for an individual is not currently possible, we show sufficient power of genomic risk scores to stratify IBD risk among individuals at diagnosis.Guo-Bo Chen, Sang Hong Lee, Grant W. Montgomery, Naomi R. Wray, Peter M. Visscher, Richard B. Gearry, Ian C. Lawrance, Jane M. Andrews, Peter Bampton, Gillian Mahy, Sally Bell, Alissa Walsh, Susan Connor, Miles Sparrow, Lisa M. Bowdler, Lisa A. Simms, Krupa Krishnaprasad, the International IBD Genetics Consortium, Graham L. Radford-Smith, and Gerhard Moser
Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways.
The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, UK, and USA comprising 52,506 individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs in KITLG and a region of 9q32. In a bivariate analysis combining the nevus results with a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B, DOCK8, and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis
Independent replication and meta-analysis for endometriosis risk loci
Endometriosis is a complex disease that affects 6-10% of women in their reproductive years and 20-50% of women with infertility. Genome-wide and candidate-gene association studies for endometriosis have identified 10 independent risk loci, and of these, nine (rs7521902, rs13394619, rs4141819, rs6542095, rs1519761, rs7739264, rs12700667, rs1537377, and rs10859871) are polymorphic in European populations. Here we investigate the replication of nine SNP loci in 998 laparoscopically and histologically confirmed endometriosis cases and 783 disease-free controls from Belgium. SNPs rs7521902, rs13394619, and rs6542095 show nominally significant (p <.05) associations with endometriosis, while the directions of effect for seven SNPs are consistent with the original reports. Association of rs6542095 at the IL1A locus with 'All' (p =.066) and 'Grade-B' (p =.01) endometriosis is noteworthy because this is the first successful replication in an independent population. Meta-analysis with the published results yields genome-wide significant evidence for rs7521902, rs13394619, rs6542095, rs12700667, rs7739264, and rs1537377. Notably, three coding variants in GREB1 (near rs13394619) and CDKN2B-AS1 (near rs1537377) also showed nominally significant associations with endometriosis. Overall, this study provides important replication in a uniquely characterized independent population, and indicates that the majority of the original genome-wide association findings are not due to chance alone
Analysis of potential protein-modifying variants in 9000 endometriosis patients and 150000 controls of European ancestry
Genome-wide association (GWA) studies have identified 19 independent common risk loci for endometriosis. Most of the GWA variants are non-coding and the genes responsible for the association signals have not been identified. Herein, we aimed to assess the potential role of protein-modifying variants in endometriosis using exome-array genotyping in 7164 cases and 21005 controls, and a replication set of 1840 cases and 129016 controls of European ancestry. Results in the discovery sample identified significant evidence for association with coding variants in single-variant (rs1801232-CUBN) and gene-level (CIITA and PARP4) meta-analyses, but these did not survive replication. In the combined analysis, there was genome-wide significant evidence for rs13394619 (P = 2.3 × 10−9) in GREB1 at 2p25.1 — a locus previously identified in a GWA meta-analysis of European and Japanese samples. Despite sufficient power, our results did not identify any protein-modifying variants (MAF > 0.01) with moderate or large effect sizes in endometriosis, although these variants may exist in non-European populations or in high-risk families. The results suggest continued discovery efforts should focus on genotyping large numbers of surgically-confirmed endometriosis cases and controls, and/or sequencing high-risk families to identify novel rare variants to provide greater insights into the molecular pathogenesis of the disease
Endometriosis risk alleles at 1p36.12 act through inverse regulation of CDC42 and LINC00339
Genome-wide association studies (GWAS) have identified markers within the WNT4 region on chromosome 1p36.12 showing consistent and strong association with increasing endometriosis risk. Fine mapping using sequence and imputed genotype data has revealed strong candidates for the causal SNPs within these critical regions; however, the molecular pathogenesis of these SNPs is currently unknown. We used gene expression data collected from whole blood from 862 individuals and endometrial tissue from 136 individuals from independent populations of European descent to examine the mechanism underlying endometriosis susceptibility. Association mapping results from 7,090 individuals (2,594 cases and 4,496 controls) supported rs3820282 as the SNP with the strongest association for endometriosis risk (P = 1.84 × 10−5, OR = 1.244 (1.126-1.375)). SNP rs3820282 is a significant eQTL in whole blood decreasing expression of LINC00339 (also known as HSPC157) and increasing expression of CDC42 (P = 2.0 ×10−54 and 4.5x10−4 respectively). The largest effects were for two LINC00339 probes (P = 2.0 ×10−54; 1.0 × 10−34). The eQTL for LINC00339 was also observed in endometrial tissue (P = 2.4 ×10−8) with the same direction of effect for both whole blood and endometrial tissue. There was no evidence for eQTL effects for WNT4. Chromatin conformation capture provides evidence for risk SNPs interacting with the promoters of both LINC00339 and CDC4 and luciferase reporter assays suggest the risk SNP rs12038474 is located in a transcriptional silencer for CDC42 and the risk allele increases expression of CDC42. However, no effect of rs3820282 was observed in the LINC00339 expression in Ishikawa cells. Taken together, our results suggest that SNPs increasing endometriosis risk in this region act through CDC42, but further functional studies are required to rule out inverse regulation of both LINC00339 and CDC42
Genome-wide DNA methylation analysis of formalin-fixed paraffin embedded colorectal cancer tissue
Formalin fixation and embedding of clinical tissue samples in paraffin is a common method for archiving biological material. These samples are often well annotated and provide an invaluable resource for research. However, this process of fixation and storage of tissue leads to DNA damage and fragmentation. The use of DNA from formalin fixed, paraffin-embedded (FFPE) tissue to interrogate methylation levels on a genome-wide scale can pose challenges. We compared fresh and matched FFPE tissue DNA samples using the Illumina Infinium HD Human Methylation 450K BeadChip platform with a companion application for repair and "restoration" of DNA from FFPE tissue. Our results showed good correlation between fresh and FFPE sample data. FFPE DNA captured 99% of the CpG sites on the array on average. Significant cancer subgroups based on the CpG island methylator phenotype (CIMP) were clearly distinguished for both fresh and FFPE sample sets with cluster and scaling analysis. The DNA methylation status for the five standard CIMP panel genes which was evaluated for all samples by the MethyLight assay was correctly assigned in both fresh and FFPE samples by the array data. We conclude that the "restoration" method followed by assay on the Infinium HD Human Methylation 450K microarray can produce good quality data for DNA from FFPE samples
Contribution of genetic variation to transgenerational inheritance of DNA methylation
Background: Despite the important role DNA methylation plays in transcriptional regulation, the transgenerational inheritance of DNA methylation is not well understood. The genetic heritability of DNA methylation has been estimated using twin pairs, although concern has been expressed whether the underlying assumption of equal common environmental effects are applicable due to intrauterine differences between monozygotic and dizygotic twins. We estimate the heritability of DNA methylation on peripheral blood leukocytes using Illumina HumanMethylation450 array using a family based sample of 614 people from 117 families, allowing comparison both within and across generations
Endometrial vezatin and its association with endometriosis risk
STUDY QUESTION: Do endometriosis risk-associated single nucleotide polymorphisms (SNPs) found at the 12q22 locus have effects on vezatin (VEZT) expression
Performance of risk prediction for inflammatory bowel disease based on genotyping platform and genomic risk score method
Background: Predicting risk of disease from genotypes is being increasingly proposed for a variety of diagnostic and prognostic purposes. Genome-wide association studies (GWAS) have identified a large number of genome-wide significant susceptibility loci for Crohn’s disease (CD) and ulcerative colitis (UC), two subtypes of inflammatory bowel disease (IBD). Recent studies have demonstrated that including only loci that are significantly associated with disease in the prediction model has low predictive power and that power can substantially be improved using a polygenic approach.
Methods: We performed a comprehensive analysis of risk prediction models using large case-control cohorts genotyped for 909,763 GWAS SNPs or 123,437 SNPs on the custom designed Immunochip using four prediction methods (polygenic score, best linear genomic prediction, elastic-net regularization and a Bayesian mixture model). We used the area under the curve (AUC) to assess prediction performance for discovery populations with different sample sizes and number of SNPs within cross-validation.
Results: On average, the Bayesian mixture approach had the best prediction performance. Using cross-validation we found little differences in prediction performance between GWAS and Immunochip, despite the GWAS array providing a 10 times larger effective genome-wide coverage. The prediction performance using Immunochip is largely due to the power of the initial GWAS for its marker selection and its low cost that enabled larger sample sizes. The predictive ability of the genomic risk score based on Immunochip was replicated in external data, with AUC of 0.75 for CD and 0.70 for UC. CD patients with higher risk scores demonstrated clinical characteristics typically associated with a more severe disease course including ileal location and earlier age at diagnosis.
Conclusions: Our analyses demonstrate that the power of genomic risk prediction for IBD is mainly due to strongly associated SNPs with considerable effect sizes. Additional SNPs that are only tagged by high-density GWAS arrays and low or rare-variants over-represented in the high-density region on the Immunochip contribute little to prediction accuracy. Although a quantitative assessment of IBD risk for an individual is not currently possible, we show sufficient power of genomic risk scores to stratify IBD risk among individuals at diagnosis