SNP mistyping in genotyping arrays--an important cause of spurious association in case-control studies

Systematic review and meta-analysis of genetic association studies of pelvic organ prolapse

INTRODUCTION AND HYPOTHESIS

Family and twin studies demonstrate that pelvic organ prolapse (POP) is heritable, but the genetic etiology is poorly understood. This review aimed to identify genetic loci and specific polymorphisms associated with POP, while assessing the strength, consistency, and risk of bias among reported associations.

METHODS

Updating an earlier systematic review, PubMed and HuGE Navigator as well as relevant conference abstracts were searched using genetic and phenotype keywords from 2015 to 2020. Screening and data extraction were performed in duplicate. Fixed and random effects meta-analyses were conducted using co-dominant models of inheritance. We assessed credibility of pooled associations using interim Venice criteria.

RESULTS

We screened 504 new abstracts and included 46 published and 7 unpublished studies. In pooled analyses we found significant associations for four polymorphisms: rs2228480 at the ESR1 gene (OR 0.67 95% CI 0.46-0.98, I² = 0.0%, Venice rating BAB), rs12589592 at the FBLN5 gene (OR 1.46 95% CI 1.11-1.82, I² = 36.3%, Venice rating BBB), rs484389 in the PGR gene (OR 0.61 95% CI 0.39-0.96, I² = 32.4%, Venice rating CBB), and rs1800012 at the COL1A1 gene (OR 0.80 95% CI 0.66-0.96, I² = 0.0%, Venice rating BAB). Further credible novel variants have also been recently identified in genome-wide association studies.

CONCLUSION

The genetic contributions to POP remain poorly understood. Several biologically plausible variants have been identified, but much work is required to establish the role of these genes in the pathogenesis of POP or to establish a role for genetic testing in clinical practice.

Genome-wide association study confirms lung cancer susceptibility loci on chromosomes 5p15 and 15q25 in an African-American population

OBJECTIVES

Genome-wide association studies (GWAS) of lung cancer have identified regions of common genetic variation with lung cancer risk in Europeans who smoke and never-smoking Asian women. This study aimed to conduct a GWAS in African Americans, who have higher rates of lung cancer despite smoking fewer cigarettes per day when compared with Caucasians. This population provides a different genetic architecture based on underlying African ancestry allowing the identification of new regions and exploration of known regions for finer mapping.

MATERIALS AND METHODS

We genotyped 1,024,001 SNPs in 1737 cases and 3602 controls in stage 1, followed by a replication phase of 20 SNPs (p<1.51×10(-5)) in an independent set of 866 cases and 796 controls in stage 2.

RESULTS AND CONCLUSION

In the combined analysis, we confirmed two loci to be associated with lung cancer that achieved the threshold of genome-wide significance: 15q25.1 marked by rs2036527 (p=1.3×10(-9); OR=1.32; 95% CI=1.20-1.44) near CHRNA5, and 5p15.33 marked by rs2853677 (p=2.8×10(-9); OR=1.28; 95% CI=1.18-1.39) near TERT. The association with rs2853677 is driven by the adenocarcinoma subtype of lung cancer (p=1.3×10(-8); OR=1.37; 95% CI=1.23-1.54). No SNPs reached genome-wide significance for either of the main effect models examining smoking - cigarettes per day and current or former smoker. Our study was powered to identify strong risk loci for lung cancer in African Americans; we confirmed results previously reported in African Americans and other populations for two loci near plausible candidate genes, CHRNA5 and TERT, on 15q25.1 and 5p15.33 respectively, are associated with lung cancer. Additional work is required to map and understand the biological underpinnings of the strong association of these loci with lung cancer risk in African Americans.

Genome-wide association study identifies genetic risk underlying primary rhegmatogenous retinal detachment

Rhegmatogenous retinal detachment (RRD) is an important cause of vision loss and can potentially lead to blindness. The underlying pathogenesis is complex and incompletely understood. We applied a two-stage genetic association discovery phase followed by a replication phase in a combined total of 2833 RRD cases and 7871 controls. The discovery phase involved a genome-wide association scan of 867 affected individuals and 1953 controls from Scotland, followed by genotyping and testing 4347 highest ranking or candidate single nucleotide polymorphisms (SNPs) in independent sets of cases (1000) and controls (2912) of Dutch and British origin. None of the SNPs selected reached a Bonferroni-corrected threshold for significance (P < 1.27 × 10(-7)). The strongest association, for rs12960119 (P = 1.58 × 10(-7)) located within an intron of the SS18 gene. Further testing was carried out in independent case-control series from London (846 cases) and Croatia (120 cases). The combined meta-analysis identified one association reaching genome-wide significance for rs267738 (OR = 1.29, P = 2.11 × 10(-8)), a missense coding SNP and eQTL for CERS2 encoding the protein ceramide synthase 2. Several of the top signals showing suggestive significance in the combined meta-analysis encompassed genes with a documented role in cell adhesion or migration, including SS18, TIAM1, TSTA3 and LDB2, which warrant further investigation. This first genetic association study of RRD supports a polygenic component underlying RRD risk since 27.4% of the underlying RRD liability could be explained by the collective additive effects of the genotyped SNP from the discovery genome-wide scan.

IPGWAS: an integrated pipeline for rational quality control and association analysis of genome-wide genetic studies

Large numbers of samples and marker loci were tested for association in genome-wide association studies (GWAS). Hence, quality control (QC) by removing individuals or markers with low genotyping quality is of utmost importance to minimize potential false positive associations. IPGWAS was developed to facilitate the identification of the rational thresholds in QC of GWAS datasets, association analysis, Manhattan plot, quantile-quantile (QQ) plot, and format conversion for genetic analyses, such as meta-analysis, genotype phasing, and imputation. IPGWAS is a multiplatform application written in Perl with a graphical user interface (GUI) and available for free at http://sourceforge.net/projects/ipgwas/.

Assessing the impact of non-differential genotyping errors on rare variant tests of association

BACKGROUND/AIMS

We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful.

METHODS

We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates.

RESULTS

Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor allele frequency decreases. While the power loss from heterozygote to common homozygote errors tends to be smaller for a given error rate, in practice heterozygote to homozygote errors are more frequent and, thus, will have measurable impact on power.

CONCLUSION

Error rates from genotype-calling technology for next-generation sequencing data suggest that substantial power loss may be seen when applying current rare variant tests of association to called genotypes.