Using SNP-chips to detect very rare pathogenic variants: retrospective population-based diagnostic evaluation

Abstract

Objective: To determine whether the sensitivity and specificity of SNP-chips are adequate for detecting rare pathogenic variants in a clinically unselected population. Design: We compared genotypes from SNP-chips (index test) with next generation sequencing data (reference standard) using a retrospective population-based cohort and standard metrics for evaluating diagnostic tests. Participants: 49,908 individuals recruited to UK Biobank with SNP-chip and next generation sequencing data, and an additional 21 individuals who purchased consumer genetic tests and shared their data online via the Personal Genomes Project. Main outcome measures: We evaluated genotyping (i.e. identification of the correct DNA base at a specific genomic location) using SNP-chips versus sequencing and split the results by frequency of that genotype in the population. We went on to select rare pathogenic variants in the BRCA1 and BRCA2 genes as an exemplar for detailed analysis of clinically actionable variants in UK Biobank, and assessed BRCA-related cancers (breast, ovarian, prostate and pancreatic) in participants using cancer registry data. Results: Overall, genotyping using SNP-chips performs well versus sequencing; sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) are all >99% for 108,574 common variants directly genotyped on the SNP-chips and sequenced in UK Biobank. However, the likelihood of a true positive result reduces dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency <0.001% in UK Biobank, the PPV is very low and only 16% of 4,711 variants from the SNP-chips confirm with sequencing data. Results are similar for SNPchip data from the Personal Genomes Project, and 20/21 individuals analysed have at least one false positive rare pathogenic variant that has been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP-chips versus sequencing in UK Biobank are: sensitivity 34.6%, specificity 98.3%, PPV 4.2% and NPV 99.9%. Rates of BRCA-related cancers in individuals in UK Biobank with a positive SNP-chip result are similar to age-matched controls (OR 1.28, P=0.07, 95% CI: 0.98 to 1.67), because the vast majority of variants are false positives, while sequence-positive individuals have a significantly increased risk (OR 3.73, P<0.001, 95% CI: 2.57 to 5.40). Conclusions: SNP-chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.