Use of SNP chips to detect 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: Retrospective, population based diagnostic evaluation.

Participants: 49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project.

Main outcome measures: Genotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data.

Results: Overall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had 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 the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03).

Conclusions: SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.

Fig 1

Explanation of genotyping using SNP chip technology. Example cluster plots for common variant (top) and rare variant (bottom). Each circle represents one person’s DNA assayed at specific position on SNP chip when known variant (G to C) exists. Automated clustering across multiple individuals is used to determine which DNA base is present in each person at that position. Pink circles in main cluster represent most common reference base (G), orange circles represent heterozygous variant (C), and pale purple circles represent uncertain or missing results due to experimental noise

Fig 2

Current medical context of SNP chip screening

Fig 3

Positive predictive value (PPV) of UK Biobank Axiom SNP chip for detecting variants at different population frequencies. Similar trend was seen with UK Biobank BiLEVE chip (supplementary figure A) and Personal Genome Project consumer data (supplementary figure B)

Fig 4

STARD diagram to report flow of participants with pathogenic BRCA variant on UK Biobank Axiom chip compared with sequencing. Similar process was followed for BiLEVE chip (supplementary figure C). QC=quality control