False Alarms in Consumer Genomics Add to Public Fear and Potential Health Care Burden.
Arthur L BeaudetDeborah CragunJinyong PangSwamy R AdapaRenee FonsecaRays H Y JiangPublished in: Journal of personalized medicine (2020)
We have entered an era of direct-to-consumer (DTC) genomics. Patients have relayed many success stories of DTC genomics about finding causal mutations of genetic diseases before showing any symptoms and taking precautions. However, consumers may also take unnecessary medical actions based on false alarms of "pathogenic alleles". The severity of this problem is not well known. Using publicly available data, we compared DTC microarray genotyping data with deep-sequencing data of 5 individuals and manually checked each inconsistently reported single nucleotide variants (SNVs). We estimated that, on average, a person would have ~5 "pathogenic" alleles reported due to wrongly reported genotypes if using a 23andMe genotyping microarray. We also found that the number of wrongly classified "pathogenic" alleles per person is at least as significant as those due to wrongly reported genotypes. We show that the scale of the false alarm problem could be large enough that the medical costs will become a burden to public health.
Keyphrases
- healthcare
- single cell
- public health
- electronic health record
- genome wide
- end stage renal disease
- big data
- high throughput
- ejection fraction
- newly diagnosed
- copy number
- chronic kidney disease
- prognostic factors
- risk factors
- gene expression
- peritoneal dialysis
- machine learning
- climate change
- physical activity
- deep learning
- social media
- patient reported outcomes
- sleep quality
- prefrontal cortex