The way I understand Personal Genomics is when one sequences/genotypes his/her genome outside of the clinical setting, usually using direct-to-consumer genetic test providers. The usefulness of personal genomics data is being disputed among clinicians when applied to healthy individuals, that is, individuals that are not affected by a genomic disorder.
Personal genome tests’ usefulness in precision medicine may be contested for a number of reasons. First, the amount of annotations that we currently hold for geno-pheno associations is rather limited, inconsistent and even spurious. There are so may different combinations of variants that may cause disease that to date we still lack the amount of data needed to classify these rare events where combinations of mutations give rise to a pathogenic phenotype. Hence, making sense of a myriad of different variations, many of them predicted to contribute slight health risks, seems to be of no use.
In addition, the studies that provide the geno-pheno associations tend to be biased to a specific type of ethnic background, usually European, for disease and controls. These biases make phenotypic predictions unreliable. Most importantly, even if predicted (pathogenic) phenotypes are real, there is also the fact that many of the predicted risks are only probabilistic.
For example, according to one estimate, my genome has about a 30% risk of causing prostate cancer (you can find details about my personal genome and those of many others via the Repositive Personal Genomics Collection). Even if this result was true, it means that of a hundred men with my same mutations, 30 would develop the disease. The problem, however, is that we do not know which of these 30 men are the ones that will develop the disease, and if there was a possible treatment for my condition, the kind of expenditure in prevention needed would potentially collapse any health system.
The challenges looking forward regarding preventive medicine are thus enormous and it is likely that the role of patients will change into ‘participants’. That means active users who are playing a role in the development of drugs, measurements and diagnoses. It is a daunting yet promising future of healthier and longer lives.
