Innovation versus evidence: to trust direct-to-consumer personal genomic tests?

Keywords::

• commercialization
• evidence
• genetics
• genomics
• human genome
• innovation

The latest genomic technology with massively parallel simultaneous analysis of millions of genetic variants across the genome has revolutionized biomedical science and the biotechnology industry [1–4]. Now, next-generation sequencing (NGS) technology with faster, cheaper and more accurate human genome sequencing permits the unprecedented identification of genome variants. Validation and assessment of causal (driver) mutations involved in disease pathogenesis, progression and therapeutic response to drugs shapes current thinking and opens new ways for personalized disease risk prediction, prevention and treatment. However, there is a big gap in moving from this excellent genotyping approach to clinical applications as multiple problems and challenges need to be overcome [5,6].

Based on multiple novel genetic variants derived from genome-wide association studies (GWAS) [7,8], several companies now promote direct-to-consumer (DTC) genetic tests. It is promoted that these genetic tools can predict an asymptomatic person’s risk for developing common complex diseases, such as cancer, cardiovascular events, diabetes and many other disorders.

Business & direct-to-consumer tests

The molecular diagnostics market has grown rapidly over the last few years. This dynamic growing multi-billion dollar market includes more than 80 companies. However, to prevent harm to the general population, government regulatory initiatives are required to accelerate the approvals of emerging molecular diagnostics by integrating biomarkers and companion pharmacogenomic tests.

Over the past 8 years, the pharmaceuticals sector has lost a stunning US$593 billion (-65%) in market capital, while the two sectors with innovation (biotechnology and medical technology) have each added US$71 billion (+46%) and US$19 billion (+6%) in market capital, respectively. One way to bridge the loss that has been selected by companies with expertise in innovation and genome sequencing technology, is to rapidly develop and commercialize DTC medical tests.

The first complete draft of a human genome sequencing 10 years ago and the completion of the HapMap Project in 2007 [9], which can be used as a reference database, have enabled GWAS to identify disease-risk genetic variants [8,10]. Based on these developments and rapidly decreasing genome sequencing costs, several companies developed and now provide DTC genetic tests for predicting the risks of various common diseases. This genetic variant-based market promotes itself through the internet and emails stating that with a few thousand-dollar DTC genomic tests one’s risk of developing cancer, diabetes and other common diseases can now be estimated.

However, the goal for developing robust molecular, genetic and imaging markers for widespread clinical use is elusive. Research efforts in general population risk stratification, successful screening, early detection of a disease and drug response prediction have little or no clinical success. For example, two of the most popular and widely used screening methods are mammography and prostate-specific antigen for breast and prostate cancer screening, respectively. However, large-scale screening trials demonstrate only modest mortality rate reductions and these should be balanced with the harm derived from false-positive results. Based on this current evidence it should be emphasized that the time has come for us to stop using these screening markers as indicators of the quality of our healthcare system and try to develop novel robust markers [11,12].

Limitations & harms

Valid concerns for the clinical reliability of DTC genomic tests raise a series of limitations in both the scientific background and clinical evaluation of these tests.

The development of these DTC genetic tools was based on incomplete genome-wide analysis and preliminary data. First, data from partial genome sequencing were used. As a result, only a part of human SNPs was used to identify genetic variants. Moreover, by including only point mutations, such as SNPs, but not somatic mutations, such as genomic rearrangements and copy-number changes (which have an important role in complex disease pathogenesis, such as cancer) [13], these tests can provide only a limited landscape of the genetic causes underlying complex diseases. Second, the methodology for a valid distinction between driver (causal) and passenger (non-causal) mutations has not yet been fully determined. Third, epigenetic and epigenomic alterations that also have a major role in understanding of phenotypic differences among individuals and patients [14,15] have not been considered when developing these medical tests. Fourth, insights into the functional role of genes and mutations may represent an essential step towards the development of robust biomarkers for wide clinical use. Unfortunately, research on understanding genetic regulation, the complexity of which is one of the great wonders of nature and represents a daunting challenge to unravel, is still in its infancy [16]. Unsurprisingly the poor understanding of genetic regulation has not been considered by those providing DTC genomic tests.

From a critical clinical point of view, valid concerns and skepticism are raised regarding the offering and promoting of DTC tests in an absence of regulatory mechanisms and rigorous criteria required for their approval. Clinical validity, including clinical sensitivity, specificity and utility (the balance between the health-related benefits and the harm) are considered useful requirements. Such approaches can protect the general population and public or private insurance systems not only from unnecessary expenses but also from potential health harms. However, this clinical assessment requires long-term evaluation that is in contrast to a rapid incorporation of innovation for a healthcare improvement [17–19]. Genomic medicine presents profound challenges. Never before has the gap between the quantity of information and our ability to interpret it been so great. Whole-genome sequencing will produce abnormal results in all who are tested: everyone will have positive results, false positives and false negatives. Some results may prove harmful and some will be useless. Preserving the health benefits of genomics while minimizing the harms, will be an important research goal.

Considering this potential risk for public health and individuals [19], the US FDA recently sent a letter informing Pathway Genomics and another 19 companies that their DNA testing and interpretation service “appears to meet the definition of a device” and may, therefore, require FDA approval [101]. Moreover, the FDA held meetings in June and July 2010 on how and what to regulate [102,103]. Less than 1% of genetic testing is currently overseen by regulatory agencies, such as the FDA and the Medicines and Healthcare Products Regulatory Agency (MHRA) in the UK [17]. Increasingly, such agencies are responding to calls to exert greater control – from politicians, healthcare administrators and government advisory committees, as well as from geneticists and the public. Similarly, other agencies, such as the Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS), emphasize that direct consumer involvement in the genetic revolution is to be welcomed, but consumers must be protected from unrealistic claims and misinterpretations of complex, dynamic genomic information [18].

Gene–environment interactions

Emerging evidence accumulating from both experimental and clinical data strongly supports ideas and intellectual concepts that common diseases, particularly cancer, mostly arises from gene–gene and gene–environment interactions rather than a simple accumulation of genetic and epigenetic alterations over a cutoff value [20–29]. Although the number of somatic and heritable mutations involved, for example, in cancer initiation, appears to be relatively limited to fewer than 20–30 DNA changes (‘hits’) that can be detected by NGS [13], the big challenge is how to understand the regulation and interactions of all the mutated genes that drive the transformation of normal cells to defective or cancer cells [30]. For example, breast cancer arises from both the accumulation of driver mutations and from their interactions with environmental and lifestyle factors, including age at menarche, menopause, parity, first and subsequent pregnancies, breast feeding, exogenous estrogen use, body mass index, diet, physical exercise, height and alcohol consumption [31]. Even in hereditary breast cancer, which is mostly caused by high-risk, rare heritable mutations in BRCA1 or BRCA2 genes, the interactions of these genes with environmental factors define and explain why approximately 25% of women carrying these mutations will not develop breast cancer in their life [32].

Without understanding genetic regulation (one of the great wonders of nature) and complex dynamic nonlinear networks as the chaotic biological and environmental systems, the probability of personalized disease risk predictions in asymptomatic individuals through innovative biomarkers will be limited. Exciting research is underway, including functional genomics [27,28], and predicting nonlinear dynamic bioenvironmental interactions inference [33]. In addition, large-scale systematic studies exploring human and cancer genomes and epigenomes using NGS platforms have been launched recently [34–36]. Significant data emerging from these international consortiums and further technological advances with simultaneously multiplexing complete sequencing of human genomes and epigenomes [37] will provide important insights in understanding genetic and epigenetic coding. By combining and linking this huge set of genotyping data with established clinical data using new powerful computational strategies and network models [3,38], we will be able to explore molecular mechanisms driving diseases pathogenesis. Such innovative developments shape current rational approaches for developing robust biomarkers for individualized risks predictions, screening and effective prevention of major common diseases [5].

Conclusion

Innovation is the key value driving health improvement. However, when the scientific background and evidence of new biomarkers is weak and the clinical validity and utility of these medical tests is still lacking, such as in the case of current DTC personal genomic tests, caution is suggested given that their clinical use could provide more harms than benefits.

Financial & competing interests disclosure

The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.