Genetics, Personalized Medicine, and Clinical Epidemiology
Expectations, validity, and reality in omics

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Abstract

Diverse methods of large-scale measurements of biological processes have emerged in the last 15 years and their list is growing rapidly. Almost invariably, these advances in omics have been associated with major expectations of transforming not only biological knowledge but also medicine and health. However, practical applications of omics in biomedicine have often suffered from poor attention to issues of validity. As a consequence, major promises of personalized medicine have not yet materialized in improving patient or population outcomes. Several omics fields increasingly realize the need to safeguard the validity of their efforts, make reporting more transparent, and improve the translational potential of their studies. Many discoveries point indeed toward a highly individualized profile of health and disease, where each case is different, but this is currently difficult to translate into more effective personalized treatment or prevention. Given the exponential growth of collected data, understanding is often drowning in the sea of measurements.

Section snippets

The omics epidemics in the scientific literature

What is new?

  • The commentary discusses the expectations of the omics revolution in biosciences and how these may fail to match the validity and reality of this research.

Biomedical research has been transformed recently by the exponential increase in the ability to measure biological variables of interest in grand scale. The revolution has not affected only the basic laboratory sciences. According to the Institute for Scientific Information, three of the eight original articles that are most cited

Expectations of omics for medicine and health

Omics expect to transform the very essence of medicine and the way health is pursued—maybe even to the point where health is pursued by omics-savvy citizens themselves, without the need for organized medicine and physicians. The expectations include improvements in diagnosis, prognosis, prediction, treatment choice, individualized prevention, and eventually better outcomes [5]. A common denominator in omics is “personalized medicine”, the wish to tailor interventions to single individuals.

In search of validity in omics

Several omics fields increasingly realize the need to safeguard the validity of their research efforts. Having more complex measurements means having more opportunities for errors and biases. There is variability in the stringency required for performing, reporting, and validating omics research in different fields. For example, genome-wide association studies have routinely adopted replication as a sine qua non and stringent criteria of statistical significance adjusting for multiplicity are

Reality in omics

The reality about omics is still in the making. False-positive claims are common in many disciplines [28], and true-positive discoveries have difficulty in getting translated into useful clinical applications. Obstacles in translation include the following: small effects, unclear incremental value beyond standard knowledge and standard interventions, unclear cost-effectiveness, and gaps in knowledge how to use and interpret these technologies in everyday life and practice [4], [29]. Clearly

Individualized profiles: good or bad news?

Several applications of newer technologies realize increasingly how indeed individualized the profile of each person is. Almost each case may be different. For example, as shown by the Cancer Genome Atlas and related studies integrating information on copy number variation, gene expression profiling, and DNA methylation profiles, almost each glioblastoma seems to have its own spectrum of genetic alterations and these may affect a large number of different genes [42], [43]. Similarly, much of

Drowning in measurements?

In all, even if the claims of immediate medical utility are apparently overstated, omics are fascinating science. The wealth of information is astonishing and even intoxicating. Omics are here to stay—or actually to grow even more complex. However, the increase in the amount of information is such that we are already unable to perform some of the analyses that a seasoned epidemiologist would be tempted to do. For example, forget about evaluating in full-scale three-way interactions on a

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