In 2006, a forward-thinking article described the emerging field of medical genomics and its potential to transform healthcare. The article, written by Mark Bouzyk, was published in Emory’s Momentum magazine and focused on the establishment of biobanks, the falling costs of genetic sequencing, and the promise of personalized medicine. Looking back since 2025, it is surprising to see how many of those predictions have not only come true, but have exceeded even the most optimistic expectations of that time.
The cost revolution: even more dramatic than expected
In 2006, the article noted that “sequencing and genotyping costs have been greatly reduced” and that “high-throughput genetic analysis is within the budget of many typical NIH RO1 research grants.” At the time, this represented a significant advance; Genetic analysis was finally becoming accessible to mainstream researchers.
The reality of 2025 has far exceeded those predictions. What cost thousands of dollars per genome in 2006 now costs only hundreds and, in some cases, even less. Whole genome sequencing, which once required years and billions of dollars, can now be completed in days for less than $1,000. Some companies offer consumer genetic testing for less than $100. The cost drop was not only considerable: it was revolutionary, being reduced by factors of thousands rather than incremental improvements.
Personalized medicine: from concept to clinical reality
The 2006 article described pharmaceutical companies exploring how “genetic variations indicate which people are better candidates for a particular drug.” This concept, known as pharmacogenomics, was largely theoretical at the time, and companies began “identifying who has the greatest potential to do well with a drug” to better select participants in clinical trials.
In 2025, pharmacogenomics has become standard practice in many therapeutic areas. Oncology leads the way, and genetic testing routinely determines which cancer patients will respond to specific targeted therapies. Medications for cardiovascular disease, mental health conditions, and many other disorders now come with companion diagnostics that test patients’ genetic profiles before prescribing them. Bouzyk’s vision of using genetic analysis “to benefit entire populations of people” has been realized through population-level genetic studies that have identified risk factors for diseases ranging from Alzheimer’s disease to diabetes, enabling preventive interventions that were impossible in 2006.
The biobanking revolution: the prediction comes true
Perhaps the most prescient aspect of the 2006 article was its discussion of biobanks, large-scale repositories of biological samples linked to demographic and health information. The article notes that “medical centers across the country are struggling to find ways to collect genetic data” and that successful centers “enjoy a clear advantage when it comes to seeking federal support and other research funding.”
This prediction turned out to be remarkably accurate. Today, biobanks have become cornerstones of genetic research around the world. The UK Biobank, launched in 2006, now contains genetic and health data from 500,000 participants and has contributed to thousands of scientific discoveries. The NIH’s All of Us research program aims to collect data from one million Americans. China’s National Gene Bank stores billions of biological samples. Virtually all major medical centers now maintain biorepositories, precisely as the article anticipated.
Concern about “dealing with issues such as IT, sample information, distribution status and consent” proved equally prescient. These ethical and logistical challenges have dominated discussions about biobanking for two decades, leading to new frameworks for informed consent, data-sharing agreements, and privacy protections.
SNP and diseases: explosion of knowledge
The 2006 paper looked at single nucleotide polymorphisms (SNPs). He noted that “more than 10 million SNPs have been identified and mapped in the human genome,” suggesting that the study of these variations “can provide important information about genetic predisposition to disease.”
This prediction grossly underestimated what would happen. Since then, genome-wide association studies have identified hundreds of thousands of genetic variants associated with diseases and traits. The databases now catalog more than 100 million SNPs. The field has moved beyond simple associations toward the use of complex polygenic risk scores that combine information from thousands of variants to predict disease risk with increasing accuracy.
Research on health disparities: complex reality
The article mentioned interest in examining why African Americans experience higher rates of disorders such as stroke and heart disease, suggesting it was important to understand “possible genetic factors that could play a role in such disparities.”
This area has revealed greater complexity than expected. Research has shown that health disparities are primarily attributable to social determinants of health, environmental factors, and access to health care rather than genetic differences. While some genetic variants show different frequencies across populations, the medical community now recognizes that focusing too much on genetic explanations can obscure the larger roles of systemic racism, poverty, and unequal access to care.
Modern genomics has also addressed the troubling reality that most genetic studies historically focused on populations of European ancestry, creating biases in databases. Efforts to increase diversity in genetic research have accelerated, although important gaps remain.
Clinical translation: faster than expected
The 2006 paper described plans to “rapidly translate new genetic knowledge into new diagnostic tools,” envisioning that “if we find that a gene is linked to a particular disease or condition, then we can develop a diagnostic test and pass it on.”
Indeed, this bench-to-bedside process has materialized, but faster than anticipated. Genetic testing is now clinically available for thousands of conditions. Newborn screening panels test for dozens of genetic disorders. Carrier screening for prospective parents has become routine. Prenatal genetic testing has moved toward comprehensive whole-exome sequencing. Cancer patients routinely receive tumor genetic profiles to guide treatment decisions.
Information exchange: largely carried out
The vision that biobank information “could be shared over the Internet, allowing researchers around the world to find samples that would potentially aid their research” has essentially become a reality. Platforms such as dbGaP and the European Genome-Phenomarch Archive now allow global data exchange between qualified researchers.
However, the initially intended openness has been tempered by concerns about privacy and the recognition that participants must have significant control over how their genetic information is used. The balance between open science and protection of participants remains an active policy area.
The Verdict: Remarkably Accurate
Looking back twenty years, the 2006 paper’s predictions about the future of genomics were surprisingly accurate. The falling costs of sequencing, the rise of personalized medicine, the importance of biobanks, and the translation of genetic discoveries into clinical tools have largely materialized as planned.
If anything, the article was too conservative in its optimism. The genomics revolution has advanced faster, penetrated deeper into clinical practice, and generated more data than even the forward-thinking experts of 2006 could have imagined. The “enormous untapped potential of clinical genetics” described two decades ago has been substantially realized, although in fact there is still enormous potential.
The vision articulated in 2006 will become a reality in 2025, validating investments in genomic infrastructure, biobanks and translational research. As we look to the next twenty years, the foundation laid by pioneers in this field promises even more dramatic advances in our understanding of human genetics and our ability to prevent, diagnose and treat diseases based on each individual’s unique genetic blueprint.
