DNA to the rescue
Experts from around the world gathered at IBM Research – Haifa to discuss the application of genetic research to medical diagnostic
Can a simple genetic test provide clues to our chances of staying healthy or getting sick? As scientists learn more about the human genome, new questions come to light. When will our family doctor be able to conduct a simple test to let us know whether or not we’re likely to suffer from hypertension, Parkinson’s, Alzheimer’s, or even mental illness? Apparently, we still have a few years to wait, as concluded by medical experts, machine learning specialists and genetic researchers who gathered to discuss how and when genetic research is likely to be applied to medical care and diagnostics.
The domain of personalized health and genome-based therapy has flourished in recent years due to the significant reduction of information storage devices, the reduction in genome testing costs, and advances in genome testing tools. Data mining and machine learning techniques have been applied to decipher the relationship between clinical status and genomic variations, with the goal of helping improve diagnostics and treatment.
Researchers at the IBM Research Lab in Haifa are involved in a number of clinical genomic analysis projects. In particular, they are focused on one of the most challenging and promising areas of research in this domain: genome-wide analysis (GWA) studies where a set of single nucleotide polymorphisms (SNPs) can be associated with a specific disease.
From the ivory tower to the hospital
This month, researchers at the Haifa lab hosted medical and genetic experts from around the world to discuss how clinical genomic research can be applied to advance today’s healthcare, bringing physicians and patients more accurate information about diseases and their treatment. Over 120 individuals from research institutes, health ministries, hospitals, and universities participated in the Clinical Genomics Analysis workshop, shared information, and discussed how to move forward in this area.
The workshop included a fascinating lineup of speakers and topics including: Postgenomic Era and P4 Medicine: Integrative Systems Biology Approaches by keynote speaker Pierre Baldi, Director, Institute for Genomics and Bioinformatics, University of California, Irvine; Enhancing Genetic Association Studies by Reordering Relevant SNPs by Hani Neuvirth-Telem, researcher at IBM Haifa; From Ivory Tower to Hospital - Bringing Clinical Genomic Research to the Medical Practice, a panel discussion with Jacques Beckmann, Mordechai Muszkat and Fabio Macciardi; The HIV Cohort Data Study: Selection and Assessment of SNP-drug Interactions Affecting Lipid Responses of HIV Patients to Antiretroviral Treatment by Diana Marek, University of Lausanne and Swiss Institute of Bioinformatics.
“We all have different visions about whether or not genetic testing will become a standard part of medical treatment in the coming years,” explained Dr. Michal Rosen–Zvi, manager of machine learning and data mining at IBM Research - Haifa. “Most people agree that it will take time until standard treatments incorporate the complex genetic testing done in research today.”
Genes at work
IBM scientists in Haifa believe that whole genome analysis, a relatively new area and technology, can provide important clues to a person’s general state of health. Although this technology is still in its early stages, most experts feel it will help find the collection of genes that are relevant to specific diseases—and eventually provide a profile for people likely to suffer from certain illnesses.
According to Rosen-Zvi, genetics are already being used to test certain diseases. For example, genetic screening has already become a standard test for HIV sufferers, where a certain drug might be very dangerous for people with particular profile (HLA type in this case) and harmless for others.
“Whole genome analysis presents only one step towards identifying which treatment may be more effective for a certain individual," explained Rosen-Zvi. The research work her team is doing for SNP on chip (pronounced ‘snip on chip’) is another step forward, but probably won’t be used in massive quantities. “Although most of the genetic tests that will be carried out in the next ten years will not be as general as the SNP on chip, they’ll probably be specific genetic tests articulated by these studies.”
Perhaps some years into the future whole gene testing will help provide insight into the genetics, and provide us with general input on the types of diseases a person might suffer from. But do we really want to know?