In a report recently published in the journal Nature Communications, scientists at IBM, the Broad Institute of MIT and Harvard, and Color, a medical tech firm, have demonstrated in-depth that the existence of genetic mutations is not a valid guide to genetic disorders. Researchers believe that diseases may be so strongly influenced by certain causes that the threat in carriers is just as minimal as in non-carriers.
The research is a result of a three-year alliance between IBM Research and the Broad Institute. They revealed their innovative attempt in the year 2019 and aimed to enable physicians to use data to help recognize patients at high risk for illnesses such as cardiovascular disorder. Insights could be important in health care and prevention, helping clinicians choose whether to recommend imaging or to recommend even delicate surgery like that of mastectomies.
In the research process, the IBM-led team developed models to examine individual genetic risk factors, clinical health history, and biomarker evidence to more reliably forecast the occurrence of disorders such as heart attacks, premature cardiac failure, and atrial fibrillation.
The research examined how the polygenic background variations and influences inside the human genome could affect the incidence of disease in genetic disorders such as familial hypercholesterolemia, inherited breast and ovarian cancer, and Lynch syndrome.
The co-authors analyzed unidentified records from over 80,000 patients across two large volumes of data, UK Biobank and Color’s own. The carriers of monogenic risk variants identified “substantial variations” of risk based on polygenic background, implying that carriers do not always develop diseases.
The use of voluminous data sets to integrate and interpret medical and genomic data from hundreds of thousands of individuals has enabled the team to shed considerable new light on a variety of severe, chronic diseases, said IBM Research Senior Scientist and co-author Kenney Ng. He has further clarified the results of the study which reveals that even though a person has a genetic disorder linked with one of these disorders, their total probability may not be as set in stone as commonly assumed. In fact, the absolute risk may be almost equivalent to an entity that does not hold a mutation at all depending on some other aspects and mutations within their particular genome.
IBM says future work will include exploring how genomics, clinical data, and AI can be used to build innovative tools that provide health professionals with insight into disease risk. The goal is to create algorithms that reliably identify a predisposition to a health disorder. They make such techniques available including the methods for measuring the probability of illness in individuals dependent on variants in the genome.
IBM also already partnered with the Broad Institute in 2016. As a part of a five-year initiative, the organization aimed to support researchers use AI and genomics. They further wish to expand their scope of studies about how cancers are increasingly immune to therapies.
