Scientists find genome sequencing useful in predicting disease

Genome sequencing is used to diagnose cancer and customise the treatments in the patients. But scientists have devised a formula that can used to predict diseases too.

By: Sudhakar Jha | | Published: September 7, 2018 3:48 pm

Genome sequencing is the way of determining the identity of DNA © Shutterstock

Genome sequencing is the way of determining the identity of DNA the order of As, Cs, Gs and Ts that make an organism s DNA. For your information, a human s DNA is made up of 3 million such genetic letters! Till now, genetic profiling is done on cancer patients to determine the DNA changes that led to cancer. However, a team of scientists have worked on the same model to figure out if it can be used to predict diseases as well. Also Read - Genome sequencing for all international patients if tested Covid-19 positive: Why it is needed?

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Michael Snyder, PhD, professor and chairperson of genetics at Stanford, and his colleagues have devised a procedure that includes genetic sequences and electronic health information to check the likelihood of a person having a certain genetic disease. Also Read - World Down Syndrome Day: Know all about this condition

For the study, the team began with a condition called abdominal aortic aneurysm, or AAA, that affects more than 3 million people every year, can be caused by genetic factors, and is hard to detect.

Published in the journal Cell, Dr. Snyder and Dr. Philip Tsao, PhD, professor of medicine at Stanford, said their method seeks to identify any likely disease-causing culprits in an ‘agnostic’ manner. The process searches the genetic information from patients with AAA and looks for the commonalities in them.

Dr. Snyder, in the paper, said that it was the key to unravelling any number of genetic diseases. It was not often the case that one, two or even a handful of genes could take the sole responsibility for a condition. It was far more likely that there was whole bunch of them that caused the condition.

The algorithm, called Hierarchical Estimate From Agnostic Learning, or HEAL, engages a form of artificial intelligence called machine learning, which shows that this approach could identify the molecular patterns that convey risk for genetic diseases.

Dr Snyder added that HEAL could identify the diseases that have ‘red flag’ genomic markers. The team is now planning to use HEAL to help understand the genetic signatures of preterm birth and autism, two conditions whose genetic foundations remain gloomy.

Published : September 7, 2018 3:48 pm

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