Revealing The Genetic Code : AI Aids In New Discovery About Psychiatric Disorders

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Medical science is pretty vast, where we have many unanswered questions. With the advancement of technology and AI in today's world, scientists and researchers are leaving no stone unturned to find answers to these questions. One such question is about common psychiatric disorders and a genetics study has uncovered the mystery behind it. Let's know more about that.

Photo Credit: Image is AI-generated

A Breakthrough In Genetics Research

Many genetic studies may have discovered new genes are a root cause of common psychiatric disorders but no one gene determines a person's risk of developing disorders like schizophrenia or bipolar disorder. It is more likely that a host of genes contribute to this risk.

Now with the help of AI, researchers at Stanford University have uncovered complex variants throughout the human genome that in all probability contributes to these psychiatric disorders. Their new study suggests that mutations occur after fertilisation, like genetic mosaicism (two or more genetically distinct cell populations can be seen in the body like two different colour eyes) that can be responsible for many disorders that also include schizophrenia and bipolar disorder.

Genes At Work

Picture this. A Genome offers instructions for every cell in our body where our genes are the chapters. About 20,000 genes give instructions to make proteins, the building blocks of life while the majority of our genes are non-coding, which means they do not give these instructions. Despite this, these genes play a significant role in genetics and regulating cell function.

Genetic variants in a coding or non-coding region can interfere with how the cell translates specific instructions. If there are no correct instructions to produce specific proteins, it can contribute to disorders that affect different aspects of our body.

About The Study

Researcher Zhou et. al compared the genomes of over 4,000 individuals around the world and their entire DNA sequence was extracted using whole genome sequencing. The data received was then uploaded into an AI algorithm that was trained to recognize many genomes across diverse ancestry which allowed them to match large, complex gene variants with specific disorders.

They tried an approach called Genome-Wide Association Study (GWAS) that included individuals with bipolar disorder or schizophrenia who were compared to a cohort of healthy controls. Though this approach can show us the location of the variants, the information is not always precise. The AI algorithm developed by Zhou et. al showcases specificity.

The AI tool identified more than 8,000 complex variants with more than 85% accuracy. To understand if these variants had any chance of being linked to psychiatric disorders, they extracted DNA from brain tissue samples of individuals that were affected by schizophrenia or bipolar disorder.

These complex variants seemed to overlap with single variants found in other GWA studies of these disorders. Like one complex variant that they found correlated with schizophrenia and bipolar disorder was the length of 4,700 base pairs, which was the basic unit of DNA.

Photo Credit: Image is AI-generated

Such findings and innovations in genetic research deepens our understanding of the human genome. As we analyze the vast amounts of genetic data, AI technology is discovering intricate relationships between large variants and certain psychiatric disorders which leads to a promising pathway for personalized medicine.

Let's wait to see what medical science along with AI has to offer us, as future studies may uncover deeper insights into the genetic causes of an array of psychiatric disorders.

Disclaimer: The information provided in this article is for general informational and educational purposes only and is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or a qualified healthcare provider with any questions you may have regarding a medical condition.