The future of healthcare is going to be changed and impacted by the use of artificial intelligence (AI), hopefully in beneficial ways. According to an article from McMaster University, researchers from the university are already using AI to spur change in the field of rare disease. After a patient presented with complex neurological symptoms, and later enrolled in a Care4Rare study, the McMaster research team identified a previously unknown form of spinocerebellar ataxia (SCA). To learn more about their findings, take a look at Human Genome Variation.

Identifying a Novel Disease Form

In 2014, a patient was first looked over by Dr. Mark Tarnopolsky, a Professor and Division Head of Neuromuscular and Neurometabolic Disorders in the Department of Pediatrics at McMaster University. The patient, and the patient’s family members, all provided Dr. Tarnopolsky with blood and skin samples. They also all underwent different testing.

Dr. Tarnopolsky and his team then used artificial intelligence – and in particular, machine learning algorithms – to evaluate microscopy images for signs of genetic alterations or variants. SAS explains that machine learning is:

a method of data analysis that automates analytical model building. It is…based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention.

In the case of genetics or genetic evaluation, machine learning is particularly helpful as it can identify potential variants or mutations that cannot be seen just through human evaluation. In the Care4Rare study, the patient also underwent whole-exome sequencing to determine potential genetic mutations. Altogether, the research showed that the patient had two gene mutations – ATXN7 and TOP1MT – which, together, prompted cell dysfunction and ataxia-related symptoms. 

To ensure the reliability of the findings, researchers also evaluated the gene mutations in fruit flies. When engineering flies with combination ATXN7 and TOP1MT mutations, the researchers saw similar symptoms and cellular dysfunction. 

Ultimately, the McMaster research team hopes that these findings can help others who are experiencing symptoms relating to spinocerebellar ataxia, but who cannot be diagnosed given the current understanding of SCA. 

What is Spinocerebellar Ataxia (SCA)?

Spinocerebellar ataxia (SCA) refers to a group of progressive hereditary conditions which occur when parts of the nervous system which control movement become damaged. The different forms of SCA are caused by different gene mutations; in some cases, the gene mutation or cause is still unknown. Regardless, SCA can cause degenerative changes in areas of the brain and spinal cord which control movement, causing poor coordination, difficulty with speech, and problems with fine motor skills. 

Altogether, there are multiple different forms of SCA, some of which have different age onsets and symptoms. However, SCA often manifests after age 18. Potential symptoms can include:

• An irregular gait
• Involuntary eye movements
• Impaired hand-eye coordination
• Slow or slurred speech
• Difficulty processing, learning, and/or remembering information
• Problems with balance
• Difficulty swallowing
• Peripheral neuropathy
• Loss of bladder control