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Home / Health / Long COVID Genes Unlocked: Breakthrough Offers Hope

Long COVID Genes Unlocked: Breakthrough Offers Hope

20 Dec

•

Summary

  • Researchers identified 32 genes causing long COVID, including 13 new ones.
  • Three distinct long COVID subtypes with unique symptoms were discovered.
  • This breakthrough aids personalized treatment strategies for patients.
Long COVID Genes Unlocked: Breakthrough Offers Hope

An Australian research team has identified 32 genes causally linked to long COVID, marking a significant advancement in understanding the post-viral illness. This discovery includes 13 genes not previously associated with the condition, offering new avenues for therapeutic development. The study, published in PLOS Computational Biology and Critical Reviews in Clinical Laboratory Sciences, also uncovered three distinct subtypes of long COVID based on symptoms and underlying biology, potentially explaining its diverse manifestations.

This breakthrough offers hope for more personalized treatment approaches. Long COVID, a complex condition affecting multiple organ systems, can persist for months or years post-infection, with symptoms ranging from severe fatigue to cognitive impairment. The new genetic insights are expected to guide the development of customized management strategies, moving beyond 'one-size-fits-all' treatments.

The research employed a novel analytical framework combining Mendelian Randomization and Control Theory with multi-omics data to establish causal links rather than mere associations. This platform has been made freely available to the scientific community for further validation and research, fostering global collaboration in the fight against long COVID.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
They identified 32 genes causally linked to long COVID, including 13 new ones, and found three distinct symptom-based subtypes.
The discovery will help develop customized management and treatment strategies, improving patient outcomes.
They combined Mendelian Randomization, Control Theory, and multi-omics data to identify causal genes.

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