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Related Concept Videos

Combinatorial Gene Control02:33

Combinatorial Gene Control

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Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
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Genetic risk factors for ME/CFS identified using combinatorial analysis.

Sayoni Das1, Krystyna Taylor1, James Kozubek1

  • 1PrecisionLife Ltd, Long Hanborough, Oxford, UK.

Journal of Translational Medicine
|December 14, 2022
PubMed
Summary
This summary is machine-generated.

This study identifies 14 key genes and 199 SNPs associated with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), offering new genetic insights for diagnosis and treatment. These findings advance understanding of ME/CFS genetic risk factors and potential pathophysiological mechanisms.

Keywords:
BiomarkersCombinatorial analyticsME/CFSNovel targetsPatient stratificationPrecision repositioning

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Area of Science:

  • Genetics
  • Immunology
  • Neuroscience

Background:

  • Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, debilitating disease with unknown causes, diagnostic criteria, and treatments.
  • Identifying genetic risk factors is crucial for understanding ME/CFS pathogenesis and improving patient outcomes.

Purpose of the Study:

  • To investigate the genetic underpinnings of ME/CFS using genome-wide association studies (GWAS) and advanced combinatorial analytics.
  • To identify specific genetic variants and genes associated with ME/CFS and explore their potential roles in disease mechanisms.

Main Methods:

  • Analysis of ME/CFS cohorts from UK Biobank using GWAS and the PrecisionLife combinatorial analytics platform.
  • Case-control design with 1000 cycles of random permutation, including replication experiments with disjoint cohorts.

Main Results:

  • Discovery of 199 single-nucleotide polymorphisms (SNPs) in 14 genes significantly associated with 91% of ME/CFS cases.
  • Identification of 15 clusters of SNPs, representing 84 high-order combinations, with strong statistical significance (p-values down to 1.6 × 10⁻⁷²).
  • Replication of key SNPs in post-viral fatigue syndrome and fibromyalgia cohorts, with noted similarities to genes associated with multiple sclerosis and long COVID.

Conclusions:

  • This research provides the first detailed genetic insights into ME/CFS pathophysiology.
  • The identified genetic factors offer potential for improved diagnostic strategies and novel therapeutic targets for ME/CFS patients.