Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis.

Journal: medRxiv : the preprint server for health sciences
Published Date: May 11, 2025

Abstract

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemic disease defined by a suite of symptoms, including unexplained persistent fatigue, post-exertional malaise (PEM), cognitive impairment, myalgia, orthostatic intolerance, and unrefreshing sleep. The disease mechanism of ME/CFS is unknown, with no effective curative treatments. In this study, we present a multi-site ME/CFS whole-genome analysis, which is powered by a novel deep learning framework, HEAL2. We show that HEAL2 not only has predictive value for ME/CFS based on personal rare variants, but also links genetic risk to various ME/CFS-associated symptoms. Model interpretation of HEAL2 identifies 115 ME/CFS-risk genes that exhibit significant intolerance to loss-of-function (LoF) mutations. Transcriptome and network analyses highlight the functional importance of these genes across a wide range of tissues and cell types, including the central nervous system (CNS) and immune cells. Patient-derived multi-omics data implicate reduced expression of ME/CFS risk genes within ME/CFS patients, including in the plasma proteome, and the transcriptomes of B and T cells, especially cytotoxic CD4 T cells, supporting their disease relevance. Pan-phenotype analysis of ME/CFS genes further reveals the genetic correlation between ME/CFS and other complex diseases and traits, including depression and long COVID-19. Overall, HEAL2 provides a candidate genetic-based diagnostic tool for ME/CFS, and our findings contribute to a comprehensive understanding of the genetic, molecular, and cellular basis of ME/CFS, yielding novel insights into therapeutic targets. Our deep learning model also offers a potent, broadly applicable framework for parallel rare variant analysis and genetic prediction for other complex diseases and traits.

Authors

  • Sai Zhang
    Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China.
  • Fereshteh Jahanbani
    Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Varuna Chander
    Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Martin Kjellberg
    Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Menghui Liu
    Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Katherine A Glass
    Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA.
  • David S Iu
    Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA.
  • Faraz Ahmed
    School of Dental Sciences, Health Campus, Universiti Sains Malaysia (USM), 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.
  • Han Li
  • Rajan Douglas Maynard
    Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Tristan Chou
    Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Johnathan Cooper-Knock
    Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK.
  • Martin Jinye Zhang
    Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Durga Thota
    Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Michael Zeineh
    Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.
  • Jennifer K Grenier
    Genomics Facility, Biotechnology Resource Center, Cornell University, Ithaca, NY, USA.
  • Andrew Grimson
    Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA.
  • Maureen R Hanson
    Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA.
  • Michael P Snyder
    Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA.

Keywords

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