NIH Deep Phenotyping and Multimodal Studies

1 Walitt et al. 2024 — Deep Phenotyping Study

Full Citation:: Walitt B, Singh K, LaMunion SR, et al. Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome. Nature Communications. 2024;15(1):907. (Walitt et al. 2024) DOI:: 10.1038/s41467-024-45107-3 Key Findings::

- Altered effort preference rather than physical or central fatigue
- CSF catechol abnormalities; B-cell abnormalities; sex-specific gene expression
- Reduced peak VO~2~ and chronotropic incompetence on CPET

Relevance to Part V:: Foundational multimodal dataset for integrated systems models; provides simultaneous immune, metabolic, and neurological parameters.

2 Heng et al. 2025 — Mapping the Complexity of ME/CFS

Full Citation:: Heng RB, Gunasegaran B, Krishnamurthy S, et al. Mapping the complexity of ME/CFS: Evidence for abnormal energy metabolism, altered immune profile, and vascular dysfunction. Cell Reports Medicine. 2025;6(12):102514. (Heng et al. 2025) DOI:: 10.1016/j.xcrm.2025.102514 Key Findings::

- Multi-omics evidence for abnormal energy metabolism, altered immune profile, and vascular dysfunction
- Integrates multiple pathophysiological domains in a single cohort

Relevance to Part V:: Key data source for integrated systems models linking energy, immune, and vascular subsystems.

3 DecodeME 2025 — ME/CFS Genome-Wide Association Study

Full Citation:: DecodeME Consortium, Ponting CP, et al. Initial Findings from the DecodeME Genome-Wide Association Study of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. medRxiv. 2025. (DecodeME Consortium, Ponting, et al. 2025) DOI:: 10.1101/2025.01.13.25320567 Key Findings::

- Largest ME/CFS GWAS to date ($n$=21,620)
- Preprint; identifies genetic risk loci for ME/CFS

Relevance to Part V:: Genetic architecture data for modeling genetic susceptibility and gene–environment interactions.

References

DecodeME Consortium, Chris P Ponting, et al. 2025. “Initial Findings from the DecodeME Genome-Wide Association Study of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.” medRxiv. https://doi.org/10.1101/2025.08.06.25333109v1.
Heng, Ruiwen Benjamin, Bavani Gunasegaran, Shivani Krishnamurthy, Sonia Bustamante, Ananda Staats, Sharron Chow, Seong Beom Ahn, et al. 2025. “Mapping the Complexity of ME/CFS: Evidence for Abnormal Energy Metabolism, Altered Immune Profile, and Vascular Dysfunction.” Cell Reports Medicine 6 (12): 102514. https://doi.org/10.1016/j.xcrm.2025.102514.
Walitt, Brian, Komudi Singh, Samuel R LaMunion, Mark Hallett, Sandra Jacobson, Kong Chen, Yoshihisa Enose-Akahata, et al. 2024. “Deep Phenotyping of Post-Infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.” Nature Communications 15 (1): 907. https://doi.org/10.1038/s41467-024-45107-3.