All ETDs from UAB

Advisory Committee Chair

Jarred Younger

Advisory Committee Members

Sylvie Mrug

Chengcui Zhang

Da Yan

Document Type

Thesis

Date of Award

2023

Degree Name by School

Master of Arts (MA) College of Arts and Sciences

Abstract

Background: There are no established etiologies, biomarkers, or approved treatments for myalgicencephalomyelitis/chronic fatigue syndrome (ME/CFS). It is thought that the ME/CFS criteria may be diagnosing individuals within a spectrum of different disease states, or even different diseases. There likely exist shared mechanisms across idiopathic pain and fatigue disorders, and diverse mechanisms underneath each individual diagnosis. The need to compare ME/CFS to similar, overlapping, and distinct disorders is a critical element in progressing our understanding of idiopathic pain and fatigue. Methods: A total of 2,731 comprehensive medical history and symptom reports were collected from respondents across the globe with a variety of diagnoses. The agreement between reporting an ME/CFS diagnosis and meeting ME/CFS criteria was assessed with Cohen’s Kappa. Dimension reduction was performed with principal component analysis and transdiagnostic clusters of pain and fatigue were investigated with unsupervised gaussian mixture models. Prior subtyping efforts were replicated with latent class analysis. Results: The agreement between meeting ME/CFS criteria and reporting an ME/CFS diagnosis was slight (κ = 0.107; SE = 0.024). Gaussian mixture modeling of a wide range of ME/CFS symptoms resulted in a five-cluster solution. Clustering of pain, fatigue, and gastrointestinal symptoms resulted in a nine-cluster solution. Healthy participants were clustered together, while ME/CFS patients did not comprise a distinct cluster. Latent class analysis of non-core symptoms in ME/CFS resulted in a 5-class solution similar to what has been previously reported. Conclusion: Results support the notion that the ME/CFS diagnosis captures a wide range of symptom profiles. Conceptualizing and assessing these groups as a singular entity may hinder research progress towards identifying biomarkers and etiologies.

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