Are there subgroups of chronic fatigue syndrome? An exploratory cluster analysis of biological markers

Tarjei Tørre Asprusten, Line Sletner, Vegard Bruun Bratholm Wyller, Tarjei Tørre Asprusten, Line Sletner, Vegard Bruun Bratholm Wyller

Abstract

Background: Chronic fatigue syndrome (CFS) is defined according to subjective symptoms only, and several conflicting case definition exist. Previous research has discovered certain biological alterations. The aim of the present study was to explore possible subgroups based on biological markers within a widely defined cohort of adolescent CFS patients and investigate to what extent eventual subgroups are associated with other variables.

Methods: The Norwegian Study of Chronic Fatigue Syndrome in Adolescents: Pathophysiology and Intervention Trial (NorCAPITAL) has previously performed detailed investigation of immunological, autonomic, neuroendocrine, cognitive and sensory processing functions in an adolescent group of CFS patients recruited according to wide diagnostic criteria. In the present study, hierarchical cluster analyses (Ward's method) were performed using representative variables from all these domains. Associations between clusters and constitutional factors (including candidate genetic markers), diagnostic criteria, subjective symptoms and prognosis were explored by standard statistical methods.

Results: A total of 116 patients (26.7% males, mean age 15.4 years) were included. The final cluster analyses revealed six clusters labelled pain tolerant & good cognitions, restored HPA dynamics, orthostatic intolerance, low-grade inflammation, pain intolerant & poor cognitions, and high vagal (parasympathetic) activity, respectively. There was substantial overlap between clusters. The pain intolerant & poor cognitions-cluster was associated with low functional abilities and quality of life, and adherence to the Canada 2003 diagnostic criteria for CFS. No other statistically significant cluster associations were discovered.

Conclusion: Within a widely defined cohort of adolescent CFS patients, clusters could be delineated, but no distinct subgroups could be identified. Associations between clusters and constitutional factors, subjective symptoms and prognosis were scarce. These results question the clinical usefulness of searching for CFS subgroups, as well as the validity of the most "narrow" CFS diagnostic criteria.

Trial registration: Clinical Trials NCT01040429.

Keywords: Adolescent; Chronic fatigue syndrome; Cluster analysis; Diagnostic criteria.

Conflict of interest statement

The authors declare that that they have no competing interests.

Figures

Fig. 1
Fig. 1
Number of variables before and after correlation analyses. A total of 69 different biomarkers was selected from the NorCAPITAL database and grouped into five domains (upper row): Endocrine, inflammatory, cardiovascular, pressure pain threshold, and cognitions. Correlation analyses among variables within each domain were performed. When two or more variables were strongly correlated (correlation coefficient ≥ 0.7), the variable considered most suitable for further analyses was carried over. Then, a final correlation analysis of all remaining variables from each domain were performed, resulting in a total of 37 variables across each of the five groups (lower row) which become the basis for subsequent cluster analyses
Fig. 2
Fig. 2
Final cluster solution and cluster characterizations. Dendrogram displaying the final cluster solution, revealing six clusters based on a total of 10 variables (each vertical bar on the x-axis corresponds to one individual). The clusters were labelled according to results presented in Table 2 (cf. manuscript for further details): The pain tolerant & good cognitions-cluster (C1) is characterized by high pressure pain threshold levels and high scores on cognitive function tests. The restored HPA dynamics-cluster (C2) is characterized by high urine cortisol:creatinin ratio. The orthostatic intolerance-cluster (C3) is characterized by a strong tachycardia response and corresponding fall in stroke volume during orthostatic challenge. The low-grade inflammation-cluster (C4) is characterized by high levels of interferon gamma (INFγ) and interferon gamma-induced protein 10 (IP-10). The pain intolerant & poor cognitions-cluster (C5) is characterized by low pressure pain threshold levels and low scores on cognitive function tests. The high vagal activity-cluster (C6) is characterized by high heart rate variability within the high-frequency (HF) domain
Fig. 3
Fig. 3
Scatterplot of the three most important variables for the final cluster formation. Each colored dot represents one individual belonging to one of the six clusters from the final cluster solution. Even though the three most important variables driving the cluster formation are used as coordinates, there is substantial overlap between the clusters

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