(254) Gene expression factor analysis differentiates pathways linked to pain, fatigue, and depression in a diverse patient sample

Chronic Fatigue Syndrome (CFS) and Fibromyalgia (FMS) are complex and often debilitating disorders with a range of co-morbidities. Previous research using quantitative mRNA leukocyte gene expression has demonstrated CFS and FMS showed markedly different expression in a large number of individual genes in response to a moderate exercise task compared to healthy people, but differences at resting baseline were few. The major goal of this exploratory study was to examine if we could group baseline expression of genes into meaningful biological factors and if these factors were associated pain and/or depression, which is a common mood co-morbidity in CFS and FMS. We included a total of 261 individuals including healthy controls (n=62), patients with FMS only (n=15), CFS only (n=33), Co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression, and assessed expression of 41 candidate genes. Exploratory factor analysis resulted in 4 independent factors, the first two with 13 genes each and last two with 6-8 genes with minimal overlap of genes between factors. We labeled these factors by function as: 1) Metabolite detecting and immune response; 2) Ion channels and cellular modulators; 3) Energy and adrenergic function and; 4) Neuronal growth and immune function. Regression analysis was then conducted with these biological factors as the dependent variables and presence of fatigue, pain, depression diagnosis, depression severity, age, and sex, as predictor variables. We found that pain and fatigue were specifically associated with Factor 2, depression diagnosis with Factor 4, and depression severity with Factors 3 and 4. These results suggest that depression and pain/fatigue may be related to dysregulation of different sets of genes. If these differences are validated in future data sets, they could be critical in helping to define clinically relevant patient subgroups and in the assessment and development of subgroup-specific treatment interventions. Chronic Fatigue Syndrome (CFS) and Fibromyalgia (FMS) are complex and often debilitating disorders with a range of co-morbidities. Previous research using quantitative mRNA leukocyte gene expression has demonstrated CFS and FMS showed markedly different expression in a large number of individual genes in response to a moderate exercise task compared to healthy people, but differences at resting baseline were few. The major goal of this exploratory study was to examine if we could group baseline expression of genes into meaningful biological factors and if these factors were associated pain and/or depression, which is a common mood co-morbidity in CFS and FMS. We included a total of 261 individuals including healthy controls (n=62), patients with FMS only (n=15), CFS only (n=33), Co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression, and assessed expression of 41 candidate genes. Exploratory factor analysis resulted in 4 independent factors, the first two with 13 genes each and last two with 6-8 genes with minimal overlap of genes between factors. We labeled these factors by function as: 1) Metabolite detecting and immune response; 2) Ion channels and cellular modulators; 3) Energy and adrenergic function and; 4) Neuronal growth and immune function. Regression analysis was then conducted with these biological factors as the dependent variables and presence of fatigue, pain, depression diagnosis, depression severity, age, and sex, as predictor variables. We found that pain and fatigue were specifically associated with Factor 2, depression diagnosis with Factor 4, and depression severity with Factors 3 and 4. These results suggest that depression and pain/fatigue may be related to dysregulation of different sets of genes. If these differences are validated in future data sets, they could be critical in helping to define clinically relevant patient subgroups and in the assessment and development of subgroup-specific treatment interventions.