Tag: gene subtypes

Gene Expression Factor Analysis to Differentiate Pathways Linked to Fibromyalgia, Chronic Fatigue Syndrome, and Depression in a Diverse Patient Sample

Abstract:

OBJECTIVE: To determine if independent candidate genes can be grouped into meaningful biologic factors, and whether these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia syndrome (FMS), while controlling for comorbid depression, sex, and age.

METHODS: We included leukocyte messenger RNA gene expression from a total of 261 individuals, including healthy controls (n = 61), patients with FMS only (n = 15), with CFS only (n = 33), with comorbid CFS and FMS (n = 79), and with medication-resistant (n = 42) or medication-responsive (n = 31) depression. We used exploratory factor analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine whether these factors were associated with specific diagnoses.

RESULTS: EFA resulted in 4 independent factors with minimal overlap of genes between factors, explaining 51% of the variance. We labeled these factors by function as 1) purinergic and cellular modulators, 2) neuronal growth and immune function, 3) nociception and stress mediators, and 4) energy and mitochondrial function. Regression analysis predicting these biologic factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (Quick Inventory for Depression Symptomatology score), but not associated with FMS.

CONCLUSION: Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters, but in opposite directions, when controlling for comorbid FMS. Given high comorbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression.

© 2016, American College of Rheumatology.

 

Source: Iacob E, Light AR, Donaldson GW, Okifuji A, Hughen RW, White AT, Light KC. Gene Expression Factor Analysis to Differentiate Pathways Linked to Fibromyalgia, Chronic Fatigue Syndrome, and Depression in a Diverse Patient Sample. Arthritis Care Res (Hoboken). 2016 Jan;68(1):132-40. doi: 10.1002/acr.22639. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4684820/ (Full article)

 

Gene profiling of patients with chronic fatigue syndrome/myalgic encephalomyelitis

Abstract:

Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) is a multisystem disease, the pathogenesis of which remains undetermined. Following two microarray studies, we reported the differential expression of 88 human genes in patients with CFS; 85 of these genes were upregulated and 3 were downregulated.

The top functional categories of these 88 genes were hematologic disease and function, immunologic disease and function, cancer, cell death, immune response, and infection. Clustering of quantitative polymerase chain reaction data from CFS/ME patients revealed seven subtypes with distinct differences in Short Form (SF)-36 scores, clinical phenotypes, and severity. Gene signatures in each subtype implicate five human genes as possible targets for specific therapy.

Development of a diagnostic test for subtype status is now a priority. The possibility that these subtypes represent individual host responses to particular microbial infections is being investigated and may provide another route to specific therapies for CFS patients.

 

Source: Kerr JR. Gene profiling of patients with chronic fatigue syndrome/myalgic encephalomyelitis. Curr Rheumatol Rep. 2008 Dec;10(6):482-91. https://www.ncbi.nlm.nih.gov/pubmed/19007540