mariovitali
Senior Member
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@Murph something related to my confirmation bias ;-)
Interestingly, hepatic fibrosis is mentioned in the paper :
and to be fair :
A predictive algorithm to identify genes that discriminate individuals with fibromyalgia syndrome diagnosis from healthy controls
A predictive algorithm to identify genes that discriminate individuals with fibromyalgia syndrome di
Objectives: Fibromyalgia syndrome (FMS) is a chronic and often debilitating condition that is characterized by persistent fatigue, pain, bowel abnormalities, and sleep disturbances. Currently, there are no definitive prognostic or diagnostic biomarkers for FMS. This study attempted to utilize a novel predictive algorithm to identify a group of genes whose differential expression discriminated individuals with FMS diagnosis from healthy controls.
Results: The small-scale signature contained 57 genes whose expressions were highly discriminatory of the FMS diagnosis. The combination of these high discriminatory genes with FR higher than 1.45 provided a leave-one-out-cross-validation accuracy for the FMS diagnosis of 85.11%. The discriminatory genes were associated with 3 canonical pathways: hepatic stellate cell activation, oxidative phosphorylation, and airway pathology related to COPD.
Interestingly, hepatic fibrosis is mentioned in the paper :
and to be fair :
Follow-up studies are warranted to address several limitations of the study. There is a very high likelihood that the list of genes generated in this study maybe artifacts of over training on a single cohort of a small number of patients. For the findings to have clinical and diagnostic utilities, the predictive genes must be validated in a larger, independent cohort of patients with FMS. Further, future studies should account the overlap of FMS and ME/CFS diagnoses in the symptom presentation of study participants and for the presence of other medical comorbidities. In addition, the selected differentially expressed genes were obtained from raw microarray data, basing on our previous finding that using raw microarray data can better generate genetic signatures that are associated with functional pathways that are a priori known for specific medical conditions.39 Future studies should consider using preprocessing techniques, such as Robust Microarray Average, to determine if similar discriminatory genes can be identified.