Principal component analysis of blood microRNA datasets facilitates diagnosis of diverse diseases
Fig 5
(A) Principal component analysis (PCA) and hierarchical clustering heatmap of blood monocyte miRNA expression profiles in chronic HIV (CHI), Long-term non-progressor (LTNP, HIV positive but asymptomatic) patients and healthy subjects (GSE38556). One miRNA, miR-378 (miR-378* is a lower level expressed form of the same miRNA) discriminates most of the HIV patients from controls and (B) also discriminates the majority of asymptomatic LTNP individuals from the chronic HIV group. (C) PCA and hierarchical clustering heatmap clearly distinguish hemophilia patients (GSE65581) from healthy controls and discriminates hemophilia A patients with inhibitors (development of neutralizing anti-FVIII antibodies) from those hemophilia A patients who did not develop inhibitors. (D) PCA and heatmap analysis aids in diagnosis of diseases, such as viral and tuberculous meningitis (GSE131708), that are difficult to differentiate clinically and identifies specific pro-survival miRNAs, i.e. miR-1273 that are associated with the less serious (viral) form of this disease.