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Separation of autistic and healthy control participants based on two sets of biomarkers.

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posted on 2016-11-08, 17:37 authored by Afaf El-Ansary, Wail M. Hassan, Hanan Qasem, Undurti N. Das

Principal component analysis (a and b) and multidimensional scaling (c and d) scatter plots based on set 1 (a and c) and set 2 biomarkers (b and d) show complete separation of autistic and healthy control groups. Hierarchical clustering shows efficient separation of autistic and healthy control groups based on set 1 (e) or 2 (f) biomarkers. Dendrograms were constructed from Canberra distances data using Neighbor joining algorithm. Heat maps depict marker values with darker grey indicative of higher values. Heat map variables from left to right are (e) PE, PS, PC, MAP2K1, IL-10, IL-12, and NFκB, and (f) PGE2, PGE2-EP2, PGES, cPLA2, 8-isoprostane, and COX-2. Autistic subjects with mild to moderate disease, those with severe disease, and control subjects are indicated with magenta, purple, and green squares, respectively.