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Table 2 Significant biomarkers after ICA analysis

From: Latent physiological factors of complex human diseases revealed by independent component analysis of clinarrays

  Significant Biomarkers Physiological Processes
Asthma Platelet Count Thrombogenesis
  Serum Sodium Serum sodium
  ALT Tissue injury
  Neutrophil Percent Acute inflammation
Type 1 Diabetes Serum Sodium Serum sodium
  Blood Urea Nitrogen Kidney function
  Platelet Count Thrombogenesis
  TSH3 Thyroid function
Type 2 Diabetes Serum Sodium Serum sodium
  ALT Tissue injury
  Platelet Count Thrombogenesis
Duchenne Muscular Dystrophy Lactate Dehydrogenase Tissue injury
  Triglycerides Lipogenesis
  Platelet Count Thrombogenesis
  AST Tissue injury
Cystic Fibrosis Total IgE IgE antibody response
  Alkaline Phosphatase Dephosphorylation
  Platelet Count Thrombogenesis
  1. Significant biomarkers for each disease are shown. Each significant biomarker was identified as a significant and statistically independent physiological factor from the patient laboratory data by ICA analysis (see Methods). Each significant biomarker was matched to a broader physiological process using a standard reference for clinical laboratory chemistry.