A metabonomics approach as a means for identification of potential biomarkers for early diagnosis of endometriosis.
Our present study focuses on the identification of predictive biomarkers in serum for the early diagnosis of endometriosis in a minimally invasive manner using (1)H-NMR based metabonomics. PLS-DA modeling of bins obtained from CPMG spectra of serum samples discriminated endometriosis patients from controls with sensitivity and specificity levels of about 80% and 90%, respectively. Compared with those from controls, serum samples from endometriosis patients showed increased levels of lactate, 3-hydroxybutyrate, alanine, leucine, valine, threonine, lysine, glycerophosphatidylcholine, succinic acid and 2-hydroxybutyrate as well as decreased levels of lipids, glucose, isoleucine and arginine. Our work offers valuable information for non-invasive diagnosis of endometriosis and may be of potential benefit to understand pathogenesis of the disease.
School of Medical Science and Technology, Indian Institute of Technology, Kharagpur, India.
Mainak
M
Dutta
Mamata
M
Joshi
Sudha
S
Srivastava
Indrani
I
Lodh
Baidyanath
B
Chakravarty
Koel
K
Chaudhury
D000596:Amino Acids / Q000097:blood*; D015415:Biomarkers / Q000097:blood; D001798:Blood Proteins / Q000032:analysis*; D042241:Early Diagnosis; D004715:Endometriosis / Q000097:blood* / Q000175:diagnosis* / Q000378:metabolism; D005260:Female; D006801:Humans; D008055:Lipids / Q000097:blood*; D009682:Magnetic Resonance Spectroscopy; D055432:Metabolomics; D012680:Sensitivity and Specificity
D000596:Amino Acids; D015415:Biomarkers; D001798:Blood Proteins; D008055:Lipids