TY - JOUR
T1 - 1H NMR spectroscopic studies on human seminal plasma
T2 - A probative discriminant function analysis classification model
AU - Gupta, Ashish
AU - Mahdi, Abbas Ali
AU - Ahmad, Mohammad Kaleem
AU - Shukla, Kamla Kant
AU - Jaiswer, Shyam Pyari
AU - Shankhwar, Satya Narain
PY - 2011/1/1
Y1 - 2011/1/1
N2 - Traditional seminal fluid-based clinical descriptors used to predict infertility and sub-fertility have shortcomings, including lack of insight into the underlying pathology. These methods are also time-consuming and labor-intensive. To address these limitations, 1H nuclear magnetic resonance (NMR) spectroscopy was used to identify and classify signature biomarkers. Semen samples collected from 60 healthy, fertile men and from 125 infertile (normozoospermic and oligozoospermic) patients. Lactate, alanine, choline, citrate, glycerophosphocholine (GPC), glutamine, tyrosine, histidine, phenylalanine, and uridine were measured by 1H NMR spectroscopy. The sperm concentration, motility, lipid peroxidation, and total protein were evaluated with standard laboratory methods in the same samples. NMR-quantified metabolites and clinical laboratory data were analyzed, separately, through linear multivariate discriminant function analysis (DFA) to determine the signature descriptors for each group. DFA reveals that alanine, citrate, GPC, tyrosine, and phenylalanine can be used to determine infertility. DFA-based classification demonstrated high accuracy (92.4% by NMR and 94.1% by clinical laboratory method) in differentiating healthy controls from infertile patients. This statistical analysis was also able to accurately classify normozoospermic to oligozoospermic samples (92.9% by NMR and 92.6% by clinical laboratory method). In conclusion, 1H NMR-based metabolic screening appears to be a promising, rapid, and non-invasive approach to probing infertility that has similar sensitivity and specificity to the tedious laboratory method.
AB - Traditional seminal fluid-based clinical descriptors used to predict infertility and sub-fertility have shortcomings, including lack of insight into the underlying pathology. These methods are also time-consuming and labor-intensive. To address these limitations, 1H nuclear magnetic resonance (NMR) spectroscopy was used to identify and classify signature biomarkers. Semen samples collected from 60 healthy, fertile men and from 125 infertile (normozoospermic and oligozoospermic) patients. Lactate, alanine, choline, citrate, glycerophosphocholine (GPC), glutamine, tyrosine, histidine, phenylalanine, and uridine were measured by 1H NMR spectroscopy. The sperm concentration, motility, lipid peroxidation, and total protein were evaluated with standard laboratory methods in the same samples. NMR-quantified metabolites and clinical laboratory data were analyzed, separately, through linear multivariate discriminant function analysis (DFA) to determine the signature descriptors for each group. DFA reveals that alanine, citrate, GPC, tyrosine, and phenylalanine can be used to determine infertility. DFA-based classification demonstrated high accuracy (92.4% by NMR and 94.1% by clinical laboratory method) in differentiating healthy controls from infertile patients. This statistical analysis was also able to accurately classify normozoospermic to oligozoospermic samples (92.9% by NMR and 92.6% by clinical laboratory method). In conclusion, 1H NMR-based metabolic screening appears to be a promising, rapid, and non-invasive approach to probing infertility that has similar sensitivity and specificity to the tedious laboratory method.
KW - Discriminant function analysis
KW - Infertility
KW - NMR spectroscopy
KW - Seminal plasma
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U2 - 10.1016/j.jpba.2010.07.021
DO - 10.1016/j.jpba.2010.07.021
M3 - Article
C2 - 20719458
AN - SCOPUS:77957021687
SN - 0731-7085
VL - 54
SP - 106
EP - 113
JO - Journal of Pharmaceutical and Biomedical Analysis
JF - Journal of Pharmaceutical and Biomedical Analysis
IS - 1
ER -