Filipe Tenorio Lira Neto1,2, Ronmilson Alves Marques3, Alexandre de Freitas Cavalcanti Filho4, Leslie Clifford Noronha Araujo5, Salvador Vilar Correia Lima6, Licarion Pinto3, Ricardo Oliveira Silva3. 1. Department of Surgery, Universidade Federal de Pernambuco, Rua Guilherme Salazar, n 150, apt 601E, Recife, PE, ZIP 52061-275, Brazil. ftenorio.uro@gmail.com. 2. Instituto de Medicina Integral Prof. Fernando Figueira, Rua dos Coelho, 300, Coelhos, Recife, PE, ZIP 50070-902, Brazil. ftenorio.uro@gmail.com. 3. Fundamental Chemistry Department, Universidade Federal de Pernambuco, Av. Jornalista Anibal Fernandes, s/n° Cidade Universitária, Recife, PE, ZIP 50740-560, Brazil. 4. Instituto de Medicina Integral Prof. Fernando Figueira, Rua dos Coelho, 300, Coelhos, Recife, PE, ZIP 50070-902, Brazil. 5. Faculdade de Medicina de Olinda, Rua Dr. Manoel de Almeida Belo, n 1333, Olinda, PE, ZIP 53030-030, Brazil. 6. Department of Surgery, Universidade Federal de Pernambuco, Hospital das Clínicas - Campus UFPE, Av. Prof. Moraes Rego,"s/n° - Bloco "A" - Térreo Cidade Universitária, Recife, PE, ZIP 50670-420, Brazil.
Abstract
PURPOSE: "Omics" techniques have been used to understand and to identify biomarkers of male infertility. We report on the first metabonomics models created to diagnose varicocele and infertility among men with varicocele. METHODS: We recruited 35 infertile men with varicocele (VI group), 21 fertile men with varicocele (VF group) and 24 fertile men without varicocele (C group). All men underwent standard semen analysis, scrotal duplex ultrasonography, and sexual hormone level measurement. Hydrogen-1 nuclear magnetic resonance (1H NMR) spectra of seminal plasma were used to create metabonomics models to discriminate between men with and without varicocele, and between fertile and infertile men with varicocele. RESULTS: Using the statistical formalisms partial least square discriminants analysis and genetic algorithm-based linear discriminant analysis (GA-LDA), we created two models that discriminated the three groups from each other with accuracy of 92.17%. We also created metabonomics models using orthogonal partial least square discriminants analysis and GA-LDA that discriminated VF group from VI group, with an accuracy of 94.64% and 100% respectively. We identified 19 metabolites that were important in group segregation: caprate, 2-hydroxy-3-methylvalerate, leucine, valine, 3-hydroxybutyrate, lactate, alanine, 4-aminobutyrate, isoleucine, citrate, methanol, glucose, glycosides, glycerol-3-phosphocoline, n-acetyltyrosine, glutamine, tyrosine, arginine, and uridine. CONCLUSIONS: 1HNMR-based metabonomics of seminal plasma can be used to create metabonomics models to discriminate between men with varicocele from those without varicocele, and between fertile men with varicocele from those infertile with varicocele. Furthermore, the most important metabolites for group segregation are involved in the oxidative stress caused by varicocele.
PURPOSE: "Omics" techniques have been used to understand and to identify biomarkers of male infertility. We report on the first metabonomics models created to diagnose varicocele and infertility among men with varicocele. METHODS: We recruited 35 infertile men with varicocele (VI group), 21 fertile men with varicocele (VF group) and 24 fertile men without varicocele (C group). All men underwent standard semen analysis, scrotal duplex ultrasonography, and sexual hormone level measurement. Hydrogen-1 nuclear magnetic resonance (1H NMR) spectra of seminal plasma were used to create metabonomics models to discriminate between men with and without varicocele, and between fertile and infertile men with varicocele. RESULTS: Using the statistical formalisms partial least square discriminants analysis and genetic algorithm-based linear discriminant analysis (GA-LDA), we created two models that discriminated the three groups from each other with accuracy of 92.17%. We also created metabonomics models using orthogonal partial least square discriminants analysis and GA-LDA that discriminated VF group from VI group, with an accuracy of 94.64% and 100% respectively. We identified 19 metabolites that were important in group segregation: caprate, 2-hydroxy-3-methylvalerate, leucine, valine, 3-hydroxybutyrate, lactate, alanine, 4-aminobutyrate, isoleucine, citrate, methanol, glucose, glycosides, glycerol-3-phosphocoline, n-acetyltyrosine, glutamine, tyrosine, arginine, and uridine. CONCLUSIONS: 1HNMR-based metabonomics of seminal plasma can be used to create metabonomics models to discriminate between men with varicocele from those without varicocele, and between fertile men with varicocele from those infertile with varicocele. Furthermore, the most important metabolites for group segregation are involved in the oxidative stress caused by varicocele.
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