A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Clinics |
Texto Completo: | https://www.revistas.usp.br/clinics/article/view/19648 |
Resumo: | OBJECTIVES: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. METHODS: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. RESULTS: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. CONCLUSIONS: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis. |
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Clinics |
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A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathyImmunoglobulin A NephropathyMetabonomicsBiomarkersProton Nuclear Magnetic Resonance SpectroscopyOrthogonal Partial Least-Squares Discriminant AnalysisOBJECTIVES: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. METHODS: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. RESULTS: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. CONCLUSIONS: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis.Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo2012-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/clinics/article/view/1964810.6061/clinics/2012(04)10Clinics; Vol. 67 No. 4 (2012); 363-373Clinics; v. 67 n. 4 (2012); 363-373Clinics; Vol. 67 Núm. 4 (2012); 363-3731980-53221807-5932reponame:Clinicsinstname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/clinics/article/view/19648/21712Sui, WeiguoLi, LipingChe, WentiGuimai, ZuoChen, JiejingLi, WuxianDai, Yonginfo:eu-repo/semantics/openAccess2012-05-24T18:46:38Zoai:revistas.usp.br:article/19648Revistahttps://www.revistas.usp.br/clinicsPUBhttps://www.revistas.usp.br/clinics/oai||clinics@hc.fm.usp.br1980-53221807-5932opendoar:2012-05-24T18:46:38Clinics - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
title |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
spellingShingle |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy Sui, Weiguo Immunoglobulin A Nephropathy Metabonomics Biomarkers Proton Nuclear Magnetic Resonance Spectroscopy Orthogonal Partial Least-Squares Discriminant Analysis |
title_short |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
title_full |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
title_fullStr |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
title_full_unstemmed |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
title_sort |
A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy |
author |
Sui, Weiguo |
author_facet |
Sui, Weiguo Li, Liping Che, Wenti Guimai, Zuo Chen, Jiejing Li, Wuxian Dai, Yong |
author_role |
author |
author2 |
Li, Liping Che, Wenti Guimai, Zuo Chen, Jiejing Li, Wuxian Dai, Yong |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Sui, Weiguo Li, Liping Che, Wenti Guimai, Zuo Chen, Jiejing Li, Wuxian Dai, Yong |
dc.subject.por.fl_str_mv |
Immunoglobulin A Nephropathy Metabonomics Biomarkers Proton Nuclear Magnetic Resonance Spectroscopy Orthogonal Partial Least-Squares Discriminant Analysis |
topic |
Immunoglobulin A Nephropathy Metabonomics Biomarkers Proton Nuclear Magnetic Resonance Spectroscopy Orthogonal Partial Least-Squares Discriminant Analysis |
description |
OBJECTIVES: Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile. METHODS: Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification. RESULTS: Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine. CONCLUSIONS: These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/clinics/article/view/19648 10.6061/clinics/2012(04)10 |
url |
https://www.revistas.usp.br/clinics/article/view/19648 |
identifier_str_mv |
10.6061/clinics/2012(04)10 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/clinics/article/view/19648/21712 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo |
publisher.none.fl_str_mv |
Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo |
dc.source.none.fl_str_mv |
Clinics; Vol. 67 No. 4 (2012); 363-373 Clinics; v. 67 n. 4 (2012); 363-373 Clinics; Vol. 67 Núm. 4 (2012); 363-373 1980-5322 1807-5932 reponame:Clinics instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Clinics |
collection |
Clinics |
repository.name.fl_str_mv |
Clinics - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
||clinics@hc.fm.usp.br |
_version_ |
1800222758192283648 |