1H NMR-based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study
Focal segmental glomerulosclerosis (FSGS) is a common glomerulonephritis, and its rates of occurrence are increasing worldwide. Proteinuria is a clinical defining feature of FSGS which correlates with the severity of podocyte injury in patients with nephrotic‐range protein excretion. Metabolite biom...
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| Veröffentlicht in: | Magnetic resonance in chemistry 2016-10, Vol.54 (10), p.821-826 |
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| creator | Kalantari, Shiva Nafar, Mohsen Samavat, Shiva Parvin, Mahmoud Nobakht M.GH, B. Fatemeh Barzi, Farnaz |
| description | Focal segmental glomerulosclerosis (FSGS) is a common glomerulonephritis, and its rates of occurrence are increasing worldwide. Proteinuria is a clinical defining feature of FSGS which correlates with the severity of podocyte injury in patients with nephrotic‐range protein excretion. Metabolite biomarkers corresponding with the level of proteinuria could be considered as non‐invasive complementary prognostic factors to proteinuria.
The urine samples of 15 patients (n = 6 women and n = 9 men) with biopsy‐proven FSGS were collected and subjected to nuclear magnetic resonance (NMR) analysis for metabolite profiling. Multivariate statistical analyses, including principal component analysis and orthogonal projection to latent structure discriminant analysis, were applied to construct a predictive model based on patients with proteinuria >3000 mg/day and |
| doi_str_mv | 10.1002/mrc.4460 |
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The urine samples of 15 patients (n = 6 women and n = 9 men) with biopsy‐proven FSGS were collected and subjected to nuclear magnetic resonance (NMR) analysis for metabolite profiling. Multivariate statistical analyses, including principal component analysis and orthogonal projection to latent structure discriminant analysis, were applied to construct a predictive model based on patients with proteinuria >3000 mg/day and <3000 mg/day. In addition, random forest was performed to predict differential metabolites, and pathway analysis was performed to find the defective pathways responsible for proteinuria.
Ten metabolites, significant in both statistical methods (orthogonal projection to latent structure discriminant analysis and random forest), were considered as prognostic biomarkers for FSGS: citrulline, dimethylamine, proline, acetoacetate, alpha‐ketoisovaleric acid, valine, isobutyrate, D‐Palmitylcarnitine, histidine, and N‐methylnicotinamide. Pathway analysis revealed impairment of the branched‐chain amino acid degradation pathways in patients with massive proteinuria.
This study shows that metabolomics can reveal the molecular changes corresponding with disease progression in patients with FSGS and provide a new insight for pathogenic pathways. Copyright © 2016 John Wiley & Sons, Ltd.
Nuclear magnetic resonance is a versatile technique for identification urine metabolite biomarker in kidney disease. We showed that citrulline and dimethylamine were the most significant changed excreted metabolites in patients with focal segmental glomerulosclerosis. Furthermore, excretion level of N‐methylnicotinamide decreased in patients with massive proteinuria. Branched‐chain amino acid degradation pathway is significantly impaired in patients with worse prognosis.
Proton NMR spectra were employed to study urine metabolite profile of patients with focal segmental glomerulosclerosis. NMR‐based metabolomics in combination with advanced multivariate statistical analysis could distinguish urine metabolite biomarker candidate difference between patients with nephrotic and subnephrotic range proteinuria. These candidates were further used for investigating the impaired pathways in these patients.</description><identifier>ISSN: 0749-1581</identifier><identifier>EISSN: 1097-458X</identifier><identifier>DOI: 10.1002/mrc.4460</identifier><language>eng</language><publisher>Bognor Regis: Blackwell Publishing Ltd</publisher><subject>1H NMR-based metabolomics ; focal segmental glomerulosclerosis ; metabolite biomarker ; random forest</subject><ispartof>Magnetic resonance in chemistry, 2016-10, Vol.54 (10), p.821-826</ispartof><rights>Copyright © 2016 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmrc.4460$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrc.4460$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,27922,27923,45572,45573</link.rule.ids></links><search><creatorcontrib>Kalantari, Shiva</creatorcontrib><creatorcontrib>Nafar, Mohsen</creatorcontrib><creatorcontrib>Samavat, Shiva</creatorcontrib><creatorcontrib>Parvin, Mahmoud</creatorcontrib><creatorcontrib>Nobakht M.GH, B. Fatemeh</creatorcontrib><creatorcontrib>Barzi, Farnaz</creatorcontrib><title>1H NMR-based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study</title><title>Magnetic resonance in chemistry</title><addtitle>Magn. Reson. Chem</addtitle><description>Focal segmental glomerulosclerosis (FSGS) is a common glomerulonephritis, and its rates of occurrence are increasing worldwide. Proteinuria is a clinical defining feature of FSGS which correlates with the severity of podocyte injury in patients with nephrotic‐range protein excretion. Metabolite biomarkers corresponding with the level of proteinuria could be considered as non‐invasive complementary prognostic factors to proteinuria.
The urine samples of 15 patients (n = 6 women and n = 9 men) with biopsy‐proven FSGS were collected and subjected to nuclear magnetic resonance (NMR) analysis for metabolite profiling. Multivariate statistical analyses, including principal component analysis and orthogonal projection to latent structure discriminant analysis, were applied to construct a predictive model based on patients with proteinuria >3000 mg/day and <3000 mg/day. In addition, random forest was performed to predict differential metabolites, and pathway analysis was performed to find the defective pathways responsible for proteinuria.
Ten metabolites, significant in both statistical methods (orthogonal projection to latent structure discriminant analysis and random forest), were considered as prognostic biomarkers for FSGS: citrulline, dimethylamine, proline, acetoacetate, alpha‐ketoisovaleric acid, valine, isobutyrate, D‐Palmitylcarnitine, histidine, and N‐methylnicotinamide. Pathway analysis revealed impairment of the branched‐chain amino acid degradation pathways in patients with massive proteinuria.
This study shows that metabolomics can reveal the molecular changes corresponding with disease progression in patients with FSGS and provide a new insight for pathogenic pathways. Copyright © 2016 John Wiley & Sons, Ltd.
Nuclear magnetic resonance is a versatile technique for identification urine metabolite biomarker in kidney disease. We showed that citrulline and dimethylamine were the most significant changed excreted metabolites in patients with focal segmental glomerulosclerosis. Furthermore, excretion level of N‐methylnicotinamide decreased in patients with massive proteinuria. Branched‐chain amino acid degradation pathway is significantly impaired in patients with worse prognosis.
Proton NMR spectra were employed to study urine metabolite profile of patients with focal segmental glomerulosclerosis. NMR‐based metabolomics in combination with advanced multivariate statistical analysis could distinguish urine metabolite biomarker candidate difference between patients with nephrotic and subnephrotic range proteinuria. These candidates were further used for investigating the impaired pathways in these patients.</description><subject>1H NMR-based metabolomics</subject><subject>focal segmental glomerulosclerosis</subject><subject>metabolite biomarker</subject><subject>random forest</subject><issn>0749-1581</issn><issn>1097-458X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNpFkM1OGzEQgC3USqSAxCNY6nmDHdu7Xm5V1CRVCUhREdwsr3c2mHrXwfYq5An62nUEgsvMHL75-xC6pGRKCZld9cFMOS_JCZpQUlcFF_LxC5qQitcFFZKeom8xPhNC6rpiE_SPrvDtelM0OkKLe0i68c731kQMrzvngx22eMxRhwNurO91-AshYuNDAKdTbtrb9IR3wSewQyY1tgPuvNEOR9j2MKRcbfNMCKPz0TgIPtp4jTXeWecTjmlsD-foa6ddhIv3fIbuFz__zFfFzd3y1_zHTWEp4aRgoIU0HatrVpqSVkC1MWYmKTMNtIIZyRnIrpHSzIxoREsr3pUz4KQrS25adoa-v83NB7-MEJN69mMY8kpFJZVC8qwlU8UbtbcODmoXbP77oChRR8cqO1ZHx2q9mR_zJ29jgtcPPrtSZcUqoR5ul2r9W5ANXUj1yP4DnCWDcg</recordid><startdate>201610</startdate><enddate>201610</enddate><creator>Kalantari, Shiva</creator><creator>Nafar, Mohsen</creator><creator>Samavat, Shiva</creator><creator>Parvin, Mahmoud</creator><creator>Nobakht M.GH, B. Fatemeh</creator><creator>Barzi, Farnaz</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>L7M</scope></search><sort><creationdate>201610</creationdate><title>1H NMR-based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study</title><author>Kalantari, Shiva ; Nafar, Mohsen ; Samavat, Shiva ; Parvin, Mahmoud ; Nobakht M.GH, B. Fatemeh ; Barzi, Farnaz</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i1040-3ea58cf39936c617e1accc2813cbed53c843e8fb88c2c5b5d174f62e40f664cd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>1H NMR-based metabolomics</topic><topic>focal segmental glomerulosclerosis</topic><topic>metabolite biomarker</topic><topic>random forest</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kalantari, Shiva</creatorcontrib><creatorcontrib>Nafar, Mohsen</creatorcontrib><creatorcontrib>Samavat, Shiva</creatorcontrib><creatorcontrib>Parvin, Mahmoud</creatorcontrib><creatorcontrib>Nobakht M.GH, B. Fatemeh</creatorcontrib><creatorcontrib>Barzi, Farnaz</creatorcontrib><collection>Istex</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Magnetic resonance in chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kalantari, Shiva</au><au>Nafar, Mohsen</au><au>Samavat, Shiva</au><au>Parvin, Mahmoud</au><au>Nobakht M.GH, B. Fatemeh</au><au>Barzi, Farnaz</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>1H NMR-based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study</atitle><jtitle>Magnetic resonance in chemistry</jtitle><addtitle>Magn. Reson. Chem</addtitle><date>2016-10</date><risdate>2016</risdate><volume>54</volume><issue>10</issue><spage>821</spage><epage>826</epage><pages>821-826</pages><issn>0749-1581</issn><eissn>1097-458X</eissn><abstract>Focal segmental glomerulosclerosis (FSGS) is a common glomerulonephritis, and its rates of occurrence are increasing worldwide. Proteinuria is a clinical defining feature of FSGS which correlates with the severity of podocyte injury in patients with nephrotic‐range protein excretion. Metabolite biomarkers corresponding with the level of proteinuria could be considered as non‐invasive complementary prognostic factors to proteinuria.
The urine samples of 15 patients (n = 6 women and n = 9 men) with biopsy‐proven FSGS were collected and subjected to nuclear magnetic resonance (NMR) analysis for metabolite profiling. Multivariate statistical analyses, including principal component analysis and orthogonal projection to latent structure discriminant analysis, were applied to construct a predictive model based on patients with proteinuria >3000 mg/day and <3000 mg/day. In addition, random forest was performed to predict differential metabolites, and pathway analysis was performed to find the defective pathways responsible for proteinuria.
Ten metabolites, significant in both statistical methods (orthogonal projection to latent structure discriminant analysis and random forest), were considered as prognostic biomarkers for FSGS: citrulline, dimethylamine, proline, acetoacetate, alpha‐ketoisovaleric acid, valine, isobutyrate, D‐Palmitylcarnitine, histidine, and N‐methylnicotinamide. Pathway analysis revealed impairment of the branched‐chain amino acid degradation pathways in patients with massive proteinuria.
This study shows that metabolomics can reveal the molecular changes corresponding with disease progression in patients with FSGS and provide a new insight for pathogenic pathways. Copyright © 2016 John Wiley & Sons, Ltd.
Nuclear magnetic resonance is a versatile technique for identification urine metabolite biomarker in kidney disease. We showed that citrulline and dimethylamine were the most significant changed excreted metabolites in patients with focal segmental glomerulosclerosis. Furthermore, excretion level of N‐methylnicotinamide decreased in patients with massive proteinuria. Branched‐chain amino acid degradation pathway is significantly impaired in patients with worse prognosis.
Proton NMR spectra were employed to study urine metabolite profile of patients with focal segmental glomerulosclerosis. NMR‐based metabolomics in combination with advanced multivariate statistical analysis could distinguish urine metabolite biomarker candidate difference between patients with nephrotic and subnephrotic range proteinuria. These candidates were further used for investigating the impaired pathways in these patients.</abstract><cop>Bognor Regis</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/mrc.4460</doi><tpages>6</tpages></addata></record> |
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| title | 1H NMR-based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study |
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