A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus
Aims/hypothesis Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or...
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| Veröffentlicht in: | Diabetologia 2013-02, Vol.56 (2), p.259-267 |
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| creator | Roscioni, S. S. de Zeeuw, D. Hellemons, M. E. Mischak, H. Zürbig, P. Bakker, S. J. L. Gansevoort, R. T. Reinhard, H. Persson, F. Lajer, M. Rossing, P. Heerspink, H. J. Lambers |
| description | Aims/hypothesis
Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria.
Methods
We conducted a prospective case–control study. Cases (
n
= 44) and controls (
n
= 44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides.
Results
The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79],
p
= 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03,
p
= 0.002; integrated discrimination index [IDI]: 0.105,
p
= 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls.
Conclusions/interpretation
Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes. |
| doi_str_mv | 10.1007/s00125-012-2755-2 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1273205614</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3192965741</sourcerecordid><originalsourceid>FETCH-LOGICAL-c511t-ff93c7906cf414c5f6a0a6f0c91f4666973c4d10af831bd1dcd157df7057bd943</originalsourceid><addsrcrecordid>eNp1kEuLFTEQRoM4ONfRH-BGAiK4aacqz9vLYfAFA25mwI2EdB5Dxn6ZdCP335vmXh8IbiqLOl_l4xDyAuEtAujLAoBMNnU0TEvZsEdkh4KzBgTbPya7bd3gXn05J09LeQAALoV6Qs4Zh72Sst2Rr1d0zWm0-UDnMC_JB9qlabD5W8i0hIXOOfjklkJ_TLmEMY33dIrU9t06pLFGLU0jXQ5zoIz6ZLuwhEKH0PdpWcszchZtX8Lz03tB7t6_u73-2Nx8_vDp-uqmcRJxaWJsudMtKBcFCiejsmBVBNdiFEqpVnMnPIKNe46dR-88Su2jBqk73wp-Qd4c7855-r6GspghFVdL2DFMazHINGcgFW7oq3_Qh2nNY21nULQMgWnNKoVHyuWplByimXOqVg4GwWzuzdG9qcNs7s2WeXm6vHZD8L8Tv2RX4PUJsMXZPmY7ulT-cFpy5JJXjh25Ulfjfch_Vfzv7z8BGHmbcw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1492102772</pqid></control><display><type>article</type><title>A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus</title><source>MEDLINE</source><source>SpringerLink Journals</source><creator>Roscioni, S. S. ; de Zeeuw, D. ; Hellemons, M. E. ; Mischak, H. ; Zürbig, P. ; Bakker, S. J. L. ; Gansevoort, R. T. ; Reinhard, H. ; Persson, F. ; Lajer, M. ; Rossing, P. ; Heerspink, H. J. Lambers</creator><creatorcontrib>Roscioni, S. S. ; de Zeeuw, D. ; Hellemons, M. E. ; Mischak, H. ; Zürbig, P. ; Bakker, S. J. L. ; Gansevoort, R. T. ; Reinhard, H. ; Persson, F. ; Lajer, M. ; Rossing, P. ; Heerspink, H. J. Lambers</creatorcontrib><description>Aims/hypothesis
Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria.
Methods
We conducted a prospective case–control study. Cases (
n
= 44) and controls (
n
= 44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides.
Results
The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79],
p
= 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03,
p
= 0.002; integrated discrimination index [IDI]: 0.105,
p
= 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls.
Conclusions/interpretation
Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes.</description><identifier>ISSN: 0012-186X</identifier><identifier>EISSN: 1432-0428</identifier><identifier>DOI: 10.1007/s00125-012-2755-2</identifier><identifier>PMID: 23086559</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Aged ; Albuminuria - pathology ; Albuminuria - urine ; Biological and medical sciences ; Biomarkers ; Biomarkers - urine ; Case-Control Studies ; Diabetes ; Diabetes Mellitus, Type 2 - pathology ; Diabetes Mellitus, Type 2 - urine ; Diabetes. Impaired glucose tolerance ; Disease prevention ; Endocrine pancreas. Apud cells (diseases) ; Endocrinopathies ; Etiopathogenesis. Screening. Investigations. Target tissue resistance ; Female ; Glucose ; Glycoproteins ; Human Physiology ; Humans ; Internal Medicine ; Kidney diseases ; Kidneys ; Male ; Medical sciences ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Middle Aged ; Nephrology. Urinary tract diseases ; Nephropathies. Renovascular diseases. Renal failure ; Peptides ; Peptides - urine ; Prospective Studies ; Proteomics ; Proteomics - methods ; Renal failure ; Urinary system involvement in other diseases. Miscellaneous ; Urine</subject><ispartof>Diabetologia, 2013-02, Vol.56 (2), p.259-267</ispartof><rights>Springer-Verlag Berlin Heidelberg 2012</rights><rights>2014 INIST-CNRS</rights><rights>Springer-Verlag Berlin Heidelberg 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c511t-ff93c7906cf414c5f6a0a6f0c91f4666973c4d10af831bd1dcd157df7057bd943</citedby><cites>FETCH-LOGICAL-c511t-ff93c7906cf414c5f6a0a6f0c91f4666973c4d10af831bd1dcd157df7057bd943</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00125-012-2755-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00125-012-2755-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27531353$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23086559$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Roscioni, S. S.</creatorcontrib><creatorcontrib>de Zeeuw, D.</creatorcontrib><creatorcontrib>Hellemons, M. E.</creatorcontrib><creatorcontrib>Mischak, H.</creatorcontrib><creatorcontrib>Zürbig, P.</creatorcontrib><creatorcontrib>Bakker, S. J. L.</creatorcontrib><creatorcontrib>Gansevoort, R. T.</creatorcontrib><creatorcontrib>Reinhard, H.</creatorcontrib><creatorcontrib>Persson, F.</creatorcontrib><creatorcontrib>Lajer, M.</creatorcontrib><creatorcontrib>Rossing, P.</creatorcontrib><creatorcontrib>Heerspink, H. J. Lambers</creatorcontrib><title>A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus</title><title>Diabetologia</title><addtitle>Diabetologia</addtitle><addtitle>Diabetologia</addtitle><description>Aims/hypothesis
Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria.
Methods
We conducted a prospective case–control study. Cases (
n
= 44) and controls (
n
= 44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides.
Results
The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79],
p
= 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03,
p
= 0.002; integrated discrimination index [IDI]: 0.105,
p
= 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls.
Conclusions/interpretation
Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes.</description><subject>Aged</subject><subject>Albuminuria - pathology</subject><subject>Albuminuria - urine</subject><subject>Biological and medical sciences</subject><subject>Biomarkers</subject><subject>Biomarkers - urine</subject><subject>Case-Control Studies</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 2 - pathology</subject><subject>Diabetes Mellitus, Type 2 - urine</subject><subject>Diabetes. Impaired glucose tolerance</subject><subject>Disease prevention</subject><subject>Endocrine pancreas. Apud cells (diseases)</subject><subject>Endocrinopathies</subject><subject>Etiopathogenesis. Screening. Investigations. Target tissue resistance</subject><subject>Female</subject><subject>Glucose</subject><subject>Glycoproteins</subject><subject>Human Physiology</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Kidney diseases</subject><subject>Kidneys</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Middle Aged</subject><subject>Nephrology. Urinary tract diseases</subject><subject>Nephropathies. Renovascular diseases. Renal failure</subject><subject>Peptides</subject><subject>Peptides - urine</subject><subject>Prospective Studies</subject><subject>Proteomics</subject><subject>Proteomics - methods</subject><subject>Renal failure</subject><subject>Urinary system involvement in other diseases. Miscellaneous</subject><subject>Urine</subject><issn>0012-186X</issn><issn>1432-0428</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kEuLFTEQRoM4ONfRH-BGAiK4aacqz9vLYfAFA25mwI2EdB5Dxn6ZdCP335vmXh8IbiqLOl_l4xDyAuEtAujLAoBMNnU0TEvZsEdkh4KzBgTbPya7bd3gXn05J09LeQAALoV6Qs4Zh72Sst2Rr1d0zWm0-UDnMC_JB9qlabD5W8i0hIXOOfjklkJ_TLmEMY33dIrU9t06pLFGLU0jXQ5zoIz6ZLuwhEKH0PdpWcszchZtX8Lz03tB7t6_u73-2Nx8_vDp-uqmcRJxaWJsudMtKBcFCiejsmBVBNdiFEqpVnMnPIKNe46dR-88Su2jBqk73wp-Qd4c7855-r6GspghFVdL2DFMazHINGcgFW7oq3_Qh2nNY21nULQMgWnNKoVHyuWplByimXOqVg4GwWzuzdG9qcNs7s2WeXm6vHZD8L8Tv2RX4PUJsMXZPmY7ulT-cFpy5JJXjh25Ulfjfch_Vfzv7z8BGHmbcw</recordid><startdate>20130201</startdate><enddate>20130201</enddate><creator>Roscioni, S. S.</creator><creator>de Zeeuw, D.</creator><creator>Hellemons, M. E.</creator><creator>Mischak, H.</creator><creator>Zürbig, P.</creator><creator>Bakker, S. J. L.</creator><creator>Gansevoort, R. T.</creator><creator>Reinhard, H.</creator><creator>Persson, F.</creator><creator>Lajer, M.</creator><creator>Rossing, P.</creator><creator>Heerspink, H. J. Lambers</creator><general>Springer-Verlag</general><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20130201</creationdate><title>A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus</title><author>Roscioni, S. S. ; de Zeeuw, D. ; Hellemons, M. E. ; Mischak, H. ; Zürbig, P. ; Bakker, S. J. L. ; Gansevoort, R. T. ; Reinhard, H. ; Persson, F. ; Lajer, M. ; Rossing, P. ; Heerspink, H. J. Lambers</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c511t-ff93c7906cf414c5f6a0a6f0c91f4666973c4d10af831bd1dcd157df7057bd943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Aged</topic><topic>Albuminuria - pathology</topic><topic>Albuminuria - urine</topic><topic>Biological and medical sciences</topic><topic>Biomarkers</topic><topic>Biomarkers - urine</topic><topic>Case-Control Studies</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 2 - pathology</topic><topic>Diabetes Mellitus, Type 2 - urine</topic><topic>Diabetes. Impaired glucose tolerance</topic><topic>Disease prevention</topic><topic>Endocrine pancreas. Apud cells (diseases)</topic><topic>Endocrinopathies</topic><topic>Etiopathogenesis. Screening. Investigations. Target tissue resistance</topic><topic>Female</topic><topic>Glucose</topic><topic>Glycoproteins</topic><topic>Human Physiology</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Kidney diseases</topic><topic>Kidneys</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Middle Aged</topic><topic>Nephrology. Urinary tract diseases</topic><topic>Nephropathies. Renovascular diseases. Renal failure</topic><topic>Peptides</topic><topic>Peptides - urine</topic><topic>Prospective Studies</topic><topic>Proteomics</topic><topic>Proteomics - methods</topic><topic>Renal failure</topic><topic>Urinary system involvement in other diseases. Miscellaneous</topic><topic>Urine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Roscioni, S. S.</creatorcontrib><creatorcontrib>de Zeeuw, D.</creatorcontrib><creatorcontrib>Hellemons, M. E.</creatorcontrib><creatorcontrib>Mischak, H.</creatorcontrib><creatorcontrib>Zürbig, P.</creatorcontrib><creatorcontrib>Bakker, S. J. L.</creatorcontrib><creatorcontrib>Gansevoort, R. T.</creatorcontrib><creatorcontrib>Reinhard, H.</creatorcontrib><creatorcontrib>Persson, F.</creatorcontrib><creatorcontrib>Lajer, M.</creatorcontrib><creatorcontrib>Rossing, P.</creatorcontrib><creatorcontrib>Heerspink, H. J. Lambers</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Diabetologia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Roscioni, S. S.</au><au>de Zeeuw, D.</au><au>Hellemons, M. E.</au><au>Mischak, H.</au><au>Zürbig, P.</au><au>Bakker, S. J. L.</au><au>Gansevoort, R. T.</au><au>Reinhard, H.</au><au>Persson, F.</au><au>Lajer, M.</au><au>Rossing, P.</au><au>Heerspink, H. J. Lambers</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus</atitle><jtitle>Diabetologia</jtitle><stitle>Diabetologia</stitle><addtitle>Diabetologia</addtitle><date>2013-02-01</date><risdate>2013</risdate><volume>56</volume><issue>2</issue><spage>259</spage><epage>267</epage><pages>259-267</pages><issn>0012-186X</issn><eissn>1432-0428</eissn><abstract>Aims/hypothesis
Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria.
Methods
We conducted a prospective case–control study. Cases (
n
= 44) and controls (
n
= 44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides.
Results
The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79],
p
= 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03,
p
= 0.002; integrated discrimination index [IDI]: 0.105,
p
= 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls.
Conclusions/interpretation
Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><pmid>23086559</pmid><doi>10.1007/s00125-012-2755-2</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
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| ispartof | Diabetologia, 2013-02, Vol.56 (2), p.259-267 |
| issn | 0012-186X 1432-0428 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1273205614 |
| source | MEDLINE; SpringerLink Journals |
| subjects | Aged Albuminuria - pathology Albuminuria - urine Biological and medical sciences Biomarkers Biomarkers - urine Case-Control Studies Diabetes Diabetes Mellitus, Type 2 - pathology Diabetes Mellitus, Type 2 - urine Diabetes. Impaired glucose tolerance Disease prevention Endocrine pancreas. Apud cells (diseases) Endocrinopathies Etiopathogenesis. Screening. Investigations. Target tissue resistance Female Glucose Glycoproteins Human Physiology Humans Internal Medicine Kidney diseases Kidneys Male Medical sciences Medicine Medicine & Public Health Metabolic Diseases Middle Aged Nephrology. Urinary tract diseases Nephropathies. Renovascular diseases. Renal failure Peptides Peptides - urine Prospective Studies Proteomics Proteomics - methods Renal failure Urinary system involvement in other diseases. Miscellaneous Urine |
| title | A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus |
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