Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes
Objectives To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D. Methods Twenty‐five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recru...
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| Veröffentlicht in: | Pediatric diabetes 2020-11, Vol.21 (7), p.1322-1332 |
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| creator | Marcovecchio, Maria Loredana Colombo, Marco Dalton, Raymond Neil McKeigue, Paul M. Benitez‐Aguirre, Paul Cameron, Fergus J. Chiesa, Scott T. Couper, Jennifer J. Craig, Maria E. Daneman, Denis Davis, Elizabeth A. Deanfield, John E. Donaghue, Kim C. Jones, Timothy W. Mahmud, Farid H. Marshall, Sally M. Neil, Andrew Colhoun, Helen M. Dunger, David B. |
| description | Objectives
To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D.
Methods
Twenty‐five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recruited to the Adolescent Type 1 Diabetes Cardio‐Renal Intervention Trial. Associations with baseline and final estimated glomerular filtration rate (eGFR), rapid decliner and rapid increaser phenotypes (eGFR slopes 3 mL/min/1.73m2/year, respectively), and albumin‐creatinine ratio (ACR) were assessed. Results were also compared with those obtained in 859 adults (age: 55.5 [46.1, 64.4) years) from the Scottish Diabetes Research Network Type 1 Bioresource.
Results
In the adolescent cohort, baseline eGFR was negatively associated with trefoil factor‐3, cystatin C, and beta‐2 microglobulin (B2M) (B coefficient[95%CI]: −0.19 [−0.27, −0.12], P = 7.0 × 10−7; −0.18 [−0.26, −0.11], P = 5.1 × 10−6; −0.12 [−0.20, −0.05], P = 1.6 × 10−3), in addition to clinical covariates. Final eGFR was negatively associated with osteopontin (−0.21 [−0.28, −0.14], P = 2.3 × 10−8) and cystatin C (−0.16 [−0.22, −0.09], P = 1.6 × 10−6). Rapid decliner phenotype was associated with osteopontin (OR: 1.83 [1.42, 2.41], P = 7.3 × 10−6), whereas rapid increaser phenotype was associated with fibroblast growth factor‐23 (FGF‐23) (1.59 [1.23, 2.04], P = 2.6 × 10−4). ACR was not associated with any of the biomarkers. In the adult cohort similar associations with eGFR were found; however, several additional biomarkers were associated with eGFR and ACR.
Conclusions
In this young population with T1D and high rates of hyperfiltration, osteopontin was the most consistent biomarker associated with prospective changes in eGFR. FGF‐23 was associated with eGFR increases, whereas trefoil factor‐3, cystatin C, and B2M were associated with baseline eGFR. |
| doi_str_mv | 10.1111/pedi.13095 |
| format | Article |
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To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D.
Methods
Twenty‐five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recruited to the Adolescent Type 1 Diabetes Cardio‐Renal Intervention Trial. Associations with baseline and final estimated glomerular filtration rate (eGFR), rapid decliner and rapid increaser phenotypes (eGFR slopes <−3 and > 3 mL/min/1.73m2/year, respectively), and albumin‐creatinine ratio (ACR) were assessed. Results were also compared with those obtained in 859 adults (age: 55.5 [46.1, 64.4) years) from the Scottish Diabetes Research Network Type 1 Bioresource.
Results
In the adolescent cohort, baseline eGFR was negatively associated with trefoil factor‐3, cystatin C, and beta‐2 microglobulin (B2M) (B coefficient[95%CI]: −0.19 [−0.27, −0.12], P = 7.0 × 10−7; −0.18 [−0.26, −0.11], P = 5.1 × 10−6; −0.12 [−0.20, −0.05], P = 1.6 × 10−3), in addition to clinical covariates. Final eGFR was negatively associated with osteopontin (−0.21 [−0.28, −0.14], P = 2.3 × 10−8) and cystatin C (−0.16 [−0.22, −0.09], P = 1.6 × 10−6). Rapid decliner phenotype was associated with osteopontin (OR: 1.83 [1.42, 2.41], P = 7.3 × 10−6), whereas rapid increaser phenotype was associated with fibroblast growth factor‐23 (FGF‐23) (1.59 [1.23, 2.04], P = 2.6 × 10−4). ACR was not associated with any of the biomarkers. In the adult cohort similar associations with eGFR were found; however, several additional biomarkers were associated with eGFR and ACR.
Conclusions
In this young population with T1D and high rates of hyperfiltration, osteopontin was the most consistent biomarker associated with prospective changes in eGFR. FGF‐23 was associated with eGFR increases, whereas trefoil factor‐3, cystatin C, and B2M were associated with baseline eGFR.</description><identifier>ISSN: 1399-543X</identifier><identifier>EISSN: 1399-5448</identifier><identifier>DOI: 10.1111/pedi.13095</identifier><identifier>PMID: 32783254</identifier><language>eng</language><publisher>Former Munksgaard: John Wiley & Sons A/S</publisher><subject>Adolescents ; Biomarkers ; complications ; Creatinine ; Cystatin C ; Diabetes ; Diabetes mellitus (insulin dependent) ; Epidermal growth factor receptors ; Fibroblast growth factors ; GFR ; Glomerular filtration rate ; kidney disease ; Kidney diseases ; Osteopontin ; Phenotypes ; Teenagers ; Trefoil factor</subject><ispartof>Pediatric diabetes, 2020-11, Vol.21 (7), p.1322-1332</ispartof><rights>2020 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2020 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3935-81c5e41c6a299e86c2ff1479a24394d20e42f3ed4c2fb0d181bdee478e20369b3</citedby><cites>FETCH-LOGICAL-c3935-81c5e41c6a299e86c2ff1479a24394d20e42f3ed4c2fb0d181bdee478e20369b3</cites><orcidid>0000-0001-6004-576X ; 0000-0002-1566-7436 ; 0000-0002-3557-3584 ; 0000-0002-7989-1998 ; 0000-0002-4415-316X ; 0000-0003-4448-8629 ; 0000-0002-2566-9304</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fpedi.13095$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fpedi.13095$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32783254$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Marcovecchio, Maria Loredana</creatorcontrib><creatorcontrib>Colombo, Marco</creatorcontrib><creatorcontrib>Dalton, Raymond Neil</creatorcontrib><creatorcontrib>McKeigue, Paul M.</creatorcontrib><creatorcontrib>Benitez‐Aguirre, Paul</creatorcontrib><creatorcontrib>Cameron, Fergus J.</creatorcontrib><creatorcontrib>Chiesa, Scott T.</creatorcontrib><creatorcontrib>Couper, Jennifer J.</creatorcontrib><creatorcontrib>Craig, Maria E.</creatorcontrib><creatorcontrib>Daneman, Denis</creatorcontrib><creatorcontrib>Davis, Elizabeth A.</creatorcontrib><creatorcontrib>Deanfield, John E.</creatorcontrib><creatorcontrib>Donaghue, Kim C.</creatorcontrib><creatorcontrib>Jones, Timothy W.</creatorcontrib><creatorcontrib>Mahmud, Farid H.</creatorcontrib><creatorcontrib>Marshall, Sally M.</creatorcontrib><creatorcontrib>Neil, Andrew</creatorcontrib><creatorcontrib>Colhoun, Helen M.</creatorcontrib><creatorcontrib>Dunger, David B.</creatorcontrib><creatorcontrib>AdDIT and the SDRNT1BIO Investigators</creatorcontrib><creatorcontrib>The AdDIT and the SDRNT1BIO Investigators</creatorcontrib><title>Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes</title><title>Pediatric diabetes</title><addtitle>Pediatr Diabetes</addtitle><description>Objectives
To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D.
Methods
Twenty‐five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recruited to the Adolescent Type 1 Diabetes Cardio‐Renal Intervention Trial. Associations with baseline and final estimated glomerular filtration rate (eGFR), rapid decliner and rapid increaser phenotypes (eGFR slopes <−3 and > 3 mL/min/1.73m2/year, respectively), and albumin‐creatinine ratio (ACR) were assessed. Results were also compared with those obtained in 859 adults (age: 55.5 [46.1, 64.4) years) from the Scottish Diabetes Research Network Type 1 Bioresource.
Results
In the adolescent cohort, baseline eGFR was negatively associated with trefoil factor‐3, cystatin C, and beta‐2 microglobulin (B2M) (B coefficient[95%CI]: −0.19 [−0.27, −0.12], P = 7.0 × 10−7; −0.18 [−0.26, −0.11], P = 5.1 × 10−6; −0.12 [−0.20, −0.05], P = 1.6 × 10−3), in addition to clinical covariates. Final eGFR was negatively associated with osteopontin (−0.21 [−0.28, −0.14], P = 2.3 × 10−8) and cystatin C (−0.16 [−0.22, −0.09], P = 1.6 × 10−6). Rapid decliner phenotype was associated with osteopontin (OR: 1.83 [1.42, 2.41], P = 7.3 × 10−6), whereas rapid increaser phenotype was associated with fibroblast growth factor‐23 (FGF‐23) (1.59 [1.23, 2.04], P = 2.6 × 10−4). ACR was not associated with any of the biomarkers. In the adult cohort similar associations with eGFR were found; however, several additional biomarkers were associated with eGFR and ACR.
Conclusions
In this young population with T1D and high rates of hyperfiltration, osteopontin was the most consistent biomarker associated with prospective changes in eGFR. FGF‐23 was associated with eGFR increases, whereas trefoil factor‐3, cystatin C, and B2M were associated with baseline eGFR.</description><subject>Adolescents</subject><subject>Biomarkers</subject><subject>complications</subject><subject>Creatinine</subject><subject>Cystatin C</subject><subject>Diabetes</subject><subject>Diabetes mellitus (insulin dependent)</subject><subject>Epidermal growth factor receptors</subject><subject>Fibroblast growth factors</subject><subject>GFR</subject><subject>Glomerular filtration rate</subject><subject>kidney disease</subject><subject>Kidney diseases</subject><subject>Osteopontin</subject><subject>Phenotypes</subject><subject>Teenagers</subject><subject>Trefoil factor</subject><issn>1399-543X</issn><issn>1399-5448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp9kE1LwzAYgIMobk4v_gAJeBFhM19dm6POqQNBDwpepKTNW83WtbNvy-i_N7NzBw_mkkCePHl5CDnlbMT9ulqBdSMumQ72SJ9LrYeBUtH-7izfeuQIcc4YD7VUh6QnRRhJEag-eb9x5dJUC6iQGsQydaYGS9eu_qRgqrylWJsPQFpmdOFsAS21DsEgUFdQY8scMIWixu5J3a6Aco-YBGrAY3KQmRzhZLsPyOvd9GXyMHx8up9Nrh-HqdQyGEY8DUDxdGyE1hCNU5FlXIXaCCW1soKBEpkEq_xFwiyPeGIBVBiBYHKsEzkgF513VZVfDWAdL50fK89NAWWDsfdI4b-KhEfP_6DzsqkKP52nlA4jJsXYU5cdlVYlYgVZvKqc79TGnMWb6PEmevwT3cNnW2WTLMHu0N_KHuAdsHY5tP-o4ufp7ayTfgOKbIwT</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>Marcovecchio, Maria Loredana</creator><creator>Colombo, Marco</creator><creator>Dalton, Raymond Neil</creator><creator>McKeigue, Paul M.</creator><creator>Benitez‐Aguirre, Paul</creator><creator>Cameron, Fergus J.</creator><creator>Chiesa, Scott T.</creator><creator>Couper, Jennifer J.</creator><creator>Craig, Maria E.</creator><creator>Daneman, Denis</creator><creator>Davis, Elizabeth A.</creator><creator>Deanfield, John E.</creator><creator>Donaghue, Kim C.</creator><creator>Jones, Timothy W.</creator><creator>Mahmud, Farid H.</creator><creator>Marshall, Sally M.</creator><creator>Neil, Andrew</creator><creator>Colhoun, Helen M.</creator><creator>Dunger, David B.</creator><general>John Wiley & Sons A/S</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T5</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6004-576X</orcidid><orcidid>https://orcid.org/0000-0002-1566-7436</orcidid><orcidid>https://orcid.org/0000-0002-3557-3584</orcidid><orcidid>https://orcid.org/0000-0002-7989-1998</orcidid><orcidid>https://orcid.org/0000-0002-4415-316X</orcidid><orcidid>https://orcid.org/0000-0003-4448-8629</orcidid><orcidid>https://orcid.org/0000-0002-2566-9304</orcidid></search><sort><creationdate>202011</creationdate><title>Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes</title><author>Marcovecchio, Maria Loredana ; Colombo, Marco ; Dalton, Raymond Neil ; McKeigue, Paul M. ; Benitez‐Aguirre, Paul ; Cameron, Fergus J. ; Chiesa, Scott T. ; Couper, Jennifer J. ; Craig, Maria E. ; Daneman, Denis ; Davis, Elizabeth A. ; Deanfield, John E. ; Donaghue, Kim C. ; Jones, Timothy W. ; Mahmud, Farid H. ; Marshall, Sally M. ; Neil, Andrew ; Colhoun, Helen M. ; Dunger, David B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3935-81c5e41c6a299e86c2ff1479a24394d20e42f3ed4c2fb0d181bdee478e20369b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescents</topic><topic>Biomarkers</topic><topic>complications</topic><topic>Creatinine</topic><topic>Cystatin C</topic><topic>Diabetes</topic><topic>Diabetes mellitus (insulin dependent)</topic><topic>Epidermal growth factor receptors</topic><topic>Fibroblast growth factors</topic><topic>GFR</topic><topic>Glomerular filtration rate</topic><topic>kidney disease</topic><topic>Kidney diseases</topic><topic>Osteopontin</topic><topic>Phenotypes</topic><topic>Teenagers</topic><topic>Trefoil factor</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marcovecchio, Maria Loredana</creatorcontrib><creatorcontrib>Colombo, Marco</creatorcontrib><creatorcontrib>Dalton, Raymond Neil</creatorcontrib><creatorcontrib>McKeigue, Paul M.</creatorcontrib><creatorcontrib>Benitez‐Aguirre, Paul</creatorcontrib><creatorcontrib>Cameron, Fergus J.</creatorcontrib><creatorcontrib>Chiesa, Scott T.</creatorcontrib><creatorcontrib>Couper, Jennifer J.</creatorcontrib><creatorcontrib>Craig, Maria E.</creatorcontrib><creatorcontrib>Daneman, Denis</creatorcontrib><creatorcontrib>Davis, Elizabeth A.</creatorcontrib><creatorcontrib>Deanfield, John E.</creatorcontrib><creatorcontrib>Donaghue, Kim C.</creatorcontrib><creatorcontrib>Jones, Timothy W.</creatorcontrib><creatorcontrib>Mahmud, Farid H.</creatorcontrib><creatorcontrib>Marshall, Sally M.</creatorcontrib><creatorcontrib>Neil, Andrew</creatorcontrib><creatorcontrib>Colhoun, Helen M.</creatorcontrib><creatorcontrib>Dunger, David B.</creatorcontrib><creatorcontrib>AdDIT and the SDRNT1BIO Investigators</creatorcontrib><creatorcontrib>The AdDIT and the SDRNT1BIO Investigators</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Pediatric diabetes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Marcovecchio, Maria Loredana</au><au>Colombo, Marco</au><au>Dalton, Raymond Neil</au><au>McKeigue, Paul M.</au><au>Benitez‐Aguirre, Paul</au><au>Cameron, Fergus J.</au><au>Chiesa, Scott T.</au><au>Couper, Jennifer J.</au><au>Craig, Maria E.</au><au>Daneman, Denis</au><au>Davis, Elizabeth A.</au><au>Deanfield, John E.</au><au>Donaghue, Kim C.</au><au>Jones, Timothy W.</au><au>Mahmud, Farid H.</au><au>Marshall, Sally M.</au><au>Neil, Andrew</au><au>Colhoun, Helen M.</au><au>Dunger, David B.</au><aucorp>AdDIT and the SDRNT1BIO Investigators</aucorp><aucorp>The AdDIT and the SDRNT1BIO Investigators</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes</atitle><jtitle>Pediatric diabetes</jtitle><addtitle>Pediatr Diabetes</addtitle><date>2020-11</date><risdate>2020</risdate><volume>21</volume><issue>7</issue><spage>1322</spage><epage>1332</epage><pages>1322-1332</pages><issn>1399-543X</issn><eissn>1399-5448</eissn><abstract>Objectives
To identify biomarkers of renal disease in adolescents with type 1 diabetes (T1D) and to compare findings in adults with T1D.
Methods
Twenty‐five serum biomarkers were measured, using a Luminex platform, in 553 adolescents (median [interquartile range] age: 13.9 [12.6, 15.2] years), recruited to the Adolescent Type 1 Diabetes Cardio‐Renal Intervention Trial. Associations with baseline and final estimated glomerular filtration rate (eGFR), rapid decliner and rapid increaser phenotypes (eGFR slopes <−3 and > 3 mL/min/1.73m2/year, respectively), and albumin‐creatinine ratio (ACR) were assessed. Results were also compared with those obtained in 859 adults (age: 55.5 [46.1, 64.4) years) from the Scottish Diabetes Research Network Type 1 Bioresource.
Results
In the adolescent cohort, baseline eGFR was negatively associated with trefoil factor‐3, cystatin C, and beta‐2 microglobulin (B2M) (B coefficient[95%CI]: −0.19 [−0.27, −0.12], P = 7.0 × 10−7; −0.18 [−0.26, −0.11], P = 5.1 × 10−6; −0.12 [−0.20, −0.05], P = 1.6 × 10−3), in addition to clinical covariates. Final eGFR was negatively associated with osteopontin (−0.21 [−0.28, −0.14], P = 2.3 × 10−8) and cystatin C (−0.16 [−0.22, −0.09], P = 1.6 × 10−6). Rapid decliner phenotype was associated with osteopontin (OR: 1.83 [1.42, 2.41], P = 7.3 × 10−6), whereas rapid increaser phenotype was associated with fibroblast growth factor‐23 (FGF‐23) (1.59 [1.23, 2.04], P = 2.6 × 10−4). ACR was not associated with any of the biomarkers. In the adult cohort similar associations with eGFR were found; however, several additional biomarkers were associated with eGFR and ACR.
Conclusions
In this young population with T1D and high rates of hyperfiltration, osteopontin was the most consistent biomarker associated with prospective changes in eGFR. FGF‐23 was associated with eGFR increases, whereas trefoil factor‐3, cystatin C, and B2M were associated with baseline eGFR.</abstract><cop>Former Munksgaard</cop><pub>John Wiley & Sons A/S</pub><pmid>32783254</pmid><doi>10.1111/pedi.13095</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-6004-576X</orcidid><orcidid>https://orcid.org/0000-0002-1566-7436</orcidid><orcidid>https://orcid.org/0000-0002-3557-3584</orcidid><orcidid>https://orcid.org/0000-0002-7989-1998</orcidid><orcidid>https://orcid.org/0000-0002-4415-316X</orcidid><orcidid>https://orcid.org/0000-0003-4448-8629</orcidid><orcidid>https://orcid.org/0000-0002-2566-9304</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Pediatric diabetes, 2020-11, Vol.21 (7), p.1322-1332 |
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| source | Access via Wiley Online Library |
| subjects | Adolescents Biomarkers complications Creatinine Cystatin C Diabetes Diabetes mellitus (insulin dependent) Epidermal growth factor receptors Fibroblast growth factors GFR Glomerular filtration rate kidney disease Kidney diseases Osteopontin Phenotypes Teenagers Trefoil factor |
| title | Biomarkers associated with early stages of kidney disease in adolescents with type 1 diabetes |
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