A Mendelian Randomization-Based Approach to Identify Early and Sensitive Diagnostic Biomarkers of Disease
Identifying markers of chronic kidney disease (CKD) that occur early in the disease process and are specific to loss of kidney function rather than other underlying causes of disease may allow earlier, more accurate identification of patients who will develop CKD. We therefore sought to identify dia...
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| Veröffentlicht in: | Clinical chemistry (Baltimore, Md.) Md.), 2019-03, Vol.65 (3), p.427-436 |
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| creator | Mohammadi-Shemirani, Pedrum Sjaarda, Jennifer Gerstein, Hertzel C Treleaven, Darin J Walsh, Michael Mann, Johannes F McQueen, Matthew J Hess, Sibylle Paré, Guillaume |
| description | Identifying markers of chronic kidney disease (CKD) that occur early in the disease process and are specific to loss of kidney function rather than other underlying causes of disease may allow earlier, more accurate identification of patients who will develop CKD. We therefore sought to identify diagnostic blood markers of early CKD that are caused by loss of kidney function by using an innovative "reverse Mendelian randomization" (MR) approach.
We applied this technique to genetic and biomarker data from 4147 participants in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial, all with known type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance. Two-sample MR was conducted using variants associated with creatinine-based eGFR (eGFR
) from the CKDGen Consortium (n = 133814) to estimate the effect of genetically decreased eGFR
on 238 serum biomarkers.
With reverse MR, trefoil factor 3 (TFF3) was identified as a protein that is increased owing to decreased eGFR
(β = 1.86 SD per SD decrease eGFR
; 95% CI, 0.95-2.76;
= 8.0 × 10
). Reverse MR findings were consistent with epidemiological associations for incident CKD in ORIGIN (OR = 1.28 per SD increase in TFF3; 95% CI, 1.18-1.38;
= 4.58 × 10
). Addition of TFF3 significantly improved discrimination for incident CKD relative to eGFR
alone (net reclassification improvement = 0.211;
= 9.56 × 10
) and in models including additional risk factors.
Our results suggest TFF3 is a valuable diagnostic marker for early CKD in dysglycemic populations and acts as a proof of concept for the application of this novel MR technique to identify diagnostic biomarkers for other chronic diseases.
NCT00069784. |
| doi_str_mv | 10.1373/clinchem.2018.291104 |
| format | Article |
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We applied this technique to genetic and biomarker data from 4147 participants in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial, all with known type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance. Two-sample MR was conducted using variants associated with creatinine-based eGFR (eGFR
) from the CKDGen Consortium (n = 133814) to estimate the effect of genetically decreased eGFR
on 238 serum biomarkers.
With reverse MR, trefoil factor 3 (TFF3) was identified as a protein that is increased owing to decreased eGFR
(β = 1.86 SD per SD decrease eGFR
; 95% CI, 0.95-2.76;
= 8.0 × 10
). Reverse MR findings were consistent with epidemiological associations for incident CKD in ORIGIN (OR = 1.28 per SD increase in TFF3; 95% CI, 1.18-1.38;
= 4.58 × 10
). Addition of TFF3 significantly improved discrimination for incident CKD relative to eGFR
alone (net reclassification improvement = 0.211;
= 9.56 × 10
) and in models including additional risk factors.
Our results suggest TFF3 is a valuable diagnostic marker for early CKD in dysglycemic populations and acts as a proof of concept for the application of this novel MR technique to identify diagnostic biomarkers for other chronic diseases.
NCT00069784.</description><identifier>ISSN: 0009-9147</identifier><identifier>EISSN: 1530-8561</identifier><identifier>DOI: 10.1373/clinchem.2018.291104</identifier><identifier>PMID: 30337280</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Aged ; Biomarkers ; Biomarkers - blood ; Cardiovascular disease ; Chronic illnesses ; Consortia ; Data processing ; Diabetes ; Diabetes mellitus ; Diabetes mellitus (non-insulin dependent) ; Diabetic Nephropathies - diagnosis ; Diagnostic systems ; Epidemiology ; Epidermal growth factor receptors ; ErbB Receptors - genetics ; Ethnicity ; Female ; Genome-Wide Association Study - statistics & numerical data ; Genomes ; Glucose ; Glucose tolerance ; Humans ; Kidney diseases ; Kidneys ; Male ; Medical diagnosis ; Mendelian Randomization Analysis - methods ; Middle Aged ; Mutation ; Proof of Concept Study ; Proteins ; Randomization ; Reclassification ; Renal Insufficiency, Chronic - diagnosis ; Risk analysis ; Risk factors ; Trefoil factor ; Trefoil Factor-3 - blood</subject><ispartof>Clinical chemistry (Baltimore, Md.), 2019-03, Vol.65 (3), p.427-436</ispartof><rights>2018 American Association for Clinical Chemistry.</rights><rights>Copyright American Association for Clinical Chemistry Mar 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c381t-473fb31c1c8673bc3ae9e8d26d2bfa82f04e4c2a1ab66e9be0c50c6ebc1844513</citedby><cites>FETCH-LOGICAL-c381t-473fb31c1c8673bc3ae9e8d26d2bfa82f04e4c2a1ab66e9be0c50c6ebc1844513</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30337280$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mohammadi-Shemirani, Pedrum</creatorcontrib><creatorcontrib>Sjaarda, Jennifer</creatorcontrib><creatorcontrib>Gerstein, Hertzel C</creatorcontrib><creatorcontrib>Treleaven, Darin J</creatorcontrib><creatorcontrib>Walsh, Michael</creatorcontrib><creatorcontrib>Mann, Johannes F</creatorcontrib><creatorcontrib>McQueen, Matthew J</creatorcontrib><creatorcontrib>Hess, Sibylle</creatorcontrib><creatorcontrib>Paré, Guillaume</creatorcontrib><title>A Mendelian Randomization-Based Approach to Identify Early and Sensitive Diagnostic Biomarkers of Disease</title><title>Clinical chemistry (Baltimore, Md.)</title><addtitle>Clin Chem</addtitle><description>Identifying markers of chronic kidney disease (CKD) that occur early in the disease process and are specific to loss of kidney function rather than other underlying causes of disease may allow earlier, more accurate identification of patients who will develop CKD. We therefore sought to identify diagnostic blood markers of early CKD that are caused by loss of kidney function by using an innovative "reverse Mendelian randomization" (MR) approach.
We applied this technique to genetic and biomarker data from 4147 participants in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial, all with known type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance. Two-sample MR was conducted using variants associated with creatinine-based eGFR (eGFR
) from the CKDGen Consortium (n = 133814) to estimate the effect of genetically decreased eGFR
on 238 serum biomarkers.
With reverse MR, trefoil factor 3 (TFF3) was identified as a protein that is increased owing to decreased eGFR
(β = 1.86 SD per SD decrease eGFR
; 95% CI, 0.95-2.76;
= 8.0 × 10
). Reverse MR findings were consistent with epidemiological associations for incident CKD in ORIGIN (OR = 1.28 per SD increase in TFF3; 95% CI, 1.18-1.38;
= 4.58 × 10
). Addition of TFF3 significantly improved discrimination for incident CKD relative to eGFR
alone (net reclassification improvement = 0.211;
= 9.56 × 10
) and in models including additional risk factors.
Our results suggest TFF3 is a valuable diagnostic marker for early CKD in dysglycemic populations and acts as a proof of concept for the application of this novel MR technique to identify diagnostic biomarkers for other chronic diseases.
NCT00069784.</description><subject>Aged</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Cardiovascular disease</subject><subject>Chronic illnesses</subject><subject>Consortia</subject><subject>Data processing</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetic Nephropathies - diagnosis</subject><subject>Diagnostic systems</subject><subject>Epidemiology</subject><subject>Epidermal growth factor receptors</subject><subject>ErbB Receptors - genetics</subject><subject>Ethnicity</subject><subject>Female</subject><subject>Genome-Wide Association Study - statistics & numerical data</subject><subject>Genomes</subject><subject>Glucose</subject><subject>Glucose tolerance</subject><subject>Humans</subject><subject>Kidney diseases</subject><subject>Kidneys</subject><subject>Male</subject><subject>Medical diagnosis</subject><subject>Mendelian Randomization Analysis - methods</subject><subject>Middle Aged</subject><subject>Mutation</subject><subject>Proof of Concept Study</subject><subject>Proteins</subject><subject>Randomization</subject><subject>Reclassification</subject><subject>Renal Insufficiency, Chronic - diagnosis</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Trefoil factor</subject><subject>Trefoil Factor-3 - blood</subject><issn>0009-9147</issn><issn>1530-8561</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNpdkctOwzAQRS0EgvL4A4QssWGT4rGdxFm2vKUiJB7ryHEm4JLYJU6RytdjVMqC1Wg0Z67mziXkGNgYRC7OTWudecNuzBmoMS8AmNwiI0gFS1SawTYZMcaKpACZ75H9EOaxlbnKdsmeYELkXLERsRN6j67G1mpHH7WrfWe_9GC9S6Y6YE0ni0XvtXmjg6d3NbrBNit6pft2RSNNn9AFO9hPpJdWvzofBmvo1PpO9-_YB-qbOAgYpQ7JTqPbgEe_9YC8XF89X9wms4ebu4vJLDFCwZDIXDSVAANGZbmojNBYoKp5VvOq0Yo3TKI0XIOusgyLCplJmcmwMqCkTEEckLO1brz7Y4lhKDsbDLatduiXoeTAo3eeiiyip__QuV_2Ll4XqUJJECxPIyXXlOl9CD025aK30d-qBFb-RFFuoih_oijXUcS1k1_xZdVh_be0-b34BjYzhxU</recordid><startdate>201903</startdate><enddate>201903</enddate><creator>Mohammadi-Shemirani, Pedrum</creator><creator>Sjaarda, Jennifer</creator><creator>Gerstein, Hertzel C</creator><creator>Treleaven, Darin J</creator><creator>Walsh, Michael</creator><creator>Mann, Johannes F</creator><creator>McQueen, Matthew J</creator><creator>Hess, Sibylle</creator><creator>Paré, Guillaume</creator><general>Oxford University Press</general><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>4U-</scope><scope>7QO</scope><scope>7RV</scope><scope>7TM</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PCBAR</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>S0X</scope><scope>7X8</scope></search><sort><creationdate>201903</creationdate><title>A Mendelian Randomization-Based Approach to Identify Early and Sensitive Diagnostic Biomarkers of Disease</title><author>Mohammadi-Shemirani, Pedrum ; Sjaarda, Jennifer ; Gerstein, Hertzel C ; Treleaven, Darin J ; Walsh, Michael ; Mann, Johannes F ; McQueen, Matthew J ; Hess, Sibylle ; Paré, Guillaume</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c381t-473fb31c1c8673bc3ae9e8d26d2bfa82f04e4c2a1ab66e9be0c50c6ebc1844513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aged</topic><topic>Biomarkers</topic><topic>Biomarkers - 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Academic</collection><jtitle>Clinical chemistry (Baltimore, Md.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mohammadi-Shemirani, Pedrum</au><au>Sjaarda, Jennifer</au><au>Gerstein, Hertzel C</au><au>Treleaven, Darin J</au><au>Walsh, Michael</au><au>Mann, Johannes F</au><au>McQueen, Matthew J</au><au>Hess, Sibylle</au><au>Paré, Guillaume</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Mendelian Randomization-Based Approach to Identify Early and Sensitive Diagnostic Biomarkers of Disease</atitle><jtitle>Clinical chemistry (Baltimore, Md.)</jtitle><addtitle>Clin Chem</addtitle><date>2019-03</date><risdate>2019</risdate><volume>65</volume><issue>3</issue><spage>427</spage><epage>436</epage><pages>427-436</pages><issn>0009-9147</issn><eissn>1530-8561</eissn><abstract>Identifying markers of chronic kidney disease (CKD) that occur early in the disease process and are specific to loss of kidney function rather than other underlying causes of disease may allow earlier, more accurate identification of patients who will develop CKD. We therefore sought to identify diagnostic blood markers of early CKD that are caused by loss of kidney function by using an innovative "reverse Mendelian randomization" (MR) approach.
We applied this technique to genetic and biomarker data from 4147 participants in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial, all with known type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance. Two-sample MR was conducted using variants associated with creatinine-based eGFR (eGFR
) from the CKDGen Consortium (n = 133814) to estimate the effect of genetically decreased eGFR
on 238 serum biomarkers.
With reverse MR, trefoil factor 3 (TFF3) was identified as a protein that is increased owing to decreased eGFR
(β = 1.86 SD per SD decrease eGFR
; 95% CI, 0.95-2.76;
= 8.0 × 10
). Reverse MR findings were consistent with epidemiological associations for incident CKD in ORIGIN (OR = 1.28 per SD increase in TFF3; 95% CI, 1.18-1.38;
= 4.58 × 10
). Addition of TFF3 significantly improved discrimination for incident CKD relative to eGFR
alone (net reclassification improvement = 0.211;
= 9.56 × 10
) and in models including additional risk factors.
Our results suggest TFF3 is a valuable diagnostic marker for early CKD in dysglycemic populations and acts as a proof of concept for the application of this novel MR technique to identify diagnostic biomarkers for other chronic diseases.
NCT00069784.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>30337280</pmid><doi>10.1373/clinchem.2018.291104</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Clinical chemistry (Baltimore, Md.), 2019-03, Vol.65 (3), p.427-436 |
| issn | 0009-9147 1530-8561 |
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| source | MEDLINE; Oxford University Press Journals Current |
| subjects | Aged Biomarkers Biomarkers - blood Cardiovascular disease Chronic illnesses Consortia Data processing Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diabetic Nephropathies - diagnosis Diagnostic systems Epidemiology Epidermal growth factor receptors ErbB Receptors - genetics Ethnicity Female Genome-Wide Association Study - statistics & numerical data Genomes Glucose Glucose tolerance Humans Kidney diseases Kidneys Male Medical diagnosis Mendelian Randomization Analysis - methods Middle Aged Mutation Proof of Concept Study Proteins Randomization Reclassification Renal Insufficiency, Chronic - diagnosis Risk analysis Risk factors Trefoil factor Trefoil Factor-3 - blood |
| title | A Mendelian Randomization-Based Approach to Identify Early and Sensitive Diagnostic Biomarkers of Disease |
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