Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease

Introduction Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including beta-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linke...

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Veröffentlicht in:Clinical proteomics 2020-05, Vol.17 (1), p.19-19, Article 19
Hauptverfasser: Zhou, Maotian, Haque, Rafi U., Dammer, Eric B., Duong, Duc M., Ping, Lingyan, Johnson, Erik C. B., Lah, James J., Levey, Allan, Seyfried, Nicholas T.
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container_issue 1
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container_title Clinical proteomics
container_volume 17
creator Zhou, Maotian
Haque, Rafi U.
Dammer, Eric B.
Duong, Duc M.
Ping, Lingyan
Johnson, Erik C. B.
Lah, James J.
Levey, Allan
Seyfried, Nicholas T.
description Introduction Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including beta-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment. Method We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (n = 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time. Results Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discri
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B. ; Lah, James J. ; Levey, Allan ; Seyfried, Nicholas T.</creator><creatorcontrib>Zhou, Maotian ; Haque, Rafi U. ; Dammer, Eric B. ; Duong, Duc M. ; Ping, Lingyan ; Johnson, Erik C. B. ; Lah, James J. ; Levey, Allan ; Seyfried, Nicholas T.</creatorcontrib><description>Introduction Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including beta-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment. Method We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (n = 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time. Results Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discriminate between individuals with AD and non-AD cognitive impairment as well as Tau/beta-amyloid ratio. Notably, SMOC1 levels in postmortem brain are highly correlated with AD pathology even in the preclinical stage of disease, indicating that CSF SMOC1 levels reflect underlying brain pathology specific for AD. Conclusion Collectively these findings highlight the utility of targeted MS approaches to quantify biomarkers associated with AD that could be used for monitoring disease progression, stratifying patients for clinical trials and measuring therapeutic response.</description><identifier>ISSN: 1542-6416</identifier><identifier>EISSN: 1559-0275</identifier><identifier>DOI: 10.1186/s12014-020-09285-8</identifier><identifier>PMID: 32514259</identifier><language>eng</language><publisher>LONDON: Springer Nature</publisher><subject>Advertising executives ; Alzheimer's disease ; Biochemical Research Methods ; Biochemistry &amp; Molecular Biology ; Biological markers ; Brain ; Development and progression ; Life Sciences &amp; Biomedicine ; Mass spectrometry ; Medical research ; Proteins ; Science &amp; Technology ; Target marketing</subject><ispartof>Clinical proteomics, 2020-05, Vol.17 (1), p.19-19, Article 19</ispartof><rights>The Author(s) 2020.</rights><rights>COPYRIGHT 2020 BioMed Central Ltd.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>52</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000556830200002</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c500t-fb353e8933c418017015196a3a3516cf597120e7c79cda95953a17b92b541e203</citedby><cites>FETCH-LOGICAL-c500t-fb353e8933c418017015196a3a3516cf597120e7c79cda95953a17b92b541e203</cites><orcidid>0000-0003-2947-7606 ; 0000-0002-4507-624X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257173/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257173/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,729,782,786,887,27931,27932,28255,53798,53800</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32514259$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhou, Maotian</creatorcontrib><creatorcontrib>Haque, Rafi U.</creatorcontrib><creatorcontrib>Dammer, Eric B.</creatorcontrib><creatorcontrib>Duong, Duc M.</creatorcontrib><creatorcontrib>Ping, Lingyan</creatorcontrib><creatorcontrib>Johnson, Erik C. B.</creatorcontrib><creatorcontrib>Lah, James J.</creatorcontrib><creatorcontrib>Levey, Allan</creatorcontrib><creatorcontrib>Seyfried, Nicholas T.</creatorcontrib><title>Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease</title><title>Clinical proteomics</title><addtitle>CLIN PROTEOM</addtitle><addtitle>Clin Proteomics</addtitle><description>Introduction Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including beta-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment. Method We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (n = 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time. Results Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discriminate between individuals with AD and non-AD cognitive impairment as well as Tau/beta-amyloid ratio. Notably, SMOC1 levels in postmortem brain are highly correlated with AD pathology even in the preclinical stage of disease, indicating that CSF SMOC1 levels reflect underlying brain pathology specific for AD. Conclusion Collectively these findings highlight the utility of targeted MS approaches to quantify biomarkers associated with AD that could be used for monitoring disease progression, stratifying patients for clinical trials and measuring therapeutic response.</description><subject>Advertising executives</subject><subject>Alzheimer's disease</subject><subject>Biochemical Research Methods</subject><subject>Biochemistry &amp; Molecular Biology</subject><subject>Biological markers</subject><subject>Brain</subject><subject>Development and progression</subject><subject>Life Sciences &amp; Biomedicine</subject><subject>Mass spectrometry</subject><subject>Medical research</subject><subject>Proteins</subject><subject>Science &amp; Technology</subject><subject>Target marketing</subject><issn>1542-6416</issn><issn>1559-0275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>AOWDO</sourceid><recordid>eNqNkluL3CAYhkNp6R7aP9CLIhS6hZKth5jEm4Vh6AkWerO9FmO-zLg1Oqtmy_TX1zTbYQd6UQUVfd6XT32L4hXBl4S09YdIKCZViSkusaAtL9snxSnhXOSthj-d1xUt64rUJ8VZjLcYU1GJ9nlxwignFeXitLi9UWEDCXo0qhhR3IFOwY-Qwh4lj-4m5ZIZ9qgLyriyh2DuM6shQBd83BmnLBrsZHrUGT-q8ANCRMahlf21BTNCuIioNxFUhBfFs0HZCC8f5vPi-6ePN-sv5fW3z1_Xq-tSc4xTOXSMM2gFY7oiLSYNJpyIWjHFOKn1wEWT7w2NboTuleCCM0WaTtCOVwQoZufF1eK7m7oReg0uBWXlLphc3156ZeTxiTNbufH3sqG8IQ3LBu8eDIK_myAmOZqowVrlwE9R0orkhitOMvpmQTfKgjRu8NlRz7hc1bRhdR7aTF3-g8q9h9Fo72Awef9I8PaRYAvKpm30dkrGu3gM0gXU-TdigOFwTYLlHBK5hETmkMg_IZGz6PXjBzpI_qYiA-0C_ITOD1EbcBoOGMaY87pl2TI3ujZJzXWt_eRSlr7_fyn7Ddet19c</recordid><startdate>20200529</startdate><enddate>20200529</enddate><creator>Zhou, Maotian</creator><creator>Haque, Rafi U.</creator><creator>Dammer, Eric B.</creator><creator>Duong, Duc M.</creator><creator>Ping, Lingyan</creator><creator>Johnson, Erik C. B.</creator><creator>Lah, James J.</creator><creator>Levey, Allan</creator><creator>Seyfried, Nicholas T.</creator><general>Springer Nature</general><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>AOWDO</scope><scope>BLEPL</scope><scope>DTL</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-2947-7606</orcidid><orcidid>https://orcid.org/0000-0002-4507-624X</orcidid></search><sort><creationdate>20200529</creationdate><title>Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease</title><author>Zhou, Maotian ; Haque, Rafi U. ; Dammer, Eric B. ; Duong, Duc M. ; Ping, Lingyan ; Johnson, Erik C. B. ; Lah, James J. ; Levey, Allan ; Seyfried, Nicholas T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c500t-fb353e8933c418017015196a3a3516cf597120e7c79cda95953a17b92b541e203</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Advertising executives</topic><topic>Alzheimer's disease</topic><topic>Biochemical Research Methods</topic><topic>Biochemistry &amp; Molecular Biology</topic><topic>Biological markers</topic><topic>Brain</topic><topic>Development and progression</topic><topic>Life Sciences &amp; Biomedicine</topic><topic>Mass spectrometry</topic><topic>Medical research</topic><topic>Proteins</topic><topic>Science &amp; Technology</topic><topic>Target marketing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Maotian</creatorcontrib><creatorcontrib>Haque, Rafi U.</creatorcontrib><creatorcontrib>Dammer, Eric B.</creatorcontrib><creatorcontrib>Duong, Duc M.</creatorcontrib><creatorcontrib>Ping, Lingyan</creatorcontrib><creatorcontrib>Johnson, Erik C. B.</creatorcontrib><creatorcontrib>Lah, James J.</creatorcontrib><creatorcontrib>Levey, Allan</creatorcontrib><creatorcontrib>Seyfried, Nicholas T.</creatorcontrib><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Clinical proteomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhou, Maotian</au><au>Haque, Rafi U.</au><au>Dammer, Eric B.</au><au>Duong, Duc M.</au><au>Ping, Lingyan</au><au>Johnson, Erik C. B.</au><au>Lah, James J.</au><au>Levey, Allan</au><au>Seyfried, Nicholas T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease</atitle><jtitle>Clinical proteomics</jtitle><stitle>CLIN PROTEOM</stitle><addtitle>Clin Proteomics</addtitle><date>2020-05-29</date><risdate>2020</risdate><volume>17</volume><issue>1</issue><spage>19</spage><epage>19</epage><pages>19-19</pages><artnum>19</artnum><issn>1542-6416</issn><eissn>1559-0275</eissn><abstract>Introduction Alzheimer's disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline. Protein biomarkers of AD brain pathology, including beta-amyloid and Tau, are reflected in cerebrospinal fluid (CSF), yet the identification of additional biomarkers linked to other brain pathophysiologies remains elusive. We recently reported a multiplex tandem-mass tag (TMT) CSF proteomic analysis of nearly 3000 proteins, following depletion of highly abundant proteins and off-line fractionation, across control and AD cases. Of these, over 500 proteins were significantly increased or decreased in AD, including markers reflecting diverse biological functions in brain. Here, we use a targeted mass spectrometry (MS) approach, termed parallel reaction monitoring (PRM), to quantify select CSF biomarkers without pre-depletion or fractionation to assess the reproducibility of our findings and the specificity of changes for AD versus other causes of cognitive impairment. Method We nominated 41 proteins (94 peptides) from the TMT CSF discovery dataset, representing a variety of brain cell-types and biological functions, for label-free PRM analysis in a replication cohort of 88 individuals that included 20 normal controls, 37 clinically diagnosed AD cases and 31 cases with non-AD cognitive impairment. To control for technical variables, isotopically labeled synthetic heavy peptide standards were added into each of the 88 CSF tryptic digests. Furthermore, a peptide pool, representing an equivalent amount of peptide from all samples, was analyzed (n = 10) across each batch. Together, this approach enabled us to assess both the intra- and inter-sample differences in peptide signal response and retention time. Results Despite differences in sample preparation, quantitative MS approaches and patient samples, 25 proteins, including Tau, had a consistent and significant change in AD in both the discovery and replication cohorts. Validated CSF markers with low coefficient of variation included the protein products for neuronal/synaptic (GDA, GAP43, SYN1, BASP1, YWHAB, YWHAZ, UCHL1, STMN1 and MAP1B), glial/inflammation (SMOC1, ITGAM, CHI3L1, SPP1, and CHIT1) and metabolic (PKM, ALDOA and FABP3) related genes. Logistical regression analyses revealed several proteins with high sensitivity and specificity for classifying AD cases from controls and other non-AD dementias. SMOC1, YWHAZ, ALDOA and MAP1B emerged as biomarker candidates that could best discriminate between individuals with AD and non-AD cognitive impairment as well as Tau/beta-amyloid ratio. Notably, SMOC1 levels in postmortem brain are highly correlated with AD pathology even in the preclinical stage of disease, indicating that CSF SMOC1 levels reflect underlying brain pathology specific for AD. Conclusion Collectively these findings highlight the utility of targeted MS approaches to quantify biomarkers associated with AD that could be used for monitoring disease progression, stratifying patients for clinical trials and measuring therapeutic response.</abstract><cop>LONDON</cop><pub>Springer Nature</pub><pmid>32514259</pmid><doi>10.1186/s12014-020-09285-8</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-2947-7606</orcidid><orcidid>https://orcid.org/0000-0002-4507-624X</orcidid><oa>free_for_read</oa></addata></record>
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subjects Advertising executives
Alzheimer's disease
Biochemical Research Methods
Biochemistry & Molecular Biology
Biological markers
Brain
Development and progression
Life Sciences & Biomedicine
Mass spectrometry
Medical research
Proteins
Science & Technology
Target marketing
title Targeted mass spectrometry to quantify brain-derived cerebrospinal fluid biomarkers in Alzheimer's disease
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