Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline
Abstract Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI),...
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| Veröffentlicht in: | Neurobiology of aging 2010-08, Vol.31 (8), p.1419-1428 |
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| creator | Nettiksimmons, J Harvey, D Brewer, J Carmichael, O DeCarli, C Jack, C.R Petersen, R Shaw, L.M Trojanowski, J.Q Weiner, M.W Beckett, L |
| description | Abstract Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD. |
| doi_str_mv | 10.1016/j.neurobiolaging.2010.04.025 |
| format | Article |
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The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.</description><identifier>ISSN: 0197-4580</identifier><identifier>EISSN: 1558-1497</identifier><identifier>DOI: 10.1016/j.neurobiolaging.2010.04.025</identifier><identifier>PMID: 20542598</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; Aged, 80 and over ; Alzheimer Disease - cerebrospinal fluid ; Alzheimer Disease - classification ; Alzheimer Disease - pathology ; Alzheimer's disease ; Amyloid beta-protein ; Biomarkers - cerebrospinal fluid ; Cerebrospinal fluid ; Clustering ; Cognition ; Cognition Disorders - cerebrospinal fluid ; Cognition Disorders - classification ; Cognition Disorders - pathology ; Cross-Sectional Studies ; Dementia ; Early diagnosis ; Female ; Follow-Up Studies ; Hippocampal volume ; Humans ; Internal Medicine ; Longitudinal Studies ; Magnetic Resonance Imaging - methods ; Male ; Neurology ; Normal controls ; Predictive Value of Tests ; Prospective Studies ; Structural magnetic resonance imaging ; Tau protein</subject><ispartof>Neurobiology of aging, 2010-08, Vol.31 (8), p.1419-1428</ispartof><rights>Elsevier Inc.</rights><rights>2010 Elsevier Inc.</rights><rights>2010 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-a6d207fb0dd3055069b357978f6aa1abf2c84381d6d57f7f90271eb44a70a51c3</citedby><cites>FETCH-LOGICAL-c526t-a6d207fb0dd3055069b357978f6aa1abf2c84381d6d57f7f90271eb44a70a51c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.neurobiolaging.2010.04.025$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20542598$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nettiksimmons, J</creatorcontrib><creatorcontrib>Harvey, D</creatorcontrib><creatorcontrib>Brewer, J</creatorcontrib><creatorcontrib>Carmichael, O</creatorcontrib><creatorcontrib>DeCarli, C</creatorcontrib><creatorcontrib>Jack, C.R</creatorcontrib><creatorcontrib>Petersen, R</creatorcontrib><creatorcontrib>Shaw, L.M</creatorcontrib><creatorcontrib>Trojanowski, J.Q</creatorcontrib><creatorcontrib>Weiner, M.W</creatorcontrib><creatorcontrib>Beckett, L</creatorcontrib><creatorcontrib>The Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><title>Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline</title><title>Neurobiology of aging</title><addtitle>Neurobiol Aging</addtitle><description>Abstract Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Alzheimer Disease - cerebrospinal fluid</subject><subject>Alzheimer Disease - classification</subject><subject>Alzheimer Disease - pathology</subject><subject>Alzheimer's disease</subject><subject>Amyloid beta-protein</subject><subject>Biomarkers - cerebrospinal fluid</subject><subject>Cerebrospinal fluid</subject><subject>Clustering</subject><subject>Cognition</subject><subject>Cognition Disorders - cerebrospinal fluid</subject><subject>Cognition Disorders - classification</subject><subject>Cognition Disorders - pathology</subject><subject>Cross-Sectional Studies</subject><subject>Dementia</subject><subject>Early diagnosis</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Hippocampal volume</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Longitudinal Studies</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Neurology</subject><subject>Normal controls</subject><subject>Predictive Value of Tests</subject><subject>Prospective Studies</subject><subject>Structural magnetic resonance imaging</subject><subject>Tau protein</subject><issn>0197-4580</issn><issn>1558-1497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkkFv1DAQhSMEokvhLyAfkDhlO3bsOJEQEqooVKrEoXC2HHuy8taxFzupuv8ehy1IcIGTD_PePOt9U1VvKGwp0PZivw24pDi46PXOhd2WQRkB3wITT6oNFaKrKe_l02oDtJc1Fx2cVS9y3gOA5LJ9Xp0xEJyJvttUD7fLMB8PmMmgM1oSAzGYcEgxH1zQnox-cZboYMmkdwFnZ0jCHIMOBombfn6hjNIdpkxcICGmqdjQW0z-SA4JrTMzMXEX3OzukVg03gV8WT0btc_46vE9r75dffx6-bm--fLp-vLDTW0Ea-dat5aBHAewtgEhoO2HRshedmOrNdXDyEzHm47a1go5yrEHJikOnGsJWlDTnFdvT3sPKX5fMM9qctmg9zpgXLKSggsOgnX_VjaNKMH9qnx3UppSU044qkMqVaSjoqBWSGqv_oSkVkgKuCqQiv31Y9AyTGh_m39RKYKrkwBLMfcOk8rGYSncuoRmVja6_016_9eitXtntL_DI-Z9XFJhnBVVmSlQt-vBrPdCy6kwgL75AdOswsw</recordid><startdate>20100801</startdate><enddate>20100801</enddate><creator>Nettiksimmons, J</creator><creator>Harvey, D</creator><creator>Brewer, J</creator><creator>Carmichael, O</creator><creator>DeCarli, C</creator><creator>Jack, C.R</creator><creator>Petersen, R</creator><creator>Shaw, L.M</creator><creator>Trojanowski, J.Q</creator><creator>Weiner, M.W</creator><creator>Beckett, L</creator><general>Elsevier Inc</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>7X8</scope><scope>7TK</scope></search><sort><creationdate>20100801</creationdate><title>Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline</title><author>Nettiksimmons, J ; Harvey, D ; Brewer, J ; Carmichael, O ; DeCarli, C ; Jack, C.R ; Petersen, R ; Shaw, L.M ; Trojanowski, J.Q ; Weiner, M.W ; Beckett, L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-a6d207fb0dd3055069b357978f6aa1abf2c84381d6d57f7f90271eb44a70a51c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Alzheimer Disease - cerebrospinal fluid</topic><topic>Alzheimer Disease - classification</topic><topic>Alzheimer Disease - pathology</topic><topic>Alzheimer's disease</topic><topic>Amyloid beta-protein</topic><topic>Biomarkers - cerebrospinal fluid</topic><topic>Cerebrospinal fluid</topic><topic>Clustering</topic><topic>Cognition</topic><topic>Cognition Disorders - cerebrospinal fluid</topic><topic>Cognition Disorders - classification</topic><topic>Cognition Disorders - pathology</topic><topic>Cross-Sectional Studies</topic><topic>Dementia</topic><topic>Early diagnosis</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Hippocampal volume</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Longitudinal Studies</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Neurology</topic><topic>Normal controls</topic><topic>Predictive Value of Tests</topic><topic>Prospective Studies</topic><topic>Structural magnetic resonance imaging</topic><topic>Tau protein</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nettiksimmons, J</creatorcontrib><creatorcontrib>Harvey, D</creatorcontrib><creatorcontrib>Brewer, J</creatorcontrib><creatorcontrib>Carmichael, O</creatorcontrib><creatorcontrib>DeCarli, C</creatorcontrib><creatorcontrib>Jack, C.R</creatorcontrib><creatorcontrib>Petersen, R</creatorcontrib><creatorcontrib>Shaw, L.M</creatorcontrib><creatorcontrib>Trojanowski, J.Q</creatorcontrib><creatorcontrib>Weiner, M.W</creatorcontrib><creatorcontrib>Beckett, L</creatorcontrib><creatorcontrib>The Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Neurosciences Abstracts</collection><jtitle>Neurobiology of aging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nettiksimmons, J</au><au>Harvey, D</au><au>Brewer, J</au><au>Carmichael, O</au><au>DeCarli, C</au><au>Jack, C.R</au><au>Petersen, R</au><au>Shaw, L.M</au><au>Trojanowski, J.Q</au><au>Weiner, M.W</au><au>Beckett, L</au><aucorp>The Alzheimer's Disease Neuroimaging Initiative</aucorp><aucorp>Alzheimer's Disease Neuroimaging Initiative</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline</atitle><jtitle>Neurobiology of aging</jtitle><addtitle>Neurobiol Aging</addtitle><date>2010-08-01</date><risdate>2010</risdate><volume>31</volume><issue>8</issue><spage>1419</spage><epage>1428</epage><pages>1419-1428</pages><issn>0197-4580</issn><eissn>1558-1497</eissn><abstract>Abstract Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>20542598</pmid><doi>10.1016/j.neurobiolaging.2010.04.025</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Neurobiology of aging, 2010-08, Vol.31 (8), p.1419-1428 |
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| subjects | Aged Aged, 80 and over Alzheimer Disease - cerebrospinal fluid Alzheimer Disease - classification Alzheimer Disease - pathology Alzheimer's disease Amyloid beta-protein Biomarkers - cerebrospinal fluid Cerebrospinal fluid Clustering Cognition Cognition Disorders - cerebrospinal fluid Cognition Disorders - classification Cognition Disorders - pathology Cross-Sectional Studies Dementia Early diagnosis Female Follow-Up Studies Hippocampal volume Humans Internal Medicine Longitudinal Studies Magnetic Resonance Imaging - methods Male Neurology Normal controls Predictive Value of Tests Prospective Studies Structural magnetic resonance imaging Tau protein |
| title | Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline |
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