Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease
Introduction The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co‐expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD. Methods We performed WGCNA to identify modules a...
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| Veröffentlicht in: | Alzheimer's & dementia : diagnosis, assessment & disease monitoring assessment & disease monitoring, 2022, Vol.14 (1), p.e12354-n/a |
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| creator | Kim, Bo‐Hyun Vasanthakumar, Aparna Li, Qingqin S. Nudelman, Kelly N.H. Risacher, Shannon L. Davis, Justin W. Idler, Kenneth Lee, Jong‐Min Seo, Sang Won Waring, Jeffrey F. Saykin, Andrew J. Nho, Kwangsik |
| description | Introduction
The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co‐expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD.
Methods
We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers.
Results
WGCNA identified five modules associated with biological clocks, with the module designated as “purple” showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers.
Conclusion
Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD.
Highlights
Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes.
Weighted gene co‐expression network analysis (WGCNA) found five modules related to biological aging.
Among the hub genes of the module, CX3CR1 was downregulated in AD.
The CX3CR1 expression level was associated with cognitive performance and brain atrophy. |
| doi_str_mv | 10.1002/dad2.12354 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_2720931163</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A761372246</galeid><sourcerecordid>A761372246</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4604-c48e527a04a5621bf26e92a4354c82e224e1f3ccfd7b3ba38733c0df2af597443</originalsourceid><addsrcrecordid>eNp9kU1v1DAQhiMEolXphR-ALHEAIe3ir8TJMepCW6mCC5wjxx5nXSX24sm2LGd-ON6mIMQBWfJYM8-8HvstipeMrhml_L3Vlq8ZF6V8UpzmwFe14s3Tv84nxTniLaWUyYZLRp8XJ6JitWKNPC1-XocZhqRnfwdEBz0e0COJjmw-tWSCeXsYcy2GXLNkgAAEvu8SIB5z3kKYvfOADyUkGjEar2ew5N7PW9L7OMbBGz0SPfgwEB9IO_7Ygp8gvUFiPYJGeFE8c3pEOH-MZ8XXjx--XFytbj5fXl-0NysjKyrzXkPJlaZSlxVnveMVNFzL_HZTc-BcAnPCGGdVL3otaiWEodZx7cpGSSnOireL7i7Fb3vAuZs8GhhHHSDuseOK00YwVomMvv4HvY37lP_nSJW1qIRSKlPrhRr0CJ0PLs5Jm7wsTN7EAM7nfKsqJlQer8oN75YGkyJiAtftkp90OnSMdkc_u6Of3YOfGX71OMO-n8D-QX-7lwG2APf5msN_pLpNu-GL6C829KoZ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2758363777</pqid></control><display><type>article</type><title>Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease</title><source>Wiley Online Library Open Access</source><source>DOAJ Directory of Open Access Journals</source><source>Wiley Online Library Journals Frontfile Complete</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><creator>Kim, Bo‐Hyun ; Vasanthakumar, Aparna ; Li, Qingqin S. ; Nudelman, Kelly N.H. ; Risacher, Shannon L. ; Davis, Justin W. ; Idler, Kenneth ; Lee, Jong‐Min ; Seo, Sang Won ; Waring, Jeffrey F. ; Saykin, Andrew J. ; Nho, Kwangsik</creator><creatorcontrib>Kim, Bo‐Hyun ; Vasanthakumar, Aparna ; Li, Qingqin S. ; Nudelman, Kelly N.H. ; Risacher, Shannon L. ; Davis, Justin W. ; Idler, Kenneth ; Lee, Jong‐Min ; Seo, Sang Won ; Waring, Jeffrey F. ; Saykin, Andrew J. ; Nho, Kwangsik ; Alzheimer's Disease Neuroimaging Initiative (ADNI) ; for the Alzheimer's Disease Neuroimaging Initiative (ADNI)</creatorcontrib><description>Introduction
The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co‐expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD.
Methods
We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers.
Results
WGCNA identified five modules associated with biological clocks, with the module designated as “purple” showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers.
Conclusion
Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD.
Highlights
Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes.
Weighted gene co‐expression network analysis (WGCNA) found five modules related to biological aging.
Among the hub genes of the module, CX3CR1 was downregulated in AD.
The CX3CR1 expression level was associated with cognitive performance and brain atrophy.</description><identifier>ISSN: 2352-8729</identifier><identifier>EISSN: 2352-8729</identifier><identifier>DOI: 10.1002/dad2.12354</identifier><identifier>PMID: 36187194</identifier><language>eng</language><publisher>United States: John Wiley & Sons, Inc</publisher><subject>AD biomarker ; Advertising executives ; Alzheimer's disease ; biological aging ; Biological clocks ; Cognition & reasoning ; CX3CR1 ; Dementia ; DNA ; DNA methylation ; epigenetic clocks ; Gene expression ; Genes ; Genetic aspects ; Genetic research ; Methylation ; Risk factors ; telomere length ; weighted gene co‐expression network analysis (WGCNA)</subject><ispartof>Alzheimer's & dementia : diagnosis, assessment & disease monitoring, 2022, Vol.14 (1), p.e12354-n/a</ispartof><rights>2022 The Authors. published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.</rights><rights>2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>2022. This work 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-c4604-c48e527a04a5621bf26e92a4354c82e224e1f3ccfd7b3ba38733c0df2af597443</citedby><cites>FETCH-LOGICAL-c4604-c48e527a04a5621bf26e92a4354c82e224e1f3ccfd7b3ba38733c0df2af597443</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fdad2.12354$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fdad2.12354$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,1411,4010,11541,27900,27901,27902,45550,45551,46027,46451</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36187194$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Bo‐Hyun</creatorcontrib><creatorcontrib>Vasanthakumar, Aparna</creatorcontrib><creatorcontrib>Li, Qingqin S.</creatorcontrib><creatorcontrib>Nudelman, Kelly N.H.</creatorcontrib><creatorcontrib>Risacher, Shannon L.</creatorcontrib><creatorcontrib>Davis, Justin W.</creatorcontrib><creatorcontrib>Idler, Kenneth</creatorcontrib><creatorcontrib>Lee, Jong‐Min</creatorcontrib><creatorcontrib>Seo, Sang Won</creatorcontrib><creatorcontrib>Waring, Jeffrey F.</creatorcontrib><creatorcontrib>Saykin, Andrew J.</creatorcontrib><creatorcontrib>Nho, Kwangsik</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative (ADNI)</creatorcontrib><creatorcontrib>for the Alzheimer's Disease Neuroimaging Initiative (ADNI)</creatorcontrib><title>Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease</title><title>Alzheimer's & dementia : diagnosis, assessment & disease monitoring</title><addtitle>Alzheimers Dement (Amst)</addtitle><description>Introduction
The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co‐expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD.
Methods
We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers.
Results
WGCNA identified five modules associated with biological clocks, with the module designated as “purple” showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers.
Conclusion
Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD.
Highlights
Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes.
Weighted gene co‐expression network analysis (WGCNA) found five modules related to biological aging.
Among the hub genes of the module, CX3CR1 was downregulated in AD.
The CX3CR1 expression level was associated with cognitive performance and brain atrophy.</description><subject>AD biomarker</subject><subject>Advertising executives</subject><subject>Alzheimer's disease</subject><subject>biological aging</subject><subject>Biological clocks</subject><subject>Cognition & reasoning</subject><subject>CX3CR1</subject><subject>Dementia</subject><subject>DNA</subject><subject>DNA methylation</subject><subject>epigenetic clocks</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic research</subject><subject>Methylation</subject><subject>Risk factors</subject><subject>telomere length</subject><subject>weighted gene co‐expression network analysis (WGCNA)</subject><issn>2352-8729</issn><issn>2352-8729</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kU1v1DAQhiMEolXphR-ALHEAIe3ir8TJMepCW6mCC5wjxx5nXSX24sm2LGd-ON6mIMQBWfJYM8-8HvstipeMrhml_L3Vlq8ZF6V8UpzmwFe14s3Tv84nxTniLaWUyYZLRp8XJ6JitWKNPC1-XocZhqRnfwdEBz0e0COJjmw-tWSCeXsYcy2GXLNkgAAEvu8SIB5z3kKYvfOADyUkGjEar2ew5N7PW9L7OMbBGz0SPfgwEB9IO_7Ygp8gvUFiPYJGeFE8c3pEOH-MZ8XXjx--XFytbj5fXl-0NysjKyrzXkPJlaZSlxVnveMVNFzL_HZTc-BcAnPCGGdVL3otaiWEodZx7cpGSSnOireL7i7Fb3vAuZs8GhhHHSDuseOK00YwVomMvv4HvY37lP_nSJW1qIRSKlPrhRr0CJ0PLs5Jm7wsTN7EAM7nfKsqJlQer8oN75YGkyJiAtftkp90OnSMdkc_u6Of3YOfGX71OMO-n8D-QX-7lwG2APf5msN_pLpNu-GL6C829KoZ</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Kim, Bo‐Hyun</creator><creator>Vasanthakumar, Aparna</creator><creator>Li, Qingqin S.</creator><creator>Nudelman, Kelly N.H.</creator><creator>Risacher, Shannon L.</creator><creator>Davis, Justin W.</creator><creator>Idler, Kenneth</creator><creator>Lee, Jong‐Min</creator><creator>Seo, Sang Won</creator><creator>Waring, Jeffrey F.</creator><creator>Saykin, Andrew J.</creator><creator>Nho, Kwangsik</creator><general>John Wiley & Sons, Inc</general><scope>24P</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IAO</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>2022</creationdate><title>Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease</title><author>Kim, Bo‐Hyun ; Vasanthakumar, Aparna ; Li, Qingqin S. ; Nudelman, Kelly N.H. ; Risacher, Shannon L. ; Davis, Justin W. ; Idler, Kenneth ; Lee, Jong‐Min ; Seo, Sang Won ; Waring, Jeffrey F. ; Saykin, Andrew J. ; Nho, Kwangsik</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4604-c48e527a04a5621bf26e92a4354c82e224e1f3ccfd7b3ba38733c0df2af597443</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>AD biomarker</topic><topic>Advertising executives</topic><topic>Alzheimer's disease</topic><topic>biological aging</topic><topic>Biological clocks</topic><topic>Cognition & reasoning</topic><topic>CX3CR1</topic><topic>Dementia</topic><topic>DNA</topic><topic>DNA methylation</topic><topic>epigenetic clocks</topic><topic>Gene expression</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genetic research</topic><topic>Methylation</topic><topic>Risk factors</topic><topic>telomere length</topic><topic>weighted gene co‐expression network analysis (WGCNA)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Bo‐Hyun</creatorcontrib><creatorcontrib>Vasanthakumar, Aparna</creatorcontrib><creatorcontrib>Li, Qingqin S.</creatorcontrib><creatorcontrib>Nudelman, Kelly N.H.</creatorcontrib><creatorcontrib>Risacher, Shannon L.</creatorcontrib><creatorcontrib>Davis, Justin W.</creatorcontrib><creatorcontrib>Idler, Kenneth</creatorcontrib><creatorcontrib>Lee, Jong‐Min</creatorcontrib><creatorcontrib>Seo, Sang Won</creatorcontrib><creatorcontrib>Waring, Jeffrey F.</creatorcontrib><creatorcontrib>Saykin, Andrew J.</creatorcontrib><creatorcontrib>Nho, Kwangsik</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative (ADNI)</creatorcontrib><creatorcontrib>for the Alzheimer's Disease Neuroimaging Initiative (ADNI)</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale Academic OneFile</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</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 Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content 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>Alzheimer's & dementia : diagnosis, assessment & disease monitoring</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Bo‐Hyun</au><au>Vasanthakumar, Aparna</au><au>Li, Qingqin S.</au><au>Nudelman, Kelly N.H.</au><au>Risacher, Shannon L.</au><au>Davis, Justin W.</au><au>Idler, Kenneth</au><au>Lee, Jong‐Min</au><au>Seo, Sang Won</au><au>Waring, Jeffrey F.</au><au>Saykin, Andrew J.</au><au>Nho, Kwangsik</au><aucorp>Alzheimer's Disease Neuroimaging Initiative (ADNI)</aucorp><aucorp>for the Alzheimer's Disease Neuroimaging Initiative (ADNI)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease</atitle><jtitle>Alzheimer's & dementia : diagnosis, assessment & disease monitoring</jtitle><addtitle>Alzheimers Dement (Amst)</addtitle><date>2022</date><risdate>2022</risdate><volume>14</volume><issue>1</issue><spage>e12354</spage><epage>n/a</epage><pages>e12354-n/a</pages><issn>2352-8729</issn><eissn>2352-8729</eissn><abstract>Introduction
The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co‐expression network analysis (WGCNA) to identify modules and dysregulated genesinvolved in biological aging in AD.
Methods
We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers.
Results
WGCNA identified five modules associated with biological clocks, with the module designated as “purple” showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers.
Conclusion
Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD.
Highlights
Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes.
Weighted gene co‐expression network analysis (WGCNA) found five modules related to biological aging.
Among the hub genes of the module, CX3CR1 was downregulated in AD.
The CX3CR1 expression level was associated with cognitive performance and brain atrophy.</abstract><cop>United States</cop><pub>John Wiley & Sons, Inc</pub><pmid>36187194</pmid><doi>10.1002/dad2.12354</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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| source | Wiley Online Library Open Access; DOAJ Directory of Open Access Journals; Wiley Online Library Journals Frontfile Complete; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central |
| subjects | AD biomarker Advertising executives Alzheimer's disease biological aging Biological clocks Cognition & reasoning CX3CR1 Dementia DNA DNA methylation epigenetic clocks Gene expression Genes Genetic aspects Genetic research Methylation Risk factors telomere length weighted gene co‐expression network analysis (WGCNA) |
| title | Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease |
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