Blood transcriptome analysis for Alzheimer’ disease in Hong Kong Chinese population
Background Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer’s disease (AD) patients are poorly understood. Method We conducted transcriptome profiling of 422 participants (208 normal controls and 214 pati...
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| Veröffentlicht in: | Alzheimer's & dementia 2021-12, Vol.17, p.e056643-n/a |
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| container_title | Alzheimer's & dementia |
| container_volume | 17 |
| creator | Zhong, Huan Zhou, Xiaopu Jiang, Yuanbing Chen, Yu Lai, Nicole Chit Hang Tong, Estella Pui‐Sze Lo, Ronnie M.N. Kwok, Timothy CY Mok, Vincent C.T. Ip, Fanny C. F. Mok, Kin Y Hardy, John Fu, Amy K.Y. Ip, Nancy Y. |
| description | Background
Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer’s disease (AD) patients are poorly understood.
Method
We conducted transcriptome profiling of 422 participants (208 normal controls and 214 patients with AD) from the Hong Kong Chinese population. WGCNA (weighted correlation network analysis) was performed to construct a co‐expression network to identify modules associated with AD and AD‐associated biomarkers.
Result
Co‐expression modules exerting significant association with AD and AD plasma biomarkers (e.g., Aβ and NFL) were identified. Pathway enrichment analysis suggested their possible involvement in specific biological pathways. Motif analysis further revealed the potential mechanisms that driving the observed blood transcriptomic changes observed in AD.
Conclusion
The co‐expression network analysis of the AD blood transcriptome changes may facilitate a better understanding of AD progression, as well as the identification of potential targets for disease intervention and monitoring. |
| doi_str_mv | 10.1002/alz.056643 |
| format | Article |
| fullrecord | <record><control><sourceid>wiley_pubme</sourceid><recordid>TN_cdi_pubmed_primary_35109159</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>ALZ056643</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1763-a504b510ad4c0caddaa0eed2ad1738ba9ef273d9ea1b9c247fbe0cb137d4ab7a3</originalsourceid><addsrcrecordid>eNo9kEFOwzAQRS0EoqWw4QDIF0ix4zhuliUCiqjEhm7YRON4Qo2cOIpboXbFNbgeJyFVoJuZr5mv0Z9HyDVnU85YfAtuP2UyTRNxQsZcyjiSscpOjzplI3IRwgdjCZtxeU5GQnKWcZmNyerOeW_opoMmlJ1tN75GCg24XbCBVr6jc7dfo62x-_n6psYGhIDUNnThm3f6fCj52jbYD1vfbh1srG8uyVkFLuDVX5-Q1cP9a76Ili-PT_l8GZVcpSICyRLdRwGTlKwEYwAYoonBcCVmGjKsYiVMhsB1VsaJqjSyUnOhTAJagZiQm-Fuu9U1mqLtbA3drvj_rzfwwfBpHe6Oe86KA7miJ1cM5Ir58m1Q4hf42mPE</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Blood transcriptome analysis for Alzheimer’ disease in Hong Kong Chinese population</title><source>Wiley Online Library All Journals</source><creator>Zhong, Huan ; Zhou, Xiaopu ; Jiang, Yuanbing ; Chen, Yu ; Lai, Nicole Chit Hang ; Tong, Estella Pui‐Sze ; Lo, Ronnie M.N. ; Kwok, Timothy CY ; Mok, Vincent C.T. ; Ip, Fanny C. F. ; Mok, Kin Y ; Hardy, John ; Fu, Amy K.Y. ; Ip, Nancy Y.</creator><creatorcontrib>Zhong, Huan ; Zhou, Xiaopu ; Jiang, Yuanbing ; Chen, Yu ; Lai, Nicole Chit Hang ; Tong, Estella Pui‐Sze ; Lo, Ronnie M.N. ; Kwok, Timothy CY ; Mok, Vincent C.T. ; Ip, Fanny C. F. ; Mok, Kin Y ; Hardy, John ; Fu, Amy K.Y. ; Ip, Nancy Y.</creatorcontrib><description>Background
Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer’s disease (AD) patients are poorly understood.
Method
We conducted transcriptome profiling of 422 participants (208 normal controls and 214 patients with AD) from the Hong Kong Chinese population. WGCNA (weighted correlation network analysis) was performed to construct a co‐expression network to identify modules associated with AD and AD‐associated biomarkers.
Result
Co‐expression modules exerting significant association with AD and AD plasma biomarkers (e.g., Aβ and NFL) were identified. Pathway enrichment analysis suggested their possible involvement in specific biological pathways. Motif analysis further revealed the potential mechanisms that driving the observed blood transcriptomic changes observed in AD.
Conclusion
The co‐expression network analysis of the AD blood transcriptome changes may facilitate a better understanding of AD progression, as well as the identification of potential targets for disease intervention and monitoring.</description><identifier>ISSN: 1552-5260</identifier><identifier>EISSN: 1552-5279</identifier><identifier>DOI: 10.1002/alz.056643</identifier><identifier>PMID: 35109159</identifier><language>eng</language><publisher>United States</publisher><ispartof>Alzheimer's & dementia, 2021-12, Vol.17, p.e056643-n/a</ispartof><rights>2021 the Alzheimer's Association</rights><rights>2021 the Alzheimer's Association.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c1763-a504b510ad4c0caddaa0eed2ad1738ba9ef273d9ea1b9c247fbe0cb137d4ab7a3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Falz.056643$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Falz.056643$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35109159$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhong, Huan</creatorcontrib><creatorcontrib>Zhou, Xiaopu</creatorcontrib><creatorcontrib>Jiang, Yuanbing</creatorcontrib><creatorcontrib>Chen, Yu</creatorcontrib><creatorcontrib>Lai, Nicole Chit Hang</creatorcontrib><creatorcontrib>Tong, Estella Pui‐Sze</creatorcontrib><creatorcontrib>Lo, Ronnie M.N.</creatorcontrib><creatorcontrib>Kwok, Timothy CY</creatorcontrib><creatorcontrib>Mok, Vincent C.T.</creatorcontrib><creatorcontrib>Ip, Fanny C. F.</creatorcontrib><creatorcontrib>Mok, Kin Y</creatorcontrib><creatorcontrib>Hardy, John</creatorcontrib><creatorcontrib>Fu, Amy K.Y.</creatorcontrib><creatorcontrib>Ip, Nancy Y.</creatorcontrib><title>Blood transcriptome analysis for Alzheimer’ disease in Hong Kong Chinese population</title><title>Alzheimer's & dementia</title><addtitle>Alzheimers Dement</addtitle><description>Background
Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer’s disease (AD) patients are poorly understood.
Method
We conducted transcriptome profiling of 422 participants (208 normal controls and 214 patients with AD) from the Hong Kong Chinese population. WGCNA (weighted correlation network analysis) was performed to construct a co‐expression network to identify modules associated with AD and AD‐associated biomarkers.
Result
Co‐expression modules exerting significant association with AD and AD plasma biomarkers (e.g., Aβ and NFL) were identified. Pathway enrichment analysis suggested their possible involvement in specific biological pathways. Motif analysis further revealed the potential mechanisms that driving the observed blood transcriptomic changes observed in AD.
Conclusion
The co‐expression network analysis of the AD blood transcriptome changes may facilitate a better understanding of AD progression, as well as the identification of potential targets for disease intervention and monitoring.</description><issn>1552-5260</issn><issn>1552-5279</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9kEFOwzAQRS0EoqWw4QDIF0ix4zhuliUCiqjEhm7YRON4Qo2cOIpboXbFNbgeJyFVoJuZr5mv0Z9HyDVnU85YfAtuP2UyTRNxQsZcyjiSscpOjzplI3IRwgdjCZtxeU5GQnKWcZmNyerOeW_opoMmlJ1tN75GCg24XbCBVr6jc7dfo62x-_n6psYGhIDUNnThm3f6fCj52jbYD1vfbh1srG8uyVkFLuDVX5-Q1cP9a76Ili-PT_l8GZVcpSICyRLdRwGTlKwEYwAYoonBcCVmGjKsYiVMhsB1VsaJqjSyUnOhTAJagZiQm-Fuu9U1mqLtbA3drvj_rzfwwfBpHe6Oe86KA7miJ1cM5Ir58m1Q4hf42mPE</recordid><startdate>202112</startdate><enddate>202112</enddate><creator>Zhong, Huan</creator><creator>Zhou, Xiaopu</creator><creator>Jiang, Yuanbing</creator><creator>Chen, Yu</creator><creator>Lai, Nicole Chit Hang</creator><creator>Tong, Estella Pui‐Sze</creator><creator>Lo, Ronnie M.N.</creator><creator>Kwok, Timothy CY</creator><creator>Mok, Vincent C.T.</creator><creator>Ip, Fanny C. F.</creator><creator>Mok, Kin Y</creator><creator>Hardy, John</creator><creator>Fu, Amy K.Y.</creator><creator>Ip, Nancy Y.</creator><scope>NPM</scope></search><sort><creationdate>202112</creationdate><title>Blood transcriptome analysis for Alzheimer’ disease in Hong Kong Chinese population</title><author>Zhong, Huan ; Zhou, Xiaopu ; Jiang, Yuanbing ; Chen, Yu ; Lai, Nicole Chit Hang ; Tong, Estella Pui‐Sze ; Lo, Ronnie M.N. ; Kwok, Timothy CY ; Mok, Vincent C.T. ; Ip, Fanny C. F. ; Mok, Kin Y ; Hardy, John ; Fu, Amy K.Y. ; Ip, Nancy Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1763-a504b510ad4c0caddaa0eed2ad1738ba9ef273d9ea1b9c247fbe0cb137d4ab7a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhong, Huan</creatorcontrib><creatorcontrib>Zhou, Xiaopu</creatorcontrib><creatorcontrib>Jiang, Yuanbing</creatorcontrib><creatorcontrib>Chen, Yu</creatorcontrib><creatorcontrib>Lai, Nicole Chit Hang</creatorcontrib><creatorcontrib>Tong, Estella Pui‐Sze</creatorcontrib><creatorcontrib>Lo, Ronnie M.N.</creatorcontrib><creatorcontrib>Kwok, Timothy CY</creatorcontrib><creatorcontrib>Mok, Vincent C.T.</creatorcontrib><creatorcontrib>Ip, Fanny C. F.</creatorcontrib><creatorcontrib>Mok, Kin Y</creatorcontrib><creatorcontrib>Hardy, John</creatorcontrib><creatorcontrib>Fu, Amy K.Y.</creatorcontrib><creatorcontrib>Ip, Nancy Y.</creatorcontrib><collection>PubMed</collection><jtitle>Alzheimer's & dementia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhong, Huan</au><au>Zhou, Xiaopu</au><au>Jiang, Yuanbing</au><au>Chen, Yu</au><au>Lai, Nicole Chit Hang</au><au>Tong, Estella Pui‐Sze</au><au>Lo, Ronnie M.N.</au><au>Kwok, Timothy CY</au><au>Mok, Vincent C.T.</au><au>Ip, Fanny C. F.</au><au>Mok, Kin Y</au><au>Hardy, John</au><au>Fu, Amy K.Y.</au><au>Ip, Nancy Y.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Blood transcriptome analysis for Alzheimer’ disease in Hong Kong Chinese population</atitle><jtitle>Alzheimer's & dementia</jtitle><addtitle>Alzheimers Dement</addtitle><date>2021-12</date><risdate>2021</risdate><volume>17</volume><spage>e056643</spage><epage>n/a</epage><pages>e056643-n/a</pages><issn>1552-5260</issn><eissn>1552-5279</eissn><abstract>Background
Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer’s disease (AD) patients are poorly understood.
Method
We conducted transcriptome profiling of 422 participants (208 normal controls and 214 patients with AD) from the Hong Kong Chinese population. WGCNA (weighted correlation network analysis) was performed to construct a co‐expression network to identify modules associated with AD and AD‐associated biomarkers.
Result
Co‐expression modules exerting significant association with AD and AD plasma biomarkers (e.g., Aβ and NFL) were identified. Pathway enrichment analysis suggested their possible involvement in specific biological pathways. Motif analysis further revealed the potential mechanisms that driving the observed blood transcriptomic changes observed in AD.
Conclusion
The co‐expression network analysis of the AD blood transcriptome changes may facilitate a better understanding of AD progression, as well as the identification of potential targets for disease intervention and monitoring.</abstract><cop>United States</cop><pmid>35109159</pmid><doi>10.1002/alz.056643</doi><tpages>1</tpages></addata></record> |
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| title | Blood transcriptome analysis for Alzheimer’ disease in Hong Kong Chinese population |
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