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Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors
Common variants may contribute to the variation of prognosis of heart failure (HF) among individual patients, but no systematical analysis was conducted using transcriptomic and whole exome sequencing (WES) data. We aimed to construct a genetic risk score (GRS) and estimate its potential as a predic...
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| Published in: | Frontiers in cardiovascular medicine 2021-04, Vol.8, p.634966-634966 |
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| creator | Hu, Dong Xiao, Lei Li, Shiyang Hu, Senlin Sun, Yang Wang, Yan Wang, Dao Wen |
| description | Common variants may contribute to the variation of prognosis of heart failure (HF) among individual patients, but no systematical analysis was conducted using transcriptomic and whole exome sequencing (WES) data. We aimed to construct a genetic risk score (GRS) and estimate its potential as a predictive tool for HF-related mortality risk alone and in combination with traditional risk factors (TRFs).
We reanalyzed the transcriptomic data of 177 failing hearts and 136 healthy donors. Differentially expressed genes (fold change >1.5 or |
| doi_str_mv | 10.3389/fcvm.2021.634966 |
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| fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_e8490338998841b18dd8bf5811d7cb68</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_e8490338998841b18dd8bf5811d7cb68</doaj_id><sourcerecordid>2526308347</sourcerecordid><originalsourceid>FETCH-LOGICAL-c462t-4f88f94ec4372bb590dfbffa2e69bfc9f3f73a56be58d7fcaba98c4e8c908e6a3</originalsourceid><addsrcrecordid>eNpVkU1P3DAQhqOqVUGUe0-Vj71k8VcS-1IJrbqABGpFQe3N8sd4MU1samep-PdNCEVwsj0z7zMzfqvqI8ErxoQ88vZ-WFFMyaplXLbtm2qfUtnVuGl-vX1x36sOS7nFGJOGi6YV76s9xqQgHaP71d_vGVywY0gRJY9ON_Ul9HoEhy5SHnUfxgd0GcpvdF1C3KITiDAGu4R-2JQBHfcpAtLRoRDROg0mRP2I-xnGG3SVtQvzU_eLaKPtmHL5UL3zui9w-HQeVNebr1fr0_r828nZ-vi8trylY829EF5ysJx11JhGYueN95pCK4230jPfMd20BhrhOm-10VJYDsJKLKDV7KA6W7gu6Vt1l8Og84NKOqjHQMpbpfO0UQ8KBJd4_lkpBCeGCOeE8Y0gxHXWtGJifVlYdzszgLMQx6z7V9DXmRhu1DbdK0FwRzmZAJ-fADn92UEZ1RCKhb7XEdKuKNrQlmHBeDeV4qXU5lRKBv_chmA1D6lm-9Vsv1rsnySfXo73LPhvNvsHkGKudA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2526308347</pqid></control><display><type>article</type><title>Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors</title><source>Open Access: PubMed Central</source><creator>Hu, Dong ; Xiao, Lei ; Li, Shiyang ; Hu, Senlin ; Sun, Yang ; Wang, Yan ; Wang, Dao Wen</creator><creatorcontrib>Hu, Dong ; Xiao, Lei ; Li, Shiyang ; Hu, Senlin ; Sun, Yang ; Wang, Yan ; Wang, Dao Wen</creatorcontrib><description>Common variants may contribute to the variation of prognosis of heart failure (HF) among individual patients, but no systematical analysis was conducted using transcriptomic and whole exome sequencing (WES) data. We aimed to construct a genetic risk score (GRS) and estimate its potential as a predictive tool for HF-related mortality risk alone and in combination with traditional risk factors (TRFs).
We reanalyzed the transcriptomic data of 177 failing hearts and 136 healthy donors. Differentially expressed genes (fold change >1.5 or <0.68 and adjusted
< 0.05) were selected for prognosis analysis using our whole exome sequencing and follow-up data with 998 HF patients. Statistically significant variants in these genes were prepared for GRS construction. Traditional risk variables were in combination with GRS for the construct of the composite risk score. Kaplan-Meier curves and receiver operating characteristic (ROC) analysis were used to assess the effect of GRS and the composite risk score on the prognosis of HF and discriminant power, respectively. We found 157 upregulated and 173 downregulated genes. In these genes, 31 variants that were associated with the prognosis of HF were finally identified to develop GRS. Compared with individuals with low risk score, patients with medium- and high-risk score showed 2.78 (95%CI = 1.82-4.24,
= 2 × 10
) and 6.54 (95%CI = 4.42-9.71,
= 6 × 10
) -fold mortality risk, respectively. The composite risk score combining GRS and TRF predicted mortality risk with an HR = 5.41 (95% CI = 2.72-10.64,
= 1 × 10
) for medium vs. low risk and HR = 22.72 (95% CI = 11.9-43.48,
= 5 × 10
) for high vs. low risk. The discriminant power of GRS is excellent with a C statistic of 0.739, which is comparable to that of TRF (C statistic = 0.791). The combination of GRS and TRF could significantly increase the predictive ability (C statistic = 0.853).
The 31-SNP GRS could well distinguish those HF patients with poor prognosis from those with better prognosis and provide clinician with reference for the intensive therapy, especially when combined with TRF.
https://www.clinicaltrials.gov/, identifier: NCT03461107.</description><identifier>ISSN: 2297-055X</identifier><identifier>EISSN: 2297-055X</identifier><identifier>DOI: 10.3389/fcvm.2021.634966</identifier><identifier>PMID: 33981732</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>Cardiovascular Medicine ; genetic risk score ; heart failure ; prediction ; prognosis ; traditional risk factors</subject><ispartof>Frontiers in cardiovascular medicine, 2021-04, Vol.8, p.634966-634966</ispartof><rights>Copyright © 2021 Hu, Xiao, Li, Hu, Sun, Wang and Wang.</rights><rights>Copyright © 2021 Hu, Xiao, Li, Hu, Sun, Wang and Wang. 2021 Hu, Xiao, Li, Hu, Sun, Wang and Wang</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c462t-4f88f94ec4372bb590dfbffa2e69bfc9f3f73a56be58d7fcaba98c4e8c908e6a3</citedby><cites>FETCH-LOGICAL-c462t-4f88f94ec4372bb590dfbffa2e69bfc9f3f73a56be58d7fcaba98c4e8c908e6a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107241/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107241/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33981732$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hu, Dong</creatorcontrib><creatorcontrib>Xiao, Lei</creatorcontrib><creatorcontrib>Li, Shiyang</creatorcontrib><creatorcontrib>Hu, Senlin</creatorcontrib><creatorcontrib>Sun, Yang</creatorcontrib><creatorcontrib>Wang, Yan</creatorcontrib><creatorcontrib>Wang, Dao Wen</creatorcontrib><title>Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors</title><title>Frontiers in cardiovascular medicine</title><addtitle>Front Cardiovasc Med</addtitle><description>Common variants may contribute to the variation of prognosis of heart failure (HF) among individual patients, but no systematical analysis was conducted using transcriptomic and whole exome sequencing (WES) data. We aimed to construct a genetic risk score (GRS) and estimate its potential as a predictive tool for HF-related mortality risk alone and in combination with traditional risk factors (TRFs).
We reanalyzed the transcriptomic data of 177 failing hearts and 136 healthy donors. Differentially expressed genes (fold change >1.5 or <0.68 and adjusted
< 0.05) were selected for prognosis analysis using our whole exome sequencing and follow-up data with 998 HF patients. Statistically significant variants in these genes were prepared for GRS construction. Traditional risk variables were in combination with GRS for the construct of the composite risk score. Kaplan-Meier curves and receiver operating characteristic (ROC) analysis were used to assess the effect of GRS and the composite risk score on the prognosis of HF and discriminant power, respectively. We found 157 upregulated and 173 downregulated genes. In these genes, 31 variants that were associated with the prognosis of HF were finally identified to develop GRS. Compared with individuals with low risk score, patients with medium- and high-risk score showed 2.78 (95%CI = 1.82-4.24,
= 2 × 10
) and 6.54 (95%CI = 4.42-9.71,
= 6 × 10
) -fold mortality risk, respectively. The composite risk score combining GRS and TRF predicted mortality risk with an HR = 5.41 (95% CI = 2.72-10.64,
= 1 × 10
) for medium vs. low risk and HR = 22.72 (95% CI = 11.9-43.48,
= 5 × 10
) for high vs. low risk. The discriminant power of GRS is excellent with a C statistic of 0.739, which is comparable to that of TRF (C statistic = 0.791). The combination of GRS and TRF could significantly increase the predictive ability (C statistic = 0.853).
The 31-SNP GRS could well distinguish those HF patients with poor prognosis from those with better prognosis and provide clinician with reference for the intensive therapy, especially when combined with TRF.
https://www.clinicaltrials.gov/, identifier: NCT03461107.</description><subject>Cardiovascular Medicine</subject><subject>genetic risk score</subject><subject>heart failure</subject><subject>prediction</subject><subject>prognosis</subject><subject>traditional risk factors</subject><issn>2297-055X</issn><issn>2297-055X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkU1P3DAQhqOqVUGUe0-Vj71k8VcS-1IJrbqABGpFQe3N8sd4MU1samep-PdNCEVwsj0z7zMzfqvqI8ErxoQ88vZ-WFFMyaplXLbtm2qfUtnVuGl-vX1x36sOS7nFGJOGi6YV76s9xqQgHaP71d_vGVywY0gRJY9ON_Ul9HoEhy5SHnUfxgd0GcpvdF1C3KITiDAGu4R-2JQBHfcpAtLRoRDROg0mRP2I-xnGG3SVtQvzU_eLaKPtmHL5UL3zui9w-HQeVNebr1fr0_r828nZ-vi8trylY829EF5ysJx11JhGYueN95pCK4230jPfMd20BhrhOm-10VJYDsJKLKDV7KA6W7gu6Vt1l8Og84NKOqjHQMpbpfO0UQ8KBJd4_lkpBCeGCOeE8Y0gxHXWtGJifVlYdzszgLMQx6z7V9DXmRhu1DbdK0FwRzmZAJ-fADn92UEZ1RCKhb7XEdKuKNrQlmHBeDeV4qXU5lRKBv_chmA1D6lm-9Vsv1rsnySfXo73LPhvNvsHkGKudA</recordid><startdate>20210426</startdate><enddate>20210426</enddate><creator>Hu, Dong</creator><creator>Xiao, Lei</creator><creator>Li, Shiyang</creator><creator>Hu, Senlin</creator><creator>Sun, Yang</creator><creator>Wang, Yan</creator><creator>Wang, Dao Wen</creator><general>Frontiers Media S.A</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20210426</creationdate><title>Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors</title><author>Hu, Dong ; Xiao, Lei ; Li, Shiyang ; Hu, Senlin ; Sun, Yang ; Wang, Yan ; Wang, Dao Wen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c462t-4f88f94ec4372bb590dfbffa2e69bfc9f3f73a56be58d7fcaba98c4e8c908e6a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Cardiovascular Medicine</topic><topic>genetic risk score</topic><topic>heart failure</topic><topic>prediction</topic><topic>prognosis</topic><topic>traditional risk factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Dong</creatorcontrib><creatorcontrib>Xiao, Lei</creatorcontrib><creatorcontrib>Li, Shiyang</creatorcontrib><creatorcontrib>Hu, Senlin</creatorcontrib><creatorcontrib>Sun, Yang</creatorcontrib><creatorcontrib>Wang, Yan</creatorcontrib><creatorcontrib>Wang, Dao Wen</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><jtitle>Frontiers in cardiovascular medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Dong</au><au>Xiao, Lei</au><au>Li, Shiyang</au><au>Hu, Senlin</au><au>Sun, Yang</au><au>Wang, Yan</au><au>Wang, Dao Wen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors</atitle><jtitle>Frontiers in cardiovascular medicine</jtitle><addtitle>Front Cardiovasc Med</addtitle><date>2021-04-26</date><risdate>2021</risdate><volume>8</volume><spage>634966</spage><epage>634966</epage><pages>634966-634966</pages><issn>2297-055X</issn><eissn>2297-055X</eissn><abstract>Common variants may contribute to the variation of prognosis of heart failure (HF) among individual patients, but no systematical analysis was conducted using transcriptomic and whole exome sequencing (WES) data. We aimed to construct a genetic risk score (GRS) and estimate its potential as a predictive tool for HF-related mortality risk alone and in combination with traditional risk factors (TRFs).
We reanalyzed the transcriptomic data of 177 failing hearts and 136 healthy donors. Differentially expressed genes (fold change >1.5 or <0.68 and adjusted
< 0.05) were selected for prognosis analysis using our whole exome sequencing and follow-up data with 998 HF patients. Statistically significant variants in these genes were prepared for GRS construction. Traditional risk variables were in combination with GRS for the construct of the composite risk score. Kaplan-Meier curves and receiver operating characteristic (ROC) analysis were used to assess the effect of GRS and the composite risk score on the prognosis of HF and discriminant power, respectively. We found 157 upregulated and 173 downregulated genes. In these genes, 31 variants that were associated with the prognosis of HF were finally identified to develop GRS. Compared with individuals with low risk score, patients with medium- and high-risk score showed 2.78 (95%CI = 1.82-4.24,
= 2 × 10
) and 6.54 (95%CI = 4.42-9.71,
= 6 × 10
) -fold mortality risk, respectively. The composite risk score combining GRS and TRF predicted mortality risk with an HR = 5.41 (95% CI = 2.72-10.64,
= 1 × 10
) for medium vs. low risk and HR = 22.72 (95% CI = 11.9-43.48,
= 5 × 10
) for high vs. low risk. The discriminant power of GRS is excellent with a C statistic of 0.739, which is comparable to that of TRF (C statistic = 0.791). The combination of GRS and TRF could significantly increase the predictive ability (C statistic = 0.853).
The 31-SNP GRS could well distinguish those HF patients with poor prognosis from those with better prognosis and provide clinician with reference for the intensive therapy, especially when combined with TRF.
https://www.clinicaltrials.gov/, identifier: NCT03461107.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>33981732</pmid><doi>10.3389/fcvm.2021.634966</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Cardiovascular Medicine genetic risk score heart failure prediction prognosis traditional risk factors |
| title | Prediction of HF-Related Mortality Risk Using Genetic Risk Score Alone and in Combination With Traditional Risk Factors |
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