Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults
To subgroup Chinese patients with newly diagnosed type 2 diabetes (T2D) by K-means cluster analysis on clinical indicators, and to explore whether these subgroups represent different genetic features and calculated cardiovascular risks. The K-means clustering analysis was performed on two cohorts (n...
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| Veröffentlicht in: | Diabetes & metabolic syndrome clinical research & reviews 2023-09, Vol.17 (9), p.102850-102850, Article 102850 |
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| creator | Wang, Weihao Jia, Tong Liu, Yiying Deng, Hongrong Chen, Zihao Wang, Jing Geng, Zhaoxu Wei, Ran Qiao, Jingtao Ma, Yanhua Jiang, Xun Xu, Wen Shao, Jian Zhou, Kaixin Li, Ying Pan, Qi Yang, Wenying Weng, Jianping Guo, Lixin |
| description | To subgroup Chinese patients with newly diagnosed type 2 diabetes (T2D) by K-means cluster analysis on clinical indicators, and to explore whether these subgroups represent different genetic features and calculated cardiovascular risks.
The K-means clustering analysis was performed on two cohorts (n = 590 and 392), both consisting of Chinese participants with newly diagnosed T2D. To assess genetic risks, multiple polygenic risk scores (PRSs) and mitochondrial DNA copy numbers (mtDNA-CN) were calculated for all participants. Furthermore, Framingham risk scores (FRS) of cardiovascular diseases in two cohorts were also calculated to verify the genetic risks.
Four clusters were identified including the mild age-related diabetes (MARD)(35.08%), mild obesity-related diabetes (MOD) (34.41%), severe autoimmune diabetes (SAID) 19.15%, and severe insulin-resistant diabetes (SIRD) 11.36% subgroups in the MARCH (metformin, and acarbose in Chinese patients as the initial hypoglycemic treatment) cohort. There was a significant difference in PRS for cardiovascular diseases (CVD) across four subgroups in the MARCH cohort (p |
| doi_str_mv | 10.1016/j.dsx.2023.102850 |
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| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2863306303</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1871402123001467</els_id><sourcerecordid>2863306303</sourcerecordid><originalsourceid>FETCH-LOGICAL-c282t-7d1b477e6485f07f8f4b7e2175c55dec8e8b950860955db900fb3b985793bae03</originalsourceid><addsrcrecordid>eNp9kcuOEzEQRS0EEkPgA9h5yaaDH_1wixUKDIw0EhtYW35UJ448duNyZ8i38LN0JqxnVXWv6pRUdQl5z9mWM95_PG49_tkKJuSqherYC3LD1aAaJmX78qnnTcsEf03eIB4Z67pRjDfk7xdTTeNLOEGiuNh9ycuMNE80wWM8Ux_MPmUET-t5BiouhoUKSE1avQPQAtHUkBMewkwfQz1QZ4oP-WTQLdGUlUAweCEq3UOCGtwT7GJIwZlII5wgIg2J7g4hAQI1fokV35JXk4kI7_7XDfl1-_Xn7ntz_-Pb3e7zfeOEErUZPLftMEDfqm5iw6Sm1g4g-NC5rvPgFCg7dkz1bFy1HRmbrLSj6oZRWgNMbsiH69655N8LYNUPAR3EaBLkBbVQvZSsl-srN4RfR13JiAUmPZfwYMpZc6YvQeijXoPQlyD0NYiV-XRl1iPhFKBodAGSAx8KuKp9Ds_Q_wAxHpOx</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2863306303</pqid></control><display><type>article</type><title>Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults</title><source>Elsevier ScienceDirect Journals</source><creator>Wang, Weihao ; Jia, Tong ; Liu, Yiying ; Deng, Hongrong ; Chen, Zihao ; Wang, Jing ; Geng, Zhaoxu ; Wei, Ran ; Qiao, Jingtao ; Ma, Yanhua ; Jiang, Xun ; Xu, Wen ; Shao, Jian ; Zhou, Kaixin ; Li, Ying ; Pan, Qi ; Yang, Wenying ; Weng, Jianping ; Guo, Lixin</creator><creatorcontrib>Wang, Weihao ; Jia, Tong ; Liu, Yiying ; Deng, Hongrong ; Chen, Zihao ; Wang, Jing ; Geng, Zhaoxu ; Wei, Ran ; Qiao, Jingtao ; Ma, Yanhua ; Jiang, Xun ; Xu, Wen ; Shao, Jian ; Zhou, Kaixin ; Li, Ying ; Pan, Qi ; Yang, Wenying ; Weng, Jianping ; Guo, Lixin</creatorcontrib><description>To subgroup Chinese patients with newly diagnosed type 2 diabetes (T2D) by K-means cluster analysis on clinical indicators, and to explore whether these subgroups represent different genetic features and calculated cardiovascular risks.
The K-means clustering analysis was performed on two cohorts (n = 590 and 392), both consisting of Chinese participants with newly diagnosed T2D. To assess genetic risks, multiple polygenic risk scores (PRSs) and mitochondrial DNA copy numbers (mtDNA-CN) were calculated for all participants. Furthermore, Framingham risk scores (FRS) of cardiovascular diseases in two cohorts were also calculated to verify the genetic risks.
Four clusters were identified including the mild age-related diabetes (MARD)(35.08%), mild obesity-related diabetes (MOD) (34.41%), severe autoimmune diabetes (SAID) 19.15%, and severe insulin-resistant diabetes (SIRD) 11.36% subgroups in the MARCH (metformin, and acarbose in Chinese patients as the initial hypoglycemic treatment) cohort. There was a significant difference in PRS for cardiovascular diseases (CVD) across four subgroups in the MARCH cohort (p < 0.05). Compared with the SIDD and SIRD subgroups, patients in the MOD subgroup had a relatively lower PRS for CVD (p < 0.05) in the MARCH cohort. Females had a higher PRS compared to males, with no significant difference in FRS across the four clusters. The MOD subgroup had a significantly lower FRS which was consistent with the results of PRS. Similar results of PRS and FRS were also replicated in the CONFIDENCE (comparison of glycemic control and b-cell function among newly diagnosed patients with type 2 diabetes treated with exenatide, insulin or pioglitazone) cohort.
There are different CVD risks in diabetic subgroups based on clinical and genetic evidence which may promote precision medicine.
•Individuals with type 2 diabetes have heterogeneity in metabolic features.•Type 2 diabetes can be classified into four subgroups with different cardiovascular risks.•The mild obesity-related diabetes subgroup has the lowest cardiovascular diseases risk.</description><identifier>ISSN: 1871-4021</identifier><identifier>EISSN: 1878-0334</identifier><identifier>DOI: 10.1016/j.dsx.2023.102850</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Cardiovascular risks ; Diabetes subgroups ; Machine learning ; Polygenic risk score</subject><ispartof>Diabetes & metabolic syndrome clinical research & reviews, 2023-09, Vol.17 (9), p.102850-102850, Article 102850</ispartof><rights>2023 Research Trust of DiabetesIndia (DiabetesIndia) and National Diabetes Obesity and Cholesterol Foundation (N-DOC)</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c282t-7d1b477e6485f07f8f4b7e2175c55dec8e8b950860955db900fb3b985793bae03</cites><orcidid>0000-0003-2609-8387 ; 0000-0002-5896-2793</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1871402123001467$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Wang, Weihao</creatorcontrib><creatorcontrib>Jia, Tong</creatorcontrib><creatorcontrib>Liu, Yiying</creatorcontrib><creatorcontrib>Deng, Hongrong</creatorcontrib><creatorcontrib>Chen, Zihao</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Geng, Zhaoxu</creatorcontrib><creatorcontrib>Wei, Ran</creatorcontrib><creatorcontrib>Qiao, Jingtao</creatorcontrib><creatorcontrib>Ma, Yanhua</creatorcontrib><creatorcontrib>Jiang, Xun</creatorcontrib><creatorcontrib>Xu, Wen</creatorcontrib><creatorcontrib>Shao, Jian</creatorcontrib><creatorcontrib>Zhou, Kaixin</creatorcontrib><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Pan, Qi</creatorcontrib><creatorcontrib>Yang, Wenying</creatorcontrib><creatorcontrib>Weng, Jianping</creatorcontrib><creatorcontrib>Guo, Lixin</creatorcontrib><title>Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults</title><title>Diabetes & metabolic syndrome clinical research & reviews</title><description>To subgroup Chinese patients with newly diagnosed type 2 diabetes (T2D) by K-means cluster analysis on clinical indicators, and to explore whether these subgroups represent different genetic features and calculated cardiovascular risks.
The K-means clustering analysis was performed on two cohorts (n = 590 and 392), both consisting of Chinese participants with newly diagnosed T2D. To assess genetic risks, multiple polygenic risk scores (PRSs) and mitochondrial DNA copy numbers (mtDNA-CN) were calculated for all participants. Furthermore, Framingham risk scores (FRS) of cardiovascular diseases in two cohorts were also calculated to verify the genetic risks.
Four clusters were identified including the mild age-related diabetes (MARD)(35.08%), mild obesity-related diabetes (MOD) (34.41%), severe autoimmune diabetes (SAID) 19.15%, and severe insulin-resistant diabetes (SIRD) 11.36% subgroups in the MARCH (metformin, and acarbose in Chinese patients as the initial hypoglycemic treatment) cohort. There was a significant difference in PRS for cardiovascular diseases (CVD) across four subgroups in the MARCH cohort (p < 0.05). Compared with the SIDD and SIRD subgroups, patients in the MOD subgroup had a relatively lower PRS for CVD (p < 0.05) in the MARCH cohort. Females had a higher PRS compared to males, with no significant difference in FRS across the four clusters. The MOD subgroup had a significantly lower FRS which was consistent with the results of PRS. Similar results of PRS and FRS were also replicated in the CONFIDENCE (comparison of glycemic control and b-cell function among newly diagnosed patients with type 2 diabetes treated with exenatide, insulin or pioglitazone) cohort.
There are different CVD risks in diabetic subgroups based on clinical and genetic evidence which may promote precision medicine.
•Individuals with type 2 diabetes have heterogeneity in metabolic features.•Type 2 diabetes can be classified into four subgroups with different cardiovascular risks.•The mild obesity-related diabetes subgroup has the lowest cardiovascular diseases risk.</description><subject>Cardiovascular risks</subject><subject>Diabetes subgroups</subject><subject>Machine learning</subject><subject>Polygenic risk score</subject><issn>1871-4021</issn><issn>1878-0334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kcuOEzEQRS0EEkPgA9h5yaaDH_1wixUKDIw0EhtYW35UJ448duNyZ8i38LN0JqxnVXWv6pRUdQl5z9mWM95_PG49_tkKJuSqherYC3LD1aAaJmX78qnnTcsEf03eIB4Z67pRjDfk7xdTTeNLOEGiuNh9ycuMNE80wWM8Ux_MPmUET-t5BiouhoUKSE1avQPQAtHUkBMewkwfQz1QZ4oP-WTQLdGUlUAweCEq3UOCGtwT7GJIwZlII5wgIg2J7g4hAQI1fokV35JXk4kI7_7XDfl1-_Xn7ntz_-Pb3e7zfeOEErUZPLftMEDfqm5iw6Sm1g4g-NC5rvPgFCg7dkz1bFy1HRmbrLSj6oZRWgNMbsiH69655N8LYNUPAR3EaBLkBbVQvZSsl-srN4RfR13JiAUmPZfwYMpZc6YvQeijXoPQlyD0NYiV-XRl1iPhFKBodAGSAx8KuKp9Ds_Q_wAxHpOx</recordid><startdate>202309</startdate><enddate>202309</enddate><creator>Wang, Weihao</creator><creator>Jia, Tong</creator><creator>Liu, Yiying</creator><creator>Deng, Hongrong</creator><creator>Chen, Zihao</creator><creator>Wang, Jing</creator><creator>Geng, Zhaoxu</creator><creator>Wei, Ran</creator><creator>Qiao, Jingtao</creator><creator>Ma, Yanhua</creator><creator>Jiang, Xun</creator><creator>Xu, Wen</creator><creator>Shao, Jian</creator><creator>Zhou, Kaixin</creator><creator>Li, Ying</creator><creator>Pan, Qi</creator><creator>Yang, Wenying</creator><creator>Weng, Jianping</creator><creator>Guo, Lixin</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-2609-8387</orcidid><orcidid>https://orcid.org/0000-0002-5896-2793</orcidid></search><sort><creationdate>202309</creationdate><title>Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults</title><author>Wang, Weihao ; Jia, Tong ; Liu, Yiying ; Deng, Hongrong ; Chen, Zihao ; Wang, Jing ; Geng, Zhaoxu ; Wei, Ran ; Qiao, Jingtao ; Ma, Yanhua ; Jiang, Xun ; Xu, Wen ; Shao, Jian ; Zhou, Kaixin ; Li, Ying ; Pan, Qi ; Yang, Wenying ; Weng, Jianping ; Guo, Lixin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c282t-7d1b477e6485f07f8f4b7e2175c55dec8e8b950860955db900fb3b985793bae03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cardiovascular risks</topic><topic>Diabetes subgroups</topic><topic>Machine learning</topic><topic>Polygenic risk score</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Weihao</creatorcontrib><creatorcontrib>Jia, Tong</creatorcontrib><creatorcontrib>Liu, Yiying</creatorcontrib><creatorcontrib>Deng, Hongrong</creatorcontrib><creatorcontrib>Chen, Zihao</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Geng, Zhaoxu</creatorcontrib><creatorcontrib>Wei, Ran</creatorcontrib><creatorcontrib>Qiao, Jingtao</creatorcontrib><creatorcontrib>Ma, Yanhua</creatorcontrib><creatorcontrib>Jiang, Xun</creatorcontrib><creatorcontrib>Xu, Wen</creatorcontrib><creatorcontrib>Shao, Jian</creatorcontrib><creatorcontrib>Zhou, Kaixin</creatorcontrib><creatorcontrib>Li, Ying</creatorcontrib><creatorcontrib>Pan, Qi</creatorcontrib><creatorcontrib>Yang, Wenying</creatorcontrib><creatorcontrib>Weng, Jianping</creatorcontrib><creatorcontrib>Guo, Lixin</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Diabetes & metabolic syndrome clinical research & reviews</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Weihao</au><au>Jia, Tong</au><au>Liu, Yiying</au><au>Deng, Hongrong</au><au>Chen, Zihao</au><au>Wang, Jing</au><au>Geng, Zhaoxu</au><au>Wei, Ran</au><au>Qiao, Jingtao</au><au>Ma, Yanhua</au><au>Jiang, Xun</au><au>Xu, Wen</au><au>Shao, Jian</au><au>Zhou, Kaixin</au><au>Li, Ying</au><au>Pan, Qi</au><au>Yang, Wenying</au><au>Weng, Jianping</au><au>Guo, Lixin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults</atitle><jtitle>Diabetes & metabolic syndrome clinical research & reviews</jtitle><date>2023-09</date><risdate>2023</risdate><volume>17</volume><issue>9</issue><spage>102850</spage><epage>102850</epage><pages>102850-102850</pages><artnum>102850</artnum><issn>1871-4021</issn><eissn>1878-0334</eissn><abstract>To subgroup Chinese patients with newly diagnosed type 2 diabetes (T2D) by K-means cluster analysis on clinical indicators, and to explore whether these subgroups represent different genetic features and calculated cardiovascular risks.
The K-means clustering analysis was performed on two cohorts (n = 590 and 392), both consisting of Chinese participants with newly diagnosed T2D. To assess genetic risks, multiple polygenic risk scores (PRSs) and mitochondrial DNA copy numbers (mtDNA-CN) were calculated for all participants. Furthermore, Framingham risk scores (FRS) of cardiovascular diseases in two cohorts were also calculated to verify the genetic risks.
Four clusters were identified including the mild age-related diabetes (MARD)(35.08%), mild obesity-related diabetes (MOD) (34.41%), severe autoimmune diabetes (SAID) 19.15%, and severe insulin-resistant diabetes (SIRD) 11.36% subgroups in the MARCH (metformin, and acarbose in Chinese patients as the initial hypoglycemic treatment) cohort. There was a significant difference in PRS for cardiovascular diseases (CVD) across four subgroups in the MARCH cohort (p < 0.05). Compared with the SIDD and SIRD subgroups, patients in the MOD subgroup had a relatively lower PRS for CVD (p < 0.05) in the MARCH cohort. Females had a higher PRS compared to males, with no significant difference in FRS across the four clusters. The MOD subgroup had a significantly lower FRS which was consistent with the results of PRS. Similar results of PRS and FRS were also replicated in the CONFIDENCE (comparison of glycemic control and b-cell function among newly diagnosed patients with type 2 diabetes treated with exenatide, insulin or pioglitazone) cohort.
There are different CVD risks in diabetic subgroups based on clinical and genetic evidence which may promote precision medicine.
•Individuals with type 2 diabetes have heterogeneity in metabolic features.•Type 2 diabetes can be classified into four subgroups with different cardiovascular risks.•The mild obesity-related diabetes subgroup has the lowest cardiovascular diseases risk.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.dsx.2023.102850</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-2609-8387</orcidid><orcidid>https://orcid.org/0000-0002-5896-2793</orcidid></addata></record> |
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| subjects | Cardiovascular risks Diabetes subgroups Machine learning Polygenic risk score |
| title | Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults |
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