Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes
Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals...
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| Veröffentlicht in: | Nature genetics 2021-11, Vol.53 (11), p.1534-1542 |
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| creator | Mansour Aly, Dina Dwivedi, Om Prakash Prasad, Rashmi B. Käräjämäki, Annemari Hjort, Rebecka Thangam, Manonanthini Åkerlund, Mikael Mahajan, Anubha Udler, Miriam S. Florez, Jose C. McCarthy, Mark I. Brosnan, Julia Melander, Olle Carlsson, Sofia Hansson, Ola Tuomi, Tiinamaija Groop, Leif Ahlqvist, Emma |
| description | Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the
TCF7L2
locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near
LRMDA
was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.
Genome-wide association and genetic risk score analyses highlight differences in genetic architecture across five subtypes of diabetes. |
| doi_str_mv | 10.1038/s41588-021-00948-2 |
| format | Article |
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TCF7L2
locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near
LRMDA
was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.
Genome-wide association and genetic risk score analyses highlight differences in genetic architecture across five subtypes of diabetes.</description><identifier>ISSN: 1061-4036</identifier><identifier>ISSN: 1546-1718</identifier><identifier>EISSN: 1546-1718</identifier><identifier>DOI: 10.1038/s41588-021-00948-2</identifier><identifier>PMID: 34737425</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>45/43 ; 692/699 ; 692/699/2743/137 ; Adolescent ; Adult ; Aged ; Aged, 80 and over ; Agriculture ; ANDIS ; Animal Genetics and Genomics ; Biomedical and Life Sciences ; Biomedicine ; Body Mass Index ; Cancer Research ; Child ; Child, Preschool ; Clinical Medicine ; Cluster analysis ; Diabetes ; Diabetes mellitus (non-insulin dependent) ; Diabetes Mellitus, Type 1 - genetics ; Diabetes Mellitus, Type 2 - etiology ; Diabetes Mellitus, Type 2 - genetics ; Endocrinology and Diabetes ; Endokrinologi och diabetes ; Etiology ; Family medical history ; Gene Function ; Genetic analysis ; Genetic Predisposition to Disease ; Genetics ; Genome-Wide Association Study ; Genomes ; Glucose ; Health risk assessment ; Human Genetics ; Humans ; Infant ; Insulin ; Insulin resistance ; Insulin secretion ; Insulin Secretion - genetics ; Klinisk medicin ; Lipids - blood ; Lipids - genetics ; Medical and Health Sciences ; Medicin och hälsovetenskap ; Metabolism ; Metabolites ; Middle Aged ; Obesity ; Patients ; Polymorphism, Single Nucleotide ; Risk analysis ; Single-nucleotide polymorphism ; Sweden ; Young Adult</subject><ispartof>Nature genetics, 2021-11, Vol.53 (11), p.1534-1542</ispartof><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2021</rights><rights>2021. The Author(s), under exclusive licence to Springer Nature America, Inc.</rights><rights>Copyright Nature Publishing Group Nov 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c482t-62db65879b44ec508db33a4568c024fde481e9ee7ab4841d60e70fd9d766b5cd3</citedby><cites>FETCH-LOGICAL-c482t-62db65879b44ec508db33a4568c024fde481e9ee7ab4841d60e70fd9d766b5cd3</cites><orcidid>0000-0002-1730-9325 ; 0000-0002-0187-3263 ; 0000-0002-8306-6202 ; 0000-0002-4400-6741 ; 0000-0002-7394-7639 ; 0000-0003-3824-9162 ; 0000-0002-6513-2384 ; 0000-0001-8670-7717 ; 0000-0002-7164-6525</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41588-021-00948-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41588-021-00948-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34737425$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://lup.lub.lu.se/record/6ed784f1-24f1-4a0d-9b59-ba9be7d1a5e1$$DView record from Swedish Publication Index$$Hfree_for_read</backlink><backlink>$$Uhttp://kipublications.ki.se/Default.aspx?queryparsed=id:148379480$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Mansour Aly, Dina</creatorcontrib><creatorcontrib>Dwivedi, Om Prakash</creatorcontrib><creatorcontrib>Prasad, Rashmi B.</creatorcontrib><creatorcontrib>Käräjämäki, Annemari</creatorcontrib><creatorcontrib>Hjort, Rebecka</creatorcontrib><creatorcontrib>Thangam, Manonanthini</creatorcontrib><creatorcontrib>Åkerlund, Mikael</creatorcontrib><creatorcontrib>Mahajan, Anubha</creatorcontrib><creatorcontrib>Udler, Miriam S.</creatorcontrib><creatorcontrib>Florez, Jose C.</creatorcontrib><creatorcontrib>McCarthy, Mark I.</creatorcontrib><creatorcontrib>Brosnan, Julia</creatorcontrib><creatorcontrib>Melander, Olle</creatorcontrib><creatorcontrib>Carlsson, Sofia</creatorcontrib><creatorcontrib>Hansson, Ola</creatorcontrib><creatorcontrib>Tuomi, Tiinamaija</creatorcontrib><creatorcontrib>Groop, Leif</creatorcontrib><creatorcontrib>Ahlqvist, Emma</creatorcontrib><creatorcontrib>Regeneron Genetics Center</creatorcontrib><creatorcontrib>Genome Informatics</creatorcontrib><creatorcontrib>RGC Management and Leadership Team</creatorcontrib><creatorcontrib>Sequencing and Lab Operations</creatorcontrib><creatorcontrib>Research Program Management</creatorcontrib><title>Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes</title><title>Nature genetics</title><addtitle>Nat Genet</addtitle><addtitle>Nat Genet</addtitle><description>Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the
TCF7L2
locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near
LRMDA
was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.
Genome-wide association and genetic risk score analyses highlight differences in genetic architecture across five subtypes of diabetes.</description><subject>45/43</subject><subject>692/699</subject><subject>692/699/2743/137</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Agriculture</subject><subject>ANDIS</subject><subject>Animal Genetics and Genomics</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Body Mass Index</subject><subject>Cancer Research</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Clinical Medicine</subject><subject>Cluster analysis</subject><subject>Diabetes</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetes Mellitus, Type 1 - genetics</subject><subject>Diabetes Mellitus, Type 2 - etiology</subject><subject>Diabetes Mellitus, Type 2 - genetics</subject><subject>Endocrinology and Diabetes</subject><subject>Endokrinologi och diabetes</subject><subject>Etiology</subject><subject>Family medical history</subject><subject>Gene Function</subject><subject>Genetic analysis</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetics</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Glucose</subject><subject>Health risk assessment</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Infant</subject><subject>Insulin</subject><subject>Insulin resistance</subject><subject>Insulin secretion</subject><subject>Insulin Secretion - genetics</subject><subject>Klinisk medicin</subject><subject>Lipids - blood</subject><subject>Lipids - genetics</subject><subject>Medical and Health Sciences</subject><subject>Medicin och hälsovetenskap</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Middle 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association analyses highlight etiological differences underlying newly defined subtypes of diabetes</title><author>Mansour Aly, Dina ; Dwivedi, Om Prakash ; Prasad, Rashmi B. ; Käräjämäki, Annemari ; Hjort, Rebecka ; Thangam, Manonanthini ; Åkerlund, Mikael ; Mahajan, Anubha ; Udler, Miriam S. ; Florez, Jose C. ; McCarthy, Mark I. ; Brosnan, Julia ; Melander, Olle ; Carlsson, Sofia ; Hansson, Ola ; Tuomi, Tiinamaija ; Groop, Leif ; Ahlqvist, Emma</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c482t-62db65879b44ec508db33a4568c024fde481e9ee7ab4841d60e70fd9d766b5cd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>45/43</topic><topic>692/699</topic><topic>692/699/2743/137</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Agriculture</topic><topic>ANDIS</topic><topic>Animal Genetics and 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Informatics</aucorp><aucorp>RGC Management and Leadership Team</aucorp><aucorp>Sequencing and Lab Operations</aucorp><aucorp>Research Program Management</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes</atitle><jtitle>Nature genetics</jtitle><stitle>Nat Genet</stitle><addtitle>Nat Genet</addtitle><date>2021-11-01</date><risdate>2021</risdate><volume>53</volume><issue>11</issue><spage>1534</spage><epage>1542</epage><pages>1534-1542</pages><issn>1061-4036</issn><issn>1546-1718</issn><eissn>1546-1718</eissn><abstract>Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the
TCF7L2
locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near
LRMDA
was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.
Genome-wide association and genetic risk score analyses highlight differences in genetic architecture across five subtypes of diabetes.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>34737425</pmid><doi>10.1038/s41588-021-00948-2</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-1730-9325</orcidid><orcidid>https://orcid.org/0000-0002-0187-3263</orcidid><orcidid>https://orcid.org/0000-0002-8306-6202</orcidid><orcidid>https://orcid.org/0000-0002-4400-6741</orcidid><orcidid>https://orcid.org/0000-0002-7394-7639</orcidid><orcidid>https://orcid.org/0000-0003-3824-9162</orcidid><orcidid>https://orcid.org/0000-0002-6513-2384</orcidid><orcidid>https://orcid.org/0000-0001-8670-7717</orcidid><orcidid>https://orcid.org/0000-0002-7164-6525</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1061-4036 |
| ispartof | Nature genetics, 2021-11, Vol.53 (11), p.1534-1542 |
| issn | 1061-4036 1546-1718 1546-1718 |
| language | eng |
| recordid | cdi_swepub_primary_oai_swepub_ki_se_457839 |
| source | MEDLINE; Springer Nature - Complete Springer Journals; Nature |
| subjects | 45/43 692/699 692/699/2743/137 Adolescent Adult Aged Aged, 80 and over Agriculture ANDIS Animal Genetics and Genomics Biomedical and Life Sciences Biomedicine Body Mass Index Cancer Research Child Child, Preschool Clinical Medicine Cluster analysis Diabetes Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 1 - genetics Diabetes Mellitus, Type 2 - etiology Diabetes Mellitus, Type 2 - genetics Endocrinology and Diabetes Endokrinologi och diabetes Etiology Family medical history Gene Function Genetic analysis Genetic Predisposition to Disease Genetics Genome-Wide Association Study Genomes Glucose Health risk assessment Human Genetics Humans Infant Insulin Insulin resistance Insulin secretion Insulin Secretion - genetics Klinisk medicin Lipids - blood Lipids - genetics Medical and Health Sciences Medicin och hälsovetenskap Metabolism Metabolites Middle Aged Obesity Patients Polymorphism, Single Nucleotide Risk analysis Single-nucleotide polymorphism Sweden Young Adult |
| title | Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T13%3A03%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_swepu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Genome-wide%20association%20analyses%20highlight%20etiological%20differences%20underlying%20newly%20defined%20subtypes%20of%20diabetes&rft.jtitle=Nature%20genetics&rft.au=Mansour%20Aly,%20Dina&rft.aucorp=Regeneron%20Genetics%20Center&rft.date=2021-11-01&rft.volume=53&rft.issue=11&rft.spage=1534&rft.epage=1542&rft.pages=1534-1542&rft.issn=1061-4036&rft.eissn=1546-1718&rft_id=info:doi/10.1038/s41588-021-00948-2&rft_dat=%3Cproquest_swepu%3E2594719567%3C/proquest_swepu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2594719567&rft_id=info:pmid/34737425&rfr_iscdi=true |