Leveraging human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide signalling
Aims/hypothesis The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling. Methods Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether...
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| Veröffentlicht in: | Diabetologia 2021-12, Vol.64 (12), p.2773-2778 |
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| creator | Karhunen, Ville Daghlas, Iyas Zuber, Verena Vujkovic, Marijana Olsen, Anette K. Knudsen, Lotte Bjerre Haynes, William G. Howson, Joanna M. M. Gill, Dipender |
| description | Aims/hypothesis
The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling.
Methods
Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the
GIP
and
GIPR
genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome.
Results
Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the
GIP
and
GIPR
genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the
GIP
and
GIPR
genes with lower BMI (estimate in SD units −0.16, 95% CI −0.30, −0.02), C-reactive protein (−0.13, 95% CI −0.19, −0.08) and triacylglycerol levels (−0.17, 95% CI −0.22, −0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome.
Conclusions/interpretation
This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted.
Data availability
All data used in this study are publicly available. The scripts for the analysis are available at:
https://github.com/vkarhune/GeneticallyProxiedGIP
.
Graphical abstract |
| doi_str_mv | 10.1007/s00125-021-05564-7 |
| format | Article |
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The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling.
Methods
Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the
GIP
and
GIPR
genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome.
Results
Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the
GIP
and
GIPR
genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the
GIP
and
GIPR
genes with lower BMI (estimate in SD units −0.16, 95% CI −0.30, −0.02), C-reactive protein (−0.13, 95% CI −0.19, −0.08) and triacylglycerol levels (−0.17, 95% CI −0.22, −0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome.
Conclusions/interpretation
This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted.
Data availability
All data used in this study are publicly available. The scripts for the analysis are available at:
https://github.com/vkarhune/GeneticallyProxiedGIP
.
Graphical abstract</description><identifier>ISSN: 0012-186X</identifier><identifier>EISSN: 1432-0428</identifier><identifier>DOI: 10.1007/s00125-021-05564-7</identifier><identifier>PMID: 34505161</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>C-reactive protein ; Cardiovascular Diseases - genetics ; Cholesterol ; Diabetes ; Diabetes mellitus (non-insulin dependent) ; Diabetes Mellitus, Type 2 - genetics ; Diabetes Mellitus, Type 2 - metabolism ; Gastric Inhibitory Polypeptide - genetics ; Gastric Inhibitory Polypeptide - metabolism ; Genome-Wide Association Study ; Genomes ; GIP protein ; Glucose - metabolism ; High density lipoprotein ; Human Genetics ; Human Physiology ; Humans ; Internal Medicine ; Liability ; Localization ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Polypeptides ; Receptors, Gastrointestinal Hormone - genetics ; Receptors, Gastrointestinal Hormone - metabolism ; Short Communication ; Statistical analysis</subject><ispartof>Diabetologia, 2021-12, Vol.64 (12), p.2773-2778</ispartof><rights>The Author(s) 2021</rights><rights>2021. The Author(s).</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/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-c474t-4beb7ac46d014d50e07f7dcba0a675b4d6bbe16164e6bd7e54e6fb80f6ee5bee3</citedby><cites>FETCH-LOGICAL-c474t-4beb7ac46d014d50e07f7dcba0a675b4d6bbe16164e6bd7e54e6fb80f6ee5bee3</cites><orcidid>0000-0001-9827-1877 ; 0000-0001-8735-284X ; 0000-0003-1004-6136 ; 0000-0001-7312-7078 ; 0000-0001-9352-621X ; 0000-0003-4924-5714 ; 0000-0001-6064-1588 ; 0000-0002-2439-7116 ; 0000-0001-7618-0050</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00125-021-05564-7$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00125-021-05564-7$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34505161$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Karhunen, Ville</creatorcontrib><creatorcontrib>Daghlas, Iyas</creatorcontrib><creatorcontrib>Zuber, Verena</creatorcontrib><creatorcontrib>Vujkovic, Marijana</creatorcontrib><creatorcontrib>Olsen, Anette K.</creatorcontrib><creatorcontrib>Knudsen, Lotte Bjerre</creatorcontrib><creatorcontrib>Haynes, William G.</creatorcontrib><creatorcontrib>Howson, Joanna M. M.</creatorcontrib><creatorcontrib>Gill, Dipender</creatorcontrib><title>Leveraging human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide signalling</title><title>Diabetologia</title><addtitle>Diabetologia</addtitle><addtitle>Diabetologia</addtitle><description>Aims/hypothesis
The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling.
Methods
Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the
GIP
and
GIPR
genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome.
Results
Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the
GIP
and
GIPR
genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the
GIP
and
GIPR
genes with lower BMI (estimate in SD units −0.16, 95% CI −0.30, −0.02), C-reactive protein (−0.13, 95% CI −0.19, −0.08) and triacylglycerol levels (−0.17, 95% CI −0.22, −0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome.
Conclusions/interpretation
This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted.
Data availability
All data used in this study are publicly available. The scripts for the analysis are available at:
https://github.com/vkarhune/GeneticallyProxiedGIP
.
Graphical abstract</description><subject>C-reactive protein</subject><subject>Cardiovascular Diseases - genetics</subject><subject>Cholesterol</subject><subject>Diabetes</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetes Mellitus, Type 2 - genetics</subject><subject>Diabetes Mellitus, Type 2 - metabolism</subject><subject>Gastric Inhibitory Polypeptide - genetics</subject><subject>Gastric Inhibitory Polypeptide - metabolism</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>GIP protein</subject><subject>Glucose - metabolism</subject><subject>High density lipoprotein</subject><subject>Human Genetics</subject><subject>Human Physiology</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Liability</subject><subject>Localization</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Polypeptides</subject><subject>Receptors, Gastrointestinal Hormone - genetics</subject><subject>Receptors, Gastrointestinal Hormone - metabolism</subject><subject>Short Communication</subject><subject>Statistical analysis</subject><issn>0012-186X</issn><issn>1432-0428</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kTtvFDEUhS1ERJbAH6BAlmhohtgzfsw2SCgCgrQSDUh0lh93Zh3N2IPtWSl1_jheNoRHQXWL893je3wQekHJG0qIvMyE0JY3pKUN4VywRj5CG8q6tiGs7R-jzVFvaC--naOnOd8QQjrOxBN03jFOOBV0g-52cICkRx9GvF9nHfAIAYq32OmicYnYhwPk4kddAJc9YKuT83GGok2cKgfDALZkHAc8TquNGRoHCwQHodTlvE4-xJLiUtklTrcLLMU7wNmPQU9VHJ-hs0FPGZ7fzwv09cP7L1fXze7zx09X73aNZZKVhhkwUlsmHKHMcQJEDtJZo4kWkhvmhDFQQwkGwjgJvM7B9GQQANwAdBfo7cl3Wc0MztYDk57Ukvys062K2qu_leD3aowH1XPR8a6vBq_vDVL8vtZfUbPPFqZJB4hrVi2XdEt7zrcVffUPehPXVAMfqcpIviVdpdoTZVPMOcHwcAwl6tixOnWsasfqZ8dK1qWXf8Z4WPlVagW6E5CrFEZIv9_-j-0Pu4u3sw</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Karhunen, Ville</creator><creator>Daghlas, Iyas</creator><creator>Zuber, Verena</creator><creator>Vujkovic, Marijana</creator><creator>Olsen, Anette K.</creator><creator>Knudsen, Lotte Bjerre</creator><creator>Haynes, William G.</creator><creator>Howson, Joanna M. 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M. ; Gill, Dipender</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-4beb7ac46d014d50e07f7dcba0a675b4d6bbe16164e6bd7e54e6fb80f6ee5bee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>C-reactive protein</topic><topic>Cardiovascular Diseases - genetics</topic><topic>Cholesterol</topic><topic>Diabetes</topic><topic>Diabetes mellitus (non-insulin dependent)</topic><topic>Diabetes Mellitus, Type 2 - genetics</topic><topic>Diabetes Mellitus, Type 2 - metabolism</topic><topic>Gastric Inhibitory Polypeptide - genetics</topic><topic>Gastric Inhibitory Polypeptide - metabolism</topic><topic>Genome-Wide Association Study</topic><topic>Genomes</topic><topic>GIP protein</topic><topic>Glucose - metabolism</topic><topic>High density lipoprotein</topic><topic>Human Genetics</topic><topic>Human Physiology</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Liability</topic><topic>Localization</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Polypeptides</topic><topic>Receptors, Gastrointestinal Hormone - genetics</topic><topic>Receptors, Gastrointestinal Hormone - metabolism</topic><topic>Short Communication</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Karhunen, Ville</creatorcontrib><creatorcontrib>Daghlas, Iyas</creatorcontrib><creatorcontrib>Zuber, Verena</creatorcontrib><creatorcontrib>Vujkovic, Marijana</creatorcontrib><creatorcontrib>Olsen, Anette K.</creatorcontrib><creatorcontrib>Knudsen, Lotte Bjerre</creatorcontrib><creatorcontrib>Haynes, William G.</creatorcontrib><creatorcontrib>Howson, Joanna M. M.</creatorcontrib><creatorcontrib>Gill, Dipender</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</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</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Diabetologia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Karhunen, Ville</au><au>Daghlas, Iyas</au><au>Zuber, Verena</au><au>Vujkovic, Marijana</au><au>Olsen, Anette K.</au><au>Knudsen, Lotte Bjerre</au><au>Haynes, William G.</au><au>Howson, Joanna M. M.</au><au>Gill, Dipender</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Leveraging human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide signalling</atitle><jtitle>Diabetologia</jtitle><stitle>Diabetologia</stitle><addtitle>Diabetologia</addtitle><date>2021-12-01</date><risdate>2021</risdate><volume>64</volume><issue>12</issue><spage>2773</spage><epage>2778</epage><pages>2773-2778</pages><issn>0012-186X</issn><eissn>1432-0428</eissn><abstract>Aims/hypothesis
The aim of this study was to leverage human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide (GIP) signalling.
Methods
Data were obtained from summary statistics of large-scale genome-wide association studies. We examined whether genetic associations for type 2 diabetes liability in the
GIP
and
GIPR
genes co-localised with genetic associations for 11 cardiometabolic outcomes. For those outcomes that showed evidence of co-localisation (posterior probability >0.8), we performed Mendelian randomisation analyses to estimate the association of genetically proxied GIP signalling with risk of cardiometabolic outcomes, and to test whether this exceeded the estimate observed when considering type 2 diabetes liability variants from other regions of the genome.
Results
Evidence of co-localisation with genetic associations of type 2 diabetes liability at both the
GIP
and
GIPR
genes was observed for five outcomes. Mendelian randomisation analyses provided evidence for associations of lower genetically proxied type 2 diabetes liability at the
GIP
and
GIPR
genes with lower BMI (estimate in SD units −0.16, 95% CI −0.30, −0.02), C-reactive protein (−0.13, 95% CI −0.19, −0.08) and triacylglycerol levels (−0.17, 95% CI −0.22, −0.12), and higher HDL-cholesterol levels (0.19, 95% CI 0.14, 0.25). For all of these outcomes, the estimates were greater in magnitude than those observed when considering type 2 diabetes liability variants from other regions of the genome.
Conclusions/interpretation
This study provides genetic evidence to support a beneficial role of sustained GIP signalling on cardiometabolic health greater than that expected from improved glycaemic control alone. Further clinical investigation is warranted.
Data availability
All data used in this study are publicly available. The scripts for the analysis are available at:
https://github.com/vkarhune/GeneticallyProxiedGIP
.
Graphical abstract</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>34505161</pmid><doi>10.1007/s00125-021-05564-7</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0001-9827-1877</orcidid><orcidid>https://orcid.org/0000-0001-8735-284X</orcidid><orcidid>https://orcid.org/0000-0003-1004-6136</orcidid><orcidid>https://orcid.org/0000-0001-7312-7078</orcidid><orcidid>https://orcid.org/0000-0001-9352-621X</orcidid><orcidid>https://orcid.org/0000-0003-4924-5714</orcidid><orcidid>https://orcid.org/0000-0001-6064-1588</orcidid><orcidid>https://orcid.org/0000-0002-2439-7116</orcidid><orcidid>https://orcid.org/0000-0001-7618-0050</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | C-reactive protein Cardiovascular Diseases - genetics Cholesterol Diabetes Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 - genetics Diabetes Mellitus, Type 2 - metabolism Gastric Inhibitory Polypeptide - genetics Gastric Inhibitory Polypeptide - metabolism Genome-Wide Association Study Genomes GIP protein Glucose - metabolism High density lipoprotein Human Genetics Human Physiology Humans Internal Medicine Liability Localization Medicine Medicine & Public Health Metabolic Diseases Polypeptides Receptors, Gastrointestinal Hormone - genetics Receptors, Gastrointestinal Hormone - metabolism Short Communication Statistical analysis |
| title | Leveraging human genetic data to investigate the cardiometabolic effects of glucose-dependent insulinotropic polypeptide signalling |
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