Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease
Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic...
Uložené v:
| Vydané v: | Diabetes care Ročník 42; číslo 7; s. 1202 |
|---|---|
| Hlavní autori: | , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
01.07.2019
|
| ISSN: | 1935-5548, 1935-5548 |
| On-line prístup: | Zistit podrobnosti o prístupe |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors.OBJECTIVEObservational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors.To examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ≥6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and meta-analyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD.RESEARCH DESIGN AND METHODSTo examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ≥6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and meta-analyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD.Genetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 × 10-12). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10-9) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 × 10-6) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02).RESULTSGenetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 × 10-12). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10-9) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 × 10-6) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02).Genetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemia-independent factors.CONCLUSIONSGenetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemia-independent factors. |
|---|---|
| AbstractList | Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors.OBJECTIVEObservational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors.To examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ≥6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and meta-analyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD.RESEARCH DESIGN AND METHODSTo examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ≥6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and meta-analyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD.Genetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 × 10-12). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10-9) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 × 10-6) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02).RESULTSGenetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 × 10-12). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10-9) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 × 10-6) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02).Genetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemia-independent factors.CONCLUSIONSGenetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemia-independent factors. |
| Author | Leong, Aaron Chen, Ji Meigs, James B Wheeler, Eleanor Liu, Ching-Ti Hivert, Marie-France Florez, Jose C Merino, Jordi Tai, E Shyong Barroso, Inês Dupuis, Josée Rotter, Jerome I |
| Author_xml | – sequence: 1 givenname: Aaron surname: Leong fullname: Leong, Aaron – sequence: 2 givenname: Ji surname: Chen fullname: Chen, Ji – sequence: 3 givenname: Eleanor surname: Wheeler fullname: Wheeler, Eleanor – sequence: 4 givenname: Marie-France surname: Hivert fullname: Hivert, Marie-France – sequence: 5 givenname: Ching-Ti surname: Liu fullname: Liu, Ching-Ti – sequence: 6 givenname: Jordi surname: Merino fullname: Merino, Jordi – sequence: 7 givenname: Josée surname: Dupuis fullname: Dupuis, Josée – sequence: 8 givenname: E Shyong surname: Tai fullname: Tai, E Shyong – sequence: 9 givenname: Jerome I surname: Rotter fullname: Rotter, Jerome I – sequence: 10 givenname: Jose C surname: Florez fullname: Florez, Jose C – sequence: 11 givenname: Inês surname: Barroso fullname: Barroso, Inês – sequence: 12 givenname: James B surname: Meigs fullname: Meigs, James B |
| BookMark | eNpNjLFOwzAURS1UJNrCwB94ZAnYsV07YxRoi1SEVMFcvdjPyJDYEKdD-XoiwcBwda7OcBZkFlNEQq45uy2F0HfOclNwzcszMueVUIVS0sz-_QuyyPmdMSalMXNyeMLosAsQ6R6iS334hjGkSOsI3SmHTJOnW-zTW5faMGluKWQKdB_yB12DHdNA_bQmDSnCcKL1MOKE-5ARMl6Scw9dxqs_Lsnr-uGl2Ra7581jU-8KK-VqLDQHxYyQ1cppw5hH7ZmVHJxnmikurGyNEM6Jllmt0PLWeFXBpLXxILFckpvf7ueQvo6Yx0MfssWug4jpmA8l15XQXK5E-QMdjliC |
| CitedBy_id | crossref_primary_10_1097_HJH_0000000000002210 crossref_primary_10_1111_1753_0407_12910 crossref_primary_10_2147_DMSO_S404683 crossref_primary_10_1136_openhrt_2021_001735 crossref_primary_10_1016_j_ebiom_2022_104259 crossref_primary_10_1055_a_2692_1606 crossref_primary_10_1186_s13098_025_01728_2 crossref_primary_10_1186_s13059_022_02837_1 crossref_primary_10_1007_s00125_021_05537_w crossref_primary_10_3389_fendo_2022_942878 crossref_primary_10_1016_j_jacc_2021_03_346 crossref_primary_10_1161_JAHA_122_029040 crossref_primary_10_1038_s41588_021_00852_9 crossref_primary_10_1038_s44325_025_00073_7 crossref_primary_10_2337_db22_0110 crossref_primary_10_1016_j_ecoenv_2023_115338 crossref_primary_10_1186_s12933_023_01875_8 crossref_primary_10_2337_dbi22_0012 crossref_primary_10_2337_db21_0905 crossref_primary_10_1371_journal_pgen_1009497 crossref_primary_10_1186_s12933_022_01540_6 crossref_primary_10_1007_s00592_025_02484_5 crossref_primary_10_1161_CIRCULATIONAHA_122_060026 crossref_primary_10_1016_j_bbi_2025_01_024 crossref_primary_10_1161_CIRCRESAHA_119_316065 crossref_primary_10_1093_ije_dyab152 crossref_primary_10_1007_s11892_019_1173_y crossref_primary_10_1186_s12933_023_02021_0 crossref_primary_10_1002_edm2_299 crossref_primary_10_1186_s12933_021_01413_4 |
| ContentType | Journal Article |
| Copyright | 2019 by the American Diabetes Association. |
| Copyright_xml | – notice: 2019 by the American Diabetes Association. |
| DBID | 7X8 |
| DOI | 10.2337/dc18-1712 |
| DatabaseName | MEDLINE - Academic |
| DatabaseTitle | MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1935-5548 |
| GroupedDBID | --- -ET ..I .XZ 08P 0R~ 18M 29F 2WC 4.4 53G 5GY 5RE 5RS 5VS 6PF 7X8 8R4 8R5 AAFWJ AAIKC AAMNW AAWTL AAYEP ABOCM ABPPZ ACGFO ACGOD ADBBV AEGXH AENEX AERZD AFRAH AHMBA AIAGR ALMA_UNASSIGNED_HOLDINGS BAWUL BENPR BTFSW CS3 DIK DU5 E3Z EBS EDB EJD EMOBN EX3 F5P GX1 H13 HZ~ IAO IEA IHR INH INR IOF IPO KQ8 L7B M0K M5~ O5R O5S O9- OK1 OVD P2P PCD Q2X RHI SV3 TDI TEORI TR2 TWZ VVN W8F WH7 WOQ WOW YHG YOC ZCG ~KM |
| ID | FETCH-LOGICAL-c446t-71a5083496d7800fe7f0c41adf070513c4b833dd3b0c75ec1b8f59ac4b78fa4e2 |
| IEDL.DBID | 7X8 |
| ISICitedReferencesCount | 32 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000472196700021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1935-5548 |
| IngestDate | Fri Sep 05 10:26:11 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 7 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c446t-71a5083496d7800fe7f0c41adf070513c4b833dd3b0c75ec1b8f59ac4b78fa4e2 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://pubmed.ncbi.nlm.nih.gov/PMC6609962 |
| PQID | 2179371463 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_2179371463 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-07-01 |
| PublicationDateYYYYMMDD | 2019-07-01 |
| PublicationDate_xml | – month: 07 year: 2019 text: 2019-07-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationTitle | Diabetes care |
| PublicationYear | 2019 |
| SSID | ssj0004488 |
| Score | 2.4516075 |
| Snippet | Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven... |
| SourceID | proquest |
| SourceType | Aggregation Database |
| StartPage | 1202 |
| Title | Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease |
| URI | https://www.proquest.com/docview/2179371463 |
| Volume | 42 |
| WOSCitedRecordID | wos000472196700021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3fS8MwEA7qRHzxt_ibCL6GNU26NE8i07EHN2Qo7G2klwSGrJ3rFPzvvbQdik-CT4VQaLncXb7cJd9HyI1DVAAdEEzqyDBpY8sMt44ZrbzPrFeunulHNRym47F-agpuZXOscpUTq0RtCwg18nYcPElhXIvb-RsLqlGhu9pIaKyTlkAoE7xajX-whctKdxIxSsJw2UxrZqFYCNW2wHH3pIIQ5a8cXC0svd3__tIe2WkgJb2rfWCfrLn8gGwNmqb5IZkMQpk7lDPoyOS2mDVXL-mKkIQWnvbdrAjkIFMc5kBNSQ0dTctX2qsEeShiW9oNbAdm8Rk-5fBxXzd3jshL7-G522eNrgID3PwtmeImkMBL3bEK8aJ3ykcgubEe4z_hAmSWCmGtyCJQiQOepT7RBodV6o108THZyIvcnRAqVNQxoLnXWSYzG-kY7QoK4zoBB0lySq5Xppug34ZmhMld8V5Ovo139od3zsk2IhVdn5O9IC2PsekuySZ8LKfl4qqa9i8InLg7 |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Mendelian+Randomization+Analysis+of+Hemoglobin+A1c+as+a+Risk+Factor+for+Coronary+Artery+Disease&rft.jtitle=Diabetes+care&rft.au=Leong%2C+Aaron&rft.au=Chen%2C+Ji&rft.au=Wheeler%2C+Eleanor&rft.au=Hivert%2C+Marie-France&rft.date=2019-07-01&rft.issn=1935-5548&rft.eissn=1935-5548&rft.volume=42&rft.issue=7&rft.spage=1202&rft_id=info:doi/10.2337%2Fdc18-1712&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1935-5548&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1935-5548&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1935-5548&client=summon |