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Chen X, Chen L. Causal Links Between Systemic Disorders and Keratoconus in European Population. Am J Ophthalmol 2024; 265:189-199. [PMID: 38705552 DOI: 10.1016/j.ajo.2024.04.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 04/28/2024] [Accepted: 04/30/2024] [Indexed: 05/07/2024]
Abstract
PURPOSE To establish the presence of a causal linkage between prevalent systemic diseases and keratoconus (KC). DESIGN Mendelian randomization (MR) analysis. METHODS After an exhaustive screening process, genetic variants linked to various systemic diseases were identified as instrumental variables at the genome-wide significance level. Subsequently, MR analyses were conducted to elucidate their potential causal connection with KC (N = 26,742). The encompassed systemic ailments comprise diabetes, hay fever/allergic rhinitis/eczema, obstructive sleep apnea, thyroid dysfunction, aortic aneurysm, major depressive disorder, inflammatory bowel disease (including Crohn's disease and ulcerative colitis), and mitral valve prolapse. Our study adheres to the principles of Strengthening the Reporting of Observational Studies in Epidemiology Using MR guidelines. RESULTS Using inverse variance weighting as the primary MR analysis method, our findings revealed that hay fever/allergic rhinitis/eczema (odds ratio, 10.144; 95% CI, 2.441-42.149; P = .001) and ulcerative colitis (odds ratio, 1.147; 95% CI, 1.054-1.248; P = .002) were associated with an increased risk of KC within the largest population under scrutiny. Conversely, the prolonged hyperglycemic state did not exhibit a potentially protective effect in delaying the pathogenesis of KC, and no correlation was observed between the two (odds ratio, 0.320; 95% CI, 0.029-3.549; P = .353). Also, obstructive sleep apnea, thyroid function, aortic aneurysm, major depressive disorder, Crohn's disease, and mitral valve prolapse did not exhibit a causal association with KC (P > .05 for all comparisons). CONCLUSIONS This study indicates an increased risk of KC related to hay fever/allergic rhinitis/eczema and ulcerative colitis, with diabetes not providing a protective effect. These findings may potentially contribute some insights to inform clinical interventions.
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Affiliation(s)
- Xiaxue Chen
- From the Department of Ophthalmology (X.C.), The Second Hospital of Jilin University, Changchun, Jilin, China.
| | - Lanlan Chen
- Department of Hepatobiliary and Pancreatic Surgery (L.C.), General Surgery Center, The First Hospital of Jilin University, Changchun, Jilin, China
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Thomas A, Haak T, Tombek A, Kulzer B, Ehrmann D, Kordonouri O, Kröger J, Schubert-Olesen O, Kolassa R, Siegmund T, Haller N, Heinemann L. How to Use Continuous Glucose Monitoring Efficiently in Diabetes Management: Opinions and Recommendations by German Experts on the Status and Open Questions. J Diabetes Sci Technol 2024:19322968241267768. [PMID: 39129243 DOI: 10.1177/19322968241267768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Today, continuous glucose monitoring (CGM) is a standard diagnostic option for patients with diabetes, at least for those with type 1 diabetes and those with type 2 diabetes on insulin therapy, according to international guidelines. The switch from spot capillary blood glucose measurement to CGM was driven by the extensive and immediate support and facilitation of diabetes management CGM offers. In patients not using insulin, the benefits of CGM are not so well studied/obvious. In such patients, factors like well-being and biofeedback are driving CGM uptake and outcome. Apps can combine CGM data with data about physical activity and meal consumption for therapy adjustments. Personalized data management and coaching is also more feasible with CGM data. The same holds true for digitalization and telemedicine intervention ("virtual diabetes clinic"). Combining CGM data with Smart Pens ("patient decision support") helps to avoid missing insulin boluses or insulin miscalculation. Continuous glucose monitoring is a major pillar of all automated insulin delivery systems, which helps substantially to avoid acute complications and achieve more time in the glycemic target range. These options were discussed by a group of German experts to identify concrete gaps in the care structure, with a view to the necessary structural adjustments of the health care system.
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Affiliation(s)
| | - Thomas Haak
- Diabetes consulting, Mergentheim Diabetes Center, Bad Mergentheim, Germany
| | - Astrid Tombek
- Diabetes consulting, Mergentheim Diabetes Center, Bad Mergentheim, Germany
| | - Bernhard Kulzer
- Diabetes consulting, Mergentheim Diabetes Center, Bad Mergentheim, Germany
- FIDAM, Forschungsinstitut Diabetes-Akademie Mergentheim (Diabetes Academy Mergentheim Research Institute), Bad Mergentheim, Germany
| | - Dominic Ehrmann
- FIDAM, Forschungsinstitut Diabetes-Akademie Mergentheim (Diabetes Academy Mergentheim Research Institute), Bad Mergentheim, Germany
| | - Olga Kordonouri
- AUF DER BULT Hospital, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Jens Kröger
- Diabetes, Hamburg City Diabetes Center, Hamburg, Germany
| | | | - Ralf Kolassa
- Diabetes, Diabetes Focus Practice Bergheim/Erft, Bergheim/Erft, Germany
| | | | - Nicola Haller
- Diabetes, Diabetes & Metabolic Center Starnberg, Starnberg, Germany
| | - Lutz Heinemann
- Science Consulting in Diabetes GmbH, Düsseldorf, Germany
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Fan R, Li S, Xue Z, Yang R, Lyu J, He H. Age-specific differences in association of glycosylated hemoglobin levels with the prevalence of cardiovascular diseases among nondiabetics: the National Health and Nutrition Examination Survey 2005-2018. BMC Cardiovasc Disord 2024; 24:310. [PMID: 38898403 PMCID: PMC11186280 DOI: 10.1186/s12872-024-03978-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/14/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND Previous research has supported the presence of an association between high glycated hemoglobin (HbA1c) levels and cardiovascular disease (CVD). The objective of the present study was to determine whether increased HbA1c levels are associated with high CVD prevalence among nondiabetics. Furthermore, we aimed to explore the possible interaction of HbA1c levels and age in regard to CVD. METHODS This cross-sectional study analyzed data of 28,534 adult participants in the National Health and Nutrition Examination Survey 2005-2018. The association between HbA1c and CVD was assessed using univariate and multivariate logistic regression models. Propensity score matching was used to reduce selection bias. Subgroup analysis and restricted cubic spline (RCS) were used to further characterize the association between HbA1c levels and CVD. We modeled additive interactions to further assess the relationship between HbA1c levels and age. RESULTS In the multivariate logistic regression model, a positive association was found between CVD and increased HbA1c levels (highest quartile [Q4] vs. lowest quartile [Q1]: odds ratio [OR] = 1.277, 95% confidence interval [CI] = 1.111-1.469, P = 0.001). In the stratified analyses, the adjusted association between HbA1c and CVD was significant for those younger than 55 years (Q4 vs. Q1: OR = 1.437, 95% CI = 1.099-1.880, P = 0.008). RCS did not reveal a nonlinear relationship between HbA1c levels and CVD among nondiabetics (P for nonlinearity = 0.609). Additionally, a high HbA1c level was favorably connected with old age on CVD, with a synergistic impact. CONCLUSIONS Increased HbA1c levels were associated with high CVD prevalence among nondiabetics. However, we still need to carefully explain the effect of age on the relationship between HbA1c and CVD in nondiabetic population. Given the correlations of HbA1c with CVDs and CV events, HbA1c might be a useful indicator for predicting CVDs and CV events in the nondiabetic population.
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Affiliation(s)
- Ruihan Fan
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, People's Republic of China
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Shuna Li
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Tianhe District, 613 W. Huangpu Avenue, Guangzhou, Guangdong, 510632, People's Republic of China
| | - Zihan Xue
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Ruida Yang
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Tianhe District, 613 W. Huangpu Avenue, Guangzhou, Guangdong, 510632, People's Republic of China.
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou, Guangdong, China.
| | - Hairong He
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, People's Republic of China.
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
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Lares-Villaseñor E, Guevara-Cruz M, Salazar-García S, Granados-Portillo O, Vega-Cárdenas M, Martinez-Leija ME, Medina-Vera I, González-Salazar LE, Arteaga-Sanchez L, Guízar-Heredia R, Hernández-Gómez KG, Serralde-Zúñiga AE, Pichardo-Ontiveros E, López-Barradas AM, Guevara-Pedraza L, Ordaz-Nava G, Avila-Nava A, Tovar AR, Cossío-Torres PE, de la Cruz-Mosso U, Aradillas-García C, Portales-Pérez DP, Noriega LG, Vargas-Morales JM. Genetic risk score for insulin resistance based on gene variants associated to amino acid metabolism in young adults. PLoS One 2024; 19:e0299543. [PMID: 38422035 PMCID: PMC10903913 DOI: 10.1371/journal.pone.0299543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024] Open
Abstract
Circulating concentration of arginine, alanine, aspartate, isoleucine, leucine, phenylalanine, proline, tyrosine, taurine and valine are increased in subjects with insulin resistance, which could in part be attributed to the presence of single nucleotide polymorphisms (SNPs) within genes associated with amino acid metabolism. Thus, the aim of this work was to develop a Genetic Risk Score (GRS) for insulin resistance in young adults based on SNPs present in genes related to amino acid metabolism. We performed a cross-sectional study that included 452 subjects over 18 years of age. Anthropometric, clinical, and biochemical parameters were assessed including measurement of serum amino acids by high performance liquid chromatography. Eighteen SNPs were genotyped by allelic discrimination. Of these, ten were found to be in Hardy-Weinberg equilibrium, and only four were used to construct the GRS through multiple linear regression modeling. The GRS was calculated using the number of risk alleles of the SNPs in HGD, PRODH, DLD and SLC7A9 genes. Subjects with high GRS (≥ 0.836) had higher levels of glucose, insulin, homeostatic model assessment- insulin resistance (HOMA-IR), total cholesterol and triglycerides, and lower levels of arginine than subjects with low GRS (p < 0.05). The application of a GRS based on variants within genes associated to amino acid metabolism may be useful for the early identification of subjects at increased risk of insulin resistance.
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Affiliation(s)
- Eunice Lares-Villaseñor
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Martha Guevara-Cruz
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Samuel Salazar-García
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Omar Granados-Portillo
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Mariela Vega-Cárdenas
- Laboratorio de Nutrición, Departamento de Ciencias en Investigación Aplicadas en Ambiente y Salud, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | | | - Isabel Medina-Vera
- Departamento de Metodología de la Investigación, Instituto Nacional de Pediatría, Ciudad de México, México
| | - Luis E. González-Salazar
- Servicio de Nutriología Clínica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Liliana Arteaga-Sanchez
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Rocío Guízar-Heredia
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Karla G. Hernández-Gómez
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Aurora E. Serralde-Zúñiga
- Servicio de Nutriología Clínica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Edgar Pichardo-Ontiveros
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Adriana M. López-Barradas
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | | | - Guillermo Ordaz-Nava
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Azalia Avila-Nava
- Hospital Regional de Alta Especialidad de la Península de Yucatán, IMSS-Bienestar, Mérida, Yucatán, Mexico
| | - Armando R. Tovar
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Patricia E. Cossío-Torres
- Departamento de Salud Pública y Ciencias Médicas, Facultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Ulises de la Cruz-Mosso
- Red de Inmunonutrición y Genómica Nutricional en las Enfermedades Autoinmunes, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, México
| | - Celia Aradillas-García
- Facultad de Medicina, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Diana P. Portales-Pérez
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Lilia G. Noriega
- Fisiología de la Nutrición, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de México, México
| | - Juan M. Vargas-Morales
- Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
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Larsson SC, Butterworth AS, Burgess S. Mendelian randomization for cardiovascular diseases: principles and applications. Eur Heart J 2023; 44:4913-4924. [PMID: 37935836 PMCID: PMC10719501 DOI: 10.1093/eurheartj/ehad736] [Citation(s) in RCA: 82] [Impact Index Per Article: 82.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/13/2023] [Accepted: 10/17/2023] [Indexed: 11/09/2023] Open
Abstract
Large-scale genome-wide association studies conducted over the last decade have uncovered numerous genetic variants associated with cardiometabolic traits and risk factors. These discoveries have enabled the Mendelian randomization (MR) design, which uses genetic variation as a natural experiment to improve causal inferences from observational data. By analogy with the random assignment of treatment in randomized controlled trials, the random segregation of genetic alleles when DNA is transmitted from parents to offspring at gamete formation is expected to reduce confounding in genetic associations. Mendelian randomization analyses make a set of assumptions that must hold for valid results. Provided that the assumptions are well justified for the genetic variants that are employed as instrumental variables, MR studies can inform on whether a putative risk factor likely has a causal effect on the disease or not. Mendelian randomization has been increasingly applied over recent years to predict the efficacy and safety of existing and novel drugs targeting cardiovascular risk factors and to explore the repurposing potential of available drugs. This review article describes the principles of the MR design and some applications in cardiovascular epidemiology.
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Affiliation(s)
- Susanna C Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Papworth Road, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK, Wellcome Genome Campus and University of Cambridge, Hinxton, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Papworth Road, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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Burgess S. Violation of the Constant Genetic Effect Assumption Can Result in Biased Estimates for Non-Linear Mendelian Randomization. Hum Hered 2023; 88:79-90. [PMID: 37651993 PMCID: PMC10614256 DOI: 10.1159/000531659] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 06/12/2023] [Indexed: 09/02/2023] Open
Abstract
INTRODUCTION Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice. METHODS We use the recently developed doubly ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D (25[OH]D) used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality. RESULTS The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method but not for the doubly ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures and less reasonable for others. If the doubly ranked method indicates that this assumption is violated, then estimates from both the residual and doubly ranked methods can be biased, although bias was smaller on average in the doubly ranked method. CONCLUSION Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly ranked methods, as well as consider transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
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7
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Burgess S, Mason AM, Grant AJ, Slob EAW, Gkatzionis A, Zuber V, Patel A, Tian H, Liu C, Haynes WG, Hovingh GK, Knudsen LB, Whittaker JC, Gill D. Using genetic association data to guide drug discovery and development: Review of methods and applications. Am J Hum Genet 2023; 110:195-214. [PMID: 36736292 PMCID: PMC9943784 DOI: 10.1016/j.ajhg.2022.12.017] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Amy M Mason
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Andrew J Grant
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Eric A W Slob
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | | | - Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; UK Dementia Research Institute at Imperial College, Imperial College London, London, UK
| | - Ashish Patel
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Haodong Tian
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Cunhao Liu
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - William G Haynes
- Novo Nordisk Research Centre Oxford, Novo Nordisk, Oxford, UK; Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - G Kees Hovingh
- Department of Vascular Medicine, Academic Medical Center, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands; Global Chief Medical Office, Novo Nordisk, Copenhagen, Denmark
| | - Lotte Bjerre Knudsen
- Chief Scientific Advisor Office, Research and Early Development, Novo Nordisk, Copenhagen, Denmark
| | - John C Whittaker
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Chief Scientific Advisor Office, Research and Early Development, Novo Nordisk, Copenhagen, Denmark
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Garfield V, Salzmann A, Burgess S, Chaturvedi N. A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach. Diabetes 2023; 72:175-183. [PMID: 36669000 PMCID: PMC7614590 DOI: 10.2337/db22-0110] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 10/24/2022] [Indexed: 01/21/2023]
Abstract
In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.
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Affiliation(s)
- Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
| | - Antoine Salzmann
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, MRC Biostatistics Unit, University of Cambridge, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London
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Gottwald-Hostalek U, Gwilt M. Vascular complications in prediabetes and type 2 diabetes: a continuous process arising from a common pathology. Curr Med Res Opin 2022; 38:1841-1851. [PMID: 35833523 DOI: 10.1080/03007995.2022.2101805] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The term, "prediabetes", describes a state of hyperglycaemia that is intermediate between true normoglycaemia and the diagnostic cut-offs for indices of glycaemia that are used to diagnose type 2 diabetes. The presence of prediabetes markedly increases the risk of developing type 2 diabetes. Numerous randomized, controlled evaluations of various agents have demonstrated significant prevention or delay of the onset of type 2 diabetes in subjects with prediabetes. Intensive lifestyle interventions and metformin have been studied most widely, with the lifestyle intervention being more effective in the majority of subjects. The application of therapeutic interventions at the time of prediabetes to preserve long-term outcomes has been controversial, however, due to a lack of evidence relating to the pathogenic effects of prediabetes and the effectiveness of interventions to produce a long-term clinical benefit. Recent studies have confirmed that prediabetes, however defined, is associated with a significantly increased risk of macrovascular and microvascular complications essentially identical to those of diabetes, and also with subclinical derangements of the function of microvasculature and neurons that likely signify increased risk of compilations in future. Normoglycaemia, prediabetes and type 2 diabetes appear to be part of a continuum of increased risk of adverse outcomes. Long-term (25-30 years) post-trial follow up of two major diabetes prevention trials have shown that short-term interventions to prevent diabetes lead to long-term reductions in the risk of complications. These findings support the concept of therapeutic intervention to preserve long-term health in people with prediabetes before type 2 diabetes becomes established.
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Moksnes MR, Graham SE, Wu KH, Hansen AF, Gagliano Taliun SA, Zhou W, Thorstensen K, Fritsche LG, Gill D, Mason A, Cucca F, Schlessinger D, Abecasis GR, Burgess S, Åsvold BO, Nielsen JB, Hveem K, Willer CJ, Brumpton BM. Genome-wide meta-analysis of iron status biomarkers and the effect of iron on all-cause mortality in HUNT. Commun Biol 2022; 5:591. [PMID: 35710628 PMCID: PMC9203493 DOI: 10.1038/s42003-022-03529-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 05/24/2022] [Indexed: 01/19/2023] Open
Abstract
Iron is essential for many biological processes, but iron levels must be tightly regulated to avoid harmful effects of both iron deficiency and overload. Here, we perform genome-wide association studies on four iron-related biomarkers (serum iron, serum ferritin, transferrin saturation, total iron-binding capacity) in the Trøndelag Health Study (HUNT), the Michigan Genomics Initiative (MGI), and the SardiNIA study, followed by their meta-analysis with publicly available summary statistics, analyzing up to 257,953 individuals. We identify 123 genetic loci associated with iron traits. Among 19 novel protein-altering variants, we observe a rare missense variant (rs367731784) in HUNT, which suggests a role for DNAJC13 in transferrin recycling. We further validate recently published results using genetic risk scores for each biomarker in HUNT (6% variance in serum iron explained) and present linear and non-linear Mendelian randomization analyses of the traits on all-cause mortality. We find evidence of a harmful effect of increased serum iron and transferrin saturation in linear analyses that estimate population-averaged effects. However, there was weak evidence of a protective effect of increasing serum iron at the very low end of its distribution. Our findings contribute to our understanding of the genes affecting iron status and its consequences on human health.
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Affiliation(s)
- Marta R Moksnes
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
| | - Sarah E Graham
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Kuan-Han Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ailin Falkmo Hansen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
| | - Sarah A Gagliano Taliun
- Department of Medicine and Department of Neurosciences, Université de Montréal, Montréal, QC, Canada
- Montréal Heart Institute, Montréal, QC, Canada
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ketil Thorstensen
- Department of Clinical Chemistry, St. Olavs hospital Trondheim University Hospital, Trondheim, Norway
| | - Lars G Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Clinical Pharmacology and Therapeutics Section, Institute for Infection and Immunity, St George's, University of London, London, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust, London, UK
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK
| | - Amy Mason
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, US National Institutes of Health, Baltimore, MD, USA
| | - Gonçalo R Abecasis
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Stephen Burgess
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs hospital Trondheim University Hospital, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Levanger, Norway
| | - Jonas B Nielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
- Department of Cardiology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Levanger, Norway
| | - Cristen J Willer
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Montréal Heart Institute, Montréal, QC, Canada
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ben M Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
- HUNT Research Centre, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Levanger, Norway.
- Clinic of Medicine, St. Olavs hospital Trondheim University Hospital, Trondheim, Norway.
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11
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Walker VM, Vujkovic M, Carter AR, Davies NM, Udler MS, Levin MG, Davey Smith G, Voight BF, Gaunt TR, Damrauer SM. Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes. Diabetologia 2022; 65:790-799. [PMID: 35129650 PMCID: PMC8960614 DOI: 10.1007/s00125-022-05653-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 11/22/2021] [Indexed: 12/31/2022]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes. METHODS Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD. RESULTS Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%). CONCLUSIONS/INTERPRETATION Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual's liability to type 2 diabetes.
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Affiliation(s)
- Venexia M Walker
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK.
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK.
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Marijana Vujkovic
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alice R Carter
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Neil M Davies
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Miriam S Udler
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Michael G Levin
- Division of Cardiovascular Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - George Davey Smith
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tom R Gaunt
- MRC University of Bristol Integrative Epidemiology Unit, Bristol, UK
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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12
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Biddinger KJ, Emdin CA, Haas ME, Wang M, Hindy G, Ellinor PT, Kathiresan S, Khera AV, Aragam KG. Association of Habitual Alcohol Intake With Risk of Cardiovascular Disease. JAMA Netw Open 2022; 5:e223849. [PMID: 35333364 PMCID: PMC8956974 DOI: 10.1001/jamanetworkopen.2022.3849] [Citation(s) in RCA: 154] [Impact Index Per Article: 77.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
IMPORTANCE Observational studies have consistently proposed cardiovascular benefits associated with light alcohol consumption, while recent genetic analyses (ie, mendelian randomization studies) have suggested a possible causal link between alcohol intake and increased risk of cardiovascular disease. However, traditional approaches to genetic epidemiology assume a linear association and thus have not fully evaluated dose-response estimates of risk across different levels of alcohol intake. OBJECTIVES To assess the association of habitual alcohol intake with cardiovascular disease risk and to evaluate the direction and relative magnitude of cardiovascular risk associated with different amounts of alcohol consumption. DESIGN, SETTING, AND PARTICIPANTS This cohort study used the UK Biobank (2006-2010, follow-up until 2016) to examine confounding in epidemiologic associations between alcohol intake and cardiovascular diseases. Using both traditional (ie, linear) and nonlinear mendelian randomization, potential associations between alcohol consumption and cardiovascular diseases (eg, hypertension and coronary artery disease) as well as corresponding association shapes were assessed. Data analysis was conducted from July 2019 to January 2022. EXPOSURES Genetic predisposition to alcohol intake. MAIN OUTCOMES AND MEASURES The association between alcohol consumption and cardiovascular diseases, including hypertension, coronary artery disease, myocardial infarction, stroke, heart failure, and atrial fibrillation. RESULTS This study included 371 463 participants (mean [SD] age, 57.0 [7.9] years; 172 400 [46%] men), who consumed a mean (SD) 9.2 (10.6) standard drinks per week. Overall, 121 708 participants (33%) had hypertension. Light to moderate alcohol consumption was associated with healthier lifestyle factors, adjustment for which attenuated the cardioprotective epidemiologic associations with modest intake. In linear mendelian randomization analyses, a 1-SD increase in genetically predicted alcohol consumption was associated with 1.3-fold (95% CI, 1.2-1.4) higher risk of hypertension (P < .001) and 1.4-fold (95% CI, 1.1-1.8) higher risk of coronary artery disease (P = .006). Nonlinear mendelian randomization analyses suggested nonlinear associations between alcohol consumption and both hypertension and coronary artery disease: light alcohol intake was associated with minimal increases in cardiovascular risk, whereas heavier consumption was associated with exponential increases in risk of both clinical and subclinical cardiovascular disease. CONCLUSIONS AND RELEVANCE In this cohort study, coincident, favorable lifestyle factors attenuated the observational benefits of modest alcohol intake. Genetic epidemiology suggested that alcohol consumption of all amounts was associated with increased cardiovascular risk, but marked risk differences exist across levels of intake, including those accepted by current national guidelines.
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Affiliation(s)
- Kiran J. Biddinger
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Connor A. Emdin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Mary E. Haas
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- now with Regeneron Pharmaceuticals, Tarrytown, New York
| | - Minxian Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - George Hindy
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- now with Regeneron Pharmaceuticals, Tarrytown, New York
- Qatar University, Doha, Qatar
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- Verve Therapeutics, Cambridge, Massachusetts
| | - Amit V. Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Krishna G. Aragam
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston
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13
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Luo S, Au Yeung SL, Schooling CM. Assessing the linear and non-linear association of HbA 1c with cardiovascular disease: a Mendelian randomisation study. Diabetologia 2021; 64:2502-2510. [PMID: 34345974 DOI: 10.1007/s00125-021-05537-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/19/2021] [Indexed: 10/20/2022]
Abstract
AIMS/HYPOTHESIS We aimed to evaluate whether genetically predicted HbA1c has an effect on the risk of cardiovascular diseases and investigate the shape of the relationship of genetically predicted HbA1c with cardiovascular diseases. METHODS We performed linear univariable, multivariable and non-linear Mendelian randomisation analyses in 373,571 white British participants (mean age 56.9) from the UK Biobank. RESULTS In univariable linear Mendelian randomisation analysis, a 1 mmol/mol increase in genetically predicted HbA1c was associated with higher risk of coronary artery disease (OR 1.03, 95% CI 1.02, 1.05), stroke (OR 1.02, 95% CI 1.00, 1.05) and hypertension (OR 1.02, 95% CI 1.01, 1.03). Multivariable Mendelian randomisation adjusted for the effect of haemoglobin gave a consistent conclusion for coronary artery disease. The associations with stroke and hypertension were directionally similar but with wider CI overlapping the null. Non-linear Mendelian randomisation indicated that the shape of the effect of genetically predicted HbA1c on cardiovascular outcomes was likely linear. CONCLUSIONS/INTERPRETATION The study suggests a detrimental effect of HbA1c on coronary artery disease in both men and women, and the effect is via a glycaemic characteristic. The shape of the genetic association of HbA1c with these cardiovascular outcomes, in particular coronary artery disease, is likely to be linear.
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Affiliation(s)
- Shan Luo
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China.
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China
- School of Public Health and Health Policy, City University of New York, New York, NY, USA
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14
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Liu B, Mason AM, Sun L, Di Angelantonio E, Gill D, Burgess S. Genetically Predicted Type 2 Diabetes Mellitus Liability, Glycated Hemoglobin and Cardiovascular Diseases: A Wide-Angled Mendelian Randomization Study. Genes (Basel) 2021; 12:1644. [PMID: 34681038 PMCID: PMC8536164 DOI: 10.3390/genes12101644] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 10/13/2021] [Accepted: 10/17/2021] [Indexed: 11/17/2022] Open
Abstract
(1) Aim: To investigate the causal effects of T2DM liability and glycated haemoglobin (HbA1c) levels on various cardiovascular disease outcomes, both in the general population and in non-diabetic individuals specifically. (2) Methods: We selected 243 variants as genetic instruments for T2DM liability and 536 variants for HbA1c. Linear Mendelian randomization analyses were performed to estimate the associations of genetically-predicted T2DM liability and HbA1c with 12 cardiovascular disease outcomes in 367,703 unrelated UK Biobank participants of European ancestries. We performed secondary analyses in participants without diabetes (HbA1c < 6.5% with no diagnosed diabetes), and in participants without diabetes or pre-diabetes (HbA1c < 5.7% with no diagnosed diabetes). (3) Results: Genetically-predicted T2DM liability was positively associated (p < 0.004, 0.05/12) with peripheral vascular disease, aortic valve stenosis, coronary artery disease, heart failure, ischaemic stroke, and any stroke. Genetically-predicted HbA1c was positively associated with coronary artery disease and any stroke. Mendelian randomization estimates generally shifted towards the null when excluding diabetic and pre-diabetic participants from analyses. (4) Conclusions: This genetic evidence supports causal effects of T2DM liability and HbA1c on a range of cardiovascular diseases, suggesting that improving glycaemic control could reduce cardiovascular risk in a general population, with greatest benefit in individuals with diabetes.
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Affiliation(s)
- Bowen Liu
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Amy M. Mason
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
| | - Luanluan Sun
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
| | - Emanuele Di Angelantonio
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
- Genetics Department, Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford OX3 7FZ, UK
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London SW17 0RE, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London SW17 0QT, UK
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (B.L.); (A.M.M.); (L.S.); (E.D.A.)
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK
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