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Kong J, Liu X, Li H, Yang C, Jiang T, Yan Y, Miao N, Mu S, Zhan Y. Exploring the causal relationship between inflammatory cytokines, metabolites, and Behcet's syndrome: Mendelian randomization. Cytokine 2025; 186:156849. [PMID: 39756125 DOI: 10.1016/j.cyto.2024.156849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/02/2024] [Accepted: 12/26/2024] [Indexed: 01/07/2025]
Abstract
INTRODUCTION Behcet's syndrome, as a vasculitic disease involving multiple systems, often induces oral mucosal ulcers. However, levels of inflammatory cytokines and metabolites are unknown for the probability of developing the disease. This study aims to reveal the causal relationship between the cytokines and metabolites and Behcet's syndrome through Mendelian randomization analysis. MATERIALS AND METHODS The instrumental variable single nucleotide polymorphisms (SNPs) were used in the study, which showed associations between 91 cytokines and 553 metabolites, respectively. To explore the causal relationship between these exposure factors and Behcet's syndrome, the random effects inverse variance weighting method was adopted. In addition, sensitivity analysis was carried out using Cochran's Q test, heterogeneity test, horizontal pleotropy test and MR-Egger intercept test to evaluate the robustness and validity of our research results. RESULTS A total of five substances were identified as causally related to Behcet's syndrome, namely, the cellular factors Interleukin 12 subunit beta(IL-12B) and Interleukin-33(IL-33), the metabolite mannitol, X-12728, and Ratio of Bisallylic groups to double bonds. Furthermore, no significant evidence suggesting heterogeneity or pleiotropy was observed. CONCLUSION Our study adds to current knowledge on the role of specific inflammatory cytokines and metabolites in aetiology of Behcet's syndrome. The identified cytokines and metabolites might be used as markers for clinical screening and prevention of Behcet's syndrome, as well as candidate molecules for future mechanism exploration and drug target selection. Further validation is needed to assess the potential of these cytokines and metabolites as pharmacological targets for Behcet's syndrome prevention.
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Affiliation(s)
- Jiaqi Kong
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xinpeng Liu
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Huishu Li
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chubo Yang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tao Jiang
- Department of Anesthesiology (Hei Long Jiang Province Key Lab of Research on Anesthesiology and Critical Care Medicine), The Second Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Ying Yan
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Nan Miao
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Sen Mu
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yuanbo Zhan
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
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Wu M, Wang W, Yang Z, Long G, Zhang Y, Yang D. Illuminating the enigmatic pathogenesis of Kawasaki disease: Unveiling novel therapeutic avenues by targeting FCGR3B-S100A12 pathway. Eur J Pharmacol 2025; 987:177154. [PMID: 39631652 DOI: 10.1016/j.ejphar.2024.177154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 11/13/2024] [Accepted: 11/27/2024] [Indexed: 12/07/2024]
Abstract
Kawasaki disease (KD) primarily affects the pediatric population and exhibits a notable incidence of drug resistance, resulting in coronary artery damage and thrombosis. This study aimed to identify innovative therapeutic targets for KD treatment. By harnessing single-cell data derived from peripheral blood mononuclear cells, we identified differentially expressed genes. Through the integration of eQTL data and Mendelian randomization analysis, we identified FCGR3B and S100A12 were causally linked to KD. The DrugBank database showed their potential as drug target candidates. GSEA further elucidated their roles on coronary artery damage and thrombosis. Furthermore, we have confirmed that the ligand-FCGR3B complex enhances the intracellular calcium concentration (Ca2+) within the cytoplasm, which in turn accelerates the secretion of S100A12, a pro-inflammatory cytokine that targets endothelial cells, from neutrophils. By integrating existing research, we proposed a synergistic effect that FCGR3B-S100A12 pathway positively modulates the development of coronary artery damage and thrombus formation, suggesting their perspectives in clinical treatment.
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Affiliation(s)
- Meng Wu
- Department of Clinical Laboratory Medicine, Children's Hospital of Nanjing Medical University, China
| | - Wenyan Wang
- Department of Nephrology, Children's Hospital of Nanjing Medical University, China
| | - Zhicheng Yang
- Department of Clinical Laboratory Medicine, Children's Hospital of Nanjing Medical University, China
| | - Guangfeng Long
- Department of Clinical Laboratory Medicine, Children's Hospital of Nanjing Medical University, China
| | - Yan Zhang
- Department of Clinical Laboratory Medicine, Children's Hospital of Nanjing Medical University, China.
| | - Daheng Yang
- Department of Clinical Laboratory Medicine, Children's Hospital of Nanjing Medical University, China.
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Hou L, Wu S, Yuan Z, Xue F, Li H. TEMR: Trans-ethnic mendelian randomization method using large-scale GWAS summary datasets. Am J Hum Genet 2025; 112:28-43. [PMID: 39689714 PMCID: PMC11739928 DOI: 10.1016/j.ajhg.2024.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2024] [Revised: 11/14/2024] [Accepted: 11/18/2024] [Indexed: 12/19/2024] Open
Abstract
Available large-scale genome-wide association study (GWAS) summary datasets predominantly stem from European populations, while sample sizes for other ethnicities, notably Central/South Asian, East Asian, African, Hispanic, etc., remain comparatively limited, resulting in low precision of causal effect estimations within these ethnicities when using Mendelian randomization (MR). In this paper, we propose a trans-ethnic MR method, TEMR, to improve the statistical power and estimation precision of MR in a target population that is underrepresented, using trans-ethnic large-scale GWAS summary datasets. TEMR incorporates trans-ethnic genetic correlation coefficients through a conditional likelihood-based inference framework, producing calibrated p values with substantially improved MR power. In the simulation study, compared with other existing MR methods, TEMR exhibited superior precision and statistical power in causal effect estimation within the target populations. Finally, we applied TEMR to infer causal relationships between concentrations of 16 blood biomarkers and the risk of developing five diseases (hypertension, ischemic stroke, type 2 diabetes, schizophrenia, and major depression disorder) in East Asian, African, and Hispanic/Latino populations, leveraging biobank-scale GWAS summary data obtained from individuals of European descent. We found that the causal biomarkers were mostly validated by previous MR methods, and we also discovered 17 causal relationships that were not identified using previously published MR methods.
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Affiliation(s)
- Lei Hou
- Department of Medical Data, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China
| | - Sijia Wu
- Department of Medical Data, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China
| | - Zhongshang Yuan
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China; Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China
| | - Fuzhong Xue
- Department of Medical Data, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China; Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China; Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China.
| | - Hongkai Li
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China; Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250000, P.R. China.
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Sun L, Zhang C, Song P, Zhong X, Xie B, Huang Y, Hu Y, Xu X, Lei X. Hypertension and 28-day mortality in sepsis patients: An observational and mendelian randomization study. Heart Lung 2024; 70:147-156. [PMID: 39671847 DOI: 10.1016/j.hrtlng.2024.11.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 11/12/2024] [Accepted: 11/26/2024] [Indexed: 12/15/2024]
Abstract
BACKGROUND Predicting and reducing the 28-day mortality in sepsis remains a challenge in this research field. OBJECTIVE This study aimed to explore the association between hypertension and 28-day mortality in sepsis. METHODS This study is a cross-sectional approach with Mendelian Randomization (MR). We used GWAS data for hypertension as the exposure and 28-day mortality in sepsis as the outcome and employed the main inverse variance weighted method along with other supplementary MR techniques to verify the causal association between hypertension and 28-day mortality in sepsis. We used sensitivity analyses to ensure the robustness of the research findings. Finally, we utilized clinical data from the Medical Information Mart for Intensive Care-IV database to assess the risk association between hypertension and 28-day mortality in sepsis using difference analysis and multivariate logistic regression analysis. RESULTS According to MR, hypertension increased the 28-day mortality in sepsis in both two datasets (FinnGen: odds ratio [OR] = 1.61, 95 % confidence interval [CI] = 1.15-2.26, p = 0.006; Medical Research Council-Integrative Epidemiological Unit: OR = 160, 95 % CI = 2.76-9250, p = 0.014). In our observational study, we included a total of 2012 sepsis patients, of which 60.5 % were male, and the average age was 55.4 years. By applying univariate and multivariate logistic regression models (univariate analysis p = 0.02, multivariate analysis p = 0.02), we observed a significantly increased risk of 28-day mortality due to hypertension in sepsis patients. CONCLUSION This study confirmed the causal relationship between hypertension and the 28-day mortality in sepsis.
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Affiliation(s)
- Lichang Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China; Research Center for Medicine and Social Development, Chongqing, China; Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China; Research Center for Public Health Security, Chongqing Medical University, Chongqing, China
| | - Cong Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Ping Song
- Big Data Center for Children's Medical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Xiaoni Zhong
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Biao Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Yingzhu Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China; Research Center for Medicine and Social Development, Chongqing, China; Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China; Research Center for Public Health Security, Chongqing Medical University, Chongqing, China
| | - Yuanjia Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China; Research Center for Medicine and Social Development, Chongqing, China; Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China; Research Center for Public Health Security, Chongqing Medical University, Chongqing, China
| | - Ximing Xu
- Big Data Center for Children's Medical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China.
| | - Xun Lei
- Department of Epidemiology and Health Statistics, School of Public Health, Chongqing Medical University, Chongqing, China; Research Center for Medicine and Social Development, Chongqing, China; Collaborative Innovation Center of Social Risks Governance in Health, Chongqing Medical University, Chongqing, China; Research Center for Public Health Security, Chongqing Medical University, Chongqing, China.
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Gruber I, Kollerits B, Forer L, Di Maio S, Schachtl-Riess JF, Kheirkhah A, Schönherr S, Schultheiss UT, Köttgen A, Eckardt KU, Coassin S, Lamina C, Kronenberg F. Lipoprotein(a) concentrations and cardiovascular disease in patients with chronic kidney disease: Results from the German Chronic Kidney Disease study. J Intern Med 2024; 296:510-526. [PMID: 39513193 DOI: 10.1111/joim.20027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2024]
Abstract
BACKGROUND Lipoprotein(a) (Lp(a)) is a causal, genetically determined risk factor for cardiovascular disease (CVD) in the general population. Patients with chronic kidney disease (CKD) have an increased CVD risk and elevated Lp(a) concentrations. Only a few studies on Lp(a) were performed in persons with mild-to-moderate CKD; none of them used genetic variants to explore potential causal associations. OBJECTIVES This study aims to investigate the association of measured and genetically predicted Lp(a) concentrations on prevalent and incident CVD events in the German Chronic Kidney Disease (GCKD) study. METHODS The study included 5043 participants of European ancestry with an estimated glomerular filtration rate (eGFR) between 30 and 60 mL/min/1.73 m2 or an eGFR >60 mL/min/1.73 m2 in the presence of overt albuminuria with a follow-up of 6.5 years. RESULTS With each 10 mg/dL higher Lp(a) concentration, odds for prevalent CVD (1290 events) increased 1.065-fold (95%CI: 1.042-1.088, p < 0.001). The risk was significantly higher in patients with Lp(a) ≥50 mg/dL but most pronounced in Lp(a) ≥70 mg/dL (odds ratio = 1.775 [1.409-2.231], p < 0.001) compared to Lp(a) <30 mg/dL. Each 10 mg/dL higher Lp(a) concentration and Lp(a) ≥70 mg/dL increased the risk for incident 3-point major adverse cardiovascular events (MACEs) (474 events): hazard ratio [HR] = 1.037 [1.009-1.067], p = 0.009 and HR = 1.335 [1.001-1.781], p = 0.050), respectively. Similar results were obtained for 4-point MACE (653 events). Analyses based on apo(a) isoforms and genetically predicted Lp(a) concentrations led to even stronger associations. CONCLUSIONS In patients with mild-to-severe CKD, elevated Lp(a) concentrations and genetic determinants of Lp(a) concentrations are significantly associated with CVD at baseline and during follow-up, independent of traditional risk factors.
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Affiliation(s)
- Ida Gruber
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Barbara Kollerits
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Silvia Di Maio
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Azin Kheirkhah
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Ulla T Schultheiss
- Faculty of Medicine and Medical Center, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany
- Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Synlab MVZ Humangenetik Freiburg GmbH, Freiburg, Germany
| | - Anna Köttgen
- Faculty of Medicine and Medical Center, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan Coassin
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
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Wen C, Chen L, Jia D, Liu Z, Lin Y, Liu G, Zhang S, Gao B. Recent advances in the application of Mendelian randomization to chronic kidney disease. Ren Fail 2024; 46:2319712. [PMID: 38522953 PMCID: PMC10913720 DOI: 10.1080/0886022x.2024.2319712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 02/12/2024] [Indexed: 03/26/2024] Open
Abstract
OBJECTIVE Chronic kidney disease (CKD) is a condition influenced by both genetic and environmental factors and has been a focus of extensive research. Utilizing Mendelian randomization, researchers have begun to untangle the complex causal relationships underlying CKD. This review delves into the advances and challenges in the application of MR in the field of nephrology, shifting from a mere summary of its principles and limitations to a more nuanced exploration of its contributions to our understanding of CKD. METHODS Key findings from recent studies have been pivotal in reshaping our comprehension of CKD. Notably, evidence indicates that elevated testosterone levels may impair renal function, while higher sex hormone-binding globulin (SHBG) levels appear to be protective, predominantly in men. Surprisingly, variations in plasma glucose and glycated hemoglobin levels seem unaffected by genetically induced changes in the estimated glomerular filtration rate (eGFR), suggesting an independent pathway for renal function impairment. RESULTS Furthermore, lifestyle factors such as physical activity and socioeconomic status emerge as significant influencers of CKD risk and kidney health. The relationship between sleep duration and CKD is nuanced; short sleep duration is linked to increased risk, while long sleep duration does not exhibit a clear causal effect. Additionally, lifestyle factors, including diet, exercise, and mental wellness activities, play a crucial role in kidney health. New insights also reveal a substantial causal connection between both central and general obesity and CKD onset, while no significant links were found between genetically modified LDL cholesterol or triglyceride levels and kidney function. CONCLUSION This review not only presents the recent achievements of MR in CKD research but also illuminates the path forwards, underscoring critical unanswered questions and proposing future research directions in this dynamic field.
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Affiliation(s)
- Chaofan Wen
- Department of Urology and Surgery, the First Hospital of Jilin University, Changchun, Jilin Province, China
| | - Lanlan Chen
- Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, the First Hospital of Jilin University, Changchun, Jilin Province, China
| | - Dan Jia
- Department of Urology and Surgery, the First Hospital of Jilin University, Changchun, Jilin Province, China
| | - Ziqi Liu
- Weifang Medical University, Weifang, Shandong Province, China
| | - Yidan Lin
- Herberger Institute for Design and Arts, Arizona State University, Tempe, AZ, USA
| | - Guan Liu
- Department of Pharmacology, Hebei Medical University, Shijiazhuang City, Hebei Province, China
| | - Shuo Zhang
- Department of Pharmacology, Hebei Medical University, Shijiazhuang City, Hebei Province, China
| | - Baoshan Gao
- Department of Urology and Surgery, the First Hospital of Jilin University, Changchun, Jilin Province, China
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Anderson JJ, Deo SV, Welsh P, MacKay DF, Ho FK, Ferguson LD, Celis-Morales C, Gill JMR, Pell JP, Sattar N. In which common chronic conditions can (or cannot) obesity and lifestyle factors explain higher concentrations of C-reactive protein? Diabetes Obes Metab 2024; 26:5786-5794. [PMID: 39300958 DOI: 10.1111/dom.15949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 08/26/2024] [Accepted: 08/30/2024] [Indexed: 09/22/2024]
Abstract
AIM Elevated C-reactive protein (CRP), a marker of inflammation, is common in many chronic conditions. We aimed to examine to what extent elevated CRP in chronic conditions could be explained by concurrent adiposity. MATERIALS AND METHODS This cross-sectional study analysed UK Biobank data on 10 chronic conditions reported at baseline. Linear regression models explored the extent to which CRP concentrations were elevated in each condition, unadjusted; adjusted for sociodemographic confounders and lifestyle and body mass index (BMI) in a series of models; or adjusted for BMI and waist circumference together or for adiposity alone. RESULTS After exclusion of participants with a potential acute infection at baseline, we tested the association in 292 772 UK Biobank participants. Linear regression showed that elevated CRP concentration was associated with all included conditions. After adjustment for sociodemographic confounders, lifestyle and BMI, chronic kidney disease, heart failure, liver disease, psoriasis, rheumatoid arthritis and chronic obstructive pulmonary disease were still associated with elevated CRP. In contrast, the association between prevalent diabetes, prior myocardial infarction (MI), hypertension and sleep apnoea and CRP could be mostly explained by adiposity alone. For example, the 42% higher CRP concentrations in diabetes compared to those without diabetes in the unadjusted model (lnCRP β: 0.35; 95% confidence interval [CI]: 0.32-0.37, p < 0.001) were completely attenuated after adjustment for BMI (lnCRP β: -0.07; 95% CI: -0.09-0.05, p < 0.001). CONCLUSIONS/INTERPRETATION In diabetes, MI, hypertension and sleep apnoea and elevated CRP appears to be accounted for by the greater adiposity typically evident in these conditions. However, for the other conditions, systemic inflammation cannot be explained by excess adiposity alone.
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Affiliation(s)
- Jana J Anderson
- Public Health, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Salil V Deo
- Public Health, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Surgical Services, Louis Stokes Cleveland VAMC, North-East Ohio VA Healthcare, Cleveland, Ohio, USA
| | - Paul Welsh
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | - Danny F MacKay
- Public Health, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Frederick K Ho
- Public Health, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Lyn D Ferguson
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | - Carlos Celis-Morales
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
- Human Performance Laboratory, Education, Physical Activity and Health Research Unit, University Católica del Maule, Talca, Chile
- Centro de Investigación en Medicina de Altura (CEIMA), Universidad Arturo Prat, Iquique, Chile
| | - Jason M R Gill
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | - Jill P Pell
- Public Health, School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
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Zhou LT, Ali AE, Jayachandran M, Haskic Z, Harris PC, Rule AD, Koo K, McDonnell SK, Larson NB, Lieske JC. Association between Kidney Stones and CKD: A Bidirectional Mendelian Randomization Study. J Am Soc Nephrol 2024; 35:1746-1757. [PMID: 39102294 PMCID: PMC11617471 DOI: 10.1681/asn.0000000000000453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 07/26/2024] [Indexed: 08/07/2024] Open
Abstract
Key Points Common kidney stones are unlikely to be an independent and direct cause of CKD in the general population. CKD may protect against kidney stones because of changes in key urinary factors critical for stone formation. Background Kidney stones and CKD are common disorders with a substantial interaction. Although observational studies have suggested a potential for enhanced CKD risk after prior kidney stones, the exact relationship remains ambiguous. Methods Shared comorbidities between two diseases were identified using unbiased screening. Genome-wide association study summary statistics were obtained from the UK Biobank (UKBB), FinnGen, and CKDGen, followed by genetic association analyses across various traits. Bidirectional Mendelian randomization (MR) analyses were performed to define causal links, complemented by multivariable MR that included the shared comorbidities including hypertension, diabetes, and obesity. Observational analyses were undertaken using cohorts from the Mayo Clinic and a UKBB subset. Results Despite identifying a total of 123 conditions as shared comorbidities, there was no significant genetic correlation between kidney stones and CKD. Unadjusted MR analysis revealed no significant association between kidney stones and CKD risk (UKBB [exposure]/FinnGen [outcome]: odds ratio [OR]=0.97, 95% confidence interval [CI], 0.88 to 1.06; FinnGen/UKBB: OR=1.17, 95% CI, 0.98 to 1.39). Kidney stones did significantly associate with a higher urinary albumin-creatinine ratio (β =0.014, 95% CI, 0.002 to –0.025), but this association disappeared in the multivariable MR model (β =0.009, 95% CI, −0.003 to 0.020). Furthermore, in a cross-sectional analysis limited to the UKBB cohort, a robust regression model did not detect an independent association between kidney stones and urinary albumin-creatinine ratio (β =0.16, 95% CI, −0.04 to 0.35) or eGFR (β =0.10, 95% CI, −0.07 to 0.28). Conversely, CKD associated with a diminished risk of kidney stones in multivariable MR models (UKBB/FinnGen: OR=0.77, 95% CI, 0.69 to 0.87; FinnGen/UKBB: OR=0.73, 95% CI, 0.66 to 0.81). Furthermore, in the Mayo Clinic cohort with available urinary biochemistries, lower eGFR was associated with lower urinary calcium excretion and urinary calcium oxalate/phosphate supersaturation. Conclusions In this study, kidney stones were not independently associated with CKD. Conversely, CKD was associated with a lower risk of calcium kidney stones likely via changes in key urinary traits, including lower calcium excretion.
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Affiliation(s)
- Le-Ting Zhou
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
- Department of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China
| | - Ahmed E. Ali
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Muthuvel Jayachandran
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Zejfa Haskic
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Peter C. Harris
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Andrew D. Rule
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Kevin Koo
- Department of Urology, Mayo Clinic, Rochester, Minnesota
| | - Shannon K. McDonnell
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Nicholas B. Larson
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - John C. Lieske
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
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Zhang Z, Zhang F, Zhang X, Lu L, Zhang L. Association of Smoking with Chronic Kidney Disease Stages 3 to 5: A Mendelian Randomization Study. HEALTH DATA SCIENCE 2024; 4:0199. [PMID: 39498379 PMCID: PMC11532587 DOI: 10.34133/hds.0199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 09/07/2024] [Accepted: 09/13/2024] [Indexed: 11/07/2024]
Abstract
Background: Previous studies suggested that smoking behavior (e.g., smoking status) was associated with an elevated risk of chronic kidney disease (CKD), yet whether this association is causal remains uncertain. Methods: We used data for half million participants aged 40 to 69 years from the UK Biobank cohort. In the traditional observational study, we used Cox proportional hazards models to calculate the associations between 2 smoking indices-smoking status and lifetime smoking index and incident CKD stages 3 to 5. Mendelian randomization (MR) approaches were used to estimate a potential causal effect. In one-sample MR, genetic variants associated with lifetime smoking index were used as instrument variables to examine the causal associations with CKD stages 3 to 5, among 344,255 UK Biobank participants with white British ancestry. We further validated our findings by a two-sample MR analysis using information from the Chronic Kidney Disease Genetics Consortium genome-wide association study. Results: In the traditional observational study, both smoking status [hazard ratio (HR): 1.26, 95% confidence interval (CI): 1.22 to 1.30] and lifetime smoking index (HR: 1.22, 95% CI: 1.20 to 1.24) were positively associated with a higher risk of incident CKD. However, both our one-sample and two-sample MR analyses showed no causal association between lifetime smoking index and CKD (all P > 0.05). The genetic instruments were validated by several statistical tests, and all sensitivity analyses showed similar results with the main model. Conclusion: Evidence from our analyses does not suggest a causal effect of smoking behavior on CKD risk. The positive association presented in the traditional observational study is possibly a result of confounding.
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Affiliation(s)
- Zhilong Zhang
- Institute of Medical Technology,
Peking University Health Science Center, Beijing, China
- National Institute of Health Data Science at Peking University,
Peking University Health Science Center, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling,
Peking University, Beijing, China
| | - Feifei Zhang
- Institute of Medical Technology,
Peking University Health Science Center, Beijing, China
- National Institute of Health Data Science at Peking University,
Peking University Health Science Center, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling,
Peking University, Beijing, China
| | - Xiaomeng Zhang
- Centre for Global Health, Usher Institute,
University of Edinburgh, Edinburgh, UK
| | - Lanlan Lu
- Xiaying Primary Health Care Center, Ningbo Yinzhou No.2 Hospital, Ningbo, Zhejiang Province, China
| | - Luxia Zhang
- Institute of Medical Technology,
Peking University Health Science Center, Beijing, China
- National Institute of Health Data Science at Peking University,
Peking University Health Science Center, Beijing, China
- State Key Laboratory of Vascular Homeostasis and Remodeling,
Peking University, Beijing, China
- Renal Division, Department of Medicine, Peking University First Hospital,
Peking University Institute of Nephrology, Beijing, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases,
Chinese Academy of Medical Sciences, Beijing, China
- Advanced Institute of Information Technology,
Peking University, Hangzhou, China
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10
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Wu R, Cheng J, Qi Y, Jiang X. Genetic link between gut microbiota, immune cells, and rheumatoid arthritis: Mechanism of action of CD28 proteins. Int J Biol Macromol 2024; 282:137212. [PMID: 39491704 DOI: 10.1016/j.ijbiomac.2024.137212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Revised: 10/26/2024] [Accepted: 11/01/2024] [Indexed: 11/05/2024]
Abstract
The gut microbiota serves a crucial function in modulating the immune responses of the host, as well as in managing inflammation within the body. In this particular study, the researchers sought to delve deeper into the specific mechanisms through which CD28 interacts with the gut microbiota and influences the functionality of immune cells. The study collected intestinal microbial samples from RA patients and healthy controls, analyzed microbial composition by high-throughput sequencing, and detected CD28 expression in T cells in combination with cellular immunology methods. At the same time, the effects of CD28 deletion on intestinal microbiota changes and inflammatory responses were evaluated using animal models. The findings from this study revealed a notable distinction in the gut microbiota profiles of individuals diagnosed with rheumatoid arthritis (RA) when compared to those of healthy control subjects. Specifically, the abundance of certain microbial species was observed to have a negative correlation with the expression levels of CD28, highlighting a complex interaction between the gut microbiome and the immune regulatory mechanisms involved in RA. Furthermore, experiments conducted on mice lacking CD28 demonstrated considerable alterations in their gut microbiota composition. These Cd28-deficient mice exhibited elevated levels of inflammatory markers, indicating an interplay between CD28 and the regulation of both the microbiota and the immune response.
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Affiliation(s)
- Rui Wu
- Department of Rheumatology and Immunology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610071, China
| | - Jia Cheng
- Department of Rheumatology and Immunology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610071, China
| | - Yan Qi
- Department of Rheumatology and Immunology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610071, China.
| | - Xiaolan Jiang
- The Medical Center of General Practice, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China.
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11
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Ma Y, Su J, Ma C. Causal relationship between amino acids and ovarian cancer in the European population: A bidirectional Mendelian randomization study and meta-analysis. Medicine (Baltimore) 2024; 103:e40189. [PMID: 39470531 PMCID: PMC11521036 DOI: 10.1097/md.0000000000040189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Revised: 10/02/2024] [Accepted: 10/03/2024] [Indexed: 10/30/2024] Open
Abstract
In recent years, an increasing number of observational studies have reported the impact of amino acids on ovarian cancer. However, Mendelian randomization studies have not yet been conducted to explore the causal relationship between them in the context of ovarian cancer. This study conducted Mendelian randomization (MR) analysis of 20 amino acids in relation to ovarian cancer data from 2 different sources within the European population, using a two-sample MR approach. The primary results from the inverse variance weighting analysis were then subjected to a meta-analysis, followed by multiple testing correction for the meta-analysis thresholds. Finally, reverse causality testing was performed on the positively associated amino acids and ovarian cancer. MR analyses were conducted for 20 amino acids with ovarian cancer data from both the Finngen R10 and Open genome-wide association study databases. The inverse variance weighted results from these 2 analyses were then combined through meta-analysis, with multiple corrections applied to the significance thresholds of the meta-analysis results. The findings showed that only cysteine had a significant association with ovarian cancer, with an (odds ratio) odds ratio value of 0.507 (95% confidence interval: 0.335-0.767, P = .025). The P-value of the combined MR and meta-analysis, after multiple testing correction, was 0.025, indicating statistical significance (P < .05). Additionally, cysteine did not show a reverse causal relationship with ovarian cancer in either data source. Cysteine is a protective factor for ovarian cancer, potentially reducing the risk of ovarian cancer and slowing the progression of the disease.
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Affiliation(s)
- Yingji Ma
- Jiaozhou Hospital of Tongji University Dongfang Hospital Qingdao, Shangdong, China
| | - Jiaqi Su
- Jiaozhou Hospital of Tongji University Dongfang Hospital Qingdao, Shangdong, China
| | - Changbo Ma
- Jiaozhou Hospital of Tongji University Dongfang Hospital Qingdao, Shangdong, China
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12
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Long Y, Dai W, Cai K, Xiao Y, Luo A, Lai Z, Wang J, Xu L, Nie H. Systemic Immune Factors and Risk of Allergic Contact Dermatitis: A Bidirectional Mendelian Randomization Study. Int J Mol Sci 2024; 25:10436. [PMID: 39408763 PMCID: PMC11476522 DOI: 10.3390/ijms251910436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2024] [Revised: 09/16/2024] [Accepted: 09/21/2024] [Indexed: 10/20/2024] Open
Abstract
Skin inflammation and immune regulation have been suggested to be associated with allergic contact dermatitis (ACD) progression, but whether the system's immune regulation is a cause or a potential mechanism is still unknown. This study aims to assess the upstream and downstream of systemic immune factors on ACD within a bidirectional Mendelian-randomization design. A bidirectional two-sample MR analysis was employed to implement the results from genome-wide association studies for 52 system immune factors and ACD. Genetic associations with systemic immune factors and ACD were obtained from the IEU Open GWAS project database. The inverse-variance weighted (IVW) method was adopted as the primary MR analysis, MR-Egger, weighted median, MR-pleiotropy residual sum, and outlier (MR-PRESSO) was also used as the sensitivity analyses. Only Tumor necrosis factor ligand superfamily member 11 (TNFS11) from among 52 systemic immune factors was associated with a protective effect of ACD. However, ACD was associated with a decrease in Interleukin-9 (IL9) and an increase in C-X-C motif chemokine 1 (GROα), Tumor necrosis factor ligand superfamily member 10 (TRAIL), C4, and complement factor B of the assessed systemic immune factors. This study identified TNFS11 as the upstream regulator and IL9, GROα, TRAIL, C4, and complement factor B as the downstream regulator of ACD, providing opportunities for new therapeutic exploitation of ACD. Nonetheless, these associations of systemic immune factors need to be verified in vivo.
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Affiliation(s)
| | | | | | | | | | | | | | - Lipeng Xu
- State Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Chinese Ministry of Education (MOE), College of Pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou 510632, China; (Y.L.); (W.D.); (K.C.); (Y.X.); (A.L.); (Z.L.); (J.W.)
| | - Hong Nie
- State Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Chinese Ministry of Education (MOE), College of Pharmacy, Jinan University, 601 Huangpu Avenue West, Guangzhou 510632, China; (Y.L.); (W.D.); (K.C.); (Y.X.); (A.L.); (Z.L.); (J.W.)
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13
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Han Y, Gao W, Wang B, Gao Z, Diao M, Zuo C, Zhang M, Diao Y, Wang C, Liu H, Gu Y. The potential causal relationship between BMI, T1D, urolithiasis, and hydronephrosis in European ancestry: A Mendelian randomization analysis. Medicine (Baltimore) 2024; 103:e39914. [PMID: 39331875 PMCID: PMC11441904 DOI: 10.1097/md.0000000000039914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/29/2024] Open
Abstract
Body mass index (BMI), type 1 diabetes (T1D), urolithiasis, and hydronephrosis are interrelated. Our aim was to analyze their causal relationships at the genetic level. Mendelian randomization is an instrumental variable analysis method that follows Mendel genetic law of random allocation of parental alleles to offspring. In observational studies, genetic variants are used as instrumental variables to infer causal relationships between exposure factors and study outcomes. All the genome-wide association study data in our study were publicly available and from published genome-wide association studies, UK Biobank, and FinnGen. Random-effects inverse variance weighted was the primary analysis method, with R Egger, weighted median, and weighted mode as supplementary methods. We examined heterogeneity, horizontal pleiotropy, and the influence of individual single nucleotide polymorphisms on the analysis. We further explored the causal relationships between BMI, T1D, urolithiasis, and hydronephrosis, as well as the robustness of the analysis results. Inverse variance weighted results showed genetic causal relationships between BMI (P = .034, odds ratio [OR] 95% confidence interval [CI] = 1.273 [1.019-1.589]), T1D (P = .028, OR 95% CI = 0.921 [0.855-0.991]), urolithiasis (P < .001, OR 95% CI = 1.361 [1.175-1.576]), and hydronephrosis. Sensitivity analyses confirmed the accuracy and robustness of these findings. Our results support significant causal roles of BMI, T1D, and urolithiasis in hydronephrosis, potentially offering new intervention strategies for preventing its development.
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Affiliation(s)
- Yangjun Han
- Department of Urology, Peking University First Hospital-Miyun Hospital, Beijing, China
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14
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Zhao K, JI S, Jiang H, Qian Y, Zhang W. Exploring the gut microbiota's effect on temporomandibular joint disorder: a two-sample Mendelian randomization analysis. Front Cell Infect Microbiol 2024; 14:1361373. [PMID: 39188419 PMCID: PMC11345233 DOI: 10.3389/fcimb.2024.1361373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 07/19/2024] [Indexed: 08/28/2024] Open
Abstract
Background Temporomandibular joint disorders (TMD) are highly prevalent among people. Numerous investigations have revealed the impact of gut microbiota in many diseases. However, the causal relationship between Temporomandibular joint disorders and gut microbiota remains unclear. Methods Genome-Wide Association Studies (GWAS) refer to the identification of sequence variations, namely single nucleotide polymorphisms (SNPs), existing across the entire human genome. GWAS data were collected on gut microbiota and TMD. Then, instrumental variables were screened through F-values and removal of linkage disequilibrium. These SNPs underwent mendelian analysis using five mathematical models. Sensitivity analysis was conducted to further verify the stability of the results. Pathogenic factors of TMD mediate the causal relationship between gut microbiota and TMD were explored through a two-step Mendelian randomization analysis. Finally, reverse mendelian analysis was conducted to account for potential reverse effects. Results The analysis of the data in this article suggests that some gut microbiota, including Coprobacter, Ruminococcus torques group, Catenibacterium, Lachnospiraceae, Turicibacter, Victivallis, MollicutesRF9, Methanobacteriales, Methanobacteriaceae, FamilyXI, Methanobacteria were identified as risk factors, while Peptococcaceae provides protection for TMD. Conclusion The research reveals the relation of gut microbiota in TMD. These findings provide insights into the underlying mechanisms and suggest potential therapeutic strategy.
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Affiliation(s)
- Kai Zhao
- Department of Stomatology, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Medical Center of Soochow University, Suzhou, China
| | - Shuaiqi JI
- Fujian Key Laboratory of Oral Diseases and Stomatological Key lab of Fujian College and University, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China
| | - Han Jiang
- Department of Stomatology, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Medical Center of Soochow University, Suzhou, China
| | - Yunzhu Qian
- Department of Stomatology, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Medical Center of Soochow University, Suzhou, China
| | - Weibing Zhang
- Department of Stomatology, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Medical Center of Soochow University, Suzhou, China
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15
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Liang Q, Zhang G, Jiang L. Association between lipoprotein (a) and risk of atherosclerotic cardiovascular disease events among maintenance hemodialysis patients in Beijing, China: a single-center, retrospective study. BMC Nephrol 2024; 25:250. [PMID: 39090533 PMCID: PMC11295529 DOI: 10.1186/s12882-024-03690-z] [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: 01/22/2024] [Accepted: 07/30/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Serum lipoprotein(a) [Lp(a)] is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD) in the general population, its association with ASCVD incidence in Chinese maintenance hemodialysis (MHD) patients remains unclear. We aimed to evaluate the relationship between Lp(a) levels and ASCVD incidence among MHD patients in Beijing, China. METHODS This retrospective, observational cohort study included MHD patients at Beijing Tongren Hospital from January 1, 2013 to December 1, 2020, and followed until December 1,2023. The primary outcome was ASCVD occurrence. Kaplan-Meier survival analysis was used to evaluate ASCVD-free survival in MHD patients, with stratification based on Lp(a) levels. Cox regression analyses were conducted to assess the association between Lp(a) levels and the occurrence of ASCVD. RESULTS A total of 265 patients were enrolled in the study. The median follow-up period were 71 months.78 (29.4%) participants experienced ASCVD events, and 118 (47%) patients died, with 58 (49.1%) deaths attributed to ASCVD. Spearman rank correlation analyses revealed positive correlations between serum Lp(a) levels and LDL-c levels, and negative correlations with hemoglobin, triglyceride, serum iron, serum creatinine, and albumin levels. Multivariate Cox regression analysis showed that Lp(a) levels ≥ 30 mg/L, increased age, decreased serum albumin levels, and a history of diabetes mellitus were significantly associated with ASCVD incidence. CONCLUSIONS This study demonstrated an independent and positive association between serum Lp(a) levels and the risk of ASCVD in MHD patients, suggesting that serum Lp(a) could potentially serve as a clinical biomarker for estimating ASCVD risk in this population.
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Affiliation(s)
- Qiaojing Liang
- Department of Nephrology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Guojuan Zhang
- Department of Nephrology, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
| | - Liping Jiang
- Department of Nephrology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
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16
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Zhang N, Ji C, Liu L, Ye E, Yuan C. The Causal Relationship between PCSK9 Inhibitors and Osteoporosis Based on Drug-Targeted Mendelian Combined Mediation Analysis. Calcif Tissue Int 2024; 115:53-62. [PMID: 38789568 PMCID: PMC11153280 DOI: 10.1007/s00223-024-01228-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 05/08/2024] [Indexed: 05/26/2024]
Abstract
PCSK9 inhibitors have been shown to lower serum low density lipoprotein cholesterol (LDL-C) levels and are considered integral in the treatment of cardiovascular diseases. However, the potential association between PCSK9 inhibitors and osteoporosis is unclear now. In this study, drug-targeted mendelian randomization (MR) was utilized in conjunction with mediation analysis including bone mineral density (BMD), total 25-hydroxyvitamin D (T25(OH)D) levels and calcium supplementation to investigate the causal relationship between PCSK9 inhibitors and osteoporosis. The LDL-C level was chosen as the exposure variable in a sample size of 173,082 individuals. We conducted a MR analysis on the relationship between PCSK9 inhibitors and osteoporosis, elucidating the mediators involved. Utilizing the inverse variance weighted (IVW) method, we found the risk of osteoporosis was reduced by 0.6% in those who used PCSK9 inhibitors compared with non-users (OR: 0.994, 95%CI: 0.991-0.998, P < 0.001). In people aged 30-45 years, the risk of low BMD was 1.176 times higher among PCSK9 inhibitor users compared to non-users (OR: 1.176, 95%CI: 1.017-1.336, P = 0.045). Conversely, people aged 45-60 years who used PCSK9 inhibitors had a 14.9% lower risk of low BMD compared to non-users (OR: 0.851, 95%CI: 0.732-0.968, P = 0.007). Mediation analysis revealed that 43.33% of the impact of PCSK9 inhibitors on osteoporosis was mediated through BMD levels, with the remaining 56.67% being a direct effect. Effects of PCSK9 inhibitors on BMD levels varied in different ages. In addition, the risk of high serum T25(OH)D levels were 1.091 times among PCSK9 inhibitor users compared to non-users (OR: 1.091, 95%CI: 1.065-1.112, P < 0.001), providing valuable insights for clinicians.
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Affiliation(s)
- Naidan Zhang
- Department of Laboratory Medicine, Peoples Hospital of Deyang City, No 173, the First Section of North Taishan Road, Deyang, 618000, China.
| | - Chaixia Ji
- Department of Laboratory Medicine, Peoples Hospital of Deyang City, No 173, the First Section of North Taishan Road, Deyang, 618000, China
| | - Li Liu
- Department of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China
| | - Ermei Ye
- Department of Laboratory Medicine, Peoples Hospital of Deyang City, No 173, the First Section of North Taishan Road, Deyang, 618000, China
| | - Chengliang Yuan
- Department of Laboratory Medicine, Peoples Hospital of Deyang City, No 173, the First Section of North Taishan Road, Deyang, 618000, China
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Shuai H, Wang Z, Xiao Y, Ge Y, Mao H, Gao J. Genetically supported causality between gut microbiota, immune cells, and ischemic stroke: a two-sample Mendelian randomization study. Front Microbiol 2024; 15:1402718. [PMID: 38894965 PMCID: PMC11185428 DOI: 10.3389/fmicb.2024.1402718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/06/2024] [Indexed: 06/21/2024] Open
Abstract
Background Previous studies have highlighted a robust correlation between gut microbiota/immune cells and ischemic stroke (IS). However, the precise nature of their causal relationship remains uncertain. To address this gap, our study aims to meticulously investigate the causal association between gut microbiota/immune cells and the likelihood of developing IS, employing a two-sample Mendelian randomization (MR) analysis. Methods Our comprehensive analysis utilized summary statistics from genome-wide association studies (GWAS) on gut microbiota, immune cells, and IS. The primary MR method employed was the inverse variance-weighted (IVW) approach. To address potential pleiotropy and identify outlier genetic variants, we incorporated the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) technique, along with MR-Egger regression. Heterogeneity was assessed using Cochran's Q-test. Additionally, leave-one-out analysis was conducted to pinpoint any individual genetic variant influencing the observed causal associations. Finally, a reverse MR analysis was performed to explore the potential of reverse causation. Results Our investigation revealed four gut microbial taxa and 16 immune cells with a significant causal relationship with IS (p < 0.05). Notably, two bacterial features and five immunophenotypes were strongly associated with a lower IS risk: genus.Barnesiella.id.944 (OR: 0.907, 95% CI: 0.836-0.983, p = 0.018), genus.LachnospiraceaeNK4A136group.id.11319 (OR: 0.918, 95% CI: 0.853-0.983, p = 0.988), Activated & resting Treg % CD4++ (OR: 0.977, 95% CI: 0.956-0.998, p = 0.028). Additionally, significant associations between IS risk and two bacterial features along with eleven immunophenotypes were observed: genus.Paraprevotella.id.962 (OR: 1.106, 95% CI: 1.043-1.172, p < 0.001), genus.Streptococcus.id.1853 (OR: 1.119, 95% CI: 1.034-1.210, p = 0.005), CD127 on granulocyte (OR: 1.039, 95% CI: 1.009-1.070, p = 0.011). Our analyses did not reveal heterogeneity based on the Cochrane's Q-test (p > 0.05) nor indicate instances of horizontal pleiotropy according to MR-Egger and MR-PRESSO analyses (p > 0.05). Furthermore, the robustness of our MR results was confirmed through leave-one-out analysis. Conclusion Our study provides further evidence supporting the potential association between gut microbiota and immune cells in relation to IS, shedding light on the underlying mechanisms that may contribute to this condition. These findings lay a solid foundation for future investigations into targeted prevention strategies.
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Affiliation(s)
- Han Shuai
- Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China
- Peking University People’s Hospital, Qingdao Women and Children’s Hospital, Qingdao University, Qingdao, China
| | - Zi Wang
- Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China
| | - Yinggang Xiao
- Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China
| | - Yali Ge
- Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China
| | - Hua Mao
- Peking University People’s Hospital, Qingdao Women and Children’s Hospital, Qingdao University, Qingdao, China
| | - Ju Gao
- Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China
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18
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Ciofani JL, Han D, Allahwala UK, Bhindi R. Aortic Stenosis and Renal Function: A Bidirectional Mendelian Randomization Analysis. J Am Heart Assoc 2024; 13:e034102. [PMID: 38639330 PMCID: PMC11179900 DOI: 10.1161/jaha.123.034102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 02/16/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Large observational studies have demonstrated a clear inverse association between renal function and risk of aortic stenosis (AS). Whether this represents a causal, reverse causal or correlative relationship remains unclear. We investigated this using a bidirectional 2-sample Mendelian randomization approach. METHODS AND RESULTS We collected summary statistics for the primary analysis of chronic kidney disease (CKD) and AS from genome-wide association study meta-analyses including 480 698 and 653 867 participants, respectively. We collected further genome-wide association study summary statistics from up to 1 004 040 participants for sensitivity analyses involving estimated glomerular filtration rate (eGFR) derived from creatinine, eGFR derived from cystatin C, and serum urea nitrogen. Inverse-variance weighted was the primary analysis method, with weighted-median, weighted-mode, Mendelian randomization-Egger, and Mendelian randomization-Pleiotropy Residual Sum and Outlier as sensitivity analyses. We did not find evidence of a causal relationship between genetically predicted CKD liability as the exposure and AS as the outcome (odds ratio [OR], 0.94 per unit increase in log odds of genetic liability to CKD [95% CI, 0.85-1.04], P=0.26) nor robust evidence of AS liability as the exposure and CKD as the outcome (OR, 1.04 per unit increase in log odds of genetic liability to AS [95% CI, 0.97-1.12], P=0.30). The sensitivity analyses were neutral overall, as were the analyses using eGFR derived from creatinine, eGFR derived from cystatin C, and serum urea nitrogen. All positive controls demonstrated strong significant associations. CONCLUSIONS The present study did not find evidence of a substantial effect of genetically predicted renal impairment on risk of AS. This has important implications for research efforts that attempt to identify prevention and treatment targets for both CKD and AS.
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Affiliation(s)
- Jonathan L. Ciofani
- Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
- Department of CardiologyRoyal North Shore HospitalSydneyNSWAustralia
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK
| | - Daniel Han
- Medical Research Council Laboratory of Molecular BiologyCambridgeUK
- Department of Physiology, Development and NeuroscienceUniversity of CambridgeCambridgeUK
- School of Mathematics and StatisticsUniversity of New South WalesSydneyNSWAustralia
| | - Usaid K. Allahwala
- Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
- Department of CardiologyRoyal North Shore HospitalSydneyNSWAustralia
| | - Ravinay Bhindi
- Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
- Department of CardiologyRoyal North Shore HospitalSydneyNSWAustralia
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Ren F, Yang C, Feng K, Shang Q, Liu J, Kang X, Wang X, Wang X. An exploration of causal relationships between nine neurological diseases and the risk of breast cancer: a Mendelian randomization study. Aging (Albany NY) 2024; 16:7101-7118. [PMID: 38663930 PMCID: PMC11087125 DOI: 10.18632/aging.205745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 03/18/2024] [Indexed: 05/08/2024]
Abstract
BACKGROUND Some preceding researches have observed that certain neurological disorders, such as Alzheimer's disease and multiple sclerosis, may affect breast cancer risk. However, whether there are causal relationships between these neurological conditions and breast cancer is inconclusive. This study was designed to explore whether neurological disorders affected the risks of breast cancer overall and of the two subtypes (ER+ and ER-). METHODS In the course of this study, genome-wide association study (GWAS) data for nine neurological diseases (Alzheimer's disease, multiple sclerosis, Parkinson's disease, myasthenia gravis, generalized epilepsy, intracerebral haemorrhage, cerebral atherosclerosis, brain glioblastoma, and benign meningeal tumour) were collected from the Complex Trait Genetics lab and the MRC Integrative Epidemiology Unit, and single-nucleotide polymorphisms (SNPs) extensively associated with these neurological ailments had been recognized as instrumental variables (IVs). GWAS data on breast cancer were collected from the Breast Cancer Association Consortium (BCAC). Two-sample Mendelian randomization (MR) analyses as well as multivariable MR analyses were performed to determine whether these SNPs contributed to breast cancer risk. Additionally, the accuracy of the results was evaluated using the false discovery rate (FDR) multiple correction method. Both heterogeneity and pleiotropy were evaluated by analyzing sensitivities. RESULTS According to the results of two-sample MR analyses, Alzheimer's disease significantly reduced the risks of overall (OR 0.925, 95% CI [0.871-0.982], P = 0.011) and ER+ (OR 0.912, 95% CI [0.853-0.975], P = 0.007) breast cancer, but there was a negative result in ER- breast cancer. However, after multiple FDR corrections, the effect of Alzheimer's disease on overall breast cancer was not statistically significant. In contrast, multiple sclerosis significantly increased ER+ breast cancer risk (OR 1.007, 95% CI [1.003-1.011], P = 0.001). In addition, the multivariable MR analyses showed that Alzheimer's disease significantly reduced the risk of ER+ breast cancer (IVW: OR 0.929, 95% CI [0.864-0.999], P=0.047; MR-Egger: OR 0.916, 95% CI [0.846-0.992], P=0.031); however, multiple sclerosis significantly increased the risk of ER+ breast cancer (IVW: OR 1.008, 95% CI [1.003-1.012], P=4.35×10-4; MR-Egger: OR 1.008, 95% CI [1.003-1.012], P=5.96×10-4). There were no significant associations between the remainder of the neurological diseases and breast cancer. CONCLUSIONS This study found the trends towards a decreased risk of ER+ breast cancer in patients with Alzheimer's disease and an increased risk in patients with multiple sclerosis. However, due to the limitations of Mendelian randomization, we cannot determine whether there are definite causal relationships between neurological diseases and breast cancer risk. For conclusive evidences, more prospective randomized controlled trials will be needed in the future.
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Affiliation(s)
- Fei Ren
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Chenxuan Yang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Kexin Feng
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Qingyao Shang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Jiaxiang Liu
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiyu Kang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xin Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiang Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Lonardo A. Association of NAFLD/NASH, and MAFLD/MASLD with chronic kidney disease: an updated narrative review. METABOLISM AND TARGET ORGAN DAMAGE 2024; 4. [DOI: 10.20517/mtod.2024.07] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
Abstract
Chronic kidney disease (CKD) and nonalcoholic fatty liver disease (NAFLD), metabolic dysfunction-associated fatty liver disease (MAFLD) and metabolic dysfunction-associated steatotic liver disease (MASLD) account for substantial financial burden worldwide. These alarming features call for enhanced efforts to prevent and manage the development and progression of CKD. Accumulating evidence supporting a causal role of NAFLD/MAFLD/MASLD-in CKD opens new horizons to achieve this aim. Recent epidemiological studies and meta-analyses exploring the association of NAFLD/MAFLD/MASLD with CKD and the characteristics of NAFLD/MAFLD/MASLD associated with the odds of incident CKD are discussed. The involved pathomechanisms, including the common soil hypothesis, genetics, gut dysbiosis, and portal hypertension, are examined in detail. Finally, lifestyle changes (diet and physical exercise), direct manipulation of gut microbiota, and drug approaches involving statins, renin-angiotensin-aldosterone system inhibitors, GLP-1 Receptor Agonists, Sodium-glucose cotransporter-2, pemafibrate, and vonafexor are examined within the context of prevention and management of CKD among those with NAFLD/MAFLD/MASLD. The evolving NAFLD/MAFLD/MASLD nomenclature may generate confusion among practicing clinicians and investigators. However, comparative studies investigating the pros and contra of different nomenclatures may identify the most useful definitions among NAFLD/MAFLD/MASLD and strategies to identify, prevent, and halt the onset and progression of CKD.
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21
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Zou X, Huang H, Tan Y. Genetically determined metabolites in allergic conjunctivitis: A Mendelian randomization study. World Allergy Organ J 2024; 17:100894. [PMID: 38590722 PMCID: PMC10999487 DOI: 10.1016/j.waojou.2024.100894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/05/2024] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
Background Allergic conjunctivitis (AC) afflicts a significant portion of the global populace. Yet, its metabolic foundations remain largely unexplored. Methods We applied Mendelian Randomization (MR) and Linkage Disequilibrium Score Regression (LDSC) to scrutinize a cohort comprising 20 958 AC cases and 356 319 controls. Data were amalgamated from the metabolomics GWAS server and the FinnGen project, under strict quality control protocols. Results Using two-sample MR analysis, 486 blood metabolites were investigated in relation to AC. The IVW approach highlighted 18 metabolites as closely tied to AC risk; of these, 16 retained significance post sensitivity assessments for heterogeneity and horizontal pleiotropy. LDSC analysis, adopted to bolster our findings and negate confounders from shared genetic markers, revealed 8 metabolites with marked heritability, including: palmitate (OR = 0.614), 3-methoxytyrosine (OR = 0.657), carnitine (OR = 1.368), threonate (OR = 0.828), N-[3-(2-Oxopyrrolidin-1-yl)propyl]acetamide (OR = 1.257), metoprolol acid metabolite (OR = 0.982), oleoylcarnitine (OR = 0.635), and 2-palmitoylglycerophosphocholine (OR = 1.351). Conclusion AC is precipitated by ocular responses to environmental allergens. Our study unveils a causal link between 8 blood metabolites and AC. This insight accentuates the role of metabolites in AC onset, suggesting novel avenues for its early prediction, targeted prevention, and tailored therapeutic interventions.
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Affiliation(s)
- Xuyan Zou
- Changsha Aier Eye Hospital, Aier Eye Hospital Group, Changsha, 410000, China
| | - Haiyan Huang
- Clinical Medical College of Guizhou Medical University, Guiyang, 550004, China
| | - Yao Tan
- Department of Ophthalmology, The Third Xiangya Hospital, Central South University, Changsha, 410000, China
- Postdoctoral Station of Clinical Medicine, The Third Xiangya Hospital, Central South University, Changsha, 410000, China
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22
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Yang H, Zhang Y, Li X, Liu Z, Bai Y, Qian G, Wu H, Li J, Guo Y, Yang S, Chen L, Yang J, Han J, Ma S, Yang J, Yu L, Shui R, Jin X, Wang H, Zhang F, Chen T, Li X, Zong X, Liu L, Fan J, Wang W, Zhang Y, Shi G, Wang D, Tao S. Associations between sleep problems and cardiometabolic risk in maintenance hemodialysis patients: A multicenter study. Heliyon 2024; 10:e27377. [PMID: 38496884 PMCID: PMC10944224 DOI: 10.1016/j.heliyon.2024.e27377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/19/2024] Open
Abstract
The incidence of cardiovascular disease is increasing around the world, and it is one of the main causes of death in chronic kidney diseases patients. It is urgent to early identify the factors of cardiometabolic risk. Sleep problems have been recognized as a risk factor for cardiometabolic risk in both healthy people and chronic patients. However, the relationship between sleep problems and cardiometabolic risk has not been clearly explored in hemodialysis patients. This study aimed to investigate the relationship between sleep problems and cardiometabolic risk in 3025 hemodialysis patients by a multicenter study. After adjusting for confounders, binary logistic regression models showed that hemodialysis patients reported sleep duration greater than 7 h were more likely to be with hypertension, hyperglycemia, hypertriglyceridemia, and hypercholesterolemia. Patients reported sleep duration less than 7 h were more likely to be with hypertriglyceridemia and hypercholesterolemia, but the risks of hyperglycemia and Low HDL-cholesterol were decreased. Poor sleep quality was negatively correlated to low HDL cholesterol and hypertriglyceridemia. Moreover, gender-based differences were explained.
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Affiliation(s)
- Huan Yang
- Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, China
| | - Yingxin Zhang
- Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, China
| | - Xiuyong Li
- Blood Purification Center, NO.2 People's Hospital of Fuyang City, 1088 Yinghe West Road, Fuyang, 236015, China
| | - Zhi Liu
- Department of Nephrology, The First Affiliated Hospital of Anhui University of Science & Technology, 203 Huaibin Road, Huainan, 232000, China
| | - Youwei Bai
- Department of Nephrology, The Second People's Hospital of Lu'an City, 73 Mozitan Road, Lu'an, 237000, China
| | - Guangrong Qian
- Department of Nephrology, Maanshan People's Hospital, 45 Hubei Road, Maanshan, 243099, China
| | - Han Wu
- Blood Purification Center, Bozhou People's Hospital, 616 Duzhong Road, Bozhou, 236814, China
| | - Ji Li
- Department of Nephrology, Tongling People's Hospital, 468 Bijiashan Road, Tongling, 244099, China
| | - Yuwen Guo
- Department of Nephrology, Lujiang County People's Hospital, 32 Wenmingzhong Road, Lujiang, 231501, China
| | - Shanfei Yang
- Department of Nephrology, Shouxian County Hospital, Northeast of the Intersection of Binyang Avenue and Dongjin Avenue, Shouxian County, 232200, China
| | - Lei Chen
- Department of Nephrology, Hefei Jinnan Kidney Hospital, Northeast of the Intersection of Fozhang Road and Beihai Road, Hefei, 230071, China
| | - Jian Yang
- Department of Nephrology, Funan County People's Hospital, 36 Santa Road, Funan County, 236300, China
| | - Jiuhuai Han
- Department of Nephrology, Anqing Municipal Hospital, 87 East Tianzhushan Road, Anqing, 246003, China
| | - Shengyin Ma
- Department of Nephrology, Anhui Wanbei Coal-Electricity Group General Hospital, 125 Huaihe West Road, Suzhou, 234099, China
| | - Jing Yang
- Department of Nephrology, The First People's Hospital of Hefei, 390 Huaihe Road, Hefei, 230061, China
| | - Linfei Yu
- Department of Nephrology, The People's Hospital of Taihu, 196 Renmin Road, Taihu County, 246400, China
| | - Runzhi Shui
- Blood Purification Center, Huangshan City People's Hospital, 4 Liyuan Road, Huangshan, 245000, China
| | - Xiping Jin
- Department of Nephrology, Huainan Chao Yang Hospital, 15 Renmin South Road, Huainan, 232007, China
| | - Hongyu Wang
- Department of Nephrology, Lixin County People's Hospital, Intersection of Wenzhou Road and Feihe Road, Lixin County, 236700, China
| | - Fan Zhang
- Department of Nephrology, Dongzhi County People's Hospital, 70 Jianshe Road, Dongzhi County, 247299, China
| | - Tianhao Chen
- Department of Nephrology, Tianchang City People's Hospital, 137 Jianshe East Road, Tianchang, 239399, China
| | - Xinke Li
- Department of Nephrology, Xiaoxian People's Hospital, 58 Jiankang Road, Xiaoxian Conty, 235200, China
| | - Xiaoying Zong
- Department of Nephrology, The Second Affiliated Hospital of Bengbu Medical College, 633 Longhua Road, Bengbu, 233017, China
| | - Li Liu
- Department of Nephrology, The Second People's Hospital of Hefei, 246 Heping Road, Hefei, 230012, China
| | - Jihui Fan
- Department of Nephrology, Huaibei People's Hospital, 66 Huaihai West Road, Huaibei, 235000, China
| | - Wei Wang
- Department of Nephrology, The People's Hospital of Xuancheng City, 51 Dabatang Road, Xuancheng, 242099, China
| | - Yong Zhang
- Department of Nephrology, Lujiang County Hospital of TCM, 350 Zhouyu Avenue, Lujiang County, 231501, China
| | - Guangcai Shi
- Department of Nephrology, The Fifth People's Hospital of Hefei, Yuxi Road, Hefei, 230011, China
| | - Deguang Wang
- Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, China
| | - Shuman Tao
- Department of Nephrology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, China
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Osborne AJ, Bierzynska A, Colby E, Andag U, Kalra PA, Radresa O, Skroblin P, Taal MW, Welsh GI, Saleem MA, Campbell C. Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease. NPJ Syst Biol Appl 2024; 10:28. [PMID: 38459044 PMCID: PMC10924093 DOI: 10.1038/s41540-024-00350-8] [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: 09/04/2023] [Accepted: 02/20/2024] [Indexed: 03/10/2024] Open
Abstract
Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.
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Affiliation(s)
- Amy J Osborne
- Intelligent Systems Laboratory, University of Bristol, Bristol, BS8 1TW, UK.
| | - Agnieszka Bierzynska
- Bristol Renal, University of Bristol and Bristol Royal Hospital for Children, Bristol, BS1 3NY, UK
| | - Elizabeth Colby
- Bristol Renal, University of Bristol and Bristol Royal Hospital for Children, Bristol, BS1 3NY, UK
| | - Uwe Andag
- Department of Metabolic and Renal Diseases, Evotec International GmbH, Marie-Curie-Strasse 7, 37079, Göttingen, Germany
| | - Philip A Kalra
- Department of Renal Medicine, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Stott Lane, Salford, M6 8HD, UK
| | - Olivier Radresa
- Department of Metabolic and Renal Diseases, Evotec International GmbH, Marie-Curie-Strasse 7, 37079, Göttingen, Germany
| | - Philipp Skroblin
- Department of Metabolic and Renal Diseases, Evotec International GmbH, Marie-Curie-Strasse 7, 37079, Göttingen, Germany
| | - Maarten W Taal
- Centre for Kidney Research and Innovation, University of Nottingham, Derby, UK
| | - Gavin I Welsh
- Bristol Renal, University of Bristol and Bristol Royal Hospital for Children, Bristol, BS1 3NY, UK
| | - Moin A Saleem
- Bristol Renal, University of Bristol and Bristol Royal Hospital for Children, Bristol, BS1 3NY, UK
| | - Colin Campbell
- Intelligent Systems Laboratory, University of Bristol, Bristol, BS8 1TW, UK.
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Liu Y, Wang R, Li S, Zhang C, Lip GYH, Thabane L, Li G. Relationship Between Lipoprotein(a), Renal Function Indicators, and Chronic Kidney Disease: Evidence From a Large Prospective Cohort Study. JMIR Public Health Surveill 2024; 10:e50415. [PMID: 38294877 PMCID: PMC10867749 DOI: 10.2196/50415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 12/05/2023] [Accepted: 01/03/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) poses a significant global public health challenge. While lipoprotein(a) (Lp[a]) has been established as a significant factor in cardiovascular disease, its connection to CKD risk remains a topic of debate. Existing evidence indicates diverse risks of kidney disease among individuals with various renal function indicators, even when within the normal range. OBJECTIVE This study aims to investigate the joint associations between different renal function indicators and Lp(a) regarding the risks of incident CKD in the general population. METHODS The analysis involved a cohort of 329,415 participants without prior CKD who were enrolled in the UK Biobank between 2006 and 2010. The participants, with an average age of 56 (SD 8.1) years, included 154,298/329,415 (46.84%) males. At baseline, Lp(a) levels were measured using an immunoturbidimetric assay and classified into 2 groups: low (<75 nmol/L) and high (≥75 nmol/L). To assess participants' baseline renal function, we used the baseline urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR). The relationship between Lp(a), renal function indicators, and the risk of CKD was evaluated using multivariable Cox regression models. These models were adjusted for various factors, including sociodemographic variables, lifestyle factors, comorbidities, and laboratory measures. RESULTS A total of 6003 incident CKD events were documented over a median follow-up period of 12.5 years. The association between elevated Lp(a) levels and CKD risk did not achieve statistical significance among all participants, with a hazard ratio (HR) of 1.05 and a 95% CI ranging from 0.98 to 1.13 (P=.16). However, a notable interaction was identified between Lp(a) and UACR in relation to CKD risk (P for interaction=.04), whereas no significant interaction was observed between Lp(a) and eGFR (P for interaction=.96). When compared with the reference group with low Lp(a) and low-normal UACR (<10 mg/g), the group with high Lp(a) and low-normal UACR exhibited a nonsignificant association with CKD risk (HR 0.98, 95% CI 0.90-1.08; P=.74). By contrast, both the low Lp(a) and high-normal UACR (≥10 mg/g) group (HR 1.16, 95% CI 1.08-1.24; P<.001) and the high Lp(a) and high-normal UACR group (HR 1.32, 95% CI 1.19-1.46; P<.001) demonstrated significant associations with increased CKD risks. In individuals with high-normal UACR, elevated Lp(a) was linked to a significant increase in CKD risk, with an HR of 1.14 and a 95% CI ranging from 1.03 to 1.26 (P=.01). Subgroup analyses and sensitivity analyses consistently produced results that were largely in line with the main findings. CONCLUSIONS The analysis revealed a significant interaction between Lp(a) and UACR in relation to CKD risk. This implies that Lp(a) may act as a risk factor for CKD even when considering UACR. Our findings have the potential to provide valuable insights into the assessment and prevention of CKD, emphasizing the combined impact of Lp(a) and UACR from a public health perspective within the general population. This could contribute to enhancing public awareness regarding the management of Lp(a) for the prevention of CKD.
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Affiliation(s)
- Yingxin Liu
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Ruoting Wang
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Shuai Li
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Changfa Zhang
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom
- Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Lehana Thabane
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Guowei Li
- Center for Clinical Epidemiology and Methodology, Guangdong Second Provincial General Hospital, Guangzhou, China
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
- Father Sean O'Sullivan Research Centre, St Joseph's Healthcare Hamilton, Hamilton, ON, Canada
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Wang Z, Xiao Y, Lu J, Zou C, Huang W, Zhang J, Liu S, Han L, Jiao F, Tian D, Jiang Y, Du X, Ma RCW, Jiang G. Investigating linear and nonlinear associations of LDL cholesterol with incident chronic kidney disease, atherosclerotic cardiovascular disease and all-cause mortality: A prospective and Mendelian randomization study. Atherosclerosis 2023; 387:117394. [PMID: 38029611 DOI: 10.1016/j.atherosclerosis.2023.117394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND AIMS Observational studies suggest potential nonlinear associations of low-density lipoprotein cholesterol (LDL-C) with cardio-renal diseases and mortality, but the causal nature of these associations is unclear. We aimed to determine the shape of causal relationships of LDL-C with incident chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality, and to evaluate the absolute risk of adverse outcomes contributed by LDL-C itself. METHODS Observational analysis and one-sample Mendelian randomization (MR) with linear and nonlinear assumptions were performed using the UK Biobank of >0.3 million participants with no reported prescription of lipid-lowering drugs. Two-sample MR on summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen (N = 625,219) was employed to replicate the relationship for kidney traits. The 10-year probabilities of the outcomes was estimated by integrating the MR and Cox models. RESULTS Observationally, participants with low LDL-C were significantly associated with a decreased risk of ASCVD, but an increased risk of CKD and all-cause mortality. Univariable MR showed an inverse total effect of LDL-C on incident CKD (HR [95% CI]:0.84 [0.73-0.96]; p = 0.011), a positive effect on ASCVD (1.41 [1.29-1.53]; p<0.001), and no significant causal effect on all-cause mortality. Multivariable MR, controlling for high-density lipoprotein cholesterol (HDL-C) and triglycerides, identified a positive direct effect on ASCVD (1.32 [1.18-1.47]; p<0.001), but not on CKD and all-cause mortality. These results indicated that genetically predicted low LDL-C had an inverse indirect effect on CKD mediated by HDL-C and triglycerides, which was validated by a two-sample MR analysis using summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen consortium (N = 625,219). Suggestive evidence of a nonlinear causal association between LDL-C and CKD was found. The 10-year probability curve showed that LDL-C concentrations below 3.5 mmol/L were associated with an increased risk of CKD. CONCLUSIONS In the general population, lower LDL-C was causally associated with lower risk of ASCVD, but appeared to have a trade-off for an increased risk of CKD, with not much effect on all-cause mortality. LDL-C concentration below 3.5 mmol/L may increase the risk of CKD.
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Affiliation(s)
- Zhenqian Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yang Xiao
- National Clinical Research Centre for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jiawen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Chenfeng Zou
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Wenyu Huang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Jiaying Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Liyuan Han
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Feng Jiao
- Guangzhou Centre for Applied Mathematics, Guangzhou University, Guangzhou, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yawen Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China; Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
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Xie Z, Qin Y. Is diet related to osteoarthritis? A univariable and multivariable Mendelian randomization study that investigates 45 dietary habits and osteoarthritis. Front Nutr 2023; 10:1278079. [PMID: 38035348 PMCID: PMC10687195 DOI: 10.3389/fnut.2023.1278079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 11/03/2023] [Indexed: 12/02/2023] Open
Abstract
Background Diet is a safe intervention for many chronic diseases as a modifiable lifestyle. However, the potential causal effect of many dietary intake habits on the risk of osteoarthritis has not been fully understood. The purpose of this study was to reveal the potential causal relationship of 45 genetically predicted dietary intakes with osteoarthritis and its subtypes. Methods Data on 45 dietary intakes were obtained from the UK Biobank study of approximately 500,000 participants, and data on six osteoarthritis-related phenotypes were obtained from the Genetics of Osteoarthritis Consortium study of 826,690 participants. We performed univariable Mendelian randomization (MR), multivariable MR and linkage disequilibrium score regression (LDSC) analyses. Results In univariate analyses, 59 potential associations between diet and osteoarthritis were found. After false discovery rate (FDR) correction and sensitivity analyses, 23 reliable causal evidence were identified. In multivariate analyses, controlling separately for the effects of body mass index, total body bone mineral density, and smoking status, eight robust causal relationships remained: Muesli intake was negatively associated with knee osteoarthritis, spine osteoarthritis and total knee replacement. Dried fruit intake had a negative association with osteoarthritis of knee and total knee replacement. Eating cheese may reduce the risk of osteoarthritis in the knee and spine. And alcohol usually taken with meals was associated with a reduced risk of total knee replacement. LDSC analyses showed significant genetic correlations between all exposures and their corresponding outcomes, respectively, in these eight causal relationships. Conclusion Evidence of dietary effects on osteoarthritis is provided in our study, which has important implications for the prevention, management, and intervention of osteoarthritis in common sites through rational dietary modification.
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Affiliation(s)
| | - Yanguo Qin
- Department of Orthopedics, The Second Hospital of Jilin University, Changchun, China
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Wu S, Kong M, Song Y, Peng A. Ethnic disparities in bidirectional causal effects between serum uric acid concentrations and kidney function: Trans-ethnic Mendelian randomization study. Heliyon 2023; 9:e21108. [PMID: 37908715 PMCID: PMC10613891 DOI: 10.1016/j.heliyon.2023.e21108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 09/12/2023] [Accepted: 10/16/2023] [Indexed: 11/02/2023] Open
Abstract
Introduction Researchers have investigated the causal effect between serum uric acid (SUA) concentrations and kidney function for decades, but studies produced inconsistent results. This study aimed to clarify the bidirectional causal effects between SUA concentrations and kidney function and to explore the potential ethnic disparities by conducting a trans-ethnic Mendelian randomization study in European, African, and Asian ancestries. Materials and methods The summary-level data for this study were obtained from the Global Urate Genetics Consortium, CKDGen Consortium, UK Biobank, and Japan Biobank for different outcomes and exposures, respectively. The traits of kidney function were estimated glomerular filtration rate from serum creatinine (eGFRcr), estimated glomerular filtration rate from cystatin C (eGFRcys), and blood urea nitrogen (BUN). Using the multiplicative random-effects inverse variance weighting mode, our primary analysis produced robust results despite heterogeneity. Additionally, we performed the Mendelian randomization pleiotropy residual sum and outlier test to eliminate the horizontal pleiotropy and obtain accurate results. Results Our findings revealed that elevated SUA concentrations had causal effects on declined eGFRcys, BUN, and a diagnosis of chronic kidney disease in European ancestries and eGFRcr in Asian ancestries. Additionally, the causal effects of declined eGFRcr and elevated BUN concentrations on elevated SUA concentrations were observed in both European and Asian ancestries. However, no bidirectional causal effect was found between SUA concentrations and eGFRcr among African ancestries. Conclusions This trans-ethnic Mendelian randomization study confirmed the bidirectional causal effects between SUA concentrations and kidney function and highlighted the importance of considering ethnic disparities in clinical treatments.
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Affiliation(s)
| | | | - Yaxiang Song
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Ai Peng
- Center for Nephrology and Clinical Metabolomics and Division of Nephrology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
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Skarpsno ES, Simpson MR, Seim A, Hrozanova M, Bakøy MA, Klevanger NE, Aasdahl L. App-Delivered Cognitive-Behavioral Therapy for Insomnia Among Patients with Comorbid Musculoskeletal Complaints and Insomnia Referred to 4-Week Inpatient Multimodal Rehabilitation: Protocol for a Randomized Clinical Trial. Nat Sci Sleep 2023; 15:799-809. [PMID: 37850197 PMCID: PMC10577252 DOI: 10.2147/nss.s419520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 09/20/2023] [Indexed: 10/19/2023] Open
Abstract
Background Insomnia is prevalent among patients receiving treatment for long-term musculoskeletal complaints in inpatient rehabilitation settings. Cognitive-behavioral therapy for insomnia (CBT-I) is effective for improving sleep quality in patients with pain, but a lack of therapists often limits the capacity to use this therapy in rehabilitation programs. The aim of this randomized clinical trial (RCT) is to evaluate the effectiveness of app-delivered CBT-I adjunct to inpatient multimodal rehabilitation for individuals with comorbid musculoskeletal complaints and insomnia, compared with rehabilitation (usual care) only. Methods This RCT has two parallel arms: 1) inpatient multimodal rehabilitation and 2) app-delivered CBT-I adjunct to inpatient multimodal rehabilitation. Patients referred to Unicare Helsefort (Norway) with long-term chronic musculoskeletal complaints are invited to the study. Eligible and consenting participants will be randomized to the intervention and usual care at a ratio of 2:1. Assessments will be carried out at baseline (prior to randomization), 6 weeks (at the end of rehabilitation), 3 months (primary outcome), as well as 6 and 12 months after the rehabilitation. The primary outcome is insomnia severity measured at 3 months. Secondary outcomes include pain intensity, health-related quality of life, fatigue, physical function, work ability, expectations about sick leave length, sick leave, and prescribed medication. Exploratory analyses are planned to identify moderators and mediators of the effect of the app-delivered intervention. Discussion This RCT will provide novel knowledge about the effectiveness of app-delivered CBT-I as an adjunct to usual care among patients participating in inpatient multimodal pain rehabilitation. Regardless of the results from this trial, the results will improve our understanding of the utility of dCBT-I in the field of rehabilitation and the importance of adding sleep therapy to this patient group. Trial Registration This trial was prospectively registered in ClinicalTrials.gov October 10, 2022 (ClinicalTrials.gov identifier: NCT05572697).
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Affiliation(s)
- Eivind Schjelderup Skarpsno
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, St. Olavs Hospital, Trondheim, Norway
| | - Melanie Rae Simpson
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Arnfinn Seim
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Unicare Helsefort Rehabilitation Centre, Rissa, Norway
| | - Maria Hrozanova
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Nina Elisabeth Klevanger
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Lene Aasdahl
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Unicare Helsefort Rehabilitation Centre, Rissa, Norway
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Ahmed A, Amin H, Drenos F, Sattar N, Yaghootkar H. Genetic Evidence Strongly Supports Managing Weight and Blood Pressure in Addition to Glycemic Control in Preventing Vascular Complications in People With Type 2 Diabetes. Diabetes Care 2023; 46:1783-1791. [PMID: 37556814 DOI: 10.2337/dc23-0855] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 07/05/2023] [Indexed: 08/11/2023]
Abstract
OBJECTIVE To investigate the causal association of type 2 diabetes and its components with risk of vascular complications independent of shared risk factors obesity and hypertension and to identify the main driver of this risk. RESEARCH DESIGN AND METHODS We conducted Mendelian randomization (MR) using independent genetic variants previously associated with type 2 diabetes, fasting glucose, HbA1c, fasting insulin, BMI, and systolic blood pressure as instrumental variables. We obtained summary-level data for 18 vascular diseases (15 for type 2 diabetes) from FinnGen and publicly available genome-wide association studies as our outcomes. We conducted univariable and multivariable MR, in addition to sensitivity tests to detect and minimize pleiotropic effects. RESULTS Univariable MR analysis showed that type 2 diabetes was associated with 9 of 15 outcomes; BMI and systolic blood pressure were associated with 13 and 15 of 18 vascular outcomes, respectively; and fasting insulin was associated with 4 and fasting glucose with 2. No robust association was found for HbA1c instruments. With adjustment for correlated traits in the multivariable test, BMI and systolic blood pressure, consistent causal effects were maintained, while five associations with type 2 diabetes (chronic kidney disease, ischemic heart disease, heart failure, subarachnoid hemorrhage, and intracerebral hemorrhage) were attenuated to null. CONCLUSIONS Our findings add strong evidence to support the importance of BMI and systolic blood pressure in the development of vascular complications in people with type 2 diabetes. Such findings strongly support the need for better weight and blood pressure management in type 2 diabetes, independent of glucose lowering, to limit important complications.
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Affiliation(s)
- Altayeb Ahmed
- Centre for Inflammation Research and Translational Medicine, Department of Life Sciences, Brunel University London, London, U.K
| | - Hasnat Amin
- Centre for Inflammation Research and Translational Medicine, Department of Life Sciences, Brunel University London, London, U.K
| | - Fotios Drenos
- Centre for Inflammation Research and Translational Medicine, Department of Life Sciences, Brunel University London, London, U.K
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, U.K
| | - Hanieh Yaghootkar
- College of Health and Science, University of Lincoln, Lincoln, Lincolnshire, U.K
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30
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Wang Y, Zhang L, Zhang W, Tang M, Cui H, Wu X, Zhao X, Chen L, Yan P, Yang C, Xiao C, Zou Y, Liu Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Jiang X, Zhang B. Understanding the relationship between circulating lipids and risk of chronic kidney disease: a prospective cohort study and large-scale genetic analyses. J Transl Med 2023; 21:671. [PMID: 37759214 PMCID: PMC10537816 DOI: 10.1186/s12967-023-04509-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 09/06/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND This study aims to comprehensively investigate the phenotypic and genetic relationships between four common lipids (high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; total cholesterol, TC; and triglycerides, TG), chronic kidney disease (CKD), and estimated glomerular filtration rate (eGFR). METHODS We first investigated the observational association of lipids (exposures) with CKD (primary outcome) and eGFR (secondary outcome) using data from UK Biobank. We then explored the genetic relationship using summary statistics from the largest genome-wide association study of four lipids (N = 1,320,016), CKD (Ncase = 41,395, Ncontrol = 439,303), and eGFR(N = 567,460). RESULTS There were significant phenotypic associations (HDL-C: hazard ratio (HR) = 0.76, 95%CI = 0.60-0.95; TG: HR = 1.08, 95%CI = 1.02-1.13) and global genetic correlations (HDL-C: [Formula: see text] = - 0.132, P = 1.00 × 10-4; TG: [Formula: see text] = 0.176; P = 2.66 × 10-5) between HDL-C, TG, and CKD risk. Partitioning the whole genome into 2353 LD-independent regions, twelve significant regions were observed for four lipids and CKD. The shared genetic basis was largely explained by 29 pleiotropic loci and 36 shared gene-tissue pairs. Mendelian randomization revealed an independent causal relationship of genetically predicted HDL-C (odds ratio = 0.91, 95%CI = 0.85-0.98), but not for LDL-C, TC, or TG, with the risk of CKD. Regarding eGFR, a similar pattern of correlation and pleiotropy was observed. CONCLUSIONS Our work demonstrates a putative causal role of HDL-C in CKD and a significant biological pleiotropy underlying lipids and CKD in populations of European ancestry. Management of low HDL-C levels could potentially benefit in reducing the long-term risk of CKD.
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Affiliation(s)
- Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Chenghan Xiao
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Ling Zhang
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Yuqin Yao
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China
| | - Zhenmi Liu
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China.
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041, Sichuan, China.
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Kowalczyk NS, Prochaska ML, Worcester EM. Metabolomic profiles and pathogenesis of nephrolithiasis. Curr Opin Nephrol Hypertens 2023; 32:490-495. [PMID: 37530089 PMCID: PMC10403267 DOI: 10.1097/mnh.0000000000000903] [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] [Indexed: 08/03/2023]
Abstract
PURPOSE OF REVIEW Kidney stone disease is caused by supersaturation of urine with certain metabolites and minerals. The urine composition of stone formers has been measured to prevent stone recurrence, specifically calcium, uric acid, oxalate, ammonia, citrate. However, these minerals and metabolites have proven to be unreliable in predicting stone recurrence. Metabolomics using high throughput technologies in well defined patient cohorts can identify metabolites that may provide insight into the pathogenesis of stones as well as offer possibilities in therapeutics. RECENT FINDINGS Techniques including 1H-NMR, and liquid chromatography paired with tandem mass spectroscopy have identified multiple possible metabolites involved in stone formation. Compared to formers of calcium oxalate stones, healthy controls had higher levels of hippuric acid as well as metabolites involved in caffeine metabolism. Both the gut and urine microbiome may contribute to the altered metabolome of stone formers. SUMMARY Although metabolomics has offered several potential metabolites that may be protective against or promote stone formation, the mechanisms behind these metabolomic profiles and their clinical significance requires further investigation.
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Lyssenko V, Vaag A. Genetics of diabetes-associated microvascular complications. Diabetologia 2023; 66:1601-1613. [PMID: 37452207 PMCID: PMC10390394 DOI: 10.1007/s00125-023-05964-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 04/27/2023] [Indexed: 07/18/2023]
Abstract
Diabetes is associated with excess morbidity and mortality due to both micro- and macrovascular complications, as well as a range of non-classical comorbidities. Diabetes-associated microvascular complications are those considered most closely related to hyperglycaemia in a causal manner. However, some individuals with hyperglycaemia (even those with severe hyperglycaemia) do not develop microvascular diseases, which, together with evidence of co-occurrence of microvascular diseases in families, suggests a role for genetics. While genome-wide association studies (GWASs) produced firm evidence of multiple genetic variants underlying differential susceptibility to type 1 and type 2 diabetes, genetic determinants of microvascular complications are mostly suggestive. Identified susceptibility variants of diabetic kidney disease (DKD) in type 2 diabetes mirror variants underlying chronic kidney disease (CKD) in individuals without diabetes. As for retinopathy and neuropathy, reported risk variants currently lack large-scale replication. The reported associations between type 2 diabetes risk variants and microvascular complications may be explained by hyperglycaemia. More extensive phenotyping, along with adjustments for unmeasured confounding, including both early (fetal) and late-life (hyperglycaemia, hypertension, etc.) environmental factors, are urgently needed to understand the genetics of microvascular complications. Finally, genetic variants associated with reduced glycolysis, mitochondrial dysfunction and DNA damage and sustained cell regeneration may protect against microvascular complications, illustrating the utility of studies in individuals who have escaped these complications.
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Affiliation(s)
- Valeriya Lyssenko
- Department of Clinical Science, Mohn Research Center for Diabetes Precision Medicine, University of Bergen, Bergen, Norway.
- Department of Clinical Sciences, Lund University Diabetes Center, Lund University, Lund, Sweden.
| | - Allan Vaag
- Department of Clinical Sciences, Lund University Diabetes Center, Lund University, Lund, Sweden
- Steno Diabetes Center Copenhagen, Herlev, Denmark
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Zhang W, Zhang L, Yang L, Xiao C, Wu X, Yan P, Cui H, Yang C, Zhu J, Wu X, Tang M, Wang Y, Chen L, Liu Y, Zou Y, Zhang L, Yang C, Yao Y, Li J, Liu Z, Zhang B, Jiang X. Migraine, chronic kidney disease and kidney function: observational and genetic analyses. Hum Genet 2023; 142:1185-1200. [PMID: 37306871 PMCID: PMC10449948 DOI: 10.1007/s00439-023-02575-9] [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: 03/22/2023] [Accepted: 05/23/2023] [Indexed: 06/13/2023]
Abstract
Epidemiological studies demonstrate an association between migraine and chronic kidney disease (CKD), while the genetic basis underlying the phenotypic association has not been investigated. We aimed to help avoid unnecessary interventions in individuals with migraine through the investigation of phenotypic and genetic relationships underlying migraine, CKD, and kidney function. We first evaluated phenotypic associations using observational data from UK Biobank (N = 255,896). We then investigated genetic relationships leveraging genomic data in European ancestry for migraine (Ncase/Ncontrol = 48,975/540,381), CKD (Ncase/Ncontrol = 41,395/439,303), and two traits of kidney function (estimated glomerular filtration rate [eGFR, N = 567,460] and urinary albumin-to-creatinine ratio [UACR, N = 547,361]). Observational analyses suggested no significant association of migraine with the risk of CKD (HR = 1.13, 95% CI = 0.85-1.50). While we did not find any global genetic correlation in general, we identified four specific genomic regions showing significant for migraine with eGFR. Cross-trait meta-analysis identified one candidate causal variant (rs1047891) underlying migraine, CKD, and kidney function. Transcriptome-wide association study detected 28 shared expression-trait associations between migraine and kidney function. Mendelian randomization analysis suggested no causal effect of migraine on CKD (OR = 1.03, 95% CI = 0.98-1.09; P = 0.28). Despite a putative causal effect of migraine on an increased level of UACR (log-scale-beta = 0.02, 95% CI = 0.01-0.04; P = 1.92 × 10-3), it attenuated to null when accounting for both correlated and uncorrelated pleiotropy. Our work does not find evidence supporting a causal association between migraine and CKD. However, our study highlights significant biological pleiotropy between migraine and kidney function. The value of a migraine prophylactic treatment for reducing future CKD in people with migraine is likely limited.
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Affiliation(s)
- Wenqiang Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Li Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Luo Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Urology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Chenghan Xiao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xueyao Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Peijing Yan
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Chao Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Jingwei Zhu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Xuan Wu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Mingshuang Tang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yutong Wang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Lin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yunjie Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yanqiu Zou
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Ling Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Iatrical Polymer Material and Artificial Apparatus, School of Polymer Science and Engineering, Sichuan University, Chengdu, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Yuqin Yao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
| | - Zhenmi Liu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ben Zhang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xia Jiang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, South Renmin Road, Wuhou District, Chengdu, 610041 China
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Liu X, Yu Y, Hou L, Yu Y, Wu Y, Wu S, He Y, Ge Y, Wei Y, Luo Q, Qian F, Feng Y, Li H, Xue F. Association between dietary habits and the risk of migraine: a Mendelian randomization study. Front Nutr 2023; 10:1123657. [PMID: 37351190 PMCID: PMC10282154 DOI: 10.3389/fnut.2023.1123657] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 05/19/2023] [Indexed: 06/24/2023] Open
Abstract
Objective The important contribution of dietary triggers to migraine pathogenesis has been recognized. However, the potential causal roles of many dietary habits on the risk of migraine in the whole population are still under debate. The objective of this study was to determine the potential causal association between dietary habits and the risk of migraine (and its subtypes) development, as well as the possible mediator roles of migraine risk factors. Methods Based on summary statistics from large-scale genome-wide association studies, we conducted two-sample Mendelian randomization (MR) and bidirectional MR to investigate the potential causal associations between 83 dietary habits and migraine and its subtypes, and network MR was performed to explore the possible mediator roles of 8 migraine risk factors. Results After correcting for multiple testing, we found evidence for associations of genetically predicted coffee, cheese, oily fish, alcohol (red wine), raw vegetables, muesli, and wholemeal/wholegrain bread intake with decreased risk of migraine, those odds ratios ranged from 0.78 (95% CI: 0.63-0.95) for overall cheese intake to 0.61 (95% CI: 0.47-0.80) for drinks usually with meals among current drinkers (yes + it varies vs. no); while white bread, cornflakes/frosties, and poultry intake were positively associated with the risk of migraine. Additionally, genetic liability to white bread, wholemeal/wholegrain bread, muesli, alcohol (red wine), cheese, and oily fish intake were associated with a higher risk of insomnia and (or) major depression disorder (MDD), each of them may act as a mediator in the pathway from several dietary habits to migraine. Finally, we found evidence of a negative association between genetically predicted migraine and drinking types, and positive association between migraine and cups of tea per day. Significance Our study provides evidence about association between dietary habits and the risk of migraine and demonstrates that some associations are partly mediated through one or both insomnia and MDD. These results provide new insights for further nutritional interventions for migraine prevention.
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Affiliation(s)
- Xinhui Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yuanyuan Yu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Lei Hou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yifan Yu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yutong Wu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Sijia Wu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yina He
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yilei Ge
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yun Wei
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qingxin Luo
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Fengtong Qian
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yue Feng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Hongkai Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
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Kintu C, Soremekun O, Kamiza AB, Kalungi A, Mayanja R, Kalyesubula R, Bagaya S B, Jjingo D, Fabian J, Gill D, Nyirenda M, Nitsch D, Chikowore T, Fatumo S. The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study. EBioMedicine 2023; 90:104537. [PMID: 37001235 PMCID: PMC10070509 DOI: 10.1016/j.ebiom.2023.104537] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 03/08/2023] [Accepted: 03/08/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Observational studies have investigated the effect of serum lipids on kidney function, but these findings are limited by confounding, reverse causation and have reported conflicting results. Mendelian randomization (MR) studies address this confounding problem. However, they have been conducted mostly in European ancestry individuals. We, therefore, set out to investigate the effect of lipid traits on the estimated glomerular filtration rate (eGFR) based on serum creatinine in individuals of African ancestry. METHODS We used the two-sample and multivariable Mendelian randomization (MVMR) approaches; in which instrument variables (IV's) for the predictor (lipid traits) were derived from summary-level data of a meta-analyzed African lipid GWAS (MALG, n = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (n = 13,612) & the Africa Wits-IN-DEPTH partnership for Genomics studies (AWI-Gen) dataset (n = 10,603). The outcome IV's were computed from the eGFR summary-level data of African-ancestry individuals within the Million Veteran Program (n = 57,336). A random-effects inverse variance method was used in our primary analysis, and pleiotropy was adjusted for using robust and penalized sensitivity testing. The lipid predictors for the MVMR were high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG). FINDINGS We found a significant causal association between genetically predicted low-density lipoprotein (LDL) cholesterol and eGFR in African ancestry individuals β = 1.1 (95% CI [0.411-1.788]; p = 0.002). Similarly, total cholesterol (TC) showed a significant causal effect on eGFR β = 1.619 (95% CI [0.412-2.826]; p = 0.009). However, the IVW estimate showed that genetically predicted HDL-C β = -0.164, (95% CI = [-1.329 to 1.00]; p = 0.782), and TG β = -0.934 (CI = [-2.815 to 0.947]; p = 0.33) were not significantly causally associated with the risk of eGFR. In the multivariable analysis inverse-variance weighted (MVIVW) method, there was evidence for a causal association between LDL and eGFR β = 1.228 (CI = [0.477-1.979]; p = 0.001). A significant causal effect of Triglycerides (TG) on eGFR in the MVIVW analysis β = -1.3 ([-2.533 to -0.067]; p = 0.039) was observed as well. All the causal estimates reported reflect a unit change in the outcome per a 1 SD increase in the exposure. HDL showed no evidence of a significant causal association with eGFR in the MVIVW method (β = -0.117 (95% CI [-1.252 to 0.018]; p = 0.840)). We found no evidence of a reverse causal impact of eGFR on serum lipids. All our sensitivity analyses indicated no strong evidence of pleiotropy or heterogeneity between our instrumental variables for both the forward and reverse MR analysis. INTERPRETATION In this African ancestry population, genetically predicted higher LDL-C and TC are causally associated with higher eGFR levels, which may suggest that the relationship between LDL, TC and kidney function may be U-shaped. And as such, lowering LDL_C does not necessarily improve risk of kidney disease. This may also imply the reason why LDL_C is seen to be a poorer predictor of kidney function compared to HDL. In addition, this further supports that more work is warranted to confirm the potential association between lipid traits and risk of kidney disease in individuals of African Ancestry. FUNDING Wellcome (220740/Z/20/Z).
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Affiliation(s)
- Christopher Kintu
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda; MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Opeyemi Soremekun
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Abram B Kamiza
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Allan Kalungi
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Richard Mayanja
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Robert Kalyesubula
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda; MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda
| | - Bernard Bagaya S
- Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda
| | - Daudi Jjingo
- African Center of Excellence in Bioinformatics (ACE-B), Makerere University, Kampala 10101, Uganda
| | - June Fabian
- Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Wits Donald Gordon Medical Centre, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - 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
| | - Moffat Nyirenda
- MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Tinashe Chikowore
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda; Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
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Kjaergaard AD, Krakauer J, Krakauer N, Teumer A, Winkler TW, Ellervik C. Allometric body shape indices, type 2 diabetes and kidney function: A two-sample Mendelian randomization study. Diabetes Obes Metab 2023. [PMID: 36855799 DOI: 10.1111/dom.15037] [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] [Received: 01/23/2023] [Revised: 02/24/2023] [Accepted: 02/26/2023] [Indexed: 03/02/2023]
Abstract
AIM To examine the association between body mass index (BMI)-independent allometric body shape indices and kidney function. MATERIALS AND METHODS We performed a two-sample Mendelian randomization (MR) analysis, using summary statistics from UK Biobank, CKDGen and DIAGRAM. BMI-independent allometric body shape indices were: A Body Shape Index (ABSI), Waist-Hip Index (WHI) and Hip Index (HI). Kidney function outcomes were: urinary albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate and blood urea nitrogen. Furthermore, we investigated type 2 diabetes (T2D) as a potential mediator on the pathway to albuminuria. The main analysis was inverse variance-weighted random-effects MR in participants of European ancestry. We also performed several sensitivity MR analyses. RESULTS A 1-standard deviation (SD) increase in genetically predicted ABSI and WHI levels was associated with higher UACR (β = 0.039 [95% confidence interval: 0.016, 0.063] log [UACR], P = 0.001 for ABSI, and β = 0.028 [0.012, 0.044] log [UACR], P = 6 x 10-4 for WHI) in women, but not in men. Meanwhile, a 1-SD increase in genetically predicted HI was associated with lower UACR in women (β = -0.021 [-0.041, 0.000] log [UACR], P = 0.05) and in men (β = -0.026 [-0.058, 0.005] log [UACR], P = 0.10). Corresponding estimates in individuals with diabetes were substantially augmented. Risk of T2D increased for genetically high ABSI and WHI in women (P < 6 x 10-19 ) only, but decreased for genetically high HI in both sexes (P < 9 x 10-3 ). No other associations were observed. CONCLUSIONS Genetically high HI was associated with decreased risk of albuminuria, mediated through decreased T2D risk in both sexes. Opposite associations applied to genetically high ABSI and WHI in women only.
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Affiliation(s)
- Alisa D Kjaergaard
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
- Joslin Diabetes Center, Boston, Massachusetts, USA
| | - Jesse Krakauer
- Associated Physicians/Endocrinology, Berkley, Michigan, USA
| | - Nir Krakauer
- Department of Civil Engineering, City College of New York and Earth and Environmental Sciences, Graduate Center, City University of New York, New York, New York, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Christina Ellervik
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Data and Development, Sorø, Denmark
- Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
- Department of Laboratory Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
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37
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Ala-Korpela M. The epidemiological quest for the role of vitamin D turned non-linear-and simply made sense. Int J Epidemiol 2023; 52:1-4. [PMID: 36416418 DOI: 10.1093/ije/dyac218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 11/03/2022] [Indexed: 11/24/2022] Open
Affiliation(s)
- Mika Ala-Korpela
- Systems Epidemiology, Research Unit of Population Health, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland and NMR Metabolomics Laboratory, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
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Zhang L, Tang L, Chen S, Chen C, Peng B. A nomogram for predicting the 4-year risk of chronic kidney disease among Chinese elderly adults. Int Urol Nephrol 2023; 55:1609-1617. [PMID: 36720744 DOI: 10.1007/s11255-023-03470-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 01/12/2023] [Indexed: 02/02/2023]
Abstract
BACKGROUND Chronic kidney disease (CKD) has become a major public health problem across the globe, leading to various complications. This study aimed to construct a nomogram to predict the 4-year risk of CKD among Chinese adults. METHODS The study was based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 3562 participants with complete information in CHARLS2011 and CHARLS2015 were included, and further divided into the training cohort and the validation cohort by a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to select variables of the nomogram. The nomogram was evaluated by receiver-operating characteristic curve, calibration plots, and decision curve analysis (DCA). RESULTS In all, 2494 and 1068 participants were included in the training cohort and the validation cohort, respectively. A total of 413 participants developed CKD in the following 4 years. Five variables selected by multivariate logistic regression were incorporated in the nomogram, consisting of gender, hypertension, the estimated glomerular filtration rate (eGFR), hemoglobin, and Cystatin C. The area under curve was 0.809 and 0.837 in the training cohort and the validation cohort, respectively. The calibration plots showed agreement between the nomogram-predicted probability and the observed probability. DCA indicated that the nomogram had potential clinical use. CONCLUSIONS A predictive nomogram was established and internally validated in aid of identifying individuals at increased risk of CKD.
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Affiliation(s)
- Lijuan Zhang
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Lan Tang
- Physical Examination Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Siyu Chen
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Chen Chen
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Bin Peng
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China.
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Soremekun O, Dib MJ, Rajasundaram S, Fatumo S, Gill D. Genetic heterogeneity in cardiovascular disease across ancestries: Insights for mechanisms and therapeutic intervention. CAMBRIDGE PRISMS. PRECISION MEDICINE 2023; 1:e8. [PMID: 38550935 PMCID: PMC10953756 DOI: 10.1017/pcm.2022.13] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/09/2022] [Accepted: 12/15/2022] [Indexed: 11/03/2024]
Abstract
Cardiovascular diseases (CVDs) are complex in their aetiology, arising due to a combination of genetics, lifestyle and environmental factors. By nature of this complexity, different CVDs vary in their molecular mechanisms, clinical presentation and progression. Although extensive efforts are being made to develop novel therapeutics for CVDs, genetic heterogeneity is often overlooked in the development process. By considering molecular mechanisms at an individual and ancestral level, a richer understanding of the influence of environmental and lifestyle factors can be gained and more refined therapeutic interventions can be developed. It is therefore expedient to understand the molecular and clinical heterogeneity in CVDs that exists across different populations. In this review, we highlight how the mechanisms underlying CVDs vary across diverse population ancestry groups due to genetic heterogeneity. We then discuss how such genetic heterogeneity is being leveraged to inform therapeutic interventions and personalised medicine, highlighting examples across the CVD spectrum. Finally, we present an overview of how polygenic risk scores and Mendelian randomisation can foster more robust insight into disease mechanisms and therapeutic intervention in diverse populations. Fulfilment of the vision of precision medicine requires more exhaustive leveraging of the genetic variability across diverse ancestry populations to improve our understanding of disease onset, progression and response to therapeutic intervention.
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Affiliation(s)
- Opeyemi Soremekun
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Molecular Bio-Computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, South Africa
| | - Marie-Joe Dib
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London, UK
| | - Skanda Rajasundaram
- Centre for Evidence-Based Medicine, University of Oxford, Oxford, UK
- Faculty of Medicine, Imperial College London, London, UK
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Non-Communicable Disease Epidemiology (NCDE), London School of Hygiene and Tropical Medicine, London, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- British Heart Foundation Centre of Excellence, Imperial College London, London, UK
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Fujii R, Pattaro C. Genetically-instrumented public health: facing obesity to prevent chronic kidney disease. Cardiovasc Res 2022; 118:3013-3015. [PMID: 36305100 DOI: 10.1093/cvr/cvac168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 10/17/2022] [Indexed: 12/13/2022] Open
Affiliation(s)
- Ryosuke Fujii
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano/Bozen, Italy.,Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan.,Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Cristian Pattaro
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano/Bozen, Italy
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Ahmed A, Sattar N, Yaghootkar H. Advancing a causal role of type 2 diabetes and its components in developing macro- and microvascular complications via genetic studies. Diabet Med 2022; 39:e14982. [PMID: 36256488 PMCID: PMC9827870 DOI: 10.1111/dme.14982] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/07/2022] [Accepted: 10/16/2022] [Indexed: 02/06/2023]
Abstract
The role of diabetes in developing microvascular and macrovascular complications has been subject to extensive research. Despite multiple observational and genetic studies, the causal inference of diabetes (and associated risk factors) on those complications remains incomplete. In this review, we focused on type 2 diabetes, as the major form of diabetes, and investigated the evidence of causality provided by observational and genetic studies. We found that genetic studies based on Mendelian randomization provided consistent evidence of causal inference of type 2 diabetes on macrovascular complications; however, the evidence for causal inference on microvascular complications has been somewhat limited. We also noted high BMI could be causal for several diabetes complications, notable given high BMI is commonly upstream of type 2 diabetes and the recent calls to target weight loss more aggressively. We emphasize the need for further studies to identify type 2 diabetes components that mostly drive the risk of those complications. Even so, the genetic evidence summarized broadly concurs with the need for a multifactorial risk reduction approach in type 2 diabetes, including addressing excess adiposity.
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Affiliation(s)
- Altayeb Ahmed
- Department of Life Sciences, Centre for Inflammation Research and Translational MedicineBrunel University LondonLondonUK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic HealthUniversity of GlasgowGlasgowUK
| | - Hanieh Yaghootkar
- Department of Life Sciences, Centre for Inflammation Research and Translational MedicineBrunel University LondonLondonUK
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Bouazza A, Tahar A, AitAbderrhmane S, Saidani M, Koceir EA. Modulation of cardiometabolic risk and CardioRenal syndrome by oral vitamin D 3 supplementation in Black and White Southern Sahara residents with chronic kidney disease Stage 3: focus on racial and ethnic disparities. Ren Fail 2022; 44:1243-1262. [PMID: 35930297 PMCID: PMC9359195 DOI: 10.1080/0886022x.2022.2106244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/20/2022] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVES Several studies have shown that cholecalciferol supplementation (25OHD-S) in chronic kidney disease (CKD) improves kidney injury by reducing fibrosis-related vascular calcification and declining apoptosis-linked nephron damage. METHODS The oral 25OHD-S was evaluated in 60,000 IU/month/36 weeks versus in 2000 IU/d/24 weeks in CKD Stage 3 with serum 25OHD level < 20 ng/mL. The study was undertaken on 156 black subjects and 150 white subjects Southern Sahara (SS). All biomarkers of cardiometabolic (CMet) and cardiorenal (CRenal) syndrome, Renin-angiotensin-aldosterone system (RAAS) profile, secondary hyperparathyroidism (SHPT), N-terminal pro B-type natriuretic peptide (NT-proBNP), Troponin T (cTnT) and atherogenicity risk were assessed by biochemical methods. Estimate glomerular filtration rate (eGFR) by chronic CKD-EPI equation formula. Total serum vitamin D by liquid chromatography-tandem mass spectrometry (MS). RESULTS Vitamin D deficiency alters in the same manner CMet, CRenal, and others biomarkers in both groups SS; however, these disorders are more acute in blacks compared to whites SS. Oral 25OHD-S a highlighted improvement of eGFR drop, SHPT decrease, decline proteinuria, and cardiac failure risk (NT-proBNP and cTnT) attenuation. Concomitantly, 25OHD-S normalizes Renin, Aldosterone, and Angiotensin System (RAAS) activity. Nevertheless, homocysteine and Lp (a) do not modulate by 25OHD-S. CONCLUSIONS The oral vitamin D3 supplementation, according the dose, and the treatment duration does not like in black-skinned people versus to white-skinned inhabitants, while the 02 groups are native to the same Saharan environment. It emerge that a high intermittent dose through an extensive supplementation (60,000 IU/36 weeks) was more effective in black subjects. At opposite, a lower dose during a short period supplementation is sufficient (2000 IU/24 weeks) in white subjects.
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Affiliation(s)
- Asma Bouazza
- Nutrition and Dietetics in Human Pathologies Post Graduate School, Bioenergetics, Intermediary Metabolism team, Biology and Organisms Physiology laboratory, USTHB, Algiers, Algeria
| | - Amina Tahar
- Nutrition and Dietetics in Human Pathologies Post Graduate School, Bioenergetics, Intermediary Metabolism team, Biology and Organisms Physiology laboratory, USTHB, Algiers, Algeria
| | | | - Messaoud Saidani
- Clinical Nephrology Exploration Unit, Dialysis and Kidney Transplantation Unit, University Hospital Center of Beni Messous, Algiers, Algeria
| | - Elhadj-Ahmed Koceir
- Nutrition and Dietetics in Human Pathologies Post Graduate School, Bioenergetics, Intermediary Metabolism team, Biology and Organisms Physiology laboratory, USTHB, Algiers, Algeria
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Zhao H, Rasheed H, Nøst TH, Cho Y, Liu Y, Bhatta L, Bhattacharya A, Hemani G, Davey Smith G, Brumpton BM, Zhou W, Neale BM, Gaunt TR, Zheng J. Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases. CELL GENOMICS 2022; 2:None. [PMID: 36388766 PMCID: PMC9646482 DOI: 10.1016/j.xgen.2022.100195] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 06/06/2022] [Accepted: 09/21/2022] [Indexed: 11/07/2022]
Abstract
Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ancestries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease prevention across ancestries and illustrate the value of meta-analysis of biobanks in drug development.
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Affiliation(s)
- Huiling Zhao
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Humaria Rasheed
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Therese Haugdahl Nøst
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Community Medicine, UIT The Arctic University of Norway, 9037 Tromsø, Norway
| | - Yoonsu Cho
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Yi Liu
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Institute of Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Global Biobank Meta-analysis Initiative
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
- Department of Community Medicine, UIT The Arctic University of Norway, 9037 Tromsø, Norway
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Institute of Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- NIHR Bristol Biomedical Research Centre, Bristol, UK
- HUNT Research Center, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7600 Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI 48109, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Ben Michael Brumpton
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
- HUNT Research Center, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, 7600 Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Wei Zhou
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI 48109, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Tom R. Gaunt
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Brumpton BM, Graham S, Surakka I, Skogholt AH, Løset M, Fritsche LG, Wolford B, Zhou W, Nielsen JB, Holmen OL, Gabrielsen ME, Thomas L, Bhatta L, Rasheed H, Zhang H, Kang HM, Hornsby W, Moksnes MR, Coward E, Melbye M, Giskeødegård GF, Fenstad J, Krokstad S, Næss M, Langhammer A, Boehnke M, Abecasis GR, Åsvold BO, Hveem K, Willer CJ. The HUNT study: A population-based cohort for genetic research. CELL GENOMICS 2022; 2:100193. [PMID: 36777998 PMCID: PMC9903730 DOI: 10.1016/j.xgen.2022.100193] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/10/2022] [Accepted: 09/13/2022] [Indexed: 11/06/2022]
Abstract
The Trøndelag Health Study (HUNT) is a population-based cohort of ∼229,000 individuals recruited in four waves beginning in 1984 in Trøndelag County, Norway. Approximately 88,000 of these individuals have available genetic data from array genotyping. HUNT participants were recruited during four community-based recruitment waves and provided information on health-related behaviors, self-reported diagnoses, family history of disease, and underwent physical examinations. Linkage via the Norwegian personal identification number integrates digitized health care information from doctor visits and national health registries including death, cancer and prescription registries. Genome-wide association studies of HUNT participants have provided insights into the mechanism of cardiovascular, metabolic, osteoporotic, and liver-related diseases, among others. Unique features of this cohort that facilitate research include nearly 40 years of longitudinal follow-up in a motivated and well-educated population, family data, comprehensive phenotyping, and broad availability of DNA, RNA, urine, fecal, plasma, and serum samples.
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Affiliation(s)
- Ben M. Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway
| | - Sarah Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - Mari Løset
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- Department of Dermatology, Clinic of Orthopaedy, Rheumatology and Dermatology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Lars G. Fritsche
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Brooke Wolford
- Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - 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
| | - Jonas Bille Nielsen
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - Oddgeir L. Holmen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
| | - Maiken E. Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
| | - Laurent Thomas
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- Department of Clinical and Molecular Medicine, NTNU Norwegian University of Science and Technology, Trondheim, Norway
- BioCore—Bioinformatics Core Facility, NTNU Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Laxmi Bhatta
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - Humaira Rasheed
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - He Zhang
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hyun Min Kang
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Whitney Hornsby
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marta Riise Moksnes
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - Eivind Coward
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - Mads Melbye
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - Guro F. Giskeødegård
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
| | - Jørn Fenstad
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
| | - Steinar Krokstad
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
- Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Marit Næss
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim 7030, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, 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 7030, Norway
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
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Tomaszewski M, Morris AP, Howson JMM, Franceschini N, Eales JM, Xu X, Dikalov S, Guzik TJ, Humphreys BD, Harrap S, Charchar FJ. Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications. Kidney Int 2022; 102:492-505. [PMID: 35690124 PMCID: PMC9886011 DOI: 10.1016/j.kint.2022.04.045] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/10/2022] [Accepted: 04/22/2022] [Indexed: 02/06/2023]
Abstract
Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.
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Affiliation(s)
- Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK; Manchester Heart Centre and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK.
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Joanna M M Howson
- Department of Genetics, Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd, Oxford, UK
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sergey Dikalov
- Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Tomasz J Guzik
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK; Department of Internal and Agricultural Medicine, Jagiellonian University College of Medicine, Kraków, Poland
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Stephen Harrap
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Fadi J Charchar
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia; Health Innovation and Transformation Centre, School of Science, Psychology and Sport, Federation University Australia, Ballarat, Victoria, Australia; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
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Aarestrup J, Blond K, Vistisen D, Jørgensen ME, Frimodt-Møller M, Jensen BW, Baker JL. Childhood body mass index trajectories and associations with adult-onset chronic kidney disease in Denmark: A population-based cohort study. PLoS Med 2022; 19:e1004098. [PMID: 36129893 PMCID: PMC9491561 DOI: 10.1371/journal.pmed.1004098] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 08/22/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Although excess adult adiposity is a strong risk factor for chronic kidney disease (CKD), evidence for associations with early life body size is limited. We investigated whether childhood body mass index (BMI) trajectories are associated with adult-onset CKD and end-stage kidney disease (ESKD) using a population-based cohort. Further, we examined the role of adult-onset type 2 diabetes (T2D) in these associations. METHODS AND FINDINGS We included 151,506 boys and 148,590 girls from the Copenhagen School Health Records Register, born 1930 to 1987 with information on measured weights and heights at ages 6 to 15 years. Five sex-specific childhood BMI trajectories were analyzed. Information on the main outcomes CKD and ESKD, as well as T2D, came from national health registers. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were estimated using Poisson regression adjusted for year of birth. During a median of 30.8 person-years of follow-up, 5,968 men and 3,903 women developed CKD and 977 men and 543 women developed ESKD. For both sexes, the rates of CKD and ESKD increased significantly with higher child BMI trajectories in comparison with the average BMI trajectory (40% to 43% of individuals) and the below-average BMI trajectory (21% to 23% of individuals) had the lowest rates. When including T2D, most associations were significant and men (IRR = 1.39, 95% CI: 1.13 to 1.72) and women (IRR = 1.54, 95% CI: 1.28 to 1.86) with the obese childhood BMI trajectory (2% of individuals) had significantly higher CKD rates than the average BMI trajectory, whereas for ESKD, the associations were positive, but nonsignificant, for men (IRR = 1.38, 95% CI: 0.83 to 2.31) but significant for women (IRR = 1.97, 95% CI: 1.25 to 3.11) with the obese BMI trajectory. A main study limitation is the use of only hospital-based CKD diagnoses. CONCLUSIONS Individuals with childhood BMI trajectories above average had higher rates of CKD and ESKD than those with an average childhood BMI trajectory. When including T2D, most associations were significant, particularly with CKD, emphasizing the potential information that the early appearance of above-average BMI growth patterns provide in relation to adult-onset CKD beyond the information provided by T2D development.
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Affiliation(s)
- Julie Aarestrup
- Center for Clinical Research and Prevention, Copenhagen University Hospital—Bispebjerg and Frederiksberg, Frederiksberg, Denmark
| | - Kim Blond
- Center for Clinical Research and Prevention, Copenhagen University Hospital—Bispebjerg and Frederiksberg, Frederiksberg, Denmark
| | - Dorte Vistisen
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen K, Denmark
| | - Marit E. Jørgensen
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Steno Diabetes Center Greenland, Nuuk, Greenland
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | | | - Britt W. Jensen
- Center for Clinical Research and Prevention, Copenhagen University Hospital—Bispebjerg and Frederiksberg, Frederiksberg, Denmark
| | - Jennifer L. Baker
- Center for Clinical Research and Prevention, Copenhagen University Hospital—Bispebjerg and Frederiksberg, Frederiksberg, Denmark
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Kjaergaard AD, Teumer A, Witte DR, Stanzick KJ, Winkler TW, Burgess S, Ellervik C. Obesity and Kidney Function: A Two-Sample Mendelian Randomization Study. Clin Chem 2022; 68:461-472. [PMID: 34922334 PMCID: PMC7614591 DOI: 10.1093/clinchem/hvab249] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/05/2021] [Indexed: 09/12/2023]
Abstract
BACKGROUND Obesity and type 2 diabetes (T2D) are correlated risk factors for chronic kidney disease (CKD). METHODS Using summary data from GIANT (Genetic Investigation of Anthropometric Traits), DIAGRAM (DIAbetes Genetics Replication And Meta-analysis), and CKDGen (CKD Genetics), we examined causality and directionality of the association between obesity and kidney function. Bidirectional 2-sample Mendelian randomization (MR) estimated the total causal effects of body mass index (BMI) and waist-to-hip ratio (WHR) on kidney function, and vice versa. Effects of adverse obesity and T2D were examined by stratifying BMI variants by their association with WHR and T2D. Multivariable MR estimated the direct causal effects of BMI and WHR on kidney function. The inverse variance weighted random-effects MR for Europeans was the main analysis, accompanied by several sensitivity MR analyses. RESULTS One standard deviation (SD ≈ 4.8 kg/m2) genetically higher BMI was associated with decreased estimated glomerular filtration rate (eGFR) [β=-0.032 (95% confidence intervals: -0.036, -0.027) log[eGFR], P = 1 × 10-43], increased blood urea nitrogen (BUN) [β = 0.010 (0.005, 0.015) log[BUN], P = 3 × 10-6], increased urinary albumin-to-creatinine ratio [β = 0.199 (0.067, 0.332) log[urinary albumin-to-creatinine ratio (UACR)], P = 0.003] in individuals with diabetes, and increased risk of microalbuminuria [odds ratios (OR) = 1.15 [1.04-1.28], P = 0.009] and CKD [1.13 (1.07-1.19), P = 3 × 10-6]. Corresponding estimates for WHR and for trans-ethnic populations were overall similar. The associations were driven by adverse obesity, and for microalbuminuria additionally by T2D. While genetically high BMI, unlike WHR, was directly associated with eGFR, BUN, and CKD, the pathway to albuminuria was likely through T2D. Genetically predicted kidney function was not associated with BMI or WHR. CONCLUSIONS Genetically high BMI is associated with impaired kidney function, driven by adverse obesity, and for albuminuria additionally by T2D.
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Affiliation(s)
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany, and DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Daniel R. Witte
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark, and Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Kira-Julia Stanzick
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, and Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge
| | - Christina Ellervik
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200, Denmark; Department of Data and Development, Sorø, Region Zealand, Denmark; Department of Pathology, Harvard Medical School, Boston, MA-02215, USA; and Department of Laboratory Medicine, Boston Children’s Hospital, Boston, MA-02215, USA
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Gao L, Wang K, Ni QB, Fan H, Zhao L, Huang L, Yang M, Li H. Educational Attainment and Ischemic Stroke: A Mendelian Randomization Study. Front Genet 2022; 12:794820. [PMID: 35222520 PMCID: PMC8876515 DOI: 10.3389/fgene.2021.794820] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/24/2021] [Indexed: 11/25/2022] Open
Abstract
Observational studies have evaluated the potential association of socioeconomic factors such as higher education with the risk of stroke but reported controversial findings. The objective of our study was to evaluate the potential causal association between higher education and the risk of stroke. Here, we performed a Mendelian randomization analysis to evaluate the potential association of educational attainment with ischemic stroke (IS) using large-scale GWAS datasets from the Social Science Genetic Association Consortium (SSGAC, 293,723 individuals), UK Biobank (111,349 individuals), and METASTROKE consortium (74,393 individuals). We selected three Mendelian randomization methods including inverse-variance-weighted meta-analysis (IVW), weighted median regression, and MR–Egger regression. IVW showed that each additional 3.6-year increase in years of schooling was significantly associated with a reduced IS risk (OR = 0.54, 95% CI: 0.41–0.71, and p = 1.16 × 10–5). Importantly, the estimates from weighted median (OR = 0.49, 95% CI: 0.33–0.73, and p = 1.00 × 10–3) and MR–Egger estimate (OR = 0.18, 95% CI: 0.06–0.60, and p = 5.00 × 10–3) were consistent with the IVW estimate in terms of direction and magnitude. In summary, we provide genetic evidence that high education could reduce IS risk.
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Affiliation(s)
- Luyan Gao
- Department of Neurology, Tianjin Fourth Central Hospital, The Fourth Central Hospital Affilicated to Nankai University, The Fourth Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Kun Wang
- Taishan Academy of Medical Sciences, Taian City Central Hospital, Taian, China
| | - Qing-Bin Ni
- Taishan Academy of Medical Sciences, Taian City Central Hospital, Taian, China
| | - Hongguang Fan
- Department of Neurology, Tianjin Fourth Central Hospital, The Fourth Central Hospital Affilicated to Nankai University, The Fourth Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Lan Zhao
- Department of Neurology, Tianjin Fourth Central Hospital, The Fourth Central Hospital Affilicated to Nankai University, The Fourth Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Lei Huang
- Department of Neurology, Tianjin Fourth Central Hospital, The Fourth Central Hospital Affilicated to Nankai University, The Fourth Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Mingfeng Yang
- Second Affiliated Hospital, Brain Science Institute, Key Laboratory of Cerebral Microcirculation in Universities of Shandong, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian, China
- *Correspondence: Mingfeng Yang, ; Huanming Li,
| | - Huanming Li
- Department of Cardiovascular, Tianjin Fourth Central Hospital, The Fourth Central Hospital Affilicated to Nankai University, The Fourth Central Clinical College of Tianjin Medical University, Tianjin, China
- *Correspondence: Mingfeng Yang, ; Huanming Li,
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Xie Y, Qi H, Li B, Wen F, Zhang F, Guo C, Zhang L. Serum lipoprotein (a) associates with the risk of renal function damage in the CHCN-BTH Study: Cross-sectional and Mendelian randomization analyses. Front Endocrinol (Lausanne) 2022; 13:1023919. [PMID: 36506069 PMCID: PMC9727385 DOI: 10.3389/fendo.2022.1023919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 10/28/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Evidence regarding the effects of lipoprotein (a) [lp(a)] and renal function remains unclear. The present study aimed to explore the causal association of serum lp(a) with renal function damage in Chinese general adults. METHODS A total of 25343 individuals with available lp(a) data were selected from the baseline survey of the Cohort Study on Chronic Disease of Communities Natural Population in Beijing, Tianjin, and Hebei (CHCN-BTH). Five renal function indexes [estimated glomerular filtration rate (eGFR), serum creatinine (Scr), blood urea nitrogen (BUN), uric acid (UA), high-sensitivity C-reactive protein(CRPHS)] were analyzed. The restricted cubic spline (RCS) method, logistic regression, and linear regression were used to test the dose-response association between lp(a) and renal function. Stratified analyses related to demographic characteristics and disease status were performed. Two-sample Mendelian randomization (MR) analysis was used to obtain the causal association of lp(a) and renal function indexes. Genotyping was accomplished by MassARRAY System. RESULTS Lp(a) levels were independently associated with four renal function indexes (eGFR, Scr, BUN, CRPHS). Individuals with a higher lp(a) level had a lower eGFR level, and the association with Scr estimated GFR was stronger in individuals with a lower lp(a) level (under 14 mg/dL). . The association was similar in individuals regardless of diabetes or hypertension. MR analysis confirmed the causal association of two renal function indexes (Scr and BUN). For MR analysis, each one unit higher lp(a) was associated with 7.4% higher Scr (P=0.031) in the inverse-variance weighted method. But a causal effect of genetically increased lp(a) level with increased eGFR level which contrasted with our observational results was observed. CONCLUSION The observational and causal effect of lp(a) on Scr and BUN were founded, suggesting the role of lp(a) on the risk of renal function damage in general Chinese adults.
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