scholarly journals Phenome-wide association study of a comprehensive health check-up database in a Korea population: Clinical application & trans-ethnic comparison

2020 ◽  
Author(s):  
Eun Kyung Choe ◽  
Manu Shivakumar ◽  
Anurag Verma ◽  
Shefali Setia Verma ◽  
Seung Ho Choi ◽  
...  
Keyword(s):  
Association Study ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
International Classification Of Diseases ◽  
European Population ◽  
Health Check ◽  
Phenotype Definition ◽  
Multiple Phenotypes ◽  
Comprehensive Health ◽  
The Uk

AbstractsBackgroundThe expanding use of the phenome-wide association study (PheWAS) faces challenges in the context of using International Classification of Diseases billing codes for phenotype definition, imbalanced study population ethnicity, and constrained application of the results to clinical practice or research.MethodsWe performed a PheWAS utilizing deep phenotypes corroborated by comprehensive health check-ups in a Korean population, along with trans-ethnic comparisons through the UK Biobank and Biobank Japan Project. Network analysis, visualization of cross-phenotype mapping, and causal inference mapping with Mendelian randomization were conducted in order to make robust, clinically applicable interpretations.ResultsOf the 136 phenotypes extracted from the health check-up database, the PheWAS associated 65 phenotypes with 14,101 significant variants (P < 4.92×10−10). In the association study for body mass index, our population showed 583 exclusive loci relative to the Japanese population and 669 exclusive loci relative to the European population. In the meta-analysis with Korean and Japanese populations, 72.5% of phenotypes had uniquely significant variants. Tumor markers and hematologic phenotypes had a high degree of phenotype-phenotype pairs. By Mendelian randomization, one skeletal muscle mass phenotype was causal and two were outcomes. Among phenotype pairs from the genotype-driven cross-phenotype associations, 71.65% also demonstrated penetrance in correlation analysis using a clinical database.ConclusionsThis comprehensive analysis of PheWAS results based on a health check-up database will provide researchers and clinicians with a panoramic overview of the networks among multiple phenotypes and genetic variants, laying groundwork for the practical application of precision medicine.

scholarly journals Genome-Wide Association Meta-Analysis Supports Genes Involved in Valve and Cardiac Development to Associate With Mitral Valve Prolapse

2021 ◽  
Author(s):  
Mengyao Yu ◽  
Sergiy Kyryachenko ◽  
Stephanie Debette ◽  
Philippe Amouyel ◽  
Jean-Jacques Schott ◽  
...  
Keyword(s):  
Mitral Valve ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Cardiac Development ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Additional Risk ◽  
Genome Wide ◽  
The Uk

Background: Mitral valve prolapse (MVP) is a common cardiac valve disease, which affects 1 in 40 in the general population. Previous genome-wide association study have identified 6 risk loci for MVP. But these loci explained only partially the genetic risk for MVP. We aim to identify additional risk loci for MVP by adding data set from the UK Biobank. Methods: We reanalyzed 1007/479 cases from the MVP-France study, 1469/862 controls from the MVP-Nantes study for reimputation genotypes using HRC and TOPMed panels. We also incorporated 434 MVP cases and 4527 controls from the UK Biobank for discovery analyses. Genetic association was conducted using SNPTEST and meta-analyses using METAL. We used FUMA for post-genome-wide association study annotations and MAGMA for gene-based and gene-set analyses. Results: We found TOPMed imputation to perform better in terms of accuracy in the lower ranges of minor allele frequency below 0.1. Our updated meta-analysis included UK Biobank study for ≈8 million common single-nucleotide polymorphisms (minor allele frequency >0.01) and replicated the association on Chr2 as the top association signal near TNS1 . We identified an additional risk locus on Chr1 ( SYT2 ) and 2 suggestive risk loci on chr8 ( MSRA ) and chr19 ( FBXO46 ), all driven by common variants. Gene-based association using MAGMA revealed 6 risk genes for MVP with pronounced expression levels in cardiovascular tissues, especially the heart and globally part of enriched GO terms related to cardiac development. Conclusions: We report an updated meta-analysis genome-wide association study for MVP using dense imputation coverage and an improved case-control sample. We describe several loci and genes with MVP spanning biological mechanisms highly relevant to MVP, especially during valve and heart development.

Abstract P147: Genome Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases Using the UK Biobank Data

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Yanjun Guo ◽  
Wonil Chung ◽  
Zhilei Shan ◽  
Liming Liang
Keyword(s):  
Cardiovascular Diseases ◽  
Genetic Correlation ◽  
Multiple Testing ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Uk Biobank ◽  
Increased Risk ◽  
The Uk ◽  
Cardiovascular Traits ◽  
Shared Genetic

Background: Patients with RA have a 2-10 folds increased risk of cardiovascular diseases (CVD) and CVD accounts for almost 50% of the excess mortality in patients with RA when compared with general population, but the mechanisms underlying such associations are largely unknown. Methods: We examined the genetic correlation, causality, and shared genetic variants between RA (Ncase=6,756, Ncontrol=452,476) and CVD (Ncase=44,246, Ncontrol=414,986) using LD Score regression (LDSC), generalized summary-data-based Mendelian Randomization (GSMR), and cross-trait meta-analysis in the UK Biobank Data. Results: In the present study, RA was significantly genetically correlated with MI, angina, CHD, and CVD after correcting for multiple testing (Rg ranges from 0.40 to 0.43, P<0.05/5). Interestingly, when stratified by frequent usage of aspirin and paracetamol, we observed increased genetic correlation between RA and CVD for participants without aspirin usage ( Rg increased to 0.54 [95%CI: 0.54, 0.78] for angina; P value=6.69х10 -6 ), and for participants with usage of paracetamol ( Rg increased to 0.75 [95%CI: 0.20, 1.29] for MI; P value=8.90х10 -3 ). Cross-trait meta-analysis identified 9 independent loci that were shared between RA and at least one of the genetically correlated CVD traits including PTPN22 at chr1p13.2 , BCL2L11 at chr2q13 , and CCR3 at chr3p21.31 ( P single trait <1х10 -3 and P meta <5х10 -8 ) highlighting potential shared etiology between them which include accelerating atherosclerosis and upregulating oxidative stress and vascular permeability. Finally, Mendelian randomization analyses observed inconsistent instrumental effects and were unable to conclude the causality and directionality between RA and CVD. Conclusion: Our results supported positive genetic correlation between RA and multiple cardiovascular traits, and frequent usage of aspirin and paracetamol may modify their associations, but instrumental analyses were unable to conclude the causality and directionality between them.

scholarly journals Bayesian mixture model for clustering rare-variant effects in human genetic studies

2021 ◽  
Author(s):  
Guhan Ram Venkataraman ◽  
Yosuke Tanigawa ◽  
Matti Pirinen ◽  
Manuel A Rivas
Keyword(s):  
Mixture Model ◽  
Rare Variant ◽  
Rare Variants ◽  
Meta Analysis ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Multiple Phenotypes ◽  
Aggregation Techniques ◽  
Bayesian Mixture ◽  
The Uk

Rare-variant aggregate analysis from exome and whole genome sequencing data typically summarizes with a single statistic the signal for a gene or the unit that is being aggre- gated. However, when doing so, the effect profile within the unit may not be easily characterized across one or multiple phenotypes. Here, we present an approach we call Multiple Rare-Variants and Phenotypes Mixture Model (MRPMM), which clusters rare variants into groups based on their effects on the multivariate phenotype and makes statistical inferences about the properties of the underlying mixture of genetic effects. Using summary statistic data from a meta-analysis of exome sequencing data of 184,698 individuals in the UK Biobank across 6 populations, we demonstrate that our mixture model can identify clusters of variants responsible for significantly disparate effects across a multivariate phenotype; we study three lipid and three renal traits separately. The method is able to estimate (1) the proportion of non-null variants, (2) whether variants with the same predicted consequence in one gene behave similarly, (3) whether variants across genes share effect profiles across the multivariate phenotype, and (4) whether different annotations differ in the magnitude of their effects. As rare-variant data and aggregation techniques become more common, this method can be used to ascribe further meaning to association results.

scholarly journals Causal effect of atrial fibrillation/flutter on chronic kidney disease: A bidirectional two-sample Mendelian randomization study

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261020
Author(s):  
Masahiro Yoshikawa ◽  
Kensuke Asaba ◽  
Tomohiro Nakayama
Keyword(s):  
Atrial Fibrillation ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
European Population ◽  
Genome Wide Association Studies ◽  
The Uk

Chronic kidney disease (CKD) and atrial fibrillation are both major burdens on the health care system worldwide. Several observational studies have reported clinical associations between CKD and atrial fibrillation; however, causal relationships between these conditions remain to be elucidated due to possible bias by confounders and reverse causations. Here, we conducted bidirectional two-sample Mendelian randomization analyses using publicly available summary statistics of genome-wide association studies (the CKDGen consortium and the UK Biobank) to investigate causal associations between CKD and atrial fibrillation/flutter in the European population. Our study suggested a causal effect of the risk of atrial fibrillation/flutter on the decrease in serum creatinine-based estimated glomerular filtration rate (eGFR) and revealed a causal effect of the risk of atrial fibrillation/flutter on the risk of CKD (odds ratio, 9.39 per doubling odds ratio of atrial fibrillation/flutter; 95% coefficient interval, 2.39–37.0; P = 0.001), while the causal effect of the decrease in eGFR on the risk of atrial fibrillation/flutter was unlikely. However, careful interpretation and further studies are warranted, as the underlying mechanisms remain unknown. Further, our sample size was relatively small and selection bias was possible.

scholarly journals High Level of Uromodulin Increases the Risk of Hypertension: A Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Ruilian You ◽  
Lanlan Chen ◽  
Lubin Xu ◽  
Dingding Zhang ◽  
Haitao Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Inverse Variance ◽  
The Uk ◽  
High Level

Background: The association of uromodulin and hypertension has been observed in clinical studies, but not proven by a causal relationship. We conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between uromodulin and blood pressure.Methods: We selected single nucleotide polymorphisms (SNPs) related to urinary uromodulin (uUMOD) and serum uromodulin (sUMOD) from a large Genome-Wide Association Studies (GWAS) meta-analysis study and research in PubMed. Six datasets based on the UK Biobank and the International Consortium for Blood Pressure (ICBP) served as outcomes with a large sample of hypertension (n = 46,188), systolic blood pressure (SBP, n = 1,194,020), and diastolic blood pressure (DBP, n = 1,194,020). The inverse variance weighted (IVW) method was performed in uUMOD MR analysis, while methods of IVW, MR-Egger, Weighted median, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were utilized on sUMOD MR analysis.Results: MR analysis of IVM showed the odds ratio (OR) of the uUMOD to hypertension (“ukb-b-14057” and “ukb-b-14177”) is 1.04 (95% Confidence Interval (CI), 1.03-1.04, P &lt; 0.001); the effect sizes of the uUMOD to SBP are 1.10 (Standard error (SE) = 0.25, P = 8.92E-06) and 0.03 (SE = 0.01, P = 2.70E-04) in “ieu-b-38” and “ukb-b-20175”, respectively. The β coefficient of the uUMOD to DBP is 0.88 (SE = 0.19, P = 4.38E-06) in “ieu-b-39” and 0.05 (SE = 0.01, P = 2.13E-10) in “ukb-b-7992”. As for the sUMOD, the OR of hypertension (“ukb-b-14057” and “ukb-b-14177”) is 1.01 (95% CI 1.01–1.02, all P &lt; 0.001). The β coefficient of the SBP is 0.37 (SE = 0.07, P = 1.26E-07) in “ieu-b-38” and 0.01 (SE = 0.003, P = 1.04E-04) in “ukb-b-20175”. The sUMOD is causally associated with elevated DBP (“ieu-b-39”: β = 0.313, SE = 0.050, P = 3.43E-10; “ukb-b-7992”: β = 0.018, SE = 0.003, P = 8.41E-09).Conclusion: Our results indicated that high urinary and serum uromodulin levels are potentially detrimental in elevating blood pressure, and serve as a causal risk factor for hypertension.

scholarly journals Effect of n-3 polyunsaturated fatty acids on ischemic heart disease and cardiometabolic risk factors: a two-sample Mendelian randomization study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bayi Xu ◽  
Zhixia Xu ◽  
Duanmin Xu ◽  
Xuerui Tan
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Blood Pressure ◽  
Fatty Acids ◽  
Cardiometabolic Risk ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Cardiometabolic Risk Factors ◽  
Uk Biobank ◽  
The Uk

Abstract Background The cardioprotective ability of n-3 polyunsaturated fatty acids (PUFAs) is controversial. Most studies suggest a specific role for PUFAs in cardioprotection from ischemic heart disease (IHD). However, few studies have used genetic biomarkers of n-3 PUFAs to examine their potential relationships with IHD. This study aimed to use Mendelian randomization to evaluate whether genetically-predicted n-3 PUFAs affect IHD and cardiometabolic risk factors (CRFs). Methods Genetic variants strongly (p < 5 × 10–8) and independently (r2 > 0.1) associated with n-3 PUFAs were derived from the CHARGE Consortium (including 8,866 subjects of European ancestry) and were used as instrumental variables (IVs) for evaluating the effect of n-3 PUFAs, including α-linolenic acid (ALA), docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), and eicosapentaenoic acid (EPA). Data on the associations between the IVs and IHD, myocardial infarction, and CRFs (including diabetes, lipids, blood pressure, body mass index, and waist-to-hip ratio (WHR)) were obtained from the UK Biobank SOFT CAD GWAS with the CARDIoGRAMplusC4D 1000 Genomes-based GWAS (113,937 IHD cases and 339,115 controls), the Myocardial Infarction Genetics and CARDIoGRAM Exome consortia (42,335 MI cases and 78,240 controls), the DIAbetes Genetics Replication And Meta-analysis consortium (26,676 diabetes mellitus cases and 132,532 controls), the Global Lipids Genetics Consortium (n = 196,475), the International Consortium for Blood Pressure (n = 69,395), and the meta-analysis of GWAS for body fat distribution in the UK Biobank and Genetic Investigation of Anthropometric Traits (n = 694,649). Results Genetically-predicted higher ALA was associated with lower risk of IHD, type 2 diabetes (T2D), and lower serum lipids. The effect size per 0.05-unit increase (about 1 standard deviation) in plasma ALA level) was − 1.173 (95% confidence interval − 2.214 to − 0.133) for IHD. DPA and EPA had no association with IHD but were associated with a higher risk of T2D, higher levels of lipids or WHR. DHA had no association with IHD or CRFs. Conclusions Our study suggests a benefit of ALA for IHD and its main risk factors. DHA, DPA, and EPA had no association with IHD but were partly associated with increasing cardiometabolic risk factors.

scholarly journals The Causal Effects of Insomnia on Bipolar Disorder, Depression, and Schizophrenia: A Two-Sample Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Peng Huang ◽  
Yixin Zou ◽  
Xingyu Zhang ◽  
Xiangyu Ye ◽  
Yidi Wang ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorder ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Treatment Strategies ◽  
European Population ◽  
Sensitivity Analyses ◽  
Causal Mechanism ◽  
Assumption Violations

Psychiatric disorder, including bipolar disorder (BD), major depression (MDD), and schizophrenia (SCZ), affects millions of persons around the world. Understanding the disease causal mechanism underlying the three diseases and identifying the modifiable risk factors for them hold the key for the development of effective preventative and treatment strategies. We used a two-sample Mendelian randomization method to assess the causal effect of insomnia on the risk of BD, MDD, and SCZ in a European population. We collected one dataset of insomnia, three of BD, one of MDD, and three of SCZ and performed a meta-analysis for each trait, further verifying the analysis through extensive complementarity and sensitivity analysis. Among the three psychiatric disorders, we found that only insomnia is causally associated with MDD and that higher insomnia increases the risk of MDD. Specifically, the odds ratio of MDD increase of insomnia is estimated to be 1.408 [95% confidence interval (CI): 1.210–1.640, p = 1.03E-05] in the European population. The identified causal relationship between insomnia and MDD is robust with respect to the choice of statistical methods and is validated through extensive sensitivity analyses that guard against various model assumption violations. Our results provide new evidence to support the causal effect of insomnia on MDD and pave ways for reducing the psychiatric disorder burden.

Circulating galectin-3 levels are not associated with non-alcoholic fatty liver disease: A Mendelian randomization study

2021 ◽  
Author(s):  
Maxime Tremblay ◽  
Nicolas Perrot ◽  
Nooshin Ghodsian ◽  
Émilie Gobeil ◽  
Christian Couture ◽  
...  
Keyword(s):  
Mendelian Randomization ◽  
Meta Analysis ◽  
Human Diseases ◽  
Genome Wide Association ◽  
Causal Association ◽  
Uk Biobank ◽  
Alcoholic Fatty Liver ◽  
Genome Wide ◽  
Galectin 3 ◽  
The Uk

Abstract Context The impact of galectin-3 inhibitors on non-alcoholic fatty liver diseases (NAFLD)-related outcomes is currently under investigation in randomized clinical trials. Whether there is a causal association between plasma galectin-3 levels and NAFLD is unknown. Objective To evaluate the causal effect of circulating galectin-3 levels on NAFLD as well as &gt;800 other human diseases. Design Inverse variance weighted Mendelian randomization (IVW-MR) and phenome-wide MR. Setting Summary statistics of genome-wide association studies. Patients Participants of the UK Biobank, eMERGE, FinnGen, PREVEND and IMPROVE cohorts. Intervention Identification of independent single-nucleotide polymorphisms (SNPs) associated with galectin-3 levels (p&lt;5x10 -8) in the PREVEND (14 SNPs) and IMPROVE (3 SNPs) cohorts. Main outcome measures: Presence of NAFLD in a meta-analysis of genome-wide association study of the eMERGE, UK Biobank and FinnGen cohorts (3042 NAFLD cases and 504,853 controls), as well as &gt;800 other human diseases in the UK Biobank and FinnGen. Results Using IVW-MR, we found no causal association between galectin-3 levels and NAFLD in the meta-analysis of the 3 cohorts or in each individual cohort. After correction for multiple testing, we found no causal association between galectin-3 levels and &gt;800 human disease-related traits. Conclusions This MR study revealed no causal associations between circulating galectin-3 levels and NAFLD or any other disease traits, suggesting that plasma galectin-3 levels may not be directly implicated in the pathogenesis of NAFLD or other human diseases.

Genome-wide association meta-analysis in 652,134 participants identifies 9 novel susceptibility loci for aortic stenosis

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
H.Y Chen ◽  
A.M Small ◽  
C Dina ◽  
B.J Cairns ◽  
R.A Whitmer ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Association Study ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Public Institution ◽  
Pharmacological Intervention ◽  
Funding Source ◽  
Polygenic Risk ◽  
Gene Set ◽  
Genome Wide

Abstract Background Aortic stenosis (AS) is the most common form of incident valvular heart disease. While valve replacement is effective, the absence of an approved medical therapy provides no alternatives to patients with contraindications or mild disease. An improved understanding of the genetics of AS could identify targets for pharmacological intervention. Methods An inverse variance-weighted, fixed effects meta-analysis of the association of 11,591,806 variants with AS was undertaken using data from 10 European cohorts totalling 652,134 participants (13,758 cases of AS). We queried publicly available datasets to characterize the functional consequences of genome-wide significant variants, conducted a phenome-wide association study to assess their association with other outcomes, and constructed polygenic risk scores to examine their association with AS. We also performed gene- and gene-set enrichment analyses, estimated genetic correlation with cardiovascular traits, and assessed whether five lipid or immunological biomarkers were causally associated with AS using Mendelian randomization. Results Eighteen independent variants at 16 loci attained genome-wide significance in the meta-analysis, including variants at all seven previously reported loci. Many of the significant variants were intronic or intergenic, and the phenome-wide association study revealed extensive pleiotropy with apolipoprotein B, C-reactive protein, and other cardiovascular and immunological traits. A weighted polygenic risk score composed of the 18 variants was strongly associated with AS (adjusted OR per SD, 1.38; 95% CI, 1.33 to 1.44; p=4.6×10–57), and improved the discriminatory ability for AS when added to a model that contained clinical risk factors (difference in the area under the curve p=2.0×10–11). Gene-based approaches indicated higher IL6R expression in the blood among AS cases compared to controls (p=3.1×10–6), and the association of LDLR with AS (p=2.3×10–10). Gene set analyses revealed that genes bound by the transcription factor TCF7 or micro-RNAs miR-21, miR-219, miR-491, and miR-19 were differentially expressed in the liver depending on AS status (p≤5.7×10–4), suggesting disease development may be mediated by tissue-specific transcriptional and post-transcriptional regulation. Mendelian randomization supported a causal association of five lipid and immunological biomarkers with AS, including low-density lipoprotein cholesterol (OR per mmol/L, 1.61; 95% CI, 1.48 to 1.75; p=1.3×10–30). Conclusions Evidence from large-scale genetic analyses indicate that lipid metabolism, inflammation, and calcification are key contributors to AS. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Canadian Institutes of Health Research, National Institutes of Health

scholarly journals Causal effects of education on chronic kidney disease: a Mendelian randomization study

2020 ◽  
Author(s):  
Sehoon Park ◽  
Soojin Lee ◽  
Yaerim Kim ◽  
Yeonhee Lee ◽  
Min Woo Kang ◽  
...  
Keyword(s):  
Higher Education ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Causal Effects ◽  
Genome Wide Association ◽  
Uk Biobank ◽  
Education Attainment ◽  
Genome Wide ◽  
Higher Education Attainment ◽  
The Uk

Abstract Background Poor socio-economic status, including low education attainment, has been reported in chronic kidney disease (CKD) patients. We aimed to investigate the causal effects of education attainment on the risk of CKD. Methods The study was an observational cohort study including Mendelian randomization (MR) analysis. First, the clinical association between education attainment years as the exposure and prevalent CKD Stages 3–5 as the outcome was investigated by multivariable logistic regression in 308 741 individuals 40–69 years of age from the UK Biobank. MR analysis was performed with a previously reported genetic instrument from a genome-wide association meta-analysis of education attainment. Two-sample MR was performed with summary statistics for CKD in 567 460 individuals with European ancestry in the CKDGen genome-wide association meta-analysis. The findings were replicated by allele score–based MR in 321 260 individuals of white British ancestry in the UK Biobank with quality-controlled genetic data. Results Higher education attainment was significantly associated with lower adjusted odds for CKD in the clinical analysis {&gt;17 years versus &lt;16 years, adjusted odds ratio [OR] 0.910 [95% confidence interval (CI) 0.849–0.975]}. The causal estimates obtained by the inverse variance method in the two-sample MR indicated that higher genetically predicted education attainment causally reduced the risk of CKD [OR 0.934 (95% CI 0.873–0.999)]. Allele score–based MR also supported that higher education attainment was causally linked to a decreased risk of CKD [adjusted OR 0.944 (95% CI 0.922–0.966)]. Conclusion The study suggests that higher education attainment causally reduces the risk of CKD development in the general population.

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