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Teixeira SK, Rossi FPN, Patane JL, Neyra JM, Jensen AVV, Horta BL, Pereira AC, Krieger JE. Assessing the predictive efficacy of European-based systolic blood pressure polygenic risk scores in diverse Brazilian cohorts. Sci Rep 2024; 14:28123. [PMID: 39548300 PMCID: PMC11568199 DOI: 10.1038/s41598-024-79683-7] [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: 03/02/2024] [Accepted: 11/11/2024] [Indexed: 11/17/2024] Open
Abstract
Despite the identification of numerous genetic variants affecting SBP in European populations, their applicability in admixed populations remains unclear. This study evaluates the predictive efficacy of a systolic blood pressure (SBP) polygenic risk score (PRS), derived from the UK Biobank data, in two Brazilian cohorts. We analyzed 944 K genetic variants consistent across an independent UK Biobank dataset, Brazilian cohorts, and HapMap database. Results show a significant association between increased PRS and SBP, as well as hypertension, in each study groups analyzed. An increase of one standard deviation in the PRS showed a significant association with SBP (β [95% CI] (mmHg) = 5.2 [5.1-5.3], 2.8 [2.1-3.5] and 2.6 [2.2-3.0]) and hypertension (odds ratio (OR) [95% CI] = 1.56 [1.54-1.56], 1.28 [1.2-1.4] and 1.47 [1.3-1.6]) in an independent UKB dataset, Baependi, and Pelotas, respectively. The associations were weaker in the Brazilian samples and the reduced association was noticeable in the Pelotas vs. the UK comparison for hypertension stages 1 and 2 (OR [95% CI] = 2.1 [1.5-3.1] and 3.0 [1.9-4.7] vs. 2.5 [2.2-2.8] and 4.9 [4.4-5.6]), whereas the Baependi data showed no significance for stage 1 hypertension. This trend mirrors findings in homogeneous African and Asian populations with diverse genetic architecture, highlighting the limitations of European-based PRS also in admixed populations. These insights are crucial for developing tailored disease prevention and management strategies in ethnically diverse groups.
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Affiliation(s)
- Samantha K Teixeira
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil.
| | - Fernando P N Rossi
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
| | - José L Patane
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Jennifer M Neyra
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Ana Vitória V Jensen
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Bernardo L Horta
- Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Alexandre C Pereira
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Jose E Krieger
- Laboratório de Genética e Cardiologia Molecular, Faculdade de Medicina, Instituto do Coração, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, SP, Brazil.
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102
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Yu C, Jiang S, Lv B, Deng X, Xu D. Dissecting the association between blood pressure traits, hypertension, antihypertensive medications and epilepsy: A Mendelian randomization study. Epilepsy Behav 2024; 161:110140. [PMID: 39541744 DOI: 10.1016/j.yebeh.2024.110140] [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: 06/28/2024] [Revised: 10/03/2024] [Accepted: 11/02/2024] [Indexed: 11/16/2024]
Abstract
BACKGROUND Observational studies suggest that hypertension and epilepsy have a high co-occurrence, and antihypertensive medications may have impacts on the prevention and treatment of epilepsy. However, the directionality of causation between them is elusive. METHOD By leveraging genome-wide association studies (GWAS) summary data of each trait, we firstly performed bidirectional univariate Mendelian randomization (UVMR) to assess the strength and direction of the associations between pairs of traits, then multivariate MR (MVMR) was conducted to adjust for potential confounders in causalities. Cochran's Q statistics, leave-one-out analysis, MR-Egger regression and MR-Pleiotropy Residual Sum and Outlier methods (MR-PRESSO) were employed to evaluate the robustness of the results. Drug target MR was proceeded to assess the association between five classes of first-line antihypertensive medications and epilepsy. Specifically, single nucleotide polymorphisms (SNPs) extracted from GWAS data on systolic blood pressure (SBP)/diastolic blood pressure (DBP), along with expression quantitative trait loci (eQTL) were utilized as proxies for antihypertensive medications, respectively. RESULTS Forward UVMR results provided evidence that genetically predicted blood pressure traits and hypertension have causal effects on epilepsy, while reverse UVMR indicated no causal impacts of epilepsy on blood pressure traits or hypertension. The sensitivity analysis results were robust. The causalities between DBP, hypertension and epilepsy remained remarkable after adjustment by MVMR. Inverse-variance-weighted MR (IVW-MR) yielded evidence of positive association only between Beta-Blockers target genes based on DBP GWAS screening and epilepsy. Summary-data-based MR (SMR) identified a positive correlation between Beta-Blockers target gene ADRA1D and epilepsy risk. CONCLUSIONS Hypertension has a causal effect on epilepsy and managing DBP in patients with hypertension through Beta-Blockers may help prevent epilepsy.
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Affiliation(s)
- Cheng Yu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shijiu Jiang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bingjie Lv
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuejun Deng
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Da Xu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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103
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Koskeridis F, Fancy N, Tan PF, Meena D, Evangelou E, Elliott P, Wang D, Matthews PM, Dehghan A, Tzoulaki I. Multi-trait association analysis reveals shared genetic loci between Alzheimer's disease and cardiovascular traits. Nat Commun 2024; 15:9827. [PMID: 39537608 PMCID: PMC11561119 DOI: 10.1038/s41467-024-53452-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 10/14/2024] [Indexed: 11/16/2024] Open
Abstract
Several cardiovascular traits and diseases co-occur with Alzheimer's disease. We mapped their shared genetic architecture using multi-trait genome-wide association studies. Subsequent fine-mapping and colocalisation highlighted 16 genetic loci associated with both Alzheimer's and cardiovascular diseases. We prioritised rs11786896, which colocalised with Alzheimer's disease, atrial fibrillation and expression of PLEC in the heart left ventricle, and rs7529220, which colocalised with Alzheimer's disease, atrial fibrillation and expression of C1Q family genes. Single-cell RNA-sequencing data, co-expression network and protein-protein interaction analyses provided evidence for different mechanisms of PLEC, which is upregulated in left ventricular endothelium and cardiomyocytes with heart failure and in brain astrocytes with Alzheimer's disease. Similar common mechanisms are implicated for C1Q in heart macrophages with heart failure and in brain microglia with Alzheimer's disease. These findings highlight inflammatory and pleomorphic risk determinants for the co-occurrence of Alzheimer's and cardiovascular diseases and suggest PLEC, C1Q and their interacting proteins as potential therapeutic targets.
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Affiliation(s)
- Fotios Koskeridis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.
- UK Dementia Research Institute, Imperial College London, London, UK.
| | - Nurun Fancy
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Pei Fang Tan
- Institute for Human Development and Potential, Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Devendra Meena
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Dennis Wang
- Institute for Human Development and Potential, Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Paul M Matthews
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
- Systems Biology, Biomedical Research Institute of the Academy of Athens, Athens, Greece
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104
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Du Rietz E, Xie T, Wang R, Cheesman R, Garcia-Argibay M, Dong Z, Zhang J, Niebuur J, Vos M, Snieder H, Larsson H, Hartman CA. The contribution of attention-deficit/hyperactivity disorder polygenic load to metabolic and cardiovascular health outcomes: a large-scale population and sibling study. Transl Psychiatry 2024; 14:470. [PMID: 39537628 PMCID: PMC11561358 DOI: 10.1038/s41398-024-03178-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 10/14/2024] [Accepted: 11/05/2024] [Indexed: 11/16/2024] Open
Abstract
Emerging evidence suggests that ADHD is associated with increased risk for metabolic and cardiovascular (cardiometabolic) diseases. However, an understanding of the mechanisms underlying these associations is still limited. In this study we estimated the associations of polygenic scores (PGS) for ADHD with several cardiometabolic diseases and biomarkers. Furthermore, we investigated to what extent the PGS effect was influenced by direct and indirect genetic effects (i.e., shared familial effects). We derived ADHD-PGS in 50,768 individuals aged 18-90 years from the Dutch Lifelines Cohort study. Using generalised estimating equations, we estimated the association of PGS with cardiometabolic diseases, derived from self-report and several biomarkers measured during a physical examination. We additionally ran within-sibling PGS analyses, using fixed effects models, to disentangle direct effects of individuals' own ADHD genetic risk from confounding due to indirect genetic effects of relatives, as well as population stratification. We found that higher ADHD-PGS were statistically significantly associated with several cardiometabolic diseases (R-squared [R2] range = 0.03-0.50%) and biomarkers (related to inflammation, blood pressure, lipid metabolism, amongst others) (R2 range = 0.01-0.16%) (P < 0.05). Adjustment for shared familial factors attenuated the associations between ADHD-PGS and cardiometabolic outcomes (on average 56% effect size reduction), and significant associations only remained for metabolic disease. Overall our findings suggest that increased genetic liability for ADHD confers a small but significant risk increase for cardiometabolic health outcomes in adulthood. These associations were observable in the general population, even in individuals without ADHD diagnosis, and were partly explained by familial factors shared among siblings.
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Affiliation(s)
- Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
| | - Tian Xie
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rujia Wang
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rosa Cheesman
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Miguel Garcia-Argibay
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Zihan Dong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Jia Zhang
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Shenzhen Center for Chronic Disease Control, Shenzhen, Guangdong, China
| | - Jacobien Niebuur
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Melissa Vos
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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105
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Liu L, Henry J, Liu Y, Jouve C, Hulot JS, Georges A, Bouatia-Naji N. LRP1 Repression by SNAIL Results in ECM Remodeling in Genetic Risk for Vascular Diseases. Circ Res 2024; 135:1084-1097. [PMID: 39355906 PMCID: PMC11542979 DOI: 10.1161/circresaha.124.325269] [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: 07/27/2024] [Revised: 09/19/2024] [Accepted: 09/20/2024] [Indexed: 10/03/2024]
Abstract
BACKGROUND Genome-wide association studies implicate common genetic variations in the LRP1 (low-density lipoprotein receptor-related protein 1 gene) locus at risk for multiple vascular diseases and traits. However, the underlying biological mechanisms are unknown. METHODS Fine mapping analyses included Bayesian colocalization to identify the most likely causal variant. Human induced pluripotent stem cells were genome-edited using CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated protein 9) to delete or modify candidate enhancer regions and generate LRP1 knockout cell lines. Cells were differentiated into smooth muscle cells through a mesodermal lineage. Transcription regulation was assessed using luciferase reporter assay, transcription factor knockdown, and chromatin immunoprecipitation. Phenotype changes in cells were conducted using cellular assays, bulk RNA sequencing, and mass spectrometry. RESULTS Multitrait colocalization analyses pointed at rs11172113 as the most likely causal variant in LRP1 for fibromuscular dysplasia, migraine, pulse pressure, and spontaneous coronary artery dissection. We found the rs11172113-T allele to associate with higher LRP1 expression. Genomic deletion in induced pluripotent stem cell-derived smooth muscle cells supported rs11172113 to locate in an enhancer region regulating LRP1 expression. We found transcription factors MECP2 (methyl CpG binding protein 2) and SNAIL (Zinc Finger Protein SNAI1) to repress LRP1 expression through an allele-specific mechanism, involving SNAIL interaction with disease risk allele. LRP1 knockout decreased induced pluripotent stem cell-derived smooth muscle cell proliferation and migration. Differentially expressed genes were enriched for collagen-containing extracellular matrix and connective tissue development. LRP1 knockout and deletion of rs11172113 enhancer showed potentiated canonical TGF-β (transforming growth factor beta) signaling through enhanced phosphorylation of SMAD2/3 (Mothers against decapentaplegic homolog 2/3). Analyses of the protein content of decellularized extracts indicated partial extracellular matrix remodeling involving enhanced secretion of CYR61 (cystein rich angiogenic protein 61), a known LRP1 ligand involved in vascular integrity and TIMP3 (Metalloproteinase inhibitor 3), implicated in extracellular matrix maintenance and also known to interact with LRP1. CONCLUSIONS Our findings support allele-specific LRP1 expression repression by the endothelial-to-mesenchymal transition regulator SNAIL. We propose decreased LRP1 expression in smooth muscle cells to remodel the extracellular matrix enhanced by TGF-β as a potential mechanism of this pleiotropic locus for vascular diseases.
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Affiliation(s)
- Lu Liu
- Université Paris Cité, Inserm, PARCC, Paris, France
| | | | - Yingwei Liu
- Université Paris Cité, Inserm, PARCC, Paris, France
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106
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Zhou X, Zheng W, Kong W, Zeng T. Dietary patterns and diabetic microvascular complications risk: a Mendelian randomization study of European ancestry. Front Nutr 2024; 11:1429603. [PMID: 39555188 PMCID: PMC11566142 DOI: 10.3389/fnut.2024.1429603] [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: 05/08/2024] [Accepted: 10/23/2024] [Indexed: 11/19/2024] Open
Abstract
Purpose Previous observational studies about the link between dietary factors and diabetic microvascular complications (DMCs) is controversial. Thus, we systemically assessed the potential causal relationship between diet and DMCs risk using Mendelian randomization (MR) methods. Methods We used genome-wide association studies (GWAS) statistics to estimate the causal effects of 17 dietary patterns on three common DMCs in European. Summary statistics on dietary intakes were obtained from the UK biobank, and data on DMCs [diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic neuropathy (DNP)] were obtained from the FinnGen Consortium. A two-sample MR (TSMR) was conducted to explore the causal relationships of dietary habits with DMCs. In addition, multivariable MR analysis (MVMR) was performed to adjust for traditional risk factors for eating habits, and evaluated the direct or indirect effects of diet on DMCs. Results TSMR analysis revealed that salad/raw vegetable intake (odd ratio [OR]: 2.830; 95% confidence interval [CI]: 1.102-7.267; p = 0.0306) and fresh fruit intake (OR: 2.735; 95% CI: 1.622-4.611; p = 0.0002; false discovery rate [FDR] = 0.0082) increased the risk of DR, whereas cheese intake (OR: 0.742; 95% CI: 0.563-0.978; p = 0.0339) and cereal intake (OR: 0.658; 95% CI: 0.444-0.976; p = 0.0374) decreased the risk of DR. Salad/raw vegetable (OR: 6.540; 95% CI: 1.061-40.300; p = 0.0430) and fresh fruit consumption (OR: 3.573; 95% CI: 1.263-10.107; p = 0.0164) are risk factors for DN, while cereal consumption (OR: 0.380; 95% CI: 0.174-0.833; p = 0.0156) is the opposite. And genetically predicted higher pork intake increased the risk of DNP (OR: 160.971; 95% CI: 8.832-2933.974; p = 0.0006; FDR = 0.0153). The MVMR analysis revealed that cheese intake may act as an independent protective factor for DR development. Moreover, fresh fruit intake, salad/raw vegetable intake and pork intake may be independent risk factors for DR, DN and DNP, respectively. Other causal associations between dietary habits and DMCs risk may be mediated by intermediate factors. Conclusion This causal relationship study supports that specific dietary interventions may reduce the risk of DMCs.
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Affiliation(s)
- Xin Zhou
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenbin Zheng
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wen Kong
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tianshu Zeng
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, Hubei, China
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107
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Gholipourshahraki T, Bai Z, Shrestha M, Hjelholt A, Hu S, Kjolby M, Rohde PD, Sørensen P. Evaluation of Bayesian Linear Regression models for gene set prioritization in complex diseases. PLoS Genet 2024; 20:e1011463. [PMID: 39495786 PMCID: PMC11563439 DOI: 10.1371/journal.pgen.1011463] [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: 05/21/2024] [Revised: 11/14/2024] [Accepted: 10/17/2024] [Indexed: 11/06/2024] Open
Abstract
Genome-wide association studies (GWAS) provide valuable insights into the genetic architecture of complex traits, yet interpreting their results remains challenging due to the polygenic nature of most traits. Gene set analysis offers a solution by aggregating genetic variants into biologically relevant pathways, enhancing the detection of coordinated effects across multiple genes. In this study, we present and evaluate a gene set prioritization approach utilizing Bayesian Linear Regression (BLR) models to uncover shared genetic components among different phenotypes and facilitate biological interpretation. Through extensive simulations and analyses of real traits, we demonstrate the efficacy of the BLR model in prioritizing pathways for complex traits. Simulation studies reveal insights into the model's performance under various scenarios, highlighting the impact of factors such as the number of causal genes, proportions of causal variants, heritability, and disease prevalence. Comparative analyses with MAGMA (Multi-marker Analysis of GenoMic Annotation) demonstrate BLR's superior performance, especially in highly overlapped gene sets. Application of both single-trait and multi-trait BLR models to real data, specifically GWAS summary data for type 2 diabetes (T2D) and related phenotypes, identifies significant associations with T2D-related pathways. Furthermore, comparison between single- and multi-trait BLR analyses highlights the superior performance of the multi-trait approach in identifying associated pathways, showcasing increased statistical power when analyzing multiple traits jointly. Additionally, enrichment analysis with integrated data from various public resources supports our results, confirming significant enrichment of diabetes-related genes within the top T2D pathways resulting from the multi-trait analysis. The BLR model's ability to handle diverse genomic features, perform regularization, conduct variable selection, and integrate information from multiple traits, genders, and ancestries demonstrates its utility in understanding the genetic architecture of complex traits. Our study provides insights into the potential of the BLR model to prioritize gene sets, offering a flexible framework applicable to various datasets. This model presents opportunities for advancing personalized medicine by exploring the genetic underpinnings of multifactorial traits.
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Affiliation(s)
| | - Zhonghao Bai
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Merina Shrestha
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Astrid Hjelholt
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Pharmacology, Aarhus University Hospital, Aarhus, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Sile Hu
- Human Genetics Centre of Excellence, Novo Nordisk Research Centre Oxford, Oxford, United Kingdom
| | - Mads Kjolby
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Pharmacology, Aarhus University Hospital, Aarhus, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Palle Duun Rohde
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Peter Sørensen
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
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108
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Fujii R. En route to conquer the silent killer "hypertension": Integration of polygenic risk score with non-genetic determinants. Hypertens Res 2024; 47:3079-3081. [PMID: 39090181 DOI: 10.1038/s41440-024-01826-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 07/03/2024] [Indexed: 08/04/2024]
Affiliation(s)
- Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, 470-1192, Japan.
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109
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Meng Y, Mynard JP, Smith KJ, Juonala M, Urbina EM, Niiranen T, Daniels SR, Xi B, Magnussen CG. Pediatric Blood Pressure and Cardiovascular Health in Adulthood. Curr Hypertens Rep 2024; 26:431-450. [PMID: 38878251 PMCID: PMC11455673 DOI: 10.1007/s11906-024-01312-5] [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] [Accepted: 05/28/2024] [Indexed: 10/06/2024]
Abstract
PURPOSE OF REVIEW This review summarizes current knowledge on blood pressure in children and adolescents (youth), with a focus on primary hypertension-the most common form of elevated blood pressure in this demographic. We examine its etiology, progression, and long-term cardiovascular implications. The review covers definitions and recommendations of blood pressure classifications, recent developments in measurement, epidemiological trends, findings from observational and clinical studies, and prevention and treatment, while identifying gaps in understanding and suggesting future research directions. RECENT FINDINGS Youth hypertension is an escalating global issue, with regional and national variations in prevalence. While the principles of blood pressure measurement have remained largely consistent, challenges in this age group include a scarcity of automated devices that have passed independent validation for accuracy and a generally limited tolerance for ambulatory blood pressure monitoring. A multifaceted interplay of factors contributes to youth hypertension, impacting long-term cardiovascular health. Recent studies, including meta-analysis and sophisticated life-course modelling, reveal an adverse link between youth and life-course blood pressure and subclinical cardiovascular outcomes later in life. New evidence now provides the strongest evidence yet linking youth blood pressure with clinical cardiovascular events in adulthood. Some clinical trials have expanded our understanding of the safety and efficacy of antihypertensive medications in youth, but this remains an area that requires additional attention, particularly regarding varied screening approaches. This review outlines the potential role of preventing and managing blood pressure in youth to reduce future cardiovascular risk. A global perspective is necessary in formulating blood pressure definitions and strategies, considering the specific needs and circumstances in low- and middle-income countries compared to high-income countries.
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Affiliation(s)
- Yaxing Meng
- Baker Heart and Diabetes Institute, 75 Commercial Rd, Melbourne, VIC, 3004, Australia
- Baker Department of Cardiometabolic Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Jonathan P Mynard
- Heart Research Group, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- Department of Biomedical Engineering, University of Melbourne, Parkville, VIC, Australia
| | - Kylie J Smith
- Baker Heart and Diabetes Institute, 75 Commercial Rd, Melbourne, VIC, 3004, Australia
- Menzies Institute for Medical Research, University of Tasmania, TAS, Hobart, Australia
| | - Markus Juonala
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Medicine, University of Turku, Turku, Finland
| | - Elaine M Urbina
- Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati, Cincinnati, OH, USA
| | - Teemu Niiranen
- Department of Public Health Solutions, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
- Department of Internal Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Stephen R Daniels
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Bo Xi
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, China
| | - Costan G Magnussen
- Baker Heart and Diabetes Institute, 75 Commercial Rd, Melbourne, VIC, 3004, Australia.
- Baker Department of Cardiometabolic Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, VIC, Australia.
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
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Le Grand Q, Tsuchida A, Koch A, Imtiaz MA, Aziz NA, Vigneron C, Zago L, Lathrop M, Dubrac A, Couffinhal T, Crivello F, Matthews PM, Mishra A, Breteler MMB, Tzourio C, Debette S. Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease. Mol Psychiatry 2024; 29:3567-3579. [PMID: 38811690 PMCID: PMC11541005 DOI: 10.1038/s41380-024-02604-7] [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: 07/31/2023] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 05/31/2024]
Abstract
Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention.
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Affiliation(s)
- Quentin Le Grand
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Ami Tsuchida
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Alexandra Koch
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Mohammed-Aslam Imtiaz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Chloé Vigneron
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
| | - Laure Zago
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Mark Lathrop
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Victor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montreal, QC, H3A 0G1, Canada
| | - Alexandre Dubrac
- Centre de Recherche, CHU Sainte-Justine, Montréal, QC, Canada
- Département de Pathologie et Biologie Cellulaire, Université de Montréal, Montréal, QC, Canada
- Département d'Ophtalmologie, Université de Montréal, Montréal, QC, Canada
| | - Thierry Couffinhal
- University of Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600, Pessac, France
| | - Fabrice Crivello
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Paul M Matthews
- UK Dementia Research Institute and Department of Brain Sciences, Imperial College, London, UK
| | - Aniket Mishra
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Christophe Tzourio
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- Bordeaux University Hospital, Department of Medical Informatics, F-33000, Bordeaux, France
| | - Stéphanie Debette
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France.
- Bordeaux University Hospital, Department of Neurology, Institute for Neurodegenerative Diseases, F-33000, Bordeaux, France.
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Wei X, Iao WC, Zhang Y, Lin Z, Lin H. Retinal Microvasculature Causally Affects the Brain Cortical Structure: A Mendelian Randomization Study. OPHTHALMOLOGY SCIENCE 2024; 4:100465. [PMID: 39149712 PMCID: PMC11324828 DOI: 10.1016/j.xops.2024.100465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 01/05/2024] [Accepted: 01/08/2024] [Indexed: 08/17/2024]
Abstract
Purpose To reveal the causality between retinal vascular density (VD), fractal dimension (FD), and brain cortex structure using Mendelian randomization (MR). Design Cross-sectional study. Participants Genome-wide association studies of VD and FD involving 54 813 participants from the United Kingdom Biobank were used. The brain cortical features, including the cortical thickness (TH) and surface area (SA), were extracted from 51 665 patients across 60 cohorts. Surface area and TH were measured globally and in 34 functional regions using magnetic resonance imaging. Methods Bidirectional univariable MR (UVMR) was used to detect the causality between FD, VD, and brain cortex structure. Multivariable MR (MVMR) was used to adjust for confounding factors, including body mass index and blood pressure. Main Outcome Measures The global and regional measurements of brain cortical SA and TH. Results At the global level, higher VD is related to decreased TH (β = -0.0140 mm, 95% confidence interval: -0.0269 mm to -0.0011 mm, P = 0.0339). At the functional level, retinal FD is related to the TH of banks of the superior temporal sulcus and transverse temporal region without global weighted, as well as the SA of the posterior cingulate after adjustment. Vascular density is correlated with the SA of subregions of the frontal lobe and temporal lobe, in addition to the TH of the inferior temporal, entorhinal, and pars opercularis regions in both UVMR and MVMR. Bidirectional MR studies showed a causation between the SA of the parahippocampal and cauda middle frontal gyrus and retinal VD. No pleiotropy was detected. Conclusions Fractal dimension and VD causally influence the cortical structure and vice versa, indicating that the retinal microvasculature may serve as a biomarker for cortex structural changes. Our study provides insights into utilizing noninvasive fundus images to predict cortical structural deteriorations and neuropsychiatric disorders. Financial Disclosures The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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Affiliation(s)
- Xiaoyue Wei
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wai Cheng Iao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yi Zhang
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zijie Lin
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Haotian Lin
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Vision Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
- Center for Precision Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
- Hainan Eye Hospital and Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Haikou, Hainan, China
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112
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Lu L, Gu X, Yang D, Wang B, Long G. Circulating fatty acids, genetic susceptibility and hypertension: a prospective cohort study. Front Nutr 2024; 11:1454364. [PMID: 39545052 PMCID: PMC11562856 DOI: 10.3389/fnut.2024.1454364] [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: 06/25/2024] [Accepted: 10/07/2024] [Indexed: 11/17/2024] Open
Abstract
Background Combining genetic risk factors and plasma fatty acids (FAs) can be used as an effective method of precision medicine to prevent hypertension risk. Methods A total of 195,250 participants in the UK Biobank cohort were included in this study from 2006-2010. Polygenic risk scores (PRSs) were calculated for hypertension using single-nucleotide polymorphisms (SNPs). Concentrations of plasma FAs, including polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs) and saturated fatty acids (SFAs), were tested by nuclear magnetic resonance. The Cox model was used to test for the main effects of PRS, different plasma FAs and their joint effects on hypertension. Relative excess risk due to interaction (RERI) and the attributable proportion due to interaction (AP) were used to test the additive interaction. Results Plasma PUFAs, n-3 PUFAs, MUFAs and SFAs were related to the risk of hypertension (PUFAs: HR, 0.878; 95% CI, 0.868-0.888; MUFAs: HR, 1.13; 95% CI, 1.123-1.150; SFAs: HR, 1.086; 95% CI, 1.074-1.098; n-3 PUFAs: HR, 0.984; 95% CI, 0.973-0.995). Moreover, an additive interaction was found between PRS and plasma FAs, which could contribute to an approximately 10-18% risk of hypertension, and the associations between high plasma MUFAs and a high PRS of hypertension were the strongest positive [RERI: 0.178 (95% CI: 0.062, 0.294), AP: 0.079 (95% CI: 0.027, 0.130)]. Conclusion Increased plasma MUFAs or SFAs and decreased plasma PUFAs or n-3 PUFAs were associated with hypertension risk, especially among people at high genetic risk.
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Affiliation(s)
- Lingling Lu
- Department of Infectious Disease, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoli Gu
- Department of Party and Government Office, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Daheng Yang
- Department of Clinical Laboratory, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Bingjian Wang
- Department of Cardiology, Huai’an First People’s Hospital Affiliated with Nanjing Medical University, Huai’an, China
| | - Guangfeng Long
- Department of Clinical Laboratory, Children’s Hospital of Nanjing Medical University, Nanjing, China
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113
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Zhao JV, Zhang J. Using Genetics to Assess the Role of Acetate in Ischemic Heart Disease, Diabetes, and Sex-Hormone-Related Cancers: A Mendelian Randomization Study. Nutrients 2024; 16:3674. [PMID: 39519507 PMCID: PMC11547320 DOI: 10.3390/nu16213674] [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: 09/09/2024] [Revised: 10/16/2024] [Accepted: 10/22/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Acetate, a short-chain fatty acid, has gained attention for its contrasting roles, with evidence suggesting it may offer cardiovascular protection but also promote cancer, particularly those involving sex hormones. However, these influences have been scarcely assessed in epidemiological research. OBJECTIVE To investigate the relationship between acetate and ischemic heart disease (IHD), diabetes, and cancers related to sex hormones. METHODS Mendelian randomization (MR) was used to assess potential causal effects, selecting genetic variants without linkage disequilibrium (r2 < 0.001) and with genome-wide significance for acetate (p < 5 × 10-8). These variants were applied to large genome-wide association studies (GWAS) for ischemic heart disease (IHD; up to 154,373 cases), diabetes (109,731 cases), and five sex-hormone-related cancers (breast, colorectal, prostate, ovarian, and endometrial cancers, ranging from 8679 to 122,977 cases). We employed various methods for analysis, including penalized inverse variance weighting (pIVW), inverse variance weighting, weighted mode, and weighted median. RESULTS This study indicates that acetate may be associated with a lower risk of ischemic heart disease (IHD), with an odds ratio (OR) of 0.62 per standard deviation (SD) increase in acetate and a 95% confidence interval (CI) of 0.39 to 0.98. Additionally, acetate was linked to a higher breast cancer risk, with an OR of 1.26 and a 95% CI ranging from 1.08 to 1.46. This association remained robust across multiple sensitivity analyses. CONCLUSIONS Acetate, along with factors that influence its activity, may serve as possible targets for breast cancer treatment and possibly IHD, offering opportunities for new drug development.
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Affiliation(s)
- Jie V. Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China;
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China
| | - Junmeng Zhang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China;
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Zhang J, Chen ZK, Triatin RD, Snieder H, Thio CHL, Hartman CA. Mediating pathways between attention deficit hyperactivity disorder and type 2 diabetes mellitus: evidence from a two-step and multivariable Mendelian randomization study. Epidemiol Psychiatr Sci 2024; 33:e54. [PMID: 39465621 PMCID: PMC11561680 DOI: 10.1017/s2045796024000593] [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: 11/22/2023] [Revised: 05/20/2024] [Accepted: 07/14/2024] [Indexed: 10/29/2024] Open
Abstract
AIMS Type 2 diabetes (T2D) is a global health burden, more prevalent among individuals with attention deficit hyperactivity disorder (ADHD) compared to the general population. To extend the knowledge base on how ADHD links to T2D, this study aimed to estimate causal effects of ADHD on T2D and to explore mediating pathways. METHODS We applied a two-step, two-sample Mendelian randomization (MR) design, using single nucleotide polymorphisms to genetically predict ADHD and a range of potential mediators. First, a wide range of univariable MR methods was used to investigate associations between genetically predicted ADHD and T2D, and between ADHD and the purported mediators: body mass index (BMI), childhood obesity, childhood BMI, sedentary behaviour (daily hours of TV watching), blood pressure (systolic blood pressure, diastolic blood pressure), C-reactive protein and educational attainment (EA). A mixture-of-experts method was then applied to select the MR method most likely to return a reliable estimate. We used estimates derived from multivariable MR to estimate indirect effects of ADHD on T2D through mediators. RESULTS Genetically predicted ADHD liability associated with 10% higher odds of T2D (OR: 1.10; 95% CI: 1.02, 1.18). From nine purported mediators studied, three showed significant individual mediation effects: EA (39.44% mediation; 95% CI: 29.00%, 49.73%), BMI (44.23% mediation; 95% CI: 34.34%, 52.03%) and TV watching (44.10% mediation; 95% CI: 30.76%, 57.80%). The combination of BMI and EA explained the largest mediating effect (53.31%, 95% CI: -1.99%, 110.38%) of the ADHD-T2D association. CONCLUSIONS These findings suggest a potentially causal, positive relationship between ADHD liability and T2D, with mediation through higher BMI, more TV watching and lower EA. Intervention on these factors may thus have beneficial effects on T2D risk in individuals with ADHD.
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Affiliation(s)
- J Zhang
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Division of Communicable Disease Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Z K Chen
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - R D Triatin
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Faculty of Medicine, Department of Biomedical Sciences, Universitas Padjadjaran, Bandung, Indonesia
| | - H Snieder
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - C H L Thio
- Department of Epidemiology, Unit of Genetic Epidemiology and Bioinformatics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Population Health Sciences, Institute for Risk Assessment Sciences, University of Utrecht, Utrecht, The Netherlands
| | - C A Hartman
- Interdisciplinary Centre Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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115
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Jiesisibieke ZL, Schooling CM. Impact of Alcohol Consumption on Lifespan: a Mendelian randomization study in Europeans. Sci Rep 2024; 14:25321. [PMID: 39455599 PMCID: PMC11511936 DOI: 10.1038/s41598-024-73333-8] [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: 04/17/2024] [Accepted: 09/16/2024] [Indexed: 10/28/2024] Open
Abstract
Alcohol is widely used but recognized as a risk factor for several adverse health outcomes based on observational studies. How alcohol affects lifespan remains controversial, with no trial to make such an assessment available or likely. We conducted a Mendelian randomization (MR) to assess the effect of alcohol on lifespan in men and women, including a possible role of smoking and education. Strong (p < 5e- 8), independent (r2 < 0.001) genetic predictors of alcohol consumption in 2,428,851 participants of European ancestry from the Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium genome wide association study (GWAS) were applied to sex-specific GWAS of lifespan (paternal and maternal attained age) and age at recruitment to the UK Biobank. We used multivariable MR to allow for smoking and education, with systolic and diastolic blood pressure as control outcomes. Inverse variance weighted was the primary analysis with sensitivity analysis. Alcohol consumption decreased lifespan overall (- 1.09 years (logged alcoholic drinks per week), - 1.89 to - 0.3) and in men (- 1.47 years, - 2.55 to - 0.38), which remained evident after adjusting for smoking (- 1.81 years, - 3.3 to - 0.32) and education (- 1.85 years, - 3.12 to - 0.58). Estimates from sensitivity analysis were similar, and when using the genetic variant physiologically associated with alcohol use. Alcohol consumption was associated with higher blood pressure as expected. Our study indicates that alcohol does not provide any advantages for men or women but could shorten lifespan. Appropriate interventions should be implemented.
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Affiliation(s)
- Zhu Liduzi Jiesisibieke
- School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, 7 Sassoon Road, Pokfulam, Hong Kong, Hong Kong
| | - C Mary Schooling
- School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, 7 Sassoon Road, Pokfulam, Hong Kong, Hong Kong.
- Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
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Muiño E, Carcel-Marquez J, Llucià-Carol L, Gallego-Fabrega C, Cullell N, Lledós M, Martín-Campos JM, Villatoro-González P, Sierra-Marcos A, Ros-Castelló V, Aguilera-Simón A, Marti-Fabregas J, Fernandez-Cadenas I. Identification of Genetic Loci Associated With Intracerebral Hemorrhage Using a Multitrait Analysis Approach. Neurology 2024; 103:e209666. [PMID: 39298701 PMCID: PMC11446162 DOI: 10.1212/wnl.0000000000209666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/15/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Genome-wide association studies (GWASs) have only 2 loci associated with spontaneous intracerebral hemorrhage (ICH): APOE for lobar and 1q22 for nonlobar ICH. We aimed to discover new loci through an analysis that combines correlated traits (multi-trait analysis of GWAS [MTAG]) and explore a gene-based analysis, transcriptome-wide association study (TWAS), and proteome-wide association study (PWAS) to understand the biological mechanisms of spontaneous ICH providing potential therapeutic targets. METHODS We use the published MTAG of ICH (patients with spontaneous intraparenchymal bleeding) and small-vessel ischemic stroke. For all ICH, lobar ICH, and nonlobar ICH, a pairwise MTAG combined ICH with traits related to cardiovascular risk factors, cerebrovascular diseases, or Alzheimer disease (AD). For the analysis, we assembled those traits with a genetic correlation ≥0.3. A new MTAG combining multiple traits was performed with those traits whose pairwise MTAG yielded new GWAS-significant single nucleotide polymorphisms (SNPs), with a posterior-probability of model 3 (GWAS-pairwise) ≥0.6. We perform TWAS and PWAS that correlate the genetic component of expression or protein levels with the genetic component of a trait. We use the ICH cohort from UK Biobank as replication. RESULTS For all ICH (1,543 ICH, 1,711 controls), the mean age was 72 ± 2 in cases and 70 ± 2 in controls, and half of them were women. Replication cohort: 700 ICH and 399,717 controls. Novel loci were found only for all ICH (the trait containing lobar and nonlobar ICH), combining data of ICH and small vessel stroke, white matter hyperintensities volume, fractional anisotropy, mean diffusivity, and AD. We replicated 6 SNPs belonging to 2q33.2 (ICA1L, β = 0.20, SE = 0.03, p value = 8.91 × 10-12), 10q24.33 (OBFC1, β = -0.12, SE = 0.02, p value = 1.67 × 10-8), 13q34 (COL4A2, β = 0.02, SE = 0.02, p value = 2.34 × 10-11), and 19q13.32 (APOC1, β = -0.19, SE = 0.03, p value = 1.38 × 10-12; APOE, β = 0.21, SE = 0.03, p value = 2.70 × 10-11; PVRL2:CTB-129P6.4, β = 0.15, SE = 0.03, p value = 1.38 × 10-8); 2 genes (SH3PXD2A, Z-score = 4.83, p value = 6.67 × 10-7; and APOC1, Z-score: = 5.11, p value = 1.60 × 10-7); and ICA1L transcript (Z-score = 6.8, p value = 9.1 × 10-12) and protein levels (Z-score = -5.8, p value = 6.7 × 10-9). DISCUSSION Our results reinforce the role of APOE in ICH risk, replicate previous ICH-associated loci (2q33 and 13q34), and point to new ICH associations with OBFC1, PVRL2:CTB-129P6.4, APOC1, and SH3PXD2A. Our study used data from European subjects, our main limitation. These molecules could be potential targets for future studies for modulating ICH risk.
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Affiliation(s)
- Elena Muiño
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Jara Carcel-Marquez
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Laia Llucià-Carol
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Cristina Gallego-Fabrega
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Natalia Cullell
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Miquel Lledós
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Jesús M Martín-Campos
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Paula Villatoro-González
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Alba Sierra-Marcos
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Victoria Ros-Castelló
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Ana Aguilera-Simón
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Joan Marti-Fabregas
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Israel Fernandez-Cadenas
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
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Zhang J, He J, Liao Y, Xia X, Yang F. Genetic association between gut microbiome and blood pressure and blood cell count as mediator: A two-step Mendelian randomization analysis. Gene 2024; 925:148573. [PMID: 38762013 DOI: 10.1016/j.gene.2024.148573] [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: 01/25/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Previous studies have established a genetic link between gut microbiota and hypertension, but whether blood cell count plays a mediating role in this remains unknown. This study aims to explore genetic associations and causal factors involving the gut microbiome, peripheral blood cell count, and blood pressure. METHODS We utilized summary statistics derived from genome-wide association studies to conduct a two-sample mediation Mendelian randomization analysis (https://gwas.mrcieu.ac.uk/). We applied inverse variance weighted (IVW) estimation method as the primary method, along with MR Egger, Weighted median, Simple mode and Weighted mode as complementary methods. To ensure the robustness of the results, several sensitivity analyses were conducted. RESULTS Genetic variants significantly associated with the microbiome, blood pressure, or peripheral blood cell counts were selected as instrumental variables. Fourteen microbial taxa were found to have suggestive associations with diastolic blood pressure (DBP), while fifteen microbial taxa showed suggestive associations with systolic blood pressure (SBP). Meanwhile, red blood cell count, lymphocyte count, and platelet count were identified to mediate the influence of the gut microbiome on blood pressure. Specifically, red cell count was identified to mediate the effects of the phylum Cyanobacteria on DBP (mediated proportion: 8.262 %). Lymphocyte count was found mediate the effects of the genus Subdoligranulum (mediated proportion: 2.642 %) and genus Collinsella (mediated proportion: 2.749 %) on SBP. Additionally, platelet count was found to mediate the relationship between the genus Eubacterium ventriosum group and SBP, explaining 3.421 % of the mediated proportion. CONCLUSIONS Our findings highlighted that gut microbiota may have causal influence on the blood pressure by modulating blood cell counts, which sheds new light on the pathogenesis and potential clinical interventions through the intricate axis of gut microbiome, blood cell counts, and blood pressure.
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Affiliation(s)
- Jiyu Zhang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
| | - Junyi He
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China.
| | - Yuhan Liao
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
| | - Xinyi Xia
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
| | - Fen Yang
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China.
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Huang Y, Plotnikov D, Wang H, Shi D, Li C, Zhang X, Zhang X, Tang S, Shang X, Hu Y, Yu H, Zhang H, Guggenheim JA, He M. GWAS-by-subtraction reveals an IOP-independent component of primary open angle glaucoma. Nat Commun 2024; 15:8962. [PMID: 39419966 PMCID: PMC11487129 DOI: 10.1038/s41467-024-53331-0] [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: 07/14/2023] [Accepted: 10/09/2024] [Indexed: 10/19/2024] Open
Abstract
The etiology of primary open angle glaucoma is constituted by both intraocular pressure-dependent and intraocular pressure-independent mechanisms. However, GWASs of traits affecting primary open angle glaucoma through mechanisms independent of intraocular pressure remains limited. Here, we address this gap by subtracting the genetic effects of a GWAS for intraocular pressure from a GWAS for primary open angle glaucoma to reveal the genetic contribution to primary open angle glaucoma via intraocular pressure-independent mechanisms. Seventeen independent genome-wide significant SNPs were associated with the intraocular pressure-independent component of primary open angle glaucoma. Of these, 7 are located outside known normal tension glaucoma loci, 11 are located outside known intraocular pressure loci, and 2 are novel primary open angle glaucoma loci. The intraocular pressure-independent genetic component of primary open angle glaucoma is associated with glaucoma endophenotypes, while the intraocular pressure-dependent component is associated with blood pressure and vascular permeability. A genetic risk score for the intraocular pressure-independent component of primary open angle glaucoma is associated with 26 different retinal micro-vascular features, which contrasts with the genetic risk score for the intraocular pressure-dependent component. Increased understanding of these intraocular pressure-dependent and intraocular pressure-independent components provides insights into the pathogenesis of glaucoma.
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Affiliation(s)
- Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
| | - Denis Plotnikov
- Central Research Laboratory, Kazan State Medical University, Kazan, Russia
- School of Optometry & Vision Sciences, Cardiff University, Cardiff, UK
| | - Huan Wang
- Division of Population Health and Genomics, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK
| | - Danli Shi
- Experimental Ophthalmology, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
| | - Cong Li
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Shulin Tang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
| | - Hongyang Zhang
- Department of Ophthalmology, Nanfang Hospital, Southern Medical University, Guangzhou, 510080, China.
| | | | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Experimental Ophthalmology, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
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Schmidt AF, Davidson MH, Ditmarsch M, Kastelein JJ, Finan C. Lower activity of cholesteryl ester transfer protein (CETP) and the risk of dementia: a Mendelian randomization analysis. Alzheimers Res Ther 2024; 16:228. [PMID: 39415269 PMCID: PMC11481778 DOI: 10.1186/s13195-024-01594-6] [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: 07/19/2024] [Accepted: 10/02/2024] [Indexed: 10/18/2024]
Abstract
BACKGROUND Elevated concentrations of low-density lipoprotein cholesterol (LDL-C) are linked to dementia risk, and conversely, increased plasma concentrations of high-density lipoprotein cholesterol (HDL-C) and apolipoprotein-A1 (Apo-A1) associate with decreased dementia risk. Inhibition of cholesteryl ester transfer protein (CETP) meaningfully affects the concentrations of these blood lipids and may therefore provide an opportunity to treat dementia. METHODS Drug target Mendelian randomization (MR) was employed to anticipate the on-target effects of lower CETP concentration (μg/mL) on plasma lipids, cardiovascular disease outcomes, autopsy confirmed Lewy body dementia (LBD), as well as Parkinson's dementia. RESULTS MR analysis of lower CETP concentration recapitulated the blood lipid effects observed in clinical trials of CETP-inhibitors, as well as protective effects on coronary heart disease (odds ratio (OR) 0.92, 95% confidence interval (CI) 0.89; 0.96), heart failure, abdominal aortic aneurysm, any stroke, ischemic stroke, and small vessel stroke (0.90, 95%CI 0.85; 0.96). Consideration of dementia related traits indicated that lower CETP concentrations were associated higher total brain volume (0.04 per standard deviation, 95%CI 0.02; 0.06), lower risk of LBD (OR 0.81, 95%CI 0.74; 0.89) and Parkinson's dementia risk (OR 0.26, 95%CI 0.14; 0.48). APOE4 stratified analyses suggested the LBD effect was most pronounced in APOE-ε4 + participants (OR 0.61 95%CI 0.51; 0.73), compared to APOE-ε4- (OR 0.89 95%CI 0.79; 1.01); interaction p-value 5.81 × 10- 4. CONCLUSIONS These results suggest that inhibition of CETP may be a viable strategy to treat dementia, with a more pronounced effect expected in APOE-ε4 carriers.
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Affiliation(s)
- Amand F Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, 69-75 Chenies Mews, London, WC1E 6HX, UK.
- UCL British Heart Foundation Research Accelerator, 69-75 Chenies Mews, London, WC1E 6HX, UK.
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam UMC, locatie AMC Postbus 22660, Amsterdam Zuidoost, 1100 DD, The Netherlands.
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands.
| | - Michael H Davidson
- Pritzker School of Medicine, University of Chicago, 5801 S Ellis Ave, Chicago, IL, 60637, USA
- NewAmsterdam Pharma B.V, Gooimeer 2-35, Naarden, 1411 DC, Netherlands
| | - Marc Ditmarsch
- NewAmsterdam Pharma B.V, Gooimeer 2-35, Naarden, 1411 DC, Netherlands
| | - John J Kastelein
- NewAmsterdam Pharma B.V, Gooimeer 2-35, Naarden, 1411 DC, Netherlands
- Department of Vascular Medicine, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam UMC, locatie AMC Postbus 22660, Amsterdam Zuidoost, 1100 DD, The Netherlands
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, 69-75 Chenies Mews, London, WC1E 6HX, UK
- UCL British Heart Foundation Research Accelerator, 69-75 Chenies Mews, London, WC1E 6HX, UK
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
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Cheng J, Cui J, Li Y, Liu X, Jiang Y, Liu Q, Liu C, Feng H, Jiao Z, Shao X, Gao Y, Sun D, Zhang W. The RAAS system SNPs polymorphism is associated with essential hypertension risk in rural areas in northern China. Int J Med Sci 2024; 21:2694-2704. [PMID: 39512695 PMCID: PMC11539379 DOI: 10.7150/ijms.98724] [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: 05/21/2024] [Accepted: 09/19/2024] [Indexed: 11/15/2024] Open
Abstract
Objectives: Epidemiological evidence has shown that genetics and environment are associated with the risk of hypertension. However, the specific SNP effects of a cluster of crucial genes in the RAAS system on the risk of hypertension are unclear. Methods: A case-control study was performed on the baseline participants of Environment and Chronic Disease in Rural Areas of Heilongjiang China (ECDRAHC) study. According to the inclusion and exclusion criteria, 757 subjects (428 hypertensive patients) were enrolled. A total of 32 SNP sites and related haplotypes, involved in AGT (angiotensinogen), ACE (angiotensin-converting enzyme), AGTR1, CYP11B2 (aldosterone-synthase), LDLR (low-density lipoprotein receptor), LRP5 (low-density lipoprotein receptor associated protein 5), LRP6 (low-density lipoprotein receptor associated protein 6), PPARG (peroxisome proliferator-activated receptor gamma) and ACE2 (angiotensin-converting enzyme 2) genes which exert important roles in renin-angiotensin-aldosterone system (RAAS) system were analyzed. Furthermore, a polygenic scoring model was established to assess individual risk of developing hypertension based on the comprehensive SNPs effects in genes related the RAAS system. Results: After controlling the impact of confounding factors, multivariate logistic regression analysis revealed that the distribution of AGT/rs5046, LRP6/rs12823243 and ACE2/rs2285666 was associated with susceptibility to essential hypertension. In genetic score model, the score > -0.225 had a higher risk, the OR (95%CI) was 1.229 (1.110, 1.362). Conclusions: To the best of our knowledge, this is the first time a hypertension risk scoring model on RAAS associated gene cluster has been constructed, which will provide a novel approach for prevention and control of essential hypertension.
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Affiliation(s)
- Jin Cheng
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Jing Cui
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
- Harbin Center for Disease Control and Prevention, Harbin, Heilongjiang, People's Republic of China
| | - Yuanyuan Li
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Xiaona Liu
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Yuting Jiang
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Qiaoling Liu
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Chang Liu
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Hongqi Feng
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
| | - Zhe Jiao
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
| | - Xinhua Shao
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
| | - Yanhui Gao
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
| | - Dianjun Sun
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
- State Key Laboratory of Frigid Zone Cardiovascular Diseases (SKLFZCD), Harbin Medical University, Harbin, People's Republic of China
| | - Wei Zhang
- Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, People's Republic of China
- National Health Commission & Education Bureau of Heilongjiang Province, Key Laboratory of Etiology and Epidemiology, Harbin Medical University (23618504), Harbin, People's Republic of China
- Heilongjiang Provincial Key Laboratory of Trace Elements and Human Health, Harbin Medical University, Harbin, People's Republic of China
- Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, People's Republic of China
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Cui B, Chen A, Xu C, Mao C, Chen Y. Causal relationship between antihypertensive drugs and Hashimoto's thyroiditis: a drug-target Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1419346. [PMID: 39435355 PMCID: PMC11491371 DOI: 10.3389/fendo.2024.1419346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 09/17/2024] [Indexed: 10/23/2024] Open
Abstract
Introduction and objectives Recent studies have indicated a potential association of hypertension with Hashimoto's thyroiditis (HT) and other autoimmune diseases, yet the impact of antihypertensive drugs on HT risk is not well understood. Methods We employed a drug-target Mendelian randomization approach to investigate the prolonged impact of 9 classes of antihypertensive medications on HT susceptibility in European and Asian populations. Genetic variants close to or within genes associated with the drug targets and systolic blood pressure (SBP) were utilized to mimic the effects of antihypertensive medications. We focused on drugs linked to a lower risk of coronary artery disease for our main analysis. We gathered genetic data on SBP and HT risk from comprehensive genome-wide association studies available for European and Asian groups. For a supplementary analysis, we used expression quantitative trait loci (eQTLs) related to drug target genes as proxies. Results Our analysis revealed that the use of calcium channel blockers (CCBs) is linked to a reduced risk of HT in both European (OR [95% CI]: 0.96 [0.95 to 0.98] per 1 mmHg decrease in SBP; p = 3.51×10-5) and Asian populations (OR [95% CI]: 0.28 [0.12, 0.66]; p = 3.54×10-3). Moreover, genetically mimicking the use of loop diuretics (OR [95% CI]: 0.94 [0.91, 0.97]; p = 3.57×10-5) and thiazide diuretics (0.98 [0.96, 0.99]; p = 3.83×10-3) showed a significant association with a decreased risk of HT only in European population. These outcomes were confirmed when eQTLs were employed to represent the effects of antihypertensive medications. Conclusion The study suggests that CCBs and diuretics could potentially reduce the risk of HT in different populations. Additional research is needed to assess the feasibility of repurposing antihypertensive medications for the prevention of HT.
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Affiliation(s)
- Bing Cui
- Department of Blood Transfusion, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, ;China
| | - Aqin Chen
- Department of Blood Transfusion, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, ;China
| | - Chengcheng Xu
- Department of Nuclear Medicine, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, ;China
| | - Chaoming Mao
- Department of Nuclear Medicine, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, ;China
| | - Yuehua Chen
- Department of Nuclear Medicine, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, ;China
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Fan B, Zhao JV. Utilizing genetics and proteomics to assess the role of antihypertensive drugs in human longevity and the underlying pathways: a Mendelian randomization study. EUROPEAN HEART JOURNAL. CARDIOVASCULAR PHARMACOTHERAPY 2024; 10:537-546. [PMID: 38769606 DOI: 10.1093/ehjcvp/pvae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 04/24/2024] [Accepted: 05/07/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Antihypertensive drugs are known to lower cardiovascular mortality, but the role of different types of antihypertensive drugs in lifespan has not been clarified. Moreover, the underlying mechanisms remain unclear. METHODS AND RESULTS To minimize confounding, we used Mendelian randomization to assess the role of different antihypertensive drug classes in longevity and examined the pathways via proteins. Genetic variants associated with systolic blood pressure (SBP) corresponding to drug-target genes were used as genetic instruments. The genetic associations with lifespan were obtained from a large genome-wide association study including 1 million European participants from UK Biobank and LifeGen. For significant antihypertensive drug classes, we performed sex-specific analysis, drug-target analysis, and colocalization. To examine the mediation pathways, we assessed the associations of 2291 plasma proteins with lifespan, and examined the associations of drug classes with the proteins affecting lifespan. After correcting for multiple testing, genetically proxied beta-blockers (BBs), calcium channel blockers (CCBs), and vasodilators were related to longer life years (BBs: 2.03, 95% CI 0.78-3.28 per 5 mmHg reduction in SBP, CCBs: 3.40, 95% CI 1.47-5.33, and vasodilators: 2.92, 95% CI 1.08-4.77). The beneficial effects of BBs and CCBs were more obvious in men. ADRB1, CACNA2D2, CACNB3, CPT1A, CPT2, and EDNRA genes were related to extended lifespan, with CPT2 further supported by colocalization evidence. Eighty-six proteins were related to lifespan, of which four proteins were affected by CCBs. CDH1 may mediate the association between CCBs and lifespan. CONCLUSIONS Beta-blockers, CCBs, and vasodilators may prolong lifespan, with potential sex differences for BBs and CCBs. The role of CCBs in lifespan is partly mediated by CDH1. Prioritizing the potential protein targets can provide new insights into healthy aging.
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Affiliation(s)
- Bohan Fan
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR, China
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Dib MJ, Azzo JD, Zhao L, Salman O, Gan S, De Buyzere ML, De Meyer T, Ebert C, Gunawardhana K, Liu L, Gordon D, Seiffert D, Ching-Pin C, Zamani P, Cohen JB, Pourmussa B, Kun S, Gill D, Burgess S, van Empel V, Richards AM, Dennis J, Javaheri A, Mann DL, Cappola TP, Rietzschel E, Chirinos JA. Proteome-Wide Genetic Investigation of Large Artery Stiffness. JACC Basic Transl Sci 2024; 9:1178-1191. [PMID: 39534640 PMCID: PMC11551872 DOI: 10.1016/j.jacbts.2024.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 05/28/2024] [Accepted: 05/28/2024] [Indexed: 11/16/2024]
Abstract
The molecular mechanisms contributing to large artery stiffness (LAS) are not fully understood. The aim of this study was to investigate the association between circulating plasma proteins and LAS using complementary proteomic and genomic analyses. A total of 106 proteins associated with carotid-femoral pulse-wave velocity, a noninvasive measure of LAS, were identified in 1,178 individuals from the Asklepios study cohort. Mendelian randomization analyses revealed causal effects of 13 genetically predicted plasma proteins on pulse pressure, including cartilage intermediate layer protein-2, high-temperature requirement A serine peptidase-1, and neuronal growth factor-1. These findings suggest potential novel therapeutic targets to reduce LAS and its related diseases.
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Affiliation(s)
- Marie-Joe Dib
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Joe David Azzo
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lei Zhao
- Bristol Myers Squibb, Lawrenceville, New Jersey, USA
| | - Oday Salman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sushrima Gan
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Marc L. De Buyzere
- Department of Cardiovascular Diseases, Ghent University Hospital, Ghent, Belgium
| | - Tim De Meyer
- Department of Mathematical Modelling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | | | | | - Laura Liu
- Bristol Myers Squibb, Lawrenceville, New Jersey, USA
| | - David Gordon
- Bristol Myers Squibb, Lawrenceville, New Jersey, USA
| | | | | | - Payman Zamani
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jordana B. Cohen
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Renal-Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bianca Pourmussa
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Seavmeiyin Kun
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom
| | - Stephen Burgess
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Vanessa van Empel
- Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - A. Mark Richards
- Cardiovascular Research Institute, National University of Singapore, Singapore, Singapore
- Christchurch Heart Institute, University of Otago, Christchurch, New Zealand
| | | | - Ali Javaheri
- Washington University School of Medicine, St. Louis, Missouri, USA
- John J. Cochran Veterans Hospital, St. Louis, Missouri, USA
| | - Douglas L. Mann
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Thomas P. Cappola
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ernst Rietzschel
- Department of Cardiovascular Diseases, Ghent University Hospital, Ghent, Belgium
| | - Julio A. Chirinos
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Øvretveit K, Ingeström EML, Spitieris M, Tragante V, Thomas LF, Steinsland I, Brumpton BM, Gudbjartsson DF, Holm H, Stefansson K, Wisløff U, Hveem K. Polygenic Interactions With Environmental Exposures in Blood Pressure Regulation: The HUNT Study. J Am Heart Assoc 2024; 13:e034612. [PMID: 39291479 DOI: 10.1161/jaha.123.034612] [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: 04/23/2024] [Accepted: 07/10/2024] [Indexed: 09/19/2024]
Abstract
BACKGROUND The essential hypertension phenotype results from an interplay between genetic and environmental factors. The influence of lifestyle exposures such as excess adiposity, alcohol consumption, tobacco use, diet, and activity patterns on blood pressure (BP) is well established. Additionally, polygenic risk scores for BP traits are associated with clinically significant phenotypic variation. However, interactions between genetic and environmental risk factors in hypertension morbidity and mortality are poorly characterized. METHODS AND RESULTS We used genotype and phenotype data from up to 49 234 participants from the HUNT (Trøndelag Health Study) to model gene-environment interactions between genome-wide polygenic risk scores for systolic BP and diastolic BP and 125 environmental exposures. Among the 125 environmental exposures assessed, 108 and 100 were independently associated with SBP and DBP, respectively. Of these, 12 interactions were identified for genome-wide PRSs for systolic BP and 4 for genome-wide polygenic risk scores for diastolic BP, 2 of which were overlapping (P < 2 × 10-4). We found evidence for gene-dependent influence of lifestyle factors such as cardiorespiratory fitness, dietary patterns, and tobacco exposure, as well as biomarkers such as serum cholesterol, creatinine, and alkaline phosphatase on BP. CONCLUSIONS Individuals that are genetically susceptible to high BP may be more vulnerable to common acquired risk factors for hypertension, but these effects appear to be modifiable. The gene-dependent influence of several common acquired risk factors indicates the potential of genetic data combined with lifestyle assessments in risk stratification, and gene-environment-informed risk modeling in the prevention and management of hypertension.
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Affiliation(s)
- Karsten Øvretveit
- HUNT Center for Molecular and Clinical Epidemiology (MCE), Department of Public Health and Nursing Norwegian University of Science and Technology (NTNU) Trondheim Norway
| | - Emma M L Ingeström
- Cardiac Exercise Research Group (CERG), Department of Circulation and Medical Imaging Norwegian University of Science and Technology (NTNU) Trondheim Norway
| | - Michail Spitieris
- HUNT Center for Molecular and Clinical Epidemiology (MCE), Department of Public Health and Nursing Norwegian University of Science and Technology (NTNU) Trondheim Norway
- Department of Mathematical Sciences Norwegian University of Science and Technology (NTNU) Trondheim Norway
| | | | - Laurent F Thomas
- HUNT Center for Molecular and Clinical Epidemiology (MCE), Department of Public Health and Nursing Norwegian University of Science and Technology (NTNU) Trondheim Norway
- Department of Clinical and Molecular Medicine Norwegian University of Science and Technology (NTNU) Trondheim Norway
| | - Ingelin Steinsland
- Department of Mathematical Sciences Norwegian University of Science and Technology (NTNU) Trondheim Norway
| | - Ben M Brumpton
- HUNT Center for Molecular and Clinical Epidemiology (MCE), Department of Public Health and Nursing Norwegian University of Science and Technology (NTNU) Trondheim Norway
- HUNT Research Centre, Department of Public Health and Nursing Norwegian University of Science and Technology (NTNU) Levanger Norway
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen Inc. Reykjavik Iceland
- School of Engineering and Natural Sciences University of Iceland Reykjavik Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen Inc. Reykjavik Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc. Reykjavik Iceland
- Faculty of Medicine University of Iceland Reykjavik Iceland
| | - Ulrik Wisløff
- Cardiac Exercise Research Group (CERG), Department of Circulation and Medical Imaging Norwegian University of Science and Technology (NTNU) Trondheim Norway
| | - Kristian Hveem
- HUNT Center for Molecular and Clinical Epidemiology (MCE), Department of Public Health and Nursing Norwegian University of Science and Technology (NTNU) Trondheim Norway
- Department of Innovation and Research, St. Olav's Hospital Trondheim Norway
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Acharya S, Liao S, Jung WJ, Kang YS, Moghaddam VA, Feitosa MF, Wojczynski MK, Lin S, Anema JA, Schwander K, Connell JO, Province MA, Brent MR. A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study. Hum Genet 2024; 143:1241-1252. [PMID: 39276247 PMCID: PMC11485042 DOI: 10.1007/s00439-024-02701-1] [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: 03/07/2024] [Accepted: 08/15/2024] [Indexed: 09/16/2024]
Abstract
The Long Life Family Study (LLFS) enrolled 4953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8 × 10-7), 29 of which replicated in the Framingham Heart Study (FHS) cohort. Notably, 20 of the 29 replicated genes do not have a previously known trait-associated variant in the GWAS Catalog within 50 kb. Thirteen modules in Protein-Protein Interaction (PPI) networks are significantly enriched in genes with low meta-analysis p-values for at least one trait, three of which are replicated in the FHS cohort. The functional annotation of genes in these modules showed a significant over-representation of trait-related biological processes including sterol transport, protein-lipid complex remodeling, and immune response regulation. Among major findings, our results suggest a role of triglyceride-associated and mast-cell functional genes FCER1A, MS4A2, GATA2, HDC, and HRH4 in atherosclerosis risks. Our findings also suggest that lower expression of ATG2A, a gene we found to be associated with BMI, may be both a cause and consequence of obesity. Finally, our results suggest that ENPP3 may play an intermediary role in triglyceride-induced inflammation. Our pipeline is freely available and implemented in the Nextflow workflow language, making it easily runnable on any compute platform ( https://nf-co.re/omicsgenetraitassociation ).
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Affiliation(s)
- Sandeep Acharya
- Division of Computational and Data Sciences, Washington University, St Louis, MO, USA
| | - Shu Liao
- Department of Computer Science and Engineering, Washington University, St Louis, MO, USA
| | - Wooseok J Jung
- Department of Computer Science and Engineering, Washington University, St Louis, MO, USA
| | - Yu S Kang
- Department of Computer Science and Engineering, Washington University, St Louis, MO, USA
| | - Vaha Akbary Moghaddam
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Shiow Lin
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Jason A Anema
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Karen Schwander
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Jeff O Connell
- Department of Medicine, University of Maryland, Baltimore, MD, USA
| | - Michael A Province
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Michael R Brent
- Department of Computer Science and Engineering, Washington University, St Louis, MO, USA.
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McCallum L, Lip S, McConnachie A, Brooksbank K, MacIntyre IM, Doney A, Llano A, Aman A, Caparrotta TM, Ingram G, Mackenzie IS, Dominiczak AF, MacDonald TM, Webb DJ, Padmanabhan S. UMOD Genotype-Blinded Trial of Ambulatory Blood Pressure Response to Torasemide. Hypertension 2024; 81:2049-2059. [PMID: 39077768 PMCID: PMC11460757 DOI: 10.1161/hypertensionaha.124.23122] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 07/19/2024] [Indexed: 07/31/2024]
Abstract
BACKGROUND UMOD (uromodulin) has been linked to hypertension through potential activation of Na+-K+-2Cl- cotransporter (NKCC2), a target of loop diuretics. We posited that hypertensive patients carrying the rs13333226-AA UMOD genotype would demonstrate greater blood pressure responses to loop diuretics, potentially mediated by this UMOD/NKCC2 interaction. METHODS This prospective, multicenter, genotype-blinded trial evaluated torasemide (torsemide) efficacy on systolic blood pressure (SBP) reduction over 16 weeks in nondiabetic, hypertensive participants uncontrolled on ≥1 nondiuretic antihypertensive for >3 months. The primary end point was the change in 24-hour ambulatory SBP (ABPM SBP) and SBP response trajectories between baseline and 16 weeks by genotype (AA versus AG/GG) due to nonrandomized groups at baseline (ClinicalTrials.gov: NCT03354897). RESULTS Of 251 enrolled participants, 222 received torasemide and 174 demonstrated satisfactory treatment adherence and had genotype data. The study participants were middle-aged (59±11 years), predominantly male (62%), obese (body mass index, 32±7 kg/m2), with normal eGFR (92±17 mL/min/1.73 m²) and an average baseline ABPM of 138/81 mm Hg. Significant reductions in mean ABPM SBP were observed in both groups after 16 weeks (AA, -6.57 mm Hg [95% CI, -8.44 to -4.69]; P<0.0001; AG/GG, -3.22 [95% CI, -5.93 to -0.51]; P=0.021). The change in mean ABPM SBP (baseline to 16 weeks) showed a difference of -3.35 mm Hg ([95% CI, -6.64 to -0.05]; P=0.048) AA versus AG/GG genotypes. The AG/GG group displayed a rebound in SBP from 8 weeks, differing from the consistent decrease in the AA group (P=0.004 for difference in trajectories). CONCLUSIONS Our results confirm a plausible interaction between UMOD and NKCC2 and suggest a potential role for genotype-guided use of loop diuretics in hypertension management. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT03354897.
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Affiliation(s)
- Linsay McCallum
- Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom (L.M.C., S.L., A.L., G.I., S.P.)
- School of Cardiovascular and Metabolic Health (L.M.C., S.L., K.B., A.A., A.F.D., S.P.), University of Glasgow, Scotland, United Kingdom
| | - Stefanie Lip
- Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom (L.M.C., S.L., A.L., G.I., S.P.)
- School of Cardiovascular and Metabolic Health (L.M.C., S.L., K.B., A.A., A.F.D., S.P.), University of Glasgow, Scotland, United Kingdom
| | - Alex McConnachie
- Robertson Centre for Biostatistics, School of Health and Wellbeing (A.M.C.), University of Glasgow, Scotland, United Kingdom
| | - Katriona Brooksbank
- School of Cardiovascular and Metabolic Health (L.M.C., S.L., K.B., A.A., A.F.D., S.P.), University of Glasgow, Scotland, United Kingdom
| | - Iain M. MacIntyre
- Clinical Pharmacology Unit and Research Centre, University of Edinburgh/BHF Centre of Research Excellence, United Kingdom (I.M.I., T.M.C., D.J.W.)
| | - Alexander Doney
- MEMO Research, University of Dundee, Ninewells Hospital and Medical School, United Kingdom (A.D., I.S.M., T.M.M.D.)
| | - Andrea Llano
- Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom (L.M.C., S.L., A.L., G.I., S.P.)
| | - Alisha Aman
- School of Cardiovascular and Metabolic Health (L.M.C., S.L., K.B., A.A., A.F.D., S.P.), University of Glasgow, Scotland, United Kingdom
| | - Thomas M. Caparrotta
- Clinical Pharmacology Unit and Research Centre, University of Edinburgh/BHF Centre of Research Excellence, United Kingdom (I.M.I., T.M.C., D.J.W.)
| | - Gareth Ingram
- Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom (L.M.C., S.L., A.L., G.I., S.P.)
| | - Isla S. Mackenzie
- MEMO Research, University of Dundee, Ninewells Hospital and Medical School, United Kingdom (A.D., I.S.M., T.M.M.D.)
| | - Anna F. Dominiczak
- School of Cardiovascular and Metabolic Health (L.M.C., S.L., K.B., A.A., A.F.D., S.P.), University of Glasgow, Scotland, United Kingdom
| | - Thomas M. MacDonald
- MEMO Research, University of Dundee, Ninewells Hospital and Medical School, United Kingdom (A.D., I.S.M., T.M.M.D.)
| | - David J. Webb
- Clinical Pharmacology Unit and Research Centre, University of Edinburgh/BHF Centre of Research Excellence, United Kingdom (I.M.I., T.M.C., D.J.W.)
| | - Sandosh Padmanabhan
- Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom (L.M.C., S.L., A.L., G.I., S.P.)
- School of Cardiovascular and Metabolic Health (L.M.C., S.L., K.B., A.A., A.F.D., S.P.), University of Glasgow, Scotland, United Kingdom
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Ye C, Liu D, Kong L, Wang Y, Dou C, Xu M, Zheng J, Zheng R, Li M, Zhao Z, Lu J, Chen Y, Wang W, Bi Y, Xu Y, Wang T, Ning G. Effect of Relative Protein Intake on Hypertension and Mediating Role of Physical Fitness and Circulating Fatty Acids: A Mendelian Randomization Study. Mayo Clin Proc 2024; 99:1589-1605. [PMID: 39001774 DOI: 10.1016/j.mayocp.2024.02.019] [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] [Received: 10/10/2023] [Revised: 01/25/2024] [Accepted: 02/20/2024] [Indexed: 07/15/2024]
Abstract
OBJECTIVE To investigate the causal effect of protein intake on hypertension and the related mediating pathways. PATIENTS AND METHODS Using genome-wide association study summary statistics of European ancestry, we applied univariable and multivariable Mendelian randomization to estimate the bidirectional associations of relative protein intake and related metabolomic signatures with hypertension (FinnGen: Ncase=42,857/Ncontrol=162,837; UK Biobank: Ncase=77,723/Ncontrol=330,366) and blood pressure (International Consortium of Blood Pressure: N=757,601) and two-step Mendelian randomization to assess the mediating roles of 40 cardiometabolic factors therein. Mendelian randomization estimates of hypertension from FinnGen and UK Biobank were meta-analyzed without heterogeneity. We performed the study from May 15, 2023, to September 15, 2023. RESULTS Each 1-SD higher relative protein intake was causally associated with 69% (odds ratio, 0.31; 95% CI, 0.11 to 0.89) lower hypertension risk independent of the effects of other macronutrients, and was the only macronutrient associated with 2.21 (95% CI, 0.52 to 3.91) mm Hg lower pulse pressure, in a unidirectional manner. Higher plant protein-related metabolomic signature (glycine) was associated with lower hypertension risk and pulse pressure, whereas higher animal protein-related metabolomic signatures (leucine, isoleucine, valine, and isovalerylcarnitine [only systolic blood pressure]) were associated with higher hypertension risk, pulse pressure, and systolic blood pressure. The effect of relative protein intake on hypertension was causally mediated by frailty index (mediation proportion, 40.28%), monounsaturated fatty acids (13.81%), saturated fatty acids (11.39%), grip strength (5.34%), standing height (3.99%), and sitting height (3.61%). CONCLUSION Higher relative protein intake causally reduces the risk of hypertension, partly mediated by physical fitness and circulating fatty acids.
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Affiliation(s)
- Chaojie Ye
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dong Liu
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lijie Kong
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiying Wang
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chun Dou
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Xu
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zheng
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruizhi Zheng
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Guang Ning
- 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, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Sung HL, Lin WY. Causal effects of cardiovascular health on five epigenetic clocks. Clin Epigenetics 2024; 16:134. [PMID: 39334501 PMCID: PMC11438310 DOI: 10.1186/s13148-024-01752-5] [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: 08/03/2024] [Accepted: 09/25/2024] [Indexed: 09/30/2024] Open
Abstract
BACKGROUND This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored. METHODS AND RESULTS We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population. CONCLUSIONS Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.
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Affiliation(s)
- Hsien-Liang Sung
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Room 501, No. 17, Xu-Zhou Road, Taipei, 100, Taiwan
| | - Wan-Yu Lin
- Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Room 501, No. 17, Xu-Zhou Road, Taipei, 100, Taiwan.
- Master of Public Health Degree Program, College of Public Health, National Taiwan University, Taipei, Taiwan.
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Parker N, Koch E, Shadrin AA, Fuhrer J, Hindley GFL, Stinson S, Jaholkowski P, Tesfaye M, Dale AM, Wingo TS, Wingo AP, Frei O, O'Connell KS, Smeland OB, Andreassen OA. Leveraging the Genetics of Psychiatric Disorders to Prioritize Potential Drug Targets and Compounds. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.24.24314069. [PMID: 39399035 PMCID: PMC11469398 DOI: 10.1101/2024.09.24.24314069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Background Genetics has the potential to inform biologically relevant drug treatment and repurposing which may ultimately improve patient care. In this study, we combine methods which leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds. Methods We used the largest available genome-wide association studies, in European ancestry, of four psychiatric disorders [i.e., attention deficit hyperactivity disorder (ADHD), bipolar disorder, depression, and schizophrenia] along with genes encoding drug targets. With this data, we conducted drug enrichment analyses incorporating the novel and biologically specific GSA-MiXeR tool. We then conducted a series of molecular trait analyses using large-scale transcriptomic and proteomic datasets sampled from brain and blood tissue. This included the novel use of the UK Biobank proteomic data for a proteome-wide association study of psychiatric disorders. With the accumulated evidence, we prioritize potential drug targets and compounds for each disorder. Findings We reveal candidate drug targets shared across multiple disorders as well as disorder-specific targets. Drug prioritization indicated genetic support for several currently used psychotropic medications including the antipsychotic paliperidone as the top ranked drug for schizophrenia. We also observed genetic support for other commonly used psychotropics (e.g., clozapine, risperidone, duloxetine, lithium, and valproic acid). Opportunities for drug repurposing were revealed such as cholinergic drugs for ADHD, estrogens for depression, and gabapentin enacarbil for schizophrenia. Our findings also indicate the genetic liability to schizophrenia is associated with reduced brain and blood expression of CYP2D6, a gene encoding a metabolizer of drugs and neurotransmitters, suggesting a genetic risk for poor drug response and altered neurotransmission. Interpretation Here we present a series of complimentary and comprehensive analyses that highlight the utility of genetics for informing drug development and repurposing for psychiatric disorders. Our findings present novel opportunities for refining psychiatric treatment.
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Affiliation(s)
- Nadine Parker
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Elise Koch
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Alexey A Shadrin
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Julian Fuhrer
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Guy F L Hindley
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Stinson
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Piotr Jaholkowski
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Markos Tesfaye
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anders M Dale
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Thomas S Wingo
- Department of Neurology, University of California, Davis, Sacramento, CA USA
| | - Aliza P Wingo
- Department of Psychiatry, University of California, Davis, Sacramento, CA, USA
- Division of Mental Health, VA Medical Center, Mather, CA, USA
| | - Oleksandr Frei
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Kevin S O'Connell
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Olav B Smeland
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- Centre for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, Norway
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Chen J, Chen L, Zhang X, Yao W, Xue Z. Exploring causal associations of antioxidants from supplements and diet with attention deficit/hyperactivity disorder in European populations: a Mendelian randomization analysis. Front Nutr 2024; 11:1415793. [PMID: 39381354 PMCID: PMC11459460 DOI: 10.3389/fnut.2024.1415793] [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: 04/11/2024] [Accepted: 09/10/2024] [Indexed: 10/10/2024] Open
Abstract
Background Antioxidants from both supplements and diet have been suggested to potentially reduce oxidative stress in individuals with ADHD. However, there is a lack of studies utilizing the Mendelian randomization (MR) method to explore the relationship between dietary and supplemental antioxidants with ADHD. Methods This study employed two-sample mendelian randomization. Various specific antioxidant dietary supplements (such as coffee, green tea, herbal tea, standard tea, and red wine intake per week), along with diet-derived circulating antioxidants including Vitamin C (ascorbate), Vitamin E (α-tocopherol), Vitamin E (γ-tocopherol), carotene, Vitamin A (retinol), zinc, and selenium (N = 2,603-428,860), were linked to independent single nucleotide polymorphisms (SNPs). Data on ADHD was gathered from six sources, comprising 246,888 participants. The primary analytical method utilized was inverse variance weighting (IVW), with sensitivity analysis conducted to assess the robustness of the main findings. Results In different diagnostic periods for ADHD, we found that only green tea intake among the antioxidants was significantly associated with a reduced risk of ADHD in males (OR: 0.977, CI: 0.963-0.990, p < 0.001, FDR = 0.065), with no evidence of pleiotropy or heterogeneity observed in the results. Additionally, a nominal causal association was found between green tea intake and childhood ADHD (OR: 0.989, 95% CI: 0.979-0.998, p = 0.023, FDR = 0.843). No causal relationships were detected between the intake of other antioxidant-rich diets and ADHD. Conclusion Our study found a significant inverse association between green tea intake and male ADHD, suggesting that higher green tea consumption may reduce ADHD risk in males. Further research is needed to explore optimal doses and underlying mechanisms.
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Affiliation(s)
- Jing Chen
- Department of Pediatrics, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lifei Chen
- Department of Pediatrics, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xinguang Zhang
- Department of Pediatrics, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wenbo Yao
- Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zheng Xue
- Department of Pediatrics, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Zhu Y, Wang Y, Cui Z, Liu F, Hu C, Hu J. Multi-trait analysis reveals risk loci for heart failure and the shared genetic etiology with blood lipids, blood pressure, and blood glucose. Cell Rep 2024; 43:114735. [PMID: 39276349 DOI: 10.1016/j.celrep.2024.114735] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 06/22/2024] [Accepted: 08/23/2024] [Indexed: 09/17/2024] Open
Abstract
Phenotypic associations have been reported between heart failure (HF) and blood lipids (BLs), blood pressure (BP), and blood glucose (BG). However, the shared genetic etiology underlying these associations remains incompletely understood. Conducting a large-scale multi-trait association study for HF with these traits, we discovered 143 previously unreported genomic risk loci for HF. Results showed that 46, 35, and 14 colocalized loci were shared by HF with BLs, BP, and BG, respectively. Notably, the loci shared by HF with these traits rarely overlapped, indicating distinct mechanisms. The combination of gene-mapping, gene-based, and transcriptome-wide association analyses prioritized noteworthy candidate genes (such as lipoprotein lipase [LPL], G protein-coupled receptor kinase 5 [GRK5], and troponin C1, slow skeletal and cardiac type [TNNC1]) for HF. Enrichment analysis revealed that HF exhibited comparable characteristics to cardiovascular traits and metabolic traits correlated to BLs, BP, and BG. Finally, we reported drug repurposing candidates and plasma protein targets for HF. These results provide biological insights into the pathogenesis of these comorbidities of HF.
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Affiliation(s)
- Yanchen Zhu
- Cardiology Department, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Yahui Wang
- Cardiology Department, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Zhaorui Cui
- Cardiology Department, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Fani Liu
- Cardiology Department, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Chunyu Hu
- Graduate School, China Academy of Chinese Medical Sciences, Beijing, China.
| | - Jiqiang Hu
- Cardiology Department, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China.
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132
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Wang N, Ye Z, Ma T. TIPS: a novel pathway-guided joint model for transcriptome-wide association studies. Brief Bioinform 2024; 25:bbae587. [PMID: 39550224 PMCID: PMC11568880 DOI: 10.1093/bib/bbae587] [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: 08/02/2024] [Revised: 10/03/2024] [Accepted: 10/30/2024] [Indexed: 11/18/2024] Open
Abstract
In the past two decades, genome-wide association studies (GWAS) have pinpointed numerous SNPs linked to human diseases and traits, yet many of these SNPs are in non-coding regions and hard to interpret. Transcriptome-wide association studies (TWAS) integrate GWAS and expression reference panels to identify the associations at gene level with tissue specificity, potentially improving the interpretability. However, the list of individual genes identified from univariate TWAS contains little unifying biological theme, leaving the underlying mechanisms largely elusive. In this paper, we propose a novel multivariate TWAS method that Incorporates Pathway or gene Set information, namely TIPS, to identify genes and pathways most associated with complex polygenic traits. We jointly modeled the imputation and association steps in TWAS, incorporated a sparse group lasso penalty in the model to induce selection at both gene and pathway levels and developed an expectation-maximization algorithm to estimate the parameters for the penalized likelihood. We applied our method to three different complex traits: systolic and diastolic blood pressure, as well as a brain aging biomarker white matter brain age gap in UK Biobank and identified critical biologically relevant pathways and genes associated with these traits. These pathways cannot be detected by traditional univariate TWAS + pathway enrichment analysis approach, showing the power of our model. We also conducted comprehensive simulations with varying heritability levels and genetic architectures and showed our method outperformed other established TWAS methods in feature selection, statistical power, and prediction. The R package that implements TIPS is available at https://github.com/nwang123/TIPS.
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Affiliation(s)
- Neng Wang
- Department of Mathematics, University of Maryland, College Park, MD 20742, United States
- Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, United States
| | - Zhenyao Ye
- Department of Epidemiology and Public Health, University of Maryland, Baltimore, MD 21201, United States
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, United States
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Xu L, Zhou G, Jiang W, Zhang H, Dong Y, Guan L, Zhao H. JointPRS: A Data-Adaptive Framework for Multi-Population Genetic Risk Prediction Incorporating Genetic Correlation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.29.564615. [PMID: 37961111 PMCID: PMC10634936 DOI: 10.1101/2023.10.29.564615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Genetic prediction accuracy for non-European populations is hindered by the limited sample size of Genome-wide association studies (GWAS) data in these populations. Additionally, it is challenging to tune model parameters with a small tuning dataset for methods that require tuning data, which is often the case for non-European samples. To address these challenges, we propose JointPRS, a novel, data-adaptive framework that simultaneously models multiple populations using GWAS summary statistics. JointPRS incorporates genetic correlation structures into the prediction framework, enabling accurate performance even without individual-level tuning data. Additionally, it uniquely employs a data-adaptive approach, providing a robust solution when only a small tuning dataset is available. Through extensive simulations and real data applications to 22 quantitative traits and four binary traits in five continental populations (European (EUR); East Asian (EAS); African (AFR); South Asian (SAS); and Admixed American (AMR)) evaluated using the UK Biobank (UKBB) and All of Us (AoU), we demonstrate that JointPRS outperforms six other state-of-art methods across three different data scenarios (no tuning data, tuning and testing data from the same cohort, and tuning and testing data from different cohorts) for most traits in non-European populations, while maintaining model simplicity and computational efficiency.
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Affiliation(s)
- Leqi Xu
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Geyu Zhou
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Wei Jiang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Yikai Dong
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Leying Guan
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
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134
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Zhang S, Yu H, Zhao Y, Gong A, Guan C, Chen S, Xiao B, Lu J. Genetically predicted hypothyroidism, thyroid hormone treatment, and the risk of cardiovascular diseases: a mendelian randomization study. BMC Cardiovasc Disord 2024; 24:479. [PMID: 39256710 PMCID: PMC11386095 DOI: 10.1186/s12872-024-04132-2] [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: 02/22/2024] [Accepted: 08/19/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND In this study, we explored the impact of hypothyroidism and thyroid hormone replacement therapy on the risk of developing cardiovascular diseases, including myocardial infarction, heart failure, and cardiac death, via Mendelian randomization analysis. METHODS Genetic instrumental variables related to hypothyroidism, levothyroxine treatment (refer to Participants were taking the medication levothyroxine sodium) and adverse cardiovascular events were obtained from a large publicly available genome-wide association study. Two-sample Mendelian randomization analysis was performed via inverse-variance weighting as the primary method. To ensure the reliability of our findings, we performed MR‒Egger regression, Cochran's Q statistic, and leave-one-out analysis. Additionally, multivariable Mendelian randomization was employed to regulate confounding factors, including systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), diabetes, cholesterol, low-density lipoprotein (LDL), triglycerides and metformin. A mediation analysis was conducted to assess the mediating effects on the association between exposure and outcome by treating atrial fibrillation and stroke as mediator variables of levothyroxine treatment and bradycardia as mediator variables of hypothyroidism. RESULTS Genetically predicted hypothyroidism and levothyroxine treatment were significantly associated with the risk of experiencing myocardial infarction [levothyroxine: odds ratio (OR) 3.75, 95% confidence interval (CI): 1.80-7.80; hypothyroidism: OR: 15.11, 95% CI: 2.93-77.88]. Levothyroxine treatment was also significantly related to the risk of experiencing heart failure (OR: 2.16, 95% CI: 1.21-3.88). However, no associations were detected between hypothyroidism and the risk of experiencing heart failure or between hypothyroidism or levothyroxine treatment and the risk of experiencing cardiac death. After adjusting for confounding factors, the results remained stable. Additionally, mediation analysis indicated that atrial fibrillation and stroke may serve as potential mediators in the relationships between levothyroxine treatment and the risk of experiencing heart failure or myocardial infarction. CONCLUSION The results of our study suggest a positive association between hypothyroidism and myocardial infarction and highlight the potential effects of levothyroxine treatment, the main thyroid hormone replacement therapy approach, on increasing the risk of experiencing myocardial infarction and heart failure.
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Affiliation(s)
- Shuaidan Zhang
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Hangtian Yu
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Yan Zhao
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Angwei Gong
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Chengjian Guan
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Shuchen Chen
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Bing Xiao
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China
| | - Jingchao Lu
- Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, People's Republic of China.
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Broadaway KA, Brotman SM, Rosen JD, Currin KW, Alkhawaja AA, Etheridge AS, Wright F, Gallins P, Jima D, Zhou YH, Love MI, Innocenti F, Mohlke KL. Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits. Am J Hum Genet 2024; 111:1899-1913. [PMID: 39173627 PMCID: PMC11393674 DOI: 10.1016/j.ajhg.2024.07.017] [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: 01/04/2024] [Revised: 07/24/2024] [Accepted: 07/25/2024] [Indexed: 08/24/2024] Open
Abstract
Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.
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Affiliation(s)
- K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jonathan D Rosen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Abdalla A Alkhawaja
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Fred Wright
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA; Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA
| | - Paul Gallins
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Dereje Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Yi-Hui Zhou
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy, Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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R Muralitharan R, Nakai ME, Snelson M, Zheng T, Dinakis E, Xie L, Jama H, Paterson M, Shihata W, Wassef F, Vinh A, Drummond GR, Kaye DM, Mackay CR, Marques FZ. Influence of angiotensin II on the gut microbiome: modest effects in comparison to experimental factors. Cardiovasc Res 2024; 120:1155-1163. [PMID: 38518247 PMCID: PMC11368123 DOI: 10.1093/cvr/cvae062] [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: 10/18/2023] [Revised: 12/12/2023] [Accepted: 01/08/2024] [Indexed: 03/24/2024] Open
Abstract
AIMS Animal models are regularly used to test the role of the gut microbiome in hypertension. Small-scale pre-clinical studies have investigated changes to the gut microbiome in the angiotensin II hypertensive model. However, the gut microbiome is influenced by internal and external experimental factors, which are not regularly considered in the study design. Once these factors are accounted for, it is unclear if microbiome signatures are reproduceable. We aimed to determine the influence of angiotensin II treatment on the gut microbiome using a large and diverse cohort of mice and to quantify the magnitude by which other factors contribute to microbiome variations. METHODS AND RESULTS We conducted a retrospective study to establish a diverse mouse cohort resembling large human studies. We sequenced the V4 region of the 16S rRNA gene from 538 samples across the gastrointestinal tract of 303 male and female C57BL/6J mice randomized into sham or angiotensin II treatment from different genotypes, diets, animal facilities, and age groups. Analysing over 17 million sequencing reads, we observed that angiotensin II treatment influenced α-diversity (P = 0.0137) and β-diversity (i.e. composition of the microbiome, P < 0.001). Bacterial abundance analysis revealed patterns consistent with a reduction in short-chain fatty acid producers, microbial metabolites that lower blood pressure. Furthermore, animal facility, genotype, diet, age, sex, intestinal sampling site, and sequencing batch had significant effects on both α- and β-diversity (all P < 0.001). Sampling site (6.8%) and diet (6%) had the largest impact on the microbiome, while angiotensin II and sex had the smallest effect (each 0.4%). CONCLUSION Our large-scale data confirmed findings from small-scale studies that angiotensin II impacted the gut microbiome. However, this effect was modest relative to most of the other factors studied. Accounting for these factors in future pre-clinical hypertensive studies will increase the likelihood that microbiome findings are replicable and translatable.
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Affiliation(s)
- Rikeish R Muralitharan
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
- Institute for Medical Research, Ministry of Health Malaysia, Kuala Lumpur, Malaysia
- Victorian Heart Institute, Monash University, 631 Blackburn Road, Clayton, 3800 Melbourne, Australia
| | - Michael E Nakai
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
| | - Matthew Snelson
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
- Victorian Heart Institute, Monash University, 631 Blackburn Road, Clayton, 3800 Melbourne, Australia
| | - Tenghao Zheng
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
| | - Evany Dinakis
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
| | - Liang Xie
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
| | - Hamdi Jama
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
| | - Madeleine Paterson
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
| | - Waled Shihata
- Heart Failure Research Group, Baker Heart and Diabetes Institute, 75 Commercial Road, 3004 Melbourne, Australia
| | - Flavia Wassef
- Centre for Cardiovascular Biology and Disease Research (CCBDR), La Trobe Institute of Medical Science (LIMS), Bundoora, Victoria, Australia
- Department of Microbiology, Anatomy, Physiology and Pharmacology, School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Victoria, Australia
| | - Antony Vinh
- Centre for Cardiovascular Biology and Disease Research (CCBDR), La Trobe Institute of Medical Science (LIMS), Bundoora, Victoria, Australia
- Department of Microbiology, Anatomy, Physiology and Pharmacology, School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Victoria, Australia
| | - Grant R Drummond
- Centre for Cardiovascular Biology and Disease Research (CCBDR), La Trobe Institute of Medical Science (LIMS), Bundoora, Victoria, Australia
- Department of Microbiology, Anatomy, Physiology and Pharmacology, School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Victoria, Australia
| | - David M Kaye
- Heart Failure Research Group, Baker Heart and Diabetes Institute, 75 Commercial Road, 3004 Melbourne, Australia
- Department of Cardiology, Alfred Hospital, Melbourne, Australia
- Central Clinical School, Faculty of Medicine Nursing and Health Sciences, Monash University, Melbourne, Australia
| | - Charles R Mackay
- Infection and Immunity Program, Monash Biodiscovery Institute, Monash University, Melbourne, Australia
- Department of Biochemistry, Monash University, Melbourne, Australia
- School of Pharmaceutical Sciences, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
| | - Francine Z Marques
- Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash University, 18 Innovation Walk, Clayton, 3800 Melbourne, Australia
- Victorian Heart Institute, Monash University, 631 Blackburn Road, Clayton, 3800 Melbourne, Australia
- Heart Failure Research Group, Baker Heart and Diabetes Institute, 75 Commercial Road, 3004 Melbourne, Australia
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137
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Letsou W. Settling the score: what composite measures of social determinants tell us about hypertension risk. JNCI Cancer Spectr 2024; 8:pkae065. [PMID: 39222406 PMCID: PMC11368122 DOI: 10.1093/jncics/pkae065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 07/31/2024] [Indexed: 09/04/2024] Open
Affiliation(s)
- William Letsou
- Department of Biological and Chemical Sciences, New York Institute of Technology, Old Westbury, NY, USA
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138
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Huang R, Kong X, Geng R, Wu J, Chen T, Li J, Li C, Wu Y, You D, Zhao Y, Zhong Z, Ni S, Bai J. Joint and interactive associations of body mass index and genetic factors with cardiovascular disease: a prospective study in UK Biobank. BMC Public Health 2024; 24:2371. [PMID: 39223569 PMCID: PMC11367834 DOI: 10.1186/s12889-024-19916-6] [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: 01/15/2024] [Accepted: 08/28/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Both body mass index (BMI) and genetic factors independently contribute to cardiovascular disease (CVD). However, it is unclear whether genetic risk modifies the association between BMI and the risk of incident CVD. This study aimed to investigate whether BMI categories and genetic risk jointly and interactively contribute to incident CVD events, including hypertension (HTN), atrial fibrillation (AF), coronary heart disease (CHD), stroke, and heart failure (HF). METHODS A total of 496,851 participants from the UK Biobank with one or more new-onset CVD events were included in the analyses. BMI was categorized as normal weight (< 25.0 kg/m2), overweight (25.0-29.9 kg/m2), and obesity (≥ 30.0 kg/m2). Genetic risk for each outcome was defined as low (lowest tertile), intermediate (second tertile), and high (highest tertile) using polygenic risk score. The joint associations of BMI categories and genetic risk with incident CVD were investigated using Cox proportional hazard models. Additionally, additive interactions were evaluated. RESULTS Among the 496,851 participants, 270,726 (54.5%) were female, with a mean (SD) age was 56.5 (8.1) years. Over a median follow-up (IQR) of 12.4 (11.5-13.1) years, 102,131 (22.9%) participants developed HTN, 26,301 (5.4%) developed AF, 32,222 (6.9%) developed CHD, 10,684 (2.2%) developed stroke, and 13,304 (2.7%) developed HF. Compared with the normal weight with low genetic risk, the obesity with high genetic risk had the highest risk of CVD: HTN (HR: 3.96; 95%CI: 3.84-4.09), AF (HR: 3.60; 95%CI: 3.38-3.83), CHD (HR: 2.76; 95%CI: 2.61-2.91), stroke (HR: 1.44; 95%CI: 1.31-1.57), and HF (HR: 2.47; 95%CI: 2.27-2.69). There were significant additive interactions between BMI categories and genetic risk for HTN, AF, and CHD, with relative excess risk of 0.53 (95%CI: 0.43-0.62), 0.67 (95%CI: 0.51-0.83), and 0.37 (95%CI: 0.25-0.49), respectively. CONCLUSIONS BMI and genetic factors jointly and interactively contribute to incident CVD, especially among participants with high genetic risk. These findings have public health implications for identifying populations more likely to have cardiovascular benefit from weight loss interventions.
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Affiliation(s)
- Ruyu Huang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xinxin Kong
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Rui Geng
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Jingwei Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Temple University, Philadelphia, PA, 19122, USA
| | - Tao Chen
- Center for Health Economics, University of York, York, YO105DD, UK
| | - Jiong Li
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Chunjian Li
- Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Yaqian Wu
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Dongfang You
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Yang Zhao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Zihang Zhong
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
| | - Senmiao Ni
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
| | - Jianling Bai
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
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Dunn ME, Kithcart A, Kim JH, Ho AJH, Franklin MC, Romero Hernandez A, de Hoon J, Botermans W, Meyer J, Jin X, Zhang D, Torello J, Jasewicz D, Kamat V, Garnova E, Liu N, Rosconi M, Pan H, Karnik S, Burczynski ME, Zheng W, Rafique A, Nielsen JB, De T, Verweij N, Pandit A, Locke A, Chalasani N, Melander O, Schwantes-An TH, Baras A, Lotta LA, Musser BJ, Mastaitis J, Devalaraja-Narashimha KB, Rankin AJ, Huang T, Herman G, Olson W, Murphy AJ, Yancopoulos GD, Olenchock BA, Morton L. Agonist antibody to guanylate cyclase receptor NPR1 regulates vascular tone. Nature 2024; 633:654-661. [PMID: 39261724 PMCID: PMC11410649 DOI: 10.1038/s41586-024-07903-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 08/02/2024] [Indexed: 09/13/2024]
Abstract
Heart failure is a leading cause of morbidity and mortality1,2. Elevated intracardiac pressures and myocyte stretch in heart failure trigger the release of counter-regulatory natriuretic peptides, which act through their receptor (NPR1) to affect vasodilation, diuresis and natriuresis, lowering venous pressures and relieving venous congestion3-8. Recombinant natriuretic peptide infusions were developed to treat heart failure but have been limited by a short duration of effect9,10. Here we report that in a human genetic analysis of over 700,000 individuals, lifelong exposure to coding variants of the NPR1 gene is associated with changes in blood pressure and risk of heart failure. We describe the development of REGN5381, an investigational monoclonal agonist antibody that targets the membrane-bound guanylate cyclase receptor NPR1. REGN5381, an allosteric agonist of NPR1, induces an active-like receptor conformation that results in haemodynamic effects preferentially on venous vasculature, including reductions in systolic blood pressure and venous pressure in animal models. In healthy human volunteers, REGN5381 produced the expected haemodynamic effects, reflecting reductions in venous pressures, without obvious changes in diuresis and natriuresis. These data support the development of REGN5381 for long-lasting and selective lowering of venous pressures that drive symptomatology in patients with heart failure.
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Affiliation(s)
| | | | - Jee Hae Kim
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | | | | | - Jan de Hoon
- Center for Clinical Pharmacology, University Hospitals Leuven, Leuven, Belgium
| | - Wouter Botermans
- Center for Clinical Pharmacology, University Hospitals Leuven, Leuven, Belgium
| | | | - Ximei Jin
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | | | | | | | | | - Nina Liu
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | - Hao Pan
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | | | | | | | - Jonas B Nielsen
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Tanima De
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Niek Verweij
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Anita Pandit
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Adam Locke
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Naga Chalasani
- Indiana University School of Medicine & Indiana University Health, Indianapolis, IN, USA
| | - Olle Melander
- The Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Aris Baras
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Luca A Lotta
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | | | | | | | - Tammy Huang
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Gary Herman
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | | | | | | | | | - Lori Morton
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
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The Mega Vascular Cognitive Impairment and Dementia (MEGAVCID) consortium. A genome-wide association meta-analysis of all-cause and vascular dementia. Alzheimers Dement 2024; 20:5973-5995. [PMID: 39046104 PMCID: PMC11497727 DOI: 10.1002/alz.14115] [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: 06/09/2023] [Revised: 04/30/2024] [Accepted: 05/20/2024] [Indexed: 07/25/2024]
Abstract
INTRODUCTION Dementia is a multifactorial disease with Alzheimer's disease (AD) and vascular dementia (VaD) pathologies making the largest contributions. Yet, most genome-wide association studies (GWAS) focus on AD. METHODS We conducted a GWAS of all-cause dementia (ACD) and examined the genetic overlap with VaD. Our dataset includes 800,597 individuals, with 46,902 and 8702 cases of ACD and VaD, respectively. Known AD loci for ACD and VaD were replicated. Bioinformatic analyses prioritized genes that are likely functionally relevant and shared with closely related traits and risk factors. RESULTS For ACD, novel loci identified were associated with energy transport (SEMA4D), neuronal excitability (ANO3), amyloid deposition in the brain (RBFOX1), and magnetic resonance imaging markers of small vessel disease (SVD; HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). DISCUSSION Our study identified genetic risks underlying ACD, demonstrating overlap with neurodegenerative processes, vascular risk factors, and cerebral SVD. HIGHLIGHTS We conducted the largest genome-wide association study of all-cause dementia (ACD) and vascular dementia (VaD). Known genetic variants associated with AD were replicated for ACD and VaD. Functional analyses identified novel loci for ACD and VaD. Genetic risks of ACD overlapped with neurodegeneration, vascular risk factors, and cerebral small vessel disease.
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Hoang N, Sardaripour N, Ramey GD, Schilling K, Liao E, Chen Y, Park JH, Bledsoe X, Landman BA, Gamazon ER, Benton ML, Capra JA, Rubinov M. Integration of estimated regional gene expression with neuroimaging and clinical phenotypes at biobank scale. PLoS Biol 2024; 22:e3002782. [PMID: 39269986 PMCID: PMC11424006 DOI: 10.1371/journal.pbio.3002782] [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: 03/22/2024] [Revised: 09/25/2024] [Accepted: 08/01/2024] [Indexed: 09/15/2024] Open
Abstract
An understanding of human brain individuality requires the integration of data on brain organization across people and brain regions, molecular and systems scales, as well as healthy and clinical states. Here, we help advance this understanding by leveraging methods from computational genomics to integrate large-scale genomic, transcriptomic, neuroimaging, and electronic-health record data sets. We estimated genetically regulated gene expression (gr-expression) of 18,647 genes, across 10 cortical and subcortical regions of 45,549 people from the UK Biobank. First, we showed that patterns of estimated gr-expression reflect known genetic-ancestry relationships, regional identities, as well as inter-regional correlation structure of directly assayed gene expression. Second, we performed transcriptome-wide association studies (TWAS) to discover 1,065 associations between individual variation in gr-expression and gray-matter volumes across people and brain regions. We benchmarked these associations against results from genome-wide association studies (GWAS) of the same sample and found hundreds of novel associations relative to these GWAS. Third, we integrated our results with clinical associations of gr-expression from the Vanderbilt Biobank. This integration allowed us to link genes, via gr-expression, to neuroimaging and clinical phenotypes. Fourth, we identified associations of polygenic gr-expression with structural and functional MRI phenotypes in the Human Connectome Project (HCP), a small neuroimaging-genomic data set with high-quality functional imaging data. Finally, we showed that estimates of gr-expression and magnitudes of TWAS were generally replicable and that the p-values of TWAS were replicable in large samples. Collectively, our results provide a powerful new resource for integrating gr-expression with population genetics of brain organization and disease.
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Affiliation(s)
- Nhung Hoang
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Neda Sardaripour
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Grace D. Ramey
- Biological and Medical Informatics Division, University of California, San Francisco, California, United States of America
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America
| | - Kurt Schilling
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Emily Liao
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Yiting Chen
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Jee Hyun Park
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Xavier Bledsoe
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Bennett A. Landman
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Eric R. Gamazon
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Mary Lauren Benton
- Department of Computer Science, Baylor University, Waco, Texas, United States of America
| | - John A. Capra
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California, United States of America
| | - Mikail Rubinov
- Department of Computer Science, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Psychology, Vanderbilt University, Nashville, Tennessee, United States of America
- Howard Hughes Medical Institute Janelia Research Campus, Ashburn, Virginia, United States of America
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Zhou Y, Ye R, Guo X. Modifiable risk factors mediating the impact of educational inequality on heart failure: A Mendelian randomization study. Prev Med 2024; 186:108098. [PMID: 39127305 DOI: 10.1016/j.ypmed.2024.108098] [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: 05/14/2024] [Revised: 08/07/2024] [Accepted: 08/07/2024] [Indexed: 08/12/2024]
Abstract
BACKGROUND Heart failure (HF) is a rapidly growing global disease burden with high mortality rates. We aimed to utilize mendelian randomization (MR) analyses to investigate the association between educational attainment (EA) and HF, and to evaluate the contribution of modifiable risk factors as mediators. METHODS We applied a two-sample MR approach based on the largest genome-wide association studies (GWAS) to investigate the causal relationship between EA and HF. Data collection was conducted in July 2023. We then conducted mediation analyses to explore whether body mass index (BMI), blood pressure, and type 2 diabetes mellitus (T2DM) mediate the effect of EA on HF, and utilized multivariable MR to estimate the proportion of mediation attributed to these factors. RESULTS Genetically predicted 3.4 years of additional education was associated with a decrease in the risk of HF (OR 0.76 for each 3.4 years of schooling; 95% CI 0.72, 0.81). BMI, T2DM, systolic blood pressure, and diastolic blood pressure mediated 40.82% (95% CI: 28.86%, 52.77%), 18.00% (95% CI: 12.10%, 23.90%), 11.60% (95% CI: 7.63%, 15.56%), and 7.80% (95% CI: 4.63%, 10.96%) of the EA-HF association, respectively. All risk factors combined were estimated to mediate 63.81% (95% CI: 45.91%, 81.71%) of the effect of EA on HF. CONCLUSION Higher EA has a protective effect against the risk of HF, and potential mechanisms may include regulation of BMI, blood pressure, and blood glucose. Further research is needed to understand whether interventions targeting these factors could influence the association between EA and HF risk.
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Affiliation(s)
- Yijiang Zhou
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou 310003, Zhejiang, China.
| | - Runze Ye
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou 310003, Zhejiang, China.
| | - Xiaogang Guo
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou 310003, Zhejiang, China.
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Nguyen NH, Sheng S, Banerjee A, Guerriero CJ, Chen J, Wang X, Mackie TD, Welling PA, Kleyman TR, Bahar I, Carlson AE, Brodsky JL. Characterization of hyperactive mutations in the renal potassium channel ROMK uncovers unique effects on channel biogenesis and ion conductance. Mol Biol Cell 2024; 35:ar119. [PMID: 39024255 PMCID: PMC11449386 DOI: 10.1091/mbc.e23-12-0494] [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: 12/22/2023] [Revised: 07/08/2024] [Accepted: 07/11/2024] [Indexed: 07/20/2024] Open
Abstract
Hypertension affects one billion people worldwide and is the most common risk factor for cardiovascular disease, yet a comprehensive picture of its underlying genetic factors is incomplete. Amongst regulators of blood pressure is the renal outer medullary potassium (ROMK) channel. While select ROMK mutants are prone to premature degradation and lead to disease, heterozygous carriers of some of these same alleles are protected from hypertension. Therefore, we hypothesized that gain-of-function (GoF) ROMK variants which increase potassium flux may predispose people to hypertension. To begin to test this hypothesis, we employed genetic screens and a candidate-based approach to identify six GoF variants in yeast. Subsequent functional assays in higher cells revealed two variant classes. The first group exhibited greater stability in the endoplasmic reticulum, enhanced channel assembly, and/or increased protein at the cell surface. The second group of variants resided in the PIP2-binding pocket, and computational modeling coupled with patch-clamp studies demonstrated lower free energy for channel opening and slowed current rundown, consistent with an acquired PIP2-activated state. Together, these findings advance our understanding of ROMK structure-function, suggest the existence of hyperactive ROMK alleles in humans, and establish a system to facilitate the development of ROMK-targeted antihypertensives.
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Affiliation(s)
- Nga H. Nguyen
- Department of Biological Sciences, School of Medicine, University of Pittsburgh, PA 15260
| | - Shaohu Sheng
- Renal-Electrolyte Division, Department of Medicine, School of Medicine, University of Pittsburgh, PA 15260
| | - Anupam Banerjee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, PA 15260
| | | | - Jingxin Chen
- Renal-Electrolyte Division, Department of Medicine, School of Medicine, University of Pittsburgh, PA 15260
| | - Xueqi Wang
- Renal-Electrolyte Division, Department of Medicine, School of Medicine, University of Pittsburgh, PA 15260
| | - Timothy D. Mackie
- Department of Biological Sciences, School of Medicine, University of Pittsburgh, PA 15260
| | - Paul A. Welling
- Division of Nephrology, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | - Thomas R. Kleyman
- Renal-Electrolyte Division, Department of Medicine, School of Medicine, University of Pittsburgh, PA 15260
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, PA 15260
| | - Anne E. Carlson
- Department of Biological Sciences, School of Medicine, University of Pittsburgh, PA 15260
| | - Jeffrey L. Brodsky
- Department of Biological Sciences, School of Medicine, University of Pittsburgh, PA 15260
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Kumar N, Yang ML, Sun P, Hunker KL, Li J, Jia J, Fan F, Wang J, Ning X, Gao W, Xu M, Zhang J, Chang L, Chen YE, Huo Y, Zhang Y, Ganesh SK. Genetic variation in CCDC93 is associated with elevated central systolic blood pressure, impaired arterial relaxation, and mitochondrial dysfunction. PLoS Genet 2024; 20:e1011151. [PMID: 39250516 PMCID: PMC11421807 DOI: 10.1371/journal.pgen.1011151] [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: 03/17/2023] [Revised: 09/24/2024] [Accepted: 01/23/2024] [Indexed: 09/11/2024] Open
Abstract
Genetic studies of blood pressure (BP) traits to date have been performed on conventional measures by brachial cuff sphygmomanometer for systolic BP (SBP) and diastolic BP, integrating several physiologic occurrences. Genetic associations with central SBP (cSBP) have not been well-studied. Genetic discovery studies of BP have been most often performed in European-ancestry samples. Here, we investigated genetic associations with cSBP in a Chinese population and functionally validated the impact of a novel associated coiled-coil domain containing 93 (CCDC93) gene on BP regulation. An exome-wide association study (EWAS) was performed using a mixed linear model of non-invasive cSBP and peripheral BP traits in a Han Chinese population (N = 5,954) from Beijing, China genotyped with a customized Illumina ExomeChip array. We identified four SNP-trait associations with three SNPs, including two novel associations (rs2165468-SBP and rs33975708-cSBP). rs33975708 is a coding variant in the CCDC93 gene, c.535C>T, p.Arg179Cys (MAF = 0.15%), and was associated with increased cSBP (β = 29.3 mmHg, P = 1.23x10-7). CRISPR/Cas9 genome editing was used to model the effect of Ccdc93 loss in mice. Homozygous Ccdc93 deletion was lethal prior to day 10.5 of embryonic development. Ccdc93+/- heterozygous mice were viable and morphologically normal, with 1.3-fold lower aortic Ccdc93 protein expression (P = 0.0041) and elevated SBP as compared to littermate Ccdc93+/+ controls (110±8 mmHg vs 125±10 mmHg, P = 0.016). Wire myography of Ccdc93+/- aortae showed impaired acetylcholine-induced relaxation and enhanced phenylephrine-induced contraction. RNA-Seq transcriptome analysis of Ccdc93+/- mouse thoracic aortae identified significantly enriched pathways altered in fatty acid metabolism and mitochondrial metabolism. Plasma free fatty acid levels were elevated in Ccdc93+/- mice (96±7mM vs 124±13mM, P = 0.0031) and aortic mitochondrial dysfunction was observed through aberrant Parkin and Nix protein expression. Together, our genetic and functional studies support a novel role of CCDC93 in the regulation of BP through its effects on vascular mitochondrial function and endothelial function.
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Affiliation(s)
- Nitin Kumar
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Min-Lee Yang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Pengfei Sun
- Department of Cardiology, Peking University First hospital, Beijing, China
- Department of Cardiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Kristina L. Hunker
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Jianping Li
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Jia Jia
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Fangfang Fan
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Jinghua Wang
- Laboratory of Epidemiology, Tianjin Neurological Institute, Tianjin, China
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xianjia Ning
- Laboratory of Epidemiology, Tianjin Neurological Institute, Tianjin, China
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Gao
- Department of Cardiology, Peking University Third hospital, Beijing, China
| | - Ming Xu
- Department of Cardiology, Peking University Third hospital, Beijing, China
| | - Jifeng Zhang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Lin Chang
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Y. Eugene Chen
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Yong Huo
- Department of Cardiology, Peking University First hospital, Beijing, China
| | - Yan Zhang
- Department of Cardiology, Peking University First hospital, Beijing, China
- Institute of Cardiovascular Disease, Peking University First Hospital, Beijing, China
- Hypertension Precision Diagnosis and Treatment Research Center, Peking University First Hospital, Beijing, China
| | - Santhi K. Ganesh
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
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145
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Sysojev AÖ, Alfredsson L, Klareskog L, Silberberg GN, Saevarsdottir S, Padyukov L, Magnusson PKE, Askling J, Westerlind H. Minor Genetic Overlap Among Rheumatoid Arthritis, Myocardial Infarction, and Myocardial Infarction Risk Determinants. Arthritis Rheumatol 2024; 76:1344-1352. [PMID: 38782598 DOI: 10.1002/art.42918] [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: 02/05/2024] [Revised: 03/22/2024] [Accepted: 05/16/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVE The aim of this study was to investigate whether a shared genetic susceptibility exists between individuals with rheumatoid arthritis (RA) and individuals with myocardial infarction (MI)-including major MI risk factors-and to quantify the degree of any such overlap. METHODS Genome-wide association study (GWAS) data for individuals with RA were constructed from a sample of 26,637 Swedish patients with RA and controls without RA. For patients with MI, GWAS data were obtained from a previously published meta-analysis. Genome-wide genetic correlation was estimated via linkage disequilibrium score regression. LAVA was employed to estimate local genetic correlations in ~2,500 nonoverlapping loci, including the major histocompatibility complex. The controls without RA were used for reference panel data. We also assessed stratified estimates of both genome-wide and local genetic correlation based on subsamples of individuals with seropositive RA and those with seronegative RA. Furthermore, genome-wide genetic correlation was estimated between RA and selected cardiovascular risk factors to elucidate pleiotropic relationships. RESULTS Following quality control, our GWAS of patients with RA consisted of 25,826 individuas. Genome-wide genetic correlation between patients with RA and MI was estimated to 0.13 (95% confidence interval -0.03 to 0.29). Six regions exhibited significant local genetic correlation, though none harbored any known risk single-nucleotide polymorphisms for either of the two traits. Estimates were similar in both individuals with seropositive RA and those with seronegative RA. No statistically significant genetic correlations were observed between RA risk factors and any of the MI risk factors. CONCLUSION Our findings indicate that genetic overlap between patients with RA and MI is minor. Furthermore, genetic overlap between RA and MI risk factors seem unlikely to provide a major contribution to the increased risk of MI observed in patients with RA.
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Affiliation(s)
| | | | - Lars Klareskog
- Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Gilad N Silberberg
- Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Saedis Saevarsdottir
- Karolinska Institute, Stockholm, Sweden, and deCODE genetics, Reykjavik, Iceland. Members of the Swedish Rheumatology Quality Register Biobank Group are shown in Appendix A
| | - Leonid Padyukov
- Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | | | - Johan Askling
- Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
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146
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Ni F, Liu X, Wang S. Impact of negative emotions and insomnia on sepsis: A mediation Mendelian randomization study. Comput Biol Med 2024; 180:108858. [PMID: 39067155 DOI: 10.1016/j.compbiomed.2024.108858] [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: 04/19/2024] [Revised: 06/05/2024] [Accepted: 07/06/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND Negative emotions and insomnia (NEI) can lead to inflammation, which is a characteristic of sepsis. However, the interaction among NEI and sepsis has not yet been proven. Therefore, Mendelian mediation was used to explore this relationship in this study. METHODS The genetic correlation NEI and sepsis was assessed by via linkage disequilibrium scores (LDSC). A two-sample Mendelian randomization (MR) study design was performed to examine the causal association between NEI and sepsis using the inverse variance weighted (IVW) method. The reliability of the results was estimated by weighted median and MR-Egger methods, but heterogeneity was evaluated via Radial and Cochran's Q tests. Biases in gene polymorphisms were checked by MR-Egger regression and MR-PRESSO. Mendelian mediation analyses were applied to quantify the intermediary effect and proportional contribution. RESULTS A genetic link between sepsis and depression was determined via LDSC analysis. The relationship between depression and sepsis was revealed through MR analysis [odds ratio (OR) = 1.21, 95 % confidence interval (CI) = 1.08-1.36, p = 1.07 × 10-3)]. The results were not influenced by heterogeneity or pleiotropy biases. Chitinase 3 Like 1 (CHI3L1) was a mediator with a mediation effect size of 0.12. The ratio of the intermediated effect to total effect was 10.31 %. CONCLUSION CHI3L1 is a key factor which mediates the interaction between NEI and sepsis.
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Affiliation(s)
- Fengming Ni
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, 130021, China
| | - Xinmin Liu
- Department of Neurology, The First Hospital of Jilin University, Changchun, 130021, China
| | - Shaokun Wang
- Department of Emergency, The First Hospital of Jilin University, Changchun, 130021, China.
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147
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Du K, Li A, Zhang CY, Li SM, Chen P. Repurposing antihypertensive drugs for pain disorders: a drug-target mendelian randomization study. Front Pharmacol 2024; 15:1448319. [PMID: 39268473 PMCID: PMC11390634 DOI: 10.3389/fphar.2024.1448319] [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: 06/13/2024] [Accepted: 08/16/2024] [Indexed: 09/15/2024] Open
Abstract
Objective Addressing the rising prevalence of pain disorders and limitations of current analgesics, our study explores repurposing antihypertensive drugs for pain management, inspired by the link between hypertension and pain. We leverage a drug-target Mendelian Randomization (MR) approach to explore their dual benefits and establish causal connections. Methods A comprehensive compilation of antihypertensive drug classes was undertaken through British National Formulary, with their target genes identified using the DrugBank database. Relevant single nucleotide polymorphisms (SNPs) associated with these targets were selected from published genomic studies on systolic blood pressure (SBP) as genetic instruments. These SNPs were validated through MR against acute coronary artery disease (CAD) to ensure genes not linked to CAD were excluded from acting as proxies for antihypertensive drugs. An MR analysis of 29 pain-related outcomes was conducted using the FinnGen R10 database employing the selected and validated genetic instruments. We utilized the Inverse Variance Weighted (IVW) method for primary analysis, applying Bonferroni correction to control type I error. IVW's multiplicative random effects (MRE) addressed heterogeneity, and MR-PRESSO managed pleiotropy, ensuring accurate causal inference. Results Our analysis differentiates strong and suggestive evidence in linking antihypertensive drugs to pain disorder risks. Strong evidence was found for adrenergic neuron blockers increasing migraine without aura risk, loop diuretics reducing panniculitis, and vasodilator antihypertensives lowering limb pain risk. Suggestive evidence suggests alpha-adrenoceptor blockers might increase migraine risk, while beta-adrenoceptor blockers could lower radiculopathy risk. Adrenergic neuron blockers also show a potential protective effect against coxarthrosis (hip osteoarthritis) and increased femgenpain risk (pain and other conditions related to female genital organs and menstrual cycle). Additionally, suggestive links were found between vasodilator antihypertensives and reduced radiculopathy risk, and both alpha-adrenoceptor blockers and renin inhibitors possibly decreasing dorsalgianas risk (unspecified dorsalgia). These findings highlight the intricate effects of antihypertensive drugs on pain disorders, underlining the need for further research. Conclusion The findings indicate that antihypertensive medications may exert varied effects on pain management, suggesting a repurposing potential for treating specific pain disorders. The results advocate for further research to confirm these associations and to explore underlying mechanisms, to optimize pain management practices.
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Affiliation(s)
- Kai Du
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Ao Li
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Chen-Yu Zhang
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Shu-Ming Li
- Department of Pain Medicine, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Ping Chen
- Department of Pain Medicine, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
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148
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Liu K, Zhou D, Chen L, Hao S. Depression and type 2 diabetes risk: a Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1436411. [PMID: 39268231 PMCID: PMC11390465 DOI: 10.3389/fendo.2024.1436411] [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: 05/23/2024] [Accepted: 08/05/2024] [Indexed: 09/15/2024] Open
Abstract
Background Extensive observational evidence has suggested an association between depression and type 2 diabetes (T2D). However, the causal relationships between these two diseases require further investigation. This study aimed to evaluate the bidirectional causal effect between two types of depression and T2D using two-sample Mendelian randomization (MR). Methods We applied two-step MR techniques, using single-nucleotide polymorphisms (SNPs) as the genetic instruments for analysis. We utilized summary data from genome-wide association studies (GWASs) for major depression (MD), depressive status (frequency of depressed mood in the last two weeks), T2D, and other known T2D risk factors such as obesity, sedentary behavior (time spent watching television), and blood pressure. The analysis utilized inverse variance weighted (IVW), MR-Egger regression, weighted median, weighted mode, MR pleiotropy residual sum, and outlier methods to determine potential causal relationships. Results The study found that MD was positively associated with T2D, with an odds ratio (OR) of 1.26 (95% CI: 1.10-1.43, p = 5.6×10-4) using the IVW method and an OR of 1.21 (95% CI: 1.04-1.41, p = 0.01) using the weighted median method. Depressive status was also positively associated with T2D, with an OR of 2.26 (95% CI: 1.03-4.94, p = 0.04) and an OR of 3.62 (95% CI: 1.33-9.90, p = 0.01) using the IVW and weighted median methods, respectively. No causal effects of MD and depressive status on T2D risk factors were observed, and T2D did not influence these factors. Conclusion Our study demonstrates a causal relationship between depression and an increased risk of developing T2D, with both major depression and depressive status being positively associated with T2D.
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Affiliation(s)
- Kaiyuan Liu
- Department of Endocrinology, Zhejiang Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, Zhejiang, China
| | - Diyi Zhou
- Department of Endocrinology, Zhejiang Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, Zhejiang, China
| | - Lijun Chen
- Department of Endocrinology, Zhejiang Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, Zhejiang, China
| | - Sida Hao
- Department of Urology, Zhejiang Integrated Traditional Chinese and Western Medicine Hospital, Hangzhou, Zhejiang, China
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Shen J, Valentim W, Friligkou E, Overstreet C, Choi K, Koller D, O’Donnell CJ, Stein MB, Gelernter J, Posttraumatic Stress Disorder Working Group of the Psychiatric Genomics Consortium, Lv H, Sun L, Falcone GJ, Polimanti R, Pathak GA. Genetics of posttraumatic stress disorder and cardiovascular conditions using Life's Essential 8, Electronic Health Records, and Heart Imaging. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.20.24312181. [PMID: 39228734 PMCID: PMC11370495 DOI: 10.1101/2024.08.20.24312181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
BACKGROUND Patients with post-traumatic stress disorder (PTSD) experience higher risk of adverse cardiovascular (CV) outcomes. This study explores shared loci, and genes between PTSD and CV conditions from three major domains: CV diagnoses from electronic health records (CV-EHR), cardiac and aortic imaging, and CV health behaviors defined in Life's Essential 8 (LE8). METHODS We used genome-wide association study (GWAS) of PTSD (N=1,222,882), 246 CV diagnoses based on EHR data from Million Veteran Program (MVP; N=458,061), UK Biobank (UKBB; N=420,531), 82 cardiac and aortic imaging traits (N=26,893), and GWAS of traits defined in the LE8 (N = 282,271 ~ 1,320,016). Shared loci between PTSD and CV conditions were identified using local genetic correlations (rg), and colocalization (shared causal variants). Overlapping genes between PTSD and CV conditions were identified from genetically regulated proteome expression in brain and blood tissues, and subsequently tested to identify functional pathways and gene-drug targets. Epidemiological replication of EHR-CV diagnoses was performed in AllofUS cohort (AoU; N=249,906). RESULTS Among the 76 PTSD-susceptibility risk loci, 33 loci exhibited local rg with 45 CV-EHR traits (|rg|≥0.4), four loci with eight heart imaging traits(|rg|≥0.5), and 44 loci with LE8 factors (|rg|≥0.36) in MVP. Among significantly correlated loci, we found shared causal variants (colocalization probability > 80%) between PTSD and 17 CV-EHR (in MVP) at 11 loci in MVP, that also replicated in UKBB and/or other cohorts. Of the 17 traits, the observational analysis in the AoU showed PTSD was associated with 13 CV-EHR traits after accounting for socioeconomic factors and depression diagnosis. PTSD colocalized with eight heart imaging traits on 2 loci and with LE8 factors on 31 loci. Leveraging blood and brain proteome expression, we found 33 and 122 genes, respectively, shared between PTSD and CVD. Blood proteome genes were related to neuronal and immune processes, while the brain proteome genes converged on metabolic and calcium-modulating pathways (FDR p <0.05). Drug repurposing analysis highlighted DRD2, NOS1, GFAP, and POR as common targets of psychiatric and CV drugs. CONCLUSION PTSD-CV comorbidities exhibit shared risk loci, and genes involved in tissue-specific regulatory mechanisms.
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Affiliation(s)
- Jie Shen
- Department of Cardiology, Children’s Hospital of Soochow University, Suzhou, China
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Wander Valentim
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Faculdade de Medicina da Universidade Federal de Minas Gerais, Belo Horizonte, State of Minas Gerais, Brazil
| | - Eleni Friligkou
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cassie Overstreet
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Karmel Choi
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Dora Koller
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain
| | - Christopher J. O’Donnell
- Department of Psychiatry, UC San Diego School of Medicine, University of California, San Diego, La Jolla, California; Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, California; Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Murray B. Stein
- Cardiology Section, Department of Medicine, Veterans Affairs Boston Healthcare System, West Roxbury, Massachusetts
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | | | - Haitao Lv
- Department of Cardiology, Children’s Hospital of Soochow University, Suzhou, China
| | - Ling Sun
- Department of Cardiology, Children’s Hospital of Soochow University, Suzhou, China
| | - Guido J. Falcone
- Center for Brain and Mind Health Yale University New Haven CT USA; Department of Neurology Yale University New Haven CT USA
| | - Renato Polimanti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA
| | - Gita A. Pathak
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
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Vargas JD, Abbas M, Goodney G, Gaye A. Regulatory Roles of Long Non-Coding RNAs in Arterial Stiffness and Hypertension: Insights from Two African American Studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.11.607492. [PMID: 39372764 PMCID: PMC11451656 DOI: 10.1101/2024.08.11.607492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Background Arterial stiffness, commonly assessed via pulse wave velocity (PWV), is marked by reduced arterial elasticity and serves as a significant risk factor for cardiovascular disease and an early indicator of hypertension. This study investigated the regulatory roles of long non-coding RNAs (lncRNAs) in modulating mRNAs associated with arterial stiffness and hypertension, with a particular focus on African Americans, a population disproportionately impacted by hypertension. Methods We utilized whole-blood transcriptome sequencing data from two African American (AA) cohorts with high hypertension prevalence: the GENE-FORECAST study (436 subjects) and the MH-GRID study (179 subjects). Our objectives were to: (1) identify lncRNAs and mRNAs differentially expressed (DE) between the upper and lower tertiles of PWV, (2) determine DE lncRNAs associated with the expression levels of each DE mRNA, and (3) link the lncRNA-modulated mRNAs to hypertension across both datasets. Results Differential expression analysis revealed 1,035 DE mRNAs and 31 DE lncRNAs between upper and lower PWV groups. Then lncRNA-mRNA pairs significantly associated were identified, involving 31 unique lncRNAs and 1,034 unique mRNAs. Finally, 22 of the lncRNA-modulated mRNAs initially linked to PWV were found associated with hypertension, in both datasets. Interestingly, 30 lncRNAs were linked to the expression of UCP2 (Uncoupling Protein 2), a gene implicated in oxidative stress and endothelial function. Conclusions Our findings underscore the significant roles of lncRNAs in regulating gene expression associated with arterial stiffness and hypertension. The differential expression of UCP2 in relation to PWV and hypertension, along with its potential regulation by lncRNAs, offers valuable insights into the molecular mechanisms underlying arterial stiffness and its connection with hypertension.
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Affiliation(s)
| | - Malak Abbas
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Gabriel Goodney
- National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Amadou Gaye
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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