Abstract
Red blood cell distribution width (RCDW) and mean corpuscular volume (MCV) are associated with different risk factors for hemorrhagic stroke. However, whether RCDW and MCV are causally related to hemorrhagic stroke remains poorly understood. Therefore, we explored the causality between RCDW/MCV and nontraumatic hemorrhagic strokes using Mendelian randomization (MR) methods. We extracted exposure and outcome summary statistics from the UK Biobank and FinnGen. We evaluated the causality of RCDW/MCV on four outcomes (subarachnoid hemorrhage [SAH], intracerebral hemorrhage [ICH], nontraumatic intracranial hemorrhage [nITH], and a combination of SAH, cerebral aneurysm, and aneurysm operations) using univariable MR (UMR) and multivariable MR (MVMR). We further performed colocalization and mediation analyses. UMR and MVMR revealed that higher genetically predicted MCV is protective of ICH (UMR: odds ratio [OR] = 0.89 [0.8–0.99], p = 0.036; MVMR: OR = 0.87 [0.78–0.98], p = 0.021) and nITH (UMR: OR = 0.89 [0.82–0.97], p = 0.005; MVMR: OR = 0.88 [0.8–0.96], p = 0.004). There were no strong causal associations between RCDW/MCV and any other outcome. Colocalization analysis revealed a shared causal variant between MCV and ICH; it was not reported to be associated with ICH. Proportion mediated via diastolic blood pressure was 3.1% (0.1%,14.3%) in ICH and 3.4% (0.2%,15.8%) in nITH. The study constitutes the first MR analysis on whether genetically elevated RCDW and MCV affect the risk of hemorrhagic strokes. UMR, MVMR, and mediation analysis revealed that MCV is a protective factor for ICH and nITH, which may inform new insights into the treatments for hemorrhagic strokes.
Original language | English |
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Article number | 100135 |
Journal | Human Genetics and Genomics Advances |
Volume | 3 |
Issue number | 4 |
Online published | 10 Aug 2022 |
DOIs | |
Publication status | Published - 13 Oct 2022 |
Research Keywords
- causal inference
- hemorrhagic stroke
- mean corpuscular volume
- Mendelian randomization
- red blood cell distribution width
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/
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Complex Disease Prediction, Prevention, and Treatment Using Computational Methods
HUANG, R. (Author), CHAN, K. H. K. (Supervisor), 26 Apr 2023Student thesis: Doctoral Thesis