Bidirectional Mendelian randomization study of brain imaging-derived phenotypes unveils causal associations between thalamic nuclei volume and stroke risk

Abstract

Aim: Recent advances in brain-imaging techniques have enabled the identification of brain imaging-derived phenotypes (IDPs), representing physiological brain structure. Observational studies have suggested a correlation between these IDPs and stroke, which is confounded and based on limited samples. To investigate the causal relationship between IDPs and stroke and its subtypes for an in-depth mechanistic comprehension of their interplay, we conducted a bidirectional two-sample Mendelian Randomization (MR) study leveraging the largest-scale genome-wide association studies (GWAS) of IDPs and stroke subtypes.

Methods: We utilized GWAS summary statistics from the BIG40 dataset, which included nearly 3,935 IDPs among 33,224 individuals, and GIGASTROKE, which included three etiological ischemia subtypes, as well as cerebral ischemia, intracerebral hemorrhage stroke, and overall stroke among 73,652 stroke cases and 1,234,808 controls.

Results: In the forward MR analysis, we identified eight significant IDPs influencing the risk of stroke and its subtypes after Bonferroni correction. Notably, the volume of the lateral posterior thalamus in the right hemisphere exhibited a significant negative association with all ischemic stroke (OR = 0.79; 95%CI: 0.74 to 0.84; P = 1.21e-13), all stroke (OR = 0.84; 95%CI: 0.79 to 0.89; P = 2.45e-9), and large vessel stroke (OR = 0.54; 95%CI: 0.43 to 0.69; P = 3.01e-7). Conversely, no significant causal association was observed in the reverse MR analysis.

Conclusion: This study enhances our understanding of causality between IDPs and stroke by pinpointing specific causal associations. These findings provide valuable insights into the etiology of stroke, offering potential strategies for predicting and intervening in stroke risk at the level of brain imaging.

Keywords

Brain imaging-derived phenotypes / stroke / genetics / causal inference / Mendelian randomization

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