Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders

Guo, Jing; Yu, Ke; Dong, Shanshan; Shi, Yiting; Yu, Rong; Wu, Hao; Zhang, Kun; Jiang, Feng; Chen, Yi-Xiao; Guo, Yan; Yang, Tie‐Lin

doi:10.1038/s41593-022-01174-7

Cited by 68 publications

(45 citation statements)

References 104 publications

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“…Consistent with a recent study that estimated the bidirectional casual associations between microstructural WM and psychiatric disorders [ 17 ], we excluded 15 of 27 probabilistic tractography-based WM tracts that were also characterized by TBSS analysis, resulting in a total of 60 WM tracts (12 probabilistic tractography and 48 TBSS) in the following analyses. Finally, 360 WM IDPs (60 WM tracts × 6 measurements) were included in the present study, with each IDP presenting the mean (TBSS-based tracts) or weighted-mean value (probabilistic tractography-based tracts) of a measurement within a WM tract.…”

Section: Methodsmentioning

confidence: 99%

“…If two heritable traits are causally related, there should be a genetic correlation between them [ 24 ]. This strategy has been used in previous studies to reduce multiple testing [ 17 , 25 ]. Therefore, we first performed genetic correlation analysis before MR analysis to screen the WM IDPs that were genetically associated with migraine.…”

Section: Methodsmentioning

confidence: 99%

“…MR minimizes the issues of reverse causality and confounders in observational data because genetic variants are innate and relatively independent of self-selected behaviors [ 15 , 16 ]. Large-scale genome-wide association studies (GWAS) on both brain imaging-derived phenotypes (IDPs) and neuropsychiatric disorders provide opportunities to explore the causality between exposure (e.g., brain IDPs) and outcome (e.g., diseases) [ 17 ]. Using MR, a recent study explored the causal effects of subcortical regions and intracranial volume (ICV) on migraine [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

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Causal relationships between migraine and microstructural white matter: a Mendelian randomization study

Zhao

Zhao²,

Anttila³

et al. 2023

J Headache Pain

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Background Migraine is a disabling neurological disorder with the pathophysiology yet to be understood. The microstructural alteration in brain white matter (WM) has been suggested to be related to migraine in recent studies, but these evidence are observational essentially and cannot infer a causal relationship. The present study aims to reveal the causal relationship between migraine and microstructural WM using genetic data and Mendelian randomization (MR). Methods We collected the Genome-wide association study (GWAS) summary statistics of migraine (48,975 cases / 550,381 controls) and 360 WM imaging-derived phenotypes (IDPs) (31,356 samples) that were used to measure microstructural WM. Based on instrumental variables (IVs) selected from the GWAS summary statistics, we conducted bidirectional two-sample MR analyses to infer bidirectional causal associations between migraine and microstructural WM. In forward MR analysis, we inferred the causal effect of microstructural WM on migraine by reporting the odds ratio (OR) that quantified the risk change of migraine for per 1 standard deviation (SD) increase of IDPs. In reverse MR analysis, we inferred the causal effect of migraine on microstructural WM by reporting the β value that represented SDs of changes in IDPs were caused by migraine. Results Three WM IDPs showed significant causal associations (p < 3.29 × 10− 4, Bonferroni correction) with migraine and were proved to be reliable via sensitivity analysis. The mode of anisotropy (MO) of left inferior fronto-occipital fasciculus (OR = 1.76, p = 6.46 × 10− 5) and orientation dispersion index (OD) of right posterior thalamic radiation (OR = 0.78, p = 1.86 × 10− 4) exerted significant causal effects on migraine. Migraine exerted a significant causal effect on the OD of left superior cerebellar peduncle (β = − 0.09, p = 2.78 × 10− 4). Conclusions Our findings provided genetic evidence for the causal relationships between migraine and microstructural WM, bringing new insights into brain structure for the development and experience of migraine.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Causal relationships between migraine and microstructural white matter: a Mendelian randomization study

Zhao

Zhao²,

Anttila³

et al. 2023

J Headache Pain

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“…Another emerging trend is mining large-scale observational imaging datasets and imaging-derived phenotypes (IDPs) with the Mendelian randomization approach, i.e., using genome as the instrumental variable to evaluate the potential causal relationships between IDPs and neurological or psychiatric disorders (Guo et al, 2022;Taschler et al, 2022). Reid et al have been trying to formulate functional connectivity estimation using a causal inference framework but ended up mixing different levels of concepts and restating the significance of methods sensitivity analysis (Reid et al, 2019).…”

Section: Causality In Clinical Neurosciencementioning

confidence: 99%

Claim Causality with Clarity

Wang¹,

Wang²,

Zhang³

2022

Preprint

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Causal inference has attracted enormous attention in clinical neuroscience over the past years. Interpreting causal claims properly based on reported details is crucial for the researchers. In this review, we briefly introduced the statistical basis for causal inference in terms of the potential outcome framework and distinguished the different interpretations in RCT and observational studies. Based on the recent efforts in formulating neuroscience research into a causal framework, we provide 4 recommendations to facilitate open and reproducible causal inference research.

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“…The outline of this study is shown in Fig 1 . Briefly, referring to our previous study [22], we obtained the GWAS summary data of 587 reliably measured IDPs derived from up to 33,224 European individuals of the UK Biobank (Figure 1). Summary data of five T2D-related traits All rights reserved.…”

Section: Study Overviewmentioning

confidence: 99%

Evaluation of the causal associations between brain imaging-derived phenotypes and type 2 diabetes: a bidirectional Mendelian randomization study

Dong

Tang

et al. 2022

Preprint

Self Cite

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OBJECTIVE To investigate whether the association between brain imaging-derived phenotypes (IDPs) and Type 2 diabetes (T2D) related traits is causal. DESIGN Two sample, bidirectional Mendelian randomization study. SETTING Genome wide association study (GWAS) summary data taken from various cohorts comprised of the general population (mainly composed of Europeans). PARTICIPANTS Summary data were used from previous GWAS. For IDPs, the data included up to 33,224 European individuals from the UK Biobank. For T2D-related traits, the number of participants ranged from 63,396 to 455,313. MAIN OUTCOME MEASURES A total of 587 reliable IDPs and five T2D-related traits (T2D, fasting glucose, 2h-glucose post-challenge, glycated hemoglobin, and fasting insulin). RESULTS We identified 3 IDPs with potential causal effects on T2D or fasting insulin. For example, we observed that the area of the right rostral middle frontal cortex was negatively associated with the T2D risk (OR = 0.74, 95% CI 0.65 to 0.85, P = 1.31 x 10-5). In addition, we identified potential causal effects of T2D-related traits on 6 IDPs. For example, T2D was negatively associated with the volumes of the right superior frontal gyrus (beta = -0.05, 95% CI -0.08 to -0.03, P = 2.17 x 10-5) and the right paracentral lobule (beta = -0.05, 95% CI -0.07 to -0.02, P = 1.74 x 10-4). CONCLUSIONS Our results revealed strong genetic evidence for the bidirectional causal associations between brain neuroimaging phenotypes and T2D-related traits. This will contribute to better prediction and intervention for the risk of T2D.

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Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders

Cited by 68 publications

References 104 publications

Causal relationships between migraine and microstructural white matter: a Mendelian randomization study

Causal relationships between migraine and microstructural white matter: a Mendelian randomization study

Claim Causality with Clarity

Evaluation of the causal associations between brain imaging-derived phenotypes and type 2 diabetes: a bidirectional Mendelian randomization study

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