AUTHOR=Xu Shihan , Liu Yanfei , Wang Qing , Liu Fenglan , Xu Fengqin , Liu Yue 

TITLE=Mendelian randomization study reveals a causal relationship between coronary artery disease and cognitive impairment

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1150432

DOI=10.3389/fcvm.2023.1150432

ISSN=2297-055X

ABSTRACT=Background: Growing evidence suggests that Coronary artery disease (CAD) is associated with cognitive impairment. However, these results from observational studies was not entirely consistent, with some detecting no such association. And it is necessary to explore the causal relationship between CAD and cognitive impairment.
Objective: We aimed to explore the potential casual relationship between CAD and cognitive impairment by using bidirectional two-sample mendelian randomization (MR) analyses.
Methods: Instrument variants were extracted according to strict selection criteria. And we used publicly available summary-level GWAS data. Five different methods of MR [random-effect inverse-variance weighted (IVW), MR Egger, weighted median, weighted mode and Wald ratio] were used to explore the causal relationship between CAD and cognitive impairment.
Results: There was little evidence to support a causal effect of CAD on cognitive impairment in the forward MR analysis. In the reverse MR analyses, We detect causal effects of fluid intelligence score(IVW β=-0.12,95%CI of -0.18 to -0.06,P=6.8×10−5 ) , cognitive performance(IVW β=-0.18,95%CI of -0.28 to -0.08,P=5.8×10−4) and dementia with lewy bodies(IVW OR=1.07,95%CI of 1.04 to 1.10,P=1.1×10−5) on CAD.
Conclusion: This MR analysis provides evidence of a causal association between cognitive impairment and CAD. Our findings highlight the importance of screening for coronary heart disease in patients of cognitive impairment, which might provide new insight into the prevention of CAD. Moreover, our study provides clues for risk factor identification and early prediction of CAD.