Cardiovascular Risk Factors and MRI Markers of Cerebral Small Vessel Disease

Background and objectives: Cardiovascular risk factors have been implicated in the etiology of cerebral small vessel disease (CSVD); however, whether the associations are causal remains unclear in part due to the susceptibility of observational studies to reverse causation and confounding. Here, we use mendelian randomization (MR) to determine which cardiovascular risk factors are likely to be involved in the etiology of CSVD. Methods: We used data from large-scale genome-wide association studies of European ancestry to identify genetic proxies for blood pressure, blood lipids, body mass index (BMI), type 2 diabetes, smoking initiation, cigarettes per day, and alcohol consumption. MR was performed to assess their association with 3 neuroimaging features that are altered in CSVD (white matter hyperintensities [WMH], fractional anisotropy [FA], and mean diffusivity [MD]) using genetic summary data from the UK Biobank (N = 31,855). Our primary analysis used inverse-weighted median MR, with validation using weighted median, MR-Egger, and a pleiotropy-minimizing approach. Finally, multivariable MR was performed to study the effects of multiple risk factors jointly. Results: MR analysis showed consistent associations across all methods for higher genetically proxied systolic and diastolic blood pressures with WMH, FA, and MD and for higher genetically proxied BMI with WMH. There was weaker evidence for associations between total cholesterol, low-density lipoprotein, smoking initiation, pulse pressure, and type 2 diabetes liability and at least 1 CSVD imaging feature, but these associations were not reproducible across all validation methods used. Multivariable MR analysis for blood pressure traits found that the effect was primarily through genetically proxied diastolic blood pressure across all CSVD traits. Discussion: Genetic predisposition to higher blood pressure, primarily diastolic blood pressure, and to higher BMI is associated with a higher burden of CSVD, suggesting a causal role. Improved management and treatment of these risk factors could reduce the burden of CSVD

Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

Background:Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. Methods:A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. Results:Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (beta=-4.82x10(-3) per year [95% CI, -6.49x10(-3) to -3.14x10(-3)]; P=1.82x10(-8)), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). Conclusions:The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH

Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

Background:Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. Methods:A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. Results:Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (beta=-4.82x10(-3) per year [95% CI, -6.49x10(-3) to -3.14x10(-3)]; P=1.82x10(-8)), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). Conclusions:The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH