Background and Purpose— Volumes of hemorrhage and perihematomal edema (PHE) are well-established biomarkers of primary and secondary injury, respectively, in spontaneous intracerebral hemorrhage. An automated imaging pipeline capable of accurately and rapidly quantifying these biomarkers would facilitate large cohort studies evaluating underlying mechanisms of injury. Methods— Regions of hemorrhage and PHE were manually delineated on computed tomography scans of patients enrolled in 2 intracerebral hemorrhage studies. Manual ground-truth masks from the first cohort were used to train a fully convolutional neural network to segment images into hemorrhage and PHE. The primary outcome was automated-versus-human concordance in hemorrhage and PHE volumes. The secondary outcome was voxel-by-voxel overlap of segmentations, quantified by the Dice similarity coefficient (DSC). Algorithm performance was validated on 84 scans from the second study. Results— Two hundred twenty-four scans from 124 patients with supratentorial intracerebral hemorrhage were used for algorithm derivation. Median volumes were 18 mL (interquartile range, 8–43) for hemorrhage and 12 mL (interquartile range, 5–30) for PHE. Concordance was excellent (0.96) for automated quantification of hemorrhage and good (0.81) for PHE, with DSC of 0.90 (interquartile range, 0.85–0.93) and 0.54 (0.39–0.65), respectively. External validation confirmed algorithm accuracy for hemorrhage (concordance 0.98, DSC 0.90) and PHE (concordance 0.90, DSC 0.55). This was comparable with the consistency observed between 2 human raters (DSC 0.90 for hemorrhage, 0.57 for PHE). Conclusions— We have developed a deep learning-based imaging algorithm capable of accurately measuring hemorrhage and PHE volumes. Rapid and consistent automated biomarker quantification may accelerate powerful and precise studies of disease biology in large cohorts of intracerebral hemorrhage patients.

Objective Observational studies point to an inverse correlation between low‐density lipoprotein (LDL) cholesterol levels and risk of intracerebral hemorrhage (ICH), but it remains unclear whether this association is causal. We tested the hypothesis that genetically elevated LDL is associated with reduced risk of ICH. Methods We constructed one polygenic risk score (PRS) per lipid trait (total cholesterol, LDL, high‐density lipoprotein [HDL], and triglycerides) using independent genomewide significant single nucleotide polymorphisms (SNPs) for each trait. We used data from 316,428 individuals enrolled in the UK Biobank to estimate the effect of each PRS on its corresponding trait, and data from 1,286 ICH cases and 1,261 matched controls to estimate the effect of each PRS on ICH risk. We used these estimates to conduct Mendelian Randomization (MR) analyses. Results We identified 410, 339, 393, and 317 lipid‐related SNPs for total cholesterol, LDL, HDL, and triglycerides, respectively. All four PRSs were strongly associated with their corresponding trait (all p < 1.00 × 10‐100). While one SD increase in the PRSs for total cholesterol (odds ratio [OR] = 0.92; 95% confidence interval [CI] = 0.85–0.99; p = 0.03) and LDL cholesterol (OR = 0.88; 95% CI = 0.81–0.95; p = 0.002) were inversely associated with ICH risk, no significant associations were found for HDL and triglycerides (both p > 0.05). MR analyses indicated that 1mmol/L (38.67mg/dL) increase of genetically instrumented total and LDL cholesterol were associated with 23% (OR = 0.77; 95% CI = 0.65–0.98; p = 0.03) and 41% lower risks of ICH (OR = 0.59; 95% CI = 0.42–0.82; p = 0.002), respectively. Interpretation Genetically elevated LDL levels were associated with lower risk of ICH, providing support for a potential causal role of LDL cholesterol in ICH. ANN NEUROL 2020 ANN NEUROL 2020;88:56–66

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Background and Purpose: Animal and observational studies indicate that smoking is a risk factor for aneurysm formation and rupture, leading to nontraumatic subarachnoid hemorrhage (SAH). However, a definitive causal relationship between smoking and the risk of SAH has not been established. Using Mendelian randomization (MR) analyses, we tested the hypothesis that smoking is causally linked to the risk of SAH. Methods: We conducted a 1-sample MR study using data from the UK Biobank, a large cohort study that enrolled over 500 000 Britons aged 40 to 69 from 2006 to 2010. Participants of European descent were included. SAH cases were ascertained using a combination of self-reported, electronic medical record, and death registry data. As the instrument, we built a polygenic risk score using independent genetic variants known to associate ( P <5 ×10 − 8 ) with smoking behavior. This polygenic risk score represents the genetic susceptibility to smoking initiation. The primary MR analysis utilized the ratio method. Secondary MR analyses included the inverse variance weighted and weighted median methods. Results: A total of 408 609 study participants were evaluated (mean age, 57 [SD 8], female sex, 220 937 [54%]). Among these, 132 566 (32%) ever smoked regularly, and 904 (0.22%) had a SAH. Each additional SD of the smoking polygenic risk score was associated with 21% increased risk of smoking (odds ratio [OR], 1.21 [95% CI, 1.20–1.21]; P <0.001) and a 10% increased risk of SAH (OR, 1.10 [95% CI, 1.03–1.17]; P =0.006). In the primary MR analysis, genetic susceptibility to smoking was associated with a 63% increase in the risk of SAH (OR, 1.63 [95% CI, 1.15–2.31]; P =0.006). Secondary analyses using the inverse variance weighted method (OR, 1.57 [95% CI, 1.13–2.17]; P =0.007) and the weighted median method (OR, 1.74 [95% CI, 1.06–2.86]; P =0.03) yielded similar results. There was no significant pleiotropy (MR-Egger intercept P =0.39; MR Pleiotropy Residual Sum and Outlier global test P =0.69). Conclusions: These findings provide evidence for a causal link between smoking and the risk of SAH.

Background and Objectives:Mounting evidence indicates that hypertension leads to a higher risk of dementia. Hypertension is a highly heritable trait, and a higher polygenic susceptibility to hypertension (PSH) is known to associate with higher risk of dementia. We tested the hypothesis that a higher PSH leads to worse cognitive performance in middle-aged persons without dementia. Confirming this hypothesis would support follow-up research focused on using hypertension-related genomic information to risk-stratify middle-aged adults before hypertension develops.Methods:We conducted a nested, cross-sectional genetic study within the UK Biobank. Study participants with a history of dementia or stroke were excluded. We categorized participants as having low (≤20thpercentile), intermediate, or high (≥80thpercentile) PSH according to results of 2 polygenic risk scores for systolic and diastolic blood pressure (BP) generated with data on 732 genetic risk variants. A general cognitive ability score was calculated as the first component of an analysis that included the results of five cognitive tests. Primary analyses focused on Europeans, and secondary analyses included all race/ethnic groups.Results:Of the 502,422 participants enrolled in the UKB, 48,118 (9.6%) completed the cognitive evaluation, including 42,011 (8.4%) of European ancestry. Multivariable regression models using systolic BP-related genetic variants indicated that compared to study participants with low PSH, those with intermediate and high PSH had reductions of 3.9% (beta -0.039, SE 0.012) and 6.6% (beta -0.066, SE 0.014), respectively, in their general cognitive ability score (P<0.001). Secondary analyses including all race/ethnic groups and using diastolic BP-related genetic variants yielded similar results (P<0.05 for all tests). Analyses evaluating each cognitive test separately indicated that Reaction Time, Numeric Memory, and Fluid Intelligence drove the association between PSH and general cognitive ability score (all individual tests,P<0.05).Discussion:Among non-demented, community-dwelling, middle-aged Britons, a higher PSH is associated with worse cognitive performance. These findings suggest that genetic predisposition to hypertension influences brain health in persons who have not yet developed dementia. Because information on genetic risk variants for elevated BP is available long before the development of hypertension, these results lay the foundation for further research focused on using genomic data for the early identification of high-risk middle-aged adults.