Femke van’t Hof

High risk population isolate reveals low frequency variants predisposing to intracranial aneurysms

3% of the population develops saccular intracranial aneurysms (sIAs), a complex trait, with a sporadic and a familial form. Subarachnoid hemorrhage from sIA (sIA-SAH) is a devastating form of stroke. Certain rare genetic variants are enriched in the Finns, a population isolate with a small founder population and bottleneck events. As the sIA-SAH incidence in Finland is >2× increased, such variants may associate with sIA in the Finnish population. We tested 9.4 million variants for association in 760 Finnish sIA patients (enriched for familial sIA), and in 2,513 matched controls with case-control status and with the number of sIAs. The most promising loci (p<5E-6) were replicated in 858 Finnish sIA patients and 4,048 controls. The frequencies and effect sizes of the replicated variants were compared to a continental European population using 717 Dutch cases and 3,004 controls. We discovered four new high-risk loci with low frequency lead variants. Three were associated with the case-control status: 2q23.3 (MAF 2.1%, OR 1.89, p 1.42×10-9); 5q31.3 (MAF 2.7%, OR 1.66, p 3.17×10-8); 6q24.2 (MAF 2.6%, OR 1.87, p 1.87×10-11) and one with the number of sIAs: 7p22.1 (MAF 3.3%, RR 1.59, p 6.08×-9). Two of the associations (5q31.3, 6q24.2) replicated in the Dutch sample. The 7p22.1 locus was strongly differentiated; the lead variant was more frequent in Finland (4.6%) than in the Netherlands (0.3%). Additionally, we replicated a previously inconclusive locus on 2q33.1 in all samples tested (OR 1.27, p 1.87×10-12). The five loci explain 2.1% of the sIA heritability in Finland, and may relate to, but not explain, the increased incidence of sIA-SAH in Finland. This study illustrates the utility of population isolates, familial enrichment, dense genotype imputation and alternate phenotyping in search for variants associated with complex diseases.

Impact of Inherited Genetic Variants Associated With Lipid Profile, Hypertension, and Coronary Artery Disease on the Risk of Intracranial and Abdominal Aortic Aneurysms

Background—Epidemiological studies show that an unfavorable lipid profile and coronary artery disease (CAD) are risk traits for abdominal aortic aneurysms (AAAs) but not for intracranial aneurysms (IAs), and that hypertension is a main risk trait for IAs but not for AAAs. To evaluate these observations, we investigated single-nucleotide polymorphisms associated with serum lipid levels, hypertension, and CAD and tested their contribution to AAA and IA risk. Methods and Results—We defined sets of single-nucleotide polymorphisms previously reported to be associated with serum lipid levels, CAD, and blood pressure. From previously collected genome-wide data, we extracted genotypes for these single-nucleotide polymorphism sets in 709 IA cases and 2692 controls and 807 AAA cases and 1905 controls (all of Dutch origin). We computed genetic scores for each individual by summing the observed number of risk alleles weighted by their previously published effect size. Using logistic regression, we tested the genetic scores for association with IAs and AAAs and found significant associations for genetic scores of total cholesterol (P=3.6×10-6), low-density lipoprotein-cholesterol (P=5.7×10-7), and CAD (P=0.0014) with AAAs and for the blood pressure score with IAs (P=0.0030). Conclusions—We demonstrate that genetic risk profiles of lipid factors and CAD are associated with AAAs but not with IAs, and the genetic risk profile of blood pressure is associated with IAs but not with AAAs. These findings are consistent with epidemiological observations.

Genetic risk load according to the site of intracranial aneurysms

Objective: We investigated whether risk alleles of single nucleotide polymorphisms associated with intracranial aneurysm (IA) are enriched in patients with familial IA, IA located at the middle cerebral artery (MCA), or IA rupture at a younger age. Methods: In this case-only study, we calculated genetic risk scores (GRS) for 973 Dutch and 718 Finnish patients with IA by summing effect size–weighted risk allele counts of 7 single nucleotide polymorphisms associated with IAs previously identified through genome-wide association studies. We tested the GRS for association with presence of familial IA or IA at the MCA using logistic regression, and with age at time of IA rupture using linear regression. We also calculated odds ratios with 95% confidence intervals for the proportion of patients with each characteristic in the highest compared with the lowest GRS tertile. Results: GRS were higher in IA at the MCA in the Dutch (p = 2.5 × 10−4), Finnish (p = 0.039), and combined cohort (p = 4.9 × 10−5). GRS were not associated with familial IA in the Dutch (p = 0.34), Finnish (p = 0.45), and combined cohort (p = 0.98), or with age at time of IA rupture in the Dutch (p = 0.28), Finnish (p = 0.86), and combined cohort (p = 0.45). In the combined cohort, odds ratios were 0.89 (0.67–1.20) for familial IA, 1.03 (0.79–1.34) for lower age, and 1.54 (1.20–1.98) for MCA aneurysms. Conclusions: Our findings suggest that genetic risk factors have a larger role in the development of IA at the MCA than at other sites, and that genetic heterogeneity should be considered in future genetic studies.

Circulating microRNAs in patients with intracranial aneurysms

Introduction We compared circulating microRNA (miRNA) levels in plasma of patients with intracranial aneurysms (IA) to those of controls as a first step towards finding potential biomarkers for individuals at high risk of IA development and its subsequent rupture. Patients and methods Using a PCR array we measured 370 miRNAs in plasma of 15 patients with prior aneurysmal subarachnoid hemorrhage (aSAH), of whom 11 had an additional unruptured IA (UIA), and of 15 controls. MiRNAs with a difference in levels with an absolute fold change (FC) > 1.2 and p<0.01 were further tested using real-time (RT) PCR in an additional independent set of 15 aSAH patients, 15 untreated UIA patients and 15 controls for replication (absolute FC >1.2 and p<0.05). We used receiver operating characteristic (ROC) curves to illustrate the diagnostic potential of these miRNAs. Results Three of five miRNAs with a difference in levels in the PCR array study were replicated with miRNA-183-5p decreased in all patients (FC = -2.2, p = 1.7x10-3), miRNA-200a-3p increased in aSAH patients (FC = 1.8, p = 2.8x10-2) and miRNA-let7b-5p decreased in UIA patients (FC = -1.7, p = 1.27x10-3) as compared to controls. In distinguishing aSAH patients from controls, the area under the ROC curve (AUC) was 0.80 (95% confidence interval (95% CI) 0.63–0.97) for miRNA-183-5p, and 0.74 (95% CI 0.55–0.94) for miRNA-200a-3p. In distinguishing untreated UIA patients from controls, AUC was 0.83 (95% CI 0.69–0.98) for miRNA-183-5p and 0.92 (95% CI 0.81–1) for miRNA-let-7b. Discussion/Conclusions We identified three specific circulating miRNAs that are able to discriminate between IA patients and controls. Follow-up studies should assess if these miRNAs may be used biomarkers for identifying individuals at high risk of IA development and its subsequent rupture.

Genetic variants associated with type 2 diabetes and adiposity and risk of intracranial and abdominal aortic aneurysms

Epidemiological studies show that type 2 diabetes (T2D) is inversely associated with intracranial aneurysms (IA) and abdominal aortic aneurysms (AAA). Although adiposity has not been considered a risk factor for IA, there have been inconsistent reports relating adiposity to AAA risk. We assessed whether these observations have a genetic, causal basis. To this end, we extracted genotypes of validated single-nucleotide polymorphisms associated with T2D (n=65), body mass index (BMI) (n=97) and waist-hip ratio adjusted for BMI (WHRadjBMI) (n=47) from genotype data collected in 717 IA cases and 1988 controls, and in 818 AAA cases and 3004 controls, all of Dutch descent. For each of these three traits, we computed genetic risk scores (GRS) for each individual in these case-control data sets by summing the number of risk alleles weighted by their published effect size, and tested whether these GRS were associated with risk of aneurysm. We divided the cohorts into GRS quartiles, and compared IA and AAA risk in the highest with the lowest GRS quartile using logistic regression. We found no evidence for association in IA or AAA risk between top and bottom quartiles for the genetic risk scores for T2D, BMI and WHRadjBMI. However, additional Mendelian randomization analyses suggested a trend to potentially causal associations between BMI and WHRadjBMI and risk of AAA. Overall, our results do not support epidemiological observations relating T2D to aneurysm risk, but may indicate a potential role of adiposity in AAA that requires further investigation.

Whole Blood Gene Expression Profiles of Patients with a Past Aneurysmal Subarachnoid Hemorrhage

Background The pathogenesis of development and rupture of intracranial aneurysms (IA) is largely unknown. Also, screening for IA to prevent aneurysmal subarachnoid hemorrhage (aSAH) is inefficient, as disease markers are lacking. We investigated gene expression profiles in blood of previous aSAH patients, who are still at risk for future IA, aiming to gain insight into the pathogenesis of IA and aSAH, and to make a first step towards improvement of aSAH risk prediction. Methods and Results We collected peripheral blood of 119 patients with aSAH at least two years prior, and 118 controls. We determined gene expression profiles using Illumina HumanHT-12v4 BeadChips. After quality control, we divided the dataset in a discovery (2/3) and replication set (1/3), identified differentially expressed genes, and applied (co-)differential co-expression to identify disease-related gene networks. No genes with a significant (false-discovery rate <5%) differential expression were observed. We detected one gene network with significant differential co-expression, but did not find biologically meaningful gene networks related to a history of aSAH. Next, we applied prediction analysis of microarrays to find a gene set that optimally predicts absence or presence of a history of aSAH. We found no gene sets with a correct disease state prediction higher than 40%. Conclusions No gene expression differences were present in blood of previous aSAH patients compared to controls, besides one differentially co-expressed gene network without a clear relevant biological function. Our findings suggest that gene expression profiles, as detected in blood of previous aSAH patients, do not reveal the pathogenesis of IA and aSAH, and cannot be used for aSAH risk prediction.