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Data from: Exome-chip association analysis of intracranial aneurysms

Cite this dataset

Hof, Femke van't et al. (2020). Data from: Exome-chip association analysis of intracranial aneurysms [Dataset]. Dryad.


Objective: To investigate to what extent low-frequency genetic variants (with minor allele frequencies <5%) affect the risk of intracranial aneurysms (IA). Methods: 1056 IA patients and 2097 population-based controls from the Netherlands were genotyped using the Illumina HumanExome BeadChip. After quality control (QC) of samples and single nucleotide variants (SNVs), we conducted a single variant analysis using Fisher’s exact test. We also performed the variable threshold (VT) and the sequence kernel association tests (SKAT) at different minor allele count (MAC) thresholds of ±5 and ±0 to test the hypothesis that multiple variants within the same gene are associated with IA risk. Significant results were tested in a replication cohort of 425 IA patients and 311 controls, and results of the two cohorts were combined in a meta-analysis. Results: After QC, 995 IA patients and 2080 controls remained for further analysis. The single variant analysis comprising 46,534 SNVs did not identify significant loci at the genome-wide level. The gene-based tests showed a statistically significant association for FBLN2 (best p=1x10-6 for the VT test, MAC±5). Associations were not statistically significant in the independent but smaller replication cohort (p±0.57), but became slightly stronger in a meta-analysis of the two cohorts (best p=4.8x10-7 for the SKAT, MAC>1). Conclusion: Gene-based tests indicated an association for FBLN2, a gene encoding an extracellular matrix protein implicated in vascular wall remodeling, but independent validation in larger cohorts is warranted. We did not identify any significant associations for single low-frequency genetic variants.

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