Markus, H. | bioRxiv Science

bioRxiv2018

The Subtype Specificity of Genetic Loci Associated with Stroke in 16,664 cases and 32,792 controls

BackgroundGenome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischaemic and haemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes.\n\nMethodsWe performed Bayesian multinomial regression in 16,664 stroke cases and 32,792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under two commonly used stroke classification systems, Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS). All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel.\n\nResultsSixteen loci were considered for analysis. Seven loci influenced both haemorrhagic and ischaemic stroke, three of which influenced ischaemic and haemorrhagic subtypes under both TOAST and CCS. Under CCS, 4 loci influenced both small vessel stroke and intracerebral haemorrhage. An EDNRA locus demonstrated opposing effects on ischaemic and haemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction and only one locus (12q24) was predicted to influence all ischaemic stroke subtypes.\n\nConclusionsHeterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between haemorrhagic and ischaemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.

genetics↗

bioRxiv2017

Evaluation of pre-analytical factors affecting plasma DNA analysis

Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci (mean amplicon size: 71 bp and 471 bp respectively). Using this assay, we compared performance of 7 cfDNA extraction kits and found cfDNA yield and fragment size varies significantly between them. We also compared 3 blood collection protocols used to collect plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA BCT tubes at ambient temperature processed within 24 hours and 72 hours of collection). To assess whether cell-stabilizing preservative in BCT tubes introduced noise in cfDNA, we performed digital targeted sequencing. We found no significant differences in cfDNA yield, fragment size and background sequencing noise between these protocols. In 219 clinical samples tested for quality using the ddPCR assay, cfDNA fragment size was significantly shorter in plasma samples immediately processed for ctDNA analysis compared to archived samples, suggesting background DNA contributed by lysed peripheral blood cells. In summary, we describe a multiplexed ddPCR approach that enables cfDNA quality assessment and could inform the design of future circulating tumor DNA studies.\n\nGene namesNone

genomics↗