Biology subjects

Humphrey, J.

Publications and source records attributed to Humphrey, J..

4 recordsLinked to original sources

bioRxiv2017

Prioritizing Parkinson’s Disease genes using population-scale transcriptomic data

Genome-wide association studies (GWAS) have identified over 41 susceptibility loci associated with late-onset Parkinsons Disease (PD) but identifying putative causal genes and the underlying mechanisms remains challenging. To address this, we leveraged large-scale transcriptomic datasets to prioritize genes that are likely to affect PD. We found 29 gene associations in peripheral monocytes, and 44 gene associations whose expression or differential splicing in prefrontal cortex is associated with PD. This includes many novel genes but also known associations such as MAPT, for which we found that variation in exon 3 splicing explains the common genetic association. Genes identified in our analyses are more likely to interact physically with known PD genes and belong to the same or related pathways including lysosomal and innate immune function. Overall, our study provides a strong foundation for further mechanistic studies that will elucidate the molecular drivers of PD.

genomics↗

bioRxiv2017

Weighted burden analysis of exome-sequenced case-control sample implicates synaptic genes in schizophrenia aetiology

A previous study of exome-sequenced schizophrenia cases and controls reported an excess of singleton, gene-disruptive variants among cases, concentrated in particular gene sets. The dataset included a number of subjects with a substantial Finnish contribution to ancestry. We have reanalysed the same dataset after removal of these subjects and we have also included non-singleton variants of all types using a weighted burden test which assigns higher weights to variants predicted to have a greater effect on protein function. We investigated the same 31 gene sets as previously and also 1454 GO gene sets. The reduced dataset consisted of 4225 cases and 5834 controls. No individual variants or genes were significantly enriched in cases but 13 out of the 31 gene sets were significant after Bonferroni correction and the \"FMRP targets\" set produced a signed log p value (SLP) of 7.1. The gene within this set with the highest SLP, equal to 3.4, was FYN, which codes for a tyrosine kinase which phosphorylates glutamate metabotropic receptors and ionotropic NMDA receptors, thus modulating their trafficking, subcellular distribution and function. In the most recent GWAS of schizophrenia it was identified as a \"prioritized candidate gene\". Two of the subunits of the NMDA receptor which are substrates of FYN are coded for by GRIN1 (SLP=1.7) and GRIN2B (SLP=2.1). Of note, for some sets there was a substantial enrichment of non-singleton variants. Of 1454 GO gene sets, 3 were significant after Bonferroni correction. Identifying specific genes and variants will depend on genotyping them in larger samples and/or demonstrating that they cosegregate with illness within pedigrees.

genetics↗

bioRxiv2017

Data-driven Modeling of Thrombus Size and Shape in Aortic Dissections: Role of Hemodynamics

Aortic dissection is a pathology that manifests due to micro-structural defects in the aortic wall. Blood enters the damaged wall through an intimal tear, thereby creating a so-called false lumen and exposing the blood to thrombogenic intramural constituents such as collagen. The natural history of this acute vascular injury thus depends, in part, on thrombus formation, maturation, and possible healing within the false lumen. A key question is: Why do some false lumens thrombose completely while other thrombose partially or little at all? An ability to predict the location and extent of thrombus in subjects with dissection could contribute significantly to clinical decision-making, including interventional design. We develop, for the first time, a data-driven particle-continuum model for thrombus formation in a murine model of aortic dissection. In the proposed model, we simulate a final-value problem in lieu of the original initial-value problem with significantly fewer particles that may grow in size upon activation, representing the local concentration of blood-borne species. Numerical results confirm that geometry and local hemodynamics play significant roles in the acute progression of thrombus. Despite geometrical differences between murine and human dissections, mouse models can provide considerable insight and have gained in popularity owing to their reproducibility. Our results for three classes of geometrically different false lumens show that thrombus forms and extends to a greater extent in regions with lower bulk shear rates. Dense thrombi are less likely to form in high-shear zones and in the presence of strong vortices. The present data-driven study suggests that the proposed model is robust and can be employed to assess thrombus formation in human aortic dissections.

bioengineering↗

bioRxiv2017

Seamless Multiscale Modeling of Coagulation Using Dissipative Particle Dynamics

We propose a new multiscale framework that seamlessly integrates four key components of blood clotting namely, blood rheology, cell mechanics, coagulation kinetics and transport of species and platelet adhesive dynamics. We use transport dissipative particle dynamics (tDPD), which is the extended form of original DPD, as the base solver, while a coarse-grained representation of blood cells membrane accounts for its mechanics. Our results show the dominant effect of blood flow and high Peclet numbers on the reactive transport of the chemical species signifying the importance of membrane bound reactions on the surface of adhered platelets. This new multiscale particle-based methodology helps us probe synergistic mechanisms of thrombus formation, and can open new directions in addressing other biological processes from sub-cellular to macroscopic scales.

biophysics↗