Biology subjects

Graham, J.

Publications and source records attributed to Graham, J..

4 recordsLinked to original sources

bioRxiv2018

Insights from Comparison of the Renal and Skin Single Cell Transcriptomes in Lupus Nephritis

Lupus nephritis (LN) occurs in up to 50% of patients with systemic lupus erythematosus (SLE), and is a major contributor to mortality and morbidity. LN presents as a highly heterogeneous disease both in histopathology and response to therapy. The molecular and cellular processes leading to renal damage and to the heterogeneity of the disease are not well understood. To elucidate the processes underpinning the heterogeneity of LN, we applied singlecell RNA-sequencing (scRNA-seq) to renal biopsies from LN patients. Skin biopsies were evaluated as a source of biomarkers for monitoring kidney disease. Type-I interferon (IFN) response signatures were identified in tubular cells and keratinocytes, differentiating LN patients from healthy controls. Non-responders associated with higher IFN signatures in both tissue compartments. Moreover, non-response was also associated with a fibrotic signature in the tubular cells. Receptor-ligand interaction analysis indicated that the fibrotic process is likely mediated by FGF receptors with the initiating signal originating from infiltrating leukocytes. Differential expression analysis of tubular cells between proliferative and membranous LN pointed to several fibrosis-relevant pathways, which may offer insight into their histological differences. In summary, scRNA-seq was applied to LN to deconstruct its heterogeneity and provide novel targets for personalized approaches to therapy.

immunology↗

bioRxiv2017

Simulating Pedigrees Ascertained for Multiple Disease-Affected Relatives

Background: Studies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.\n\nResults: We present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.\n\nConclusions: Through simulation, we show that affected members of a family segregating a rare disease variant tend to be more numerous and cluster in relationships more closely than those for sporadic disease. We also show that the family ascertainment process can lead to apparent anticipation in the age of onset. Finally, we use simulation to gain insight into the limit on the proportion of ascertained families segregating a causal variant. SimRVPedigree should be useful to investigators seeking insight into the family-based study design through simulation.

genetics↗

bioRxiv2017

Using gene genealogies to localize rare variants associated with complex traits in diploid populations

Background and AimsMany methods can detect trait association with causal variants in candidate genomic regions; however, a comparison of their ability to localize causal variants is lacking. We extend a previous study of the detection abilities of these methods to a comparison of their localization abilities.\n\nMethodsThrough coalescent simulation, we compare several popular association methods. Cases and controls are sampled from a diploid population to mimic human studies. As benchmarks for comparison, we include two methods that cluster phenotypes on the true genealogical trees, a naive Mantel test considered previously in haploid populations and an extension that takes into account whether case haplotypes carry a causal variant. We first work through a simulated dataset to illustrate the methods. We then perform a simulation study to score the localization and detection properties.\n\nResultsIn our simulations, the association signal was localized least precisely by the naive Mantel test and most precisely by its extension. Most other approaches had intermediate performance similar to the single-variant Fishers-exact test.\n\nConclusionsOur results confirm earlier findings in haploid populations about potential gains in performance from genealogy-based approaches. They also highlight differences between haploid and diploid populations when localizing and detecting causal variants.

genetics↗

bioRxiv2016

Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation

Both genetic variants and brain region abnormalities are recognized to play a role in cognitive decline. We explore the association between singlenucleotide polymorphisms (SNPs) in linkage regions for Alzheimers disease and rates of decline in brain structure using data from the Alzheimers Disease Neuroimaging Initiative (ADNI).\n\nIn an initial discovery stage, we assessed the presence of linear association between the minor allele counts of 75,845 SNPs in the Alzgene linkage regions and predicted rates of change in structural MRI measurements for 56 brain regions using an RV test. In a second, refinement stage, we reduced the number of SNPs using a bootstrap-enhanced sparse canonical correlation analysis (SCCA) with a fixed tuning parameter. Each SNP was assigned an importance measure proportional to the number of times it was estimated to have a nonzero coefficient in repeated re-sampling from the ADNI-1 sample. We created refined lists of SNPs based on importance probabilities greater than 50% and 90%, respectively. In a third, validation stage, we assessed the multivariate association between these refined lists of SNPs and the rates of structural change in the independent ADNI-2 study dataset.\n\nThere was strong statistical evidence for linear association between the SNPs in the Alzgene linkage regions and the 56 imaging phenotypes in both the ADNI-1 and ADNI-2 samples (p < 0.0001). The bootstrap-enhanced SCCA identified 1,694 priority SNPs with importance probabilities > 50% and 22 SNPs with importance probabilities > 90%. The 1,694 prioritized SNPs in the ADNI-1 data were associated with imaging phenotypes in the ADNI-2 data (p = 0.0021).\n\nThis manuscript presents an analysis that addresses challenges in current imaging genetics studies such as biased sampling designs and highdimensional data with low-signal. Genes corresponding to priority SNPs having the highest contribution in the validation data have previously been implicated or hypothesized to be implicated in AD, including GCLC, IDE, and STAMBP1andFAS. We hypothesize that the effect sizes of the 1,694 SNPs in the priority set are likely small, but further investigation within this set may advance understanding of the missing heritability in late-onset Alzheimers disease. Multivariate analysis; Linkage regions; Imaging genetics; Endophenotypes; Inverse probability weighting; Variable importance probabilities

neuroscience↗