Biology subjects

Feinberg, A. P.

Publications and source records attributed to Feinberg, A. P..

4 recordsLinked to original sources

bioRxiv2018

Peripheral blood DNA methylation and autism spectrum disorder

Background\n\nSeveral reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size, and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies.\n\nMethods\n\nDNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample.\n\nFindings\n\nIn this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12x10-7. Seven CpGs showed differences at p < 1x10-5 and 48 at 1x10-4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpGs hits, which was consistent across EWAS and meQTL discovery p-value thresholds.\n\nConclusions\n\nWe report the largest case-control EWAS study of ASD to date. No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the 7 sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.

genomics↗

bioRxiv2017

GPU-accelerated alignment of bisulfite-treated short-read sequences

The alignment of bisulfite-treated DNA sequences (BS-seq reads) to a large genome involves a significant computational burden beyond that required to align non-bisulfite-treated reads. In the analysis of BS-seq data, this can present an important performance bottleneck that can potentially be addressed by appropriate software-engineering and algorithmic improvements. One strategy is to integrate this additional programming logic into the read-alignment implementation in a way that the software becomes amenable to optimizations that lead to both higher speed and greater sensitivity than can be achieved without this integration.\n\nWe have evaluated this approach using Arioc, a short-read aligner that uses GPU (general-purpose graphics processing unit) hardware to accelerate computationally-expensive programming logic. We integrated the BS-seq computational logic into both GPU and CPU code throughout the Arioc implementation. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments reported by the most widely used BS-seq read aligners. With simulated reads, Arioc's accuracy is equal to or better than the other read aligners we evaluated. With human sequencing reads, Arioc's throughput is at least 10 times faster than existing BS-seq aligners across a wide range of sensitivity settings.\n\nThe Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license.

bioinformatics↗

bioRxiv2017

Neuronal brain region-specific DNA methylation andchromatin accessibility are associated with neuropsychiatric disease heritability

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions, yet little is known about brain region-specific epigenetic differences. Here, we compared prefrontal cortex, anterior cingulate gyrus, hippocampus and nucleus accumbens from 6 individuals, performing whole genome bisulfite sequencing for DNA methylation. In addition, we have performed ATAC-seq for chromatin accessibility, and RNA-seq for gene expression in the nucleus accumbens and prefrontal cortex from 6 additional individuals. We found substantial neuron- and brain region-specific differences in both DNA methylation and chromatin accessibility which were largely non-overlapping, and were greatest between nucleus accumbens and the other regions. In contrast, glial methylation and chromatin were relatively homogeneous across brain regions, although neuron/glia ratios varied greatly, demonstrating the necessity for cellular fractionation. Gene expression was also largely the same across glia from different brain regions and substantially different for neurons. Expression was correlated with methylation and accessibility across promoters and known enhancers. Several classes of transcription factor binding sites were enriched at regions of differential methylation and accessibility, including many that respond to synaptic activity. Finally, both regions of differential methylation and those of differential accessibility showed a surprising >10-fold enrichment of explained heritability associated with addictive behavior, as well as schizophrenia- and neuroticism-associated regions, suggesting that common psychiatric illness is mediated through brain region-specific epigenetic marks.

neuroscience↗

bioRxiv2016

Cross-tissue integration of genetic and epigenetic data offers insight into autism spectrum disorder

Epigenetics is an emerging area of investigation for Autism Spectrum Disorder (ASD). Integration of epigenetic information with ASD genetic results may elucidate functional insights not possible via either source of information in isolation. We used concurrent genotype and DNA methylation (DNAm) data from cord blood and peripheral blood from preschool-aged children to identify SNPs associated with DNA methylation, or methylation quantitative trait loci (meQTLs), and combined this with publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-associated SNPs were enriched for fetal brain (OR = 3.55; p < 0.001) and peripheral blood meQTLs (OR = 1.58; p < 0.001). The CpG site targets of ASD meQTLs across cord, blood, and brain tissues were enriched for immune-related pathways, consistent with other expression and DNAm results in ASD, and revealing pathways not implicated by genes identified from ASD rare variant work. Further, DNaseI hypersensitive sites and the STAT1 and TAF1 transcription factor binding sites were enriched for meQTL target CpGs of SNPs associated with psychiatric conditions. This joint analysis of genotype and DNAm demonstrates the potential utility of both brain and blood-based DNAm for insights into ASD and psychiatric phenotypes more broadly.

genomics↗