Biology subjects

Shabalin, A. A.

Publications and source records attributed to Shabalin, A. A..

3 recordsLinked to original sources

bioRxiv2018

Cell-type-specific methylome-wide association studies implicate neurodegenerative processes and neuroimmune communication in major depressive disorder

We studied the methylome in three collections of human postmortem brain (N=206) and blood samples (N=1,132) of subjects with major depressive disorder (MDD) and controls. Using an epigenomic deconvolution approach we performed cell-type-specific methylome-wide association studies (MWAS) within sub-populations of neurons/glia and granulocytes/T-cells/B-cells/monocytes for bulk brain and blood data, respectively. Multiple MWAS findings in neurons/glia replicated across brain collections (ORs=509-538, P-values<1x10-5) and were reproducible in an array-based MWAS of sorted neurons/glia from a fourth brain collection (N=58). Pathway analyses implicated p75NTR/VEGF signaling, neurodegeneration, and blood-brain barrier perturbation. Cell-type-specific analysis in blood identified associations in CD14+ monocytes -- a cell type strongly linked to neuroimmune processes and stress. Top results in neurons/glia/bulk and monocytes were enriched for genes supported by GWAS for MDD (ORs=2.02-2.87, P-values=0.003 to <1x10-5), neurodegeneration and other psychiatric disorders. In summary, we identified novel MDD-methylation associations by using epigenomic deconvolution that provided important mechanistic insights for the disease.

genomics↗

bioRxiv2017

Genome-wide association study of suicide death:Results from the first wave of Utah completed suicide data

ObjectiveSuicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort. MethodsThe analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression. ResultsGWAS identified two genome-wide significant loci (6 SNPs, p<5x10-8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder. ConclusionsIn this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.

genomics↗

bioRxiv2017

Building a schizophrenia genetic network: Evidence that Transcription Factor 4 regulates schizophrenia risk genes.

The transcription factor 4 (TCF4) locus is a robust association finding with schizophrenia (SZ), but little is known about the genes regulated by the encoded transcription factor. Therefore, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) of TCF4 in neural-derived (SH-SY5Y) cells to identify genome-wide TCF4 binding sites, followed by data integration with SZ association findings. We identified 11,322 TCF4 binding sites overlapping in two ChIP-seq experiments. These sites are significantly enriched for the TCF4 Ebox binding motif (>85% having [≥]1 Ebox) and implicate a gene set enriched for genes down-regulated in TCF4 siRNA knockdown experiments, indicating the validity of our findings. The TCF4 gene set was also enriched among 1) Gene Ontology categories such as axon/neuronal development, 2) genes preferentially expressed in brain, in particular pyramidal neurons of the somatosensory cortex, and 3) genes down-regulated in post-mortem brain tissue from SZ patients (OR=2.8, permutation p<4x10-5). Considering genomic alignments, TCF4 binding sites significantly overlapped those for neural DNA binding proteins such as FOXP2 and the SZ-associated EP300. TCF4 binding sites were modestly enriched among SZ risk loci from the Psychiatric Genomic Consortium (OR=1.56, p=0.03). In total, 130 TCF4 binding sites occurred in 39 of the 108 regions published in 2014. Thirteen genes within the 108 loci had both a TCF4 binding site {+/-}10kb and were differentially expressed in siRNA knockdown experiments of TCF4, suggesting direct TCF4 regulation. These findings confirm TCF4 as an important regulator of neural genes and point towards functional interactions with potential relevance for SZ.

genetics↗