Statistical Genomics and Data Analysis Core

National Institute Of Mental Health

Investigators

Linked publications, trials & patents

Abstract

In FY2018, we completed 30 consulting projects including a variety of data analysis, statistical modeling for neuronal spiking, genomic mechanism investigation of psychiatric disorders including obsessive compulsive disorder and schizophrenia. Below we highlight two service projects which led to a publication. Example 1: Project Leaders - Lora Deuitch (PI: Robert Innis) The effects of expression of inflammatory markers on efflux transporters in drug-resistant mesial temporal lobe epilepsy tissue. The goal of this project was to measure the expression of COX-1, COX-2, TSPO as well as P-gp, BCRP, in brain tissue samples from individuals with drug-resistant mesial temporal lobe epilepsy (MTLE). Formalin-fixed, paraffin-embedded surgical brain tissue was obtained from 33 participants with drug-resistant MTLE. Statistical significance for the expression of the inflammatory proteins amongst cell types was determined using Kruskal-Wallis test: (Dunns multiple comparison). To compare protein levels between the MTS and non-MTS groups, Wilcoxon rank sum tests were performed. And logistic regression analysis was then performed to assess the association between MTS and the protein/cell expression with batch effect as a covariate. Pairwise linear correlations between ABC transporter and inflammatory protein expression were evaluated using the Pearson correlation coefficients. COX-1 was expressed in microglia, and COX-2 and TSPO were expressed in microglia and neurons. BCRP density correlated significantly with TSPO density, suggesting a potential relationship between inflammatory markers and efflux transporters. It was the first study to measure the cellular expression of COX-1, COX-2, and TSPO in microglia, astrocytes, and neurons in surgical brain tissue samples from individuals with drug-resistant MTLE. Further research is needed to determine the effects of the COX inflammatory pathway in epilepsy, and how it relates to the expression of the ABC transporters P-gp and BCRP. The work was published in Epilepsia (2018) and Dr. Kang, the Staff Scientist in the Core, was invited to be an author by the authors of the manuscript. Example 2: Project Leaders - PI: K. Berman Haploids calling in the 7q11.23 regions in individuals with Williams syndrome (WS) Dr. Bermans lab requested Dr. Yaos help to complete a R script to determine haploid and triploid genotypes and their association with vascular phenotypes in Williams syndrome and 7q11.23 duplication syndrome. Williams syndrome and 7q11.23 duplication syndrome (Dup7) show contrasting syndromic symptoms. However, within each group there is considerable interindividual variability in the degree to which these phenotypes are expressed. The existing software to identify areas of copy number variation (CNV) from SNP-chip data could not provide non-diploid genotypes in CNV regions. Dr. Yao offered critical advice and led to a development of a new method for identifying haploid and triploid genotypes in CNV regions. In Dr. Bermans samples, haploid calls in the 7q11.23 region were made for 99% of SNPs in the WS group, and triploid calls for 98.8% of SNPS in the individuals who carried Dup1. Furthermore, it was found that the G alleles of SNP rs2528795 in the ELN gene were associated with aortic stenosis in individuals with WS with a p-value of 0.0049. Interestingly, the A allele of the same SNP was associated with aortic dilation in DUP7. Therefore, the commonly available SNP-chip information can be used to make haploid and triploid calls in individuals with CNVs and be related to variability in specific genes to variability in syndromic phenotypes using the aortic arteriopathy phenotype. The work was published in BMC Med Genet. in 2018. In addition to collaborating with other laboratories within NIH, we designed and conducted a basic statistics course focused on brain science. This course was aimed at both intramural research trainees (including post-baccalaureate fellows and post-doctoral fellows) that were interested in learning basic statistical tools that could apply to their research. And it was well received. Independent and Collaborative Research We collaborated with multiple investigators from Johns Hopkins University, Harvard University, Brown University, University of California and University of Los Angeles. Together, we conducted a meta-analysis for two genome-wide association studies (GWASs) of obsessive compulsive disorder (OCD). We discovered new genes/SNPs that are associated with OCD. To detail, we investigated a total of 2688 individuals of European ancestry with OCD and 7037 gnomically matched controls. No single-nucleotide polymorphisms (SNPs) reached genome-wide significance. However, in comparison with the two individual GWASs, the distribution of P-values shifted toward significance. The top haplotypic blocks were tagged with rs4733767 (P=7.1 10-7; odds ratio (OR)=1.21; confidence interval (CI): 1.12-1.31, CASC8/CASC11), rs1030757 (P=1.1 10-6; OR=1.18; CI: 1.10-1.26, GRID2) and rs12504244 (P=1.6 10-6; OR=1.18; CI: 1.11-1.27, KIT). Variants located in or near the genes ASB13, RSPO4, DLGAP1, PTPRD, GRIK2, FAIM2 and CDH20, identified in linkage peaks and the original GWASs, were among the top signals. Polygenic risk scores for each individual study predicted case-control status in the other by explaining 0.9% (P=0.003) and 0.3% (P=0.0009) of the phenotypic variance in OCGAS and the European IOCDF-GC target samples, respectively. The common SNP heritability in the combined OCGAS and IOCDF-GC sample was estimated to be 0.28 (s.e.=0.04). Strikingly, 65% of the SNP-based heritability in the OCGAS sample was accounted for by SNPs with minor allele frequencies of 40%. In addition, we also examined the allele frequency distribution of the common variation heritability of OCD. Albeit the fact that the confidence intervals of each allele frequency bin are large because of the limited sample sizes, the majority of the heritability (65%) was accounted for by SNPs with high MAF (for example, >40%) in both the OCGAS sample and combined sample. Although there were no genome-wide significant findings, the 53.7kb haplotype block encompassing the top SNP, rs4733767, contains 25 H3K27Ac peaks in the ENCODE/ROADMAP data, suggesting it has regulatory potential. This meta-study, to some extent, shed light to the complex genetic architecture of obsessive-compulsive disorder.