Nazanin Karbalai

Restless Legs Syndrome-associated intronic common variant in Meis1 alters enhancer function in the developing telencephalon

Genome-wide association studies (GWAS) identified the MEIS1 locus for Restless Legs Syndrome (RLS), but causal single nucleotide polymorphisms (SNPs) and their functional relevance remain unknown. This locus contains a large number of highly conserved noncoding regions (HCNRs) potentially functioning as cis-regulatory modules. We analyzed these HCNRs for allele-dependent enhancer activity in zebrafish and mice and found that the risk allele of the lead SNP rs12469063 reduces enhancer activity in the Meis1 expression domain of the murine embryonic ganglionic eminences (GE). CREB1 binds this enhancer and rs12469063 affects its binding in vitro. In addition, MEIS1 target genes suggest a role in the specification of neuronal progenitors in the GE, and heterozygous Meis1-deficient mice exhibit hyperactivity, resembling the RLS phenotype. Thus, in vivo and in vitro analysis of a common SNP with small effect size showed allele-dependent function in the prospective basal ganglia representing the first neurodevelopmental region implicated in RLS.

Replication and meta-analysis of TMEM132D gene variants in panic disorder.

A recent genome-wide association study in patients with panic disorder (PD) identified a risk haplotype consisting of two single-nucleotide polymorphisms (SNPs) (rs7309727 and rs11060369) located in intron 3 of TMEM132D to be associated with PD in three independent samples. Now we report a subsequent confirmation study using five additional PD case–control samples (n=1670 cases and n=2266 controls) assembled as part of the Panic Disorder International Consortium (PanIC) study for a total of 2678 cases and 3262 controls in the analysis. In the new independent samples of European ancestry (EA), the association of rs7309727 and the risk haplotype rs7309727–rs11060369 was, indeed, replicated, with the strongest signal coming from patients with primary PD, that is, patients without major psychiatric comorbidities (n=1038 cases and n=2411 controls). This finding was paralleled by the results of the meta-analysis across all samples, in which the risk haplotype and rs7309727 reached P-levels of P=1.4e−8 and P=1.1e−8, respectively, when restricting the samples to individuals of EA with primary PD. In the Japanese sample no associations with PD could be found. The present results support the initial finding that TMEM132D gene contributes to genetic susceptibility for PD in individuals of EA. Our results also indicate that patient ascertainment and genetic background could be important sources of heterogeneity modifying this association signal in different populations.

Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

Summary Depression risk is exacerbated by genetic factors and stress exposure; however, the biological mechanisms through which these factors interact to confer depression risk are poorly understood. One putative biological mechanism implicates variability in the ability of cortisol, released in response to stress, to trigger a cascade of adaptive genomic and non-genomic processes through glucocorticoid receptor (GR) activation. Here, we demonstrate that common genetic variants in long-range enhancer elements modulate the immediate transcriptional response to GR activation in human blood cells. These functional genetic variants increase risk for depression and co-heritable psychiatric disorders. Moreover, these risk variants are associated with inappropriate amygdala reactivity, a transdiagnostic psychiatric endophenotype and an important stress hormone response trigger. Network modeling and animal experiments suggest that these genetic differences in GR-induced transcriptional activation may mediate the risk for depression and other psychiatric disorders by altering a network of functionally related stress-sensitive genes in blood and brain. Video Abstract

PTPN2 Gene Variants Are Associated with Susceptibility to Both Crohn's Disease and Ulcerative Colitis Supporting a Common Genetic Disease Background

Background Genome-wide association studies identified PTPN2 (protein tyrosine phosphatase, non-receptor type 2) as susceptibility gene for inflammatory bowel diseases (IBD). However, the exact role of PTPN2 in Crohns disease (CD) and ulcerative colitis (UC) and its phenotypic effect are unclear. We therefore performed a detailed genotype-phenotype and epistasis analysis of PTPN2 gene variants. Methodology/Principal Findings Genomic DNA from 2131 individuals of Caucasian origin (905 patients with CD, 318 patients with UC, and 908 healthy, unrelated controls) was analyzed for two SNPs in the PTPN2 region (rs2542151, rs7234029) for which associations with IBD were found in previous studies in other cohorts. Our analysis revealed a significant association of PTPN2 SNP rs2542151 with both susceptibility to CD (p = 1.95×10−5; OR 1.49 [1.34–1.79]) and UC (p = 3.87×10−2, OR 1.31 [1.02–1.68]). Moreover, PTPN2 SNP rs7234029 demonstrated a significant association with susceptibility to CD (p = 1.30×10−3; OR 1.35 [1.13–1.62]) and a trend towards association with UC (p = 7.53×10−2; OR 1.26 [0.98–1.62]). Genotype-phenotype analysis revealed an association of PTPN2 SNP rs7234029 with a stricturing disease phenotype (B2) in CD patients (p = 6.62×10−3). Epistasis analysis showed weak epistasis between the ATG16L1 SNP rs2241879 and PTPN2 SNP rs2542151 (p = 0.024) in CD and between ATG16L1 SNP rs4663396 and PTPN2 SNP rs7234029 (p = 4.68×10−3) in UC. There was no evidence of epistasis between PTPN2 and NOD2 and PTPN2 and IL23R. In silico analysis revealed that the SNP rs7234029 modulates potentially the binding sites of several transcription factors involved in inflammation including GATA-3, NF-κB, C/EBP, and E4BP4. Conclusions/Significance Our data confirm the association of PTPN2 variants with susceptibility to both CD and UC, suggesting a common disease pathomechanism for these diseases. Given recent evidence that PTPN2 regulates autophagosome formation in intestinal epithelial cells, the potential link between PTPN2 and ATG16L1 should be further investigated.

GLIDE: GPU-Based Linear Regression for Detection of Epistasis

Due to recent advances in genotyping technologies, mapping phenotypes to single loci in the genome has become a standard technique in statistical genetics. However, one-locus mapping fails to explain much of the phenotypic variance in complex traits. Here, we present GLIDE, which maps phenotypes to pairs of genetic loci and systematically searches for the epistatic interactions expected to reveal part of this missing heritability. GLIDE makes use of the computational power of consumer-grade graphics cards to detect such interactions via linear regression. This enabled us to conduct a systematic two-locus mapping study on seven disease data sets from the Wellcome Trust Case Control Consortium and on in-house hippocampal volume data in 6 h per data set, while current single CPU-based approaches require more than a year’s time to complete the same task.

Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs

Motivation: In recent years, numerous genome-wide association studies have been conducted to identify genetic makeup that explains phenotypic differences observed in human population. Analytical tests on single loci are readily available and embedded in common genome analysis software toolset. The search for significant epistasis (gene–gene interactions) still poses as a computational challenge for modern day computing systems, due to the large number of hypotheses that have to be tested. Results: In this article, we present an approach to epistasis detection by exhaustive testing of all possible SNP pairs. The search strategy based on the Hilbert–Schmidt Independence Criterion can help delineate various forms of statistical dependence between the genetic markers and the phenotype. The actual implementation of this search is done on the highly parallelized architecture available on graphics processing units rendering the completion of the full search feasible within a day. Availability:The program is available at http://www.mpipsykl.mpg.de/epigpuhsic/. Contact: tony@mpipsykl.mpg.de

A Genome-Wide Association Study Suggests Novel Loci Associated with a Schizophrenia-Related Brain-Based Phenotype

Patients with schizophrenia and their siblings typically show subtle changes of brain structures, such as a reduction of hippocampal volume. Hippocampal volume is heritable, may explain a variety of cognitive symptoms of schizophrenia and is thus considered an intermediate phenotype for this mental illness. The aim of our analyses was to identify single-nucleotide polymorphisms (SNP) related to hippocampal volume without making prior assumptions about possible candidate genes. In this study, we combined genetics, imaging and neuropsychological data obtained from the Mind Clinical Imaging Consortium study of schizophrenia (n = 328). A total of 743,591 SNPs were tested for association with hippocampal volume in a genome-wide association study. Gene expression profiles of human hippocampal tissue were investigated for gene regions of significantly associated SNPs. None of the genetic markers reached genome-wide significance. However, six highly correlated SNPs (rs4808611, rs35686037, rs12982178, rs1042178, rs10406920, rs8170) on chromosome 19p13.11, located within or in close proximity to the genes NR2F6, USHBP1, and BABAM1, as well as four SNPs in three other genomic regions (chromosome 1, 2 and 10) had p-values between 6.75×10−6 and 8.3×10−7. Using existing data of a very recently published GWAS of hippocampal volume and additional data of a multicentre study in a large cohort of adolescents of European ancestry, we found supporting evidence for our results. Furthermore, allelic differences in rs4808611 and rs8170 were highly associated with differential mRNA expression in the cis-acting region. Associations with memory functioning indicate a possible functional importance of the identified risk variants. Our findings provide new insights into the genetic architecture of a brain structure closely linked to schizophrenia. In silico replication, mRNA expression and cognitive data provide additional support for the relevance of our findings. Identification of causal variants and their functional effects may unveil yet unknown players in the neurodevelopment and the pathogenesis of neuropsychiatric disorders.

Solid Organ Transplantation in Patients with Inflammatory Bowel Diseases (IBD): Analysis of Transplantation Outcome and IBD Activity in a Large Single Center Cohort

Background Currently, limited data of the outcome of inflammatory bowel disease (IBD) in patients after solid organ transplantation (SOT) are available. We aimed to analyze effects of SOT on the IBD course in a large IBD patient cohort. Methods Clinical data from 1537 IBD patients were analyzed for patients who underwent SOT (n = 31) between July 2002 and May 2014. Sub-analyses included SOT outcome parameters, IBD activity before and after SOT, and efficacy of IBD treatment. Results 4.74% of patients with ulcerative colitis (UC) and 0.84% of patients with Crohn’s disease (CD) underwent SOT (p = 2.69 x 10−6, UC vs. CD). 77.4% of patients with SOT underwent liver transplantation (LTx) with tacrolimus-based immunosuppressive therapy after SOT. All LTx were due to primary sclerosing cholangitis (PSC) or PSC overlap syndromes. Six patients (19.4%) required renal transplantation and one patient (3.2%) heart transplantation. A survival rate of 83.9% after a median follow-up period of 103 months was observed. Before SOT, 65.0% of patients were in clinical remission and 5 patients received immunosuppressive therapy (16.1%). After SOT, 61.0% of patients were in remission (p = 1.00 vs. before SOT) and 29.0% required IBD-specific immunosuppressive or anti-TNF therapy (p = 0.54 vs. before SOT). 42.9% of patients with worsening of IBD after SOT were at higher risk of needing steroid therapy for increased IBD activity (p = 0.03; relative risk (RR): 10.29; 95% CI 1.26–84.06). Four patients (13.0%) needed anti-TNF therapy after SOT (response rate 75%). Conclusions SOT was more common in UC patients due to the higher prevalence of PSC-related liver cirrhosis in UC. Despite mainly tacrolimus-based immunosuppressive regimens, outcome of SOT and IBD was excellent in this cohort. In this SOT cohort, concomitant immunosuppressive therapy due to IBD was well tolerated.

The challenges of genome-wide interaction studies: Lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10−8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (N total = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.

Cost-effective GPU-Grid for Genome-wide Epistasis Calculations

BACKGROUND Until recently, genotype studies were limited to the investigation of single SNP effects due to the computational burden incurred when studying pairwise interactions of SNPs. However, some genetic effects as simple as coloring (in plants and animals) cannot be ascribed to a single locus but only understood when epistasis is taken into account [1]. It is expected that such effects are also found in complex diseases where many genes contribute to the clinical outcome of affected individuals. Only recently have such problems become feasible computationally. OBJECTIVES The inherently parallel structure of the problem makes it a perfect candidate for massive parallelization on either grid or cloud architectures. Since we are also dealing with confidential patient data, we were not able to consider a cloud-based solution but had to find a way to process the data in-house and aimed to build a local GPU-based grid structure. METHODS Sequential epistatsis calculations were ported to GPU using CUDA at various levels. Parallelization on the CPU was compared to corresponding GPU counterparts with regards to performance and cost. RESULTS A cost-effective solution was created by combining custom-built nodes equipped with relatively inexpensive consumer-level graphics cards with highly parallel GPUs in a local grid. The GPU method outperforms current cluster-based systems on a price/performance criterion, as a single GPU shows speed performance comparable up to 200 CPU cores. CONCLUSION The outlined approach will work for problems that easily lend themselves to massive parallelization. Code for various tasks has been made available and ongoing development of tools will further ease the transition from sequential to parallel algorithms.