Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

GWAS for executive function and processing speed suggests involvement of the CADM2 gene

To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.

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

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.

Genome-wide studies of verbal declarative memory in nondemented older people: the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium

BACKGROUND

Memory performance in older persons can reflect genetic influences on cognitive function and dementing processes. We aimed to identify genetic contributions to verbal declarative memory in a community setting.

METHODS

We conducted genome-wide association studies for paragraph or word list delayed recall in 19 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, comprising 29,076 dementia- and stroke-free individuals of European descent, aged ≥45 years. Replication of suggestive associations (p < 5 × 10(-6)) was sought in 10,617 participants of European descent, 3811 African-Americans, and 1561 young adults.

RESULTS

rs4420638, near APOE, was associated with poorer delayed recall performance in discovery (p = 5.57 × 10(-10)) and replication cohorts (p = 5.65 × 10(-8)). This association was stronger for paragraph than word list delayed recall and in the oldest persons. Two associations with specific tests, in subsets of the total sample, reached genome-wide significance in combined analyses of discovery and replication (rs11074779 [HS3ST4], p = 3.11 × 10(-8), and rs6813517 [SPOCK3], p = 2.58 × 10(-8)) near genes involved in immune response. A genetic score combining 58 independent suggestive memory risk variants was associated with increasing Alzheimer disease pathology in 725 autopsy samples. Association of memory risk loci with gene expression in 138 human hippocampus samples showed cis-associations with WDR48 and CLDN5, both related to ubiquitin metabolism.

CONCLUSIONS

This largest study to date exploring the genetics of memory function in ~40,000 older individuals revealed genome-wide associations and suggested an involvement of immune and ubiquitin pathways.

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.

Integrating gene expression and epidemiological data for the discovery of genetic interactions associated with cancer risk

Dozens of common genetic variants associated with cancer risk have been identified through genome-wide association studies (GWASs). However, these variants only explain a modest fraction of the heritability of disease. The missing heritability has been attributed to several factors, among them the existence of genetic interactions (G × G). Systematic screens for G × G in model organisms have revealed their fundamental influence in complex phenotypes. In this scenario, G × G overlap significantly with other types of gene and/or protein relationships. Here, by integrating predicted G × G from GWAS data and complex- and context-defined gene coexpression profiles, we provide evidence for G × G associated with cancer risk. G × G predicted from a breast cancer GWAS dataset identified significant overlaps [relative enrichments (REs) of 8-36%, empirical P values < 0.05 to 10(-4)] with complex (non-linear) gene coexpression in breast tumors. The use of gene or protein data not specific for breast cancer did not reveal overlaps. According to the predicted G × G, experimental assays demonstrated functional interplay between lipoma-preferred partner and transforming growth factor-β signaling in the MCF10A non-tumorigenic mammary epithelial cell model. Next, integration of pancreatic tumor gene expression profiles with pancreatic cancer G × G predicted from a GWAS corroborated the observations made for breast cancer risk (REs of 25-59%). The method presented here can potentially support the identification of genetic interactions associated with cancer risk, providing novel mechanistic hypotheses for carcinogenesis.

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.

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.

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.

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.

ANK3 and CACNA1C--missing genetic link for bipolar disorder and major depressive disorder in two German case-control samples

Recent genome-wide association studies (GWAS) and metaanalyses revealed genetic associations for ANK3 (ankyrin 3) and CACNA1C (alpha 1C subunit of the L-type voltage gated calcium channel) with bipolar disorder (BPD). Several findings from clinical, epidemiological, and genetic studies point towards a common biological background of BPD and major depressive disorder (MDD). We were interested whether this also applies for ANK3 and CACNA1C and tested associations of single nucleotide polymorphisms (SNPs) in these genes with MDD in two Caucasian case-control samples. Sample 1 (Munich Antidepressant Response Signature Project/MARS - MDD) consisted of 720 depressed inpatients and 542 psychiatric healthy controls. Sample 2 (unipolar recurrent depression (URD)) consisted of 827 patients with URD and 860 psychiatric healthy controls. After stringent quality control we analyzed 262 SNPs (sample 1) and 504 SNPs (sample 2) and imputed further 5771 SNPs (sample 1) and 5534 SNPs (sample 2) from Hapmap Phase 2 data in the ANK3 and CACNA1C gene regions. Additionally, a metaanalysis of both samples was performed. Several SNPs in both genes were nominally associated with MDD with the highest association in the 3'-region of ANK3 (rs10994143, nominal p = 3.3*10(-4)) in the metaanalysis of both samples. None of these results remained significant after correction for multiple testing. No association of MDD with SNPs previously reported in BPD studies could be detected. By analyzing the LD-structure, our highest associated SNPs could not be linked to the SNPs previously reported in BPD. Regarding ANK3 and CACNA1C, our findings do not support a strong genetic link between BPD and MDD for these two genes.

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 Crohn's 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.

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.