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Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ genetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N combined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).

In 2008, van den Oord et al. identified in a genome-wide association study the MAM domain containing glycosylphosphatidylinositol anchor 2 gene (MDGA2 or MAMDC1) as a new candidate for neuroticism. In addition to the replication attempt of this association, we further investigated the role of MDGA2 with respect to harm avoidance (HA), a personality trait highly related to neuroticism. In a sample of mentally healthy volunteers (n=541) and depressed patients (n=199), neuroticism and HA were assessed with Eysenck's Revised Personality Questionnaire and Cloninger's Tridimensional Personality Questionnaire. Genotypic information (Illumina Bead Chip HumanHap300) of 100 single nucleotide polymorphisms (SNPs) located in the MDGA2 gene (±5 kb) was available, and additional four SNPs for replication were imputed. We were able to replicate the association between MDGA2 and neuroticism for the strongest SNPs of the genome-wide association study. It could further be shown that volunteers homozygous for the T-allele of SNP rs2416054 showed higher scores in the HA4 subscale 'Fatigability and asthenia' (Pnominal=0.0006), remaining significant after correction for multiple testing (Pwy-corrected=0.045). The same SNP also showed an association with HA4 in the patients' sample (Pnominal=0.03). Our finding provides further support for a link between variants in the MDGA2 gene and specific neuroticism-related phenotypes.

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.

The lifetime prevalence of panic disorder (PD) is up to 4% worldwide and there is substantial evidence that genetic factors contribute to the development of PD. Single-nucleotide polymorphisms (SNPs) in TMEM132D, identified in a whole-genome association study (GWAS), were found to be associated with PD in three independent samples, with a two-SNP haplotype associated in each of three samples in the same direction, and with a P-value of 1.2e-7 in the combined sample (909 cases and 915 controls). Independent SNPs in this gene were also associated with the severity of anxiety symptoms in patients affected by PD or panic attacks as well as in patients suffering from unipolar depression. Risk genotypes for PD were associated with higher TMEM132D mRNA expression levels in the frontal cortex. In parallel, using a mouse model of extremes in trait anxiety, we could further show that anxiety-related behavior was positively correlated with Tmem132d mRNA expression in the anterior cingulate cortex, central to the processing of anxiety/fear-related stimuli, and that in this animal model a Tmem132d SNP is associated with anxiety-related behavior in an F2 panel. TMEM132D may thus be an important new candidate gene for PD as well as more generally for anxiety-related behavior.

Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case-control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair.

Sixty percent of the patients with restless legs syndrome (RLS) report a positive family history. To date five loci have been mapped on chromosome 12q, 14q, 9p, 2q, and 20p (RLS1-5) but no gene has been identified so far. To identify genes related to RLS, we performed a three-stage association study (explorative study, replication study, high-density mapping) in two Caucasian RLS case-control samples of altogether 918 independent cases and controls. In the explorative study (367 cases and controls, respectively), we screened 1536 SNPs in 366 genes in a 21 Mb region encompassing the RLS1 critical region on chromosome 12. Armitage trend test revealed three genomic regions that were significant (P < 0.05). In the replication study (551 cases and controls, respectively) we genotyped the most significant SNPs of Stage 1. After correction for multiple testing, association was observed with SNP rs7977109 (P(nominal) = 0.00175, P(Westfall-Young) = 0.04895, OR = 0.76228, 95% CI = 0.64310-0.90355), which is in the neuronal nitric oxide synthase (NOS1) gene. High-density mapping using altogether 34 tagging and coding SNPs of the NOS1 gene in both case-control samples further confirmed the significant association results to NOS1. Ten more SNPs revealed significance with nominal P-values from 0.0001 to 0.0482 (genotypic test and Armitage test). Altogether, this study provides evidence for an association of variants in the NOS1 gene and RLS, and suggests the involvement of the NO/arginine pathway in the pathogenesis of RLS. Potential usage of NO modulating agents as new treatment options for RLS have become a challenging aspect for future research of this disorder., (2007 Movement Disorder Society)

The clinical efficacy of a systemically administered drug acting on the central nervous system depends on its ability to pass the blood-brain barrier, which is regulated by transporter molecules such as ABCB1 (MDR1). Here we report that polymorphisms in the ABCB1 gene predict the response to antidepressant treatment in those depressed patients receiving drugs that have been identified as substrates of ABCB1 using abcb1ab double-knockout mice. Our results indicate that the combined consideration of both the medication's capacity to act as an ABCB1-transporter substrate and the patient's ABCB1 genotype are strong predictors for achieving a remission. This finding can be viewed as a further step into personalized antidepressant treatment.

The stress hormone-regulating hypothalamic-pituitary-adrenal (HPA) axis has been implicated in the causality as well as the treatment of depression. To investigate a possible association between genes regulating the HPA axis and response to antidepressants and susceptibility for depression, we genotyped single-nucleotide polymorphisms in eight of these genes in depressed individuals and matched controls. We found significant associations of response to antidepressants and the recurrence of depressive episodes with single-nucleotide polymorphisms in FKBP5, a glucocorticoid receptor-regulating cochaperone of hsp-90, in two independent samples. These single-nucleotide polymorphisms were also associated with increased intracellular FKBP5 protein expression, which triggers adaptive changes in glucocorticoid receptor and, thereby, HPA-axis regulation. Individuals carrying the associated genotypes had less HPA-axis hyperactivity during the depressive episode. We propose that the FKBP5 variant-dependent alterations in HPA-axis regulation could be related to the faster response to antidepressant drug treatment and the increased recurrence of depressive episodes observed in this subgroup of depressed individuals. These findings support a central role of genes regulating the HPA axis in the causality of depression and the mechanism of action of antidepressant drugs.