Schizophrenia and bipolar disorder have a largely unknown pathophysiology and etiology, but they are highly heritable. Although linkage and association studies have identified a series of chromosomal regions likely to contain susceptibility genes, progress in identifying causative genes has been largely disappointing. However, rapid technological advances are beginning to lead to new insights. Systematic genome-wide association and follow-up studies have reported genome-wide significant association findings of common variants for schizophrenia and bipolar disorder. The risk conferred by individual variants is small, and some variants confer a risk for both disorders. In addition, recent studies have identified rare, large structural variants (copy number variants) that confer a greater risk for schizophrenia. This review summarizes recent developments in genetic research into schizophrenia and bipolar disorder, and discusses possible future directions in this field.

Major depression (MD) is one of the most prevalent psychiatric disorders and a leading cause of loss in work productivity. A combination of genetic and environmental risk factors probably contributes to MD. We present data from a genome-wide association study revealing a neuron-specific neutral amino acid transporter (SLC6A15) as a susceptibility gene for MD. Risk allele carrier status in humans and chronic stress in mice were associated with a downregulation of the expression of this gene in the hippocampus, a brain region implicated in the pathophysiology of MD. The same polymorphisms also showed associations with alterations in hippocampal volume and neuronal integrity. Thus, decreased SLC6A15 expression, due to genetic or environmental factors, might alter neuronal circuits related to the susceptibility for MD. Our convergent data from human genetics, expression studies, brain imaging, and animal models suggest a pathophysiological mechanism for MD that may be accessible to drug targeting.

We conducted a genome-wide association study (GWAS) and a follow-up study of bipolar disorder (BD), a common neuropsychiatric disorder. In the GWAS, we investigated 499,494 autosomal and 12,484 X-chromosomal SNPs in 682 patients with BD and in 1300 controls. In the first follow-up step, we tested the most significant 48 SNPs in 1729 patients with BD and in 2313 controls. Eight SNPs showed nominally significant association with BD and were introduced to a meta-analysis of the GWAS and the first follow-up samples. Genetic variation in the neurocan gene (NCAN) showed genome-wide significant association with BD in 2411 patients and 3613 controls (rs1064395, p = 3.02 × 10(-8); odds ratio = 1.31). In a second follow-up step, we replicated this finding in independent samples of BD, totaling 6030 patients and 31,749 controls (p = 2.74 × 10(-4); odds ratio = 1.12). The combined analysis of all study samples yielded a p value of 2.14 × 10(-9) (odds ratio = 1.17). Our results provide evidence that rs1064395 is a common risk factor for BD. NCAN encodes neurocan, an extracellular matrix glycoprotein, which is thought to be involved in cell adhesion and migration. We found that expression in mice is localized within cortical and hippocampal areas. These areas are involved in cognition and emotion regulation and have previously been implicated in BD by neuropsychological, neuroimaging, and postmortem studies.

We undertook a two-stage genome-wide association study (GWAS) of Alzheimer's disease (AD) involving over 16,000 individuals, the most powerful AD GWAS to date. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the apolipoprotein E (APOE) locus (most significant SNP, rs2075650, P = 1.8 x 10(-157)) and observed genome-wide significant association with SNPs at two loci not previously associated with the disease: at the CLU (also known as APOJ) gene (rs11136000, P = 1.4 x 10(-9)) and 5' to the PICALM gene (rs3851179, P = 1.9 x 10(-8)). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimer's disease in the combined dataset (rs11136000, P = 8.5 x 10(-10), odds ratio = 0.86; rs3851179, P = 1.3 x 10(-9), odds ratio = 0.86).

The objective of this study was to investigate the hypothesis that borderline personality disorder (BPD) and bipolar disorder (BD) share genetic variation through analysis of known genetic risk factors for BD in a well-characterized BPD case-control cohort. Genotyping of five genome-wide significant variants identified for BD (in CACNA1C, ANK3, and ODZ4) was performed in 673 BPD cases and 748 controls. A nominally significant association with BPD was found for rs1006737 in CACNA1C (P=0.0498). Sex-specific analysis showed that this signal was present only in women. This is the first report of an association between a BD risk gene and BPD where selection was not based on a priori hypotheses about its function, but on an unbiased hypothesis-free screening of the genome. Genome-wide association data of large samples of BPD are warranted and will eventually identify new risk genes and the overlap between BPD and BD if it exists.

Bladder exstrophy-epispadias complex (BEEC), the severe end of the urorectal malformation spectrum, has a profound impact on continence as well as sexual and renal functions. It is widely accepted that for the majority of cases the genetic basis appears to be multifactorial. Here, we report the first study which utilizes genome-wide association methods to analyze a cohort comprising patients presenting the most common BEEC form, classic bladder exstrophy (CBE), to identify common variation associated with risk for isolated CBE. We employed discovery and follow-up samples comprising 218 cases/865 controls and 78 trios in total, all of European descent. Our discovery sample identified a marker near SALL1, showing genome-wide significant association with CBE. However, analyses performed on follow-up samples did not add further support to these findings. We were also able to identify an association with CBE across our study samples (discovery: P = 8.88 × 10(-5); follow-up: P = 0.0025; combined: 1.09 × 10(-6)) in a highly conserved 32 kb intergenic region containing regulatory elements between WNT3 and WNT9B. Subsequent analyses in mice revealed expression for both genes in the genital region during stages relevant to the development of CBE in humans. Unfortunately, we were not able to replicate the suggestive signal for WNT3 and WNT9B in a sample that was enriched for non-CBE BEEC cases (P = 0.51). Our suggestive findings support the hypothesis that larger samples are warranted to identify association of common variation with CBE.

Nonsyndromic cleft lip with or without cleft palate (nsCL/P) is among the most common human birth defects with multifactorial etiology. Here, we present results from a genome-wide imputation study of nsCL/P in which, after adding replication cohort data, four novel risk loci for nsCL/P are identified (at chromosomal regions 2p21, 14q22, 15q24 and 19p13). On a systematic level, we show that the association signals within this high-density dataset are enriched in functionally-relevant genomic regions that are active in both human neural crest cells (hNCC) and mouse embryonic craniofacial tissue. This enrichment is also detectable in hNCC regions primed for later activity. Using GCTA analyses, we suggest that 30% of the estimated variance in risk for nsCL/P in the European population can be attributed to common variants, with 25.5% contributed to by the 24 risk loci known to date. For each of these, we identify credible SNPs using a Bayesian refinement approach, with two loci harbouring only one probable causal variant. Finally, we demonstrate that there is no polygenic component of nsCL/P detectable that is shared with nonsyndromic cleft palate only (nsCPO). Our data suggest that, while common variants are strongly contributing to risk for nsCL/P, they do not seem to be involved in nsCPO which might be more often caused by rare deleterious variants. Our study generates novel insights into both nsCL/P and nsCPO etiology and provides a systematic framework for research into craniofacial development and malformation.

Schizophrenia and bipolar disorder are major psychiatric disorders with high heritability and overlapping genetic variance. Here we perform a genome-wide association study in an ethnically homogeneous cohort of 904 schizophrenia cases and 1,640 controls drawn from the Ashkenazi Jewish population. We identify a novel genome-wide significant risk locus at chromosome 4q26, demonstrating the potential advantages of this founder population for gene discovery. The top single-nucleotide polymorphism (SNP; rs11098403) demonstrates consistent effects across 11 replication and extension cohorts, totalling 23, 191 samples across multiple ethnicities, regardless of diagnosis (schizophrenia or bipolar disorder), resulting in Pmeta=9.49 × 10(-12) (odds ratio (OR)=1.13, 95% confidence interval (CI): 1.08-1.17) across both disorders and Pmeta=2.67 × 10(-8) (OR=1.15, 95% CI: 1.08-1.21) for schizophrenia alone. In addition, this intergenic SNP significantly predicts postmortem cerebellar gene expression of NDST3, which encodes an enzyme critical to heparan sulphate metabolism. Heparan sulphate binding is critical to neurite outgrowth, axon formation and synaptic processes thought to be aberrant in these disorders.

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic ("z-score") of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a "relative enrichment score" for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3.

Lithium is a first-line treatment in bipolar disorder, but individual response is variable. Previous studies have suggested that lithium response is a heritable trait. However, no genetic markers of treatment response have been reproducibly identified.

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis.

Schizophrenia is a severe neuropsychiatric disorder with high heritability, though its exact etiopathogenesis is yet unknown. An increasing number of studies point to the importance of white matter anomalies in the pathophysiology of schizophrenia. While several studies have identified the impact of schizophrenia susceptibility gene variants on gray matter anatomy in both schizophrenia patients and healthy risk variant carriers, studies dealing with the impact of these gene variants on white matter integrity are still scarce. We here present a study on the effects of a Dysbindin schizophrenia susceptibility gene variant on fiber tract integrity in healthy young subjects. 101 subjects genotyped for Dysbindin-gene variant rs1018381, though without personal or first degree relative history of psychiatric disorders underwent diffusion tensor imaging (DTI), 83 of them were included in the final analysis. We used Tract-Based Spatial Statistics (TBSS) analysis to delineate the major fiber tracts. Carriers of the minor allele T of the rs1018381 in the Dysbindin gene showed two clusters of reduced fractional anisotropy (FA) values in the perihippocampal region of the right temporal lobe compared to homozygote carriers of the major allele C. Clusters of increased FA values in T-allele carriers were found in the left prefrontal white matter, the right fornix, the right midbrain area, the left callosal body, the left cerebellum and in proximity of the right superior medial gyrus. Dysbindin has been implicated in neurite outgrowth and morphology. Impairments in anatomic connectivity as found associated with the minor Dysbindin allele in our study may result in increased risk for schizophrenia due to altered fiber tracts.

To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights.

Dowling-Degos disease (DDD) is an autosomal dominant genodermatosis characterized by progressive and disfiguring reticulate hyperpigmentation of the flexures. We performed a genomewide linkage analysis of two German families and mapped DDD to chromosome 12q, with a total LOD score of 4.42 ( theta =0.0) for marker D12S368. This region includes the keratin gene cluster, which we screened for mutations. We identified loss-of-function mutations in the keratin 5 gene (KRT5) in all affected family members and in six unrelated patients with DDD. These represent the first identified mutations that lead to haploinsufficiency in a keratin gene. The identification of loss-of-function mutations, along with the results from additional functional studies, suggest a crucial role for keratins in the organization of cell adhesion, melanosome uptake, organelle transport, and nuclear anchorage.

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

The role of genetic risk markers for Alzheimer's disease (AD) in mediating the neurocognitive endophenotypes (NEs) of subjects with mild cognitive impairment (MCI) has rarely been studied. The aim of the present study was to investigate the relationship between well-known AD-associated single-nucleotide polymorphisms (SNPs) and individual NEs routinely evaluated during diagnosis of MCI, AD, and other dementias. The Fundació ACE (ACE) dataset, comprising information from 1245 patients with MCI, was analyzed, including the total sample, amnestic MCI (aMCI) (n = 811), and non-amnestic MCI (naMCI) (n = 434). As probable-MCI (Pr-MCI) patients with memory impairment have a higher risk of AD, which could influence the statistical power to detect genetic associations, the MCI phenotype was also stratified into four related conditions: Pr-aMCI (n = 262), Pr-naMCI (n = 76), possible (Pss)-aMCI (n = 549), and Pss-naMCI (n = 358). Validation analyses were performed using data from the German study on Aging, Cognition, and Dementia in primary care patients (AgeCoDe), and the German Dementia Competence Network (DCN). SNP associations with NEs were calculated in PLINK using multivariate linear regression analysis adjusted for age, gender, and education. In the total MCI sample, APOE-ε4 was significantly associated with the memory function NEs "delayed recall (DR)" (β = -0.76, p = 4.1 × 10-10), "learning" (β = -1.35, p = 2.91 × 10-6), and "recognition memory" (β = -0.58, p = 9.67 × 10-5); and with "DR" in the aMCI group (β = -0.36, p = 2.96 × 10-5). These results were confirmed by validation in the AgeCoDe (n = 503) and DCN (n = 583) datasets. APOE-ε4 was also significantly associated with the NE "learning" in individuals classified as having Pss-aMCI (β = -1.37, p = 5.82 × 10-5). Moreover, there was a near study-wide significant association between the HS3ST1 locus (rs6448799) and the "backward digits" working memory NE (β = 0.52, p = 7.57 × 10-5) among individuals with Pr-aMCI, while the AP2A2 locus (rs10751667) was significantly associated with the language NE "repetition" (β = -0.19, p = 5.34 × 10-6). Overall, our findings support specific associations of established AD-associated SNPs with MCI NEs.

Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.

The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) genome-wide association study (GWAS) data sets, totalling 11,734 cases and 29,468 controls. A significant genetic correlation between these two B-cell malignancies was shown (Rg = 0.4, P = 0.0046). Furthermore, four of the 45 known CLL risk loci were shown to associate with MM risk and five of the 23 known MM risk loci associate with CLL risk. By integrating eQTL, Hi-C and ChIP-seq data, we show that these pleiotropic risk loci are enriched for B-cell regulatory elements and implicate B-cell developmental genes. These data identify shared biological pathways influencing the development of CLL and, MM and further our understanding of the aetiological basis of these B-cell malignancies.

Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype-phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted.

Several susceptibility loci for classical Hodgkin lymphoma have been reported. However, much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies, a new genome-wide association study, and replication totalling 5,314 cases and 16,749 controls. We identify risk loci for all classical Hodgkin lymphoma at 6q22.33 (rs9482849, P = 1.52 × 10-8) and for nodular sclerosis Hodgkin lymphoma at 3q28 (rs4459895, P = 9.43 × 10-17), 6q23.3 (rs6928977, P = 4.62 × 10-11), 10p14 (rs3781093, P = 9.49 × 10-13), 13q34 (rs112998813, P = 4.58 × 10-8) and 16p13.13 (rs34972832, P = 2.12 × 10-8). Additionally, independent loci within the HLA region are observed for nodular sclerosis Hodgkin lymphoma (rs9269081, HLA-DPB1*03:01, Val86 in HLA-DRB1) and mixed cellularity Hodgkin lymphoma (rs1633096, rs13196329, Val86 in HLA-DRB1). The new and established risk loci localise to areas of active chromatin and show an over-representation of transcription factor binding for determinants of B-cell development and immune response.