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The molecular mechanisms underlying major depressive disorder (MDD) are largely unknown. Limited success of previous genetics studies may be attributable to heterogeneity of MDD, aggregating biologically different subtypes. We examined the polygenic features of MDD and two common clinical subtypes (typical and atypical) defined by symptom profiles in a large sample of adults with established diagnoses. Data were from 1530 patients of the Netherlands Study of Depression and Anxiety (NESDA) and 1700 controls mainly from the Netherlands Twin Register (NTR). Diagnoses of MDD and its subtypes were based on DSM-IV symptoms. Genetic overlap of MDD and subtypes with psychiatric (MDD, bipolar disorder, schizophrenia) and metabolic (body mass index (BMI), C-reactive protein, triglycerides) traits was evaluated via genomic profile risk scores (GPRS) generated from meta-analysis results of large international consortia. Single nucleotide polymorphism (SNP)-heritability of MDD and subtypes was also estimated. MDD was associated with psychiatric GPRS, while no association was found for GPRS of metabolic traits. MDD subtypes had differential polygenic signatures: typical was strongly associated with schizophrenia GPRS (odds ratio (OR)=1.54, P=7.8e-9), while atypical was additionally associated with BMI (OR=1.29, P=2.7e-4) and triglycerides (OR=1.21, P=0.006) GPRS. Similar results were found when only the highly discriminatory symptoms of appetite/weight were used to define subtypes. SNP-heritability was 32% for MDD, 38% and 43% for subtypes with, respectively, decreased (typical) and increased (atypical) appetite/weight. In conclusion, MDD subtypes are characterized by partially distinct polygenic liabilities and may represent more homogeneous phenotypes. Disentangling MDD heterogeneity may help the psychiatric field moving forward in the search for molecular roots of depression.

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project. © 2014 Macmillan Publishers Limited All rights reserved.

Genetic variation in a population can be summarized through principal component analysis (PCA) on genome-wide data. PCs derived from such analyses are valuable for genetic association studies, where they can correct for population stratification. We investigated how to capture the genetic population structure in a well-characterized sample from the Netherlands and in a worldwide data set and examined whether (1) removing long-range linkage disequilibrium (LD) regions and LD-based SNP pruning significantly improves correlations between PCs and geography and (2) whether genetic differentiation may have been influenced by migration and/or selection. In the Netherlands, three PCs showed significant correlations with geography, distinguishing between: (1) North and South; (2) East and West; and (3) the middle-band and the rest of the country. The third PC only emerged with minimized LD, which also significantly increased correlations with geography for the other two PCs. In addition to geography, the Dutch North-South PC showed correlations with genome-wide homozygosity (r=0.245), which may reflect a serial-founder effect due to northwards migration, and also with height (♂: r=0.142, ♀: r=0.153). The divergence between subpopulations identified by PCs is partly driven by selection pressures. The first three PCs showed significant signals for diversifying selection (545 SNPs-the majority within 184 genes). The strongest signal was observed between North and South for the functional SNP in HERC2 that determines human blue/brown eye color. Thus, this study demonstrates how to increase ancestry signals in a relatively homogeneous population and how those signals can reveal evolutionary history. © 2013 Macmillan Publishers Limited.

To access publisher's full text version of this article click on the hyperlink at the bottom of the page We tested whether polygenic risk scores for schizophrenia and bipolar disorder would predict creativity. Higher scores were associated with artistic society membership or creative profession in both Icelandic (P = 5.2 × 10(-6) and 3.8 × 10(-6) for schizophrenia and bipolar disorder scores, respectively) and replication cohorts (P = 0.0021 and 0.00086). This could not be accounted for by increased relatedness between creative individuals and those with psychoses, indicating that creativity and psychosis share genetic roots. Innovative Medicines Initiative 115008 European Union GA 286213 National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust King's College London Netherlands Organisation for Scientific Research NWO Investments 175.010.2005.011 911-03-012 Research Institute for Diseases in the Elderly 014-93-015 RIDE2 Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) 050-060-810 Erasmus Medical Center Erasmus University, Rotterdam Netherlands Organization for the Health Research and Development (ZonMw) Research Institute for Diseases in the Elderly (RIDE) Ministry of Education, Culture, and Science Ministry for Health, Welfare, and Sports European Commission (DG XII) Municipality of Rotterdam Netherlands Organization for Scientific Research (NWO) MagW/ZonMW BBMRI-NL 184.021.007 VU University Institute for Health and Care Research (EMGO+) Neuroscience Campus Amsterdam European Science Council (ERC) Genetics of Mental Illness 230374 Avera Institute for Human Genetics and US National Institute of Mental Health 1RC2MH089951-01 1RC2 MH089995 Ragnar Soderberg Foundation E9/11 Swedish Research Council 421-2013-1061 Jan Wallander and Tom Hedelius Foundation P2012-0002:1 Sven and Dagmar Salen Foundation Bank of Sweden Tercentenary Foundation M11-0451:1 Karolinska Institutet Netherlands Scientific Organization NWO 480-05-003 info:eu-repo/grantAgreement/EC/FP7/286213

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.