Genome-wide meta-analysis of ascertainment and symptom structures of major depression in case-enriched and community cohorts.

BACKGROUND: Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. METHODS: We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. RESULTS: The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms). CONCLUSION: The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

Genetic structure of major depression symptoms across clinical and community cohorts.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and aetiological subtypes. There are several challenges to integrating symptom data from genetically-informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. We conducted genome-wide association studies of major depressive symptoms in three clinical cohorts that were enriched for affected participants (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for missing data patterns in the community cohorts (use of Depression and Anhedonia as gating symptoms). The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analysing genetic association data.

Examining sex differences in neurodevelopmental and psychiatric genetic risk in anxiety and depression.

Anxiety and depression are common mental health disorders and have a higher prevalence in females. They are modestly heritable, share genetic liability with other psychiatric disorders, and are highly heterogeneous. There is evidence that genetic liability to neurodevelopmental disorders, such as attention deficit hyperactivity disorder (ADHD) is associated with anxiety and depression, particularly in females. We investigated sex differences in family history for neurodevelopmental and psychiatric disorders and neurodevelopmental genetic risk burden (indexed by ADHD polygenic risk scores (PRS) and rare copy number variants; CNVs) in individuals with anxiety and depression, also taking into account age at onset. We used two complementary datasets: 1) participants with a self-reported diagnosis of anxiety or depression (N = 4,178, 65.5% female; mean age = 41.5 years; N = 1,315 with genetic data) from the National Centre for Mental Health (NCMH) cohort and 2) a clinical sample of 13,273 (67.6% female; mean age = 45.2 years) patients with major depressive disorder (MDD) from the Psychiatric Genomics Consortium (PGC). We tested for sex differences in family history of psychiatric problems and presence of rare CNVs (neurodevelopmental and >500kb loci) in NCMH only and for sex differences in ADHD PRS in both datasets. In the NCMH cohort, females were more likely to report family history of neurodevelopmental and psychiatric disorders, but there were no robust sex differences in ADHD PRS or presence of rare CNVs. There was weak evidence of higher ADHD PRS in females compared to males in the PGC MDD sample, particularly in those with an early onset of MDD. These results do not provide strong evidence of sex differences in neurodevelopmental genetic risk burden in adults with anxiety and depression. This indicates that sex may not be a major index of neurodevelopmental genetic heterogeneity, that is captured by ADHD PRS and rare CNV burden, in adults with anxiety and depression.

Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk.

Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing 'depression-like' shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.8 ± 1.2 years) to map T-PRS onto brain morphology measures, including Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index, as well as broad MDD risk, indexed by self-reported family history of depression. We conducted side-by-side comparisons with a PRS independently derived from a Psychiatric Genomics Consortium (PGC) MDD GWAS (PGC-PRS), and sought to link T-PRS with diagnosis and symptom severity directly in PGC-MDD participants (n = 29,340, 59% women; 12,923 MDD cases, 16,417 controls). T-PRS was associated with smaller amygdala volume in women (t = -3.478, p = 0.001) and lower prefrontal gyrification across sexes. In men, T-PRS was associated with hypergyrification in temporal and occipital regions. Prefrontal hypogyrification mediated a male-specific indirect link between T-PRS and familial depression (b = 0.005, p = 0.029). PGC-PRS was similarly associated with lower amygdala volume and cortical gyrification; however, both effects were male-specific and hypogyrification emerged in distinct parietal and temporo-occipital regions, unassociated with familial depression. In PGC-MDD, T-PRS did not predict diagnosis (OR = 1.007, 95% CI = [0.997-1.018]) but correlated with symptom severity in men (rho = 0.175, p = 7.957 × 10-4) in one cohort (N = 762, 48% men). Depression-like shifts in cortical gene expression have sex-specific effects on brain morphology and may contribute to broad depression vulnerability in men.

The association between genetically determined ABO blood types and major depressive disorder.

ABO blood types and their corresponding antigens have long been assumed to be related to different human diseases. So far, smaller studies on the relationship between mental disorders and blood types yielded contradicting results. In this study we analyzed the association between ABO blood types and lifetime major depressive disorder (MDD). We performed a pooled analysis with data from 26 cohorts that are part of the MDD working group of the Psychiatric Genomics Consortium (PGC). The dataset included 37,208 individuals of largely European ancestry of which 41.6% were diagnosed with lifetime MDD. ABO blood types were identified using three single nucleotide polymorphisms in the ABO gene: rs505922, rs8176746 and rs8176747. Regression analyses were performed to assess associations between the individual ABO blood types and MDD diagnosis as well as putative interaction effects with sex. The models were adjusted for sex, cohort and the first ten genetic principal components. The percentage of blood type A was slightly lower in cases than controls while blood type O was more prominent in cases. However, these differences were not statistically significant. Our analyses found no evidence of an association between ABO blood types and major depressive disorder.

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression.

BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.

Time Course of Changes in Peripheral Blood Gene Expression During Medication Treatment for Major Depressive Disorder.

Changes in gene expression (GE) during antidepressant treatment may increase understanding of the action of antidepressant medications and serve as biomarkers of efficacy. GE changes in peripheral blood are desirable because they can be assessed easily on multiple occasions during treatment. We report here on GE changes in 68 individuals who were treated for 8 weeks with either escitalopram alone, or escitalopram followed by bupropion. GE changes were assessed after 1, 2, and 8 weeks of treatment, with significant changes observed in 156, 121, and 585 peripheral blood gene transcripts, respectively. Thirty-one transcript changes were shared between the 1- and 8-week time points (seven upregulated, 24 downregulated). Differences were detected between the escitalopram- and bupropion-treated subjects, although there was no significant association between GE changes and clinical outcome. A subset of 18 genes overlapped with those previously identified as differentially expressed in subjects with MDD compared with healthy control subjects. There was statistically significant overlap between genes differentially expressed in the current and previous studies, with 10 genes overlapping in at least two previous studies. There was no enrichment for genes overexpressed in nervous system cell types, but there was a trend toward enrichment for genes in the WNT/ß-catenin pathway in the anterior thalamus; three genes in this pathway showed differential expression in the present and in three previous studies. Our dataset and other similar studies will provide an important source of information about potential biomarkers of recovery and for potential dysregulation of GE in MDD.

An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype.

BACKGROUND: The genetics of depression has been explored in genome-wide association studies that focused on either major depressive disorder or depressive symptoms with mostly negative findings. A broad depression phenotype including both phenotypes has not been tested previously using a genome-wide association approach. We aimed to identify genetic polymorphisms significantly associated with a broad phenotype from depressive symptoms to major depressive disorder. METHODS: We analyzed two prior studies of 70,017 participants of European ancestry from general and clinical populations in the discovery stage. We performed a replication meta-analysis of 28,328 participants. Single nucleotide polymorphism (SNP)-based heritability and genetic correlations were calculated using linkage disequilibrium score regression. Discovery and replication analyses were performed using a p-value-based meta-analysis. Lifetime major depressive disorder and depressive symptom scores were used as the outcome measures. RESULTS: The SNP-based heritability of major depressive disorder was 0.21 (SE = 0.02), the SNP-based heritability of depressive symptoms was 0.04 (SE = 0.01), and their genetic correlation was 1.001 (SE = 0.2). We found one genome-wide significant locus related to the broad depression phenotype (rs9825823, chromosome 3: 61,082,153, p = 8.2 × 10-9) located in an intron of the FHIT gene. We replicated this SNP in independent samples (p = .02) and the overall meta-analysis of the discovery and replication cohorts (1.0 × 10-9). CONCLUSIONS: This large study identified a new locus for depression. Our results support a continuum between depressive symptoms and major depressive disorder. A phenotypically more inclusive approach may help to achieve the large sample sizes needed to detect susceptibility loci for depression.

Genome-wide Association for Major Depression Through Age at Onset Stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium.

BACKGROUND: Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset. METHODS: Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer's disease, and coronary artery disease. RESULTS: We identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11-1.21, p = 5.2 × 10-11). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD. CONCLUSIONS: We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder.

The promise of psychiatric pharmacogenomics.

Clinicians already face "personalized" medicine every day while experiencing the great variation in toxicities and drug efficacy among individual patients. Pharmacogenetics studies are the platform for discovering the DNA determinants of variability in drug response and tolerability. Research now focuses on the genome after its beginning with analyses of single genes. Therapeutic outcomes from several psychotropic drugs have been weakly linked to specific genetic variants without independent replication. Drug side effects show stronger associations to genetic variants, including human leukocyte antigen loci with carbamazepine-induced dermatologic outcome and MC4R with atypical antipsychotic weight gain. Clinical implementation has proven challenging, with barriers including a lack of replicable prospective evidence for clinical utility required for altering medical care. More recent studies show promising approaches for reducing these barriers to routine incorporation of pharmacogenetics data into clinical care.

NPAS1 represses the generation of specific subtypes of cortical interneurons.

Little is known about genetic mechanisms that regulate the ratio of cortical excitatory and inhibitory neurons. We show that NPAS1 and NPAS3 transcription factors (TFs) are expressed in progenitor domains of the mouse basal ganglia (subpallium, MGE, and CGE). NPAS1(-/-) mutants had increased proliferation, ERK signaling, and expression of Arx in the MGE and CGE. NPAS1(-/-) mutants also had increased neocortical inhibition (sIPSC and mIPSC) and generated an excess of somatostatin(+) (SST) (MGE-derived) and vasoactive intestinal polypeptide(+) (VIP) (CGE-derived) neocortical interneurons, but had a normal density of parvalbumin(+) (PV) (MGE-derived) interneurons. In contrast, NPAS3(-/-) mutants showed decreased proliferation and ERK signaling in progenitors of the ganglionic eminences and had fewer SST(+) and VIP(+) interneurons. NPAS1 repressed activity of an Arx enhancer, and Arx overexpression resulted in increased proliferation of CGE progenitors. These results provide insights into genetic regulation of cortical interneuron numbers and cortical inhibitory tone.

Evidence for linkage and association of GABRB3 and GABRA5 to panic disorder.

Panic disorder (PD) is a debilitating anxiety disorder characterized by episodes of intense fear with autonomic and psychological symptoms that lead to behavioral impairment. A convergence of genetic and biological evidence implicates gamma-aminobutyric acid type A receptor subunits on chromosome 15q12 as candidate genes for PD. This study investigated 120 Caucasian, multiplex PD pedigrees using regional microsatellites (chr15q11-13) and found support for linkage (logarithm of odds (LOD) ⩾2), with a prominent parent-of-origin effect. Genotyping with 10 single-nucleotide polymorphisms (SNPs) showed linkage to GABRB3 (rs11631421, LOD=4.6) and GABRA5 (rs2075716, LOD=2.2), and allelic association to GABRB3 (rs8024564, p=0.005; rs8025575, p=0.02) and GABRA5 (rs35399885, p=0.05). Genotyping of an independent Sardinian PD trio sample also supported association in the region, again with a parent-of-origin effect. These findings provide genetic evidence for the involvement of the genes GABRB3 and GABRA5 in the susceptibility to PD.

Rare copy number variation in treatment-resistant major depressive disorder.

BACKGROUND: While antidepressant treatment response appears to be partially heritable, no consistent genetic associations have been identified. Large, rare copy number variants (CNVs) play a role in other neuropsychiatric diseases, so we assessed their association with treatment-resistant depression (TRD). METHODS: We analyzed data from two genome-wide association studies comprising 1263 Caucasian patients with major depressive disorder. One was drawn from a large health system by applying natural language processing to electronic health records (i2b2 cohort). The second consisted of a multicenter study of sequential antidepressant treatments, Sequenced Treatment Alternatives to Relieve Depression. The Birdsuite package was used to identify rare deletions and duplications. Individuals without symptomatic remission, despite two antidepressant treatment trials, were contrasted with those who remitted with a first treatment trial. RESULTS: CNV data were derived for 778 subjects in the i2b2 cohort, including 300 subjects (37%) with TRD, and 485 subjects in Sequenced Treatment Alternatives to Relieve Depression cohort, including 152 (31%) with TRD. CNV burden analyses identified modest enrichment of duplications in cases (empirical p = .04 for duplications of 100-200 kilobase) and a particular deletion region spanning gene PABPC4L (empirical p = .02, 6 cases: 0 controls). Pathway analysis suggested enrichment of CNVs intersecting genes regulating actin cytoskeleton. However, none of these associations survived genome-wide correction. CONCLUSIONS: Contribution of rare CNVs to TRD appears to be modest, individually or in aggregate. The electronic health record-based methodology demonstrated here should facilitate collection of larger TRD cohorts necessary to further characterize these effects.

A pilot study evaluating genetic and environmental factors for postpartum depression.

OBJECTIVE: To assess the influence of genetic and environmental risk factors upon postpartum depression. DESIGN: Case-control, prospective study. SETTING: The University of California at San Francisco Obstetric and Gynecology Clinic. PARTICIPANTS: Mothers screened for postpartum depression six weeks after delivery with the Edinburgh Postnatal Depression Scale and recruited as cases and controls. MEASUREMENTS: Eligible subjects completed a series of assessments and a structured clinical interview to confirm diagnosis of depression. Deoxyribonucleic acid was obtained for genotyping of 81 single nucleotide polymorphisms in 12 genes hypothesized to be postpartum depression-related. RESULTS: Twenty-four cases and 24 controls were eligible for analysis. Three single necleotide polymorphisms in the serotonin 2A receptor (HTR2A) gene were associated with postpartum depression. The strongest association at a functional promoter polymorphism (rs6311), a functional promoter single nucleotide polymorphisms (p=0.002, odds ratio 0.25, 95% confidence interval:0.10-0.63), was a finding robust to population stratification. Gene-wide association was significant for HTR2A (permuted p=0.008), but not when corrected for all 12 genes. Analysis of demographic and psychosocial risk factors identified distressed relationship, unplanned pregnancy, and a previous history of depression as significant predictive variables (p≤0.05). CONCLUSIONS: This pilot data suggests deoxyribonucleic acid variations in HTR2A may be associated with postpartum depression. Psychosocial variables were also identified as risk factors. The relative influence of these variables on the manifestation of postpartum depression is yet to be determined.

A genome-wide association study of a sustained pattern of antidepressant response.

Genome-wide association studies (GWAS) have failed to replicate common genetic variants associated with antidepressant response, as defined using a single endpoint. Genetic influences may be discernible by examining individual variation between sustained versus unsustained patterns of response, which may distinguish medication effects from non-specific, or placebo responses to active medication. We conducted a GWAS among 1116 subjects with Major Depressive Disorder from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial who were characterized using Growth Mixture Modeling as showing a sustained versus unsustained pattern of clinical response over 12 weeks of treatment with citalopram. Replication analyses examined 585 subjects from the Genome-based Therapeutic Drugs for Depression (GENDEP) trial. The strongest association with sustained as opposed to unsustained response in STAR*D involved a single nucleotide polymorphism (SNP; rs10492002) within the acyl-CoA synthetase short-chain family member 3 gene (ACSS3, p-value=4.5×10(-6), odds ratio=0.61). No SNPs met our threshold for genome-wide significance. SNP data were available in GENDEP for 18 of the top 25 SNPs in STAR*D. The most replicable association was with SNP rs7816924 (p=0.008, OR=1.58); no SNP met the replication p-value threshold of 0.003. Joint analysis of these 18 SNPs resulted in the strongest signal coming from rs7816924 (p=2.11×10(-7)), which resides in chondroitin sulfate N-acetylgalactosaminyltransferase 1 gene (CSGALNACT1). An exploratory genetic pathway analysis revealed evidence for an involvement of the KEGG pathway of long-term potentiation (FDR=.02). Results suggest novel genetic associations to sustained response.

Spontaneous brain activity in combat related PTSD.

Posttraumatic stress disorder (PTSD) is a prevalent psychiatric disorder, especially in combat veterans. Existing functional neuroimaging studies have provided important insights into the neural mechanisms of PTSD using various experimental paradigms involving trauma recollection or other forms of emotion provocation. However it is not clear whether the abnormal brain activity is specific to the mental processes related to the experimental tasks or reflects general patterns across different brain states. Thus, studying intrinsic spontaneous brain activity without the influence of external tasks may provide valuable alternative perspectives to further understand the neural characteristics of PTSD. The present study evaluated the magnitudes of spontaneous brain activity of male US veterans with or without PTSD, with the two groups matched on age, gender, and ethnicity. Amplitudes of low frequency fluctuation (ALFF), a data driven analysis method, were calculated on each voxel of the resting state fMRI data to measure the magnitudes of spontaneous brain activity. Results revealed that PTSD subjects showed increased spontaneous activity in the amygdala, ventral anterior cingulate cortex, insula, and orbital frontal cortex, as well as decreased spontaneous activity in the precuneus, dorsal lateral prefrontal cortex and thalamus. Within the PTSD group, larger magnitudes of spontaneous activity in the thalamus, precuneus and dorsal lateral prefrontal cortex were associated with lower re-experiencing symptoms. Comparing our results with previous functional neuroimaging findings, increased activity of the amygdala and anterior insula and decreased activity of the thalamus are consistent patterns across emotion provocation states and the resting state.

Using the high-risk family design to identify biomarkers for major depression.

The familial nature of major depressive disorder (MDD) is now well recognized. We followed children and grandchildren of probands with and without MDD to examine transmission of depression over generations, and to identify early vulnerability markers prior to the onset of disease. The study now includes three generations and five completed assessment waves spanning 25 years, with a sixth wave underway. Beginning with the fourth wave, we collected measures of brain structure (magnetic resonance imaging, MRI) and physiology (electroencephalography, EEG) and DNA in order to examine at a biological level why the offspring of depressed parents were at higher risk. In this paper, we provide an overview of the study design, the main findings, including new data, and the role of the high-risk design in translational research. We demonstrate that offspring of depressed parents ('high-risk'), when compared with those of non-depressed parents ('low-risk'), were at increased risk for depressive and anxiety disorders, with anxiety appearing earlier and being a predisposing factor for MDD. Offspring with two generations previously affected were at greatest risk. Thinning of the cortical mantle (MRI) and reduced resting-state activity (EEG) within the right parieto-temporal hemisphere differentiated high- from low-risk offspring, regardless of whether the offspring had MDD, suggesting that these measures might serve as familial trait markers for depression and related syndromes. The high- and low-risk offspring also differed by serotonin transporter promoter length polymorphism genotypes, even though the same genotypes were not associated with the presence of MDD. The high-risk epidemiological design appears to be a particularly valuable asset in translational research as it allows targeting of biological processes that emerge prior to the onset of disease, and identifies individuals at high risk for the disorder who may carry the trait or marker but not yet be affected.

A mega-analysis of genome-wide association studies for major depressive disorder.

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.