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Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = −0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Major Depressive Disorder (MDD) often is associated with significant cognitive dysfunction. We conducted a meta-analysis of genome-wide interaction of MDD and cognitive function using data from four large European cohorts in a total of 3510 MDD cases and 6057 controls. In addition, we conducted analyses using polygenic risk scores (PRS) based on data from the Psychiatric Genomics Consortium (PGC) on the traits of MDD, Bipolar disorder (BD), Schizophrenia (SCZ), and mood instability (MIN). Functional exploration contained gene expression analyses and Ingenuity Pathway Analysis (IPA®). We identified a set of significantly interacting single nucleotide polymorphisms (SNPs) between MDD and the genome-wide association study (GWAS) of cognitive domains of executive function, processing speed, and global cognition. Several of these SNPs are located in genes expressed in brain, with important roles such as neuronal development (REST), oligodendrocyte maturation (TNFRSF21), and myelination (ARFGEF1). IPA® identified a set of core genes from our dataset that mapped to a wide range of canonical pathways and biological functions (MPO, FOXO1, PDE3A, TSLP, NLRP9, ADAMTS5, ROBO1, REST). Furthermore, IPA® identified upstream regulator molecules and causal networks impacting on the expression of dataset genes, providing a genetic basis for further clinical exploration (vitamin D receptor, beta-estradiol, tadalafil). PRS of MIN and meta-PRS of MDD, MIN and SCZ were significantly associated with all cognitive domains. Our results suggest several genes involved in physiological processes for the development and maintenance of cognition in MDD, as well as potential novel therapeutic agents that could be explored in patients with MDD associated cognitive dysfunction.

A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex—areas that constitute hub nodes of the salience network—represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n = 2271), followed by meta-analysis and replication in a fifth cohort (n = 865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk. CA extern

Background Major depressive disorder (MDD) and type 2 diabetes mellitus (T2DM) are common public health disorders that often co-occur. This study aims to determine whether gene expression profiles from individuals with MDD or T2DM overlap and if there are any functional interconnectivity between identified genes using protein-protein interaction (PPI). Methods The DNA microarray datasets were extracted from the Gene Expression Omnibus. Gene expression dataset GSE98793 from a case-control study of MDD (64 healthy control subjects, 128 patients) and dataset GSE15653 from a case-control study of T2DM (nine controls, nine individuals with T2DM) were used for this secondary and post-hoc analysis. GO enrichment analyses and Reactome pathway enrichment analysis were performed for functional enrichment analyses with the shared genes. PPI networks, PPI clusters and hub genes were performed to detect the potential relationships among differentially expressed genes (DEG) -encoding proteins in both MDD and T2DM. Results A total of 3640 DEGs were identified in the MDD group when compared to the control group, whereas 3700 DEGs were identified in the T2DM group when compared to the control groups, among which 244 DEGs were overlap genes. The identified DEGs were enriched for Interleukin-4 and Interleukin-13 signaling, neutrophil degranulation, as well as other select species of the innate immune system. The biological processes of neurofibrillary tangle assembly regulation, tau-protein kinase activity regulation, amyloid-beta clearance regulation, amyloid-beta formation regulation and neuron apoptotic processes were also identified. Molecular function analysis indicated that identified genes were mainly enriched for amyloid-beta binding. 925 out of 1006 protein-protein interactions and six sub-networks were identified reflecting the disparate biological domains of overlapping genes. Ten hub genes further highlight the putative importance of tau-protein kinase activity, inflammatory response and neuron apoptotic regulatory processes across MDD and T2DM. Conclusions Our results indicate that an overlapping genetic architecture subserves MDD and T2DM. Genes relevant to the innate immune system, tau protein formation, and cellular aging were identified. Results indicate that the common, often comorbid, conditions of MDD and T2DM have a pathoetiologic nexus.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.

A complex interplay between genetic and environmental factors determines the individual risk of depressive disorders. Vitamin D has been shown to stimulate the expression of the tryptophan hydroxylase 2 (TPH2) gene, which is the rate-limiting enzyme for serotonin production in the brain. Therefore, we investigate the hypothesis that serum vitamin D levels moderate the interaction between the serotonin transporter promotor gene polymorphism (5-HTTLPR) and childhood abuse in depressive disorders. Two independent samples from the Study of Health in Pomerania (SHIP-LEGEND: n = 1 997; SHIP-TREND-0: n = 2 939) were used. Depressive disorders were assessed using questionnaires (BDI-II, PHQ-9) and interview procedures (DSM-IV). Besides serum vitamin D levels (25(OH)D), a functional polymorphism (rs4588) of the vitamin D-binding protein is used as a proxy for 25(OH)D. S-allele carriers with childhood abuse and low 25(OH)D levels have a higher mean BDI-II score (13.25) than those with a higher 25(OH)D level (9.56), which was not observed in abused LL-carriers. This significant three-way interaction was replicated in individuals with lifetime major depressive disorders when using the rs4588 instead of 25(OH)D (p = 0.0076 in the combined sample). We conclude that vitamin D relevantly moderates the interaction between childhood abuse and the serotonergic system, thereby impacting vulnerability to depressive disorders.

Importance Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations.Objective To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement.Design, Setting, and Participants This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019.Main Outcomes and Measures A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables.Results Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R2 = 0.41; 95% CI, 0.38-0.44), depression symptoms (R2 = 0.28; 95% CI, 0.25-0.32), global functioning (R2 = 0.16; 95% CI, 0.14-0.20), and quality of life (R2 = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial η2 = 0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort.Conclusions and Relevance Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.

Background Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases. Methods We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases. Results PRS for both population IQ (P = 4.39 × 10–28) and EA (P = 1.27 × 10–26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS. Conclusions Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors.

Supplemental Digital Content is available in the text., Background and Purpose— Structural integrity of the white matter is a marker of cerebral small vessel disease, which is the major cause of vascular dementia and a quarter of all strokes. Genetic studies provide a way to obtain novel insights in the disease mechanism underlying cerebral small vessel disease. The aim was to identify common variants associated with microstructural integrity of the white matter and to elucidate the relationships of white matter structural integrity with stroke, major depressive disorder, and Alzheimer disease. Methods— This genome-wide association analysis included 8448 individuals from UK Biobank—a population-based cohort study that recruited individuals from across the United Kingdom between 2006 and 2010, aged 40 to 69 years. Microstructural integrity was measured as fractional anisotropy- (FA) and mean diffusivity (MD)-derived parameters on diffusion tensor images. White matter hyperintensity volumes (WMHV) were assessed on T2-weighted fluid-attenuated inversion recovery images. Results— We identified 1 novel locus at genome-wide significance (VCAN [versican]: rs13164785; P=3.7×10−18 for MD and rs67827860; P=1.3×10−14 for FA). LD score regression showed a significant genome-wide correlation between FA, MD, and WMHV (FA-WMHV rG 0.39 [SE, 0.15]; MD-WMHV rG 0.56 [SE, 0.19]). In polygenic risk score analysis, FA, MD, and WMHV were significantly associated with lacunar stroke, MD with major depressive disorder, and WMHV with Alzheimer disease. Conclusions— Genetic variants within the VCAN gene may play a role in the mechanisms underlying microstructural integrity of the white matter in the brain measured as FA and MD. Mechanisms underlying white matter alterations are shared with cerebrovascular disease, and inherited differences in white matter microstructure impact on Alzheimer disease and major depressive disorder.

Increasing age is tightly linked to decreased thickness of the human neocortex. The biological mechanisms that mediate this effect are hitherto unknown. The DNA methylome, as part of the epigenome, contributes significantly to age-related phenotypic changes. Here, we identify an epigenetic signature that is associated with cortical thickness (P=3.86 × 10−8) and memory performance in 533 healthy young adults. The epigenetic effect on cortical thickness was replicated in a sample comprising 596 participants with major depressive disorder and healthy controls. The epigenetic signature mediates partially the effect of age on cortical thickness (P, Cortical thickness has high heritability estimates and is known to be influenced by genetic factors. Here, Freytag and colleagues show that DNA methylation patterns of peripheral blood monocytes are also correlated with cortical thickness and memory performance in human.

Epigenetic alterations provide a potential mechanism to account for the numerous gene-environment interactions that have been reported in association with neuropsychiatric phenotypes. In context to major depression disorder (MDD), where postmortem and neuroimaging studies provide insights into dysfunctional brain regions, involvement of genetic heterogeneity also revealed the complexity of this disorder. Despite intensive research during the past several decades and information from genome wide studies, pathophysiology of depressive disorders remained elusive. To evaluate the impact of epigenetic pressure on this disease, we took advantage of DNA isolated from different sections of human brain (prefrontal cortex and hippocampus) from clinically well-defined depressed patients and healthy individuals and performed pyrosequencing for DNA methylation analysis. Herein, we focused on two genes DLG4 (PSD-95) and GJA-1 (Connexin43) known to be associated with neuropsychiatric behavior. Comparing MDD with controls we found no differences of DNA methylation. Our results clearly demonstrate that DNA methylation levels on these particular genes are not associated with depression related phenotype.

BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Institute of Human Genetics, Department of Genomics, Life and Brain Center, Institute for Genomic Mathematics, Department of Psychiatry, University of Bonn, German Center for Neurodegenerative Diseases (DZNE), Bonn, Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Mannheim, Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Molecular and Clinical Neurobiology, Department of Psychiatry, Ludwig-Maximilians University, Munich, Department of Psychiatry, University of Halle-Wittenberg, Halle, Section of Psychiatric Genetics, Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Gottingen, Germany, Institute of Neuroscience and Medicine (INM-1), Structural and Functional Organisation of the Brain, Genomic Imaging, Research Centre Juelich, Juelich, Germany and Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA

The role of the brain-derived neurotrophic factor (BDNF) in the pathophysiology of major depressive disorder (MDD) remains to be elucidated. Recent post hoc analyses indicated a potential association of three polymorphisms in the BDNF gene with worse treatment outcome in patients with the subtype of melancholic depression. We aimed at replicating these findings in a German naturalistic multicenter follow-up. Three polymorphisms in the BDNF gene (rs7103411, rs6265 (Val66Met) and rs7124442) were genotyped in 324 patients with MDD and 470 healthy controls. We applied univariate tests and logistic regression models stratifying for depression subtype and gender. The three polymorphisms were not associated with MDD as diagnosis. Further, no associations were found in univariate tests. With logistic regression, we only found a tendency towards an association of the rs6265 (Val66Met) polymorphism with overall response to treatment (response rates: GG (val/val) < GA (val/met) < AA (met/met); p = 0.0129) and some gender differences for the rs6265 (Val66Met) and rs7103411 polymorphisms. Treatment outcome stratified for subtypes of depression did not differ significantly between the investigated polymorphisms or using haplotype analyses. However, results showed a tendency towards significance. At this stage, we cannot support an influence of these three polymorphisms. Further studies in larger patient samples to increase sample sizes of subgroups are warranted.

Factors contributing to treatment-emergent suicidal ideation (TESI) using antidepressants have been in the focus of recent research strategies. We investigated previously established clinical predictors of TESI and combined these with several polymorphisms of candidate genes in patients with major depressive disorder. Common polymorphisms involved in the tryptophan hydroxylase 1 (TPH1) and 2 (TPH2), serotonin transporter, monoamine oxidase A (MAOA) and brain-derived neurotrophic factor (BDNF) were investigated in a naturalistic inpatient study of the German research network on depression. We compared patients showing TESI with non-TESI suicidal patients and with non-suicidal patients using univariate tests to detect relevant factors, which were further tested in logistic regression and CART (Classification and Regression Trees) analyses. Of the 269 patients, TESI occurred in 22 patients (17 female), 117 patients were defined as non-TESI suicidal patients, and 130 patients were classified as non-suicidal. When comparing cases with both control groups we found the TPH2 rs1386494 (C/T) polymorphism to be moderately associated with TESI (Univariate tests: TESI vs. non-suicidality: p=0.005; adjusted: p=0.09; TESI vs. non-TESI suicidal patients: p=0.0024; adjusted: p=0.086). This polymorphism remained the only significant genetic factor in addition to clinical predictors in logistic regression and CART analyses. CART analyses suggested interactions with several clinical predictors. Haplotype analyses further supported a contribution of this polymorphism in TESI. The TPH2 rs1386494 (C/T) polymorphism might contribute to the genetic background of TESI. This polymorphism has been previously associated with committed suicide and major depressive disorder. The small number of cases warrants replication in larger patient samples. Lack of a placebo control group hampers definite conclusions on an association with antidepressive treatment.

Background Dysfunctions of serotonergic neurotransmission are supposed to be involved in the pathogenesis of psychiatric disorders such as major depressive disorder (MDD). The concentration of serotonin (5-hydroxytryptamine, 5-HT) in the synaptic cleft is essentially regulated by the 5-HT transporter (5-HTT). A length polymorphism repeat in the 5-HTT promoter region, termed 5-HTTLPR, has been commonly investigated for an association with psychiatric disorders. Methods Genotyping of the 5-HTTLPR is time-consuming and technically challenging. Recently, a two-SNP haplotype was identified that tags the 5-HTTLPR at r 2 =0.775. This allows extraction of 5-HTTLPR genotype information from large genome-wide association study (GWAS) data sets. In the present study we performed haplotype analysis using a German GWAS case-control dataset to test for an association between MDD and the two-SNP tagging haplotype for 5-HTTLPR. Results We detected a significant association between the TA haplotype (tagging the S-allele of the 5-HTTLPR) and MDD. Our result is consistent with previous findings of an association between the 5-HTTLPR S-allele and MDD. Limitations Using the two-SNP tagging haplotype did not allow testing of the tri-allelic genotype (but only the two-allelic genotype). This and the fact that the haplotype tags the 5-HTTLPR with an imperfect linkage disequilibrium of r 2 =0.775 may lead to some loss of power. Conclusions Our results provide further support for an involvement of the 5-HTTLPR in MDD and represent the first example of demonstrating association between MDD and the S-allele of the length polymorphism repeat using common SNP information from SNP-array data.

The majority of genetic risk factors for major depressive disorder (MDD) still await identification. Since copy number variants (CNVs) have been implicated in various neuropsychiatric disorders, the question arises as to whether CNVs also play a role in MDD. We performed a genome-wide CNV study using Illumina's SNP array data from 604 MDD patients and 1,643 controls. Putative CNVs were detected with the CNV algorithms QuantiSNP and PennCNV. CNVs with ≥30 consecutive SNPs and a log Bayes Factor/confidence value of ≥30 were statistically analyzed using PLINK. Further analyses and technical verification were only performed in the case of regions for which CNV calls from both programs showed nominal significance. Set-based tests were used to test whether common variants in the CNV regions showed association in two GWAS datasets of MDD. CNVs from four chromosomal regions were associated with MDD. The following were more frequent in patients than controls: microdeletions in 7p21.3 (P = 0.033) and 18p11.32 (P = 0.030); microduplications in 15q26.3 (P = 0.033); and the combination of microdeletion/duplications in 16p11.2 (P ≤ 0.018). SNPs in CNV region 16p11.2 showed significant association in a set-based test (P = 0.026). Microdeletions/duplications in 16p11.2 are the most promising CNVs, since these affect genes and CNVs in this region have been implicated in other neuropsychiatric disorders. The association finding for common SNPs provides further support for the hypothesis that this region is involved in the development of MDD. © 2012 Wiley Periodicals, Inc.

Recent genome-wide association studies have pointed to single-nucleotide polymorphisms (SNPs) in genes encoding the neuronal calcium channel CaV1.2 (CACNA1C; rs1006737) and the presynaptic active zone protein Piccolo (PCLO; rs2522833) as risk factors for affective disorders, particularly major depression. Previous neuroimaging studies of depression-related endophenotypes have highlighted the role of the subgenual cingulate cortex (CG25) in negative mood and depressive psychopathology. Here, we aimed to assess how recently associated PCLO and CACNA1C depression risk alleles jointly affect memory-related CG25 activity as an intermediate phenotype in clinically healthy humans. To investigate the combined effects of rs1006737 and rs2522833 on the CG25 response, we conducted three functional magnetic resonance imaging studies of episodic memory formation in three independent cohorts (N=79, 300, 113). An epistatic interaction of PCLO and CACNA1C risk alleles in CG25 during memory encoding was observed in all groups, with carriers of no risk allele and of both risk alleles showing higher CG25 activation during encoding when compared with carriers of only one risk allele. Moreover, PCLO risk allele carriers showed lower memory performance and reduced encoding-related hippocampal activation. In summary, our results point to region-specific epistatic effects of PCLO and CACNA1C risk variants in CG25, potentially related to episodic memory. Our data further suggest that genetic risk factors on the SNP level do not necessarily have additive effects but may show complex interactions. Such epistatic interactions might contribute to the 'missing heritability' of complex phenotypes.