Alterations in hippocampal volume are a known marker for first-episode psychosis (FEP) as well as for the clinical high-risk state. The Polygenic Schizophrenia-related Risk Score (PSRS), derived from a large case–control study, indicates the polygenic predisposition for schizophrenia in our clinical sample. A total of 65 at-risk mental state (ARMS) and FEP patients underwent structural magnetic resonance imaging. We used automatic segmentation of hippocampal volumes using the FSL-FIRST software and an odds-ratio-weighted PSRS based on the publicly available top single-nucleotide polymorphisms from the Psychiatric Genomics Consortium genome-wide association study (GWAS). We observed a negative association between the PSRS and hippocampal volumes (β=−0.42, P=0.01, 95% confidence interval (CI)=(−0.72 to −0.12)) across FEP and ARMS patients. Moreover, a higher PSRS was significantly associated with a higher probability of an individual being assigned to the FEP group relative to the ARMS group (β=0.64, P=0.03, 95% CI=(0.08–1.29)). These findings provide evidence that a subset of schizophrenia risk variants is negatively associated with hippocampal volumes, and higher values of this PSRS are significantly associated with FEP compared with the ARMS. This implies that FEP patients have a higher genetic risk for schizophrenia than the total cohort of ARMS patients. The identification of associations between genetic risk variants and structural brain alterations will increase our understanding of the neurobiology underlying the transition to psychosis.

Working memory (WM) is an important endophenotype in neuropsychiatric research and its use in genetic association studies is thought to be a promising approach to increase our understanding of psychiatric disease. As for any genetically complex trait, demonstration of sufficient heritability within the specific study context is a prerequisite for conducting genetic studies of that trait. Recently developed methods allow estimating trait heritability using sets of common genetic markers from genome-wide association study (GWAS) data in samples of unrelated individuals. Here we present single-nucleotide polymorphism (SNP)-based heritability estimates (h2SNP) for a WM phenotype. A Caucasian sample comprising a total of N=2298 healthy and young individuals was subjected to an N-back WM task. We calculated the genetic relationship between all individuals on the basis of genome-wide SNP data and performed restricted maximum likelihood analyses for variance component estimation to derive the h2SNP estimates. Heritability estimates for three 2-back derived WM performance measures based on all autosomal chromosomes ranged between 31 and 41%, indicating a substantial SNP-based heritability for WM traits. These results indicate that common genetic factors account for a prominent part of the phenotypic variation in WM performance. Hence, the application of GWAS on WM phenotypes is a valid method to identify the molecular underpinnings of WM.

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<0.001). A multilocus genetic score reflecting genetic variability of this signature is associated with memory performance (P=0.0003) in 3,346 young and elderly healthy adults. The genomic location of the contributing methylation sites points to the involvement of specific immune system genes. The decomposition of blood methylome-wide patterns bears considerable potential for the study of brain-related traits.

Emotional information is better remembered than neutral information. Extensive evidence indicates that the amygdala and its interactions with other cerebral regions play an important role in the memory-enhancing effect of emotional arousal. While the cerebellum has been found to be involved in fear conditioning, its role in emotional enhancement of episodic memory is less clear. To address this issue, we used a whole-brain functional MRI approach in 1,418 healthy participants. First, we identified clusters significantly activated during enhanced memory encoding of negative and positive emotional pictures. In addition to the well-known emotional memory–related cerebral regions, we identified a cluster in the cerebellum. We then used dynamic causal modeling and identified several cerebellar connections with increased connection strength corresponding to enhanced emotional memory, including one to a cluster covering the amygdala and hippocampus, and bidirectional connections with a cluster covering the anterior cingulate cortex. The present findings indicate that the cerebellum is an integral part of a network involved in emotional enhancement of episodic memory.

Depressive symptoms exist on a continuum, the far end of which is found in depressive disorders. Utilizing the continuous spectrum of depressive symptoms may therefore contribute to the understanding of the biological underpinnings of depression. Gene set enrichment analysis (GSEA) is an important tool for the identification of gene groups linked to complex traits, and was applied in the present study on genome-wide association study (GWAS) data of depression scores and their brain-level structural correlates in healthy young individuals. On symptom level (i.e. depression scores), robust enrichment was identified for two gene sets: NCAM1 Interactions and Collagen Formation. Depression scores were also associated with decreased fractional anisotropy (FA) - a brain white matter property - within the forceps minor and the left superior temporal longitudinal fasciculus. Within each of these tracts, mean FA value of depression score-associated voxels was used as a phenotype in a subsequent GSEA. The NCAM1 Interactions gene set was significantly enriched in these tracts. By linking the NCAM1 Interactions gene set to depression scores and their structural brain correlates in healthy participants, the current study contributes to the understanding of the molecular underpinnings of depressive symptomatology.