DICER1 is an enzyme that generates mature microRNAs (miRNAs), which regulate gene expression post-transcriptionally in brain and other tissues and is involved in synaptic maturation and plasticity. Here, through genome-wide differential gene expression survey of post-traumatic stress disorder (PTSD) with comorbid depression (PTSD&Dep), we find that blood DICER1 expression is significantly reduced in cases versus controls, and replicate this in two independent cohorts. Our follow-up studies find that lower blood DICER1 expression is significantly associated with increased amygdala activation to fearful stimuli, a neural correlate for PTSD. Additionally, a genetic variant in the 3' un-translated region of DICER1, rs10144436, is significantly associated with DICER1 expression and with PTSD&Dep, and the latter is replicated in an independent cohort. Furthermore, genome-wide differential expression survey of miRNAs in blood in PTSD&Dep reveals miRNAs to be significantly downregulated in cases versus controls. Together, our novel data suggest DICER1 plays a role in molecular mechanisms of PTSD&Dep through the DICER1 and the miRNA regulation pathway.

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.

MicroRNAs are important regulators of gene expression and associated with stress-related psychiatric disorders. Here, we report that exposing mice to chronic stress led to a specific increase in microRNA-15a levels in the amygdala-Ago2 complex and a concomitant reduction in the levels of its predicted target, FKBP51, which is implicated in stress-related psychiatric disorders. Reciprocally, mice expressing reduced levels of amygdalar microRNA-15a following exposure to chronic stress exhibited increased anxiety-like behaviors. In humans, pharmacological activation of the glucocorticoid receptor, as well as exposure to childhood trauma, was associated with increased microRNA-15a levels in peripheral blood. Taken together, our results support an important role for microRNA-15a in stress adaptation and the pathogenesis of stress-related psychopathologies.

Accelerated epigenetic aging, the difference between the DNA methylation-predicted age (DNAm age) and the chronological age, is associated with a myriad of diseases. This study investigates the relationship between epigenetic aging and risk and protective factors of PTSD. Genome-wide DNA methylation analysis was performed in 211 individuals including combat-exposed Australian veterans (discovery cohort, n = 96 males) and trauma-exposed civilian males from the Grady Trauma Project (replication cohort, n = 115 males). Primary measures included the Clinician Administered PTSD Scale for DSM-5 and the Connor-Davidson Resilience Scale (CD-RISC). DNAm age prediction was performed using the validated epigenetic clock calculator. Veterans with PTSD had increased PTSD symptom severity (P-value = 3.75 × 10-34) and lower CD-RISC scores (P-value = 7.5 × 10-8) than veterans without PTSD. DNAm age was significantly correlated with the chronological age (P-value = 3.3 × 10-6), but DNAm age acceleration was not different between the PTSD and non-PTSD groups (P-value = 0.24). Evaluating potential protective factors, we found that DNAm age acceleration was significantly associated with CD-RISC resilience scores in veterans with PTSD, these results remained significant after multiple testing correction (P-value = 0.023; r = 0.32). This finding was also replicated in an independent trauma-exposed civilian cohort (P-value = 0.02; r = 0.23). Post-hoc factor analyses revealed that this association was likely driven by "self-efficacy" items within the CD-RISC (P-value = 0.015; r = 0.35). These results suggest that among individuals already suffering from PTSD, some aspects of increased resilience might come at a biological cost.

Panic disorder (PD) affects about four million Europeans, with women affected twice as likely as men, causing substantial suffering and high economic costs. The etiopathogenesis of PD remains largely unknown, but both genetic and environmental factors contribute to risk. An epigenome-wide association study (EWAS) was conducted to compare medication-free PD patients (n = 89) with healthy controls (n = 76) stratified by gender. Replication was sought in an independent sample (131 cases, 169 controls) and functional analyses were conducted in a third sample (N = 71). DNA methylation was assessed in whole blood using the Infinium HumanMethylation450 BeadChip. One genome-wide association surviving FDR of 5% (cg07308824, P = 1.094 × 10-7, P-adj = 0.046) was identified in female PD patients (N = 49) compared to controls (N = 48). The same locus, located in an enhancer region of the HECA gene, was also hypermethylated in female PD patients in the replication sample (P = 0.035) and the significance of the association improved in the meta-analysis (P-adj = 0.004). Methylation at this CpG site was associated with HECA mRNA expression in another independent female sample (N = 71) both at baseline (P = 0.046) and after induction by dexamethasone (P = 0.029). Of 15 candidates, 5 previously reported as associated with PD or anxiety traits also showed differences in DNA methylation after gene-wise correction and included SGK1, FHIT, ADCYAP1, HTR1A, HTR2A. Our study examines epigenome-wide differences in peripheral blood for PD patients. Our results point to possible sex-specific methylation changes in the HECA gene for PD but overall highlight that this disorder is not associated with extensive changes in DNA methylation in peripheral blood.

Limited controlled data exist to guide treatment choices for clinicians caring for patients with major depressive disorder (MDD). Although many putative predictors of treatment response have been reported, most were identified through retrospective analyses of existing datasets and very few have been replicated in a manner that can impact clinical practice. One major confound in previous studies examining predictors of treatment response is the patient's treatment history, which may affect both the predictor of interest and treatment outcomes. Moreover, prior treatment history provides an important source of selection bias, thereby limiting generalizability. Consequently, we initiated a randomized clinical trial designed to identify factors that moderate response to three treatments for MDD among patients never treated previously for the condition.

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.

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

Epidemiologic and genetic studies suggest common environmental and genetic risk factors for a number of psychiatric disorders, including depression, bipolar disorder, and schizophrenia. Genetic and environmental factors, especially adverse life events, not only have main effects on disease development but also may interact to shape risk and resilience. Such gene by adversity interactions have been described for FKBP5, an endogenous regulator of the stress-neuroendocrine system, conferring risk for a number of psychiatric disorders. In this review, we present a molecular and cellular model of the consequences of FKBP5 by early adversity interactions. We illustrate how altered genetic and epigenetic regulation of FKBP5 may contribute to disease risk by covering evidence from clinical and preclinical studies of FKBP5 dysregulation, known cell-type and tissue-type expression patterns of FKBP5 in humans and animals, and the role of FKBP5 as a stress-responsive molecular hub modulating many cellular pathways. FKBP5 presents the possibility to better understand the molecular and cellular factors contributing to a disease-relevant gene by environment interaction, with implications for the development of biomarkers and interventions for psychiatric disorders.

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.

A major research finding in the field of Biological Psychiatry is that symptom-based categories of mental disorders map poorly onto dysfunctions in brain circuits or neurobiological pathways. Many of the identified (neuro) biological dysfunctions are "transdiagnostic", meaning that they do not reflect diagnostic boundaries but are shared by different ICD/DSM diagnoses. The compromised biological validity of the current classification system for mental disorders impedes rather than supports the development of treatments that not only target symptoms but also the underlying pathophysiological mechanisms. The Biological Classification of Mental Disorders (BeCOME) study aims to identify biology-based classes of mental disorders that improve the translation of novel biomedical findings into tailored clinical applications.

Single cell RNA-seq has revolutionized transcriptomics by providing cell type resolution for differential gene expression and expression quantitative trait loci (eQTL) analyses. However, efficient power analysis methods for single cell data and inter-individual comparisons are lacking. Here, we present scPower; a statistical framework for the design and power analysis of multi-sample single cell transcriptomic experiments. We modelled the relationship between sample size, the number of cells per individual, sequencing depth, and the power of detecting differentially expressed genes within cell types. We systematically evaluated these optimal parameter combinations for several single cell profiling platforms, and generated broad recommendations. In general, shallow sequencing of high numbers of cells leads to higher overall power than deep sequencing of fewer cells. The model, including priors, is implemented as an R package and is accessible as a web tool. scPower is a highly customizable tool that experimentalists can use to quickly compare a multitude of experimental designs and optimize for a limited budget.

Atherosclerotic cardiovascular disease (ACVD) is a lipid-driven inflammatory disease and one of the leading causes of death worldwide. Lipid deposits in the arterial wall lead to the formation of plaques that involve lipid oxidation, cellular necrosis, and complement activation, resulting in inflammation and thrombosis. The present study found that homozygous deletion of the CFHR1 gene, which encodes the plasma complement protein factor H-related protein 1 (FHR-1), was protective in two cohorts of patients with ACVD, suggesting that FHR-1 accelerates inflammation and exacerbates the disease. To test this hypothesis, FHR-1 was isolated from human plasma and was found to circulate on extracellular vesicles and to be deposited in atherosclerotic plaques. Surface-bound FHR-1 induced the expression of pro-inflammatory cytokines and tissue factor in both monocytes and neutrophils. Notably, plasma concentrations of FHR-1, but not of factor H, were significantly (p < 0.001) elevated in patients with ACVD, and correlated with the expression of the inflammation markers C-reactive protein, apolipoprotein serum amyloid protein A, and neopterin. FHR-1 expression also significantly correlated with plasma concentrations of low-density lipoprotein (LDL) (p < 0.0001) but not high-density lipoprotein (HDL). Taken together, these findings suggest that FHR-1 is associated with ACVD.

Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.

The placenta is a central organ during early development, influencing trajectories of health and disease. DNA methylation (DNAm) studies of human placenta improve our understanding of how its function relates to disease risk. However, DNAm studies can be biased by cell type heterogeneity, so it is essential to control for this in order to reduce confounding and increase precision. Computational cell type deconvolution approaches have proven to be very useful for this purpose. For human placenta, however, an assessment of the performance of these estimation methods is still lacking. Here, we examine the performance of a newly available reference-based cell type estimation approach and compare it to an often-used reference-free cell type estimation approach, namely RefFreeEWAS, in placental genome-wide DNAm samples taken at birth and from chorionic villus biopsies early in pregnancy using three independent studies comprising over 1000 samples. We found both reference-free and reference-based estimated cell type proportions to have predictive value for DNAm, however, reference-based cell type estimation outperformed reference-free estimation for the majority of data sets. Reference-based cell type estimations mirror previous histological knowledge on changes in cell type proportions through gestation. Further, CpGs whose variation in DNAm was largely explained by reference-based estimated cell type proportions were in the proximity of genes that are highly tissue-specific for placenta. This was not the case for reference-free estimated cell type proportions. We provide a list of these CpGs as a resource to help researchers to interpret results of existing studies and improve future DNAm studies of human placenta.

Genome-wide gene expression analyses are invaluable tools for studying biological and disease processes, allowing a hypothesis-free comparison of expression profiles. Traditionally, transcriptomic analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders. Here, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress receptor agonist dexamethasone in 8 mouse brain regions important for stress processing. By applying a combination of differential network- and expression-analyses, we find that these explain distinct but complementary biological mechanisms of the glucocorticoid responses. Additionally, network analysis identifies new differentially connected partners of risk genes and can be used to generate hypotheses on molecular pathways affected. With DiffBrainNet (http://diffbrainnet.psych.mpg.de), we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

Childhood maltreatment (CM) is an established major risk factor for a number of negative health outcomes later in life. While epigenetic mechanisms, such as DNA methylation (DNAm), have been proposed as a means of embedding this environmental risk factor, little is known about its timing and trajectory, especially in very young children. It is also not clear whether additional environmental adversities, often experienced by these children, converge on similar DNAm changes. Here, we calculated a cumulative adversity score, which additionally to CM includes socioeconomic status (SES), other life events, parental psychopathology and epigenetic biomarkers of prenatal smoking and alcohol consumption. We investigated the effects of CM alone as well as the adversity score on longitudinal DNAm trajectories in the Berlin Longitudinal Child Study. This is a cohort of 173 children aged 3-5 years at baseline of whom 86 were exposed to CM. These children were followed-up for 2 years with extensive psychometric and biological assessments as well as saliva collection at 5 time points providing genome-wide DNAm levels. Overall, only a few DNAm patterns were stable over this timeframe, but less than 10 DNAm regions showed significant changes. At baseline, neither CM nor the adversity score associated with DNAm changes. However, in 6 differentially methylated regions (DMRs), CM and the adversity score significantly moderated DNAm trajectories over time. A number of these DMRs have previously been associated with adverse prenatal exposures. In our study, children exposed to CM also presented with epigenetic signatures indicative of increased prenatal exposure to tobacco and alcohol, as compared to non-CM exposed children. These epigenetic signatures of prenatal exposure strongly correlate with DNAm regions associated with CM and the adversity score. Finally, weighted correlation network analysis revealed a module of CpGs exclusively associated with CM. While our study identifies DNAm loci specifically associated with CM, especially within long non-coding RNAs, the majority of associations were found with the adversity score with convergent association with indicators of adverse prenatal exposures. This study highlights the importance of mapping not only of the epigenome but also the exposome and extending the observational timeframe to well before birth.

Prenatal inflammation has been proposed as an important mediating factor in several adverse pregnancy outcomes. C-reactive protein (CRP) is an inflammatory cytokine easily measured in blood. It has clinical value due to its reliability as a biomarker for systemic inflammation and can indicate cellular injury and disease severity. Elevated levels of CRP in adulthood are associated with alterations in DNA methylation. However, no studies have prospectively investigated the relationship between maternal CRP levels and newborn DNA methylation measured by microarray in cord blood with reasonable epigenome-wide coverage. Importantly, the timing of inflammation exposure during pregnancy may also result in different effects. Thus, our objective was to evaluate this prospective association of CRP levels measured during multiple periods of pregnancy and in cord blood at delivery which was available in one cohort (i.e., Effects of Aspirin in Gestation and Reproduction trial), and also to conduct a meta-analysis with available data at one point in pregnancy from three other cohorts from the Pregnancy And Childhood Epigenetics consortium (PACE). Secondarily, the impact of maternal randomization to low dose aspirin prior to pregnancy on methylation was assessed.

Glucocorticoids (GCs) play a pivotal role in fetal programming. Antenatal treatment with synthetic GCs (sGCs) in individuals in danger of preterm labor is common practice. Adverse short- and long-term effects of antenatal sGCs have been reported, but their effects on placental epigenetic characteristics have never been systematically studied in humans.

Overweight and obesity are associated with altered stress reactivity and increased inflammation. However, it is not known whether stress-induced changes in brain function scale with BMI and if such associations are driven by peripheral cytokines. Here, we investigate multimodal stress responses in a large transdiagnostic sample using predictive modeling based on spatio-temporal profiles of stress-induced changes in activation and functional connectivity. BMI is associated with increased brain responses as well as greater negative affect after stress and individual response profiles are associated with BMI in females (pperm < 0.001), but not males. Although stress-induced changes reflecting BMI are associated with baseline cortisol, there is no robust association with peripheral cytokines. To conclude, alterations in body weight and energy metabolism might scale acute brain responses to stress more strongly in females compared to males, echoing observational studies. Our findings highlight sex-dependent associations of stress with differences in endocrine markers, largely independent of peripheral inflammation.