Biology subjects

Koenen, K.

Publications and source records attributed to Koenen, K..

5 recordsLinked to original sources

bioRxiv2026

Fine mapping of PTSD GWAS reveals a role for amygdala Foxp2 in regulation of fear and threat responses

Post-traumatic Stress Disorder (PTSD) is a debilitating psychiatric condition caused by severe trauma exposure and characterized by ongoing dysregulation of fear processing, hyperarousal, and amygdala activation, but with limited effective treatments. Recent large-scale genome-wide association studies (GWAS) of PTSD have identified the transcription factor FOXP2 as a highly-significant, top putative risk gene. Both fine-mapping of the PTSD GWAS with amygdala-specific expression quantitative trait loci (eQTL) data, and transcriptome-wide association analyses, show that altered expression of FOXP2 is associated with increased PTSD risk. In vertebrates, FOXP2 mRNA is most densely expressed in the intercalated cells (ITCs) of the amygdala. ITC neurons receive excitatory input from external regulatory and sensory brain regions, as well as the basolateral amygdala, and send inhibitory projections to the central amygdala, which regulates downstream fear responses. While ITCs are critical for conditioned fear acquisition and extinction, the role of the FOXP2 gene in modulating fear-related behaviors remains unknown. Here, we used complementary bioinformatic, molecular, circuit, behavioral, and electrophysiological approaches to characterize the function of mouse (Foxp2) and human (FOXP2) orthologs in amygdala-mediated fear learning. To assess Foxp2 function in vivo, we first used shRNA-mediated knockdown (KD) of Foxp2 in ITC neurons of adult mice. Targeted Foxp2 KD robustly and significantly reduced freezing (threat/fear expression) during and after auditory fear conditioning. Whole-cell recordings from individual ITC neurons revealed that Foxp2 KD increased their intrinsic membrane excitability and action potential frequency, consistent with hypothesized enhanced inhibitory output to the central amygdala and thus reduced fear expression. This hyperexcitability was associated with reduced potassium channel conductance. Bulk RNA sequencing (RNA-seq) of mouse amygdala after ITC Foxp2 KD confirmed decreased potassium channel transcription and revealed broader Foxp2-dependent regulation of multiple genes implicated in fear learning, including Wnt, Crh (which encodes corticotropin-releasing hormone), and neurokinin signaling pathways. Consistent with these findings, bulk RNA-seq of medial amygdala postmortem tissue from humans with PTSD versus neurotypical controls showed decreased potassium channel transcription in samples with low FOXP2 expression. Downstream transcriptional changes following Foxp2 KD in the mouse amygdala also showed marked enrichment of genes identified in PTSD risk loci from the largest PTSD GWAS to date. Specifically, downregulated genes were enriched for mouse orthologs of Tier 1 PTSD GWAS risk genes. This enrichment appears to reflect subcortical Foxp2 signaling within the amygdala, driven predominantly by decreased expression of genes lacking promoter-anchored chromatin loops. This finding suggests that Foxp2 may directly bind regulatory elements of multiple top PTSD risk genes, acting as a key regulatory node for fear-related pathways in the amygdala. Collectively, our findings establish FOXP2 as a central transcriptional regulator of fear-related gene networks in the amygdala and potential regulatory hub for PTSD genetic risk.

neuroscience↗

bioRxiv2020

Heterogeneous Mediation Analysis for Causal Inference

DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mechanism of PTSD for African Americans still remains unknown. To fill this gap, in this paper, we investigate how DNAm mediates the effects of traumatic experiences on PTSD symptoms in the Detroit Neighborhood Health Study (DNHS) (2008-2013) which involves primarily African Americans adults. To achieve this, we develop a new mediation analysis approach for high-dimensional potential DNAm mediators. A key novelty of our method is that we consider heterogeneity in mediation effects across sub-populations. Specifically, mediators in different sub-populations could have opposite effects on the outcome, and thus could be difficult to identify under a traditional homogeneous model framework. In contrast, the proposed method can estimate heterogeneous mediation effects and identifies sub-populations in which individuals share similar effects. Simulation studies demonstrate that the proposed method outperforms existing methods for both homogeneous and heterogeneous data. We also present our mediation analysis results of a dataset with 125 participants and more than 450, 000 CpG sites from the DNHS study. The proposed method finds three sub-groups of subjects and identifies DNAm mediators corresponding to genes such as HSP90AA1 and NFATC1 which have been linked to PTSD symptoms in literature. Our finding could be useful in future finer-grained investigation of PTSD mechanism and in the development of new treatments for PTSD.

bioinformatics↗

bioRxiv2020

The Impact of Psychopathology, Social Adversity and Stress-relevant DNAm on Prospective Risk for Post-traumatic Stress: A Machine Learning Approach

BackgroundA range of factors have been identified that contribute to greater incidence, severity, and prolonged course of post-traumatic stress disorder (PTSD), including: comorbid and/or prior psychopathology; social adversity such as low socioeconomic position, perceived discrimination, and isolation; and biological factors such as genomic variation at glucocorticoid receptor regulatory network (GRRN) genes. This complex etiology and clinical course make identification of people at higher risk of PTSD challenging. Here we leverage machine learning (ML) approaches to identify a core set of factors that may together predispose persons to PTSD. MethodsWe used multiple ML approaches to assess the relationship among DNA methylation (DNAm) at GRRN genes, prior psychopathology, social adversity, and prospective risk for PTS severity (PTSS). ResultsML models predicted prospective risk of PTSS with high accuracy. The Gradient Boost approach was the top-performing model with mean absolute error of 0.135, mean square error of 0.047, root mean square error of 0.217, and R2 of 95.29%. Prior PTSS ranked highest in predicting the prospective risk of PTSS, accounting for >88% of the prediction. The top ranked GRRN CpG site was cg05616442, in AKT1, and the top ranked social adversity feature was loneliness. ConclusionMultiple factors including prior PTSS, social adversity, and DNAm play a role in predicting prospective risk of PTSS. ML models identified factors accounting for increased PTSS risk with high accuracy, which may help to target risk factors that reduce the likelihood or course of PTSD, potentially pointing to approaches that can lead to early intervention.

bioinformatics↗

bioRxiv2018

Testing Causal Bidirectional Influences between Physical Activity and Depression using Mendelian Randomization

BackgroundBurgeoning evidence from randomized controlled trials and prospective cohort studies suggests that physical activity protects against depression, pointing to a potential modifiable target for prevention. However, the direction of this inverse association is not clear: physical activity may reduce risk for depression, and/or depression may result in decreased physical activity. Here, we used bidirectional two-sample Mendelian randomization (MR) to test causal influences between physical activity and depression.\n\nMethodsFor genetic instruments, we selected independent top SNPs associated with major depressive disorder (MDD, N = 143,265) and two physical activity phenotypes--self-reported (N = 377,234) and objective accelerometer-based (N = 91,084)--from the largest available, non-overlapping genome-wide association results. We used two sets of genetic instruments: (1) only SNPs previously reported as genome-wide significant, and (2) top SNPs meeting a more relaxed threshold (p < 1x10-7). For each direction of influence, we combined the MR effect estimates from each instrument SNP using inverse variance weighted (IVW) meta-analysis, along with other standard MR methods such as weighted median, MR-Egger, and MR-PRESSO.\n\nResultsWe found evidence for protective influences of accelerometer-based activity on MDD (IVW odds ratio (OR) = 0.74 for MDD per 1 SD unit increase in average acceleration, 95% confidence interval (CI) = 0.59-0.92, p =.006) when using SNPs meeting the relaxed threshold (i.e., 10 versus only 2 genome-wide significant SNPs, which provided insufficient data for sensitivity analyses). In contrast, we found no evidence for negative influences of MDD on accelerometer-based activity (IVW b = 0.04 change in average acceleration for MDD versus control status, 95% CI = -0.43-0.51, p =.87). Furthermore, we did not see evidence for causal influences between self-reported activity and MDD, in either direction and regardless of instrument SNP criteria.\n\nDiscussionWe apply MR for the first time to examine causal influences between physical activity and MDD. We discover that objectively measured--but not self-reported--physical activity is inversely associated with MDD. Of note, prior work has shown that accelerometer-based physical activity is more heritable than self-reported activity, in addition to being more representative of actual movement. Our findings validate physical activity as a protective factor for MDD and point to the importance of objective measurement of physical activity in epidemiological studies in relation to mental health. Overall, this study supports the hypothesis that enhancing physical activity is an effective prevention strategy for depression.

genetics↗

bioRxiv2018

Prospective Study of Polygenic Risk, Protective Factors, and Incident Depression Following Combat Deployment in US Army Soldiers

BackgroundWhereas genetic susceptibility increases risk for major depressive disorder (MDD), non-genetic protective factors may mitigate this risk. In a large-scale prospective study of US Army soldiers, we examined whether trait resilience and/or unit cohesion could buffer against the onset of MDD following combat deployment, even in soldiers at high polygenic risk.\n\nMethodsData were analyzed from 4,182 soldiers of European ancestry assessed before and after their deployment to Afghanistan. Incident MDD was defined as no MDD episode at predeployment, followed by a MDD episode following deployment. Polygenic risk scores were constructed from the largest available MDD genome-wide association study. We first examined main effects of the MDD PRS and each protective factor on incident MDD. We then tested effects of each protective factor on incident MDD across strata of polygenic risk.\n\nResultsPolygenic risk showed a dose-response relationship to depression, such that soldiers at high polygenic risk had greatest odds for incident MDD. Both unit cohesion and trait resilience were prospectively associated with reduced risk for incident MDD. Notably, the protective effect of unit cohesion persisted even in soldiers at highest polygenic risk.\n\nConclusionsPolygenic risk was associated with new-onset MDD in deployed soldiers. However, unit cohesion--an index of perceived support and morale--was protective against incident MDD even among those at highest genetic risk, and may represent a potent target for promoting resilience in vulnerable soldiers. Findings illustrate the value of combining genomic and environmental data in a prospective design to identify robust protective factors for mental health.

genetics↗