Biology subjects

Forster, G. L.

Publications and source records attributed to Forster, G. L..

5 recordsLinked to original sources

bioRxiv2023

Differing effects of alcohol use on epigenetic and brain age in adult children of alcoholic parents

It is known that being the adult child of an alcoholic (ACoA) can confer a wide variety of increased health and psychological risks, including higher rates of anxiety, depression, and posttraumatic stress disorder symptoms. Additionally, ACoAs are at greater risk of developing substance use disorders than individuals from non-alcoholic families. To better understand the psychobiological factors underlying these risks, ACoA individuals with risky hazardous alcohol use (n=14) and those not engaged in hazardous use (n=14) were compared to a group of healthy controls. We examined structural brain differences and applied machine learning algorithms to predict biological brain and DNA methylation ages to investigate differences between these groups. Contrary to our hypothesis, we found that hazardous and non-hazardous ACoA groups had lower predicted brain ages than the healthy control group (n=100), which may result from neuro-developmental differences between ACoA groups and controls. When examining specific brain regions, we observed decreased cortical volume within bilateral pars orbitalis and frontal poles, as well as the left middle temporal gyrus and entorhinal cortex within the hazardous alcohol ACoA group, all areas consistent with previous research examining how alcohol use affects brain structure. When looking at the epigenetic aging data, the hazardous ACoA participants had increased predicted epigenetic age difference scores compared to the control group (n=34) and the non-hazardous ACoA participant groups. In summary, the results demonstrate a decreased brain age in the ACoAs compared to control, concurrent with increased epigenetic age specifically in the hazardous ACoA group, laying the foundation for future research to identify individuals that may have an increased susceptibility to developing hazardous alcohol use. Together, these results provide a better understanding of the associations between epigenetic factors, brain structure, and alcohol use disorders.

neuroscience↗

bioRxiv2023

Sex differences in the effects of mild traumatic brain injury and progesterone treatment on anxiety-like behavior and fear conditioning in rats

Mild traumatic brain injuries (mild TBIs) commonly occur in young adults of both sexes, oftentimes in high-stress environments. In humans, sex differences have been observed in the development of post-concussive anxiety and PTSD-like behaviors. Progesterone, a sex steroid that has neuroprotective properties, restores cognitive function in animal models following more severe TBI, but its effectiveness in preventing the psychological symptoms associated with mild TBI has not been evaluated. Using a model of mild TBI that pairs a social stressor (social defeat) with weight drop, male and naturally estrous-cycling female rats were treated with 4 mg/kg progesterone or vehicle once daily for 5 days after injury. Behavioral measures, including elevated plus maze (EPM), contextual fear conditioning, and novel object recognition (NOR) were assessed following progesterone treatment. Anxiety-like behavior was increased by mild TBI in male rats, with a smaller effect seen in female rats in the diestrus phase at the time of EPM testing. In contrast, mild TBI impaired fear learning in female rats in estrus at the time of fear acquisition. Progesterone treatment failed to attenuate post-mild TBI anxiety-like behavior in either sex. Furthermore, progesterone increased fear conditioning and impaired NOR discrimination in male rats, independent of TBI status. Overall, both sex and estrous cycle contributed to psychological outcomes following mild TBI, which were not ameliorated by post-TBI progesterone. This suggests sex steroids play an important role as a moderator of the expression of mild TBI-induced psychological symptoms, rather than as a potential treatment for their underlying etiology.

neuroscience↗

bioRxiv2022

Multimodal Imaging-Based Classification of PTSD Using Data-Driven Computational Approaches: A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BackgroundCurrent clinical assessments of Posttraumatic stress disorder (PTSD) rely solely on subjective symptoms and experiences reported by the patient, rather than objective biomarkers of the illness. Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. Here we aimed to classify individuals with PTSD versus controls using heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. MethodsWe analyzed brain MRI data from 3,527 structural-MRI; 2,502 resting state-fMRI; and 1,953 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls (TEHC and HC) using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. ResultsWe found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history across all three modalities (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. ConclusionOur findings highlight the promise offered by machine learning methods for the diagnosis of patients with PTSD. The utility of brain biomarkers across three MRI modalities and the contribution of DVAE models for improving generalizability offers new insights into neural mechanisms involved in PTSD. Significance Classifying PTSD from trauma-unexposed healthy controls (HC) using three imaging modalities performed well ([~]75% AUC), but performance suffered markedly when classifying PTSD from trauma-exposed healthy controls (TEHC) using three imaging modalities ([~]60% AUC). Using deep learning for feature reduction (denoising variational auto-encoder; DVAE) dramatically reduced the number of features with no concomitant performance degradation. Utilizing denoising variational autoencoder (DVAE) models improves generalizability across heterogeneous multi-site data compared with the traditional machine learning frameworks

neuroscience↗

bioRxiv2019

Hippocampal subfield volumes are uniquely affected in PTSD and depression: International analysis of 31 cohorts from the PGC-ENIGMA PTSD Working Group

BackgroundPTSD and depression commonly co-occur and have been associated with smaller hippocampal volumes compared to healthy and trauma-exposed controls. However, the hippocampus is heterogeneous, with subregions that may be uniquely affected in individuals with PTSD and depression.\n\nMethodsWe used random effects regressions and a harmonized neuroimaging protocol based on FreeSurfer (v6.0) to identify sub-structural hippocampal markers of current PTSD (C-PTSD), depression, and the interaction of these conditions across 31 cohorts worldwide (N=3,115; Mage=38.9{+/-}13.9 years). Secondary analyses tested these associations by sex and after modeling the simultaneous effects of remitted PTSD, childhood trauma, mild traumatic brain injury, and alcohol use disorder.\n\nResultsA significant negative main effect of depression (n=800, vs. no depression, n=1456) was observed in the hippocampal tail ({beta}=-0.13) and CA1 ({beta}=-0.09) after adjusting for covariates and multiple testing (adjusted ps (q)=0.028). A main effect of C-PTSD (n=1042 vs. control, n=1359) was not significant, but an interaction between C-PTSD and depression was significant in the CA1 ({beta}=-0.24, q=0.044). Pairwise comparisons revealed significantly smaller CA1 volumes in individuals with C-PTSD+Depression than controls ({beta}=-0.12, q=0.012), C-PTSD-only ({beta}=-0.17, q=0.001), and Depression-only ({beta}=-0.18, q=0.023). Follow-up analyses revealed sex effects in the hippocampal tail of depressed females, and an interaction effect of C-PTSD and depression in the fimbria of males.\n\nConclusionsCollectively our results suggest that depression is a stronger predictor of hippocampal volumetry than PTSD, particularly in the CA1, and provide compelling evidence of more pronounced hippocampal phenotypes in comorbid PTSD and depression compared to either condition alone.

neuroscience↗

bioRxiv2019

Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed, which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3,049 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1,446 individuals with PTSD and 1,603 controls (2152 males/897 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohens d=-0.12, p=0.0021). The tapetum connects the left and right hippocampus, structures for which structure and function have been consistently implicated in PTSD. Results remained significant/similar after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

neuroscience↗