Biology subjects

Flory, J. D.

Publications and source records attributed to Flory, J. D..

3 recordsLinked to original sources

bioRxiv2021

Modeling gene x environment interactions in PTSD using glucocorticoid-induced transcriptomics in human neurons

Post-traumatic stress disorder (PTSD) results from severe trauma exposure, but the extent to which genetic and epigenetic risk factors impact individual clinical outcomes is unknown. We assessed the impact of genomic differences following glucocorticoid administration by examining the transcriptional profile of human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons and live cultured peripheral blood mononuclear cells from combat veterans with PTSD (n=5) and without PTSD (n=5). This parallel examination in baseline and glucocorticoid-treated conditions resolves cell-type specific and diagnosis-dependent elements of stress response, and permits discrimination of gene expression signals associated with PTSD risk from those induced by stress. Computational analyses revealed neuron-specific glucocorticoid-response expression patterns that were enriched for transcriptomic patterns observed in clinical PTSD samples. PTSD-specific signatures, albeit underpowered, accurately stratify veterans with PTSD relative to combat-exposed controls. Overall, in vitro PTSD and glucocorticoid response signatures in blood and brain cells represent exciting new platforms with which to test the genetic and epigenetic mechanisms underlying PTSD, identify biomarkers of PTSD risk and onset, and conduct drug-screening to identify novel therapeutics to prevent or ameliorate clinical phenotypes.

pathology↗

bioRxiv2019

Genomic Influences on Self-Reported Childhood Maltreatment

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to 1) identify genetic variation associated with reported childhood maltreatment, 2) calculate the relevant SNP-based heritability estimates, and 3) quantify the genetic overlap of reported childhood maltreatment with mental and physical health-related phenotypes. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n=124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder working group (PGC-PTSD) (n=26,290). Heritability estimations for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression (LDSR). Two genome-wide significant loci associated with childhood maltreatment, located on chromosomes 3p13 (rs142346759, beta=0.015, p=4.35x10-8, FOXP1) and 7q31.1 (rs10262462, beta=-0.016, p=3.24x10-8, FOXP2), were identified in the discovery dataset but were not replicated in the PGC-PTSD sample. SNP-based heritability for childhood maltreatment was estimated to be [~]6%. Childhood maltreatment was most significantly genetically correlated with depressive symptoms (rg=0.70, p=4.65x10-40). This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. FOXP genes could influence traits such as depression and thereby be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with various psychiatric disorders, may ultimately be useful in in developing targeted treatment and prevention strategies.

genomics↗

bioRxiv2018

Mechanistic insights on metabolic dysfunction in PTSD: Role of glucocorticoid receptor sensitivity and energy deficit

PTSD is associated with metabolic comorbidities; however it is not clear how the neuroendocrine disturbances affect metabolism. To analyze this we employed a systems biological approach using an integrated mathematical model of metabolism, HPA axis and inflammation. We combined the metabolomics, neuroendocrine, clinical lab and cytokine data from combat-exposed veterans with and without PTSD, to characterize the differences in regulatory effects. We used the pattern of fold change in metabolites representing pathway level differences as reference for metabolic control analysis (MCA) using the model. MCA revealed parameters constituting the HPA axis, inflammation and GPCR pathway that yielded metabolic dysfunction consistent with PTSD. To support this, we performed causal analysis between regulatory components and the significantly different metabolites in our sample. Causal inference revealed that the changes in glucocorticoid receptor sensitivity were mechanistically associated with metabolic dysfunction and the effects were jointly mediated by insulin resistance, inflammation, oxidative stress and energy deficit.

systems biology↗