Biology subjects

Jett, M.

Publications and source records attributed to Jett, M..

4 recordsLinked to original sources

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↗

bioRxiv2019

Role of enhanced glucocorticoid receptor sensitivity in inflammation in PTSD: Insights from a computational model for circadian-neuroendocrine-immune interactions

Although glucocorticoid resistance contributes to increased inflammation, individuals with post-traumatic stress disorder (PTSD) exhibit increased glucocorticoid receptor (GR) sensitivity along with increased inflammation. It is not clear how inflammation co-exists with a hyper-responsive hypothalamic pituitary adrenal axis (HPA axis). To understand this better, we developed and analyzed an integrated mathematical model for the HPA axis and the immune system. We performed mathematical simulations for a dexamethasone suppression test and IC50-dexamethasone for cytokine suppression, by varying model parameters. The model analysis suggests that increasing the steepness of the dose response curve for GR activity may reduce anti-inflammatory effects of GRs at the ambient glucocorticoid levels thereby increasing pro-inflammatory response. The adaptive response of pro-inflammatory cytokine mediated stimulatory effects on the HPA-axis is reduced due to dominance of the GR-mediated negative feedback on the HPA-axis. To verify these hypotheses we analyzed the clinical data on neuro-endocrine variables and cytokines obtained from war-zone veterans with and without PTSD. We observed significant group differences for cortisol and ACTH suppression tests, pro-inflammatory cytokines TNF and IL6, hs-CRP, promoter methylation of GR gene and IC50-Dex for lysozyme suppression. Causal inference modelling revealed significant associations between cortisol suppression and post-dex cortisol decline, promoter methylation of NR3C1-1F, IC50-Dex and pro-inflammatory cytokines. We noted significant mediation effects of NR3C1-1F promoter methylation on inflammatory cytokines through changes in GR sensitivity. Our findings suggest that increased GR sensitivity may contribute to increased inflammation, therefore, interventions to restore GR sensitivity may normalize inflammation in PTSD.

systems biology↗

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↗

bioRxiv2018

Altered Fecal Microbiota and Urine Metabolome as Signatures of Soman Poisoning

The experimental pathophysiology of organophosphorus (OP) chemical exposure has been extensively reported. Here, we describe an altered fecal microbiota and urine metabolome that follows intoxication with soman, a lipophilic G class chemical warfare nerve agent. Non-anaesthetized Sprague-Dawley male rats were subcutaneously administered soman at 0.8 - 1.0 of the median lethal dose (LD50) and evaluated for signs of toxicity. Animals were stratified based on seizing activity to evaluate effects of soman exposure on fecal bacterial biota and urine metabolites. Soman exposure reshaped fecal bacterial biota by preferentially expanding Facklamia, Agrobacterium, Bilophila, Enterobacter, and Morganella genera of the Firmicutes and Proteobacteria phyla, some of which are known to hydrolyze OPs. However, analogous changes were not observed in the bacterial biota of the ileum, which remained the same irrespective of dose or seizing status of animals after exposure. Interestingly, when considering just the seizing status of animals, we found that the urine metabolome was markedly altered. Leukotriene C4, kynurenic acid, 5-hydroxyindoleacetic acid, norepinephrine, and aldosterone were excreted at much higher rates at 72 hrs in seizing animals, consistent with early multi-organ involvement during soman poisoning. However, at 75 days post soman exposure, bacterial biota stabilized and no differences were observed. These findings demonstrate the feasibility of using the dysbiosis of fecal bacterial biota in combination with urine metabolome alterations as forensic evidence for OP exposure temporally.\n\nImportanceThe paucity of assays to determine physiologically relevant OP exposure presents an opportunity to explore the use bacterial sentinels in combination with urine to assess changes in the exposed host. Recent advances in technologies and computational approaches have enabled researches to survey large community level changes of gut bacterial biota and metabolomic changes in various biospecimens. Here, we profile combined changes in bacterial biota and urine metabolome due to chemical warfare OP exposure. The significance of our work is to reveal that monitoring bacterial biota and urine metabolites as surrogates of OP exposure in biospecimens suitable for existing clinical laboratory workflows is plausible without the need for the development of new technology, invasive procedures, or complicated analytical approaches. The larger value of such an approach is that any setting with a moderate clinical chemistry and microbiology capability can determine pre-symptomatic exposure to enhance current triage standards in case of mass exposures, refugee movements, humanitarian missions, and training settings once an algorithm has been validated. In the event of \"potential\" exposures by time or distance, this assay can be further developed to estimate affected radius or time dimension for health monitoring and treatment interventions.

physiology↗