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Biology subjects

Yehuda, R.

Publications and source records attributed to Yehuda, R..

6 recordsLinked to original sources

Identity Domains Reveal How Life Experiences and the Microbiome Shape Individuality and Uncover the Presence of Social Memory in Drosophila

Personality is comprised of enduring traits that shape behavior across contexts and over time. Yet outside humans, research often equates individuality with personality, focusing on how one animal differs from another in each behavior. This overlooks the latent space that spans an animals behavioral repertoire, how it is shaped by innate tendencies and prior experiences, and how it differs from transient factors. Here, we bridge this gap by integrating a data-driven framework with unbiased trait interpretation via large language models, revealing how social, sexual, and physiological conditions systematically alter the expression of personality-like traits in Drosophila melanogaster. This approach yielded four identities: space-use (exploration), time-use (social investment), avoidance, and aggression. Large language models produced strong consensus on the interpretation of some of these axes and divergence on others. These dimensions proved stable within individuals yet shifted predictably following mating, isolation, and microbiome manipulation, often in sex dependent ways. Notably, flies behaved differently toward familiar and unfamiliar peers, revealing a capacity for social memory. These findings bridge temperament and personality, showing how life history reshapes baseline tendencies into individualized profiles within constrained dimensions. They establish Drosophila as a tractable system for uncovering the biological logic of personality and advancing cross-species principles for individuality research. Significance StatementPersonality is often treated as a hallmark of complex brains, yet we show that fruit flies express stable behavioral identities with systematic, experience driven plasticity. Using a mathematical framework, we resolve four stable traits and map how sex, social experience, and the gut microbiome shift their expression. We further demonstrate social recognition in flies: they treat familiar cage mates differently from newcomers over repeated encounters, evidencing social memory, a striking result given their simple nervous system. Finally, we introduce large language models to provide objective, reproducible interpretations of trait dimensions, reducing human bias. These advances establish a general, quantitative approach to personality and social behavior in a tractable genetic model.

neuroscience↗

Common genetic variation impacts molecular stress response in the brain

To explain why individuals exposed to identical stressors experience divergent clinical outcomes, we determine how molecular encoding of stress modifies genetic risk for brain disorders. Analysis of post-mortem brain (n=304) revealed 8557 stress-interactive expression quantitative trait loci (eQTLs) that dysregulate expression of 915 eGenes in response to stress, and lie in stress-related transcription factor binding sites. Response to stress is robust across experimental paradigms: up to 50% of stress-interactive eGenes validate in glucocorticoid treated hiPSC-derived neurons (n=39 donors). Stress-interactive eGenes show brain region- and cell type-specificity, and, in post-mortem brain, implicate glial and endothelial mechanisms. Stress dysregulates long-term expression of disorder risk genes in a genotype-dependent manner; stress-interactive transcriptomic imputation uncovered 139 novel genes conferring brain disorder risk only in the context of traumatic stress. Molecular stress-encoding explains individualized responses to traumatic stress; incorporating trauma into genomic studies of brain disorders is likely to improve diagnosis, prognosis, and drug discovery. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/573459v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1e07fa9org.highwire.dtl.DTLVardef@1dd530forg.highwire.dtl.DTLVardef@17822a5org.highwire.dtl.DTLVardef@2a889f_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

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↗

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↗

Analysis of Genetically Regulated Gene Expression identifies a trauma type specific PTSD gene, SNRNP35

PTSD has significant genetic heritability; however, it is unclear how genetic risk influences tissue-specific gene expression. We used brain and non-brain transcriptomic imputation models to impute genetically regulated gene expression (GReX) in 9,087 PTSD-cases and 23,811 controls and identified thirteen significant GReX-PTSD associations. The results suggest substantial genetic heterogeneity between civilian and military PTSD cohorts. The top study-wide significant PTSD-association was with predicted downregulation of the Small Nuclear Ribonucleoprotein U11/U12 Subunit 35 (SNRNP35) in the BA9 region of the prefrontal cortex (PFC) in military cohorts. In peripheral leukocytes from 175 U.S. Marines, the observed PTSD differential gene expression correlated with the predicted blood GReX differences for these individuals, and deployment stress downregulated SNRNP35 expression, primarily in Marines with post-deployment PTSD. SNRNP35 is a subunit of the minor spliceosome complex and SNRNP35 knockdown in cells validated its functional importance in U12-intron splicing. Finally, mimicking acute activation of the endogenous stress axis in mice downregulated PFC Snrnp35 expression.

genetics↗

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↗