Biology subjects

Perkins, D.

Publications and source records attributed to Perkins, D..

7 recordsLinked to original sources

bioRxiv2026

STING agonists in combination with epigenetic drugs potentiate ZNFX1-driven inflammatory necroptosis in TP53-mutated AML

TP53-mutated acute myeloid leukemia (AML) has dismal outcomes with current treatments and represents a critical unmet need. TP53-mutated AML is proposed to be susceptible to immunotherapeutic approaches but, to date, there is no established immunotherapy for this sub-group. Expression of stimulator of interferon genes (STING), a key innate immune driver that activates interferon (IFN) signaling, is decreased by epigenetic silencing or mutation in many cancers, including those with TP53 mutations. Here, we report that response to the next-generation synthetic STING agonist C92 is potentiated in AML cell lines and primary cells with TP53-mutated versus wild-type (WT) cells, representing a previously undescribed vulnerability of these leukemia cells to STING small molecule therapies. Moreover, combining treatment with the DNA methyltransferase inhibitor (DNMTi) decitabine (DAC), significantly increases STING activation, with marked transcriptome-wide increase in repetitive elements (REs) and upregulation of a critical set of interferon-related genes. Cell death in TP53 KO versus WT AML is specifically dependent on innate immune zinc finger NFX1-type containing 1 (ZNFX1) and Z-DNA-binding protein 1 (ZBP1) driving increased cleavage and activation of Receptor-Interacting-Serine/Threonine-Protein Kinase 3 (RIPK3) and mixed lineage kinase domain-like protein (MLKL), suggesting mechanisms of necroptosis. Finally, C92 and DAC combination significantly reduces leukemia burden in humanized AML mouse models, accompanied by increased immune responses, including cytokines and cytotoxic T lymphocytes in the leukemia microenvironment. These results support development of clinical trial strategies combining STING agonists with DNMTis for patients with TP53-mutated AML. SummaryO_LITP53-mutated AML potentiates effects of novel next-generation STING agonist C92, with unique allosteric and non-cyclic dinucleotide (non-CD) mechanism of action, inducing increased STING activation and cytokine release C_LIO_LISTING agonists and DNMTis, synergistically increase STING activation with marked transcriptome-wide increase in repetitive elements (REs) and upregulation of a critical set of interferon-related genes in TP53-mutated AML C_LIO_LISTING agonists induce necroptosis via a STING-ZNFX1-ZBP1-necroptosis axis in TP53-mutated AML. C_LIO_LIThis drug combination reduces leukemia burden, activates immune responses in AML models and supports translation for high-risk AML patients. C_LI Statement of Translational RelevanceThis pre-clinical study identifies a novel therapeutic vulnerability in (TP53)-mutated acute myeloid leukemia (AML), a poor prognosis subtype with a critical unmet need. Novel next-generation STING agonist C92, with unique allosteric and non-cyclic dinucleotide (non-CD) mechanism of action, induces increased STING activation and cytokine release, compared with WT TP53 in AML cell lines and primary cells, and has superior STING activity with respect to several STING agonists currently in clinical studies. Combining C92 treatment with the DNA methyltransferase inhibitor (DNMTi) decitabine (DAC) synergistically increases STING activation, with marked transcriptome-wide increase in repetitive elements (REs) and upregulation of a critical set of interferon-related genes, driving ZNFX1-driven inflammatory necroptotic cell death. Utilizing humanized mouse models, C92 in combination with DAC significantly reduces leukemia burden and enhances cytotoxic T-cell responses in the tumor microenvironment, supporting clinical translation for high-risk AML patients.

cancer biology↗

bioRxiv2023

Disentangling the multiple drivers of ecological adaptation in a microorganism

To survive and reproduce, living organisms need to maintain an efficient balance between energy intake and energy expenditure. Changes in environmental conditions can disrupt previously efficient energy allocation strategies, and organisms are required to change their behaviour, physiology, or morphology to cope with the new environment. However, how multiple phenotypic traits interact with one another and with environmental conditions to shape energy allocation remains poorly understood. To better understand this type of phenotype-environment interactions, we develop a predictive framework, grounded in energetic and biophysical principles that allows us to make predictions on how metabolic rate and movement speed should change in response to environmental temperature and resource supply, differentiating between short-term, acute exposure to novel conditions and longer-term exposure that allows acclimation or adaptation. We tested these predictions by exposing axenic populations of the ciliate Tetrahymena pyriformis to different combinations of temperature and resource availability. We measured population growth, cell size, respiration, and movement. Acute increases in temperature led to higher movement speeds and respiration rates, consistent with expectations from physical scaling relationships such as the Boltzmann-Arrhenius equation and the viscous drag acting on movement. However, by around 3.5 days after the introduction of Tetrahymena into a novel environment, all measured traits shifted toward values closer to those of the original environment. These changes likely reflect phenotypic acclimation responses that restored a more efficient energy allocation under the new conditions. Changes in cell size played a key role in this process, by simultaneously affecting multiple phenotypic traits, including metabolic rate and the energetic costs of movement. In small microbial consumers like Tetrahymena, body size can change rapidly, relative to ecological and seasonal timescales. Changes in body size can therefore be effectively leveraged - alongside physiological and biochemical regulations - to cope with environmental changes. Open researchThe raw data and all the analysis code used for this work are publicly available on github (https://github.com/pernafrost/Tetrahymena), and they are also deposited in Dryad (https://doi.org/10.5061/dryad.2v6wwpzvv). By downloading and running the code, it is possible to reproduce all the figures presented in the manuscript and in the Appendix. Please refer to the linked repositories for additional information, and feel free to contact the authors in case you need additional guidance.

ecology↗

bioRxiv2022

Linking Choroid Plexus Enlargement with Plasma Analyte and Structural Phenotypes in Clinical High Risk for Psychosis: A Multisite Neuroimaging Study

BackgroundChoroid plexus (ChP) enlargement exists in first-episode and chronic psychosis, but whether enlargement occurs before psychosis onset is unknown. This study investigated whether ChP volume is enlarged in individuals with clinical high-risk (CHR) for psychosis and whether these changes are related to clinical, neuroanatomical, and plasma analytes. MethodsClinical and neuroimaging data from the North American Prodrome Longitudinal Study 2 (NAPLS2) was used for analysis. 509 participants (169 controls, 340 CHR) were recruited. Conversion status was determined after 2-years of follow-up, with 36 psychosis converters. The lateral ventricle ChP was manually segmented from baseline scans. A subsample of 31 controls and 53 CHR had plasma analyte and neuroimaging data. ResultsCompared to controls, CHR (d=0.23, p=0.017) and non-converters (d=0.22, p=0.03) demonstrated higher ChP volumes, but not in converters. In CHR, greater ChP volume correlated with lower cortical (r=-0.22, p<0.001), subcortical gray matter (r=-0.21, p<0.001), and total white matter volume (r=-0.28,p<0.001), as well as larger lateral ventricle volume (r=0.63,p<0.001). Greater ChP volume correlated with makers functionally associated with the lateral ventricle ChP in CHR [CCL1 (r=-0.30, p=0.035), ICAM1 (r=0.33, p=0.02)], converters [IL1{beta} (r=0.66, p=0.004)], and non-converters [BMP6 (r=-0.96, p<0.001), CALB1 (r=-0.98, p<0.001), ICAM1 (r=0.80, p=0.003), SELE (r=0.59, p=0.026), SHBG (r=0.99, p<0.001), TNFRSF10C (r=0.78, p=0.001)]. ConclusionsCHR and non-converters demonstrated significantly larger ChP volumes compared to controls. Enlarged ChP was associated with neuroanatomical alterations and analyte markers functionally associated with the ChP. These findings suggest that the ChP may be a key explanatory biomarker in CHR for psychosis.

neuroscience↗

bioRxiv2021

Restored TDCA and Valine Levels Imitate the Effects of Bariatric Surgery

Obesity is widespread and linked to various co-morbidities. Bariatric surgery has been identified as the only effective treatment, promoting sustained weight loss and the remission of co-morbidities. We performed sleeve-gastrectomies (SGx) in a pre-clinical mouse model of diet-induced obesity (DIO), delineating the effects on long-term remission from obesity. SGx resulted in sustained weight loss and improved glucose tolerance. Mass-spectrometric metabolomic profiling revealed significantly reduced systemic levels of taurodeoxycholic acid (TDCA) and L-valine in DIO mice. Notably, TDCA and L-Valine levels were restored after SGx in both human and mice to levels comparable with lean controls. Strikingly, combined systemic treatment with TDCA and valine induced a profound weight loss in DIO mice analogous to effects observed after SGx. Utilizing indirect calorimetry, we confirmed reduced food intake as causal for TDCA/valine-mediated weight loss via a central inhibition of the melanin-concentrating hormone. In summary, we identified restored TDCA/valine levels as an underlying mechanism of SGx-derived effects on weight loss. Of translational relevance, TDCA and L-valine are presented as novel agents promoting weight loss while reversing obesity-associated metabolic disorders.

cell biology↗

bioRxiv2019

Genetic and clinical analyses of psychosis spectrum symptoms in a large multi-ethnic youth cohort reveal significant link with ADHD.

ObjectivePsychotic symptoms are an important feature of severe neuropsychiatric disorders, but are also common in the general population, especially in youth. The genetic etiology of psychosis symptoms in youth remains poorly understood. To characterize genetic risk for psychosis spectrum symptoms (PS), we leverage a community-based multi-ethnic sample of children and adolescents aged 8-22 years, the Philadelphia Neurodevelopmental Cohort (n = 7,225, 20% PS).\n\nMethodsUsing an elastic net regression model, we aim to classify PS status using polygenic scores (PGS) based on a range of heritable psychiatric and brain-related traits in a multi-PGS model. We also perform univariate PGS associations and evaluate age-specific effects.\n\nResultsThe multi-PGS analyses do not improve prediction of PS status over univariate models, but reveal that the attention deficit hyperactivity disorder (ADHD) PGS is robustly and uniquely associated with PS (OR 1.12 (1.05, 1.18) P = 0.0003). This association is: i) driven by subjects of European ancestry (OR=1.23 (1.14, 1.34), P=4.15x10-7) but is not observed in African American subjects (P=0.65) and ii) independent of phenotypic overlap. We also find a significant interaction with age (P=0.01), with a stronger association in younger children. In an independent sample, we replicate an increased ADHD PGS in 328 youth at clinical high risk for psychosis, compared to 216 unaffected controls (OR 1.06, CI(1.01, 1.11), P= 0.02).\n\nConclusionsOur findings suggest that PS in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, one more akin to ADHD, and shed light on how genetic risk can be investigated across early disease trajectories.

genetics↗

bioRxiv2017

Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium

Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared underlying neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, are implicated in the progression to full psychosis.

neuroscience↗

bioRxiv2017

Toward leveraging big data in human functional connectomics: Generalization of brain graphs across scanners, sessions, and paradigms

While graph theoretical modeling has dramatically advanced our understanding of complex brain systems, the feasibility of aggregating brain graphic data in large imaging consortia remains unclear. Here, using a battery of cognitive, emotional and resting fMRI paradigms, we investigated the reproducibility of functional connectomic measures across multiple sites and sessions. Our results revealed overall fair to excellent reliability for a majority of measures during both rest and tasks, in particular for those quantifying connectivity strength, network segregation and network integration. Higher reliabilities were detected for cognitive tasks (vs rest) and for weighted networks (vs binary networks). While network diagnostics for several primary functional systems were consistently reliable independently of paradigm, those for cognitive-emotional systems were reliable predominantly when challenged by task. Different data aggregation approaches yielded significantly different reliability. In addition, we showed that after accounting for observed reliability, satisfactory statistical power can be achieved in the multisite context with a total sample size of approximately 250 when the effect size is at least moderate. Our findings provide direct evidence for the generalizability of brain graphs for both resting and task paradigms in large consortia and encourage the use of multisite, multisession scans to enhance power for human functional connectomic studies.

neuroscience↗