Biology subjects

Khader, S.

Publications and source records attributed to Khader, S..

8 recordsLinked to original sources

bioRxiv2026

CD40 ligand and IFN-γ induce proinflammatory activity and microglia-mediated neurodegeneration in human stem cell models

The cluster of differentiation 40 (CD40)/CD40 ligand (CD40L) co-stimulatory pathway plays a critical role in the activation and regulation of immune networks involving both adaptive and innate immune cells. Dysregulation of this pathway has been implicated in multiple autoimmune diseases, including multiple sclerosis (MS). MS is characterized by progressive neurodegeneration driven by compartmentalized neuroinflammation within the central nervous system (CNS), sustained low-grade T cell infiltration at the blood-brain barrier, and T cell reactivation at CNS border tissues. CD40L-expressing T cells can activate CD40-expressing microglia, which are a critical effector cell that contribute to neurodegeneration in MS. However, the consequence of this functional interaction in the brain remains poorly understood. Here, we demonstrate that the combination of CD40L and interferon-gamma (IFN-{gamma}), a cytokine produced by activated T cells, induces a robust inflammatory response and cell death in human induced pluripotent stem cells (hiPSC)-derived microglia. Stimulation with CD40L elicited microglial clustering, morphological transformation, and robust release of proinflammatory cytokines including interleukin-12 (IL-12), tumor necrosis factor-alpha (TNF-), and IL-6. Anti-CD40L antibody treatment reversed both cell death and inflammatory response and partially normalized the associated transcriptional changes. Furthermore, using an hiPSC-derived tri-culture system comprising neurons, astrocytes, and microglia, we demonstrated that CD40L and IFN-{gamma} trigger microglia-dependent neuronal dysregulation and death. Anti-CD40L treatment substantially attenuated neuronal injury. Finally, transcriptomic enrichment analysis identified CD40L-mediated microglial gene expression signatures that correlated with CD40 expression in primary progressive MS brain tissue but not in the normal-appearing white matter of healthy controls. Collectively, these findings support a role for the microglial CD40/T cell CD40L axis in MS pathology and suggest CD40L blockade as a potential therapeutic strategy warranting further investigation.

neuroscience↗

bioRxiv2026

RNA Editing of DEGS1 Links Genetic Risk to Ceramide Dysregulation and Astrocyte Toxicity in ALS

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with ~90% of cases being sporadic. Although genome-wide association studies have identified numerous genetic risk loci, these variants account for only a portion of ALS heritability, suggesting that additional genetic and regulatory mechanisms contribute to disease risk. Furthermore, the mechanisms linking common variants to disease pathogenesis remain poorly understood. Adenosine-to-inosine (A-to-I) RNA editing is dysregulated in ALS, yet systematic identification of disease-relevant editing events and their functional consequences has been limited. We performed comprehensive RNA editing analysis across eight central nervous system regions from a Target ALS cohort, identifying 752 differentially edited sites in 304 genes. Global RNA editing was significantly reduced in ALS tissues, particularly in spinal cord and choroid plexus, with altered editing in genes involved in immune signaling, stress response and RNA processing. Through genetic colocalization analysis integrating editing quantitative trait loci (edQTLs) with ALS GWAS data, we identified common variants at the DEGS1 locus associated with both increased 3' UTR editing and elevated ALS risk (posterior probability >0.88). DEGS1 encodes dihydroceramide desaturase 1, a key enzyme converting dihydroceramide to ceramide, the precursor to all sphingolipid species. Using CRISPR-generated DEGS1 knockout iPSCs and lipidomic profiling, we demonstrated that DEGS1 is essential for ceramide synthesis and downstream sphingolipid production in astrocytes. Functional validation revealed that ALS-associated editing of the DEGS1 3' UTR significantly increased DEGS1 protein expression. Critically, astrocytes expressing the fully edited DEGS1 3' UTR increased ceramide levels and reduced cell viability compared to those expressing the unedited construct. These findings establish a novel regulatory link between RNA editing, sphingolipid metabolism and ALS pathogenesis. Our results demonstrate that common genetic variants can influence disease risk through post-transcriptional mechanisms that alter lipid homeostasis in astrocytes, a cell type increasingly recognized as central to ALS progression.

neuroscience↗

bioRxiv2026

The Human Pleiotropic Map of GWAS Associations and Therapeutic Implications

Genetic support for drug targets substantially increases clinical success rates, establishing genome-wide association studies (GWAS) as central to therapeutic hypothesis generation. However, the same genetic evidence that reveals causal gene-disease relationships simultaneously exposes organism-level safety liabilities--a dimension requiring principled, genome-wide quantification. Here we systematically analyse 100,526 GWAS to yield 789,453 credible sets and gene prioritisations for 15,641 genes, with discovery showing no saturation as GWAS expand and increase diversity. We find that 64% of GWAS-implicated genes are pleiotropic, associated with traits across multiple diseases and showing a non-linear relationship between the degree of pleiotropy and clinical success. Highly pleiotropic genes--concentrated in immune, inflammatory, and oncogenic signalling programmes--are enriched in safety-terminated clinical programmes, mouse lethal knockouts, and cancer driver genes, establishing gene-level pleiotropy as a potential measure of genetically-informed organism-level safety liability. Protein-altering variant (PAV) support amplifies therapeutic signal (OR = 6.0), yet PAV targets show higher average pleiotropy, introducing a competing safety liability. Combining PAV support with intermediate pleiotropy (2-5 therapeutic areas) resolves this tension, yielding OR = 10.3 and relative success = 4.8--a profile already satisfied by 52 approved therapies. As GWAS continue to expand in scale and resolution, these findings lay the groundwork for increasingly sophisticated target discovery strategies that yield safer and more effective therapeutic hypotheses.

genomics↗

bioRxiv2024

PPARγ downregulation in colonic CD8+ T cells results in epithelial barrier disruption in people with HIV on antiretroviral therapy

A hallmark of HIV infection is disruption of intestinal barrier integrity that persists in people with HIV (PWH) despite treatment with antiretroviral therapy (ART). This disruption is central to HIV disease progression, yet the causes remain incompletely understood. We report a novel mechanism by which immunometabolic defects in colon resident CD8+ T cells in PWH lead to intestinal epithelial apoptosis and disruption of intestinal barrier integrity. We show that in PWH, these cells downregulate the lipid sensor peroxisome proliferator-activated receptor-{gamma} (PPAR{gamma}), which results in reduced intracellular lipid droplets, impaired fatty acid oxidation, and acquisition of lipids by CD8+ T cells from intestinal epithelial cells, which then contributes to epithelial cell death. Our findings indicate that HIV-associated immunometabolic dysregulation of colon CD8+ T cell leads to loss of intestinal epithelial homeostasis. These results identify potential new strategies to reduce comorbidities in PWH and other disorders with disrupted intestinal barrier integrity.

immunology↗

bioRxiv2024

Mast cells promote pathology and susceptibility in tuberculosis

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), infects approximately one-fourth of the worlds population. We reported an increased accumulation of mast cells (MCs) in the lungs of macaques with active pulmonary TB (PTB), compared with those with latent TB infection (LTBI). MCs respond in vitro to Mtb exposure via degranulation and by inducing proinflammatory cytokines. In the current study, we demonstrate an increased production of chymase by MCs in granulomas of humans and macaques with PTB. Single-cell (sc) RNA sequencing analysis revealed distinct MC transcriptional programs between LTBI and PTB, with PTB associated MCs enriched in interferon gamma, oxidative phosphorylation, and MYC signaling. In a mouse model, MC deficiency led to improved control of Mtb infection that coincided with reduced accumulation of lung myeloid cells and diminished lung inflammation at chronic stages of infection. Airway transfer of MCs into wild-type Mtb infected mice showed increased neutrophils, decreased recruited macrophages, and elevated Mtb dissemination to the spleen. Together, these findings highlight MCs as active drivers of TB pathogenesis and potential targets for host-directed therapies for TB.

immunology↗

bioRxiv2021

Pleiotropic Variability Score: A Genome Interpretation Metric to Quantify Phenomic Associations of Genomic Variants

A more complete understanding of phenomic space is critical for elucidating genome-phenome relationships and for assessing disease risk from genome sequencing. To incorporate knowledge of how related a variants associations are, we developed a new genome interpretation metric called Pleiotropic Variability Score (PVS). PVS uses semantic reasoning to score the relatedness of a genetic variants associated phenotypes based on those phenotypes relationships in the human phenotype ontology (HPO) and disease ontology (DO). We tested 78 unique semantic similarity methods and integrated six robust metrics to define the pleiotropy score of SNPs. We computed PVS for 12,541 SNPs which were mapped to 382 HPO and 317 DO unique phenotype terms in a genotype-phenotype catalog (10,021 SNPs mapped to DO phenotypes and 8,569 SNPs mapped to HPO phenotypes). We validated the utility of PVS by computing pleiotropy using an electronic health record linked genomic database (BioME, n=11,210). Further we demonstrate the application of PVS in personalized medicine using "personalized pleiotropy score" reports for individuals with genomic data that could potentially aid in variant interpretation. We further developed a software framework to incorporate PVS into VCF files and to consolidate pleiotropy assessment as part of genome interpretation pipelines. As the genome-phenome catalogs are growing, PVS will be a useful metric to assess genetic variation to find SNPs with highly pleiotropic effects. Additionally, variants with varying degree of pleiotropy can be prioritized for explorative studies to understand specific roles of SNPs and pleiotropic hubs in mediating novel phenotypes and drug development.

bioinformatics↗

bioRxiv2019

fragilityindex: An R Package for Statistical Fragility Estimates in Biomedicine

Poor reproducibility is a growing crisis in biomedical research. The fragility index was introduced as a convenient measure to estimate how fragile statistical results in clinical trials are to small perturbations in event outcome counts. There is currently no freely available R package to produce this calculation. Furthermore, the original definition of the method is applicable only to 2x2 contingency tables. As such, we developed an R package to calculate fragility index. We have also extended the concept of a statistical fragility index to two of the most commonly used methods in clinical research, survival analysis via weighted log-rank tests and logistic regression, and implemented these technique sin this R package. We describe example applications of these methods to existing publically available datasets. This R package is freely available under the AGPL license on CRAN (https://cran.r-project.org/web/packages/fragilityindex/index.html). The most recent versions may be downloaded and installed via Github (https://github.com/kippjohnson/fragilityindex).

bioinformatics↗

bioRxiv2018

Predictive modeling of susceptibility to substance abuse, mortality and drug-drug interactions in opioid patients

Opioid addiction causes high degree of morbidity and mortality. Preemptive identification of patients at risk of opioid dependence and developing intelligent clinical decisions to deprescribe opioids to the vulnerable patient population may help in reducing the burden. Identifying patients susceptible to mortality due to opioid-induced side effects and understanding the landscape of drug-drug interaction pairs aggravating opioid usage are significant, yet, unexplored research questions. In this study, we present a collection of predictive models to identify patients at risk of opioid abuse, mortality and drug-drug interactions in the context of opioid usage. Using publicly available dataset from MIMIC-III, we developed predictive models (opioid abuse models a=Logistic Regression; b=Extreme Gradient Boosting and mortality model= Extreme Gradient Boosting) and identified potential drug-drug interaction patterns. To enable the translational value of our work, the predictive model and all associated software code is provided. This repository could be used to build clinical decision aids and thus improve the optimization of prescription rates for vulnerable population.

epidemiology↗