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Haddad, L.

Publications and source records attributed to Haddad, L..

4 recordsLinked to original sources

Liver microbiome composition associates with histological severity and PNPLA3 genotype in metabolic dysfunction-associated steatotic liver disease

BACKGROUNDMetabolic dysfunction-associated steatotic liver disease (MASLD) is a systemic immunometabolic disorder rapidly increasing worldwide, affecting nearly 38% of adults. Gut dysbiosis and host genetic factors, such as PNPLA3 I148M variant, modulate disease development and progression. Through the gut-liver axis, increased intestinal permeability enables microbial translocation to the liver, promoting inflammation and metabolic disruption. However, the composition and functional potential of the hepatic microbiome remain poorly characterized. Understanding its relationship with histological injury and genetic susceptibility may provide novel mechanistic insights. We hypothesized that the hepatic microbiome composition and function are associated with histological severity and PNPLA3 genotype in this disease. AIMTo characterize the hepatic microbiome and assess its association with histological severity and PNPLA3 genotype. METHODSThis cross-sectional observational study included 30 patients with MASLD from a tertiary care hospital. Liver tissue underwent shotgun metagenomic sequencing. Histological severity was assessed using the NAFLD Activity Score (NAS). PNPLA3 genotype was determined by PCR. Differential abundance and functional enrichment analyses were performed using MaAsLin2. Somatic variants were identified using Mutect2. Correlation networks were constructed using Spearmans correlation coefficients. RESULTSPatients with advanced histological injury (NAS [≥]5) and PNPLA3 I148M carriers showed a trend toward higher somatic mutational load and a markedly reduced microbial abundance. Analyses revealed broad compositional shifts across bacterial, fungal, viral, and eukaryotic taxa, affecting both commensal and context-dependent pathobiont lineages. Pseudomonas species were enriched, whereas Siphoviridae phages were depleted in advanced disease and PNPLA3 I148M carriers. Functional analysis revealed enrichment of pathways related to nutrient transport and metabolic stress adaptation, while TonB-associated functions were enriched in advanced liver injury but depleted in PNPLA3 I148M carriers. Network analysis identified Sphingomonas leidyi as a keystone node associated with hexosamine metabolism. Salmonella enterica abundance positively correlated with somatic variant burden, suggesting a link between microbial signatures and genomic instability. Histological progression and the risk PNPLA3 genotype were accompanied by marked topological simplification, reflecting less resilient community structures. CONCLUSIONSThe hepatic microbiome in MASLD is a low-biomass, polymicrobial ecosystem shaped by the host genetic background. Its functional activity, taxonomic composition and system architecture bidirectionally relate to liver DNA instability and the severity of histological damage. Core tipThis study characterizes the multi-kingdom hepatic microbiome in MASLD using FFPE-derived metagenomics. We demonstrate that microbial abundance-including bacteria, fungi, protozoa, and viruses- significantly decreases with increased histological severity and the PNPLA3 risk genotype. Rather than global diversity shifts, results showed that disease progression could be linked to specific functional adaptations and simplified microbial network connectivity. In addition, we described associations between specific taxa and somatic mutational burden, suggesting a link between microbial signals and genomic instability. These findings indicate that changes in the liver microbiome as a whole, rather than specific taxonomic modifications, influence MASLD pathophysiology.

molecular biology↗

Emergence of a novel hypervirulent extensively drug-resistant ST383 Klebsiella pneumoniae lineage carrying ICEKp5 in Lebanon

Klebsiella pneumoniae ST383 has emerged as a high-risk clone, characterized by carbapenem resistance and increasing detection of hypervirulence determinants. We describe a novel ST383 lineage in Lebanon, defined by the acquisition of ICEKp5, which carries the yersiniabactin locus. Three ST383 K. pneumoniae clinical isolates (LBN_CAKp91, LBN_CTKp3, LBN_CTKp11) recovered from a Lebanese medical center were subjected to whole-genome sequencing. Comparative genomic analysis included regional ST383 strains and previously characterized Lebanese isolates. The study isolates formed a tight, monophyletic cluster (3-9 SNPs) that is phylogenetically distinct from the previously reported Lebanese ST383 clone (>164 SNPs) and grouped most closely to an Egyptian ST383 strain (59-65 SNPs). All three isolates carried ICEKp5 with yersiniabactin lineage ybt14, a feature absent in the earlier Lebanese ST383 clone. The isolates were the only ST383 strains to harbor the full spectrum of hypervirulence determinants to date, including capsule regulators (rmpA, rmpA2), aerobactin (iucABCD, iutA), yersiniabactin, and the hypervirulence biomarker peg-344. All isolates carried dual carbapenemases (blaOXA-48 and blaNDM-5) in addition to blaCTX-M-15 and blaCTX-M-14b. The genetic environments of blaOXA-48 and blaNDM-5 were highly conserved across geographically diverse ST383 isolates, indicating common plasmid origins. This study documents the emergence of a novel hypervirulent extensively drug-resistant (XDR) ST383 K. pneumoniae lineage in Lebanon. The acquisition of ICEKp5, combined with plasmid-borne hypervirulence and resistance determinants, reveals the concerning convergence of hypervirulence and XDR. Enhanced surveillance and infection control measures are urgently needed to monitor this emerging high-risk clone.

genomics↗

Learning evoked centrality dynamics in the schizophrenia brain: Entropy, heterogeneity and inflexibility of brain networks

BackgroundBrain network dynamics are responsive to task induced fluctuations, but such responsivity may not hold in schizophrenia (SCZ). We introduce and implement Centrality Dynamics (CD), a method developed specifically to capture task-driven dynamic changes in graph theoretic measures of centrality. We applied CD to fMRI data in SCZ and Healthy Controls (HC) acquired during a learning paradigm. MethodsfMRI (3T Siemens Verio) was acquired in 88 participants (49 SCZ). Time series were extracted from 246 functionally defined cerebral nodes. We applied a dynamic widowing technique to estimate 280 partially overlapping connectomes (30,135 region-pairs in each connectome). In each connectome we calculated every nodes Betweenness Centrality (BC) before building 246 unique time series (representing a nodes CD) from a nodes BC in successive connectomes. Next, in each group nodes were clustered based on similarities in CD. ResultsClustering gave rise to fewer sub-networks in SCZ, and these were formed by nodes with greater functional heterogeneity. These sub-networks also showed greater ApEn (indicating greater stochasticity) but lower amplitude variability (suggesting less adaptability to task-induced dynamics). Higher ApEn was associated with worse clinical symptoms. LimitationsCentrality Dynamics is a new method for network discovery in health and schizophrenia but will need further extension to other tasks and psychiatric conditions, before we achieve a fuller understanding of its promise. ConclusionThe brains functional connectome is not static under task-driven conditions, and characterizing the dynamics of the connectome will provide new insight on the dysconnection syndrome that is schizophrenia. Centrality Dynamics provides novel characterization of task-induced changes in the brains connectome and shows that in the schizophrenia brain, learning-evoked sub-network dynamics were less responsive to learning evoked changes and showed greater stochasticity.

neuroscience↗

Locally secreted BiTEs complement CAR T cells by enhancing solid tumor killing

Bispecific T-cell engagers (BiTEs) are bispecific antibodies that redirect T cells to target antigen-expressing tumors. BiTEs can be secreted by T cells through genetic engineering and perform anti-tumor activity. We hypothesized that BiTE-secreting T cells could be a valuable T cell-directed therapy in solid tumors, with distinct properties in mono- or multi-valent strategies incorporating chimeric antigen receptor (CAR) T cells. Glioblastomas represent a good model for solid tumor heterogeneity and represent a significant therapeutic challenge. We detected expression of tumor-associated epidermal growth factor receptor (EGFR), EGFR variant III (EGFRvIII), and interleukin-13 receptor alpha 2 (IL13R2) on glioma tissues and glioma cancer stem cells. These antigens formed the basis of a multivalent approach, using a conformation-specific tumor-related EGFR targeting antibody (806) and Hu08, an IL13R2-targeting antibody, as the scFvs to generate new BiTE molecules. Compared with 806CAR T cells and Hu08CAR T cells, BiTE T cells demonstrated prominent activation, cytokine production, and cytotoxicity in response to target-positive gliomas. Superior response activity was also demonstrated in BiTE secreting bivalent targeting T cells compared with bivalent targeting CAR T cells, which significantly delayed tumor growth in a glioma mouse model. In summary, BiTEs secreted by mono- or multi- valent targeting T cells have potent anti-tumor activity in vitro and in vivo with significant sensitivity and specificity, demonstrating a promising strategy in solid tumor therapy.

cancer biology↗