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Laird, A.

Publications and source records attributed to Laird, A..

13 recordsLinked to original sources

Human white matter tracts aligned with canonical functional brain networks

White matter tracts form the structural backbone of large-scale brain networks, yet their relation to functional organization remains poorly defined. Although major pathways are well characterized anatomically, their relationship to distributed cognitive systems has not been systematically established. Here, we constructed a population-level white matter tract termination atlas and projected tract endpoints onto the cortical surface to characterize their spatial organization. We integrated this atlas with large-scale meta-analytic decoding to derive functional profiles for individual tracts. Functional decoding revealed that white matter tracts exhibited distinct and biologically interpretable cognitive signatures. Hierarchical clustering of these profiles further showed that tracts organize into coherent ensembles defined by shared functional associations. These tract ensembles recapitulated canonical intrinsic brain networks across multiple cortical atlases, including a notable ensemble that demonstrated alignment with the default mode, salience, and frontoparietal control networks, corresponding to the core architecture of the triple-network model of cognitive control. This finding identified a candidate structural backbone linking distributed functional systems implicated across neuropsychiatric conditions. Together, these results demonstrate that white matter architecture is organized according to large-scale functional principles and establish a tract-to-network framework for linking structural connectivity to cognition.

neuroscience↗

Development and characterisation of an optimised in vitro differentiation protocol for deriving hepatocyte-like cells from mouse embryonic stem cells

IntroductionReliable generation of hepatocyte-like cells (HLCs) from pluripotent stem cells remains limited by heterogeneity and incomplete maturation of the cells. Derivation of induced pluripotent- and embryonic stem cells into hepatocytes typically relies on complex, and costly reagent-intensive protocols, with inconsistent reporting of differentiation efficiencies and functional maturation criteria. Variability in protocol designs highlights the need for optimisation, particularly in mouse embryonic stem cells (mESCs) systems that can be more comparable with mouse models for underpinning translational and toxicological studies. Here, we developed and evaluated two cytokine-based strategies: an advanced hepatic-inducing cocktail (A-HIC) and a simplified hepatic-inducing cocktail (HIC), both designed to reduce complexity while increasing functional maturation. MethodsHepatic differentiation and maturation were assessed by morphology, immunofluorescence, flow cytometry, and qRT-PCR. Functional competence was evaluated via urea production, glutathione synthesis, indocyanine green handling, cytochrome P450 inducibility, and impedance-based cell layer integrity monitoring. ResultsMorphological, molecular and phenotypic analyses confirmed that both protocols supported hepatic lineage progression, generating heterogeneous populations of hepatoblast-like and more mature HLCs. Gene expression confirmed the loss of pluripotency, transient endoderm induction, and subsequent hepatic specification. Functionally, cells exhibited glycogen storage, inducible urea production, glutathione depletion, and active ICG uptake and clearance, with stable monolayer formation by day 21. A-HIC-derived HLCs demonstrated enhanced maturation, with higher ASGR1 expression and stronger Cyp1a1 induction. DiscussionThese findings suggest that both protocols generate functional HLCs; however, A-HIC yields a higher proportion of functionally mature cells with reduced variability. This approach enables a simple, cost-effective, and time-efficient generation of HLCs, supported by improved functional characterisation with potential applicability to more complex pluripotent systems, including human iPSC-based models for disease modelling and toxicology.

cell biology↗

Cannabis Use by People with HIV is Associated with an Anti-Inflammatory Immunometabolic Phenotype in Monocyte-Derived Macrophages

Chronic neuroinflammation is associated with comorbidities in people with HIV (PWH) on antiretroviral therapy (ART). While cannabis use is associated with reduced neuroinflammation and neurocognitive impairment (NCI) in PWH, the underlying mechanisms are unknown. To address this gap in knowledge, we analyzed monocyte-derived macrophages (MDMs) from a cohort of 50 PWH and 33 people without HIV (mean age: 61.9 years), categorized by frequency of cannabis use (naive/low, moderate, daily). We performed immunocytochemistry, RNA sequencing, and qPCR on MDMs and quantified related biomarkers in donor plasma. In this cohort study, daily cannabis use in PWH was associated with less global neurocognitive deficits, and with an anti-inflammatory immunometabolic-phenotype in MDMs characterized by (1) a metabolic shift from glycolysis to oxidative phosphorylation, (2) higher mitochondrial numbers, (3) altered cytokine profiles (pro-inflammatory downregulation, anti-inflammatory upregulation), and (4) higher brain-derived neurotrophic factor (BDNF) expression. These cellular changes were corroborated by a plasma biomarker profile in PWH including (1) lower levels of growth differentiation factor 15 and soluble triggering receptor expressed on myeloid cells 2, and (2) higher mature BDNF/precursor BDNF ratios that correlated with better cognition. Thus, cannabis use may mitigate NCI in PWH by immunometabolically reprogramming MDM function towards an anti-inflammatory and neuroprotective state. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/709579v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@15fb1adorg.highwire.dtl.DTLVardef@189d79corg.highwire.dtl.DTLVardef@aa6a89org.highwire.dtl.DTLVardef@3852f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Expanding the definition of MHC Class I peptide binding promiscuity to support vaccine discovery across cancers with CARMEN

Promiscuity in T-cell antigen landscapes refers to the dual flexibility of peptides binding multiple MHC alleles and MHC alleles presenting diverse arrays of peptides. By understanding how neoantigens are shared across varied HLA backgrounds, promiscuity analysis can inform the selection of cancer-vaccine targets that reach a wider segment of the population and help refine patient stratification for diverse immunotherapies. We expand the concept of promiscuity to encompass peptides, MHC alleles, individuals, populations, and genomic regions. Our CARMEN database release harmonizes data from 72 publications (2,323 samples) across tissue types, with a focus on cancer. Using Gibbs clustering and dimensionality reduction (UMAP), we systematically map promiscuity and immunological versatility across these biological levels. Gene and mutation analysis reveals recurrent cancer mutations in highly promiscuous genomic regions, highly mutated cancer genes that avoid presented regions, and sheds light on genomic regions important to response to immunotherapy.

bioinformatics↗

Meta all the way down: An overview of neuroimaging meta-analyses

Meta-analyses are invaluable tools for navigating the rapidly expanding scientific literature. Given their high value, ensuring the quality of meta-analyses is paramount. We conducted a multifaceted overview, examining each step in a manual neuroimaging meta-analysis on a large scale. We used four novel datasets comprising over 14,000 papers, including fMRI meta-analyses, fMRI studies, studies included in meta-analyses, and studies associated with image data on NeuroVault. Regarding successes, two-thirds of meta-analyses stated that they followed PRISMA guidelines, and 65% included a flowchart describing their inclusion process. We point out several areas for improvement. Pre-registration was fairly rare (20%), and only half listed their exact search strategy. There could be a location bias in which papers are included, and many did not include enough studies to be robust against publication bias (68% of meta analyses have less than 30 studies included). We also offer ideas for future directions. As image based meta-analysis is the gold standard, we have indicated which topics have the most image data available. The potential redundancy of topics can be visualized in our paper, and we recommend future meta-analyses be in conversation with past ones by citing and discussing previous similar work. By addressing these findings, the neuroimaging community can collectively improve the field of neuroimaging meta-analyses.

neuroscience↗

Plasma Cell-Free DNA in Acute and Chronic Aortic Syndromes.

Acute aortic syndromes and other acute aortic events are commonly misdiagnosed and associated with high mortality and morbidity. There is need for a blood-based biomarker to indicate the acutely unstable aorta. Plasma cell-free DNA (cfDNA) is an established diagnostic marker in prenatal testing and cancer. Its use as a potential diagnostic marker in aortic disease remains to be demonstrated. We found that plasma short-fragment (50-700bp) cfDNA concentration is significantly increased in patients with both acute and chronic aortic disease compared with several control groups, and is significantly increased in acute versus chronic aortic disease. Plasma sf-cfDNA may differentiate acute aortic syndromes from other acute presentations of chest pain with good diagnostic accuracy and could prove a significant advance in the management of aortic disease.

genomics↗

DNA methylation is a key determinant of response to targeted and immune checkpoint therapies in metastatic renal cell carcinoma

The response to targeted therapies and immune checkpoint inhibitors for patients suffering from metastatic clear cell renal cell carcinoma (ccRCC) is heterogeneous and currently not predictable in clinic. In this work, a comprehensive integrated study of 700 ccRCCs profiled by DNA methylation and RNA sequencing showed that the hyper-methylated tumors exhibited a worse prognosis, a higher fraction of cycling tumor cells and a lower activity of homeobox transcription factors. To translate the use of DNA methylation information into a clinical setting, we developed a simple model accurately predicting the ccRCC methylation subtypes (AUC-ROCs of 0.91) from two gene expression ratios (IGF2BP3/PCCA, TNNT1/TMEM88). In addition, these methylation subtypes were significantly associated with the therapeutic outcome of patients to anti-PD-1, mTOR inhibitor or tyrosine kinase inhibitor therapies. Overall, our framework for predicting the ccRCC DNA methylation subtypes from targeted gene expression data is easy to translate in clinic and contributes to better personalization of ccRCC therapies.

bioinformatics↗

Long-read Spatial Transcriptomic Profiling of Patient-derived ccRCC Tumoroids Reveals Heterogeneity in Isoform and Gene Expression

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of kidney cancer characterized by its diverse tumor composition featuring various subclonal populations that hinder effective treatment responses. Tumoroids present an avenue for modelling this diversity and replicating the intricate tumor heterogeneity. Spatial transcriptomics preserves the spatial context of gene expression enabling us to study distinct tumor areas and the influence on overall diversity. Our spatial transcriptomics analysis uncovered tumor clusters with distinct genetic profiles that showcase various functional areas in depth and offer valuable understandings into the diversity of ccRCC types. Some of these tumor clusters exhibited activity in genes responsible for protein catabolism and reduced abundance of genes related to mitochondrial respiration processes. We also show isoform expression within tumoroids, in particular glutaminase (GLS) especially with the prevalence of the highly metabolically active GAC isoform that is expressed in regions where mitochondrial gene abundance is lower; whereas the KGA isoform displayed a more focal expression pattern. Combining long-read spatial transcriptomics with organoid models presents a novel strategy for unravelling gene and transcript level complexity.

cancer biology↗

Spatial Metabolomics co-registered with Multiplex Phenotyping for the Evaluation of Human Kidney Tissue

A workflow has been evaluated that utilises a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled analysis. The impact of varying DESI-MSI conditions (e.g., temperature, scan rate, acquisition time) on the detection of small molecules and on tissue quality for integration into typical clinical pathology workflows assessed in human kidney.

systems biology↗

Microenvironment of metastatic site reveals key predictors of PD-1 blockade response in renal cell carcinoma

Immune checkpoint blockade (ICB) therapies have improved the overall survival (OS) of many patients with advanced cancers. However, the response rate to ICB varies widely among patients, exposing non-responders to potentially severe immune-related adverse events. The discovery of new biomarkers to identify patients responding to ICB is now a critical need in the clinic. We therefore investigated the tumor microenvironment (TME) of advanced clear cell renal cell carcinoma (ccRCC) samples from primary and metastatic sites to identify molecular and cellular markers of response to ICB. We revealed a significant discrepancy in treatment response between subgroups based on cell fractions inferred from metastatic sites. One of the subgroups was enriched in non-responders and harbored a lower fraction of CD8+ T cells and plasma cells, as well as a decreased expression of immunoglobulin genes. In addition, we developed the Tumor-Immunity Differential (TID) score which combines features from tumor cells and the TME to accurately predict response to anti-PD-1 immunotherapy (AUC-ROC=0.88, log-rank tests for PFS P < 0.0001, OS P = 0.01). Finally, we also defined TID-related genes (YWHAE, CXCR6 and BTF3), among which YWHAE was validated as a robust predictive marker of ICB response in independent cohorts of pre- or on-treatment biopsies of melanoma and lung cancers. Overall, these results provide a rationale to further explore variations in the cell composition of metastatic sites, and underlying gene signatures, to predict patient response to ICB treatments. One Sentence SummaryTumor microenvironment balance of metastasis and associated genes are key predictors of immunotherapy patient response in kidney cancer.

bioinformatics↗

Single cell analysis of senescent epithelia reveals targetable mechanisms promoting fibrosis

Progressive fibrosis and maladaptive organ repair result in significant morbidity and millions of premature deaths annually. Senescent cells accumulate with ageing and after injury and are implicated in organ fibrosis, but the mechanisms by which senescence influences repair are poorly understood. Using two murine models of injury and repair we show that obstructive injury generates senescent epithelia which persist after resolution of the original injury, promote ongoing fibrosis and impede adaptive repair. Depletion of senescent cells with ABT263 reduces fibrosis in reversed ureteric obstruction and after renal ischaemia-reperfusion injury. We validate these findings in humans, showing that senescence and fibrosis persist after relieved renal obstruction. We next characterise senescent epithelia in murine renal injury using single cell RNA-Seq. We extend our classification to human kidney and liver disease and identify conserved pro-fibrotic proteins which we validate in vitro and in human disease. We demonstrate that one such molecule, Protein Disulfide Isomerase Family A Member 3 (PDIA3), is essential for TGF-beta mediated fibroblast activation. Inhibition of PDIA3 in vivo significantly reduces kidney fibrosis during ongoing renal injury and as such represents a new potential therapeutic pathway. Analysis of the signalling pathways of senescent epithelia connects senescence to organ fibrosis, permitting rational design of anti-fibrotic therapies.

cell biology↗

A comprehensive library of canonical and non-canonical MHC class I antigens for cancer vaccine development.

A longstanding disconnect between the growing number of MHC Class I immunopeptidomic studies and genomic medicine hinders cancer vaccine design. We develop COD-dipp to genomically map the full spectrum of detected canonical and non-canonical (non-exonic) MHC Class I antigens from 26 cancer studies. We demonstrate that patient mutations in regions overlapping physically identified antigens better predict immunotherapy response when compared to neoantigen predictions. We suggest a vaccine design approach using 140,966 highly immune-visible regions of the genome annotated by their expression and haplotype frequency in the human population. These regions tend to be highly conserved, mutated in cancer and harbor 7.8 times more immunogenicity. Intersecting pan-cancer mutations with these immune surveilled regions revealed a potential to create off-the-shelf multi-epitope vaccines against public neoantigens. Here we release COD-dipp, a cancer vaccine toolkit as a web-application (https://www.proteogenomics.ca/COD-dipp) and open-source high-throughput resource.

bioinformatics↗

Protein disulphide isomerase (PDI) is protective against several types of DNA damage, including that induced by amyotrophic lateral sclerosis-associated mutant TDP-43 in neuronal cells/ in vitro models

Protein disulphide isomerase (PDI) is a chaperone that catalyses the formation of thiol-disulphide bonds during protein folding. Whilst up-regulation of PDI is a protective mechanism to regulate protein folding, an increasingly wide range of cellular functions have been ascribed to PDI. Originally identified in the endoplasmic reticulum (ER), PDI has now been detected in many cellular locations, including the nucleus. However, its role in this cellular compartment remains undefined. PDI is implicated in multiple diseases, including amyotrophic lateral sclerosis (ALS), a fatal and rapidly progressing neurodegenerative condition affecting motor neurons. Loss of essential proteins from the nucleus is an important feature of ALS. This includes TAR DNA-binding protein-43 (TDP-43), a DNA/RNA binding protein present in a pathological form in the cytoplasm in almost all (97%) ALS cases, that is also mutated in a proportion of familial cases. PDI is protective against disease-relevant phenotypes associated with dysregulation of protein homeostasis (proteostasis) in ALS. DNA damage is also increasingly linked to ALS, which is induced by pathological forms of TDP-43 by impairment of its normal function in the non-homologous end-joining (NHEJ) mechanism of DNA repair. However, it remains unclear whether PDI is protective against DNA damage in ALS. In this study we demonstrate that PDI was protective against several types of DNA damage, induced by either etoposide, hydrogen peroxide (H2O2), or ALS-associated mutant TDP-43M337V in neuronal cells. This was demonstrated using widely used DNA damage markers, phosphorylated H2AX and 53BP1, which is specific for NHEJ. Moreover, we also show that PDI translocates into the nucleus following DNA damage. Here PDI is recruited directly to sites of DNA damage, implying that it has a direct role in DNA repair. This study therefore identifies a novel role of PDI in the nucleus in preventing DNA damage.

neuroscience↗