Biology subjects

Campbell, K.

Publications and source records attributed to Campbell, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Biomolecular condensation of cMLCK enables myosin motor phosphorylation in the heart

The heart needs to adapt its output to the metabolic demands of the organism. Phosphorylation of the myosin motors by cardiac myosin light chain kinase (cMLCK) increases heart muscle contractile function, yet its regulation and mechanism of action have remained unclear. Here, we show that cMLCK undergoes liquid-liquid phase separation and forms biomolecular condensates associated with the sarcoplasmic reticulum of cardiac muscle cells. Condensates selectively enrich enzymatic cofactors and substrates, which increases the catalytic activity of cMLCK. Our study reveals that cMLCK is fine-tuned to work in the molecular environment of condensates, enabling physiologically relevant levels of cardiac myosin motor phosphorylation. These findings establish a condensate-based mechanism for the spatial and temporal regulation of cardiac thick filament contractile function.

biochemistry↗

bioRxiv2026

Hearts may grow concentrically to balance ATP supply and demand and eccentrically to stabilize titin-based stress

Hearts change their wall thickness (concentric growth) and chamber size (eccentric growth) as they adapt to circulatory demands and the intrinsic function of their contractile cells. Factors associated with wall thickening include variants of sarcomeric proteins that enhance contractility, mitochondrial dysfunction, and hypertension. Chambers can dilate due to many factors including sarcomeric variants that depress contractility and aortic and / or mitral valve insufficiency. Despite intensive study, the mechanisms that regulate cardiac growth remain unclear. It is also uncertain whether inherited variants induce growth via the same mechanisms as more common clinical pathologies, such as hypertension. Here we show that computer simulations of a beating left ventricle reproduce both variant and non-variant-related growth patterns when myocytes grow concentrically to regulate intracellular ATP concentration and eccentrically to maintain titin-based intracellular stress. The simulations support the hypothesis that cardiac growth reflects homeostatic feedback through three interacting systems whereby myocytes add or remove mitochondria and sarcomeres (1) in parallel to match ATP generation to myocardial energy demand, and (2) in series to regulate passive tension, while (3) the autonomic nervous system regulates cardiac power, and thus myocardial ATPase, via baroreflex control. The new framework provides a mechanistic basis for the patterns of eccentric and concentric growth induced by a wide range of clinically-relevant conditions and could facilitate in silico testing of potential therapies for cardiac disease. Significance statementHearts grow in response to both physiological and pathological stimuli. The patterns of concentric (wall thickening / thinning) and eccentric (chamber dilation / constriction) induced by different challenges are well recognized but the underlying mechanisms remain unclear. This work presents simulations of a beating left ventricle where (1) concentric growth is regulated by myocytes attempting to stabilize the intracellular ATP concentration and (2) eccentric growth is regulated by titin-mediated stress. The calculations reproduce the growth associated with inherited variants of sarcomeric proteins, mitochondrial dysfunction, hypertension, and both mitral and aortic valve insufficiency. The new ability to predict cardiac growth and its potential modification by treatments, including myotropes, brings the field closer to in silico optimization of therapy for cardiovascular disease.

biophysics↗

bioRxiv2026

MOSAIC: Model-based, Subgroup-Aware Identification of Driver Mutations in Cancer

In cancer genomics, recurrent patterns of mutual exclusivity within a gene set can indicate shared biological context and involvement in tumorigenesis. However, existing methods are not designed to distinguish between mutual exclusivity arising from meaningful biological interactions from those influenced by heterogeneity between underlying patient subpopulations. In this work, we introduce MOSAIC, a novel statistical framework that models patient subgroup heterogeneity in mutual exclusivity analyses. In experiments with simulated data and real data from The Cancer Genome Atlas, we show that MOSAIC amplifies subgroup-specific mutual exclusivity signals, including between IDH1 and IDH2 in young low grade glioma patients, while reducing the effect of signals produced by underlying subgroup structures, such as distinct genomic lineages associated with histological subtypes of endometrial cancer. Finally, we demonstrate that MOSAIC is more powerful than existing p-value combination methods for patient subgroup stratification. MOSAIC is available as an open-source tool at https://github.com/reynalab/mosaic.

bioinformatics↗

bioRxiv2026

Single-molecule analysis sheds light on cardiac myosin dysfunction due to hypertrophic cardiomyopathy mutation A57D in ventricular myosin light chain-1 (MLC1v)

Ventricular myosin light chain-1 (MLC1v) is a key structural and function-modulating component of the {beta}-cardiac myosin ({beta}M-II) motor complex. Single-point mutations in MLC1v are linked to severe forms of hypertrophic cardiomyopathy (HCM) and sudden cardiac death (SCD) at a young age. However, the molecular mechanisms underlying the motor dysfunction responsible for HCM phenotype development are not fully understood. Here, we investigated native {beta}M-II motors isolated from septal myectomy sample of an HCM patient, harboring a rare homozygous mutation in MLC1v (A57D). Using a pure population of mutant motors (MUT), and sensitive single-molecule functional analysis approach, we directly assessed the primary functional alterations in {beta}M-II bearing A57D MLC1v mutation. In optical trap single-molecules measurements, the mutant motors displayed increased actomyosin (AM) interaction duration in strongly bound state (ton), corresponding to 3-fold reduced AM detachment rate than wild type myosin (WT). The MUT myosin also generated a shorter powerstroke size ({delta}). Ensemble average analysis of AM interaction events demonstrated that both the first powerstroke ({delta}1) associated with Pi release and the second powerstroke ({delta}2) linked to ADP release were reduced in MUT myosin. Moreover, the increased actomyosin cross-bridge stiffness in the AM.ADP state was observed for MUT compared to WT motors. Consistent with slower AM detachment rate and shorter stroke size, reconstituted human mutant {beta}M-II displayed slower actin filament gliding speed. Alterations in sarcomere-level mechanics included increased Ca2+ sensitivity of force generation and prolonged relaxation time, as predicted by FiberSim modelling. Molecular dynamics simulations indicated that the substitution of alanine by aspartate altered MLC1v interactions with myosin heavy chain (MyHC) and light chain 2 (MLC2v), affecting the curvature and flexibility of the lever arm. Overall, these studies establish the molecular mechanism underlying the primary myosin dysfunction due to A57D MLC1v mutation and further highlight the crucial role of MLC1v-mediated regulation of myosin function. Understanding the precise changes in the mutant myosins biomechanical properties is directly relevant to comprehending the initial triggers for pathological cardiac remodeling in HCM patients and designing tailored therapeutic interventions.

biophysics↗

bioRxiv2025

Multicenter HFpEF study identifies sex disparity linked with two discrete cardiac proteomic signatures

Heart failure with preserved ejection fraction (HFpEF) is epidemic, with an incidence exceeding that of heart failure with reduced ejection fraction (HFrEF). Sex differences in HFpEF phenotype have been observed, particularly linked to aging and metabolic comorbidities in women. Here, we report a multi-centre proteomic analysis of HFpEF and HFrEF cardiac samples. Using tissues and clinical data derived from multiple institutional biobanks, in-depth characterization of the proteome of ventricular samples was undertaken. Relative to HFrEF, the HFpEF cohort exhibited minimal proteome composition overlap and pronounced heterogeneity. A key finding of this investigation is that sex per se did not confer a distinctive proteomic HFpEF signature. Rather, two HFpEF proteomic profiles were identified, differing significantly in sex ratios. The identification of two Clusters revealed that HFpEF has two predominant proteomic signatures at the molecular level, marked by differences in the extent and nature of structural and contractile machinery and by local cellular and ECM communications. Upstream regulator analysis identified various molecular leads to be pursued in defining these two HFpEF profiles. Our findings offer specific opportunities for new exploration of therapeutic options to target the spectrum of HFpEF proteomic diversity and identify potential drug targeting prospects.

molecular biology↗

bioRxiv2025

Cold-water gut isolate from threespine stickleback (Gasterosteus aculeatus) reveals polypropylene surface oxidation and co-culture inhibition

Polyethylene terephthalate (PET) and polypropylene (PP), two of the most widely produced plastics in the United States, persist in cold-water environments where plastic-degrading microbes have been poorly characterized. Understanding how gut microbes interact and contribute to plastic degradation is essential for developing potential microbiome-based bioremediation strategies. We isolated 184 microbes from wild Alaskan threespine stickleback (Gasterosteus aculeatus) guts across six lakes and screened for plastic degrading potential using lipase/esterase assays and biofilm formation on PET and PP. During the screen for microbes with plastic degrading potential, we discovered that stickleback gut microbiota members enhance and suppressed the lipase, esterase, and biofilm activity of other microbes. Isolates with the highest plastic degrading potential were incubated in minimal media with PET or PP as the sole carbon source to determine whether plastic degradation potential is enhanced. Surface analysis identified a Pseudomonas trivialis strain that exhibited degradation of PP in monoculture; however, this activity was suppressed in the presence of another gut isolate, Pseudomonas germanica. These results demonstrate that microbes associated with the wild threespine stickleback gut microbiome possess plastic degradation potential and provide insights into how microbial interactions can either promote or inhibit bioremediation of plastic pollution in cold-water environments.

microbiology↗

bioRxiv2025

Accelerating Biomolecular Modeling with AtomWorks andRF3

Deep learning methods trained on protein structure databases have revolutionized biomolecular structure prediction, but developing and training new models remains a considerable challenge. To facilitate the development of new models, we present AtomWorks: a broadly applicable data framework for developing state-of-the-art biomolecular foundation models spanning diverse tasks, including structure prediction, generative protein design, and fixed backbone sequence design. We use AtomWorks to train RosettaFold-3 (RF3), a structure prediction network capable of predicting arbitrary biomolecular complexes with an improved treatment of chirality that narrows the performance gap between closed-source AlphaFold3 (AF3) and existing open-source implementations. We expect that AtomWorks will accelerate the next generation of open-source biomolecular machine learning models and that RF3 will be broadly useful as a structure prediction tool. To this end, we release the AtomWorks framework (https://github.com/RosettaCommons/atomworks), together with curated training data, code and model weights for RF3 (https://github.com/RosettaCommons/modelforge) under a permissive BSD license.

biochemistry↗

bioRxiv2025

Direct measurement of mavacamten and deoxyATP perturbation of the SRX/DRX ratio in porcine cardiac myofibrils using a simple, accessible and multiplexed approach

Cardiac muscle adapts to varying physiological demands by modulating the number of active myosin II motors available for contraction. These motors are organized into thick filaments in the sarcomere and generate force through an ATP-dependent interaction with thin filaments that contain actin. To conserve energy, when demand is low myosin can occupy the super-relaxed (SRX) state, which acts as a reserve. Here, we build upon the earlier studies from the Cooke lab to quantify the size of this cardiac reserve using fluorescence imaging of Cy3-ATP directly in myofibrils. This approach employs a pulse-chase method and exploits the high permeability of isolated myofibrils to monitor nucleotide release in situ. By preserving sarcomeric architecture while enabling rapid reagent exchange, this method bridges the gap between complex single-molecule imaging and traditional stopped-flow bulk assays using MANT-ATP. Using this approach we have studied biochemical perturbation of the SRX reserve with deoxyATP and mavacamten. DeoxyATP caused large depletion of the cardiac reserve, and mavacamten increased its size, consistent with its clinical application. Our results demonstrate the utility of this technique and the potential for further enhancement using multiplexing, holding promise for future applications in health and disease.

biophysics↗

bioRxiv2025

A hormonally regulated gating mechanism controls EMT timing to ensure progenitor cell specification occurs prior to epithelial breakdown

Epithelial-to-mesenchymal transitions (EMTs) are essential for morphogenesis, converting static epithelial cells into migratory mesenchymal cells. As EMT disrupts epithelial barriers, its timing must be tightly regulated during development. We investigated this regulation in the Drosophila posterior embryonic midgut, where the GATA transcription factor Serpent (Srp) drives a collective partial EMT in the principal midgut epithelial cells (PMECs). Srp is expressed well before PMEC-EMT initiation and is also required for an earlier event: the specification and delamination of endoblasts, which give rise to different midgut lineages including adult midgut progenitors (AMPs). Here we identify the steroid hormone ecdysone as a temporal cue that triggers PMEC-EMT. Although Srp activates and represses numerous genes during early stages of midgut development, including polarity regulators such as crumbs (crb), the removal of polarity proteins and E-Cadherin from the membrane of PMECs only properly occurs in the presence of ecdysone signalling. This suggests that Srp primes cells transcriptionally for EMT, which proceeds only once polarity and adhesion proteins are downregulated post-translationally. When PMECs undergo a premature EMT, this leads to a reduction in the number of progenitor cells, suggesting that maintaining epithelial integrity until after endoblasts are selected is crucial for early fate decisions. These findings reveal that ecdysone functions as a EMT gatekeeper, ensuring that EMT is temporally restricted to occur only after progenitor specification, and in coordination with other developmental processes. More broadly, our work shows that in this context, transcriptional priming of EMT can be uncoupled from its execution, which is post-translationally triggered by hormonal signals. Given the conserved role of nuclear steroid hormone receptors as GATA co-factors and their association with poor prognosis in cancer, this may represent a broader strategy by which systemic cues regulate EMT in development and cancer.

developmental biology↗

bioRxiv2025

Damage and Misrepair Signatures: Compact Representations of Pan-cancer Mutational Processes

Mutational signatures of single-base substitutions (SBSs) characterize somatic mutation processes which contribute to cancer development and progression. However, current mutational signatures do not distinguish the two independent steps that generate SBSs: the initial DNA damage followed by erroneous repair. To address this modelling gap we developed DAMUTA, a hierarchical Bayesian probabilistic model that infers separate signatures for each process, and captures their sample-specific interaction. We applied DAMUTA to 18,974 pan-cancer whole genome sequencing mutation catalogues from 23 cancer types and show that tissue-specificity in mutation patterns is driven largely by variability in damage processes. We also show that misrepair processes are predictive of DNA damage response deficiencies. Unlike existing approaches, DAMUTA distinguishes damage from misrepair contributions, and we demonstrate significant improvements over a mutational-burden baseline or signatures from the COSMIC database. Our analysis reveals a shared pan-cancer pattern of early clonal transition-mutations which shifts to a more uniform substitution pattern consistent with increased reliance on translesion synthesis for damage tolerance. DAMUTA thus generates a compact set of signatures which resolves redundancies of current signature models, disentangles the effects of DNA damage and misrepair processes, and facilitates improved stratification of tumours, while providing a framework towards a unified pan-cancer model of the cellular response to DNA damage.

genomics↗

bioRxiv2025

Automated registration of spatial expression data scales multimodal integration to large cohorts

Recent advances in spatial proteomics enable quantification of the spatial distribution of protein expression across a variety of scales, resolutions, and multiplexing. Registering images from such technologies across modalities is an essential task that enables both the integration of complementary imaging technologies and validation of biological findings. This can be particularly challenging when the modalities capture fundamentally different types of data, such as light intensity, probe counts, or heavy metal counts. However, few datasets and methods address this problem at scale. Here, we introduce the largest dataset to date of cross-modality imaging of both cell line and tissue slides suitable for benchmarking registration methods. We further present Twocan, a Bayesian optimization framework that enables robust automated registration between immunofluorescence imaging and highly multiplex spatial proteomics data. Our method achieves significantly higher registration success rates compared to existing approaches across our comprehensive dataset of 954 image pairs.

bioinformatics↗

bioRxiv2025

Spatial control of myosin regulatory light chain phosphorylation modulates cardiac thick filament mechano-sensing

The heart can adapt its performance in response to changing metabolic demands of the rest of the body. A central mechanism intrinsic to the heart is to modulate the function of the cardiac contractile proteins via post-translational modifications. Although phosphorylation of the cardiac myosin motor-associated regulatory light chain (RLC) by cardiac myosin light chain kinase (cMLCK) has been recognized as a key signalling pathway to increase myocardial contractile function, little is known about its molecular mechanism of action. Here, we show that phosphorylation of RLC is not a stochastic process but a spatially tightly controlled mechanism. Myosin motors in the region of the thick filament associated with cardiac myosin binding protein-C (cMyBP-C) are the primary target for phosphorylation by cMLCK. Moreover, phosphorylation of RLC likely only leads to activation of one of the two myosin motors of the cardiac myosin molecule and increases their force-dependent recruitment. We propose that RLC phosphorylation exerts its functional effects via increasing the gain of the mechano-signalling between different zones of the thick filament. A better mechanistic understanding of the role of RLC phosphorylation likely underpins the development of therapeutic interventions for both heart disease and heart failure.

biochemistry↗

bioRxiv2025

Multi-view deep learning of highly multiplexed imaging data improves association of cell states with clinical outcomes

Highly multiplexed imaging technologies can quantify the expression of 10s-100s of proteins and their modifications at sub-cellular resolution. Applications to tissue specimens across a broad array of pathologies have enabled patient subtyping in terms of novel cell states and spatial cell communities and linked their prevalence and overall architecture to patient outcomes. While highly multiplexed imaging analysis workflows typically summarize each cell in terms of its post-segmentation mean expression, additional cellular information can be quantified including cell morphology, sub-cellular expression patterns, and spatial cellular context, ultimately giving a multi-modal view of each cell. While deep latent variable models such as variational autoencoders (VAEs) are well established for other multi-modal single-cell assays, their ability to integrate these multiple views of a cell from highly multiplexed imaging data remains largely unknown. Here, we explore the abilities of multi-modal VAEs to learn unified latent cellular representations from multiple views of each single-cell quantified from highly multiplexed imaging, including mean expression, morphology, sub-cellular protein co-localization, and spatial cellular context, while conditioning on technical and batch specific effects. We first discuss strategies for training and hyperparameter optimization of such models across a set of highly multiplexed imaging datasets of breast and melanoma cancers. We next quantify the relevance of the integrated multi-modal latent space in predicting patient-specific clinical outcomes and demonstrate competitive performance across a range of outcomes compared to existing baselines. Then, we explore the ability of the cellular representations to learn cellular phenotypes that align with known cell types and find that the expression-specific latent representation can identify clusters more closely aligned with known lymphocyte and epithelial subpopulations compared to established workflows. Finally, we test the ability of each representation to perform consistent batch integration across different cohorts and discuss the considerations on taking known background variables into account.

bioinformatics↗

bioRxiv2025

Runx1 and Runx2 act in concert to suppress Wnt/β-catenin-driven mammary tumourigenesis

The genes encoding transcription factor RUNX1 and its binding partner CBFB have been reported to be mutated in human breast cancer. Here, we provide evidence that Runx1 loss of function results in accelerated disease onset and tumour development in mouse models of breast cancer, in keeping with a tumour suppressor role for RUNX1 in this disease setting. Combined deletion of Runx1 and the related family member Runx2 resulted in mammary epithelial cells becoming exquisitely sensitive to WNT-driven transformation, with the emergence of multiple tumours early in life. Clonogenic assays indicated that Runx1 ablation induced a stem cell like phenotype in mammary epithelial cells, whilst transcriptome analysis demonstrated activation of multiple oncogenic pathways, especially when Runx2 was co- deleted. Interestingly, altered Runx expression in the mammary epithelium also drove profound alterations in the tumour microenvironment, impacting the immune landscape. These results highlight that Runx1 restricts some forms of breast cancer and inhibits the full oncogenic potential of aberrant WNT signalling. Loss of Runx2 itself did not result in tumour promotion, yet the dramatic effects of combined Runx1 and Runx2 loss suggest that Runx2 can substitute for Runx1 in dampening the oncogenic effects of WNT signalling.

cancer biology↗

bioRxiv2024

Evolution of polyamine resistance in Staphylococcus aureus through modulation of potassium transport

Microbes must adapt to diverse biotic and abiotic factors encountered in host environments. Polyamines are an abundant class of aliphatic molecules that play essential roles in fundamental cellular processes across the tree of life. Surprisingly, the bacterial pathogen Staphylococcus aureus is highly sensitive to polyamines encountered during infection, and acquisition of a polyamine resistance locus has been implicated in spread of the prominent USA300 methicillin-resistant S. aureus lineage. At present, alternative pathways of polyamine resistance in staphylococci are largely unknown. Here we applied experimental evolution to identify novel mechanisms and consequences of S. aureus adaption when exposed to increasing concentrations of the polyamine spermine. Evolved populations of S. aureus exhibited striking evidence of parallel adaptation, accumulating independent mutations in the potassium transporter genes ktrA and ktrD. Mutations in either ktrA or ktrD are sufficient to confer polyamine resistance and function in an additive manner. Moreover, we find that ktr mutations provide increased resistance to multiple classes of unrelated cationic antibiotics, suggesting a common mechanism of resistance. Consistent with this hypothesis, ktr mutants exhibit alterations in cell surface charge indicative of reduced affinity and uptake of cationic molecules. Finally, we observe that laboratory-evolved ktr mutations are also present in diverse natural S. aureus isolates, suggesting these mutations may contribute to antimicrobial resistance during human infections. Collectively this study identifies a new role for potassium transport in S. aureus polyamine resistance with consequences for susceptibility to both host-derived and clinically-used antimicrobials.

microbiology↗

bioRxiv2024

Nutrient Sensing Receptor GPRC6A Regulates mTORC1 Signaling and Tau Biology

Tauopathies, including Alzheimers disease (AD), comprise microtubule-associated protein tau aggregates that cause neuronal cell death and clinical cognitive decline. Reducing overall tau abundance remains a central strategy for therapeutics; however, no disease-modifying treatment exists to date. One principal pathway for balancing cellular proteostasis includes the mechanistic target of rapamycin complex 1 (mTORC1) signaling. Recently, arginine emerged as one of the primary amino acids to activate mTORC1 through several intracellular arginine sensors and an extracellular arginine receptor, namely the G protein-coupled receptor (GPCR) family C, group 6, member A (GPRC6A). Human AD brains were previously reported with elevated mTORC1 signaling; however, it is unclear whether arginine sensing and signaling to mTORC1 plays a role in tauopathies. Herein, we examined arginine sensing associated with mTORC1 signaling in the human AD and animal models of tauopathy. We found that human AD brains maintained elevated levels of arginine sensors with potential uncoupling of arginine sensing pathways. Furthermore, we observed increased GPRC6A and arginine in the brain, accompanied by increased mTORC1 signaling and decreased autophagy in a mouse model of tauopathy (Tau PS19). We also discovered that both supplementing arginine and overexpressing GPRC6A in cell culture models could independently activate mTORC1 and promote tau accumulation. In addition, we found that suppressing GPRC6A signaling by either genetic reduction or pharmacological antagonism reduced tau accumulation, phosphorylation, and oligomerization. Overall, these findings uncover the crucial role of arginine sensing pathways in deregulating mTORC1 signaling in tauopathies and identify GPRC6A as a promising target for future therapeutics in tauopathies and other proteinopathies. Significance StatementTauopathies, including Alzheimers disease (AD), accumulate pathogenic tau protein inclusions that potentially contribute to the hyperactive mechanistic target of rapamycin complex 1 (mTORC1) signaling and eventually cause neuronal cell death. Here, we presented novel findings that AD and animal models of tauopathy maintained increased expression of arginine sensors and uncoupling of arginine sensing associated with mTORC1 signaling. We investigated the role of a putative extracellular arginine and basic L-amino acid sensing G protein-coupled receptor (GPCR) family C, group 6, member A (GPRC6A) in activating mTORC1 and accelerating pathogenic tau phenotypes in several cell models. Additionally, we showed that genetic repression or antagonism of GPRC6A signaling provides a novel therapeutic target for tauopathies and other proteinopathies.

neuroscience↗

bioRxiv2024

GelBox: Open-source software to improve rigor and reproducibility when analyzing gels and immunoblots

GelBox is open-source software that was developed with the goal of enhancing rigor, reproducibility, and transparency when analyzing gels and immunoblots. It combines image adjustments (cropping, rotation, brightness, and contrast), background correction, and band-fitting in a single application. Users can also associate each lane in an image with metadata (for example, sample type). GelBox data files integrate the raw data, supplied metadata, image adjustments, and band-level analyses in a single file to improve traceability. GelBox has a user-friendly interface and was developed using MATLAB. The software, installation instructions, and tutorials, are available at https://campbell-muscle-lab.github.io/GelBox/.

biochemistry↗

bioRxiv2024

Genetic polymorphisms of Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3) gene in African American kidney transplant recipients are associated with post-transplant graft failure

BackgroundAfrican American (AA) kidney transplant recipients exhibit a higher rate of graft loss compared to other racial and ethnic populations, highlighting the need to identify causative factors underlying this disparity. MethodWe analyzed RNA sequences of pretransplant whole blood from subjects followed in three kidney transplant cohorts to identify single nucleotide polymorphisms (SNPs) associated with death censored graft loss (DCGL). We employed a meta-analysis to uncover key transcriptional signatures and pathways associated with the identified SNPs and used single cell RNA to define cellular specificity. We characterized SNP functions using in vitro immunological and survival assays and tested for associations between the identified SNPs and other immune-related diseases using a [~]30,100 subject, electronic health record (EHR)-linked database. ResultsWe uncovered a cluster of four consecutive missense SNPs in the Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3, a negative immune response regulator) gene that strongly associated with DCGL. This LILRB3-4SNPs cluster encodes missense mutations at amino acids 617-618 proximal to a SHP-1/2 phosphatase-binding ITIM motif. LILRB3-4SNPs is specifically enriched within subjects of AA ancestry (8.6% prevalence vs 2.3% in Hispanic and 0.1% in European populations), is not linked to APOL1 G1/G2 alleles, and exhibited a strong association with DCGL. Analysis of PBMC and transplant biopsies from recipients with LILRB3-4SNPs showed evidence of enhanced adaptive immune responsiveness and ferroptosis-associated death in monocytes. Overexpression of the variant allele in THP-1 cells (macrophage line) induced augmented inflammation and ferroptosis, which were attenuated by a ferroptosis inhibitor, verifying a causal link. The LILRB3-4SNPs also associated with multiple systemic and organ-specific immune-related diseases in AAs, consistent with conferring a broadly relevant immune function. Conclusionthe LILRB3-4SNPs represent a functionally important, distinct genetic risk factor for kidney transplant outcome and development/severity of other immune-related diseases in patients of AA ancestry. Pharmacological targeting of ferroptosis should be tested to prevent or treat these disease processes in AA recipients carrying LILRB3-4SNPs.

genetics↗