Biology subjects

Aghaeepour, N.

Publications and source records attributed to Aghaeepour, N..

11 recordsLinked to original sources

bioRxiv2026

LENS: a transferable neuromuscular signature of musculoskeletal pain intensity

Self-reported pain remains the clinical standard for assessing musculoskeletal pain severity, but its subjectivity limits objective diagnosis, monitoring, and therapeutic development. We present LENS (Latent sEMG Neuromuscular Signature), which decodes exertion-evoked musculoskeletal pain intensity from surface electromyography (sEMG) alone. LENS was pre-trained via a cross-modal self-supervised objective that reconstructs muscle oxygenation from sEMG in 183 adults. LENS was trained exclusively on healthy muscle physiology and generalized to an independent healthy cohort (Spearman's {rho}=0.52) and discriminated moderate-to-severe pain (AUROC=0.83). Using a label-free test-time adaptation, LENS generalized to an unseen chronic musculoskeletal pain cohort--myogenous temporomandibular disorder (mTMD)--with comparable performance ({rho}=0.61; AUROC=0.86). Reverse transfer, from mTMD to controls, was substantially weaker, an asymmetry attributable to elevated motor variability in chronic pain; excluding highly variable mTMD participants recovered performance, indicating a conserved pain signature masked by pathology-specific motor noise. LENS offers a scalable, physiological correlate of musculoskeletal pain from a single sEMG channel.

neuroscience↗

bioRxiv2026

Blood-brain barrier dysfunction predicts cognitive trajectory after ischemic stroke

Ischemic stroke doubles the risk of dementia.1-4 Stroke severity and location affect cognition early,5,6 but late dementia risk is not related to infarct characteristics, nor is it reduced by preventing additional strokes,3,6,7 and its mechanism is unknown. We identified a plasma proteomic signature of chronic stroke that was consistent with blood-brain barrier (BBB) dysfunction, including a 58% decrease in plasma levels of platelet-derived growth factor B and downregulation of its pathway compared to healthy controls. During 2 years of follow-up, the stroke-specific proteome was accentuated in stroke survivors who subsequently declined in the processing speed/executive function cognitive domain. To test BBB function, we performed dynamic contrast-enhanced MRI 6-9 months after stroke in an additional cohort and found 1.7-fold higher whole brain BBB leakage compared to controls. Finally, we compared autopsy tissue from people with infarcts and dementia at death to those with infarcts and no dementia. Those who died with dementia had dramatic loss of vascular mural cell coverage compared to those without dementia (median 0.7% vs. 27%). Thus, our proteomic, functional, and structural data implicate chronic BBB dysfunction in cognitive decline late after stroke, revealing potential proteomic and imaging biomarkers and, importantly, a novel target for intervention.

neuroscience↗

bioRxiv2025

Systemic immune dysregulation in hypertensive disorders of pregnancy persists years after delivery

BackgroundHypertensive disorders of pregnancy (HDP), including preeclampsia and gestational hypertension, are associated with an increased risk of cardiovascular disease (CVD) later in life. Mechanisms that link HDP to CVD, however, remain unclear. MethodsWe used a high-dimensional single-cell mass cytometry approach to profile the distribution and functional responses of maternal immune cells in three separate groups of HDP cases and normotensive controls, sampled antepartum, postpartum, and several years postpartum (midlife). We used multivariable sparse modeling to distinguish HDP cases from controls. ResultsWe accurately distinguished HDP cases from controls at all three study timepoints, with area under the receiver operator characteristic (AUROC) curve values of 0.814 for the antepartum group, 0.757 for the postpartum group, and 0.692 for the midlife group. Distinct immune signatures for each model underscore the dynamic dysregulation of the immune system throughout life. In addition, we identified a persistent immune dysregulation signal among HDP cases at all three timepoints, characterized by increased B cell frequency and decreased pSTAT3 response upon cytokine stimulation in classical monocytes. ConclusionsPersistent immune dysregulation among women with a history of an HDP may contribute to elevated long-term risk of CVD development.

immunology↗

bioRxiv2025

Single-cell-level digital twins for preterm birth prevention strategies

Digital twin models can accelerate therapeutic development by enabling low-risk testing of candidate interventions. In preterm labor (PTL), a major pregnancy complication where clinical trials face unique ethical and financial barriers, digital twins are especially valuable for evaluating new therapies targeting immune dysfunctions driving PTL. Yet, current models lack single-cell resolution, limiting detection of cell-type-specific mechanisms, off-target effects, and the design of personalized interventions. We present Simulated Immunome Modeling of Clinical Outcomes (SIMCO), a single-cell-level digital twin framework that models immunomodulatory treatment effects on the timing of labor using immunome-wide, single-cell simulations. SIMCOs digital twins are trained and validated on a newly generated mass cytometry atlas of the pregnant immunome exposed to nine candidate drugs preselected for PTL prevention. Applying SIMCO to an independent cohort of pregnant individuals, we simulate treatment effects on gestational length, screening for candidate drugs that delay labor timing and providing system-level mechanistic insight for each drug candidate. Tetrahydrofolate, maprotiline, and the combination of aspirin and lansoprazole emerged as top candidates for PTL prevention, delaying labor onset primarily through enhanced mTOR signaling in innate immune cells and attenuated JAK/STAT signaling in naive CD4 T cells. The codebase is available at https://github.com/ofondeur/SIMCO/.

immunology↗

bioRxiv2025

Blockade of VCAM1 or VLA4 preserves cerebrovasculature and prevents cognitive decline late after stroke

Infarct-induced neurodegeneration occurs chronically after stroke, doubling the risk of dementia. Endothelial vascular cell adhesion molecule 1 (VCAM1) facilitates blood-brain barrier opening and immune cell diapedesis by binding very late antigen 4 (VLA4) on immune cells. We hypothesized that vascular dysfunction persists after stroke and contributes to chronic neuroinflammation and cognitive decline via signaling through the VLA4/VCAM1 axis. We used adult (3-5 month old) and middle-aged (10 month old) C57BL/6J male & female mice and a permanent middle cerebral artery occlusion stroke model. Sham surgery consisted of an identical procedure without occlusion of the artery. We quantified vascular integrity using blood vessel length, pericyte coverage of vasculature, tight junctions, and extravascular fibrinogen leakage by immunostaining. Cognitive testing was performed using both Barnes maze and novel object recognition prior to stroke, and 1 and 6 weeks after stroke, and replicated in both male and female mice. We utilized anti-VCAM1, anti-VLA4 or isotype control antibodies to block VCAM1 or VLA4 function, and then to confirm mechanisms we utilized single cell RNA sequencing on immune and endothelial cells, aptamer-based plasma proteomics, and additional immunostaining for vascular integrity. Mouse brains exhibited signs of persistent vascular dysfunction and loss of blood-brain barrier integrity at 8 weeks after stroke, compared to sham animals. We observed reduced ZO-1 tight junction and pericyte coverage of vasculature, and increased extravascular fibrinogen. Mice with stroke also developed a cognitive deficit in both Barnes maze and novel object by 6 weeks. Treatment with anti-VCAM1 or anti-VLA4 resulted in mice with stroke performing as well as sham mice treated with isotype control antibody on both the Barnes maze and novel object recognition tasks. Anti-VCAM1 and anti-VLA4 both increased expression of blood-brain barrier maintenance genes in brain endothelial cells, while only minimally altering immune cell gene expression. Immune cell infiltration was reduced by anti-VCAM1 but not anti-VLA4 in tissue sections. In contrast to this, both antibodies increased blood vessel length and pericyte vascular coverage. Finally, extravascular fibrinogen was reduced by both antibody treatments in multiple brain regions. Together, our findings establish the VLA4/VCAM1 axis as a promising target to preserve vascular integrity and prevent cognitive decline late after stroke. Our data is consistent with a model where blocking either VCAM1 or VLA4 chronically after stroke promotes new blood vessel growth and maturation and restores the blood-brain barrier to prevent infarct-induced neurodegeneration.

neuroscience↗

bioRxiv2024

An immune signature of postoperative cognitive decline in elderly patients

Postoperative cognitive decline (POCD) is the predominant complication affecting elderly patients following major surgery, yet its prediction and prevention remain challenging. Understanding biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This longitudinal study involving 26 elderly patients undergoing orthopedic surgery aimed to characterize the impact of peripheral immune cell responses to surgical trauma on POCD. Trajectory analyses of single-cell mass cytometry data highlighted early JAK/STAT signaling exacerbation and diminished MyD88 signaling post-surgery in patients who developed POCD. Further analyses integrating single-cell and plasma proteomic data collected before surgery with clinical variables yielded a sparse predictive model that accurately identified patients who would develop POCD (AUC = 0.80). The resulting POCD immune signature included one plasma protein and ten immune cell features, offering a concise list of biomarker candidates for developing point-of-care prognostic tests to personalize perioperative management of at-risk patients. The code and the data are documented and available at https://github.com/gregbellan/POCD. TeaserModeling immune cell responses and plasma proteomic data predicts postoperative cognitive decline.

neuroscience↗

bioRxiv2024

Single-Cell Peripheral Immunoprofiling of Lewy Body Disease in a Multi-site Cohort

Studies implicated peripheral organs involvement in the development of Lewy body disease (LBD), a spectrum of neurodegenerative diagnoses that include Parkinsons Disease (PD) without or with dementia (PDD) and dementia with Lewy bodies (DLB). This study characterized peripheral immune responses unique to LBD at single-cell resolution. Peripheral mononuclear cell (PBMC) samples were collected from sites across the U.S. The diagnosis groups comprise healthy controls (HC, n=164), LBD (n=132), Alzheimers disease dementia (ADD, n=98), other neurodegenerative disease controls (NDC, n=21), and immune disease controls (IDC, n=14). PBMCs were activated with three stimulants, stained by surface and intracellular signal markers, and analyzed by flow cytometry, generating 1,184 immune features. Our model classified LBD from HC with an AUROC of 0.90{+/-}0.06. The same model distinguished LBD from ADD, NDC, IDC, or other common conditions associated with LBD. Model predictions were driven by pPLC{gamma}2, p38, and pSTAT5 signals from specific cell populations and activations.

neuroscience↗

bioRxiv2021

Single-synapse analyses of Alzheimers disease implicate pathologic tau, DJ1, CD47, and ApoE

Synaptic molecular characterization is limited for Alzheimers disease (AD). We used mass cytometry to quantify 38 probes in approximately 17 million single synaptic events from human brains without pathologic change or with pure AD or Lewy body disease (LBD), non-human primates (NHP), and PS/APP mice. Synaptic molecular integrity in humans and NHP was similar. Although not detected in human synapses, A{beta} was in PS/APP mice synaptic events. Clustering and pattern identification of human synapses showed expected disease-specific differences, like increased hippocampal pathologic tau in AD and reduced caudate dopamine transporter in LBD, and revealed novel findings including increased hippocampal CD47 and lowered DJ1 in AD and higher ApoE in AD dementia. Our results were independently supported by multiplex ion beam imaging of intact tissue.

neuroscience↗

bioRxiv2021

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-{kappa}B immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression. SummaryFeyaerts et al. demonstrate that an integrated analysis of plasma and single-cell proteomics differentiates COVID-19 severity and reveals severity-specific biological signatures associated with the dysregulation of the JAK/STAT, MAPK/mTOR, and NF-{kappa}B immune signaling networks and the mobilization of the renin-angiotensin and hemostasis systems.

immunology↗

bioRxiv2020

Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models of PTB. We found that whole blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r=0.83), as well as the delivery date in normal pregnancies (r=0.86), with an accuracy comparable to ultrasound. However, unlike the latter, transcriptomic data collected at <37 weeks of gestation predicted the delivery date of one third of spontaneous (sPTB) cases within 2 weeks of the actual date. Based on samples collected before 33 weeks in asymptomatic women we found expression changes preceding preterm prelabor rupture of the membranes that were consistent across time points and cohorts, involving, among others, leukocyte-mediated immunity. Plasma proteomic random forests predicted sPTB with higher accuracy and earlier in pregnancy than whole blood transcriptomic models (e.g. AUROC=0.76 vs. AUROC=0.6 at 27-33 weeks of gestation).

bioinformatics↗

bioRxiv2020

Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive Power

The dense network of interconnected cellular signaling responses quantifiable in peripheral immune cells provide a wealth of actionable immunological insights. While high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, limited cohort size together with the high dimensionality of data increases the possibility of false positive discoveries and model overfitting. We introduce a machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive power even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictive power for clinically-relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset.

bioinformatics↗