Biology subjects

Ai, J.

Publications and source records attributed to Ai, J..

17 recordsLinked to original sources

bioRxiv2026

A genome-scale ORF screen for resilience factors that protect the RPE and restore vision in aged mice

Aging is a complex phenomenon, yet therapeutic discovery has largely relied on testing individual hypothesis-driven targets. Here, we performed a genome-scale open reading frame (ORF) screen for oxidative-stress resistance in retinal pigment epithelium (RPE) cells, which are vulnerable to oxidative damage during aging. The screen identified nine protective ORFs including antioxidant factors and an epithelial-to-mesenchymal transition regulator. Notably, we also identified three factors that reduce transcriptomic age including the cardiac transcription factor NKX2-5. NKX2-5 conferred robust oxidative resilience in vitro and in vivo. Domain dissection revealed that its homeodomain is dispensable for resilience, enabling development of NKX2-5{Delta}HD, which retained protective activity without detectable toxicity over 14 months. In middle-aged mice, subretinal NKX2-5{Delta}HD restored visual and electrophysiological function, and its systemic delivery improved grip strength and reduced frailty in late-aged mice. These findings highlight the value of unbiased, genome-scale gain-of-function screening, as resilience factors normally expressed in other contexts can be reengineered as potential therapeutics for age-related decline in other tissues.

genetics↗

bioRxiv2026

Spatially Distinct Macrophage Subsets Drive Myofibroblast Heterogeneity and Maladaptive Fibrosis in Lupus Nephritis

ObjectivesLupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE), leading to progressive renal fibrosis and functional decline. Understanding the interplay between immune cells and stromal cells is needed to develop effective therapeutic strategies. Here, we investigated the landscape of macrophage-fibroblast interactions in human LN and validated these findings in mouse models. MethodsWe characterized distinct fibroblast subsets and their interactions with renal macrophages using single-cell RNA sequencing (scRNAseq) of 156 human LN biopsies and 30 healthy controls from the AMP-SLE cohort, and spatial transcriptomics of biopsies from 6 LN patients. In vitro co-culture studies using mouse models were performed to further define functional consequences of these interactions. ResultsWe identified two myofibroblast subsets: a pro-inflammatory subset (Myofib1) enriched in the tubulointerstitium, and a fibrotic/remodeling subset (Myofib2) in glomeruli, both correlating with the histologic chronicity index. Spatial transcriptomics revealed different colocalization patterns, with Myofib1 interacting with activated resident macrophage (RM) subsets and Myofib2 with glomerular infiltrating disease-associated macrophages. In vitro co-culture studies demonstrated that nephritic RMs promote a pro-inflammatory, remodeling fibroblast phenotype that impairs wound healing and drives a Myofib1-like gene program, whereas disease-associated macrophages generated profibrotic fibroblasts with dysregulated reparative capacity. Cell-cell communication analyses identified key ligand-receptor interactions mediating this crosstalk, including Spp1/integrins, Sema4/PlexinB, and NAMPT/INSR. ConclusionsOur data reveal a spatially and functionally heterogeneous landscape of macrophage-fibroblast crosstalk in LN. These findings advance our understanding of renal fibrogenesis in LN, highlighting specific fibro-inflammatory circuits that may represent therapeutic targets to prevent chronic renal damage.

immunology↗

bioRxiv2026

High-dimensional spatial proteomics and novel machine learning pipeline identifies disease specific renal damage states

Lupus nephritis (LuN) and renal allograft rejection (RAR) manifest inflammation and fibrosis that ultimately lead to kidney failure. To quantitatively assess spatial injury patterns, we collected high dimensional spatial proteomics data from 23 LuN, 33 RAR, and 8 kidney control (KC) biopsies. We developed a computational pipeline to segment and classify tubules, capillaries, and glomeruli in whole-slide images using three trained neural networks (Renal Damage diagnosis, RDDx). RDDx achieved high accuracy and generalizability, reliably identifying small capillaries and differentiating tubular and vascular inflammation in kidney tissues. Both LuN and RAR showed reduced tubular and capillary areas with expanded interstitial space. LuN displayed patchy clusters of stressed and inflamed tubules, whereas RAR exhibited diffuse injury. Within RAR, T cell-mediated rejection (TCMR) showed intense tubulitis while antibody-mediated rejection (ABMR) featured proliferating and inflamed capillaries near atrophic tubules. RDDx quantitative metric outputs correlated with histopathological scores, highlighting their reproducibility and clinical relevance. Stressed tubules in mildly inflamed LuN biopsies suggested they were a sensitive injury marker, while proliferating capillaries revealed microvascular remodeling in ABMR. These findings indicated RDDx can identify and quantify damage mechanisms specific to each renal disease thus facilitating future mechanistic studies and therapeutic target discovery.

immunology↗

bioRxiv2025

Transplantation of active mitochondria condensed in liquid-liquid phase-separated hydrogels ameliorates myocardial ischemia-reperfusion injury

Mitochondrial dysfunction is a key driver of myocardial ischemia-reperfusion injury (MIRI), which exacerbates cardiac damage following the restoration of blood flow. Although single-phase hydrogel-based mitochondria transplantation therapy (MTT) holds promise for restoring cellular energy metabolism, its effectiveness is limited by extracellular calcium-induced mitochondrial degradation. In this study, we design a thermo-sensitive hydrogel utilizing liquid-liquid phase separation (LLPS), composed of gelatin and polyethylene glycol (PEG), to condense freshly isolated mitochondria. Compared to conventional single-phase hydrogels, the LLPS hydrogel significantly increases the sol-gel transition temperature above physiological levels, allowing it to remain injectable at body temperature while enabling rapid mitochondrial release following transplantation. More importantly, the LLPS structure enhances mitochondrial packing density and protects the activity of condensed mitochondria against calcium toxicity through spatial confinement and gelatin-mediated calcium chelation. In vitro, LLPS hydrogel-condensed mitochondria exhibit improved mitochondrial membrane potential and ATP production ability compared to those delivered via single-phase gelatin hydrogel. In vivo, mitochondria released from the LLPS hydrogel are effectively internalized by cardiomyocytes, resulting in improved cardiac function and reduced tissue damage after MIRI. These findings suggest that LLPS-based hydrogels offer a promising strategy to enhance MTT efficacy for MIRI and other mitochondria-related disorders.

bioengineering↗

bioRxiv2025

Reprogramming Factors Activate a Non-Canonical Oxidative Resilience Pathway That Can Rejuvenate RPEs and Restore Vision

Oct4, Sox2, and Klf4 (OSK) Yamanaka factors induce pluripotency and reverse age-related epigenetic changes, yet the mechanisms by which they promote rejuvenation remain poorly explored. Oxidative stress contributes to CNS aging and retinal pigmented epithelium (RPE) degeneration in age-related macular degeneration. We find that OSK expression in RPE restores retinal structure and visual function in aged mice and promotes oxidative resilience through a non-canonical, Tet2-independent pathway. Integrative functional genomics identifies GSTA4, a detoxifying enzyme that clears the lipid peroxidation byproduct 4-HNE, as a necessary and sufficient OSK effector. Dynamic GSTA4 regulation by OSK recapitulates a stem cell derived stress resilience program. GSTA4 overexpression alone enhances mitochondrial resilience, rejuvenates the aged RPE transcriptome, and reverses visual decline. GSTA4 is consistently upregulated across diverse lifespan-extending interventions suggesting a broader pro-longevity role. These findings uncover a previously unrecognized protective axis driven by Yamanaka factors that circumvents reprogramming, providing therapeutic insights for age-related diseases. HIGHLIGHTSO_LIOSK-GSTA4 provides a dynamic, Tet2-independent stress-resilience axis. C_LIO_LIFunctional genomics pinpoints GSTA4 as a direct downstream effector activated by OSK. C_LIO_LIRPE aging involves progressive accumulation of 4-HNE that can be detoxified by GSTA4. C_LIO_LIEnhancing GSTA4 rejuvenates RPE cells, restores vision and is associated with lifespan-extending interventions. C_LI

genetics↗

bioRxiv2025

Resolution of in situ inflammation in human lupus nephritis into principal immune cell trajectories

In human lupus nephritis (LuN), tubulointerstitial inflammation (TII) is prognostically more important than glomerular inflammation. However, a comprehensive understanding of both TII complexity and heterogeneity is lacking. Herein, we used high-dimensional confocal microscopy and specialized computer vision techniques to quantify immune cell populations and localize these within normal and diseased renal cortex structures. With these tools, we compared LuN to renal allograft rejection (RAR) and normal kidney. In both LuN and RAR, the 33 characterized immune cell populations formed discrete subgroups whose constituents co-varied in prevalence across biopsies. In both diseases, these co-variant immune cell subgroups organized into the same unique niches. Therefore, inflammation could be resolved into trajectories representing the relative prevalence and density of cardinal immune cell members of each co-variant subgroup. Indeed, in any one biopsy, the inflammatory state could be characterized by quantifying constituent immune cell trajectories. Remarkably, LuN heterogeneity could be captured by quantifying a few myeloid immune cell trajectories while RAR was more complex with additional T cell trajectories. Our studies identify rules governing renal inflammation and thus provide an approach for resolving LuN into discrete mechanistic categories. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/638655v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@109dd33org.highwire.dtl.DTLVardef@995037org.highwire.dtl.DTLVardef@161525dorg.highwire.dtl.DTLVardef@6692d8_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

immunology↗

bioRxiv2025

c-Rel drives pancreatic cancer metastasis through Fibronectin-Integrin signaling-induced isolation stress resistance and EMT activation

Pancreatic ductal adenocarcinoma remains one of the deadliest malignancies, with limited treatment options and a high recurrence rate. Recurrence happens often with metastasis, for which cancer cells must adapt to isolation stress to successfully colonize distant organs. While the fibronectin-integrin axis has been implicated in this adaptation, its regulatory mechanisms require further elaboration. Here, we identify c-Rel as an oncogenic driver in PDAC, promoting epithelial-to-mesenchymal transition (EMT) plasticity, extracellular matrix (ECM) remodeling, and resistance to isolation stress. Mechanistically, c-Rel directly regulates fibronectin (Fn1) and CD61 (itgb3) transcription, enhancing cellular plasticity and survival under anchorage-independent conditions. Fibronectin is not essential for EMT, but its absence significantly impairs metastatic colonization, highlighting a tumor-autonomous role for FN1 in isolation stress adaptation. These findings establish c-Rel as a key regulator of PDAC metastasis by controlling circulating tumor cell (CTC) niche and survival, suggesting that targeting the c-Rel-fibronectin-integrin axis could provide new therapeutic strategies to mitigate disease progression and recurrence.

cancer biology↗

bioRxiv2024

Cardiac Reprogramming with Drug Resistance Alleviates Doxorubicin-induced Cardiotoxicity in Mice and Pigs

Doxorubicin (Dox)-induced cardiotoxicity represents a significant clinical adverse effect associated with cancer chemotherapy treatment. The systematic toxicity associated with the currently available drug dexrazoxane has limited its clinical utility. Inspired by cancer drug resistance mechanisms, we propose a novel strategy termed Transient overexpression of p-glycoprotein (P-gp) for Cardiac reprogramming (TopCare) to induce cardiac drug resistance as a treatment for cardiotoxicity. This approach involves reprogramming cardiomyocytes by delivering lipid nanoparticles (LNPs)-based mRNA therapeutics to induce temporary P-gp overexpression, which in turn reduces intracellular Dox levels and suppresses cytotoxic effects. Our results demonstrated that LNPs with P-gp mRNAs (P-gp LNPs) enhance P-gp expression in H9c2 cells, significantly lowering the cytotoxicity of both Dox and paclitaxel (PTX). In a mouse model with Dox-induced cardiotoxicity, it was observed that P-gp LNPs effectively promoted P-gp overexpression in cardiomyocytes, with a time-dependent decline in P-gp protein levels. This TopCare strategy resulted in improved survival rates, restored cardiac function, and reduced myocardial fibrosis and structural cardiac alterations. Furthermore, studies in large animals have shown that intrapericardial (iPC) injection of P-gp LNPs effectively mitigates adverse effects and restores cardiac function in pig models of Dox-induced cardiotoxicity. The significant cardioprotective effects achieved through cardiac drug resistance highlight the safety, efficacy, and clinical potential of the TopCare strategy for alleviating doxorubicin-induced cardiotoxicity.

bioengineering↗

bioRxiv2024

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses significant challenges to the effective diagnosis and treatment of ccRCC. To address this problem, we propose a deep reinforcement learning-based computational approach named RL-GenRisk to identify ccRCC risk genes. Distinct from traditional supervised models, RL-GenRisk frames the identification of ccRCC risk genes as a Markov decision process, combining the graph convolutional network and Deep Q-Network for risk gene identification. Moreover, a well-designed data-driven reward is proposed for mitigating the lim-itation of scant known risk genes. The evaluation demonstrates that RL-GenRisk outperforms existing methods in ccRCC risk gene identification. Additionally, RL-GenRisk identifies ten novel ccRCC risk genes. We successfully validated epidermal growth factor receptor (EGFR), corroborated through independent datasets and biological experimentation. This approach may also be used for other diseases in the future.

bioinformatics↗

bioRxiv2024

BRWD1 establishes epigenetic states for germinal center initiation, maintenance, and function

Germinal center (GC) B cells segregate into three subsets that compartmentalize the antagonistic molecular programs of selection, proliferation, and somatic hypermutation. In bone marrow, the epigenetic reader BRWD1 orchestrates and insulates the sequential stages of cell proliferation and Igk recombination. We hypothesized BRWD1 might play similar insulative roles in the periphery. In Brwd1-/- follicular B cells, GC initiation and class switch recombination following immunization were inhibited. In contrast, in Brwd1-/- GC B cells there was admixing of chromatin accessibility across GC subsets and transcriptional dysregulation including induction of inflammatory pathways. This global molecular GC dysregulation was associated with specific defects in proliferation, affinity maturation, and tolerance. These data suggest that GC subset identity is required for some but not all GC-attributed functions. Furthermore, these data demonstrate a central role for BRWD1 in orchestrating epigenetic transitions at multiple steps along B cell developmental and activation pathways.

immunology↗

bioRxiv2024

Pseudo-spectral angle mapping for automated pixel-level analysis of highly multiplexed tissue image data

The rapid development of highly multiplexed microscopy systems has enabled the study of cells embedded within their native tissue, which is providing exciting insights into the spatial features of human disease [1]. However, computational methods for analyzing these high-content images are still emerging, and there is a need for more robust and generalizable tools for evaluating the cellular constituents and underlying stroma captured by high-plex imaging [2]. To address this need, we have adapted spectral angle mapping - an algorithm used widely in hyperspectral image analysis - to compress the channel dimension of high-plex immunofluorescence images. As many high-plex immunofluorescence imaging experiments probe unique sets of protein markers, existing cell and pixel classification models do not typically generalize well. Pseudospectral angle mapping (pSAM) uses reference pseudospectra - or pixel vectors - to assign each pixel in an image a similarity score to several cell class reference vectors, which are defined by each unique staining panel. Here, we demonstrate that the class maps provided by pSAM can directly provide insight into the prevalence of each class defined by reference pseudospectra. In a dataset of high-plex images of colon biopsies from patients with gut autoimmune conditions, sixteen pSAM class representation maps were combined with instance segmentation of cells to provide cell class predictions. Finally, pSAM detected a diverse set of structure and immune cells when applied to a novel dataset of kidney biopsies imaged with a 43-marker panel. In summary, pSAM provides a powerful and readily generalizable method for evaluating high-plex immunofluorescence image data. Significance StatementUnderstanding the cellular constituents captured by highly multiplexed tissue imaging is a major limitation affecting the usability of these novel imaging methods. Many imaging experiments have uniquely designed staining panels, reducing the generalizability of cell classification models to new datasets. We present pseudospectral angle mapping (pSAM), which can compress high-dimensional image data into class representations. We demonstrate that the class representations generated by pSAM can be used to interpret high-plex image data and guide cell classification. Importantly, we also demonstrate that pSAM can generalize to new image datasets--collected with a different staining panel in samples from different tissues--without manual image annotation, subjective intensity gating, or re-training an algorithm.

bioinformatics↗

bioRxiv2023

Neutralization of SARS-CoV-2 BQ.1.1 and XBB.1.5 by Breakthrough Infection Sera from Previous and Current Waves in China

SARS-CoV-2 is continuing to evolve and diversify, with an array of various Omicron sub-lineages, including BA.5, BA.2.75, BN.1, BF.7, BQ.1, BQ.1.1, XBB and XBB.1.5, now circulating globally at recent time. In this study, we evaluated the neutralization sensitivity of a comprehensive panel of Omicron subvariants to sera from different clinical cohorts, including individuals who received homologous or heterologous booster vaccinations, vaccinated people who had Delta or BA.2 breakthrough infection in previous waves, and patients who had BA.5 or BF.7 breakthrough infection in the current wave in China. All the Omicron subvariants exhibited substantial neutralization evasion, with BQ.1, BQ.1.1, XBB.1, and XBB.1.5 being the strongest escaped subvariants. Sera from Omicron breakthrough infection, especially the recent BA.5 or BF.7 breakthrough infection, exhibited higher neutralizing activity against all Omicron sub-lineages, indicating the chance of BA.5 and BF.7 being entirely replaced by BQ or XBB subvariants in China in a short-term might be low. We also demonstrated that the BQ and XBB subvariants were the most resistant viruses to monoclonal antibodies. Continuing to monitor the immune escape of SARS-CoV-2 emerging variants and developing novel broad-spectrum vaccines and antibodies are still crucial.

immunology↗

bioRxiv2022

Neutralization of Omicron BA.4/BA.5 and BA.2.75 by Booster Vaccination or BA.2 Breakthrough Infection Sera

Many new Omicron sub-lineages have been reported to evade neutralizing antibody response, including BA.2, BA.2.12.1, BA.4 and BA.5. Most recently, another emerging sub-lineage BA.2.75 has been reported in multiple countries. In this study, we constructed a comprehensive panel of pseudoviruses (PsVs), including wild-type, Delta, BA.1, BA.1.1, BA.2, BA.3, BA.2.3.1, BA.2.10.1, BA.2.12.1, BA.2.13, BA.2.75 and BA.4/BA.5, with accumulate coverage reached 91% according to the proportion of sequences deposited in GISAID database since Jan 1st, 2022. We collected serum samples from healthy adults at day14 post homologous booster with BBIBP-CorV, or heterologous booster with ZF2001, primed with two doses of BBIBP-CorV, or from convalescents immunized with three-dose inactivated vaccines prior to infection with Omicron BA.2, and tested their neutralization activity on this panel of PsVs. Our results demonstrated that all Omicron sub-lineages showed substantial evasion of neutralizing antibodies induced by vaccination and infection, although BA.2.75 accumulated the largest number of mutations in its spike, BA.4 and BA.5 showed the strongest serum escape. However, BA.2 breakthrough infection could remarkably elevated neutralization titers against all different variants, especially titers against BA.2 and its derivative sub-lineages.

immunology↗

bioRxiv2022

Antibody Resistance of SARS-CoV-2 Omicron BA.1, BA.1.1, BA.2 and BA.3 Sub-lineages

The SARS-CoV-2 Omicron variant has been partitioned into four sub-lineages designated BA.1, BA.1.1, BA.2 and BA.3, with BA.2 becoming dominant worldwide recently by outcompeting BA.1 and BA.1.1. We and others have reported the striking antibody evasion of BA.1 and BA.2, but side-by-side comparison of susceptibility of all the major Omicron sub-lineages to vaccine-elicited or monoclonal antibody (mAb)-mediated neutralization are urgently needed. Using VSV-based pseudovirus, we found that sera from individuals vaccinated by two doses of inactivated whole-virion vaccines (BBIBP-CorV) showed very weak to no neutralization activity, while a homologous inactivated vaccine booster or a heterologous booster with protein subunit vaccine (ZF2001) markedly improved the neutralization titers against all Omicron variants. The comparison between sub-lineages indicated that BA.1.1, BA.2 and BA.3 had comparable or even greater antibody resistance than BA.1. We further evaluated the neutralization profile of a panel of 20 mAbs, including 10 already authorized or approved, against these Omicron sub-lineages as well as viruses with different Omicron spike single or combined mutations. Most mAbs lost their neutralizing activity completely or substantially, while some demonstrated distinct neutralization patterns among Omicron sub-lineages, reflecting their antigenic difference. Taken together, our results suggest all four Omicron sub-lineages threaten the efficacies of current vaccines and antibody therapeutics, highlighting the importance of vaccine boosters to combat the emerging SARS-CoV-2 variants.

microbiology↗

bioRxiv2021

In lupus nephritis, specific in situ inflammatory states are associated with refractory disease and progression to renal failure

In human lupus nephritis (LN), tubulointerstitial inflammation (TII) on biopsy predicts progression to end stage renal disease (ESRD). However, while approximately half of patients with moderate or severe TII develop ESRD, half do not. Therefore, we hypothesized that TII is heterogeneous, with distinct inflammatory states associated with different renal outcomes. We interrogated renal biopsies from LN longitudinal and cross-sectional cohorts using both conventional and highly multiplexed confocal microscopy. To accurately segment cells across whole biopsies, and to understand their spatial relationships, we developed unique computational pipelines by training and implementing several deep learning models and other computer vision techniques. Surprisingly, across biopsies, high B cell densities were strongly associated with protection from ESRD. In contrast, elevated CD4-T cell population densities, which included CD8, {gamma}{delta} and double negative (CD4-CD8-{delta}-, DN) T cells, were associated with both acute refractory renal failure and gradual progression to ESRD. Interestingly, lymphocytes and dendritic cells were organized into discrete clusters or neighborhoods that could be characterized by the enrichment for specific cell populations. B cells were often organized into large neighborhoods with CD4+ T cells including T follicular helper-like cells. In contrast, the CD4-T cell populations formed small cellular neighborhoods whose frequency predicted subsequent progression to ESRD. These data reveal that in LN, specific in situ inflammatory states are associated with refractory disease and progression to ESRD. One sentence summaryUsing deep machine learning to analyze confocal microscopy data, we demonstrate that in lupus nephritis, CD4-T cell populations, including CD8+ and {gamma}{delta} T cells, organize into specific spatial neighborhoods that predict progression to renal failure.

immunology↗

bioRxiv2020

Extravagant leaf display in Actinidia kolomikta attracting pollinators and maintaining photosynthetic capacity

Pollinators usually are attracted by flower displays, but whether non-green leaves display can function as a flower guide is less well studied. Furthermore, it is still largely unknown whether photosynthetic cost is paid-off by benefits afforded by attraction pollinators and how non-green leaves maintain photosynthetic capacity. Thus, white leaf and inflorescence/flower traits, pollinator visitation, fruit set and seed production, spectral properties, leaf structure, net photosynthetic rate and chlorophyll fluorescence of adaxial and abaxial surface were studied in Actinidia kolomikta (Rupr. & Maxim.) Maxim. The reproductive branches of A. kolomikta have a large number of white leaves at the exterior canopy, but white inflorescences grow at the canopys interior, and we found that showy display of white leaves attracted pollinators reach the flowers. Although incident light was reflected largely, we found that photosynthetic rate of white leaves was maintained at relatively high levels. Furtherly, spongy tissue play the vital role in maintenance photosynthetic capacity of white leaves, which effectively supports inflorescence development during flowering. Thus, white leaves of A. kolomikta enhanced reproductive fitness through attracting pollinators and decreasing reproductive cost: (1) spatially via white leaves locating at reproductive branches and temporally via synchronism between white leaves and flowers; (2) increasing white leaves display and decreasing investment in reproduction; (3) compensatory mechanisms via maintaining photosynthetic capacity of white leaves. Therefore, we propose that these dual functions of white leaves during blossom lower the plants cost of reproduction, and that this is an adaptation to the climatic challenges of the high altitudes and latitudes at which it grows.

plant biology↗

bioRxiv2019

Cross Trial Meta and Time Series Pharmacodynamic Analyses of Apremilast Effects

Finding biomarkers that provide shared link between disease severity, drug-induced pharmacodynamic effects and response status in human trials can provide number of values for patient benefits: elucidating current therapeutic mechanism-of-action, and, back-translating to fast-track development of next-generation therapeutics. Both opportunities are predicated on proactive generation of human molecular profiles that capture longitudinal trajectories before and after pharmacological intervention. Here, we present the largest plasma proteomic biomarker dataset available to-date and the corresponding analyses from placebo-controlled Phase III clinical trials of the phosphodiesterase type 4 inhibitor apremilast in psoriasis (PSOR), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) from 526 subjects overall. Using approximately 150 plasma analytes tracked across three time points, we identified IL-17A and KLK-7 as biomarkers for disease severity and apremilast pharmacodynamic effect in psoriasis patients. Combined decline rate of KLK-7, PEDF, MDC and ANGPTL4 by Week 16 represented biomarkers for the responder subgroup, shedding insights into therapeutic mechanisms. In ankylosing spondylitis patients, IL-6 and LRG-1 were identified as biomarkers with concordance to disease severity. Apremilast-induced LRG-1 increase was consistent with the overall lack of efficacy in ankylosing spondylitis. Taken together, these findings expanded the mechanistic knowledge base of apremilast and provided translational foundations to accelerate future efforts including compound differentiation, combination, and repurposing.

bioinformatics↗