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Sun, R.

Publications and source records attributed to Sun, R..

At least 37 records · Page 2Linked to original sources

PKU tags, novel genetically encoded shape tags for cell labeling in light and electron microscopy

Distinguishing among neuronal cell types is crucial for deciphering complex neural networks and brain functions. However, the current repertoire of cell-labeling tools compatible with light microscopy (LM) and/or electron microscopy (EM) is limited compared to the vast number of cell types in the brain. Here, we introduce PKU (polymer king-size unit) tags, genetically encoded "shape tags" that leverage the polymerization of self-assembling proteins, spectrally distinct fluorescent proteins and, optionally, a nuclear targeting sequence to generate a series of multi-shaped (spherical or filamentous), multi-colored (blue, green, red, near-infrared) and multi-localized (cytosolic or nuclear) tags. By co-expressing multiple PKU tags within the same cell, a combinatorial strategy further expands the repertoire, which can theoretically yield hundreds of unique labeling patterns. Expressing PKU tags in vivo provides multi-cell-type labeling and neuronal circuit tracing, without altering the animals behavior or transcriptomic profiles. Moreover, when fused to the peroxidase APEX2, PKU tags maintain their shape-specific features, providing shape "barcoding" using EM. Thus, PKU tags represent a versatile and efficient toolkit for studying connectomics using both LM and EM.

neuroscience↗

Fragment-Based Development of NSP14 Exonuclease Inhibitors Confounded by Batch-to-Batch Variability

Point mutations in the exonuclease (ExoN) site of non-structural protein 14 (NSP14) compromise the fitness of betacoronaviruses like SARS-CoV-2, implicating NSP14 ExoN inhibition as an antiviral strategy. However, there are no advanced compounds that inhibit NSP14s ExoN activity. Building upon the reported crystal structures of two fragments bound to NSP14s ExoN site, we identified a series of 3,5-disubsituted pyrazoles that bound to and inhibited NSP14 ExoN. However, upon resynthesis, we discovered that these putative leads were false positives, perhaps due to contaminating divalent cations which potently inhibit NSP14 ExoN. Our results provide a cautionary tale to the field about the sensitivity of NSP14 to divalent cations and illustrate the challenges associated with directly targeting the NSP14 ExoN site via fragment merging.

biochemistry↗

Studying macromolecular composition in cell-cell interfaces using 3D membrane reconstitution systems

During direct communication between two cells, the plasma membranes of each cell serve as a platform for ligand-receptor interaction initiating downstream signalling cascades. In immune cell signalling, this cell-cell interface - the immune synapse - is highly spatiotemporally organized. Multiple stimulatory and co-stimulatory signals need to be integrated over time to ensure proper immune cell function. This process is still not fully understood given the vast complexity of interactions between proteins, lipids, glycocalyx and associated cortical actin cytoskeleton. To examine the impact of a single component, the use of model membrane systems has increased. Here, we developed a fully artificial system to study the interface between two vesicles and a semi-artificial one between a live cell and a vesicle to reconstitute 3D contacts. We investigated the distribution and reorganization of immune cell proteins at artificial and semi-artificial contacts. Using our vesicle-vesicle system, we show the enrichment and depletion of different proteins in the synapse. Using the cell-vesicle system we showed how different peptides with varying affinity presented by the same MHC class I affect T cell activation. We further explored the distribution of glycocalyx elements at the cell-cell contact and showed differential partitioning of different sugar moieties in the interface. While we focused on the T cell interface here, our model systems are powerful tools to study distribution and reorganization of lipids, proteins and glycocalyx components at any cell-cell contact.

biophysics↗

Pan-cancer analysis reveals that tumor microbiomes generate specific epitopes through transcriptional reprogramming

The therapeutic promise of tumor microbial peptides faces a critical safety paradox: tumors and peritumor tissues harbor compositionally similar microbiomes, yet safe immunotherapy demands tumor-specific targeting. We performed comprehensive transcriptomic analysis of microbial communities from 1,868 tumor and peritumor samples across 11 cancer types. Although 88.5% of microbial species are present in both tissue types, tumor and peritumor tissues exhibit profound transcriptional divergence: only 34.1% of microbial genes are expressed in both tissue types, and merely 18.2% of predicted HLA-binding peptides overlap. This transcriptional divergence represents microbial transcriptional reprogramming (MTR) in tumor tissues, through which microbes activate distinct genomic regions while adapting to tumor microenvironmental pressures, thereby generating tumor-specific peptide repertoires. Using Microbial Transcriptional Reprogramming Index (MiTRI) to quantify MTR, we found that higher MiTRI values correlate with expanded immunogenic peptide repertoires. Mass spectrometry-based immunopeptidomics confirmed that 25% of naturally presented microbial peptides originate from MTR regions. Crucially, in microsatellite-stable colorectal cancer, neo-adjuvant therapy responders exhibited significantly higher MiTRI values. T cell receptors (TCRs) recognized MTR-derived epitopes at 2.10-fold higher rates than genome-wide epitopes, accounting for 79.1% of clonally expanded TCRs. These findings establish MTR as the principle that ensures the tumor-specificity and safety of micorbiome-directed immunotherapy.

cancer biology↗

Auditory Stimulus Information Entropy Modulates Inter-Brain Synchronization: Evidence from Wireless EEG Hyperscanning

Inter-brain synchronization (IBS) - reflecting inter-individual correlated neural activity during interaction - marks shared experiences like music listening. The ability of complex auditory stimuli (e.g., music) to induce IBS links to their information dynamics, notably the uncertainty they evoke, which challenges the nervous systems predictive coding. Based on mutual prediction theory (interacting individuals simultaneously process their own behavior and predict their partners; accurate mutual predictions lead to convergent neural representations and thus IBS), this study hypothesized that higher stimulus uncertainty enhances IBS (heightened uncertainty reduces independent predictability, promoting convergent representations and stronger IBS). Using information entropy to quantify uncertainty, the study conducted hyperscanning, manipulated entropy across Resting State and 6 Hz auditory stimuli (ASSR, MMN, AHER, Dream Wedding), and measured IBS via phase-locking values (PLV). Results showed frequency specificity: 6 Hz PLV increased with entropy (DW {approx} AHER > MMN {approx} ASSR > Resting State); Alpha band had highest PLV in Resting State. Critically, PLVs differed significantly between any two conditions, and each experimental conditions PLV was also significantly different from that of the Resting State. Findings confirm a 6 Hz-specific positive association between auditory uncertainty and IBS, suggesting musical elements may facilitate social interaction by modulating entropy, with entropy-IBS relations showing frequency dependence.

neuroscience↗

Host Phosphatase PPM1G Governs Influenza vRNP Homeostasis by Orchestrating NP Phosphorylation Dynamics and Autophagy

The influenza viral ribonucleoprotein (vRNP) serves as the machinery for viral RNA replication. It self - assembles from the RNA - dependent RNA polymerase (RdRp), viral RNA, and nucleoprotein (NP). During vRNP replication, NP proteins must rapidly switch between monomeric and polymeric states to sustain dynamic equilibrium, which relies on NP phosphorylation-dephosphorylation cycling and is crucial for viral nucleic acid replication. However, the regulatory mechanisms controlling this process remain poorly understood. In this study, we employed an RdRp/vRNP-targeted affinity mass spectrometry-based differential analysis method, discovered that the cellular protein phosphatase Mg2+/Mn2+-dependent 1G (PPM1G) is a phosphatase of NP and required for maintaining viral polymerase activity. Overexpression of PPM1G decreased viral replication. In ppm1g flox/flox-Sftpc Cre mice, lethal influenza infection led to survival and mild disease, as well as reduced lung viral loads and inflammation. These results suggest that PPM1G is a key host molecule for maintaining steady state of viral replication. PPM1G expression is upregulated upon influenza virus infection. This heightened expression occurs in response to increased viral protein production, simultaneously leading to elevated dephosphorylation of NP, which accelerates NP polymerization to promote viral replication. Meanwhile, surplus NP can be degraded through the ATG7 autophagylysosome pathway. Our research elucidates a mechanism that PPM1G maintains viral replication homeostasis by regulating NP status and fate.

microbiology↗

Establishment of a Systemic Lupus Erythematosus Mouse Model in Humanized CD3/CD19 Mice and Evaluation of the Efficacy of a Human Bispecific Antibody

Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease affecting multiple organ systems and is considered one of the most severe autoimmune diseases worldwide, significantly impacting womens health. B cells play a crucial role in disease pathogenesis by becoming abnormally activated and producing autoantibodies that attack the bodys normal tissues, leading to inflammation and organ damage. Therefore, targeting the human B cell receptor has emerged as a promising strategy for therapeutic intervention. In this study, we established an SLE animal model using double-humanized CD3/CD19 mice, in which human CD3 and CD19 genes replaced their murine counterparts. The phenotype was confirmed by ELISA and flow cytometry. hCD3/hCD19 mice induced by a combination of pristine x 2, imiquimod (IMQ) and nephrectomy exhibited several key features of SLE, including anti-dsDNA antibody production, proteinuria, increased immune cell populations, and kidney lesions. Furthermore, treatment of these humanized mice with anti-human CD3/CD19 bispecific antibodies significantly inhibited these pathological indicators. Thus, pristine x 2, IMQ and nephrectomy induced hCD3/hCD19 mice provide a validated preclinical model for investigating novel therapeutic agents targeting B cells in SLE. Graphical abstractThis study explores the effects of different modeling strategies on agent induction, with a particular emphasis on the link between the induced agents and their corresponding clinical manifestations. Through an extensive literature review and experimental validation, a novel approach for inducing systemic lupus erythematosus (SLE) has been established. By employing gene editing techniques, mouse CD3 and CD19 antibody recognition sites were substituted with their human equivalents. This humanized mouse model enables the direct assessment of humanized bispecific antibodies in the context of SLE induction. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/668572v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@652c83org.highwire.dtl.DTLVardef@4d6233org.highwire.dtl.DTLVardef@6a2f8forg.highwire.dtl.DTLVardef@1587652_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Large Impact of Genetic Data Processing Steps on Stability and Reproducibility of Set-Based Analyses in Genome-Wide Association Studies

Genome-wide association studies (GWAS) are crucial to human genetics research, yet their stability and reproducibility are often questioned. This work describes, analyzes, and provides tools for overcoming reproducibility challenges in two highly popular components of GWAS: set-based (a) hypothesis testing and (b) effect size estimation. Specifically, we focus on how the set-based natures of (a) and (b) often fuel non-reproducible results due to differences in data processing pipelines that are rarely discussed. First, we describe the processing challenges in a statistical model misspecification framework. Second, we analytically calculate the differences in power and amounts of bias that can arise in (a) and (b), respectively, due to small data processing choices. Third, we provide tools for quantifying and avoiding the data processing obstacles in GWAS. We validate our analytical calculations through a simulation study, and we demonstrate the aforementioned challenges empirically through analysis of a whole-exome sequencing study of pancreatic cancer. Author SummaryThe lack of reproducibility and stability in genome-wide association studies (GWAS) have been widely reported. Here, we demonstrate how such reproducibility challenges arise in a common component of GWAS, set-based hypothesis testing and estimation studies. Specifically, we show how minor, seemingly harmless decisions in how scientists prepare their data can lead to major differences in the final conclusions. These data processing steps are rarely reported in detail, further obscuring their importance. Our work precisely measures the impact of data processing steps on power and bias of common modeling approaches. As a partial solution for future GWAS, we also provide an R software package to interact with our results, which can be used to assess the impact of choices at the design stage of GWAS studies. We further analyze a pancreatic cancer dataset using two modern pipelines and show how the pipelines produce very different results for ATM, a gene that has been previously linked with pancreatic cancer. Using the tools provided by this work can help significantly improve the reproducibility and stability of set-based results, enhancing the translational potential of GWAS investigations.

genetics↗

Cerebellum metastasis model of HER2-positive breast cancer unveils key role of IL34-induced Arg1+ macrophages.

Brain metastases occur in up to 40% of Stage IV breast cancer patients. The cerebellum is a frequent location for metastases in HER2-positive breast cancer patients, but the mechanisms for this are unknown. Here, we developed a syngeneic, immunocompetent mouse model for breast cancer brain metastases by stereotactically injecting mouse HER2-overexpressing breast cancer organoids into the cerebellum. Growth of these cerebellar metastases was monitored by MRI and trastuzumab optical imaging using a near-infrared fluorophore conjugated to trastuzumab. Spatial transcriptomics identified interleukin-34 production by breast cancer cells inducing ARG1+ macrophages at the invading edge of the metastasis. Treatment with a blocking antibody to interleukin-34s receptor, CSF1R, produced tumor shrinkage. These findings have immediate translation potential as a CSF1R-blocking antibody is FDA-approved. Further, it demonstrates that cancer-associated inflammation bordering the brain metastasis promotes metastatic growth and offers a molecularly targeted strategy to treat inflammation in brain metastasis. Graphical summary O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/660224v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@9f1a50org.highwire.dtl.DTLVardef@178acc5org.highwire.dtl.DTLVardef@196d803org.highwire.dtl.DTLVardef@3fe631_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

A continuous-time microparasite model incorporating infection intensity and parasite aggregation

Disease outcomes depend heavily on infection intensity which is often heterogeneous across and within host populations. Most individuals carry low pathogen loads and a few carry high loads, a pattern known as aggregation. While well-characterized in macroparasite systems, aggregation and infection intensity are rarely incorporated into microparasite models. This raises key questions: Do similar mechanisms underlie aggregation in macro- and microparasite systems? And how do aggregation and load-dependent effects shape outcomes such as host suppression and virulence-transmission trade-offs? To address these questions, we developed a novel continuous time microparasite model that allows the pathogen load distribution across hosts to evolve dynamically, shaped by within- and between-host processes. We applied this framework to the amphibian chytrid fungus system involving Batrachochytrium den-drobatidis (Bd), a fungal pathogen threatening amphibian populations worldwide. Our results show that load-dependent mortality reduces aggregation, while faster within-host replication increases it. Aggregation, in turn, weakens host suppression and flat-tens virulence-transmission trade-off, shifting peak transmission to higher replication rates. Overall, our continuous-time microparasite model provides new insights into how infection intensity and aggregation influence host-pathogen dynamics and offers a valuable framework for advancing theoretical and data-driven understanding of how within-host processes scale to population-level disease dynamics for microparasites.

ecology↗

A Radiomic Approach to Clinical MRI Refines the Thalamus-Cognition Link in Multiple Sclerosis

Background and ObjectivesRadiomics extracts imaging features that may not be detectable through conventional volumetric analyses. Given their role in multiple sclerosis (MS), we applied radiomics to thalamic nuclei and examined their associations with cognitive performance. MethodsA total of 601 individuals were included (342 people with MS-PwMS from two cohorts, and 259 healthy controls-HC). Radiomic features (RF) and volumes were extracted from the whole thalamus, five thalamic nuclei, and the putamen segmented on 3D T1-weighted images. Cognitive performance was assessed using the Symbol Digit Modalities Test (SDMT) and Paced Auditory Serial Addition Test (PASAT) in PwMS, and the Digit Symbol Substitution Test (DSST) in HC. In the first MS cohort, multivariate linear regression in a discovery set (N=103) identified thalamus-derived RF associated with SDMT, which were retested in a replication set (N=63). Their associations with PASAT in a second MS cohort (N=176) and DSST in HC were also evaluated. We then tested whether the same RF, when extracted from the putamen, were associated with SDMT. LASSO models assessed the combined predictive value of RF and volumes. Figure 2 presents an overview of the involvement of different cohorts in the study, outlining the specific study objectives and the statistical analysis approaches employed. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/657698v1_fig2.gif" ALT="Figure 2"> View larger version (40K): org.highwire.dtl.DTLVardef@6f1dd8org.highwire.dtl.DTLVardef@11069c6org.highwire.dtl.DTLVardef@905512org.highwire.dtl.DTLVardef@1c12171_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Overview of the involvement of different cohorts in the study, specific study objectives and the statistical analysis approaches employed. Abbreviations: SDMT: Symbol Digit Modalities Test, PASAT: Paced Auditory Serial Addition Test, DSST: Digit Symbol Substitution Test, LASSO: Least Absolute Shrinkage and Selection Operator. C_FIG ResultsTwenty-eight RF-ROI pairs were associated with SDMT in the replication set (FDR<0.05). Of these, 24 were also associated with PASAT (FDR[&le;]0.03), and 2 with DSST. Only ventral nuclei volume showed replicated associations among volumetrics. Only 4 putamen-derived pairs were associated with SDMT (FDR=0.04). LASSO results confirmed RF outperformed volumes. DiscussionRF extracted from the thalamus are strongly associated with cognitive performance in PwMS, outperforming volumetric measures and supporting their potential as sensitive imaging biomarkers.

neuroscience↗

From Structure to Immunogenicity: Decoding Correlated Dynamics atthe Peptide MHC interface to Understand TCR Recognition

The interaction between a class I peptide-major histocompatibility complex (pMHC) and a T cell receptor (TCR) plays a central role in the elicitation of CD8+ T cell immune responses. As a result, considerable effort has been invested in understanding the structural, dynamic, and biophysical parameters that govern this recognition event, including designing altered peptide ligands (APLs) which seek to modulate the downstream signaling outcomes. However, dynamic links between modified peptide positions and distant residues have until yet been ill resolved. Using an integrative approach combining crystallographic ensemble and single models with atomistic molecular dynamics simulations and correlational analysis, we have established an approach that allows us to identify coupled dynamics between spatially distant residues at the pMHC interface. Furthermore, we constructed a network encoding the inter-residue couplings observed throughout the simulations. This computational workflow corroborates well with experimental data and leads to novel insights regarding the differential immunogenicity of the closely related peptides analyzed in this study. Ultimately, we present an intuitive and comprehensive strategy for decoding the linked dynamics at the pMHC interface allowing for mechanistic insights into the biophysical bases governing immunogenicity. One Sentence SummaryThe dynamics at the pMHC interface can be encoded as a biophysically relevant network to yield molecular insights into immunogenicity

immunology↗

Imputation Disparities Driven by Recent Selectionand Their Impact on Disease Risk Estimation in East and Southeast Asian Populations

Using genotype data consisting of 8,316 individuals, we systematically evaluated imputation performance across six state-of-the-art reference panels for Chinese and Thai populations. A substantial proportion of variants identified through whole-genome sequencing, especially low-frequency variants, remained undetected by existing reference panels. In the Chinese population, the TOPMed panel required an R2 threshold of 0.60-0.70 to achieve comparable imputation accuracy of the ChinaMAP panel without R2 filtering, challenging the standard practice of applying a fixed R2 threshold for downstream analyses. Regional analysis highlighted the role of recent selection in imputation discrepancies and revealed an enrichment of immune-related genes in poorly imputed regions. In addition, we showed that the selection of reference panels and R2 thresholds could significantly influence estimation of polygenic risk score for disease prediction. These findings underscore the importance of developing ancestrally diverse reference panels and provide valuable guidelines for improving genotype imputation in East and Southeast Asian populations.

genomics↗

Mapping the spatial architecture of glioblastoma from core to edge delineates niche-specific tumor cell states and intercellular interactions

Treatment resistance in glioblastoma (GBM) is largely driven by the extensive multi-level heterogeneity that typifies this disease. Despite significant progress toward elucidating GBMs genomic and transcriptional heterogeneity, a critical knowledge gap remains in defining this heterogeneity at the spatial level. To address this, we employed spatial transcriptomics to map the architecture of the GBM ecosystem. This revealed tumor cell states that are jointly defined by gene expression and spatial localization, and multicellular niches whose composition varies along the tumor core-edge axis. Ligand-receptor interaction analysis uncovered a complex network of intercellular communication, including niche- and region-specific interactions. Finally, we found that CD8 positive GZMK positive T cells colocalize with LYVE1 positive CD163 positive myeloid cells in vascular regions, suggesting a potential mechanism for immune evasion. These findings provide novel insights into the GBM tumor microenvironment, highlighting previously unrecognized patterns of spatial organization and intercellular interactions, and novel therapeutic avenues to disrupt tumor-promoting interactions and overcome immune resistance.

cancer biology↗

Mutational insights into human kynurenine aminotransferase 1: modulation of transamination and β-elimination activities across diverse substrates

Human kynurenine aminotransferase 1 (hKYAT1) plays a crucial role in the transamination of aromatic amino acids and kynurenine. This promiscuous homodimeric enzyme transaminates various amino acids into their corresponding alpha-keto acids. Additionally, hKYAT1 is known to catalyze the beta-elimination of cysteine-S-conjugates and cysteine-Se-conjugates. In this study, we performed mutational analyses of hKYAT1, targeting its catalytic, ligand-binding, and substrate-binding sites. The transamination activity of thirteen mutant variants was systematically evaluated against sixteen different amino acid substrates, including kynurenine, selenomethionine (SeMet), and Se-methylselenocysteine (MSC), as well as for the {beta}-elimination of SeMet and MSC. Our results demonstrate that mutations of residues E27 in the catalytic site and H279 in the substrate-stabilizing site significantly enhanced the transamination of several amino acids, including phenylalanine, tryptophan, histidine, and MSC. The H279F mutation increased transamination and {beta}-elimination of MSC by two- and 1.5-fold, respectively. Furthermore, mutation at the ligand-binding residues R398 and N185 abolished the transamination activity of hKYAT1. Interestingly, none of the tested mutations affected the transamination of L-kynurenine, a natural substrate of hKYAT1. These findings provide a foundation for the rational design of selective inhibitors with potential therapeutic applications.

bioengineering↗

SAXS reveals the molecular basis underlying pH-driven G3BP1 conformational dynamics: implications for stress granule formation

G3BP1 is the central node and molecular switch in stress granule (SG) assembly. However, structural insights into full-length G3BP1 remain elusive owing to its extensive intrinsically disordered regions (IDRs). Using size-exclusion chromatography-coupled small-angle X-ray scattering (SEC-SAXS), we have characterized the solution architecture and conformational dynamics of full-length G3BP1. Under physiological conditions, G3BP1 adopts an elongated, head-to-head antiparallel homodimeric conformation, whereas acidification induces a pronounced conformational compaction. Subsequent biophysical studies reveal that this compact state enables robust RNA-mediated and, notably, homotypic phase separation in vitro. Deletion of the RGG region abolishes this acidity-induced compaction and markedly impairs phase separation, establishing a causal link between the RGG-dependent conformational switch and phase separation propensity. By moving beyond hypothetical models to experimental solution-state data, our work fills a longstanding void in the field and provides critical insights into the structural plasticity that underlies G3BP1 function, offering a missing structural link essential for deciphering the molecular mechanism of SG formation. We propose that stress-associated physicochemical changes, specifically localized acidification coupled with mRNA accumulation, trigger this reversible structural reconfiguration of G3BP1, thereby facilitating phase separation.

molecular biology↗

Development of DARPin T cell engagers for specific targeting of tumor-associated HLA/peptide complexes

The compromise between affinity and specificity in TCR-dependent targeting of HLA-restricted tumor-associated antigens presents a significant challenge in developing efficacious immunotherapies. As such, T cell engagers which circumvent these limitations are of particular interest. We have established a process to generate bispecific Designed Ankyrin Repeat Proteins (DARPins) that simultaneously target HLA-I molecules in complex with tumor-associated peptides and CD3{varepsilon}. High-affinity HLA-A*0201/NY-ESO1157-165-specific DARPins were isolated after only four rounds of in-vitro selection from naive DARPin libraries. Combining HLA-A*0201/NY-ESO1157-165-specific DARPins with a CD3{varepsilon}-specific DARPin created potent T cell engagers which elicited CD8+ T cell activation towards tumor targets with high peptide specificity, as confirmed by X-scanning mutagenesis and functional killing assays. The cryo-EM structure of a ternary DARPin/HLA-A*0201/NY-ESO1157-165 complex revealed a rigid and concave DARPin surface that binds to the entire length of the peptide-binding cleft, contacting both -helices and the peptide. The present results unveil promising immuno-oncotherapeutic approaches with the possibility of rapidly developing DARPins with high affinity and specificity to HLA/peptide targets that can be readily combined with a new generation of anti-CD3{varepsilon}-specific DARPins.

synthetic biology↗

High-efficiency likelihood inference of shared proteomic architectures across 50 complex human traits

Advancements in genetic correlation estimation have elucidated genome-wide pleiotropys influence on phenotypic correlations among human complex traits and diseases. However, the role of proteomic domains in these correlations remains underexplored. Traditional genetic correlation analysis assumptions, including the minute effects of SNPs and their linkage disequilibrium, do not suit proteomic data. We present a novel method, Likelihood-based Estimation for Proteomic Correlation (LEAP), tailored to provide unbiased estimation of shared proteomic architectures between trait pairs. LEAP notably decreases computational demands by approximately 1000-fold compared to conventional bivariate linear mixed models. We applied LEAP to data from the UK Biobank Pharma Proteomics Project, identifying 585 significant proteomic correlations among 1,225 pairs of 50 biochemical, anthropometric, and behavioral traits. Furthermore, we quantified the distinct proteomic and genetic contributions to phenotypic correlations, highlighting significant gender differences. This study provides a comprehensive computational approach for proteomic correlation estimation, clarifying the specific roles of genomics and proteomics in complex trait correlations. Our findings not only advance the understanding of proteomic contributions to phenotypic traits but also suggest potential applications for evaluating shared omics architectures in other domains such as transcriptomics and metabolomics.

bioinformatics↗