Biology subjects

Brody, J.

Publications and source records attributed to Brody, J..

8 recordsLinked to original sources

bioRxiv2026

Machine learning cross-platform proteomic imputation enables protein quality scoring and replication of epidemiological associations

High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKBs original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.

bioinformatics↗

bioRxiv2025

PIN1 Drives Cellular Plasticity and Immune Modulation in Chronic Pancreatitis

Background and AimsChronic pancreatitis (CP) is characterized by inflammation, fibrosis, and acinar-to-ductal metaplasia (ADM). PIN1, known to drive oncogenic signaling and cellular plasticity in cancer, has an unexplored role in CP. This study investigates PIN1s expression and function in CP pathogenesis using human tissues and mouse models. MethodsPIN1 expression was assessed in human CP tissue microarrays (TMAs) via immunohistochemistry (IHC) and cyclic immunofluorescence (CyCIF). Acute and chronic pancreatitis were induced in wild-type (WT) and PIN1 knockout (PIN1KO) mice using caerulein. Disease progression was monitored histologically, and immune profiling was conducted using flow cytometry. Pharmacological inhibition was performed using a small molecule PIN1 inhibitor-Sulfopin, and effects were evaluated by histology, qPCR, and cytokine analysis. Single-cell RNA sequencing (scRNA-seq) was performed on pancreatic tissues to perform pathway analysis and intercellular communication. ResultsPIN1 expression was elevated in human CP tissues, correlating with disease severity and ADM. In mice, both acute and chronic pancreatitis increased PIN1 expression, but only in our chronic PIN1KO mice displayed reduced pancreatic injury, fibrosis, ADM, and modulated immune infiltration. Pharmacological PIN1 inhibition mimicked the protective effects of genetic knockout, dampening inflammatory pathways. scRNA-seq revealed that PIN1 inhibition altered the intercellular communication networks between epithelial, immune, and stromal cells. ConclusionPIN1 drives cellular plasticity, immune modulation, and disease progression in CP. Targeting PIN1 may offer a therapeutic strategy to mitigate CP. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/653850v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@67f9fcorg.highwire.dtl.DTLVardef@4d4c1forg.highwire.dtl.DTLVardef@c099d7org.highwire.dtl.DTLVardef@b41aa5_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender. Shah, V. (2025) https://BioRender.com/undefined

cell biology↗

bioRxiv2024

Bispecific antibody targeting of lipid nanoparticles

Lipid nanoparticles (LNP) are the most clinically advanced non-viral gene delivery system. While progress has been made for enhancing delivery, cell specific targeting remains a challenge. Targeting moieties such as antibodies can be chemically-conjugated to LNPs however, this approach is complex and has challenges for scaling up. Here, we developed an approach to generate antibody-conjugated LNPs that utilizes a bispecific antibody (bsAb) as the targeting bridge. As a docking site for the bsAb, we generated LNPs with a short epitope, derived from hemagglutinin antigen (HA), embedded in the PEG component of the particle (LNPHA). We generated bsAb in which one domain binds HA and the other binds different cell surface proteins, including PD-L1, CD4, CD5, and SunTag. Non-chemical conjugation of the bsAb and LNP resulted in a major increase in the efficiency and specificity of transfecting cells expressing the cognate target. LNP/bsAb mediated a 4-fold increase in in vivo transfection of PD-L1 expressing cancer cells, and a 26-fold increase in ex vivo transfection of quiescent primary human T cells. Additionally, we created a universal bsAb recognizing HA and anti-rat IgG2, enabling LNP tethering to off-the-shelf antibodies such as CD4, CD8, CD20, CD45, and CD3. By utilizing a molecular dock and bsAb technology, these studies demonstrate a simple and effective strategy to generate antibody-conjugated LNPs, enabling precise and efficient mRNA delivery.

bioengineering↗

bioRxiv2022

The functional impact of rare variation across the regulatory cascade

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis (MESA) which included several hundred individuals with whole genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, ten years apart. We evaluated each multi-omic phenotypes ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62x and rare frameshift variants 216x as frequently as controls, compared to 13x to 27x for expression or protein effects alone. We developed a Bayesian hierarchical model to prioritize specific rare variants underlying multi-omic signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimers disease.

genomics↗

bioRxiv2022

Liver Endothelium Microenvironment Promotes HER3-mediated Cell Growth in Pancreatic ductal adenocarcinoma

[~]90% metastatic pancreatic ductal adenocarcinoma (mPDAC) occurs in the liver, and the 5-year survival rate for patients with mPDAC is only at 3%. We previously reported that liver endothelial cells (ECs) secreted soluble factors to promote colorectal cancer cell survival in a paracrine fashion. However, the effects of liver ECs on mPDAC have not been elucidated. In this study, we used primary ECs from non-neoplastic liver tissues. We treated PDAC cells with conditioned medium (CM) from liver ECs, with CM from PDAC as controls, and determined that liver EC-secreted factors increased PDAC cell growth. Using an unbiased receptor tyrosine kinase array, we identified human epidermal growth factor receptor 3 (HER3, also known as ErbB3) as a key mediator in EC-induced growth in PDAC cells that have HER3 expression (HER3 +ve). We found that EC-secreted neuregulins activated the HER3-AKT signaling axis, and that depleting neuregulins from EC CM or blocking HER3 with an antibody, seribantumab, attenuated EC-induced proliferation in HER3 +ve PDAC cells, but not in cells without HER3 expression. Furthermore, we determined that EC CM increased PDAC xenograft growth in vivo, and that seribantumab blocked EC-induced growth in xenografts with HER3 expression. These findings elucidated a paracrine role of liver ECs in promoting PDAC cell growth, and identified the HER3-AKT axis as a key mediator in EC-induced functions in PDAC cells with HER3 expression. Implicationsover 70% mPDAC express HER3. This study suggests the potential of using HER3-targeted therapies for treating patients with HER3 +ve mPDAC.

cancer biology↗

bioRxiv2022

Ongoing Replication Stress Response and New Clonal T Cell Development Discriminate Between Liver and Lung Recurrence Sites and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

Background and AimsMetastatic pancreatic adenocarcinoma (mPDAC) is lethal, yet a subset of patients who have metastatic disease that spreads only to the lung have better outcomes. We identified unique transcriptomic and immune features that distinguish patients who develop metastases in the liver (liver cohort) versus those with lung-avid but liver-averse mPDAC (lung cohort). MethodsWe used clinical data from the Oregon Pancreas Tissue Registry to identify PDAC patients with liver and/or lung metastases. Gene expression and genomic alteration data from 290 PDAC tumors were used to identify features unique to patients from the liver and lung cohorts. In parallel, T cell receptor sequencing data from 289 patients were used to identify immune features unique to patients in the lung cohort. ResultsLung cohort patients had better survival outcomes than liver cohort patients. Primary tumors from patients in the liver cohort expressed a novel gene signature associated with ongoing replication stress (RS) response predictive of poor patient outcome independent from known subtypes. In contrast, patients with tumors lacking the RS response signature survived longer, especially if their tumors had alterations in DNA damage repair genes. A subset of patients in the lung cohort demonstrated new T cell clonal development in their primary and metastatic tumors leading to diverse peripheral blood TCR repertoires. ConclusionLiver-avid metastatic PDAC is associated with an ongoing RS response, whereas tumors lacking the RS response with ongoing T cell clonal responses may have unique vulnerabilities allowing long-term survival in patients with lung-avid, liver-averse metastatic PDAC.

cancer biology↗

bioRxiv2020

Population sequencing data reveal a compendium of mutational processes in human germline

Mechanistic processes underlying human germline mutations remain largely unknown. Variation in mutation rate and spectra along the genome is informative about the biological mechanisms. We statistically decompose this variation into separate processes using a blind source separation technique. The analysis of a large-scale whole genome sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. Seven of these processes lend themselves to a biological interpretation. One process is driven by bulky DNA lesions that resolve asymmetrically with respect to transcription and replication. Two processes independently track direction of replication fork and replication timing. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions. We also demonstrate that a recently discovered mutagenic process specific to oocytes can be localized solely from population sequencing data. This process is spread across all chromosomes and is highly asymmetric with respect to the direction of transcription, suggesting a major role of DNA damage.

genetics↗

bioRxiv2019

Genome Sequencing Unveils a New Regulatory Landscape of Platelet Reactivity

Exaggerated platelet aggregation at the site of vascular injury is the underlying pathophysiology of thrombotic diseases. Here, we conduct the largest whole genome sequencing (WGS) effort to uncover the genetic determinants of platelet aggregation. Leveraging 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) individuals deeply phenotyped for platelet aggregation, we identify 18 loci using single-variant approaches. This includes the novel RGS18 locus encoding a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with eQTL signatures for RGS18 expression in platelets. A gene-based approach focusing on deleterious coding variants identifies the SVEP1 gene, previously shown to be associated with coronary artery disease, as a novel determinant of platelet aggregation. Finally, in an integrative approach leveraging epigenetic data on megakaryocytes, we find strong association between rare variants mapping to a super enhancer region for PEAR1. This is a novel finding implicating the importance of rare variants with regulatory potential in a previously documented GWAS-identified locus.

genomics↗