Biology subjects

Arnaout, R.

Publications and source records attributed to Arnaout, R..

12 recordsLinked to original sources

bioRxiv2026

Reconstruction of FACS-partitioned Adaptive Immune Receptor Repertoires from FACS-partitioned B and T Cell Subsets

Adaptive immune-receptor repertoire sequencing (AIRRseq) is crucial for understanding immune system diversity and its relationship to disease dynamics. Partitioning of total B and T cells into their major subsets with distinct immunological functions - IgM+ vs. class-switched B cells (IgG+ > IgA+) and CD4+ vs. CD8+ T cells, respectively - allows for AIRRseq-based analysis of the unique contributions of each compartment to the overall immune response, a major advantage over traditional bulk sequencing workflows. However, data from these subsets is not directly comparable with the vast majority of publicly available AIRRseq data, which comes from unfractionated B and T cells, an important incompatibility. Here we investigate computational methods for reconstructing complete AIRRseq repertoires from partitioned B and T cell subsets in diverse individuals. Peripheral blood mononuclear cells (PBMCs) were partitioned via positive selection of IgM+ B-cell subsets and CD4+ T cells using immunomagnetic beads; genomic DNA was then extracted and B- and T-cell receptors were sequenced. Four reconstruction methods are introduced and evaluated for concordance with matching unpartitioned repertoires to assess preservation of key repertoire characteristics. Results show that these methods enable accurate estimates of overall immune-repertoire diversity from B- and T-cell subsets in a way that simply pooling the sequence data from sub-repertoires cannot.

immunology↗

bioRxiv2025

HuBIE: The Human Blood Immunome Encyclopedia Of TCRs and BCRs in Bloodstream Infections and Cancer

T and B cells are central to adaptive immunity, where they identify and neutralize foreign antigens and cancer neo-antigens. Large-scale elucidation of T- and B-cell receptors (TCRs and BCRs) through immune-repertoire sequencing promises novel diagnostics, prognostic markers, and therapeutic strategies. However, progress is hampered by small cohort sizes, a lack of real-world patient diversity, and heterogeneous sample processing, impeding cross-study comparability. To overcome these limitations, here we introduce the Human Blood Immunome Encyclopedia (HuBIE), comprising immune-repertoire data from 2,614 samples collected from 1,941 participants. The cohort includes a range of bloodstream infections, several cancer types, and control participants, with many individuals providing longitudinal samples. We employed Roches immune receptor Primer Extension Target Enrichment (immunoPETE) platform to perform simultaneous targeted sequencing of T-cell receptor {beta} chains (TRB), T-cell receptor {delta} chains (TRD), and immunoglobulin heavy chains (IGH), thereby profiling TCRs and BCRs in all participants. We provide a comprehensive description of immune-repertoire diversity in cancer and bloodstream infections and examine variations across demographic variables such as age and race. We find significant differences in TRB and IGH composition across ethnic groups, and show that the fall in repertoire diversity with age follows distinct patterns for TRB, TRD, and IGH and is accompanied by age-related differences in VJ gene usage. Finally we demonstrate that greater immunological diversity is associated with improved survival but only for elderly participants. HuBIE thus constitutes a valuable resource for the immune-repertoire community, enabling large-scale mapping of the human immunome to accelerate development of diagnostics, prognostic biomarkers, and innovative therapeutic strategies.

immunology↗

bioRxiv2024

lucie: An Improved Python Package for Loading Datasets from the UCI Machine Learning Repository

The University of California-Irvine (UCI) Machine Learning (ML) Repository (UCIMLR) is consistently cited as one of the most popular dataset repositories, hosting hundreds of high-impact datasets. However, a significant portion, including 28.4% of the top 250, cannot be imported via the ucimlrepo package that is provided and recommended by the UCIMLR website. Instead, they are hosted as .zip files, containing nonstandard formats that are difficult to import without additional ad hoc processing. To address this issue, here we present lucie--load University California Irvine examples--a utility that automatically determines the data format and imports many of these previously non-importable datasets, while preserving as much of a tabular data structure as possible. lucie was designed using the top 100 most popular datasets and benchmarked on the next 130, where it resulted in a success rate of 95.4% vs. 73.1% for ucimlrepo. lucie is available as a Python package on PyPI with 98% code coverage.

bioinformatics↗

bioRxiv2023

Contrasting Effects of SARS-CoV-2 Vaccination vs. Infection on Antibody and TCR Repertoires

Antibodies and helper T cells play important roles in SARS-CoV-2 infection and vaccination. We sequenced B- and T-cell receptor repertoires (BCR/TCR) from the blood of 251 infectees, vaccinees, and controls to investigate whether features of these repertoires could predict subjects SARS-CoV-2 neutralizing antibody titer (NAbs), as measured by enzyme-linked immunosorbent assay (ELISA). We sequenced recombined immunoglobulin heavy-chain (IGH), TCR{beta} (TRB), and TCR{delta} (TRD) genes in parallel from all subjects, including select B- and T-cell subsets in most cases, with a focus on their hypervariable CDR3 regions, and correlated this AIRRseq data with demographics and clinical findings from subjects electronic health records. We found that age affected NAb levels in vaccinees but not infectees. Intriguingly, we found that vaccination and infection have an effect on non-productively recombined IGHs, suggesting an effect that precedes clonal selection. We found that repertoires binding capacity to known SARS-CoV-2-specific CD4+ TRBs performs as well as the best hand-tuned approximate or "fuzzy" matching at predicting a protective level of NAbs, while also being more robust to repertoire sample size and not requiring hand-tuning. The overall conclusion from this large, unbiased, clinically well annotated dataset is that B- and T-cell adaptive responses to SARS-CoV-2 infection and vaccination are surprising, subtle, and diffuse. We discuss methodological and statistical challenges faced in attempting to define and quantify such strong-but-diffuse repertoire signatures and present tools and strategies for addressing these challenges.

immunology↗

bioRxiv2022

Repertoire-Scale Measures of Antigen Binding

Antibodies and T-cell receptors (TCRs) are the fundamental building blocks of adaptive immunity. Repertoire-scale functionality derives from their epitope-binding properties, just as macroscopic properties like temperature derive from microscopic molecular properties. However, most approaches to repertoire-scale measurement, including sequence diversity and entropy, are not based on antibody or TCR function in this way. Thus, they potentially overlook key features of immunological function. Here we present a framework that describes repertoires in terms of the epitope-binding properties of their constituent antibodies and TCRs, based on analysis of thousands of antibody-antigen and TCR-peptide-major-histocompatibility-complex binding interactions and over 400 high-throughput repertoires. We show that repertoires consist of loose overlapping classes of antibodies and TCRs with similar binding properties. We demonstrate the potential of this framework to distinguish specific responses vs. bystander activation in influenza vaccinees, stratify CMV-infected cohorts, and identify potential immunological "super-agers." Classes add a new dimension to assessment of immune function.

immunology↗

bioRxiv2022

ct2vl: Converting Ct Values to Viral Loads for SARS-CoV-2 RT-qPCR Test Results

RT-qPCR is the de facto reference method for detecting the presence of SARS-CoV-2 genomic material in infected individuals (1). Although RT-qPCR is inherently quantitative and despite SARS-CoV-2 viral loads varying by 10 orders of magnitude and therefore being potentially highly clinically informative, in practice SARS-CoV-2 RT-qPCR results are usually reported qualitatively as simply positive or negative. This is both because of the mathematical complexity of converting from Ct values to viral loads and because the same Ct value can correspond to orders-of-magnitude differences in viral load depending on the testing platform (2, 3, 4). To address this problem, here we present ct2vl, a Python package designed to help individual clinical laboratories, investigators, and test developers convert from Ct values to viral loads on their own platforms, using only the data generated during validation of those platforms. It allows any user to convert Ct values to viral loads and is readily applicable to other RT-qPCR tests. ct2vl is open source, has 100% code coverage, and is freely available via the Python Package Index (PyPI). IMPORTANCEUp to now, COVID-19 test results have been reported as positive vs. negative, even though "positive" can mean anywhere from 1 copy of SARS-CoV-2 virus per milliliter of transport media to over 1 billion copies/mL, with attendant clinical consequences. Democratizing access to this quantitative data is the first step toward its eventual incorporation into test development, the research literature, and clinical care.

microbiology↗

bioRxiv2020

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1, a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

bioinformatics↗

bioRxiv2020

Private Antibody Repertoires Are Public

When faced with a given pathogen, the antibody response generally functions similarly across different people,1-4 but the source of this similarity has been unclear. One hypothesis was that people share a high proportion of the same VDJ-recombined antibody genes, but this has been disproven.5,6 An alternative is that people share a high proportion of functionally similar antibodies,7,8 but testing this hypothesis requires a method for measuring functional similarity that scales to the millions of antibodies per repertoire and across multiple repertoires, which is impossible experimentally. We recently described a framework for doing so computationally,9 which revealed that repertoires consist of loose overlapping functional classes of antibodies with similar antigen-binding capacities;10-12 this framework allowed us to estimate a repertoires antigen-binding capacity,{tau} , for the ideal target of any given antibody. Here, we show that this framework supports the second hypothesis, and provide the first comprehensive demonstration of overwhelming functional overlap between repertoires from 20 different individuals directly from sequence, without need of binding studies. Overlap is highest among the young and falls with age, due to the selective loss of antibodies that represent a core set of shared or "public" antigen-binding capacities. We reveal considerable heterogeneity in antigen-binding capacities for antibodies against influenza, HIV, and SARS-CoV-2, and show that while some of these classes shrink with age, others persist across individuals. These discoveries change our understanding of repertoire diversity and have implications for vaccine and therapeutic-antibody development, especially for the aged.

immunology↗

bioRxiv2020

SARS-CoV2 Testing: The Limit of Detection Matters

Resolving the COVID-19 pandemic requires diagnostic testing to determine which individuals are infected and which are not. The current gold standard is to perform RT-PCR on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of ~100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss more infected patients, resulting in more false negatives. However, the false-negative rate for a given LoD remains unknown. Here we address this question using over 27,500 test results for patients from across our healthcare network tested using the Abbott RealTime SARS-CoV-2 EUA. These results suggest that each 10-fold increase in LoD is expected to increase the false negative rate by 13%, missing an additional one in eight infected patients. The highest LoDs on the market will miss a majority of infected patients, with false negative rates as high as 70%. These results suggest that choice of assay has meaningful clinical and epidemiological consequences. The limit of detection matters.

microbiology↗

bioRxiv2019

Repertoire-Based Diagnostics Using Statistical Biophysics

A fundamental challenge in immunology is diagnostic classification based on repertoire sequence. We used the principle of maximum entropy (MaxEnt) to build compact representations of antibody (IgH) and T-cell receptor (TCR{beta}) CDR3 repertoires based on the statistical biophysical patterns latent in the frequency and ordering of repertoires constituent amino acids. This approach results in substantial advantages in quality, dimensionality, and training speed compared to MaxEnt models based solely on the standard 20-letter amino-acid alphabet. Descriptor-based models learn patterns that pure amino-acid-based models cannot. We demonstrate the utility of descriptor models by successfully classifying influenza vaccination status (AUC=0.97, p=4x10-3), requiring only 31 samples from 14 individuals. Descriptor-based MaxEnt modeling is a powerful new method for dissecting, encoding, and classifying complex repertoires.

immunology↗

bioRxiv2018

Immunological Diversity with Similarity

A diverse immune repertoire is considered a hallmark of good health, but measuring diversity requires a framework that incorporates not only sequences relative frequencies but also their functional similarity to each other. Using experimentally measured dissociation constants from over 1,300 antibody-antigen and T-cell receptor (TCR)-peptide pairs, we developed a framework for functional immunological diversity based on binding and applied it to nearly 400 high-throughput antibody and TCR repertoires to reveal patterns in immunological memory, infection, vaccination, and aging. We show that functional diversity adds information that is not captured by raw diversity, revealing signatures of e.g. clonal selection, and that unlike raw diversity, functional diversity is a robust measure that does not require correction for sampling error. Finally, we show that according to functional diversity, unlike raw diversity, individuals repertoires overlap substantially, indicating a definable ceiling for the functional diversity of human adaptive immunity. Similarity redefines diversity in complex systems.

immunology↗

bioRxiv2018

Peripartum cardiomyopathy and hypertensive disorders of pregnancy and cardiovascular events among 1.6 million California pregnancies

BackgroundCardiovascular complications during and soon after pregnancy present an opportunity to assess risk for subsequent cardiovascular disease. We sought to determine whether peripartum cardiomyopathy and hypertensive disorder of pregnancy subtypes predict future myocardial infarction, heart failure, or stroke independent of one another and independent of other risks like gestational diabetes, preterm birth, and intrauterine growth restriction.\n\nMethods and ResultsThe California Healthcare Cost and Utilization Project database was used to identify all hospitalized pregnancies from 2005-2009, with follow-up through 2011, for a retrospective cohort study. Pregnancies, exposures, covariates and outcomes were defined by ICD-9 codes. Among 1.6 million pregnancies (mean age 28y; median follow-up time to event 2.7y), 558 cases of peripartum cardiomyopathy, 123,603 cases of hypertensive disorders of pregnancy, 107,636 cases of gestational diabetes, 116,768 preterm births, and 23,504 cases of intrauterine growth restriction were observed. Using multivariable Cox proportional hazards models, peripartum cardiomyopathy was independently associated with a 13.0-fold increase in myocardial infarction [95%CI, 4.1-40.9], a 39.2-fold increase in heart failure [95%CI, 30.0-51.9], and a 7.7-fold increase in stroke [95%CI, 2.4-24.0]. Hypertensive disorders of pregnancy were associated with a 1.4 [95%CI, 1.0-2.0] to 7.6 [95%CI, 5.4-10.7] fold higher risk of myocardial infarction, heart failure, and stroke. Gestational diabetes, preterm birth, and intrauterine growth restriction had more modest associations with CVD.\n\nConclusionsThese findings support close monitoring of women with cardiovascular pregnancy complications for prevention of early subsequent cardiovascular events and further study of mechanisms underlying their development.

epidemiology↗