Leying Guan
A5004224053- Long-Term Effects of COVID-19
- Statistical Methods and Inference
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Gene expression and cancer classification
- vaccines and immunoinformatics approaches
- Anomaly Detection Techniques and Applications
- Sparse and Compressive Sensing Techniques
- Influenza Virus Research Studies
- Gene Regulatory Network Analysis
- Bacterial Infections and Vaccines
- Advanced Statistical Process Monitoring
- Machine Learning and Algorithms
- Genetic and phenotypic traits in livestock
- COVID-19 and Mental Health
- Bioinformatics and Genomic Networks
- Statistical Distribution Estimation and Applications
- Fault Detection and Control Systems
- Genetic Associations and Epidemiology
- Distributed Sensor Networks and Detection Algorithms
- Statistical Methods in Clinical Trials
- Single-cell and spatial transcriptomics
- RNA modifications and cancer
- Statistical Methods and Bayesian Inference
- Advanced biosensing and bioanalysis techniques
Yale University
2019-2025
Guangzhou Medical University
2024
State Key Laboratory of Respiratory Disease
2024
University of New Haven
2023
Stanford University
2017-2019
University of Finance and Economics
2015
Tsinghua University
2014
Abstract Post-acute infection syndromes may develop after acute viral disease 1 . Infection with SARS-CoV-2 can result in the development of a post-acute syndrome known as long COVID. Individuals COVID frequently report unremitting fatigue, post-exertional malaise, and variety cognitive autonomic dysfunctions 2–4 However, biological processes that are associated persistence these symptoms unclear. Here 275 individuals or without were enrolled cross-sectional study included multidimensional...
Abstract Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated female sex distinctive comorbidities. During...
Summary Strong sex differences in the frequencies and manifestations of Long COVID (LC) have been reported with females significantly more likely than males to present LC after acute SARS-CoV-2 infection 1–7 . However, whether immunological traits underlying differ between sexes, such explain differential symptomology is currently unknown. Here, we performed sex-based multi-dimensional immune-endocrine profiling 165 individuals 8 without an exploratory, cross-sectional study identify key...
The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1–3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling >15,000 longitudinal blood nasal samples 540 participants the using 14 distinct assays. These unbiased analyses identify cellular molecular signatures present within 72 h hospital admission that...
Age is a major risk factor for severe coronavirus disease 2019 (COVID-19), yet the mechanisms behind this relationship have remained incompletely understood. To address this, we evaluated impact of aging on host immune response in blood and upper airway, as well nasal microbiome prospective, multicenter cohort 1031 vaccine-naïve patients hospitalized COVID-19 between 18 96 years old. We performed mass cytometry, serum protein profiling, anti–severe acute respiratory syndrome 2 (SARS-CoV-2)...
COVID-19 vaccines have prevented millions of deaths. Yet, a small fraction the population reports chronic debilitating condition after vaccination, often referred to as post- vaccination syndrome (PVS). To explore potential pathobiological features associated with PVS, we conducted decentralized, cross-sectional study involving 42 PVS participants and 22 healthy controls enrolled in Yale LISTEN study. Compared controls, exhibited differences immune profiles, including reduced circulating...
Significance In modern hospital systems where complicated, severely ill patient populations are the norm, there is currently no reliable way to forecast use of perishable medical resources enable a smart and economic deliver optimal care. We here demonstrate statistical model using data quantitatively forecast, days in advance, need for platelet transfusions. This approach can be leveraged significantly decrease wastage, and, if adopted nationwide, would save approximately 80 million dollars...
IMPACC is a multicenter longitudinal study assessing clinical and immunologic manifestations of COVID-19 in hospitalized patients.
We consider the multi-class classification problem when training data and out-of-sample test may have different distributions propose a method called BCOPS (balanced conformal optimized prediction sets). constructs set
Abstract The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the IgM N-glycosylation has not been studied viral infection. analysis from healthy controls hospitalized disease 2019 (COVID-19) patients reveals increased high-mannose sialylation that correlates with COVID-19 severity. These trends are confirmed within SARS-CoV-2-specific...
Abstract Background Long COVID contributes to the global burden of disease. Proposed root cause hypotheses include persistence SARS-CoV-2 viral reservoir, autoimmunity, and reactivation latent herpesviruses. Patients have reported various changes in symptoms after COVID-19 vaccinations, leaving uncertainty about whether vaccine-induced immune responses may alleviate or worsen disease pathology. Methods In this prospective study, we evaluated vaccination 16 vaccine-naïve individuals with...
Summary We propose a new inference framework called localized conformal prediction. It generalizes the of prediction by offering single-test-sample adaptive construction that emphasizes local region around this test sample, and can be combined with different scores. The proposed enjoys an assumption-free finite sample marginal coverage guarantee, it also offers additional guarantees under suitable assumptions. demonstrate how to change from using several scores, we illustrate potential gain...
Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, well prediction of responses to vaccination or therapy. These are identified from high-throughput profiling assays through a combination dimensionality reduction machine learning techniques. The genes, proteins, metabolites, other analytes that compose also generate hypotheses on the underlying mechanisms driving responses, thus improving understanding. Dimensionality is critical step in...
Chronic viral infections are ubiquitous in humans, with individuals harboring multiple latent viruses that can reactivate during acute illnesses. Recent studies have suggested SARS-CoV-2 infection lead to reactivation of such as Epstein-Barr Virus (EBV) and cytomegalovirus (CMV), yet, the extent impact COVID-19 its effect on host immune system remain incompletely understood. Here we present a comprehensive multi-omic analysis all known chronically infecting 1,154 hospitalized patients, from...
Genetic risk prediction for non-European populations is hindered by limited Genome-Wide Association Study (GWAS) sample sizes and small tuning datasets. We propose JointPRS, a data-adaptive framework that leverages genetic correlations across multiple using GWAS summary statistics. It achieves accurate predictions without individual-level data remains effective in the presence of set thanks to its approach. Through extensive simulations real applications 22 quantitative four binary traits...
Abstract Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex heterogeneous multiorgan disease that can have severe impact on individuals' quality of life. Diagnosis ME/CFS based symptom presentation, and significant goal for the field to establish meaningful subtypes. The heterogeneity in literature suggests individuals living with may suffer from overlapping but different underlying pathophysiological mechanisms. We enrolled 40 participants 41 matched healthy control...
The post-acute sequelae of SARS-CoV-2 (PASC), also known as long COVID, remain a significant health issue that is incompletely understood. Predicting which acutely infected individuals will go on to develop COVID challenging due the lack established biomarkers, clear disease mechanisms, or well-defined sub-phenotypes. Machine learning (ML) models offer potential address this by leveraging clinical data enhance diagnostic precision. We utilized data, including antibody titers and viral load...
Following SARS-CoV-2 infection, ∼10-35% of COVID-19 patients experience long COVID (LC), in which often debilitating symptoms persist for at least three months. Elucidating the biologic underpinnings LC could identify therapeutic opportunities. We utilized machine learning methods on analytes and patient reported outcome surveys provided over 12 months after hospital discharge from >500 hospitalized IMPACC cohort to a multi-omics "recovery factor". participants who experienced had lower...
Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing differences in outcome. Comparing such is challenging due variability study designs. To address this, we established a community resource compare predicting B. pertussis booster generate experimental data for explicit purpose of model evaluation. We here describe our second prediction challenge using this resource, where benchmarked 49...
Single-cell RNA sequencing (scRNA-seq) is an important technique for obtaining biological insights at cellular resolution, with scRNA-seq batch integration a key step before downstream statistical analysis. Despite the plethora of methods proposed, achieving reliable correction while preserving heterogeneity signals that define cell type continues to pose challenge. To address this, we propose scCRAFT, autoencoder model separates cell-type-related from effects multi-batch integration....
ABSTRACT Background Predicting mortality risk in patients with COVID-19 remains challenging, and accurate prognostic assays represent a persistent unmet clinical need. We aimed to identify validate parsimonious transcriptomic signatures that accurately predict fatal outcomes within 48 hours of hospitalization. Methods studied 894 hospitalized for across 20 US hospitals enrolled the prospective Immunophenotyping Assessment Cohort (IMPACC) peripheral blood mononuclear cells (PBMC) nasal swabs...
Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases encephalitis and death. To identify cellular molecular signatures distinguishing WNV severity, we employed systems profiling peripheral blood severely ill individuals infected WNV. We interrogated immune responses longitudinally acute infection through convalescence employing single-cell protein transcriptional complemented matched serum proteomics metabolomics...