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Petrova B, Syphurs C, Culhane AJ, Chen J, Chen E, Cotsapas C, Esserman D, Montgomery R, Kleinstein S, Smolen K, Mendez K, Lasky-Su J, Steen H, Levy O, Diray-Arce J, Kanarek N
medRxiv : the preprint server for health sciences
2025-03-03
PMID: 40093216
HIPC 2 (2015)
Abstract:
While the public health burden of SARS-CoV-2 infection has lessened due to natural and vaccine-acquired immunity, the emergence of less virulent variants, and antiviral medications, COVID-19 continues to take a significant toll. There are > 10,000 new hospitalizations per week in the U.S., many of whom develop post-acute sequelae of SARS-CoV-2 (PASC), or "long COVID", with long-term health issues and compromised quality of life. Early identification of individuals at high risk of severe COVID-19 is key for monitoring and supporting respiratory status and improving outcomes. Therefore, precision tools for early detection of patients at high risk of severe disease can reduce morbidity and mortality. Here we report an untargeted and longitudinal metabolomic study of plasma derived from adult patients with COVID-19. One-carbon metabolism, a pathway previously shown as critical for viral propagation and disease progression, and a potential target for COVID-19 treatment, scored strongly as differentially abundant in patients with severe COVID-19. A follow-up targeted metabolite profiling revealed that one arm of the one-carbon metabolism pathway, the methionine cycle, is a major driver of the metabolic profile associated with disease severity. The methionine cycle produces S-adenosylmethionine (SAM), the methyl group donor important for methylation of DNA, RNA, and proteins, and its high abundance was reported to correlate with disease severity. Further, genomic data from the profiled patients revealed a genetic contributor to methionine metabolism and identified the C677T allele of the MTHFR gene as a pre-existing predictor of disease trajectory - patients homozygous for the MTHFR C677T have higher incidence of experiencing severe disease. Our results raise the possibility that screening for the common genetic MTHFR variant may be an actionable approach to stratify risk of COVID severity and may inform novel precision COVID-19 treatment strategies.
Bos S, Zambrana JV, Duarte E, Graber AL, Huffaker J, Montenegro C, Premkumar L, Gordon A, Kuan G, Balmaseda A, Harris E
The Lancet. Infectious diseases
2025-03-01
PMID: 39489898
Adolescent
Child
Child, Preschool
Cohort Studies
Dengue
Dengue Virus
Enzyme-Linked Immunosorbent Assay
Female
HIPC 2 (2015)
Humans
Male
Nicaragua
Prospective Studies
Serogroup
Serotyping
Abstract:
[{'@Label': 'BACKGROUND', '@NlmCategory': 'BACKGROUND', '#text': 'Dengue is the most prevalent mosquito-borne viral disease and a major public health problem worldwide. Most primary infections with the four dengue virus serotypes (DENV1-4) are inapparent; nonetheless, whether the distribution of symptomatic versus inapparent infections by serotype varies remains unknown. Here, we present (1) the evaluation of a DENV1-4 envelope domain III multiplex microsphere-based assay (EDIII-MMBA) to serotype inapparent primary infections and (2) its application leveraging 17 years of prospective sample collection from the Nicaraguan Pediatric Dengue Cohort Study (PDCS).'}, {'@Label': 'METHODS', '@NlmCategory': 'METHODS', '#text': 'We analysed primary DENV infections in the PDCS from 2004 to 2022 detected by inhibition ELISA (iELISA) or RT-PCR. First, we evaluated the performance of the EDIII-MMBA for serotyping with samples characterised by RT-PCR or focus reduction neutralisation test. Next, we analysed a subset of inapparent primary DENV infections in the PDCS with the EDIII-MMBA to evaluate the epidemiology of inapparent infections. Remaining infections were inferred using stochastic imputation, taking year and neighbourhood into account. Infection incidence and percentage of inapparent, symptomatic, and severe infections were analysed by serotype.'}, {'@Label': 'FINDINGS', '@NlmCategory': 'RESULTS', '#text': 'Between Aug 30, 2004, and March 10, 2022, a total of 5931 DENV-naive participants were followed in the PDCS. There were 1626 primary infections (382 symptomatic, 1244 inapparent) detected by iELISA or RT-PCR over the study period. The EDIII-MMBA demonstrated excellent overall accuracy (100%, 95% CI 95·8-100) for serotyping inapparent primary DENV infections when evaluated against gold-standard serotyping methods. Of the 1244 inapparent infections, we analysed 574 (46%) using the EDIII-MMBA. We found that the majority of primary infections were inapparent, with DENV3 exhibiting the highest likelihood of symptomatic (pooled odds ratio compared with DENV1: 2·13, 95% CI 1·28-3·56) and severe (6·75, 2·01-22·62) primary infections, whereas DENV2 was similar to DENV1 in both analyses. Considerable within-year and between-year variation in serotype distribution between symptomatic and inapparent infections and circulation of serotypes undetected in symptomatic cases were observed in multiple years.'}, {'@Label': 'INTERPRETATION', '@NlmCategory': 'CONCLUSIONS', '#text': 'Our study indicates that case surveillance skews the perceived epidemiological footprint of DENV. We reveal a more complex and intricate pattern of serotype distribution in inapparent infections. The substantial differences in infection outcomes by serotype emphasises the need for vaccines with balanced immunogenicity and efficacy across serotypes.'}, {'@Label': 'FUNDING', '@NlmCategory': 'BACKGROUND', '#text': 'National Institute of Allergy and Infectious Diseases (National Institutes of Health) and Bill & Melinda Gates Foundation.'}, {'@Label': 'TRANSLATION', '@NlmCategory': 'UNASSIGNED', '#text': 'For the Spanish translation of the abstract see Supplementary Materials section.'}]
Gabernet G, Maciuch J, Gygi JP, Moore JF, Hoch A, Syphurs C, Chu T, Jayavelu ND, Corry DB, Kheradmand F, Baden LR, Sekaly RP, McComsey GA, Haddad EK, Cairns CB, Rouphael N, Fernandez-Sesma A, Simon V, Metcalf JP, Agudelo Higuita NI, Hough CL, Messer WB, Davis MM, Nadeau KC, Pulendran B, ...
bioRxiv : the preprint server for biology
2025-02-14
PMID: 39990442
HIPC 1 (2010)
HIPC 2 (2015)
HIPC 3 (2022)
Yale University
Abstract:
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 of LC could identify therapeutic opportunities. We utilized machine learning methods on biologic analytes and patient reported outcome surveys provided over 12 months after hospital discharge from >500 hospitalized COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor". IMPACC participants who experienced LC had lower recovery factor scores compared to participants without LC. Biologic characterization revealed increased levels of plasma proteins associated with inflammation, elevated transcriptional signatures of heme metabolism, and decreased androgenic steroids in LC patients. The recovery factor was also associated with altered circulating immune cell frequencies. Notably, recovery factor scores were predictive of LC occurrence in patients as early as hospital admission, irrespective of acute disease severity. Thus, the recovery factor identifies patients at risk of LC early after SARS-CoV-2 infection and reveals LC biomarkers and potential treatment targets.
Jayavelu ND, Samaha H, Wimalasena ST, Hoch A, Gygi JP, Gabernet G, Ozonoff A, Liu S, Milliren CE, Levy O, Baden LR, Melamed E, Ehrlich LIR, McComsey GA, Sekaly RP, Cairns CB, Haddad EK, Schaenman J, Shaw AC, Hafler DA, Montgomery RR, Corry DB, Kheradmand F, Atkinson MA, Brakenridge SC, ...
medRxiv : the preprint server for health sciences
2025-02-13
PMID: 39990570
HIPC 1 (2010)
HIPC 2 (2015)
HIPC 3 (2022)
Yale University
Abstract:
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 long COVID is challenging due to the lack of established biomarkers, clear disease mechanisms, or well-defined sub-phenotypes. Machine learning (ML) models offer the potential to address this by leveraging clinical data to enhance diagnostic precision. We utilized clinical data, including antibody titers and viral load measurements collected at the time of hospital admission, to predict the likelihood of acute COVID-19 progressing to long COVID. Our machine learning models achieved median AUROC values ranging from 0.64 to 0.66 and AUPRC values between 0.51 and 0.54, demonstrating their predictive capabilities. Feature importance analysis revealed that low antibody titers and high viral loads at hospital admission were the strongest predictors of long COVID outcomes. Comorbidities, including chronic respiratory, cardiac, and neurologic diseases, as well as female sex, were also identified as significant risk factors for long COVID. Our findings suggest that ML models have the potential to identify patients at risk for developing long COVID based on baseline clinical characteristics. These models can help guide early interventions, improving patient outcomes and mitigating the long-term public health impacts of SARS-CoV-2.
Szabo PA, Levitin HM, Connors TJ, Chen D, Jin J, Thapa P, Guyer R, Caron DP, Gray JI, Matsumoto R, Kubota M, Brusko M, Brusko TM, Farber DL, Sims PA
bioRxiv : the preprint server for biology
2025-02-06
PMID: 39974963
Columbia University
HIPC 2 (2015)
HIPC 3 (2022)
Abstract:
The first years of life are essential for the development of memory T cells, which rapidly populate the body's diverse tissue sites during infancy. However, the degree to which tissue memory T cell responses in early life reflect those during adulthood is unclear. Here, we use single cell RNA-sequencing of resting and ex vivo activated T cells from lymphoid and mucosal tissues of infant (aged 2-9 months) and adult (aged 40-65 years) human organ donors to dissect the transcriptional programming of memory T cells over age. Infant memory T cells demonstrate a unique stem-like transcriptional profile and tissue adaptation program, yet exhibit reduced activation capacity and effector function relative to adults. Using CRISPR-Cas9 knockdown, we define Helios (IKZF2) as a critical transcriptional regulator of the infant-specific tissue adaptation program and restricted effector state. Our findings reveal key transcriptional mechanisms that control tissue T cell fate and function in early life.
Bramon Mora B, Lindsay H, Thiébaut A, Stuart KD, Gottardo R
Bioinformatics (Oxford, England)
2025-02-04
PMID: 39798134
Cluster Analysis
Computational Biology
HIPC 2 (2015)
HIPC 3 (2022)
Molecular Sequence Annotation
Seattle Children's Research Institute
Single-Cell Analysis
Software
Abstract:
[{'@Label': 'SUMMARY', '#text': 'In this article, we present tagtango, an innovative R package and web application designed for robust and intuitive comparison of single-cell clusters and annotations. It offers an interactive platform that simplifies the exploration of differences and similarities among different clustering and annotation methods. Leveraging single-cell data analysis and different visualizations, it allows researchers to dissect the underlying biological differences across groups. tagtango is a user-friendly application that is portable and works seamlessly across multiple operating systems.'}, {'@Label': 'AVAILABILITY AND IMPLEMENTATION', '#text': 'tagtango is freely available at https://github.com/bernibra/tagtango as an R package as well as an online web service at https://tagtango.unil.ch.'}]
Caron DP, Specht WL, Chen D, Wells SB, Szabo PA, Jensen IJ, Farber DL, Sims PA
Cell reports methods
2025-01-27
PMID: 39814026
Cell Lineage
Columbia University
Gene Expression Profiling
HIPC 2 (2015)
HIPC 3 (2022)
Humans
Sequence Analysis, RNA
Single-Cell Analysis
T-Lymphocyte Subsets
Transcriptome
Abstract:
Single-cell RNA sequencing (scRNA-seq) is invaluable for profiling cellular heterogeneity and transcriptional states, but transcriptomic profiles do not always delineate subsets defined by surface proteins. Cellular indexing of transcriptomes and epitopes (CITE-seq) enables simultaneous profiling of single-cell transcriptomes and surface proteomes; however, accurate cell-type annotation requires a classifier that integrates multimodal data. Here, we describe multimodal classifier hierarchy (MMoCHi), a marker-based approach for accurate cell-type classification across multiple single-cell modalities that does not rely on reference atlases. We benchmark MMoCHi using sorted T lymphocyte subsets and annotate a cross-tissue human immune cell dataset. MMoCHi outperforms leading transcriptome-based classifiers and multimodal unsupervised clustering in its ability to identify immune cell subsets that are not readily resolved and to reveal subset markers. MMoCHi is designed for adaptability and can integrate annotation of cell types and developmental states across diverse lineages, samples, or modalities.
Pickering H, Schaenman J, Phan HV, Maguire C, Tsitsiklis A, Rouphael N, Higuita NIA, Atkinson MA, Brakenridge S, Fung M, Messer W, Salehi-Rad R, Altman MC, Becker PM, Bosinger SE, Eckalbar W, Hoch A, Doni Jayavelu N, Kim-Schulze S, Jenkins M, Kleinstein SH, Krammer F, Maecker HT, Ozonoff A, ...
Nature communications
2025-01-10
PMID: 39794319
Adult
Aged
Antibodies, Viral
Chemokines
COVID-19
Female
Gene Expression Profiling
HIPC 1 (2010)
HIPC 2 (2015)
HIPC 3 (2022)
Host Microbial Interactions
Humans
Immunity, Innate
Male
Middle Aged
Organ Transplantation
Prospective Studies
SARS-CoV-2
Transplant Recipients
Yale University
Abstract:
Coronavirus disease 2019 (COVID-19) poses significant risks for solid organ transplant recipients, who have atypical but poorly characterized immune responses to infection. We aim to understand the host immunologic and microbial features of COVID-19 in transplant recipients by leveraging a prospective multicenter cohort of 86 transplant recipients age- and sex-matched with 172 non-transplant controls. We find that transplant recipients have higher nasal SARS-CoV-2 viral abundance and impaired viral clearance, and lower anti-spike IgG levels. In addition, transplant recipients exhibit decreased plasmablasts and transitional B cells, and increased senescent T cells. Blood and nasal transcriptional profiling demonstrate unexpected upregulation of innate immune signaling pathways and increased levels of several proinflammatory serum chemokines. Severe disease in transplant recipients, however, is characterized by a less robust induction of pro-inflammatory genes and chemokines. Together, our study reveals distinct immune features and altered viral dynamics in solid organ transplant recipients.
da Silva Antunes R, Fajardo-Rosas V, Yu ED, Gálvez RI, Abawi A, Alexandar Escarrega E, Martínez-Pérez A, Johansson E, Goodwin B, Frazier A, Dan JM, Crotty S, Seumois G, Weiskopf D, Vijayanand P, Sette A
bioRxiv : the preprint server for biology
2025-01-09
PMID: 39829792
HIPC 2 (2015)
HIPC 3 (2022)
La Jolla Institute for Immunology
Abstract:
The long-term effects of repeated COVID-19 vaccinations on adaptive immunity remain incompletely understood. Here, we conducted a comprehensive three-year longitudinal study examining T cell and antibody responses in 78 vaccinated individuals without reported symptomatic infections. We observed distinct dynamics in Spike-specific humoral and cellular immune responses across multiple vaccine doses. While antibody titers incrementally increased and stabilized with each booster, T cell responses rapidly plateaued, maintaining remarkable stability across CD4+ and CD8+ subsets. Notably, approximately 30% of participants showed CD4+ T cell reactivity to non-Spike antigens, consistent with asymptomatic infections. Single-cell RNA sequencing revealed a diverse landscape of Spike-specific T cell phenotypes, with no evidence of increased exhaustion or significant functional impairment. However, qualitative changes were observed in individuals with evidence of asymptomatic infection, exhibiting unique immunological characteristics, including increased frequencies of Th17-like CD4+ T cells and GZMKhi/IFNR CD8+ T cell subsets. Remarkably, repeated vaccinations in this group were associated with a progressive increase in regulatory T cells, potentially indicating a balanced immune response that may mitigate immunopathology. By regularly stimulating T cell memory, boosters contribute to a stable and enhanced immune response, which may provide better protection against symptomatic infections.
Carrillo FAB, Ojeda S, Sanchez N, Plazaola M, Collado D, Miranda T, Saborio S, Mercado BL, Monterrey JC, Arguello S, Campredon L, Chu Z, Carlson CJ, Gordon A, Balmaseda A, Kuan G, Harris E
medRxiv : the preprint server for health sciences
2025-01-07
PMID: 39830280
HIPC 2 (2015)
Abstract:
[{'@Label': 'BACKGROUND', '@NlmCategory': 'UNASSIGNED', '#text': 'Dengue, chikungunya, and Zika are mosquito-borne diseases of major human concern. Differential diagnosis is complicated in children and adolescents by their overlapping clinical features (signs, symptoms, and complete blood count results). Few studies have directly compared the three diseases. We assessed clinical features of cases aged 2-17 years experiencing these diseases.'}, {'@Label': 'METHODS', '@NlmCategory': 'UNASSIGNED', '#text': 'We characterized 1,405 dengue, 517 chikungunya, and 522 Zika pediatric cases occurring from January 2006 through December 2023 in a Nicaraguan cohort study. Clinical records and laboratory results across the first 10 days of illness were examined from a primary care health center. All cases were laboratory-confirmed. Data were analyzed with generalized additive models, generalized mixed models, and machine learning models.'}, {'@Label': 'FINDINGS', '@NlmCategory': 'UNASSIGNED', '#text': 'The prevalence of many clinical features exhibited by dengue, chikungunya, and Zika cases differed substantially overall, by age, and by day of illness. Dengue cases were differentiated most by abdominal pain, leukopenia, nausea/vomiting, and basophilia; chikungunya cases were differentiated most by arthralgia and the absence of leukopenia and papular rash; and Zika cases were differentiated most by rash and lack of fever and lymphocytopenia. Dengue and chikungunya cases exhibited similar temperature dynamics during acute illness, and their temperatures were higher than Zika cases. Sixty-two laboratory-confirmed afebrile dengue cases, which would not be captured by any widely used international case definition, presented very similarly to afebrile Zika cases, though some exhibited warning signs of disease severity. The presence of arthralgia, the presence of basophilia, and the absence of fever were the most important model-based predictors of chikungunya, dengue, and Zika, respectively.'}, {'@Label': 'INTERPRETATIONS', '@NlmCategory': 'UNASSIGNED', '#text': 'These findings substantially update our understanding of dengue, chikungunya, and Zika in children while identifying various clinical features that could improve differential diagnoses. The occurrence of afebrile dengue warrants reconsideration of current case definitions.'}, {'@Label': 'FUNDING', '@NlmCategory': 'UNASSIGNED', '#text': 'US National Institutes of Health R01AI099631, P01AI106695, U01AI153416, U19AI118610.'}]
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