An autoantibody signature predictive for multiple sclerosis.

Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. In this study, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster in approximately 10% of PwMS who share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active preclinical period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically or radiologically isolated neuroinflammatory syndromes.

Challenges and advances in the medical treatment of granulomatous amebic encephalitis.

Granulomatous amebic encephalitis, caused by the free-living amebae Balamuthia mandrillaris or Acanthamoeba species, is a rare and deadly infectious syndrome with a current mortality rate of >90%. Much work remains to define the optimal treatment for these infections. Here, we provide a comprehensive overview of the supporting evidence behind antimicrobials currently recommended by the Centers for Disease Control and Prevention (CDC) with updated statistics on survival rates and medication usage from the CDC Free-Living Ameba Database. We also discuss promising treatments, especially the emerging therapeutic agent nitroxoline, and provide recommendations for the next steps in this area.

The antibiotic resistance reservoir of the lung microbiome expands with age in a population of critically ill patients.

Antimicrobial resistant lower respiratory tract infections are an increasing public health threat and an important cause of global mortality. The lung microbiome can influence susceptibility of respiratory tract infections and represents an important reservoir for exchange of antimicrobial resistance genes. Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene burden, however, corollary studies in the lung microbiome remain absent. We performed an observational study of children and adults with acute respiratory failure admitted to the intensive care unit. From tracheal aspirate RNA sequencing data, we evaluated age-related differences in detectable antimicrobial resistance gene expression in the lung microbiome. Using a multivariable logistic regression model, we find that detection of antimicrobial resistance gene expression was significantly higher in adults compared with children after adjusting for demographic and clinical characteristics. This association remained significant after additionally adjusting for lung bacterial microbiome characteristics, and when modeling age as a continuous variable. The proportion of adults expressing beta-lactam, aminoglycoside, and tetracycline antimicrobial resistance genes was higher compared to children. Together, these findings shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Pulmonary microbiome and transcriptome signatures reveal distinct pathobiologic states associated with mortality in two cohorts of pediatric stem cell transplant patients.

Lung injury is a major determinant of survival after pediatric hematopoietic cell transplantation (HCT). A deeper understanding of the relationship between pulmonary microbes, immunity, and the lung epithelium is needed to improve outcomes. In this multicenter study, we collected 278 bronchoalveolar lavage (BAL) samples from 229 patients treated at 32 children's hospitals between 2014-2022. Using paired metatranscriptomes and human gene expression data, we identified 4 patient clusters with varying BAL composition. Among those requiring respiratory support prior to sampling, in-hospital mortality varied from 22-60% depending on the cluster (p=0.007). The most common patient subtype, Cluster 1, showed a moderate quantity and high diversity of commensal microbes with robust metabolic activity, low rates of infection, gene expression indicating alveolar macrophage predominance, and low mortality. The second most common cluster showed a very high burden of airway microbes, gene expression enriched for neutrophil signaling, frequent bacterial infections, and moderate mortality. Cluster 3 showed significant depletion of commensal microbes, a loss of biodiversity, gene expression indicative of fibroproliferative pathways, increased viral and fungal pathogens, and high mortality. Finally, Cluster 4 showed profound microbiome depletion with enrichment of Staphylococci and viruses, gene expression driven by lymphocyte activation and cellular injury, and the highest mortality. BAL clusters were modeled with a random forest classifier and reproduced in a geographically distinct validation cohort of 57 patients from The Netherlands, recapitulating similar cluster-based mortality differences (p=0.022). Degree of antibiotic exposure was strongly associated with depletion of BAL microbes and enrichment of fungi. Potential pathogens were parsed from all detected microbes by analyzing each BAL microbe relative to the overall microbiome composition, which yielded increased sensitivity for numerous previously occult pathogens. These findings support personalized interpretation of the pulmonary microenvironment in pediatric HCT, which may facilitate biology-targeted interventions to improve outcomes.

Autoantibodies against type I IFNs in humans with alternative NF-κB pathway deficiency.

Patients with autoimmune polyendocrinopathy syndrome type 1 (APS-1) caused by autosomal recessive AIRE deficiency produce autoantibodies that neutralize type I interferons (IFNs)1,2, conferring a predisposition to life-threatening COVID-19 pneumonia3. Here we report that patients with autosomal recessive NIK or RELB deficiency, or a specific type of autosomal-dominant NF-κB2 deficiency, also have neutralizing autoantibodies against type I IFNs and are at higher risk of getting life-threatening COVID-19 pneumonia. In patients with autosomal-dominant NF-κB2 deficiency, these autoantibodies are found only in individuals who are heterozygous for variants associated with both transcription (p52 activity) loss of function (LOF) due to impaired p100 processing to generate p52, and regulatory (IκBδ activity) gain of function (GOF) due to the accumulation of unprocessed p100, therefore increasing the inhibitory activity of IκBδ (hereafter, p52LOF/IκBδGOF). By contrast, neutralizing autoantibodies against type I IFNs are not found in individuals who are heterozygous for NFKB2 variants causing haploinsufficiency of p100 and p52 (hereafter, p52LOF/IκBδLOF) or gain-of-function of p52 (hereafter, p52GOF/IκBδLOF). In contrast to patients with APS-1, patients with disorders of NIK, RELB or NF-κB2 have very few tissue-specific autoantibodies. However, their thymuses have an abnormal structure, with few AIRE-expressing medullary thymic epithelial cells. Human inborn errors of the alternative NF-κB pathway impair the development of AIRE-expressing medullary thymic epithelial cells, thereby underlying the production of autoantibodies against type I IFNs and predisposition to viral diseases.

Validation of a murine proteome-wide phage display library for identification of autoantibody specificities.

Autoimmunity is characterized by loss of tolerance to tissue-specific as well as systemic antigens, resulting in complex autoantibody landscapes. Here, we introduce and extensively validate the performance characteristics of a murine proteome-wide library for phage display immunoprecipitation and sequencing (PhIP-seq) in profiling mouse autoantibodies. This library was validated using 7 genetically distinct mouse lines across a spectrum of autoreactivity. Mice deficient in antibody production (Rag2-/- and µMT) were used to model nonspecific peptide enrichments, while cross-reactivity was evaluated using anti-ovalbumin B cell receptor-restricted OB1 mice as a proof of principle. The PhIP-seq approach was then utilized to interrogate 3 distinct autoimmune disease models. First, serum from Lyn-/- IgD+/- mice with lupus-like disease was used to identify nuclear and apoptotic bleb reactivities. Second, serum from nonobese diabetic (NOD) mice, a polygenic model of pancreas-specific autoimmunity, was enriched in peptides derived from both insulin and predicted pancreatic proteins. Lastly, Aire-/- mouse sera were used to identify numerous autoantigens, many of which were also observed in previous studies of humans with autoimmune polyendocrinopathy syndrome type 1 carrying recessive mutations in AIRE. These experiments support the use of murine proteome-wide PhIP-seq for antigenic profiling and autoantibody discovery, which may be employed to study a range of immune perturbations in mouse models of autoimmunity profiling.

The antibiotic resistance reservoir of the lung microbiome expands with age.

Antimicrobial resistant lower respiratory tract infections (LRTI) are an increasing public health threat, and an important cause of global mortality. The lung microbiome influences LRTI susceptibility and represents an important reservoir for exchange of antimicrobial resistance genes (ARGs). Studies of the gut microbiome have found an association between age and increasing antimicrobial resistance gene (ARG) burden, however corollary studies in the lung microbiome remain absent, despite the respiratory tract representing one of the most clinically significant sites for drug resistant infections. We performed a prospective, multicenter observational study of 261 children and 88 adults with acute respiratory failure, ranging in age from 31 days to ≥ 89 years, admitted to intensive care units in the United States. We performed RNA sequencing on tracheal aspirates collected within 72 hours of intubation, and evaluated age-related differences in detectable ARG expression in the lung microbiome as a primary outcome. Secondary outcomes included number and classes of ARGs detected, proportion of patients with an ARG class, and composition of the lung microbiome. Multivariable logistic regression models (adults vs children) or continuous age (years) were adjusted for sex, race/ethnicity, LRTI status, and days from intubation to specimen collection. Detection of ARGs was significantly higher in adults compared with children after adjusting for sex, race/ethnicity, LRTI diagnosis, and days from intubation to specimen collection (adjusted odds ratio (aOR): 2.16, 95% confidence interval (CI): 1.10-4.22). A greater proportion of adults compared with children had beta-lactam ARGs (31% (CI: 21-41%) vs 13% (CI: 10-18%)), aminoglycoside ARGs (20% (CI: 13-30%) vs 2% (CI: 0.6-4%)), and tetracycline ARGs (14% (CI: 7-23%) vs 3% (CI: 1-5%)). Adults ≥70 years old had the highest proportion of these three ARG classes. The total bacterial abundance of the lung microbiome increased with age, and microbiome alpha diversity varied with age. Taxonomic composition of the lung microbiome, measured by Bray Curtis dissimilarity index, differed between adults and children (p = 0.003). The association between age and increased ARG detection remained significant after additionally including lung microbiome total bacterial abundance and alpha diversity in the multivariable logistic regression model (aOR: 2.38, (CI: 1.25-4.54)). Furthermore, this association remained robust when modeling age as a continuous variable (aOR: 1.02, (CI: 1.01-1.03) per year of age). Taken together, our results demonstrate that age is an independent risk factor for ARG detection in the lower respiratory tract microbiome. These data shape our understanding of the lung resistome in critically ill patients across the lifespan, which may have implications for clinical management and global public health.

Systematic functional interrogation of SARS-CoV-2 host factors using Perturb-seq.

Genomic and proteomic screens have identified numerous host factors of SARS-CoV-2, but efficient delineation of their molecular roles during infection remains a challenge. Here we use Perturb-seq, combining genetic perturbations with a single-cell readout, to investigate how inactivation of host factors changes the course of SARS-CoV-2 infection and the host response in human lung epithelial cells. Our high-dimensional data resolve complex phenotypes such as shifts in the stages of infection and modulations of the interferon response. However, only a small percentage of host factors showed such phenotypes upon perturbation. We further identified the NF-κB inhibitor IκBα (NFKBIA), as well as the translation factors EIF4E2 and EIF4H as strong host dependency factors acting early in infection. Overall, our study provides massively parallel functional characterization of host factors of SARS-CoV-2 and quantitatively defines their roles both in virus-infected and bystander cells.

In host evolution of beta lactam resistance during active treatment for Pseudomonas aeruginosa bacteremia.

Multidrug-resistant (MDR) Pseudomonas aeruginosa has been declared a serious threat by the United States Centers for Disease Control and Prevention. Here, we used whole genome sequencing (WGS) to investigate recurrent P. aeruginosa bloodstream infections in a severely immunocompromised patient. The infections demonstrated unusual, progressive increases in resistance to beta lactam antibiotics in the setting of active treatment with appropriate, guideline-directed agents. WGS followed by comparative genomic analysis of isolates collected over 44 days demonstrated in host evolution of a single P. aeruginosa isolate characterized by stepwise acquisition of two de-novo genetic resistance mechanisms over the course of treatment. We found a novel deletion affecting the ampC repressor ampD and neighboring gene ampE, which associated with initial cefepime treatment failure. This was followed by acquisition of a porin nonsense mutation, OprD, associated with resistance to carbapenems. This study highlights the potential for in-host evolution of P. aeruginosa during bloodstream infections in severely immunocompromised patients despite appropriate antimicrobial therapy. In addition, it demonstrates the utility of WGS for understanding unusual resistance patterns in the clinical context.

Detection of High-Risk Paraneoplastic Antibodies against TRIM9 and TRIM67 Proteins.

OBJECTIVE: Co-occurring anti-tripartite motif-containing protein 9 and 67 autoantibodies (TRIM9/67-IgG) have been reported in only a very few cases of paraneoplastic cerebellar syndrome. The value of these biomarkers and the most sensitive methods of TRIM9/67-IgG detection are not known. METHODS: We performed a retrospective, multicenter study to evaluate the cerebrospinal fluid and serum of candidate TRIM9/67-IgG cases by tissue-based immunofluorescence, peptide phage display immunoprecipitation sequencing, overexpression cell-based assay (CBA), and immunoblot. Cases in which TRIM9/67-IgG was detected by at least 2 assays were considered TRIM9/67-IgG positive. RESULTS: Among these cases (n = 13), CBA was the most sensitive (100%) and revealed that all cases had TRIM9 and TRIM67 autoantibodies. Of TRIM9/67-IgG cases with available clinical history, a subacute cerebellar syndrome was the most common presentation (n = 7/10), followed by encephalitis (n = 3/10). Of these 10 patients, 70% had comorbid cancer (7/10), 85% of whom (n = 6/7) had confirmed metastatic disease. All evaluable cancer biopsies expressed TRIM9 protein (n = 5/5), whose expression was elevated in the cancerous regions of the tissue in 4 of 5 cases. INTERPRETATION: TRIM9/67-IgG is a rare but likely high-risk paraneoplastic biomarker for which CBA appears to be the most sensitive diagnostic assay. ANN NEUROL 2023;94:1086-1101.

Rubella virus tropism and single-cell responses in human primary tissue and microglia-containing organoids.

Rubella virus is an important human pathogen that can cause neurological deficits in a developing fetus when contracted during pregnancy. Despite successful vaccination programs in the Americas and many developed countries, rubella remains endemic in many regions worldwide and outbreaks occur wherever population immunity is insufficient. Intense interest since rubella virus was first isolated in 1962 has advanced our understanding of clinical outcomes after infection disrupts key processes of fetal neurodevelopment. Yet it is still largely unknown which cell types in the developing brain are targeted. We show that in human brain slices, rubella virus predominantly infects microglia. This infection occurs in a heterogeneous population but not in a highly microglia-enriched monoculture in the absence of other cell types. By using an organoid-microglia model, we further demonstrate that rubella virus infection leads to a profound interferon response in non-microglial cells, including neurons and neural progenitor cells, and this response is attenuated by the presence of microglia.

Autoantigen profiling reveals a shared post-COVID signature in fully recovered and long COVID patients.

Some individuals do not return to baseline health following SARS-CoV-2 infection, leading to a condition known as long COVID. The underlying pathophysiology of long COVID remains unknown. Given that autoantibodies have been found to play a role in severity of SARS-CoV-2 infection and certain other post-COVID sequelae, their potential role in long COVID is important to investigate. Here, we apply a well-established, unbiased, proteome-wide autoantibody detection technology (T7 phage-display assay with immunoprecipitation and next-generation sequencing, PhIP-Seq) to a robustly phenotyped cohort of 121 individuals with long COVID, 64 individuals with prior COVID-19 who reported full recovery, and 57 pre-COVID controls. While a distinct autoreactive signature was detected that separated individuals with prior SARS-CoV-2 infection from those never exposed to SARS-CoV-2, we did not detect patterns of autoreactivity that separated individuals with long COVID from individuals fully recovered from COVID-19. These data suggest that there are robust alterations in autoreactive antibody profiles due to infection; however, no association of autoreactive antibodies and long COVID was apparent by this assay.

Whole-genome sequencing rule-out of suspected hospital-onset Rhizopus outbreaks.

Two independent temporal-spatial clusters of hospital-onset Rhizopus infections were evaluated using whole-genome sequencing (WGS). Phylogenetic analysis confirmed that isolates within each cluster were unrelated despite epidemiological suspicion of outbreaks. The ITS1 region alone was insufficient for accurate analysis. WGS has utility for rapid rule-out of suspected nosocomial Rhizopus outbreaks.

Antigenic responses are hallmarks of fibrotic interstitial lung diseases independent of underlying etiologies.

Interstitial lung diseases (ILD) are heterogeneous conditions that may lead to progressive fibrosis and death of affected individuals. Despite diversity in clinical manifestations, enlargement of lung-associated lymph nodes (LLN) in fibrotic ILD patients predicts worse survival. Herein, we revealed a common adaptive immune landscape in LLNs of all ILD patients, characterized by highly activated germinal centers and antigen-activated T cells including regulatory T cells (Tregs). In support of these findings, we identified serum reactivity to 17 candidate auto-antigens in ILD patients through a proteome-wide screening using phage immunoprecipitation sequencing. Autoantibody responses to actin binding LIM protein 1 (ABLIM1), a protein highly expressed in aberrant basaloid cells of fibrotic lungs, were correlated with LLN frequencies of T follicular helper cells and Tregs in ILD patients. Together, we demonstrate that end-stage ILD patients have converging immune mechanisms, in part driven by antigen-specific immune responses, which may contribute to disease progression.

A Predictive Autoantibody Signature in Multiple Sclerosis.

Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. Here, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster of PwMS that share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active prodromal period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid (CSF) and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically- or radiologically-isolated neuroinflammatory syndromes.

Integrated host/microbe metagenomics enables accurate lower respiratory tract infection diagnosis in critically ill children.

BACKGROUNDLower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging because noninfectious respiratory illnesses appear clinically similar and because existing microbiologic tests are often falsely negative or detect incidentally carried microbes, resulting in antimicrobial overuse and adverse outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and treatment remains unclear.METHODSWe used tracheal aspirate RNA-Seq to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n = 117) or of noninfectious respiratory failure (n = 50). We then developed a classifier that integrates the host LRTI probability, abundance of respiratory viruses, and dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm.RESULTSThe host classifier achieved a median AUC of 0.967 by cross-validation, driven by activation markers of T cells, alveolar macrophages, and the interferon response. The integrated classifier achieved a median AUC of 0.986 and increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n = 94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those.CONCLUSIONLower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.FUNDINGSupport for this study was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Heart, Lung, and Blood Institute (UG1HD083171, 1R01HL124103, UG1HD049983, UG01HD049934, UG1HD083170, UG1HD050096, UG1HD63108, UG1HD083116, UG1HD083166, UG1HD049981, K23HL138461, and 5R01HL155418) as well as by the Chan Zuckerberg Biohub.

Validation of a murine proteome-wide phage display library for the identification of autoantibody specificities.

Autoimmunity is characterized by loss of tolerance to tissue-specific as well as systemic antigens, resulting in complex autoantibody landscapes. Here, we introduce and extensively validate the performance characteristics of a murine proteome-wide library for phage display immunoprecipitation and sequencing (PhIP-seq), to profile mouse autoantibodies. This system and library were validated using seven genetic mouse models across a spectrum of autoreactivity. Mice deficient in antibody production (Rag2-/- and µMT) were used to model non-specific peptide enrichments, while cross-reactivity was evaluated using anti-ovalbumin B cell receptor (BCR)-restricted OB1 mice as a proof of principle. The PhIP-seq approach was then utilized to interrogate three distinct autoimmune disease models. First, serum from Lyn-/- IgD+/- mice with lupus-like disease was used to identify nuclear and apoptotic bleb reactivities, lending support to the hypothesis that apoptosis is a shared origin of these antigens. Second, serum from non-obese diabetic (NOD) mice, a polygenic model of pancreas-specific autoimmunity, enriched peptides derived from both insulin and predicted pancreatic proteins. Lastly, Aire-/- mouse sera were used to identify numerous auto-antigens, many of which were also observed in previous studies of humans with autoimmune polyendocrinopathy syndrome type 1 (APS1) carrying recessive mutations in AIRE. Among these were peptides derived from Perilipin-1, a validated autoimmune biomarker of generalized acquired lipodystrophy in humans. Autoreactivity to Perilipin-1 correlated with lymphocyte infiltration in adipose tissue and underscores the approach in revealing previously unknown specificities. These experiments support the use of murine proteome-wide PhIP-seq for antigenic profiling and autoantibody discovery, which may be employed to study a range of immune perturbations in mouse models of autoimmunity.

Autoantigen profiling reveals a shared post-COVID signature in fully recovered and Long COVID patients.

Some individuals do not return to baseline health following SARS-CoV-2 infection, leading to a condition known as Long COVID. The underlying pathophysiology of Long COVID remains unknown. Given that autoantibodies have been found to play a role in severity of COVID infection and certain other post-COVID sequelae, their potential role in Long COVID is important to investigate. Here we apply a well-established, unbiased, proteome-wide autoantibody detection technology (PhIP-Seq) to a robustly phenotyped cohort of 121 individuals with Long COVID, 64 individuals with prior COVID-19 who reported full recovery, and 57 pre-COVID controls. While a distinct autoreactive signature was detected which separates individuals with prior COVID infection from those never exposed to COVID, we did not detect patterns of autoreactivity that separate individuals with Long COVID relative to individuals fully recovered from SARS-CoV-2 infection. These data suggest that there are robust alterations in autoreactive antibody profiles due to infection; however, no association of autoreactive antibodies and Long COVID was apparent by this assay.

Antibodies to repeat-containing antigens in Plasmodium falciparum are exposure-dependent and short-lived in children in natural malaria infections.

Protection against Plasmodium falciparum, which is primarily antibody-mediated, requires recurrent exposure to develop. The study of both naturally acquired limited immunity and vaccine induced protection against malaria remains critical for ongoing eradication efforts. Towards this goal, we deployed a customized P. falciparum PhIP-seq T7 phage display library containing 238,068 tiled 62-amino acid peptides, covering all known coding regions, including antigenic variants, to systematically profile antibody targets in 198 Ugandan children and adults from high and moderate transmission settings. Repeat elements - short amino acid sequences repeated within a protein - were significantly enriched in antibody targets. While breadth of responses to repeat-containing peptides was twofold higher in children living in the high versus moderate exposure setting, no such differences were observed for peptides without repeats, suggesting that antibody responses to repeat-containing regions may be more exposure dependent and/or less durable in children than responses to regions without repeats. Additionally, short motifs associated with seroreactivity were extensively shared among hundreds of antigens, potentially representing cross-reactive epitopes. PfEMP1 shared motifs with the greatest number of other antigens, partly driven by the diversity of PfEMP1 sequences. These data suggest that the large number of repeat elements and potential cross-reactive epitopes found within antigenic regions of P. falciparum could contribute to the inefficient nature of malaria immunity.

Low Prevalence of Interferon α Autoantibodies in People Experiencing Symptoms of Post-Coronavirus Disease 2019 (COVID-19) Conditions, or Long COVID.

Interferon (IFN)-specific autoantibodies have been implicated in severe coronavirus disease 2019 (COVID-19) and have been proposed as a potential driver of the persistent symptoms characterizing "long COVID," a type of postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We report that only 2 of 215 participants with convalescent SARS-CoV-2 infection tested over 394 time points, including 121 people experiencing long COVID symptoms, had detectable IFN-α2 antibodies. Both had been hospitalized during the acute phase of the infection. These data suggest that persistent anti-IFN antibodies, although a potential driver of severe COVID-19, are unlikely to contribute to long COVID symptoms in the postacute phase of the infection.