Microbial longitudinal studies are powerful experimental designs utilized to classify diseases, determine prognosis, and analyze microbial systems dynamics. In longitudinal studies, only identifying differential features between two phenotypes does not provide sufficient information to determine whether a change in the relative abundance is short-term or continuous. Furthermore, sample collection in longitudinal studies suffers from all forms of variability such as a different number of subjects per phenotypic group, a different number of samples per subject, and samples not collected at consistent time points. These inconsistencies are common in studies that collect samples from human subjects. We present MetaLonDA, an R package that is capable of identifying significant time intervals of differentially abundant microbial features. MetaLonDA is flexible such that it can perform differential abundance tests despite inconsistencies associated with sample collection. Extensive experiments on simulated datasets quantitatively demonstrate the effectiveness of MetaLonDA with significant improvement over alternative methods. We applied MetaLonDA to the DIABIMMUNE cohort ( https://pubs.broadinstitute.org/diabimmune ) substantiating significant early lifetime intervals of exposure to Bacteroides and Bifidobacterium in Finnish and Russian infants. Additionally, we established significant time intervals during which novel differentially relative abundant microbial genera may contribute to aberrant immunogenicity and development of autoimmune disease. MetaLonDA is computationally efficient and can be run on desktop machines. The identified differentially abundant features and their time intervals have the potential to distinguish microbial biomarkers that may be used for microbial reconstitution through bacteriotherapy, probiotics, or antibiotics. Moreover, MetaLonDA can be applied to any longitudinal count data such as metagenomic sequencing, 16S rRNA gene sequencing, or RNAseq. MetaLonDA is publicly available on CRAN ( https://CRAN.R-project.org/package=MetaLonDA ).

The COVID-19 pandemic has resulted in a growing number of patients experiencing persistent symptoms and physiological changes after recovering from acute SARS-CoV-2 infection, known as Long COVID. Long COVID is characterized by recurring symptoms and inflammation across multiple organ systems. Diagnosis can be challenging, influenced by factors like demographics, comorbidities, and immune responses. Long COVID impacts various organ systems and can have neuropsychological effects. Health disparities, particularly related to race, contribute to a higher burden of infection and ongoing symptoms in minority populations. Managing Long COVID entails addressing a spectrum of symptoms that encompass physical, cognitive, and psychological aspects. The recovery period for patients with Long COVID can vary significantly, influenced by factors like the severity of the disease, hospitalization, comorbidities, and age. Currently, there are no universally effective treatments, although certain interventions show promise, necessitating further research. Self-management and rehabilitation programs can provide relief, but more research is needed to establish their effectiveness. Preventive measures such as vaccination and the use of antiviral medications and metformin. It is imperative to conduct further research to develop evidence-based guidelines and gain a better understanding of the long-term implications of COVID-19. Long COVID could have substantial economic impact on the labor market, productivity, healthcare expenditures, and overall economic growth. To address the challenges patients with long-term complications face, there is a focus on strategies like promoting telework and flexible work arrangements to accommodate diverse symptoms, particularly chronic fatigue and other Long COVID effects. In conclusion, this review emphasizes the multifaceted complexity of Long COVID and the ongoing need to address its potential long-term health and economic impacts.

MicroRNAs (miRNAs) act as post-transcriptional regulators of gene expression. In sarcoidosis, aberrant miRNA expression may enhance immune responses mounted against an unknown antigenic agent. We tested whether a distinct miRNA signature functions as a diagnostic biomarker and explored its role as an immune modulator in sarcoidosis. The expression of miRNAs in peripheral blood mononuclear cells from subjects who met clinical and histopathologic criteria for sarcoidosis was compared with that observed in matched controls in the ACCESS (A Case Controlled Etiologic Study of Sarcoidosis) study. Signature miRNAs were determined by miRNA microarray analysis and validated by quantitative RT-PCR. Microarray analysis identified 54 mature, human feature miRNAs that were differentially expressed between the groups. Significant feature miRNAs that distinguished subjects with sarcoidosis from controls were selected by means of probabilistic models adjusted for clinical variables. Eight signature miRNAs were chosen to verify the diagnosis of sarcoidosis in a validation cohort, and distinguished subjects with sarcoidosis from controls with a positive predictive value of 88%. We identified both novel and previously described genes and molecular pathways associated with sarcoidosis as targets of these signature miRNAs. Additionally, we demonstrate that signature miRNAs (hsa-miR-150-3p and hsa-miR-342-5p) are significantly associated with reduced lymphocytes and airflow limitations, both of which are known markers of a poor prognosis. Together, these findings suggest that a circulating miRNA signature serves as a noninvasive biomarker that supports the diagnosis of sarcoidosis. Future studies will test the miRNA signature as a prognostication tool to identify unfavorable changes associated with poor clinical outcomes in sarcoidosis.

Patients with autoimmune inflammatory rheumatic diseases (AIIRDs) are at increased risk for severe infections. Vaccine responses and safety profiles may differ between AIIRD patients and the general population. While patients with autoimmune inflammatory rheumatic diseases (AIIRDs) often experience diminished humoral responses and reduced vaccine efficacy, factors such as the type of immunosuppressant medications used and the specific vaccine employed contribute to these outcomes. Notably, individuals undergoing B cell depletion therapy tend to have poor vaccine immunogenicity. However, despite these considerations, vaccine responses are generally considered clinically sufficient. Ideally, immunosuppressed AIIRD patients should receive vaccinations at least two weeks before commencing immunosuppressive treatment. However, it is common for many patients to already be on immunosuppressants during the immunization process. Vaccination rarely triggers flares in AIIRDs; if flares occur, they are typically mild. Despite the heightened infection risk, including COVID-19, among AIIRD patients with rheumatoid arthritis, systemic lupus erythematosus, sarcoidosis, and other diseases on immunosuppressants, the vaccination rates remain suboptimal. The future directions of vaccination in the era of immunosuppression will likely involve customized vaccines with enhanced adjuvants and alternative delivery methods. By addressing the unique challenges faced by immunosuppressed individuals, we may improve vaccine efficacy, reduce the risk of infections, and ultimately enhance the health outcomes. Additionally, clinical trials to evaluate the safety and efficacy of temporarily discontinuing immunosuppressants during vaccination in various AIIRDs are crucial.

Asthma symptoms are often exacerbated by the common-cold-causing rhinovirus (RV). In this study, we characterized the temporal behavior of circulating exosomal microRNAs (ExoMiRNAs) in a longitudinal bi-phasic case-control study of mild asthmatics (n = 12) and matched non-atopic healthy controls (n = 12) inoculated with rhinovirus. We aimed to define clinical and immunologic characteristics associated with differentially expressed (DE) miRNAs. In total, 26 DE ExoMiRNAs, including hsa-let-7f-5p, hsa-let-7a-5p, hsa-miR-122-5p, hsa-miR-101-3p, and hsa-miR-126-3p, were identified between asthmatic and healthy subjects after inoculation with RV. Time series clustering identified a unique Cluster of Upregulated DE ExoMiRNAs with augmenting mean expression and a distinct Cluster of Downregulated DE ExoMiRNAs with mean expression decline in asthmatic subjects upon RV challenge. Notably, the Upregulated Cluster correlated with Th1 and interferon-induced cytokines/chemokines (IFN-$\gamma$ and IFN-$\gamma$-inducible protein-10) and interleukin-10 (IL-10). Conversely, the Downregulated Cluster correlated with IL-13, a Th2 cytokine, pulmonary function measurements (FVC%, FEV1%, and PEF%), and inflammatory biomarkers (FeNO, eosinophil%, and neutrophil%). Key ExoMiRNA–target gene and anti-viral defense mechanisms of the Upregulated and Downregulated Clusters were identified by network and gene enrichment analyses. Our findings provide insight into the regulatory role of ExoMiRNAs in RV-induced asthma.

Background: End-stage renal disease (ESRD) patients experience immune compromise characterized by complex alterations of both innate and adaptive immunity, and results in higher susceptibility to infection and lower response to vaccination. This immune compromise, coupled with greater risk of exposure to infectious disease at hemodialysis (HD) centers, underscores the need for examination of the immune response to the COVID-19 mRNA-based vaccines.Methods: The immune response to the COVID-19 BNT162b2 mRNA vaccine was assessed in 20 HD patients and cohort-matched controls. RNA sequencing of peripheral blood mononuclear cells was performed longitudinally before and after each vaccination dose for a total of six time points per subject. Anti-spike antibody levels were quantified prior to the first vaccination dose (V1D0) and 7 d after the second dose (V2D7) using anti-spike IgG titers and antibody neutralization assays. Anti-spike IgG titers were additionally quantified 6 mo after initial vaccination. Clinical history and lab values in HD patients were obtained to identify predictors of vaccination response.Results: Transcriptomic analyses demonstrated differing time courses of immune responses, with prolonged myeloid cell activity in HD at 1 wk after the first vaccination dose. HD also demonstrated decreased metabolic activity and decreased antigen presentation compared to controls after the second vaccination dose. Anti-spike IgG titers and neutralizing function were substantially elevated in both controls and HD at V2D7, with a small but significant reduction in titers in HD groups (p<0.05). Anti-spike IgG remained elevated above baseline at 6 mo in both subject groups. Anti-spike IgG titers at V2D7 were highly predictive of 6-month titer levels. Transcriptomic biomarkers after the second vaccination dose and clinical biomarkers including ferritin levels were found to be predictive of antibody development.Conclusions: Overall, we demonstrate differing time courses of immune responses to the BTN162b2 mRNA COVID-19 vaccination in maintenance HD subjects comparable to healthy controls and identify transcriptomic and clinical predictors of anti-spike IgG titers in HD. Analyzing vaccination as an in vivo perturbation, our results warrant further characterization of the immune dysregulation of ESRD.Funding: F30HD102093, F30HL151182, T32HL144909, R01HL138628. This research has been funded by the University of Illinois at Chicago Center for Clinical and Translational Science (CCTS) award UL1TR002003.