Hyperactive and damaging inflammation is a hallmark of severe rather than mild Coronavirus disease 2019 (COVID-19). To uncover key inflammatory differentiators between severe and mild COVID-19, we applied an unbiased single-cell transcriptomic analysis. We integrated two single-cell RNA-seq datasets with COVID-19 patient samples, one that sequenced bronchoalveolar lavage (BAL) cells and one that sequenced peripheral blood mononuclear cells (PBMCs). The combined cell population was then analyzed with a focus on genes associated with disease severity. The immunomodulatory long non-coding RNAs (lncRNAs) NEAT1 and MALAT1 were highly differentially expressed between mild and severe patients in multiple cell types. Within those same cell types, the concurrent detection of other severity-associated genes involved in cellular stress response and apoptosis regulation suggests that the pro-inflammatory functions of these lncRNAs may foster cell stress and damage. Thus, NEAT1 and MALAT1 are potential components of immune dysregulation in COVID-19 that may provide targets for severity related diagnostic measures or therapy.

Obesity is a growing epidemic in most developed countries including the United States resulting in an increased number of obese patients with end-stage renal disease. A previous study has shown that obese patients with end-stage renal disease have a survival benefit with transplantation compared with dialysis. However, due to serious comorbidities, many centers place restrictions on the selection of obese patients for transplantation. Further, due to obese patients having an increased risk of diabetes, it is unclear whether obesity can be an independent risk, independent of diabetes for increasing adverse renal transplant outcomes. To investigate the role of obesity in kidney transplantation, we used the Scientific Registry of Transplant Recipients database. After filtering for subjects that had the full set of covariates including age, gender, graft type, ethnicity, diabetes, peripheral vascular disease, dialysis time and time period of transplantation for our analysis, 191,091 subjects were included in the analyses. Using multivariate logistic regression analyses adjusted for covariates we determined whether obesity is an independent risk factor for adverse outcomes such as delayed graft function, acute rejection, urine protein and graft failure. Cox regression modeling was used to determine hazard ratios of graft failure. Using multivariate model analyses, we found that obese patients have significantly increased risk of adverse transplant outcomes, including delayed graft function, graft failure, urine protein and acute rejection. Cox regression modeling hazard ratios showed that obesity also increased risk of graft failure. Life-table survival curves showed that obesity may be a risk factor independent of diabetes mellitus for a shorter time to graft failure. A key observation in our study is that the risks for adverse outcome of obesity are progressive with increasing body mass index. Furthermore, pre-obese overweight recipients compared with normal weight recipients also had increased risks of adverse outcomes related to kidney transplantation.

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 ).

Differences in asthma severity may be related to inflammation in the airways. The lower airway microbiota has been associated with clinical features such as airway obstruction, symptom control, and response to corticosteroids. To assess the relationship between local airway inflammation, severity of disease, and the lower airway microbiota in atopic asthmatics. A cohort of young adult, atopic asthmatics with intermittent or mild/moderate persistent symptoms (n = 13) were assessed via bronchoscopy, lavage, and spirometry. These individuals were compared to age matched non-asthmatic controls (n = 6) and to themselves after six weeks of treatment with fluticasone propionate (FP). Inflammation of the airways was assessed via a cytokine and chemokine panel. Lower airway microbiota composition was determined by metagenomic shotgun sequencing. Unsupervised clustering of cytokines and chemokines prior to treatment with FP identified two asthmatic phenotypes (AP), termed AP1 and AP2, with distinct bronchoalveolar lavage inflammatory profiles. AP2 was associated with more obstruction, compared to AP1. After treatment with FP reduced MIP-1β and TNF-α and increased IL-2 was observed. A module of highly correlated cytokines that include MIP-1β and TNF-α was identified that negatively correlated with pulmonary function. Independently, IL-2 was positively correlated with pulmonary function. The airway microbiome composition correlated with asthmatic phenotypes. AP2, prior to FP treatment, was enriched with Streptococcus pneumoniae. Unique associations between IL-2 or the cytokine module and the microbiota composition of the airways were observed in asthmatics subjects prior to treatment but not after or in controls. The underlying inflammation in atopic asthma is related to the composition of microbiota and is associated with severity of airway obstruction. Treatment with inhaled corticosteroids was associated with changes in the airway inflammatory response to microbiota.

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.

Prenatal maternal exposure to air pollution may cause adverse health effects in offspring, potentially through altered immune responses. Maternal psychosocial distress can also alter immune function and may increase gestational vulnerability to air pollution exposure. We investigated whether prenatal exposure to air pollution is associated with altered immune responses in cord blood mononuclear cells (CBMCs) and potential modification by maternal depression in 463 women recruited in early pregnancy (1999–2001) into the Project Viva longitudinal cohort. We estimated black carbon (BC), fine particulate matter (PM_2.5), residential proximity to major roadways, and near-residence traffic density, averaged over pregnancy. Women reported depressive symptoms in mid-pregnancy (Edinburgh Postnatal Depression Scale) and depression history by questionnaire. Immune responses were assayed by concentrations of three cytokines (IL-6, IL-10, and TNF-α), in unstimulated or stimulated (phytohemagglutinin (PHA), cockroach extract (Bla g 2), house dust mite extract (Der f 1)) CBMCs. Using multivariable linear or Tobit regression analyses, we found that CBMCs production of IL-6, TNF-a, and IL-10 were all lower in mothers exposed to higher levels of PM_2.5 during pregnancy. A suggestive but not statistically significant pattern of lower cord blood cytokine concentrations from ever (versus never) depressed women exposed to PM_2.5, BC, or traffic was also observed and warrants further study.