Animal models of stress and related conditions, including depression, have shown that elevated peripheral levels of inflammatory cytokines have downstream consequences on glutamate (Glu) in the brain. Although studies in human adults with depression have reported evidence of higher inflammation but lower Glu in the anterior cingulate cortex (ACC), the extent to which peripheral inflammation contributes to glutamatergic abnormalities in adolescents with depression is not well-understood. It is also unclear whether antioxidants, such as ascorbate (Asc), may buffer against the effects of inflammation on Glu metabolism. Fifty-five depressed adolescents were recruited in the present cross-sectional study and provided blood samples, from which we assayed pro-inflammatory cytokines, and underwent a short-TE proton magnetic spectroscopy scan at 3T, from which we estimated Glu and Asc in the dorsal ACC. In the 31 adolescents with usable cytokine and Glu data, we found that IL-6 was significantly positively associated with dorsal ACC Glu (β = 0.466 ± 0.199, p = 0.029). Of the 16 participants who had usable Asc data, we found that at higher levels of dorsal ACC Asc, there was a negative association between IL-6 and Glu (interaction effect: β = -0.906 ± 0.433, p = 0.034). Importantly, these results remained significant when controlling for age, gender, percentage of gray matter in the dorsal ACC voxel, BMI, and medication (antidepressant and anti-inflammatory) usage. While preliminary, our results underscore the importance of examining both immune and neural contributors to depression and highlight the potential role of anti-inflammatory compounds in mitigating the adverse effects of inflammation (e.g., glutamatergic neuroexcitotoxicity). Future studies that experimentally manipulate levels of inflammation, and of ascorbate, and that characterize these effects on cortical glutamate concentrations and subsequent behavior in animals and in humans are needed.

The clinical trajectory of COVID-19 may be influenced by previous responses to heterologous viruses. We examined the relationship of Abs against different viruses to clinical trajectory groups from the National Institutes of Health IMPACC (Immunophenotyping Assessment in a COVID-19 Cohort) study of hospitalized COVID-19 patients. Whereas initial Ab titers to SARS-CoV-2 tended to be higher with increasing severity (excluding fatal disease), those to seasonal coronaviruses trended in the opposite direction. Initial Ab titers to influenza and parainfluenza viruses also tended to be lower with increasing severity. However, no significant relationship was observed for Abs to other viruses, including measles, CMV, EBV, and respiratory syncytial virus. We hypothesize that some individuals may produce lower or less durable Ab responses to respiratory viruses generally (reflected in lower baseline titers in our study), and that this may carry over into poorer outcomes for COVID-19 (despite high initial SARS-CoV-2 titers). We further looked at longitudinal changes in Ab responses to heterologous viruses, but found little change during the course of acute COVID-19 infection. We saw significant trends with age for Ab levels to many of these viruses, but no difference in longitudinal SARS-CoV-2 titers for those with high versus low seasonal coronavirus titers. We detected no difference in longitudinal SARS-CoV-2 titers for CMV seropositive versus seronegative patients, although there was an overrepresentation of CMV seropositives among the IMPACC cohort, compared with expected frequencies in the United States population. Our results both reinforce findings from other studies and suggest (to our knowledge) new relationships between the response to SARS-CoV-2 and Abs to heterologous viruses.

Background/objectives

Bone is a preferred site of breast cancer metastasis, suggesting the presence of tissue-specific features that attract and promote the outgrowth of breast cancer cells. We sought to identify parameters of human bone tissue associated with breast cancer cell osteotropism and colonization in the metastatic niche.

Methods

Migration and colonization patterns of MDA-MB-231-fLuc-EGFP (luciferase-enhanced green fluorescence protein) and MCF-7-fLuc-EGFP breast cancer cells were studied in co-culture with cancellous bone tissue fragments isolated from 14 hip arthroplasties. Breast cancer cell migration into tissues and toward tissue-conditioned medium was measured in Transwell migration chambers using bioluminescence imaging and analyzed as a function of secreted factors measured by multiplex immunoassay. Patterns of breast cancer cell colonization were evaluated with fluorescence microscopy and immunohistochemistry.

Results

Enhanced MDA-MB-231-fLuc-EGFP breast cancer cell migration to bone-conditioned versus control medium was observed in 12/14 specimens (P = .0014) and correlated significantly with increasing levels of the adipokines/cytokines leptin (P = .006) and IL-1β (P = .001) in univariate and multivariate regression analyses. Fluorescence microscopy and immunohistochemistry of fragments underscored the extreme adiposity of adult human bone tissues and revealed extensive breast cancer cell colonization within the marrow adipose tissue compartment.

Conclusions

Our results show that breast cancer cells migrate to human bone tissue-conditioned medium in association with increasing levels of leptin and IL-1β, and colonize the bone marrow adipose tissue compartment of cultured fragments. Bone marrow adipose tissue and its molecular signals may be important but understudied components of the breast cancer metastatic niche.

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Chronic inflammation, a decline in immune responsiveness, and reduced cardiovascular function are all associated with aging, but the relationships among these phenomena remain unclear. Here, we longitudinally profiled a total of 84 signaling conditions in 91 young and older adults and observed an age-related reduction in cytokine responsiveness within four immune cell lineages, most prominently T cells. The phenotype can be partially explained by elevated baseline levels of phosphorylated STAT (pSTAT) proteins and a different response capacity of naive versus memory T cell subsets to interleukin 6 (IL-6), interferon α (IFN-α), and, to a lesser extent, IL-21 and IFN-γ. Baseline pSTAT levels tracked with circulating levels of C-reactive protein (CRP), and we derived a cytokine response score that negatively correlates with measures of cardiovascular disease, specifically diastolic dysfunction and atherosclerotic burden, outperforming CRP. Thus, we identified an immunological link between inflammation, decreased cell responsiveness in the JAK-STAT pathway, and cardiovascular aging. Targeting chronic inflammation may ameliorate this deficiency in cellular responsiveness and improve cardiovascular function.

Bone marrow mononuclear cell (BM-MNC) therapy in ST-elevation acute myocardial infarction (STEMI) has no biological inclusion criteria. Here, we analyzed 63 biomarkers and cytokines in baseline plasma samples from 77 STEMI patients treated with BM-MNCs in the TIME and Late-TIME trials as well as 61 STEMI patients treated with placebo. Response to cell therapy was defined by changes in left ventricular ejection fraction, systolic/diastolic volumes, and wall motion indexes. We investigated the clinical value of circulating proteins in outcome prediction using significance testing, partial least squares discriminant analysis, and receiver operating characteristic (ROC) analysis. Responders had higher biomarker levels (76-94% elevated) than non-responders. Several biomarkers had values that differed significantly (P < 0.05) between responders and non-responders including stem cell factor, platelet-derived growth factor, and interleukin-15. We then used these lead candidates for ROC analysis and found multiple biomarkers with values areas under the curve >0.70 including interleukin 15. These biomarkers were not involved in the placebo-treated subjects suggesting that they may have predictive power. We conclude that plasma profiling after STEMI may help identify patients with a greater likelihood of response to cell-based treatment. Prospective trials are needed to assess the predictive value of the circulating biomarkers.

BACKGROUNDProlonged symptoms after SARS-CoV-2 infection are well documented. However, which factors influence development of long-term symptoms, how symptoms vary across ethnic groups, and whether long-term symptoms correlate with biomarkers are points that remain elusive.METHODSAdult SARS-CoV-2 reverse transcription PCR-positive (RT-PCR-positive) patients were recruited at Stanford from March 2020 to February 2021. Study participants were seen for in-person visits at diagnosis and every 1-3 months for up to 1 year after diagnosis; they completed symptom surveys and underwent blood draws and nasal swab collections at each visit.RESULTSOur cohort (n = 617) ranged from asymptomatic to critical COVID-19 infections. In total, 40% of participants reported at least 1 symptom associated with COVID-19 six months after diagnosis. Median time from diagnosis to first resolution of all symptoms was 44 days; median time from diagnosis to sustained symptom resolution with no recurring symptoms for 1 month or longer was 214 days. Anti-nucleocapsid IgG level in the first week after positive RT-PCR test and history of lung disease were associated with time to sustained symptom resolution. COVID-19 disease severity, ethnicity, age, sex, and remdesivir use did not affect time to sustained symptom resolution.CONCLUSIONWe found that all disease severities had a similar risk of developing post-COVID-19 syndrome in an ethnically diverse population. Comorbid lung disease and lower levels of initial IgG response to SARS-CoV-2 nucleocapsid antigen were associated with longer symptom duration.TRIAL REGISTRATIONClinicalTrials.gov, NCT04373148.FUNDINGNIH UL1TR003142 CTSA grant, NIH U54CA260517 grant, NIEHS R21 ES03304901, Sean N Parker Center for Allergy and Asthma Research at Stanford University, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative, Sunshine Foundation, Crown Foundation, and Parker Foundation.

Motivation

Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.

Results

We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.

Availability and implementation

Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.

Supplementary information

Supplementary data are available at Bioinformatics online.

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 of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.