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Human immunodeficiency virus 1 (HIV-1) infection is characterized by a dynamic and persistent state of viral replication that overwhelms the host immune system in the absence of antiretroviral therapy (ART). The impact of prolonged treatment on the antiviral efficacy of HIV-1-specific CD8+T cells has nonetheless remained unknown. Here, we used single-cell technologies to address this issue in a cohort of aging individuals infected early during the pandemic and subsequently treated with continuous ART. Our data showed that long-term ART was associated with a process of clonal succession, which effectively rejuvenated HIV-1-specific CD8+T cell populations in the face of immune senescence. Tracking individual transcriptomes further revealed that initially dominant CD8+T cell clonotypes displayed signatures of exhaustion and terminal differentiation, whereas newly dominant CD8+T cell clonotypes displayed signatures of early differentiation and stemness associated with natural control of viral replication. These findings reveal a degree of immune resilience that could inform adjunctive treatments for HIV-1.

In response to the COVID-19 pandemic caused by SARS-CoV-2, governments have adopted a wide range of non-pharmaceutical interventions (NPI). These include stringent measures such as strict lockdowns, closing schools, bars and restaurants, curfews, and barrier gestures such as mask-wearing and social distancing. Deciphering the effectiveness of each NPI is critical to responding to future waves and outbreaks. To this end, we first develop a dynamic model of the French COVID-19 epidemics over a one-year period. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of infection that includes a dynamic transmission rate over time. Multilevel data across French regions are integrated using random effects on the parameters of the mechanistic model, boosting statistical power by multiplying integrated observation series. We estimate the parameters using a new population-based statistical approach based on a Kalman filter, used for the first time in analysing real-world data. We then fit the estimated time-varying transmission rate using a regression model that depends on the NPIs while accounting for vaccination coverage, the occurrence of variants of concern (VoC), and seasonal weather conditions. We show that all NPIs considered have an independent significant association with transmission rates. In addition, we show a strong association between weather conditions that reduces transmission in summer, and we also estimate increased transmissibility of VoC.

A recent study reported exaggerated false positives by popular differential expression methods when analyzing large population samples. We reproduce the differential expression analysis simulation results and identify a caveat in the data generation process. Data not truly generated under the null hypothesis led to incorrect comparisons of benchmark methods. We provide corrected simulation results that demonstrate the good performance of dearseq and argue against the superiority of the Wilcoxon rank-sum test as suggested in the previous study.

Antibodies against citrullinated fibrinogen (anti–Cit‐fibrinogen) have been implicated in rheumatoid arthritis (RA) and associated with cardiovascular risk in RA. The objective of this study was to examine the association between anti–Cit‐fibrinogens and coronary artery disease (CAD) outcomes. We performed the study in an RAcohort based in a large academic institution linked with electronic medical record data containing information on CADoutcomes from medical record review. Using a published bead‐based assay method, we measured 10 types of anti–Cit‐fibrinogens. We applied a score test to determine the association between the anti–Cit‐fibrinogens as a group with CADoutcomes. Principal components analysis (PCA) was performed to assess whether the anti–Cit‐fibrinogens clustered into groups. Each group was then additionally tested for association with CAD. Sensitivity analyses were also performed using a published International Classification of Disease, Ninth Revision code group for ischemic heart disease (IHD) as the outcome. We studied 1,006 RAsubjects (mean ± SDage 61.0 ± 13.0 years; 72.2% anti–cyclic citrullinated peptide positive). As a group, anti–Cit‐fibrinogen was associated with CAD(P= 1.1 × 10−4). From the PCAanalysis, we observed 3 main groups, of which only 1 group, containing 7 of the 10 anti–Cit‐fibrinogens, was significantly associated with CADoutcomes (P= 0.015). In the sensitivity analysis, all anti–Cit‐fibrinogens as a group remained significantly associated with IHD(P= 2.9 × 10−4). Anti–Cit‐fibrinogen antibodies as a group were associated with CADoutcomes in our RAcohort, with the strongest signal for association arising from a subset of the autoantibodies.

Ebola virus disease is a severe hemorrhagic fever with a high fatality rate. We investigate transcriptome profiles at 3 h, 1 day, and 7 days after vaccination with Ad26.ZEBOV and MVA-BN-Filo. 3 h after Ad26.ZEBOV injection, we observe an increase in genes related to antigen presentation, sensing, and T and B cell receptors. The highest response occurs 1 day after Ad26.ZEBOV injection, with an increase of the gene expression of interferon-induced antiviral molecules, monocyte activation, and sensing receptors. This response is regulated by the HESX1, ATF3, ANKRD22, and ETV7 transcription factors. A plasma cell signature is observed on day 7 post-Ad26.ZEBOV vaccination, with an increase of CD138, MZB1, CD38, CD79A, and immunoglobulin genes. We have identified early expressed genes correlated with the magnitude of the antibody response 21 days after the MVA-BN-Filo and 364 days after Ad26.ZEBOV vaccinations. Our results provide early gene signatures that correlate with vaccine-induced Ebola virus glycoprotein-specific antibodies.

Predicting vaccine efficacy remains a challenge. We used a systems vaccinology approach to identify early innate immune correlates of antibody induction in humans receiving the Ebola vaccine rVSV-ZEBOV. Blood samples from days 0, 1, 3, 7, and 14 were analyzed for changes in cytokine levels, innate immune cell subsets, and gene expression. Integrative statistical analyses with cross-validation identified a signature of 5 early innate markers correlating with antibody titers on day 28 and beyond. Among those, IP-10 on day 3 and MFI of CXCR6 on NK cells on day 1 were independent correlates. Consistently, we found an early gene expression signature linked to IP-10. This comprehensive characterization of early innate immune responses to the rVSV-ZEBOV vaccine in humans revealed immune signatures linked to IP-10. These results suggest correlates of vaccine-induced antibody induction and provide a rationale to explore strategies for augmenting the effectiveness of vaccines through manipulation of IP-10.

Clustering is part of unsupervised analysis methods that group samples into homogeneous and separate subgroups of observations also called clusters. To interpret the clusters, statistical hypothesis testing is often used to infer the variables that significantly separate the estimated clusters from each other. However, data-driven hypotheses are thus used for the inference process because the hypotheses are derived from the clustering results. This double use of the data leads traditional hypothesis test to fail to control the Type I error rate particularly because of uncertainty in the clustering process and the potential artificial differences it could create. Three novel statistical hypothesis tests are introduced, each designed to account for the clustering process. These tests efficiently control the Type I error rate by identifying only variables that contain a true signal separating groups of observations. The proposed tests were applied in two distinct contexts: animal ecology and immunology, demonstrating the relevance of the results with real datasets. [ABSTRACT FROM AUTHOR]