Influenza vaccine response profiles are affected by vaccine preparation and preexisting immunity, but not HIV infection

Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 1-Overview of Knowledge Discovery Techniques in Artificial Intelligence

Aim

To perform a systematic review on the application of artificial intelligence (AI) based knowledge discovery techniques in pharmacoepidemiology.

Study Eligibility Criteria

Clinical trials, meta-analyses, narrative/systematic review, and observational studies using (or mentioning articles using) artificial intelligence techniques were eligible. Articles without a full text available in the English language were excluded.

Data Sources

Articles recorded from 1950/01/01 to 2019/05/06 in Ovid MEDLINE were screened.

Participants

Studies including humans (real or simulated) exposed to a drug.

Results

In total, 72 original articles and 5 reviews were identified via Ovid MEDLINE. Twenty different knowledge discovery methods were identified, mainly from the area of machine learning (66/72; 91.7%). Classification/regression (44/72; 61.1%), classification/regression + model optimization (13/72; 18.0%), and classification/regression + features selection (12/72; 16.7%) were the three most frequent tasks in reviewed literature that machine learning methods has been applied to solve. The top three used techniques were artificial neural networks, random forest, and support vector machines models.

Conclusions

The use of knowledge discovery techniques of artificial intelligence techniques has increased exponentially over the years covering numerous sub-topics of pharmacoepidemiology.

Systematic Review Registration

Systematic review registration number in PROSPERO: CRD42019136552.

Mucosal Vaccine Approaches for Prevention of HIV and SIV Transmission

Optimal protective immunity to HIV will likely require that plasma cells, memory B cells and memory T cells be stationed in mucosal tissues at portals of viral entry. Mucosal vaccine administration is more effective than parenteral vaccine delivery for this purpose. The challenge has been to achieve efficient vaccine uptake at mucosal surfaces, and to identify safe and effective adjuvants, especially for mucosally administered HIV envelope protein immunogens. Here, we discuss strategies used to deliver potential HIV vaccine candidates in the intestine, respiratory tract, and male and female genital tract of humans and nonhuman primates. We also review mucosal adjuvants, including Toll-like receptor agonists, which may adjuvant both mucosal humoral and cellular immune responses to HIV protein immunogens.

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

Immunologic response to vaccine challenge in pregnant PTPN22 R620W carriers and non-carriers

Objectives

Influenza infection is a significant cause of respiratory morbidity among pregnant women. Seasonal influenza vaccination engages innate immune receptors to promote protective immunity. A coding polymorphism (R620W) in PTPN22 imparts elevated risk for human infection and autoimmune disease, predisposes to diminished innate immune responses, and associates with reduced immunization responses. We sought to quantify the effects of PTPN22-R620W on humoral and cell-mediated immune responses to the inactivated influenza vaccine among healthy pregnant women.

Study Design

Immune responses were measured in healthy pregnant R620W carrier (n = 17) and non-carrier (n = 33) women receiving the 2013 quadrivalent inactivated influenza vaccine (Fluzone). Hemagglutination inhibition assays were performed to quantify neutralizing antibodies; functional influenza-reactive CD4 T cells were quantified by flow cytometry, and influenza-specific CD8 T cells were enumerated with MHC Class I tetramers. Antibody seroconversion data were evaluated by Chi-square analysis, and the Mann-Whitney or Wilcoxon signed-rank tests were applied to T cell response data.

Results

PTPN22 R620W carrier (n = 17) and non-carrier (n = 33) groups did not differ in age, parity, BMI, gestational age at time of vaccine, or history of prior influenza vaccination. After Fluzone exposure, 51.5% of non-carriers met criteria for antibody seroconversion to H1N1 influenza, compared with 23.5% of R620W carriers (p = 0.06). Influenza-reactive CD4 T cells showed modest increase at days 9–15 after vaccination in both R620W carriers and non-carriers (p = 0.02 and p = 0.04, respectively). However, there was no difference in overall response between the two groups (p = 0.6). The vaccine did not result in significant induction of influenza-specific CD8 T cells in either group.

Conclusions

There was no significant difference among healthy pregnant R620W carriers and non-carriers in H1N1 antibody seroconversion rates after influenza vaccination. Studies of larger cohorts will be needed to define the effect of PTPN22 risk allele carriage on antibody and T cell responses to influenza vaccination during pregnancy.

Original Antigenic Sin Response to RNA Viruses and Antiviral Immunity

The human immune system has evolved to fight against foreign pathogens. It plays a central role in the body's defense mechanism. However, the immune memory geared to fight off a previously recognized pathogen, tends to remember an original form of the pathogen when a variant form subsequently invades. This has been termed 'original antigenic sin'. This adverse immunological effect can alter vaccine effectiveness and sometimes cause enhanced pathogenicity or additional inflammatory responses, according to the type of pathogen and the circumstances of infection. Here we aim to give a simplified conceptual understanding of virus infection and original antigenic sin by comparing and contrasting the two examples of recurring infections such as influenza and dengue viruses in humans.

Downfall of the current antibody correlates of influenza vaccine response in yearly vaccinated subjects: Toward qualitative rather than quantitative assays

Response to seasonal influenza vaccination is currently evaluated by antibody correlates that estimate vaccine seroconversion as well as immune protection. These correlates rely on the general dogmas surrounding seasonal influenza vaccination; that is, that vaccine-induced antibodies would exclusively generate immunity to influenza vaccine strains and that protective immunity would wane before the next season. Here, we summarize recently reported data on immunity to seasonal influenza in healthy individuals and rediscuss results on yearly vaccinated pediatric immunocompromised patients that together highlight the need for revision of the current correlates of vaccine response to shift from quantitative to qualitative measurements.

Immunocompromised Travelers: Demographic Characteristics, Travel Destinations, and Pretravel Health Care from the U.S. Global TravEpiNet Consortium

An increasing number of immunocompromised individuals are pursuing international travel, and a better understanding of their international travel patterns and pretravel health care is needed. We evaluated the clinical features, itineraries, and pretravel health care of 486 immunocompromised international travelers seen at Global TravEpiNet sites from January 2009 to June 2012. We used bivariate analyses and logistic regressions using random intercept models to compare demographic and travel characteristics, vaccines administered, and medications prescribed for immunocompromised travelers versus 30,702 immunocompetent travelers. Immunocompromised travelers pursued itineraries that were largely similar to those of immunocompetent travelers, with nearly one-third of such travelers visiting countries with low human development indices. Biological agents, including tumor necrosis factor blockers, were commonly used immunosuppressive medications among immunocompromised travelers. A strong collaboration between travel-medicine specialists, primary care doctors, and specialist physicians is needed to prepare immunocompromised people for international travel. Incorporating routine questioning and planning regarding travel into the primary care visits of immunocompromised people may be useful.

A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

BACKGROUND

Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual's ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics.

METHODS

Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires.

RESULTS

We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients' immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude.

CONCLUSIONS

Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.