Fc Characteristics Mediate Selective Placental Transfer of IgG in HIV-Infected Women.

The placental transfer of maternal IgG is critical for infant protection against infectious pathogens. However, factors that modulate the placental transfer of IgG remain largely undefined. HIV-infected women have impaired placental IgG transfer, presenting a unique "disruption model" to define factors that modulate placental IgG transfer. We measured the placental transfer efficiency of maternal HIV and pathogen-specific IgG in US and Malawian HIV-infected mothers and their HIV-exposed uninfected and infected infants. We examined the role of maternal HIV disease progression, infant factors, placental Fc receptor expression, IgG subclass, and glycan signatures and their association with placental IgG transfer efficiency. Maternal IgG characteristics, such as binding to placentally expressed Fc receptors FcγRIIa and FcγRIIIa, and Fc region glycan profiles were associated with placental IgG transfer efficiency. Our findings suggest that Fc region characteristics modulate the selective placental transfer of IgG, with implications for maternal vaccine design and infant health.

Durability of Protection Against COVID-19 Through the Delta Surge for the NVX-CoV2373 Vaccine.

BACKGROUND: Protein-based vaccines for COVID-19 provide a traditional vaccine platform with long-lasting protection for non-SARS-CoV-2 pathogens and may complement messenger RNA vaccines as a booster dose. While NVX-CoV2373 showed substantial early efficacy, the durability of protection has not been delineated. METHODS: The PREVENT-19 vaccine trial employed a blinded crossover design; the original placebo arm received NVX-CoV2373 after efficacy was established. Using novel statistical methods that integrate surveillance data of circulating strains with post-crossover cases, we estimated placebo-controlled vaccine efficacy and durability of NVX-CoV2373 against both pre-Delta and Delta strains of SARS-CoV-2. RESULTS: Vaccine efficacy against pre-Delta strains of COVID-19 was 89% (95% CI: 75%, 95%) and 87% (72%, 94%) at 0 and 90 days after 2 doses of NVX-CoV2373, respectively, with no evidence of waning (p=0.93). Vaccine efficacy against the Delta strain was 88% (71%, 95%), 82% (56%, 92%), and 77% (44%, 90%) at 40, 120, and 180 days, respectively, with evidence of waning (p<0.01). In sensitivity analyses, the estimated Delta vaccine efficacy at 120 days ranged from 66% (15%, 86%) to 89% (74%, 95%) per various assumptions of the surveillance data. CONCLUSION: NVX-CoV2373 has high initial efficacy against pre-Delta and Delta strains of COVID-19 with little evidence of waning for pre-Delta strains through 90 days and moderate waning against Delta strains over 180 days.

A controlled effects approach to assessing immune correlates of protection.

An immune correlate of risk (CoR) is an immunologic biomarker in vaccine recipients associated with an infectious disease clinical endpoint. An immune correlate of protection (CoP) is a CoR that can be used to reliably predict vaccine efficacy (VE) against the clinical endpoint and hence is accepted as a surrogate endpoint that can be used for accelerated approval or guide use of vaccines. In randomized, placebo-controlled trials, CoR analysis is limited by not assessing a causal vaccine effect. To address this limitation, we construct the controlled risk curve of a biomarker, which provides the causal risk of an endpoint if all participants are assigned vaccine and the biomarker is set to different levels. Furthermore, we propose a causal CoP analysis based on controlled effects, where for the important special case that the biomarker is constant in the placebo arm, we study the controlled vaccine efficacy curve that contrasts the controlled risk curve with placebo arm risk. We provide identification conditions and formulae that account for right censoring of the clinical endpoint and two-phase sampling of the biomarker, and consider G-computation estimation and inference under a semiparametric model such as the Cox model. We add modular approaches to sensitivity analysis that quantify robustness of CoP evidence to unmeasured confounding. We provide an application to two phase 3 trials of a dengue vaccine indicating that controlled risk of dengue strongly varies with 50$\%$ neutralizing antibody titer. Our work introduces controlled effects causal mediation analysis to immune CoP evaluation.

Optimizing deep learning-based segmentation of densely packed cells using cell surface markers.

BACKGROUND: Spatial molecular profiling depends on accurate cell segmentation. Identification and quantitation of individual cells in dense tissues, e.g. highly inflamed tissue caused by viral infection or immune reaction, remains a challenge. METHODS: We first assess the performance of 18 deep learning-based cell segmentation models, either pre-trained or trained by us using two public image sets, on a set of immunofluorescence images stained with immune cell surface markers in skin tissue obtained during human herpes simplex virus (HSV) infection. We then further train eight of these models using up to 10,000+ training instances from the current image set. Finally, we seek to improve performance by tuning parameters of the most successful method from the previous step. RESULTS: The best model before fine-tuning achieves a mean Average Precision (mAP) of 0.516. Prediction performance improves substantially after training. The best model is the cyto model from Cellpose. After training, it achieves an mAP of 0.694; with further parameter tuning, the mAP reaches 0.711. CONCLUSION: Selecting the best model among the existing approaches and further training the model with images of interest produce the most gain in prediction performance. The performance of the resulting model compares favorably to human performance. The imperfection of the final model performance can be attributed to the moderate signal-to-noise ratio in the imageset.

Correlates of Protection, Thresholds of Protection, and Immunobridging among Persons with SARS-CoV-2 Infection.

Several studies have shown that neutralizing antibody levels correlate with immune protection from COVID-19 and have estimated the relationship between neutralizing antibodies and protection. However, results of these studies vary in terms of estimates of the level of neutralizing antibodies required for protection. By normalizing antibody titers, we found that study results converge on a consistent relationship between antibody levels and protection from COVID-19. This finding can be useful for planning future vaccine use, determining population immunity, and reducing the global effects of the COVID-19 pandemic.

The clinical effect of point-of-care HIV diagnosis in infants: a systematic review and meta-analysis.

BACKGROUND: Timely diagnosis and treatment of HIV is crucial in HIV-exposed infants to prevent the high rates of mortality seen during the first 2 years of life if HIV is untreated. However, challenges with sample transportation, testing, and result delivery to caregivers have led to long delays in treatment initiation. We aimed to compare the clinical effect of point-of-care HIV testing versus laboratory-based testing (standard of care) in HIV-exposed infants. METHODS: We did a systematic review and meta-analysis and searched PubMed, MEDLINE, Cochrane Central Register of Controlled Trials, Embase, Conference Proceedings Citation Index-Science, and WHO Global Index Medicus, from Jan 1, 2014, to Aug 31, 2020. Studies were included if they pertained to the use of point-of-care nucleic acid testing for infant HIV diagnosis, had a laboratory-based nucleic acid test as the comparator or standard of care against the index test (same-day point-of-care testing), evaluated clinical outcomes when point-of-care testing was used, and included HIV-exposed infants aged younger than 2 years. Studies were excluded if they did not use a laboratory-based comparator, a nucleic acid test that had been approved by a stringent regulatory authority, or diagnostic-accuracy or performance evaluations (eg, no clinical outcomes included). Reviews, non-research letters, commentaries, and editorials were also excluded. The risk of bias was evaluated using the ROBINS-I framework. Data were extracted from published reports. Data from all studies were analysed using frequency statistics to describe the overall populations evaluated and their results. Key outcomes were time to result delivery and antiretroviral therapy initiation, and proportion of HIV-positive infants initiated on antiretroviral therapy within 60 days after sample collection. FINDINGS: 164 studies were identified by the search and seven were included in the analysis, comprising 37 377 infants in total across 15 countries, including 25 170 (67%) who had point-of-care HIV testing and 12 207 (33%) who had standard-of-care testing. The certainty of evidence was high. Same-day point-of-care testing led to a significantly shorter time between sample collection and result delivery to caregivers compared with standard-of-care testing (median 0 days [95% CI 0-0] vs 35 days [35-37]). Time from sample collection to antiretroviral therapy initiation in infants found to be HIV-positive was significantly lower with point-of-care testing compared with standard of care (median 0 days [95% CI 0-1] vs 40 days [36-44]). When each study's result was weighted equally, 90·3% (95% CI 76·7-96·5) of HIV-positive infants diagnosed using point-of-care testing had started antiretroviral therapy within 60 days of sample collection, compared with only 51·6% (27·1-75·7) who had standard-of-care testing (odds ratio 8·74 [95% CI 6·6-11·6]; p<0·0001). INTERPRETATION: Overall, the certainty of the evidence in this analysis was rated as high for the primary outcomes related to result delivery and treatment initiation, with no serious risk of bias, inconsistency, indirectness, or imprecision. In HIV-exposed infants, same-day point-of-care HIV testing was associated with significantly improved time to result delivery, time to antiretroviral therapy initiation, and proportion of HIV-positive infants starting antiretroviral therapy within 60 days compared with standard of care. FUNDING: The Bill & Melinda Gates Foundation.

A controlled effects approach to assessing immune correlates of protection.

An immune correlate of risk (CoR) is an immunologic biomarker in vaccine recipients associated with an infectious disease clinical endpoint. An immune correlate of protection (CoP) is a CoR that can be used to reliably predict vaccine efficacy (VE) against the clinical endpoint and hence is accepted as a surrogate endpoint that can be used for accelerated approval or guide use of vaccines. In randomized, placebo-controlled trials, CoR analysis is limited by not assessing a causal vaccine effect. To address this limitation, we construct the controlled risk curve of a biomarker, which provides the causal risk of an endpoint if all participants are assigned vaccine and the biomarker is set to different levels. Furthermore, we propose a causal CoP analysis based on controlled effects, where for the important special case that the biomarker is constant in the placebo arm, we study the controlled vaccine efficacy curve that contrasts the controlled risk curve with placebo arm risk. We provide identification conditions and formulae that account for right censoring of the clinical endpoint and two-phase sampling of the biomarker, and consider G-computation estimation and inference under a semiparametric model such as the Cox model. We add modular approaches to sensitivity analysis that quantify robustness of CoP evidence to unmeasured confounding. We provide an application to two phase 3 trials of a dengue vaccine indicating that controlled risk of dengue strongly varies with 50$\%$ neutralizing antibody titer. Our work introduces controlled effects causal mediation analysis to immune CoP evaluation.

Frequent Development of Broadly Neutralizing Antibodies in Early Life in a Large Cohort of Children With Human Immunodeficiency Virus.

BACKGROUND: Recent studies have indicated that broadly neutralizing antibodies (bnAbs) in children may develop earlier after human immunodeficiency virus (HIV) infection compared to adults. METHODS: We evaluated plasma from 212 antiretroviral therapy-naive children with HIV (1-3 years old). Neutralization breadth and potency was assessed using a panel of 10 viruses and compared to adults with chronic HIV. The magnitude, epitope specificity, and immunoglobulin (Ig)G subclass distribution of Env-specific antibodies were assessed using a binding antibody multiplex assay. RESULTS: One-year-old children demonstrated neutralization breadth comparable to chronically infected adults, whereas 2- and 3-year-olds exhibited significantly greater neutralization breadth (P = .014). Likewise, binding antibody responses increased with age, with levels in 2- and 3-year-old children comparable to adults. Overall, there was no significant difference in antibody specificities or IgG subclass distribution between the pediatric and adult cohorts. It is interesting to note that the neutralization activity was mapped to a single epitope (CD4 binding site, V2 or V3 glycans) in only 5 of 38 pediatric broadly neutralizing samples, which suggests that most children may develop a polyclonal neutralization response. CONCLUSIONS: These results contribute to a growing body of evidence suggesting that initiating HIV immunization early in life may present advantages for the development of broadly neutralizing antibody responses.

Testing a global null hypothesis using ensemble machine learning methods.

Testing a global null hypothesis that there are no significant predictors for a binary outcome of interest among a large set of biomarker measurements is an important task in biomedical studies. We seek to improve the power of such testing methods by leveraging ensemble machine learning methods. Ensemble machine learning methods such as random forest, bagging, and adaptive boosting model the relationship between the outcome and the predictor nonparametrically, while stacking combines the strength of multiple learners. We demonstrate the power of the proposed testing methods through Monte Carlo studies and show the use of the methods by applying them to the immunologic biomarkers dataset from the RV144 HIV vaccine efficacy trial.

Rapid Collection of Human Rectal Secretions Using OriCol Devices Is Suitable for Measurement of Mucosal Ig without Blood Contamination.

Measurements of IgG and IgA in human rectal secretions are used to evaluate the Abs elicited by HIV vaccines or the bioaccumulation following immunoprophylaxis at the sites of HIV exposure. To improve sampling methods and tolerability of the procedure, we optimized a balloon device (OriCol) for rectal microbiome sampling requiring 10 second inflation and compared this method to a 5 minute collection using sponges. Lubrication of the device did not interfere with IgG, IgA, or hemoglobin ELISA. Lubricated OriCols inflated to 30 cc minimized hemoglobin contamination (<4.68 ng/ml) compared with collections with two sponge types (Weck-Cel: 267.2 ng/ml, p < 0.0001; and Merocel: 59.38 ng/ml, p = 0.003). Median human serum albumin for OriCols was 14.9 µg/ml, whereas Merocels and Weck-Cels were 28.57 µg/ml (p = 0.0005) and 106.2 µg/ml (p = 0.0002), respectively. Consistent with reduced systemic contamination, the median IgG measured in OriCol-collected rectal secretions (986 ng) was lower than secretions from sponges (Weck-Cel: 8588 ng, p < 0.0001; Merocel: 2509 ng, p = 0.0389). The median IgA yield of samples using the OriCol method (75,253 ng) was comparable to that using Merocel (71,672 ng; p = 0.6942) but significantly higher than Weck-Cel sponges (16,173 ng, p = 0.0336). Median recovery volumes for OriCols were 800 µl, whereas Merocels and Weck-Cels were 615 µl (p = 0.0010) and 655 µl (p = 0.0113), respectively. The balloon device was acceptable among 23 participants, as 85.1% experiencing their first collection ranked it as "seven: acceptable - a lot" or "six: acceptable - somewhat" in a seven-point Likert scale. Therefore, lubricated OriCols inflated to 30 cc allowed for a rapid, well-tolerated, blood-free collection of human rectal secretions.

Clinical Endpoints for Evaluating Efficacy in COVID-19 Vaccine Trials.

Several vaccine candidates to protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (COVID-19) have entered or will soon enter large-scale, phase 3, placebo-controlled randomized clinical trials. To facilitate harmonized evaluation and comparison of the efficacy of these vaccines, a general set of clinical endpoints is proposed, along with considerations to guide the selection of the primary endpoints on the basis of clinical and statistical reasoning. The plausibility that vaccine protection against symptomatic COVID-19 could be accompanied by a shift toward more SARS-CoV-2 infections that are asymptomatic is highlighted, as well as the potential implications of such a shift.

A Deferred-Vaccination Design to Assess Durability of COVID-19 Vaccine Effect After the Placebo Group Is Vaccinated.

Multiple candidate vaccines to prevent COVID-19 have entered large-scale phase 3 placebo-controlled randomized clinical trials, and several have demonstrated substantial short-term efficacy. At some point after demonstration of substantial efficacy, placebo recipients should be offered the efficacious vaccine from their trial, which will occur before longer-term efficacy and safety are known. The absence of a placebo group could compromise assessment of longer-term vaccine effects. However, by continuing follow-up after vaccination of the placebo group, this study shows that placebo-controlled vaccine efficacy can be mathematically derived by assuming that the benefit of vaccination over time has the same profile for the original vaccine recipients and the original placebo recipients after their vaccination. Although this derivation provides less precise estimates than would be obtained by a standard trial where the placebo group remains unvaccinated, this proposed approach allows estimation of longer-term effect, including durability of vaccine efficacy and whether the vaccine eventually becomes harmful for some. Deferred vaccination, if done open-label, may lead to riskier behavior in the unblinded original vaccine group, confounding estimates of long-term vaccine efficacy. Hence, deferred vaccination via blinded crossover, where the vaccine group receives placebo and vice versa, would be the preferred way to assess vaccine durability and potential delayed harm. Deferred vaccination allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain them on placebo, yet still allows important insights about immunologic and clinical effectiveness over time.

Four-parameter paired response curve for serial dilution assays.

Newer immunoassay platforms offer improved signal-to-noise ratio but are more expensive. Thus, it is more cost efficient to perform these assays at a few selected, rather than a full series of, sample dilutions. We propose a new four-parameter paired response curve to model the relationship between assay outcomes from two sample dilutions and study likelihood-based inference. Given a fitted paired response curve, we can predict assay outcomes for de novo dilutions of samples, which enables cross-protocol comparison of immune response biomarkers even when different protocols use different sample dilutions. Numerical studies on both simulated and real data are presented.

Improving random forest predictions in small datasets from two-phase sampling designs.

BACKGROUND: While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases-a common situation in biomedical studies, which often have rare outcomes and covariates whose measurement is resource-intensive. METHODS: Using an immunologic marker dataset from a phase III HIV vaccine efficacy trial, we seek to optimize random forest prediction performance using combinations of variable screening, class balancing, weighting, and hyperparameter tuning. RESULTS: Our experiments show that while class balancing helps improve random forest prediction performance when variable screening is not applied, class balancing has a negative impact on performance in the presence of variable screening. The impact of the weighting similarly depends on whether variable screening is applied. Hyperparameter tuning is ineffective in situations with small sample sizes. We further show that random forests under-perform generalized linear models for some subsets of markers, and prediction performance on this dataset can be improved by stacking random forests and generalized linear models trained on different subsets of predictors, and that the extent of improvement depends critically on the dissimilarities between candidate learner predictions. CONCLUSION: In small datasets from two-phase sampling design, variable screening and inverse sampling probability weighting are important for achieving good prediction performance of random forests. In addition, stacking random forests and simple linear models can offer improvements over random forests.

Fast Grid Search and Bootstrap-based Inference for Continuous Two-phase Polynomial Regression Models.

Two-phase polynomial regression models (Robison, 1964; Fuller, 1969; Gallant and Fuller, 1973; Zhan et al., 1996) are widely used in ecology, public health, and other applied fields to model nonlinear relationships. These models are characterized by the presence of threshold parameters, across which the mean functions are allowed to change. That the threshold is a parameter of the model to be estimated from the data is an essential feature of two-phase models. It distinguishes them, and more generally, multi-phase models, from the spline models and has profound implications for both computation and inference for the models. Estimation of two-phase polynomial regression models is a non-convex, non-smooth optimization problem. Grid search provides high quality solutions to the estimation problem, but is very slow when done by brute force. Building upon our previous work on piecewise linear two-phase regression models estimation, we develop fast grid search algorithms for two-phase polynomial regression models and demonstrate their performance. Furthermore, we develop bootstrap-based pointwise and simultaneous confidence bands for mean functions. Monte Carlo studies are conducted to demonstrate the computational and statistical properties of the proposed methods. Three real datasets are used to help illustrate the application of two-phase models, with special attention on model choice.

Fc Gamma Receptor Polymorphisms Modulated the Vaccine Effect on HIV-1 Risk in the HVTN 505 HIV Vaccine Trial.

HIV Vaccine Trials Network (HVTN) 505 was a phase 2b efficacy trial of a DNA/recombinant adenovirus 5 (rAd5) HIV vaccine regimen. Although the trial was stopped early for lack of overall efficacy, later correlates of risk and sieve analyses generated the hypothesis that the DNA/rAd5 vaccine regimen protected some vaccinees from HIV infection yet enhanced HIV infection risk for others. Here, we assessed whether and how host Fc gamma receptor (FcγR) genetic variations influenced the DNA/rAd5 vaccine regimen's effect on HIV infection risk. We found that vaccine receipt significantly increased HIV acquisition compared with placebo receipt among participants carrying the FCGR2C-TATA haplotype (comprising minor alleles of four FCGR2C single-nucleotide polymorphism [SNP] sites) (hazard ratio [HR] = 9.79, P = 0.035) but not among participants without the haplotype (HR = 0.86, P = 0.67); the interaction of vaccine and haplotype effect was significant (P = 0.034). Similarly, vaccine receipt increased HIV acquisition compared with placebo receipt among participants carrying the FCGR3B-AGA haplotype (comprising minor alleles of the 3 FCGR3B SNPs) (HR = 2.78, P = 0.058) but not among participants without the haplotype (HR = 0.73, P = 0.44); again, the interaction of vaccine and haplotype was significant (P = 0.047). The FCGR3B-AGA haplotype also influenced whether a combined Env-specific CD8+ T-cell polyfunctionality score and IgG response correlated significantly with HIV risk; an FCGR2A SNP and two FCGR2B SNPs influenced whether anti-gp140 antibody-dependent cellular phagocytosis correlated significantly with HIV risk. These results provide further evidence that Fc gamma receptor genetic variations may modulate HIV vaccine effects and immune function after HIV vaccination.IMPORTANCE By analyzing data from the HVTN 505 efficacy trial of a DNA/recombinant adenovirus 5 (rAd5) vaccine regimen, we found that host genetics, specifically Fc gamma receptor genetic variations, influenced whether receiving the DNA/rAd5 regimen was beneficial, neutral, or detrimental to an individual with respect to HIV-1 acquisition risk. Moreover, Fc gamma receptor genetic variations influenced immune responses to the DNA/rAd5 vaccine regimen. Thus, Fc gamma receptor genetic variations should be considered in the analysis of future HIV vaccine trials and the development of HIV vaccines.

Rank-based two-sample tests for paired data with missing values.

Two-sample location problem is one of the most encountered problems in statistical practice. The two most commonly studied subtypes of two-sample location problem involve observations from two populations that are either independent or completely paired, but a third subtype can oftentimes occur in practice when some observations are paired and some are not. Partially paired two-sample problems, also known as paired two-sample problems with missing data, often arise in biomedical fields when it is difficult for some invasive procedures to collect data from an individual at both conditions we are interested in comparing. Existing rank-based two-sample comparison procedures for partially paired data, however, do not make efficient use of all available data. In order to improve the power of testing procedures for this problem, we propose several new rank-based test statistics and study their asymptotic distributions and, when necessary, exact variances. Through extensive numerical studies, we show that the best overall power come from the proposed tests based on weighted linear combinations of the test statistics comparing paired data and the test statistics comparing independent data, using weights inversely proportional to their variances. We illustrate the proposed methods with a real data example from HIV research for prevention.

HIV-Exposed Infants Vaccinated with an MF59/Recombinant gp120 Vaccine Have Higher-Magnitude Anti-V1V2 IgG Responses than Adults Immunized with the Same Vaccine.

In the RV144 vaccine trial, IgG responses against the HIV envelope variable loops 1 and 2 (V1V2) were associated with decreased HIV acquisition risk. We previously reported that infants immunized with an MF59-adjuvanted rgp120 vaccine developed higher-magnitude anti-V1V2 IgG responses than adult RV144 vaccinees. To determine whether the robust antibody response in infants is due to differences in vaccine regimens or to inherent differences between the adult and infant immune systems, we compared Env-specific IgG responses in adults and infants immunized with the same MF59- and alum-adjuvanted HIV envelope vaccines. At peak immunogenicity, the magnitudes of the gp120- and V1V2-specific IgG responses were comparable between adults and infants immunized with the alum/MNrgp120 vaccine (gp120 median fluorescence intensities [FIs] in infants = 7,118 and in adults = 11,510, P = 0.070; V1V2 median MFIs of 512 [infants] and 804 [adults], P = 0.50), whereas infants immunized with the MF59/SF-2 rgp120 vaccine had higher-magnitude antibody levels than adults (gp120 median FIs of 15,509 [infants] and 2,290 [adults], P < 0.001; V1V2 median FIs of 23,926 [infants] and 1,538 [adults]; P < 0.001). Six months after peak immunogenicity, infants maintained higher levels Env-specific IgG than adults. Anti-V1V2 IgG3 antibodies that were associated with decreased HIV-1 risk in RV144 vaccinees were present in 43% of MF59/rgp120-vaccinated infants but only in 12% of the vaccinated adults (P = 0.0018). Finally, in contrast to the rare vaccine-elicited Env-specific IgA in infants, rgp120 vaccine-elicited Env-specific IgA was frequently detected in adults. Our results suggest that vaccine adjuvants differently modulate gp120-specific antibody responses in adults and infants and that infants can robustly respond to HIV Env immunization.IMPORTANCE More than 150,000 pediatric HIV infections occur yearly, despite the availability of antiretroviral prophylaxis. A pediatric HIV vaccine could reduce the number of these ongoing infant infections and also prime for long-term immunity prior to sexual debut. We previously reported that immunization of infants with an MF59-adjuvanted recombinant gp120 vaccine induced higher-magnitude, potentially protective anti-V1V2 IgG responses than in adult vaccinees receiving the moderately effective RV144 vaccine. In the present study, we demonstrate that the robust response observed in infants is not due to differences in vaccine regimen or vaccine dose between adults and infants. Our results suggest that HIV vaccine adjuvants may differentially modulate immune responses in adults and infants, highlighting the need to conduct vaccine trials in pediatric populations.

Maximum diversity weighting for biomarkers with application in HIV-1 vaccine studies.

While studying the association between risk of HIV-1 infection and vaccine-elicited immune responses in preventative HIV-1 vaccine recipients, we encountered a need to combine a collection of biomarkers in an unsupervised fashion with the goal of preserving signal diversity within that collection. Inspired by methods for weighting protein sequences from the biological sequence analysis literature, we propose novel methods for weighting biomarkers, which we call maximum diversity weights. These weights are defined as the weights that maximize measures of signal diversity within a collection of biomarkers. While the optimization problems do not admit analytical solutions, they are convex and hence can be solved efficiently using iterative search algorithms. Through Monte Carlo studies and a real data example from HIV-1 vaccine research, we show that using maximum diversity weights in association studies can lead to an increase in power over other commonly used weights such as uniform weights or principal component-based weights.