Data from: Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods

<i>FCRLA</i> polymorphisms associate with <i>FCRLA</i> expression in human B cells.

<p>A. Scatterplot of the eQTL p-values (-log10 scale) for the association of SNPs across the FcγR region with the expression of <i>FCRLA</i> as mapped in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>]. For simplicity, for each SNP only the smallest p-value from different levels of expression, i.e. exon, transcript, and gene, is shown. The green vertical bar indicates the location of the <i>FCGR2C</i> SNPs identified in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref002" target="_blank">2</a>]. The black horizontal line segments at the top indicate the positions of Refseq annotated FcγR genes, with the locations of <i>FCGR2C</i> and <i>FCRLA</i> labeled. B. Close view of SNPs around <i>FCRLA</i> in UCSC genome browser (hg19, chr1:161,670,571–161,688,007). The top track shows the genomic locations and the association p-values (-log10 scale) for those SNPs that passed the significance cutoff of FDR < 0.05 in their associations with the expression of <i>FCRLA</i> at different levels as reported in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>], i.e. exon, transcript, and gene. Highlighted in color cyan are SNPs with smallest p-values (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.s004" target="_blank">S1 Table</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.s005" target="_blank">S2 Table</a>). The middle two horizontal tracks show the LD between each of the corresponding SNPs shown on top track and the SNP rs114945036. RefSeq gene annotation is shown at the bottom. C. Scatterplot of raw RNA-seq read counts (log2 scale) of RefSeq annotated <i>FCGR2C</i> (x-axis) and <i>FCRLA</i> (y-axis) in B cells from each of those 462 individuals. The number on the top-right corner shows the Pearson correlation coefficient.</p

<i>FCGR2C</i> Polymorphisms Associated with HIV-1 Vaccine Protection Are Linked to Altered Gene Expression of Fc-γ Receptors in Human B Cells

<div><p>The phase III Thai RV144 vaccine trial showed an estimated vaccine efficacy (VE) to prevent HIV-1 infection of 31.2%, which has motivated the search for immune correlates of vaccine protection. In a recent report, several single nucleotide polymorphisms (SNPs) in <i>FCGR2C</i> were identified to associate with the level of VE in the RV144 trial. To investigate the functional significance of these SNPs, we utilized a large scale B cell RNA sequencing database of 462 individuals from the 1000 Genomes Project to examine associations between <i>FCGR2C</i> SNPs and gene expression. We found that the <i>FCGR2C</i> SNPs that associated with vaccine efficacy in RV144 also strongly associated with the expression of <i>FCGR2A/C</i> and one of them also associated with the expression of Fc receptor-like A (<i>FCRLA</i>), another Fc-γ receptor (FcγR) gene that was not examined in the previous report. These results suggest that the expression of FcγR genes is influenced by these SNPs either directly or in linkage with other causal variants. More importantly, these results motivate further investigations into the potential for a causal association of expression and alternative splicing of <i>FCGR2C</i> and other FcγR genes with the HIV-1 vaccine protection in the RV144 trial and other similar studies.</p></div

<i>FCGR2C</i> polymorphisms associate with FcγR gene expression in B cells in the European (EUR) population.

<p>A. The boxplot shows the distribution of the expression (y-axis) of the last exon (hg19, chr1: 161487765–161489358) of <i>FCGR2A</i> in B cells from the 373 EUR individuals as quantified in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>], stratified by the genotypes (x-axis) of the SNP rs114945036. Individual expression levels are (horizontal line = median; bottom and top of box = 25^th and 75^th percentile). Expression in individuals is shown in blue dots. The significance of the association is indicated immediately above, which were mapped in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>] using a linear model implemented in Matrix eQTL [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref010" target="_blank">10</a>]. B. Similar as A, for the SNP rs78603008. C. Similar as A, for the SNP rs138747765. D. Similar as A, for the SNP rs138747765 and the expression of the third exon (hg19, chr1:161680550–161680702) of <i>FCRLA</i> (Fc receptor-like A) in B cells.</p

Immune-Correlates Analysis of an HIV-1 Vaccine Efficacy Trial Reveals an Association of Nonspecific Interferon-γ Secretion with Increased HIV-1 Infection Risk: A Cohort-Based Modeling Study

<div><p>Background</p><p>Elevated risk of HIV-1 infection among recipients of an adenovirus serotype 5 (Ad5)-vectored HIV-1 vaccine was previously reported in the Step HIV-1 vaccine efficacy trial. We assessed pre-infection cellular immune responses measured at 4 weeks after the second vaccination to determine their roles in HIV-1 infection susceptibility among Step study male participants.</p><p>Methods</p><p>We examined <i>ex vivo</i> interferon-γ (IFN-γ) secretion from peripheral blood mononuclear cells (PBMC) using an ELISpot assay in 112 HIV-infected and 962 uninfected participants. In addition, we performed flow cytometric assays to examine T-cell activation, and <i>ex vivo</i> IFN-γ and interleukin-2 secretion from CD4⁺ and CD8⁺ T cells. We accounted for the sub-sampling design in Cox proportional hazards models to estimate hazard ratios (HRs) of HIV-1 infection per 1-log_e increase of the immune responses.</p><p>Findings</p><p>We found that HIV-specific immune responses were not associated with risk of HIV-1 infection. However, each 1-log_e increase of mock responses measured by the ELISpot assay (i.e., IFN-γ secretion in the absence of antigen-specific stimulation) was associated with a 62% increase of HIV-1 infection risk among vaccine recipients (HR = 1.62, 95% CI: (1.28, 2.04), p<0.001). This association remains after accounting for CD4⁺ or CD8⁺ T-cell activation. We observed a moderate correlation between ELISpot mock responses and CD4⁺ T-cells secreting IFN-γ (ρ = 0.33, p = 0.007). In addition, the effect of the Step vaccine on infection risk appeared to vary with ELISpot mock response levels, especially among participants who had pre-existing anti-Ad5 antibodies (interaction p = 0.04).</p><p>Conclusions</p><p>The proportion of cells, likely CD4⁺ T-cells, producing IFN-γ without stimulation by exogenous antigen appears to carry information beyond T-cell activation and baseline characteristics that predict risk of HIV-1 infection. These results motivate additional investigation to understand the potential link between IFN-γ secretion and underlying causes of elevated HIV-1 infection risk among vaccine recipients in the Step study.</p></div

Hazard ratios (HRs) for HIV-1 infection per 1- log_e increase of Immune responses among vaccine recipients.

<p>*All unadjusted immune variable models included only the indicated immune variable(s) as predictor(s) of HIV-1 infection without adjustment of other baseline covariates.</p><p>**In addition to the indicated immune variable (s), all adjusted immune variable models adjusted for baseline covariates including circumcision status, Ad5 seropositivity, region, race, age, HSV-2 serostatus, recreational drug usage, unprotected receptive anal sex with HIV+ male partner, unprotected insertive anal sex with HIV+ male partner, and number of male partners.</p><p>Hazard ratios (HRs) for HIV-1 infection per 1- log_e increase of Immune responses among vaccine recipients.</p

Distribution of Immune Reponses in Infected and Uninfected Vaccine and Placebo Recipients in the Immune Correlates Analysis Study.

<p>Panel A includes the IFN-γ-secreting cellular responses measured by the ELISpot assay. Panel B includes T-cell activation responses measured by the flow cytometric assay. Box-plots show the 25th percentile (lower edge of the box), 50th percentile (horizontal line in the box), and 75th percentile (upper edge of the box) for the immune responses, with participants stratified according to HIV-1 infection status and treatment assignment. The tip of the vertical bars indicate the most extreme data points, which are no more than 1.5 times the interquartile range from the box. The distribution plots of other immune responses measured by the ICS assay are shown in Figures S2 of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108631#pone.0108631.s001" target="_blank">Information S1</a>.</p

Hazard ratios (HRs) for HIV-1 infection by vaccination assignment (3^rd column) and by mock response quartiles (6^th column).

<p>Results were obtained from Cox regression models with interaction terms between ELISpot mock responses and vaccination assignment overall and in subgroups.</p><p>Hazard ratios (HRs) for HIV-1 infection by vaccination assignment (3^rd column) and by mock response quartiles (6^th column).</p

Week 8 Samples for the Immune-Correlates Analysis.

<p>Rows A, B and C indicate available data from the ELISpot, T-cell activation and ICS assays, respectively. We used the ELISpot assay to measure non-HIV-specific (mock) and HIV-specific (Gag, Pol and Nef) ex vivo IFN-γ-secreting PBMC, the T-cell activation assay to measure CD4⁺ and CD8⁺ T-cell activation marked by Ki-67^hiBcL-2^lo, and the ICS assay to measure CMV- and HIV-specific (Gag, Pol and Nef) <i>ex vivo</i> IFN-γ/IL-2 secretion from CD4⁺ and CD8⁺ T cells. We also measured a subset of these samples for Ad5-specific <i>ex vivo</i> IFN-γ/IL-2 secretion from CD4⁺ and CD8⁺ T cells by the ICS assay (Figure S3 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108631#pone.0108631.s001" target="_blank">Information S1</a>).</p

Baseline predictors of ELISpot mock responses among vaccine and placebo recipients.^*

<p>*Estimates are shown for predictors identified in the best-fitting multivariate linear regression models based on the AIC model-selection criterion.</p><p>Baseline predictors of ELISpot mock responses among vaccine and placebo recipients.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108631#nt104" target="_blank">*</a>}</p