CD40 knockdown and CD40-luciferase assay in BL2 cells.

<p>(A) Schematic of the canonical CD40 – NF-|B signaling pathway in B cells. (B) RNAi perturbation of <i>CD40</i> in two distinct clones derived from BL2 cells decreases CD40 protein levels by 55% (left) and 40% (middle) compared to the BL2 parent line (black, right); (C) More CD40 on the surface of BL2 cells increases RelA (p65) phosphorylation following activation with tCD40L, as measured by Western blot, with maximum activation at 15 minutes. Results are shown for the same two shRNA lines and parental BL2 cell line as in (B). This is a representative example of multiple experiments. (D) Titration of tCD40L leads to increased luciferase activity. Each experiment was performed in triplicate. The red circle represents ∼80% maximum luciferase activity (64 ng/ml tCD40L). Luciferase activity at baseline (i.e., no tCD40L activation) was subtracted from each measurement to plot results. (E) Titration of IKK inhibitor VII leads to inhibition of luciferase activity following tCD40L activation. Each experiment was performed in duplicate. (F) The luciferase assay is robust, with Z'-factor>0.80 and >60-fold inhibition of luciferase activity without killing cells across different plates.</p

Genetic data on risk of RA and CD40 protein levels.

<p>(A) The regional association plot from analysis of Immunochip (iChip) data in 7,222 CCP+ cases and 15,870 controls. Gene location is shown along the bottom of the graph, with observed –log(P) value along the left Y-axis and recombination rate along the right Y-axis. Each SNP is plotted is a circle, with color scheme (red to white) in reference to the extent of linkage disequilibrium with the index SNP, rs4810485 (labeled as a diamond). (B) The regional association plot from analysis of iChip data and CD40 protein levels in 90 healthy control individuals. (C) A box-whisker's plot of SNP (rs4810485) and CD40 protein levels in B cells from healthy control individuals, where T = non-risk allele and G = risk allele. (D) A box-whisker's plot of SNP (rs4810485) and <i>CD40</i> mRNA levels in PBMC's from two separate collections (total of 1,441 healthy control individuals); T = non-risk allele and G = risk allele.</p

Small molecule screen of CD40-mediated NF-kB signaling in BL2 cells.

<p>(A) Results from duplicate experiments screening 1,982 compounds. Red circles are our positive control (IKK inhibitor VII); grey circles are our neutral controls (DMSO only); and blue circles are test compounds. The red dashed line indicates >2SD from the mean of the neutral controls, which defines our “hit” compounds (n = 81 compounds). (B) Dose-response curves for two compounds known to inhibit inflammation [CID = 5282230 (tranilast)] or NF-|B signaling [CID = 5282360 (4-hydroxy-estradiol)] in the BL2-NF|B-Luc cell lines. (C) Dose-response curves for two compounds not previously implicated in inflammation, NF-κB signaling, CD40 signaling, or other biological pathways related to rheumatoid arthritis: CID = 306804, [4-(1-acetyl-4-oxo-2H-3,1-benzoxazin-2-yl)phenyl] acetate; and CID = 7309015, 8-[(Z)-3-(3,4-dimethoxyphenyl)prop-2-enoyl]-7-hydroxy-4-methylchromen-2-one. Red line = cells activated with tCD40L; black line = cells activated with either CD40 or LPS (in BL2-TLR4-NFκB-Luc cells); green line = cell toxicity, as measured by CellTiter-Glo.</p

Percent maximum inhibition for two “known” and two “novel” compounds in both BL2-NFκB-Luc and Ramos-NFκB-Luc cell lines.

<p>For each compound, we calculate the maximum amount of inhibition observed at the highest concentration of drug relative to zero luciferase activity.</p

Relative IC₅₀ for two “known” and two “novel” compounds in both BL2-NFκB-Luc and Ramos-NFκB-Luc cell lines.

<p>Relative IC₅₀ is the concentration required to bring the dose-response curve to the halfway point between the top and bottom plateaus of the curve.</p

Power calculations for LogR, G+GxE, and LT approaches in simulated data.

<p>For each statistic we display power to attain P<5<b>×</b>10⁻⁸ based on 1,000,000 simulations of 3000 cases and 3000 controls, for various effect sizes <i>γ</i>. The increase in power (ratio of y-axis values) for LT versus LogR is 22.8% for <i>γ</i> = 0.1, and 23.0% when computing average power across all values of <i>γ</i>. For γ = 0 the power was 5.0% for all statistics when the P-value threshold is 0.05. G+GxE performs worse due to an extra degree of freedom.</p

Average χ² statistics for LT versus other approaches in simulated data.

<p>For each statistic we display average results across 1,000,000 simulations, for various effect sizes <i>γ</i>. All statistics are χ²(1 dof). Logistic regression with an interaction term (G+GxE) values been converted from χ²(2 dof) to the equivalent χ²(1 dof) value. At an effect size of 0 all statistics give the expected value under the null. OR LBMI is the odds ratio computed from cases with BMI = 24. OR HBMI is the odds ratio for cases with BMI = 35.</p

Inferred covariates and effect sizes on the liability scale.

<p>LT model is the liability threshold model for each disease with parameters estimated using the LTPub method. For diseases with multiple covariates, models with all covariates and each covariate separately are given. %Variance Explained is the fraction of variance explained on the liability scale in the study data for each of the covariates in each of the diseases when all covariates are used in the model, and is specific to the distribution of covariates in each particular study. BMI30 is a binary variable, which is 1 if an individual's BMI is greater than 30 and 0 otherwise. Type 2 diabetes (T2D), prostate cancer (PC), lung cancer (LC), breast cancer (BC), rheumatoid arthritis (RA), end-stage kidney disease (ESKD), and age-related macular degeneration (AMD).</p

Summary statistics across all datasets.

<p>The sum of each of the test statistics across all of the SNPs in each of the diseases. LTPub vs LogR is the % increase of LTPub compared to LogR. It has a median value of 16%. Type 2 diabetes (T2D), prostate cancer (PC), lung cancer (LC), breast cancer (BC), rheumatoid arthritis (RA), end-stage kidney disease (ESKD), and age-related macular degeneration (AMD).</p

Illustration of liability threshold model: simulated T2D example.

<p>The posterior mean of <i>ε</i> for low-BMI and high-BMI cases is the expected value of <i>ε</i> given that it exceeds <u>c(t</u>−)+m. High-BMI cases have a lower posterior mean relative to low-BMI cases since they require a smaller contribution from genetics to exceed the threshold in the liability threshold model.</p