Laboratory and demographic predictors of functional assay positive status in suspected heparin-induced thrombocytopenia: A multicenter retrospective cohort study.

Heparin-induced thrombocytopenia (HIT) is an antibody-mediated immune response against platelet factor 4 (PF4) bound to heparin anticoagulants. A priori identification of patients at-risk for HIT remains elusive and a number of risk factors have been identified, but these associations and their effect sizes have limited validation in large cohorts of suspected HIT patients. The aim of this study was to investigate existing anti-PF4/heparin antibody thresholds and model the relationship of demographic variables and anti-PF4/heparin antibody levels with functional assay positivity across multiple institutions in the absence of detailed clinical data. In a large collection of suspected HIT patients (n = 8904), we tested for associations between laboratory and demographic variables and functional assay positive status as well as anti-PF4/heparin antibody levels. We also tested for correlation between IgG-specific and polyspecific (IgG/IgA/IgM) anti-PF4/heparin antibody values and their ability to predict functional assay positive status using area under the receiver operating characteristic (AUROC). Logistic regression identified increasing anti-PF4/heparin antibody OD levels (OR = 51.84 [37.27-74.34], p < 2.0 × 10-16) and female sex (OR = 1.47 [1.19-1.82], p = 3.5 × 10-4) as risk factors for positive functional assay in the largest cohort with consistent effect sizes in two other cohorts. In a subset of 1175 patients, polyspecific and IgG-specific anti-PF4/heparin antibody values were heterogeneous (mean coefficient of variation = 31.9 %), but strongly correlated (rho = 0.878; p < 2 × 10-16) with similar prediction of functional assay positivity (polyspecific AUROC = 0.976 and IgG-specific AUROC = 0.980). Thus, we recapitulate previously identified risk factors of functional assay positivity, providing precise effect sizes in a large observational population of suspected HIT patients. Our data reinforce the necessity of functional assay confirmation and suggest that, despite heterogeneity, polyspecific and IgG-specific anti-PF4/heparin antibody assays predict functional assay positive status similarly, even in the absence of 4Ts scores and detailed clinical data.

Local Ancestry-Informed Candidate Pathway Analysis of Warfarin Stable Dose in Latino Populations.

Accuracy of warfarin dose prediction algorithms may be improved by including data from diverse populations in genetic studies of dose variability. Here, we surveyed single nucleotide polymorphisms in vitamin K-related genetic pathways for association with warfarin dose requirements in two admixed Latino populations in standard-principal component adjusted and contemporary-local ancestry adjusted regression models. A total of five variants from vitamin K-related genes/pathways were associated with warfarin dose in both cohorts (P < 0.0125) in standard models. Local ancestry-adjusted analysis unveiled 35 associated variants with absolute effects ranging from ß = 9.04 ( ±2.23) to 39.18 ( ±10.89) per ancestral allele in the discovery cohort and ß = 6.47 (± 2.02) to 17.82 (± 6.83) in the replication cohort. Importantly, we demonstrate the technical validity of the Tractor model in cohorts with admixed ancestry from three founder populations and bring attention to the technical hurdles obstructing the inclusion of diverse, especially admixed, populations in pharmacogenomic research.

Bringing pharmacomicrobiomics to the clinic through well-designed studies.

Pharmacomicrobiomic studies investigate drug-microbiome interactions, such as the effect of microbial variation on drug response and disposition. Studying and understanding the interactions between the gut microbiome and drugs is becoming increasingly relevant to clinical practice due to its potential for avoiding adverse drug reactions or predicting variability in drug response. The highly variable nature of the human microbiome presents significant challenges to assessing microbes' influence. Studies aiming to explore drug-microbiome interactions should be well-designed to account for variation in the microbiome over time and collect data on confounders such as diet, disease, concomitant drugs, and other environmental factors. Here, we assemble a set of important considerations and recommendations for the methodological features required for performing a pharmacomicrobiomic study in humans with a focus on the gut microbiome. Consideration of these factors enable discovery, reproducibility, and more accurate characterization of the relationships between a given drug and the microbiome. Furthermore, appropriate interpretation and dissemination of results from well-designed studies will push the field closer to clinical relevance and implementation.

Genome-wide association study of platelet factor 4/heparin antibodies in heparin-induced thrombocytopenia.

Heparin, a widely used anticoagulant, carries the risk of an antibody-mediated adverse drug reaction, heparin-induced thrombocytopenia (HIT). A subset of heparin-treated patients produces detectable levels of antibodies against complexes of heparin bound to circulating platelet factor 4 (PF4). Using a genome-wide association study (GWAS) approach, we aimed to identify genetic variants associated with anti-PF4/heparin antibodies that account for the variable antibody response seen in HIT. We performed a GWAS on anti-PF4/heparin antibody levels determined via polyclonal enzyme-linked immunosorbent assays. Our discovery cohort (n = 4237) and replication cohort (n = 807) constituted patients with European ancestry and clinical suspicion of HIT, with cases confirmed via functional assay. Genome-wide significance was considered at α = 5 × 10-8. No variants were significantly associated with anti-PF4/heparin antibody levels in the discovery cohort at a genome-wide significant level. Secondary GWAS analyses included the identification of variants with suggestive associations in the discovery cohort (α = 1 × 10-4). The top variant in both cohorts was rs1555175145 (discovery ß = -0.112 [0.018], P = 2.50 × 10-5; replication ß = -0.104 [0.051], P = .041). In gene set enrichment analysis, 3 gene sets reached false discovery rate-adjusted significance (q < 0.05) in both discovery and replication cohorts: "Leukocyte Transendothelial Migration," "Innate Immune Response," and "Lyase Activity." Our results indicate that genomic variation is not significantly associated with anti-PF4/heparin antibody levels. Given our power to identify variants with moderate frequencies and effect sizes, this evidence suggests genetic variation is not a primary driver of variable antibody response in heparin-treated patients with European ancestry.

ABO O blood group as a risk factor for platelet reactivity in heparin-induced thrombocytopenia.

Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. We performed a genome-wide association study (GWAS) with positive functional assay as the outcome in a large discovery cohort of patients divided into 3 groups: (1) functional assay-positive cases (n = 1269), (2) antibody-positive (functional assay-negative) controls (n = 1131), and (3) antibody-negative controls (n = 1766). Significant associations (α = 5 × 10-8) were investigated in a replication cohort (α = 0.05) of functional assay-confirmed HIT cases (n = 177), antibody-positive (function assay-negative) controls (n = 258), and antibody-negative controls (n = 351). We observed a strong association for positive functional assay with increasing PF4/heparin immunoglobulin-G (IgG) level (odds ratio [OR], 16.53; 95% confidence interval [CI], 13.83-19.74; P = 1.51 × 10-209) and female sex (OR, 1.15; 95% CI, 1.01-1.32; P = .034). The rs8176719 C insertion variant in ABO was significantly associated with positive functional assay status in the discovery cohort (frequency = 0.41; OR, 0.751; 95% CI, 0.682-0.828; P = 7.80 × 10-9) and in the replication cohort (OR, 0.467; 95% CI, 0.228-0.954; P = .0367). The rs8176719 C insertion, which encodes all non-O blood group alleles, had a protective effect, indicating that the rs8176719 C deletion and the O blood group were risk factors for HIT (O blood group OR, 1.42; 95% CI, 1.26-1.61; P = 3.09 × 10-8). Meta-analyses indicated that the ABO association was independent of PF4/heparin IgG levels and was stronger when functional assay-positive cases were compared with antibody-positive (functional assay-negative) controls than with antibody-negative controls. Sequencing and fine-mapping of ABO demonstrated that rs8176719 was the causal single nucleotide polymorphism (SNP). Our results clarify the biology underlying HIT pathogenesis with ramifications for prediction and may have important implications for related conditions, such as vaccine-induced thrombotic thrombocytopenia.

Prediction of Water Distributions and Displacement at Protein-Ligand Interfaces.

The retention and displacement of water molecules during formation of ligand-protein interfaces play a major role in determining ligand binding. Understanding these effects requires a method for positioning of water molecules in the bound and unbound proteins and for defining water displacement upon ligand binding. We describe an algorithm for water placement and a calculation of ligand-driven water displacement in >9000 protein-ligand complexes. The algorithm predicts approximately 38% of experimental water positions within 1.0 Å and about 83% within 1.5 Å. We further show that the predicted water molecules can complete water networks not detected in crystallographic structures of the protein-ligand complexes. The algorithm was also applied to solvation of the corresponding unbound proteins, and this allowed calculation of water displacement upon ligand binding based on differences in the water network between the bound and unbound structures. We illustrate use of this approach through comparison of water displacement by structurally related ligands at the same binding site. This method for evaluation of water displacement upon ligand binding may be of value for prediction of the effects of ligand modification in drug design.

Machine Learning for Prediction of Stable Warfarin Dose in US Latinos and Latin Americans.

Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model's ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients (n = 7,030), inclusion of additional predictor variables led to a small but significant improvement in prediction of dose relative to the IWPC algorithm (47.8 versus 46.7% in IWPC, p = 1.43 × 10-15). Nonlinear models using IWPC variables did not significantly improve prediction of dose over the linear IWPC algorithm. In ULLA patients alone (n = 1,734), IWPC performed similarly to all other linear and nonlinear pharmacogenetic algorithms. Our results reinforce the validity of IWPC in a large, ethnically diverse population and suggest that additional variables that capture warfarin dose variability may improve warfarin dose prediction algorithms.

Immunopharmacogenomics: Mechanisms of HLA-Associated Drug Reactions.

The human leukocyte antigen (HLA) system is the most polymorphic in the human genome that has been associated with protection and predisposition to a broad array of infectious, autoimmune, and malignant diseases. More recently over the last two decades, HLA class I alleles have been strongly associated with T-cell-mediated drug hypersensitivity reactions. In the case of abacavir hypersensitivity and HLA-B*57:01, the 100% negative predictive value and low number needed to test to prevent a single case has led to a durable and effective global preprescription screening strategy. However, HLA associations are still undefined for most drugs clinically associated with different delayed drug hypersensitivity phenotypes, and an HLA association relevant to one population is not generalizable across ethnicities. Furthermore, while a specific risk HLA allele is necessary for drug-induced T-cell activation, it is not sufficient. The low and incomplete positive predictive value has hindered efforts at clinical implementation for many drugs but has provided the impetus to understand the mechanisms of HLA class I restricted T-cell-mediated drug hypersensitivity reactions. Current research has focused on defining the contribution of additional elements of the adaptive immune response and other genetic and ecologic risk factors that contribute to drug hypersensitivity risk. In this review we focus on new insights into immunological, pharmacological, and genetic mechanisms underpinning HLA-associated drug reactions and the implications for future translation into clinical care.

Elucidation of Cellular Contributions to Heparin-Induced Thrombocytopenia Using Omic Approaches.

Heparin-induced thrombocytopenia (HIT) is an unpredictable, complex, immune-mediated adverse drug reaction associated with a high mortality. Despite decades of research into HIT, fundamental knowledge gaps persist regarding HIT likely due to the complex and unusual nature of the HIT immune response. Such knowledge gaps include the identity of a HIT immunogen, the intrinsic roles of various cell types and their interactions, and the molecular basis that distinguishes pathogenic and non-pathogenic PF4/heparin antibodies. While a key feature of HIT, thrombocytopenia, implicates platelets as a seminal cell fragment in HIT pathogenesis, strong evidence exists for critical roles of multiple cell types. The rise in omic technologies over the last decade has resulted in a number of agnostic, whole system approaches for biological research that may be especially informative for complex phenotypes. Applying multi-omics techniques to HIT has the potential to bring new insights into HIT pathophysiology and identify biomarkers with clinical utility. In this review, we review the clinical, immunological, and molecular features of HIT with emphasis on key cell types and their roles. We then address the applicability of several omic techniques underutilized in HIT, which have the potential to fill knowledge gaps related to HIT biology.

Genetic Admixture and Survival in Diverse Populations with Pulmonary Arterial Hypertension.

Rationale: Limited information is available on racial/ethnic differences in pulmonary arterial hypertension (PAH).Objectives: Determine effects of race/ethnicity and ancestry on mortality and disease outcomes in diverse patients with PAH.Methods: Patients with Group 1 PAH were included from two national registries with genome-wide data and two local cohorts, and further incorporated in a global meta-analysis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for transplant-free, all-cause mortality in Hispanic patients with non-Hispanic white (NHW) patients as the reference group. Odds ratios (ORs) for inpatient-specific mortality in patients with PAH were also calculated for race/ethnic groups from an additional National Inpatient Sample dataset not included in the meta-analysis.Measurements and Main Results: After covariate adjustment, self-reported Hispanic patients (n = 290) exhibited significantly reduced mortality versus NHW patients (n = 1,970) after global meta-analysis (HR, 0.60 [95% CI, 0.41-0.87]; P = 0.008). Although not significant, increasing Native American genetic ancestry appeared to account for part of the observed mortality benefit (HR, 0.48 [95% CI, 0.23-1.01]; P = 0.053) in the two national registries. Finally, in the National Inpatient Sample, an inpatient mortality benefit was also observed for Hispanic patients (n = 1,524) versus NHW patients (n = 8,829; OR, 0.65 [95% CI, 0.50-0.84]; P = 0.001). An inpatient mortality benefit was observed for Native American patients (n = 185; OR, 0.38 [95% CI, 0.15-0.93]; P = 0.034).Conclusions: This study demonstrates a reproducible survival benefit for Hispanic patients with Group 1 PAH in multiple clinical settings. Our results implicate contributions of genetic ancestry to differential survival in PAH.