Abstract WP115: Association of HDAC9, TWIST1, and FERD3L Expression With the Risk of Intracranial Aneurysm

Background and Purpose: Subarachnoid hemorrhage is a devastating consequence of ruptured IA, therefore early identification is important. Identification of biomarkers may improve the understanding of IA pathogenesis and can be used to improve patient management. A risk allele (rs10230207) has been associated with IA incidence and is located nearby the HDAC9, TWIST1 and FERD3L genes. Changes in the expression of one or both of these genes is believed to be related to the increased risk of IA. We test the hypothesis that patients harboring this risk allele have changes in the expression of these genes, which can be measured in their blood.

Methods: Immortalized B-lymphocytes from patients with unruptured IA and population controls were obtained from the NINDS repository. Subject genomic DNA was isolated and genotyped for the presence of the risk allele using assays directed toward either rs10230207, or rs11767221, a SNP in high linkage disequilibrium with rs10230207. HDAC9, TWIST1, and FERD3L mRNA and protein were analyzed in each cell line. HDAC9 and TWIST1 protein and mRNA levels were confirmed in peripheral blood mononuclear cells (PBMCs) from the whole blood of subjects with and without IA.

Results: IA cases expressed more HDAC9 (p=0.005) and less TWIST1 and FERD3L (p=0.0200 and 0.0320 respectively) compared to the population controls. The GWAS association of IA with rs10230207 in the Finnish and Dutch population was replicated in the NINDS sample population. Within the sample population, the odds of IA was 7.25 higher given the presence of the risk allele compared to no risk allele (95% CI 2.023-24.96). While changes in HDAC9 expression was not associated with the presence of the risk allele, decreased expression of TWIST1 and FERD3L were associated with the risk allele. Changes in TWIST1 and FERD3L were confirmed in genotyped case and control PBMCs

Conclusions: The presence of the rs10230207 risk allele was not associated with changes in HDAC9 but was associated with decreased TWIST1 and FERD3L expression in case and control immortalized lymphoblasts, which was confirmed in patient PBMCs. Our studies demonstrate a potential marker associated with IA risk. Future studies are aimed at looking at the positive and negative predictive values of TWIST1 levels and IA.

Synergistic Cytotoxicity from Drugs and Cytokines In Vitro as an Approach to Classify Drugs According to Their Potential to Cause Idiosyncratic Hepatotoxicity: A Proof-of-Concept Study

Idiosyncratic drug-induced liver injury (IDILI) typically occurs in a small fraction of patients and has resulted in removal of otherwise efficacious drugs from the market. Current preclinical testing methods are ineffective in predicting which drug candidates have IDILI liability. Recent results suggest that immune mediators such as tumor necrosis factor-α (TNF) and interferon-γ (IFN) interact with drugs that cause IDILI to kill hepatocytes. This proof-of-concept study was designed to test the hypothesis that drugs can be classified according to their ability to cause IDILI in humans using classification modeling with covariates derived from concentration-response relationships that describe cytotoxic interaction with cytokines. Human hepatoma (HepG2) cells were treated with drugs associated with IDILI or with drugs lacking IDILI liability and cotreated with TNF and/or IFN. Detailed concentration-response relationships were determined for calculation of parameters such as the maximal cytotoxic effect, slope, and EC₅₀ for use as covariates for classification modeling using logistic regression. These parameters were incorporated into multiple classification models to identify combinations of covariates that most accurately classified the drugs according to their association with human IDILI. Of 14 drugs associated with IDILI, almost all synergized with TNF to kill HepG2 cells and were successfully classified by statistical modeling. IFN enhanced the toxicity mediated by some IDILI-associated drugs in the presence of TNF. In contrast, of 10 drugs with little or no IDILI liability, none synergized with inflammatory cytokines to kill HepG2 cells and were classified accordingly. The resulting optimal model classified the drugs with extraordinary selectivity and specificity.