Traumatic brain injury (TBI) is the largest non-genetic, non-aging related risk factor for Alzheimers disease (AD). We report here that TBI induces tau acetylation (ac-tau) at sites acetylated also in human AD brain. This is mediated by S-nitrosylated-GAPDH, which simultaneously inactivates Sirtuinl deacetylase and activates p300/CBP acetyltransferase, increasing neuronal ac-tau. Subsequent tau mislocalization causes neurodegeneration and neurobehavioral impairment, and ac-tau accumulates in the blood. Blocking GAPDH S-nitrosylation, inhibiting p300/CBP, or stimulating Sirtuinl all protect mice from neurodegeneration, neurobehavioral impairment, and blood and brain accumulation of ac-tau after TBI. Ac-tau is thus a therapeutic target and potential blood biomarker of TBI that may represent pathologic convergence between TBI and AD. Increased ac-tau in human AD brain is further augmented in AD patients with history of TBI, and patients receiving the p300/CBP inhibitors salsalate or diflunisal exhibit decreased incidence of AD and clinically diagnosed TBI.
Background Vincristine (VCR) is a critical part of treatment in pediatric malignancies and is associated with dose-dependent peripheral neuropathy (vincristine-induced peripheral neuropathy [VIPN]). Our previous findings show VCR metabolism is regulated by the CYP3A5 gene. Individuals who are low CYP3A5 expressers metabolize VCR slower and experience more severe VIPN as compared to high expressers. Preliminary observations suggest that Caucasians experience more severe VIPN as compared to nonCaucasians. Procedure Kenyan children with cancer who were undergoing treatment including VCR were recruited for a prospective cohort study. Patients received IV VCR 2 mg/m2/dose with a maximum dose of 2.5 mg as part of standard treatment protocols. VCR pharmacokinetics (PK) sampling was collected via dried blood spot cards and genotyping was conducted for common functional variants in CYP3A5, multi-drug resistance 1 (MDR1), and microtubule-associated protein tau (MAPT). VIPN was assessed using five neuropathy tools. Results The majority of subjects (91%) were CYP3A5 high-expresser genotype. CYP3A5 low-expresser genotype subjects had a significantly higher dose and body surface area normalized area under the curve than CYP3A5 high-expresser genotype subjects (0.28 ± 0.15 hr·m2/l vs. 0.15 ± 0.011 hr·m2/l, P = 0.027). Regardless of which assessment tool was utilized, minimal neuropathy was detected in this cohort. There was no difference in the presence or severity of neuropathy assessed between CYP3A5 high- and low-expresser genotype groups. Conclusion Genetic factors are associated with VCR PK. Due to the minimal neuropathy observed in this cohort, there was no demonstrable association between genetic factors or VCR PK with development of VIPN. Further studies are needed to determine the role of genetic factors in optimizing dosing of VCR for maximal benefit.
Interactions between multiple drugs may yield excessive risk of adverse effects. This increased risk is not uniform for all combinations, although some combinations may have constant adverse effect risks. We developed a statistical model using medical record data to identify drug combinations that induce myopathy risk. Such combinations are revealed using a novel mixture model, comprised of a constant risk model and a dose–response risk model. The dose represents the number of drug combinations. Using an empirical Bayes estimation method, we successfully identified high-dimensional (two to six) drug combinations that are associated with excessive myopathy risk at significantly low local false-discovery rates. From the curve of a dose–response model and high-dimensional drug interaction data, we observed that myopathy risk increases as the drug interaction dimension increases. This is the first time that such a dose–response relationship for high-dimensional drug interactions was observed and extracted from the medical record database.
Polypharmacy increases the risk of drug-drug interactions (DDIs). Combining epidemiological studies with pharmacokinetic modeling, we detected and evaluated high-dimensional DDIs among 30 frequent drugs. Multidrug combinations that increased the risk of myopathy were identified in the US Food and Drug Administration Adverse Event Reporting System (FAERS) and electronic medical record (EMR) databases by a mixture drug-count response model. CYP450 inhibition was estimated among the 30 drugs in the presence of 1 to 4 inhibitors using in vitro / in vivo extrapolation. Twenty-eight three-way and 43 four-way DDIs had significant myopathy risk in both databases and predicted increases in the area under the concentration-time curve ratio (AUCR) >2-fold. The high-dimensional DDI of omeprazole, fluconazole, and clonidine was associated with a 6.41-fold (FAERS) and 18.46-fold (EMR) increased risk of myopathy local false discovery rate (<0.005); the AUCR of omeprazole in this combination was 9.35. The combination of health record informatics and pharmacokinetic modeling is a powerful translational approach to detect high-dimensional DDIs.
The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) is an important source for detecting adverse drug event (ADE) signals. In this article, we propose a three‐component mixture model (3CMM) for FAERS signal detection. In 3CMM, a drug‐ADE pair is assumed to have either a zero relative risk (RR), or a background RR (mean RR = 1), or an increased RR (mean RR >1). By clearly defining the second component (mean RR = 1) as the null distribution, 3CMM estimates local false discovery rates (FDRs) for ADE signals under the empirical Bayes framework. Compared with existing approaches, the local FDR's top signals have noninferior or better sensitivities to detect true signals in both FAERS analysis and simulation studies. Additionally, we identify that the top signals of different approaches have different patterns, and they are complementary to each other.
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