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OBJECTIVES: Studies showed angiotensin II type 2 receptor/angiotensin II type 4 receptor (AT2R/AT4R) stimulatory antihypertensive was associated with a lower risk of dementia and cognitive impairment compared to the inhibitory one. This study aimed to identify the racial and ethnic differences in using these agents among the USA adults with hypertension. METHODS: A cross-sectional study was conducted using data from the Medical Expenditure Panel Survey (MEPS, 2016-2019). Individuals with a diagnosis of hypertension or self-reported hypertension and without dementia or Alzheimer's disease diagnosis were included in the analysis. We applied two multivariable logistic regressions to compare racial/ethnic differences in AT2R/AT4R stimulatory antihypertensive use and AT2R/AT4R inhibitory antihypertensive use, adjusting for covariates. RESULTS: Twenty-four thousand five hundred eighty-one individuals with hypertension and without dementia or Alzheimer's disease were identified. Among non-Hispanic Whites, 72.39% were using AT2R/AT4R inhibitory antihypertensive agents, vs. 66.97% using AT2R/AT4R stimulatory antihypertensive agents. In contrast, both non-Hispanic Black and Asian Americans were using more AT2R/AT4R stimulatory agents than inhibitory ones (16.40% vs. 12.16% and 4.79% vs. 3.43%, respectively). Compared to non-Hispanic White, non-Hispanic Black (OR 1.980, 95% CI 1.839-2.132) and non-Hispanic Asian Americans (OR 1.545, 95% CI 1.356-1.761) were significantly associated with higher odds of prescribing AT2R/AT4R stimulatory agents, while Hispanics (OR 0.744, 95% CI 0.685-0.808) were associated with lower odds of prescribing AT2R/AT4R inhibitory agents compared to non-Hispanic Whites. CONCLUSIONS: The results showed that the high-dementia risk populations like non-Hispanic Black and Asian American races are proportionally prescribed with higher use of low-dementia risk antihypertensive agents, compared to non-Hispanic Whites.
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Disruptions in polyamine metabolism have been identified as contributing factors to various central nervous system disorders. Our laboratory has previously highlighted the crucial role of polyamine oxidation in retinal disease models, specifically noting elevated levels of spermine oxidase (SMOX) in inner retinal neurons. Our prior research demonstrated that inhibiting SMOX with MDL 72527 protected against vascular injury and microglial activation induced by hyperoxia in the retina. However, the effects of SMOX inhibition on retinal neovascularization and vascular permeability, along with the underlying molecular mechanisms of vascular protection, remain incompletely understood. In this study, we utilized the oxygen-induced retinopathy (OIR) model to explore the impact of SMOX inhibition on retinal neovascularization, vascular permeability, and the molecular mechanisms underlying MDL 72527-mediated vasoprotection in the OIR retina. Our findings indicate that inhibiting SMOX with MDL 72527 mitigated vaso-obliteration and neovascularization in the OIR retina. Additionally, it reduced OIR-induced vascular permeability and Claudin-5 expression, suppressed acrolein-conjugated protein levels, and downregulated P38/ERK1/2/STAT3 signaling. Furthermore, our results revealed that treatment with BSA-Acrolein conjugates significantly decreased the viability of human retinal endothelial cells (HRECs) and activated P38 signaling. These observations contribute valuable insights into the potential therapeutic benefits of SMOX inhibition by MDL 72527 in ischemic retinopathy.
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Electronic health records (EHRs) contain a vast array of phenotypic data on large numbers of individuals, often collected over decades. Due to the wealth of information, EHR data have emerged as a powerful resource to make first discoveries and identify disparities in our healthcare system. While the number of EHR-based studies has exploded in recent years, most of these studies are directed at associations with disease rather than pharmacotherapeutic outcomes, such as drug response or adverse drug reactions. This is largely due to challenges specific to deriving drug-related phenotypes from the EHR. There is great potential for EHR-based discovery in clinical pharmacology research, and there is a critical need to address specific challenges related to accurate and reproducible derivation of drug-related phenotypes from the EHR. This review provides a detailed evaluation of challenges and considerations for deriving drug-related data from EHRs. We provide an examination of EHR-based computable phenotypes and discuss cutting-edge approaches to map medication information for clinical pharmacology research, including medication-based computable phenotypes and natural language processing. We also discuss additional considerations such as data structure, heterogeneity and missing data, rare phenotypes, and diversity within the EHR. By further understanding the complexities associated with conducting clinical pharmacology research using EHR-based data, investigators will be better equipped to design thoughtful studies with more reproducible results. Progress in utilizing EHRs for clinical pharmacology research should lead to significant advances in our ability to understand differential drug response and predict adverse drug reactions.