Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
J Biomed Inform. 2024 Nov;159:104743. doi: 10.1016/j.jbi.2024.104743. Epub 2024 Oct 31.
2017 blood pressure (BP) categories focus on cardiac risk. We hypothesize that studying the balance between mechanisms that increase or decrease BP across the medical phenome will lead to new insights. We devised a classifier that uses BP measures to assign individuals to mutually exclusive categories centered in the upper (Htn), lower (Hotn) and middle (Naf) zones of the BP spectrum; and examined the epidemiologic and phenotypic patterns of these BP-categories.
We classified a cohort of 832,560 deidentified electronic health records by BP-category; compared the frequency of BP-categories and four subtypes of Htn and Hotn by sex and age-decade; visualized the distributions of systolic, diastolic, mean arterial and pulse pressures stratified by BP-category; and ran Phenome-wide Association Studies (PheWAS) for Htn and Hotn. We paired knowledgebases for hypertension and hypotension and computed aggregate knowledgebase status (KB-status) indicating known associations. We assessed alignment of PheWAS results with KB-status for phecodes in the knowledgebase, and paired PheWAS correlations with KB-status to surface phenotypic patterns.
BP-categories represent distinct distributions within the multimodal distributions of systolic and diastolic pressure. They are centered in the upper, lower, and middle zones of mean arterial pressure and provide a different signal than pulse pressure. For phecodes in the knowledgebase, 85% of positive correlations align with KB-status. Phenotypic patterns for Htn and Hotn overlap for several phecodes and are separate for others. Our analysis suggests five candidates for hypothesis testing research, two where the prevalence of the association with Htn or Hotn may be under appreciated, three where mechanisms that increase and decrease blood pressure may be affecting one another's expression.
PairedPheWAS methods may open a phenome-wide path to disentangling hypertension and chronic hypotension. Our classifier provides a starting point for assigning individuals to BP-categories representing the upper, lower, and middle zones of the BP spectrum. 4.7 % of individuals matching 2017 BP categories for normal, elevated BP or isolated hypertension, have diastolic pressure < 60. Research is needed to fine-tune the classifier, provide external validation, evaluate the clinical significance of diastolic pressure < 60, and test the candidate hypotheses.
2017 年血压（BP）分类侧重于心脏风险。我们假设，研究增加或降低血压的机制在整个医学表型中的平衡将带来新的见解。我们设计了一种分类器，该分类器使用 BP 测量值将个体分配到 BP 谱的上（Htn）、下（Hotn）和中（Naf）区的互斥类别中；并检查了这些 BP 类别的流行病学和表型模式。
我们通过 BP 类别对 832560 个匿名电子健康记录进行了分类；按性别和年龄十年比较了 BP 类别和四种 Htn 和 Hotn 亚型的频率；根据 BP 类别分层显示收缩压、舒张压、平均动脉压和脉搏压的分布；并对 Htn 和 Hotn 进行了全表型关联研究（PheWAS）。我们将高血压和低血压知识库配对，并计算了表示已知关联的综合知识库状态（KB-status）。我们评估了 PheWAS 结果与知识库中 phecodes 的 KB-status 的一致性，并将 PheWAS 相关性与 KB-status 配对以发现表型模式。
BP 类别代表收缩压和舒张压多模态分布中的不同分布。它们位于平均动脉压的上、下和中间区域，提供了不同于脉搏压的信号。对于知识库中的 phecodes，85%的正相关与 KB-status 一致。Htn 和 Hotn 的表型模式在一些 phecodes 中重叠，而在其他 phecodes 中则分开。我们的分析表明，有五个候选者可以进行假设检验研究，其中两个可能低估了与 Htn 或 Hotn 相关的关联的普遍性，三个可能影响血压升高和降低的机制相互影响。
配对 PheWAS 方法可能为解开高血压和慢性低血压的表型提供一条途径。我们的分类器为将个体分配到代表 BP 谱的上、下、中区域的 BP 类别提供了一个起点。4.7%符合 2017 年正常、升高的 BP 或孤立性高血压 BP 类别的个体，其舒张压<60。需要进一步研究来调整分类器，提供外部验证，评估舒张压<60 的临床意义，并测试候选假设。
