Dua Pamila, Prasher Bhavana, Seth Sandeep, Pandey Shivam, Maulik Subir Kumar, Reeta K H
Department of Pharmacology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India.
Department of Ayurgenomics, Institute of Genomics and Integrative Biology, CSIR, South Campus, Delhi, 110025, India.
J Ayurveda Integr Med. 2025 Aug 18;16(5):101178. doi: 10.1016/j.jaim.2025.101178.
Several biochemical tests and biomarkers are well-known for the assessment of risk towards coronary artery disease (CAD). However, conflicting results pose a significant challenge probably due to phenotypic heterogeneity. In Ayurveda, individuals are classified into phenotypes- Prakriti, which helps in predicting an individual's susceptibility to disease, its prognosis and selection of therapy. In the present study, an attempt was made to overcome this challenge with an aim to identify the association between different constitution types as mentioned in Ayurveda with biochemical markers for precisely predicting the risks for CAD.
200 clinically stable CAD patients and 100 healthy controls were recruited from the Cardiology OPD, AIIMS, New Delhi, India. A comprehensive set of tests to incorporate various aspects of CAD pathophysiology was performed. Assessment of Prakriti was done clinically and with AI/ML algorithm based validated questionnaire.
The monocyte-lymphocyte ratio (MLR), fasting blood sugar, urea, creatinine, uric acid, and NT-pro BNP were significantly higher in CAD patients as compared to healthy controls. Prakriti stratification revealed maximum number of patients with Kapha Prakriti. MLR and IL-6 (associated with inflammatory and peripheral endothelial dysfunction) were high in Vata patients; diabetic control (associated with plaque instability and malfunctioned RAAS) was poor in Kapha patients and NT-pro BNP (associated with myocardial hypoxia) was higher in Pitta patients.
Though, several biochemical parameters were associated with risks for CAD, Prakriti classification provided more insights into the precise risks. This dual approach may help in guiding personalized treatment options in CAD management.
几种生化检测和生物标志物在评估冠状动脉疾病（CAD）风险方面广为人知。然而，由于表型异质性，相互矛盾的结果构成了重大挑战。在阿育吠陀医学中，个体被分为不同的表型——体质类型，这有助于预测个体对疾病的易感性、疾病预后以及治疗选择。在本研究中，试图克服这一挑战，旨在确定阿育吠陀医学中提到的不同体质类型与生化标志物之间的关联，以精确预测CAD风险。
从印度新德里全印医学科学研究所（AIIMS）心脏病科门诊招募了200例临床稳定的CAD患者和100例健康对照。进行了一系列综合检测，以纳入CAD病理生理学的各个方面。通过临床评估和基于人工智能/机器学习算法的经过验证的问卷对体质类型进行评估。
与健康对照相比，CAD患者的单核细胞与淋巴细胞比值（MLR）、空腹血糖、尿素、肌酐、尿酸和NT-前脑钠肽显著更高。体质类型分层显示，痰湿体质的患者数量最多。风型患者的MLR和白细胞介素-6（与炎症和外周内皮功能障碍相关）较高；痰湿型患者的血糖控制（与斑块不稳定和肾素-血管紧张素-醛固酮系统功能失调相关）较差，而火型患者的NT-前脑钠肽（与心肌缺氧相关）较高。
虽然有几种生化参数与CAD风险相关，但体质类型分类能更深入地了解精确风险。这种双重方法可能有助于指导CAD管理中的个性化治疗选择。
