Abbas Tahseen, Chaturvedi Gaura, Prakrithi P, Pathak Ankit Kumar, Kutum Rintu, Dakle Pushkar, Narang Ankita, Manchanda Vijeta, Patil Rutuja, Aggarwal Dhiraj, Girase Bhushan, Srivastava Ankita, Kapoor Manav, Gupta Ishaan, Pandey Rajesh, Juvekar Sanjay, Dash Debasis, Mukerji Mitali, Prasher Bhavana
Centre of Excellence for Applied Development of Ayurveda Prakriti and Genomics, CSIR Ayurgenomics Unit-TRISUTRA, CSIR-Institute of Genomics & Integrative Biology, Delhi 110020, India.
Informatics and Big Data Unit, CSIR-Institute of Genomics & Integrative Biology, Mathura Road, Delhi 110020, India.
J Pers Med. 2022 Mar 18;12(3):489. doi: 10.3390/jpm12030489.
Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed "". It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 () and rs941590 () that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.
精准医学旨在从传统的反应性医学转向一种能够在疾病发生前识别风险群体的系统。然而，患病个体和健康个体之间的表型异质性对风险分层和早期可采取行动干预的识别标志物构成了重大挑战。在阿育吠陀医学中，个体基于被称为“”的多系统表型在表型上被分为七种体质类型。这使得能够预测健康和疾病轨迹，并选择健康干预措施。我们假设，对表型同质类型的健康个体进行外显子组测序可能有助于识别与体质类型相关的功能变异。来自两个基因同质队列（印度北部和西部）的144名健康分层个体和对照的外显子组揭示了健康个体中代谢紊乱、肝脏疾病以及身体和血液学测量等疾病/特征的差异风险。这些单核苷酸多态性（SNP）也与印欧背景对照有显著差异。在这些之中，我们重点介绍了新的SNP rs304447（）和rs941590（），它们可以解释免疫反应、出血或血栓形成的差异轨迹。我们的方法证明了在一项有充分效力的研究中需要相对较小的样本量。这项研究突出了整合独特表型分析方法以识别预测标志物和健康人群中高危人群的潜力。
