Development of a Blood-Based Transcriptional Risk Score for Chronic Obstructive Pulmonary Disease

A whole blood-based transcriptional risk score for nonobese type 2 diabetes predicts dynamic changes in glucose metabolic traits

“…To the best of our knowledge, the present study is the first to examine the effects of wb-TRS on nonobese T2D risk and dynamic change of related cardiometabolic traits by using peripheral blood transcriptional markers. Recently, several studies proposed the concept of TRS or polygenetic TRS, which used cumulative gene expression information to provide an additional layer of biological interpretability and performed better than both traditional risk factors and polygenic risk score for predicting Crohn's disease, chronic obstructive pulmonary disease, and lung function [8,[26][27][28]. Our study is in line with previous studies showing transcriptional variance is a reliable intermediary mediating associations of genotypes with complex phenotypes [5,6,29] and provides evidence of implement of blood transcriptional profile could yield a promising better predictive effect on T2D and the dynamic changes in related cardiometabolic traits.…”

“…As an alternative, blood transcriptome could better predict TSGE for ~60% of the genes on average, with up to 81.7% in skeletal muscle, 71.5% in visceral adipose tissue, and 52.4% in pancreas [5]. Blood transcriptome has been emerging as a potential novel approach for complex diseases to understand contribution of genes expression to biological functions and to identify key genes that confer to complex disease susceptibility [6][7][8][9], such as cardiovascular, psychiatry and chronic obstructive pulmonary disease. However, rare studies have investigated the performance of the 2 peripheral blood transcriptional markers in evaluating the risk and prediction of T2D.…”

Contemporary Concise Review 2022: Chronic obstructive pulmonary disease

“…The role of genetic variation beyond AAT remains controversial; it undoubtedly exists but quantifying it is difficult. Several polygenic risk scores have been constructed from very large data sets and this year their predictive value has been improved by adding a transcriptomic profile for COPD 21 . How far these scores can be operationalized remains unclear but they help us understand the complex genesis of COPD.…”

“…Several polygenic risk scores have been constructed from very large data sets and this year their predictive value has been improved by adding a transcriptomic profile for COPD. 21 How far these scores can be operationalized remains unclear but they help us understand the complex genesis of COPD. A major neglected area is the impact of the timing of gene-environment interactions and this has been highlighted by Agusti and colleagues 22 who propose the term GETomics to incorporate a time domain into our mechanistic thinking.…”