Multimodal plasma metabolomics and lipidomics in elucidating metabolic perturbations in tuberculosis patients with concurrent type 2 diabetes

Impaired resolution of blood transcriptomes through tuberculosis treatment with diabetes comorbidity

“…People with type 2 diabetes have complex metabolic and lipid disturbances, including elevated triglycerides, reduced high‐density lipoproteins and increased low‐density lipoproteins in blood. Such changes have also been observed in TB‐DM co‐morbidity, 50 with measurements of altered carbohydrate, amino acid and lipid metabolism able to clearly discriminate between TB and TB‐DM 51 . It is likely not the hyperglycaemia per se which has caused the alterations in the gene expression in people with TB‐DM in the current study: rather this would be the overall result of the complex metabolic disturbance.…”

“…Such changes have also been observed in TB‐DM co‐morbidity, 50 with measurements of altered carbohydrate, amino acid and lipid metabolism able to clearly discriminate between TB and TB‐DM. 51 It is likely not the hyperglycaemia per se which has caused the alterations in the gene expression in people with TB‐DM in the current study: rather this would be the overall result of the complex metabolic disturbance. Here, the overall consistency in change of gene expression through treatment, irrespective of diabetes status, enabled derivation of accurate predictive models of TB treatment response, which could be used effectively in populations with or without diabetes.…”

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

“…Horizontal (metabolomics and lipidomics) and vertical (genomics, transcriptomics, proteomics, and metabolomics) multi-omics data integration present a powerful approach to capture a holistic view of the molecular landscape, which could provide a comprehensive understanding of an individual's response to anti-TB drugs [ 123 , 124 ]. These approaches are described as prospects to improve the better-personalized medicine of TB and allow the discovery of biosignatures for treatment monitoring and clinical outcomes (efficacy and AEs) [ 123 , [125] , [126] , [127] ]. Long et al.…”

“…Yen et al. [ 127 ] established multi-modal data analysis to elucidate the metabolic perturbations in TB patients with concurrent type 2 diabetes. This comprehensive profiling increases the knowledge of TB patients with diabetes comorbidities and contributes to developing more effective and safe treatment [ 127 ].…”

“…[ 127 ] established multi-modal data analysis to elucidate the metabolic perturbations in TB patients with concurrent type 2 diabetes. This comprehensive profiling increases the knowledge of TB patients with diabetes comorbidities and contributes to developing more effective and safe treatment [ 127 ]. Collectively, these multi-modal data will be the foundation for constructing predictive models for personalized dosing, efficacy, ADRs and drug resistance prediction and management, and the estimate of the probability of treatment failure ( Fig.…”