AIMC Topic: Biomarkers

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Integrating machine learning and bioinformatics approaches to identify novel diagnostic gene biomarkers for diabetic mice.

Scientific reports
Diabetes is a complex metabolic disorder, and its pathogenesis involves the interplay of genetic, environmental factors, and lifestyle choices. With the rising prevalence and increasing associated chronic complications, identifying and understanding ...

Exploring the link between the ZJU index and sarcopenia in adults aged 20-59 using NHANES and machine learning.

Scientific reports
Sarcopenia, characterized by progressive loss of muscle mass and function, is a growing public health concern. The ZJU index, a novel metabolic marker, integrates lipid metabolism and glucose regulation parameters. While its association with metaboli...

Development and validation of peripheral blood DNA methylation signatures to predict response to biological therapy in adults with Crohn's disease (EPIC-CD): an epigenome-wide association study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Biological therapeutics are widely used in Crohn's disease, with evidence of efficacy from randomised trials and real-world experience. Primary non-response is a common, poorly understood problem. We aimed to assess blood methylation as a...

Advancing patient monitoring, diagnostics, and treatment strategies for transplant precision medicine.

Lancet (London, England)
Transplant medicine faces substantial challenges, as patients require lifelong immunosuppression to prevent graft rejection. Immunosuppressive regimens to date, while reasonably effective at preventing acute rejection, cause numerous health complicat...

Plasma Lyso-PE 22:6 and Lyso-PE 20:4 are associated with development of mild to moderate depression revealed by metabolomics: a pilot study.

BMC psychiatry
BACKGROUND: Mild to moderate depression (MMD), as an early stage of depression, has a high incidence and may progress to severe depression, even leading to suicide. The lack of effective screening and treatment is due to the unknown metabolic changes...

Lactylation associated biomarkers and immune infiltration in aortic dissection.

Scientific reports
Protein lactylation, a novel post-translational modification (PTM), has emerged as a critical factor in disease processes related to glycolysis and immune responses. However, its role in aortic dissection (AD) has yet to be thoroughly investigated. T...

A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.

Scientific reports
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...

Metabolomic biomarkers could be molecular clocks in timing stroke onset.

Scientific reports
The preferred treatment for acute ischaemic stroke (AIS) is intravenous thrombolysis (IVT) administered within 4.5 hours (h) of symptom onset. This study aimed to identify metabolomic biomarkers for distinguishing AIS patients within 4.5 h of symptom...

Enrichment of extracellular vesicles using Mag-Net for the analysis of the plasma proteome.

Nature communications
Extracellular vesicles (EVs) in plasma are composed of exosomes, microvesicles, and apoptotic bodies. We report a plasma EV enrichment strategy using magnetic beads called Mag-Net. Proteomic interrogation of this plasma EV fraction enables the detect...

Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank.

Scientific reports
Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we develo...