AIMC Topic: Metabolome

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Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning algorithms.

Science advances
Biological aging clocks produce age estimates that can track with age-related health outcomes. This study aimed to benchmark machine learning algorithms, including regularized regression, kernel-based methods, and ensembles, for developing metabolomi...

Mapping Thrombosis Serum Markers by H-NMR Allied with Machine Learning Tools.

Molecules (Basel, Switzerland)
Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). H-NMR-based metabonomics data of the serum samples of patient...

Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction.

Frontiers in immunology
BACKGROUND: Cancer remains a leading cause of mortality worldwide. A non-invasive screening solution was required for early diagnosis of cancer. Multi-cancer early detection (MCED) tests have been considered to address the challenge by simultaneously...

Unravelling metabolite-microbiome interactions in inflammatory bowel disease through AI and interaction-based modelling.

Biochimica et biophysica acta. Molecular basis of disease
Inflammatory Bowel Diseases (IBDs) are chronic inflammatory disorders of the gastrointestinal tract and colon affecting approximately 7 million individuals worldwide. The knowledge of specific pathology and aetiological mechanisms leading to IBD is l...

Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.

Journal of translational medicine
BACKGROUND: It is unclear regarding the association between metabolomic state/genetic risk score(GRS) and brain volumes and how much of variance of brain volumes is attributable to metabolomic state or GRS.

Interpretable Machine Learning Algorithms Identify Inetetamab-Mediated Metabolic Signatures and Biomarkers in Treating Breast Cancer.

Journal of clinical laboratory analysis
BACKGROUND: HER2-positive breast cancer (BC), a highly aggressive malignancy, has been treated with the targeted therapy inetetamab for metastatic cases. Inetetamab (Cipterbin) is a recently approved targeted therapy for HER2-positive metastatic BC, ...

Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health.

International journal of molecular sciences
Reliable predictors of long-term all-cause mortality are needed for middle-aged and older populations. Previous metabolomics mortality studies have limitations: a low number of participants and metabolites measured, measurements mainly using nuclear ...

Metabolomic profiling of dengue infection: unraveling molecular signatures by LC-MS/MS and machine learning models.

Metabolomics : Official journal of the Metabolomic Society
BACKGROUND & OBJECTIVE: The progression of dengue fever to severe dengue (SD) is a major public health concern that impairs the capacity of the medical system to predict and treat dengue patients. Hence, the present study used a metabolomic approach ...

Machine learning-causal inference based on multi-omics data reveals the association of altered gut bacteria and bile acid metabolism with neonatal jaundice.

Gut microbes
Early identification of neonatal jaundice (NJ) appears to be essential to avoid bilirubin encephalopathy and neurological sequelae. The interaction between gut microbiota and metabolites plays an important role in early life. It is unclear whether th...

An end-to-end deep learning method for mass spectrometry data analysis to reveal disease-specific metabolic profiles.

Nature communications
Untargeted metabolomic analysis using mass spectrometry provides comprehensive metabolic profiling, but its medical application faces challenges of complex data processing, high inter-batch variability, and unidentified metabolites. Here, we present ...