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Oct 08, 2022
Five Brief Summaries of the Latest Research Articles on Metabolomics and Multi-Omics in the Field of Medicine.
1. Nat Commun | Delayed Gut Microbiota Maturation as a Hallmark of Pediatric Allergic Disease
Allergic diseases impact millions worldwide, with increasing prevalence linked to gut microbiome alterations. Maturation of the infant immune system parallels gut microbiota development, potentially influencing immune programming. A study with participants from the CHILD birth cohort (n = 1115) explored early-life influences on four allergic diagnoses at age 5: atopic dermatitis (AD), asthma (As), food allergy (FA), and allergic rhinitis (AR). Shotgun metagenomic and metabolomic profiling (n = 589) revealed impaired 1-year microbiota maturation as a universal feature of pediatric allergies. Key metabolic imbalances, such as compromised mucous integrity and elevated oxidative activity, mediated the link between microbiota maturation at age 1 and allergic diagnoses at age 5. Microbiota maturation offers insight into deviations from normative development for allergy prediction and prevention.
2. Microbiome | Multi-Omics Insights into Antidepressant Treatment for Major Depressive Disorder
The gut-brain axis disturbance is implicated in major depressive disorder (MDD). However, the effects of antidepressants on the gut microbiota and their role in treatment efficacy remain unclear. A multi-omics study involving 110 MDD patients treated with escitalopram (ESC) for 12 weeks compared to 166 healthy individuals uncovered ESC's impact on blood metabolism and the gut microbiota. ESC improved abnormal blood metabolism in MDD patients by modulating amino acids and fatty acids. While ESC showed limited inhibitory effects on the gut microbiota, machine learning-based analysis linked gut microbiota to changes in plasma metabolites, including tryptophan and its microbiota-derived metabolite, indole-3-propionic acid (I3PA). This study sheds light on the intricate relationship among antidepressants, gut microbiota, and the blood metabolome.
Rising peanut allergy rates prompt investigations into development for prevention and therapy insights. Microbiota and their metabolites shape food allergy risk. A longitudinal study examined infants at allergy risk (n=122) who were followed through mid-childhood, with 28.7% developing peanut allergy. Lower infant gut microbiome diversity correlated with peanut allergy development. Temporal changes in specific microbiota and metabolite levels differed in children with peanut allergies. Metabolites associated with peanut allergy clustered in histidine metabolism. The study highlights distinct gut microbiome and metabolome dynamics in peanut allergy development, informing potential prevention strategies.
Understanding the molecular heterogeneity of HER2-low breast cancer, particularly in the Chinese population, is crucial for precise management. A study of 434 Chinese patients integrated genomic, transcriptomic, proteomic, and metabolomic data. HER2-low tumors exhibited unique characteristics in the hormone receptor-negative subgroup. Non-basal-like HER2-low tumors in this subgroup resembled HER2-positive disease and featured PIK3CA mutations, FGFR4/PTK6/ERBB4 overexpression, and lipid metabolism activation. Among hormone receptor - positive tumors, HER2-low tumors showed less loss/deletion in 17q peaks than HER2-0 tumors. This work reveals the heterogeneity of HER2-low breast cancers and emphasizes the need for precise stratification based on hormone receptor status and molecular subtype.
Molecular classification holds promise for prognosis and precision therapy in hepatocellular carcinoma (HCC). This study developed a molecular classification based on the fatty acid degradation (FAD) pathway, evaluating its role in guiding personalized therapy. Data from 41 HCC patients, including anti-PD-1 therapy recipients, were analyzed through RNA sequencing, PCR-array, lipidomics, metabolomics, and proteomics. Single-cell RNA sequencing explored the tumor microenvironment. Nearly 60 publicly-available multi-omics datasets were examined. FAD subtypes (F1, F2, and F3) were identified based on clinical, mutational, epigenetic, metabolic, and immunological characteristics. These subtypes offer insights into individualized HCC therapy and clinical decision-making.
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