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ORIGINAL RESEARCH article

Front. Neurosci.
Sec. Neurodevelopment
Volume 18 - 2024 | doi: 10.3389/fnins.2024.1520982
This article is part of the Research Topic Advancing Neurodevelopmental Disorder Models with Human iPSC and Multi-Omics Integration View all 3 articles

MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets

Provisionally accepted
Jared Lichtarge Jared Lichtarge 1Gerarda Cappuccio Gerarda Cappuccio 1,2Soumya Pati Soumya Pati 1,2Alfred Kwabena Dei– Ampeh Alfred Kwabena Dei– Ampeh 1,2Senghong Sing Senghong Sing 2,3LiHua Ma LiHua Ma 4Zhandong Liu Zhandong Liu 1,2Mirjana Maletic-Savatic Mirjana Maletic-Savatic 1,2,5*
  • 1 Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, Texas, United States
  • 2 Baylor College of Medicine, Houston, United States
  • 3 College of Natural Sciences and Mathematics, University of Houston, Houston, Texas, United States
  • 4 Rice University, Houston, Texas, United States
  • 5 Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA, Houston, Ohio, United States

The final, formatted version of the article will be published soon.

    In the rapidly advancing field of 'omics research, there is an increasing demand for sophisticated bioinformatic tools to enable efficient and consistent data analysis. As biological datasets, particularly metabolomics, become larger and more complex, innovative strategies are essential for deciphering the intricate molecular and cellular networks.We introduce a pioneering analytical approach that combines Principal Component Analysis (PCA) with Graphical Lasso (GLASSO). This method is designed to reduce the dimensionality of large datasets while preserving significant variance. For the first time, we applied the PCA-GLASSO algorithm (i.e. MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.The MetaboLINK analysis of longitudinal metabolomics data has revealed distinct pathways related to amino acids, lipids, and energy metabolism, uniquely associated with specific cell progenies. These findings suggest that different metabolic pathways play a critical role at different stages of cellular development, each contributing to diverse cellular functions.Discussion: Our study demonstrates the efficacy of the MetaboLINK approach in analyzing NMR-based longitudinal metabolomic datasets, highlighting key metabolic shifts during cellular transitions. We share the methodology and the code to advance general 'omics research, providing a powerful tool for dissecting large datasets in neurobiology and other fields.

    Keywords: Metabolome, PCA, Glasso, MetaboLINK, hESC, Embryonic bodies, rosettes, neuroprogenitors

    Received: 01 Nov 2024; Accepted: 20 Dec 2024.

    Copyright: © 2024 Lichtarge, Cappuccio, Pati, Dei– Ampeh, Sing, Ma, Liu and Maletic-Savatic. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Mirjana Maletic-Savatic, Baylor College of Medicine, Houston, United States

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