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Updated: Oct 18, 2026

Lipidomics and Transcriptomics in Neurological Diseases
Published on: March 18, 2022
Decoding the Rare: Integrative Genomics, Predictive Algorithms and Lipidomics as a Guide for in Lysosomal Storage
Isidro Arévalo-Vargas1, Irene Serrano-Gonzalo2, Sonia Roca-Esteve2
1Universidad de Zaragoza, Departamento de Bioquímica, Biología Molecular y Celular, Zaragoza, Spain; Fundación para el Estudio y la Terapéutica de la Enfermedad de Gaucher y Otras Lisosomales, Zaragoza, Spain; Corporación Unificada Nacional de Educación Superior, Bogotá, Colombia.
Background:
Lysosomal storage disorders (LSDs) are rare, inherited metabolic conditions characterized by the accumulation of undegraded substrates within lysosomes, leading to progressive multisystemic disease. Clinical and genetic heterogeneity poses significant diagnostic and therapeutic challenges.
Objective:
This review explores the evolution of LSD diagnostics and highlights the integration of genomic, computational, and biochemical approaches, as well as their implications for personalized medicine.
Content:
This narrative review is based on a literature search conducted in PubMed, Scopus, and Web of Science, focusing on diagnostic strategies and biomarker development in LSDs. Traditional diagnostic methods, based on clinical suspicion, enzymatic assays, and substrate quantification, are limited by phenotypic variability and diagnostic uncertainty. Recent advances in next-generation sequencing (NGS), lipidomic profiling, particularly via liquid chromatography-tandem mass spectrometry (LC-MS/MS), and in silico variant prediction tools have redefined the diagnostic workflow. When used together, these methodologies allow for more accurate diagnoses, support the classification of variants of uncertain significance (VUS), and guide therapy selection. Biomarkers such as globotriaosylsphingosine (Lyso-Gb3) and glucosylsphingosine (Lyso-Gb1) have become key tools for diagnosing and monitoring specific LSDs, though their performance may vary based on clinical context and patient characteristics. Significant challenges remain, including methodological variability, lack of biomarker standardization, ethical concerns related to genomic testing, and limited clinical integration of multiomic data.
Conclusion:
The diagnostic landscape for LSDs is shifting toward integrative, personalized approaches. Continued progress will depend on interdisciplinary collaboration, technological development, and harmonized frameworks that ensure equitable access and sustainable innovation, serving as a guiding compass for LSD research.
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