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The search for biomarkers which would be helpful in diagnosing or predicting the course of diseases of unknown etiology, such as autism or Parkinson's disease (PD), is challenging due to the complex nature of these conditions and their diverse biochemical backgrounds. With help comes metabolomics. Metabolomics studies allow qualitative and quantitative analysis of metabolites which can act as disease markers. Traditional biochemical methods are not always sensitive enough to detect metabolites present at very low concentrations in body fluids. Therefore, chromatographic techniques, especially gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), along with other detection options, are often used in metabolomic studies. The high sensitivity of both methods allows detection of metabolites even in trace amounts, which is crucial for diagnosing neurological diseases, where biochemical changes can be subtle and difficult to detect. Metabolomics research into autism and PD contributes to a better understanding of mechanisms of their development at cellular and molecular levels. Identifying biomarkers may help uncover metabolic changes affecting central nervous system (CNS) functions, such as neurotransmitters, which may be related to communication and social impairments in autism. Similarly, metabolites linked to dopaminergic neuronal degeneration or oxidative stress are being sought in Parkinson's disease. Examples of potential biomarkers include specific fatty acids, products of lipid peroxidation, or compounds related to energy metabolism, which may be indicative of ongoing neurodegenerative processes in the brain. However, more specific diagnostic indicators are still needed, making metabolomic studies together with bioinformatics analysis a valuable tool for the development of personalized diagnostics, but also for monitoring the course of disease and therapeutic strategies in diseases of the CNS. This article presents metabolites which can be considered potential prognostic and diagnostic markers in autism and Parkinson's disease.
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