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Metabolites
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The Future Perspective on Screening and Diagnosis of Inborn Errors...
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The Future Perspective on Screening and Diagnosis of Inborn Errors of Metabolism

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (15 May 2026) | Viewed by 2081

Editors

Dr. Luiz Carlos Santana-Da-Silva

E-Mail Website
Guest Editor
Laboratory of Inborn Errors of Metabolism, Institute of Biological Sciences, Federal University of Pará, Belém, PA 66075-110, Brazil
Interests: inborn errors of metabolism; cell biology; newborn screening
Dr. Olga Yaneth Echeverri-Peña

E-Mail Website
Guest Editor
Lab 303A, Instituto de Errores Innatos del Metabolismo, Facultad de Ciencias, Pontificia Universidad Javeriana, Carrera 7 # 43-82, Ed. 54, Bogotá 110231, Colombia
Interests: inborn errors of metabolism; IEM diagnostic approach; omics sciences for IEM; IEM biomarkers search; new diagnostic techniques
Dr. Angela J. Espejo-Mojica

E-Mail Website
Guest Editor
Facultad de Ciencias, Pontificia Universidad Javeriana, Bogota, Colombia
Interests: inborn errors of metabolism; gene therapy; enzyme replacement therapy

Special Issue Information

Dear Colleagues,

This Special Issue, "The Future Perspective on Screening and Diagnosis of Inborn Errors of Metabolism", provides a comprehensive examination of the evolving landscape of IEM diagnostics.  It explores the current state-of-the-art and anticipates future directions in the detection, screening, and diagnosis of these complex disorders. The Special Issue offers a detailed review of novel methodologies, including advanced genetic screening techniques, the identification and validation of novel biomarkers, and the development of sophisticated diagnostic platforms. A key focus is the integration of these advancements into clinical practice, with particular attention on the principles of precision medicine and the implementation of early intervention strategies. The scope encompasses a broad range of topics, including, but not limited to, the following: next-generation sequencing and its applications in IEM diagnostics; the role of “omics” sciences in identifying molecular signatures; the integration of artificial intelligence and machine learning for data analysis and diagnostic support; and the application of advanced data analytics for improving diagnostic accuracy. Furthermore, the Special Issue addresses the development and validation of diagnostic algorithms, the optimization of newborn screening programs, and the adaptation of emerging technologies. The overarching goal is to stimulate research, inform clinical practice, and facilitate the translation of scientific discoveries into improved patient outcomes on a global scale.

Dr. Luiz Carlos Santana-Da-Silva
Dr. Olga Yaneth Echeverri-Peña
Dr. Ángela J. Espejo-Mojica
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • inborn errors of metabolism (IEM)
  • genetic disorders
  • diagnostics
  • biomarkers
  • omics sciences
  • imaging techniques (MRS, PET)
  • molecular techniques (NGS, gene editing)
  • personalized medi-cine
  • early detection

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Published Papers (4 papers)

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13 pages, 1121 KB  
Article
Plasma Aromatic L-Amino Acid Decarboxylase Activity by HPLC as a Functional Biomarker for the Diagnosis of Aromatic L-Amino Acid Decarboxylase Deficiency
by Norashareena Mohamed Shakrin, Norzahidah Khalid, Nor Azimah Abdul Azize, Yusnita Yakob, Abdah Md. Akim and Julaina Abdul Jalil
Metabolites 2026, 16(7), 444; https://doi.org/10.3390/metabo16070444 - 25 Jun 2026
Viewed by 190
Abstract
Background/Objectives: Aromatic L-amino acid decarboxylase deficiency (AADC-D; OMIM #608643) is a rare autosomal recessive neurometabolic disorder caused by pathogenic variants in the DDC gene, leading to impaired of monoamine neurotransmitter biosynthesis. AADC, a pyridoxal-5′-phosphate (PLP)-dependent enzyme, catalyzes the conversion of L-dopa and [...] Read more.
Background/Objectives: Aromatic L-amino acid decarboxylase deficiency (AADC-D; OMIM #608643) is a rare autosomal recessive neurometabolic disorder caused by pathogenic variants in the DDC gene, leading to impaired of monoamine neurotransmitter biosynthesis. AADC, a pyridoxal-5′-phosphate (PLP)-dependent enzyme, catalyzes the conversion of L-dopa and 5-hydroxytryptophan (5-HTP) to dopamine and serotonin, respectively. Early diagnosis remains challenging due to the limited specificity of current biochemical approaches. This study aimed to evaluate plasma AADC enzyme activity using these physiological substrates by High-Performance Liquid Chromatography (HPLC)-based method and assess its potential utility in the biochemical diagnosis of AADC deficiency. Methods: Plasma AADC activity was quantified using physiological substrates (L-dopa and 5-HTP) by HPLC with electrochemical and fluorescence detection. Sanger sequencing of the DDC gene was performed in two suspected patients to identify pathogenic variants. Results: Two genetically confirmed AADC-D patients demonstrated reduced enzyme activity. Using L-dopa as substrate, enzyme activity in patients was 12.4 and 26.1 pmol/min/mL, both below the published reference interval (36–129 pmol/min/mL). Using 5-HTP as substrate, enzyme activity was 1.5 and 5.1 pmol/min/mL; Patient 1 showed activity below the reference interval (2.0–7.1 pmol/min/mL), while Patient 2 demonstrated activity within the lower range of reported values. Reduced enzyme activity was consistent with the clinical features and molecular findings with identification of pathogenic variants in the DDC gene (c.175G>A and c.714+4A>T). Conclusions: Plasma AADC activity measurement demonstrates potential as a functional biochemical biomarker that augments molecular genetic testing in the biochemical evaluation of AADC deficiency. Further studies involving larger patient cohorts are required to further evaluate its diagnostic performance and broader clinical applicability. Full article
(This article belongs to the Special Issue The Future Perspective on Screening and Diagnosis of Inborn Errors of Metabolism)
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13 pages, 1189 KB  
Article
Screening and Stratification Utility of GDF-15 and FGF-21 in Individuals Evaluated for Suspected Mitochondrial Disease: A Malaysian Cohort Study
by Affandi Omar, Dyg Pertiwi Abg Kamaludin, Wan Ahmad Syazani Mohamed, Fatimah Diana Amin Nordin, Rosnani Mohamed, Badrul Hisyam Razali, Imilia Ismail, Ngu Lock Hock and Julaina Abdul Jalil
Metabolites 2026, 16(6), 372; https://doi.org/10.3390/metabo16060372 - 29 May 2026
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Abstract
Background/Objectives: Early detection of mitochondrial disorders remains challenging due to phenotypic heterogeneity and limited access to definitive molecular diagnostics. Circulating biomarkers such as growth differentiation factor-15 (GDF-15) and fibroblast growth factor-21 (FGF-21) have emerged as potential adjunct indicators. This study evaluated the [...] Read more.
Background/Objectives: Early detection of mitochondrial disorders remains challenging due to phenotypic heterogeneity and limited access to definitive molecular diagnostics. Circulating biomarkers such as growth differentiation factor-15 (GDF-15) and fibroblast growth factor-21 (FGF-21) have emerged as potential adjunct indicators. This study evaluated the screening and stratification utility of GDF-15 and FGF-21 in individuals assessed for suspected mitochondrial disease. Methods: Archived biological specimens collected between 2016 and 2017 were analysed from 221 individuals stratified into clinically high-risk, screen-positive non-high-risk, post-mortem unexplained death and healthy controls groups. Plasma and fibroblast lysate concentrations of GDF-15 and FGF-21 were quantified using enzyme-linked immunosorbent assays. Biomarker performance was assessed using receiver operating characteristic (ROC) analysis, comparative group analysis and correlation testing across clinically defined referral groups. Results: Both biomarkers were significantly elevated in clinically high-risk and screen-positive individuals compared with controls. GDF-15 demonstrated better discriminatory performance than FGF-21, with an area under the curve (AUC) of 0.7187 ± 0.0556 versus 0.6301 ± 0.0603. At a threshold of 300 pg/mL, GDF-15 demonstrated high sensitivity with moderate specificity for differentiation between clinically defined high-risk individuals and controls. Correlation analysis showed weak associations between GDF-15 and lactate and ammonia, while FGF-21 correlated modestly with glucose and alkaline phosphatase. A moderate positive correlation was observed between GDF-15 and FGF-21 across the overall cohort. Conclusions: GDF-15 and, to a lesser extent, FGF-21 may support early screening and stratification of individuals evaluated for suspected mitochondrial disease and assist in prioritising cases for further diagnostic evaluation. Full article
(This article belongs to the Special Issue The Future Perspective on Screening and Diagnosis of Inborn Errors of Metabolism)
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9 pages, 709 KB  
Communication
Towards Next-Generation Sequencing as a First-Tier Diagnostic Test for Fructose-1,6-Bisphosphatase Deficiency
by Nadine Yazbeck, Abir Barhoumi and Pascale E. Karam
Metabolites 2026, 16(1), 56; https://doi.org/10.3390/metabo16010056 - 8 Jan 2026
Viewed by 645
Abstract
Background: Advances in genomic technologies combined with tandem mass newborn screening have enabled early detection and management of several common inborn errors of metabolism. Fructose-1,6-bisphosphatase deficiency, an autosomal recessive treatable disorder reported in around 150 patients worldwide, remains underdiagnosed despite an excellent prognosis [...] Read more.
Background: Advances in genomic technologies combined with tandem mass newborn screening have enabled early detection and management of several common inborn errors of metabolism. Fructose-1,6-bisphosphatase deficiency, an autosomal recessive treatable disorder reported in around 150 patients worldwide, remains underdiagnosed despite an excellent prognosis with early detection. Although common in highly consanguineous populations, diagnosis is often delayed due to the non-specific clinical and biochemical profile. Methods: This report explores the diagnostic pathway using first-tier next-generation sequencing of three novel cases of fructose-1,6-bisphosphatase deficiency in a tertiary care center in Lebanon. Results: Two patients were diagnosed with first-tier exome sequencing within one month of presentation and had an excellent outcome at 6 years of follow-up. The third patient, undiagnosed for 10 years, suffered from neurological sequalae. The molecular profile was remarkable in two patients for exon 2 deletion in the FBP1 gene, a founder mutation reported in Turkish and Armenian patients, and a rare frameshift mutation in the third case. Conclusions: The use of next-generation sequencing as as a first-tier test for FBP deficiency is a non-invasive and rapid method for early diagnosis and management of this rare yet treatable disorder. It can detect both disease-causing variants and large deletions, founder mutations as well, delineating the molecular profile in populations where this disorder is highly prevalent. Full article
(This article belongs to the Special Issue The Future Perspective on Screening and Diagnosis of Inborn Errors of Metabolism)
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50 pages, 1968 KB  
Systematic Review
Historical Perspectives, Classification and Diagnostic Approaches of Inborn Errors of Metabolism: A Systematic Review and Meta-Analysis
by Janvière Mutamuliza, Elizabeth Gori, Léon Mutesa and François-Guillaume Debray
Metabolites 2026, 16(7), 445; https://doi.org/10.3390/metabo16070445 - 25 Jun 2026
Viewed by 188
Abstract
Background: Inborn errors of metabolism (IEMs) represent a diverse group of genetic disorders affecting biochemical pathways. Despite advances in diagnostic technologies, comprehensive understanding of their historical evolution, classification systems, and diagnostic approaches remains fragmented. Objectives: This systematic review and meta-analysis aimed to synthesize [...] Read more.
Background: Inborn errors of metabolism (IEMs) represent a diverse group of genetic disorders affecting biochemical pathways. Despite advances in diagnostic technologies, comprehensive understanding of their historical evolution, classification systems, and diagnostic approaches remains fragmented. Objectives: This systematic review and meta-analysis aimed to synthesize evidence on the historical development, classification frameworks, and diagnostic modalities for IEMs, diagnostic accuracy, and prevalence estimates, providing a comprehensive resource for clinicians and researchers. Methods: Following PRISMA 2020 guidelines, we conducted a systematic search of seven electronic databases (PubMed/MEDLINE, Embase, Scopus, Web of Science, Google Scholar, SciSpace and ArXiv) from January 2000 to March 2026. Studies addressing historical perspectives, classification systems, or diagnostic approaches for IEMs were included. Two independent reviewers performed screening, data extraction, and quality assessment. Meta-analyses were conducted using random-effects models for diagnostic accuracy and prevalence estimates. Results: From 1342 identified records, 54 studies met the inclusion criteria, encompassing 8,234,567 individuals across 35 countries. Historical analysis revealed 16 major milestones from Garrod’s 1902 “chemical individuality” concept to the current AI-powered diagnostics. Four major classification systems were identified: pathophysiological (intoxication, energy deficiency, complex molecule disorders), biochemical pathway (amino acid, organic acid, urea cycle, carbohydrate, fatty acid oxidation, mitochondrial, peroxisomal, lysosomal disorders), organelle-based, and the integrated Society for the Study of Inborn Errors of Metabolism (SSIEM) nosology. Meta-analysis demonstrated high diagnostic performance of tandem mass spectrometry (MS/MS) with a pooled sensitivity of 99.1% (95% CI: 98.6–99.5) and specificity of 99.8% (95% CI: 99.7–99.9%). The pooled global prevalence of IEMs was 50.9 per 100,000 live births (95% CI 45.2–56.8). Next-generation sequencing achieved a diagnostic yield of 42.8% (95% CI: 38.2–47.5%) in suspected cases. Emerging AI-powered diagnostic tools demonstrated high discrimination performance with area under the curve (AUC) values exceeding 0.95 for specific IEM, though external validation remains limited. Newborn screening expanded from single-disease to comprehensive panels detecting over 50 disorders. Conclusions: This comprehensive review demonstrates that IEMs have evolved from rare curiosities to systematically diagnosable conditions through technological advances. Integration of metabolomics, genomics, proteomics and artificial intelligence promises further diagnostic improvements. Standardized classification systems and evidence-based diagnostic algorithms are essential for optimal patient care. Future directions include artificial intelligence-enhanced diagnostics, expanded screening, and personalized medicine approaches. Full article
(This article belongs to the Special Issue The Future Perspective on Screening and Diagnosis of Inborn Errors of Metabolism)
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