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Fabry disease, an X-linked lysosomal storage disorder caused by galactosidase α (GLA) gene mutations, exhibits diverse clinical manifestations, and poses significant diagnostic challenges. Early diagnosis and treatment are crucial for improved patient outcomes, pressing the need for reliable biomarkers. In this study, we aimed to identify miRNA candidates as potential biomarkers for Fabry disease using the KingFisher™ automated isolation method and NanoString nCounter® miRNA detection assay. Clinical serum samples were collected from both healthy subjects and Fabry disease patients. RNA extraction from the samples was performed using the KingFisher™ automated isolation method with the MagMAX mirVanaTM kit or manually using the Qiagen miRNeasy kit. The subsequent NanoString nCounter® miRNA detection assay showed consistent performance and no correlation between RNA input concentration and raw count, ensuring reliable and reproducible results. Interestingly, the detection range and highly differential miRNA between the control and disease groups were found to be distinct depending on the isolation method employed. Nevertheless, enrichment analysis of miRNA-targeting genes consistently revealed significant associations with angiogenesis pathways in both isolation methods. Additionally, our investigation into the impact of enzyme replacement therapy on miRNA expression indicated that some differential miRNAs may be sensitive to treatment. Our study provides valuable insights to identify miRNA biomarkers for Fabry disease. While different isolation methods yielded various detection ranges and highly differential miRNAs, the consistent association with angiogenesis pathways suggests their significance in disease progression. These findings lay the groundwork for further investigations and validation studies, ultimately leading to the development of non-invasive and reliable biomarkers to aid in early diagnosis and treatment monitoring for Fabry disease.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11515968 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0301733 | PLOS |
Acta Cardiol
September 2025
Department of Cardiovascular Diseases, University Hospital Centre Zagreb, Zagreb, Croatia.
Orphanet J Rare Dis
September 2025
Department of Medical and Surgical Sciences (DIMEC), Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Rationale & Objective: Late-onset Anderson-Fabry disease appears in adulthood, usually with prevalent cardiac involvement. The N215S (p.Asn215Ser) missense mutation represents the most frequent late-onset variant in European countries.
View Article and Find Full Text PDFJ Med Genet
September 2025
Inherited Renal Disorders, Nephrology Department, Fundació Puigvert, IR Sant Pau, RICORS2040, Universitat Autònoma de Barcelona, Barcelona, Spain.
Background: Fabry disease is a progressive, X-linked lysosomal disorder caused by reduced or absent α-galactosidase A activity due to variants. Females with Fabry disease often experience diagnostic delays and an underappreciated disease burden owing to their variable disease presentation and progression.
Methods: We conducted a analysis of all females from the clinical studies FACETS (NCT00925301) and ATTRACT (NCT01218659) and their open-label extensions, assessing baseline characteristics and long-term efficacy of migalastat regarding cardiac and renal function and Fabry-associated clinical events (FACEs).
Malays J Pathol
August 2025
Inborn Errors of Metabolism & Genetics Unit, NMCRC, Institute for Medical Research, National Institutes of Health (NIH), Ministry of Health Malaysia, Selangor, Malaysia.
Lysosomal storage disorders (LSD) are storage disorders involving the malfunction of degradation enzymes in the lysosome. This study aimed to calculate the birth prevalence and carrier frequency of LSDs in the Malaysian population, to compare our results with previously reported epidemiologic data from other populations, and to describe the mutation spectrum in Malaysia. Between 2008 and 2017, 2.
View Article and Find Full Text PDFJMIR AI
August 2025
Department of Nephrology and Hypertension, Hannover Medical School, Carl-Neuberg-Strasse 1, Hannover, 30625, Germany, 49 511 532 3745.
Background: Rare diseases, which affect millions of people worldwide, pose a major challenge, as it often takes years before an accurate diagnosis can be made. This delay results in substantial burdens for patients and health care systems, as misdiagnoses lead to inadequate treatment and increased costs. Artificial intelligence (AI)-powered symptom checkers (SCs) present an opportunity to flag rare diseases earlier in the diagnostic work-up.
View Article and Find Full Text PDF