{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n Recent investigations into non‐coding RNA biomarkers suggest that EAF1‐AS1—a long intergenic non‐coding RNA—is emerging as a candidate regulatory molecule in complex human diseases. In the context of chronic kidney disease (CKD), early diagnosis is hindered by the lack of highly sensitive traditional markers. The review highlighted in"}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": "emphasizes the promise of including novel biomarkers such as ncRNAs and lincRNAs in CKD detection and prognosis. Although not examined in isolation, EAF1‐AS1 is considered among these potential lincRNA biomarkers that could reflect underlying pathological processes and thereby improve early detection and monitoring of CKD progression."}]}, {"type": "t", "text": "\n \n "}, {"type": "p", "children": [{"type": "t", "text": "\n Similarly, research into Parkinson’s disease (PD) underscores the importance of genetic variants located in non‐coding regions and their tissue‐specific regulatory effects. The study described in"}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": "used machine learning to integrate tissue‐specific eQTL data with known PD-associated variants. Here, long non-coding RNAs like EAF1‐AS1 are implicated as potential mediators for translating non-coding genetic variation into altered gene expression profiles, which may contribute to disease etiology. Although detailed mechanistic insights into EAF1‐AS1 function remain to be fully elucidated, its inclusion among promising non-coding RNA biomarkers supports the notion that it might modulate gene regulatory networks in a tissue-specific manner relevant to both renal and neurodegenerative pathologies.\n "}]}, {"type": "t", "text": "\n \n "}, {"type": "p", "children": [{"type": "t", "text": "\n Overall, while direct functional evidence for EAF1‐AS1 is still emerging, its recognition in these studies positions it as a potential diagnostic and prognostic biomarker—a molecule that may enhance our understanding of disease mechanisms in CKD and PD, and offer new avenues for therapeutic intervention.\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Jacek Rysz, Anna Gluba-Brzózka, Beata Franczyk, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Novel Biomarkers in the Diagnosis of Chronic Kidney Disease and the Prediction of Its Outcome."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Int J Mol Sci (2017)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.3390/ijms18081702"}], "href": "https://doi.org/10.3390/ijms18081702"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "28777303"}], "href": "https://pubmed.ncbi.nlm.nih.gov/28777303"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Daniel Ho, William Schierding, Sophie L Farrow, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Front Genet (2022)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.3389/fgene.2021.785436"}], "href": "https://doi.org/10.3389/fgene.2021.785436"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "35047012"}], "href": "https://pubmed.ncbi.nlm.nih.gov/35047012"}]}]}]}