Browsing by Author "Krüger, Dennis M."

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Plasma miRNAs across the Alzheimer's disease continuum: Relationship to central biomarkers
    (Wiley, 2024) Liu, Shiwei; Park, Tamina; Krüger, Dennis M.; Pena-Centeno, Tonatiuh; Burkhardt, Susanne; Schutz, Anna-Lena; Huang, Yen-Ning; Rosewood, Thea; Chaudhuri, Soumilee; Cho, MinYoung; Risacher, Shannon L.; Wan, Yang; Shaw, Leslie M.; Sananbenesi, Farahnaz; Brodsky, Alexander S.; Lin, Honghuang; Krunic, Andre; Krzysztof Blusztajn, Jan; Saykin, Andrew J.; Delalle, Ivana; Fischer, Andre; Nho, Kwangsik; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Introduction: MicroRNAs (miRNAs) play important roles in gene expression regulation and Alzheimer's disease (AD) pathogenesis. Methods: We investigated the association between baseline plasma miRNAs and central AD biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 803): amyloid, tau, and neurodegeneration (A/T/N). Differentially expressed miRNAs and their targets were identified, followed by pathway enrichment analysis. Machine learning approaches were applied to investigate the role of miRNAs as blood biomarkers. Results: We identified nine, two, and eight miRNAs significantly associated with A/T/N positivity, respectively. We identified 271 genes targeted by amyloid-related miRNAs with estrogen signaling receptor-mediated signaling among the enriched pathways. Additionally, 220 genes targeted by neurodegeneration-related miRNAs showed enrichment in pathways including the insulin growth factor 1 pathway. The classification performance of demographic information for A/T/N positivity was increased up to 9% with the inclusion of miRNAs. Discussion: Plasma miRNAs were associated with central A/T/N biomarkers, highlighting their potential as blood biomarkers. Highlights: We performed association analysis of microRNAs (miRNAs) with amyloid/tau/neurodegeneration (A/T/N) biomarker positivity. We identified dysregulated miRNAs for A/T/N biomarker positivity. We identified Alzheimer's disease biomarker-specific/common pathways related to miRNAs. miRNAs improved the classification for A/T/N positivity by up to 9%. Our study highlights the potential of miRNAs as blood biomarkers.
  • Thumbnail Image
    Item
    The plasma miRNAome in ADNI: Signatures to aid the detection of at-risk individuals
    (Wiley, 2024) Krüger, Dennis M.; Pena-Centeno, Tonatiuh; Liu, Shiwei; Park, Tamina; Kaurani, Lalit; Pradhan, Ranjit; Huang, Yen-Ning; Risacher, Shannon L.; Burkhardt, Susanne; Schütz, Anna-Lena; Wan, Yang; Shaw, Leslie M.; Brodsky, Alexander S.; DeStefano, Anita L.; Lin, Honghuang; Schroeder, Robert; Krunic, Andre; Hempel, Nina; Sananbenesi, Farahnaz; Krzysztof Blusztajn, Jan; Saykin, Andrew J.; Delalle, Ivana; Nho, Kwangsik; Fischer, Andre; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Introduction: MicroRNAs are short non-coding RNAs that control proteostasis at the systems level and are emerging as potential prognostic and diagnostic biomarkers for Alzheimer's disease (AD). Methods: We performed small RNA sequencing on plasma samples from 847 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. Results: We identified microRNA signatures that correlate with AD diagnoses and help predict the conversion from mild cognitive impairment (MCI) to AD. Discussion: Our data demonstrate that plasma microRNA signatures can be used to not only diagnose MCI, but also, critically, predict the conversion from MCI to AD. Moreover, combined with neuropsychological testing, plasma microRNAome evaluation helps predict MCI to AD conversion. These findings are of considerable public interest because they provide a path toward reducing indiscriminate utilization of costly and invasive testing by defining the at-risk segment of the aging population. Highlights: We provide the first analysis of the plasma microRNAome for the ADNI study. The levels of several microRNAs can be used as biomarkers for the prediction of conversion from MCI to AD. Adding the evaluation of plasma microRNA levels to neuropsychological testing in a clinical setting increases the accuracy of MCI to AD conversion prediction.