Circular RNA expression profile of Alzheimer’s disease and its clinical significance as biomarkers for the disease risk and progression

https://doi.org/10.1016/j.biocel.2020.105747Get rights and content

Abstract

Objective

To investigate circular RNA (circRNA) expression profile via microarray, and further assess the potential of candidate circRNAs as biomarkers in Alzheimer’s disease (AD).

Methods

CircRNA expression profile in cerebrospinal fluid from 8 AD patients and 8 control (Ctrl) subjects was assessed by microarray. Subsequently, 10 candidate circRNAs from microarray were validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in cerebrospinal fluid from 80 AD patients and 40 Ctrl subjects.

Results

By microarray, 112 circRNAs were upregulated and 51 circRNAs were downregulated in AD patients compared with Ctrl subjects, and these circRNAs were enriched in AD related pathways such as neurotrophin signaling pathway, natural killer cell mediated cytotoxicity and cholinergic synapse. By RT-qPCR, circ-LPAR1, circ-AXL and circ-GPHN were increased, whereas circ-PCCA, circ-HAUS4, circ-KIF18B and circ-TTC39C were decreased in AD patients compared with Ctrl subjects, and these circRNAs were disclosed to predict AD risk by receiver operating characteristics curve analysis. Further forward-stepwise multivariate logistic regression revealed that circ-AXL, circ-GPHN, circ-ITPR3, circ-PCCA and cic-TTC39C were independent predictive factors for AD risk. Besides, in AD patients, circ-AXL and circ-GPHN negatively correlated, while circ-PCCA and circ-HAUS4 positively correlated with mini–mental state examination score; Circ-AXL negatively correlated, while circ-PCCA, circ-HAUS4 and circ-KIF18B positively correlated with Aβ42; Circ-AXL and circ-GPHN positively correlated, whereas circ-HAUS4 negatively correlated with t-tau; Circ-AXL positively correlated with p-tau.

Conclusion

Our study provides an overview of circRNA expression profile in AD, and identifies that circ-AXL, circ-GPHN and circ-PCCA hold clinical implications for guiding disease management in AD patients.

Introduction

Alzheimer’s disease (AD) is the main cause of dementia in elderly population, which is marked by the accumulation of neurotoxic amyloid plaques, hyperphosphorylated tau tangles, neuroinflammation and extensive neuronal cell death in brain [[1], [2], [3]]. It is estimated to affect 40.0 million individuals (mostly older than 60 years) worldwide [3]. Generally, AD patients experience a long asymptomatic preclinical phase (more than 20 years) before the clinical onset of typical symptoms [4]. As the disease manifests, AD patients begin to suffer from devasting, persistent and progressive memory loss combined with cognitive decline and loss of independent care, which poses a great emotional and financial burden to both families and society [3]. Despite decades of tremendous pharmaceutical industry efforts to develop drug treatments for halting the progression of AD symptoms or curing AD, there is still no effective drug treatment available yet [5]. Therefore, it is of particular importance to investigate potential biomarkers for predicting disease risk, guiding management and decision-making of AD.

Circular RNAs (CircRNAs) is a class of endogenous noncoding RNAs, and are generated from back-splicing events and defined by covalently closed circular configuration without 5’ end caps and 3’ polyadenylated tails [6]. CircRNAs have been misinterpreted as by-products of aberrant splicing without any function for decades [7]. In recent years, a growing number of studies have focused on circRNAs and gradually uncover that a select number of circRNAs (such as circRNA Cdr1as and circ_000950) function as microRNAs (miRNAs) sponges to disturb the downstream signaling pathways of these miRNAs and participate in the pathogenesis of neurodegenerative diseases [[8], [9], [10]]. Notably, with the advent and application of microarrays coupled with novel bioinformatic analysis, our understanding about circRNA expression profile has been built and extended in various diseases [[11], [12], [13]]. Regarding AD, just presently two studies based on the mouse model, which analyze the circRNA expression profile of AD mice and disclose that a number of circRNAs are involved in the pathogenesis of AD [14,15]. For instance, 85 circRNAs are dysregulated (45 upregulated and 40 downregulated) in 10-month-old senescence accelerated mice P8 (SAMP8) compared with age-matched senescence-accelerated mouse resistant R1 (SAMR1), and mmu_circRNA_017963 is validated to be positively correlated with the progression of AD [14]. Another study illustrates that 10 circRNAs are differentially expressed (4 upregulated and 6 downregulated) in Panax notoginseng saponins (PNS)-treated SAMP8 compared with PNS-untreated SAMP8, and mmu_circRNA_013636 as well as mmu_circRNA_012180 participate in AD-associated signaling pathways [15]. However, in clinical studies, there is currently no report about the circRNA expression profile in AD patients.

In the current study, initially, we characterized the circRNA expression profile of 8 AD patients and 8 control (Ctrl) subjects by microarray analysis. Subsequently, we further used reverse transcription quantitative polymerase chain reaction (RT-qPCR) to validate 10 candidate circRNAs (top 5 upregulated and top 5 downregulated from microarray analysis) in 80 AD patients and 40 Ctrl subjects. Lastly, we investigated the correlation of 10 candidate circRNAs with disease risk and disease severity of AD. Through these explorations, we aimed to evaluate the potential of circRNA expression profile in predicting disease risk and assisting management of AD in clinical practice.

Section snippets

Participants

Eighty AD patients and forty Ctrl subjects were consecutively recruited in People’s Hospital of Zhengzhou University. The inclusion criteria of AD patients were: (1) newly diagnosed as AD according to the NIA-AA criteria [16], (2) presenting with decreased amyloid β-42 (Aβ42) (<550 pg/mL), increased total tau (t-tau) (≥350 pg/mL) and increased phosphorylated tau (p-tau) (≥70 pg/mL) in cerebrospinal fluid (CSF); (3) age≥40 years. And the patients who complicated with brain injuries (such as

Comparison of clinical features between 8 AD patients and 8 Ctrl subjects

For microarray analysis, 8 AD patients and 8 Ctrl subjects were included. No difference of mean age (P = 0.727), gender (P = 0.282) or mean education duration (P = 0.177) was observed between AD patients and Ctrl subjects. As for the mean MMSE score, it was decreased in AD patients compared with Ctrl subjects (P < 0.001). Besides, the mean Aβ42 level (P < 0.001) was lower, whereas the mean t-tau level (P < 0.001), mean p-tau level (P = 0.001) and mean 8-OHG level (P = 0.001) were higher in AD

Discussion

In the present study, a microarray analysis of circRNA expression profile in 8 AD patients and 8 Ctrl subjects disclosed that circRNA expression profile could differentiate AD patients from Ctrl subjects, and dysregulated circRNAs were enriched in multiple pathophysiology processes of AD, especially regarding neuron cell death, neuroinflammation and neurodegeneration pathways. Further validation by RT-qPCR in 80 AD patients and 40 Ctrl subjects found that circ-LPAR1, circ-AXL, circ-GPHN,

Conclusion

In conclusion, the present study provides a comprehensive overview of dysregulated circRNAs in AD, and identifies that circ-AXL, circ-GPHN and circ-PCCA may hold the clinical value for predicting disease risk and progression of AD. These findings may provide valuable insights for supporting patient care, guiding management and decision making of AD in clinics.

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgements

This study was supported by Beijing Medical and Health Foundation (No. B17773) and The 23456 Talent Project of Henan Provincial People’s Hospital.

References (35)

  • R.J. Bateman et al.

    Clinical and biomarker changes in dominantly inherited Alzheimer’s disease

    N Engl J Med

    (2012)
  • W.V. Graham et al.

    Update on Alzheimer’s Disease Therapy and Prevention Strategies

    Annu Rev Med

    (2017)
  • Z. Wang et al.

    Identifying circRNA-associated-ceRNA networks in the hippocampus of Abeta1-42-induced Alzheimer’s disease-like rats using microarray analysis

    Aging (Albany NY)

    (2018)
  • M. Piwecka et al.

    Loss of a mammalian circular RNA locus causes miRNA deregulation and affects brain function

    Science

    (2017)
  • H. Yang et al.

    Circular RNA circ_0000950 promotes neuron apoptosis, suppresses neurite outgrowth and elevates inflammatory cytokines levels via directly sponging miR-103 in Alzheimer's disease

    Cell Cycle

    (2019)
  • Z. Dong et al.

    CircRNA expression profiles and function prediction in peripheral blood mononuclear cells of patients with acute ischemic stroke

    J Cell Physiol

    (2019)
  • X. Yang et al.

    Novel circular RNA expression profile of uveal melanoma revealed by microarray

    Chin J Cancer Res

    (2018)
  • Cited by (54)

    • An insight into the TAM system in Alzheimer's disease

      2023, International Immunopharmacology
    • Circ_0002945 functions as a competing endogenous RNA to promote Aβ<inf>25-35</inf>-induced endoplasmic reticulum stress and apoptosis in SK-N-SH cells and human primary neurons

      2022, Brain Research
      Citation Excerpt :

      Moreover, the circHDAC9/miR-138/sirtuin-1 ceRNA network exerts crucial activity in synaptic function and Aβ production during AD (Lu et al., 2019). Circ_0002945, produced by the back-splicing of exons of AXL receptor tyrosine kinase (AXL), is upregulated in the cerebrospinal fluid of AD patients, and it may be a potential biomarker for the risk prediction and detection of AD (Li et al., 2020). However, it remains poorly understood whether circ_0002945 can impact AD pathogenesis.

    • Circular RNA AXL increases neuron injury and inflammation through targeting microRNA-328 mediated BACE1 in Alzheimer's disease

      2022, Neuroscience Letters
      Citation Excerpt :

      The data showed that circ-AXL promoted neuron injury and inflammation in cellular AD models. The possible explanations might be that: (1) circ- AXL might serve as a competing endogenous RNA to target miR-328, consequently regulating BACE1 expression, which was involved in AD progression [15,16]; (2) our previous study discovered that circ-AXL might potentially target other microRNAs playing a crucial role in AD, such as miR-1233-5p, etc. [5,17,18]. The dysregulation of miRNA leads to neurodegenerative disorders, such as Parkinson’s disease, Huntington's disease, and AD [19–22].

    View all citing articles on Scopus
    View full text