Differential gene expression of blood-based ABCA9, CNOT8, SESN1, UCP3, MAP2K1 and DDIT4 in Alzheimer’s disease

Authors

  • Ainon Zahariah Samsudin Brain Degeneration & Therapeutic Group, Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.
  • Kalavathy Ramasamy Collaborative Drug Discovery Research (CDDR) Group, Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.
  • Siong Meng Lim Collaborative Drug Discovery Research (CDDR) Group, Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.
  • Ai Vyrn Chin Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia.
  • Maw Pin Tan Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia.
  • Shahrul Bahyah Kamaruzzaman Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia.
  • Baharudin Ibrahim Faculty of Pharmacy, University of Malaya, 50603 Kuala Lumpur, Malaysia
  • Abu Bakar Abdul Majeed Brain Degeneration & Therapeutic Group, Faculty of Pharmacy, Universiti Teknologi MARA (UiTM), 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia.

DOI:

https://doi.org/10.31117/neuroscirn.v6i4.262

Keywords:

Alzheimer’s disease, ATP-binding cassette, biomarkers, blood, transcriptomics

Abstract

This study uncovered differential gene expression in blood to distinguish subjects with probable Alzheimer’s disease (AD) from normal elderly participants (non-demented controls, NDC). The participants were recruited via training (Phase 1) and validation cohorts (Phase 2). The changes of gene expression in blood samples from the training cohort (92 AD vs 92 NDC) were assessed using the microarray technology. The Partial Least Square Discrimination Analysis (PLSDA) was then used to develop a disease classifier algorithm (accuracy = 88.3%). Six differentially expressed genes  were validated through RT-qPCR using blood samples from the validation cohort [(25 AD, 25 NDC, 12 mild cognitive impairment (MCI) and 12 vascular dementia (VaD) subjects] . The PLSDA model indicated a good separation between AD and NDC [area under the receiver operating characteristic curve (ROC AUC) = 0.88]. ABCA9, CNOT8, SESN1, UCP3, MAP2K1 and DDIT4 were found to be differentially expressed between the two groups. Validation of the panel of six genes gave an overall accuracy of 82.0% (AUC=0.86). The ABCA9 mRNA level, which was significantly (p < 0.05) lower in the AD group, correctly classified 90.9% of all subjects (AUC=0.94). This group of  genes may be responsible for dysregulation of pathways related to inflammation, mitochondrial dysfunction, oxidative injury, DNA damage, apoptosis and lipid metabolism. The disease classifier algorithm discriminated probable AD from MCI and VaD at specificity of 83.3% and 75.0%, respectively. These findings warrant further validation of potential blood-based biomarkers in larger samples of clinical AD.

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2023-12-31

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Samsudin, A. Z., Ramasamy, K., Lim, S. M., Chin, A. V., Tan, M. P., Kamaruzzaman, S. B., Ibrahim, B. and Abdul Majeed, A. B. (2023) “Differential gene expression of blood-based ABCA9, CNOT8, SESN1, UCP3, MAP2K1 and DDIT4 in Alzheimer’s disease”, Neuroscience Research Notes, 6(4), pp. 262.1–262.14. doi: 10.31117/neuroscirn.v6i4.262.

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Vol. 6 No. 4 (2023): Regular Issue

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Copyright (c) 2023 Ainon Zahariah Samsudin, Kalavathy Ramasamy, Siong Meng Lim, Ai Vyrn Chin, Maw Pin Tan, Shahrul Bahyah Kamaruzzaman, Baharudin Ibrahim, Abu Bakar Abdul Majeed

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