Alzheimer's disease (AD) is a neurodegenerative disorder linked to mitochondrial energy metabolism dysfunction. This study investigated differentially expressed genes (DEGs) related to this process.
Objective
We aimed to identify key mitochondrial energy metabolism-related DEGs in the blood of patients with AD, construct their regulatory networks, evaluate their diagnostic potential, and explore their link with the immune microenvironment.
Methods
We analyzed AD datasets from gene expression datasets (GEO) and mitochondrial genes from GeneCards using R to identify DEGs. Hub genes were screened via protein–protein interaction (PPI) network analysis. Functional enrichment analysis, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), and regulatory network construction (mRNA-miRNA, mRNA-TF) were performed. Immune infiltration and receiver operating characteristic (ROC) analyses assessed immunological associations and diagnostic value.
Results
Fifteen mitochondrial energy metabolism-related DEGs were identified. PPI analysis revealed nine hub genes. Regulatory networks were successfully constructed. ROC analysis confirmed the strong diagnostic potential of these hubs, which also showed significant correlations with eleven immune cell types
Conclusions
We developed an AD diagnostic framework based on mitochondrial metabolism DEGs. These findings reveal mitochondrial–immune interactions in AD and provide novel candidate biomarkers for early diagnosis.
GaoYLiuX. Secular trends in the incidence of and mortality due to Alzheimer's disease and other forms of dementia in China from 1990 to 2019: an age-period-cohort study and joinpoint analysis. Front Aging Neurosci2021; 13: 709156.
2.
HanSZhangMJeongYY, et al.The role of mitophagy in the regulation of mitochondrial energetic status in neurons. Autophagy2021; 17: 4182–4201.
3.
MisraniATabassumSYangL. Mitochondrial dysfunction and oxidative stress in Alzheimer's disease. Front Aging Neurosci2021; 13: 617588.
4.
WangYGeYHuaS, et al.Aloe-emodin improves mitophagy in Alzheimer's disease via activating the AMPK/PGC-1α/SIRT3 signaling pathway. CNS Neurosci Ther2025; 31: e70346.
5.
LeeHJJungYHChoiGE, et al.Urolithin A suppresses high glucose-induced neuronal amyloidogenesis by modulating TGM2-dependent ER-mitochondria contacts and calcium homeostasis. Cell Death Differ2021; 28: 184–202.
6.
SunXZhangHYaoD, et al.Integrated bioinformatics analysis identifies hub genes associated with viral infection and Alzheimer's disease. J Alzheimers Dis2022; 85: 1053–1061.
7.
ZhangJGaoSLiuW. Bioinformatics-based analysis of circadian rhythm regulation mechanisms in Alzheimer's disease. J Alzheimers Dis2023; 94: 1209–1224.
8.
WangFXuJXuSJ, et al.Analysis and identification genetic effect of SARS-CoV-2 infections to Alzheimer's disease patients by integrated bioinformatics. J Alzheimers Dis2022; 85: 729–744.
9.
TakedaKNakamuraA. Regulation of immune and neural function via leukocyte Ig-like receptors. J Biochem2017; 162: 73–80.
10.
LeandroGSEvangelistaAFLoboRR, et al.Changes in expression profiles revealed by transcriptomic analysis in peripheral blood mononuclear cells of Alzheimer's disease patients. J Alzheimers Dis2018; 66: 1483–1495.
11.
XuHJiaJ. Single-cell RNA sequencing of peripheral blood reveals immune cell signatures in Alzheimer's disease. Front Immunol2021; 12: 645666.
12.
Moreno-VillanuevaMJimenez-ChavezLEKriegerS, et al.Transcriptomics analysis reveals potential mechanisms underlying mitochondrial dysfunction and T cell exhaustion in astronauts’ blood cells in space. Front Immunol2024; 15: 1512578.
13.
SoodSGallagherIJLunnonK, et al.A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status. Genome Biol2015; 16: 185.
14.
DavisSMeltzerPS. GEOquery: a bridge between the gene expression omnibus (GEO) and BioConductor. Bioinformatics2007; 23: 1846–1847.
15.
YeZZhangHKongF, et al.Comprehensive analysis of alteration landscape and its clinical significance of mitochondrial energy metabolism pathway-related genes in lung cancers. Oxid Med Cell Longev2021; 2021: 9259297.
16.
LeekJTJohnsonWEParkerHS, et al.The SVA package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics2012; 28: 882–883.
17.
RitchieMEPhipsonBWuD, et al.Limma powers differential expression analyses for RNA-Sequencing and microarray studies. Nucleic Acids Res2015; 43: e47–e47.
18.
ZhangHMeltzerPDavisS. RCircos: an R package for Circos 2D track plots. BMC Bioinformatics2013; 14: 244.
19.
XuJQinSYiY, et al.Delving into the heterogeneity of different breast cancer subtypes and the prognostic models utilizing scRNA-Seq and Bulk RNA-Seq. Int J Mol Sci2022; 23: 9936.
20.
MiHMuruganujanAEbertD, et al.PANTHER Version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res2019; 47: D419–D426.
21.
KanehisaM. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res2000; 28: 27–30.
22.
YuGWangLGHanY, et al.Clusterprofiler: an R package for comparing biological themes among gene clusters. OMICS2012; 16: 284–287.
23.
SubramanianATamayoPMoothaVK, et al.Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A2005; 102: 15545–15550.
24.
SzklarczykDGableALLyonD, et al.STRING V11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res2019; 47: D607–D613.
25.
ChinCHChenSHWuHH, et al.Cytohubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol2014; 8: S11.
26.
ShannonPMarkielAOzierO, et al.Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res2003; 13: 2498–2504.
27.
YangXLiYLvR, et al.Study on the multitarget mechanism and key active ingredients of herba siegesbeckiae and volatile oil against rheumatoid arthritis based on network pharmacology. Evid Based Complement Alternat Med2019; 2019: 8957245.
28.
VlachosISParaskevopoulouMDKaragkouniD, et al.DIANA-TarBase v7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions. Nucleic Acids Res2015; 43: D153–D159.
29.
ZhangQLiuWZhangHM, et al.hTFtarget: a comprehensive database for regulations of human transcription factors and their targets. Genom Proteomics Bioinform2020; 18: 120–128.
30.
ZhouKRLiuSSunWJ, et al.ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data. Nucleic Acids Res2017; 45: D43–D50.
SongZWangKWHagarHC, et al.Hyperphosphorylated tau inflicts intracellular stress responses that are mitigated by apomorphine. Mol Neurobiol2024; 61: 2653–2671.
33.
GongBJiWChenX, et al.Recent advancements in strategies for abnormal protein clearance in Alzheimer's disease. Mini Rev Med Chem2022; 22: 2260–2270.
34.
Guzman-MartinezLMaccioniRBFaríasGA, et al.Biomarkers for Alzheimer's disease. Curr Alzheimer Res2019; 16: 518–528.
35.
KallioELÖhmanHKautiainenH, et al.Cognitive training interventions for patients with Alzheimer's disease: a systematic review. J Alzheimers Dis2017; 56: 1349–1372.
36.
GalberCCarissimiSBaraccaA, et al.The ATP synthase deficiency in human diseases. Life (Basel)2021; 11: 325.
37.
KadenbachB. Regulation of mitochondrial respiration and ATP synthesis via cytochrome c oxidase. Rend Lincei Sci Fis Nat2018; 29: 421–435.
38.
LiuYSunYGuoY, et al.An overview: the diversified role of mitochondria in cancer metabolism. Int J Biol Sci2023; 19: 897–915.
39.
KimHKNohYHNiliusB, et al.Current and upcoming mitochondrial targets for cancer therapy. Semin Cancer Biol2017; 47: 154–167.
40.
WangHHanXGaoS. Identification of potential biomarkers for pathogenesis of Alzheimer's disease. Hereditas2021; 158: 23.
41.
TianBXSunWWangSH, et al.Differential expression and clinical significance of COX6C in human diseases. Am J Transl Res2021; 13: 1–10.
42.
KongPLeiPZhangS, et al.Integrated microarray analysis provided a new insight of the pathogenesis of Parkinson's disease. Neurosci Lett2018; 662: 51–58.
43.
HuangDChenLJiQ, et al.Lead aggravates Alzheimer's disease pathology via mitochondrial copper accumulation regulated by COX17. Redox Biol2024; 69: 102990.
44.
MannersHNRoySKalitaJK. Intrinsic-overlapping co-expression module detection with application to Alzheimer's disease. Comput Biol Chem2018; 77: 373–389.
45.
ZhuMWangL. Whole blood mRNA expression pattern differentiates AD patients and healthy controls through bioinformatics analysis. J Biol Life Sci2019; 10: 46.
46.
ShilSKKagawaYUmaruBA, et al.Ndufs4 ablation decreases synaptophysin expression in hippocampus. Sci Rep2021; 11: 10969.
47.
Armand-UgonMAnsoleagaBBerjaouiS, et al.Reduced mitochondrial activity is early and steady in the entorhinal cortex but it is mainly unmodified in the frontal cortex in Alzheimer's disease. Curr Alzheimer Res2017; 14: 1327–1334.
48.
ChangWSWangYHZhuXT, et al.Genome-wide profiling of miRNA and mRNA expression in Alzheimer's disease. Med Sci Monit2017; 23: 2721–2731.
49.
JohriA. Disentangling mitochondria in Alzheimer's disease. Int J Mol Sci2021; 22: 11520.
50.
IllesPUlrichHChenJF, et al.Purinergic receptors in cognitive disturbances. Neurobiol Dis2023; 185: 106229.
51.
ZhangCRissmanRAFengJ. Characterization of ATP alternations in an Alzheimer's disease transgenic mouse model. J Alzheimers Dis2015; 44: 375–378.
ZhangPFWangZTLiuY, et al.Peripheral immune cells and cerebrospinal fluid biomarkers of Alzheimer's disease pathology in cognitively intact older adults: the CABLE study. J Alzheimers Dis2022; 87: 721–730.
54.
MonsonegoANemirovskyAHarpazI. CD4T Cells in immunity and immunotherapy of Alzheimer's disease. Immunology2013; 139: 438–446.
55.
ZhuangXZhangGBaoM, et al.Development of a novel immune infiltration-related diagnostic model for Alzheimer's disease using bioinformatic strategies. Front Immunol2023; 14: 1147501.
56.
ThomeADFaridarABeersDR, et al.Functional alterations of myeloid cells during the course of Alzheimer's disease. Mol Neurodegener2018; 13: 61.
57.
ZhangIWCurtoALópez-VicarioC, et al.Mitochondrial dysfunction governs immunometabolism in leukocytes of patients with acute-on-chronic liver failure. J Hepatol2022; 76: 93–106.
58.
LiuWLiHGaoY, et al.Mitochondrial dysfunction of peripheral blood mononuclear cells is associated with lung carcinogenesis. Int Immunopharmacol2024; 133: 111958.
59.
XieJGorléNVandendriesscheC, et al.Low-grade peripheral inflammation affects brain pathology in the AppNL-G-Fmouse model of Alzheimer's disease. Acta Neuropathol Commun2021; 9: 163.
60.
KrishnanDMenonRNMathuranathPS, et al.A novel role for SHARPIN in amyloid-β phagocytosis and inflammation by peripheral blood-derived macrophages in Alzheimer's disease. Neurobiol Aging2020; 93: 131–141.
61.
GoldeckDWitkowskiJMFülopT, et al.Peripheral immune signatures in Alzheimer disease. Curr Alzheimer Res2016; 13: 739–749.
62.
SunWHuY. eQTL mapping using RNA-Seq data. Stat Biosci2013; 5: 198–219.
63.
ParkJWTokheimCShenS, et al.Identifying differential alternative splicing events from RNA sequencing data using RNASeq-MATS. Methods Mol Biol2013; 1038: 171–179.
64.
DaoPNumanagićILinYY, et al.ORMAN: optimal resolution of ambiguous RNA-Seq multimappings in the presence of novel isoforms. Bioinformatics2014; 30: 644–651.
65.
KnightJShamP. Design and analysis of association studies using pooled DNA from large twin samples. Behav Genet2006; 36: 665–677.
66.
ZernantJKülmMDharmarajS, et al.Genotyping microarray (disease chip) for leber congenital amaurosis: detection of modifier alleles. Invest Ophthalmol Vis Sci2005; 46: 3052–3059.
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