Journal of Shandong University (Health Sciences) ›› 2026, Vol. 64 ›› Issue (9): 26-35.doi: 10.6040/j.issn.1671-7554.0.2025.1202

• Clinical Medicine • Previous Articles    

Causal effects of plasma and urinary metabolites on Alzheimers disease: a metabolome-wide Mendelian randomization study

PENG Qiang1,2, ZHANG Xueqin2, WEN Jun1,2, WANG Kai2, ZHANG Xiaojuan2, LIU Shiping3   

  1. 1. School of Clinical Medicine, North Sichuan Medical College, Nanchong 637100, Sichuan, China;
    2.Guangyuan Mental Health Centre(Affiliated Hospital of North Sichuan Medical College, Guangyuan Third Peoples Hospital), Guangyuan 628001, Sichuan, China;
    3. Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan, China
  • Published:2026-09-09

Abstract: Objective To identify metabolic biomarkers causally associated with Alzheimers disease(AD)using Mendelian randomization(MR)and metabolomics, explore related risk factors, and elucidate the mediating role of metabolites. Methods Two-sample MR was used to evaluate the causal associations of 690 plasma metabolites and 211 urinary metabolites with AD. Functional enrichment analysis of potential metabolic markers was performed using Met Origin, and druggability assessment was conducted via Drug Bank. MR analyses were further performed to identify modifiable risk factors for AD and their causal relationships with candidate metabolites, followed by two-step MR to assess mediating effects of metabolites. Results Thirteen plasma metabolites and seven urinary metabolites showed significant causal associations with AD(P<0.05). Functional enrichment analysis identified five significantly enriched metabolic pathways(P<0.05). Druggability assessment indicated two metabolites as potential therapeutic targets. Additionally, five modifiable risk factors for AD were identified(P<0.05), and mediation analysis confirmed the mediating roles of two metabolites in risk factor-induced AD. Conclusion Thirteen plasma metabolites and seven urinary metabolites were causally associated with AD. Among them, S-adenosylhomocysteine and lactose emerged as potential therapeutic targets, while epiandrosterone sulfate and 1-palmitoyl-2-oleoyl-GPI mediated the effects of depressive symptoms and Parkinsons disease on AD, respectively.

Key words: Alzheimers disease, Mendelian randomization, Metabolites, Causal association, Risk factors, Mediation

CLC Number: 

  • R749.1+6
[1] Gauthier, Webster C, Servaes S, et al. World Alzheimer Report 2022: life after diagnosis: navigating treatment, care and support[R]. London, England: Alzheimers Disease International, 2022 [2025-10-20]. https://www.alzint.org/resource/world-alzheimer-report-2022/
[2] Wilson R S, Segawa E, Boyle P A, et al. The natural history of cognitive decline in Alzheimers disease[J]. Psychol Aging, 2012, 27(4): 1008-1017.
[3] Marucci G, Buccioni M, Ben D D, et al. Efficacy of acetylcholinesterase inhibitors in Alzheimers disease[J]. Neuropharmacology, 2021, 190: 108352. DOI:10.1016/j.neuropharm.2020.108352
[4] Rani S, Dhar S B, Khajuria A, et al. Advanced overview of biomarkers and techniques for early diagnosis of Alzheimers disease[J]. Cell Mol Neurobiol, 2023, 43(6): 2491-2523.
[5] Yuan Y, Zhao G, Zhao Y. Dysregulation of energy metabolism in Alzheimers disease[J]. J Neurol, 2024, 272(1): 2. DOI:10.1007/s00415-024-12800-8
[6] Han R R, Liang J, Zhou B. Glucose metabolic dysfunction in neurodegenerative diseases: new mechanistic insights and the potential of hypoxia as a prospective therapy targeting metabolic reprogramming[J]. Int J Mol Sci, 2021, 22(11): 5887. DOI:10.3390/ijms22115887
[7] Butterfield D A, Halliwell B. Oxidative stress, dysfunctional glucose metabolism and Alzheimer disease[J]. Nat Rev Neurosci, 2019, 20(3): 148-160.
[8] Li H M, Qiu C S, Du L Y, et al. Causal association between circulating metabolites and dementia: a Mendelian randomization study[J]. Nutrients, 2024, 16(17): 2879. DOI:10.3390/nu16172879
[9] Cao D, Zhang Y N, Zhang S B, et al. Risk of Alzheimers disease and genetically predicted levels of 1,400 plasma metabolites: a Mendelian randomization study[J]. Sci Rep, 2024, 14: 26078. DOI:10.1038/s41598-024-77921-6
[10] Kurbatova N, Garg M, Whiley L, et al. Urinary metabolic phenotyping for Alzheimers disease[J]. Sci Rep, 2020, 10: 21745. DOI:10.1038/s41598-020-78031-9
[11] Wang Y Y, Sun Y, Wang Y, et al. Urine metabolomics phenotyping and urinary biomarker exploratory in mild cognitive impairment and Alzheimers disease[J]. Front Aging Neurosci, 2023, 15: 1273807. DOI:10.3389/fnagi.2023.1273807
[12] Bellenguez C, Küçükali F, Jansen I E, et al. New insights into the genetic etiology of Alzheimers disease and related dementias[J]. Nat Genet, 2022, 54(4): 412-436.
[13] Schwartzentruber J, Cooper S, Liu J Z, et al. Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimers disease risk genes[J]. Nat Genet, 2021, 53(3): 392-402.
[14] Chen Y H, Lu T Y, Pettersson-Kymmer U, et al. Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases[J]. Nat Genet, 2023, 55(1): 44-53.
[15] Schlosser P, Li Y, Sekula P, et al. Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans[J]. Nat Genet, 2020, 52(2): 167-176.
[16] Burgess S, Thompson S G. Avoiding bias from weak instruments in Mendelian randomization studies[J]. Int J Epidemiol, 2011, 40(3): 755-764.
[17] Bowden J, Smith G D, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression[J]. Int J Epidemiol, 2015, 44(2): 512-525.
[18] Sun J, Zhao J H, Zhou S Y, et al. Systematic investigation of genetically determined plasma and urinary metabolites to discover potential interventional targets for colorectal cancer[J]. JNCI J Natl Cancer Inst, 2024, 116(8): 1303-1312.
[19] Zhang X X, Tian Y, Wang Z T, et al. The epidemio-logy of Alzheimers disease modifiable risk factors and prevention[J]. J Prev Alzheimers Dis, 2021, 8(3): 313-321.
[20] Hersi M, Irvine B, Gupta P, et al. Risk factors associated with the onset and progression of Alzheimers disease: a systematic review of the evidence[J]. NeuroToxicology, 2017, 61: 143-187. DOI:10.1016/j.neuro.2017.03.006
[21] Liu Y L, Xiao X W, Yang Y, et al. The risk of Alzheimers disease and cognitive impairment characteristics in eight mental disorders: a UK Biobank observational study and Mendelian randomization analysis[J]. Alzheimers Dement, 2024, 20(7): 4841-4853.
[22] Xue F, Gao L Y, Chen T T, et al. Parkinsons disease rs117896735 variant Regulates INPP5F expression in brain tissues and increases risk of Alzheimers disease[J]. J Alzheimers Dis, 2022, 89(1): 67-77.
[23] Huang H, Fang C M, Niu H X, et al. Effects of donepezil treatment on plasma and urine metabolites in amyloid beta-induced Alzheimers disease rats[J]. J Chromatogr B, 2023, 1224: 123766. DOI:10.1016/j.jchromb.2023.123766
[24] Yang J Z, Wu S, Yang J, et al. Amyloid beta-correlated plasma metabolite dysregulation in Alzheimers disease: an untargeted metabolism exploration using high-resolution mass spectrometry toward future clinical diagnosis[J]. Front Aging Neurosci, 2023, 15: 1189659. DOI:10.3389/fnagi.2023.1189659
[25] Zhang S, Lachance B B, Mattson M P, et al. Glucose metabolic crosstalk and regulation in brain function and diseases[J]. Prog Neurobiol, 2021, 204: 102089. DOI:10.1016/j.pneurobio.2021.102089
[26] Minhas P S, Jones J R, Latif-Hernandez A, et al. Restoring hippocampal glucose metabolism rescues cognition across Alzheimers disease pathologies[J]. Science, 2024, 385(6711): eabm6131. DOI:10.1126/science.abm6131
[27] Castro M B, Ferreira B K, Cararo J H, et al. Evidence of oxidative stress in brain and liver of young rats submitted to experimental galactosemia[J]. Metab Brain Dis, 2016, 31(6): 1381-1390.
[28] Wachsmuth H R, Weninger S N, Duca F A. Role of the gut-brain axis in energy and glucose metabolism[J]. Exp Mol Med, 2022, 54(4): 377-392.
[29] López-Gambero A J, Martínez F, Salazar K, et al. Brain glucose-sensing mechanism and energy homeostasis[J]. Mol Neurobiol, 2019, 56(2): 769-796.
[30] Escribano BM, Muñoz-Jurado A, Luque E, et al. Lactose and casein cause changes on biomarkers of oxidative damage and dysbiosis in an experimental model of multiple sclerosis[J]. CNS Neurol Disord Drug Targets, 2022, 21(8): 680-692.
[31] Megur A, Baltriukien(·overe)D, Bukelskien(·overe)V, et al. The microbiota-gut-brain axis and Alzheimers disease: neuroinflammation is to blame?[J]. Nutrients, 2021, 13(1): 37. DOI:10.3390/nu13010037
[32] Vitku J, Hill M, Kolatorova L, et al. Steroid sulfation in neurodegenerative diseases[J]. Front Mol Biosci, 2022, 9: 839887. DOI:10.3389/fmolb.2022.839887
[33] Strac DS, Konjevod M, Perkovic MN, et al. Dehydroepiandrosterone(DHEA)and its sulphate(DHEAS)in Alzheimers disease[J]. Curr Alzheimer Res, 2020, 17(2): 141-157.
[34] Upadhyayula PS, Higgins DM, Mela A, et al. Dietary restriction of cysteine and methionine sensitizes gliomas to ferroptosis and induces alterations in energetic metabolism[J]. Nat Commun, 2023, 14: 1187. DOI:10.1038/s41467-023-36630-w
[35] Paul B D, Sbodio J I, Snyder S H. Cysteine metabolism in neuronal redox homeostasis[J]. Trends Pharmacol Sci, 2018, 39(5): 513-524.
[36] Prudova A, Bauman Z, Braun A, et al. S-adenosylmethionine stabilizes cystathionine β-synthase and modulates redox capacity[J]. Proc Natl Acad Sci U S A, 2006, 103(17): 6489-6494.
[37] Yang H B, Luo K, Peters B A, et al. Diet, gut micro-biota, and histidine metabolism toward imidazole propionate production in relation to type 2 diabetes[J]. Diabetes Care, 2025, 48(7): 1225-1232.
[38] Li D, Zhou L H, Cao Z, et al. Associations of environmental factors with neurodegeneration: an exposome-wide Mendelian randomization investigation[J]. Ageing Res Rev, 2024, 95: 102254. DOI:10.1016/j.arr.2024.102254
[39] Kusters C D J, Paul K C, Romero T, et al. Among men, androgens are associated with a decrease in Alzheimers disease risk[J]. Alzheimers Dement, 2023, 19(9): 3826-3834.
[40] Souza-Teodoro L H, Davies N M, Warren H R, et al. DHEA and response to antidepressant treatment: a Mendelian randomization analysis[J]. J Psychiatr Res, 2024, 173: 151-156.
[41] Wang R C, Hatano T, Hattori N, et al. Interplay of GBA1 with lysosomal dysfunction and inflammation in Parkinsons disease[J]. Neural Regen Res, 2025. DOI:10.4103/nrr.nrr-d-25-01082
[42] Qin B Q, Fu Y, Raulin A C, et al. Lipid metabolism in health and disease: mechanistic and therapeutic insights for Parkinsons disease[J]. Chin Med J, 2025, 138(12): 1411-1423.
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