Non-invasive biomarkers for mild cognitive impairment and Alzheimer's disease

被引:7
作者
Botello-Marabotto, Marina [1 ,2 ,4 ]
Martinez-Bisbal, M. Carmen [1 ,2 ,3 ,4 ,5 ,10 ]
Calero, Miguel [6 ,7 ,8 ]
Bernardos, Andrea [3 ,4 ,8 ]
Pastor, Ana B. [6 ]
Medina, Miguel [5 ,6 ]
Martinez-Manez, Ramon [1 ,2 ,4 ,5 ,9 ]
机构
[1] Univ Valencia, Univ Politecn Valencia, Inst Interuniv Invest Reconocimiento Mol & Desarro, Valencia, Spain
[2] Univ Politecn Valencia, Unidad Mixta Invest Nanomed & Sensores, Inst Invest Sanitaria La Fe IISLAFE, Valencia, Spain
[3] Univ Valencia, Dept Quim Fis, Valencia, Spain
[4] CIBER Bioingn Biomat & Nanomed CIBER BBN, Bellaterra, Spain
[5] Univ Politecn Valencia, Ctr Invest Principe Felipen, Unidad Mixta UPV CIPF Invest Mecanismos Enfermeda, Valencia, Spain
[6] Ctr Invest Biomed Red Enfermedades Neurodegenerat, Madrid, Spain
[7] CIEN Fdn, Queen Sofia Fdn Alzheimer Res Ctr, Madrid, Spain
[8] Inst Salud Carlos III, Madrid, Spain
[9] Univ Politecn Valencia, Dept Quim, Valencia, Spain
[10] Fac Quim, Dept Quim Fis, C Doctor Moliner 50, Valencia 46100, Spain
关键词
Metabolomics; Alzheimer's disease; Mild cognitive impairment; NMR spectroscopy; Biomarkers; METABOLOMICS; SPECTROSCOPY; DIAGNOSIS; GLUTAMINE; URINE; BRAIN; BLOOD;
D O I
10.1016/j.nbd.2023.106312
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Alzheimer's disease is the most common type of dementia in the elderly. It is a progressive degenerative disorder that may begin to develop up to 15 years before clinical symptoms appear. The identification of early biomarkers is crucial to enable a prompt diagnosis and to start effective interventions. In this work, we conducted a metabolomic study using proton Nuclear Magnetic Resonance (1H NMR) spectroscopy in serum samples from patients with neuropathologically confirmed Alzheimer's disease (AD, n = 51), mild cognitive impairment (MCI, n = 27), and cognitively healthy controls (HC, n = 50) to search for metabolites that could be used as biomarkers. Patients and controls underwent yearly clinical follow-ups for up to six years. MCI group included samples from three subgroups of subjects with different disease progression rates. The first subgroup included subjects that remained clinically stable at the MCI stage during the period of study (stable MCI, S-MCI, n = 9). The second subgroup accounted for subjects which were diagnosed with MCI at the moment of blood extraction, but progressed to clinical dementia in subsequent years (MCI-to-dementia, MCI-D, n = 14). The last subgroup was composed of subjects that had been diagnosed as dementia for the first time at the moment of sample collection (incipient dementia, Incp-D, n = 4). Partial Least Square Discriminant Analysis (PLS-DA) models were developed. Three models were obtained, one to discriminate between AD and HC samples with high sensitivity (93.75%) and specificity (94.75%), another model to discriminate between AD and MCI samples (100% sensitivity and 82.35% specificity), and a last model to discriminate HC and MCI with lower sensitivity and specificity (67% and 50%). Differences within the MCI group were further studied in an attempt to determine those MCI subjects that could develop AD-type dementia in the future. The relative concentration of metabolites, and metabolic pathways were studied. Alterations in the pathways of alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and beta-alanine metabolism, were found when HC and MCI- D patients were compared. In contrast, no pathway was found disturbed in the comparison of S-MCI with HC groups. These results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and set a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.
引用
收藏
页数:13
相关论文
共 50 条
[11]   NMR metabolomics of human blood and urine in disease research [J].
Duarte, Iola F. ;
Diaz, Silvia O. ;
Gil, Ana M. .
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 2014, 93 :17-26
[12]   Serum Metabolite Markers of Dementia Through Quantitative NMR Analysis: The Importance of Threonine-Linked Metabolic Pathways [J].
Figueira, Joao ;
Adolfsson, Rolf ;
Adolfsson, Annelie Nordin ;
Nyberg, Lars ;
Ohman, Anders .
JOURNAL OF ALZHEIMERS DISEASE, 2019, 69 (03) :763-774
[13]   Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS) [J].
Fuss, Taylor L. ;
Cheng, Leo L. .
METABOLITES, 2016, 6 (01)
[14]   Mild cognitive impairment [J].
Gauthier, S ;
Reisberg, B ;
Zaudig, M ;
Petersen, RC ;
Ritchie, K ;
Broich, K ;
Belleville, S ;
Brodaty, H ;
Bennett, D ;
Chertkow, H ;
Cummings, JL ;
de Leon, M ;
Feldman, H ;
Ganguli, M ;
Hampel, H ;
Scheltens, P ;
Tierney, MC ;
Whitehouse, P ;
Winblad, B .
LANCET, 2006, 367 (9518) :1262-1270
[15]  
Gauthier S., 2021, Alzheimer's Disease International
[16]  
Gholamy Afshin., 2018, WHY 7030 8020 RELATI
[17]  
Govindaraju V, 2000, NMR BIOMED, V13, P129, DOI 10.1002/1099-1492(200005)13:3<129::AID-NBM619>3.0.CO
[18]  
2-V
[19]   The severe mini-mental state examination: A new neuropsychologic instrument for the bedside assessment of severely impaired patients with Alzheimer disease [J].
Harrell, LE ;
Marson, D ;
Chatterjee, A ;
Parrish, JA .
ALZHEIMER DISEASE & ASSOCIATED DISORDERS, 2000, 14 (03) :168-175
[20]   Aging, Alzheimer's Disease and Dysfunctional Glycolysis; Similar Effects of Too Much and Too Little [J].
Hipkiss, Alan R. .
AGING AND DISEASE, 2019, 10 (06) :1328-1331