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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

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Front. Med.    2024, Vol. 18 Issue (3) : 446-464    https://doi.org/10.1007/s11684-023-1047-1
Progress on early diagnosing Alzheimer’s disease
Yixin Chen1, Murad Al-Nusaif1, Song Li1, Xiang Tan1, Huijia Yang1, Huaibin Cai2, Weidong Le1,3()
1. Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital of Dalian Medical University, Dalian 116021, China
2. Transgenic Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
3. Institute of Neurology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China; Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, China
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Abstract

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.

Keywords Alzheimer’s disease      early diagnosis      non-cognitive symptoms      biomarkers     
Corresponding Author(s): Weidong Le   
Just Accepted Date: 18 March 2024   Online First Date: 20 May 2024    Issue Date: 17 June 2024
 Cite this article:   
Yixin Chen,Murad Al-Nusaif,Song Li, et al. Progress on early diagnosing Alzheimer’s disease[J]. Front. Med., 2024, 18(3): 446-464.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-023-1047-1
https://academic.hep.com.cn/fmd/EN/Y2024/V18/I3/446
Fig.1  Non-cognitive manifestation and clinical biomarkers in the preclinical stage of AD are addressed in this review. ↑, increase. ↓, decrease. *The symptom is solely based on animal studies, lacking clinical evidence. Abbreviations: BPSD, behavioral and psychological symptoms of dementia; CRD, circadian rhythm disruptions; NREM, non-rapid eye movement; EEG, electroencephalogram; ERG, electroretinography; Aβ, amyloid-beta; PET, positron emission tomography; T-tau, total-tau protein; P-tau, phosphorylated-tau protein; NfL, neurofilament light chain; GFAP, glial fibrillary acidic protein; HSV, herpes simplex virus; P. gingivalis, Porphyromonas gingivalis;AD, Alzheimer’s disease. (The graphic was created with BioRender.com.)
Fig.2  Clinical tactic for early diagnosis, prevention, and treatment in the preclinical stage of AD. (A) Main pathological changes in preclinical AD. (B) Non-cognitive manifestations in the preclinical stage of AD. (C) Main biomarkers in preclinical AD. Abbreviations: AD, Alzheimer’s disease; BPSD, behavioral and psychological symptoms of dementia; Aβ, amyloid-beta; T-tau, total-tau protein; P-tau, phosphorylated-tau protein; miRNA, microRNA. (The graphic was created with BioRender.com.)
Fig.3  Historical review of AD diagnosis. Abbreviations: NINCDS-ADRDA, National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer’s Disease and Related Disorders Association; AD, Alzheimer’s disease; PET, positron emission tomography; CSF, cerebrospinal fluid; IWG, International Working Group; NIA-AA, National Institute on Aging and the Alzheimer’s Association; A, amyloid; T, pathologic tau; N, neurodegeneration; Aβ, amyloid-beta; GFAP, glial fibrillary acidic protein; NfL, neurofilament light chain. (The graphic was created with BioRender.com.)
Targeted biomarkersMechanismChanges in the early stage of AD
PET imaging
18F-AV-45These ligands exhibit high accuracy for brain amyloidosis [59]Brain amyloid deposits before symptomatic phase [59]
18F-GE067
18F-BAY94-9172
18F-D15-AV-45
18F-FIBT
18F-AZD4694
11C-Kln83α7nAChRThese specific probes interact directly with the α7nAChR in the living human brain [60]Astrocytic α7nAChR expression is linked to early Aβ pathology [61]
18F-ASEM
18F-MK-6240P-tau18F-MK-6240 has a higher affinity to tau tangles [62]Tau deposits in the transentorhinal cortex in the cognitively unimpaired elderly [62]
18F-flortaucipirRadionuclide metabolismThe brain region of tau load is related to cognitive function [63]
Other novel imaging techniques
NBThe probe detects the hydrophobic structure of the C-terminus of Aβ [64]Brain amyloid deposits before symptomatic phase [59]
MRSMetabolite levelChemical shift phenomenonMyo-inositol level increased in the asymptomatic stage of AD [65]
Retinal detection
OCTRetinal thicknessTomographyA reduction in the total retinal thickness and macular volume [55]
OCT-ARetinal vascular anatomy and functionAngiographyA significant foveal avascular zone and thinner mean inner foveal thickness [56]
ERGNAReflect the elevated retinal neuron activity [58]An increase in ERG amplitudes [58]
Tab.1  Novel imaging techniques for early diagnosis of AD
CategoryNon-cognitive symptomSample sizeAge range (year)Gender distributionBaseline cognitionHR95% CIFollow-up (year)References
BPSDDepression158775–83.450% femaleCN1.63a1.23–2.165[36]
Irritability158775–83.450% femaleCN1.84a1.31–2.585[36]
Anxiety158775–83.450% femaleCN1.87a1.28–2.735[36]
Agitation158775–83.450% femaleCN3.06a1.89–4.935[36]
Apathy158775–83.450% femaleCN2.26a1.49–3.415[36]
CRDSleep-onset latency132266.1±7.653% femaleCN1.531.14–2.0511.2[41]
Short sleep duration795950.6±2.633.1% femaleCN1.371.10–1.7225.7±5.1[43]
Wake after sleep onset132266.1±7.653% femaleCN1.421.07–1.9011.2[41]
Sensory impairmentOlfactory disorder143079.5±5.350.6% femaleCN2.18b1.36–3.513.5[53]
Retina thickness3062–9253% femaleCNNA, AUC=0.80070.66–0.943[56]
Hearing loss82 03962–6752.1% femaleCN1.911.55–2.3611[66]
Dual sensory deficits292774.6±4.859.2% femaleCN3.672.04–6.608[68]
Physical changesGait speed28770–8557% femaleCNNANA15[74]
Gait speed and activity fragmentation52073±851% femaleCN1.191.07–1.327.3±2.7[73]
Fractal regulation109781±7.476.9% femaleCN1.281.07–1.5211[75]
Cardiovascular dysfunctionHypertension24755–8375% femaleCNNANA4[79]
Tab.2  Longitudinal study data of non-cognitive symptoms
CategoryBiomarkersSample sizeAge range (year)Gender distributionBaseline cognitionHR95% CIFollow-up (year)References
Blood-based biomarkersAβ426071.6±9.856.7% femaleCNNA, AUC=0.806NA1.07±0.2[90]
P-tau T181132773.5±6.462% femaleCNNANA16[92]
P-tau T21717173±5.460.5% femaleCNNA, R2=0.41NA6[94]
GFAP16420–8622%–38% femaleCNNANA6.1±7.5[96]
NfL16420–8622%–38% femaleCNNANA6.1±7.5[96]
ExosomeMicroRNA20362.7–63.851% femaleCNNA, AUC=0.85–0.88NA5–7[108]
Endocrine disordersInsulin resistance447 91540–7354.4% femaleCN2.382.07–2.7311[116]
Cortisol9155–9049.45% femaleCN1.420.56–3.607[119]
Lowest thyrotropin52097159% femaleCN2.391.47–3.8712.7[121]
Highest thyrotropin52097159% femaleCN2.151.31–3.5212.7[121]
Testosterone158 58556–65100% maleCN1.431.13–1.817[122]
Lower SHBG158 58556–65100% maleCN0.530.34–0.847[122]
Tab.3  Longitudinal study data of biomarkers
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