Establish Diagnostic and Prognostic Models for Preclinical AD Patients Based on Multimodal MRI, Behavioral, Genetic, and Plasma Biomarkers

Nanjing University

Status: Enrolling

Conditions: Mild Cognitive Impairment; Alzheimer Disease, Late Onset; Subjective Cognitive Decline

Treatments: Other: Multimodal magnetic resonance imaging scanning, behavioral, genetic and plasma biomarker testing

Study type: Observational

Funder types: Other

Identifiers

NCT06561906

2023-341-01

Details and patient eligibility

About

To establish the diagnostic and prognostic models that could help the preclinical identification of subjects at higher risk of clinical progression to mild cognitive impairment and dementia based on combined features of baseline demographic, cognitive, behavioral, multimodal MRI, genetic, and plasma data.

Full description

Alzheimer's disease (AD) is a global concern. Due to the lack of effective therapeutic methods targeting late-stage AD patients, it is critical to investigate brain alterations in the preclinical stage to pave the way for early diagnosis and intervention. Structural and functional magnetic resonance imaging (MRI) has been proven to be an effective and non-invasive approach to explore the neural mechanisms underlying neurological disorders. Genetic factors such as apolipoprotein E and plasma biomarkers play important roles in AD development and progression. However, the interaction effects of risk genes and different pathologic pathways implicated in the pathogenesis of AD remain unclear. Furthermore, the diagnostic and prognostic models that could predict future cognitive decline or clinical progression based on objective features derived from baseline demographic, cognitive, behavioral, multimodal MRI, genetic, and plasma data need to be further explored.

We aim to investigate the neural basis underlying early cognitive deficits using structural and functional MRI data combined with novel analytical methods such as dynamic functional connectivity, surface-based morphometry, graph theory, multilayer network, functional-structural coupling, hidden Markov model, and connectome gradient mapping. Secondly, to explore the interaction effects of risk genes, which may help a better illustration of different biological pathways implicated in the pathogenesis of Alzheimer's disease. Thirdly, to investigate the divergent and dynamic abnormalities of multimodal imaging markers across different stages of Alzheimer's disease and their associations with plasma biomarkers, which may enhance our understanding of the neuropathological mechanisms. Fourthly, to provide scientific evidence on the potential targets for early intervention of neurodegenerative diseases. Lastly, to establish the diagnostic and prognostic models that could help the preclinical identification of subjects at higher risk of clinical progression to mild cognitive impairment and dementia based on combined features of baseline multimodal biomarkers. These studies may help a better understanding of the neural and biological basis underlying AD and pave the way for early diagnosis and intervention.

Enrollment: 1,000 estimated patients

Sex: All

Ages: 50 to 79 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• The inclusion criteria were 50-79 years old and having 8 or more years of education.

Exclusion criteria

• Participants with a history of stroke, other neurological disorders that could lead to cognitive impairment (Parkinson's disease, encephalitis, epilepsy, brain tumors, etc.), severe anxiety or depression, and contraindications for magnetic resonance imaging (MRI) were not enrolled.

Trial design

1,000 participants in 4 patient groups

Normal control

Description:

Subjects without memory complaints and associated worries and do not meet the diagnostic criteria for mild cognitive impairment (MCI) are recruited as normal control (NC).

Treatment:

Other: Multimodal magnetic resonance imaging scanning, behavioral, genetic and plasma biomarker testing

Subjective cognitive decline

Description:

Subjects who complain of memory decline within the last 5 years and express worries associated with memory decline and do not meet the diagnostic criteria for MCI are defined as subjective cognitive decline (SCD).

Treatment:

Other: Multimodal magnetic resonance imaging scanning, behavioral, genetic and plasma biomarker testing

Mild cognitive impairment

Description:

Participants are considered MCI patients with scores \>1 standard deviation (SD) below the normative means in both subtests within one cognitive domain or \>1 SD below the normative means in three single tests in three different domains.

Treatment:

Other: Multimodal magnetic resonance imaging scanning, behavioral, genetic and plasma biomarker testing

Alzheimer's disease dementia

Description:

Patients are diagnosed as AD dementia by an experienced neurologist based on MMSE and CSF/PET biomarker evidence.

Treatment:

Other: Multimodal magnetic resonance imaging scanning, behavioral, genetic and plasma biomarker testing