This is a cross-sectional and longitudinal study to investigate the characteristic changes in Papez's circuit neural network activity and connectivity based on multimodal MRI, and through follow-up study of the interaction between the internal brain regions of Papez circuit and the function of the external neural network, a prediction model of the characteristic changes of Papez circuit neural network was constructed based on machine learning technology.
T2DM patients may have multidimensional cognitive impairment, which is related to the damage of key brain regions in Papez's circuit. The purpose of this study is to establish a prediction model for the occurrence, development, and severity of cognitive impairment by using machine learning of Papez circuit neural network in T2DM patients. This will allow for early intelligent assessment with high accuracy and efficiency, and assist in clinical personalized treatment and early intervention. The research center has 1 principal investigator, 4 sub-investigators, and 1 nurse. Participants will include 200 patients with type 2 diabetes recruited from outpatient and inpatient departments. Additionally, 200 healthy controls will be recruited from the community. Each subject will undergo clinical information collection, biochemical measurements including fasting blood glucose, C-peptide, HbA1c, blood lipid, postprandial blood glucose, and postprandial C-peptide, multimodal MRI scans, and cognitive assessments at baseline and each follow-up visit. The study duration is 6 years, with a follow-up every 36 months. At the end of the study, all assessments will be performed again for all recruited subjects.
Study Type
OBSERVATIONAL
Enrollment
400
No intervention：all participants did not receive any intervention measures throughout the study
Department of Endocrinology, Nanjing First Hospital, Nanjing Medical University
Nanjing, Jiangsu, China
RECRUITINGBaseline brain structural MRI scan
To calculate the volumes of whole brain and target brain regions
Time frame: Within 1 week after neuropsychological tests
Baseline brain functional MRI scan
To evaluate Papez loop cross-scale network variation
Time frame: Within 1 week after neuropsychological tests
Baseline brain diffusion tensor MRI scan
To trace and reconstruct the nerve fiber tracts between the Papez circuit related brain regions and between the circuit and the outer brain regions, and to construct a structural connection network according to the characteristics of white matter conduction pathways
Time frame: Within 1 week after neuropsychological tests
Baseline brain arterial spin labeling MRI scan
To calculate the blood perfusion in the whole brain and Papez circuit
Time frame: Within 1 week after neuropsychological tests
Baseline neuropsychological performance
Montreal Cognitive Assessment，MoCA：It includes 11 examination items in 8 cognitive domains with a total score of 30 points
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Mini-mental State Examination，MMSE：The highest score is 30 points, with scores between 27-30 indicating normal and scores below 27 indicating cognitive impairment
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Complex Figure Test, CFT: The total score is 36 points, including position score and shape score
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Verbalfluencytest, VFT: includes semantic fluency test, speech fluency test, and action fluency test
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Trail making testTMT：includes two parts, A and B
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Auditory Verbal Learning Test， VALT
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Digit span test,DST
Time frame: Day 1 of entry study
Baseline neuropsychological performance
Digit Symbol Substitution Test, DSST
Time frame: Day 1 of entry study
Baseline peripheral blood neuropathology biomarkers level
Fasting blood glucose（mmol/L）
Time frame: Blood samples will be collected on day 1 of the entry study
Baseline peripheral blood neuropathology biomarkers level
C-peptide（nmol/l）
Time frame: Blood samples will be collected on day 1 of the entry study
Baseline peripheral blood neuropathology biomarkers level
HbA1c（mmol/mol）
Time frame: Blood samples will be collected on day 1 of the entry study
Baseline peripheral blood neuropathology biomarkers level
blood lipid（mmol/L）
Time frame: Blood samples will be collected on day 1 of the entry study
Baseline peripheral blood neuropathology biomarkers level
postprandial blood glucose（mmol/L）
Time frame: Blood samples will be collected on day 1 of the entry study
Baseline peripheral blood neuropathology biomarkers level
postprandial C-peptide（nmol/l）
Time frame: Blood samples will be collected on day 1 of the entry study
Longitudinal changes of brain structural MRI scan
Compare the changes of the volumes of whole brain and target brain regions from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of brain functional MRI scan
Compare the changes of the Papez circuit cross-scale network variation from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of brain diffusion tensor MRI scan
Compare the changes of the Papez circuit structural network from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of brain arterial spin labeling MRI scan
Compare the changes of blood perfusion in the whole brain and Papez circuit from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Montreal Cognitive Assessment(MoCA) change from the baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Mini-mental State Examination (MMSE) change from the baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Complex Figure Test (CFT) change from the baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Verbalfluencytest (VFT) change from the baseline to each follow-up time points
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Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Trail making test (TMT) change from the baseline to each follow-up time points; includes two parts, A and B
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Auditory Verbal Learning Test (VALT) change from the baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Digit span test (DST) change from the baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of neuropsychological performance
Compare the Digit Symbol Substitution Test (DSST) change from the baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of peripheral blood neuropathology biomarkers leve
Compare the fasting blood glucose（mmol/L）changes from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of peripheral blood neuropathology biomarkers leve
Compare the C-peptide（nmol/l）changes from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of peripheral blood neuropathology biomarkers leve
Compare the HbA1c（mmol/mol）changes from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of peripheral blood neuropathology biomarkers leve
Compare the blood lipid（mmol/L）changes from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of peripheral blood neuropathology biomarkers leve
Compare the postprandial blood glucose（mmol/L）changes from baseline to each follow-up time points
Time frame: 36 months, 72 months
Longitudinal changes of peripheral blood neuropathology biomarkers leve
Compare the postprandial C-peptide（nmol/l）changes from baseline to each follow-up time points
Time frame: 36 months, 72 months
Machine learning of multimodal MRI data
Multimodal MRI data for machine learning, can be in different levels of calculation and analysis and research on the characteristics of neural network, found a pattern classification and predict unknown data effectively, find out the Papez loop associated with insulin resistance characteristics of neural network
Time frame: 72 months