Cognitive Impairment, Insulin Resistance, Type 2 Diabetes
Conditions
Keywords
Type 2 Diabetes, Insulin Resistance, Papez circuit, Multimodal magnetic resonance imaging, Machine learning
Brief summary
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.
Detailed description
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.
Interventions
OTHERNo Intervention: Observational Cohort
No intervention：all participants did not receive any intervention measures throughout the study
Sponsors
Nanjing First Hospital, Nanjing Medical University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
45 Years to 70 Years
Healthy volunteers
Yes
Inclusion criteria
1. T2DM patients met the diagnostic criteria for diabetes (WHO, 1999) with a duration of 3-20 years; The control group met the criteria of fasting blood glucose \< 6.1mmol/l and glycosylated hemoglobin \< 5.7%; 2. right-handed, aged 45-70 years, with ≥8 years of education; 3. no contraindications to MRI scanning such as electronic and metal device implantation; 4. The visual acuity or corrected visual acuity and binaural hearing can meet the needs of the evaluation, and can cooperate to complete the examination. 5. without a history of substance abuse or dependence, evaluation is not used during the period of calm sleeping pills and antidepressants, not long-term use of drugs to improve cognitive.
Exclusion criteria
1. patients with acute metabolic complications or a history of severe hypoglycemia; 2. severe heart, liver, lung, kidney and hematopoietic system diseases; Hyperthyroidism or hypothyroidism; Stroke, alzheimer's disease, epilepsy, Parkinson's disease and other neurological history; A history of mental illness such as depression, mania, or alcohol dependence; History of loss of consciousness due to neurological diseases or traumatic brain injury; 3. one month before the laboratory examination, with a record and surgical trauma infection;
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Baseline brain structural MRI scan | Within 1 week after neuropsychological tests | To calculate the volumes of whole brain and target brain regions |
| Baseline brain functional MRI scan | Within 1 week after neuropsychological tests | To evaluate Papez loop cross-scale network variation |
| Baseline brain diffusion tensor MRI scan | Within 1 week after neuropsychological tests | 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 |
| Baseline brain arterial spin labeling MRI scan | Within 1 week after neuropsychological tests | To calculate the blood perfusion in the whole brain and Papez circuit |
| Baseline neuropsychological performance | Day 1 of entry study | Montreal Cognitive Assessment，MoCA：It includes 11 examination items in 8 cognitive domains with a total score of 30 points |
| Baseline peripheral blood neuropathology biomarkers level | Blood samples will be collected on day 1 of the entry study | Fasting blood glucose（mmol/L） |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Longitudinal changes of brain structural MRI scan | 36 months, 72 months | Compare the changes of the volumes of whole brain and target brain regions from baseline to each follow-up time points |
| Machine learning of multimodal MRI data | 72 months | 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 |
| Longitudinal changes of brain functional MRI scan | 36 months, 72 months | Compare the changes of the Papez circuit cross-scale network variation from baseline to each follow-up time points |
| Longitudinal changes of brain diffusion tensor MRI scan | 36 months, 72 months | Compare the changes of the Papez circuit structural network from baseline to each follow-up time points |
| Longitudinal changes of brain arterial spin labeling MRI scan | 36 months, 72 months | Compare the changes of blood perfusion in the whole brain and Papez circuit from baseline to each follow-up time points |
| Longitudinal changes of neuropsychological performance | 36 months, 72 months | Compare the Montreal Cognitive Assessment(MoCA) change from the baseline to each follow-up time points |
| Longitudinal changes of peripheral blood neuropathology biomarkers leve | 36 months, 72 months | Compare the fasting blood glucose（mmol/L）changes from baseline to each follow-up time points |
Countries
China
Contacts
Primary ContactWenqing Xia, PHD
Outcome results
None listed