Application of biomarker in preparation of product for diagnosing and / or evaluating cognitive impairment after type 2 diabetes mellitus stroke

Abstract

The invention relates to the technical field of biomedicine, in particular to application of a biomarker in preparation of a product for diagnosing and / or evaluating cognitive impairment after type 2 diabetes mellitus stroke. The combination of the biomarkers PPARGC1 and Nrf2 can accurately diagnose the acute-stage cognitive impairment of the type 2 diabetes mellitus stroke and evaluate the acute-stage and subacute / chronic-stage continuous cognitive impairment after the type 2 diabetes mellitus stroke, and provides a more timely clinical strategy.

Description

Technical Field

[0001] The present invention relates to the field of biomedical technology, and in particular to the use of biomarkers in preparing products for diagnosing and / or evaluating cognitive impairment after stroke in type 2 diabetes. Background Art

[0002] Ischemic stroke is the leading cause of death and disability worldwide and an important cause of poststroke cognitive impairment (PSCI). PSCI is characterized by cognitive deficits that usually appear 3 to 6 months after overt stroke, with a prevalence of approximately 50% in the first year after stroke. This directly affects function and quality of life after stroke and is associated with poor functional prognosis.

[0003] Astrocytes exhibit mitochondrial oxidative phosphorylation (OXPHOS) activity, which is essential for their bioenergetics, proliferation, and survival. Astrocytes are increasingly becoming an important target for neuroprotection in stroke. They can transfer mitochondria to neurons, thereby promoting neurological recovery from ischemic injury after stroke. Mitochondrial dysfunction has been identified as a major cause of cognitive impairment. Peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1α, PPARGC1) has been shown to promote mitochondrial biogenesis and OXPHOS. Overexpression of PGC-1α may improve cognitive function in Alzheimer's disease (AD) mice by regulating mitochondrial dynamics. Nuclear factor erythroid 2-related factor 2 (Nrf2) is also a key regulator of mitochondrial function. Aged mice lacking Nrf2 exhibit cognitive impairment compared with wild-type animals, which is associated with impaired mitochondrial function and reduced synaptic density. A recent meta-analysis of PSCI found that diabetes is one of the most important vascular risk factors. Diabetes aggravates the severity of PSCI, which may be due to hyperglycemia exacerbating mitochondrial dysfunction and cognitive deficits.

[0004] Exosomes are an important class of extracellular vesicles (EVs) that can transport proteins, nucleic acids, and lipids and are considered to be important mediators of intercellular communication. Exosomes containing central nervous system (CNS) components can be detected in peripheral blood through the blood-brain barrier (BBB). However, the relationship between mitochondrial proteins in serum astrocyte-derived exosomes (ADEs) and PSCI and specific evidence are still lacking. Summary of the invention

[0005] The present invention provides the use of biomarkers in the preparation of products for diagnosing and / or evaluating cognitive impairment after type 2 diabetes stroke. The combination of biomarkers PPARGC1 and Nrf2 can accurately diagnose cognitive impairment in the acute phase of type 2 diabetes stroke, provide more timely clinical strategies, and solve the problems existing in the prior art.

[0006] The technical solution adopted by the present invention is:

[0007] Use of a biomarker in the preparation of a product for diagnosing and / or evaluating cognitive impairment after stroke in type 2 diabetes, wherein the biomarker is PPARGC1 and / or Nrf2.

[0008] Furthermore, the biomarker is a combination of PPARGC1 and Nrf2.

[0009] Furthermore, the biomarkers PPARGC1 and Nrf2 are derived from mitochondrial proteins in peripheral blood serum astrocyte-derived exosomes ADEs.

[0010] Furthermore, by detecting the expression level of the biomarker, it is possible to diagnose or evaluate whether the type 2 diabetic post-stroke patient has acute cognitive impairment, persistent cognitive impairment or aggravated cognitive impairment after ischemic stroke.

[0011] Furthermore, the expression levels of PPARGC1 and Nrf2 in serum ADE of patients with cognitive impairment in the acute phase of ischemic stroke were significantly lower than those of patients without cognitive impairment; the low expression levels of PPARGC1 and Nrf2 in serum ADE of patients existed simultaneously in the acute phase and subacute / chronic phase of ischemic stroke, indicating that the patients had persistent cognitive impairment.

[0012] Furthermore, the acute phase refers to within 3 months after ischemic stroke; the subacute / chronic phase refers to 3-12 months after ischemic stroke.

[0013] Furthermore, low expression levels of PPARGC1 and Nrf2 refer to PPARGC1 levels ≤ 2392.66 pg / ml and NrF2 levels ≤ 347.695 pg / ml.

[0014] Furthermore, compared with the group without cognitive impairment after type 2 diabetes stroke, the PPARGC1 level in the acute phase cognitive impairment group was 1815.13 (1250.32-2594.51) pg / mL vs. 2521.21 (1522.82-3106.22) pg / mL (p<0.001); the Nrf2 level was 250.63 (199.74-312.34) pg / mL vs. 278.13 (223.53-331.17) pg / mL (p=0.032), indicating that the significantly low expression of PPARGC1 and Nrf2 is a key marker for the diagnosis of acute cognitive impairment.

[0015] Furthermore, the above application, through the simultaneous detection of PPARGC1 and Nrf2, performed ROC curve analysis, and the diagnostic accuracy of acute cognitive impairment in patients with type 2 diabetes after stroke was 81.8%.

[0016] Furthermore, there is no cognitive dysfunction in the acute phase after stroke in type 2 diabetes, but low PPARGC1 and Nrf2 levels in the subacute / chronic phase, indicating that patients' cognitive impairment worsens.

[0017] Furthermore, the product includes a chip or a kit.

[0018] Furthermore, the kit is a PCR kit for detecting PPARGC1 and Nrf2.

[0019] Beneficial effects of the present invention:

[0020] The present invention prospectively studies the relationship between mitochondrial proteins PPARGC1, Nrf2 and PSCI in serum ADEs of patients with type 2 diabetes mellitus (T2DM) in the acute phase of ischemic stroke. It is determined that PPARGC1, Nrf2 and PSCI are associated, and the significantly low level expression of the two markers can accurately diagnose cognitive dysfunction in the acute phase after stroke in patients. The combination of the two biomarkers provides help for the early diagnosis of cognitive impairment after stroke in type 2 diabetes, and can be used as an effective basis for diagnosis and prediction, facilitating early and effective therapeutic intervention, and providing more timely clinical strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1Comparison of the concentrations of mitochondrial proteins PPARGC1 and Nrf2 in astrocyte-derived exosomes between the two groups of the present invention; CI is the cognitive impairment group, NCI is the non-cognitive impairment group, *p<0.05, **p<0.01, ***p<0.001;

[0022] Figure 2 This is the receiver operating characteristic (ROC) curve of the present invention. DETAILED DESCRIPTION

[0023] In order to clearly illustrate the technical features of the present invention, the present invention is described in detail below through specific implementation methods in conjunction with the accompanying drawings.

[0024] 1. Clinical Trials

[0025] The present invention recruited T2DM patients with mild to moderate AIS for the first time from August 2020 to March 2022 and a National Institutes of Health Stroke Scale (NIHSS) ≤ 10. These patients were hospitalized in the Department of Neurology of Weihai Municipal Hospital within 72 hours of symptom onset. The diagnosis of AIS was based on the 1989 World Health Organization criteria and confirmed by magnetic resonance imaging (MRI).

[0026] Exclusion criteria were as follows: hemorrhagic stroke, transient ischemic stroke, stroke caused by trauma or invasive surgery, dementia or cognitive impairment (score ≥3.19 on the Elderly Cognitive Decline Questionnaire), neurological diseases that may affect cognition (such as Parkinson's disease), taking medications that may affect cognitive function, severe heart, liver, and kidney diseases, and inability to complete neuropsychological assessment. Neurological assessment included verification of stroke pathogenesis and NIHSS. Cardiovascular risk factors were determined by medical history and laboratory results. All subjects signed informed consent before enrollment. This study followed the Declaration of Helsinki and was approved by the Ethics Committee of Weihai Hospital.

[0027] 1.1 Neuropsychological assessment

[0028] The Beijing version of the Montreal Cognitive Assessment (MoCA) was used to assess cognitive function and cognitive subdomains (including visual executive function, naming, attention, language, and abstraction) of all participants in the acute phase and subacute / chronic phase (3, 6, and 12 months after stroke) of ischemic stroke. In the acute phase of ischemic stroke, a MoCA score < 25 was considered acute cognitive impairment.

[16] In the subacute / chronic phase after ischemic stroke, a MoCA score of <25 was classified as PSCI (post-stroke cognitive impairment), and a MoCA score of ≥25 was classified as no post-stroke cognitive impairment. Patients with the same cognitive impairment in the acute and subacute / chronic phases were classified as persistent cognitive impairment. Patients with no cognitive impairment in the acute phase but cognitive impairment in the subacute / chronic phase were classified as worsening cognitive impairment.

[0029] Hamilton Depression Rating Scale-17 (HAMD-17) was used to assess depressive symptoms, and HAMD-17 scores ≥ 17 were considered depressive symptoms. The STOP-Bang questionnaire was used to assess the risk of obstructive sleep apnea (OSA), and STOP-Bang scores ≥ 3 were considered high risk of OSA.

[0030] 1.2 Magnetic resonance data acquisition

[0031] Whole-brain MRI and brain magnetic resonance angiography (MRA) were obtained on the same 3.0T Skyra MRI scanner (Siemens, Erlangen, Germany). T1-weighted and T2-weighted fluid-attenuated inversion recovery (FLAIR) images, apparent diffusion coefficient (ADC) images, and diffusion-weighted imaging (DWI) images were acquired. Image acquisition parameters were: repeat time (TR) 4040 ms, echo time (TE) 64 ms, field of view (FOV) 220 × 220, matrix size = 512 × 512, slice thickness = 5 mm. Three-dimensional TOF-MRA scanning parameters were: TR 21 ms, TE 3.43 ms, FOV 200 mm × 180 mm, matrix 313 × 384, signal excitation number 1, and slice thickness 0.7 mm. Infarct volumes were calculated on DWI images using a semi-automated free open-source 3D slicer software (http: / / www.slicer.org). The infarct area was determined using the “Segment Editor” in 3D Slicer. Characteristic MRI features were used to assess small vessel disease (SVD), including lacunar infarcts, white matter hyperintensities (WMHs), cerebral microbleeds (CMBs), enlarged perivascular spaces (PVS), and brain atrophy. White matter hyperintensities were defined as the presence of areas of high intensity in the white matter on FLAIR images. WMHs in periventricular and deep white matter were visually assessed using the Fazekas score. We used a visual rating scale to assess PVS and calculated PVS visible on MRI of the basal ganglia (BGPVS) on one side. SVD was graded from 0 to 4 based on a Fazekas score of ≥2 for deep WMHs or a periventricular score of ≥3, the presence of ≥1 lacunes, ≥1 CMB, and a BGPVS score of ≥2. In this study, AIS was divided into three types according to imaging data: cortical infarction, subcortical infarction, and infratentorial infarction.

[0032] 1.3 Extraction of exosomes and quantification of mitochondria

[0033] After fasting for 12 hours, peripheral blood was collected from the patient's forearm vein. The blood samples were centrifuged (4000g, centrifugation for 10 minutes) to separate the cells from the cell debris, and then 500μl of the supernatant was transferred to a sterile centrifuge tube. 126μl / tube of the kit method exosome precipitation solution (SystemBiosciences, EXOQ20A-1, CA, USA) was added to each tube, mixed to a cloudy state, and incubated at 4°C for 60 minutes. After centrifugation at 1500×g for 30 minutes at 4°C, total exosomes were isolated from each sample.

[0034] To extract astrocyte-enriched exosomes, total exosomes were resuspended in 250 μl of Dulbecco's phosphate-buffered saline, vortexed, and incubated with 2.3 μl of glutamine aspartate transporter (ACSA-1) biotinylated antibody (Miltenyi Biotec, 130-118-984, Auburn, CA) in 50 μl of 3% bovine serum albumin for 60 min at 20°C. Then, 25 μl of streptavidin-agarose resin (Thermo Fisher Scientific, 53117, Waltham, MA, USA) containing 50 μl of 3% bovine serum albumin was added and incubated at 4°C for 30 min. 4℃, 800×g centrifugation for 10 minutes, discard the supernatant, be careful not to suck away the resin below, place in 100μl 0.05M glycine-HCl (pH 3.0) vortex shake for 10 minutes, centrifuge at 4000×g for 10 minutes (4℃). Then transfer the supernatant to a pre-cooled Eppendorf tube containing 100μl 10% bovine serum albumin and 20μl 1M Tris-HCl (pH 8.6), and then add 550μl mammalian protein extraction reagent (M-PER) (Thermo Fisher Scientific, 78505, Waltham, MA, USA), and store the astrocyte-derived exosome lysate at -80℃.

[0035] Exosomes were identified using transmission electron microscopy. A small portion of the exosomes was resuspended in 50 μl of 1× phosphate buffered saline solution and mixed with 50 μl of 4% paraformaldehyde solution. Then 10 μl of the exosome suspension was dropped onto the sealing film, and the Formvar-carbon copper mesh was immersed in the exosome suspension with the Formvar membrane facing down and fixed for 30 minutes. 50 μl of 1× phosphate buffered saline solution was dropped onto the sealing film and rinsed for a total of 40 minutes, 10 minutes each time. The other side of the copper mesh was kept dry and the Formvar membrane was facing down. After rinsing, 50 μl of 1% glutaraldehyde was dropped onto the sealing film, immersed in 5 μl, and rinsed again with phosphate buffered saline for 40 minutes, the method was the same as above. After rinsing, it was immersed in 3% tungsten phosphate solution for negative staining for 3 minutes, and the negative staining solution was blotted with filter paper and dried at room temperature. Exosomes were identified morphologically using a Hitachi H7500 electron microscope.

[0036] After confirming that the exosomes were successfully extracted, the exosomes were quantified: 250 μl of M-PER containing EDTA and a mixture of protease inhibitors was added, and the mixture was shaken and centrifuged. 2 μl of supernatant was used for BCA exosome total protein concentration determination. The protein sample was diluted 1:25, and the protein standard was diluted with 1× phosphate buffered saline solution to prepare standard protein solutions of 500 μg / ml, 400 μg / ml, 300 μg / ml, 200 μg / ml, 100 μg / ml, 50 μg / ml, 25 μg / ml, and 0 μg / ml concentrations. 25 μl of protein solution / standard was added to the 96-well plate. BCA reagent (Servicebio, G2026, Wuhan) A solution and B solution (50:1) were prepared into a mixture and 200 μl was added to each well. Incubate in the dark for 30 minutes (37°C). Place in the full wavelength microplate reader-Varioskan LUX 3020 instrument (Thermo Fisher Scientific Oy, Finland), wavelength 562nm, determine the concentration and prepare a standard curve. Then use protein blotting to detect exosome protein markers: mix the separated exosomes with the loading buffer and put them in a 100℃ water bath for 5 minutes, centrifuge, place on ice, and wait for loading. Prepare SDS-PAGE separation gel and gradually add each solution with a concentration of 12%, mix and add to two glass plates for gel making, and seal with isopropanol. After the lower layer of gel solidifies, pour out the isopropanol, rinse with deionized water and dry, and prepare the concentrated gel. Add each solution with a concentration of 5% and mix, add to two glass plates for gel making, immediately insert the comb, and pull out the comb after solidification. Place the gel tank on ice and pour in the electrophoresis buffer, load 10-35μl into each well, and record the order of loading. Prepare electrophoresis buffer [Tris. hydrochloric acid 3.028g (25mM), Gly 14.413g (192mM), 10% SDS 10ml (0.1% SDS, dilute to 1000ml with deionized water] in advance, precool at 4℃; transfer buffer [Tris. hydrochloric acid 3.028g (25mM), Gly 14.413g (192mM), methanol 100ml, dilute to 1000ml with deionized water], precool at 4℃. Upper gel 60V, 30 minutes; lower gel 110V, 120 minutes. After the electrophoresis, the gel needs to be rinsed in phosphate buffer solution for 2 minutes, and then soaked in transfer buffer for equilibrium. Soak the cut PVDF membrane (Millipore, IPVH00010) in methanol for 2 minutes, then soak in deionized water for 2 minutes, and finally soak in transfer buffer for equilibrium for 15 minutes. Transfer on ice, 100V constant voltage transfer for 50 minutes. Placement of mat, membrane and gel: red, (+) white rack, mat, filter paper, membrane, gel, filter paper, mat, black rack (-), black. The transfer band is from - to +. After the transfer is completed, soak the membrane in phosphate buffered saline for 3-5 minutes and cut the membrane.Block with 5% skim milk (0.75g milk powder + 15ml phosphate buffered saline) at 37°C for 1-2 hours. Wash the membrane with 1× phosphate buffered saline-T (1000ml 1× phosphate buffered saline + 1ml Tween-20) for 5-10 minutes, 3 times. Dilute the primary antibody according to the antibody instructions [CD63 antibody: 1:500; TSG101 antibody (PROTEINTECH, 28283-1-AP, USA): 1:1000; HSP70 antibody (PROTEINTECH, 10995-1-AP, USA): 1:2000; Calnexin antibody (PROTEINTECH, 10427-2-AP, USA): 1:2000] and incubate overnight on a shaker at 4°C. Take the shaker out of the ice storage and wash the membrane with 1× phosphate buffered saline-T for 5-10 minutes, 3 times. Secondary antibodies [rabbit secondary antibody (Jackson Immuno Research, 111-035-003, USA) 1:5000; mouse secondary antibody (Jackson Immuno Research, 115-035-003, USA) 1:10000] were added and incubated on a shaker at 37°C for 2 h. The membrane was washed with 1× phosphate buffered saline-T for 5 min, 5 times, and developed by chemiluminescence.

[0037] Enzyme-linked immunosorbent assay (ELISA) kits were used to quantify the four-span exosome markers CD63 (RayBio, ELH-CD63, Norcross, GA 30092, USA), human peroxisome proliferator-activated receptor gamma coactivator 1α (PPARGC1) (Signalway Antibody Company, EK8377, Maryland, USA), and human Nrf2 (Nrf2) (Abcam Company, ab277397, Cambridge, UK). The ADEs level of CD63 protein was determined to normalize the exosome content. The intra-group coefficient of variation was less than 10%, and the inter-group coefficient of variation was less than 10% to 12%. The ELISA microplate was read using a V Arioskan LUX 3020 instrument (ThermoFisher Scientific Oy, Ratastie 2, Vantaa, Finland). Serum samples from all subjects were analyzed by the same technician who was unaware of the clinical data.

[0038] 2. Results

[0039] 2.1 Baseline demographics and biomarker characteristics

[0040] A total of 244 patients were included in the acute phase of this study. The participants were divided into a cognitive impairment group and a non-cognitive impairment group, of which 181 patients (74.18%) had cognitive impairment. In the acute phase of ischemic stroke, the levels of PPARGC1 and Nrf2 in serum ADE in the cognitive impairment group were significantly lower than those in the non-cognitive impairment group. Specifically, the PPARGC1 level was 1815.13 (1250.32-2594.51) pg / mL vs. 2521.21 (1522.82-3106.22) pg / mL (p<0.001); the Nrf2 level was 250.63 (199.74-312.34) pg / mL vs. 278.13 (223.53-331.17) pg / mL (p=0.032), see Figure 1 .

[0041] 2.2 Predictive value of PPARGC1 and Nrf2 in serum ADEs for cognitive impairment after stroke in type 2 diabetes

[0042] To explore the potential of PPARGC1 and Nrf2 in serum ADEs as prognostic biomarkers for PSCI in patients with T2DM, binary logistic regression and multivariate logistic regression models were used, with cognitive function as the dependent variable and PPARGC1 and Nrf2 as independent variables.

[0043] At 3-month follow-up after stroke, after adjusting for age, sex, education, BMI, hypertension, current smoking and drinking, lower ADE levels of PPARGC1 and Nrf2 were associated with an increased risk of PSCI (OR 0.830, 95% CI 0.706-0.975; OR 0.772, 95% CI 0.647-0.921) and persistent cognitive impairment after stroke (OR 0.803, 95% CI 0.678-0.950; OR 0.757, 95% CI 0.628-0.911) (Table 1).

[0044] Table 1 ORs and 95% CIs of cognitive impairment 3 months after ischemic stroke

[0045]

[0046] Note: Model 0: Unadjusted. Model 1: Adjusted for age, gender, and years of education. Model 2: Adjusted for age, gender, years of education, BMI, hypertension, smoking, and drinking. OR, odds ratio. CI, confidence interval.

[0047] Similar results were observed at 6-month follow-up after stroke. After adjusting for covariates, T2DM patients with lower PPARGC1 and Nrf2 levels in serum ADE had higher incidences of PSCI (OR 0.793, 95% CI 0.673-0.936; OR 0.813, 95% CI 0.686-0.965) and persistent cognitive impairment after stroke (OR 0.778, 95% CI 0.654-0.924; OR 0.797, 95% CI 0.665-0.955) (Table 2).

[0048] Table 2 ORs and 95% CIs for cognitive impairment 6 months after ischemic stroke

[0049]

[0050]

[0051] Note: Model 0: Unadjusted. Model 1: Adjusted for age, gender, and years of education. Model 2: Adjusted for age, gender, years of education, BMI, hypertension, smoking, and drinking. OR, odds ratio. CI, confidence interval.

[0052] After 12 months of follow-up, similar results were observed. Low serum ADE levels of PPARGC1 and Nrf2 were associated with an increased risk of PSCI (unadjusted OR 0.841, 95% CI 0.725-0.976; unadjusted OR 0.831, 95% CI 0.720-0.959) and persistent cognitive impairment after stroke (unadjusted OR 0.829, 95% CI 0.711-0.967; unadjusted OR 0.815, 95% CI 0.701-0.948) (Table 3).

[0053] Table 3 ORs and 95% CIs for cognitive impairment 12 months after ischemic stroke

[0054]

[0055] Note: Model 0: Unadjusted. Model 1: Adjusted for age, gender, and years of education. Model 2: Adjusted for age, gender, years of education, BMI, hypertension, smoking, and drinking. OR, odds ratio. CI, confidence interval.

[0056] 2.3 Diagnostic value of serum astrocyte-derived exosome mitochondrial protein for cognitive dysfunction in acute stroke in type 2 diabetic patients

[0057] Receiver operating characteristic (ROC) curve analysis was performed to verify the diagnostic value of serum astrocyte-derived exosomal mitochondrial proteins (PPARGC1 and Nrf2) for cognitive dysfunction in acute stroke of type 2 diabetes. The accuracy of serum astrocyte-derived exosomal complement protein PPARGC1 for the diagnosis of cognitive dysfunction in acute stroke of type 2 diabetes was 78.1%; the accuracy of serum astrocyte-derived exosomal complement protein Nrf2 for the diagnosis was 75.2%; the accuracy of combined PPARGC1 and Nrf2 for the diagnosis of cognitive dysfunction in acute stroke of type 2 diabetes was 81.8%.

[0058] 3. Discussion and Conclusion

[0059] The present invention explores the relationship between PPARGC1, Nrf2 and PSCI in serum ADE of patients with T2DM combined with ischemic stroke at three time points. The results show that decreased levels of PPARGC1 and Nrf2 in serum ADE are associated with increased risk of PSCI and persistent cognitive impairment after stroke.

[0060] Low levels of PPARGC1 and Nrf2 in serum ADEs may be risk factors for PSCI, suggesting that their combination has the potential to serve as a biomarker for the acute diagnosis of PSCI in T2DM patients and for predicting the persistence of cognitive impairment. In addition, mitochondrial dysfunction may be a potential pathophysiological mechanism and new therapeutic target for PSCI.

[0061] The above specific implementation manner cannot be used as a limitation on the protection scope of the present invention. For those skilled in the art, any substitution, improvement or change made to the implementation manner of the present invention falls within the protection scope of the present invention.

[0062] The matters not described in detail in the present invention are all known technologies to those skilled in the art.

Claims

1. Use of a biomarker in the preparation of a product for diagnosing and / or evaluating cognitive impairment after stroke in type 2 diabetes, characterized in that: The biomarkers are PPARGC1 and / or Nrf2.

2. The use according to claim 1, characterized in that: The biomarker is a combination of PPARGC1 and Nrf2.

3. The use according to claim 1, characterized in that: The biomarkers PPARGC1 and Nrf2 are derived from mitochondrial proteins in peripheral blood serum astrocyte-derived exosomes ADEs.

4. The use according to claim 1, characterized in that: By detecting the expression level of the biomarker, it is possible to diagnose or evaluate whether type 2 diabetic post-stroke patients have acute cognitive impairment, persistent cognitive impairment or aggravated cognitive impairment after ischemic stroke.

5. The use according to claim 4, characterized in that: The expression levels of PPARGC1 and Nrf2 in serum ADE of patients with cognitive impairment in the acute phase of ischemic stroke were significantly lower than those of patients without cognitive impairment; the low expression levels of PPARGC1 and Nrf2 in serum ADE of patients existed simultaneously in the acute phase and subacute / chronic phase of ischemic stroke, indicating that the patients had persistent cognitive impairment.

6. The use according to claim 4, characterized in that: Low expression levels of PPARGC1 and Nrf2 refer to PPARGC1 levels ≤ 2392.66 pg / ml and NrF2 levels ≤ 347.695 pg / ml.

7. The use according to claim 1, characterized in that: The product includes a chip or a kit.

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