收稿日期: 2023-08-03
录用日期: 2023-11-30
网络出版日期: 2024-02-28
基金资助
国家自然科学基金(31972935)
Study of metabolic association between elevated fasting blood glucose and cognitive deterioration
Received date: 2023-08-03
Accepted date: 2023-11-30
Online published: 2024-02-28
Supported by
National Natural Science Foundation of China(31972935)
目的·分析探讨空腹血糖(fasting blood glucose,FBG)升高人群中导致认知功能恶化的影响因素和导致认知功能恶化风险变化的代谢线索。方法·从阿尔茨海默病神经影像学计划数据库中下载阿尔茨海默病队列数据,并筛选出具有FBG数据和随访数据的样本,获得其临床资料[包括年龄、性别、身体质量指数、教育程度、载脂蛋白E4(apolipoprotein E4,APOE4)基因型、人种]和代谢指标数据(包括氨基酸、脂肪酸、蛋白质等)。根据受试者的FBG水平和认知障碍阶段诊断,将其分为正常FBG并无/有认知功能恶化组、FBG升高并无/有认知功能恶化组。采用单因素分析、Cox比例风险回归模型、正交偏最小二乘判别分析、Spearman相关性分析对数据进行分析。结果·共纳入1 317例具有FBG数据且具有较为完整的临床资料与代谢物数据的受试者,其中FBG正常(>3.9 mmol/L且<6.1 mmol/L)共1 153例,FBG升高(≥6.1 mmol/L)共164例。FBG正常的受试者中,275例有认知功能恶化;FBG升高的受试者中,53例有认知功能恶化。基线人口统计学特征分析结果显示,正常FBG组和高FBG组在性别、人种上差异有统计学意义,无认知功能恶化组和有认知功能恶化组在年龄、性别、APOE4基因携带率上差异有统计学意义(均P<0.05)。Cox回归分析表明,认知功能恶化的主要促进因素依次为APOE4基因阳性、FBG升高和年龄增长(HR=2.22,HR=1.38,HR=1.02;均P<0.05)。不同FBG水平下无认知功能恶化和有恶化组的基线代谢指标,以及认知功能恶化前与认知功能恶化后的代谢指标的差异分析结果显示:在认知功能恶化人群中,高密度脂蛋白(high-density lipoproteins,HDL)携带的磷脂在总脂质中的比值显著升高;低密度脂蛋白(low-density lipoprotein,LDL)颗粒浓度及其携带的脂质含量在认知功能恶化后显著升高。相关性分析结果显示,在认知功能恶化人群中,缬氨酸、亮氨酸不仅与FBG水平显著相关,还与血浆磷酸化tau蛋白(phosphorylated tau,pTau)水平显著相关;HDL携带的胆固醇含量、磷脂与总脂质的比值与脑脊液pTau水平显著相关。结论·相较于FBG正常的人群,FBG升高人群认知功能恶化风险显著增加;且不同FBG水平下,无认知功能恶化人群和有认知功能恶化的人群以及认知恶化前与认知恶化后显著差异的代谢指标有所不同。总体而言,LDL及其携带的脂质、HDL携带的磷脂在认知功能恶化过程中呈上升趋势,且支链氨基酸中的缬氨酸与亮氨酸与pTau水平有显著相关性,提示这几个代谢指标在认知功能恶化过程中或许起重要作用。
吴丽蓉 , 陈瑞华 , 晁筱雯 , 郭雨槐 , 孙涛 , 李梦慈 , 陈天璐 . 空腹血糖升高与认知功能恶化的代谢关联研究[J]. 上海交通大学学报(医学版), 2024 , 44(2) : 212 -222 . DOI: 10.3969/j.issn.1674-8115.2024.02.007
Objective ·To analyze and explore the influencing factors that lead to cognitive deterioration in individuals with elevated fasting blood glucose (FBG) and the metabolic clues associated with changes in the risk of cognitive deterioration. Methods ·Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were downloaded, and the samples with FBG and follow-up data were selected from the database. Clinical information, including age, gender, body mass index, education years,apolipoprotein E4 (APOE4) genotype and race, and corresponding metabolic indicator data, including amino acids, fatty acids, proteins and others were obtained. Based on the FBG levels and diagnosis of cognitive impairment stages in Alzheimer's disease, the subjects were categorized into four groups: normal FBG without/with cognitive deterioration, and elevated FBG without/with cognitive deterioration. The univariate analysis method, the Cox proportional hazards model, orthogonal projections to latent structures discriminant analysis (OPLSDA), and Spearman correlation analysis were employed for data analysis. Results ·A total of 1 317 subjects were included, among which 1 153 had normal FBG level (>3.9 mmol/L and <6.1 mmol/L) and 164 had elevated FBG level (≥6.1 mmol/L). In the normal FBG group, 275 subjects showed cognitive deterioration, while in the elevated FBG group, 53 subjects showed cognitive deterioration. Univariate analysis revealed significant differences in gender and race between the normal FBG and elevated FBG group, and significant differences in age, gender, and APOE4 genotype between the groups with and without cognitive deterioration (all P<0.05). Cox regression analysis indicated that primary influencing factors for cognitive deterioration were APOE4 positivity, elevated FBG, and increasing age in order (HR=2.22,HR=1.38,HR=1.02; all P<0.05). In the analysis of baseline metabolic indicators in the groups without and with cognitive deterioration, as well as metabolic indicators before and after cognitive deterioration at different FBG levels, the results of the analysis of variance revealed that in the cognitively deteriorated population, the ratio of phospholipids carried by high-density lipoproteins (HDL) to total lipids was significantly higher; low-density lipoprotein (LDL) particle concentration and the lipids carried by LDL were significantly higher after cognitive deterioration. Correlation analysis showed that valine and leucine were significantly correlated not only with FBG level but also with phosphorylated tau (pTau) level in the plasma in the cognitively deteriorated population. Cholesterol and the ratio of phospholipids to total lipids carried by HDL were significantly correlated with pTau levels in cerebrospinal fluid (CSF). Conclusion ·Compared to the individuals with normal FBG level, those with high FBG level have a significantly higher risk of cognitive deterioration. Additionally, different metabolic indicators show significant differences between the groups without and with cognitive deterioration, as well as metabolic indicators before and after cognitive deterioration at different FBG levels. Overall, LDL and its lipid content, and HDL-carried phospholipids show an increasing trend during cognitive deterioration, and the branched-chain amino acids valine and leucine are significantly correlated with pTau levels in CSF and plasma, suggesting that these metabolic markers may play an important role in cognitive deterioration.
Key words: hyperglycemia; cognitive impairment; metabolomics; risk factor; lipoprotein
1 | 《中国老年2型糖尿病防治临床指南》编写组. 中国老年2型糖尿病防治临床指南(2022年版)[J]. 中国糖尿病杂志, 2022, 30(1): 2-51. |
1 | Authoring Committee for the Clinical Guidelines on the Prevention and Treatment of Elderly Diabetes in China. Clinical guidelines for the prevention and treatment of type 2 diabetes mellitus in the elderly in China (2022 edition)[J]. Chinese Journal of Diabetes Mellitus, 2022, 30(1): 2-51. |
2 | 中华医学会内分泌学分会. 糖尿病患者认知功能障碍专家共识[J]. 中华糖尿病杂志, 2021, 13(7): 678-694. |
2 | Chinese Society of Endocrinology. Expert consensus on cognitive dysfunction in patients with diabetes mellitus[J]. Chinese Journal of Diabetes Mellitus, 2021, 13(7): 678-694. |
3 | HOWARTH C, GLEESON P, ATTWELL D. Updated energy budgets for neural computation in the neocortex and cerebellum[J]. J Cereb Blood Flow Metab, 2012, 32(7): 1222-1232. |
4 | CAMANDOLA S, MATTSON M P. Brain metabolism in health, aging, and neurodegeneration[J]. EMBO J, 2017, 36(11): 1474-1492. |
5 | SZABLEWSKI L. Glucose transporters in brain: in health and in Alzheimer's disease[J]. J Alzheimers Dis, 2017, 55(4): 1307-1320. |
6 | BAO H, LIU Y M, ZHANG M G, et al. Increased β-site APP cleaving enzyme 1-mediated insulin receptor cleavage in type 2 diabetes mellitus with cognitive impairment[J]. Alzheimers Dement, 2021, 17(7): 1097-1108. |
7 | QU M L, ZUO L H, ZHANG M R, et al. High glucose induces tau hyperphosphorylation in hippocampal neurons via inhibition of ALKBH5-mediated Dgkh m6A demethylation: a potential mechanism for diabetic cognitive dysfunction[J]. Cell Death Dis, 2023, 14(6): 385. |
8 | WANG J, LI L, ZHANG Z, et al. Extracellular vesicles mediate the communication of adipose tissue with brain and promote cognitive impairment associated with insulin resistance[J]. Cell Metab, 2022, 34(9): 1264-1279.e8. |
9 | NHO K, KUEIDER-PAISLEY A, MAHMOUDIANDEHKORDI S, et al. Altered bile acid profile in mild cognitive impairment and Alzheimer's disease: relationship to neuroimaging and CSF biomarkers[J]. Alzheimers Dement, 2019, 15(2): 232-244. |
10 | SOININEN P, KANGAS A J, WüRTZ P, et al. High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism[J]. Analyst, 2009, 134(9): 1781-1785. |
11 | PETERSEN R C, AISEN P S, BECKETT L A, et al. Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization[J]. Neurology, 2010, 74(3): 201-209. |
12 | MCKHANN G, DRACHMAN D, FOLSTEIN M, et al. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease[J]. Neurology, 1984, 34(7): 939-944. |
13 | JAGIELSKI A C, JIANG C Q, XU L, et al. Glycaemia is associated with cognitive impairment in older adults: the Guangzhou Biobank Cohort Study[J]. Age Ageing, 2015, 44(1): 65-71. |
14 | GONZáLEZ H M, TARRAF W, GONZáLEZ K A, et al. Diabetes, cognitive decline, and mild cognitive impairment among diverse Hispanics/Latinos: study of Latinos-investigation of neurocognitive aging results (HCHS/SOL)[J]. Diabetes Care, 2020, 43(5): 1111-1117. |
15 | WOODIE L, BLYTHE S. The differential effects of high-fat and high-fructose diets on physiology and behavior in male rats[J]. Nutr Neurosci, 2018, 21(5): 328-336. |
16 | TAN B L, NORHAIZAN M E. Effect of high-fat diets on oxidative stress, cellular inflammatory response and cognitive function[J]. Nutrients, 2019, 11(11): 2579. |
17 | REITZ C, TANG M X, LUCHSINGER J, et al. Relation of plasma lipids to Alzheimer disease and vascular dementia[J]. Arch Neurol, 2004, 61(5): 705-714. |
18 | BAUMGART M, SNYDER H M, CARRILLO M C, et al. Summary of the evidence on modifiable risk factors for cognitive decline and dementia: a population-based perspective[J]. Alzheimer's Dement, 2015, 11(6): 718-726. |
19 | STROM B L, SCHINNAR R, KARLAWISH J, et al. Statin therapy and risk of acute memory impairment[J]. JAMA Intern Med, 2015, 175(8): 1399-1405. |
20 | OLSSON A G, ANGELIN B, ASSMANN G, et al. Can LDL cholesterol be too low? Possible risks of extremely low levels[J]. J Intern Med, 2017, 281(6): 534-553. |
21 | ISO H, JACOBS D R Jr, WENTWORTH D, et al. Serum cholesterol levels and six-year mortality from stroke in 350 977 men screened for the multiple risk factor intervention trial[J]. N Engl J Med, 1989, 320(14): 904-910. |
22 | WHITE P J, MCGARRAH R W, HERMAN M A, et al. Insulin action, type 2 diabetes, and branched-chain amino acids: a two-way street[J]. Mol Metab, 2021, 52: 101261. |
23 | SHIDA Y, ENDO H, OWADA S, et al. Branched-chain amino acids govern the high learning ability phenotype in Tokai high avoider (THA) rats[J]. Sci Rep, 2021, 11(1): 23104. |
24 | COLE J T, MITALA C M, KUNDU S, et al. Dietary branched chain amino acids ameliorate injury-induced cognitive impairment[J]. Proc Natl Acad Sci U S A, 2010, 107(1): 366-371. |
25 | SIDDIK M A B, MULLINS C A, KRAMER A, et al. Branched-chain amino acids are linked with Alzheimer's disease-related pathology and cognitive deficits[J]. Cells, 2022, 11(21): 3523. |
26 | EUSER S M, SATTAR N, WITTEMAN J C M, et al. A prospective analysis of elevated fasting glucose levels and cognitive function in older people: results from PROSPER and the Rotterdam Study[J]. Diabetes, 2010, 59(7): 1601-1607. |
27 | GANGULI M, BEER J C, ZMUDA J M, et al. Aging, diabetes, obesity, and cognitive decline: a population-based study[J]. J Am Geriatr Soc, 2020, 68(5): 991-998. |
28 | NAGAI N, ITO Y, SASAKI H. Hyperglycemia enhances the production of amyloid β1-42 in the lenses of Otsuka Long-Evans Tokushima Fatty rats, a model of human type 2 diabetes[J]. Invest Ophthalmol Vis Sci, 2016, 57(3): 1408-1417. |
29 | YANG Y, WU Y L, ZHANG S T, et al. High glucose promotes Aβ production by inhibiting APP degradation[J]. PLoS One, 2013, 8(7): e69824. |
30 | EXALTO L G, van der FLIER W M, SCHELTENS P, et al. Glycemia and levels of cerebrospinal fluid amyloid and tau in patients attending a memory clinic[J]. J Am Geriatr Soc, 2010, 58(7): 1318-1321. |
31 | LU Y H, JIANG X J, LIU S L, et al. Changes in cerebrospinal fluid tau and β-amyloid levels in diabetic and prediabetic patients: a meta-analysis[J]. Front Aging Neurosci, 2018, 10: 271. |
32 | ARNOLD S E, ARVANITAKIS Z, MACAULEY-RAMBACH S L, et al. Brain insulin resistance in type 2 diabetes and Alzheimer disease: concepts and conundrums[J]. Nat Rev Neurol, 2018, 14(3): 168-181. |
33 | BUTTERFIELD D A, HALLIWELL B. Oxidative stress, dysfunctional glucose metabolism and Alzheimer disease[J]. Nat Rev Neurosci, 2019, 20(3): 148-160. |
34 | NGUYEN T T, TA Q T H, NGUYEN T K O, et al. Type 3 diabetes and its role implications in Alzheimer's disease[J]. Int J Mol Sci, 2020, 21(9): 3165. |
/
〈 |
|
〉 |