Journal List > Yonsei Med J > v.56(1) > 1031796

Ma, Feng, Qian, Yang, Liu, Han, Zhu, and Li: Insulin Resistance Is an Important Risk Factor for Cognitive Impairment in Elderly Patients with Primary Hypertension

Abstract

Purpose

Insulin resistance plays a role in the development of dementia and hypertension. We investigated a possible relationship between cognitive impairment and insulin resistance in elderly Chinese patients with primary hypertension.

Materials and Methods

One hundred and thirty-two hypertensive elderly patients (>60 years) were enrolled in this study, and assigned into either the cognitive impairment group (n=61) or the normal cognitive group (n=71). Gender, age, education, body mass index (BMI), waist hip ratio (WHR), total cholesterol (TC), triglyceride (TG), C-reactive protein (CRP), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), creatinine (Cr), fasting plasma glucose (FPG), fasting insulin (FINS), homeostasis model of assessment for insulin resistance index (HOMA-IR), systolic blood pressure, diastolic blood pressure, smoking history, atherosclerosis and the proportion of uncontrolled hypertension were compared between the two groups. Multi-factorial logistic regression analysis was performed.

Results

No significant differences were found in gender, age, TC, CRP, HDL-C, LDL-C, Cr, BP, smoking history, atherosclerosis and the proportion of uncontrolled hypertension between the two groups. The cognitive impairment group had lower education levels, and higher BMI, WHR, TG, FPG, FINS, and HOMA-IR levels than the control group. Logistic regression analysis revealed the levels of education, BMI, WHR, and HOMA-IR as independent factors that predict cognitive impairment in patients.

Conclusion

Our study demonstrates that poor education and increased BMI, WHR, and HOMA-IR are independent risk factors for cognitive impairment in elderly patients with hypertension. Insulin resistance plays an important role in the development of cognitive impairment in primary elderly hypertensive patients.

INTRODUCTION

With the aging of the Chinese population, the prevalence of hypertension and dementia has been steadily rising. This, in turn, has had major adverse effects on the well-being of the elderly. Alzheimer's disease (AD) is a leading cause of dementia, which is characterized by progressive deterioration of memory and cognition. AD is a major source of morbidity and mortality worldwide, and its strain on our society, in general and particularly on the affected individuals, is enormous. Mild cognitive impairment (MCI) is an intermediate state that separates normal aging-associated cognitive changes from pathological dementia. Many studies have found that insulin resistance (IR) plays an important role in the occurrence and development of hypertension and dementia.1 Sporadic AD, which alters the brain insulin signaling pathway, is now recognized as type 3 diabetes mellitus (T3DM).2,3 Peripheral IR without T2DM is a risk factor and facet for AD.4,5,6 It is associated with reduced basal and insulin-induced activation of cerebral IRs, higher cerebral neuritic plaque loads, lower hippocampal volume and cognitive performance, inhibited cerebrocortical glucose metabolism, and reduced memory recall.7,8,9,10,11 IR causes cognitive dysfunction, and increases the risk of developing dementia. Therefore, it is of a great importance to explore its critical role in the development of cognitive impairment in primary elderly hypertensive patients to appropriately apply therapeutic interventions that may hinder the progression of the disease.
The intertwined epidemics of hypertension and IR pose a major public health challenge.12 A variety of mechanisms link IR and hypertension. Of note, essential hypertension related genes such as AGT, NOS3, NPPA, ADRB2, ADD1, and SCNN1A are known to be IR-related gene markers.13,14,15 IR increases the expression of insoluble amyloid beta protein (Aβ), and activates signaling pathways related to the development of cognitive impairment and AD by increasing the production of advanced glycation end (AGEs) product.16 The incidence of MCI is associated with IR.17 To our best knowledge, however, it remains unknown whether IR is an important risk factor for cognitive impairment in primary elderly hypertensive patients. In the present study, we aimed to explore the relationship between cognitive impairment and IR in elderly hypertensive Chinese patients.

MATERIALS AND METHODS

Participants

Elderly patients (average age of 68.03±9.71 years) with primary hypertension (n=132, male=91, female=41), were recruited from the Department of Geriatrics, Xuanwu Hospital, Capital Medical University from August 2008 to October 2011. Inclusion criteria consisted of advanced age (≥60 years) suffering from primary hypertension. Exclusion criteria included secondary hypertension, diabetes, cancer, recent acute infection, severe cardiac, liver or kidney dysfunction, cerebrovascular disease, severe Parkinson's disease, depression or anxiety, hypothyroidism, intracranial space-occupying, alcohol dependence, cognitive dysfunction after traumatic brain injury, alcohol and drug abuse. Hypertension was defined as systolic blood pressure (SBP) ≥140 mm Hg, diastolic blood pressure (DBP) ≥90 mm Hg, current treatment with antihypertensive medication, or a self-reported diagnosis of hypertension. All the participants underwent a standardized clinical assessment, which included a medical history, and physical and neurological examination together with the Mini Mental State Examination (MMSE) tests, Montreal Cognitive Assessment (MoCA) tests, psychometric evaluation and MRI. Normal cognitive function was defined as MoCA >26 (if schooling <12 years, the boundary value was set at 25) and MMSE >24. MCI was diagnosed according to the revised Petersen criteria.18 These criteria included a decline in memory, objectively verified by neuropsychological testing in combination with a precise history from the participant, proxy, or both, and adjusted for age and education, or a decline in other cognitive domains, with normal functional activities.19 Patients with vascular cognitive impairment were excluded in the study. Participants were assigned to either the hypertension with cognitive impairment group (case group, n= 61) or the hypertension with normal cognitive function group (control group, n=71). All patients were under antihypertensive medication treatment. Informed consent was obtained from all participants prior to the study. This clinical investigation was approved by the Ethics Committee of Xuanwu Hospital, Capital Medical University, China.

Data collection

A comprehensive questionnaire was conducted by trained investigators. Participants' height, weight, waist circumference, and hip diameter were measured. Body mass index (BMI) and waist-hip ratio (WHR) were subsequently calculated.

Blood test

Venous blood was collected from those patients who were admitted to the hospital early in the morning following an overnight fast (with the exception of drinking water) for at least 8-10 hours, blood was collected from the patients and then coagulated at room temperature for 30 minutes. The supernatant of blood was collected after centrifugation for 15 minutes at 1000 rpm and stored at -20℃ pending for analysis. Serum total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), serum creatinine (Cr), fasting blood glucose (FPG), and fasting insulin (FINS) were determined using a Hitachi 7600 automatic biochemical analyzer (Hitachi, Tokyo, Japan).

Statistical analysis

An unpaired T test was conducted using SPSS for Windows (version 12.0, SPSS Inc., Chicago, IL, USA). Data were expressed as means±standard error of the mean (SEM). The Rank Sum Test method was used for data that were not distributed normally. The education level, BMI, WHR, TC, and homeostasis model of assessment for insulin resistance index (HOMA-IR) were fixed as independent variables. A positive or negative classification of cognitive impairment was considered as the dependent variable. Logistic regression was used in multifactor analysis. Differences with a p value <0.05 and p<0.01 were considered statistically significant and very significant, respectively. In logistic regression, B>0 and p<0.05 indicate a risk factor, whereas B<0 and p<0.05 indicate a protective factor.

RESULTS

Comparison of single factors between the two groups

Shown in Table 1 are comparisons between the two groups in terms of gender, age, education level, BMI, WHR, TC, TG, C-reactive protein (CRP), HDL-C, LDL-C, Cr, FPG, FINS, HOMA-IR, SBP, DBP, smoking, atherosclerosis, and uncontrolled hypertension. The education level of the case group was lower than that of the control group, whereas BMI, WHR, TG, FPG, FINS, and HOMA-IR of the case group were higher than those of the control group. There were no differences in gender, age, course of hypertension, blood pressure level, and basic diseases between the two groups.

Logistic regression analysis

Table 2 shows that the education level (B=-1.171, p=0), BMI (B=0.980, p=0.022), WHR (B=1.020, p=0.015), and HOMA-IR (B=1.500, p=0) were independent factors of cognitive impairment in elderly patients with hypertension. High BMI, WHR, and HOMA-IR were significant risk factors, whereas a high education level was a protective factor.

DISCUSSION

To our knowledge, this is the first clinical study that systematically investigated the effects of IR on cognitive impairment in elderly Chinese patients with hypertension. Our results showed that elderly hypertensive patients with impaired cognitive function had lower education levels and higher BMI, WHR, TG, FPG, FINS, and HOMA-IR levels than those with normal cognitive function. A high degree of education has been widely recognized as a major protective factor against cognitive impairment.20 HOMA-IR is positively associated with waist circumstances and TG.21 Conversely, abdominal obesity and hyperlipidemia can promote IR and cognitive impairment in patients, in part due to an increased level of oxidative stress and secreted inflammatory cytokines.22 Insulin plays an important role in maintaining normal brain function.23,24 Insulin action requires an interaction with insulin receptors which are highly expressed in the hippocampus and cerebral cortex. The insulin-insulin receptor complex activates an intracellular signaling cascade including a tyrosine kinase involved in energy metabolism. It also supports and protects neurons by regulating glucose metabolism, and improves the learning and memory function by regulating the flux of neurotransmitters.25 As glucose metabolism in the brain neurons is also regulated by insulin, IR can cause an impaired cognitive function. It has been demonstrated that an abnormal glucose metabolism significantly increases the risk of cognitive impairment in stroke patients.26 Additionally, hippocampal volume, a recognized risk factor in the development of cognitive impairment, was significantly reduced in individuals with increased waist circumference. Importantly, a decreased hippocampal volume and an increased waste circumference are closely correlated with AD.27
In the present study, we have found that IR is an important risk factor for the cognitive impairment in elderly patients with primary hypertension, however, the pathogenesis remains unclear. We hypotheses that the mechanism of IR on cognitive function may involve the following factors: 1) IR promotes the metabolism of Aβ and Tau hyperphosphorylation, resulting in sugar, fat, protein, and other metabolic disorders, and neuronal degeneration together with an impaired cognitive function under hyperinsulinemia;28,29 2) IR protein is rich in the specific learning and memory regions of the brain.30 IR impairs brain tissue oxygen metabolism, downregulates peroxisome proliferator-activated receptor γ (PPARγ) expression, upregulates AGE and receptor for advanced glycation end product (RAGE) levels, and enhances the phosphorylation of nuclear factor kappa B (NF-κB), thereby, facilitating interactions between the AGE-RAGE pathway and PPARγ in IR animals;31,32 3) Inflammatory cytokines. Although we could not find any difference in serum CRP concentration between the two groups, mild hyperinsulinemia can increase inflammatory cytokines such as interleukin (IL)-1a, IL-6, and tumor necrosis factor (TNF)-a in cerebrospinal fluid (CSF) and plasma.33,34 AD has been confirmed to involve inflammation in the brain;33,34 and 4) Hypercortisolism. Hyperinsulinemia can induce hypercortisolemia through the hypothalamic pituitary adrenal axis, inhibiting granule cell regeneration, modulating hippocampal long term potentiation and long term depression and ultimately impairing cognitive function. Brain IR, specifically in the hippocampal formation and the cerebellar cortex, appears to be an early and common feature of AD. It is accompanied by insulin-like growth factor 1 (IGF-1) signaling resistance and is closely associated with IRS-1-PI3K pathway dysfunction potentially triggered by Aβ oligomers, resulting in cognitive decline.35,36
Our present findings indicate that poor education, BMI, WHR, and HOMA-IR are all independent risk factors for the cognitive impairment in elderly patients with hypertension. Clinicians, therefore, should place emphasis on the diagnosis of IR in their attempt to attenuate the development of cognitive impairment in elderly patients with hypertension. In light of the present study, intervention toward early and effective management to reduce IR appears to have important implications for the prevention and treatment of cognitive impairment.

Conclusions

Our present study found that IR is an important risk factor for cognitive impairment in primary elderly hypertensive patients. Our findings contribute to a growing body of evidence linking IR to AD and identify risk factors for dementia-associated memory loss.

Limitations

Participation in this study was restricted to patients living in Beijing. Hence, our results may not be representative of the overall Chinese population. Moreover, since the cross-sectional study cannot reflect the association between risk factors and outcomes, a follow-up study is warranted.

Figures and Tables

Table 1

Factor Comparisons between the Two Groups

ymj-56-89-i001
Control group Case group
Sex (male/female) 50/21 41/20
Age (yrs) 67.91±8.97 68.17±9.92
Education (≥college, %) 48 (67.61) 27 (44.26)
BMI (kg/m2) 22.9±2.3 26.8±2.2
WHR 0.81±0.05 0.93±0.06
TC (mmol/L) 5.09±0.57 5.17±0.62
TG (mmol/L) 1.7±0.5 2.3±0.6
CRP (mmol/L) 0.47±0.11 0.48±0.13
HDL-C (mmol/L) 1.8±0.4 1.7±0.3
LDL-C (mmol/L) 2.7±0.4 2.9±0.5
Cr (mmol/L) 38.0±17.7 40.7±19.4
FPG (mmol/L) 5.2±0.9 6.1±1.3
FINS (mU/L) 9.3±3.7 21.7±12.9
HOMA-IR 2.1±1.3 5.9±3.1
SBP (mm Hg) 138.9±39.7 140.3±42.1
DBP (mm Hg) 75.0±22.6 77.2±24.3
Smoking (yes, %) 17 (23.94) 15 (24.59)
Atherosclerosis (yes, %) 18 (25.35) 16 (26.22)
Uncontrolled hypertension (yes, %) 9 (12.68) 8 (13.11)

BMI, body mass index; WHR, waist hip ratio; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; CRP, C-reactive protein; Cr, creatinine; FPG, fasting plasma glucose; FINS, fasting insulin; HOMA-IR, homeostasis model of assessment for insulin resistance index; SBP, systolic blood pressure; DBP, diastolic blood pressure.

Compared to the control group, *p<0.05, p<0.01.

All patients were under antihypertensive medication treatment.

Table 2

Logistic Regression Analysis

ymj-56-89-i002
Factors B S.E. Wald df Sig Exp (B) 95% CI
Lower Upper
Education -1.171 0.323 12.301 1 0.000 3.212 1.671 6.200
BMI 0.980 0.437 5.171 1 0.022 2.690 1.150 6.331
WHR 1.020 0.403 8.898 1 0.015 3.002 1.075 5.711
TC 0.379 0.364 1.050 1 0.303 1.465 0.715 2.960
HOMA-IR 1.500 0.359 15.707 1 0.000 4.500 2.212 8.102

BMI, body mass index; WHR, waist hip ratio; TC, total cholesterol; HOMA-IR, homeostasis model of assessment for insulin resistance index; S.E., standard error; CI, confidence interval.

ACKNOWLEDGEMENTS

This work was supported by the following grants: The Ministry of Health Welfare Industry Special Fund (201002011), MOE (Ministry of Education in China) Project of Humanities and Social Sciences (12YJCZH146), and Beijing Municipal Health Bureau Research Fund (Jing 13-02).

Notes

The authors have no financial conflicts of interest.

References

1. Steen E, Terry BM, Rivera EJ, Cannon JL, Neely TR, Tavares R, et al. Impaired insulin and insulin-like growth factor expression and signaling mechanisms in Alzheimer's disease--is this type 3 diabetes? J Alzheimers Dis. 2005; 7:63–80.
crossref
2. Cukierman-Yaffee T. The relationship between dysglycemia and cognitive dysfunction. Curr Opin Investig Drugs. 2009; 10:70–74.
3. Craft S. Insulin resistance and Alzheimer's disease pathogenesis: potential mechanisms and implications for treatment. Curr Alzheimer Res. 2007; 4:147–152.
crossref
4. Ohara T, Doi Y, Ninomiya T, Hirakawa Y, Hata J, Iwaki T, et al. Glucose tolerance status and risk of dementia in the community: the Hisayama study. Neurology. 2011; 77:1126–1134.
crossref
5. Schrijvers EM, Witteman JC, Sijbrands EJ, Hofman A, Koudstaal PJ, Breteler MM. Insulin metabolism and the risk of Alzheimer disease: the Rotterdam Study. Neurology. 2010; 75:1982–1987.
crossref
6. Janson J, Laedtke T, Parisi JE, O'Brien P, Petersen RC, Butler PC. Increased risk of type 2 diabetes in Alzheimer disease. Diabetes. 2004; 53:474–481.
crossref
7. Baker LD, Cross DJ, Minoshima S, Belongia D, Watson GS, Craft S. Insulin resistance and Alzheimer-like reductions in regional cerebral glucose metabolism for cognitively normal adults with prediabetes or early type 2 diabetes. Arch Neurol. 2011; 68:51–57.
crossref
8. Mielke JG, Taghibiglou C, Liu L, Zhang Y, Jia Z, Adeli K, et al. A biochemical and functional characterization of diet-induced brain insulin resistance. J Neurochem. 2005; 93:1568–1578.
crossref
9. Pratchayasakul W, Kerdphoo S, Petsophonsakul P, Pongchaidecha A, Chattipakorn N, Chattipakorn SC. Effects of high-fat diet on insulin receptor function in rat hippocampus and the level of neuronal corticosterone. Life Sci. 2011; 88:619–627.
crossref
10. Matsuzaki T, Sasaki K, Tanizaki Y, Hata J, Fujimi K, Matsui Y, et al. Insulin resistance is associated with the pathology of Alzheimer disease: the Hisayama study. Neurology. 2010; 75:764–770.
crossref
11. Rasgon NL, Kenna HA, Wroolie TE, Kelley R, Silverman D, Brooks J, et al. Insulin resistance and hippocampal volume in women at risk for Alzheimer's disease. Neurobiol Aging. 2011; 32:1942–1948.
crossref
12. De Boer MP, Meijer RI, Wijnstok NJ, Jonk AM, Houben AJ, Stehouwer CD, et al. Microvascular dysfunction: a potential mechanism in the pathogenesis of obesity-associated insulin resistance and hypertension. Microcirculation. 2012; 19:5–18.
crossref
13. Sarzani R, Salvi F, Dessì-Fulgheri P, Rappelli A. Renin-angiotensin system, natriuretic peptides, obesity, metabolic syndrome, and hypertension: an integrated view in humans. J Hypertens. 2008; 26:831–843.
crossref
14. Kashyap SR, Defronzo RA. The insulin resistance syndrome: physiological considerations. Diab Vasc Dis Res. 2007; 4:13–19.
crossref
15. Haenni A, Lind L, Reneland R, Lithell H. Blood pressure changes in relation to sodium and calcium status in induced hyperinsulinemia. Blood Press. 2000; 9:116–120.
crossref
16. Singh R, Barden A, Mori T, Beilin L. Advanced glycation end-products: a review. Diabetologia. 2001; 44:129–146.
crossref
17. den Heijer T, Vermeer SE, van Dijk EJ, Prins ND, Koudstaal PJ, Hofman A, et al. Type 2 diabetes and atrophy of medial temporal lobe structures on brain MRI. Diabetologia. 2003; 46:1604–1610.
crossref
18. Winblad B, Palmer K, Kivipelto M, Jelic V, Fratiglioni L, Wahlund LO, et al. Mild cognitive impairment--beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med. 2004; 256:240–246.
crossref
19. Desideri G, Kwik-Uribe C, Grassi D, Necozione S, Ghiadoni L, Mastroiacovo D, et al. Benefits in cognitive function, blood pressure, and insulin resistance through cocoa flavanol consumption in elderly subjects with mild cognitive impairment: the Cocoa, Cognition, and Aging (CoCoA) study. Hypertension. 2012; 60:794–801.
crossref
20. Mortamais M, Portet F, Brickman AM, Provenzano FA, Muraskin J, Akbaraly TN, et al. Education modulates the impact of white matter lesions on the risk of mild cognitive impairment and dementia. Am J Geriatr Psychiatry. 2014; 22:1336–1345.
crossref
21. Kavanagh K, Fairbanks LA, Bailey JN, Jorgensen MJ, Wilson M, Zhang L, et al. Characterization and heritability of obesity and associated risk factors in vervet monkeys. Obesity (Silver Spring). 2007; 15:1666–1674.
crossref
22. Gustafsson S, Lind L, Söderberg S, Zilmer M, Hulthe J, Ingelsson E. Oxidative stress and inflammatory markers in relation to circulating levels of adiponectin. Obesity (Silver Spring). 2013; 21:1467–1473.
crossref
23. Luchsinger JA. Adiposity, hyperinsulinemia, diabetes and Alzheimer's disease: an epidemiological perspective. Eur J Pharmacol. 2008; 585:119–129.
24. Salkovic-Petrisic M, Hoyer S. Central insulin resistance as a trigger for sporadic Alzheimer-like pathology: an experimental approach. J Neural Transm Suppl. 2007; 217–233.
crossref
25. Apparsundaram S, Sung U, Price RD, Blakely RD. Trafficking-dependent and -independent pathways of neurotransmitter transporter regulation differentially involving p38 mitogen-activated protein kinase revealed in studies of insulin modulation of norepinephrine transport in SK-N-SH cells. J Pharmacol Exp Ther. 2001; 299:666–677.
26. Liu H, Xu J, Qu L. Recent study on the relationship between insulin resistance and stroke. Chin J Clin Rehabil. 2003; 7:3864–3866.
27. Jagust W, Harvey D, Mungas D, Haan M. Central obesity and the aging brain. Arch Neurol. 2005; 62:1545–1548.
crossref
28. Yaffe K. Metabolic syndrome and cognitive disorders: is the sum greater than its parts? Alzheimer Dis Assoc Disord. 2007; 21:167–171.
29. Zhao WQ, Townsend M. Insulin resistance and amyloidogenesis as common molecular foundation for type 2 diabetes and Alzheimer's disease. Biochim Biophys Acta. 2009; 1792:482–496.
crossref
30. Zhao W, Chen H, Xu H, Moore E, Meiri N, Quon MJ, et al. Brain insulin receptors and spatial memory. Correlated changes in gene expression, tyrosine phosphorylation, and signaling molecules in the hippocampus of water maze trained rats. J Biol Chem. 1999; 274:34893–34902.
31. Fernandes ML, Saad MJ, Velloso LA. Effects of age on elements of insulin-signaling pathway in central nervous system of rats. Endocrine. 2001; 16:227–234.
crossref
32. Liu X, Zheng M, Hao Y, Hou L, Zhang S. Effects of Pioglitazone on cognition function and AGEs-RAGE system in insulin resistance in rats. J Shandong Univ (Health Sci). 2008; 46:954–958.
33. Lazarov O, Robinson J, Tang YP, Hairston IS, Korade-Mirnics Z, Lee VM, et al. Environmental enrichment reduces Abeta levels and amyloid deposition in transgenic mice. Cell. 2005; 120:701–713.
crossref
34. Wu L, Zhu W, Pei Y, Qu Z, Tong J, Zhang T, et al. Correlational study between cognitive function and serum cytokine concentration in senile dementia patients. Chin J Clin. 2012; 6:135–138.
35. Hamed SA, Youssef AH, Elserogy YE, Herdan O, Abd-Elaal RF, Metwaly NA, et al. Cognitive function in patients with Type 2 Diabetes Mellitus: Relationship to stress hormone (Cortisol). J Neurol Neurosci. 2013; 4:3.
36. Talbot K, Wang HY, Kazi H, Han LY, Bakshi KP, Stucky A, et al. Demonstrated brain insulin resistance in Alzheimer's disease patients is associated with IGF-1 resistance, IRS-1 dysregulation, and cognitive decline. J Clin Invest. 2012; 122:1316–1338.
crossref
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