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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 22  |  Issue : 4  |  Page : 171-178

Cognitive impairment and reduced antioxidant capacity in patients with type 2 diabetes


Department of Human Physiology, Bayero University, Kano, Nigeria

Date of Submission08-Jul-2018
Date of Acceptance03-Sep-2018
Date of Web Publication29-Nov-2019

Correspondence Address:
Dr. Isyaku Mukhtar Gwarzo
Department of Human Physiology, Bayero University, Kano
Nigeria
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DOI: 10.4103/smj.smj_37_18

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  Abstract 


Background: Type 2 diabetes (T2D) has been linked to mild cognitive impairment (MCI). Increased oxidative stress and a decrease in antioxidant capacity are believed to be one of the pathophysiological mechanisms mediating MCI in T2D. Objective: The aim of this study was to assess MCI and total antioxidant capacity in T2D patients and their nondiabetic controls. Materials and methods: A total of 34 T2D patients attending the diabetic clinic of Murtala Muhammad Specialist Hospital, Kano, between June and December 2017 and age, sex, and level of education matched controls were recruited for the study. MCI was assessed using Montreal cognitive assessment test (MoCA) version 7.3. Serum albumin, total protein, uric acid, bilirubin, and malondialdehyde (MDA) were determined using spectrophotometric method, whereas Vitamins C and E were determined using competitive-ELISA (Elabscience, USA). Data were analyzed on SPSS version 23.0. The value of P ≤ 0.05 was considered statistically significant. Results: Diabetic group had significantly lower MoCA score (U = 216.50, P = 0.001), compared to the controls (19.5 and 26, respectively). MoCA score was influenced by sex (U = 88.0, P = 0.05) and level of education (χ2 =12.826, P = 0.005) among diabetic patients. MoCA score was correlated with serum levels of Vitamin E (ρ = −0.412, P = 0.015), total protein (ρ = −0.359, P = 0.037), and level of education of the diabetic patients (χ2 =14.664, P = 0.002). Diabetic patients had significantly higher serum MDA (U = 238.50, P = 0.001) (0.19 nmol/ml and 0.11 nmol/ml, respectively) and lower serum bilirubin (U = 351.50, P = 0.05) (1.28 mg/dl and 1.68 mg/dl, respectively). Conclusion: There was MCI with median MoCA score of 19.50 among the diabetics. T2D was associated with MCI, increased oxidative stress and reduced antioxidant capacity. Routine screening for MCI should be employed in the management of T2D.

Keywords: Antioxidant capacity, Kano, mild cognitive impairment, oxidative stress, type 2 diabetes


How to cite this article:
Yarube IU, Gwarzo IM. Cognitive impairment and reduced antioxidant capacity in patients with type 2 diabetes. Sahel Med J 2019;22:171-8

How to cite this URL:
Yarube IU, Gwarzo IM. Cognitive impairment and reduced antioxidant capacity in patients with type 2 diabetes. Sahel Med J [serial online] 2019 [cited 2019 Dec 7];22:171-8. Available from: http://www.smjonline.org/text.asp?2019/22/4/171/272140




  Introduction Top


Diabetes mellitus has been described by the World Health Organization as an important public health problem, one of four noncommunicable diseases targeted for action by world leaders.[1] There has been a steady rise in the prevalence of diabetes mellitus globally, with prevalence rising from 108 million people in 1980–422 million people affected in 2014.[1] The rise in the prevalence of the disease appears to be more apparent in developing countries than in developed countries.[2] There is an estimated 7 million people living with diabetes globally yet to be diagnosed and another 79 million who are prediabetic.[3]

In Nigeria, prevalence of diabetes mellitus is estimated to be 3.3% with an age-adjusted comparative prevalence of 2.9%–7.8% in 2017.[4]

Mild cognitive impairment (MCI) is a term used to describe a state of decline in cognitive function that is between normal aging process and dementia, it is considered an important risk factor for dementia.[5]

Reported prevalence of MCI among Type 2 diabetes (T2D) patients varies greatly, it ranges from 5.5% to 7.7% in people over 60 years of age and 15%–41% of these progress to dementia.[5] In another study, a prevalence rate of cognitive dysfunction of 40% was reported among T2D patients in South-East Nigeria.[6]

Various mechanisms have been linked to the pathogenesis of MCI in T2D.[7] Prominent among which are: Hyperglycemia, insulin resistance, oxidative stress, mitochondrial dysfunction, and advanced glycation end products.[8]

There has been debate over the years concerning the exact role of oxidative stress in T2D and its complications. While some believe that it is the primary event leading to T2D and its complications,[8],[9] others believe that it is a secondary event resulting from an overload of metabolic pathways involved in combating reactive oxygen and nitrogen species.[10] Whether oxidative stress is the primary event leading up to the development of T2D and its complications or not, what is now obvious is the overwhelming evidence implicating oxidative stress in the pathogenesis of complications of T2D and MCI.[11],[12],[13],[14] Despite this overwhelming evidence of the deleterious effects of oxidative stress on T2D, one large-scale clinical trial with classic antioxidants failed to demonstrate any benefits to diabetic patients.[15]

The global burden of T2D with its attendant economic consequences calls for concerted effort in developing ways to halt the progression of the disease. MCI, with its propensity to progress to full-blown dementia, will undoubtedly compound the outlook of T2D patients. The aim of this study was to assess the prevalence of MCI and total antioxidant capacity (TAC) in T2D patients attending the diabetic clinic of Murtala Muhammad Specialist Hospital, Kano, Nigeria.


  Materials and Methods Top


Study area and population

The study was conducted at the diabetic clinic of Murtala Muhammad Specialist Hospital, Kano, Nigeria between June and December 2017.

Ethical consideration

Ethical clearance was obtained from the Ethics subcommittee of health operational research of unit of Kano state ministry of health on January 5, 2017 with certificate number MOH/Off/797/T.I/279.

Sample size determination

The sample size was determined using computer software for power and sample size determination according to Lenth,[16] after a pilot study. A minimum sample size of 32 was obtained.

Study design and sampling technique

The study design was descriptive, analytical study. A total of 34 T2D patients (17 males and 17 females) and age, sex, and level of education matched controls were recruited using systematic sampling technique. Selection of patients was based on inclusion and exclusion criteria.

Inclusion criteria

  • All male and female patientsd with T2D of <65 years of age who signed written informed consent for the study
  • Healthy nondiabetic patients matched for age, sex, and level of education were included as controls.


Exclusion criteria

  • Patients 65 years and above
  • Patients with history or evidence of neuropsychiatric illness
  • Patients who declined to sign consent form
  • History or evidence of recent smoking or alcohol usage within the last 2 years
  • Patients with evidence of on-going depression.


Data collection

A data capture form was used to obtain sociodemographic information of the participants. All the subjects were screened for depression using Beck's depression inventory-II. All patients with BDI II score of 19 and above were excluded from the study.[17]

Montreal cognitive assessment (MoCA) test version 7.3 was used to assess cognitive function. The total possible score is 30 points; a score of 26 and above is considered normal while a score of <26 is considered MCI. The test was administered according to the author's guidelines and instructions.[18]

Laboratory procedures

Samples for determination of various parameters were collected between 7 and 8 am after an overnight fast using plain bottles. Serum was extracted from the samples after centrifuging at 4100 g for 5 min and stored at −20°C. Serum uric acid, bilirubin, total protein, albumin, and malondialdehyde (MDA) were determined by enzymatic methods described by Kabasakalian et al.,[19] Jendrassik and Grof [20] Kingsley,[21] Doumas et al.,[22] and Ohkawa et al.,[23] respectively. It involves the use of appropriate reagent(s) for each of the parameter which gave characteristic color that was measured using spectrophotometry. 721-VIS Spectrophotometer (Yangzhou wandong Medical Co., Ltd. China) was used to determine absorbances for each of the parameters. The actual concentration of each parameter was then manually calculated from the absorbance and concentration of the standard. Competitive-ELISA kits (Elabscience, Houston, Texas, USA) were used to determine serum Vitamins C and E using VERSAmax™ Tunable Microplate Reader 0112 (Molecular Devices Corporation, CA, USA).

Data analysis

Data were analyzed using Statistical Package for Social Scientists version 23.0 (IBM Corp., Armonk, NY, USA),[24] and expressed as median, frequencies, and percentages. Nonparametric statistics were used in the analysis after normality tests. Mann–Whitney U-test and Kruskal–Wallis tests were used to compare medians between diabetic and nondiabetic groups. The significance of Spearman's correlation coefficient was determined to assess the association between cognitive function and continuous variables. Values of P ≤ 0.05 were considered statistically significant.


  Results Top


Normality test

Majority of the characteristics in both diabetic and nondiabetic groups were not normally distributed (P < 0.05). This informed the use of nonparametric statistics to analyze the data – [Table 1].
Table 1: Normality tests for participants' clinico-laboratory characteristics

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Sociodemographic characteristics of the participants

Median age of the participants in the diabetic and nondiabetic groups was 55 (28–65) years. The participants comprised 17 males and 17 females in each of the groups. There was no statistically significant difference in age (U = 574.00, P = 0.961) or sex (U = 578.00, P = 1.00) composition of the two groups. Majority (91.2%) of the diabetic participants were diagnosed at least a year before this study. Details of other sociodemographic characteristics are presented in [Table 2].
Table 2: Sociodemographic characteristics of the participants

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Cognitive and anti-oxidant characteristics of the participants

The clinico-laboratory findings of diabetic and nondiabetic patients are presented in [Table 3]. The diabetic patients had MCI as indicated by a median MoCA score of 19.50; while the controls had normal cognitive function as adjudged by a median MoCA score of 26.0. The difference in MoCA score of the two groups was statistically significant (U = 216.50, P = 0.001).
Table 3: Clinico-laboratory characteristics of the diabetic and nondiabetic control subjects

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The diabetic group had significantly higher (U = 238.50, P = 0.001) MDA concentrations compared to the controls (0.19 and 0.11 nmol/ml, respectively). This signifies higher levels of products of lipid peroxidation among the diabetic group compared with the nondiabetic group and implies that there were more oxidative stress and less anti-oxidant capacity among the diabetic group compared to the nondiabetic.

The diabetic group had lower median values of serum bilirubin compared with the non-diabetic control (1.28 mg/dl and 1.68 mg/dl, respectively) and the difference was statistically significant (U = 351.50, P = 0.050). However, the values of bilirubin were above normal (0.3 mg/dl – 1.2 mg/dl) in both groups.[25] This suggests full anti-oxidant capacity in the diabetic and controls based on this parameter.

Serum uric acid levels in the diabetic and non-diabetic groups (0.32 mg/dl for each group) although not significantly different (U = 443.50, P = 0.099), were below normal limits (2.6 mg/dl–8.2 mg/dl)[26] and hence indicate increased oxidative stress and deceased anti-oxidant capacity in the two groups.

There was no statistically significant difference in the median values of serum Vitamin C and E between the diabetic group and their non-diabetic controls (U = 446.50, P = 0.107; U = 453.00, P = 0.125, respectively). This implies no oxidative stress and normal anti-oxidant capacity as assessed using these parameters.

The diabetic group had significantly higher median values of serum albumin and total protein compared to the non-diabetic control (U = 248.50, P = 0.001; U = 364.50, P = 0.001, respectively). Although diabetic group had higher serum albumin and total protein values compared to the control, both values were within normal limits (3.6 mg/dl–7.64 mg/dl; 5.84 g/dl–10.38 g/dl, respectively)[27] and hence did not point to oxidative stress and suggests normal antioxidant capacity in both groups.

Overall, the assessment of antioxidant markers suggests a moderate decrease in antioxidant capacity in the diabetic group as indicated by an increase in MDA level and a decrease in the uric acid level below normal values. Whereas, there was only a mild decrease in antioxidant capacity in the control group as indicated by decreased serum uric acid values below normal.

Influence of characteristics of the diabetic patients on montreal cognitive assessment test score

Results of the influence of MoCA score on socio-demographic characteristics are presented in [Table 4]. There was a significant influence of sex in the diabetic group (U = 88.00, P = 0.05) on MoCA score, with males having a score of 20 and females having a score of 19. Furthermore, MoCA score was also influenced by the level of education among the diabetics (χ2 = 12.83, P = 0.005). Among the diabetics, those with secondary education had the highest score of 28, followed by those with primary and informal education with 21 and 18, respectively.
Table 4: Variation of the Montreal cognitive assessment score according to the sociodemographic characteristics of the diabetic subjects

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Cognitive score was not influenced by other socio-demographic characteristics of the diabetics- age (U = 36.00, P = 0.075), ethnicity (χ2 = 0.144, P = 0.931), place of residence (χ2 = 0.194, P = 0.908) marital status (χ2 = 4.158, P = 0.125), and duration of diabetes (χ2 = 0.793, P = 0.851).

Relationship of montreal cognitive assessment test score with characteristics of the diabetic patients

Level of education of the diabetics was significantly associated with MoCA score (χ2 = 14.664, P = 0.002) as shown in [Table 5]. There was a significant negative correlation between serum total protein and MoCA score (r = −0.359, P = 0.037), meaning that as serum total protein decreases MoCA score increases. Serum Vitamin E was negatively correlated with MoCA score (r = −0.412, P = 0.015), implying that as serum Vitamin E decreases MoCA score increases.
Table 5: Relationship of Montreal cognitive assessment score with characteristics of diabetic patients

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  Discussion Top


The diabetic group had MCI while the nondiabetic group had a normal cognitive function. T2D has been linked with the development of MCI by many studies.[28],[29],[30],[31] A number of mechanisms have been proposed to explain the pathogenesis of MCI in T2D. At the heart of these mechanisms is sustained hyperglycemia and insulin resistance.[32] Persistent hyperglycemia, through diversion of excess glucose to polyol pathway, lead to depletion of NADPH which is required for regeneration of antioxidant enzymes and hence leading to the production of free radicals.[33] Hyperglycemia also causes nonenzymatic glycation of protein leading to the generation of advanced glycation end products and overflow of electrons from mitochondria in the electron transport chain.[34] These processes lead to increased production of reactive oxygen and nitrogen species with subsequent micro- and macrovascular damages, especially in the brain.[35] Cerebral atrophy, white matter changes, and lacunar infarcts have been revealed in the brain of diabetic patients with cognitive impairment on MRI.[36],[37],[38] The finding of this study on cognitive function agrees with previous studies that reported MCI in T2D patients compared to nondiabetic controls.[31],[32],[33],[34],[35],[36],[37],[38],[39],[40],[41]

However, while the majority of the diabetic patients had impaired cognitive function, about two third of the nondiabetic controls also had the same condition. This implies that, apart from diabetes other factors could also account for the decline in cognitive function observed. In this study, cognitive function varied according to levels of education of the participants. Over half of the participants in this study in both diabetic and nondiabetic groups had no formal education. Formal education is likely to provide for better socioeconomic status, improved quality of life, and better social interactions. All these are associated with the better cognitive development and slow rate of cognitive decline.[42],[43]

Cognition also varied according to sex with male diabetic having higher score compared to their female counterparts. Women in this part of the world are more likely to be less formally educated and socioeconomically less empowered than their male counterparts.[44] They are also more likely to live without a partner at old age and hence without emotional, social, and economic support.[44] These could be the reasons for their lower cognitive scores compared to men.

This study found statistically significant elevation in serum MDA level among diabetic patients compared to their non-diabetic controls. This indicates increased oxidative stress activity among the diabetic patients compared to the non-diabetic controls. This is in agreement with previous researchers who reported increase in serum MDA levels among diabetic patients compared to their nondiabetic controls.[45],[46] Oxidative stress causes increase in serum level of products of lipid peroxidation (like MDA), protein glycation, and nucleic acid fragmentation on one hand and depletion of enzymatic and small molecule antioxidants on the other.[47] There were statistically significant lower serum bilirubin values among diabetic patients compared to the nondiabetic control. Depletion of bilirubin as a small molecule antioxidant among the diabetic patients implies increased oxidative stress. This is in agreement with what was reported by other researchers.[48],[49] Bilirubin is an end product of hemoglobin metabolism which is produced from the reduction of biliverdin by biliverdin reductase in the liver.[49] Recent evidence suggest that bilirubin is a powerful endogenous antioxidant.[50] It scavenges free radicals, prevent free radical-mediated lipid peroxidation, and inhibit tumor necrosis factor mediated-vascular endothelial injury.[49],[50]

There was no statistically significant difference in serum uric acid values between diabetic and non-diabetic controls. However, serum uric acid levels in both groups were lower than the normal limits. This indicates increased oxidative stress and decreased antioxidant capacity in both groups. Serum uric acid is the second main extracellular antioxidant and being a free radical scavenger, its serum level should fall in conditions of increased free radical generation.[48]

There were statistically significant higher levels of serum albumin and total protein among diabetic patients compared to their nondiabetic controls. However, despite the apparent increase, the values in both diabetic and nondiabetic groups were within normal limits. This implies that serum albumin and total protein in both groups did not point to oxidative stress. Albumin and plasma proteins are potent endogenous anti-oxidants. Increase in the generation of free radicals would naturally lead to depletion of antioxidants such as serum albumin and serum total protein.[48],[51] Albumin is a plasma protein synthesized and secreted by the liver. It acts as an antioxidant by binding to and neutralizing the deleterious effects of free radicals.[52]

There was no statistically significant difference in serum Vitamins C and E among diabetic and nondiabetic groups, and the values were within normal limits. This implies that Vitamins C and E values in both groups did not point to oxidative stress. Both Vitamins C and E act as free radical scavengers. They bind to and inactivate free radical and thereby rendering them harmless.[53] Therefore, in conditions of increased oxidative stress activity like diabetes, the serum level of these vitamins decreases.

Over the years, oxidative stress has been reported to play a role in the development of diabetes and its complications.[54] It is said to occur when there is an imbalance between the prooxidants and antioxidants in favor of the former.[8] The reactive oxygen and nitrogen species generated in the process attack and damage biological molecules leading to lipid peroxidation, protein glycation, and nucleic acid fragmentation.[8],[55],[56] This leads to an increase in serum products of lipid peroxidation, protein glycation, and nucleic acid fragmentation and depletion of both enzymatic and nonenzymatic antioxidants.

Because of the heterogeneous nature of small molecule antioxidants, it is often difficult to conclude antioxidant status of an individual based on a single molecule. A more objective measure that takes in to account the overall contribution of all the small molecule antioxidants is called TAC. It is used to conclude the overall antioxidant status.[57] T2D is associated with increased generation of reactive oxygen and nitrogen species. These reactive species are scavenged by small molecule antioxidants leading to their depletion in the extracellular fluid. This study has demonstrated a significant increase in serum MDA and decrease in serum uric acid but no change in serum albumin, total protein, Vitamins C and E among diabetic group compared to the non-diabetic group. This indicates increased oxidative stress and decreased anti-oxidant capacity among diabetic group compared to the nondiabetic group.


  Conclusion Top


It was concluded that the diabetic patients had MCI with median MoCA score of 19.50. The MCI was influenced by sex and level of education; and was associated with education, serum levels of Vitamin E and total proteins. There was a moderate decrease in antioxidant capacity among the diabetics as indicated by an increase in MDA level and a decrease in the uric acid level below normal values.

Acknowledgment

We would like to acknowledge the Directorate of Research, Innovation, and Partnership of Bayero University, Kano for a grant to carry out this work.

Financial support and sponsorship

We received a grant from Directorate of Research, Innovation, and Partnership of Bayero University, Kano, for this work.

Conflicts of interest

There are no conflicts of interest.



 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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