Abstract
Objectives
Malnutrition of vitamin A (retinol) and vitamin E (α-tocopherol, α-TOH) was observed in type 2 diabetes mellitus (T2DM) or dementia patients. However, how these vitamins affect cognitive function of subjects with T2DM was seldom reported. The objective of this study was to determine the association of circulating retinol and α-TOH with cognition in aging subjects with T2DM.
Methods
A total of 448 T2DM subjects and 448 age, gender and education matched control subjects (aged 55–75 years) were included in the study. Demographic characters of the participants were collected. Food frequency questionnaire (FFQ) method was used to collect dietary intake information. To assess the status of cognition, the MoCA test was used. Circulating retinol and α-TOH levels were compared between T2DM and non-T2DM subjects. Correlation of circulating retinol and α-TOH levels with cognitive function was analyzed in T2DM subjects. The effect of serum retinol and α-TOH levels on the risk of MCI in T2DM patients was explored.
Results
We found that T2DM-MCI subjects demonstrate lower serum retinol level than T2DM-nonMCI subjects (P < 0.01). Serum retinol level was positively correlated to cognitive function in T2DM subject (P < 0.05). T2DM subjects with higher circulating retinol level demonstrate higher cognitive scores in visual and executive, attention, language, memory and delayed recall domains (P < 0.05).
Conclusion
Diminished circulating retinol predicts an increased risk of MCI in T2DM patients. Our findings provide suggestions that optimal retinol nutritional status might benefit cognition and decrease the risk of MCI in aging subjects with T2DM.
Key words: Retinol, α-tocopherol, type 2 diabetes mellitus, cognition
Introduction
Dementia has become a global public health problem. Current data estimated that 131.5 million people are expected to suffer from dementia worldwide by 2050 (1). Alzheimer's disease (AD) is the most common form of dementia, which contributing approximately 70% of all dementia cases (2). However, the underlying mechanisms of AD remain unclear. AD and type 2 diabetes mellitus (T2DM) are highly prevalent chronic disease in aging population. Studies have shown that there are many similar patho-physiological characteristics in AD and T2DM, such as insulin resistance, abnormal glucose metabolism and enhanced oxidative stress in peripheral tissues (3, 4, 5). Additionally, brain insulin resistance was suggested to involve in the pathogenesis of AD through affecting glucose metabolism, amyloid-β (Aβ) deposition, and tau processing (6, 7, 8, 9). Therefore, insulin resistance was suggested as one of the potential mechanism linking T2DM with AD, and may be a potential target for the clinical treatment of AD. Mild cognitive dysfunction (mild cognitive impairment, MCI), as the early stage of AD, is preventable. To explore the relationship between T2DM and MCI in the elderly will help to achieve timely clinical diagnosis and intervention of AD, and therefore reduce the prevalence of AD throughout the world.
Increasing number of studies has confirmed the correlation between vitamin E (VE) and vitamin A (VA) deficiency and the risk of insulin resistance and T2DM. Recent studies have found that VA deficiency is closely related to insulin resistance and lipid metabolism disorders (10). Decreased serum VA level in T2DM patients have been indicated by population-based large-scale investigations (11). The influence of VE on the antioxidant status and glycemic index of T2DM patients was also reported by previous studies (12). Significant decrease of serum VE level was found in subjects with T2DM, and serum VE status was reported negatively correlating with insulin resistance and oxidative stress in T2DM (13). All these results indicated that optimal VA and VE nutritional status are crucially important in reducing the risk of T2DM.
VA and VE are both essential micro-nutrient for normal brain function. The deficiency of VA was reportedly associated with cognitive decline and increased risk of MCI in the elderly (14). Clinical studies also found that patients with AD demonstrated lower plasma or cerebrospinal fluid VA and beta-carotene concentrations; however, VA dietary intervention could efficiently delay the progression of dementia (15). Moreover, lower daily intake of VE may also potentially contribute to neuro-degeneration, as well as an increased risk of AD [16]. Progressive neurologic disorders have been observed in the patients with VE deficiency (17). It was reported that the AD patients demonstrate lower plasma VE level than non-demented controls (18, 19). These results highlight the essential role of VA and VE in maintaining normal cognitive function in aging population.
Taken together, the current evidences indicate that the elderly with VA or VE deficiency and T2DM may be at high risk of MCI or AD. However, to date, few study has explore the relationship between circulating VA and VE status and cognition in subjects with T2DM. Therefore, this study aimed to investigate the relationship between circulating vitamin level and global cognitive function, as well as the different domains of cognitive performances in aging subjects with T2DM.
Methods
Participants
A total of 448 patients (162 males and 286 females) with T2DM and 448 age, gender and education level matched normal control subjects (162 males and 286 females) were recruited from community health service center of Nanyuan and Wulituo (Beijing, China). Diabetes mellitus were diagnosed according to the criteria of World Health Organization (1999), including one or more of the following status: (1) for a person with severe symptoms, a fasting blood glucose (FBG) ≥ 7mmol/L, a random blood glucose ≥ 11.1mmol/L or a 2h blood glucose level ≥ 11.10mmol/L when a 75g oral glucose tolerance test was required; (2) for the asymptomatic patients, at least one additional blood glucose over the diagnostic cutoff value was essential (20). Exclusion criteria of the participants were: presence of acute diabetic complications, including diabetic ketoacidosis, hyperosmolar nonketotic diabetic coma, diabetic lactic acidosis, and severe hypoglycemia; severe diseases or conditions known to affect cognitive function (e.g., inflammatory diseases, recent history of heart or respiratory failure, chronic liver disease or renal failure, malignant tumors, a recent history of alcohol abuse, history of cerebral apoplexy or cerebral infarction); history of alcoholism or drug abuse within 2 months. The subjects with AD, Parkinson's disease (PD), long-term frequency intake of anti-depressants and medication acting on central nervous system, or those unable to finish the cognition tests were also excluded from the study.
Anthropometric Measurements and Socio-demographic Variables
Anthropometric parameters (height and weight) of the participants were measured. Body mass indices (BMI) were calculated as weight (kg)/height (m)2. Demographic characteristics information (e.g., age, gender and education), lifestyle factors [e.g., smoking, alcohol drinking, physical activity, reading habit, and housekeeping, the duration of T2DM, current treatment for diabetes, AD family history and medical history of chronic diseases were collected by self-administered questionnaires adopted from our previous studies (21, 22). Educational level was assessed as the highest level attained and classified into six categories (illiterate, primary school, junior high school, high school, junior college, undergraduate and above).
Dietary Survey
Participants were visited at a community health service center by specifically trained nutritionists and registered nurses. A validated semi-quantitative food frequency questionnaire (FFQ) was used to assess the habitual consumption of 10 food groups (fruit and vegetable, whole grain, legume, red meat, poultry, fish, eggs, nuts, cooking oil, milk, comprising 35 items in total). This questionnaire was adopted from a questionnaire used for the Dietary Investigation of Chinese Residents, which was organized by the Chinese Nutrition Society (CNS). The food intake survey documented the information, including the consumption frequencies (daily and weekly) and the amount of foods consumed.
Cognitive Tests
Global cognitive function was assessed with the Beijing version of Montreal Cognitive Assessment (MoCA) by well-trained medical doctors from the community health service center. The MoCA test is an extensively used cognitive screening tool with high sensitivity and specificity for early detection of MCI, which consists of seven cognitive domains including visual-spatial and executive ability, naming, attention, abstraction, language, delayed memory recall and orientation functions. According to a previous study conducted in elderly Chinese population, the cut-off points used for MCI diagnosis were as follows: 13/14 for individuals with no formal education, 19/20 for individuals with 1 to 6 years of education, and 24/25 for individuals with 7 or more years of education. The cut-offs above were shown to be sensitive and efficient in the diagnosis of MCI in elderly Chinese population (23).
Measurement of Plasma Parameters, Vitamin Levels and ApoE genotyping
After a 12h fasting, venous blood samples were extracted and centrifuged in lithium heparin tubes at 3000rpm for 15min at 4°C. Serum glucose (GLU), triglyceride (TG) and total cholesterol (TC) were measured by an ILAB8600 clinical chemistry analyzer (Instrumentation Laboratory Lexington, WI, USA). High density lipoprotein cholesterol (HDL-c) was determined by using a commercially available assay from Instrumentation Laboratory (Lexington, WI, USA). Low density lipoprotein cholesterol (LDL-c) was calculated using the Friedewald formula (24). All samples of each subject were analyzed within a single batch, and the inter-assay coefficients of variation (CV) for all determinations were less than 5%. Serum retinol and α-tocopherol (α-TOH) concentrations were measured by reverse phase high-performance liquid chromatography (Waters Chromatograph) simultaneously as previously described (25).
DNA was extracted from frozen peripheral blood using the Wizare genomic DNA purification kit (Promega, Madison, WI, USA). ApoE genotypes were determined by Polymerase Chain Reaction (PCR) amplification and Restricted Fragment Length Polymorphism (RFLP) analysis according to the method described by Hixson (26). For the purpose of quality control of the genotyping, 20% of DNA samples were dependably genotyped again by different operators.
Statistical Analyses
Data was analyzed with the software SPSS 19.0 (Chicago, IL, USA). Continuous variables were presented as means ± standard deviation (SD) or mean (95% confidence interval, CI). Gender, smoking, alcohol drinking, physical activity, AD family history, reading habit and housekeeping were presented as categorical variables. Chi-square test was used for the comparison of binary categorical variables difference between groups. Partial correlation analysis was used to explore the relationship between serum vitamins (α-TOH and retinol) levels and cognitive performance. Participants were first classified according to MCI and non-MCI groups. The demographic characters, circulating parameters and diet were compared. General linear model (GLM) was used to compare the means of the detected parameters and vitamin levels. The following putative confounding factors were included in the analyses when comparing serum parameters: age, gender, BMI, physical activity, smoking and alcohol drinking. For cognition analysis, we stratified the participants according to quartile of circulating vitamin levels and factors including gender, age, BMI, education, reading habit, housekeeping, physical activity, AD family history, hyperlipidemia, duration of T2DM, current treatment for diabetes, and ApoE genotype were adjusted. Logistic regression model was run to evaluate the risk of cognitive impairment. We adjusted for demographic variables including age, gender, education levels, smoking, alcohol drinking, reading habit, housekeeping, hyperlipidemia, the duration of T2DM, current treatment for diabetes, AD family history and ApoE genotype in the model.
Statistical significance was set at P < 0.05.
Results
Demographic Characters of Participants
Totally, 448 T2DM patients and 448 age, gender and education level matched normal control subjects were included in data analysis. As shown in Table 1, the T2DM patients and control subjects have similar demographic characters including BMI, lifestyle, AD family history and ApoE genotypes (P > 0.05). The percentage of subjects with hyperlipidemia was higher in subjects with T2DM (57.6%) than that in control subjects (40.8%) (P < 0.01).
Table 1.
Demographics of the participants
| Demographic character | Normal (n = 448) | T2DM (n = 448) | P value |
|---|---|---|---|
| Age, mean ± SD | 65.62 ± 6.27 | 65.65 ± 6.32 | 0.934 |
| BMI (kg/m2), mean ± SD | 25.35 ± 3.60 | 25.43 ± 3.59 | 0.734 |
| Education, n (%) | 0.769 | ||
| Illiterate | 26 (5.8) | 28 (6.3) | |
| Primary school | 79 (17.7) | 80 (17.9) | |
| Junior high school | 202 (45.2) | 201 (45.0) | |
| High school | 108 (24.2) | 107 (23.9) | |
| Junior college | 21 (4.7) | 21 (4.7) | |
| Undergraduate and above | 11 (2.5) | 10 (2.2) | |
| Life style | |||
| Smoking, n (%) | 0.299 | ||
| Yes | 360 (80.4) | 75 (16.7) | |
| No | 88 (19.6) | 373 (83.3) | |
| Alcohol drinking, n (%) | 0.662 | ||
| Yes | 138 (30.8) | 131 (29.2) | |
| No | 310 (69.2) | 317 (70.8) | |
| Physical activity, n (%) | 0.277 | ||
| Never | 39 (8.7) | 38 (8.5) | |
| 1–3 times/week | 60 (13.4) | 50 (11.2) | |
| 4–5 times/week | 48 (10.7) | 39 (8.7) | |
| everyday | 300 (67.1) | 321 (71.7) | |
| Reading habit, n (%) | 0.224 | ||
| Yes | 201 (44.9) | 182 (40.6) | |
| No | 247 (55.1) | 266 (59.4) | |
| Housekeeping, n (%) | 0.119 | ||
| Yes | 417 (93.1) | 403 (90.0) | |
| No | 31 (6.9) | 45 (10.0) | |
| ApoE genotype | 0.307 | ||
| E3 | 298 (66.5) | 314 (71.2) | |
| E2 | 67 (15.0) | 59 (13.4) | |
| E4 | 83 (18.5) | 68 (15.4) | |
| AD family history | 0.713 | ||
| Yes | 38 (8.5) | 34 (7.6) | |
| No | 410 (91.5) | 414 (92.4) | |
| Hyperlipidemia | < 0.01 | ||
| Yes | 183 (40.8) | 258 (57.6) | |
| No | 265 (59.2) | 190 (42.4) | |
| MCI | 0.386 | ||
| Yes | 132 (29.5) | 145 (32.4) | |
| No | 316 (70.5) | 303 (67.6) | |
BMI, body mass index; ApoE, apolipoprotein E; T2DM: type 2 diabetes mellitus; AD: Alzheimer's disease; MCI: mild cognitive impairment. Demographic characteristics including age and BMI were compared by using t- tests; gender, education level, lifestyle and ApoE allele frequencies were compared by using Chi-square test. P < 0.05 was considered as significance.
Serum Parameters in Normal and T2DM Subjects
According to the MCI diagnostic criteria, 145 patients with T2DM had MCI, and 132 non-T2DM control subjects had MCI. As shown in Table 2, T2DM patients demonstrated increased serum GLU level (P < 0.01). Compared to normal subjects, T2DM subjects have lower serum TC, HDL-c and LDL-c levels (P < 0.05).
Table 2.
Serum parameter of normal or T2DM participants
| Serum parameters | Normal (n = 448) | T2DM (n = 448) | P value | ||
|---|---|---|---|---|---|
| Non-MCI (n =316) | MCI (n =132) | Non-MCI (n =303) | MCI (n =145) | ||
| GLU (mmol/L) | 5.33 (5.11, 5.56) | 5,51 (5.17, 5.85) | 7.32 (7.09, 7.54){suab} | 7.67 (7.34, 7.99){suab} | < 0.01 |
| TC (mmol/L) | 5.04 (4.93, 5.16) | 5.21 (5.03, 5.38) | 4.71 (4.60, 4.83){suab} | 4.87 (4.70, 5.04){sub} | < 0.01 |
| TG (mmol/L) | 1.92 (1.76, 2.08) | 1.85 (1.60, 2.10) | 1.89 (1.73, 2.05) | 1.90 (1.66, 2.13) | 0.97 |
| HDL-c (mmol/L) | 1.40 (1.36, 1.43) | 1.49 (1.44, 1.54){sua} | 1.33 (1.30, 1.36){suab} | 1.41 (1.36, 1.46){subc} | < 0.01 |
| LDL-c (mmol/L) | 3.05 (2.95, 3.15) | 2.97 (2.82, 3.13) | 2.82 (2.72, 2.92)a | 2.66 (2.52, 2.81){suab} | < 0.01 |
| HDL/LDL | 0.50 (0.48, 0.53) | 0.55 (0.51, 0.59){sua} | 0.52 (0.50, 0.55) | 0.59 (0.55, 0.62){suac} | < 0.01 |
| Retinol (µg/ml) | 0.61 (0.59, 0.63) | 0.54 (0.51, 0.57){sua} | 0.59 (0.57, 0.61){sub} | 0.50 (0.47, 0.53){suac} | < 0.01 |
| Retinol/TG+TC (mg/mmol) | 0.09 (0.09, 0.10) | 0.08 (0.08, 0.09){sua} | 0.10 (0.09, 0.10){sub} | 0.08 (0.07, 0.08){suac} | < 0.01 |
| α-TOH (µg/ml) | 11.75 (11.34, 12.16) | 11.80 (11.17, 12.43) | 11.40 (10.98, 11.81) | 12.22 (11.62, 12.82) | 0.17 |
| α-TOH/TG+TC (mg/mmol) | 1.71 (1.66, 1.75) | 1.72 (1.65, 1.78) | 1.77 (1.72, 1.81) | 1.84 (1.77, 1.90){suab} | 0.01 |
| α-TOH/retinol | 21.25 (20.13, 22.38) | 24.18 (22.47, 25.88){sua} | 21.44 (20.32, 22.57){sub} | 26.79 (25.16, 28.43){suabc} | < 0.01 |
Data were expressed as mean (95% CI). Glu, glucose; HDL-c, high density lipoprotein cholesterol; LDL-c, low density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; T2DM: type 2 diabetes mellitus; MCI, mild cognitive impairment. General Linear Model (GLM) was used for data serum parameters comparison. During the comparison of serum parameters between groups, factors including age, BMI, education level, smoking, alcohol drinking, physical activity, the duration of T2DM and current treatment for diabetes were adjusted. P < 0.05 was considered as significance.
MCI subjects demonstrated higher serum HDL-c and HDL/LDL levels, but lower retinol and lipid-adjusted retinol levels than non-MCI subjects (P < 0.01). The T2DM subjects with MCI (T2DM-MCI subjects) demonstrated the lowest serum retinol levels (P < 0.01). Increased serum lipid-adjusted α-TOH level was observed in T2DM-MCI subjects (P < 0.01). MCI subjects showed higher serum α-TOH/retinol ratio than non-MCI subjects (P <0.01); and the highest serum α-TOH/retinol ratio was observed in T2DM-MCI subjects (P < 0.01).
Dietary Intake of Normal and T2DM Subjects
T2DM patients have lower daily fruit intake than normal subjects (P < 0.01). The T2DM-MCI subjects have the lowest daily vegetable, fruit and vegetable and fish intake, but the highest daily milk and egg intakes (P < 0.05). MCI subjects have higher daily whole grain intakes than non-MCI subjects (P < 0.05). The highest daily milk and egg intake was observed in T2DM-MCI subjects (P < 0.05) (Supporting information Table 1).
Correlation Coefficients between Serum Vitamins and Cognition
Significant correlation between serum retinol, lipid-adjusted retinol levels with cognitive function in T2DM subjects was observed. Circulating retinol level was positively correlated with visual and executive (r = 0.19, P < 0.01), attention (r = 0.12, P < 0.05), language (r = 0.22, P < 0.01), memory and delayed recall (r = 0.20, P < 0.01) abilities and total MoCA score (r = 0.25, P < 0.01). Correlation of circulating α-TOH level with cognitive performance was observed in T2DM subjects (P < 0.05). However, after adjusting α-TOH level with lipids (TG+TC), the correlation became insignificant (P > 0.05). Serum α-TOH/retinol ratio was negatively correlated with visual and executive (r = −0.18, P < 0.01), attention (r = −0.15, P < 0.01), language (r = −0.15, P < 0.01), memory and delayed recall (r = −0.16, P < 0.01) abilities and total MoCA score (r = −0.24, P < 0.01) (Supporting information Table 2).
Serum Parameters and Cognition According to Serum Retinol Level in T2DM Subjects
The participants were categorized according to the quartile of lipid-adjusted serum retinol level, and then the difference of serum parameters and cognitive function were compared. As shown in Table 3, subjects with Q1 level of serum retinol demonstrated the highest serum GLU, TC, TG and HDL-c levels (P < 0.05). Following the increase of serum retinol status, serum GLU, TC, TG, HDL-c, α-TOH levels and α-TOH/retinol ratio exhibited a decreased trend (P < 0.05). The lowest serum α-TOH level and α-TOH/retinol ratio were observed in subjects with Q4 level of serum lipid-adjusted retinol (P < 0.01).
Table 3.
Serum parameters and cognition according to lipids adjusted retinol level in subjects with T2DM (n = 448)
| Parameters and cognition | Retinol/TG+TC | P value | |||
|---|---|---|---|---|---|
| Q1 (n = 115) | Q2 (n = 110) | Q3 (n = 112) | Q4 (n = 111) | ||
| Serum parameters | |||||
| GLU (mmol/L) | 8.09 (7.61, 8.57) | 7.46 (6.97, 7.94) | 7.20 (6.72, 7.68){sua} | 6.97 (6.49, 7.46){sua} | 0.011 |
| TC (mmol/L) | 5.30 (5.11, 5.49) | 4.99 (4.80, 5.18)a | 4.70 (4.51, 4.89)* | 4.19 (4.00, 4.39){suabc} | < 0.01 |
| TG (mmol/L) | 2.95 (2.66, 3.24) | 1.79 (1.50, 2.08)a | 1.62 (1.33, 1.91){sua} | 1.40 (1.11, 1.69){sua} | < 0.01 |
| HDL-c (mmol/L) | 1.41 (1.35, 1.47) | 1.41 (1.35, 1.47) | 1.33 (1.27, 1.39) | 1.30 (1.24, 1.36)* | 0.018 |
| LDL-c (mmol/L) | 2.85 (2.67, 3.02) | 2.79 (2.62, 2.97) | 2.84 (2.67, 3.02) | 2.62 (2.44, 2.80) | 0.242 |
| HDL/LDL | 0.54 (0.50, 0.58) | 0.56 (0.52, 0.61) | 0.54 (0.50, 0.58) | 0.55 (0.50, 0.59) | 0.813 |
| α-TOH (µg/ml) | 13.88 (13.15, 14.60) | 12.44 (11.71, 13.17)a | 11.39 (10.67, 12.11){sub} | 9.77 (9.04, 10.49) | < 0.01 |
| α-TOH/TG+TC (mg/mmol) | 1.71 (1.63, 1.80) | 1.87 (1.79, 1.95)a | 1.85 (1.77, 1.93) | 1.78 (1.70, 1.86) | 0.030 |
| α-TOH/retinol | 35.37 (33.99, 36.75) | 26.10 (24.71, 27.48)a | 19.24 (17.87,20.61){suab} | 13.55 (12.17, 14.93){suabc} | < 0.01 |
| Cognition | |||||
| MocA Score | 22.73 (21.98, 23.48) | 22.97 (22.20, 23.74) | 24.67 (23.92, 25.43)* | 25.52 (24.75, 26.29)* | < 0.01 |
| Visual and executive | 3.33 (3.10, 3.56) | 3.49 (3.26, 3.73) | 3.77 (3.54, 4.00){sua} | 3.95 (3.72, 4.19)* | 0.002 |
| Naming | 2.83 (2.76, 2.91) | 2.83 (2.76, 2.91) | 2.89 (2.82, 2.97) | 2.94 (2.86, 3.02) | 0.197 |
| Attention | 5.09 (4.88, 5.29) | 5.17 (4.96, 5.38) | 5.46 (5.25, 5.66){sua} | 5.55 (5.34, 5.76)* | 0.006 |
| Language | 1.81 (1.65, 1.97) | 1.85 (1.69, 2.02) | 2.09 (1.93, 2.26)* | 2.15 (1.98, 2.31)* | 0.012 |
| Abstraction | 1.38 (1.24, 1.51) | 1.44 (1.30, 1.58) | 1.62 (1.48, 1.76){sua} | 1.47 (1.33, 1.61) | 0.092 |
| Memory and delayed recall | 2.49 (2.21, 2.77) | 2.34 (2.06, 2.63) | 2.75 (2.47, 3.03) | 3.21 (2.92, 3.50){suabc} | < 0.01 |
| Orientation | 5.79 (5.66, 5.91) | 5.76 (5.64, 5.89) | 5.85 (5.73, 5.98) | 5.85 (5.72, 5.98) | 0.724 |
Data were expressed as mean (95% CI). Glu, glucose; HDL-c, high density lipoprotein cholesterol; LDL-c, low density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; α-TOH: α-tocopherol; T2DM: type 2 diabetes mellitus. General Linear Model (GLM) was used for data serum parameters and cognition comparison. During the comparison of serum parameters and cognition between groups, factors including age, BMI, education level, smoking, alcohol drinking, physical activity, reading habit, housekeeping, hyperlipidemia, the duration of T2DM, current treatment for diabetes, AD family history and ApoE genotype were adjusted. P < 0.05 was considered as significance.
Cognition of the T2DM subjects exhibited an increased trend following the increase of serum retinol level. The subjects with Q4 level of serum retinol have the highest global cognition (total MoCA score) and the highest cognitive scores in visual and executive, attention, language, memory and delayed recall domains (P < 0.05).
Serum Parameters and Cognition According to Serum α-TOH Level in T2DM Subjects
Following the increase of serum lipid-adjusted α-TOH level, TC, TG and LDL-c exhibited a decreased trend; and the subjects with Q4 level of α-TOH have the lowest serum TC, TG and LDL-c levels (P < 0.05). Serum HDL-c and HDL/ LDL, presented an increased trend according to the increase of lipid-adjusted α-TOH, and the highest serum HDL-c and HDL/LDL ratio were observed in subjects with Q4 level of serum α-TOH (P < 0.01). Serum retinol level showed a decreased trend following the increase of lipid-adjusted α-TOH level, and the lowest serum retinol level was observed in subjects with Q4 level of lipid-adjusted α-TOH (P < 0.01). Following the increase of serum lipid-adjusted α-TOH, α-TOH/retinol ratio demonstrated an increased trend correspondingly. The subjects with Q4 level of lipid-adjusted α-TOH showed the highest α-TOH/retinol ratio (P < 0.01) (Supporting information Table 3).
No difference of cognitive performance was observed among T2DM subjects with different quartile level of serum α-TOH (P > 0.05) (Supporting information Table 3).
Serum Parameters and Cognition According to α-TOH/ retinol Ratio in T2DM Subjects
As shown in Table 4, the lowest serum GLU, TC, TG, HDL-c and HDL/LDL levels were observed in subjects with Q1 level of α-TOH/retinol ratio (P < 0.05). The subjects with Q4 level of α-TOH/retinol ratio have the lowest serum LDL-c level (P < 0.05). Following the increase of serum α-TOH/ retinol ratio, serum retinol and lipid-adjusted retinol levels decreased correspondingly; and the lowest serum retinol and lipid-adjusted retinol levels were observed in subjects with Q4 level of α-TOH/retinol ratio (P < 0.01). Serum α-TOH and lipid-adjusted α-TOH levels increased following the increase of serum α-TOH/retinol ratio; and the highest α-TOH and lipid-adjusted α-TOH levels were observed in subjects with Q4 level of α-TOH/retinol ratio (P < 0.01).
Table 4.
Serum parameters and cognition according to α-TOH/retinol ratio in subjects with T2DM (n = 448)
| Parameters and cognition | α-TOH/retinol | P value | |||
|---|---|---|---|---|---|
| Q1 (n = 108) | Q2 (n = 112) | Q3 (n = 113) | Q4 (n = 115) | ||
| Serum parameters | |||||
| GLU (mmol/L) | 6.71 (6.22, 7.20) | 7.58 (7.10, 8.07){sua} | 7.46 (6.98, 7.93){sua} | 7.95 (7.47, 8.44){sua} | < 0.01 |
| TC (mmol/L) | 4.55 (4.34, 4.75) | 4.82 (4.62, 5.03) | 4.75 (4.56, 4.95) | 5.03 (4.83, 5.24){sua} | 0.013 |
| TG (mmol/L) | 1.54 (1.23, 1.85) | 1.91 (1.61, 2.22) | 1.67 (1.38, 1.97) | 2.62 (2.32, 2.92){suabc} | < 0.01 |
| HDL-c (mmol/L) | 1.27 (1.22, 1.33) | 1.32 (1.26, 1.38) | 1.41 (1.36, 1.47){suab} | 1.43 (1.37, 1.49){suab} | < 0.01 |
| LDL-c (mmol/L) | 2.96 (2.78, 3.13) | 2.87 (2.69, 3.04) | 2.66 (2.49, 2.83){sua} | 2.61 (2.44, 2.79){suab} | 0.023 |
| HDL/LDL | 0.48 (0.44, 0.52) | 0.51 (0.47, 0.55) | 0.60 (0.56, 0.64){suab} | 0.59 (0.55, 0.63){suab} | < 0.01 |
| Retinol (µg/ml) | 0.76 (0.74, 0.78) | 0.62 (0.60, 0.64){sua} | 0.47 (0.44, 0.49){suab} | 0.41 (0.38, 0.43){suabc} | < 0.01 |
| Retinol/TG+TC (mg/mmol) | 0.13 (0.13, 0.13) | 0.10 (0.09, 0.10){sua} | 0.08 (0.07, 0.08){suab} | 0.06 (0.05, 0.06){suabc} | < 0.01 |
| α-TOH (µg/ml) | 9.17 (8.50, 9.84) | 11.15 (10.49, 11.81){sua} | 11.74 (11.09, 12.39) | 15.28 (14.63, 15.94) | < 0.01 |
| α-TOH/TG+TC (mg/mmol) | 1.54 (1.47, 1.62) | 1.70 (1.63, 1.78){sua} | 1.89 (1.82, 1.96){suab} | 2.07 (1.99, 2.14){suabc} | < 0.01 |
| Cognition | |||||
| MocA Score | 25.55 (24.77, 26.34) | 24.37 (23.61, 25.13){sua} | 23.44 (22.69, 24.19){sua} | 22.57 (21.82, 23.32){suab} | < 0.01 |
| Visual and executive | 3.89 (3.65, 4.13) | 3.77 (3.53, 4.13) | 3.52 (3.29, 3.75){sua} | 3.37 (3.13, 3.60){suab} | 0.011 |
| Naming | 2.92 (2.84, 2.99) | 2.86 (2.79, 2.94) | 2.85 (2.77, 2.92) | 2.88 (2.80, 2.96) | 0.653 |
| Attention | 5.58 (5.36, 5.79) | 5.35 (5.14, 5.55) | 5.34 (5.14, 5.54) | 4.99 (4.79, 5.20){suabc} | < 0.01 |
| Language | 2.15 (1.98, 2.32) | 2.06 (1.89, 2.22) | 1.92 (1.76, 2.08) | 1.78 (1.62, 1.94){suab} | 0.016 |
| Abstraction | 1.56 (1.41, 1.70) | 1.53 (1.39, 1.67) | 1.42 (1.28, 1.55) | 1.41 (1.27, 1.55) | 0.352 |
| Memory and delayed recall | 3.16 (2.87, 3.46) | 2.81 (2.53, 3.10) | 2.53 (2.25, 2.81){sua} | 2.31 (2.03, 2.59){suab} | < 0.01 |
| Orientation | 5.84 (5.71, 5.97) | 5.79 (5.66, 5.92) | 5.82 (5.70, 5.95) | 5.81 (5.68, 5.94) | 0.959 |
Data were expressed as mean (95% CI). Glu, glucose; HDL-c, high density lipoprotein cholesterol; LDL-c, low density lipoprotein cholesterol; TC, total cholesterol; TG, triglyceride; α-TOH: α-tocopherol; T2DM: type 2 diabetes mellitus. General Linear Model (GLM) was used for data serum parameters and cognition comparison. During the comparison of serum parameters and cognition between groups, factors including age, BMI, education level, smoking, alcohol drinking, physical activity, reading habit, housekeeping, hyperlipidemia, the duration of T2DM, current treatment for diabetes, AD family history, and ApoE genotype were adjusted. P < 0.05 was considered as significance.
Following the increase of serum α-TOH/retinol ratio, global cognition and cognitive performance in visual and executive, attention, language, and memory and delayed recall domains exhibited a decreased trend. The lowest cognitive performance was observed in subjects with Q4 level of α-TOH/retinol ratio (P < 0.01).
Serum Vitamins Levels and Risk of MCI in T2DM Subjects
The effect of circulating retinol and α-TOH levels on the risk of MCI in T2DM subjects was presented in Table 5. Increase of circulating α-TOH and lipid-adjusted α-TOH level had no effect on the risk of MCI in T2DM subjects (P > 0.05). The increase of circulating retinol demonstrated a protective effect on the cognitive function in T2DM subjects, which was demonstrated by the decreased risk of MCI in subjects with Q2 (OR = 0.53, P < 0.05), Q3 (OR = 0.26, P < 0.01) and Q4 (OR = 0.15, P < 0.01) level of retinol. The increase of circulating lipid-adjusted retinol also predicts a decrease risk of MCI in T2DM subjects, which was indicated by the decreased risk of MCI in subjects with Q2 (OR = 0.74, P < 0.05), Q3 (OR = 0.26, P < 0.01) and Q4 (OR = 0.19, P < 0.01) level of lipid-adjusted retinol. T2DM subjects with Q3 (OR = 3.79, P <0.01) or Q4 (OR = 5.36, P <0.01) level of α-TOH/retinol ratio demonstrated an increased risk of MCI.
Table 5.
Logistic analysis of serum α-TOH, retinol levels and the risk of MCI in subjects with T2DM (n = 448)
| Predictors | B | SE | Wald | Adjusted OR | 95/% CI | P value |
|---|---|---|---|---|---|---|
| Effect of α-TOH | ||||||
| α-TOH Q1 (reference) | {su-} | {su-} | {su-} | 1 | {su-} | {su-} |
| α-TOH Q2 | −0.10 | 0.33 | 0.09 | 0.90 | 0.48, 1.72 | 0.76 |
| α-TOH Q3 | −0.15 | 0.33 | 0.20 | 0.86 | 0.45, 1.65 | 0.65 |
| α-TOH Q4 | 0.44 | 0.33 | 1.73 | 1.55 | 0.81, 2.96 | 0.19 |
| Effect of lipid-adjusted α-TOH | ||||||
| α-TOH/TG+TC Q1 (reference) | {su-} | {su-} | {su-} | 1 | {su-} | {su-} |
| α-TOH/TG+TC Q2 | −0.21 | 0.33 | 0.39 | 0.82 | 0.43, 1.55 | 0.53 |
| α-TOH/TG+TC Q3 | 0.33 | 0.32 | 1.06 | 1.39 | 0.74, 2.59 | 0.30 |
| α-TOH/TG+TC Q4 | 0.28 | 0.32 | 0.77 | 1.32 | 0.71, 2.44 | 0.38 |
| Effect of retinol | ||||||
| Retinol Q1 (reference) | {su-} | {su-} | {su-} | 1 | {su-} | {su-} |
| Retinol Q2 | −0.63 | 0.30 | 4.51 | 0.53 | 0.30, 0.95 | 0.03 |
| Retinol Q3 | −1.33 | 0.31 | 18.12 | 0.26 | 0.14, 0.49 | < 0.01 |
| Retinol Q4 | −1.89 | 0.35 | 28.83 | 0.15 | 0.08, 0.30 | < 0.01 |
| Effect of lipid-adjusted retinol | ||||||
| Retinol/TG+TC Q1 (reference) | {su-} | {su-} | {su-} | 1 | {su-} | {su-} |
| Retinol/TG+TC Q2 | −0.30 | 0.29 | 1.07 | 0.74 | 0.42, 1.31 | 0.30 |
| Retinol/TG+TC Q3 | −1.37 | 0.33 | 17.11 | 0.26 | 0.13, 0.49 | < 0.01 |
| Retinol/TG+TC Q4 | −1.67 | 0.35 | 22.22 | 0.19 | 0.09, 0.38 | < 0.01 |
| Effect of α-TOH/retinol ratio | ||||||
| α-TOH/retinol Q1 (reference) | {su-} | {su-} | {su-} | 1 | {su-} | {su-} |
| α-TOH/retinol Q2 | 0.56 | 0.35 | 2.50 | 1.75 | 0.88, 3.49 | 0.11 |
| α-TOH/retinol Q3 | 1.33 | 0.35 | 14.88 | 3.79 | 1.93, 7.46 | < 0.01 |
| α-TOH/retinol Q4 | 1.68 | 0.35 | 22.99 | 5.36 | 2.70, 10.66 | < 0.01 |
Logistic regression models were created to evaluate the effects of serum α-TOH, retinol on the risk of MCI. Confounding factors such as age, sex, BMI, education level, smoking, alcohol drinking, physical activity, reading habit, housekeeping, hyperlipidemia, the duration of T2DM, current treatment for diabetes, AD family history and ApoE genotype were adjusted during analysis. MCI: mild cognitive impairment; α-TOH: α-tocopherol; SE: standard error; OR: odds ratio; CI: confidence interval; Q: quartile.
Discussion
Circulating VA and VE levels were reported inversely correlating with the risk of T2DM and dementia in aging population (27, 28). However, to date, the association of in vivo VA and VE status and cognitive function in T2DM subjects was seldom reported. To our knowledge, this is the first study to explore the association of circulating VE and VA levels and cognitive function in T2DM subjects. Our data indicated that diminished circulating retinol concentration and increased α-TOH/retinol ratio might predict cognitive decline and an increased risk of MCI in aging subjects with T2DM.
Population based cohort studies indicated that insulin resistance could increase the risk of cognitive impairment in the elderly (29, 30), which indicating that T2DM subjects were in high risk of MCI or AD. In the current study, although no statistical significance, we observed higher incidence of MCI in T2DM subjects than that in age, gender and education level matched non-T2DM subjects (Table 1). Additionally, lower circulating retinol status and lipid-adjusted retinol levels were observed in subjects with MCI (Table 2). Similar results were indicated by Zeng's study, which indicated that patients with mild to moderate cognitive impairment showed significantly lower serum VA level (31). Moreover, Handing's epidemiology studies also found that serum β-carotene level is positively correlated with learning, memory and cognitive function in aging population (32). These results together with ours indicated that optimal circulating retinol status might benefit cognitive function, as well as decrease the risk of cognition decline in the elderly.
It is interesting to find that T2DM subjects with MCI (T2DM-MCI subjects) demonstrated lower serum retinol and lipid-adjusted retinol status than non-T2DM subjects (Table 2). Moreover, the significant correlation between circulating retinol level with cognitive function (Supporting information Table 2) further illuminated the potential impact of retinol status on cognitive performance in T2DM subjects. Besides, increased serum GLU and TC concentrations were also observed in subjects with low circulating retinol level (Table 2), which indicates the involvement of retinol in glucose and lipid metabolism. The impacts of VA on the metabolism of insulin and the pathological progress of T2DM have been extensively reported by previous studies (33). VA dietary supplementation have been found to inhibit adipogenesis, improve insulin sensitivity and relieve hyperlipidemia in obese experimental animals (34, 35). However, a low VA status favors increased fat deposition in the adipose tissue of animal models and in cultured preadipocytes (36). Kuang's study also found that VA deficiency attenuated the high fat diet (HFD)-induced obesity, and VA status altered the expression levels of proteins required for glucose metabolism and insulin signaling (37). These findings indicated the involvement of retinol and insulin signaling in the neurobiological process of AD.
As an important brain region that regulates learning and memory, the hippocampus is rich in the expression of insulin receptors (38). Moreover, chronic peripheral hyperinsulinemia caused by insulin resistance terminally lowers brain insulin level. And this reduction of brain insulin level may in turn lead to diminished clearance of the beta amyloid (Aβ) peptide and increased hyperphosphorylation of tau, the typical pathologic features of AD neuropathology (39). The role of VA in affecting insulin metabolism was also reported by previous studies. VA could regulate the gene and protein expression of insulin degradation enzyme (IDE) (40). It is well known that IDE was an essential enzyme in the metabolism of Aβ in brain, and might play an essential role in the pathophysiological changes of AD (41). The regulation of IDE expression caused by VA treatment in neuron cells indicated the linkage between VA, insulin resistance and AD (42). Additionally, accumulating evidences suggest that retinol could modulate Aβ plaque formation and hippocampal function in brain (43). The dysfunction of retinoic acid signaling also contribute to AD pathobiology (44, 45). In the current study, we found that, following the increase of serum lipid-adjusted VA status, cognitive function of T2DM subjects exhibited an increased trend; while, serum GLU and lipids parameters (including TC, TG and HDL-c) demonstrated a decreased trend (Table 3). These results indicated the association of VA and glucose metabolism in affecting cognitive function. We also detected the protective role of circulating VA status in decreasing the risk of MCI in T2DM subjects (Table 5). These findings suggested that lower serum retinol level might predispose T2DM patients to cognition decline, as well as an increased risk of MCI.
The anti-amyloidogenic properties and anti-neurodegenerative effects of VE have been indicated by previous studies (46). Moreover, compared to non-demented controls, reduced circulating VE concentration was observed in AD patients (47). Inconsistent with previous findings, in the present study, although the T2DM-MCI subjects exhibited increased lipid-adjusted VE status, the correlation of VE levels with cognitive function became insignificant after adjusting VE level with lipid (Supporting information Table 2). After grouping the T2DM subjects according to lipid-adjusted VE level, we only observed the difference of circulating lipid parameters, but no difference of cognitive function was found among groups (Supporting information Table 3). These results fall in line with the positive correlation between serum α-TOH status and lipid parameters observed in previous study (48). Moreover, the significant increase of circulating HDL-C and HDL/LDL found in MCI subjects further hints the modifying effect of lipids on the relationship between VE and cognitive function. All these results indicated the lipid-dependent association of VE and cognitive performance.
The negative correlation between α-TOH/retinol ratio and cognition was reported by our previous study (49). In the present study, we consistently detected the negative correlation between α-TOH/retinol ratio and cognitive function in T2DM subjects. This finding was further ascertained by the results of logistic analysis, which indicates that increased serum α-TOH/retinol ratio predicted a high risk of MCI in T2DM subjects (Table 5). Adverse interactions of VA and VE absorption and tissue accumulation have been reported by others' studies (50, 51). An optimal interactive state between VE and VA might be essential to maintain their normal physiological functions in vivo (52). High α-TOH/retinol ratio might partly attribute to VE-rich (such as whole grains, milk and egg), but VA-less (low vegetable intake) dietary consumption in T2DM-MCI subjects (Supporting information Table 1). Additionally, significant correlations of α-TOH and retinol with HDL-c and LDL-c levels have been reported previously (53). Therefore, the changes of serum α-TOH/retinol ratio might be an indicator of circulating lipid profiles. Given previous evidence as to the association of lipids and cognitive function (54, 55), the altered serum lipid profiles are likely to explain the difference of cognitive performance across the subjects with different α-TOH/retinol ratio.
Several limitations should be considered when interpreting our findings. First, attributed to the different lifestyle and diet patterns, circulating vitamin status of participants in present study might be different from that of individuals in western countries. Therefore, extrapolation of our conclusions to other populations should be considered with caution. Secondly, although several common confounding factors were adjusted during data analysis, selection bias, information bias and confounding have been indicated in previous cross-sectional study (56), therefore, there were potential for residual confounding. Finally, small sample size is another shortcoming. Additional large scale cohort studies are needed to elucidate the effect(s) of serum α-TOH and retinol on cognitive function in T2DM subjects.
In spite of these limitations, to the best of our knowledge, this is the first study to explore the association of circulating α-TOH and retinol with cognitive function in T2DM subjects. Currently, there are 230 million elderly people aged 60 or above in China, accounting for 16.7 percent of the total population. The prevalence of diabetes in the elderly was 22.86% (57). The increasing number of elderly population and the elderly with diabetes indicate that the prevalence of AD will increase dramatically in China. We are the first to reveal the relationship between circulating α-TOH and retinol with cognitive function in aging T2DM subjects. Our findings will provide important implications for future nutritional intervention to prevent MCI and AD in the elderly, especially in aging subjects with T2DM.
Conclusion
Totally, our data indicate that optimal in vivo VA nutrition might play an important role in maintaining normal cognitive function in aging population, especially the T2DM subjects. Future well-designed prospective cohort research should be directed at exploring the mechanisms through which that retinol affecting cognitive function in aging T2DM subjects.
Acknowledgments
This study was supported by the grants from the National Natural Science Foundation of China (No. 81673148; No.81973027).
Ethical standards
The study protocol was approved by the Human Ethics Committee of the Capital Medical University (No. 2012SY23). The procedures followed the ethical standards of the Helsinki Declaration of 1975.
Conflict of Interest and Funding Disclosure
The authors declare no conflicts of interest.
Electronic Supplementary Material
Supplementary material is available for this article at https://doi.org/10.1007/s12603-020-1328-1 and is accessible for authorized users.
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