Adiponectin, leptin and IL-1 β in elderly diabetic patients with mild cognitive impairment - PDF

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Metab Brain Dis (2016) 31: DOI /s ORIGINAL ARTICLE Adiponectin, leptin and IL-1 β in elderly diabetic patients with mild cognitive impairment Malgorzata Gorska-Ciebiada 1

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Metab Brain Dis (2016) 31: DOI /s ORIGINAL ARTICLE Adiponectin, leptin and IL-1 β in elderly diabetic patients with mild cognitive impairment Malgorzata Gorska-Ciebiada 1 & Malgorzata Saryusz-Wolska 1 & Anna Borkowska 1 & Maciej Ciebiada 2 & Jerzy Loba 1 Received: 9 May 2015 /Accepted: 23 September 2015 /Published online: 2 October 2015 # The Author(s) This article is published with open access at Springerlink.com Abstract The aim of the study was to determine the serum levels of adiponectin, leptin and IL-1 β in elderly diabetic patients with and without mild cognitive impairment (MCI) and to examine the associations of these markers with clinical and cognitive parameters. A biochemical evaluation was performed of 62 seniors with type 2 diabetes (T2DM) and MCI, and 132 seniors with T2DM but without MCI (controls). Serum leptin and IL-1 β levels were higher and adiponectin concentration was lower in MCI patients than controls. In MCI subjects, adiponectin level was negatively correlated with leptin, IL-1 β levels and BMI. Leptin concentration was correlated with IL-1 β level. Univariate logistic regression models revealed that the factors which increased the likelihood of diagnosis of MCI in elderly patients with T2DM were higher levels of HbA1c, leptin, IL-1 β and triglycerides, as well as lower levels of adiponectin and HDL cholesterol. Similarly, previous CVD, hypertension, hyperlipidemia, retinopathy, nephropathy, hypoglycemia, longer duration of diabetes, increased number of co-morbidities, older age, fewer years of formal education were found to be associated with MCI. The multivariable model indicated fewer years of formal education, previous CVD, hypertension, increased number of co-morbidities, higher HbA1c and IL-1 β levels and lower adiponectin level. Elderly diabetic patients with MCI have higher levels of leptin and IL-1 β and lower levels of * Malgorzata Gorska-Ciebiada 1 2 Department of Internal Medicine and Diabetology, Medical University of Lodz, ul. Pomorska 251, Lodz, Poland Department of General and Oncological Pneumology, Medical University of Lodz, ul. Kopcinskiego 22, Lodz, Poland adiponectin. Further prospective studies are needed to determine the role of these markers in the progression to dementia. Keywords Adiponectin. Diabetes. IL-1 β. Leptin. Mild cognitive impairment Introduction (T2DM) is a chronic disease with wellestablished cross-sectional and longitudinal associations with cognitive impairment (Cukierman et al. 2005; Munshi et al. 2006; Ott et al. 1996). Mild cognitive impairment (MCI) is defined as a transition stage between normal aging and dementia. Many studies indicate that T2DM is a risk factor for MCI (Gorska-Ciebiada et al. 2014; Cheng et al. 2012; Kodl and Seaquist 2008). On the other hand aging itself is also related to cognitive dysfunction: the prevalence of MCI in subjects aged 70 years and older is % (Petersen et al. 2009; Sinclairetal.2000). Recent studies have suggested that inflammation may play an important role in the presence and development of MCI (Hermida et al. 2012; Gorska-Ciebiada et al. 2015; Umegaki et al. 2011; Barnes et al. 2006). IL-1 β is one of the proinflammatory cytokines involved in damage of islet beta cells (Palmer et al. 1989). One study performed in rats found that pancreatic tissues expressed elevated levels of IL-1β, and IL-1β-driven inflammatory cascade in diabetes (Ehses et al. 2009). This imbalance between IL-1β and IL-1 receptor antagonist leads to pancreatic islet inflammation and release of insulin. Using a recombinant human IL-1 receptor antagonist is one of the novel anti-inflammatory treatments which lead to the correction of beta cells dysfunction and decreased systemic inflammation in T2DM (Akash et al. 2012). There is also strong evidence that inflammation can pay a 258 Metab Brain Dis (2016) 31: crucial role in the brain during Alzheimer s disease. Lue et al. (2012) propose that diabetes causes macro and microvascular complications which impair blood brain barrier function and endothelial cell activation. Microglia in the brain became activated by vascular injury and start a process of functional and morphological transformation and degeneration (Lue et al. 2012). Although many studies show increased expression of inflammatory mediators and microglial activation in MCI and dementia it has been hypothesized that pro-inflammatory cytokines are derived from peripheral sources like adipose tissue. It is possible that central and peripheral inflammation pathways are responsible both for the neurodegeneration process. The adipose tissue produces many pro-inflammatory cytokines including IL-1β,IL 6,IL 18 andtnf-α (Monteiro and Azevedo 2010). The levels of these mediators were elevated in peripheral blood of patients with Alzheimer Disease (Swardfager et al. 2010). Adipose tissue also produces also an pro-inflammatory hormone: leptin. T2DM and obesity is associated with hyperleptinemia and subsequent leptin resistance. Studies suggest that leptin can act as a neuro-inflammatory signal, one which may attract different immune cells and stimulate the production of such cytokines as IL-1β (Lam and Lu 2007). The leptin receptors are present in microglia and regulate the synthesis of IL-1β. High levels of plasma leptin are associated with the production of IL-1β (Lafrance et al. 2010). Thus, it has been proposed that hyperleptinemia and leptin resistance may lead to a higher inflammatory response in the brain (Misiak et al. 2012). Another protein secreted by adipose tissue is adiponectin, which is highly involved in modulation of insulin sensitivity, homeostasis of glucose and fatty acids and anti-inflammatory action (Ouchi et al. 2003). Adiponectin has also been described to have neuroprotective activities with its receptors located in the brain (Letra et al. 2014). A little literature data is available concerning the protective role of adiponectin in mild cognitive impairment. In one study reduced amounts of subcutaneous fat and low levels of plasma adiponectin were found to be associated with MCI in men (Kamogawa et al. 2010). Although the findings so far suggest that some inflammatory mediators and adipocytokines can be involved in cognitive function in elderly subjects with T2DM are limited. Therefore, the aim of the current study was firstly, to determine the serum levels of adiponectin, leptin and IL-1 β in elderly diabetic patients with and without MCI, and secondly, to examine the relationships between these three markers and clinical and cognitive parameters. Materials and methods Study population A survey was conducted among 194 unselected elders attending an outpatient clinic belonging to the Department of Internal Medicine and Diabetology, University Hospital no 1, Lodz, Poland. A brief recruitment screening was conducted by the investigators to identify potential participants based on the following inclusion criteria: age 65 and over, diabetes type 2 diagnosed minimum 1 year earlier, ability to understand and cooperate with study procedures. The exclusion criteria were diagnosed depression or dementia, use of possible or known cognition-impairing drugs in the previous 3 month, presence of neoplasm, constant alcohol or substance abuse, severe visual, mobility, or motor coordination impairment, history of head trauma, inflammatory or infectious brain disease, severe neurological or psychiatric illness. The first part of visit included a morning blood draw after a h overnight fast, blood pressure measurements, height and weight assessment and complete physical examination. Capillary glucose level measurement was performed after breakfast to ensure that participants were not hypoglycemic at the time of cognitive testing. The second part of the visit took place in a private area in the clinic. The subjects completed a questionnaire describing baseline demographics and underwent cognitive testing. Participant characteristics, clinical evaluation and risk factor assessment Demographic variables and possible risk factors were recorded in a standardized interview. Weight and height were measured to calculate body mass index (BMI=weight/ height 2 [Kg/ m 2 ]). A detailed medical history of diabetes type 2 was taken: diabetes duration, current treatment for diabetes and complications if present, co-morbid diseases of the patient (hyperlipidemia, hypertension, cardiovascular disease, lung disease, cancer, gastrointestinal tract diseases and other) and their treatment. Educational level was recorded in years of education. Diabetic vascular complications were assessed based on the existence of nephropathy, retinopathy, neuropathy, cardiovascular disease (CVD) and stroke. Hypertension was defined as either a history of hypertension or use of any antihypertensive agents, Hyperlipidemia defined as use of any lipid lowering agent or an untreated serum LDL cholesterol level 2.6 mmol/l or/ and triglycerides 1.7 mmol/l. Blood biochemistry After overnight fasting, blood samples were taken by venipuncture to assess serum levels of glycosylated hemoglobin (HbA1c), total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C). All the parameters were measured in a centralized laboratory. Metab Brain Dis (2016) 31: Determination of serum adiponectin, leptin and IL-1 β The serum levels of adiponectin, leptin and IL-1 β were determined by Quantikine Human Immunoassay ELISA kit (R & D System, Minneapolis, USA) according to the manufacturer s instructions. Minimum detectable concentrations were: ng/ml for adiponectin, 7.8 pg/ml for leptin, and 1 pg/ml for IL-1 β. Neuropsychological evaluations All participants underwent the following tests: the Montreal Cognitive Assessment (MoCA) (Nasreddine et al. 2005) to evaluate the cognitive impairment, Katz Basic Activities of Daily living (BADL) and Lawton Instrumental Activities of Daily Living (IADL) questionnaires to collect information on daily activities (Katz et al. 1970; Lawton and Brody 1969). The MoCA tests 8 cognitive domains, visual-spatial ability, attention, executive function, immediate memory, delayed memory, language, abstraction, calculation, and orientation, for a maximum total score of 30. The normal MoCA score is 26, with one point added if the subject has fewer than 12 years of formal education. The MoCA is better than other tools to detect MCI in the elderly patients with type 2 diabetes (Alagiakrishnan et al. 2013). MCI was diagnosed based on criteria established by the 2006 European Alzheimer s Disease Consortium which is the currently available standard test (Petersen 2004; Portet et al. 2006). The criteria include: cognitive complaints coming from the patients or their families, the reporting of a decline in cognitive functioning relative to previous abilities during the past year by the patient or informant, cognitive disorders as evidenced by clinical evaluation (impairment in memory or in another cognitive domain, which in this study was assessed by MoCA), absence of major repercussions on daily life (measured in our study by the Katz BADL and Lawton IADL), and absence of dementia. The cutoff points for MoCA scores (19/30) are recommended for the diagnosis of Dementia - in epidemiological studies. Patients with a score of 19 or below were excluded from the study as suffering from dementia and referred to a psychiatrist for further care. Two groups of subjects were evaluated: group 1 - patients with MCI and group 2 - patients without MCI (controls). Ethics The study was operated in accordance with the World Medical Association s Declaration of Helsinki. Each participant was identified by a number to maintain privacy. The approval was obtained from the independent local ethics committee of the Medical University of Lodz (No RNN/420/13/KB). The purpose, nature, and potential risks of the experiments were fully explained to the subjects, and all subjects gave their written, informed consent at the beginning of the study. The study included only patients who were fully able to understand and cooperate with the study procedures. Statistical analysis All continues results are presented as means±sd. Frequencies and percentages were calculated to enable comparison of characteristics between patients with MCI and controls. Normality of distributions was assessed using the Shapiro-Wilk test. The descriptive statistics for the categorical variables were tested using the χ 2, and the continuous variables using the Student s T-test or the Mann Whitney-U test where applicable. Relationships were assessed using the Pearson s correlation analysis for normally distributed variables and Spearman rank correlation for non-normally distributed variables. As many factors can influence the results, the simple logistic regression was performed to select socalled independent factors which increase the selection risk of MCI in elderly patients with type 2 diabetes. The independent variables entered in the model at step one were: demographic variables (age, gender, education), duration of diabetes, glycaemic control (HbA1c level), cardiovascular diseases (MI, angina, stroke), cardiovascular risk factors (BMI, smoking status, hyperlipidaemia, previous HA or use of HA drugs), microvascular complications, presence of hypoglycemia, number of co-morbid conditions, and the levels of lipids, adiponectin, leptin and IL-1 β. We choose variables based on current literature which can potentially can influence the results (Cukierman-Yaffe et al. 2009; Umegaki et al. 2011; Misiak et al. 2012). Multivariable regression was then used to select the Bstrongest^ factor from the independent risk factors. All the significant variables with p 0.05 included in simple logistic regression model were introduced to this analysis. The multivariable model was optimized, using a stepwise approach (backward elimination with Wald criteria). Odds ratios (OR) were computed and presented with the 95 % interval of confidence (CI). A p- value of less than 0.05 was considered statistically significant. Statistica 10.0 (StatSoft, Poland, Krakow) was used for analysis. Results The baseline characteristics of the study group Tables 1 and 2 present the characteristics of type 2 diabetic elderly patients with and without MCI. The χ 2 test showed that patients with MCI were more often diagnosed with CVD, hypertension, hyperlipidemia, retinopathy, nephropathy and hypoglycemia compared to controls. No 260 Metab Brain Dis (2016) 31: Table 1 Characteristics of type 2 diabetic elderly patients with and without MCI Variable with MCI (n=62) without MCI (n=132) χ 2 P value Gender, Female 32 (51.6 %) 50 (37.8 %) Smoked tobacco regularly 12 (19.4 %) 34 (25.7 %) Macrovascular complications Previous CVD 48 (77.4 %) 28 (21.2 %) P 0.001 Stroke 2 (3.2 %) 5 (3.78 %) Previous HA/ use of HA drugs 60 (96.7 %) 93 (70.4 %) P 0.001 Hyperlipidemia 56 (90.3 %) 86 (65.15 %) P 0.001 Microvascular complications Retinopathy 43 (69.4 %) 43 (32.6 %) P 0.001 Nephropathy 32 (51.6 %) 38 (28.8 %) Neuropathy 10 (16.1 %) 13 (9.8 %) Treatment OAD 61 (98.4 %) 126 (95.4 %) Insulin 23 (37.1 %) 47 (35.6 %) Hypoglycemia 38 (61.29 %) 48 (36.36 %) MCI mild cognitive impairment, CVD cardiovascular disease, HA hypertension, OAD oral anti-diabetic drug. Data are mean SD values. χ 2 test was used to test for significant differences significant differences were found between the groups with regard to sex, smoking habit, stroke, neuropathy, type of concomitant disease or treatment. Furthermore, the Mann Whitney U-test and Student s T-testshowed that patients with MCI tended to be older, less educated, with a longer duration of diabetes, higher number of comorbidities, higher BMI, higher levels of HbA1c and triglicerydes, and lower concentrations of HDL cholesterol (Table 3). MoCA score was significantly lower in subjects with MCI compared with controls. Lastly, there were no significant differences between the groups with regard to total cholesterol and LDL cholesterol levels (p 0.05). Table 2 Comparison of concomitant disease and drug use by type 2 diabetic elderly patients with and without MCI Variable with MCI (n=62) without MCI (n=132) Other diseases: Lung disease (%) 11 (17.7 %) 14 (10.6 %) Atrial fibrillation (%) 14 (22.6 %) 22 (16.6 %) Heart failure (%) 16 (25.8 %) 22 (16.6 %) Gastrointerstinal tract disease (%) 29 (46.7 %) 41 (31.1 %) Kidney disease (%) 15 (24.2 %) 24 (18.2 %) Thyroid diasease (%) 17 (27.4 %) 30 (22.7 %) Other treatment: Angiotensin-converting enzyme 35 (56.5 %) 56 (42.4 %) inhibitors (%) Angiotensin II receptor blockers % 25 (40.3 %) 49 (37.1 %) Diuretics (%) 23 (37.1 %) 32 (24.2 %) P 0.001 Calcium channel blockers (%) 20 (32.3 %) 39 (29.5 %) a1-blockers (%) 7 (11.3 %) 11 (8.3 %) B-blockers (%) 43 (69.3 %) 48 (36.3 %) P 0.001 Antiplatelet medications (%) 48 (77.4 %) 69 (52.6 %) Lipid-lowering medications (%) 42 (67.7 %) 89 (67.4 %) χ 2 p MCI - mild cognitive impairment, Data are mean SD values. χ 2 test was used to test for significant differences Metab Brain Dis (2016) 31: Table 3 Clinical characteristics and biochemical parameters of type 2 diabetic elderly patients with and without MCI Variable with MCI (n=62) without MCI (n=132) Z/t P value Age (years) 74.7± ± P 0.001 Education-years 9.8± ± P 0.001 Duration of T2DM (years) 10.63± ± P 0.001 BMI (kg/m 2 ) 29.8± ± Adiponectin (μg/ml) 6.06± ± P 0.001 Leptin (ng/ml) 25.19± ± P 0.001 IL-1 β (ng/ml) 1.59± ± P 0.001 HbA1c (%) 7.62±0.69 7± P 0.001 CHOL-C (mmol/l) 10.13± ± LDL-C (mmol/l) 5.79± ± TG (mmol/l) 10.29± ± P 0.001 HDL-C (mmol/l) 2.36± ± P 0.001 Co-morbidity (n) 6.3± ± P 0.001 MoCA score 21.5± ± P 0.001 Katz BADL score 4.95± ± Lawton IADL score 7.98±0.12 8± T2DM diabetes type 2, BMI body mass index, CHOL total cholesterol; HbA1c glycosylated hemoglobin; HDL-C high-density lipoprotein cholesterol; LDL-C low density lipoprotein cholesterol; TG triglycerides; MoCA - Montreal Cognitive Assessment; BADL Basic Activities of Daily living, IADL Instrumental Activities of Daily Living, Data are mean SD values. Mann Whitney U test (Z), or t test was used to test for significant differences Serum levels of adiponectin, leptin and IL-1 β in MCI subjects and controls Serum levels of leptin and IL-1 β were significantly increased in patients with MCI compared to controls (p 0.001). Serum concentrations of adiponectin were lower in subjects with cognitive impairment (Table 3). In the group of diabetic elderly patients with MCI adiponectin level was negatively correlated with leptin level (r= 0.64, p 0.001), with IL-1 β level (r= 0.7, p 0.001) and with BMI (r= 0.78, p 0.001). Leptin concentration was positively correlated with IL-1 β level (r= 0.54, p 0.001). Furthermore, both leptin and IL-1 β levels were highly correlated with BMI. A positive but weak correlation was found between IL-1 β level and MoCA score, and a negative correlation between adiponectin level and MoCA score. Leptin level was inversely correlated with HDL cholesterol level. The results are presented in Table 4. Since the levels of adipokines, as leptin and adiponectin, are dependent of body fat mass content and the group with T2DM and MCI had significantly higher BMI values than the other group, we divided all subjects into groups adjusted for BMI (Table 5). We observed that the adipokines results observed between the 2 groups persist significant after statistical adjustment for BMI. The only doubt occurs in group of patients with BMI below 25.9, however among subjects with MCI only 5 persons had such low BMI values therefore these data should be interpreted with caution. The majority of patients had BMI higher than 26 and in those we observed that elderly diabetic patients with MCI have higher levels of leptin and IL-1 β and lower levels of adiponectin. Logistic regression models The univariate logistic regression models revealed that the
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