Olfactory Dysfunction Mediates
Adiposity in Cognitive Impairment
of Type 2 Diabetes: Insights From
Clinical and Functional
Neuroimaging Studies
https://doi.org/10.2337/dc18-2584
OBJECTIVE
Large numbers of people with type 2 diabetes are obese. However, changes in cognition and related brain function in obese people with diabetes have not been characterized. Here, we investigated cognition, olfactory function, and odor-induced brain alterations in these patients and therapeutic effects of glucagon-like peptide 1 receptor agonists (GLP-1Ras) on their psychological behavior and olfactory networks.
RESEARCH DESIGN AND METHODS
Cognitive, olfactory, and odor-induced brain activation assessments were admin-istered to 35 obese and 35 nonobese people with type 2 diabetes and 35 control subjects matched for age, sex, and education. Among them, 20 obese individuals with diabetes with inadequately glycemic control and metformin monotherapy received GLP-1Ra treatment for 3 months and were reassessed for metabolic, cognitive, olfactory, and neuroimaging changes.
RESULTS
Obese subjects with diabetes demonstrated lower scores of general cognition and olfactory threshold, decreased left hippocampal activation, and disrupted seed-based functional connectivity with right insula compared with nonobese subjects with diabetes. Negative associations were found between adiposity and episodic memory and between fasting insulin and processing speed test time in diabetes. Mediation analyses showed that olfactory function and left hippocampus activation mediated these correlations. With 3-month GLP-1Ra treatment, obese subjects with diabetes exhibited improved Montreal Cognitive Assessment (MoCA) score, olfactory test total score, and enhanced odor-induced right parahippocampus activation.
CONCLUSIONS
Obese subjects with type 2 diabetes showed impaired cognition, and dysfunctional olfaction and brain networks, the latter of which mediated adiposity in cognitive impairment of diabetes. GLP-1Ras ameliorated cognitive and olfactory abnormal-ities in obese subjects with diabetes, providing new perspectives for early diagnosis and therapeutic approaches for cognitive decrements in these patients.
1Department of Endocrinology, Drum Tower Hospital, Nanjing University Medical School, Nanjing, China
2
Department of Radiology, Drum Tower Hospital, Nanjing University Medical School, Nanjing, China
3Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
4
Center for NMR Research, Department of Ra-diology, Pennsylvania State University College of Medicine, Hershey, PA
5George M. Leader Foundation Alzheimer’s Lab-oratory, Department of Neurosurgery, Pennsyl-vania State University College of Medicine, Hershey, PA
Corresponding author: Yan Bi, [email protected] Received 18 December 2018 and accepted 17 April 2019
Clinical trial reg. no. NCT 02738671, clinicaltrials. gov
This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/suppl/ doi:10.2337/dc18-2584/-/DC1.
Z.Z., B.Z., X.W., and D.Z. contributed equally to the manuscript.
© 2019 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More infor-mation is available at http://www.diabetesjournals .org/content/license.
Zhou Zhang,1Bing Zhang,2,3Xin Wang,3 Xin Zhang,2Qing X. Yang,4,5Zhao Qing,2 Wen Zhang,2Dalong Zhu,1and Yan Bi1
PATHO
PHYSIOLOGY/C
OMPLICAT
IONS
Diabetes Care Publish Ahead of Print, published online May 21, 2019 Diabetes Care Publish Ahead of Print, published online May 21, 2019 Diabetes Care Publish Ahead of Print, published online May 21, 2019
The prevalence of being overweight or obese among people with type 2 diabetes was 87.1% in the U.S. from 2005 to 2010 (1) and 58.3% in China in 2011 (2). Obese individuals with diabetes are more suscep-tible to diabetes complications in heart, brain, eyes, and kidneys (3,4). Cognitive decline and dementia are recognized as cerebral comorbidities associated with di-abetes (5). Cognitive deficits, especially in executive function, impact self-care and medical compliance of these patients. Pre-vention, early diagnosis, and management of cognitive decrements present significant challenges.
Recently, neuroimaging techniques have attracted attention as they expand the research scope from animals to hu-mans, allowing for visualizations of deep brain structures to assess early patho-logical changes, therapeutic targets, and neurofeedback to treatment (6). In struc-tural and functional neuroimaging stud-ies, people with diabetes have generally exhibited regional brain atrophy, small-vessel diseases, aberrant brain sponta-neous brain activation, and disrupted functional connectivity underlying cog-nitive impairment (7). Particularly, obese individuals with type 2 diabetes have had pronounced cortical atrophy and white matter integrity disruption in MRI studies compared with normal-weight diabetes (8). However, the majority of functional neuroimaging studies in obese subjects with diabetes focused on eating behavior and energy homeostasis rather than cog-nitive function (9).
Olfactory dysfunction, characterized by increased odor thresholds and im-paired odor discrimination and recogni-tion, is an early risk sign of preclinical dementia and associated with the trajec-tories from normal cognition to mild cognitive impairment and late-life demen-tia (10,11). Epidemiological studies using olfactory tests found that patients with diabetes have decreased olfactory acuity (12). Furthermore, odor-induced func-tional MRI (fMRI) obtains clues about vulnerable brain regions before clinical measurable cognitive decline (13). Our previous study detected olfactory behav-ior and functional dysfunction in cog-nitively intact diabetes (14). However, associations between cognitive function, olfactory function, and olfactory central networks in obese individuals with dia-betes, and how to improve olfaction associated with diabetes, remain unclear.
Glucagon-like peptide 1 receptors (GLP-1Rs) are found in central neural cells, particularly in the olfactory bulb and hippocampus (15). The antidiabetes GLP-1R agonists (GLP-1Ras) have been reported to partially reverse decreased brain glucose metabolism in Alzheimer disease (16). Little is known about their efficacy for olfactory and neurological disorders in patients with diabetes.
Therefore, this study evaluated the patterns and interrelationships of cog-nition, olfactory function and odor-induced brain functional activations in obese patients with type 2 diabetes, and investigated the therapeutic effects of GLP-1Ras treatment on cognition, olfaction and olfactory brain function in these patients.
RESEARCH DESIGN AND METHODS
Participants
This study was conducted from January 2016 to August 2018 at Drum Tower Hospital, Nanjing University Medical School. The flowchart is presented in Supplementary Fig. 1. A total of 105 sub-jects including 35 obese and 35 nonobese participants with type 2 diabetes and 35 normal control subjects were enrolled and matched for age, sex, and education. All participants were right-handed and aged between 35 and 70 years and possessed .6 years of education. De-mographic data and medication status of all participants were collected. Resting blood pressure, height, weight, and waist circumferences were measured. Type 2 diabetes diagnosis was based on the American Diabetes Association criteria (17). Standard BMI cutoffs were used to define normal weight (BMI ,25 kg/m2), overweight (25 kg/m2# BMI ,30 kg/m2), and obesity (BMI$30 kg/m2) (18). Con-trol subjects were included if they had normal glucose tolerance, were normal weight, and if their cognitive status was classified as normal by Montreal Cogni-tive Assessment (MoCA) (scores $26), while participants with diabetes were included with normal cognition or mild cognitive impairment assessed by MoCA (scores$19) (19). Exclusion criteria for all participants were a history of neurological and psychiatric disorders, abnormal thy-roid, pancreatitis, cardiovascular or cere-brovascular disease, nasal pathologies, alcohol or substance abuse, steroid treat-ment, infections, or inability to undergo tests or MRI scanning.
This study was registered on Clinical-Trails.gov (NCT 02738671) and was ap-proved by the ethics committee of Drum Tower Hospital in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants.
Anthropometric and Biochemical Measurements
DEXA scans (Lunar iDXA software; GE Healthcare, Milwaukee, WI) were used to measure body fat distribution. Pa-tients with diabetes underwent a 100-g standard meal test, and control subjects underwent a 75-g oral glucose tolerance test (OGTT). Plasma glucose, insulin, and C-peptide concentrations were mea-sured at fasting and 2 h after a meal. Serum fasting total cholesterol, tri-glyceride, and HDL and LDL cholesterol concentrations were measured. Insulin resistance andb-cell function were es-timated using the HOMA2 Calculator (HOMA2_v2.2.3; Diabetes Trials Unit, University of Oxford).
Cognitive Assessments
General cognition was evaluated by the Mini-Mental State Examination (MMSE) and MoCA (Beijing Version). Multiple cognitive subdomains including episodic memory, working memory, word flu-ency, executive function, and informa-tion processing speed were evaluated with the following tests: 16-word Phila-delphia Verbal Learning Test and Wechs-ler Memory Scale, Trail Making Test Part A and Part B, Animal Naming Test, Boston Naming Test, Digit Span Test (forward and backward), and Stroop Color and Word Test (parts I, II, and III). Psycho-logical status was evaluated by the Clin-ical Dementia Rating and the Hamilton Depression Rating Scale. All tests re-quired;60 min to complete in a fixed order. Subject groupings were not known to examiners.
Olfactory Tests
Olfactory testing was performed using Olfactory Function Assessment by Com-puterized Testing (OLFACT) (Osmic Enter-prises, Inc.). Based on the University of Pennsylvania Smell Identification Test (UPSIT), OLFACT tests were computer-ized, standardcomputer-ized, and self-administered. Higher scores indicated better ability to detect, identify, and memorize odors. Threshold testing was performed by a series of binary dilutions of n-butanol
solution in light mineral oil, and scores ranged from 1 to 13.5. Olfactory identi-fication and memory tests included two tasks: task A with 10 different odors (menthol, clove, leather, strawberry, li-lac, pineapple, smoke, soap, grape, and lemon), and task B with 20 odors (ba-nana, garlic, cherry, baby powder, grass, tutti-frutti, peach, chocolate, dirt, or-ange, and the 10 odors in the task A). Each participant was asked to identify each odor from four pictures in tasks A and B and to indicate whether each was old or new in task B. There was a 10-min break between the two tasks.
Odor-Induced fMRI
fMRI Paradigm
The odor-induced fMRI task was used as previously described (Supplementary Fig. 2) (14). Each participant underwent a series of scans to measure temporal brain response to four increasing con-centrations of lavender odors (0.032%, 0.10%, 0.32%, and 1.0) diluted in 1,2-propanediol (Sigma-Aldrich, St. Louis, MO). The visual cues of“+” and “smell” were used for baseline and odor stimu-lation, respectively. Each concentration was assessed three times, with fresh air and scent occurring alternately. Partic-ipants were instructed to press a button once they smelled the lavender scent.
MRI
Brain MRI data were acquired using a 3.0T MR-scanner (Achieva TX; Philips Medical Systems, Eindhoven, the Nether-lands) with an eight-channel head coil. fMRI was acquired with a gradient-echo planar imaging sequence scan (repetition time 2,000 ms, echo time 30 ms,field of view 192 mm3 192 mm 3 140 mm, slice thickness 4 mm, gap 0 mm,flip angle 90°, and voxel size 3 mm3 3 mm 3 4 mm), with 230 volumes for resting state and 222 volumes for task. Structural images were acquired with high-resolution T1-weighted three-dimensional fast field echo (3D-FFE) structural scans (repeti-tion time 9.7 ms, echo time 4.6 ms,field of view 256 mm3 256 mm 3 192 mm, flip angle 8°, and voxel size 1 mm 3 1 mm3 1 mm).
Data Preprocessing
Preprocessing of fMRI data was performed using Statistical Parametric Mapping 8 (SPM) and Data Processing & Analysis for Brain Imaging (DPABI_V3.1_180801) (20) in the following stages: 1) removing
thefirst six time points in the task sequence andfirst 10 time points in the resting state sequence, 2) correction for head move-ment, 3) segmentation of high-resolution T1 image and alignment with fMRI image, 4) spatial normalization to Montreal Neu-rological Institute (MNI) space template, 5) spatial smoothing, and 6) linear detrending and temporal bandpass filtering (0.01– 0.08 Hz) for resting state sequence. Par-ticipants with excessive head movement or image artifacts (.2.5° rotation or .2.5 mm shift) were excluded.
Brain Activation Analysis
A general linear model was used to estimate odor-induced brain activation. Contrasts between“fresh air . rest” and “scent . rest” for each participant were made. Bilateral parahippocampus, amyg-dala, piriform cortex, insula, orbitofron-tal cortex, and hippocampus in AAL templates and Brodmann areas 28 and 34 (entorhinal cortices) were extracted and merged as olfactory regions of in-terest (ROIs) (total cluster size 5,029 voxels) for further analyses (14).
Functional Connectivity Analysis
Brain regions showing significantly dif-ferent activations among control sub-jects and nonobese and obese patients with diabetes were selected as seed regions for functional connectivity anal-yses to determine correlations between the two olfactory brain regions.
GLP-1Ra Treatment of Obese Patients with Diabetes
After information collection, olfactory and cognitive assessments, and fMRI scans, obese subjects with diabe-tes with inadequate glycemic control (HbA1c between 7% (53 mmol/mol)
and 9% (75 mmol/mol)), a stable dose of 1,500 mg daily metformin monother-apy, and stable weight were included in the GLP-1Ra group. Patients receiv-ing dipeptidyl peptidase 4 inhibitors and incretin-based or insulin therapy were excluded (Supplementary Fig. 1). Twenty obese individuals with type 2 diabetes were included, provided writ-ten informed consent before participa-tion, and were randomized to liraglutide (Victoza) or exenatide (Byetta) treat-ment. Liraglutide was administered starting at 0.6 mg daily and, if well tolerated, increased to 1.2 mg and then 1.8 mg daily within 2 weeks. Exenatide (Byetta) was administered
starting at 5 mg twice daily and in-creased to 10 mg twice daily within 2 weeks.
After 3-month GLP-1Ra treatment, these patients underwent anthropomet-ric and biochemical measurements, stan-dard meal tolerance tests, and cognitive, olfactory, and odor-induced fMRI eval-uation. A MoCA alternative version was used to avoid duplication. Olfactory tests and odor-induced fMRI scans used the same procedures as used at baseline. One patient treated with liraglutide was excluded for image artifacts, and there-fore 19 obese patients with diabetes were included for further analyses.
Statistical Analysis
Clinical Data, Cognitive Assessment, and Olfactory Tests
Analyses were performed using SPSS software (version 20.0; SPSS, Chicago, IL). One-way analysis and post hoc tests (Dunnett’s T3) of variance (ANOVA) were performed for continuous variables and Pearson x2 for dichotomous variables. Independent-samples t tests were per-formed to compare duration and body fat distribution in groups with diabetes. Paired t tests were used to investigate effects of 3-month GLP-1Ra treatment on anthropometric and metabolic parame-ters. Liner regression with vascular risk factors included was applied to compare cognitive and olfactory functions among three groups. Mixed model regression including age, sex, education, and vas-cular risk factors showing significant dif-ferences after treatment was used to evaluate the effects of GLP-1Ras on olfaction and cognition in obese subjects with diabetes. P , 0.05 indicated sta-tistical significance.
fMRI Data Analysis
fMRI data were analyzed by DPABI soft-ware. One-way ANCOVA was performed to determine the differences in brain activation and seed-based functional connectivity among three groups with correction for age, sex, education, and vascular risk factors (blood pressure and serum lipids). Paired t tests were con-ducted to investigate effects of GLP-1Ra treatment on olfactory functional alter-ations in obese patients with diabetes. The significance threshold correction was based on Gaussian random field (GRF) theory with a voxel level of P, 0.001 and a cluster level of P, 0.05.
Correlation and Mediation Analysis
For assessment of relationships between olfactory test scores and cognitive as-sessments, partial rank correlation anal-ysis corrected for age, sex, and education was performed. Additionally, a Bonferroni correction was applied to reduce the inflation of type 1 error from multiple comparisons.
For determination of how metabolic parameters influenced cognition through olfaction, linear regression was per-formed for mediation analyses using the PROCESS SPSS macro (21). All analyses involved 5,000 bias-corrected bootstrap 95% CIs, and P, 0.05 indicated statistical significance.
Sample Size Calculation
Based on the brain activation changes in the olfactory regions of interest in the odor-induced task fMRI of our previous study (14), for achievement of 90% power and detection of differences among the means (SD 0.52) in a one-way ANOVA study at a 0.05 significance level, the sample size is no less than 32 individuals for each group in three groups. PASS (Power Analysis and Sample Size) software (version 11; NCSS, LLC, Kaysville, UT) was used to estimate the sample size.
RESULTS
Lower General Cognition Scores in Obese Subjects With Type 2 Diabetes
Control subjects and nonobese and obese participants with diabetes were matched for age, sex, educational years, and alcohol and smoking habits. Patients with diabetes had higher HbA1c, fasting
and 2-h plasma glucose, HOMA2 of in-sulin resistance (HOMA2-IR), and rest-ing systolic blood pressure and lower HDL levels compared with control sub-jects. Obese individuals with diabetes had higher fasting and 2-h C-peptide levels, HOMA2-IR, HOMA2 of b-cell function (HOMA2-B), and fat ratio in the trunk and android region compared with nonobese subjects with diabetes (Table 1).
Compared with nonobese subjects with diabetes, obese subjects with di-abetes had significantly lower general cognitive scores on the MMSE (29.06 1.3 vs. 28.4 6 1.2, P = 0.014) after adjustment for blood pressure and HDL level. No statistically significant dif-ferences were observed between the
two diabetes groups in other cognitive subdomains except for working memory (Table 1).
Impaired Olfactory Function, Decreased Odor-Induced Brain Activation, and Disrupted Seed-Based Functional Connectivity in Obese Subjects with Diabetes
Compared with that in nonobese partic-ipants with diabetes, olfactory threshold score was lower in obese subjects with diabetes (9.7 6 2.4 vs. 8.3 6 2.8, P = 0.028), indicating that obese patients with diabetes exhibited impaired abil-ity to detect odors. There were no significant differences in olfactory identification or memory tests scores among the three groups (Table 1). Meanwhile, subgroup analyses in con-trol subjects and subjects with diabetes with intact cognition (MoCA $26) showed that subjects with diabetes likewise had lower olfactory threshold score than control subjects (Supplementary Table 1).
Decreased activation in left hippocam-pus was observed in patients with di-abetes compared with control subjects after correction for age, sex, education, and vascular risk factors. These decreases were more pronounced in obese subjects with diabetes than those in nonobese subjects with diabetes (with GRF correc-tion, voxel level P, 0.001, cluster level P , 0.05, and cluster size threshold 14 voxels) (Fig. 1A and Supplementary Table 2). Moreover, subgroup analyses in cognitively intact subjects with diabetes and control subjects also demonstrated significant decreased left hippocampal activation in subjects with diabetes (Supplementary Fig. 3).
Further, olfactory brain regions that showed significantly different activations among the three groups during the task in the left hippocampus and surrounding areas were used as seed regions for resting state functional connectivity analyses. Obese patients with diabetes exhibited decreased functional connec-tivity between seed regions and right insula compared with nonobese subjects with diabetes and control subjects (with GRF correction, voxel level P, 0.001, cluster level P, 0.05, and cluster size threshold 23 voxels) (Fig. 1B and Supplementary Table 2). These results indicated that obese patients with di-abetes had more pronounced olfactory
function impairment, decreased olfac-tory brain activation, and disrupted seed-based functional connectivity com-pared with nonobese subjects with di-abetes and control subjects.
Olfactory Function and Brain Activation Mediated Adiposity and Insulin Release in Cognitive Function of Participants with Diabetes
After adjustment for age, sex, and edu-cation with a Bonferroni correction with a rigorous P, 0.0018, both olfac-tory threshold and olfacolfac-tory test total score showed significantly positive ciations with MoCA and negative asso-ciations with executive function time in patients with diabetes (Supplementary Table 3). Meanwhile, left hippocampus (seed regions) activation showed positive correlation with olfactory (r = 0.376, P = 0.002) and MoCA (r = 0.322, P = 0.008) test scores after adjustment for age, sex, and education (Supplementary Fig. 4A and B). Mediation analysis revealed that left hippocampal activation impacted general cognition through olfactory func-tion (b = 0.567 [95% bootstrap CI 0.140, 1.282]) (Fig. 2A).
Next, we determined associations of metabolic parameters in diabetes with cognitive and olfactory assessments and odor-induced brain activation after ad-justment for age, sex, and education. Negative associations were observed be-tween BMI and left hippocampal activa-tion (r =20.328, P = 0.007), seed-based functional connectivity (r =20.321, P = 0.008), and olfactory test total score (r =20.254, P = 0.038) (Supplementary Fig. 4C–E). Interestingly, android region fat ratio also showed negative correlation with olfactory test total score (r =20.314, P = 0.016) and episodic memory (r =20.300, P = 0.022) (Supplementary Fig. 4F and G). Meanwhile, fasting insulin release positively correlated with left hippocampal activation (r = 0.302, P = 0.013) and negatively corre-lated with processing speed test time (r =20.319, P = 0.009) (Supplementary Fig. 4H and I).
Further, mediation analyses with cor-rection for age, sex and education showed that olfactory test total score mediated the correlation between an-droid region fat ratio and episodic memory (b = 20.884 [95% bootstrap CI21.987, 20.1168]) (Fig. 2B). Mean-while, left hippocampus activation also
mediated the association between BMI and olfactory function (b =20.174, 95% bootstrap CI [20.437, 20.024]) (Fig. 2C) and that between fasting insulin
release and processing speed time (b = 20.531 [95% bootstrap CI 21.346, 20.047]) (Fig. 2D). Taken together, both olfactory function and
brain network showed mediating ef-fects on relationships of adiposity and insulin release with cognitive function in diabetes (Fig. 2E).
Table 1—Demographics, clinical and metabolic characteristics, cognitive assessment scores, and olfactory test scores Index Control subjects (n = 35) Nonobese subjects with diabetes (n = 35) Obese subjects with diabetes (n = 35) P value, all P value, diabetes Demographic factors Age (years) 50.36 8.0 51.26 8.0 50.86 10.3 0.916 0.997 Male sex (n, %)# 19, 54.3 20, 57.1 20, 57.1 0.962 1.000 Education (years) 12.96 3.2 12.86 2.9 12.56 2.4 0.761 0.915 Alcohol consumption (%)# 10, 28.6 8, 22.9 12, 34.3 0.571 0.290 Smoking habits (%)# 11, 31.4 13, 37.1 12, 34.3 0.881 0.803 Diabetes-related characteristics
Duration of diabetes (years)§ d 9.16 5.2 8.96 5.9 d 0.879
HbA1c(%) 5.66 0.3 8.36 1.4 8.16 1.3 ,0.001* 0.958
HbA1c(mmol/mol) 386 3.3 676 15.3 656 14.2 d d
Fasting glucose (mmol/L) 5.06 0.4 8.36 2.3 7.66 1.7 ,0.001* 0.481 2-h postprandial glucose (mmol/L) 6.06 1.1 14.26 4.6 14.36 4.2 ,0.001* 0.999 Fasting insulin (mIU/mL) 8.46 4.0 10.46 17.0 12.76 9.1 0.160 0.099 2-h postprandial insulin (mIU/mL) 53.26 39.5 29.46 23.9 42.66 35.9 0.007* 0.071 Fasting C-peptide (pmol/L) 697.16 208.4 581.26 252.2 868.56 380.8 ,0.001* 0.001* 2-h postprandial C-peptide (pmol/L) 2,712.86 1,067.8 1,4286 690.8 1,956.16 974.1 ,0.001* 0.033*
HOMA2-IR 1.06 0.5 1.66 0.6 2.16 1.0 ,0.001* 0.005* HOMA2-B 101.36 28.2 52.76 28.7 79.56 40.3 ,0.001* 0.007* Obesity-related characteristics BMI (kg/m2) 23.76 2.5 24.56 2.2 32.16 2.0 ,0.001* ,0.001* Weight (kg) 65.46 8.4 68.36 8.5 88.26 12.3 ,0.001* ,0.001* Waist circumference (cm) 83.56 7.9 88.96 5.7 103.86 10.9 ,0.001* ,0.001* WHR 0.866 0.06 0.926 0.04 0.986 0.08 ,0.001* ,0.001*
Body fat testing by DEXA§ n = 32 n = 29
Arms (% fat) 11.76 1.8 11.06 2.1 0.195
Legs (% fat) 25.26 5.1 22.66 4.1 0.033*
Trunk (% fat) 57.96 6.0 62.56 5.2 0.003*
Android area (% fat) 9.26 1.7 11.06 1.6 ,0.001*
Gynoid area (% fat) 13.16 2.0 12.46 1.8 0.137
Vascular risk factors
Systolic blood pressure (mmHg) 122.36 16.7 129.76 11.9 137.26 15.9 ,0.001* 0.081 Diastolic blood pressure (mmHg) 78.36 14.7 80.36 9.7 85.46 12.5 0.054 0.172
TG (mmol/L) 1.56 0.9 1.56 0.7 1.86 1.1 0.243 0.422 TC (mmol/L) 4.86 0.9 4.56 1.1 4.66 1.3 0.514 0.964 HDL cholesterol (mmol/L) 1.36 0.4 1.16 0.4 1.06 0.3 0.010* 0.587 LDL cholesterol (mmol/L) 2.86 0.9 2.66 0.8 2.76 1.1 0.697 0.895 Cognitive assessment& MoCA,26 (n, %)# 0 7, 20.0 8, 22.9 d 0.569 MMSE 29.26 0.8 29.06 1.3 28.46 1.2 0.037* 0.014* MoCA 28.36 1.4 27.46 2.3 26.66 2.11 0.004* 0.050 Episodic memory† 0.206 0.96 0.056 1.06 20.25 6 0.96 0.146 0.162 Working memory† 0.176 0.87 0.246 1.03 20.41 6 0.99 0.063 0.019* Wordfluency† 0.176 1.06 20.17 6 1.00 0.006 0.93 0.498 0.704 Processing speed (time)† 20.10 6 0.95 20.10 6 0.86 0.216 1.17 0.559 0.145 Executive functions (time)† 20.13 6 0.9 20.04 6 1.02 0.176 1.08 0.299 0.306 Olfactory test&
Olfactory threshold 10.66 2.7 9.76 2.4 8.36 2.8 0.008* 0.028* Odor identification task A (10 odors) 8.66 1.0 8.36 1.1 8.46 1.7 0.943 0.969 Odor identification task B (20 odors) 15.76 1.9 15.76 2.0 15.06 2.8 0.786 0.254 Odor memory test (10 old odors) 8.16 1.2 8.16 1.5 7.66 1.7 0.308 0.215 Odor memory test (10 new odors) 8.06 1.2 7.76 1.4 7.66 1.7 0.728 0.809 Olfactory test total score 50.96 4.7 49.66 5.9 46.86 8.0 0.183 0.098 Data are means6 SD and, as indicated, mean standardized z scores 6 SD. TC, total cholesterol; TG, triglycerides. One-way ANOVA and post hoc tests (Dunnett’s T3). #Pearson x2analysis for dichotomous variables, and §independent samples t test for duration and DEXA data. &Adjusted for systolic and diastolic blood pressure and HDL cholesterol.†Mean standardized z scores 6 SD. *P , 0.05 was considered significant.
Ameliorative Effects of GLP-1Ra Treatment on Cognitive and Olfactory Function and Odor-Induced Brain Functional Activation in Obese Subjects with Diabetes
Significantly, GLP-1Ra treatment for 3 months resulted in an average of 6.1 kg weight loss (89.4 6 14.4 vs. 83.3 6 13.6, P , 0.001) and a 1.6% (16.4 mmol/mol) HbA1cdecrease (636
9.8 vs. 46 6 10.9 mmol/mol, P , 0.001) in obese patients with diabetes (Supplementary Table 4). In addition, 2-h postprandial insulin, C-peptide, and HDL cholesterol levels were increased while systolic blood pressure was de-creased when compared with baseline (P, 0.05).
Of note, general cognition (MoCA) (26.66 2.4 vs. 27.9 6 1.9, P = 0.014) and olfactory function (48.5 6 8.4 vs. 50.06 8.3, P = 0.008) were increased after treatment with adjustment for age, sex, education, duration, and blood pres-sure. Particularly, the cognitive subdo-mains of recall memory (2.8 6 1.4 vs. 3.76 1.2, P = 0.005) and olfactory iden-tification ability (15.6 6 3.0 vs. 16.6 6 2.9, P = 0.002) were improved (Supplemen-tary Table 4). In addition, significantly in-creased right parahippocampus activation was observed in obese patients with di-abetes compared with baseline (with GRF correction, voxel level P, 0.001, cluster level P, 0.05, and cluster size threshold 13 voxels) (Fig. 3 and Supplementary Table 5). No differences were found after treat-ment in other cognitive subdomains. No cluster was found after GRF correction in the seed-based functional connectivity analysis.
Importantly, reduced significance of GLP-1Ra effects on MoCA, recall mem-ory, olfactory identification, and olfac-tory test total score was observed when BMI or HbA1cor both were included in
the mixed models (Supplementary Table 6). In addition, no difference of func-tional activation in the right parahippo-campus was observed when neither HbA1c nor BMI was included as a
co-variate (with GRF correction, voxel level P, 0.001 and cluster level P , 0.05, and no cluster was found). There were no significant differences in metabolic characteristics, cognitive assessment, olfactory test scores, or odor-induced brain activation between liraglutide and exenatide treatments (Supplementary Table 7).
Figure 1—Odor-induced brain activation and seed-based functional connectivity among control subjects (n = 35) and nonobese (n = 35) and obese (n = 35) subjects with type 2 diabetes (T2DM) adjusted for covariates of age, education, BMI, and vascular risk factors. ANCOVA indicated significantly decreased odor-induced brain activations in obese subjects with diabetes compared with nonobese subjects with diabetes and control subjects (cluster size threshold: 14 voxels), specifically in left hippocampus. These regions showing significant difference among three groups were taken as seed regions for functional connectivity analysis (A). Significantly decreased functional connectivity with right insula was demonstrated in obese subjects with diabetes compared with nonobese subjects with diabetes and control subjects (with GRF correction, voxel level P, 0.001, cluster level P , 0.05, and cluster size threshold 23 voxels) (B). *P , 0.05, **P , 0.01, and ***P, 0.001 were considered significant. L, left.
CONCLUSIONS
This study found that obese individuals with type 2 diabetes exhibited pro-nounced impaired general cognition, olfac-tory threshold score, odor-induced brain activation, and seed-based func-tional connectivity relative to subjects with nonobese diabetes. Adiposity negatively correlated, while insulin re-lease positively correlated, with cogni-tive function in patients with diabetes.
Olfactory function and functional net-work performed mediating roles in these correlations. GLP-1Ra treatment signi fi-cantly improved MoCA and olfactory test total score and increased odor-induced brain activation in subjects with obese diabetes.
Cognitive dysfunction in patients with diabetes has attracted much attention in research and clinical care (22). Diabetes-associated cognitive decrements are re-ported to develop ;50% faster than
those in normal cognitive aging (5). Moreover, ample scientific and epidemi-ological research has shown that obesity and its accompanied adverse health con-ditions are related to cognitive impair-ment (23). Obese subjects with diabetes, especially those with central obesity, are reported to have worse cognitive func-tion and higher risk of dementia than normal-weight patients with type 2 di-abetes (8,24). This study also showed pronounced decrements in general
Figure 2—Mediation models including olfactory system as mediators of the associations among adiposity, insulin release, and cognitive function in diabetes. Associations of left hippocampus activation, the mediator of olfactory test score, and MoCA scores (n = 70) (A); associations of android region fat ratio, the mediator of olfactory test total score, and episodic memory (n = 61) (B); associations of BMI, the mediator of left hippocampus activation, and olfactory test total score (n = 70) (C); and associations of fasting insulin, the mediator of left hippocampus activation, and processing speed test time (n = 70) (D). These mediation models indicated that olfactory system mediated adiposity and insulin release in cognitive function in diabetes (E). Standardizedb-coefficient was derived from mediation models controlling for age, sex, and education. Values are standardized path coefficients with SEs or 95% CIs in parentheses. *P, 0.05, **P , 0.01, and ***P , 0.001 was considered significant.
cognition of obese subjects with diabetes compared with nonobese subjects with diabetes (Table 1).
Olfactory dysfunction is considered an early predictor of neurodegeneration and is associated with late-life cognitive impairment (25). And olfactory testing is a useful utility for screening cognitive decline progression due to its indepen-dence from cognitive confounds such as intelligence quotient and education. Lower scores on olfactory function test were observed in patients with type 2 diabetes and were related to poor cognitive performance (26). This study and our previous work (14) also demonstrated lower olfactory threshold scores in patients with diabetes than in control subjects and positive associations of olfactory function with general cog-nition and executive function with use of a Bonferroni correction with a rigorous P, 0.0018 (Supplementary Table 3).
Neuroimaging techniques MRI and fMRI provide early diagnostic insights for neurological diseases by detecting deep brain structures and providing real-time neurofeedback. MRI studies showed that obese people with type 2 diabetes had reduced cortical thick-ness compared with normal-weight peo-ple with diabetes (8). Similarly, we also
observed smaller intracranial volume in obese individuals with diabetes (Supplementary Table 8). Moreover, fMRI bridges the gap between brain structures and behavioral function by tracking neural reactions to various ex-ternal stimuli and tasks (7). Previously, most task-based fMRI studies in obese patients with diabetes focused on eat-ing behavior and neural activations in reward and motivation systems and evaluated therapeutic effects of antidia-betes drugs or bariatric surgery on brain reactions to food cues (6,27,28). Our previous work firstly provided new functional neuroimaging insights into the cognition-associated olfactory net-work in patients with type 2 diabetes and reported that these patients with intact cognition exhibited decreased olfactory activation and disrupted olfactory func-tional connectivity (14).
Both our subgroup analyses in cogni-tively intact individuals (Supplemen-tary Table 1 and Supplemen(Supplemen-tary Fig. 3) and our previous study (14) showed impaired olfactory performance and dis-rupted olfactory functional alterations in subjects with diabetes compared with control subjects, supporting the idea that such olfactory abnormalities were specifically related to type 2 diabetes.
Noteworthy, obese patients with diabe-tes in this study showed impaired general cognition, olfactory threshold, decreased odor-induced left hippocampus activa-tion, and disrupted seed-based func-tional connectivity compared with nonobese subjects with diabetes (Table 1 and Fig. 1), indicating that obese people with diabetes suffered more pronounced cognitive and olfactory dysfunction than nonobese subjects with diabetes.
Further, we investigated the inherent link of olfaction with adiposity and cog-nition in diabetes. We found a negative correlation of the android region fat ra-tio with cognitive funcra-tion in diabetes (Supplementary Fig. 4G). Meanwhile, olfactory function and olfactory cortex activation served as mediators between adiposity and cognitive function after adjustment for age, sex, and education (Fig. 2B and C). Indeed, the brain olfac-tory network not only serves as a nutritional sensor in the reward circuit (29) but also has direct connections to the hippocampus, a brain region vital to memory and primarily affected in dementia and functions in odor memory processing (30). In mammals, brain olfactory structures of olfactory epithelium, olfactory bulb, piriform cortex, and hippocampus are reported
Figure 3—Odor-induced brain activation in obese patients with diabetes treated with GLP-1Ras for 3 months (n = 19). Paired t tests demonstrated significantly increased odor-induced brain activation in obese diabetes (with GRF correction, voxel level: P , 0.001, cluster level: P , 0.05, cluster size threshold: 13 voxels), specifically in right parahippocampus. ***P , 0.001 was considered significant. L, left.
to express a high density of metabolic hormone receptors (31). Previous studies showed that adipokines secreted from adipose tissues, such as leptin and adi-ponectin, bind to receptors on olfactory sensory neurons and enhance synaptic plasticity (32). Metabolic disorders dis-turb these pathways in olfactory areas, causing loss of olfactory neurons in rats (33) and resulting in chronic olfactory impairment and aberrant brain activa-tion patterns in response to odors (34), which may result in dysfunctional odor memory processing.
Extensive efforts have been spent exploring lifestyle or drug interventions to delay dementia (22). Some antidia-betes drugs exhibit therapeutic effects on neurological diseases (35), particu-larly GLP-1Ras. In addition to inducing weight loss, and improving glucose ho-meostasis and cardiovascular function, GLP-1Ras are shown to cross the blood-brain barrier and exert neuroprotective effects (36). GLP-1Rs are distributed in mammalian brains (15). In mouse mod-els, glucagon-like peptide 1 was reported to increase activity of mitral cells that encode olfactory information in the ol-factory bulb by decreasing activity of the voltage-dependent potassium channels, Kv1.3 (37). GLP-1Ras were shown to improve synaptic plasticity and recogni-tion memory by stimulating neurogene-sis, reduce neurotoxic amyloid oligomer levels, and alleviate neuroinflammation and oxidative stress in rats (36). Human studies indicated that GLP-1Ra therapies reduced decline of brain glucose metab-olism and cognition in Alzheimer disease patients (16) and reduced brain activa-tion response to food stimulaactiva-tions in patients with type 2 diabetes (27). This study provided new evidence of therapeutic effects of GLP-1Ras on cog-nition, olfactory function, and olfactory brain activity in obese diabetes. In this study, GLP-1Ra treatment for 3 months significantly improved MoCA, olfactory test total score, and olfactory brain activation (Fig. 3 and Supplementary Tables 4 and 5). Such neuroprotective effects of GLP-1Ras might benefit from reducing visceral fat and potentially relevant to glucose homeostasis or its own effects on neurogenesis. Neverthe-less, the significant effects of GLP-1Ras on MoCA, recall memory, olfactory test total score, and odor-induced func-tional activation were weakened or
disappeared when BMI or HbA1c was
included as a covariate (Supplementary Table 6), indicating that such GLP-1Ra– related improvements may have oc-curred partly through glycemic control and weight loss. Long-term evaluations are necessary to determine the cogni-tive outcomes of GLP-1Ra therapies in diabetes.
Of note, this study had two major strengths: distinguished from conven-tional olfactory assessment tools such as the UPSIT and Open Essence test (12), the olfactory function test in this study was designed based on the UPSIT and conducted by computerized processes that regulated time, duration, and odor concentrations and automatically recorded and scored performance to ensure data accuracy and reliability. Sec-ondly, regarding olfactory fMRI techni-ques, we verified the reproducibility of odor-induced fMRI signals (38) and ap-plied rigorous thresholds and covariate corrections to minimize inflated false positive rates resulting from multiple comparisons in fMRI data (39).
The limitations of the current study were as follows. Firstly, relationships among adiposity, olfactory function, and cognition in diabetes were dem-onstrated in this observational study; however, the potential causal role of obesity-diabetes status on olfaction and cognition should be evaluated in the future. Moreover, severe or morbidly obese patients with diabetes were not in-cluded in this study due to the MRI space constraint. Additionally, although this study demonstrated that the preclinical cognitive and olfactory dysfunction in obese patients with diabetes was im-proved by GLP-1Ra treatment, whether GLP-1Ras show ubiquitous neuroprotec-tive effects in all people with diabetes cannot be determined, as nonobese sub-jects with diabetes in this study did not receive GLP-1Ra treatment. Further ran-domized controlled trials are also war-ranted to clarify whether the risk of cognitive outcome events can be re-duced by GLP-1Ra therapy in patients with diabetes with clinical cognitive im-pairment.
In conclusion, this pilot study demon-strated that obese patients with diabetes had more pronounced impairment in cognitive and olfactory function and more disrupted odor-induced brain func-tional activity than nonobese diabetes.
Olfaction mediated adiposity in cognition of patients with diabetes. Of note, cognitive and olfactory abnormalities can be amelio-rated by GLP-1Ra treatment. This study characterized cognition and related brain functional changes in obese patients with diabetes, enhanced the significance of ol-factory dysfunction as an early diagnostic signal for cognitive decline in these patients, and provided corresponding potential ther-apeutic approaches.
Acknowledgments. The authors thank all vol-unteers for their participation in this study and thank medical personnel from Department of Endocrinology and Department of Radiology, Drum Tower Hospital, for their valuable assis-tance.
Funding. This study was supported by grants from the National Natural Science Foundation of China (81570737, 81570736, 81770819, 81500612, 81400832, 81600637, 81600632, 81703294, 81800752, and 81800719), the Na-tional Key Research and Development Program of China (2016YFC1304804 and 2017YFC1309605), the Jiangsu Provincial Key Medical Discipline (ZDXKB2016012), Jiangsu Provincial Medical Talent (ZDRCA2016062), the Key Project of Nanjing Clinical Medical Science, the Key Research and Development Program of Jiangsu Province of China (BE2015604 and BE2016606), the Six Talent Peaks project of Jiangsu Province of China (WSN-165 and SWYY-091), the Fundamental Research Funds for the Central Universities (021414380208, 021414380142, and 021414380160), the Nanj-ing Science and Technology Development Project (201605019), and the Medical Scien-tific Research Foundation of Jiangsu Province of China (Q2017006).
Duality of Interest. No potential conflicts of interest relevant to this article were reported. Author Contributions. Z.Z. contributed to data collection and statistical analyses and wrote the manuscript. B.Z. designed the protocol and re-viewed the manuscript. X.W. contributed to data collection and MRI analysis and wrote the man-uscript. X.Z. and Q.X.Y. designed the protocol. Z.Q. contributed to MRI analysis. W.Z. contrib-uted to data collection. D.Z. conceived and designed the study. Y.B. designed the study and oversaw all clinical aspects of study conduct and manuscript preparation. Y.B. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Prior Presentation. Parts of this study were presented in abstract form at the 12th Inter-national Diabetes Federation Western Pacific Region Congress/10th Scientific Meeting of Asian Association for the Study of Diabetes, Kuala Lumpur, Malaysia, 22–25 November 2018.
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