Amyloid deposition and small vessel disease are associated with cognitive function in older adults with type 2 diabetes

Diabetes is associated with cognitive decline, but the underlying mechanisms are complex and their relationship with Alzheimer’s Disease biomarkers is not fully understood. We assessed the association of small vessel disease (SVD) and amyloid burden with cognitive functioning in 47 non-demented older adults with type-2 diabetes from the Israel Diabetes and Cognitive Decline Study (mean age 78Y, 64% females). FLAIR-MRI, Vizamyl amyloid-PET, and T1W-MRI quantified white matter hyperintensities as a measure of SVD, amyloid burden, and gray matter (GM) volume, respectively. Mean hemoglobin A1c levels and duration of type-2 diabetes were used as measures of diabetic control. Cholesterol level and blood pressure were used as measures of cardiovascular risk. A broad neuropsychological battery assessed cognition. Linear regression models revealed that both higher SVD and amyloid burden were associated with lower cognitive functioning. Additional adjustments for type-2 diabetes-related characteristics, GM volume, and cardiovascular risk did not alter the results. The association of amyloid with cognition remained unchanged after further adjustment for SVD. Our findings suggest that SVD and amyloid pathology may independently contribute to lower cognitive functioning in non-demented older adults with type-2 diabetes, supporting a multimodal approach for diagnosing, preventing, and treating cognitive decline in this population.


Introduction
Diabetes is consistently associated with cognitive decline and dementia 1 .Various factors have been suggested to contribute to this association, including altered insulin signaling, hyperglycemia, advanced glycation, chronic low-grade in ammation, small vessel disease (SVD), large vessel disease, and Alzheimer's disease (AD) pathology 2 , but speci c pathways and their relationship with AD biomarkers are complex and not fully understood.Brain imaging correlates for some of these pathological mechanisms include white matter hyperintensities (WMH) as a measure of SVD, total gray matter (GM) thickness/volume as a measure of atrophy, and quanti ed amyloidbeta (Aβ) load on amyloid-PET.
WMHs are thought to re ect demyelination and axonal loss as a consequence of chronic ischemia caused by cerebral SVD 3 .Diabetesrelated abnormalities in small vessels, such as seen throughout the body in patients with diabetes, may be the cause of such microangiopathic brain changes.In agreement, WMHs have been shown to be more prevalent in patients with diabetes and linked to cognition and cognitive decline 3,4 , though were found insu cient to explain all the associations between diabetes and cognition 4 .
The association between diabetes and AD is controversial.Some studies have shown that diabetes is associated with increased risk for clinical AD 5 , though most clinico-pathological studies have failed to show such an association 6 .Other studies even found lower AD pathology in brains of patients with diabetes 7,8 .In line with the clinico-pathological studies, many AD biomarker-based studies encompassing PET imaging or cerebro-spinal uid (CSF) found no association between diabetes and AD biomarkers 9 .
The association of amyloid pathology and cognitive functioning is also controversial with some studies showing that higher amyloid pathology is associated with lower cognitive functioning 10 , while others showing no such association 11 .There is scarce knowledge about the impact of amyloid deposition on cognition in patient with diabetes 12 .
In this work we aim to assess the association between SVD, amyloid burden measured by PET imaging, and GM volume with cognitive functioning in older adults with type-2 diabetes (T2D).We hypothesize that both pathological biomarkers are associated with cognition in patients with diabetes, contributing to the lower cognitive functioning and higher dementia rates seen in this population.

Amyloid SUVR and cognitive functioning
Higher Aβ-SUVR was associated with lower global cognitive functioning, adjusting for demographics and the time interval between PET and cognitive testing (Model 1: β=-1.30,SD=0.47, p=0.01;Table 2).The association of Aβ-SUVR with global cognition was essentially unchanged with increasing degree of adjustments of covariates, type-2 diabetes characteristics (Model 2), GM volume (Model 3), and cardiovascular risk and depression (Model 4).Except for education (β=0.12,SD=0.03, p<0.001), all covariates were not associated with global cognition (Table 2) Similar models for the cognitive domains showed that higher Aβ-SUVR was signi cantly associated with worse executive and language functioning when adjusting for demographics (β =-1.47,SD=0.49, p=0.004 and β=-1.20,SD=0.55, p=0.04, respectively, Figure 1 and supplementary table 1).Additional adjustments for diabetes-related characteristics, and then also for total GM volume, did not alter the results.Amyloid in the frontal, parietal, cingulate, and temporal cortices was associated with cognition.The beta estimates of the models across the four regions were similar (Supplementary table 2), suggesting that amyloid deposition affects the brain globally in a similar way.
Further adjustment for total GM volume did not alter the results (Supplementary table 2, model 2).
As Aβ-SUVR and WMH were both associated with cognition we sought to further assess the relationship between the two and GM volume.In a secondary analysis using Spearman's rank-order correlation, we found no associations between the three brain measures as shown in supplementary Table 3.
Finally, the association between Aβ-SUVR and global cognition remained unchanged when adding WMH as covariate in addition to adjustment for type-2 diabetes related characteristics and GM (β=-1.17,SD=0.44, p=0.01).

Discussion
In this cross-sectional study of non-demented older adults with type-2 diabetes we found that higher amyloid pathology and WMH volume were associated with lower cognitive functioning after adjusting for sociodemographic variables, type-2 diabetes related characteristics, GM volume, and cardiovascular risk.Further adjustment for WMH showed that the association of amyloid with cognitive functioning remains signi cant.Taken together, our ndings suggest that amyloid and SVD are distinct pathological mechanisms that independently contribute to lower cognitive functioning in non-demented older adults with type-2 diabetes.
Recent work from MEMENTO 12 , a clinic-based cohort that recruits non-demented older adults, showed that SVD, neurodegeneration, and amyloid pathology are independently associated with lower cognition and that the association between diabetes and cognition is mainly mediated by greater neurodegeneration.Our work is in line with these ndings, expands them to a population-based cohort, accounts for HbA1c, and adds the aspect of non-atrophy-dependent contribution of amyloid pathology to cognition.
Longitudinal studies indicate that cognitive decline is faster in amyloid positive cognitively normal adults 13 but cross-sectional studies show mixed results.Our ndings are in line with previous studies demonstrating an association between higher amyloid and cognitive impairment 10,14 , though other studies did not nd such an association 11 .This complex relationship between amyloid deposition and cognitive functioning may depend on the speci c cohort characteristics and disease stage.This is consistent with the robust association we observed between amyloid and executive functions, the cognitive domain most affected in diabetes 15 .
The rate of amyloid positivity in our cohort (11/47, 23%) were lower than the accepted rates for this age range, ~35% for 80Y with normal cognition 16 .Such lower amyloid positivity rates have been suggested before in patients with type-2 diabetes 17 and warrant further investigation in larger cohorts.Our results suggest that the association of amyloid with cognition does not depend on frank amyloid positivity since the best model t was linear, rather than quadratic and does not depend on the speci c localization of amyloid deposition.
Taken together, our ndings suggest that though lower rates of amyloid pathology may be seen in patients with type-2 diabetes, the presence of amyloid may be clinically important as it contributes to lower cognition independent of glycemic control level, SVD or brain atrophy.
Although data from cross-sectional studies have been ambiguous 3 , prospective studies demonstrate that SVD as indicated by WMHs is associated with, and directly contributes to, cognitive decline in the general population 3 .It has also been shown that type-2 diabetes is associated with higher levels of SVD 4 .Consistent with our ndings, some studies demonstrate an association between higher degree of SVD and lower cognitive functioning in patients with diabetes 12 .
Strengths of our study include measurable criteria (rather than self-reported) for type-2 diabetes diagnosis, a broad cognitive battery, amyloid-PET and MRI performed on the same patients with quanti able measurements for both.Limitations include the cross-sectional design, relatively small number of patients, risk for selection bias, and relatively small number of amyloid-positive scans.
In conclusion, we found that higher amyloid and SVD burden are independently associated with lower cognitive functioning, after adjusting for glycemic control.Our ndings suggest that multiple factors may independently contribute to cognitive decline in nondemented older adults with type-2 diabetes, indicating a multimodal and individualized approach for the prevention, diagnosis, and treatment of cognitive decline in this population.

Methods
Participants.This is a cross-sectional study utilizing the subset of subjects from the Israel Diabetes and Cognitive Decline Study (IDCD) cohort 18 that were randomly selected to have both amyloid-PET and brain MRI (scanned between 2013 and 2019).The IDCD is a longitudinal community-based cohort study that recruits cognitively normal, older adults (>65Y), with type-2 diabetes, from the Maccabi Healthcare Services, the second largest HMO in Israel, providing detailed medical information on each participant, including diagnoses, medications, and blood exams.
The research was conducted in accordance with the relevant ethical guidelines and regulations.Signed informed consent was obtained from all participants.The Research Ethics Committee of Icahn School of Medicine at Mount Sinai, Sheba Medical Center, and Maccabi Healthcare Services approved the study.

Glycemic control measurements.
Hemoglobin A1c (HbA1c) data was provided by Maccabi.All HbA1c levels available in Maccabi up to PET-date for amyloid analysis and MRI-date for WMH analysis were averaged for each participant and used as a measure of glycemic control.

Cardiovascular risk and depression.
Mean cholesterol levels and systolic and diastolic blood pressure measurements were provided by Maccabi and added to the statistical models.The score of the geriatric depression scale (GDS) at baseline was used as a measure of depression.
Preprocessing -T1-weighted images were processed using voxel-based morphometry (VBM http://www.l.ion.ucl.ac.uk/ spm/ext/#VBMtools) 20 and implemented in Statistical Parametric Mapping (SPM8) as previously described 21 .Total GM volume adjusted to total intracranial volume (ICV) was used for analysis.WMH volume was extracted from FLAIR images using SPM8 and its Lesion Segmentation Toolbox (LST) with k=0.15 as previously described 19