key: cord-1021942-djs061w4
authors: Novak, Vera; Mantzoros, Christos S.; Novak, Peter; McGlinchey, Regina; Dai, Weiying; Lioutas, Vasileios; Buss, Stephanie; Fortier, Catherine B.; Khan, Faizan; Aponte Becerra, Laura; Ngo, Long H.
title: MemAID: Memory advancement with intranasal insulin vs. placebo in type 2 diabetes and control participants: a randomized clinical trial
date: 2022-04-28
journal: J Neurol
DOI: 10.1007/s00415-022-11119-6
sha: 88ca83320f0f92a8912406e437958ec1ff52df0e
doc_id: 1021942
cord_uid: djs061w4

BACKGROUND: This study aimed at assessing the long-term effects of intranasal insulin (INI) on cognition and gait in older people with and without type 2 diabetes mellitus (T2DM). METHODS: Phase 2 randomized, double-blinded trial consisted of 24 week treatment with 40 IU of INI (Novolin(®) R, off-label use) or placebo (sterile saline) once daily and 24 week follow-up. Primary outcomes were cognition, normal (NW), and dual-task (DTW) walking speeds. Of 244 randomized, 223 completed baseline (51 DM-INI, 55 DM-Placebo, 58 Control-INI, 59 Control-Placebo; 109 female, 65.8 ± 9.1; 50–85 years old); 174 completed treatment (84 DM, 90 Controls); 156 completed follow-up (69 DM). RESULTS: DM-INI had faster NW (~ 7 cm/s; p = 0.025) and DTW on-treatment (p = 0.007; p = 0.812 adjusted for baseline difference) than DM-Placebo. Control-INI had better executive functioning on-treatment (p = 0.008) and post-treatment (p = 0.007) and verbal memory post-treatment (p = 0.004) than Control-Placebo. DM-INI increased cerebral blood flow in medio-prefrontal cortex (p < 0.001) on MRI. Better vasoreactivity was associated with faster DTW (p < 0.008). In DM-INI, plasma insulin (p = 0.006) and HOMA-IR (p < 0.013) decreased post-treatment. Overall INI effect demonstrated faster walking (p = 0.002) and better executive function (p = 0.002) and verbal memory (p = 0.02) (combined DM-INI and Control-INI cohort, hemoglobin A1c-adjusted). INI was not associated with serious adverse events, hypoglycemic episodes, or weight gain. CONCLUSION: There is evidence for positive INI effects on cognition and gait. INI-treated T2DM participants walked faster, showed increased cerebral blood flow and decreased plasma insulin, while controls improved executive functioning and verbal memory. The MemAID trial provides proof-of-concept for preliminary safety and efficacy and supports future evaluation of INI role to treat T2DM and age-related functional decline. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00415-022-11119-6.

Type 2 diabetes mellitus (T2DM) accelerates brain aging [1, 2] and increases risk for dementia [3] . Insulin plays a key role in energy metabolism, neurovascular coupling [4] and signaling among functional networks [5] [6] [7] . Brain insulin resistance, microvascular disease and impaired insulin signaling may be common pathways for cognitive decline in aging [5] , diabetes and Alzheimer disease [3, 4, 8] . Intranasal insulin (INI) enters the brain along the olfactory, trigeminal pathways and perivascular channels, bypassing the blood-brain barrier, and binds to receptors in multiple cortical regions, insula, hippocampus, hypothalamus, cerebellum and substantia nigra, thus stimulating dopaminergic and hypothalamic pathways [9] [10] [11] [12] . INI has been shown to improve verbal memory [13] and has emerged as a potential treatment for cognitive impairment in elderly [8, 14, 15] . Underlying mechanisms supporting INI effects include enhancement of brain metabolism [16] , regional perfusion [17, 18] and functional connectivity [10, [19] [20] [21] [22] . INI improvements in verbal and visuospatial memory in older T2DM and healthy adults are likely mediated by regional vasodilatation [21, 23] and functional connectivity between hippocampus and default mode networks [23, 24] . INI effects on gait have not been studied. Gait is a complex task and walking speed is an important indicator of overall health [25] . Slower walking speed correlates with brain hypoperfusion in T2DM [26] and can predict cognitive impairment and disability [23, 25] .

We conducted a prospective randomized placebo-controlled Phase 2 trial-Memory Advancement with Intranasal Insulin in Type 2 Diabetes (MemAID)-to determine long-term INI effects on cognition and walking speed in participants with and without diabetes and safety.

MemAID was a prospective double-blinded, placebocontrolled Phase 2 trial that assessed effects of INI compared to placebo treatment over 24 weeks with 24 weeks of follow-up in participants with and without diabetes randomized into four treatment arms. Primary hypotheses were that INI-treated T2DM participants would have better outcomes in memory and other specific cognitive domains, faster normal (NW) and dual-task walking (DTW) speeds, and better daily functionality, as compared to placebo-treated participants with diabetes. We also hypothesized that INI-treated controls would perform better on these outcomes, compared to placebo-treated controls [28] .

A Magnetic Resonance Imaging (MRI) Substudy evaluated INI effects on cerebral blood flow (CBF) and vasoreactivity to hypercapnia and hypocapnia. We evaluated long-term INI safety including adverse events, metabolic profile, weight and hypoglycemic episodes. A Safety Substudy was conducted in subcutaneous insulin-dependent T2DM participants (T2DM-IDDM). This study was carried out in accordance with the recommendations of ethical standards of the BIDMC, BWH and Harvard Medical School. The BIDMC Committee on Clinical Investigation, BWH and Harvard Catalyst CEDE reviewed and approved the study. All participants signed the informed consent in accordance with the Declaration of Helsinki. A Data and Safety Monitoring Board monitored progress and adverse events (AEs). Study screening began October 6, 2015 at BIDMC and June 22, 2017 at BWH. The first patient was randomized at BIDMC on November 5, 2015. In October 2017, the trial protocol and sample size were modified following National Institute of Diabetes and Kidney Diseases (NIDDK) guidance. The Safety substudy in T2DM-IDDM and enrollment of T2DM-IDDM participants were stopped due to high rate of dropouts. Retention strategies were implemented to reduce drop-out rate (participation incentives, transportation, flexible scheduling and skipping visits; Supplementary Appendix). On March 25, 2020, due to COVID-19 pandemic, on-site visits and MRI scans were stopped. The last patient was seen via virtual visit on May 21, 2020, and the study was concluded on May 31, 2020.

The total of 668 subjects were contacted, 289 signed informed consent, 244 were eligible, enrolled and randomized; 223 completed baseline, 221 initiated treatment, 174 (84 DM; 90 controls) completed the 24 week (168 days) treatment and 156 (69 DM; 87 controls) completed the 24 week follow-up. The trial remained under-enrolled for T2DM groups (84 of 120 planned enrollment; 70%), but reached the target for controls (90 of 90 planned enrollment; 100%) ( Fig. 1A, Consort diagram) . Retention strategies and stopping enrollment of T2DM-IDDM group reduced overall drop-out rate from 28 to 17%. Due to COVID-19, 13 (11 T2DM) participants missed 23 on-site assessments and seven end-of treatment MRI scans, and ten participants were censored due to study ending. Participants were recruited from the community, BIDMC, BWH, and Joslin Diabetes Center.

Eligible participants were 50-85 years old and able to walk for six minutes. T2DM participants were treated with diet, non-insulin oral or injectable agents. Controls had fasting plasma glucose.

(< 126 mg/dL) and hemoglobin A1c (HbA 1c , < 6.5%). Excluded were persons with T1DM, T2DM-IDDM (enrollment stopped in 2017), intolerance to insulin, history of severe hypoglycemia, more than one hypoglycemic episode during the entire study [29] , dementia or mini mental state exam (MMSE) scores ≤ 20, serious systemic diseases, recent hospitalizations or drug abuse. INI or placebo was added to participants' routine medication regimen.

Study procedures consisted of a phone screen, on-site screening (visit 1), baseline (visit 2), and four assessments at 8 week intervals, three medication refill visits during 24 week treatment (visits 2-8), and four assessments during 24 week post-treatment (visits 9-12) (Fig. 1B) . Baseline and the first intervention assessment were done on the same day (visit 2). Visit nine was at 1 week after visit eight, and it was replaced by a phone call in 2017. Assessment visits included fasting metabolic panels, anthropometrics, cognitive, functional and mood tests, NW and DTW [28] , duration about 3 h. Baseline Charlson co-morbidity index used ICD-10 codes [30] . Participants kept a diary of daily medication usage and weekly self-monitored blood glucose (SMBG). Safety outcomes, AEs and medication adherence were assessed at each visit. The study physicians evaluated participants at baseline and any AE occurrence.

Participants were randomized into four groups. The study statistician (L.N.) designed code that used randomly selected blocks with sizes four, eight and twelve to ensure uniform distribution of baseline characteristics between DM-INI vs. DM-placebo and Control-INI vs. Control-Placebo.

The PI, co-investigators, staff, participants and participants' providers were blinded to assignments.

Insulin/placebo was delivered using the ViaNase™ electronic atomizers (Kurve Technology, Inc. Lynnwood, WA, USA). Participants administered 40 IU (0.4 mL) of human [31] . BIDMC and BWH research pharmacy performed sterility procedures, reconstituted study drug and dispensed according to the randomization code.

Primary outcomes were cognitive measures, NW and DTW speeds. The Cambridge Cognition computerized system (CANTAB) was used to assess attention, memory and executive function using a battery of validated tests with parallel versions to reduce practice effects [32] . Cognitive outcomes were converted to scaled z scores and summed to create composite measures [33] .

The executive function composite score included the following: paired associates learning (PAL, total errors adjusted) and spatial working memory (SWM, total errors and strategy to complete tasks). Lower score indicates better performance. Verbal memory composite score included verbal immediate free recall and immediate and delayed verbal recognition memory (VRM). Higher score indicates better performance.

Gait was measured during a 6 min walk at usual speed and 6 min dual-task walking (counting backwards subtracting seven) using the Mobility Lab System (APDM, Inc., Portland, OR). Gait speed was calculated from the total distance walked over six minutes in 45 m hallway, excluding turns.

Mood was assessed with the geriatric depression scale, a validated self-report measure of mood (scale 0-30). Disability was assessed with the World Health Organization Disability Assessment Schedule (WHODAS) 2.0, a validated self-reported measure of cognition, mobility, self-care, getting along and life activities domains. The summary score was converted into a percentage score (0 no disability-100 full disability). The Wechsler Adult Reading and Comprehension test was used as a proxy for intelligence and was adjusted for age, sex and education (scale 50-128). Laboratory chemistries included blood, metabolic, lipid and renal panels collected at baseline. Fasting serum glucose, finger stick glucose, HbA 1c , fructosamine, serum insulin and C-reactive peptide were collected at assessment visits (Quest Diagnostics™, Secaucus, NJ, USA).

MRIs were acquired using a GE Discovery MR750 3 Tesla scanner (GE Medical Systems, Milwaukee, WI) with a receive-only 32-channel head-array coil, and a body transmit coil.

T1-weighted anatomical images were acquired with a 3D brain volume (BRAVO) sequence. Perfusion images were acquired at normocapnia (supine rest for 6 min), hypercapnia (rebreathing of 5% CO 2 and 95% air for 2 min) and hypocapnia (hyperventilation for 2 min) with vital signs and CO 2 monitoring using a pseudo-continuous arterial spin labeling (PCASL) sequence and 3D stack of spirals rapid acquisition with relaxation enhancement (RARE) sequence. Resting cerebral blood flow (CBF) maps [34, 35] were divided by their global mean to normalize differences among subjects. CBF responses to CO 2 challenge were calculated as the difference in CBF maps between hypercapnia and normocapnia (vasodilatation), and between hypocapnia and normocapnia (vasoconstriction), respectively. Vasodilation reactivity and vasoconstriction reactivity maps were normalized by dividing the vasodilatation and vasoconstriction maps by the corresponding CO 2 changes. Vasomotor range was calculated as the difference between vasodilatation and vasoconstriction maps, divided by CO 2 changes [26, 36] . CBF and vasoreactivity maps were analyzed on a voxel-by-voxel basis using statistical non-parametric mapping (SnPM) software, voxellevel threshold p < 0.005. The non-parametric approach used was more robust with the nominal false positive rate of 5% [37] compared to the parametric approach.

MemAID database (Study TRAX © Macon, GA, USA) is FDA-and Health Insurance Portability and Accountability Act-compliant web-based data management software. It was used to enter and manage data, determine eligibility, track enrollment, study progress and AEs. Data quality audits were conducted regularly, to review data and correct errors. A geographically redundant storage, 256-bit encryption and a dedicated firewall protected the data.

Primary outcomes were cognition and gait (executive function, verbal learning composite scores, NW and DTW). We hypothesized that INI-treated participants with diabetes would have faster walking speed than placebo-treated T2DM participants. We also tested this hypothesis for DTW, executive function, and verbal memory. The same four hypotheses were tested in controls. Variables were collected at baseline, on-treatment visits 2-8 (0, 1, 55, 113, 165 average days from baseline) and post-treatment visits 9-12 (173, 227, 282, 333 average days from baseline). Linear mixed-effects models were used to estimate the effects of INI in the DM and Control groups. Intention-to-treat analyses (ITT-Model) included data from 223 randomized subjects who completed the baseline visit. Per-protocol analyses (PP-Model) included data from 175 participants who were compliant with treatment and used medication daily for more than 109 days (65% of 168 days treatment period); 48 non-compliant participants (22%) were excluded.

Primary outcomes were compared between DM-INI and DM-Placebo groups and between Control-INI and Control placebo groups at baseline, on-treatment and post-treatment. A spatial power variance-covariance structure was used to model within-subject correlated measurements where the number of days from the baseline visit was used as the power of the autoregressive correlation coefficient. Each efficacy and safety outcome variable was modeled separately.

The independent variables in the model included a fourlevel indicator variable for the following four treatment groups: a three-level time indicator variable (TIMEG) representing baseline, on-treatment and post-treatment period and an interaction term between TIMEG and treatment group.

An average number of treatment days at each assessment visit was used as a continuous repeated variable and subjects were included as random effects. Restricted maximum likelihood estimation method and linear contrasts were used to obtain the estimated mean difference and 95% confidence interval between INI and Placebo for each outcome variable. Safety analyses used the same linear mixed-effects models.

Nominal p values without adjustment for multiple comparisons were specified to show the effects of each primary outcome variable modeled separately within DM and Control groups. Multiple comparison adjustment of the type-I error of 0.05 was not implemented because the null hypothesis of our study was not based on a composite hypothesis of the "or" conditions [15, 38, 39] . We did not test the "composite" null hypothesis that INI had an effect on NW or DT walking speed or executive function or verbal memory or differences between the DM and Control groups. However, we specifically and a priori set four separate null hypotheses testing each of these outcomes of interest separately. For each of the four outcomes, we used a type-I error of 0.05. No stratification of data was used to obtain the comparisons between INI and placebo for each group (DM, Controls) or time point (baseline, on-treatment, post-treatment) because that would cause a loss in statistical power. Rather, we used a single linear mixed effects model with all observations for each outcome. We used linear contrasts (linear combinations of the model betas of main effects and interaction with time period), which yielded the estimated mean difference of the outcome (e.g. gait speed) between INI vs. placebo for each group within each time period (two-tailed p-values).

Potential confounding effects of baseline differences were accounted for by randomization and by including baseline in the model. We carried out additional analyses by examining the INI effect in the combined cohort of DM and Control participants. We also examined models that would yield the overall INI effect from both DM and Control cohort by first testing for the significance of the interaction between cohort (DM, Control) and treatment group (INI, Placebo). Due to non-significance, we estimated the overall INI effect by removing the interaction and adjusting the model using HbA 1c , a good proxy for DM versus Control classification. For each outcome, we computed ITT and PP models (as described above), adjusted for HbA 1c as a continuous variable (Supplementary Appendix). We carried out additional subgroup analyses in the Control group by examining the INI effect in controls with pre-diabetes vs. normoglycemic controls using linear mixed-effects models as described above.

Adverse events analyses used Fisher's exact test and chi-square test. Data were converted from Study TRAX © (Macon, GA, USA). The code and data analyses were generated using Statistical Analyses Software (SAS), Version 9. 

We computed the required sample size based on the expected estimated mean difference at the end of treatment between the DM-Placebo and DM-INI group for cognitive (SWM errors, SWM strategy, VRM total recall) and gait variables. We set type-I error rate at 0.05, power of 0.80 or above, effect size of 15% improvement due to INI, and obtained n = 120 for the DM group (60 DM-INI; 60 DM-Placebo) and n = 90 for the Control group (45 Control-INI; 45 Control-Placebo) yielding 210 patients with data at the end of the treatment period.

Baseline characteristics of 223 randomized participants were similar between DM-INI and DM Placebo and between Control-INI and Control-Placebo (Table 1) . DM participants had more co-morbidities and worse cognition and gait; 48 controls (41%) had pre-diabetes. Figure 2 shows intention-to-treat analyses for NW, DTW, executive function and verbal memory and comparisons between DM-INI and DM-Placebo, and between Control-INI and Control-Placebo groups at baseline, during treatment and post-treatment. Table 2 shows differences and confidence intervals for DM-INI vs. DM-Placebo and for Control-INI vs. Control-Placebo at baseline, on-treatment and post-treatment using intention-to-treat (ITT-Model, 223 randomized participants, Table 2 ). DM-INI also had faster DTW at baseline (p = 0.013), during treatment (p = 0.007) and borderline post-treatment (p = 0.087; Fig. 2A , B). On-treatment DTW was not significant after adjusting for baseline difference (p = 0.812). Executive function and verbal memory composite scores did not differ between DM-INI and DM-Placebo (Fig. 2C, D) . Control-INI improved cognition and had borderline faster NW on-treatment (p = 0.051; difference 5.28 cm/s) (ITT-Model, Table 2 ) compared to Control-Placebo, but DTW did not change (Fig. 2E, F) . Control-INI achieved better executive function composite scores on treatment (lower score indicates better performance, p = 0.008; model estimate difference -0.64) and post-treatment (p = 0.007; difference -0.76) (Fig. 2G, Table 2 ), and better verbal memory composite scores post-treatment (higher score indicates better performance, p = 0.004; difference 0.79) compared to Control-Placebo (Fig. 2H) . On-treatment, Control-INI made fewer errors during learning (PAL p = 0.026, SWM p = 0.03), demonstrated better strategy during visuospatial memory task (SWM, p = 0.034) and delayed verbal recall (VRM p = 0.002) as compared to Control-Placebo. Post-treatment, Control-INI also made fewer errors (PAL, p = 0.003) and showed better decision making strategy (SWM, p = 0.023), immediate (p = 0.013) and delayed recall (p = 0.002), and recognition memory (VRM, p = 0.008).

We also evaluated an overall INI treatment effect in a combined cohort of DM and control participants. INI-treated participants (DM-INI and Control-INI) had similar baseline characteristics to Placebo-treated participants (DM-Placebo and Control-Placebo) and there were no differences in main outcomes (Supplementary (Table 3) HbA 1c effect was significant in all models. No effects were found on mood or WHODAS 2.0. Sex, age, race, ethnicity and insulin sensitizers had no significant effects on cognitive or gait outcomes because of randomization.

We have identified that of 117 controls, 48 participants met criteria for pre-diabetes (baseline HbA 1c 5.7-6.4%) and 69 participants were normoglycemic (baseline HbA 1c < 5.7%). INI treated participants with pre-diabetes (n = 21) have shown trend toward the better performance on NW and DTW as compared to placebo-treated participants with pre-diabetes (n = 27) ( Table 4 ). INI-treated participants with pre-diabetes performed better on executive function tests on-treatment (p = 0.003) and post-treatment (p = 0.009) and on verbal memory tests post-treatment (p = 0.005), compared to placebo-treated participants with pre-diabetes. A similar trend was observed for normoglycemic controls (INI: n = 37, Placebo n = 32).

We aimed to enroll 40 T2DM participants; 18 completed baseline scans; 11 completed end-of-treatment scans; seven scans were cancelled due to COVID-19. All 11 participants were treatment compliant. INI treatment increased resting CBF in right medial pre-frontal cortex (mPFC) as compared to baseline (corrected cluster-level p = 0.03; similar trend on the left; Fig. 3A , i). Regional analysis of the mPFC cluster showed that CBF increased in all eight T2DM-INI ◂ participants and decreased in three T2DM-Placebo subjects (Fig. 3B, i) . Hypercapnia-induced CBF increase was attenuated in the anterior/middle cingulate (p = 0.023), inferior parietal cortex (p = 0.024) and posterior cingulate/precuneus cortex (p = 0.003) (Fig. 3A, ii and Fig. 3B, ii) . Hypocapniainduced CBF reduction was smaller in the occipital and parietal junction (p = 0.024; Fig. 3A iii, Fig. 3B, iii) . A faster DTW was associated with increased post-treatment vasodilatation reactivity in cerebellum (p = 0.008; n = 11; Fig. 3C , i), decreased post-treatment vasoconstriction reactivity in the entire brain except the right temporal regions (p = 0.006; Fig. 3C , ii) and decreased post-treatment vasomotor range in the entire brain, due to decreased vasoconstriction (p = 0.007; Fig. 3C, iii) . Statistically different changes were observed within each cluster for relative CBF (t = 7.35, p < 10 -4 ), vasodilation (t = 4.36, p = 0.0018), and vasoconstriction (t = 5.82, p < 10 -4 ). Better performance on SWM (less errors) was associated with absolute vasodilatation in occipital and parietal regions (p = 0.041).

Study compliance was 78%; 175 participants self-reported medication device usage > 65% (> 109 days). DM-INI group had lower plasma insulin (p = 0.006) and HOMA-IR (Homeostatic Model Assessment of Insulin Resistance; p = 0.013) (Fig. 4 A, B) . INI treatment did not change HbA 1c , weight, waist circumference or BMI (Fig. 4C, D) , but fasting serum 

We aimed to enroll 20 T2DM-IDDM participants. We screened 86 T2DM-IDDM participants, 14 (nine INI, five Placebo) were randomized and five (two INI, three Placebo) completed treatment and follow-up (Fig A.1) . Participants completed one week of continuous glucose monitoring (CGM) (Medtronic iPro2; Medtronic, Northridge CA, USA) and measured SMBG five times daily (Accu-Check ® , Aviva PluF. Hoffman-La Roche Ltd, Basel, CH) [40] before and after INI/Placebo treatment initiation. Capillary glucose on CGM did not decline for 2 h after INI or placebo administration (Fig. 5 A, B) . No interactions were observed between INI and subcutaneous insulins. Five T2DM-IDDM subjects had seven hypoglycemic AEs (Supplementary Table A.6) . Two T2DM-IDDM subjects treated with INI had two asymptomatic level-2 hypoglycemic AEs (five episodes on CGM) and five subjects (two INI and three Placebo) had five level-1 hypoglycemic AEs. CGM-recorded hypoglycemic episodes occurred at nighttime, before INI administration (done in the morning). Distribution of hypoglycemic episodes on CGM was similar between INI and placebo, and between baseline and the first week on treatment. In two INI-treated participants, HbA 1c , fasting plasma and capillary glucose declined from baseline, but the average values during treatment and follow-up were similar to the three placebo-treated participants (Supplementary Table A.6 ).

MemAID Phase 2 trial provided preliminary evidence for positive INI effects on cognition and gait. INI-treated T2DM participants demonstrated faster walking speed, increased cerebral blood flow and lower plasma insulin and insulin resistance (HOMA-IR) as compared to placebo, while INItreated controls showed improved executive functioning, verbal memory and borderline faster NW. In the combined cohort of INI-treated participants, overall INI effect demonstrated faster walking and better executive functioning and memory. In the Control group, INI-treated participants with pre-diabetes demonstrated better executive functioning and memory. The four main outcomes and the individual outcomes all showed trends toward improvement on INI treatment with clinically relevant effect sizes.

At baseline, participants with diabetes walked slower, had worse cognition, microvascular disease, neuropathy and moderate disability. Controls served as a clinical reference for normal aging population with preserved cognition, mobility and functionality (overweight, 41% pre-diabetic, 30% hypertensive, none-to-mild disability). DM-INI group had faster normal and dual-task walking during treatment and post-treatment, as compared to DM-Placebo, likely due to an improvement of brain perfusion [12, 22, 24] . For NW, the DM-INI effect was ~ 6.5 cm/s for NW and ~ 5.28 cm/s for Control-INI on-treatment. We also analyzed the INI effects in the combined cohort of T2DM and control participants, adjusting for HbA 1c (range 4.8-11.8% from normal, prediabetes, controlled and uncontrolled diabetes). INI-treated participants walked faster on-treatment (NW ~ 6.42 cm/s; DTW ~ 5.8 cm/s). Walking speed is an important vital sign in the elderly and slows down ~ 1 cm/s per year (from 112 cm/s at age 50 to 84 cm/s for 80 + years old) [41] . Therefore, in our cohort of 50-85 year olds with DM and control participants, we would expect an average decline of walking by ~ 0.5 cm/s or more per 6 month period. Slower walking is a clinical predictor of well-being that correlates with cognitive decline [27] , hospitalizations, disability and death [25, 42] .

The Table 2 ). For the overall combined effect of INI (Table 3, In T2DM participants, resting CBF increased after INItreatment in the right mPFC cortex, while CBF declined after Placebo-treatment. On-INI improvement of regional perfusion was consistent with other studies in non-diabetic participants [17, 18] . A faster DTW on INI treatment was associated with increased vasodilatation reactivity and decreased vasoconstriction reactivity in cerebellum, motor and visuospatial processing regions. DTW is a complex daily task that involves interactions among visuospatial, motor, memory and executive function networks. T2DM was associated with decreased CBF in the resting state default mode, visual and cerebellum networks. T2DM-related resting state perfusion pattern involved basal ganglia, insular, frontal and temporal cortex and limbic system and was associated walking speed and cognitive performance [34] . Our results suggest that INI may improve perfusion deficit in the prefrontal cortex in T2DM.

Attenuation of vasodilatation responses in the cingulate may be related to CBF increases in mPFC, due to connections between limbic system and pre-frontal cortex and to their role in modulating emotions and cognitive functions. T2DM participants had exaggerated vasoconstriction reactivity (about twice as much than non-diabetic controls), which correlated with intracellular adhesion molecules in the frontal, temporal parietal and occipital regions, and they also had reduced vasodilatation reactivity which correlated with vascular adhesion molecules in the parietal and occipital regions [36] . Lower baseline vasoreactivity was associated with slower NW and DTW over the 2 year period [26] . Therefore, in persons with diabetes a lower resting state perfusion [43] , worse vasoreactivity and functional connectivity [23, 34] were associated with vascular inflammation and microvascular disease [36] , which correlated with worse cognitive performance [2] and slower walking [26] . In addition, diabetic peripheral neuropathy was associated with gray matter and cerebellar atrophy, reduced functional connectivity between frontal lobe and motor areas and worse executive function [44, 45] . Possible beneficial effects of INI treatment on vasoreactivity in T2DM need confirmation in larger studies.

Insulin resistance negatively affects learning and executive function in normal aging, pre-diabetes and diabetes [8, 22] . In pre-diabetes, HbA 1c correlates with reduction of insular gray matter and in diabetes with cerebellar gray matter atrophy and decreased integrity of frontal lobe white matter pathways [46] . Therefore, the age and diabetes-related structural changes in the gray and white matter, insulin resistance and microvascular disease may limit responses to INI treatment. In T2DM participants, serum insulin and HOMA-IR declined after INI treatment, suggesting a decrease in insulin resistance. A dose of 160 IU of human insulin improved whole-body insulin sensitivity, as assessed by the hyperinsulinemic-euglycemic clamp. Insulin-sensitizing effect correlated with increased CBF in hypothalamus, larger blood flow fluctuations in insular cortex, and increased heart rate variability (an estimate of parasympathetic autonomic nervous system activity) suggests modulation of central metabolic and homeostatic activity by INI [19, 47] . INI-induced decline in insulin resistance or increased whole-body insulin sensitivity and/or less endogenous insulin production [19, 47] reflects pleiotrophic effects of INI on hypothalamic energy metabolism regulation, perfusion and neuroprotection [5] [6] [7] [8] . Therefore, improvement of insulin sensitivity by INI may potentially have protective effects for prevention of dementia in T2DM [48] .

Response to INI may depend upon the dose, treatment duration and method to effectively deliver INI to the olfactory epithelium in the upper nasal cavity, which warrants further investigation. INI dose of 40 IU increased regional blood flow and brain energy [17, 18] and modulated activity in the hypothalamus and orbitofrontal cortex [10] . INI modulates signaling in insular, cortex, mesolimbic system and hypothalamus [22] . High 160 IU dose increased functional connectivity between mPFC and midbrain in people with high insulin resistance, but the effect declined after an hour and was similar to 40 IU dose response [20] , suggesting interactions among the dose, insulin resistance and time course of the response. A 160 IU dose decreased blood [49] . However, these studies varied in the INI dose, insulin type (short-intermediatelong acting), method of delivery, MRI analyses and functional assessments [50] . Future longitudinal studies using dose-response design and effective nose-to-brain delivery methods are needed to detect thresholds for INI efficacy which may be different in older people with and without DM.

MemAID trial findings, although of potential clinical significance, demonstrated potential for improvement of cognition and gait but not for disability and daily living activities in INI-treated subjects. Due to COVID-19 pandemic, 23 on-site assessments and seven end-of treatment MRI scans were stopped and diabetes groups remained under-enrolled. Analyses of combined cohort (INI-treated vs. Placebo-treated participants) have overcome this limitation and have shown positive INI effects on the main outcomes. INI treatment was safe and was not associated with severe AEs or hypoglycemia, consistently with previous studies [51] . T2DM-IDDM subgroup had a highest rate of screen failures due to exclusion criteria and lack of interest in participating, and a high drop-out rate. INI treatment in T2DM-IDDM did not show risk of hypoglycemia or interactions with subcutaneous insulins, despite of intensive glucose lowering therapy. The study population was well-educated, had normal walking speeds and minimal cognitive impairment. Gait speed could have been influenced by participants acclimating to the testing environment. These factors may have limited the observed INI differences and may affect the generalizability of results.

The MemAID trial provided evidence for positive INI effects on cognition and gait in older people with and without T2DM and proof-of-concept for preliminary safety and efficacy.

INI-treated diabetic participants had faster walking speed, increased cerebral blood flow and less insulin resistance, while INI-treated controls performed better on executive function and verbal memory tasks. Overall, INI effect demonstrated improvements of walking speed, executive function and verbal memory. These findings are clinically relevant and warrant further investigation in a larger clinical trial. content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University, or its affiliated academic healthcare centers, or the National Institutes of Health. This research study was supported with study drug from Novo-Nordisk Inc.; Bagsvaerd, Denmark through an independent ISS grant (ISS-001063) (to V.N). Safety sub-study was supported with CGM monitoring devices and supplies from Medtronic Inc., Northridge CA, USA through an independent grant NERP15-031 to V.N. Novo Nordisk, Inc. and Medtronic, Inc. reviewed the manuscript, but had no participation in data analyses, manuscript preparation or submission decision.

Author contributions VN: designed the study and obtained funding, overseen all aspects of the study conduct, experiments, and writing the manuscript. CSM, LN, PN and WD: contributed to study design, conduct and manuscript preparation. LN: designed and conducted analyses, overseen data processing and integrity. WD: designed and analyzed MRI data. PN: was BWH-site PI. RMG: was Harvard Study Site PI. RMG, CBF: overseen neuropsychological testing. FK and LAB: contributed to study and conduct analysis. SB, VL, PN: were study physicians. All authors contributed to the data interpretation and manuscript preparation. VN and LN: are the guarantors of this work, had full access to all of the data from the study, and take responsibility of the data and accuracy of the data analyses. Ethical standard statement Ethocal state was added in section Standard protocol approvals, registrations, and patient consents. This study was carried out in accordance with the recommendations of ethical standards of the BIDMC, BWH and Harvard Medical School. The BIDMC Committee on Clinical Investigation, BWH and Harvard Catalyst CEDE reviewed and approved the study. All participants signed the informed consent in accordance with the Declaration of Helsinki.

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