Persistent COVID-19-associated olfactory dysfunction (C19OD), along with other neurologic and cognitive deficits are common features of long COVID. This study aims to evaluate longitudinal trends in neurocognitive performance within a cohort with C19OD. In individuals with perceived C19OD we performed serial psychophysical olfactory and neurocognitive assessments at baseline and follow-up one year later. At baseline evaluation, individuals with C19OD were found to have diminished cognitive functioning compared to normosmic counterparts across several domains, including attention, executive functioning, language, learning and memory, and psychomotor speed. At subsequent one-year follow-up assessment, C19OD participants demonstrated cognitive recovery, with performance comparable to normosmic counterparts. These findings suggest that early associations between C19OD and certain neurocognitive domains may dissipate upon repeated longitudinal evaluation, with partial resolution of cognitive deficits despite persistent C19OD.

Background:Evidence from neuroscience, epidemiology, and electronic health records studies implicates herpes simplex viruses (HSV) as potentially etiologic for Alzheimer disease (AD).Methods:The VALMCI study was conducted in a research outpatient clinic specializing in memory disorders. The efficacy and side effects of valacyclovir 4 g/day were compared with placebo in a 12-month pilot, randomized, double-blind trial of participants with mild cognitive impairment (MCI), seropositivity to HSV1 or HSV2, and positive 18F-florbetapir PET scan.Results:Totally, 42 of 50 participants (84%) completed the trial. In linear mixed-effects model analyses with age, sex, and apolipoprotein E e4 genotype as covariates, change in the primary outcome of 18F-florbetapir PET mean SUVR was not significant with least-squares mean difference -0.01 (95% CI: -0.12 to 0.10; P=0.82). For secondary cognitive and functional outcomes, PACC composite z-score showed the least square mean difference 0.16 (95% CI: -0.17 to 0.49; P=0.32), and ADCS-ADL-PI score showed the least square mean difference 1.96 (95% CI: -0.43 to 4.34; P=0.11).Conclusion:The results do not support the use of valacyclovir in the treatment of individuals with MCI with HSV seropositivity and PET amyloid positivity.

BACKGROUND:Evidence from neuroscience, epidemiology, and electronic health records studies implicates herpes simplex viruses (HSV) as potentially etiologic for Alzheimer disease (AD). METHODS:The VALMCI study was conducted in a research outpatient clinic specializing in memory disorders. The efficacy and side effects of valacyclovir 4 g/day were compared with placebo in a 12-month pilot, randomized, double-blind trial of participants with mild cognitive impairment (MCI), seropositivity to HSV1 or HSV2, and positive 18 F-florbetapir PET scan. RESULTS:Totally, 42 of 50 participants (84%) completed the trial. In linear mixed-effects model analyses with age, sex, and apolipoprotein E e4 genotype as covariates, change in the primary outcome of 18 F-florbetapir PET mean SUVR was not significant with least-squares mean difference -0.01 (95% CI: -0.12 to 0.10; P =0.82). For secondary cognitive and functional outcomes, PACC composite z -score showed the least square mean difference 0.16 (95% CI: -0.17 to 0.49; P =0.32), and ADCS-ADL-PI score showed the least square mean difference 1.96 (95% CI: -0.43 to 4.34; P =0.11). CONCLUSION:The results do not support the use of valacyclovir in the treatment of individuals with MCI with HSV seropositivity and PET amyloid positivity.

Background: Persistent COVID-associated olfactory dysfunction (C19OD) negatively impacts quality of life (QoL). This prospective longitudinal cohort study sought to determine which aspects of chemosensory recovery may preferentially influence QoL improvement in this population. Methods: Individuals with C19OD (N = 100) completed chemosensory and QoL assessment with Sniffin' Sticks, Taste Assessment, Questionnaire of Olfactory Disorders-Negative Statements (QOD-NS), and QOD-PAR at baseline and 1 year. Multivariable analyses assessed baseline and longitudinal associations between chemosensory dysfunction and QOD-NS. Results: QoL associated with TDI (Coef.; [CI]; p-value: -0.32; [-0.62, -0.032]; 0.030), threshold (-0.82; [-1.5, -0.14]; 0.019), QOD-Par (-1.0; [-0.20, -1.9]; 0.016), and self-reported gustatory dysfunction (GD) (-7.4; [-14, -0.46]; 0.037) at baseline assessment, though quantitative GD did not associate with QoL. Longitudinally, improvements in discrimination (-1.2; [-2.3, -0.18]; 0.023) and QOD-Par (-2.5; [-0.99, -4.1]; 0.002) scores were associated with improved QoL. Individuals with improved parosmia symptoms experienced a 12.86 (12.99, 0.040) QOD-NS point improvement from baseline compared to 5.91 (7.98, < 0.001) for those with persistent parosmia. Conclusions: Independent of mental health, chemosensory function independently drives QoL in C19OD. Parosmia, low odor threshold, and patient-reported GD are all associated with poorer QoL at baseline. Longitudinally, the ability to differentiate among odors is an important correlate of improvement of smell-related QoL in C19OD patients, while parosmia is the strongest driver of longitudinal recovery of smell-related QoL in C19OD. Trending domain-specific olfactory performance in C19OD may allow for improved patient counseling and QoL prognosis.

BACKGROUND:Alzheimer's Disease (AD) prognosis is extremely heterogeneous, even with a similar burden of global tau and amyloid (Aβ) deposition in the brain, which makes it challenging to develop targeted therapeutic interventions and to counsel families on disease prognosis. METHOD:The TPI is based on 4 components: 1) Remote interaction (TPIri) between Aβ and tau pathologies in regions that are functionally and/or structurally connected, but spatially distinct; 2) Local interaction (TPIli) between spatially co-localized Aβ and tau pathology; and subject-specific 3) Functional connectivity (TPIfc) and 4) Structural connectivity (TPIsc) between regions that can facilitate the spread of tau in the brain. RESULT:From an ongoing study of 112 participants with early accumulation of Ab and Tau, longitudinal data were available on 27 participants (2-3 years of follow-up). Using these data and all 4 TPI components as independent variables, we built a LASSO model to predict future tau accumulation, controlling for covariates. The obtained coefficients were used to compute our TPI, and its predictability was assessed by its association with actual longitudinal tau accumulation (within-sample validation). Furthermore, we compared our model, using subject-specific connectomes, with a conventional model using group-averaged connectomes. As seen in Figure 1, while both TPIs (obtained by subject-specific; r=0.8, p <10-5; and group-averaged connectomes: r=0.58, p <0.007) predicted longitudinal tau accumulation, the subject-specific TPI significantly outperformed the group-averaged TPI in predicting subsequent tau (DSlope t=2.96, p <0.009) and accounts for 30% more variance in the prediction. CONCLUSION:Despite a small sample size, we demonstrate that an imaging index that incorporates baseline Ab, tau, and subject-specific connectivity can accurately predict future accumulation of tau. Validation in a larger cohort is ongoing.

Mild cognitive impairment (MCI) is a clinical cognitive deficit that is not severe enough to meet the threshold for Alzheimer's Disease (AD); however, MCI patients have an increased risk of developing AD. Therefore, a diagnosis of MCI may represent a critical turning point in the trajectory of developing AD. Establishing neurological signatures of MCI using network control theory (NCT) may allow more informed diagnosis, and an understanding of its underlying mechanisms could pave the way for novel treatments. Functional MRI (fMRI) metrics were collected in MCI patients (n = 57, mean age = 66.68) and healthy controls (HC) (n = 500, mean age = 72.25). The average structural connectivity matrix was obtained using age-matched controls from the Human Connectome Project-Aging dataset. Commonly recurring brain states were identified via k-means clustering of activation matrices over 200 regions using the Schafer atlas. NCT was used to compute the transition energy (TE): the minimum energy required to transition between each pair of brain states. The entropy of each region’s activity was calculated using SampEn, and was then correlated with TE using Pearson’s correlation. Pairwise/global (average of all brain state pairs) TE and global entropy (average of all regions) were compared between MCI and HC using ANCOVA with age and sex as covariates. The brain states identified via k-means clustering were high and low amplitude activity in the visual, somatomotor, and limbic networks (Figure 1). While there were no significant differences in pairwise or global TE between MCI and HC (Figures 2-3), MCI had significantly lower global entropy than HC. ANCOVA revealed that increased age is associated with increased entropy. Pearson correlation showed a significant inverse relationship between global TE and entropy across individuals (r = −0.13) (Figure 3). Entropy of brain activity measured with fMRI is a promising neuroimaging biomarker of MCI, which is often underdiagnosed or diagnosed with delay. Future work will investigate regional entropy reduction patterns between MCI and AD patients to establish the use of these metrics in disease progression, and to get a more detailed picture of brain activity changes in individuals with these diagnoses.

Introduction:Patients with mild cognitive impairment (MCI) have shown disruptions in both brain structure and function, often studied separately. However, understanding the relationship between brain structure and function can provide valuable insights into this early stage of cognitive decline for better treatment strategies to avoid its progression. Network Control Theory (NCT) is a multi-modal approach that captures the alterations in the brain's energetic landscape by combining the brain's functional activity and the structural connectome. Our study aims to explore the differences in the brain's energetic landscape between people with MCI and healthy controls (HC). Methods:Four hundred ninety-nine HC and 55 MCI patients were included. First, k-means was applied to functional MRI (fMRI) time series to identify commonly recurring brain activity states. Second, NCT was used to calculate the minimum energy required to transition between these brain activity states, otherwise known as transition energy (TE). The entropy of the fMRI time series as well as PET-derived amyloid beta (Aβ) and tau deposition were measured for each brain region. The TE and entropy were compared between MCI and HC at the network, regional, and global levels using linear models where age, sex, and intracranial volume were added as covariates. The association of TE and entropy with Aβ and tau deposition was investigated in MCI patients using linear models where age, sex, and intracranial volume were controlled. Results:Commonly recurring brain activity states included those with high and low amplitude activity in visual (+/-), default mode (+/-), and dorsal attention (+/-) networks. Compared to HC, MCI patients required lower transition energy in the limbic network (adjusted p = 0.028). Decreased global entropy was observed in MCI patients compared to HC (p = 7.29e-7). There was a positive association between TE and entropy in the frontoparietal network (p = 7.03e-3). Increased global Aβ was associated with higher global entropy in MCI patients (ρ = 0.632, p = 0.041). Conclusion:Lower TE in the limbic network in MCI patients may indicate either neurodegeneration-related neural loss and atrophy or a potential functional upregulation mechanism in this early stage of cognitive impairment. Future studies that include people with AD are needed to better characterize the changes in the energetic landscape in the later stages of cognitive impairment.

Previous studies have linked impaired odor identification and global cognition with increased risk of cognitive decline and transition to dementia. However, the reverse question remains: if individuals have intact performance on these measures, are they at reduced risk for transition? We aimed to examine the accuracy of intact odor identification and global cognition for identifying lack of transition to dementia/cognitive decline using the population-based Mayo Clinic Study of Aging and compare their accuracy against and in combination with amyloid PET (Positron Emission Tomography). n = 647 participants age≥55 without dementia completed at baseline the Brief Smell Identification Test (BSIT; ‘Intact’ = 9-12), Blessed Information-Memory-Concentration Test (BIMCT; ‘Intact’ = 18-20,), and amyloid PET (‘Normal/Intact’ SUVR<1.48). We calculated sensitivity, specificity, positive predictive value, and negative predictive value for these measures, with “lack of transition to dementia” as the gold standard/target. “Lack of cognitive decline” (cognitively unimpaired to mild cognitive impairment [MCI]; cognitively unimpaired to dementia; or MCI to dementia) was a secondary target. 94.7% of participants (613/647) did not transition to dementia and 84.2% (545/647) did not cognitively decline over 11.25-year-follow-up. The combination of intact BSIT+BIMCT had high rates of lack of transition to dementia (98.3%, 355/361) and lack of cognitive decline (93.1%, 336/361). This combination yielded mixed sensitivity (0.579) and specificity (0.824) though had high positive predictive value (0.983) for identifying lack of transition to dementia. Intact amyloid PET alone exhibited comparable rates of lack of transition to dementia (99.0%, 418/423) and lack of cognitive decline (92.4%, 391/423). When evaluated conjointly, the combination of all three intact measures also had mixed sensitivity (0.421) and specificity (0.962) though higher positive predictive value (PPV = 0.996) for lack of transition to dementia. 99.6% (258/259) of participants with intact/normal status on all three did not transition to dementia and 96.5% (250/259) did not cognitively decline. This replicates prior reports that intact olfaction/global cognition have strong utility for identifying individuals unlikely to develop MCI/dementia. Intact/normal amyloid PET further enhances the positive predictive value. Clinically, identifying individuals at low risk of transition can shorten diagnostic workups, reduce need for early follow-up visits, and screen patients in-or-out of clinical trials.

BACKGROUND:Olfaction and memory are each independently disrupted in Alzheimer's disease (AD) early in the clinical course. Odor memory measures combining these two systems may be more capable of distinguishing these disorders than measure of either system in isolation. The purpose of this study is to evaluate psychophysical and demographic factors affecting odor memory performance and the association of odor memory performance with well-established measures of olfaction and cognition. METHOD:N = 47 participants (Mean age=33.4, SD=14.6, range=19-60, 48.9% female) with intact olfaction and cognition completed a battery of olfactory and cognitive tests. The novel odor recognition memory test (ORMT) had an encoding phase during which participants rated familiarity of ten odors, followed by a 20-minute delayed yes/no recognition phase involving ten old and ten new odors. The discriminability index (d') was the primary outcome variable. Pearson correlations, t tests, and Wilcoxon tests were used to evaluate association with other measures and demographic variables. RESULT:Performance on the ORMT (d') was strongly correlated (r[45]=0.50, p <0.001) with performance on a visual recognition memory test (Rey Complex Figure Test [RCFT], d'). Importantly, ORMT performance was not significantly correlated with performance on measures of dissimilar cognitive domains, including global cognition (MoCA, r=0.05, p = 0.725), visuospatial constructional ability (RCFT Copy, r=0.11, p = 0.453), odor identification (r[45]=0.17, p = 0.266), odor discrimination (r[45]=0.23, p = 0.119), odor threshold (r[45]=0.11, p = 0.455), or Sniffin' Sticks TDI composite (r[45]=0.26, p = 0.082). Odors rated as 'familiar' during encoding were significantly more often true positives during recognition than 'unfamiliar' odors (W=825, z=-5.12, p <0.001). Odor intensity and pleasantness ratings were not significantly associated with recognition. ORMT performance was not associated with age (r = 0.02, p = 0.871) or sex (t[45]=0.94, p = 0.353). CONCLUSION:In cognitively intact individuals, the ORMT exhibited preliminary evidence of convergent validity through strong association with a well-established visual recognition memory test and evidence of divergent validity through unrelatedness to distinct cognitive and olfactory constructs. This simple, inexpensive, well-tolerated test represents a method of assessing recognition memory using a sensory domain less prone to interference effects. Since AD biomarkers associate with odor memory measures beyond psychophysical olfaction, ongoing studies in larger populations at-risk for AD will determine the prognostic utility of the ORMT.

Early detection of dementia and cognitive impairment is recommended for persons 65 years and older during wellness primary care visits. The importance of early detection has increased with the availability of new treatments for early Alzheimer's disease (AD). However, there is no clear approach for early detection in primary care. Odor identification deficits predict AD in epidemiological studies and may be useful for early detection. Our objective was to compare the accuracy of a short odor identification test with a short cognitive screening test for the detection of dementia and cognitive impairment in elderly persons with cognitive concerns. This was a cross-sectional study of 600 participants 65 years and older, without known mild cognitive impairment (MCI) or dementia, with cognitive concerns, attending primary care practices in New York City. The odor identification test was the Brief Smell Identification Test (BSIT). The comparator test was the Mini Mental Status Exam II (MMSE). Cognitive diagnoses were made using the National Alzheimer’s Coordinating Center Uniform Data set (NACC-UDS) version 3 forms with slight modifications by a diagnosis consensus committee. Test performance was compared using Receiver Operating Characteristic analyses. The mean age of the sample was 72.65 ± 6.31 years, 73.3% were female, 63.3% were Hispanic, 17.5% non-Hispanic Black, and 27.0% non-Hispanic White; 23.5% had normal cognition, 27.6% had cognitive impairment-not mild cognitive impairment (MCI), 31.1% had amnestic MCI, 5.6% had non-amnestic MCI, and 12% had dementia. The MMSE was superior to the BSIT in detecting dementia (AUC 0.89 vs 0.78, p =0.0007, Figure Panel A) and any cognitive impairment (AUC 0.79 vs 0.63, p <0.0001, Figure Panel B). Combining abnormal scores in the BSIT (< 9) to MMSE (< 24) improved the MMSE’s specificity (0.98 combined vs. 0.92 MMSE alone) and positive predictive value (PPV) in detecting cognitive impairment (0.98 combined vs. 0.95 MMSE alone). The MMSE was superior to the BSIT in detecting dementia and cognitive impairment in primary care but using both tests improved specificity and PPV for identifying persons with subjective complaints needing further cognitive and biomarker evaluation.

Alzheimer's Disease (AD) prognosis is extremely heterogeneous, even with a similar burden of global tau and amyloid (Aβ) deposition in the brain, which makes it challenging to develop targeted therapeutic interventions and to counsel families on disease prognosis. The TPI is based on 4 components: 1) Remote interaction (TPIri) between Aβ and tau pathologies in regions that are functionally and/or structurally connected, but spatially distinct; 2) Local interaction (TPIli) between spatially co-localized Aβ and tau pathology; and subject-specific 3) Functional connectivity (TPIfc) and 4) Structural connectivity (TPIsc) between regions that can facilitate the spread of tau in the brain. From an ongoing study of 112 participants with early accumulation of Ab and Tau, longitudinal data were available on 27 participants (2-3 years of follow-up). Using these data and all 4 TPI components as independent variables, we built a LASSO model to predict future tau accumulation, controlling for covariates. The obtained coefficients were used to compute our TPI, and its predictability was assessed by its association with actual longitudinal tau accumulation (within-sample validation). Furthermore, we compared our model, using subject-specific connectomes, with a conventional model using group-averaged connectomes. As seen in Figure 1, while both TPIs (obtained by subject-specific; r=0.8, p  <10-5; and group-averaged connectomes: r=0.58, p  <0.007) predicted longitudinal tau accumulation, the subject-specific TPI significantly outperformed the group-averaged TPI in predicting subsequent tau (DSlope t=2.96, p  <0.009) and accounts for 30% more variance in the prediction. Despite a small sample size, we demonstrate that an imaging index that incorporates baseline Ab, tau, and subject-specific connectivity can accurately predict future accumulation of tau. Validation in a larger cohort is ongoing.

Background To identify classes of cognitively impaired older individuals based on their neuropsychiatric symptoms(NPS) and to investigate the contribution of NPS class to cognitive decline and Alzheimer’s disease(AD) risk in mild cognitive impairment(MCI). Methods Our study included 1,472 participants(age range 55-91) from the Alzheimer’s Disease Neuroimaging Initiative(ADNI) who were diagnosed with MCI or mild AD and had a complete neuropsychiatric Inventory at their baseline visit. We employed latent class analysis to categorize groups by NPS patterns. Linear mixed models of repeated measures(LMMRMs) were used to compare changes in cognitive performance across 5years as a function of NPS class. Subsequently, the Cox proportional hazards model was employed in individuals with MCI to assess whether rate of conversion to AD differed across the NPS groups. Results We identified three latent classes of NPS: No NPS (n=799, 51.7%), Apathy/Affective (n=572, 39.8%), Complex (n=108, 8.5%) NPS. In longitudinal analyses we observed interactions between class and time, indicating accelerated cognitive decline in memory and executive function in the Apathy/Affective class. In MCI, hazard ratios for conversion to AD were 1.39(95% CI: 1.10-1.76) for the Apathy/Affective class and 2.03(95% CI: 1.33-3.10) for the Complex class compared to the No NPS group after adjusting for age, sex, education, global cognition, and ApoE4 positivity. Conclusions Among cognitively impaired elderly, empirically derived clusters of NPS profiles were associated with cognitive decline and risk of conversion from MCI to AD. Such NPS classes may reflect specific neurobiological mechanisms within or related to AD-related neurodegeneration. Further studies with biological markers are needed to clarify these neurobiological mechanisms.

Digital cognitive twins could transform cognitive training into a personalized, clinically grounded and ethically governed modality for preventive use.

BackgroundOdor identification deficits predict Alzheimer's disease (AD) in epidemiological studies.ObjectiveTo compare the accuracy of a short odor identification test with a short cognitive screening test for the detection of dementia and cognitive impairment in elderly persons with cognitive concerns.MethodsThis was a cross-sectional study of 600 participants 65 years and older, without known mild cognitive impairment (MCI) or dementia, with cognitive concerns, attending primary care practices in New York City. The odor identification test was the Brief Smell Identification Test (BSIT). The comparator test was the Mini Mental Status Exam II (MMSE). Cognitive diagnoses were made using the National Alzheimer's Coordinating Center Uniform Data set (NACC-UDS) version 3 forms with slight modifications. Test performance was compared using Receiver Operating Characteristic analyses.ResultsThe mean age was 72.65 ± 6.31 years, 73.3% were female, 63.3% were Hispanic, 13.5% non-Hispanic Black, and 20.8% non-Hispanic White; 23.5% were classified as normal cognition, 27.7% as cognitive impairment-not mild cognitive impairment (MCI), 31.2% as amnestic MCI, 5.7% as non-amnestic MCI, and 12% as dementia. The MMSE was superior to the BSIT in detecting dementia and any cognitive impairment. Combining abnormal scores in the BSIT (≤8) to MMSE (≤24) improved the MMSE's specificity and positive predictive value (PPV) in detecting cognitive impairment.ConclusionsThe MMSE was superior to the BSIT in detecting dementia and cognitive impairment in primary care but using both tests improved specificity and PPV for identifying persons with subjective complaints needing further cognitive and biomarker evaluation.

The energetic and entropic organization of the brain's functional activity in mild cognitive impairment (MCI) has yet to be fully characterized. Network Control Theory (NCT) is a multi-modal approach that captures alterations in the brain's energetic landscape by combining the brain's functional activity and the structural connectome. Entropy is another complementary metric that can quantify the complexity and predictability in a neural time series, offering insights into the brain's dynamic functional activity. Our study aims to explore the differences in the brain's energetic and entropic landscape between people with MCI and healthy controls (HC). Four hundred ninety-nine HC and 55 MCI patients were included. First, k-means clustering was applied to functional MRI (fMRI) time series to identify commonly recurring brain activity states. Second, NCT was used to calculate the minimum energy required to transition between these brain activity states, otherwise known as transition energy (TE). The entropy of the fMRI time series as well as PET-derived amyloid beta (Aβ) and tau deposition were measured for each brain region. The TE and entropy were compared between MCI and HC at the network, regional, and global levels using linear models where age, sex, and intracranial volume were added as covariates. The association of TE and entropy with Aβ and tau deposition was investigated in MCI patients using linear models where age, sex, and intracranial volume were controlled. Commonly recurring brain activity states included those with high (+) and low (-) amplitude activity in visual (+/-), default mode (+/-), and dorsal attention (+/-) networks. Compared to HC, MCI patients required lower transition energy in the limbic network (adjusted p = 0.028). Decreased global entropy was observed in MCI patients compared to HC (p = 7.29e-7). There was a positive association between TE and entropy in the frontoparietal network (p = 7.03e-3). Increased global Aβ was associated with higher global entropy in MCI patients (ρ = 0.632, p = 0.041). Lower TE in the limbic network in MCI patients may indicate either neurodegeneration-related neural loss and atrophy or a potential functional upregulation mechanism in this early stage of cognitive impairment. Future studies that include people with Alzheimer's Disease (AD) are needed to better characterize the changes in the energetic landscape in the later stages of cognitive impairment.

Infections may be etiologic or contribute to Alzheimer’s disease (AD) pathology. Evidence from neuroscience, epidemiology, and electronic health records data implicates herpes simplex viruses in AD, but controlled clinical trials of anti-herpetic drugs have not been conducted. In 120 participants at 3 U.S. sites with mild AD, or mild cognitive impairment (MCI) with positive AD biomarkers, the anti-herpetic oral drug valacyclovir at 4 g/day, repurposed as an anti-AD drug, was compared to placebo (60 valacyclovir, 60 placebo) in a Phase 2 randomized, double-blind, parallel group trial. Seropositivity to herpes simplex virus (HSV) 1 or 2 was required. Acyclovir, the main metabolite of valacyclovir, was measured in plasma and in CSF in a subsample. The primary outcome was change in the 11-item Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog11); secondary outcomes included the Alzheimer’s Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) scale, Montreal Cognitive Assessment (MoCA), and neuroimaging conducted at baseline and 78 weeks utilizing 18F Florbetapir PET (mean of six brain regions), structural MRI indices, and 18F MK-6240 PET tau imaging in a subsample. Mixed model analyses adjusted for baseline score of the variable. The primary outcome, ADAS-Cog11 score, showed greater worsening on valacyclovir than placebo at 78 weeks (LS Means difference 3.91, 95% CI 1.03 to 6.8, p =.01) with non-significant differences at 12, 26 and 52 weeks in the same direction. ADCS-ADL, the main functional measure, and other secondary clinical outcomes did not differ significantly between the treatment groups. Change in amyloid burden for 18F Florbetapir PET and tau for 18F MK-6240 PET, and MRI cortical thickness and hippocampal volume, showed no treatment group differences. Mean plasma acyclovir concentration following oral doses of 4 g/day was 7140±5780 ng/ml (66 samples) and CSF acyclovir concentrations were 1260±460 ng/ml at week 12 ( n =6) and 1270±1100 ng/ml at week 78 ( n =3), which confirmed CNS penetration for valacyclovir. Adverse events did not differ significantly between valacyclovir and placebo. Valacyclovir was not efficacious as an antiviral treatment for participants with AD and herpes simplex virus seropositivity. The potential etiological role of herpes simplex viruses in AD needs re-consideration.

Objective:Assessment of olfactory function with psychophysical testing requires cognitive demand to correctly pair test odors with remembered scents. Individuals suffering from long-Corona Virus Disease 2019 (long-COVID-19) may develop a decline in neurocognitive performance, which may be concurrent with persistent olfactory dysfunction (OD). Given the rigorous cognitive demand of the unprompted identification (UI) olfactory assessment, the goal of this study is to understand whether it could serve as a proxy for specific neurocognitive domains during clinical assessment of olfaction. Methods:Participants from our long-COVID cohorts with persistent OD underwent a panel of neurocognitive screening followed by olfactory assessment of threshold followed by unprompted (UI) and prompted identification (PI) tests using Sniffin' Sticks. Hierarchical linear mixed-effect models were used to understand the relative impact of each neurocognitive variable after controlling for demographics and olfactory threshold scores. Results:Neurocognitive variables demonstrated common correlation trends. Models containing Montreal Cognitive Assessment (MoCA) and digit-span backward scores had statistically significant fits for both UI (MoCA: χ 2 = 10.20, p = 0.001/digit-span backward: χ 2 = 4.27, p = 0.04) and PI (MoCA: χ 2 = 4.51, p = 0.03/digit-span backward: χ 2 = 5.04, p = 0.02) linear mixed-effect models, but UI was further explained by logical memory (χ 2 = 7.84, p = 0.005), verbal fluency (χ 2 = 8.79, p = 0.003), and digit-span forward (χ 2 = 12.30, p = 0.0004). These relationships were statistically significant after controlling for demographic and olfactory threshold covariates. Conclusions:UI and PI have interrelated neurocognitive dependence on global cognition (MoCA) and executive function (digit-span backward) among long-COVID participants. As UI draws upon neurocognitive domains of episodic (logical memory), semantic (verbal fluency), and working memory (digit-span forward), the inclusion of a UI task may provide supplementary screening for cognitive impairments in those undergoing clinical olfactory assessment, particularly among those with lingering effects of COVID-19.

This proceedings article summarizes the inaugural "T Cells in the Brain" symposium held at Columbia University. Experts gathered to explore the role of T cells in neurodegenerative diseases. Key topics included characterization of antigen-specific immune responses, T cell receptor (TCR) repertoire, microbial etiology in Alzheimer's disease (AD), and microglia-T cell crosstalk, with a focus on how T cells affect neuroinflammation and AD biomarkers like amyloid beta and tau. The symposium also examined immunotherapies for AD, including the Valacyclovir Treatment of Alzheimer's Disease (VALAD) trial, and two clinical trials leveraging regulatory T cell approaches for multiple sclerosis and amyotrophic lateral sclerosis therapy. Additionally, single-cell RNA/TCR sequencing of T cells and other immune cells provided insights into immune dynamics in neurodegenerative diseases. This article highlights key findings from the symposium and outlines future research directions to further understand the role of T cells in neurodegeneration, offering innovative therapeutic approaches for AD and other neurodegenerative diseases. HIGHLIGHTS: Researchers gathered to discuss approaches to study T cells in brain disorders. New technologies allow high-throughput screening of antigen-specific T cells. Microbial infections can precede several serious and chronic neurological diseases. Central and peripheral T cell responses shape neurological disease pathology. Immunotherapy can induce regulatory T cell responses in neuroinflammatory disorders.

Sensory functions of organs of the head and neck allow humans to interact with the environment and establish social bonds. With aging, smell, taste, vision, and hearing decline. Evidence suggests that accelerated impairment in sensory abilities can reflect a shift from healthy to pathological aging, including the development of Alzheimer's disease (AD) and other neurological disorders. While the drivers of early sensory alteration in AD are not elucidated, insults such as trauma and infections can affect sensory function. Herein, we review the involvement of the major head and neck sensory systems in AD, with emphasis on microbes exploiting sensory pathways to enter the brain (the "gateway" hypothesis) and the potential feedback loop by which sensory function may be impacted by central nervous system infection. We emphasize detection of sensory changes as first-line surveillance in senior adults to identify and remove potential insults, like microbial infections, that could precipitate brain pathology.

Background: There is a need for integration and comprehensive characterization of environmental determinants of Alzheimer’s disease. The Environmental Justice Index (EJI) is a new measure that consolidates multiple environmental health hazards. Objective: This analysis aims to explore how environmental vulnerabilities vary by race/ethnicity and whether they predict cognitive outcomes in a clinical trial of mild cognitive impairment (MCI). Methods: We used data from a clinical trial of 107 MCI participants (28% minorities). Using the EJI, we extracted 40 measures of neighborhood environmental and social vulnerability including air and water pollution, access to recreational spaces, exposure to coal and lead mines, and area poverty. We also examined the relationship of the EJI to the Area Deprivation Index (ADI). Data was analyzed using regressions, correlations, and t-tests. Results: Environmental Burden Rank (EBR) across the sample (0.53±0.32) was near the 50th percentile nationally. When divided by race/ethnicity, environmental ( p = 0.025) and social ( p < 0.0001) vulnerabilities were significantly elevated for minorities, specifically for exposure to ozone, diesel particulate matter, carcinogenic air toxins, and proximity to treatment storage and disposal sites. ADI state decile was not correlated with the EBR. Neither EBR nor ADI were a significant predictor of cognitive decline. Conclusions: To our knowledge, this is the first study to link the EJI to an MCI trial. Despite limitations of a relatively small sample size, the study illustrates the potential of the EJI to provide deeper phenotyping of the exposome and diversity in clinical trial subjects.