MCI Participants Research Articles

The association of hyperglycemia and kidney dysfunction with cognitive impairment in community‐dwelling older adults in Taiwan

AbstractBackgroundDiabetes was considered one of the risk factors for dementia. However, one‐third of diabetic patients also suffer from kidney disease. It remains unclear the intercorrelation between blood sugar and kidney function that affects the occurrence of mild cognitive impairment for people with normal blood sugar levels. This study aimed to explore the relationship between hyperglycemia and kidney dysfunction (KD) on cognitive impairment in older adults.MethodThis is an eight‐year cohort study (2011‐2019). A total of 509 non‐demented older adults were recruited from the elderly health checkup program at baseline (2011‐2013) with three biannual follow‐ups. Global and domain‐specific (memory, attention, executive function, and language) cognition were assessed by the Taiwanese version of Montreal Cognitive Assessment (MoCA‐T) and a battery of neuropsychological tests, respectively. MCI was defined as a MoCA‐T score of 22 or 23. Hyperglycemia was defined as fasting blood glucose greater than 100 mg/dL. KD was defined as having either glomerular filtration rate < 60 ml/min/1.73 m2 or proteinuria. The generalized linear mixed model was utilized to examine the effects of hyperglycemia and KD on cognitive performance.ResultThe prevalence of MCI was 9.4% at baseline. Hyperglycemia [adjusted odds ratio (aOR) = 1.91] and KD (aOR = 1.98) were significantly associated with the risk of MCI over eight years after adjusting for covariates, respectively. In addition, hyperglycemia and KD were significantly associated with poor performance of logical memory (β:‐0.51 to ‐0.01), executive function (β:‐0.25 to ‐0.003), attention (β:‐0.07 to ‐0.03), and verbal fluency (β:‐0.08 to ‐0.005). Hyperglycemia and KD was associated with an increased risk of MCI participants aged less than 75 years (aOR = 2.19–2.21) and in APOE ε4 non‐carriers (aOR = 2.02–2.15).ConclusionOur finding indicated that poor glycemic control and kidney function were associated with an increased risk of MCI or poor performance of cognitive domains in older adults. Cognitive impairment may be reversible through optimal management of glycemia and kidney disease; interventions (e.g., self‐management education, dietary restriction, and sufficient physical activity, etc.) at the early stage will be helpful to prevent dementia.

5 Cross-cultural Diagnostic Validity of the Multilingual Naming Test (MINT) in a Sample of Older Adults.

Objective:The current study aimed to evaluate the psychometric properties and diagnostic accuracy of the 32-item version of the Multilingual Naming Test (MINT) in a sample of English and Spanish monolinguals and bilingual older adults from two ethnic groups (EA; European Americans and HA; Hispanic American) with typical and atypical aging. An IRT model was used to identify 24 MINT Items assessed across ethnicity and language testing groups (Spanish and English). We analyzed the discriminant and predictive validity of the 32-item and 24-item scales across diagnostic groups (cognitively normal [CN], mild cognitive impairment [MCI], and dementia [AD]). Diagnostic accuracy was then assessed with both versions applying ROC (Receiver Operating Characteristics) curve reporting using AUC (Area Under the Curve). We expected the MINT to distinguish between the CN and AD groups but not between CN and MCI and the MCI and AD. We conducted IRT analyses to evaluate the cross-language validity of the items from the 32-item MINT in English and Spanish through Rasch Analysis across our two ethnic groups. Finally, we tested the association between MINT scores and MRI volumetric measures of language-related areas in both cerebral hemispheres’ temporal and frontal lobes.Participants and Methods:The sample comprised 281 participants (178 females) enrolled in the 1Florida Alzheimer’s Disease Research Center (ADRC), with 175 participants self-identified as HA (51 tested in English and 124 in Spanish) and 106 EA, all of them monolingual English speakers. The participants were classified into three diagnostic groups: 1. CN (n = 94); 2. MCI (n = 148); and 3. AD (n = 39). Participants are evaluated yearly through a comprehensive neuropsychological battery, including the MINT is a standard CN task that requires patients to retrieve words upon presentation of a line drawing.Results:We obtained a ceiling effect in four items (Butterfly, Glove, Watch, and Candle). Four items were easier in English (Blind, Gauge, Porthole, and Pestle) and four in Spanish (Dustpan, Funnel, Anvil, and Mortar). In the 32-item version of the MINT, EA scored significantly higher than HA, but when removing those eight items, the ethnic difference was attenuated and no longer statistically significant (controlling for education). The ROC curves showed that both versions of the MINT had poor accuracy when identifying CN participants and were acceptable in identifying dementia participants but unacceptable for classifying MCI participants. The 32-item MINT in English and Spanish and the 24-item MINT in Spanish were significantly correlated with the bilateral MTG. However, the 24-item MINT in English was only correlated with this area’s volume in the right hemisphere. The left FG correlated with MINT scores regardless of language and MINT version. We also found some differential correlations depending on the language of administration. The bilateral hippocampi, STG, MTG and FG, and right ITG were significantly correlated only with MINT Spanish scores, while the left ITG was significant only when either version of the MINT was administered in English.Conclusions:Our results highlight the importance of analyzing cross-cultural samples when implementing neuropsychological tests.

A - 35 The Relationship between Perceived Social Support and Everyday Cognition in Mild Cognitive Impairment: a Longitudinal Study.

Explore the relationship between perceived social support and changes in informant-rated cognitive ability in people with mild cognitive impairment (pwMCI) enrolled in a lifestyle intervention program. Based on prior literature, we hypothesized lower levels of social support would be associated with greater declines in executive functioning (EF) over time. Forty-nine pwMCI who enrolled in a 12-month comprehensive lifestyle program completed the Multidimensional Scale of Perceived Social Support (MSPSS), and their informants completed the Everyday Cognition Scale (ECog) pre- and post-program. Change scores were calculated for the ECog Total Score and EF subscale. MCI participants were classified into three groups based on ECog change: Declined (n = 17), Stable (n = 17), and Improved (n = 15). Pearson correlations were conducted between MSPSS, ECog, and EF change scores within each group. There was no significant difference in baseline ECog ratings between groups, F(2,46) = 0.36, p = 0.70 or baseline MSPSS F(2,46) = 1.23, p = 0.30. For the Declined group, a trend emerged suggesting higher MSPSS was associated with declines in EF (r = 0.27, p = 0.07). The relationship between MSPSS and ECog total scores was not significant (p = 0.16). No trends or associations were observed in the Stable or Improved groups. Findings were counter to initial hypotheses. Although further work is needed, this effect may relate to Reciprocity Theory which posits those who require more social support experience emotional distress due to feelings of unwanted dependence and a lack of perceived ability to reciprocate support. This experience may adversely affect EF through an increase in negative emotions and stress. Further exploration of moderators of this relationship is warranted.

Psychodynamic-based virtual reality cognitive training system with personalized emotional arousal elements for mild cognitive impairment patients

Background and objectiveMild cognitive impairment (MCI) is a serious threat to the physical health and quality of life of the elderly, as well as a heavy burden on families and society. The current computer-based rehabilitation training ignores the role of emotions in cognitive impairment rehabilitation, making it difficult to improve patient engagement and efficiency. To address this, a psychodynamics-based cognitive rehabilitation training method with personalized emotional arousal elements was proposed using virtual reality technology. MethodsOur proposed method contains four training tasks, which cover (audiovisual memory, attention & processing, working memory, abstract & Logic, spatial pathfinding) and six positive emotional arousal elements (sensory feedback, achievement system, multiplayer interaction, score comparison, relaxation scenarios, and peaceful videos) to motivate participants to persist during cognitive training continuously and maintain a positive mental attitude toward training. The six emotional arousal elements were divided into two personalized combinations—full combination and half combination—based on the results of the pre-assessment and were dynamically distributed throughout both the training tasks and post-training. ResultsFifteen participants with MCI were recruited to complete the proposed experiment and validate the effectiveness of the system. They were first asked to complete two assessments (e.g., the big five scale and the positive and negative affect scale) to investigate their personalities. Based on the results of the assessments, they were provided with a full or half combination of arousal elements in the training tasks and post-training. Finally, the acceptability of the system and task experience were assessed using questionnaires. Notably, there was a significant increase in training scores for participants who completed a six-week training period (66.7%, 33.4%, and 25.0% for attention and processing, working memory, and abstraction and logic, respectively). The results show that positive emotional arousal had a positive effect on the MCI participants. The training tasks and arousal elements can improve cognitive function and enhance the confidence and engagement of participants. There were no significant differences in cognitive domain training scores between the two groups. ConclusionsThis personalized cognitive training system has the potential to serve as a convenient solution for complementary treatment of MCI.

Stability in cognitive classification as a function of severity of impairment and ethnicity: A longitudinal analysis

Objective The interaction of ethnicity, progression of cognitive impairment, and neuroimaging biomarkers of Alzheimer’s Disease remains unclear. We investigated the stability in cognitive status classification (cognitively normal [CN] and mild cognitive impairment [MCI]) of 209 participants (124 Hispanics/Latinos and 85 European Americans). Methods Biomarkers (structural MRI and amyloid PET scans) were compared between Hispanic/Latino and European American individuals who presented a change in cognitive diagnosis during the second or third follow-up and those who remained stable over time. Results There were no significant differences in biomarkers between ethnic groups in any of the diagnostic categories. The frequency of CN and MCI participants who were progressors (progressed to a more severe cognitive diagnosis at follow-up) and non-progressors (either stable through follow-ups or unstable [progressed but later reverted to a diagnosis of CN]) did not significantly differ across ethnic groups. Progressors had greater atrophy in the hippocampus (HP) and entorhinal cortex (ERC) at baseline compared to unstable non-progressors (reverters) for both ethnic groups, and more significant ERC atrophy was observed among progressors of the Hispanic/Latino group. For European Americans diagnosed with MCI, there were 60% more progressors than reverters (reverted from MCI to CN), while among Hispanics/Latinos with MCI, there were 7% more reverters than progressors. Binomial logistic regressions predicting progression, including brain biomarkers, MMSE, and ethnicity, demonstrated that only MMSE was a predictor for CN participants at baseline. However, for MCI participants at baseline, HP atrophy, ERC atrophy, and MMSE predicted progression.

Prevalence and clinical associations of atrophy subtypes using clinical routine image analysis software in MCI patients from a memory clinic population

AbstractBackgroundThree patterns of brain atrophy have been consistently identified in cases of Alzheimer’s dementia [1]: a limbic‐predominant (LP) phenotype, with atrophy of the hippocampus but relatively spared neocortex; a hippocampal sparing (HS) phenotype, with atrophy in the cortex (especially lateral temporal and parietal lobes) but sparing of the hippocampus; and a typical/diffuse (TD) phenotype that presents with atrophy in both. A recent study extended this concept to a less severely affected memory clinic population (the MEMENTO Study). Here, we assessed atrophy subtypes in that same population using an approach based on the output of QyScore® an FDA‐approved and CE‐marked image analysis software.Method1642 MCI participants from the MEMENTO cohort (Age 71±9, MMSE 27.8±2.0, CDR‐SB 0.6±0.7) had 3DT1 MRI scans analyzed with QyScore®. 678 (41%) had amyloid status from CSF or PET, of which 193 (28%) were amyloid‐positive (A+). Neurodegeneration‐positive (N+) atrophy subtypes were defined on individual scans using z‐scores from parietal cortex and hippocampus volumes referenced to 1290 cognitively normal individuals. LP and HS were defined by atrophy (z←1.64) of parietal lobe or hippocampus only, and TD by atrophy in both structures (otherwise N‐).ResultThe proportion of single‐domain amnestic (aMCIsd), multi‐domain amnestic (aMCImd), single‐domain non‐amnestic (naMCIsd) and multi‐domain non‐amnestic (naMCImd) individuals was 10%, 50%, 21% and 18% respectively. N+ subtypes were more prevalent in amnestic (aMCIsd 18%, aMCImd 17%) than non‐amnestic (naMCIsd 8%, naMCImd 10%) presentations. N+ subtypes were more common in A+ participants, especially the amnestic presentations (aMCIsd 42%, aMCImd 29%). Overall, the HS subtype was the most common (8% of all cases, 16% of A+ cases), followed by LP (4%/6%) and TD (2%/3%). The LP subtype was more prevalent in amnestic presentations.ConclusionThe relatively low prevalence of the TD subtype in this cohort is consistent with [2]. The overall prevalence of N+ subtypes in MEMENTO by this method is intermediate between those previously reported using a similar method for ADNI CN A+ and aMCI A+ cohorts [3].[1] Ferriera et al. (2020) Neurology 94:436 [2] Planche et al. (2021) Alz & Dem 17(4):651 [3] Charil et al. (2018) AAIC

Associations of cortisol with neuroinflammation biomarkers in a memory clinic cohort

AbstractBackgroundCortisol, one of the most important mediators of stress in humans, is often found increased in Alzheimer’s disease (AD) patients and correlates with disease severity. Stress response and inflammation are two systems that are tightly associated to one another. Several lines of evidence suggest that cortisol can promote inflammation. However, less is known on the interaction of cortisol with neuroinflammation in the context of AD, and to the best of our knowledge there are no human studies that have systematically explored the association of these two systems in AD patients so far. The aim of this study was to investigate levels of cerebrospinal fluid (CSF) biomarkers of neuroinflammation and their relationship to salivary cortisol in a memory clinic cohort.MethodA total of 108 memory clinic patients with subjective cognitive decline (SCI, n = 40), mild cognitive impairment (MCI, n = 39) and AD (n = 29), from the Karolinska University Hospital in Stockholm, Sweden, were included in this study. Salivary cortisol was collected at six timepoints during the day on two days, to quantify awakening cortisol, cortisol awakening response (CAR), bedtime cortisol and total cortisol. CSF levels of 37 neuroinflammation and cerebrovascular dysfunction biomarkers were determined by a multiplex immunoassay. Associations among cortisol and neuroinflammation markers were assessed by linear regression models adjusting for age and diagnosis. ANCOVA tests were used to compare biomarker levels between the diagnostic groups.ResultAwakening cortisol was significantly elevated in the AD group compared to the SCI and MCI participants. Higher IP‐10 and placental growth factor (PlGF) levels were associated with decreased CAR independent of age and diagnosis. Thymus and activation‐regulated chemokine (TARC), CRP, intracellular adhesion molecule 1 (ICAM‐1) and vascular cell adhesion molecule 1 (VCAM‐1) levels were upregulated in MCI participants compared to SCI and AD.ConclusionWe provide evidence that the HPA axis is altered in AD. Moreover, salivary cortisol is associated to neuroinflammation in an age and diagnosis independent manner. Finally, neuroinflammatory and vascular dysfunction regulators are increased in CSF during MCI stages followed by a drop in their levels in AD participants, presumably reflecting a more active role of neuroinflammation at an early state.

Electrophysiological signatures of memory depletion in mild cognitive impairment

AbstractBackgroundMCI diagnosis does not necessarily imply the development of dementia. For this reason, characterizing the MCI profile is fundamental to the early identification of electrophysiological markers associated with a higher risk of developing Alzheimer’s Disease (AD). Longitudinal studies demonstrated that the delay recall measure is a good predictor of conversion and is one of the most common manifestations of the preclinical stage. This study has for purpose compared the power spectrum in the resting‐state of MCI and their relationship with neuropsychological and structural measures.MethodWe compared the power spectrum in resting‐state eyes‐closed magnetoencephalographic of 93 MCI participants (aged from 64 to 87) recruited from the Hospital Universitario San Carlos (Madrid, Spain). According to their memory performance in delay recall, the sample was split into (i) ‘moderate’ MCI (n = 52) group and (ii) ‘severe’ MCI (n = 41) group. The groups did not differ in age or years of education.ResultsThe severe MCI patients showed higher theta power than patients with moderate MCI were significant differences between both. Also, moderate MCI correlated significantly with years of education (rho = ‐0.31, p < 0.02) and TMT A time (rho = 0.40, p < 0.004). In the Severe MCI group, the theta power showed significant correlation with MMSE (rho = ‐0.43, p < 0.001) and total hippocampus (rho = 0.41, p < 0.001).ConclusionLoss of delay recall performance seems to be associated with electrophysiological alterations that can be used as non‐invasive markers of AD progression.

Decoding the heterogeneity of Alzheimer’s disease diagnosis and progression using multilayer networks

Alzheimer’s disease (AD) is a multifactorial and heterogeneous disorder, which makes early detection a challenge. Studies have attempted to combine biomarkers to improve AD detection and predict progression. However, most of the existing work reports results in parallel or compares normalized findings but does not analyze data simultaneously. We tested a multi-dimensional network framework, applied to 490 subjects (cognitively normal [CN] = 147; mild cognitive impairment [MCI] = 287; AD = 56) from ADNI, to create a single model capable of capturing the heterogeneity and progression of AD. First, we constructed subject similarity networks for structural magnetic resonance imaging, amyloid-β positron emission tomography, cerebrospinal fluid, cognition, and genetics data and then applied multilayer community detection to find groups with shared similarities across modalities. Individuals were also followed-up longitudinally, with AD subjects having, on average, 4.5 years of follow-up. Our findings show that multilayer community detection allows for accurate identification of present and future AD (≈90%) and is also able to identify cases that were misdiagnosed clinically. From all MCI participants who developed AD or reverted to CN, the multilayer model correctly identified 90.8% and 88.5% of cases respectively. We observed similar subtypes across the full sample and when examining multimodal data from subjects with no AD pathology (i.e., amyloid negative). Finally, these results were also validated using an independent testing set. In summary, the multilayer framework is successful in detecting AD and provides unique insight into the heterogeneity of the disease by identifying subtypes that share similar multidisciplinary profiles of neurological, cognitive, pathological, and genetics information.

Asymmetries in the theta/beta ratio distinguish cognitively normal elderly from those with mild cognitive impairment

AbstractBackgroundThe search for psychophysiological markers that distinguish normal from abnormal aging has produced many candidate EEG dynamics, but relatively little research has been done (or at least reported) on the theta/beta ratio or brain wave asymmetries.MethodsWe previously reported frontal asymmetries (frontal alpha and frontal beta asymmetry) originally investigated in the context of anxiety and approach‐avoidance motivation that distinguish MCI from healthy, cognitively normal persons (HC). Another potentially more cognitively‐involved marker, the ratio of theta to beta frequencies (TBR), originally investigated as a marker of attention deficits, might also usefully distinguish cognitive HC from MCI. We took advantage of a previously collected data set to conduct an exploratory analysis of the pattern of TBR in HC and MCI participants. Resting state EEG (rsEEG) was measured before and after a simple motion direction discrimination task. We investigated the standard frontal TBR as measured at frontal electrode FZ. We estimated power spectral density in the resting state (eyes closed) for both pre‐ and post‐task, extracting estimates of TBR at electrode Fz.ResultsWe found that MCI had significantly higher TBR than cognitively normal elderly, F(1,95)=4.98, p=0.028, with no effect of timepoint and no interaction. We then explored the possibility that TBR itself has meaningful asymmetries, calculating the TBR asymmetry at the following electrode pairs: F3‐F4, C3‐C4, CP3‐CP4, P3‐P4, PO3‐PO4. This analysis revealed an interesting pattern, with group (HC vs. MCI) interacting with location, F(4,380)=5.25, p<0.001. Relative to HC, MCI participants had higher TBR on the right (positive TBR asymmetry) in frontal electrodes (F3‐F4), but higher TBR on the left (negative TBR asymmetry) over parietal‐occipital sites (P3‐P4 and PO3‐PO4). The parietal asymmetry may reflect the early spread of lesions from inferior temporal regions to areas subserving language and visuospatial processing, but the frontal asymmetry is less obviously tied to known progression of brain lesions, and may reflect heterogeneity in the underlying pathogenesis of this sample of people with MCI.ConclusionTBR asymmetries obtained in rsEEG can contribute significantly to successful discrimination of older persons with MCI from those with normal cognitive functioning.

Efficacy in linguistic characteristics: I‐CONECT project

AbstractBackgroundResearchers have documented ample evidence suggesting progressive decline in linguistic and syntactic abilities due to cognitive decline. Among measures of syntactic complexity derived from natural language processing (NLP) approaches, we hypothesized that the number of coordinated phrases (CPs, an indicator of sentence complexity) would improve from an intervention which intended to enhance cognitive function by providing social interactions through frequent video‐chats.MethodIn the I‐CONECT project, the experimental group engaged in a high dose of semi‐structured conversations (four times per week) via video‐chats, with additional weekly 10 minutes telephone check‐ins. The control group received only the weekly telephone check‐ins. We analyzed language samples derived from the weekly phone check‐ins (WPCs) in this study. WPCs mainly ask about social activities engaged by the participant during the previous week with some semi‐structured open‐ended questions. Out of 186 subjects who were randomized to the trial, 113 subjects had at least one recording of WPCs with sufficient recording quality during the 2nd, 3rd and 4th weeks of the intervention (baseline) and during the 3 weeks (i.e., 22, 23, 24th) before the month 6 (M6) assessments. We extracted the number of CPs from WPCs of 52 experimental (25 MCI, 27 normal) and 61 control (34 MCI, 27 normal) participants. We regressed CP scores at M6 on age, gender, years of education, the experimental (vs. control) group, controlling for baseline CP scores using a linear regression model.ResultAmong the MCI group, the experimental group’s CP scores were 0.60 points higher than the control group (p = 0.046) at M6, which is equivalent to over 10 years of age difference in CP scores (i.e., ‐0.055×10 = ‐0.55), controlling for covariates listed above (see Figure 1). Among those with normal cognition, we did not find any significant differences between the two groups at M6 (p = 0.414).ConclusionWe found that an indicator of sentence complexity improved among the experimental group compared with the control group among the MCI participants. Our results indicated that language measures are capable of tracking clinically meaningful changes in language samples capitalizing their potential use in clinical trials as automated outcome measures.

Longitudinal evolution of neuropathological substrates of Alzheimer’s disease in obese patients

AbstractBackgroundObesity is a metabolic condition with increasing prevalence all over the world. Patients with a body mass index (BMI) higher than 30 are considered obese. Obesity is also a risk factor for chronic morbidities such as type 2 diabetes and may increase the risk of developing Alzheimer's disease (AD). Not much is known about longitudinal changes in Alzheimer’s pathology in these patients. We hypothesised that BMI would predict longitudinal pathological alterations derived from imaging parameters.Method252 participants (n=107 obese non‐diabetic patients with BMI>30) cognitively normal (n=80) and with mild cognitive impairment (n=172) were evaluated from the Alzheimer’s Disease Neuroimaging Initiative (Mean age = 73.6 years, SD = 8.0). All participants had two T1‐weighted MPRAGE MRI scans within two‐years (Mean gap=718 days, SD=107). Regional cortical thickness was measured on T1‐MPRAGE using FreeSurfer v.6.0. Individual gray matter density maps were computed using voxel‐based morphometry (VBM) and regional values were sampled in various cortical regions. Regional cortical thickness and gray matter density are expressed as delta values between baseline and followup (Value followup ‐ Value Baseline). Spearman’s correlation coefficients were calculated to assess the relationship between BMI and imaging biomarkers.ResultIn the whole cohort, we found that BMI is significantly negatively correlated with longitudinal changes in cortical thickness in anterior cingulate (ACC, p=0.0073, r=‐0.17) and posterior cingulate (PCC, p=0.0147, r=‐0.15) cortical thickness. We also found that BMI is significantly negatively correlated with longitudinal changes in frontal (p=0.0184, r=‐0.15), parietal (p=0.0057, r=‐0.18) and temporal (p=0.0141, r=‐0.16) gray matter density. When looking only at MCI participants, we found similar results with even stronger correlations. BMI is significantly negatively correlated with delta anterior cingulate (ACC, p=0.0008, r=‐0.25) and posterior cingulate (PCC, p=0.004, r=‐0.22) cortical thickness.ConclusionIn this cohort of obese and non‐obese participants cognitively normal and with MCI, we found that obesity was associated with a longitudinal 2‐years worsening of macrostructural changes. Higher BMI was associated with a higher reduction of cortical thickness and with a decreased gray matter density in several brain regions.

Cognitive assessment in diverse populations: implications for Alzheimer’s disease clinical trials

AbstractBackgroundBy 2060, racially/ethnically diverse individuals will constitute almost half of all older adults in the US and experience largest increases in dementia burden. Appropriate representation of diverse participants in clinical trials is critical to ensure generalizability of outcomes. Screening/inclusion criteria for trials often involve a brief cognitive assessment to indicate overall disease severity. We examined the Mini‐Mental State Examination (MMSE), the most widely used assessment, as a recruitment tool in diverse older adults.MethodData from 10,377 older adults (8,585 controls, 1,752 MCI; 232 Asian, 1,641 Black, 623 Hispanic, 7,841 White) were drawn from the National Alzheimer’s Coordinating Center (NACC) uniform data set. Only MCI participants for whom AD was presumed to be the primary etiology per NACC protocol were included. We performed logistic regressions to examine the likelihood of performing at/above a conventional MMSE cutoff of 24 in MCI participants. Multivariable regressions were performed to examine associations between 1) demographic variables and MMSE performance in controls, and 2) MMSE and CDR Sum of Boxes (CDR‐SB) in all participants.ResultCompared to White participants, Asian (OR = 0.46 [0.24‐0.99]), Black (OR = 0.53 [0.35‐0.80]), and Hispanic (OR = 0.38 [0.24‐0.61]) older adults with MCI were significantly less likely to perform at/above MMSE cutoff. Regressions in controls revealed a significant race/ethnicity by education interaction with greater magnitude of the association between education and MMSE in Black and Hispanic participants controlling for age, sex, and primary language. Associations between MMSE and CDR‐SB were significantly weaker in Black and Hispanic participants (Figure 1) and participants without high school education after controlling for age, sex, and primary language.ConclusionWe found that the MMSE has a greater education bias and weaker functional validity among Black and Hispanic older adults. Findings suggest that using an MMSE cutoff may be an inappropriate criterion for assessing disease stage among underrepresented participants. We discuss the implications of findings for the current state of diversity in clinical trials and for clinical diagnostic practice with diverse older adults. Focus points will include the need for culturally fair, sensitive, and psychometrically robust brief cognitive measures and the critical importance of incorporating social determinants of health into clinical and research practices.

Microstructural changes in the white matter tracts of the brain due to mild cognitive impairment

AbstractBackgroundMild cognitive impairment (MCI) is an early stage of memory loss or cognitive decline and progresses to Alzheimer’s disease at a rate of about 15% per year. It is important to study the effects of MCI on the brain. Here we present a novel along‐tract analysis of microstructural brain metrics computed from diffusion MRI. We extract, map, and visualize the profile of microstructural abnormalities on 3D models of fiber tracts, yielding fine‐scale maps of the effects of MCI.MethodsWe analyzed multi‐shell diffusion‐weighted MRI data with 127 volumes from 131 ADNI3 participants (age: 55‐91years, 74F,57M). Participants included 44 with MCI and 87 cognitively normal controls (CN). Pre‐processed using the ADNI3 dMRI protocol. We applied multi‐shell‐multi‐tissue CSD and a probabilistic particle‐filtering‐tracking to generate whole‐brain tractograms. We applied DIPY’s BUAN tractometry pipeline to extract 30 white matter tracts from all subjects and evaluate the effects of MCI on 4 DTI measures (FA, MD, RD, and AD) along the length of the tracts. BUAN applies Linear‐Mixed‐Models with DTI measures set as the response variable, group mean modeled as fixed effects term, and subject‐specific mean as random effects term.ResultsWe report significant group differences between MCI and CN in 6 bundles with p‐values<0.01 and <0.001 (Fig.1). In Fig.1 and Fig2, the columns and rows show results from six bundles for four DTI measures (see Fig.2 for keywords). Fig.2 highlights areas with significant differences on the tracts with black color where for MD, p‐values<0.001 and for the rest of the 3 measures, p‐values<0.01. Fig.3 reports significant effects of MCI on the rest of the tracts and measures with p‐values<0.001. We find lower mean FA and higher mean MD, AD, and RD in the MCI, compared to the control group.ConclusionWe applied the BUAN tractometry pipeline to map and visualize the effects of MCI on the white matter tracts of the brain. We found significant microstructural group differences in tracts where FA decreases and diffusivity measures increase in MCI participants.

Prevalence and clinical associations of atrophy subtypes using clinical routine image analysis software in MCI patients from a memory clinic population

AbstractBackgroundThree patterns of brain atrophy have been consistently identified in cases of Alzheimer’s dementia [1]: a limbic‐predominant (LP) phenotype, with atrophy of the hippocampus but relatively spared neocortex; a hippocampal sparing (HS) phenotype, with atrophy in the cortex (especially lateral temporal and parietal lobes) but sparing of the hippocampus; and a typical/diffuse (TD) phenotype that presents with atrophy in both. A recent study extended this concept to a less severely affected memory clinic population (the MEMENTO Study). Here, we assessed atrophy subtypes in that same population using an approach based on the output of QyScore® an FDA‐approved and CE‐marked image analysis software.Method1642 MCI participants from the MEMENTO cohort (Age 71±9, MMSE 27.8±2.0, CDR‐SB 0.6±0.7) had 3DT1 MRI scans analyzed with QyScore®. 678 (41%) had amyloid status from CSF or PET, of which 193 (28%) were amyloid‐positive (A+). Neurodegeneration‐positive (N+) atrophy subtypes were defined on individual scans using z‐scores from parietal cortex and hippocampus volumes referenced to 1290 cognitively normal individuals. LP and HS were defined by atrophy (z<‐1.64) of parietal lobe or hippocampus only, and TD by atrophy in both structures (otherwise N‐).ResultThe proportion of single‐domain amnestic (aMCIsd), multi‐domain amnestic (aMCImd), single‐domain non‐amnestic (naMCIsd) and multi‐domain non‐amnestic (naMCImd) individuals was 10%, 50%, 21% and 18% respectively. N+ subtypes were more prevalent in amnestic (aMCIsd 18%, aMCImd 17%) than non‐amnestic (naMCIsd 8%, naMCImd 10%) presentations. N+ subtypes were more common in A+ participants, especially the amnestic presentations (aMCIsd 42%, aMCImd 29%). Overall, the HS subtype was the most common (8% of all cases, 16% of A+ cases), followed by LP (4%/6%) and TD (2%/3%). The LP subtype was more prevalent in amnestic presentations.ConclusionThe relatively low prevalence of the TD subtype in this cohort is consistent with [2]. The overall prevalence of N+ subtypes in MEMENTO by this method is intermediate between those previously reported using a similar method for ADNI CN A+ and aMCI A+ cohorts [3].[1] Ferriera et al. (2020) Neurology 94:436 [2] Planche et al. (2021) Alz & Dem 17(4):651 [3] Charil et al. (2018) AAIC

Posterior hippocampal redundancy: A marker of non‐pathological brain aging

AbstractBackgroundSeveral neural mechanisms underlying brain resilience to Alzheimer’s disease (AD) have been proposed, including redundant neural connections between the posterior hippocampi and all other brain regions (pHipp‐redundancy), and global functional connectivity of the left frontal cortex (gLFC). It remains unclear whether these two mechanisms confer resilience to AD pathologies through similar or distinctive mechanisms. We examined if redundancy, measured through graph theory, underlies the neuroprotective effects of both pHipp‐redundancy and gLFC connectivity in the early stage of AD pathologies.MethodFrom the ADNI database, 370 CN and MCI participants were utilized. Aβ‐positivity (Aβ+) was defined as PET AV45 SUVR normalized to cerebellum greater than 1.11. Resting state data were preprocessed using fMRIprep (v20.2.6). Network graphs were constructed with 263 functional ROIs as nodes and z‐transformed correlations between each node as edges. Redundancy was calculated by summing the direct and indirect paths (path lengths=1‐4) between each hippocampal region (i.e., anterior and posterior hippocampal regions, bilaterally and LFC) and its 262 connections. Group differences (Aβ‐status, diagnosis) were computed in R using non‐parametric ANCOVA models with 10,000 permutations. Regression analyses were conducted to examine if Aβ‐status and diagnosis moderated the relationship between SUVR and redundancy. Models covaried for age, sex, education, and APOE4.ResultAcross CN and MCI, Aβ‐ had higher bilateral pHipp‐redundancy than Aβ+ (p’s<.034). Diagnosis significantly moderated the relationship between SUVR and left pHipp‐redundancy (β=0.112, p=.042). CN exhibited a stronger negative relationship between SUVR and left pHipp‐redundancy than MCI (p<.001). Finally, in CN, Aβ‐status significantly moderated the relationship between SUVR and right aHipp‐redundancy (β=0.358, p=.012), showing that in Aβ‐ CN, redundancy decreased with higher SUVR (p=.01), while in Aβ+ CN, redundancy remained the same as SUVRs increased. No relationships between Aβ‐status and redundancy, and interactions between SUVR and Aβ‐status or diagnosis, were significant in LFC.ConclusionTogether, these findings suggest that bilateral pHipp‐redundancy may reflect normal brain aging without Aβ, rather than resilience in pathological aging, and a distinctive mechanism of brain aging from that of gLFC connectivity in the progression of AD.

Posterior hippocampal redundancy: A marker of non‐pathological brain aging

AbstractBackgroundSeveral neural mechanisms underlying brain resilience to Alzheimer’s disease (AD) have been proposed, including redundant neural connections between the posterior hippocampi and all other brain regions (pHipp‐redundancy), and global functional connectivity of the left frontal cortex (gLFC). It remains unclear whether these two mechanisms confer resilience to AD pathologies through similar or distinctive mechanisms. We examined if redundancy, measured through graph theory, underlies the neuroprotective effects of both pHipp‐redundancy and gLFC connectivity in the early stage of AD pathologies.MethodFrom the ADNI database, 370 CN and MCI participants were utilized. Aβ‐positivity (Aβ+) was defined as PET AV45 SUVR normalized to cerebellum greater than 1.11. Resting state data were preprocessed using fMRIprep. Network graphs were constructed with 263 functional ROIs as nodes and z‐transformed correlations between each node as edges. Redundancy was calculated by summing the direct and indirect paths (path lengths=1‐4) between each hippocampal region (i.e., anterior and posterior hippocampal regions, bilaterally and LFC) and its 262 connections. Group differences (Aβ‐status, diagnosis) were computed in R using non‐parametric ANCOVA models with 10,000 permutations. Regression analyses were conducted to examine if Aβ‐status and diagnosis moderated the relationship between SUVR and redundancy. Models covaried for age, sex, education, and APOE4.ResultAcross CN and MCI, Aβ‐ had higher bilateral pHipp‐redundancy than Aβ+ (p’s<.034). Diagnosis significantly moderated the relationship between SUVR and left pHipp‐redundancy (B=16143.0, p=.042). CN exhibited a stronger negative relationship between SUVR and left pHipp‐redundancy than MCI (B=‐20161.59, t=3.08, p<.001). Finally, in CN, Aβ‐status significantly moderated the relationship between SUVR and right aHipp‐redundancy (B=59345.0, p=.012), showing that in Aβ‐ CN, redundancy decreased with higher SUVR (B=‐60532.07, t=2.82, p=.01), while in Aβ+ CN, redundancy remained the same as SUVRs increased. No relationships between Aβ‐status and redundancy, and interactions between SUVR and Aβ‐status or diagnosis, were significant in LFC.ConclusionTogether, these findings suggest that bilateral pHipp‐redundancy may reflect normal brain aging without Aβ, rather than resilience in pathological aging, and a distinctive mechanism of brain aging from that of gLFC connectivity in the progression of AD.

Is cortical grey matter diffusivity an early biomarker for neuronal damage?

AbstractBackgroundThere is growing evidence that pathological changes in Alzheimer’s disease (AD) begin several years before the symptom onset. Neuroimaging approaches can be used to detect microstructural alterations in the early stages of neurodegeneration using diffusion‐weighted MRI. Cortical grey matter mean diffusivity (cMD) is thought to be increased in AD following pathological alterations resulting in disrupted neuronal function, neuronal death and cellular atrophy. We hypothesised that changes in MD could be detected early in the disease progression and that they would be correlated with structural imaging biomarkers.Method72 patients (mean age=69.1, SD=9.2) cognitively normal (CN, n=21) and with mild cognitive impairment (MCI, n=51) were included in this study. All participants underwent T1‐weighted MPRAGE MRI, diffusion tensor imaging (DTI) and PET amyloid ([18F]flutemetamol). Regional cortical thickness was measured on T1‐MPRAGE using FreeSurfer v.6.0. DTI data were processed with FSL v.6.0 to compute MD maps. Standard uptake ratio (SUVR) values were calculated in SPM12 to identify the amyloid deposition within cortical regions. Amyloid status (Aβ‐positive/Aβ‐negative) was determined from processed data using a cerebellar gray matter reference to create target‐to‐cerebellar ratio. Subjects were considered positive with an uptake value of greater than mean+2SD of the control subjects. Student's t‐test were used to compare imaging modalities between CN and MCI participants. Pearson’s correlation coefficients were calculated to assess the relationship between imaging modalities.ResultThere was a significantly increased MD in MCI compared to CN participants in hippocampus (p=0.0213) and in medial temporal lobe (p=0.033). There were no significant group differences neither in whole brain mean cortical thickness (p=0.6984) nor in temporal cortical thickness (p=0.0923). Interestingly, when splitting subjects based on their amyloid status, we found that whole brain MD was significantly negatively correlated with whole brain cortical thickness in amyloid negative (CN+MCI amyloid negative, p<0.001) but not in amyloid positive (CN+MCI amyloid positive, p=0.99).ConclusionWe found that changes in gray matter diffusivity could be detected in the early stages of AD pathology. We also found that there is a direct relationship between MD and structural changes (i.e. cortical thickness) only before amyloid deposition suggesting that MD provides information about early microstructural changes before macrostructural changes.

The role of IGFBP2 in pre‐symptomatic Alzheimer's disease: a multimodal longitudinal study of cognitively unaffected individuals with a family history of sporadic Alzheimer’s disease

AbstractBackgroundInsulin‐like growth factors (IGF) play pivotal roles in neurogenesis, neuronal survival, synaptogenesis and compensatory repair mechanisms following injury. Insulin‐like growth factor binding proteins (IGFBP) bind to IGFs, and regulate interactions between IGFs and their cell surface receptors. In the brain, IGFBP2 is the most abundant IGFBP. Several studies have observed altered IGFBP2 levels in Alzheimer’s disease (AD) patients. However, the role of IGFBP2 during pre‐symptomatic AD remains unknown. Thus, we used longitudinal data acquired from the pre‐symptomatic PREVENT‐AD cohort to examine its possible contributions to AD pathophysiology.MethodFor initial cross‐sectional analyses, the Mini‐Mental State Examination was used to stage the participants (PREVENT‐AD, CCNA and Douglas cohorts) across the AD spectrum. Olink’s primer extension assay was used to measure cerebrospinal fluid (CSF) IGFBP2 levels. PREVENT‐AD participants were followed longitudinally for 6‐8 years. Annual visits included cognitive performance assessments, lumbar punctures and neuroimaging. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) evaluated five cognitive domains (immediate memory, delayed memory, attention, language and visuospatial abilities) and included a total summary score.ResultCSF IGFBP2 levels were significantly reduced in MCI (p < 0.001) and AD participants (p = 0.027 and p < 0.001 respectively), relative to controls (Figure 1). In the PREVENT‐AD cohort, baseline CSF IGFBP2 levels were negatively correlated with RBANS cognitive performance trajectory slopes estimated over the course of 6 to 8 years, for the delayed memory (p = 0.003), visuospatial (p = 0.008) and total scale indices (p = 0.021) (Figure 2). However, baseline CSF IGFBP2 levels were not associated with cognitive decline for the immediate memory (p = 0.162), attention (p = 0.890) and language (p = 0.841) indices (Figure 3). Finally, in the PREVENT‐AD cohort, baseline CSF IGFBP2 levels were negatively correlated with baseline left entorhinal cortex volume (p = 0.011), but were not correlated with right entorhinal cortex volume (p = 0.868)(Figure 4).ConclusionOur results suggest that IGFBP2 may exhibit a bi‐directional association with AD stage pathology. Our findings revealed that IGFBP2 is strongly correlated with early cognitive decline in the delayed memory and visuospatial domains, in pre‐symptomatic individuals.

Prediction of Progression Along the Transition Points within the Continuum of Cognitive Impairment from Subjective Cognitive Complaints to Dementia Using Dyadic Patterns of Subjective Reporting

AbstractBackgroundThe validity of Subjective Cognitive Complaints (SCCs) from dyadic patterns to predict progression to dementia is not yet clear. Some studies suggest that the validity of informant report in predicting dementia increases as cognitive function and awareness of symptoms decline. Our aim was to compare validity of informant and participant reports, and its agreement, to predict progression to MCI and conversion to dementia.MethodA total of 226 participants from the CompAS study were longitudinally assessed (intervals 18–24 months). The sample consisted of SCD (198) and MCI (28) participants. SCCs from participants and informants were assessed at baseline, 1st and 2nd follow‐ups using the QAM questionnaire. Informant‐participant total score agreement (disagreement, over‐ and under‐estimation, were identically considered) were calculated. Logistic regressions were separately performed to distinguish SCD stables and participants progressing either from SCD to MCI/dementia or from MCI to dementia using SCCs reports from participants, informants and agreement as predictive variables.ResultsInformant report at baseline significantly predicted conversion to dementia from baseline to the 3rd follow‐up (β = .173; SE = .048; p<.001; OR = 1.189, CI = 1.082‐1.306), similarly to that observed for informant reports at 1st follow‐up to predict conversion from 1st to the 3rd follow‐up (β = .225; SE = .050; p = .001; OR = 1.252; CI = 1.135‐1.381), and at 2nd follow‐up to predict conversion from 2nd to the 3rd follow‐up (β = .271; SE = .083; p<.001; OR = 1.313; CI = 1.110–1.552) (see Table 1).Informant report at baseline also successfully predicted the progression to MCI from baseline to the 3rd follow‐up (β = .139; SE = .057; p = .017; OR = 1.49; CI = 1.025‐1.288), similarly to that observed for informant reports at 1st (β = .124; SE = .056; p = .026; OR = 1.132; CI = 1.015‐1.264), and the 2nd follow‐ups (β = .195; SE = .073; p = .008; OR = 1.216; CI = 1.053‐1.404) (see Table 2).Conversion to dementia (β = .113; SE = .048; p = .018; OR = 1.119; CI = 1.020‐1.229) and progression to MCI (β = .138; SE = .054; p = .011; OR = 1.148; CI = 1.032‐1.277) using Self‐report were only significantly predicted using 1st follow‐up reports.Agreement did not significantly predict the progression to MCI or dementia at any of measurement points.ConclusionsInformant report successfully predicted progression and conversion at any transition point. Self‐reports were only predictive at 1st follow‐up. Agreement did not significantly predict progression and conversion.