Subjective Cognitive Impairment Research Articles

AGE-FRIENDLY ENVIRONMENT PROMOTES WELL-BEING IN PEOPLE WITH SUBJECTIVE MEMORY IMPAIRMENT

Abstract Objectives Older people with cognitive impairment are more likely to feel lonely and to have lower well-being compared to others (Shankar et al., 2017). One way to overcome difficulties and loneliness is to live in an Age Friendly Environment (AFE) (Gibney et al., 2020). Living in an AFE enables older people to stay active even when function deteriorates (Cramm et al., 2018) and thus- maintain low loneliness and high well-being (Domènech-Abella et al., 2021). Approximately 18%-25% of people aged 60 and over whose objective cognitive function is normal report a subjective cognitive impairment (Röhr et al., 2020; Zullo et al., 2021). They are less active (Parikh et al., 2016) and so, they are lonelier (Montejo Carrasco et al., 2020). The aim of this study was to examine whether living in an AFE enables people coping with subjective memory impairment to maintain higher well-being than those who don’t. Methods Applying a correlational study design, 105 community dwelling older adults (mean age 74.5; SD-6.54), 62% of whom were women, were recruited. Hayes’ PROCESS macro (Model 7) assessed relationships between socio-demographic data, subjective social support (SS), loneliness, a sense of belonging, AFE, active ageing and negative affect (NA). Results Findings demonstrated a significant indirect association between age-friendly environments and negative affect, which was moderated by subjective memory impairment. Moreover, we found an interaction between AFE and memory.. Those with SMI experienced less loneliness in an AFE In conclusion, AFE is crucial for individuals with SMI to reduce loneliness and negative affect. Conclusion This study is the first to show that when AFE is low, people with subjective memory impairment cope with more loneliness compared to those without it, but when AFE is high then there is no difference in the level of loneliness between people with or without subjective memory impairment. Hence, AFE is especially significant for those coping with subjective memory impairment for reducing loneliness and negative affect. Authorities should strive to create AFE to promote active aging and high WB of older people living in the community.

Comorbidities associated with symptoms of subjective cognitive decline in individuals aged 45-64.

Early-stage cognitive decline occurs when an individual experiences memory loss or other cognitive impairment but does not meet the criteria for Alzheimer's disease (AD) or other dementias. After diagnosis of mild cognitive impairment (MCI), approximately 5-15 % of cases progress to dementia per year. AD and many other causes of dementia are presently incurable. Early recognition of cognitive decline can allow healthcare providers to reduce the risk of disease progression. Literature is scarce on factors that can increase the incidence of cognitive decline, especially in early ages; this is further exacerbated by difficulty tracking the prevalence of mild cognitive symptoms. This analysis aims to determine demographic and comorbid factors that predispose individuals to higher rates of early-stage subjective cognitive impairment in order to determine which individuals should be screened at earlier stages. We conducted a cross-sectional analysis of data from the Subjective Cognitive Decline module of the 2017-2021 Behavioral Risk Factor Surveillance System (BRFSS). Applying survey design and sampling weights, we constructed binary logistic regression models to assess associations, via odds ratios (OR), between comorbidities and subjective cognitive decline (SCD). Alpha was set at 0.05 and confidence intervals (CIs) are reported at 95 %. Our sample included 110,305 participants representing 13.4 million US adults aged 45-64 years. Results showed that individuals with diabetes (OR: 2.29, CI: 2.09-2.51), hypertension (OR: 1.98, CI: 1.81-2.17), stroke (OR: 4.61, CI: 4.07-5.22), myocardial infarction (MI [OR: 3.09, CI: 2.73-3.49]), coronary heart disease (CHD [OR: 3.26, CI: 2.88-3.69]), depression (OR: 5.65, CI: 5.21-6.11), and chronic kidney disease (CKD [OR: 3.08, CI: 2.66-3.58]) experienced higher rates of SCD. Further, there were higher rates of SCD among individuals who identified as American Indian/Alaskan Native (AI/AN), those with low educational attainment, and those with lower incomes. Our findings show that all comorbidities listed were correlated with higher rates of memory loss or confusion. Investigation of factors that are associated with an increased risk of developing new or worsening cognitive decline allows healthcare professionals to properly screen and treat these individuals early, before progressing to conditions that are currently incurable. Future studies into the mechanisms of these diseases in contributing to cognitive decline can illuminate specific effective treatment options.

Machine learning analyses identify multi-modal frailty factors that selectively discriminate four cohorts in the Alzheimer’s disease spectrum: a COMPASS-ND study

BackgroundFrailty indicators can operate in dynamic amalgamations of disease conditions, clinical symptoms, biomarkers, medical signals, cognitive characteristics, and even health beliefs and practices. This study is the first to evaluate which, among these multiple frailty-related indicators, are important and differential predictors of clinical cohorts that represent progression along an Alzheimer’s disease (AD) spectrum. We applied machine-learning technology to such indicators in order to identify the leading predictors of three AD spectrum cohorts; viz., subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD. The common benchmark was a cohort of cognitively unimpaired (CU) older adults.MethodsThe four cohorts were from the cross-sectional Comprehensive Assessment of Neurodegeneration and Dementia dataset. We used random forest analysis (Python 3.7) to simultaneously test the relative importance of 83 multi-modal frailty indicators in discriminating the cohorts. We performed an explainable artificial intelligence method (Tree Shapley Additive exPlanation values) for deep interpretation of prediction effects.ResultsWe observed strong concurrent prediction results, with clusters varying across cohorts. The SCI model demonstrated excellent prediction accuracy (AUC = 0.89). Three leading predictors were poorer quality of life ([QoL]; memory), abnormal lymphocyte count, and abnormal neutrophil count. The MCI model demonstrated a similarly high AUC (0.88). Five leading predictors were poorer QoL (memory, leisure), male sex, abnormal lymphocyte count, and poorer self-rated eyesight. The AD model demonstrated outstanding prediction accuracy (AUC = 0.98). Ten leading predictors were poorer QoL (memory), reduced olfaction, male sex, increased dependence in activities of daily living (n = 6), and poorer visual contrast.ConclusionsBoth convergent and cohort-specific frailty factors discriminated the AD spectrum cohorts. Convergence was observed as all cohorts were marked by lower quality of life (memory), supporting recent research and clinical attention to subjective experiences of memory aging and their potentially broad ramifications. Diversity was displayed in that, of the 14 leading predictors extracted across models, 11 were selectively sensitive to one cohort. A morbidity intensity trend was indicated by an increasing number and diversity of predictors corresponding to clinical severity, especially in AD. Knowledge of differential deficit predictors across AD clinical cohorts may promote precision interventions.

Quality of life in patients with subjective cognitive impairment compared with those diagnosed with mild cognitive impairment or dementia referred to a rural and remote memory clinic

AbstractBackgroundPerceived cognitive decline is a significant source of anxiety for many patients, especially as awareness of dementia grows. We sought to compare whether quality of life (QOL) in patients with subjective cognitive impairment (SCI) who performed normally on a neuropsychological battery significantly differed from those diagnosed with mild cognitive impairment (MCI), Alzheimer’s disease (AD), or non‐Alzheimer’s dementia (non‐AD) at initial assessment in a rural and remote memory clinic.Method610 patients referred to our Rural and Remote Memory Clinic (RRMC) between 2004‐2019 were included in this study. As part of their RRMC assessment, each patient and their caregiver independently rated the patient’s QOL using the Quality of Life of the Patient (QOLPT) scale. We compared self‐reported and caregiver‐reported patient QOL scores in those with SCI (n = 166) to those diagnosed with MCI (n = 98), AD (n = 228), and non‐AD (n = 118).ResultPatients with SCI self‐reported significantly lower QOL compared to patients with AD (mean 34.55 vs 35.96, p<0.05). Interestingly, the reverse was seen in caregivers: SCI caregivers rated patient QOL higher than AD caregivers (mean 34.61 vs 31.72, p<0.001). Patients with SCI also reported lower QOL than patients with MCI (mean 35.55 vs 36.97, p<0.05). SCI caregivers reported higher patient QOL than their non‐AD counterparts (mean 34.61 vs 31.17, p<0.001). Caregiver‐rated patient QOL was higher in those with MCI compared to AD (mean 34.52 vs 31.72, p<0.001). Patients with MCI self‐reported higher QOL scores compared to patients with non‐AD (mean 36.97 vs 34.81, p<0.05). Similarly, MCI caregivers reported higher patient QOL than non‐AD caregivers (mean 34.52 vs 31.72, p<0.001). No other comparisons were statistically significant.ConclusionAlthough they lacked clinically significant cognitive deficits, patients with SCI self‐reported significantly lower QOL than patients with MCI and AD, although patients with MCI self‐reported higher QOL than patients with non‐AD. Conversely, caregiver‐reported patient QOL was higher for patients with SCI than patients with AD and non‐AD. MCI caregivers also reported higher patient QOL compared to AD and non‐AD caregivers. This shows that SCI seriously impacts QOL. More work needs to be done on how we can better support patients with SCI to improve their QOL.

Masseter muscle volume measured by MRI correlated with cognitive function in a memory clinic

AbstractBackground“Oral frailty” which indicates a decline in oral function, has been focused on the fact that it can also affect cognitive function in the elderly population. Although Several studies have been attempted for establishing the utility of the cross‐sectional area or volume of masticatory muscles as objective indices reflecting oral frailty, no report has examined the relationship between masticatory muscles volume and cognitive function in detail. In this study, we aimed to clarify the relationship between size of masseter muscle, one of major masticatory muscles, and cognitive function in the elderly.MethodA total of 349 subjects (mean age 77.3 +/‐ 9.2 years, 126 males and 223 females, 58 with subjective cognitive impairment, 88 with mild cognitive impairment, and 203 with dementia), who visited the Memory clinic of Tohoku University Hospital with a chief complaint of forgetfulness by March 2018 were included. Using 3D T1‐weighted images acquired on a 3‐Tesla MRI system, the bilateral masseter muscle cross‐sectional area was automatically calculated for all subjects using a custom deep‐learning image‐processing model trained on a subset of subjects to identify the relevant muscles and consistent section. Then, partial correlations with the MMSE score were conducted, adjusting for age and gender.ResultThe mean left and right masseter muscle cross‐sectional area are 399.3±84.7mm2 in subjective cognitive impairment, 387.9±106.5 mm2 in mild cognitive impairment, and 355.1±88.4 mm2 in dementia, respectively (p < 0.01). Adjusted for age and sex, they showed a significant correlation with MMSE (R = 0.151, p < 0.01). For post‐hoc stratified analysis, there was a significant correlation between mean masseter muscle cross‐sectional area and MMSE with female patients (R = 0.049, p < 0.05), whereas no correlation with male patients after adjusted age (R = 0.025, p > 0.05).ConclusionOur result revealed that the masseter muscle cross‐sectional area obtained from MRI may be related to cognitive function in the patients with complaint of forgetfulness. Therefore the masticatory function may reflect cognitive function in the elderly who are vulnerable in their memory, and the cross‐sectional area of masseter muscle based on MRI could be a potential indicator for predicting dementia risk.

The role of sleep disturbances in the association between housing conditions and subjective cognitive impairment

AbstractBackgroundAdverse housing conditions such as crowding, air pollution, or insufficient heat are associated with cognitive impairment. However, the mechanism linking adverse housing conditions and cognitive impairment is not fully understood. Adverse housing can affect sleep – an essential physiologic activity for cognitive function, yet this pathway is understudied. We tested associations between housing condition, sleep disturbances, and cognitive impairment.MethodsThis study utilized data from the Health and Retirement Study, a longitudinal panel study among adults (2020). Participants (n = 2,639) completed questionnaires on housing, sleep disturbances, and cognition. Housing was measured by self‐reported ratings of their homes physical condition (1‐excellent to 5‐poor). Sleep disturbances were self‐reported as trouble falling asleep, trouble waking up during the night, and trouble with waking up too early and not being able fall asleep again, and each item was scored from 0 (rarely/never) to 2 (most of the time). Cognitive impairment was defined as a participant rating of fair or poor regarding their memory at the present time. Logistic regression models were fit to test associations between housing and sleep and cognitive impairment after adjustment for age, sex, and race.ResultsThe sample had a mean age of 66.2+10.6 years, and 60% were female, 21.4% Black, 64.6% White, and 11.4% other racial group. The prevalence of cognitive impairment and sleep disturbance was 28.7% and 42.8%, respectively. Individuals living in adverse housing conditions had 32% and 48% higher odds of sleep disturbances [Adjusted Odds Ratio (aOR) = 1.32, 95% confidence interval (1.21, 1.43)] and cognitive impairment [aOR = 1.48 (1.36, 1.62)], respectively. Sleep disturbances were associated with higher odds of cognitive impairment, OR = 2.04 (1.71, 2.44). After adjustment for sleep disturbances, the association between housing condition and cognitive impairment was slightly attenuated, aOR = 1.40 (1.28, 1.54).ConclusionsLiving in adverse housing conditions were associated with greater sleep disturbances and subjective cognitive impairment. Results suggest that sleep may explain a small portion of the association between housing conditions and cognitive impairment, but a formal test of mediation is needed. Housing and sleep may be points of intervention for reducing cognitive impairment.

Subjective cognitive impairment score associate with regional amyloid burden and brain atrophy in subjective cognitive decline subjects

AbstractBackgroundSubjective cognitive decline (SCD) is now regarded as the first preclinical stage of Alzheimer’s disease (AD) spectrum disorders. It is important to predict which patients would progress to dementia, and screening tools might be helpful. In this study, we aimed to investigate the possible correlations between AD biomarkers‐regional amyloid burden and volume changes‐and Korean Dementia Screening Questionnaire‐Cognition (KDSQ‐C) score in SCD.MethodThis study analyzed SCD data from prospective population cohort study from July 2018 to December 2020. Brain magnetic resonance imaging (MRI) volumetry, visual and standardized uptake value ratio (SUVR) analysis of 18F‐Florbetaben brain amyloid Positron Emission Tomography (PET) were performed. Demographics, physical data, social and physiological functions were also obtained.KDSQ‐C was administered to SCD subjects as part of the clinical evaluation at the 36 month follow‐up visit. KDSQ‐C included 15 questions that assess 3 dimensions: memory impairment (items 1‐5), other cognitive impairments including language impairments (items 6‐10), and the ability to perform complex tasks in daily life (items 11‐15).ResultPrevalence of subjective cognitive impairment (KDSQ‐C ≧6) among 86 subjects was 73.3%.. No significant difference was observed between groups in terms of demographic characteristics including age, sex and APOE Ɛ4 status and neuropsychological test. However, regional SUVR (amygdala, inferior temporal gyrus and precuneus) and global SUVR were significantly higher in subjectively cognitive impaired group(p<0.05). There were no brain volume differences between groups.For volumetry and KDSQ‐C correlation analysis, partial correlation analysis controlled for age, sex and APOE Ɛ4 status showed significant negative correlation between left entorhinal cortex, right hippocampal volume and KDSQ‐C (r = ‐0.230, p = 0.046; r = ‐0.226, p = 0.049). Similar association was also found between KDSQ‐C memory domain score and brain volume.ConclusionKDSQ‐C can be a useful tool for screening SCD patients at a higher risk with higher amyloid deposition and brain atrophy.This study was supported by a grant from the Ministry of Health and Welfare, HI18C0530

Clinical Manifestations.

Memory complaints are common in elderly and have various etiologies, including functional cognitive disorder (FCD). Diagnosis of FCD is supported by clinical evidence of incongruity with a neurodegenerative disorder and/or evidence of internal inconsistency - the ability to perform a task well at certain times, but with impaired ability at other times. The prevalence of features suggesting FCD in organic disorders is unclear. We assessed the presence of clinical features of internal inconsistency and other possible discriminators of FCD from organic causes in patients with mild cognitive impairment (MCI) and subjective cognitive impairment (SCI). Patients attending our tertiary memory clinic in a period of one year with SCI or MCI were included. Exclusion criteria were toxic or metabolic causes of cognitive decline, major psychiatric disorders, co-morbid neurological conditions that could affect cognition, and uncertainty of diagnosis of organic disorder or FCD. Medical records were reviewed for evidence of internal inconsistency and other suggested discriminators between functional and organic etiology. Demographic, cognitive and clinical data were compared between groups. We evaluated 39 patients with FCD and 57 with organic disorders. MCI was more common in patients with organic disorders. However, most patients with FCD also had MCI. Patients with FCD were younger and performed better on cognitive assessments, but with significant overlap between groups (Table 1). While patients with FCD more commonly attended the appointment alone and reported greater concern about their symptoms than their supporters, these features were unspecific (Table 2). Patients with FCD reported symptoms that could represent normal experiences and provided detailed descriptions of memory lapses more commonly. While less sensitive, memory perfectionism and symptoms occurring only in specific situations were highly specific for FCD. Differentiation between functional and organic cognitive disorders based on history and examination can be challenging. Features suggesting internal inconsistency and incongruity with neurodegeneration may also appear in organic causes of SCI and MCI. Their varying specificity and sensitivity for FCD need to be taken into account when considering the diagnosis. Improving the identification of FCD could in turn improve identification of patients with prodromal neurodegeneration.

A systematic review of the impact of amyloid PET scan disclosure on psychological and behavioral outcomes for persons with cognitive impairment and their caregivers

AbstractBackgroundAmyloid‐β PET scans are a potentially useful diagnostic tool, however there is limited understanding of the impact of amyloid disclosure on persons with cognitive impairment and their caregivers. This study aimed to systematically review the impact of amyloid scan disclosure on patient and caregiver psychological and behavioral outcomes.MethodWe searched Medline, Embase and PsychInfo to identify relevant articles. Studies of any design including persons with subjective cognitive impairment, MCI and dementia and their caregivers were included. Outcomes were limited to psychological and behavioral outcomes recorded following disclosure. All articles were screened for eligibility by two reviewers.ResultWe identified 9 papers from 6 studies. Depression, anxiety and test‐related distress were the most common psychological outcomes and recall and knowledge of the scan result were the most common behavioral outcomes. The psychological impact of amyloid disclosure varied depending on the scan recipient’s level of impairment and scan result. Higher test related distress was observed in persons with MCI and elevated amyloid and higher levels of anxiety were found in their caregivers. Most persons with cognitive impairment and their caregivers were able to recall the scan result. However, one study found that gains in knowledge regarding the scan recipients diagnosis following disclosure were comparable to receiving psychoeducation.ConclusionPsychological responses to amyloid PET scan disclosure depends on the recipient’s level of impairment and the scan result itself. Persons with MCI and a positive scan result, and their caregivers were at greater risk of distress or anxiety and may benefit from additional post‐diagnostic support. Participants were able to correctly recall their scan results and reported an increase in knowledge regarding their diagnosis. However, psychoeducation may be equally effective at enhancing patient and caregiver knowledge, at a lower cost.

Value of blood‐based biomarkers for differential diagnosis of Alzheimer’s disease: the ActiGliA cohort

AbstractBackgroundCerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers of Alzheimer’s disease (AD), ß‐amyloid (Aß) and tau, can identify early disease stages with high accuracy. However, this approach is not suitable for routine clinical care because of the high costs and invasiveness. Implementation of blood‐based biomarkers (BBBM) in the diagnostic process may facilitate the identification of persons with AD in the earliest stage possible and may reliably differentiate AD from healthy aging and other non‐AD dementias like corticobasal syndrome (CBS).MethodFrom the prospective ActiGliA study we included 27 participants with probable AD (including participants with mild cognitive impairment [n = 16] and AD‐related dementia [n = 11]), 17 age‐matched controls with subjective cognitive impairment, 9 participants with corticobasal syndrome and underlying Aß‐pathology (Aß[+]CBS), and 26 participants with Aß[‐]negative CBS. The diagnostic value of different BBBMs in differentiating amyloid‐positive from ‐negative cases was examined. All participants underwent a thorough diagnostic work‐up, including CSF and blood sampling, neuropsychological tests, amyloid‐PET, and magnetic resonance imaging. Blood biomarkers (Aß1‐40, Aβ1‐42, apolipoprotein E4 [ApoE4], glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL], and phosphorylated‐tau181 [pTau181]) were measured using Elecsys® plasma prototype immunoassays.ResultIn amyloid‐positive cases, plasma concentrations of Aβ1‐42/1‐40 ratio were decreased while ApoE, GFAP, and pTau181 levels were elevated. In the entire cohort, blood and CSF levels of both Aß1‐42/Aß1‐40 ratio and pTau181 were significantly positively correlated. ApoE4, GFAP, and particularly pTau181 levels showed a strong negative association with neuropsychological performance. A positive association between NfL levels and hippocampal atrophy was demonstrated. pTau181 levels revealed an are under the curve (AUC) of 0.885 in the discrimination between amyloid‐positive and ‐negative cases, plasma ApoE4 levels and Aß1‐42/Aß1‐40 ratio showed an AUC of 0.774 resp. 0.815. Regarding differentiation of AD from healthy aging and other dementias, elevated NfL levels were associated with a diagnosis of CBS and Aß[+]CBS, while elevated pTau181 and ApoE4 levels indicated a diagnosis of AD.ConclusionBBBMs may be useful in differentiating amyloid PET‐positive from amyloid PET‐negative cases and in differentiating AD from healthy aging and non‐Alzheimer dementias. These results must be validated in a larger cohort.

Yoga for prevention of cognitive decline in older women with cardiovascular risk factors and cognitive decline.

AbstractBackgroundYoga may produce positive effects on cognitive functions in older adults at risk for cognitive decline. In this study (NCT03503669), we investigated neural and peripheral biomarkers therapeutic response in older women with subjective cognitive decline (SCD) and cerebrovascular risk factors (CVRFs) following three months of yoga compared to memory enhancement training (MET).MethodWe conducted a randomized, controlled trial to assess the efficacy of Kundalini yoga (YOGA) and memory enhancement training (MET) on mood and cognitive functioning in a group of older women with CVRFs and SCD. RNA sequencing and cytokine/chemokine assays were analyzed as well as a multimodal MRI (Siemens 3T Prisma scanner).ResultA total of 79 patients (YOGA = 40; MET = 39) were randomized and 63 completed the 24‐week follow‐up (Mean age = 66.5 years and mean MMSE was 28.4). At 12‐weeks and 24‐weeks, both interventions demonstrated improvement in frequency of forgetting (MFQ‐Factor 1) (F(1, 76) = 0.2, p = 0.7). At 24‐weeks, YOGA participants demonstrated between‐ and within‐groups improvements in seriousness of forgetting/MFQ‐Factor 2 (effect size (95% confidence interval) = ‐0.73 (‐1.26, ‐0.19)). Compared to MET, at 12‐ and 24‐weeks follow‐up, YOGA uniquely modulated targets related to interferon signaling and innate and adaptive immunity. Compared to YOGA, MET participants displayed higher Eotaxin‐1 levels (F(2,67) = 3.94, p = 0.02). On sMRI‐Compared to KY + KK, MET showed reductions in GMV in left prefrontal, pre‐ and post‐central, supramarginal, superior temporal and pericalcarine cortices, right paracentral, postcentral, superior and inferior parietal cortices. Right hippocampal volume increased after yoga. rs‐fMRI analysis showed a left anterior hippocampal subregion assigned to the default mode network (DMN) with greater increases in connectivity with largely ventral visual stream regions with YOGA than with MET (p<.001), in associations with lower stress (p<.05).ConclusionAt 24‐weeks follow‐up, YOGA yielded a significant, large effect size improvement in subjective cognitive impairment, and a robust mediation of inflammatory‐immune pathways, including suppression of pro‐inflammatory molecules. YOGA also offered neuroprotective effects compared to MET. These results suggest clinical, neural and biological benefits to YOGA for SCD in post‐menopausal women at risk for AD.

Cognitive Health and Functional Abilities of Illiterate Older Peruvians

AbstractBackgroundThe demographic changes are clearly affecting developing countries like Peru. Is estimated that approximately 7% of the population in the capital city of Lima, Peru, lives with dementia but there is no knowledge of the cognitive health of illiterate older in urban and rural communities outside Lima, where 41.5% of older adults living in these communities are illiterate. On the other hand, Peru is home to tremendous social and geocultural diversity, which may mitigate the worrisome dementia risk. In this respect, it is interesting to note that many older Peruvians remain active preserved and prolonged functional independence in their respective communities for long periods of time. Additionally, in Peru, several brief cognitive tests have been validated in urban cohorts (mostly within Lima) with elementary level education, but, to our knowledge, no brief tests of cognition or functionality have been validated in illiterate Peruvians. These observations raise important research questions that the present pilot proposal seeks to begin investigating.MethodsWe are characterizing the cognitive health and functional abilities of rural and urban illiterate older adults living in two geoculturally‐distinct regions of Peru, the Andean and Amazonian regions. Within the Andes region, we are studying a cohort of illiterate older adults living in the urban area of Cuzco and another cohort from the rural area of Pomacanchis ‐ Cuzco; within the Amazon region, we will study a cohort of illiterate older adults living in the urban area of Iquitos and another cohort from the rural area of San Reyes. We are conducting a gold standard neurological, neuropsychological, and functional evaluations in all enrolled participants in each of the four cohorts and these will be used to arrive at a multidisciplinary consensus diagnosis of suspected normal aging, subjective cognitive impairment, mild neurocognitive disorder (or mild cognitive impairment), or major neurocognitive disorder (or dementia). We are correlating these diagnoses with results of brief cognitive tests and a brief functionality assessment, the MMSE, RUDAS, the BHA ‐ TabCAT, and the adapted version of PFAQ.Results In collection process ConclusionThis pilot project represents the initial steps towards addressing these hypotheses and will generate unique data.

Sleep disturbances, cortisol, and neuroimaging correlates among memory clinic patients

AbstractBackgroundSleep disturbances are increasingly acknowledged as a preclinical marker for Alzheimer’s disease (AD), however, the mechanisms underlying the association between sleep disturbances and dementia remain unclear. Sleep disturbances may affect AD through brain morphology changes and vascular damage, as sleep disturbances are known to be linked with altered grey‐ and white‐matter integrity. Moreover, sleep and brain changes may be linked with cortisol levels. Sleep disturbances have been proposed to parallel cortisol dysregulation, and older individuals with preclinical AD have altered awakening cortisol, a feature that is intensified among people also suffering from sleep disturbances.MethodThe study is based on 146 memory clinic patients from the Karolinska University Hospital memory clinic (Sweden). Participants are in the age range 47‐86 years and diagnosed with either subjective cognitive impairment or mild cognitive impairment. Self‐reported sleep disturbances are measured by the Karolinska Sleep Questionnaire. Brain imaging (MRI or CT) was used to semi‐quantify brain atrophy using four visual rating scales: Medial Temporal Atrophy, Global Cortical Atrophy, Koedam (posterior brain atrophy) and Fazekas (white‐matter lesions) scales. Lastly, saliva cortisol has been sampled 6 times daily to measure diurnal cortisol patterns.ResultOrdinal logistic regressions show significant associations between sleep disturbances and brain parameters. Insufficient sleep (OR = 1.30, p = 0.048) is associated with greater odds of white‐matter lesions, and apnea (OR = 1.26, p = 0.036) and snoring (OR = 1.38, p = 0.045) are associated with greater odds of posterior brain atrophy. Increased daytime sleepiness is associated with both reduced awakening cortisol (β = ‐0.03, p = 0.025) and a flattened cortisol curve (β = ‐0.04, p = 0.019). Apnea is associated with reduced awakening cortisol (β = ‐0.06, p = 0.013). However, cortisol was not found to significantly interact with sleep in predicting brain outcomes.ConclusionThese results show that various sleep disturbance parameters (short sleep duration, apnea, and snoring) are associated with neuroimaging correlates, while daytime sleepiness and apnea are associated with markers of dysregulated cortisol patterns. The results suggest that neuroimaging correlates and cortisol measures may clarify the mechanisms underlying the associations between sleep disturbance and cognitive impairment, and the combination of objective sleep measures and neuroimaging markers in future studies may further reveal the mechanisms.

Blood biomarkers of Alzheimer’s disease as predictors of eligibility for disease‐modifying treatment

AbstractBackgroundBlood biomarkers show promise in screening for Alzheimer’s disease (AD) brain pathology, but best predictors of eligibility for disease‐modifying treatment remain unclear. We have previously reported estimates for potential eligibility for anti‐amyloid treatment in a real‐life memory clinic setting (Rosenberg et al., Neurology 2022); the current study explored associations between AD blood biomarkers and treatment eligibility.MethodStudy population consisted of 224 patients from the Karolinska University Hospital Theme Aging Memory Clinic, with complete data (clinical, CSF, MRI, and plasma biomarkers Aβ40, Aβ42, NFL, GFAP, ptau181, ptau231). In total, 57% had subjective cognitive impairment, 21% mild cognitive impairment, and 22% dementia. Blood biomarkers were analysed using ultrasensitive Single molecule array (Simoa). Logistic regression models were used with zero‐skewness log‐transformed blood markers as predictors of treatment eligibility (defined based on the published use recommendations for anti‐amyloid treatment aducanumab). Areas under the curve (AUCs) were calculated for a pragmatic model including age, sex, and global cognition (MoCA) (base model), and for each model including blood biomarkers (alone and in combinations, with or without base model).ResultThirty‐two out of 224 patients (14%) were classified as potentially eligible for anti‐amyloid treatment. AUC for the base model was 0.65 (95% confidence interval 0.56–0.74). AUCs for models including only blood markers were 0.76 (0.69–0.83; Aβ42/40), 0.77 (0.70–0.84; NFL), 0.80 (0.73–0.88; GFAP), 0.81 (0.74–0.89; ptau181), 0.83 (0.76–0.90; ptau231), and 0.87 (0.82–0.93; all markers). AUC was 0.89 (0.83–0.94) for the full model (all data). In a scenario where the base model was combined with a single blood marker, highest AUCs were observed for models including ptau231 or GFAP (both 0.83, 0.75–0.90).ConclusionAll blood biomarkers, individually and combined, outperformed the commonly available clinical variables in predicting potential eligibility for disease‐modifying treatment. Ptau markers, especially ptau231, and GFAP seem most promising in this context.

Vitamin B12 deficiency presenting as subjective cognitive impairment

Vitamin B12 deficiency presenting as subjective cognitive impairment

Psychometric evaluation of the German version of the Mild Behavioural Impairment Checklist (MBI‐C)

AbstractBackgroundNeuropsychiatric symptoms (NPS) are common in pre‐dementia state and are associated with an increased risk of dementia. The concept of Mild Behavioral Impairment (MBI) addresses this circumstance. However, to date, instruments that measure MBI in a standardized method are lacking. Therefore, the Mild Behavioral Impairment Checklist (MBI‐C) was developed on the basis of the MBI diagnostic criteria. Our aim was to psychometrically evaluate the German version of the MBI‐C.MethodWe interviewed 86 dyads of individuals with either subjective cognitive impairment (SCD), mild cognitive impairment (MCI), or cognitively healthy individuals, paired each of them with a relative and test the reliability, validity and acceptance of the MBI‐C.ResultThe internal consistency of both MBI‐C versions were at a questionable to acceptable level (α = 0.64‐0.86) and the interrater reliability was good to excellent (patients: ICC = 0.94, CI [0.91–0.96]; informants: ICC = 0.86, CI [0.79–0.90]). Informant‐rated MBI‐C correlated strongly with the Neuropsychiatric Inventory (NPI) total score (r = 0.51; p ≤.001). All participants found the MBI‐C acceptable.ConclusionThe German MBI‐C is an instrument to assess MBI in healthy individuals, individuals with SCD, and those with MCI. It has acceptable psychometric properties. Further studies should address a larger sample of individuals in a pre‐dementia state to confirm the findings of our study. Moreover, the factor structure should be investigated.

Subjective cognitive impairment and biomarkers of Alzheimer’s disease

AbstractBackgroundSubjective cognitive impairment (SCI) is common in older adults. It may represent the earliest clinical manifestation of cognitive decline and Alzheimer’s disease (AD).Objectives1) to evaluate associations between SCI and cerebrospinal fluid (CSF) biomarkers of AD; 2) to identify specific single questions or question combinations that are related to the presence of cerebral AD pathology; 3) to evaluate whether using SCI related scores or specific questions combined with other clinical features and biomarkers may improve prediction of cognitive decline.MethodWe conducted a longitudinal study in 164 non‐demented subjects participating on a biomarker study in a memory clinic setting, aged 53 to 88 years, with CDR scores of 0 (N = 84) and 0.5 (N = 80). SCI was assessed using the Cognitive Complaint Interview (CCI, Thomas‐Antérion et al., 2006), a validated 10 items questionnaire. Accordingly, SCI is defined as present when the subject answers “yes” to 3 or more items; and/or to item 5, and/or to items A, 4, 5, 7, 8. All participants underwent comprehensive neuropsychological evaluations and CSF biomarkers analysis. “Amyloid positivity" and “AD pathology” were defined according to the CSF Aβ1‐42 levels and pTau181/Aβ1‐42 ratio, respectively. Logistic regressions were used to address the associations of interest.ResultsParticipants with SCI had significantly lower Aβ1‐42 and higher Tau and pTau181 levels compared to those without SCI. SCI was associated with amyloid positivity while CCI total score and the question A (reporting changes in memory) were associated with both amyloid positivity and AD pathology in the whole cohort. When performing analysis separately in the CDR = 0 and CDR = 0.5 subgroups the associations remained significant in the CDR = 0.5 group. Only question 6 (difficulties in finding words) was associated with AD pathology in the CDR = 0 group. Results on the prediction of cognitive decline at follow‐up visits will be presented at the conference.ConclusionIn dementia‐free subjects from this memory clinic cohort SCI‐related scores and single questions indicate amyloid positivity and the presence of AD pathology depending on the absence/presence of mild cognitive impairment. Further studies are needed to evaluate the diagnostic and prognostic utility of cognitive complains in memory clinic patients.

Lower Physical Activity Is Associated With Objective But Not Subjective Cognitive Impairment In Older Adults Without Dementia

AbstractBackgroundPhysical activity has been associated with better performance on cognitive assessments for older adults in both observational and interventional studies. Older adults who exercise the 150 minutes a week recommended by the Physical Activity Guidelines for Americans were also less likely to report subjective cognitive decline on the Behavioral Risk Factor Surveillance System than those with lower levels of physical activity. Potential explanations for a cognitive benefit from exercise include reduction of vascular risk factors, preservation of brain mass and neuronal structural integrity, and promotion of psychological health and self‐efficacy.MethodCross‐sectional data on exercise habits, self‐reported memory problems, and cognition were collected for 137 older adults without dementia as part of a larger observational study. Participants were categorized as meeting (3 or more hours a week of physical activity) or not meeting (< 3 hours) physical activity recommendations. We used multivariable logistic regression to evaluate the association between exercise and self‐reported memory problem, and linear regression for association between exercise and total score on the Montreal Cognitive Assessment (MoCA) after adjusting for potential confounders including age, sex, level of education, cognitive status (CDR global score of 0 vs 0.5), and Geriatric Depression Scale score.ResultData on baseline exercise was available for 103 cognitively normal older adults and 34 with mild cognitive impairment (MCI). Mean participant age was 66.6 years and 58.4% were female. 48 participants (35%) reported exercising at least 3 hours per week. Participants with at least 3 hours a week of physical activity had significantly higher scores on the MoCA compared with those with less than 3 hours a week (B = 1.22, p = 0.040) after adjusting for age, sex, level of education, cognitive status, and depressive symptoms. There was no association between physical activity and participant‐reported memory symptoms using the same covariates (B = ‐0.50, p = 0.223).ConclusionWeekly physical activity levels consistent with current guidelines were associated with better performance on a cognitive assessment in older adults without dementia. Physical activity was not associated with presence or absence of a self‐reported memory problem in this sample.

Identifying and differentiating dementias with EEG fractal dimension distributions

AbstractBackgroundAlzheimer’s disease dementia (AD‐dementia) and non‐AD dementia have both been associated with decreases in fractal dimension and spectral slowing in electroencephalography (EEG). Here, we describe a set of EEG features ‐ Fractal Dimension Distributions (FDD) ‐ which quantifies the stability of fractal dimensions over time within specific frequency bands. We compare the performance of models trained using this FDD feature to models using age, spectral power, or overall fractal dimension.MethodWe analyzed resting‐state data from older adults (age M = 71, range = 55‐86) with subjective cognitive impairment (SCI; N = 97, 59 female) or dementia (N = 51, 32 female), including 38 with AD (N = 33). We calculated the Fractal Dimension Distributions (FDD) by first computing the Higuchi fractal dimension within moving windows, then summarizing the distribution of these fractal values using the mean and standard deviation within standard frequency bands. Finally, we trained regularized logistic regression models to classify participants as having SCI or dementia, and as having SCI or AD‐dementia. We compared the performance of models using FDD or standard measures of fractal dimension. Models were evaluated using balanced accuracy, weighted sensitivity, and weighted specificity calculated using 5‐fold cross‐validation.ResultFor SCI vs Dementia, the model using FDD (accuracy = 74%, sensitivity = 67%, specificity = 81%, p < .001) had higher accuracy, sensitivity, and specificity than models trained on age, standard measures of fractal dimension, or spectral power. Similarly, the model trained to predict SCI vs AD‐Dementia was most accurate when using FDD (accuracy = 73%, sensitivity = 59%, specificity = 97%, p < .005). The features useful for discriminating SCI from Dementia partially overlapped with the features useful for discriminating SCI from AD‐Dementia.ConclusionOur novel feature, FDD, outperforms standard measures of fractal dimensions or spectral band power at discriminating between SCI and dementia. Moreover, FDD may help to distinguish between AD and other varieties of dementia.

Associations of white matter hyperintensities with cerebrovascular architecture in Alzheimer’s disease and related dementias

AbstractBackgroundMRI‐detected white matter hyperintensities (WMHs), a marker of cerebrovascular‐pathology, are common in Alzheimer’s disease (AD) and related dementias (ADRDs). In stroke, WMH‐volume was found to correlate most with stroke risk‐factors in the anterior cerebral arterial‐territory. Since the relationship between WMHs and arterial‐territories remains unexplored in the ADRDs, we systematically investigated WMHs’ spatial distribution (1) in 8 ADRDs relative to cognitively unimpaired (CU), and (2) across arterial‐territories per ADRD.MethodsThe extensive CCNA‐COMPASS‐ND cohort (N = 927) allowed us to investigate 9 clinical categories: CU, subjective (SCI) and mild (MCI) cognitive impairment, vascular MCI (V‐MCI), AD, vascular AD (V‐AD), Lewy‐body dementia (LBD), fronto‐temporal dementia (FTD), and Parkinson’s disease (PD) (Fig.1A). FLAIR and T1w MRI‐scans were used to segment WMHs (Dadar et al.,2017). Following registration to standard space, an arterial‐territory atlas (Schirmer et al.,2019) was used to calculate WMH‐volumes in 10 regions (Fig.1B). Statistical analyses were run on whole‐brain‐WMH‐volume and regional‐WMH‐ratios (region‐size‐normalized‐WMH‐volume/whole‐brain‐WMH‐volume). Data‐analyses used a series of linear models accounting for clinical category, age, and sex – followed by pairwise group‐comparisons corrected for multiple comparisons.Results 1) Relative to CU: Whole‐brain‐WMH‐volumes were higher for V‐MCI, V‐AD, and FTD. WMH‐ratios were higher in MCA and LMCA for 2 ADRDs (SCI;V‐MCI) and lower in PCA, LPCA, and RPCA for SCI. WMH‐ratios were higher in ACA or LACA and lower in PCA, LPCA, or RPCA for 4 ADRDs (V‐MCI;V‐AD;FTD;PD) (Fig.1C). Sex‐analyses: Men’s WMH‐volumes were higher in whole‐brain (CU;V‐MCI;FTD), while their WMH‐ratios were higherin LMCA (CU), but lower in ACA (SCI;MCI), LACA (MCI), and RACA (SCI). 2) MCA contained higher WMH‐ratios than ACA and PCA in all clinical categories. Relative to PCA, ACA’s WMH‐ratio was higher in 2 ADRDs (V‐MCI;V‐AD) and lower in 4 (CU;MCI;AD;PD). Pairwise‐group comparisons between all left/right arterial‐territories demonstrated consistent results (Fig.2). Asymmetry‐analyses: The right arterial side had higher WMH‐ratios in ACA (CU;V‐MCI), MCA (CU;SCI;MCI;V‐MCI;AD;V‐AD;PD), and PCA (MCI;AD).ConclusionWe identified arterial‐territories of increased susceptibility to WMH‐formation per ADRD. The two most prevalent ADRDs (AD;V‐AD) were found to accumulate WMHs in a territory‐specific manner – higher WMH‐ratios in ACA for V‐AD and PCA for AD. Overall, the arterial‐territory‐specific WMH‐signatures identified may improve ADRD‐diagnosis accuracy.