Introduction:Post-acute COVID-19 syndrome (PACS) has been widely associated with cognitive symptoms, however, the nature and severity of effects on cognitive function have been difficult to establish amid other aspects of PACS symptomatology. The current study used a regression modeling approach to parse unique and combined contributions of neuropsychological test performance, psychiatric symptoms, and inflammatory cytokine levels in predicting cognitive symptom severity, as measured by questionnaire responses from patient and observer perspectives. Methods:Forty-one patients presenting to a university medical center neurology clinic with cognitive complaints ≥ 4 months after COVID-19 symptom onset were included in the analysis. Results:Although pre-morbid cognitive status was estimated to be at or above-average across participants, nearly 50% performed below expectation on three or more neuropsychological tests. Subjective Cognitive Decline Questionnaire (SCD-Q) ratings were clinically elevated, both from patient (MyCog) and observer (TheirCog) perspectives, yet bivariate relationships with neuropsychological and other measures of PACS symptomatology were non-significant. When combined in regression models, 36% of variance in MyCog score was explained by measures of anxiety, premorbid intelligence, and current neuropsychological test performance. TheirCog scores were explained by a unique set of neuropsychological tests, accounting for 33% of variance cumulatively. Measures of depression, fatigue, and inflammatory cytokines concentrations did not enter either model. Discussion:Taken together, cognitive sequelae of PACS appear to be rooted in changes in brain function that are detectable by objective neuropsychological testing. Although comorbidities associated with PACS can contribute to the experience of cognitive symptoms, we find cognitive symptoms, whether self-reported or observed, to be more directly associated with neuropsychological test performance than ongoing fatigue, psychiatric symptoms, or inflammatory processes.

Practice effects are a well-known cognitive phenomenon that is reduced in patients with Alzheimer’s disease (AD). We aimed to investigate whether cognitively unimpaired (CU) individuals within the Alzheimer’s continuum (i.e., positive amyloid-β biomarker) display decreased practice effects on serial neuropsychological testing. We included 310 CU from four Spanish research centers, classified into controls (n = 250) or Aβ+ (n = 60). In the main cohort (Cohort A; n = 209), participants underwent neuropsychological assessment at baseline and annually during a 2-year follow-up (FU 1 and FU 2 ). A “long-term cohort” (Cohort B; n = 101) was employed to assess practice effects over longer time periods (i.e., two follow-up sessions at years 3 and 6 from baseline). Practice effects were defined as simple discrepancy scores (SDS) by subtracting Z-scores at FU 2 from Z-scores at baseline for each neuropsychological variable, and linear mixed effects models (LME) were run to assess the temporal evolution of practice effects according to the two groups. There were no cross-sectional differences between the control and Aβ+ groups in none of the neuropsychological scores at baseline (Fig. 1). The Aβ+ group displayed lower practice effects than the controls in terms of SDS in several neuropsychological outcomes (Fig. 2). In Cohort A, LME showed negative slopes by the Aβ+ group in verbal memory measures such as the free learning score (β = -0.37, SD = 0.12, p = 0.0034), delayed free recall (β = -0.43, SD = 0.15, p = 0.0047) and delayed total recall (β = -0.46, SD = 0.17, p = 0.0069) from the Free and Cued Selective Reminding Test; as well as in language tasks (Boston Naming Test; β = -0.26, SD = 0.087, p = 0.0025) and executive function measures (Trail Making Test; β = -0.33, SD = 0.12, p = 0.0094) (Fig. 3A). In Cohort B, similar findings were observed in visual memory measures, such as the Rey-Osterrieth Complex Figure immediate (β = -0.80, SD = 0.35, p = 0.024) and delayed (β = -1.25, SD = 0.34, p = 0.00038) recall (Fig. 3B). Individuals with normal cognition who are in the Alzheimer’s continuum show decreased practice effects over serial neuropsychological testing. Our findings suggest the reduction of practice effects, particularly in memory measures, as an indicator of subtle cognitive decline in the earliest phase of the Alzheimer’s continuum and could be particularly relevant for the design and interpretation of primary prevention trials on disease-modifying therapies.

INTRODUCTION:Specific features of subjective cognitive decline (SCD-plus) have been proposed to indicate an increased risk of preclinical Alzheimer's disease (AD). However, few studies have examined how these features relate to AD biomarkers in cognitively unimpaired (CU) older adults. METHODS:Meta-analyses were performed using cross-sectional data from nine cohorts (n = 7219, mean age (SD): 71.17 (5.9), 56.5% female) to determine associations of SCD-plus features with positron emission tomography (PET)- or cerebrospinal fluid (CSF)-derived amyloid beta (Aβ) and tau biomarkers. RESULTS:Participants with preclinical AD (community-based only) were more likely to fulfill SCD-plus features. The presence of self-reported memory decline, associated concern/worry, and a higher number of fulfilled features were all associated with high Aβ levels. Only the latter was associated with abnormal tau. DISCUSSION:Simultaneous endorsement of multiple SCD-plus features is a robust indicator of abnormal AD biomarkers in CU older adults, whereas isolated SCD features seem only sensitive to elevated Aβ, supporting their value as early behavioral markers of preclinical AD. HIGHLIGHTS:About two-tenths of our sample had abnormal amyloid beta (Aβ) levels with evidence of subjective cognitive decline (SCD). Preclinical AD subsamples (community-based) had a higher percentage of participants meeting SCD-plus features. Self-reported memory decline and concern/worry were the sole features associated with high Aβ, but not tau, burden. A higher number of fulfilled SCD-plus features are linked to high Aβ and tau burden. Use of multiple SCD-plus features may help identify early stages of biological AD.

ImportanceDepressive symptoms are associated with cognitive decline in older individuals. Uncertainty about underlying mechanisms hampers diagnostic and therapeutic efforts. This large-scale study aimed to elucidate the association between depressive symptoms and amyloid pathology.ObjectiveTo examine the association between depressive symptoms and amyloid pathology and its dependency on age, sex, education, and APOE genotype in older individuals without dementia.Design, Setting, and ParticipantsCross-sectional analyses were performed using data from the Amyloid Biomarker Study data pooling initiative. Data from 49 research, population-based, and memory clinic studies were pooled and harmonized. The Amyloid Biomarker Study has been collecting data since 2012 and data collection is ongoing. At the time of analysis, 95 centers were included in the Amyloid Biomarker Study. The study included 9746 individuals with normal cognition (NC) and 3023 participants with mild cognitive impairment (MCI) aged between 34 and 100 years for whom data on amyloid biomarkers, presence of depressive symptoms, and age were available. Data were analyzed from December 2022 to February 2024.Main Outcomes and MeasuresAmyloid-β1-42 levels in cerebrospinal fluid or amyloid positron emission tomography scans were used to determine presence or absence of amyloid pathology. Presence of depressive symptoms was determined on the basis of validated depression rating scale scores, evidence of a current clinical diagnosis of depression, or self-reported depressive symptoms.ResultsIn individuals with NC (mean [SD] age, 68.6 [8.9] years; 5664 [58.2%] female; 3002 [34.0%] APOE ε4 carriers; 937 [9.6%] had depressive symptoms; 2648 [27.2%] had amyloid pathology), the presence of depressive symptoms was not associated with amyloid pathology (odds ratio [OR], 1.13; 95% CI, 0.90-1.40; P = .29). In individuals with MCI (mean [SD] age, 70.2 [8.7] years; 1481 [49.0%] female; 1046 [44.8%] APOE ε4 carriers; 824 [27.3%] had depressive symptoms; 1668 [55.8%] had amyloid pathology), the presence of depressive symptoms was associated with a lower likelihood of amyloid pathology (OR, 0.73; 95% CI 0.61-0.89; P = .001). When considering subgroup effects, in individuals with NC, the presence of depressive symptoms was associated with a higher frequency of amyloid pathology in APOE ε4 noncarriers (mean difference, 5.0%; 95% CI 1.0-9.0; P = .02) but not in APOE ε4 carriers. This was not the case in individuals with MCI.Conclusions and RelevanceDepressive symptoms were not consistently associated with a higher frequency of amyloid pathology in participants with NC and were associated with a lower likelihood of amyloid pathology in participants with MCI. These findings were not influenced by age, sex, or education level. Mechanisms other than amyloid accumulation may commonly underlie depressive symptoms in late life.

In cognitively unimpaired (CU) older adults, the presence of a subjective cognitive decline (SCD) combined with evidence of abnormal b-amyloid (Ab) is proposed as stage 2 of Alzheimer’s disease (AD) by the NIA-AA framework (Jack et al., 2018). However, the associations found between SCD and preclinical AD are inconsistent across studies, highlighting the importance of better understanding which specific SCD features are associated with either Ab or tau burden. The present study includes cross-sectional data from 9 independent cohorts with a total of 7217 CU older adults (57% female), aged 69.34 (1.20) years, recruited from general and memory-clinic populations. Ab and tau biomarkers were measured by positron emission tomography (PET) or cerebrospinal fluid (CSF). Using established cut-offs, 28% of participants were Aβ+, and 12% were Aβ+T+ (approximately one-third of the sample had available tau data). We examined four SCD- plus criteria as well as the mean number of SCD criteria met (i.e., mean SCD-severity) in relation to both biomarker status and levels in logistic/linear regressions adjusted for age and sex for each cohort. Summary statistics were extracted for meta-analyses. The overall frequency of stage 2 AD varied from 7-16% [4-26%] according to each SCD- plus criterion endorsement. Only 1-5% [0-8%] of participants meeting the SCD- plus criteria also had both high Aβ and tau burden (Fig.1) . The presence of self-reported memory decline (SMD), an associated concern/worry, and a higher mean SCD-severity were each associated with high Ab (status and continuous). Only the latter was associated with high tau status (Fig.2) . Onset of SCD within the last 5 years, and feeling of worse performance than same-age peers, were not associated with AD biomarkers at a Bonferroni-corrected threshold. Our results suggest that widespread endorsement of multiple SCD features is more powerful than a single criterion alone in identifying both Aβ and tau in CU older adults. We found that the isolated SCD criterion was particularly sensitive to elevated Aβ, even after adjustment for tau, supporting the power of SCD as a very early behavioral marker of preclinical AD.

INTRODUCTION:We previously applied generalized additive models for location, scale, and shape to derive amyloid β-negative next-generation norms (NGN) for a comprehensive neuropsychological battery. Here, we evaluated the accuracy of NGN in detecting cognitive impairment compared to traditional norms (TN). METHODS:This multicenter study included N = 2405 participants classified as cognitively normal (CN, n = 987) or with mild cognitive impairment (MCI, n = 1418) using conventional criteria. All participants underwent neuropsychological testing and cerebrospinal fluid Alzheimer's disease (AD) biomarker assessment. We used actuarial neuropsychological criteria to reclassify all participants using TN and NGN. Diagnostic groups were compared on cognitive performance, AD biomarker positivity, and longitudinal cognitive trajectories. RESULTS:Nineteen percent of TN-classified CN participants were diagnosed with MCI by NGN, whereas 3% of TN-classified MCI were identified as CN by NGN. NGN demonstrated stronger associations with neuropsychological performance, AD biomarkers, and progression than TN. DISCUSSION:NGN enhance the detection of objective cognitive impairment, with direct implications for clinical practice and research. Highlights:Next-generation norms (NGN) reclassify one of every five cases from cognitively normal (CN) to mild cognitive impairment (MCI).This group shows poor cognitive performance and a high prevalence of amyloid β positivity.NGN-based diagnosis of MCI predicts cognitive progression on follow-up.Results indicate that NGN improve the detection of objective cognitive impairment.NGN can inform biomarker use, therapy indication, and clinical trial design.

Neuropsychological performance guides diagnostic and therapeutic decision-making on Alzheimer’s disease (AD) and related disorders. Despite broad recognition that amyloid-beta (Aβ) impacts cognition during preclinical AD, the added value of Aβ-negative norms remains uncertain. Furthermore, normative modeling is constrained by limitations inherent to traditional methods. Here, we derived next-generation norms (NGN) for a comprehensive neuropsychological battery and compared their utility with that of traditional norms (TN). This multicenter study included 2405 non-demented participants conventionally identified as cognitively normal (CN, n = 987) or with mild cognitive impairment (MCI, n = 1418) ( Table 1 ). All participants had extensive neuropsychological data and CSF AD biomarkers at baseline. Based on the performance of 774 Aβ-negative CN individuals, we derived NGN using generalized additive models for location, scale, and shape (GAMLSS). First, we compared the accuracy of NGN and TN to discriminate Aβ-positive from Aβ-negative MCI participants. Next, we actuarially reclassified all participants as CN or MCI according to both TN and NGN, and we examined the concordance of these classifications with AD biomarkers. For a subset of participants with clinical follow-up (n = 1318), linear mixed-effects modeling was used to capture the longitudinal change in Clinical Dementia Rating Scale-Sum of Boxes. The Akaike Information Criteria (AIC) was employed to select the best model. Age-, education-, and sex-adjusted percentiles were obtained for 14 neuropsychological measures across main cognitive domains (memory, language, attention, executive functioning, and visuospatial skills) ( Table 2 ). NGN outperformed TN at detecting prodromal AD for verbal memory measures, with all but one of the differences reaching statistical significance (p<0.05). Most participants were actuarially reclassified as either CN (43%) or MCI (52%) based on both TN and NGN. Among conflicting diagnoses (5%), the MCI/CN group (3%) -individuals diagnosed with MCI according to TN but considered CN as per NGN- was analogous to the CN/CN group, while the CN/MCI (2%) paralleled the MCI/MCI group in their rates of Aβ-positivity ( Figure 1 ). Cognitive status based on NGN better predicted clinical progression than TN (AIC = 5195.5 vs 5206.1, respectively). NGN incorporating Aβ status and GAMLSS yield stronger associations with biomarkers and disease progression than TN. This has direct implications for clinical practice and research.

INTRODUCTION:Recent research has suggested increased sensitivity of Alzheimer's disease (AD)-negative neuropsychological norms; concurrently, generalized additive models for location, scale, and shape (GAMLSS) have emerged as a promising alternative to traditional norming approaches. Here, we developed amyloid β-negative (Aβ-) next-generation norms (NGN) for a comprehensive neuropsychological battery using GAMLSS. METHODS:We included N = 987 cognitively normal (CN) individuals from a Spanish multicenter study with extensive neuropsychological data and cerebrospinal fluid AD biomarker assessment. NGN were developed using GAMLSS based on the performance of n = 774 Aβ- CN individuals aged 30-90 years. RESULTS:Age-, education-, and sex-adjusted z-scores were obtained for 14 measures covering the main cognitive domains (memory, language, attention/executive, and visuospatial functions). A user-friendly calculator for the z-scores was made available in an open-access ShinyApp to facilitate their application. DISCUSSION:NGN may improve the detection of objective cognitive impairment in clinical and research settings. Highlights:Brain amyloid β (Aβ) is associated with poorer performance in cognitively normal individuals.We provide GAMLSS-based Aβ-negative norms for 14 neuropsychological measures.Age, education, and often sex significantly influence cognitive performance.An online calculator for the demographically adjusted z-scores is freely available.

INTRODUCTION:We aimed to determine whether cognitively unimpaired (CU) amyloid- beta-positive (Aβ+) individuals display decreased practice effects on serial neuropsychological testing. METHODS:We included 209 CU participants from three research centers, 157 Aβ- controls and 52 Aβ+ individuals. Participants underwent neuropsychological assessment at baseline and annually during a 2-year follow-up. We used linear mixed-effects models to analyze cognitive change over time between the two groups, including time from baseline, amyloid status, their interaction, age, sex, and years of education as fixed effects and the intercept and time as random effects. RESULTS:The Aβ+ group showed reduced practice effects in verbal learning (β = -1.14, SE = 0.40, p = 0.0046) and memory function (β = -0.56, SE = 0.19, p = 0.0035), as well as in language tasks (β = -0.59, SE = 0.19, p = 0.0027). DISCUSSION:Individuals with normal cognition who are in the Alzheimer's continuum show decreased practice effects over annual neuropsychological testing. Our findings could have implications for the design and interpretation of primary prevention trials. HIGHLIGHTS:This was a multicenter study on practice effects in asymptomatic Aβ+ individuals. We used LME models to analyze cognitive trajectories across multiple domains. Practice-effects reductions might be an indicator of subtle cognitive decline. Implications on clinical and research settings within the AD field are discussed.

BackgroundThe association between lifestyle factors and Alzheimer's disease (AD) pathophysiology remains incompletely understood.ObjectiveThe aim of this study was to assess the association of alcohol consumption, smoking behavior, sleep quality and physical, cognitive, and social activity with cerebral amyloid pathology.MethodsFor this cross-sectional study, we selected participants from the Amyloid Biomarker Study data pooling initiative. We used generalized estimating equations to assess associations of dichotomized lifestyle measures with amyloid pathology.ResultsWe included 9171 participants with normal cognition (NC) and 2555 participants with mild cognitive impairment (MCI) from the Amyloid Biomarker Study. Of participants with NC, 58% were women, 34% were APOE ε4 carrier, and 27% had amyloid pathology. Of participants with MCI, 48% were women, 47% were APOE ε4 carrier, and 57% had amyloid pathology. In NC, cognitively active participants were less likely to have amyloid pathology (OR = 0.77, 95%CI 0.66-0.89, p < 0.001). In MCI, participants who had ever smoked or had sleep problems were less likely to have amyloid pathology (OR = 0.85, 95%CI 0.73-0.99, p = 0.029; OR = 0.62, 95%CI 0.45-0.86, p = 0.004).ConclusionsIn NC, cognitive activity was associated with a lower frequency of amyloid pathology. In MCI, favorable lifestyle behaviors were not associated with a lower frequency of amyloid pathology. The results of the current study contribute to the broader evidence base on lifestyle and AD by further characterizing the role of lifestyle behaviors in AD pathology across different clinical stages.

BACKGROUND:Anti-leucine-rich glioma-inactivated protein 1 (LGI1) encephalitis is an autoimmune disorder that can be treated with immunotherapy, but the symptoms that remain after treatment have not been well described. We aimed to characterise the clinical features of patients with anti-LGI1 encephalitis for 1 year starting within the first year after initial immunotherapy. METHODS:For this prospective cohort study, we recruited patients with anti-LGI1 encephalitis as soon as possible after they had received conventional immunotherapy for initial symptoms; patients were recruited from 21 hospitals in Spain. Patients were excluded if they had an interval of more than 1 year since initial immunotherapy, had pre-existing neurodegenerative or psychiatric disorders, or were unable to travel to Hospital Clínic de Barcelona (Barcelona, Spain). Patients visited Hospital Clínic de Barcelona on three occasions-the first at study entry (visit 1), the second 6 months later (visit 2), and the third 12 months after the initial visit (visit 3). They underwent neuropsychiatric and videopolysomnography assessments at each visit. Healthy participants who were matched for age and sex and recruited from Hospital Clínic de Barcelona underwent the same investigations at study entry and at 12 months. Cross-sectional comparisons of clinical features between groups were done with conditional logistic regression, and binary logistic regression was used to assess associations between cognitive outcomes at 12 months and clinical features before initial immunotherapy and at study entry. FINDINGS:Between May 1, 2019, and Sept 30, 2022, 42 participants agreed to be included in this study. 24 (57%) participants had anti-LGI1 encephalitis (mean age 63 years [SD 12]; 13 [54%] were female and 11 [46%] were male) and 18 (43%) were healthy individuals (mean age 62 years [10]; 11 [61%] were female and seven [39%] were male). At visit 1 (median 88 days [IQR 67-155] from initiation of immunotherapy), all 24 patients had one or more symptoms; 20 (83%) patients had cognitive deficits, 20 (83%) had psychiatric symptoms, 14 (58%) had insomnia, 12 (50%) had rapid eye movement (REM)-sleep behaviour disorder, nine (38%) had faciobrachial dystonic seizures, and seven (29%) had focal onset seizures. Faciobrachial dystonic seizures were unnoticed in four (17%) of 24 patients and focal onset seizures were unnoticed in five (21%) patients. At visit 1, videopolysomnography showed that 19 (79%) patients, but no healthy participants, had disrupted sleep structure (p=0·013); 15 (63%) patients and four (22%) healthy participants had excessive fragmentary myoclonus (p=0·039), and nine (38%) patients, but no healthy participants, had myokymic discharges (p=0·0051). These clinical and videopolysomnographic features led to additional immunotherapy in 15 (63%) of 24 patients, which resulted in improvement of these features in all 15 individuals. However, at visit 3, 13 (65%) of 20 patients continued to have cognitive deficits. Persistent cognitive deficits at visit 3 were associated with no use of rituximab before visit 1 (odds ratio [OR] 4·0, 95% CI 1·5-10·7; p=0·0015), REM sleep without atonia at visit 1 (2·2, 1·2-4·2; p=0·043), and presence of LGI1 antibodies in serum at visit 1 (11·0, 1·1-106·4; p=0·038). INTERPRETATION:Unsuspected but ongoing clinical and videopolysomnography alterations are common in patients with anti-LGI1 encephalitis during the first year or more after initial immunotherapy. Recognising these alterations is important as they are treatable, can be used as outcome measures in clinical trials, and might influence cognitive outcome. FUNDING:Fundació La Caixa.

AbstractWe aimed to characterize the cognitive profile of post-acute COVID-19 syndrome (PACS) patients with cognitive complaints, exploring the influence of biological and psychological factors. Participants with confirmed SARS-CoV-2 infection and cognitive complaints ≥ 8 weeks post-acute phase were included. A comprehensive neuropsychological battery (NPS) and health questionnaires were administered at inclusion and at 1, 3 and 6 months. Blood samples were collected at each visit, MRI scan at baseline and at 6 months, and, optionally, cerebrospinal fluid. Cognitive features were analyzed in relation to clinical, neuroimaging, and biochemical markers at inclusion and follow-up. Forty-nine participants, with a mean time from symptom onset of 10.4 months, showed attention-executive function (69%) and verbal memory (39%) impairment. Apathy (64%), moderate-severe anxiety (57%), and severe fatigue (35%) were prevalent. Visual memory (8%) correlated with total gray matter (GM) and subcortical GM volume. Neuronal damage and inflammation markers were within normal limits. Over time, cognitive test scores, depression, apathy, anxiety scores, MRI indexes, and fluid biomarkers remained stable, although fewer participants (50% vs. 75.5%; p = 0.012) exhibited abnormal cognitive evaluations at follow-up. Altered attention/executive and verbal memory, common in PACS, persisted in most subjects without association with structural abnormalities, elevated cytokines, or neuronal damage markers.

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T‐T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2‐year follow‐up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross‐sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross‐sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross‐sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross‐sectional and longitudinal data.

OBJECTIVE:Self-perceived cognitive functioning, considered highly relevant in the context of aging and dementia, is assessed in numerous ways-hindering the comparison of findings across studies and settings. Therefore, the present study aimed to link item-level self-report questionnaire data from international aging studies. METHOD:We harmonized secondary data from 24 studies and 40 different questionnaires with item response theory (IRT) techniques using a graded response model with a Bayesian estimator. We compared item information curves to identify items with high measurement precision at different levels of the self-perceived cognitive functioning latent trait. Data from 53,030 neuropsychologically intact older adults were included, from 13 English language and 11 non-English (or mixed) language studies. RESULTS:We successfully linked all questionnaires and demonstrated that a single-factor structure was reasonable for the latent trait. Items that made the greatest contribution to measurement precision (i.e., "top items") assessed general and specific memory problems and aspects of executive functioning, attention, language, calculation, and visuospatial skills. These top items originated from distinct questionnaires and varied in format, range, time frames, response options, and whether they captured ability and/or change. CONCLUSIONS:This was the first study to calibrate self-perceived cognitive functioning data of geographically diverse older adults. The resulting item scores are on the same metric, facilitating joint or pooled analyses across international studies. Results may lead to the development of new self-perceived cognitive functioning questionnaires guided by psychometric properties, content, and other important features of items in our item bank. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

OBJECTIVE Subtle decline in memory is thought to arise in the preclinical phase of Alzheimer's disease (AD). However, detecting these initial cognitive difficulties cross-sectionally has been challenging, and the exact nature of the decline is still debated. Accelerated long-term forgetting (ALF) has been recently suggested as one of the earliest and most sensitive indicators of memory dysfunction in subjects at risk of developing AD. The objective of this study was to design and validate the 1-week memory battery (1WMB) for assessing episodic memory and ALF in cognitively unimpaired individuals. METHOD The 1WMB is unique in that it assesses multimodal memory and measures recall at both short delay (20 min) and at long term (1 week). Forty-five cognitively unimpaired subjects were assessed with 1WMB and standardized neuropsychological tests. Subjective cognitive decline (SCD), levels of anxiety and depression, and cognitive reserve were also measured. RESULTS The tests of 1WMB showed a high internal consistency, and concurrent validity was observed with standard tests of episodic memory and executive functions. The analysis revealed a greater loss of information at 1 week compared to short-term forgetting (20 min). Performance in the 1WMB was affected by age and educational level, but was not associated with levels of anxiety and depression. Unlike standard tests, performance in the 1WMB correlated with measures of SCD. CONCLUSION Our findings indicate that the 1WMB has good psychometric properties, and future studies are needed to explore its potential usefulness to assess cognitively unimpaired subjects at increased risk of developing AD. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Despite previous studies establishing cognitive impairment as a major complaint in post-acute COVID-19 syndrome (PACS), a deeper understanding of the neuropsychological features and underlying causes is needed. We aimed to characterize the cognitive profile of patients affected with cognitive PACS and the influence of biological and psychological factors. We performed a prospective single-center study. We included participants with confirmed SARS-CoV-2 infection and long-term symptoms ≥ 8 weeks after onset who were referred to our unit because of cognitive complaints. All participants completed a comprehensive neuropsychological battery (NPS) and questionnaires assessing depression (Beck Depression Inventory), anxiety (Beck Anxiety Inventory), apathy (Starkstein Apathy Scale) and fatigue (Multidimensional Fatigue Inventory) at baseline and +1, +3 and +6 months. We collected blood samples and cerebrospinal fluid (CSF) to obtain biochemical and immunological profiles. Group comparisons, correlations and Principal component analysis (PCA) were performed. Longitudinal analyses are ongoing. Forty-nine participants were included (79.6% female, mean age 50.1 (SD 7.9). At the time of assessment, they presented multiple symptoms other than cognitive complaints (88% fatigue, 61% headache, 63% dyspnea, and 10% fever). The NPS showed that executive functions were the most affected (up to 29% of the sample had at least one test altered), followed by memory (at least one test altered in 25%) (Figure 1). On the contrary, language and praxis were preserved. Participants presented with anxiety symptoms (minimal 8.7%, mild in 34.8%, moderate 26.1%, severe 30.4%), depressive symptoms (none 34.8%, mild 26.1%, borderline clinical depression 23.9%, moderate 8.7%, severe 6.5%), and clinically relevant apathy in 64.4%. The sample presented a mean score of total fatigue of 58 (min 48, max 68), (scores 20-100). Fever and or moderate/severe anxiety were associated with lower scores in some memory and executive functions subtests (Figure 2). Most of the variability in the sample was explained by executive functions subtests (PCA, Figure 3). Patients presented increased levels of interleukins (IL) IL-1b, IL-17a and IL-18 in CSF compared to controls. Cognitive PACS predominantly affected executive functions and memory. Fever and moderate/severe anxiety were associated with worse cognitive outcomes. Several inflammatory markers were altered in cognitive PACS.

Post-acute Covid-19 syndrome (PACS) frequently refers to cognitive complaints. It is not yet clear whether there is an association between cognitive symptoms with brain changes or neuropsychiatric symptoms. Our aims are 1) to study cross-sectional and longitudinal MRI brain measures in a cohort of PACS and 2) their association with cognitive performance and mood disturbances. We performed a prospective single-center study with 3T-T1w MRI of 49 PACS patients at a cross-sectional level. These participants had confirmed SARS-CoV2 infection, ≥ 8 weeks after symptoms onset and cognitive complaints. All participants completed a comprehensive neuropsychological battery (NPS) and questionnaires assessing depression, anxiety, and subjective cognitive complaints (SCD). We obtained global MRI measures (e.g; gray and white matter volumes and mean cortical thickness) with FreeSurfer. We measured correlations of global MRI measures with SCD, memory and executive function outcomes, anxiety, and depression. All analyses were corrected for multiple comparisons. 44 PACS subjects had a 6-month follow-up MRI: in these, we performed longitudinal analyses with Generalized Linear Mixed-Effects Models to study changes between visits in global MRI measures. Demographics are shown in Table 1. We did not find any correlation between clinical outcomes (SCD, anxiety, depression) and MRI findings. Visual memory (Rey figure’s recall) and cognitive interference inhibition and processing speed ((Stroop’s color-word condition) were positively correlated with global gray and white matter volume measures (Figure 1). We did not identify changes in global MRI measures at 6 months in PACS participants. In PACS, worse visual memory and executive function, but not other clinical outcomes, were associated with lower global structural MRI indexes. We did not observe global longitudinal changes in MRI.

Background and objective Alzheimer’s disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC. Methods We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14–3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity. Results We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability. Conclusion We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.

Two genetic variants in strong linkage disequilibrium (rs9536314 and rs9527025) in the Klotho (KL) gene, encoding a transmembrane protein, implicated in longevity and associated with brain resilience during normal aging, were recently shown to be associated with Alzheimer disease (AD) risk in cognitively normal participants who are APOE ε4 carriers. Specifically, the participants heterozygous for this variant (KL-SVHET+) showed lower risk of developing AD. Furthermore, a neuroprotective effect of KL-VSHET+ has been suggested against amyloid burden for cognitively normal participants, potentially mediated via the regulation of redox pathways. However, inconsistent associations and a smaller sample size of existing studies pose significant hurdles in drawing definitive conclusions. Here, we performed a well-powered association analysis between KL-VSHET+ and five different AD endophenotypes; brain amyloidosis measured by positron emission tomography (PET) scans (n = 5,541) or cerebrospinal fluid Aβ42 levels (CSF; n = 5,093), as well as biomarkers associated with tau pathology: the CSF Tau (n = 5,127), phosphorylated Tau (pTau181; n = 4,778) and inflammation: CSF soluble triggering receptor expressed on myeloid cells 2 (sTREM2; n = 2,123) levels. Our results found nominally significant associations of KL-VSHET+ status with biomarkers for brain amyloidosis (e.g., CSF Aβ positivity; odds ratio [OR] = 0.67 [95% CI, 0.55-0.78], β = 0.72, p = 0.007) and tau pathology (e.g., biomarker positivity for CSF Tau; OR = 0.39 [95% CI, 0.19-0.77], β = -0.94, p = 0.007, and pTau; OR = 0.50 [95% CI, 0.27-0.96], β = -0.68, p = 0.04) in cognitively normal participants, 60-80 years old, who are APOE e4-carriers. Our work supports previous findings, suggesting that the KL-VSHET+ on an APOE ε4 genotype background may modulate Aβ and tau pathology, thereby lowering the intensity of neurodegeneration and incidence of cognitive decline in older controls susceptible to AD.