Neural basis of fatigue in post-COVID syndrome and relationships with cognitive complaints and cognition.

The main objective was to evaluate structural and functional connectivity correlates of fatigue in post-COVID syndrome, and to investigate the relationships with an objective measure of mental fatigue and with subjective cognitive complaints. One-hundred and twenty-nine patients were recruited after 14.79 ± 7.17 months. Patients were evaluated with fatigue, neuropsychological, and subjective cognitive complaints assessments. Structural and functional magnetic resonance imaging were acquired, and functional connectivity, white matter diffusivity and grey matter volume were evaluated. Fatigue was present in 86 % of patients, and was highly correlated to subjective cognitive complaints. Fatigue was associated with structural and functional connectivity mostly in frontal areas but also temporal, and cerebellar areas, showing mental fatigue different pattern of functional connectivity correlates compared to physical fatigue. White matter diffusivity correlates were similar in fatigue and subjective cognitive complaints, located in the forceps minor, anterior corona radiata and anterior cingulum. Findings confirm that fatigue in post-COVID syndrome is related to cerebral connectivity patterns, evidencing its brain substrates. Moreover, results highlight the relationship between fatigue and subjective cognitive complaints. These findings point out the relevance of the multidisciplinary assessment of post-COVID syndrome patients with subjective cognitive complaints, in order to unravel the symptomatology beneath the patient's complaints.

Comparison of the Diagnostic Accuracy of Five Cognitive Screening Tests for Diagnosing Mild Cognitive Impairment in Patients Consulting for Memory Loss.

Objectives: We aimed to evaluate and compare the diagnostic capacity of five cognitive screening tests for the diagnosis of mild cognitive impairment (MCI) in patients consulting by memory loss. Methods: A cross-sectional study involving 140 participants with a mean age of 74.42 ± 7.60 years, 87 (62.14%) women. Patients were classified as MCI or cognitively unimpaired according to a comprehensive neuropsychological battery. The diagnostic properties of the following screening tests were compared: Mini-Mental State Examination (MMSE), Addenbrooke's Cognitive Examination III (ACE-III) and Mini-Addenbrooke (M-ACE), Memory Impairment Screen (MIS), Montreal Cognitive Assessment (MoCA), and Rowland Universal Dementia Assessment Scale (RUDAS). Results: The area under the curve (AUC) was 0.861 for the ACE-III, 0.867 for M-ACE, 0.791 for MoCA, 0.795 for MMSE, 0.731 for RUDAS, and 0.672 for MIS. For the memory components, the AUC was 0.869 for ACE-III, 0.717 for MMSE, 0.755 for MoCA, and 0.720 for RUDAS. Cronbach's alpha was 0.827 for ACE-III, 0.505 for MMSE, 0.896 for MoCA, and 0.721 for RUDAS. Correlations with Free and Cued Selective Reminding Test were moderate with M-ACE, ACE-III, and MoCA, and moderate for the other tests. The M-ACE showed the best balance between diagnostic capacity and time of administration. Conclusions: ACE-III and its brief version M-ACE showed better diagnostic properties for the diagnosis of MCI than the other screening tests. MoCA and MMSE showed adequate properties, while the diagnostic capacity of MIS and RUDAS was limited.

Detection of cerebrospinal fluid biomarkers changes of Alzheimer's disease using a cognitive stress test in persons with subjective cognitive decline and mild cognitive impairment.

Introduction: Timely and accurate diagnosis of the earliest manifestations of Alzheimer's disease (AD) is critically important. Cognitive challenge tests such as the Loewenstein Acevedo Scales for Semantic Interference and Learning (LASSI-L) have shown favorable diagnostic properties in a number of previous investigations using amyloid or FDG PET. However, no studies have examined LASSI-L performance against cerebrospinal fluid biomarkers of AD, which can be affected before the distribution of fibrillar amyloid and other changes that can be observed in brain neuroimaging. Therefore, we aimed to evaluate the relationship between LASSI-L scores and CSF biomarkers and the capacity of the cognitive challenge test to detect the presence of amyloid and tau deposition in patients with subjective cognitive decline and amnestic mild cognitive impairment (MCI). Methods: One hundred and seventy-nine patients consulting for memory loss without functional impairment were enrolled. Patients were examined using comprehensive neuropsychological assessment, the LASSI-L, and cerebrospinal fluid (CSF) biomarkers (Aß1-42/Aß1-40 and ptau181). Means comparisons, correlations, effect sizes, and ROC curves were calculated. Results: LASSI-L scores were significantly associated with CSF biomarkers Aß1-42/Aß1-40 in patients diagnosed with MCI and subjective cognitive decline, especially those scores evaluating the capacity to recover from proactive semantic interference effects and delayed recall. A logistic regression model for the entire sample including LASSI-L and age showed an accuracy of 0.749 and an area under the curve of 0.785 to detect abnormal amyloid deposition. Conclusion: Our study supports the biological validity of the LASSI-L and its semantic interference paradigm in the context of the early stages of AD. These findings emphasize the utility and the convenience of including sensitive cognitive challenge tests in the assessment of patients with suspicion of early stages of AD.

Cognitive profile in multiple sclerosis and post-COVID condition: a comparative study using a unified taxonomy.

Post-COVID condition (PCC) and multiple sclerosis (MS) share some clinical and demographic features, including cognitive symptoms and fatigue. Some pathophysiological mechanisms well-known in MS, such as autoimmunity, neuroinflammation and myelin damage, have also been implicated in PCC. In this study, we aimed to compare the cognitive phenotypes of two large cohorts of patients with PCC and MS, and to evaluate the relationship between fatigue and cognitive performance. Cross-sectional study including 218 patients with PCC and 218 with MS matched by age, sex, and years of education. Patients were evaluated with a comprehensive neuropsychological protocol and were categorized according to the International Classification of Cognitive Disorders system. Fatigue and depression were also assessed. Cognitive profiles of PCC and MS largely overlapped, with a greater impairment in episodic memory in MS, but with small effect sizes. The most salient deficits in both disorders were in attention and processing speed. The severity of fatigue was greater in patients with PCC. Still, the correlations between fatigue severity and neuropsychological tests were more prominent in the case of MS. There were no differences in the severity of depression among groups. Our study found similar cognitive profiles in PCC and MS. Fatigue was more severe in PCC, but was more associated with cognitive performance in MS. Further comparative studies addressing the mechanisms related to cognitive dysfunction and fatigue may be of interest to advance the knowledge of these disorders and develop new therapies.

A multi-site study on sex differences in cortical thickness in non-demented Parkinson's disease.

Clinical, cognitive, and atrophy characteristics depending on sex have been previously reported in Parkinson's disease (PD). However, though sex differences in cortical gray matter measures in early drug naïve patients have been described, little is known about differences in cortical thickness (CTh) as the disease advances. Our multi-site sample comprised 211 non-demented PD patients (64.45% males; mean age 65.58 ± 8.44 years old; mean disease duration 6.42 ± 5.11 years) and 86 healthy controls (50% males; mean age 65.49 ± 9.33 years old) with available T1-weighted 3 T MRI data from four international research centers. Sex differences in regional mean CTh estimations were analyzed using generalized linear models. The relation of CTh in regions showing sex differences with age, disease duration, and age of onset was examined through multiple linear regression. PD males showed thinner cortex than PD females in six frontal (bilateral caudal middle frontal, bilateral superior frontal, left precentral and right pars orbitalis), three parietal (bilateral inferior parietal and left supramarginal), and one limbic region (right posterior cingulate). In PD males, lower CTh values in nine out of ten regions were associated with longer disease duration and older age, whereas in PD females, lower CTh was associated with older age but with longer disease duration only in one region. Overall, male patients show a more widespread pattern of reduced CTh compared with female patients. Disease duration seems more relevant to explain reduced CTh in male patients, suggesting worse prognostic over time. Further studies should explore sex-specific cortical atrophy trajectories using large longitudinal multi-site data.

A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers.

AIMS: The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values. METHODS: We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aß(1-42), Aß(1-42)/Aß(1-40) ratio, tTau, and pTau. RESULTS: The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia. CONCLUSION: We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.

FDG-PET-based neural correlates of Addenbrooke's cognitive examination III scores in Alzheimer's disease and frontotemporal degeneration.

Introduction: The Addenbrooke's Cognitive Examination III (ACE-III) is a brief test useful for neuropsychological assessment. Several studies have validated the test for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD). In this study, we aimed to examine the metabolic correlates associated with the performance of ACE-III in AD and behavioral variant FTD. Methods: We enrolled 300 participants in a cross-sectional study, including 180 patients with AD, 60 with behavioral FTD (bvFTD), and 60 controls. An 18F-Fluorodeoxyglucose positron emission tomography study was performed in all cases. Correlation between the ACE-III and its domains (attention, memory, fluency, language, and visuospatial) with the brain metabolism was estimated. Results: The ACE-III showed distinct neural correlates in bvFTD and AD, effectively capturing the most relevant regions involved in these disorders. Neural correlates differed for each domain, especially in the case of bvFTD. Lower ACE-III scores were associated with more advanced stages in both disorders. The ACE-III exhibited high discrimination between bvFTD vs. HC, and between AD vs. HC. Additionally, it was sensitive to detect hypometabolism in brain regions associated with bvFTD and AD. Conclusion: Our study contributes to the knowledge of the brain regions associated with ACE-III, thereby facilitating its interpretation, and highlighting its suitability for screening and monitoring. This study provides further validation of ACE-III in the context of AD and FTD.

Unraveling brain fog in post-COVID syndrome: Relationship between subjective cognitive complaints and cognitive function, fatigue, and neuropsychiatric symptoms.

BACKGROUND AND PURPOSE: "Brain fog" is a frequent and disabling symptom that can occur after SARS-CoV-2 infection. However, its clinical characteristics and the relationships among brain fog and objective cognitive function, fatigue, and neuropsychiatric symptoms (depression, anxiety) are still unclear. In this study, we aimed to examine the characteristics of brain fog and to understand how fatigue, cognitive performance, and neuropsychiatric symptoms and the mutual relationships among these variables influence subjective cognitive complaints. METHODS: A total of 170 patients with cognitive complaints in the context of post-COVID syndrome were evaluated using a comprehensive neuropsychological protocol. The FLEI scale was used to characterize subjective cognitive complaints. Correlation analysis, regression machine-learning algorithms, and mediation analysis were calculated. RESULTS: Cognitive complaints were mainly attention and episodic memory symptoms, while executive functions (planning) issues were less often reported. The FLEI scale, a mental ability questionnaire, showed high correlations with a fatigue scale and moderate correlations with the Stroop test, and anxiety and depressive symptoms. Random forest algorithms showed an R2 value of 0.409 for the prediction of FLEI score, with several cognitive tests, fatigue and depression being the best variables used in the prediction. Mediation analysis showed that fatigue was the main mediator between objective and subjective cognition, while the effect of depression was indirect and mediated through fatigue. CONCLUSIONS: Brain fog associated with COVID-19 is mainly characterized by attention and episodic memory, and fatigue, which is the main mediator between objective and subjective cognition. Our findings contribute to understanding the pathophysiology of brain fog and emphasize the need to unravel the main mechanisms underlying brain fog, considering several aspects.

Hippocampal subfield abnormalities and biomarkers of pathologic brain changes: from SARS-CoV-2 acute infection to post-COVID syndrome.

BACKGROUND: Cognitive deficits are among the main disabling symptoms in COVID-19 patients and post-COVID syndrome (PCS). Within brain regions, the hippocampus, a key region for cognition, has shown vulnerability to SARS-CoV-2 infection. Therefore, in vivo detailed evaluation of hippocampal changes in PCS patients, validated on post-mortem samples of COVID-19 patients at the acute phase, would shed light into the relationship between COVID-19 and cognition. METHODS: Hippocampal subfields volume, microstructure, and perfusion were evaluated in 84 PCS patients and compared to 33 controls. Associations with blood biomarkers, including glial fibrillary acidic protein (GFAP), myelin oligodendrocyte glycoprotein (MOG), eotaxin-1 (CCL11) and neurofilament light chain (NfL) were evaluated. Besides, biomarker immunodetection in seven hippocampal necropsies of patients at the acute phase were contrasted against eight controls. FINDINGS: In vivo analyses revealed that hippocampal grey matter atrophy is accompanied by altered microstructural integrity, hypoperfusion, and functional connectivity changes in PCS patients. Hippocampal structural and functional alterations were related to cognitive dysfunction, particularly attention and memory. GFAP, MOG, CCL11 and NfL biomarkers revealed alterations in PCS, and showed associations with hippocampal volume changes, in selective hippocampal subfields. Moreover, post mortem histology showed the presence of increased GFAP and CCL11 and reduced MOG concentrations in the hippocampus in post-mortem samples at the acute phase. INTERPRETATION: The current results evidenced that PCS patients with cognitive sequalae present brain alterations related to cognitive dysfunction, accompanied by a cascade of pathological alterations in blood biomarkers, indicating axonal damage, astrocyte alterations, neuronal injury, and myelin changes that are already present from the acute phase. FUNDING: Nominative Grant FIBHCSC 2020 COVID-19. Department of Health, Community of Madrid. Instituto de Salud Carlos III through the project INT20/00079, co-funded by European Regional Development Fund "A way to make Europe" (JAMG). Instituto de Salud Carlos III (ISCIII) through Sara Borrell postdoctoral fellowship Grant No. CD22/00043) and co-funded by the European Union (MDC). Instituto de Salud Carlos III through a predoctoral contract (FI20/000145) (co-funded by European Regional Development Fund "A way to make Europe") (MVS). Fundación para el Conocimiento Madri+d through the project G63-HEALTHSTARPLUS-HSP4 (JAMG, SOM).

Are there cognitive and neuroimaging signatures in long COVID?

This scientific commentary refers to 'Markers of limbic system damage following SARS-CoV-2 infection', by Thomasson et al. (https://doi.org/10.1093/braincomms/fcad177).