ECAS correlation with metabolic alterations on FDG-PET imaging in ALS.

Background: Cognitive impairment is observed in up to 50% of patients with amyotrophic lateral sclerosis (ALS). The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is an ALS-specific multi-domain screening tool. Few studies have examined the relationship between ECAS scores and [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) findings. Objective: To assess the relationship between ECAS scores and glucose metabolism patterns on [18F]FDG -PET images in ALS. Methods: We collected [18F]FDG-PET images from 65 patients with ALS and 39 healthy controls. ECAS scores were collected on all patients and we calculated the correlation to [18F]FDG-PET in order to investigate the potential links between cognition and glucose metabolism. Results: We observed hypometabolism in the frontal cortex, insula, and limbic system, together with hypermetabolism in the cerebellum in patients with ALS compared to controls. A lower ECAS total score was associated with lower glucose metabolism in the right orbitofrontal gyrus and higher glucose metabolism in lateral occipital, medial occipital, and cerebellar regions, among patients with ALS. Similar results, although less widespread, were observed in the analyses of ECAS ALS-specific scores. Conclusions: The metabolic patterns in [18F]FDG -PET show that changes in the glucose metabolism of corresponding areas are related to cognitive dysfunction in ALS, and can be detected using the ECAS.

Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease.

Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aß-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aß-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.

Investigating underlying brain structures and influence of mild and subjective cognitive impairment on dual-task performance in people with Parkinson's disease.

Cognitive impairment can affect dual-task abilities in Parkinson's disease (PD), but it remains unclear whether this is also driven by gray matter alterations across different cognitive classifications. Therefore, we investigated associations between dual-task performance during gait and functional mobility and gray matter alterations and explored whether these associations differed according to the degree of cognitive impairment. Participants with PD were classified according to their cognitive function with 22 as mild cognitive impairment (PD-MCI), 14 as subjective cognitive impairment (PD-SCI), and 20 as normal cognition (PD-NC). Multiple regression models associated dual-task absolute and interference values of gait speed, step-time variability, and reaction time, as well as dual-task absolute and difference values for Timed Up and Go (TUG) with PD cognitive classification. We repeated these regressions including the nucleus basalis of Meynert, dorsolateral prefrontal cortex, and hippocampus. We additionally explored whole-brain regressions with dual-task measures to identify dual-task-related regions. There was a trend that cerebellar alterations were associated with worse TUG dual-task in PD-SCI, but also with higher dual-task gait speed and higher dual-task step-time variability in PD-NC. After multiple comparison corrections, no effects of interest were significant. In summary, no clear set of variables associated with dual-task performance was found that distinguished between PD cognitive classifications in our cohort. Promising but non-significant trends, in particular regarding the TUG dual-task, do however warrant further investigation in future large-scale studies.

Nucleus Basalis of Meynert Degeneration Predicts Cognitive Decline in Corticobasal Syndrome.

BACKGROUND: Cognitive changes are common in corticobasal syndrome (CBS) and significantly impact quality of life and caregiver burden. However, relatively few studies have investigated the neural substrates of cognitive changes in CBS, and reliable predictors of cognitive impairment are currently lacking. The nucleus basalis of Meynert (NbM), which serves as the primary source of cortical cholinergic innervation, has been functionally associated with cognition. This study aimed to explore whether patients with CBS exhibit reduced NbM volumes compared with healthy control participants and whether NbM degeneration can serve as a predictor of cognitive impairment in patients with CBS. METHODS: In this study, we investigated in vivo volumetric changes of the NbM in 38 patients with CBS and 84 healthy control participants. Next, we assessed whether gray matter degeneration of the NbM evaluated at baseline could predict cognitive impairment during a 12-month follow-up period in patients with CBS. All volumetric analyses were performed using 3T T1-weighted images obtained from the 4-Repeat Tauopathy Neuroimaging Initiative. RESULTS: Patients with CBS displayed significantly lower NbM volumes than control participants (p < .001). Structural damage of the NbM also predicted the development of cognitive impairment in patients with CBS as assessed by longitudinal measurements of the Clinical Dementia Rating Sum of Boxes (p < .001) and Mini-Mental State Examination (p = .035). CONCLUSIONS: Our findings suggest that NbM atrophy may represent a promising noninvasive in vivo marker of cognitive decline in CBS and provide new insights into the neural mechanisms that underlie cognitive impairment in CBS.

Dynamic multilayer functional connectivity detects preclinical and clinical Alzheimer's disease.

Increasing evidence suggests that patients with Alzheimer's disease present alterations in functional connectivity but previous results have not always been consistent. One of the reasons that may account for this inconsistency is the lack of consideration of temporal dynamics. To address this limitation, here we studied the dynamic modular organization on resting-state functional magnetic resonance imaging across different stages of Alzheimer's disease using a novel multilayer brain network approach. Participants from preclinical and clinical Alzheimer's disease stages were included. Temporal multilayer networks were used to assess time-varying modular organization. Logistic regression models were employed for disease stage discrimination, and partial least squares analyses examined associations between dynamic measures with cognition and pathology. Temporal multilayer functional measures distinguished all groups, particularly preclinical stages, overcoming the discriminatory power of risk factors such as age, sex, and APOE ϵ4 carriership. Dynamic multilayer functional measures exhibited strong associations with cognition as well as amyloid and tau pathology. Dynamic multilayer functional connectivity shows promise as a functional imaging biomarker for both early- and late-stage Alzheimer's disease diagnosis.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

INTRODUCTION: Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. MATERIALS AND METHODS: We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. RESULTS: CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. DISCUSSION: These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. HIGHLIGHTS: Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Effects of current alcohol use on brain volume among older adults in the Gothenburg H70 Birth Cohort study 2014-16.

Brain gray- and white matter changes is well described in alcohol-dependent elderly subjects; however, the effect of lower levels of alcohol consumption on the brain is poorly understood. We investigated the impact of different amounts of weekly alcohol consumption on brain structure in a population-based sample of 70-year-olds living in Gothenburg, Sweden. Cross-sectional data from 676 participants from The Gothenburg H70 Birth Cohort Study 2014-16 were included. Current alcohol consumers were divided into seven groups based on self-reported weekly amounts of alcohol consumption in grams (g) (0-50 g/week, used as reference group, 51-100 g/week, 101-150 g/week, 151-200 g/week, 201-250 g/week, 251-300 g/week, and > 300 g/week). Subcortical volumes and cortical thickness were assessed on T1-weighted structural magnetic resonance images using FreeSurfer 5.3, and white matter integrity assessed on diffusion tensor images, using tract-based statistics in FSL. General linear models were carried out to estimate associations between alcohol consumption and gray- and white matter changes in the brain. Self-reported consumption above 250 g/week was associated with thinning in the bilateral superior frontal gyrus, the right precentral gyrus, and the right lateral occipital cortex, in addition to reduced fractional anisotropy (FA) and increased mean diffusivity (MD) diffusively spread in many tracts all over the brain. No changes were found in subcortical gray matter structures. These results suggest that there is a non-linear relationship between alcohol consumption and structural brain changes, in which loss of cortical thickness only occur in non-demented 70-year-olds who consume more than 250 g/week.

Statins and cognitive decline in patients with Alzheimer's and mixed dementia: a longitudinal registry-based cohort study.

BACKGROUND: Disturbances in brain cholesterol homeostasis may be involved in the pathogenesis of Alzheimer's disease (AD). Lipid-lowering medications could interfere with neurodegenerative processes in AD through cholesterol metabolism or other mechanisms. OBJECTIVE: To explore the association between the use of lipid-lowering medications and cognitive decline over time in a cohort of patients with AD or mixed dementia with indication for lipid-lowering treatment. METHODS: A longitudinal cohort study using the Swedish Registry for Cognitive/Dementia Disorders, linked with other Swedish national registries. Cognitive trajectories evaluated with mini-mental state examination (MMSE) were compared between statin users and non-users, individual statin users, groups of statins and non-statin lipid-lowering medications using mixed-effect regression models with inverse probability of drop out weighting. A dose-response analysis included statin users compared to non-users. RESULTS: Our cohort consisted of 15,586 patients with mean age of 79.5 years at diagnosis and a majority of women (59.2 %). A dose-response effect was demonstrated: taking one defined daily dose of statins on average was associated with 0.63 more MMSE points after 3 years compared to no use of statins (95% CI: 0.33;0.94). Simvastatin users showed 1.01 more MMSE points (95% CI: 0.06;1.97) after 3 years compared to atorvastatin users. Younger (< 79.5 years at index date) simvastatin users had 0.80 more MMSE points compared to younger atorvastatin users (95% CI: 0.05;1.55) after 3 years. Simvastatin users had 1.03 more MMSE points (95% CI: 0.26;1.80) compared to rosuvastatin users after 3 years. No differences regarding statin lipophilicity were observed. The results of sensitivity analysis restricted to incident users were not consistent. CONCLUSIONS: Some patients with AD or mixed dementia with indication for lipid-lowering medication may benefit cognitively from statin treatment; however, further research is needed to clarify the findings of sensitivity analyses.

DOPA decarboxylase is an emerging biomarker for Parkinsonian disorders including preclinical Lewy body disease.

The diagnosis of Parkinsonian disorders is currently based on clinical criteria, which have limited sensitivity until most dopaminergic neurons are lost. Here we show that cerebrospinal fluid levels of DOPA decarboxylase (DDC) (also known as aromatic L-amino acid decarboxylase) can accurately identify patients with Lewy body disease (LBD) (area under the curve (AUC) = 0.89; PFDR = 2.6 × 10-13) and are associated with worse cognitive performance (P < 0.05). We also found that DDC can detect preclinical LBD stages in clinically unimpaired individuals with a positive seed amplification α-synuclein assay (AUC = 0.81, P = 1.0 × 10-5) and that this biomarker could predict progression to clinical LBD over a 3-year period in preclinical cases (hazard ratio = 3.7 per s.d. change, confidence interval = 1.1-12.7). Moreover, DDC levels were also increased in atypical Parkinsonian disorders but not in non-Parkinsonian neurodegenerative disorders. These cerebrospinal fluid results were replicated in an independent cohort, where we also found that DDC levels in plasma could identify both LBD and atypical Parkinsonian disorders (AUC = 0.92, P = 1.3 × 10-14). Our results show that DDC might have a future role in clinical practice as a biomarker of dopaminergic dysfunction to detect Parkinsonian disorders even during the preclinical disease stages and predict their progression to clinical LBD.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight.

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Age-related differences in the functional topography of the locus coeruleus and their implications for cognitive and affective functions.

The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.

Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis.

INTRODUCTION: High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. METHODS: Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. RESULTS: Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. CONCLUSION: These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.

Neurofilament light predicts worse nonmotor symptoms and depression in Parkinson's disease.

BACKGROUND: The identification of biomarkers that reflect worse progression of nonmotor symptoms (NMS) in Parkinson's disease (PD) is currently an unmet need. The main aim of this study was to investigate whether cerebrospinal fluid (CSF) and serum neurofilament light (NfL), measured at baseline or longitudinally, can be used to predict the progression of NMS in patients with PD. METHODS: Baseline and longitudinal NfL levels were measured in the CSF and serum in 392 PD patients and 184 healthy controls from the Parkinson's Progression Marker Initiative. NMS were assessed using several scales, including, but not restricted to, the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part I, the Geriatric Depression Scale (GDS) and the State-Trait Anxiety Inventory (STAI). The relationship between baseline and longitudinal NfL levels with changes in NMS was assessed using linear mixed effects models (LME) in PD patients. In addition, we compared CSF and serum NfL levels between groups and assessed the relationship between NfL biomarkers with baseline NMS. Finally, to assess the specificity of our findings we ran the previous LME models using other biomarkers such as CSF amyloid-ß1-42, total tau, phosphorylated tau181 and total α-synuclein and we also ran the models in healthy controls. RESULTS: Baseline levels and longitudinal changes in serum and CSF NfL predicted worse longitudinal MDS-UPDRS-I and depression scores over time in PD (p < 0.01). This relationship remained significant only for CSF NfL when controlling for motor and cognitive status. Furthermore, longitudinal changes in serum and CSF NfL were associated with worse anxiety over time in PD patients (p < 0.05). In contrast to CSF NfL, serum NfL levels were slightly higher at baseline (p = 0.043) and showed significant longitudinal increases (p < 0.001) in PD patients compared to controls. There were no significant correlations between NfL levels (CSF or serum) with other NMS scales, baseline NMS variables, other biomarkers or in healthy controls. CONCLUSIONS: Our findings indicate that both serum and CSF NfL are associated with worse longitudinal NMS burden, particularly in relation to the progression of depression and anxiety. Serum NfL showed stronger associations with NMS suggesting it could potentially be used as a non-invasive marker of NMS progression for PD.

Cognitive effects of Lewy body pathology in clinically unimpaired individuals.

α-Synuclein aggregates constitute the pathology of Lewy body (LB) disease. Little is known about the effects of LB pathology in preclinical (presymptomatic) individuals, either as isolated pathology or coexisting with Alzheimer's disease (AD) pathology (ß-amyloid (Aß) and tau). We examined the effects of LB pathology using a cerebrospinal fluid α-synuclein-seed amplification assay in 1,182 cognitively and neurologically unimpaired participants from the BioFINDER study: 8% were LB positive, 26% Aß positive (13% of those were LB positive) and 16% tau positive. LB positivity occurred more often in the presence of Aß positivity but not tau positivity. LB pathology had independently negative effects on cross-sectional and longitudinal global cognition and memory and on longitudinal attention/executive function. Tau had cognitive effects of a similar magnitude, but these were less pronounced for Aß. Participants with both LB and AD (Aß and tau) pathology exhibited faster cognitive decline than those with only LB or AD pathology. LB, but not AD, pathology was associated with reduced sense of smell. Only LB-positive participants progressed to clinical LB disease over 10 years. These results are important for individualized prognosis, recruitment and choice of outcome measures in preclinical LB disease trials, but also for the design of early AD trials because >10% of individuals with preclinical AD have coexisting LB pathology.

Validity and reliability measures of the Swedish Karolinska version of the Edinburgh Cognitive and Behavioral ALS Screen (SK-ECAS).

OBJECTIVE: Cognitive and behavioral impairment is observed in up to 50% of patients with amyotrophic lateral sclerosis (ALS). The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is a 5-domain screening tool customized for quick cognitive screening in patients with ALS. Although the ECAS is available in Swedish at the Karolinska University Hospital (SK-ECAS), it has not yet been validated in Sweden stressing the need to assess validity and reliability of the SK-ECAS Version A. METHODS: The study included 176 patients with ALS or other motor neuron disease diagnosed between September 2017 and October 2021 at the Karolinska ALS Clinical Research Center in Stockholm, Sweden, and 35 age-matched healthy control subjects. SK-ECAS was validated against the Montreal Cognitive Assessment (MoCA) and optimal cutoffs, receiver operating characteristic (ROC) curve and area under the curve (AUC) were calculated. RESULTS: We identified an optimal cutoff of 108 for the SK-ECAS total score and 82 for the SK-ECAS ALS-specific score to detect cognitive impairment. The SK-ECAS showed good performance in indicating abnormal cognition with an AUC of 0.73 for SK-ECAS ALS-specific score and 0.77 for SK-ECAS total score. There was good internal consistency with a Cronbach's alpha of 0.79. CONCLUSIONS: This study demonstrates good validity and reliability indices for SK-ECAS Version A for the detection of cognitive impairment in newly diagnosed ALS patients.

Age-related differences in the functional topography of the locus coeruleus: implications for cognitive and affective functions.

The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging and whether it is associated with cognition and mood. Here we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years old (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.

Sex differences in multilayer functional network topology over the course of aging in 37543 UK Biobank participants.

Aging is a major risk factor for cardiovascular and neurodegenerative disorders, with considerable societal and economic implications. Healthy aging is accompanied by changes in functional connectivity between and within resting-state functional networks, which have been associated with cognitive decline. However, there is no consensus on the impact of sex on these age-related functional trajectories. Here, we show that multilayer measures provide crucial information on the interaction between sex and age on network topology, allowing for better assessment of cognitive, structural, and cardiovascular risk factors that have been shown to differ between men and women, as well as providing additional insights into the genetic influences on changes in functional connectivity that occur during aging. In a large cross-sectional sample of 37,543 individuals from the UK Biobank cohort, we demonstrate that such multilayer measures that capture the relationship between positive and negative connections are more sensitive to sex-related changes in the whole-brain connectivity patterns and their topological architecture throughout aging, when compared to standard connectivity and topological measures. Our findings indicate that multilayer measures contain previously unknown information on the relationship between sex and age, which opens up new avenues for research into functional brain connectivity in aging.

Nonlinear changes in delayed functional network topology in Alzheimer's disease: relationship with amyloid and tau pathology.

BACKGROUND: Alzheimer's disease is a neurodegenerative disorder associated with the abnormal deposition of pathological processes, such as amyloid-ß and tau, which produces nonlinear changes in the functional connectivity patterns between different brain regions across the Alzheimer's disease continuum. However, the mechanisms underlying these nonlinear changes remain largely unknown. Here, we address this question using a novel method based on temporal or delayed correlations and calculate new whole-brain functional networks to tackle these mechanisms. METHODS: To assess our method, we evaluated 166 individuals from the ADNI database, including amyloid-beta negative and positive cognitively normal subjects, patients with mild cognitive impairment, and patients with Alzheimer's disease dementia. We used the clustering coefficient and the global efficiency to measure the functional network topology and assessed their relationship with amyloid and tau pathology measured by positron emission tomography, as well as cognitive performance using tests measuring memory, executive function, attention, and global cognition. RESULTS: Our study found nonlinear changes in the global efficiency, but not in the clustering coefficient, showing that the nonlinear changes in functional connectivity are due to an altered ability of brain regions to communicate with each other through direct paths. These changes in global efficiency were most prominent in early disease stages. However, later stages of Alzheimer's disease were associated with widespread network disruptions characterized by changes in both network measures. The temporal delays required for the detection of these changes varied across the Alzheimer's disease continuum, with shorter delays necessary to detect changes in early stages and longer delays necessary to detect changes in late stages. Both global efficiency and clustering coefficient showed quadratic associations with pathological amyloid and tau burden as well as cognitive decline. CONCLUSIONS: This study suggests that global efficiency is a more sensitive indicator of network changes in Alzheimer's disease when compared to clustering coefficient. Both network properties were associated with pathology and cognitive performance, demonstrating their relevance in clinical settings. Our findings provide an insight into the mechanisms underlying nonlinear changes in functional network organization in Alzheimer's disease, suggesting that it is the lack of direct connections that drives these functional changes.

Increased basal forebrain volumes could prevent cognitive decline in LRRK2 Parkinson's disease.

BACKGROUND AND OBJECTIVES: It has been recently suggested that LRRK2 mutations are associated with a more benign clinical phenotype and a potentially more preserved cholinergic function in Parkinson's disease (PD). However, to our knowledge, no studies have tested whether the better clinical progression observed in LRRK2-PD patients is associated with more preserved volumes of a cholinergic brain area, the basal forebrain (BF). To address this hypothesis, here we compared BF volumes in LRRK2 carriers with and without PD with respect to idiopathic PD (iPD) patients and controls, and assessed whether they are associated with better clinical progression observed in LRRK2-PD compared to iPD. METHODS: Thirty-one symptomatic LRRK2-PD patients and 13 asymptomatic LRRK2 individuals were included from the Parkinson's Progression Markers Initiative. In addition, 31 patients with iPD and 13 healthy controls matched to the previous groups were also included. BF volumes were automatically extracted from baseline T1-weighted MRI scans using a stereotactic atlas of cholinergic nuclei. These volumes were then compared between groups and their relationship with longitudinal cognitive changes was evaluated using linear mixed effects models. Mediation analyses assessed whether BF volumes mediated differences in cognitive trajectories between groups. RESULTS: LRRK2-PD patients showed significantly higher BF volumes compared to iPD (P = 0.019) as did asymptomatic LRRK2 subjects compared to controls (P = 0.008). There were no other significant differences in cortical regions or subcortical volumes between these groups. BF volumes predicted longitudinal decline in several cognitive functions in iPD patients but not in LRRK2-PD, who did not show cognitive changes over a 4-year follow-up period. BF volumes were a significant mediator of the different cognitive trajectories between iPD and LRRK2-PD patients (95% CI 0.056-2.955). DISCUSSION: Our findings suggest that mutations in LRRK2 are associated with increased BF volumes, potentially reflecting a compensatory hypercholinergic state that could prevent cognitive decline in LRRK2-PD patients.