Distinct Cognitive Phenotypes Research Articles

Autoimmune Encephalitis: A Hidden Enigma Demystified.

Autoimmune encephalitis is a condition marked by inflammation in the brain due to an immune system response targeting self-antigens within the central nervous system (CNS). This class of disorders is at least as prevalent as infectious causes of encephalitis and encompasses a wide range of conditions. The field has rapidly expanded thanks to the identification of various pathogenic autoantibodies responsible for varied neurological and neuropsychiatric diseases. These disorders often present with distinct cognitive, seizure, and movement disorder phenotypes, making them clinically identifiable. Swift identification and treatment are pivotal for improving patient outcomes and promptly diagnosing associated tumors. This article zeroes in on autoantibody-mediated encephalitis syndromes involving neuronal cell-surface antigens. It sheds light on practical aspects of diagnosis and treatment, drawing from clinical experiences in managing such cases. Additionally, it underscores the ongoing importance of neuroimmunological advances that will shape the future diagnosis and treatment of these conditions.

Structural and functional imaging features of cognitive phenotypes in pediatric multiple sclerosis.

The present study aimed to identify the clinical and MRI features of the distinct cognitive phenotypes in pediatric multiple sclerosis (pedMS). PedMS patients (n = 73) and healthy controls (n = 30) underwent clinical examination and 3.0T MRI. All patients completed neuropsychological testing, and cognitive phenotypes were identified by performing K-means clustering on cognitive scores. MRI metrics included brain T2-hyperintese lesion volume and normalized brain volumes. Within seven cognitively relevant cortical networks, structural disconnectivity (i.e., the mean percentage of streamlines connecting each pair of cortical regions passing through a lesion) and resting-state (RS) functional connectivity (FC) were estimated. Three cognitive phenotypes emerged: Preserved cognition (PC; n = 27, 37%), mild verbal learning and memory/semantic fluency involvement (MVS; n = 28, 38%), and multidomain involvement (MI; n = 18, 25%). Age, sex, and disease duration did not differ among groups. Compared with healthy subjects, PC patients had decreased RS FC within the default mode network (p = 0.045); MVS patients exhibited lower cortical volume and reduced RS FC within the frontoparietal network (all p = 0.045); and MI patients showed decreased volumes in all brain compartments except the hippocampus, and reduced RS FC within the frontoparietal network (all p ≤ 0.045). Compared to PC, MI patients had more severe disability and higher structural disconnectivity within four cortical networks (all p ≤ 0.045). Compared to PC and MVS, MI patients had lower intelligence quotient (all p ≤ 0.005). We identified three cognitive phenotypes in pedMS that demonstrate the existence of a spectrum of impairment. Such phenotypes showed distinct clinical and MRI characteristics that contributed to explain their cognitive profiles.

Trajectories in depressive symptoms and midlife brain health

Depressive symptoms may either be a risk factor or prodromal to dementia. Investigating this association in midlife may help clarify the role of depression in cognitive aging. We aimed to identify trajectories in depressive symptoms in early to mid-life and related cognitive and brain outcomes in midlife. This study includes 3944 Black and White participants (ages 26−45 years at baseline) from the Coronary Artery Risk Development in Young Adults (CARDIA) study with 20 years of follow-up. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression scale at five time points over 20 years. Growth mixture modeling (GMM) was used to identify depressive symptom trajectories. Participants completed a neuropsychological battery 20 years after baseline, including the Digit Symbol Substitution Test (DSST), Rey-Auditory Verbal Learning Test (RAVLT), Stroop Test, Montreal Cognitive Assessment (MoCA), and category and letter fluency tests. A sub-sample of participants (n = 662) underwent brain magnetic resonance imaging (MRI) to characterize gray matter volumes and white matter hyperintensities (WMHs). We identified four classes of depressive symptom trajectories: a “declining” class (n = 286, 7.3%) with initially high symptoms and subsequent decline, a class with consistently high symptoms (“steady high”; n = 264, 6.7%), a class with late increases in symptoms (“increasing”; n = 277, 7%), and a class with consistently low symptoms (“steady low”; n = 3117, 79.0%). The steady high and the increasing classes had poorer performance on all cognitive tests, while the declining class had poorer performance on the DSST, verbal fluency, and MoCA. Compared to the steady low symptom class, the steady high class had lower volumes in the entorhinal cortex (β: −180.80, 95% CI: −336.69 to −24.91) and the amygdala (β: −40.97, 95% CI: −74.09 to −7.85), the increasing class had more WMHs (β: 0.55, 95% CI: 0.22 to 0.89), and the declining class was not significantly different in any brain measures. Trajectories in depressive symptoms in young to mid-adulthood show distinct cognitive and brain phenotypes in midlife. Steady high depressive symptoms may represent a group that is at risk for dementia, whereas increasing symptoms in midlife may be associated with white matter damage.

OS08.5.A UNDERSTANDING THE ASSOCIATION BETWEEN FATIGUE AND COGNITION IN GLIOMA PATIENTS: AN OBSERVATIONAL MULTINATIONAL STUDY

Abstract BACKGROUND Both fatigue and cognitive impairment are highly prevalent in individuals with glioma and have been associated with diminished health-related quality of life. Although the two are thought to be related, evidence remains sparse, in part, due to the limited availability of data. Therefore, we aimed to investigate the relationship between fatigue and cognition in adult glioma patients. MATERIAL AND METHODS We analyzed cognitive data from adult patients with diffuse glioma at the University of California San Francisco (UCSF, n=100) and Amsterdam UMC (n=127). Comparable cognitive tests were combined by domain: attention, information processing, mental flexibility, semantic fluency, verbal learning, verbal memory, and visual search. Z-scores of ≤ -1.5 SD were considered impaired. Fatigue was assessed with the Fatigue Symptom Inventory (UCSF) and the Checklist Individual Strength (Amsterdam UMC). Linear mixed models were used to assess associations between cognitive domains and fatigue adjusted for site, grade, histology, sex, radiotherapy, and chemotherapy. Latent profile analysis was used to identify distinct fatigue-cognitive phenotypes. RESULTS UCSF patients were older (50.3 vs. 44.9 years, p=0.002), more likely to have grade 4 tumors (32% vs. 18%, p=0.025), and more years since diagnosis (2.72 vs 1.27, p<0.001). Interestingly, though UCSF patients were more impaired across nearly all cognitive domains, there was no difference in fatigue between institutions (-0.0457 vs. -0.178, p=0.60). Attention and impaired semantic fluency were associated with fatigue severity in univariate models. Using backward selection, the best-fit model included only impaired semantic fluency (estimated effect = 0.35, p= 0.014, r2=0.03). We identified four distinct cognitive phenotypes in the pooled dataset, which validated across sites, though fatigue severity did not contribute to these phenotypes. CONCLUSION Although fatigue and cognitive symptoms can overlap, the association between cognitive impairment and fatigue severity is weak. Interestingly, this important finding was validated across institutions and glioma subtypes. Further study is needed to address questions regarding the longitudinal change of symptoms. Given the limited relational overlap, fatigue and cognitive impairments should both be explicitly assessed and treated with targeted therapies. SUPPORT/DISCLOSURE Stichting Anita Veldman Foundation CCA-2019-2-21; Amsterdam University Fund 4056-2022-7-8; CCA travel grant 2022-10-10; Prins Bernhard Cultuurfondsbeurs 40042576/NOD; R.A. Laan fonds 2022-10-24; The loglio Collective; Sheri Sobrato Brisson Brain Cancer Survivorship Program.

Identification of Neuropsychological Phenotypes in Pediatric Multiple Sclerosis Using Unsupervised Machine Learning (P12-9.001)

<h3>Objective:</h3> To identify cognitive phenotypes in pediatric multiple sclerosis (MS) using an unsupervised machine learning approach. <h3>Background:</h3> Recent studies identified distinct cognitive phenotypes in adult MS patients using unsupervised machine learning approaches. <h3>Design/Methods:</h3> Fifty-three pediatric MS patients underwent clinical examination including Expanded Disability Status Scale (EDSS) to assess global disability. A comprehensive neuropsychological battery (Selective Reminding Test, Spatial Recall Test, Trail Making Test, Symbol Digit Modalities Test, Semantic verbal fluency test and Phonemic verbal fluency test) was administered to all patients. Raw scores of each test were converted to z-scores according to normative data. Cognitive tests z-scores were included in a k-means cluster analysis to identify cognitive phenotypes. Between-group comparisons of demographic, clinical and cognitive variables were computed using linear regression models or nonparametric tests as appropriate. Statistical significance was corrected for multiple comparisons (Bonferroni method). <h3>Results:</h3> In our sample, median age was 15.9 years (interquartile range [IQR] 13.6 – 16.8), 68% (36 patients) were girls and the mean disease duration was 1.8±1.7 years. Cluster analysis identified three cognitive phenotypes: preserved cognition (27 patients [51%]), mild verbal memory/semantic fluency involvement (19 patients [36%]) and severe multidomain involvement (7 patients [13%]). Across groups, there were no significant differences in age, sex and disease duration. Lower EDSS scores were found in patients with preserved cognition (median EDSS 1.0 [IQR 1.0 – 1.0]) than patients with mild verbal memory/semantic fluency involvement (median EDSS 1.5 [IQR 1.0 – 2.0]; p=0.01) and patients with severe multidomain involvement (median EDSS 2.0 [IQR 1.25 – 2.75]; p=0.004). <h3>Conclusions:</h3> Pediatric MS patients present with distinct cognitive phenotypes ranging from preserved cognition to severe multidomain involvement. Cognitive phenotypes are not associated with age, sex and disease duration. Patients with preserved cognition are characterized by low global disability. <b>Disclosure:</b> Damiano Mistri has nothing to disclose. Monica Margoni has received research support from MAGNIMS. Mr. Preziosa has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Bristol Myers Squibb . Mr. Preziosa has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Sanofi Genzyme. Mr. Preziosa has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Novartis. Mr. Preziosa has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Roche. Mr. Preziosa has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Merck. Alessandro Meani has nothing to disclose. Carmen Vizzino has nothing to disclose. Dr. Moiola has nothing to disclose. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving on a Speakers Bureau for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Springer Nature. The institution of Dr. Filippi has received research support from Biogen Idec, Merck-Serono, Novartis, Roche, Teva Pharmaceutical Industries, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, and ARiSLA (Fondazione Italiana di Ricerca per la SLA). Maria Assunta Rocca has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Bayer, Biogen, Bristol Myers Squibb, Celgene, Genzyme, Merck Serono, Novartis, Roche, and Teva. The institution of Maria Assunta Rocca has received research support from Italian Ministry of Health, MS Society of Canada and Fondazione Italiana Sclerosi Multipla.

Identifying different cognitive phenotypes and their relationship with disability in neuromyelitis optica spectrum disorder.

BackgroundThe existence, frequency, and features of cognitive impairment (CI) in patients with neuromyelitis optica spectrum disorder (NMOSD) are still debated. A precise classification and characterization of cognitive phenotypes in patients with NMOSD are lacking.MethodsA total of 66 patients with NMOSD and 22 healthy controls (HCs) underwent a neuropsychological assessment. Latent profile analysis (LPA) on cognitive test z scores was used to identify cognitive phenotypes, and ANOVA was used to define the clinical features of each phenotype. Univariate and multivariate analyses were used to explore the predictors of severe CI, and a corresponding nomogram was created to visualize the predictive model.ResultsLPA results suggested four distinct meaningful cognitive phenotypes in NMOSD: preserved cognition (n = 20, 30.3%), mild-attention (n = 21, 31.8%), mild-multidomain (n = 18, 27.3%), and severe-multidomain (n = 7, 10.6%). Patients with the last three phenotypes were perceived to have CI, which accounts for 67.6% of patients with NMOSD. Patients with NMOSD and worse cognitive function were older (p < 0.001) and had lower educational levels (p < 0.001), later clinical onset (p = 0.01), worse Expanded Disability Status Scale scores (p = 0.001), and poorer lower-limb motor function (Timed 25-Foot Walk, p = 0.029; 12-item Multiple Sclerosis Walking Scale [MSWS-12], p < 0.001). Deterioration of Nine-Hole Peg Test (odds ratio, OR: 1.115 [1, 1.243], p = 0.05) and MSWS-12 (OR: 1.069 [1.003, 1.139], p = 0.04) were the independent risk factors for severe cognitive dysfunction. Finally, a nomogram was built based on the entire cohort and the above factors to serve as a useful tool for clinicians to evaluate the risk of severe cognitive dysfunction.ConclusionsWe introduced a classification scheme for CI and highlighted that the deterioration of upper- and lower-limb motor disability potentially predicts cognitive phenotypes in NMOSD.

Neuropsychological Phenotypes in Pediatric Temporal Lobe Epilepsy

Adults with temporal lobe epilepsy (TLE) have been found to have a fairly characteristic pattern of neuropsychological performance, but there is considerably less research and more variability in findings with children. Because the cognitive domains included in most studies with children have been limited, the current study attempted to better characterize the cognitive phenotype of children with TLE using a broader neuropsychological battery. The study included 59 children with TLE (59% male) age 7 to 16 (M = 12.67; SD = 3.12) who underwent comprehensive neuropsychological evaluation. Patient results were grouped into cognitive domains (reasoning, language, visuoperceptual, verbal memory, executive function, and motor function) based upon their test performance. These factor scores were subjected to Ward's hierarchical clustering method with squared Euclidean distance. Cluster analysis revealed three distinct cognitive profiles: (1) normal functioning (20% of sample); (2) delayed verbal memory and motor weaknesses (61% of the sample); and (3) global impairment (19% of the sample). Cluster 3 had longer epilepsy duration and a higher incidence of hippocampal sclerosis (HS) compared to Cluster 1 (p < .05). There were no significant differences among the three cluster groups on demographic characteristics or remaining clinical characteristics. Children with TLE present with distinct cognitive phenotypes ranging from average performance to global impairment. Results partially support previous hypotheses highlighting the cumulative neurobiological burden on the developing brain in the context of chronic epilepsy and provide a preliminary framework for the cognitive domains most vulnerable to the TLE disease process.

Cognitive phenotypes in Parkinson's disease: A latent profile analysis.

Neurocognitive disorders in Parkinson's disease (PD) are common and heterogeneous. The aim of this study was to use a data-driven method to describe different cognitive phenotypes in PD and to explore anxiety, depression, and motor disturbances across the different cognitive profiles. Latent profile analysis was applied to the neuropsychological performances of 65 patients with idiopathic PD assessed by means of a battery of tests that encompass measures of attention, memory, executive functions, social cognition, language, and visuospatial abilities. A three-cluster model produced the best solution: Cluster A (21.54%) included patients with intact cognition or with a relatively slight cognitive impairment in memory and executive functioning; Cluster B (53.85%) included patients with an intermediate level of cognitive impairment; and Cluster C (24.61%) included patients with the most severe cognitive impairment, with greater deficit compared to Cluster B in executive functioning, and, notably, in tasks with a predominantly posterior cortical basis (naming and visuospatial abilities). The three subgroups did not differ in terms of age, gender, disease duration, motor symptom severity or side of onset, levodopa equivalent daily dose, level of anxiety, or depression; however, patients from Cluster C showed greater impairment than patients from Cluster A in measures of everyday functioning. We presented a qualitative description of three distinct cognitive phenotypes emerging from a sample of 65 PD patients. The three clusters seem to be related to daily functioning but are independent from the stage of disease, motor functioning, anxiety, and depression. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Identifying distinct cognitive phenotypes in multiple sclerosis (4284)

Identifying distinct cognitive phenotypes in multiple sclerosis (4284)

Sex-Dependent End-of-Life Mental and Vascular Scenarios for Compensatory Mechanisms in Mice with Normal and AD-Neurodegenerative Aging.

Life expectancy decreases with aging, with cardiovascular, mental health, and neurodegenerative disorders strongly contributing to the total disability-adjusted life years. Interestingly, the morbidity/mortality paradox points to females having a worse healthy life expectancy. Since bidirectional interactions between cardiovascular and Alzheimer’s diseases (AD) have been reported, the study of this emerging field is promising. In the present work, we further explored the cardiovascular–brain interactions in mice survivors of two cohorts of non-transgenic and 3xTg-AD mice, including both sexes, to investigate the frailty/survival through their life span. Survival, monitored from birth, showed exceptionally worse mortality rates in females than males, independently of the genotype. This mortality selection provided a “survivors” cohort that could unveil brain–cardiovascular interaction mechanisms relevant for normal and neurodegenerative aging processes restricted to long-lived animals. The results show sex-dependent distinct physical (worse in 3xTg-AD males), neuropsychiatric-like and cognitive phenotypes (worse in 3xTg-AD females), and hypothalamic–pituitary–adrenal (HPA) axis activation (higher in females), with higher cerebral blood flow and improved cardiovascular phenotype in 3xTg-AD female mice survivors. The present study provides an experimental scenario to study the suggested potential compensatory hemodynamic mechanisms in end-of-life dementia, which is sex-dependent and can be a target for pharmacological and non-pharmacological interventions.

Identifying the Distinct Cognitive Phenotypes in Multiple Sclerosis

Cognitive impairment is a common and disabling feature of multiple sclerosis (MS), but a precise characterization of cognitive phenotypes in patients with MS is lacking. To identify cognitive phenotypes in a clinical cohort of patients with MS and to characterize their clinical and magnetic resonance imaging (MRI) features. This multicenter cross-sectional study consecutively screened clinically stable patients with MS and healthy control individuals at 8 MS centers in Italy from January 1, 2010, to October 31, 2019. Patients with MS and healthy control individuals who were not using psychoactive drugs and had no history of other neurological or medical disorders, learning disability, severe head trauma, and alcohol or drug abuse were enrolled. Participants underwent a neurological examination and a cognitive evaluation with the Rao Brief Repeatable Battery and Stroop Color and Word Test. A subgroup of participants also underwent a brain MRI examination. Latent profile analysis was used on cognitive test z scores to identify cognitive phenotypes. Linear regression and mixed-effects models were used to define clinical and MRI features of each phenotype. A total of 1212 patients with MS (mean [SD] age, 41.1 [11.1] years; 784 women [64.7%]) and 196 healthy control individuals (mean [SD] age, 40.4 [8.6] years; 130 women [66.3%]) were analyzed in this study. Five cognitive phenotypes were identified: preserved cognition (n = 235 patients [19.4%]), mild-verbal memory/semantic fluency (n = 362 patients [29.9%]), mild-multidomain (n = 236 patients [19.5%]), severe-executive/attention (n = 167 patients [13.8%]), and severe-multidomain (n = 212 patients [17.5%]) involvement. Patients with preserved cognition and mild-verbal memory/semantic fluency were younger (mean [SD] age, 36.5 [9.8] years and 38.2 [11.1] years) and had shorter disease duration (mean [SD] 8.0 [7.3] years and 8.3 [7.6] years) compared with patients with mild-multidomain (mean [SD] age, 42.6 [11.2] years; mean [SD] disease duration, 12.8 [9.6] years; P < .001), severe-executive/attention (mean [SD] age, 42.9 [11.7] years; mean [SD] disease duration, 12.2 [9.5] years; P < .001), and severe-multidomain (mean [SD] age, 44.0 [11.0] years; mean [SD] disease duration, 13.3 [10.2] years; P < .001) phenotypes. Severe cognitive phenotypes prevailed in patients with progressive MS. At MRI evaluation, compared with those with preserved cognition, patients with mild-verbal memory/semantic fluency exhibited decreased mean (SE) hippocampal volume (5.42 [0.68] mL vs 5.13 [0.68] mL; P = .04), patients with the mild-multidomain phenotype had decreased mean (SE) cortical gray matter volume (687.69 [35.40] mL vs 662.59 [35.48] mL; P = .02), patients with severe-executive/attention had higher mean (SE) T2-hyperintense lesion volume (51.33 [31.15] mL vs 99.69 [34.07] mL; P = .04), and patients with the severe-multidomain phenotype had extensive brain damage, with decreased volume in all the brain structures explored, except for nucleus pallidus, amygdala and caudate nucleus. This study found that by defining homogeneous and clinically meaningful phenotypes, the limitations of the traditional dichotomous classification in MS can be overcome. These phenotypes can represent a more meaningful measure of the cognitive status of patients with MS and can help define clinical disability, support clinicians in treatment choices, and tailor cognitive rehabilitation strategies.

Cognitive phenotypes and their functional differences in the honey bee, Apis mellifera

Interindividual variation in cognitive ability has been widely reported across a diverse array of taxa and has recently been modelled as a broad consequence of a speed–accuracy trade-off. This trade-off can result in alternative cognitive phenotypes, which in turn could be associated with differences in behavioural and life history traits. While a growing body of literature suggests that performance in certain cognitive and behavioural traits do covary, multiple traits must be measured at these different levels to understand how differences in cognition determine variation in other traits. We tested for the presence of distinct cognitive phenotypes in the honey bee, Apis mellifera, by measuring multiple cognitive traits and determining whether these traits covary in a manner that can be used to define a cognitive axis. Our results indicate the presence of two distinct cognitive phenotypes that meet the predictions of the speed–accuracy trade-off such that fast bees are described by high associative learning, high preference for novelty and high preference for variance, compared to slow bees, and that these differences are consistent across colonies. We then determined whether there were functional differences between these two cognitive phenotypes by measuring their performance in several behavioural and life history traits. We found that fast bees also engaged in more nursing behaviour and transitioned to becoming foragers at an earlier age but we detected no difference in their social behaviour or survival. We discuss our results in terms of their possible implications for social behaviour and the pace-of-life hypothesis.

Identifying subtypes of mild cognitive impairment in Parkinson's disease using cluster analysis.

The concept of Mild Cognitive Impairment (MCI) in Parkinson's disease (PD) has shown the potential for identifying at-risk dementia patients. Identifying subtypes of MCI is likely to assist therapeutic discoveries and better clinical management of patients with PD (PWP). Recent cluster-based approaches have demonstrated dominance in memory and executive impairment in PD. The present study will further explore the role of memory and executive impairment and associated clinical features in non-demented PWP. A K-means cluster analysis was performed on ten "frontal" and "posterior" cognitive variables derived from a dataset of 85 non-demented PWP. The resulting cluster structure was chosen based on quantitative, qualitative, theoretical, and clinical validity. Cluster profiles were then created through statistical analysis of cognitive and clinical/demographic variables. A descriptive analysis of each cluster's performance on a comprehensive PD-MCI diagnostic battery was also explored. The resulting cluster structure revealed four distinct cognitive phenotypes: (1) frontal-dominant impairment; (2) posterior-cortical-dominant impairment; (3) global impairment, and (4) cognitively intact. Demographic profiling revealed significant differences in the age, gender split, global cognitive ability, and motor symptoms between these clusters. However, there were no significant differences between the clusters on measures of depression, apathy, and anxiety. These results validate the existence of distinct cognitive phenotypes within PD-MCI and encourage future research into their clinical trajectory and neuroimaging correlates.

Trajectory Analysis of Cognitive Outcomes in Children With Perinatal HIV.

Children with perinatal HIV (pHIV) may display distinct long-term cognitive phenotypes. We used group-based trajectory modeling to identify clusters of children with pHIV after similar developmental trajectories and predictors of belonging to select cognitive trajectory groups. Participants included children, 4-17 years of age, with pHIV in Thailand and Cambodia. Cognitive measures included translated versions of Intelligence Quotient tests, Color Trails Tests and Beery-Buktenica Developmental Test of Visual-Motor Integration conducted semiannually over 3-6 years. The best fit of trajectory groups was determined using maximum likelihood estimation. Multivariate logistic regression identified baseline factors associated with belonging to the lowest scoring trajectory group. Group-based trajectory analyses revealed a 3-cluster classification for each cognitive test, labeled as high, medium and low scoring groups. Most trajectory group scores remained stable across age. Verbal IQ declined in all 3 trajectory groups and the high scoring group for Children's Color Trails Test 1 and 2 showed an increase in scores across age. Children in the lowest scoring trajectory group were more likely to present at an older age and report lower household income. Group-based trajectory modeling succinctly classifies cohort heterogeneity in cognitive outcomes in pHIV. Most trajectories remained stable across age suggesting that cognitive potential is likely determined at an early age with the exception of a small subgroup of children who displayed developmental gains in select cognitive domains and may represent those with better cognitive reserve. Poverty and longer duration of untreated HIV may predispose children with pHIV to suboptimal cognitive development.

Cognitive Trajectory Phenotypes in Human Immunodeficiency Virus-Infected Patients.

The presentation of cognitive impairments in HIV-infected individuals has transformed since the introduction of antiretroviral therapies. Although the overall prevalence of cognitive impairments has not changed considerably, frank dementia is now infrequent, and milder forms of cognitive impairments predominate. Mechanistic insights to the underlying causes of these residual cognitive impairments have been elusive, in part due to the heterogenous etiology of cognitive dysfunction in this population. Here, we sought to categorize longitudinal change in HIV-infected patients based on the performance in specific cognitive domains. This study consisted of 193 participants from the CHARTER cohort with detailed demographic, clinical, and neuropsychological testing data obtained from 2 study visits interspersed by ∼6 months. Cognitive testing assessed executive function, learning and delayed recall, working memory, verbal fluency, speed of information processing, and motor skills. Change scores were calculated for each domain between the 2 study visits. Dimension reduction and clustering was accomplished by principal component analysis of change scores and k-means clustering to identify cognitive domains that group together and groups of subjects with similar patterns of change. We identified 4 distinct cognitive change phenotypes that included declines in: (1) verbal fluency, (2) executive function (3) learning and recall, and (4) motor function, with approximately equal numbers of participants in each phenotype. Each of the 4 cognitive change phenotypes identify deficits that imply perturbations in specific neural networks. Future studies will need to validate if cognitive change phenotypes are associated with alterations in associated neural pathways.

Exploring Heterogeneity on the Wisconsin Card Sorting Test in Schizophrenia Spectrum Disorders: A Cluster Analytical Investigation.

The Wisconsin Card Sorting Test (WCST) is a complex measure of executive function that is frequently employed to investigate the schizophrenia spectrum. The successful completion of the task requires the interaction of multiple intact executive processes, including attention, inhibition, cognitive flexibility, and concept formation. Considerable cognitive heterogeneity exists among the schizophrenia spectrum population, with substantive evidence to support the existence of distinct cognitive phenotypes. The within-group performance heterogeneity of individuals with schizophrenia spectrum disorder (SSD) on the WCST has yet to be investigated. A data-driven cluster analysis was performed to characterise WCST performance heterogeneity. Hierarchical cluster analysis with k-means optimisation was employed to identify homogenous subgroups in a sample of 210 schizophrenia spectrum participants. Emergent clusters were then compared to each other and a group of 194 healthy controls (HC) on WCST performance and demographic/clinical variables. Three clusters emerged and were validated via altered design iterations. Clusters were deemed to reflect a relatively intact patient subgroup, a moderately impaired patient subgroup, and a severely impaired patient subgroup. Considerable within-group heterogeneity exists on the WCST. Identification of subgroups of patients who exhibit homogenous performance on measures of executive functioning may assist in optimising cognitive interventions. Previous associations found using the WCST among schizophrenia spectrum participants should be reappraised. (JINS, 2019, 25, 750-760).

Temporal lobe epilepsy is associated with distinct cognitive phenotypes

Neuropsychological assessment is critical for understanding the impact of seizures on cognition and informing treatment decisions. While focus is often placed on examining groups based on seizure type/epilepsy syndrome, an alternate approach emphasizes empirically derived groups based solely on cognitive performance. This approach has been used to identify cognitive phenotypes in temporal lobe epilepsy (TLE). The current study sought to replicate prior work by Hermann and colleagues (2007) and identify cognitive phenotypes in a separate, larger cohort of 185 patients with TLE (92 left TLE, 93 right TLE). Cluster analysis revealed 3- and 4-cluster solutions, with clusters differentiated primarily by overall level of performance in the 3-cluster solution (Low, Middle, and High performance) and by more varying cognitive phenotypes in the 4-cluster solution (Globally Low, Low Executive Functioning/Speed, Low Language/Memory, and Globally High). Differences in cognitive performance as well as demographic and clinical seizure variables are presented. A greater proportion of the patients with left TLE were captured by Cluster 3 (Low Language/Memory) than by the other 3 clusters, though this cluster captured only approximately one-third of the overall group with left TLE. Consistent with prior findings, executive functioning and speed emerged as additional domains of interest in this sample of patients with TLE. The current results extend prior work examining cognitive phenotypes in TLE and highlight the importance of identifying the comprehensive range of potential cognitive profiles in TLE.

Cognitive phenotypes in temporal lobe epilepsy are associated with distinct patterns of white matter network abnormalities.

To identify distinct cognitive phenotypes in temporal lobe epilepsy (TLE) and evaluate patterns of white matter (WM) network alterations associated with each phenotype. Seventy patients with TLE were characterized into 4 distinct cognitive phenotypes based on patterns of impairment in language and verbal memory measures (language and memory impaired, memory impaired only, language impaired only, no impairment). Diffusion tensor imaging was obtained in all patients and in 46 healthy controls (HC). Fractional anisotropy (FA) and mean diffusivity (MD) of the WM directly beneath neocortex (i.e., superficial WM [SWM]) and of deep WM tracts associated with memory and language were calculated for each phenotype. Regional and network-based SWM analyses were performed across phenotypes. The language and memory impaired group and the memory impaired group showed distinct patterns of microstructural abnormalities in SWM relative to HC. In addition, the language and memory impaired group showed widespread alterations in WM tracts and altered global SWM network topology. Patients with isolated language impairment exhibited poor network structure within perisylvian cortex, despite relatively intact global SWM network structure, whereas patients with no impairment appeared similar to HC across all measures. These findings demonstrate a differential pattern of WM microstructural abnormalities across distinct cognitive phenotypes in TLE that can be appreciated at both the regional and network levels. These findings not only help to unravel the underlying neurobiology associated with cognitive impairment in TLE, but they could also aid in establishing cognitive taxonomies or in the prediction of cognitive course in TLE.

Neural correlates of distinct cognitive phenotypes in early Parkinson's disease

ObjectiveCognitive decline is common in Parkinson's disease (PD), but changes can occur in a variety of cognitive domains. The lack of a single cognitive phenotype complicates diagnosis and tracking. In an earlier study we used a data-driven approach to identify distinct cognitive phenotypes of early PD. Here we identify the morphometric brain differences between those different phenotypes compared with cognitively normal PD participants. MethodsSix different cognitive classes were included (Weak, Typical, Weak-Visuospatial/Strong-Memory, Weak-Visuospatial, Amnestic, Strong). Structural differences between each class and the Typical class were assessed by deformation-based morphometry. ResultsThe different groups evidenced different patterns of atrophy. Weak class had frontotemporal and insular atrophy; Weak-Visuospatial/Strong-Memory class had frontotemporal, insular, parietal, and putamen atrophy; Weak-Visuospatial class had Rolandic operculum; Amnestic class had left frontotemporal, occipital, parietal and insular atrophy when compared to the Typical class. The Strong class did not have any atrophy but had significant differences in left temporal cortex in comparison to the Typical class. ConclusionsStructural neuroimaging differences are evident in PD patients with distinct cognitive phenotypes even very early in the disease process prior to the emergence of frank cognitive impairment. Future studies will elucidate whether these have prognostic value in identifying trajectories toward dementia, or if they represent groups sensitive to different treatments.

Cluster analysis of cognitive performance in a sample of patients with Parkinson's disease.

BackgroundCognitive impairment is a common feature of Parkinson's disease (PD). The diagnoses of mild cognitive impairment (MCI) in patients with PD implies an increased risk for later development of dementia, however, it is unclear whether a specific type of cognitive loss confers increased risk for faster cognitive decline.ObjectiveDetermine whether it was possible to identify distinct cognitive phenotypes in a sample of patients with PD.MethodsA cross-sectional evaluation of 100 patients with PD recruited from a movement disorders clinic was conducted. The patients were evaluated using the simplified motor score of the UPDRS, the Hoehn and Yahr, Schwab and England, Geriatric Depression Scale, Pfeffer Functional Activities Questionnaire, Clinical Dementia Rating Scale, Mini-Mental State Examination, clock drawing test, digit span, word list battery of CERAD, Frontal Assessment Battery and verbal fluency test. We classified the patients as having normal cognition (PDNC), MCI (PDMCI) or dementia (PDD). Data were analyzed using the chi-square test, non-parametric statistics and cluster analysis.ResultsThere were 40 patients with PDD, 39 with PDMCI and 21 with PDNC. Patients with PDD were older, had longer disease duration, lower education and lower MMSE scores. Cluster analysis showed 3 general distinct cognitive profiles that represented a continuum from mild to severe impairment of cognition, without distinguishing specific cognitive profiles.ConclusionCognitive impairment in PD occurs progressively and heterogeneously in most patients. It is unclear whether the definition of the initial phenotype of cognitive loss can be used to establish the cognitive prognosis of patients.