Group-level Comparisons Research Articles

Abnormal resting-state functional connectivity of the right anterior cingulate cortex in chronic ketamine users and its correlation with cognitive impairments

BackgroundChronic ketamine use leads to cognitive impairments, however, the neural mechanisms underpinning these impairments are still unclear. AimsMany studies showed Anterior cingulate cortex (ACC)is strongly involved in cognition and drug addiction, as supported by our previous studies. The objective of this study was to assess the variations in resting-state functional connectivity (FC) changes in the right anterior cingulate cortex (ACC) of chronic ketamine users (CKUs) and their relationship with cognitive performance. MethodsThe study enrolled 28 chronic ketamine users (CKUs) and 30 healthy controls (HCs). Resting-state functional magnetic resonance imaging (fMRI) data were gathered from both groups. Cognitive functions were evaluated using the MATRICS Consensus Cognitive Battery (MCCB). ResultsCKUs demonstrated significantly poorer cognitive performance than HCs in various cognitive domains, including Visual Learning, Speed of Processing, Working Memory, and the composite score of MCCB. Group-level comparisons revealed that CKUs exhibited enhanced functional connectivity between the right ACC and the right postcentral gyrus (PCG) compared to HCs. There was a positive relationship between the connectivity of right ACC-PCG and reasoning and problem-solving score, but there was no significant association with the characteristics of ketamine use. ConclusionCKUs showed enhanced connectivity between the right ACC and the right PCG. This enhanced functional connectivity may indicate functional compensation for cognitive deficits in CKUs, especially for reasoning and problem-solving impairments in CKUs.

Task-based functional neural correlates of social cognition across autism and schizophrenia spectrum disorders

BackgroundAutism and schizophrenia spectrum disorders (SSDs) both feature atypical social cognition. Despite evidence for comparable group-level performance in lower-level emotion processing and higher-level mentalizing, limited research has examined the neural basis of social cognition across these conditions. Our goal was to compare the neural correlates of social cognition in autism, SSDs, and typically developing controls (TDCs).MethodsData came from two harmonized studies in individuals diagnosed with autism or SSDs and TDCs (aged 16–35 years), including behavioral social cognitive metrics and two functional magnetic resonance imaging (fMRI) tasks: a social mirroring Imitate/Observe (ImObs) task and the Empathic Accuracy (EA) task. Group-level comparisons, and transdiagnostic analyses incorporating social cognitive performance, were run using FSL’s PALM for each task, covarying for age and sex (1000 permutations, thresholded at p < 0.05 FWE-corrected). Exploratory region of interest (ROI)-based analyses were also conducted.ResultsImObs and EA analyses included 164 and 174 participants, respectively (autism N = 56/59, SSD N = 50/56, TDC N = 58/59). EA and both lower- and higher-level social cognition scores differed across groups. While canonical social cognitive networks were activated, no significant whole-brain or ROI-based group-level differences in neural correlates for either task were detected. Transdiagnostically, neural activity during the EA task, but not the ImObs task, was associated with lower- and higher-level social cognitive performance.LimitationsDespite attempting to match our groups on age, sex, and race, significant group differences remained. Power to detect regional brain differences is also influenced by sample size and multiple comparisons in whole-brain analyses. Our findings may not generalize to autism and SSD individuals with co-occurring intellectual disabilities.ConclusionsThe lack of whole-brain and ROI-based group-level differences identified and the dimensional EA brain-behavior relationship observed across our sample suggest that the EA task may be well-suited to target engagement in novel intervention testing. Our results also emphasize the potential utility of cross-condition approaches to better understand social cognition across autism and SSDs.

Personality matters – The interplay between consistent individual differences and mouse welfare in female C57BL6/J mice

To ensure good welfare of animals in human hands, it is essential to modify housing conditions according to the animals’ needs. Traditionally, the effects of such modifications are studied by means of group-level comparisons, thereby widely neglecting consistent inter-individual differences (i.e., so-called ‘animal personalities’). However, as animals with distinct personality types might differ in their environmental needs and hence react differently to the same environment, such systematic inter-individual differences might have important welfare consequences. This becomes particularly apparent under laboratory conditions, where animals are typically housed under highly standardized and barren environments. Against this background, we here aim to investigate personality-dependent welfare consequences in response to different housing conditions in laboratory mice. Female C57BL/6J mice were characterized for their personality type in exploration behavior and the most and the least explorative individuals were set up in either simple or in highly complex housing conditions that included constantly changing environmental enrichment items. We monitored individual welfare by studying behavioral, physiological, and immunological outcome measures. Besides personality-dependent differences in immune parameters and overall improved welfare under complex housing conditions, we indeed found hints that individual mice were differently affected in their welfare depending on the specific combination of personality type and housing condition. Specifically, highly explorative mice appeared to be more adversely affected by simple housing, but also profited more from complex housing compared to low explorative mice. These findings indicate that welfare promoting adjustments do not necessarily benefit all individuals equally and therefore, call for a shift of perspectives in the evaluation of animal welfare.

Brain dynamics supported by a hierarchy of complex correlation patterns defining a robust functional architecture

Functional magnetic resonance imaging (fMRI) provides insights into cognitive processes with significant clinical potential. However, delays in brain region communication and dynamic variations are often overlooked in functional network studies. We demonstrate that networks extracted from fMRI cross-correlation matrices, considering time lags between signals, show remarkable reliability when focusing on statistical distributions of network properties. This reveals a robust brain functional connectivity pattern, featuring a sparse backbone of strong 0-lag correlations and weaker links capturing coordination at various time delays. This dynamic yet stable network architecture is consistent across rats, marmosets, and humans, as well as in electroencephalogram (EEG) data, indicating potential universality in brain dynamics. Second-order properties of the dynamic functional network reveal a remarkably stable hierarchy of functional correlations in both group-level comparisons and test-retest analyses. Validation using alcohol use disorder fMRI data uncovers broader shifts in network properties than previously reported, demonstrating the potential of this method for identifying disease biomarkers.

Cognitive outcome after stereo-electroencephalography-guided radiofrequency thermocoagulation in temporal lobe epilepsy.

Stereo-electroencephalography (SEEG)-guided radiofrequency thermocoagulation (RFTC) is being used incrementally in the invasive diagnosis of epilepsy. There is currently a lack of information regarding the potential cognitive consequences of the extended use of this technique. This work describes, for the first time, the cognitive outcomes after RFTC in patients with temporal lobe epilepsy (TLE), evaluated longitudinally and using a control group. Forty-eight adult patients with drug-resistant unilateral TLE (30 RFTC-treated patients and 18 controls) were evaluated using a comprehensive neuropsychological protocol at baseline. In the RFTC group, two follow-up assessments were performed at 3 months and 1 year. The control group was reevaluated after 1 year. Two analyses were performed: 1) group-level analyses, in which linear mixed models were applied according to TLE lateralization (intragroup and intergroup [RFTC vs control] comparisons), and 2) individual-level analyses, in which the Reliable Change Index (RCI) algorithm was developed and a 90% CI (cutoff ± 1.64) was used to describe neuropsychological outcomes at 1 year post-RFTC. A memory subanalysis was performed in hippocampal RFTC patients (25/30). A Spearman coefficient study was conducted to determine the correlation between cognitive change and thermocoagulated contacts. Left- and right-sided TLE patients treated with RFTC showed cognitive preservation at baseline. At a group level, the short-term evaluation, including verbal and visual memory, language, and executive functions, showed preservation in these domains and no significant differences compared with baseline. In the long-term follow-up assessment (1 year after RFTC), no significant intragroup changes were found, nor were significant changes found in comparison with the control group. The RCI algorithm showed that significant individual cognitive losses and gains were infrequent. Three patients presented with naming deficits, only 1 (3.3%) of whom showed a clinically significant deficit. Significant gains were more prevalent in executive function tests with a speed component (4/20 left-sided RFTC patients). Twenty-five of the 30 (83%) patients were treated with hippocampal RFTC. No patients experienced significant loss in verbal delayed memory in the left-sided RFTC sample or in visual delayed memory in the right-sided RFTC sample. The correlations between cognitive change and RFTC contacts were mostly nonsignificant. In the group-level comparisons, discernible cognitive impairment following RFTC was not evidenced. The majority of patients did not exhibit significant individual declines during the 1-year follow-up period. Notably, the procedural intervention yielded no substantial repercussions on memory functioning following hippocampal RFTC. These findings underscore the evidence supporting the cognitive preservation associated with SEEG-guided RFTC.

The impact of CSF-filled cavities on scalp EEG and its implications.

Previous studies have found electroencephalogram (EEG) amplitude and scalp topography differences between neurotypical and neurological/neurosurgical groups, being interpreted at the cognitive level. However, these comparisons are invariably accompanied by anatomical changes. Critical to EEG are the so-called volume currents, which are affected by the spatial distribution of the different tissues in the head. We investigated the effect of cerebrospinal fluid (CSF)-filled cavities on simulated EEG scalp data. We simulated EEG scalp potentials for known sources using different volume conduction models: a reference model (i.e., unlesioned brain) and models with realistic CSF-filled cavities gradually increasing in size. We used this approach for a single source close or far from the CSF-lesion cavity, and for a scenario with a distributed configuration of sources (i.e., a "cognitive event-related potential effect"). The magnitude and topography errors between the reference and lesion models were quantified. For the single-source simulation close to the lesion, the CSF-filled lesion modulated signal amplitude with more than 17% magnitude error and topography with more than 9% topographical error. Negligible modulation was found for the single source far from the lesion. For the multisource simulations of the cognitive effect, the CSF-filled lesion modulated signal amplitude with more than 6% magnitude error and topography with more than 16% topography error in a nonmonotonic fashion. In conclusion, the impact of a CSF-filled cavity cannot be neglected for scalp-level EEG data. Especially when group-level comparisons are made, any scalp-level attenuated, aberrant, or absent effects are difficult to interpret without considering the confounding effect of CSF.

Impaired topology and connectivity of grey matter structural networks in major depressive disorder: evidence from a multi-site neuroimaging data-set.

Major depressive disorder (MDD) has been increasingly understood as a disruption of brain connectome. Investigating grey matter structural networks with a large sample size can provide valuable insights into the structural basis of network-level neuropathological underpinnings of MDD. Using a multisite MRI data-set including nearly 2000 individuals, this study aimed to identify robust topology and connectivity abnormalities of grey matter structural network linked to MDD and relevant clinical phenotypes. A total of 955 MDD patients and 1009 healthy controls were included from 23 sites. Individualised structural covariance networks (SCN) were established based on grey matter volume maps. Following data harmonisation, network topological metrics and focal connectivity were examined for group-level comparisons, individual-level classification performance and association with clinical ratings. Various validation strategies were applied to confirm the reliability of findings. Compared with healthy controls, MDD individuals exhibited increased global efficiency, abnormal regional centralities (i.e. thalamus, precentral gyrus, middle cingulate cortex and default mode network) and altered circuit connectivity (i.e. ventral attention network and frontoparietal network). First-episode drug-naive and recurrent patients exhibited different patterns of deficits in network topology and connectivity. In addition, the individual-level classification of topological metrics outperforms that of structural connectivity. The thalamus-insula connectivity was positively associated with the severity of depressive symptoms. Based on this high-powered data-set, we identified reliable patterns of impaired topology and connectivity of individualised SCN in MDD and relevant subtypes, which adds to the current understanding of neuropathology of MDD and might guide future development of diagnostic and therapeutic markers.

The Rhinoplasty Rosetta Stone: Using Rasch Analysis to Create and Validate Crosswalks between the NOSE and the SCHNOS Functional Subscale.

The Nasal Obstruction Symptom Evaluation (NOSE) and the Functional subscale of the Standardized Cosmesis and Health Nasal Outcomes Survey (SCHNOS-O) are widely used patient-reported outcome measures to measure functional outcomes of rhinoplasty. However, as different instruments produce scores on different metrics, results of these instruments cannot be linked directly, thus hindering comparison and aggregating of rhinoplasty outcome data from practices using either instrument. The aim of this study was to develop and validate crosswalks between the NOSE and the SCHNOS-O. In a sample of 552 rhinoplasty patients who completed both instruments, the NOSE and SCHNOS-O scales were co-calibrated onto a common interval-scaled metric using Rasch analysis. Separate Rasch models were run per instrument, and the latent constructs were estimated using the calibrated item parameters. By anchoring original patient-reported outcome measure scores of both instruments to this Rasch computed measurement scale, the scores of both instruments were linked. A second independent sample was used to validate the created crosswalks. Total scores on the NOSE and SCHNOS-O were strongly correlated. The Rasch-based co-calibration of the NOSE and SCHNOS-O items resulted in a model that adequately fitted the data. Back-and-forth crosswalk tables were created from the NOSE to the SCHNOS-O. For patients with moderate nasal obstruction, predicted SCHNOS-O scores were slightly higher for a given level of the NOSE. Intraclass correlation coefficients between predicted and actual scores were 0.93 for both directions, indicating adequate agreement for group-level comparisons. This study developed and validated Rasch-based crosswalks from the NOSE to the SCHNOS-O and vice versa. The provided crosswalks enhance comparison and harmonization of functional rhinoplasty outcomes.

A Systematic Review of the Single-Item Burnout Question: Its Reliability Depends on Your Purpose.

Surveillance of burnout by the gold-standard Maslach Burnout Inventory (MBI) is hindered by cost and length. The validity and benchmarking of the commonly recommended and used single-item burnout question (SIBOQ) are unknown. We sought to (1) derive an equation for predicting the gold standard MBI from the SIBOQ and (2) measure the correlation of the SIBOQ with the full MBI and its subscales. We sought studies in PubMed along with citations by and to included studies. We included studies that either correlated the SIBOQ and the MBI or reported the rates of burnout measured by both instruments. Two reviewers extracted data and CLARITY risk of bias. We used generalized linear mixed regression to separately quantify the predictive (benchmarking) and explanatory (hot-spotting) capabilities of the SIBOQ. We created a regression equation for converting SIBOQ scores to MBI scores. We meta-analyzed correlation coefficients (r) for the SIBOQ and MBI subscales. For all analyses, we considered an r of 0.7 as acceptable reliability for group-level comparisons. We included 17 studies reporting 6788 respondents. All studies had a high risk of bias, as no study had a response rate over 75% and no study was able to examine non-responders. The correlations (r) of the SIBOQ with the overall MBI were explanatory r = 0.82 and predictive r = 0.56. Regarding MBI subscales, the correlations of the SIBOQ with emotional exhaustion were adequate with r = 0.71 (95% CI 0.67-0.74; I2 = 89%), and depersonalization was r = 0.44 (95% CI 0.34-0.52; I2 = 90%). However, in 8 of 15 comparisons, the r was less than 0.70. The SIBOQ's usually adequate explanatory abilities allow "hot-spotting" to identify subgroups with high or low burnout within a single, homogenous survey fielding. However, the predictive ability of the SIBOQ indicates insufficient reliability in comparing local results to external benchmarks.

Capturing individual differences in sentence processing: How reliable is the self-paced reading task?

Advances in research on language processing have originally come from group-level comparisons, but there is now a growing interest in individual differences. To investigate individual differences, tasks that have shown robust group-level differences are often used with the implicit assumption that they will also be reliable when used as an individual differences measure. Here, we examined whether one of the primary tasks used in psycholinguistic research on language processing, the self-paced reading task, can reliably measure individual differences in relative clause processing. We replicated the well-established effects of relative clauses at the group level, with object relative clauses being more difficult to process than subject relative clauses. However, when using difference scores, the reliability of the size of the relative clause effect was close to zero because the self-paced reading times for the different relative clause types were highly correlated within individuals. Nonetheless, we found that the self-paced reading task can be used to reliably capture individual differences in overall reading speed as well as key sentence regions when the two types of relative clause sentences are considered separately. Our results indicate that both the reliability and validity of different sentence regions need to be assessed to determine whether and when self-paced reading can be used to examine individual differences in language processing.

Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression

It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.

Mapping of the PROMIS global health measure to the PROPr in the United States

BackgroundThe Patient-Reported Outcomes Measurement and Information System (PROMIS®) global health items (global-10) yield physical and mental health scale scores and the PROMIS-Preference (PROPr) scoring system estimated from PROMIS domain scores (e.g., PROMIS-29 + 2) produces a single score anchored by 0 (dead or as bad as being dead) to 1 (full health). A link between the PROMIS global-10 and the PROPr is needed.MethodsThe PROMIS-29 + 2 and the PROMIS global-10 were administered to 4102 adults in the Ipsos KnowledgePanel in 2022. The median age was 52 (range 18–94), 50% were female, 70% were non-Hispanic White, and 64% were married or living with a partner. The highest level of education completed for 26% of the sample was a high school degree or general education diploma and 44% worked full-time. We estimated correlations of the PROPr with the PROMIS global health items and the global physical and mental health scales. We examined the adjusted R2 and estimated correlations between predicted and observed PROPr scores.ResultsProduct-moment correlations between the PROMIS global health items and the PROPr ranged from 0.50 to 0.63. The PROMIS global physical health and mental health scale scores correlated 0.74 and 0.60, respectively, with the PROPr. The adjusted R2 in the regression of the PROPr on the PROMIS global health items was 64%. The equated PROPr preference scores correlated (product-moment) 0.80 (n = 4043; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation (two-way random effects model) was 0.80. The normalized mean absolute error (NMAE) was 0.45 (SD = 0.43). The adjusted R2 in the OLS regression of the PROPr on the PROMIS global health scales was 59%. The equated PROPr preference scores correlated (product-moment) was 0.77 (n = 4046; p < 0.0001) with the observed PROPr preference scores, and the intra-class correlation was 0.77. The NMAE was 0.49 (SD = 0.45).ConclusionsRegression equations provide a reasonably accurate estimate of the PROPr preference-based score from the PROMIS global health items or scales for group-level comparisons. These estimates facilitate cost-effectiveness research and meta-analyses. The estimated PROPr scores are not accurate enough for individual-level applications. Future evaluations of the prediction equations are needed.

Neurocognitive correlates of semantic memory navigation in Parkinson’s disease

Cognitive studies on Parkinson’s disease (PD) reveal abnormal semantic processing. Most research, however, fails to indicate which conceptual properties are most affected and capture patients’ neurocognitive profiles. Here, we asked persons with PD, healthy controls, and individuals with behavioral variant frontotemporal dementia (bvFTD, as a disease control group) to read concepts (e.g., ‘sun’) and list their features (e.g., hot). Responses were analyzed in terms of ten word properties (including concreteness, imageability, and semantic variability), used for group-level comparisons, subject-level classification, and brain-behavior correlations. PD (but not bvFTD) patients produced more concrete and imageable words than controls, both patterns being associated with overall cognitive status. PD and bvFTD patients showed reduced semantic variability, an anomaly which predicted semantic inhibition outcomes. Word-property patterns robustly classified PD (but not bvFTD) patients and correlated with disease-specific hypoconnectivity along the sensorimotor and salience networks. Fine-grained semantic assessments, then, can reveal distinct neurocognitive signatures of PD.

Heterogeneity in children's reading comprehension difficulties: A latent class approach.

Poor comprehenders are traditionally identified as having below-average reading comprehension, average-range word reading, and a discrepancy between the two. While oral language tends to be low in poor comprehenders, reading is a complex trait and heterogeneity may go undetected by group-level comparisons. We took a preregistered data-driven approach to identify poor comprehenders and examine whether multiple distinct cognitive profiles underlie their difficulties. Latent mixture modelling identified reading profiles in 6846 children from the Avon Longitudinal Study of Parents and Children, based on reading and listening comprehension assessments at 8-9years. A second mixture model examined variation in the cognitive profiles of weak comprehenders, using measures of reading, language, working memory, nonverbal ability, and inattention. A poor comprehender profile was not identified by the preregistered model. However, by additionally controlling for overall ability, a 6-class model emerged that incorporated a profile with relatively weak comprehension (N=947, 13.83%). Most of these children had weak reading comprehension in the context of good passage reading, accompanied by weaknesses in vocabulary and nonverbal ability. A small subgroup showed more severe comprehension difficulties in the context of additional cognitive impairments. Isolated impairments in specific components of reading are rare, yet a data-driven approach can be used to identify children with relatively weak comprehension. Vocabulary and nonverbal ability were most consistently weak within this group, with broader cognitive difficulties also apparent for a subset of children. These findings suggest that poor comprehension is best characterised along a continuum, and considered in light of multiple risks that influence severity.

Identifying relevant diffusion MRI microstructure biomarkers relating to exposure to repeated head impacts in contact sport athletes.

Repeated head impacts (RHI) without concussion may cause long-term sequelae. A growing array of diffusion MRI metrics exist, both empiric and modeled and it is hard to know which are potentially important biomarkers. Common conventional statistical methods fail to consider interactions between metrics and rely on group-level comparisons. This study uses a classification pipeline as a means towards identifying important diffusion metrics associated with subconcussive RHI. 36 collegiate contact sport athletes and 45 non-contact sport controls from FITBIR CARE were included. Regional/whole brain WM statistics were computed from 7 diffusion metrics. Wrapper-based feature selection was applied to 5 classifiers representing a range of learning capacities. Best 2 classifiers were interpreted to identify the most RHI-related diffusion metrics. Mean diffusivity (MD) and mean kurtosis (MK) are found to be the most important metrics for discriminating between athletes with and without RHI exposure history. Regional features outperformed global statistics. Linear approaches outperformed non-linear approaches with good generalizability (test AUC 0.80-0.81). Feature selection and classification identifies diffusion metrics that characterize subconcussive RHI. Linear classifiers yield the best performance and mean diffusion, tissue microstructure complexity, and radial extra-axonal compartment diffusion (MD, MK, De,⊥) are found to be the most influential metrics. This work provides proof of concept that applying such approach to small, multidimensional dataset can be successful given attention to optimizing learning capacity without overfitting and serves an example of methods that lead to better understanding of the myriad of diffusion metrics as they relate to injury and disease.

Effects of clinical, comorbid, and social determinants of health on brain ageing in people with and without HIV: a retrospective case-control study.

Neuroimaging reveals structural brain changes linked with HIV infection and related neurocognitive disorders; however, group-level comparisons between people with HIV and people without HIV do not account for within-group heterogeneity. The aim of this study was to quantify the effects of comorbidities such as cardiovascular disease and adverse social determinants of health on brain ageing in people with HIV and people without HIV. In this retrospective case-control study, people with HIV from Washington University in St Louis, MO, USA, and people without HIV identified through community organisations or the Research Participant Registry were clinically characterised and underwent 3-Tesla T1-weighted MRI between Dec 3, 2008, and Oct 4, 2022. Exclusion criteria were established by a combination of self-reports and medical records. DeepBrainNet, a publicly available machine learning algorithm, was applied to estimate brain-predicted age from MRI for people with HIV and people without HIV. The brain-age gap, defined as the difference between brain-predicted age and true chronological age, was modelled as a function of clinical, comorbid, and social factors by use of linear regression. Variables were first examined singly for associations with brain-age gap, then combined into multivariate models with best-subsets variable selection. In people with HIV (mean age 44·8 years [SD 15·5]; 78% [296 of 379] male; 69% [260] Black; 78% [295] undetectable viral load), brain-age gap was associated with Framingham cardiovascular risk score (p=0·0034), detectable viral load (>50 copies per mL; p=0·0023), and hepatitis C co-infection (p=0·0065). After variable selection, the final model for people with HIV retained Framingham score, hepatitis C, and added unemployment (p=0·0015). Educational achievement assayed by reading proficiency was linked with reduced brain-age gap (p=0·016) for people without HIV but not for people with HIV, indicating a potential resilience factor. When people with HIV and people without HIV were modelled jointly, selection resulted in a model containing cardiovascular risk (p=0·0039), hepatitis C (p=0·037), Area Deprivation Index (p=0·033), and unemployment (p=0·00010). Male sex (p=0·078) and alcohol use history (p=0·090) were also included in the model but were not individually significant. Our findings indicate that comorbid and social determinants of health are associated with brain ageing in people with HIV, alongside traditional HIV metrics such as viral load and CD4 cell count, suggesting the need for a broadened clinical perspective on healthy ageing with HIV, with additional focus on comorbidities, lifestyle changes, and social factors. National Institute of Mental Health, National Institute of Nursing Research, and National Institute of Drug Abuse.

Comparison of evoked potentials across four related developmental encephalopathies

BackgroundDeveloping biomarkers is a priority for drug development for all conditions, but vital in the rare neurodevelopmental disorders where sensitive outcome measures are lacking. We have previously demonstrated the feasibility and tracking of evoked potentials to disease severity in Rett syndrome and CDKL5 deficiency disorder. The aim of the current study is to characterize evoked potentials in two related developmental encephalopathies, MECP2 duplication syndrome and FOXG1 syndrome, and compare across all four groups to better understand the potential of these measures to serve as biomarkers of clinical severity for the developmental encephalopathies.MethodsVisual and auditory evoked potentials were acquired from participants with MECP2 duplication syndrome and FOXG1 syndrome across five sites of the Rett Syndrome and Rett-Related Disorders Natural History Study. A group of age-matched individuals (mean = 7.8 years; range = 1–17) with Rett syndrome, CDKL5 deficiency disorder, and typically-developing participants served as a comparison group. The analysis focused on group-level differences as well as associations between the evoked potentials and measures of clinical severity from the Natural History Study.ResultsAs reported previously, group-level comparisons revealed attenuated visual evoked potentials (VEPs) in participants with Rett syndrome (n = 43) and CDKL5 deficiency disorder (n = 16) compared to typically-developing participants. VEP amplitude was also attenuated in participants with MECP2 duplication syndrome (n = 15) compared to the typically-developing group. VEP amplitude correlated with clinical severity for Rett syndrome and FOXG1 syndrome (n = 5). Auditory evoked potential (AEP) amplitude did not differ between groups, but AEP latency was prolonged in individuals with MECP2 duplication syndrome (n = 14) and FOXG1 syndrome (n = 6) compared to individuals with Rett syndrome (n = 51) and CDKL5 deficiency disorder (n = 14). AEP amplitude correlated with severity in Rett syndrome and CDKL5 deficiency disorder. AEP latency correlated with severity in CDKL5 deficiency disorder, MECP2 duplication syndrome, and FOXG1 syndrome.ConclusionsThere are consistent abnormalities in the evoked potentials in four developmental encephalopathies some of which correlate with clinical severity. While there are consistent changes amongst these four disorders, there are also condition specific findings that need to be further refined and validated. Overall, these results provide a foundation for further refinement of these measures for use in future clinical trials for these conditions.

Severity of in vivo corticospinal tract degeneration is associated with survival in amyotrophic lateral sclerosis: a longitudinal, multicohort study.

This study sought to evaluate the relationship of progressive corticospinal tract (CST) degeneration with survival in patients with amyotrophic lateral sclerosis (ALS). Forty-one ALS patients and 42 healthy controls were prospectively recruited from the Canadian ALS Neuroimaging Consortium. Magnetic resonance imaging scanning and clinical evaluations were performed on participants at three serial visits with 4-month intervals. Texture analysis was performed on T1-weighted magnetic resonance imaging scans and the texture feature 'autocorrelation' was quantified. Whole-brain group-level comparisons were performed between patient subgroups. Linear mixed models were used to evaluate longitudinal progression. Region-of-interest and 3D voxel-wise Cox proportional-hazards regression models were constructed for survival prediction. For all survival analyses, a second independent cohort was used for model validation. Autocorrelation of the bilateral CST was increased at baseline and progressively increased over time at a faster rate in ALS short survivors. Cox proportional-hazards regression analyses revealed autocorrelation of the CST as a significant predictor of survival at 5 years follow-up (hazard ratio 1.28, p=0.005). Similarly, voxel-wise whole-brain survival analyses revealed that increased autocorrelation of the CST was associated with shorter survival. ALS patients stratified by median autocorrelation in the CST had significantly different survival times using the Kaplan-Meier curve and log-rank tests (χ2 = 7.402, p =0.007). Severity of cerebral degeneration is associated with survival in ALS. CST degeneration progresses faster in subgroups of patients with shorter survival. Neuroimaging holds promise as a tool to improve patient management and facilitation of clinical trials.

Elastic shape analysis of brain structures for predictive modeling of PTSD.

It is well-known that morphological features in the brain undergo changes due to traumatic events and associated disorders such as post-traumatic stress disorder (PTSD). However, existing approaches typically offer group-level comparisons, and there are limited predictive approaches for modeling behavioral outcomes based on brain shape features that can account for heterogeneity in PTSD, which is of paramount interest. We propose a comprehensive shape analysis framework representing brain sub-structures, such as the hippocampus, amygdala, and putamen, as parameterized surfaces and quantifying their shape differences using an elastic shape metric. Under this metric, we compute shape summaries (mean, covariance, PCA) of brain sub-structures and represent individual brain shapes by their principal scores under a shape-PCA basis. These representations are rich enough to allow visualizations of full 3D structures and help understand localized changes. In order to validate the elastic shape analysis, we use the principal components (PCs) to reconstruct the brain structures and perform further evaluation by performing a regression analysis to model PTSD and trauma severity using the brain shapes represented via PCs and in conjunction with auxiliary exposure variables. We apply our method to data from the Grady Trauma Project (GTP), where the goal is to predict clinical measures of PTSD. The framework seamlessly integrates accurate morphological features and other clinical covariates to yield superior predictive performance when modeling PTSD outcomes. Compared to vertex-wise analysis and other widely applied shape analysis methods, the elastic shape analysis approach results in considerably higher reconstruction accuracy for the brain shape and reveals significantly greater predictive power. It also helps identify local deformations in brain shapes associated with PTSD severity.

Psychoeducational group intervention for intellectually able adults with autism and their close relations (Prisma) – an open feasibility study

BackgroundAutism spectrum disorder (ASD) in adulthood is associated with severe impairments in functioning and poor health, while ASD is also affecting close relations. Accessible first-line interventions addressing the complex clinical needs and care coordination are lacking.MethodsThis study investigated the feasibility and preliminary effects of a new psychoeducational intervention (Prisma) developed for intellectually able adults with ASD and their close relations in an outpatient setting. The manualized Prisma intervention consist of four weekly group sessions guided by trained group leaders and providing information about autism, support, and services. Feasibility was examined through treatment completion rate and group-level comparisons between intervention completers and non-completers (Student’s t-test, Fisher’s exact test, and Pearson’s chi-squared test). Perceived treatment credibility was investigated by within-group comparisons of participant’s self-ratings from pre-intervention to post-intervention, as well as by group leaders’ ratings using an adjusted questionnaire. Treatment satisfaction was examined quantitatively regarding the session evaluations (Student’s t-tests), as well as by a qualitative thematic analysis of participants’ feedback. Preliminary efficacy was studied using paired t-tests (pre- and post-intervention).ResultsCompletion rate was 77% (n = 71 of the 92 adults with ASD) and 73% (n = 69 of the 94 close relations), respectively. Participants considered Prisma to be an acceptable intervention indicated by increases in treatment credibility and expectations from pre- to post-intervention. The group leaders reported treatment credibility in the same range as the participants. Both autistic adults and their close relations reported good treatment satisfaction for each session, while the qualitative thematic analysis indicated that Prisma could be improved by enhancing active participation. This participant feedback will be used to further improve the intervention for an upcoming RCT. Preliminary analyses of effects showed promising results with an increase in knowledge of ASD and some indications for improvements in relationship quality, mental health, quality of life, acceptance of diagnosis and burden of care.ConclusionsOverall, results indicate that the Prisma is a feasible and acceptable first-line intervention in outpatient services. Randomized controlled trials are needed to further corroborate the evidence base of this novel intervention.Trial registrationClinicaltrials.org NCT0446097, retrospectively registered July 8th 2020.