Pediatric Imaging, Neurocognition, And Genetics Research Articles

Brain structural covariance network features are robust markers of early heavy alcohol use.

Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years). Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. Graph theory metrics of segregation and integration were used to summarize SCN. Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

Schizophrenia Polygenic Risk During Typical Development Reflects Multiscale Cortical Organization

BackgroundSchizophrenia is widely recognized as a neurodevelopmental disorder. Abnormal cortical development in otherwise typically developing children and adolescents may be revealed using polygenic risk scores for schizophrenia (PRS-SCZ). MethodsWe assessed PRS-SCZ and cortical morphometry in typically developing children and adolescents (3–21 years, 46.8% female) using whole-genome genotyping and T1-weighted magnetic resonance imaging (n = 390) from the PING (Pediatric Imaging, Neurocognition, and Genetics) cohort. We contextualized the findings using 1) age-matched transcriptomics, 2) histologically defined cytoarchitectural types and functionally defined networks, and 3) case-control differences of schizophrenia and other major psychiatric disorders derived from meta-analytic data of 6 ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) working groups, including a total of 12,876 patients and 15,670 control participants. ResultsHigher PRS-SCZ was associated with greater cortical thickness, which was most prominent in areas with heightened gene expression of dendrites and synapses. PRS-SCZ–related increases in vertexwise cortical thickness were mainly distributed in association cortical areas, particularly the ventral attention network, while relatively sparing koniocortical type cortex (i.e., primary sensory areas). The large-scale pattern of cortical thickness increases related to PRS-SCZ mirrored the pattern of cortical thinning in schizophrenia and mood-related psychiatric disorders derived from the ENIGMA consortium. Age group models illustrate a possible trajectory from PRS-SCZ–associated cortical thickness increases in early childhood toward thinning in late adolescence, with the latter resembling the adult brain phenotype of schizophrenia. ConclusionsCollectively, combining imaging genetics with multiscale mapping, our work provides novel insight into how genetic risk for schizophrenia affects the cortex early in life.

Do aggregate, multimodal structural neuroimaging measures replicate regional developmental differences observed in highly cited cellular histological studies?

Influential investigations of postmortem human brain tissue showed regional differences in tissue properties at early phases of development, such as between prefrontal and primary sensory cortical regions. Large-scale neuroimaging studies enable characterization of age-related trajectories with much denser sampling of cortical regions, assessment ages, and demographic variables than postmortem tissue analyses, but no single imaging measure perfectly captures what is measured with histology. Using publicly available data from the Pediatric Imaging, Neurocognition, and Genetics (PING) study, including 951 participants with ages ranging from 3 to 21 years, we characterized cortical regional variability in developmental trajectories of multimodal brain imaging measures. Multivariate analyses integrated morphometric and microstructural cortical surface measures. To replicate foundational histological work showing delayed synapse elimination in middle frontal gyrus relative to primary sensory areas, we tested whether developmental trajectories differ between prefrontal and visual or auditory cortex. We extended this to a whole-cortex analysis of interregional differences, producing cortical parcellations with maximally different developmental trajectories. Consistent with the general conclusions of postmortem analyses, our imaging results suggest that prefrontal regions show a protracted period of greater developmental change; however, they also illustrate the challenges of drawing conclusions about the relative maturational phases of different brain regions.

Identifying genetic risk variants associated with brain volumetric phenotypes via K-sample Ball Divergence method.

Regional human brain volumes including total area, average thickness, and total volume are heritable and associated with neurological disorders. However, the genetic architecture of brain structure and function is still largely unknown and worthy of exploring. The Pediatric Imaging, Neurocognition, and Genetics (PING) data set provides an excellent resource with genome-wide genetic data and related neuroimaging data. In this study, we perform genome-wide association studies (GWAS) of 315 brain volumetric phenotypes from the PING data set including 1036 samples with 539,865 single-nucleotide polymorphisms (SNPs). We introduce a nonparametric test based on K-sample Ball Divergence (KBD) to identify genetic risk variants that influence regional brain volumes. We carry out simulations to demonstrate that KBD is a powerful test for identifying significant SNPs associated with multivariate phenotypes although controlling the type I error rate. We successfully identify nine SNPs below a significance level of 5 × 10-5 for the PING data. Among the nine identified genetic variants, two SNPs rs486179 and rs562110 are located in the ADRA1A gene that is a well-known risk factor of mental illness, such as schizophrenia and attention deficit hyperactivity disorder. Our study suggests that the nonparametric test KBD is an effective method for identifying genetic variants associated with complex diseases in large-scale GWAS of multiple phenotypes.

Neurocognitive Dysfunction and Smaller Brain Volumes in Adolescents and Adults With a Fontan Circulation.

Neurocognitive outcomes beyond childhood in people with a Fontan circulation are not well defined. This study aimed to investigate neurocognitive functioning in adolescents and adults with a Fontan circulation and associations with structural brain injury, brain volumetry, and postnatal clinical factors. In a binational study, participants with a Fontan circulation without a preexisting major neurological disability were prospectively recruited from the Australia and New Zealand Fontan Registry. Neurocognitive function was assessed by using Cogstate software in 107 participants with a Fontan circulation and compared with control groups with transposition of the great arteries (n=50) and a normal circulation (n=41). Brain MRI with volumetric analysis was performed in the participants with a Fontan circulation and compared with healthy control data from the ABIDE I and II (Autism Brain Imaging Data Exchange) and PING (Pediatric Imaging, Neurocognition, and Genetics) data repositories. Clinical data were retrospectively collected. Of the participants with a Fontan circulation who had a neurocognitive assessment, 55% were male and the mean age was 22.6 years (SD 7.8). Participants with a Fontan circulation performed worse in several areas of neurocognitive function compared with those with transposition of the great arteries and healthy controls (P<0.05). Clinical factors associated with worse neurocognitive outcomes included more inpatient days during childhood, younger age at Fontan surgery, and longer time since Fontan procedure (P<0.05). Adults with a Fontan circulation had more marked neurocognitive dysfunction than adolescents with a Fontan circulation in 2 domains (psychomotor function, P=0.01 and working memory, P=0.02). Structural brain injury was present in the entire Fontan cohort; the presence of white matter injury was associated with worse paired associate learning (P<0.001), but neither the presence nor severity of infarct, subcortical gray matter injury, and microhemorrhage was associated with neurocognitive outcomes. Compared with healthy controls, people with a Fontan circulation had smaller global brain volumes (P<0.001 in all regions) and smaller regional brain volumes in most cerebral cortical regions (P<0.05). Smaller global brain volumes were associated with worse neurocognitive functioning in several domains (P<0.05). A significant positive association was also identified between global brain volumes and resting oxygen saturations (P≤0.04). Neurocognitive impairment is common in adolescents and adults with a Fontan circulation and is associated with smaller gray and white matter brain volume. Understanding modifiable factors that contribute to brain injury to optimize neurocognitive function is paramount.

Maturation of cortical microstructure and cognitive development in childhood and adolescence: A T1w/T2w ratio MRI study.

The restructuring and optimization of the cerebral cortex from early childhood and through adolescence is an essential feature of human brain development, underlying immense cognitive improvements. Beyond established morphometric cortical assessments, the T1w/T2w ratio quantifies partly separate biological processes, and might inform models of typical neurocognitive development and developmental psychopathology. In the present study, we computed vertex‐wise T1w/T2w ratio across the cortical surface in 621 youths (3–21 years) sampled from the Pediatric Imaging, Neurocognition, and Genetics (PING) study and tested for associations with individual differences in age, sex, and both general and specific cognitive abilities. The results showed a near global linear age‐related increase in T1w/T2w ratio across the brain surface, with a general posterior to anterior increasing gradient in association strength. Moreover, results indicated that boys in late adolescence had regionally higher T1w/T2w ratio as compared to girls. Across individuals, T1w/T2w ratio was negatively associated with general and several specific cognitive abilities mainly within anterior cortical regions. Our study indicates age‐related differences in T1w/T2w ratio throughout childhood, adolescence, and young adulthood, in line with the known protracted myelination of the cortex. Moreover, the study supports T1w/T2w ratio as a promising surrogate measure of individual differences in intracortical brain structure in neurodevelopment.

A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity

BackgroundFunctional magnetic resonance imaging (fMRI) has been implemented widely to study brain connectivity. In particular, time-varying connectivity analysis has emerged as an important measure to uncover essential knowledge within the network. On the other hand, independent component analysis (ICA) has served as a powerful tool to preprocess fMRI data before performing network analysis. Together, they may lead to novel findings. MethodsWe propose a new framework (GICA-TVGL) that combines group ICA (GICA) with time-varying graphical LASSO (TVGL) to improve the power of analyzing functional connectivity (FNC) changes, which is then applied for neuro-developmental study. To investigate the performance of our proposed approach, we apply it to capture dynamic FNC using both the Philadelphia Neurodevelopmental Cohort (PNC) and the Pediatric Imaging, Neurocognition, and Genetics (PING) datasets. ResultsOur results indicate that females and males in young adult group possess substantial difference related to visual network. In addition, some other consistent conclusions have been reached by using these two datasets. Furthermore, the GICA-TVGL model indicated that females had a higher probability to stay in a stable state. Males had a higher tendency to remain in a globally disconnected mode. Comparison with existing methodThe performance of sliding window approach is largely affected by the window size selection. In addition, it also assumes temporal locality hypothesis. ConclusionOur proposed framework provides a feasible method to investigate brain dynamics and has the potential to become a widely used tool in neuroimaging studies.

O11. What Do We Know About the Power of Our Developmental Structural Neuroimaging Studies?

Understanding the details of brain development is critically important to understand the developmental processes that underlie neurodevelopmental disabilities. Numerous large-scale neuroimaging studies have been and will be performed. In this study, we used the neuroimaging data from the Pediatric Imaging, Neurocognition and Genetics (PING) cohort to set a baseline estimation of effect sizes in order to set expectations for future studies.

Use of Machine Learning to Determine Deviance in Neuroanatomical Maturity Associated With Future Psychosis in Youths at Clinically High Risk

ImportanceAltered neurodevelopmental trajectories are thought to reflect heterogeneity in the pathophysiologic characteristics of schizophrenia, but whether neural indicators of these trajectories are associated with future psychosis is unclear.ObjectiveTo investigate distinct neuroanatomical markers that can differentiate aberrant neurodevelopmental trajectories among clinically high-risk (CHR) individuals.Design, Setting, and ParticipantsIn this prospective longitudinal multicenter study, a neuroanatomical-based age prediction model was developed using a supervised machine learning technique with T1-weighted magnetic resonance imaging scans of 953 healthy controls 3 to 21 years of age from the Pediatric Imaging, Neurocognition, and Genetics (PING) study and then applied to scans of 275 CHR individuals (including 39 who developed psychosis) and 109 healthy controls 12 to 21 years of age from the North American Prodrome Longitudinal Study 2 (NAPLS 2) for external validation and clinical application. Scans from NAPLS 2 were collected from January 15, 2010, to April 30, 2012.Main Outcomes and MeasuresDiscrepancy between neuroanatomical-based predicted age (hereafter referred to as brain age) and chronological age.ResultsThe PING-derived model (460 females and 493 males; age range, 3-21 years) accurately estimated the chronological ages of the 109 healthy controls in the NAPLS 2 (43 females and 66 males; age range, 12-21 years), providing evidence of independent external validation. The 275 CHR individuals in the NAPLS 2 (111 females and 164 males; age range, 12-21 years) showed a significantly greater mean (SD) gap between model-predicted age and chronological age (0.64 [2.16] years) compared with healthy controls (P = .008). This outcome was significantly moderated by chronological age, with brain age systematically overestimating the ages of CHR individuals who developed psychosis at ages 12 to 17 years but not the brain ages of those aged 18 to 21 years. Greater brain age deviation was associated with a higher risk for developing psychosis (F = 3.70; P = .01) and a pattern of stably poor functioning over time, but only among younger CHR adolescents. Previously reported evidence of accelerated reduction in cortical thickness among CHR individuals who developed psychosis was found to apply only to those who were 18 years of age or older.Conclusions and RelevanceThese results are consistent with the view that neuroanatomical markers of schizophrenia may help to explain some of the heterogeneity of this disorder, particularly with respect to early vs later age of onset of psychosis, with younger and older individuals having differing intercepts and trajectories in structural brain parameters as a function of age. The results also suggest that baseline neuroanatomical measures are likely to be useful in estimating onset of psychosis, especially (or only) among CHR individuals with an earlier age of onset of prodromal symptoms.

The independent and interacting effects of socioeconomic status and dual-language use on brain structure and cognition.

Family socioeconomic status (SES) is strongly associated with children's cognitive development, and past studies have reported socioeconomic disparities in both neurocognitive skills and brain structure across childhood. In other studies, bilingualism has been associated with cognitive advantages and differences in brain structure across the lifespan. The aim of the current study is to concurrently examine the joint and independent associations between family SES and dual-language use with brain structure and cognitive skills during childhood. A subset of data from the Pediatric Imaging, Neurocognition and Genetics (PING) study was analyzed; propensity score matching established an equal sample (N = 562) of monolinguals and dual-language users with similar socio-demographic characteristics (Mage = 13.5, Range = 3-20 years). When collapsing across all ages, SES was linked to both brain structure and cognitive skills. When examining differences by age group, brain structure was significantly associated with both income and dual-language use during adolescence, but not earlier in childhood. Additionally, in adolescence, a significant interaction between dual-language use and SES was found, with no difference in cortical surface area (SA) between language groups of higher-SES backgrounds but significantly increased SA for dual-language users from lower-SES families compared to SES-matched monolinguals. These results suggest both independent and interacting associations between SES and dual-language use with brain development. To our knowledge, this is the first study to concurrently examine dual-language use and socioeconomic differences in brain structure during childhood and adolescence.

Functional differentiation between convergence and non-convergence zones of the striatum in children

Most cortical areas send projections to the striatum. In some parts of the striatum, the connections converge from several cortical areas. It is unknown whether the convergence and non-convergence zones of the striatum differ functionally. Here, we used diffusion-weighted magnetic resonance imaging and probabilistic fiber tracking to parcellate the striatum based on its connections to dorsolateral prefrontal, parietal and orbitofrontal cortices in two different datasets (children aged 6–7 years and adults). In both samples, quantitative susceptibility mapping (QSM) values were significantly correlated with working memory (WM) in convergence zones, but not in non-convergence zones. In children, this was also true for mean diffusivity, MD. The association of MD to WM specifically in the convergent zone was replicated in the Pediatric Imaging, Neurocognition, and Genetics (PING) dataset for 135 children aged 6–9 years. QSM data was not available in the PING dataset, and the association to QSM still needs to be replicated. These results suggest that connectivity-based segments of the striatum exhibit functionally different characteristics. The association between convergence zones and WM performance might relate to a role in integrating and coordinating activity in different cortical areas.

Whole genome association study of brain-wide imaging phenotypes: A study of the ping cohort.

Neuropsychological disorders have a biological basis rooted in brain function, and neuroimaging data are expected to better illuminate the complex genetic basis of neuropsychological disorders. Because they are biological measures, neuroimaging data avoid biases arising from clinical diagnostic criteria that are subject to human understanding and interpretation. A challenge with analyzing neuroimaging data is their high dimensionality and complex spatial relationships. To tackle this challenge, we introduced a novel distance covariance tests that can assess the association between genetic markers and multivariate diffusion tensor imaging measurements, and analyzed a genome-wide association study (GWAS) dataset collected by the Pediatric Imaging, Neurocognition, and Genetics (PING) study. We also considered existing approaches as comparisons. Our results showed that, after correcting for multiplicity, distance covariance tests of the multivariate phenotype yield significantly greater power at detecting genetic markers affecting brain structure than standard mass univariate GWAS of individual neuroimaging biomarkers. Our results underscore the usefulness of utilizing the distance covariance to incorporate neuroimaging data in GWAS.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases).

Anxiety, depression, impulsivity, and brain structure in children and adolescents.

The unique neuroanatomical underpinnings of internalizing symptoms and impulsivity during childhood are not well understood. In this study, we examined associations of brain structure with anxiety, depression, and impulsivity in children and adolescents. Participants were 7- to 21-year-olds (N = 328) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study who completed high-resolution, 3-Tesla, T1-weighted MRI and self-report measures of anxiety, depression, and/or impulsivity. Cortical thickness and surface area were examined across cortical regions-of-interest (ROIs), and exploratory whole-brain analyses were also conducted. Gray matter volume (GMV) was examined in subcortical ROIs. When considered separately, higher depressive symptoms and impulsivity were each significantly associated with reduced cortical thickness in ventromedial PFC/medial OFC, but when considered simultaneously, only depressive symptoms remained significant. Higher impulsivity, but not depressive symptoms, was associated with reduced cortical thickness in the frontal pole, rostral middle frontal gyrus, and pars orbitalis. No differences were found for regional surface area. Higher depressive symptoms, but not impulsivity, were significantly associated with smaller hippocampal GMV and larger pallidal GMV. There were no significant associations between anxiety symptoms and brain structure. Depressive symptoms and impulsivity may be linked with cortical thinning in overlapping and distinct regions during childhood and adolescence.

2.7 Everyone Likes Candi: Data Sharing and Neuroinformatics to Address Big Data Questions

A substantial amount of neuroimaging data are now being shared that will allow us to answer important questions, thanks to efforts by the NIH Pediatric Database (PEDS); Autism Brain Data Exchange (ABIDE); and Pediatric Imaging, Neurocognition and Genetics (PING). We will discuss the use of these shared resources and ways to use them to answer important questions. For example, in typical development, do multiple sources of developmental data tell us the same things about the developmental trajectory and sex effects?

Lower total and regional grey matter brain volumes in youth with perinatally-acquired HIV infection: Associations with HIV disease severity, substance use, and cognition

Despite improved survival due to combination antiretroviral therapy (cART), youth with perinatally-acquired HIV (PHIV) show cognitive deficits and developmental delay at increased rates. HIV affects the brain during critical periods of development, and the brain may be a persistent reservoir for HIV due to suboptimal blood brain barrier penetration of cART. We conducted structural magnetic resonance imaging (sMRI) and cognitive testing in 40 PHIV youth (mean age=16.7years) recruited from the NIH Pediatric HIV/AIDS Cohort Study (PHACS) who are part of the first generation of PHIV youth surviving into adulthood. Historical and current HIV disease severity and substance use measures were also collected. Total and regional cortical grey matter brain volumes were compared to a group of 334 typically-developing, HIV-unexposed and uninfected youth (frequency-matched for age and sex) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study (mean age=16.1years). PHIV youth had smaller (2.8–5.1%) total and regional grey matter volumes than HIV-unexposed and uninfected youth, with smallest volumes seen among PHIV youth with higher past peak viral load (VL) and recent unsuppressed VL. In PHIV youth, worse cognitive performance correlated with smaller volumes. This pattern of smaller grey matter volumes suggests that PHIV infection may influence brain development and underlie cognitive dysfunction seen in this population. Among PHIV youth, smaller volumes were also linked to substance use (alcohol use: 9.0–13.4%; marijuana use: 10.1–16.0%). In this study, collection of substance use information was limited to the PHIV cohort; future studies should also collect substance use information in controls to further address interactions between HIV and substance use on brain volume.

The developmental relationship between specific cognitive domains and grey matter in the cerebellum

There is growing evidence that the cerebellum is involved in cognition and cognitive development, yet little is known about the developmental relationship between cerebellar structure and cognitive subdomains in children. We used voxel-based morphometry to assess the relationship between cerebellar grey matter (GM) and language, reading, working memory, executive function, and processing speed in 110 individuals aged 8–17 years from the Pediatric Imaging, Neurocognition, and Genetics (PING) Study. Further, we examined the effect of age on the relationships between cerebellar GM and cognition. Higher scores on vocabulary, reading, working memory, and set-shifting were associated with increased GM in the posterior cerebellum (lobules VI–IX), in regions which are typically engaged during cognitive tasks in healthy adults. For reading, working memory, and processing speed, the relationship between cerebellar GM and cognitive performance changed with age in specific cerebellar subregions. As in adults, posterior lobe cerebellar GM was associated with cognitive performance in a pediatric population, and this relationship mirrored the known developmental trajectory of posterior cerebellar GM. These findings provide further evidence that specific regions of the cerebellum support cognition and cognitive development, and suggest that the strength of this relationship depends on developmental stage.

Anxiety is related to indices of cortical maturation in typically developing children and adolescents.

Anxiety is a risk factor for many adverse neuropsychiatric and socioeconomic outcomes, and has been linked to functional and structural changes in the ventromedial prefrontal cortex (VMPFC). However, the nature of these differences, as well as how they develop in children and adolescents, remains poorly understood. More effective interventions to minimize the negative consequences of anxiety require better understanding of its neurobiology in children. Recent research suggests that structural imaging studies may benefit from clearly delineating between cortical surface area and thickness when examining these associations, as these distinct cortical phenotypes are influenced by different cellular mechanisms and genetic factors. The present study examined relationships between cortical surface area and thickness of the VMPFC and a self-report measure of anxiety (SCARED-R) in 287 youths aged 7-20years from the Pediatric Imaging, Neurocognition, and Genetics (PING) study. Age and gender interactions were examined for significant associations in order to test for developmental differences. Cortical surface area and thickness were also examined simultaneously to determine whether they contribute independently to the prediction of anxiety. Anxiety was negatively associated with relative cortical surface area of the VMPFC as well as with global cortical thickness, but these associations diminished with age. The two cortical phenotypes contributed additively to the prediction of anxiety. These findings suggest that higher anxiety in children may be characterized by both delayed expansion of the VMPFC and an altered trajectory of global cortical thinning. Further longitudinal studies will be needed to confirm these findings.

White matter microstructure among youth with perinatally acquired HIV is associated with disease severity.

We investigated whether HIV disease severity was associated with alterations in structural brain connectivity, and whether those alterations in turn were associated with cognitive deficits in youth with perinatally acquired HIV (PHIV). PHIV youth (n = 40) from the Pediatric HIV/AIDS Cohort Study (PHACS) (mean age: 16 ± 2 years) were included to evaluate how current and past disease severity measures (recent/nadir CD4%; peak viral load) relate to white matter microstructure within PHIV youth. PHIV youth were compared with 314 controls from the Pediatric Imaging, Neurocognition and Genetics (PING) study. Diffusion tensor imaging and tractography were utilized to assess white matter microstructure. Mediation analyses were conducted to examine whether microstructure alterations contributed to relationships between higher disease severity and specific cognitive domains in PHIV youth. Whole brain fractional anisotropy was reduced, but radial and mean diffusivity were increased in PHIV compared with control youth. Within PHIV youth, more severe past HIV disease was associated with reduced fractional anisotropy of the right inferior fronto-occipital (IFO) and left uncinate tracts; elevated mean diffusivity of the F minor; and increased streamlines comprising the left inferior longitudinal fasciculus (ILF). Associations of higher peak viral load with lower working memory performance were partly mediated by reductions in right IFO fractional anisotropy levels. Our findings suggest that PHIV youth have a higher risk of alterations in white matter microstructure than typically developing youth, and certain alterations are related to past disease severity. Further, white matter alterations potentially mediate associations between HIV disease and working memory.

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING portal and filing a data use agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal.