Diffusion tensor imaging (DTI) studies of human brain development have consistently shown widespread, but nonlinear increases in white matter anisotropy through childhood, adolescence, and into adulthood. However, despite its sensitivity to changes in tissue microstructure, DTI lacks the specificity to disentangle distinct microstructural features of white and gray matter. Neurite orientation dispersion and density imaging (NODDI) is a recently proposed multi-compartment biophysical model of brain microstructure that can estimate non-collinear properties of white matter, such as neurite orientation dispersion index (ODI) and neurite density index (NDI). In this study, we apply NODDI to 66 healthy controls aged 7–63 years to investigate changes of ODI and NDI with brain maturation, with comparison to standard DTI metrics. Using both region-of-interest and voxel-wise analyses, we find that NDI exhibits striking increases over the studied age range following a logarithmic growth pattern, while ODI rises following an exponential growth pattern. This novel finding is consistent with well-established age-related changes of FA over the lifespan that show growth during childhood and adolescence, plateau during early adulthood, and accelerating decay after the fourth decade of life. Our results suggest that the rise of FA during the first two decades of life is dominated by increasing NDI, while the fall in FA after the fourth decade is driven by the exponential rise of ODI that overcomes the slower increases of NDI. Using partial least squares regression, we further demonstrate that NODDI better predicts chronological age than DTI. Finally, we show excellent test—retest reliability of NODDI metrics, with coefficients of variation below 5% in all measured regions of interest. Our results support the conclusion that NODDI reveals biologically specific characteristics of brain development that are more closely linked to the microstructural features of white matter than are the empirical metrics provided by DTI.

Purpose:To characterize the clinical phenotype of the recurrent copy-number variation (CNV) at 1q21.1, we assessed the psychiatric and medical phenotypes of 1q21.1 deletion and duplication carriers ascertained through clinical genetic testing and family member cascade testing, with particular emphasis on dimensional assessment across multiple functional domains. Methods:Nineteen individuals with 1q21.1 deletion, 19 individuals with the duplication, and 23 familial controls (noncarrier siblings and parents) spanning early childhood through adulthood were evaluated for psychiatric, neurologic, and other medical diagnoses, and their cognitive, adaptive, language, motor, and neurologic domains were also assessed. Twenty-eight individuals with 1q21.1 CNVs (15 deletion, 13 duplication) underwent structural magnetic resonance brain imaging.Results: Probands with 1q21.1 CNVs presented with a range of psychiatric, neurologic, and medical disorders. Deletion and duplication carriers shared several features, including borderline cognitive functioning, impaired fine and gross motor functioning, articulation abnormalities, and hypotonia. Increased frequency of Autism Spectrum Disorder (ASD) diagnosis, increased ASD symptom severity, and increased prevalence of macrocephaly were observed in the duplication relative to deletion carriers, whereas reciprocally increased prevalence of microcephaly was observed in the deletion carriers.Conclusions: Individuals with 1q21.1 deletions or duplications exhibit consistent deficits on motor and cognitive functioning and abnormalities in head circumference.

Structural magnetic resonance (MR) connectomics holds promise for the diagnosis, outcome prediction, and treatment monitoring of many common neurodevelopmental, psychiatric, and neurodegenerative disorders for which there is currently no clinical utility for MR imaging (MRI). Before computational network metrics from the human connectome can be applied in a clinical setting, their precision and their normative intersubject variation must be understood to guide the study design and the interpretation of longitudinal data. In this work, the reproducibility of commonly used graph theoretic measures is investigated, as applied to the structural connectome of healthy adult volunteers. Two datasets are examined, one consisting of 10 subjects scanned twice at one MRI facility and one consisting of five subjects scanned once each at two different facilities using the same imaging platform. Global graph metrics are calculated for unweighed and weighed connectomes, and two levels of granularity of the connectome are evaluated: one based on the 82-node cortical and subcortical parcellation from FreeSurfer and one based on an atlas-free parcellation of the gray-white matter boundary consisting of 1000 cortical nodes. The consistency of the unweighed and weighed edges and the module assignments are also computed for the 82-node connectomes. Overall, the results demonstrate good-to-excellent test-retest reliability for the entire connectome-processing pipeline, including the graph analytics, in both the intrasite and intersite datasets. These findings indicate that measurements of computational network metrics derived from the structural connectome have sufficient precision to be tested as potential biomarkers for diagnosis, prognosis, and monitoring of interventions in neurological and psychiatric diseases.

BACKGROUND: 16p11.2 breakpoint 4 to 5 copy number variants (CNVs) increase the risk for developing autism spectrum disorder, schizophrenia, and language and cognitive impairment. In this multisite study, we aimed to quantify the effect of 16p11.2 CNVs on brain structure. METHODS: Using voxel-and surface-based brain morphometric methods, we analyzed structural magnetic resonance imaging collected at seven sites from 78 individuals with a deletion, 71 individuals with a duplication, and 212 individuals without a CNV. RESULTS: Beyond the 16p11.2-related mirror effect on global brain morphometry, we observe regional mirror differences in the insula (deletion . control . duplication). Other regions are preferentially affected by either the deletion or the duplication: the calcarine cortex and transverse temporal gyrus (deletion . control; Cohen's d . 1), the superior and middle temporal gyri (deletion , control; Cohen's d , 21), and the caudate and hippocampus (control . duplication; 20.5 . Cohen's d . 21). Measures of cognition, language, and social responsiveness and the presence of psychiatric diagnoses do not influence these results. CONCLUSIONS: The global and regional effects on brain morphometry due to 16p11.2 CNVs generalize across site, computational method, age, and sex. Effect sizes on neuroimaging and cognitive traits are comparable. Findings partially overlap with results of meta-analyses performed across psychiatric disorders. However, the lack of correlation between morphometric and clinical measures suggests that CNV-associated brain changes contribute to clinical manifestations but require additional factors for the development of the disorder. These findings highlight the power of genetic risk factors as a complement to studying groups defined by behavioral criteria. Autism spectrum disorder (ASD) and related neurodevelopmental disorders are defined behaviorally and characterized by a significant clinical and etiologic heterogeneity. As a consequence, investigating ASD under the assumption of an underlying homogeneous condition has resulted in controversial findings in the field of neuroimaging (1). Increased brain growth early in development (2-4) and alterations of many regional brain volumes (5) have been implicated in ASD, but results have proven difficult to replicate (1,(6)(7)(8).To mitigate some of these issues, cohorts of individuals with shared genetic risk factors have been assembled to minimize the noise introduced by etiologic and biological heterogeneity (9). Such a "genetic-first" study design provides the opportunity to investigate a given neurodevelopmental risk (and associated mechanism) shared by individuals who carry the same genetic etiology irrespective of the psychiatric diagnosis.Copy number variants (CNVs) at the 16p11.2 (breakpoints 4-5, 29.6-30.2 Mb-hg19) (10) are among the most frequent risk factors for neurodevelopmental and psychiatric conditions.

Copy number variants (CNVs) of the chromosomal locus 16p11.2, consisting of either deletions or duplications, have been implicated in autism, schizophrenia, epilepsy, and other neuropsychiatric disorders. Since abnormal white matter microstructure can be seen in these more broadly defined clinical disorders, we used diffusion magnetic resonance imaging and tract-based spatial statistics to investigate white matter microstructural integrity in human children with 16p11.2 deletions. We show that deletion carriers, compared with typically developing matched controls, have increased axial diffusivity (AD) in many major central white matter tracts, including the anterior corpus callosum as well as bilateral internal and external capsules. Higher AD correlated with lower nonverbal IQ in the deletion carriers, but not controls. Increases in fractional anisotropy and mean diffusivity were also found in some of the same tracts with elevated AD. Closer examination with neurite orientation dispersion and density imaging revealed that fiber orientation dispersion was decreased in some central white matter tracts. Notably, these alterations of white matter are unlike microstructural differences reported for any other neurodevelopmental disorders, including autism spectrum disorders that have phenotypic overlap with the deletion carriers. These findings suggest that deletion of the 16p11.2 locus is associated with a unique widespread pattern of aberrant white matter microstructure that may underlie the impaired cognition characteristic of this CNV.