Faculty Bibliography

Individuals with copy number variants (CNV) in the 16p11.2 chromosomal region are at high risk for language disorders. We investigate whether the extent and location of focal cortical anomalies are associated with language impairment in individuals with 16p11.2 CNVs. High-resolution T1-weighted MRI scans from 30 16p11.2 deletion (16p-del), 25 16p11.2 duplication (16p-dup), and 90 noncarrier controls (NCC) were analyzed to derive personalized cortical anomaly maps through single-case cortical thickness (CT) comparison to age-matched normative samples. Focal cortical anomalies were elevated in both 16p-del and 16p-dup and their total extent was inversely correlated with Full-Scale IQ. Clusters of abnormally thick cortex were more extensive in the 16p-del group and clusters of abnormally thin cortex were more extensive in the 16p-dup group. Abnormally thick clusters were more extensive in left lateral temporal and bilateral postcentral and mesial occipital regions in 16p-del. Focal cortical anomalies in the left middle temporal region and pars opercularis (Broca's region) of children with 16-del were associated with lower scores on a comprehensive language evaluation. Results extend neuroanatomical findings in 16p11.2 syndrome to include spatially heterogenous focal cortical anomalies that appear to disrupt language ability in accordance with the functional specialization of left frontotemporal regions.

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = -0.24 to -0.73; P < 1.49 × 10-4), and lower thickness in the precentral gyri bilaterally (d = -0.34 to -0.52; P < 4.31 × 10-6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = -1.73 to -1.91, P < 1.4 × 10-19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = -0.36 to -0.52; P < 1.49 × 10-4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = -0.29 to -0.54; P < 1.49 × 10-4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = -0.27 to -0.51; P < 1.49 × 10-4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < -0.0018; P < 1.49 × 10-4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

The availability of cloud computing services has enabled the widespread adoption of the "software as a service" (SaaS) approach for software distribution, which utilizes network-based access to applications running on centralized servers. In this paper we apply the SaaS approach to neuroimaging-based age prediction. Our system, named "NAPR" (Neuroanatomical Age Prediction using R), provides access to predictive modeling software running on a persistent cloud-based Amazon Web Services (AWS) compute instance. The NAPR framework allows external users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. As a demonstration of the NAPR approach, we have developed two age prediction models that were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367, age range 6-89 years). The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3. We believe that this transparent approach to out-of-sample evaluation and comparison of neuroimaging age prediction models will facilitate the development of improved age prediction models and allow for robust evaluation of the clinical utility of these methods.

OBJECTIVE:To test the hypothesis that localization-related epilepsy is associated with widespread neuronal dysfunction beyond the ictal focus, reflected by a decrease in patients' global concentration of their proton MR spectroscopy (1H-MRS) observed marker, N-acetyl-aspartate (NAA). METHODS:Thirteen patients with localization-related epilepsy (7 men, 6 women) 40±13 (mean±standard-deviation)years old, 8.3±13.4years of disease duration; and 14 matched controls, were scanned at 3 T with MRI and whole-brain (WB) 1H MRS. Intracranial fractions of brain volume, gray and white matter (fBV, fGM, fWM) were segmented from the MRI, and global absolute NAA creatine (Cr) and choline (Cho) concentrations were estimated from their WB 1H MRS. These metrics were compared between patients and controls using an unequal variance t test. RESULTS:Patients' fBV, fGM and fWM: 0.81±0.07, 0.47±0.04, 0.31±0.04 were not different from controls' 0.79±0.05, 0.48±0.04, 0.32±0.02; nor were their Cr and Cho concentrations: 7.1±1.1 and 1.3±0.2 millimolar (mM) versus 7.7±0.7 and 1.4±0.1mM (p>0.05 all). Patients' global NAA concentration: 11.5±1.5 mM, however, was 12% lower than controls' 13.0±0.8mM (p=0.004). CONCLUSIONS:These findings indicate that neuronal dysfunction in localization-related epilepsy extends globally, beyond the ictal zone, but without atrophy or spectroscopic evidence of other pathology. This suggests a diffuse decline in the neurons' health, rather than their number, early in the disease course. WB 1H-MRS assessment, therefore, may be a useful tool for quantification of global neuronal dysfunction load in epilepsy.

OBJECTIVE:. METHODS:method on three datasets (SeizureTracker: n=3016, Human Epilepsy Project: n=107, and NeuroVista: n=15). An additional independent SeizureTracker validation dataset was used to generate a set of 200 simulated trials each for 5 different sample sizes (total N=100 to 500 by 100), assuming 20% dropout and 30% drug efficacy. "Power" was determined as the percentage of trials successfully distinguishing placebo from drug (p<0.05). RESULTS:analysis achieved >90% power at N=100 per arm while RR50 required N=200 per arm. SIGNIFICANCE/CONCLUSIONS:may increase the statistical power of an RCT relative to the traditional RR50.

Gene identification in epilepsy has mainly been limited to large families segregating genes of major effect and de novo mutations in epileptic encephalopathies. Many families that present with common non-acquired focal epilepsies and genetic generalized epilepsies remain unexplained. We assembled a cohort of 'genetically enriched' common epilepsies by collecting and phenotyping families containing multiple individuals with unprovoked seizures. We aimed to determine if specific clinical epilepsy features aggregate within families, and whether this segregation of phenotypes may constitute distinct 'familial syndromes' that could inform genomic analyses. Families with three or more individuals with unprovoked seizures were studied across multiple international centres. Affected individuals were phenotyped and classified according to specific electroclinical syndromes. Families were categorized based on syndromic groupings of affected family members, examined for pedigree structure and phenotypic patterns and, where possible, assigned specific familial epilepsy syndromes. A total of 303 families were assembled and analysed, comprising 1120 affected phenotyped individuals. Of the 303 families, 117 exclusively segregated generalized epilepsy, 62 focal epilepsy, and 22 were classified as genetic epilepsy with febrile seizures plus. Over one-third (102 families) were observed to have mixed epilepsy phenotypes: 78 had both generalized and focal epilepsy features within the same individual (n = 39), or within first or second degree relatives (n = 39). Among the genetic generalized epilepsy families, absence epilepsies were found to cluster within families independently of juvenile myoclonic epilepsy, and significantly more females were affected than males. Of the 62 familial focal epilepsy families, two previously undescribed familial focal syndrome patterns were evident: 15 families had posterior quadrant epilepsies, including seven with occipito-temporal localization and seven with temporo-parietal foci, and four families displayed familial focal epilepsy of childhood with multiple affected siblings that was suggestive of recessive inheritance. The findings suggest (i) specific patterns of syndromic familial aggregation occur, including newly recognized forms of familial focal epilepsy; (ii) although syndrome-specificity usually occurs in multiplex families, the one-third of families with features of both focal and generalized epilepsy is suggestive of shared genetic determinants; and (iii) patterns of features observed across families including pedigree structure, sex, and age of onset may hold clues for future gene identification. Such detailed phenotypic information will be invaluable in the conditioning and interpretation of forthcoming sequencing data to understand the genetic architecture and interrelationships of the common epilepsy syndromes.

OBJECTIVE: We used whole brain T1-weighted MRI to estimate the age of individuals with medically refractory focal epilepsy, and compared with individuals with newly diagnosed focal epilepsy and healthy controls. The difference between neuroanatomical age and chronological age was compared between the three groups. METHODS: Neuroanatomical age was estimated using a machine learning-based method that was trained using structural MRI scans from a large independent healthy control sample (N=2001). The prediction model was then used to estimate age from MRI scans obtained from newly diagnosed focal epilepsy patients (N=42), medically refractory focal epilepsy patients (N=94) and healthy controls (N=74). RESULTS: Individuals with medically refractory epilepsy had a difference between predicted brain age and chronological age that was on average 4.5 years older than healthy controls (p=4.6x10-5). No significant differences were observed in newly diagnosed focal epilepsy. Earlier age of onset was associated with an increased brain age difference in the medically refractory group (p=0.034). SIGNIFICANCE: Medically refractory focal epilepsy is associated with structural brain changes that resemble premature brain aging.

The classic epileptic encephalopathies, including infantile spasms (IS) and Lennox-Gastaut syndrome (LGS), are severe seizure disorders that usually arise sporadically. De novo variants in genes mainly encoding ion channel and synaptic proteins have been found to account for over 15% of patients with IS or LGS. The contribution of autosomal recessive genetic variation, however, is less well understood. We implemented a rare variant transmission disequilibrium test (TDT) to search for autosomal recessive epileptic encephalopathy genes in a cohort of 320 outbred patient-parent trios that were generally prescreened for rare metabolic disorders. In the current sample, our rare variant transmission disequilibrium test did not identify individual genes with significantly distorted transmission over expectation after correcting for the multiple tests. While the rare variant transmission disequilibrium test did not find evidence of a role for individual autosomal recessive genes, our current sample is insufficiently powered to assess the overall role of autosomal recessive genotypes in an outbred epileptic encephalopathy population