INTRODUCTION: The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE: To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS: We identified 369 nominally genome-wide significant loci ( P < 5 × 10 ⁻⁸ ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 ⁻¹⁰ ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r _G = −0.32, SE = 0.05, P = 6.5 × 10 ⁻¹² ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION: This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure.: ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

Ongoing challenges in diagnosing focal cortical dysplasia (FCD) mandate continuous research and consensus agreement to improve disease definition and classification. An International League Against Epilepsy (ILAE) Task Force (TF) reviewed the FCD classification of 2011 to identify existing gaps and provide a timely update. The following methodology was applied to achieve this goal: a survey of published literature indexed with ((Focal Cortical Dysplasia) AND (epilepsy)) between 01/01/2012 and 06/30/2021 (n = 1349) in PubMed identified the knowledge gained since 2012 and new developments in the field. An online survey consulted the ILAE community about the current use of the FCD classification scheme with 367 people answering. The TF performed an iterative clinico‐pathological and genetic agreement study to objectively measure the diagnostic gap in blood/brain samples from 22 patients suspicious for FCD and submitted to epilepsy surgery. The literature confirmed new molecular‐genetic characterizations involving the mechanistic Target Of Rapamycin (mTOR) pathway in FCD type II (FCDII), and SLC35A2 in mild malformations of cortical development (mMCDs) with oligodendroglial hyperplasia (MOGHE). The electro‐clinical‐imaging phenotypes and surgical outcomes were better defined and validated for FCDII. Little new information was acquired on clinical, histopathological, or genetic characteristics of FCD type I (FCDI) and FCD type III (FCDIII). The survey identified mMCDs, FCDI, and genetic characterization as fields for improvement in an updated classification. Our iterative clinico‐pathological and genetic agreement study confirmed the importance of immunohistochemical staining, neuroimaging, and genetic tests to improve the diagnostic yield. The TF proposes to include mMCDs, MOGHE, and “no definite FCD on histopathology” as new categories in the updated FCD classification. The histopathological classification can be further augmented by advanced neuroimaging and genetic studies to comprehensively diagnose FCD subtypes; these different levels should then be integrated into a multi‐layered diagnostic scheme. This update may help to foster multidisciplinary efforts toward a better understanding of FCD and the development of novel targeted treatment options.

The aim of the present study was (i) to compare disease progression and survival in different types of degenerative ataxia, and (ii) to identify variables that may modify the rate of disease progression. We included patients suffering from Friedreich's ataxia (FRDA, n = 83), early onset cerebellar ataxia (EOCA, n = 30), autosomal dominant cerebellar ataxia (ADCA) type I (ADCA-I, n = 273), ADCA-III (n = 13) and multiple system atrophy (MSA, n = 67). Molecular genetic testing allowed us to assign 202 ADCA-I patients to one of the following subgroups: spinocerebellar ataxia type I (SCAI, n = 36), SCA2 (n = 56) and SCA3 (n = 110). To assess disease progression we defined the following disease stages: stage 0 = no gait difficulties; stage 1 = disease onset, as defined by onset of gait difficulties; stage 2 = loss of independent gait; stage 3 = confinement to wheelchair; stage 4 = death. Disease progression was most rapid in MSA, intermediate in FRDA, ADCA-I and ADCA-III and slowest in EOCA. The rate of progression was similar in SCA1, SCA2 and SCA3. The CAG repeat length was a significant risk factor for faster progression in SCA2 and SCA3, but not in SCA1. In FRDA, the time until confinement to wheelchair was shorter in patients with earlier disease onset, suggesting that patients with long GAA repeats and early disease onset have a poor prognosis. Female gender increased the risk of becoming dependent on walking aids or a wheelchair, but it did not influence survival in FRDA, SCA3 and MSA. In SCA2, female gender was associated with shortened survival. In MSA, later age of onset increased the risk of rapid progression and death.

We performed MRI volumetric measurements of the amygdala (AM), the hippocampal formation (HF), and the anterior temporal lobe in a group of 30 patients with intractable temporal lobe epilepsy (TLE) and in seven patients with extratemporal lobe foci. Measurements were analyzed with a semiautomated software program and the results compared with those of normal controls and correlated with the findings of all other investigations. In particular, we compared the results with the lateralization of epileptic abnormalities in the EEG. Volumetric studies of AM and HF showed lateralization of measurable atrophy consistent with that derived from extracranial and intracranial EEG examinations. The HF volumes were more sensitive and provided a lateralization in 87%. Combined measurements of AM and HF showed lateralization in 93%, always congruent with the results of EEG lateralization. This slight but important additional improvement in discrimination justifies using AM measurements in MRI volumetric studies of mesial temporal structures. Volumetric studies combined with other currently employed noninvasive techniques may diminish the need for invasive methods of investigation in patients with TLE.