Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology.

Psychogenic nonepileptic seizures (PNES) represent a diagnostic challenge. When trying to distinguish between PNES and epileptic seizures (ES), clinicians rely on the presence or absence of several clinical signs. Our purpose is to establish the extent to which these signs are supported by primary data from the literature. A Medline search was used to identify primary studies that used video-EEG to define the presence or absence of different clinical signs in PNES and ES. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. 34 studies matched the inclusion criteria. A specific sign was considered well supported by the data from the primary literature if we were able to identify at least two controlled studies demonstrating its usefulness and if the data from other studies were supportive. There is good evidence from the literature that long duration, occurrence from apparent sleep with EEG-verified wakefulness, fluctuating course, asynchronous movements, pelvic thrusting, side-to-side head or body movement, closed eyes during the episode, ictal crying, memory recall and absence of postictal confusion are signs that distinguish PNES from ES. Post-ictal stertorous breathing proved to distinguish convulsive PNES from generalised tonic clonic seizures (GTCS) and should be added to the list of useful clinical signs. The final clinical diagnosis should encompass all available data, and should not rely on any single sign alone.