The purpose of this study was to analyze the clinical aspects in 130 patients presenting periodic lateralized epileptiform discharges (PLEDs) in their EEG and to compare these results with those found in the literature. Etiology, neurologic deficit, seizure occurrence, and evolution were studied in each patient by historical review. The recordings were obtained on 8- or 16-channel EEGs with electrode placement according to the International 10-20 System. Recordings containing PLEDs were selected. PLEDs were defined as repetitive periodic, focal, or hemispheric epileptiform discharges (spikes, spike and waves, polyspikes, sharp waves) usually recurring every 1 to 2 seconds. The statistical study was carried out via the chi(2) test using the computer program SPSS. The main etiology found in this group of patients was stroke (61 of 130 patients). Other processes found were brain infections, tumors, hematomas, and several other entities grouped together as miscellaneous (anoxic encephalopathy, subarachnoid hemorrhage, craniocerebral trauma, Creutzfeldt-Jacob disease, migraine, multiple sclerosis, and aminophylline intoxication). Half of these patients (65 of 130) developed seizures, mostly partial motor seizures. No significant relation between etiology and seizures was found (chi(2) = 2.81, P = 0.4222). Seizures recurred in 14 of 130 patients during a follow-up of 14.5 months. PLEDs were not recorded in any EEG at the time of seizure recurrence. PLEDs constitute a distinctive but uncommon EEG phenomenon of repetitive, periodic, and stereotyped lateralized complexes. In agreement with the literature, PLEDs were associated with an acute process and occurred early during the course of the illness in all patients studied and were usually associated with structural lesions, with stroke being the main etiology. Traditionally, seizures occur with PLEDs but it is also accepted that they can exist in patients who never develop epileptic activity, either clinically or electrically, as demonstrated in 50% of the patients studied. No significant association between seizures and any etiology could be found. It was not demonstrated that the occurrence of seizures may influence the outcome in any way.

Background and ObjectivesMost patients with amyotrophic lateral sclerosis (ALS) lack a monogenic mutation. This study evaluates ALS cumulative genetic risk in an independent Michigan and Spanish replication cohort using polygenic scores.MethodsParticipant samples from University of Michigan were genotyped and assayed for the chromosome 9 open reading frame 72 hexanucleotide expansion. Final cohort size was 219 ALS and 223 healthy controls after genotyping and participant filtering. Polygenic scores excluding the C9 region were generated using an independent ALS genome-wide association study (20,806 cases, 59,804 controls). Adjusted logistic regression and receiver operating characteristic curves evaluated the association and classification between polygenic scores and ALS status, respectively. Population attributable fractions and pathway analyses were conducted. An independent Spanish study sample (548 cases, 2,756 controls) was used for replication.ResultsPolygenic scores constructed from 275 single-nucleotide variation (SNV) had the best model fit in the Michigan cohort. An SD increase in ALS polygenic score associated with 1.28 (95% CI 1.04–1.57) times higher odds of ALS with area under the curve of 0.663 vs a model without the ALS polygenic score (pvalue = 1 × 10−6). The population attributable fraction of the highest 20th percentile of ALS polygenic scores, relative to the lowest 80th percentile, was 4.1% of ALS cases. Genes annotated to this polygenic score enriched for important ALS pathomechanisms. Meta-analysis with the Spanish study, using a harmonized 132 single nucleotide variation polygenic score, yielded similar logistic regression findings (odds ratio: 1.13, 95% CI 1.04–1.23).DiscussionALS polygenic scores can account for cumulative genetic risk in populations and reflect disease-relevant pathways. If further validated, this polygenic score will inform future ALS risk models.