Neurological Diseases and Prevalence of Antineuronal Antibodies in Patients with Autoimmune Polyendocrine Syndrome Type 1 - A National Cohort Study.

Autoimmune polyendocrine syndrome type 1 (APS-1) is a rare monogenic disease caused by mutations in the autoimmune regulator gene. Although the disease-associated autoantibodies mostly target endocrine organs, autoantibodies from patients with APS-1 bind also to rat brain structures. The patients often have GAD65-antibodies, that can cause autoimmune encephalitis. However, neurological manifestations of APS-1 have not been systematically explored. We conducted a retrospective chart review on 44 Finnish patients with APS-1 (median age 38 years, 61% females) and collected all their neurological diagnoses. To assess the prevalence of serum antineuronal antibodies in APS-1, serum samples of 24 patients (median age 36 years, 63% females) were analyzed using a fixed cell-based assay. Of the 44 APS-1 patients, 10 (23%) had also received a diagnosis of a neurological disease. Of these neurological comorbidities, migraine (n = 7; 16%), central nervous system infections (n = 3; 7%), and epilepsy (n = 2; 5%) were the most prevalent. Other diagnoses recorded for single patients were axonal sensorimotor polyneuropathy, essential tremor, idiopathic intracranial hypertension, ischemic stroke, and trigeminal neuralgia. Serum antineuronal antibodies were detected in 42% of patients tested (10/24, 50% females, median age 42 years), GAD65 antibodies being the most common finding. Antibodies against glycine and aquaporin 4 were found in low titers. In four patients, relatively high titers of GAD65 antibodies without coexisting type 1 diabetes were found, but none presented with GAD65-encephalitis. Our study suggests an association between APS-1 and neurological disorders, the mechanisms of which are to be further investigated.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics.

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.