Genomic analyses of hair from Ludwig van Beethoven

Ludwig van Beethoven (1770–1827) remains among the most influential and popular classical music composers. Health problems significantly impacted his career as a composer and pianist, including progressive hearing loss, recurring gastrointestinal complaints, and liver disease. In 1802, Beethoven requested that following his death, his disease be described and made public. Medical biographers have since proposed numerous hypotheses, including many substantially heritable conditions. Here we attempt a genomic analysis of Beethoven in order to elucidate potential underlying genetic and infectious causes of his illnesses. We incorporated improvements in ancient DNA methods into existing protocols for ancient hair samples, enabling the sequencing of high-coverage genomes from small quantities of historical hair. We analyzed eight independently sourced locks of hair attributed to Beethoven, five of which originated from a single European male. We deemed these matching samples to be almost certainly authentic and sequenced Beethoven’s genome to 24-fold genomic coverage. Although we could not identify a genetic explanation for Beethoven's hearing disorder or gastrointestinal problems, we found that Beethoven had a genetic predisposition for liver disease. Metagenomic analyses revealed furthermore that Beethoven had a hepatitis B infection during at least the months prior to his death. Together with the genetic predisposition and his broadly accepted alcohol consumption, these present plausible explanations for Beethoven’s severe liver disease, which culminated in his death. Unexpectedly, an analysis of Y chromosomes sequenced from five living members of the Van Beethoven patrilineage revealed the occurrence of an extra-pair paternity event in Ludwig van Beethoven’s patrilineal ancestry.Introduction Results - Authentication of hair samples - Genetic variants associated with somatic disease - Hepatitis B virus DNA recovered from Beethoven’s hair Discussion - Authenticity of Beethoven’s genome - Comparison with living individuals’ genomes - Origins of Beethoven’s diseases - Hepatitis B virus DNA in Beethoven’s hair - Future direction

Putative Microcircuit-Level Substrates for Attention Are Disrupted in Mouse Models of Autism

BACKGROUND: Deep layer excitatory circuits in the prefrontal cortex represent the strongest locus for genetic convergence in autism, but specific abnormalities within these circuits that mediate key features of autism, such cognitive or attentional deficits, remain unknown. Attention normally increases the sensitivity of neural populations to incoming signals by decorrelating ongoing cortical circuit activity. Here we investigated whether mechanisms underlying this phenomenon might be disrupted within deep layer prefrontal circuits in mouse models of autism. METHODS: We isolated deep layer prefrontal circuits in brain slices then used single-photon GCaMP imaging to record activity from many (50-100) neurons simultaneously, in order to study patterns of spontaneous activity generated by these circuits under normal conditions and in two etiologically distinct models of autism: mice exposed to valproic acid (VPA) in utero and FMR1 KO mice. RESULTS: We found that modest doses of the cholinergic agonist carbachol normally decorrelate spontaneous activity generated by deep layer prefrontal networks. This effect was disrupted in both VPA-exposed and FMR1 KO mice, but intact following other manipulations which do not model autism. CONCLUSIONS: Our results suggest that cholinergic modulation may contribute to attention by acting on local cortical microcircuits to decorrelate spontaneous activity. Furthermore, defects in this mechanism represent a microcircuit-level endophenotype that could link diverse genetic and developmental disruptions to attentional deficits in autism. Future studies could elucidate pathways leading from various etiologies to this circuit-level abnormality, or use this abnormality itself as a target, and identify novel therapeutic strategies that restore normal circuit function

Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks

Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex