Gascon, A. | Search bioRxiv

bioRxiv2021

Dense cortical input to the rostromedial tegmental nucleus mediates aversive signaling

AO_SCPLOWBSTRACTC_SCPLOWThe rostromedial tegmental nucleus (RMTg) encodes negative reward prediction error (RPE) and plays an important role in guiding behavioral responding to aversive stimuli. While initial studies describing the RMTg revealed the presence of cortical afferents, the density and distribution of this input has not been explored in detail. In addition, the functional consequences of cortical modulation of RMTg signaling are only just beginning to be investigated. The current study anatomically and functionally characterizes cortical input to the RMTg in rats. Findings from this work reveal dense input spanning the entire medial prefrontal cortex (PFC) as well as the orbitofrontal cortex and anterior insular cortex. Afferents were most dense in the dorsomedial subregion of the PFC (dmPFC), an area which has also been implicated in both RPE signaling and aversive responding. RMTg-projecting dmPFC neurons originate in layer V and collateralize extensively throughout the brain. In-situ mRNA hybridization further revealed that neurons in this circuit are predominantly D1 receptor-expressing with a high degree of D2 receptor colocalization. Optogenetic stimulation of dmPFC terminals in the RMTg drives avoidance, and cFos expression is enhanced in this neural circuit during exposure to aversive stimuli. Exposure to such aversive stimuli results in significant physiological and structural plasticity suggestive of a loss of top-down modulation of RMTg-mediated signaling. Altogether, these data reveal the presence of a prominent cortico-subcortical projection involved in adaptive behavioral responding and provide a foundation for future work aimed at exploring alterations in circuit function in diseases characterized by deficits in cognitive control over the balance between reward and aversion.

neuroscience↗

bioRxiv2020

Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores

Some organisations like 23andMe and the UK Biobank have large genomic databases that they re-use for multiple different genome-wide association studies (GWAS). Even research studies that compile smaller genomic databases often utilise these databases to investigate many related traits. It is common for the study to report a genetic risk score (GRS) model for each trait within the publication. Here we show that under some circumstances, these GRS models can be used to recover the genetic variants of individuals in these genomic databases--a reconstruction attack. In particular, if two GRS models are trained using a largely overlapping set of participants, then it is often possible to determine the genotype for each of the individuals who were used to train one GRS model, but not the other. We demonstrate this theoretically and experimentally by analysing the Cornell Dog Genome database. The accuracy of our reconstruction attack depends on how accurately we can estimate the rate of co-occurrence of pairs of SNPs within the private database, so if this aggregate information is ever released, it would drastically reduce the security of a private genomic database. Caution should be applied when using the same database for multiple analysis, especially when a small number of individuals are included or excluded from one part of the study.

genomics↗