linkstream2 microblog

WORKS IN PROGRESS – SPRING 2019
Decoding DNA
On the hunt for the genetic roots of mental illnesses

By Marcus Banks | March 4, 2019

QT:[[”
The model, a form of artificial intelligence, aims to use abstract knowledge gained in the research lab to improve clinical treatments for real patients. The ultimate goal, says Gerstein, is to use the model to develop pharmaceutical treatments that reduce the impact of schizophrenia. Part of the challenge in developing drugs to treat the disease is the fact that it is not a one-size-fits-all condition. “]]

https://theamericanscholar.org/decoding-dna/#.XH7RRlNKiqA

https://www.spectrumnews.org/news/analysis-spotlights-mutations-dark-regions-genome/

https://www.spectrumnews.org/news/massive-analysis-refines-map-autisms-genetic-roots/

Genome-wide prediction & functional characterization of the genetic basis of autism spectrum disorder, by @OlgaTroyanskaya lab
https://www.Nature.com/articles/nn.4353 Intersected candidate #ASD genes w/ #BrainSpan gene expression to find a pre-natal signal for the disease

.@GeoChurch ascribes his…ideas to narcolepsy
https://www.StatNews.com/2017/06/08/george-church-narcolepsy Advocates more neurodiversity, ie those w. ASD, OCD, ADD + narcolepsy

QT:{{”
“His condition has persuaded Church of the benefits of, even the need for, neurodiversity, meaning brains that work differently from most others. The world needs people with high-functioning autism and obsessive-compulsive disorder and attention deficit disorder and, yes, narcolepsy, he has come to believe.”
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Genome-wide…analysis implicates miRNA dysregulation in #ASD http://www.nature.com/neuro/journal/v19/n11/full/nn.4373.html 58 diff. expr. miRNAs incl 17 strongly down in cases

http://www.nature.com/neuro/journal/v19/n11/full/nn.4373.html

QT:{{”
The miRNA expression profiles were very similar between the frontal and temporal cortex, but were distinct in the cerebellum
(Supplementary Fig. 2a–f), consistent with previous observations for mRNAs11, 12. We therefore combined 95 covariate-matched samples (47 samples from 28 ASD cases and 48 samples from 28 controls;
Supplementary Fig. 1c and Supplementary Table 1) from the FC and TC for differential gene expression (DGE) analysis, comparing ASD and CTL using a linear mixed-effects regression framework to control for potential confounders (Online Methods). We identified 58 miRNAs showing significant (false discovery rate (FDR) < 0.05) expression changes between ASD and CTL: 17 were downregulated and 41 were upregulated in ASD cortex (Fig. 1b and Supplementary Table 2). The fold changes for the differentially expressed miRNAs were highly concordant between the FC and TC (Pearson correlation coefficient R = 0.96, P < 2.2 × 10−16; Fig. 1c).
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Genotype to phenotype relationships in ASD http://www.nature.com/neuro/journal/v18/n2/abs/nn.3907.html Expression differences in #brain development for LOF-containing, M v F, &c

Also, netbag finds subnets assoc w autism