Evidence map›Paper›PMID 32566943›Full record

ReviewHuman molecular genetics2020

Genomics at cellular resolution: insights into cognitive disorders and their evolution.

Stefano Berto, Yuxiang Liu, Genevieve Konopka

Abstract readReview
In one paragraph

Review in Human molecular genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Stefano Berto
Yuxiang Liu
Genevieve Konopka

Funding

From ion channels to graph theory in sensorimotor learningUF1NS115821 · NINDS · UNIVERSITY OF CHICAGO · PI KONOPKA, GENEVIEVE, MACLEAN, JASON NEIL · 2020 to 2020
$3.9M
Human Specific Brain DNA Methylation and Neuropsychiatric DiseasesR01MH103517 · NIMH · GEORGIA INSTITUTE OF TECHNOLOGY · PI JORDAN, IRVING KING, PREUSS, TODD M · 2015 to 2019
$3.5M
Functional dissection of mammalian vocal communicationR01DC014702 · NIDCD · UT SOUTHWESTERN MEDICAL CENTER · PI KONOPKA, GENEVIEVE · 2016 to 2020
$1.7M
NIDCD NIH HHS R01 DC014702NIMH NIH HHS R01 MH103517NINDS NIH HHS UF1 NS115821
6 · The paper itself

Abstract

High-throughput genomic sequencing approaches have held the promise of understanding and ultimately leading to treatments for cognitive disorders such as autism spectrum disorders, schizophrenia and Alzheimer's disease. Although significant progress has been made into identifying genetic variants associated with these diseases, these studies have also uncovered that these disorders are mostly genetically complex and thus challenging to model in non-human systems. Improvements in such models might benefit from understanding the evolution of the human genome and how such modifications have affected brain development and function. The intersection of genome-wide variant information with cell-type-specific expression and epigenetic information will further assist in resolving the contribution of particular cell types in evolution or disease. For example, the role of non-neuronal cells in brain evolution and cognitive disorders has gone mostly underappreciated until the recent availability of single-cell transcriptomic approaches. In this review, we discuss recent studies that carry out cell-type-specific assessments of gene expression in brain tissue across primates and between healthy and disease populations. The emerging results from these studies are beginning to elucidate how specific cell types in the evolved human brain are contributing to cognitive disorders.

Indexed as

Evolution, MolecularGenetic Predisposition to DiseaseGenetics, PopulationGenomeAnimalsCognition DisordersGenome-Wide Association StudyGenomicsHumansPrimatesTranscriptome

Identifiers

PMID32566943
PMCPMC7530518

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.