Evidence map›Paper›PMID 36153334›Full record

ArticleTranslational psychiatry2022

Quantitative trait locus analysis for endophenotypes reveals genetic substrates of core symptom domains and neurocognitive function in autism spectrum disorder.

In-Hee Lee, Ekaterina Koelliker, Sek Won Kong

Abstract read
In one paragraph

Article in Translational psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Quo Vadis translational neuroscience?Translational neuroscience · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. What are quantitative traits and how can they be used in autism research?Autism research : official journal of the International Society for Autism Research · 2023
    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.

In-Hee LeeComputational Health Informatics Program, Boston Children's Hospital, Boston, MA, 02215, USA.ORCID 0000-0002-8857-1355
Ekaterina KoellikerPsychology Department, Colby College, Waterville, ME, 04901, USA.
Sek Won KongComputational Health Informatics Program, Boston Children's Hospital, Boston, MA, 02215, USA. sekwon.kong@childrens.harvard.edu.ORCID 0000-0003-4877-7567

Funding

An environment-wide association study in autism spectrum disorders using novel bioinformatics methods and metabolomics via mass spectrometryR01MH107205 · NIMH · BOSTON CHILDREN'S HOSPITAL · PI KONG, SEK WON · 2015 to 2019
$2.1M
NIMH NIH HHS R01 MH107205NIMH NIH HHS R01MH107205
6 · The paper itself

Abstract

Autism spectrum disorder (ASD) represents a heterogeneous group of neurodevelopmental disorders and is largely attributable to genetic risk factors. Phenotypic and genetic heterogeneity of ASD have been well-recognized; however, genetic substrates for endophenotypes that constitute phenotypic heterogeneity are not yet known. In the present study, we compiled data from the Autism Genetic Resource Exchange, which contains the demographic and detailed phenotype information of 11,961 individuals. Notably, the whole-genome sequencing data available from MSSNG and iHART for 3833 individuals in this dataset was used to perform an endophenotype-wide association study. Using a linear mixed model, genome-wide association analyses were performed for 29 endophenotype scores and 0.58 million common variants with variant allele frequency ≥ 5%. We discovered significant associations between 9 genetic variants and 6 endophenotype scores comprising neurocognitive development and severity scores for core symptoms of ASD at a significance threshold of p < 5 × 10

Indexed as

Autism Spectrum DisorderEndophenotypesGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansQuantitative Trait Loci

Identifiers

PMID36153334
PMCPMC9509384

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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.