Evidence map›Paper›PMID 38766206›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Noncoding de novo mutations in

Yuan Zhang, Mian Umair Ahsan, Kai Wang

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Yuan ZhangRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Mian Umair AhsanRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Kai WangRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.

Funding

Fair Phenotype Annotation and Genomic ReinterpretationR01HG013031 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, CHUNHUA WENG · 2023 to 2026
$3.5M
NHGRI NIH HHS R01 HG013031
6 · The paper itself

Abstract

Previous genetic studies in ASD identified hundreds of high-confidence ASD genes enriched with likely deleterious protein-coding de novo mutations (DNMs). Multiple studies also demonstrated that DNMs in the non-coding genome can contribute to ASD risk. However, identification of individual risk genes enriched with noncoding DNMs has remained largely unexplored. We analyzed two datasets with over 5000 ASD families to assess the contribution of noncoding DNMs. We used two methods to assess statistical significance for noncoding DNMs: a point-based test that analyzes sites that are likely functional, and a segment-based test that analyzes 1kb genomic segments with segment-specific background mutation rates. We found that coding and noncoding DNMs in

Identifiers

PMID38766206
PMCPMC11100849

What OpenQuestion holds

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Registered trials

None linked

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.