Evidence map›Paper›PMID 38197427›Full record

ArticleeLife2024

Affected cell types for hundreds of Mendelian diseases revealed by analysis of human and mouse single-cell data.

Idan Hekselman, Assaf Vital, Maya Ziv-Agam, Lior Kerber, Ido Yairi, Esti Yeger-Lotem

Open access · goldAbstract read
In one paragraph

Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

6 authors at 1 institution in 1 country.

Idan HekselmanDepartment of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Be'er Sheva, Israel.ORCID https://orcid.org/0000-0003-0529-7838
Assaf VitalDepartment of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Maya Ziv-Agam *Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Lior Kerber *Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Be'er Sheva, Israel.ORCID https://orcid.org/0009-0005-0583-5618
Ido YairiDepartment of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
Esti Yeger-LotemDepartment of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Be'er Sheva, Israel.ORCID https://orcid.org/0000-0002-8279-7898
Ben-Gurion University of the Negev · IL

Funding

Israel Science Foundation 317/19Israel Science Foundation 401/22
6 · The paper itself

Abstract

Mendelian diseases tend to manifest clinically in certain tissues, yet their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in Mendelian diseases. Overall, we inferred the likely affected cell types for 328 diseases. We corroborated our findings by literature text-mining, expert validation, and recapitulation in mouse corresponding tissues. Based on these findings, we explored characteristics of disease-affected cell types, showed that diseases manifesting in multiple tissues tend to affect similar cell types, and highlighted cases where gene functions could be used to refine inference. Together, these findings expand the molecular understanding of disease mechanisms and cellular vulnerability.

Indexed as

Single-Cell AnalysisAnimalsBiomarkersGene ExpressionHumansMicePhenotypeBiomarkerscell-type selectivitycomputational biologydata integrationhumanMendelian diseasesmousesingle-cell transcriptomicssystems biologytissue selectivity

Identifiers

PMID38197427
PMCPMC10830129
OpenAlexW4390695629

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.