Evidence map›Paper›PMID 38633783›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Rare variant associations with birth weight identify genes involved in adipose tissue regulation, placental function and insulin-like growth factor signalling.

Katherine A Kentistou, Brandon E M Lim, Lena R Kaisinger, Valgerdur Steinthorsdottir, Luke N Sharp, Kashyap A Patel, Vinicius Tragante, Gareth Hawkes, Eugene J Gardner, Thorhildur Olafsdottir and 12 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. 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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 3 institutions in 2 countries.

Katherine A KentistouMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.ORCID 0000-0002-5816-664X
Brandon E M LimDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Lena R KaisingerMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
Valgerdur SteinthorsdottirdeCODE genetics/Amgen, Inc., 102 Reykjavik, Iceland.
Luke N SharpDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Kashyap A PatelDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.ORCID 0000-0002-9240-8104
Vinicius TragantedeCODE genetics/Amgen, Inc., 102 Reykjavik, Iceland.
Gareth HawkesDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Eugene J GardnerMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
Thorhildur OlafsdottirdeCODE genetics/Amgen, Inc., 102 Reykjavik, Iceland.
Andrew R WoodDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Yajie ZhaoMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
Gudmar ThorleifssondeCODE genetics/Amgen, Inc., 102 Reykjavik, Iceland.
Felix R DayMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
Susan E OzanneMRC Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK.
Andrew T HattersleyDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.ORCID 0000-0001-5620-473X
Stephen O'RahillyMRC Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK.ORCID 0000-0003-2199-4449
Kari StefanssondeCODE genetics/Amgen, Inc., 102 Reykjavik, Iceland.
Ken K OngMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
Robin N BeaumontDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
John R B PerryMRC Epidemiology Unit, Box 285 Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK.
Rachel M FreathyDepartment of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
University of Cambridge · GBUniversity of Exeter · GBdeCODE Genetics (Iceland) · IS

Funding

Integrating genomic studies of gestational duration and birth weight to understand maternal and fetal causes of adverse pregnancy outcomes and links with later diseasesR01HD101669 · NICHD · CINCINNATI CHILDRENS HOSP MED CTR · PI FREATHY, RACHEL, JACOBSSON, BO · 2021 to 2024
$2.1M
NICHD NIH HHS R01 HD101669Wellcome Trust
6 · The paper itself

Abstract

Investigating the genetic factors influencing human birth weight may lead to biological insights into fetal growth and long-term health. Genome-wide association studies of birth weight have highlighted associated variants in more than 200 regions of the genome, but the causal genes are mostly unknown. Rare genetic variants with robust evidence of association are more likely to point to causal genes, but to date, only a few rare variants are known to influence birth weight. We aimed to identify genes that harbour rare variants that impact birth weight when carried by either the fetus or the mother, by analysing whole exome sequence data in UK Biobank participants. We annotated rare (minor allele frequency <0.1%) protein-truncating or high impact missense variants on whole exome sequence data in up to 234,675 participants with data on their own birth weight (fetal variants), and up to 181,883 mothers who reported the birth weight of their first child (maternal variants). Variants within each gene were collapsed to perform gene burden tests and for each associated gene, we compared the observed fetal and maternal effects. We identified 8 genes with evidence of rare fetal variant effects on birth weight, of which 2 also showed maternal effects. One additional gene showed evidence of maternal effects only. We observed 10/11 directionally concordant associations in an independent sample of up to 45,622 individuals (sign test

Identifiers

PMID38633783
PMCPMC11023655
OpenAlexW4393947964

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.