Evidence map›Paper›PMID 40209151›Full record

ArticlePLoS genetics2025

Exploring the molecular basis of the genetic correlation between body mass index and brain morphological traits.

Daniela Fusco, Camilla Marinelli, Mathilde André, Lucia Troiani, Martina Noè, Fabrizio Pizzagalli, Davide Marnetto, Paolo Provero

Abstract read
In one paragraph

Article in PLoS genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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

8 authors.

Daniela FuscoDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.ORCID https://orcid.org/0009-0009-9062-571X
Camilla MarinelliDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.
Mathilde AndréDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.ORCID https://orcid.org/0000-0002-3279-0102
Lucia TroianiDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.
Martina NoèDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.
Fabrizio PizzagalliDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.ORCID https://orcid.org/0000-0003-4582-0224
Davide MarnettoDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.ORCID https://orcid.org/0000-0001-9573-0601
Paolo ProveroDepartment of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.ORCID https://orcid.org/0000-0001-8664-8630

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several studies have demonstrated significant phenotypic and genetic correlations between body mass index (BMI) and brain morphological traits derived from structural magnetic resonance imaging (sMRI). We use the sMRI, BMI, and genetic data collected by the UK Biobank to systematically compute the genetic correlations between area, volume, and thickness measurements of hundreds of brain structures on one hand, and BMI on the other. In agreement with previous literature, we find many such measurements to have negative genetic correlation with BMI. We then dissect the molecular mechanisms underlying such correlations using brain eQTL data and summary-based Mendelian randomization, thus producing an atlas of genes whose genetically regulated expression in brain tissues is pleiotropic with brain morphology and BMI. Fine-mapping followed by colocalization analysis allows, in several cases, the identification of credible sets of variants likely to be causal for both the macroscopic phenotypes and for gene expression. In particular, epigenetic fine mapping identifies variant rs7187776 in the 5' UTR of the TUFM gene as likely to be causal of increased BMI and decreased caudate volume, possibly through the creation, by the alternate allele, of an ETS binding site leading to increased chromatin accessibility, specifically in microglial cells.

Indexed as

Body Mass IndexBrainFemaleGenome-Wide Association StudyHumansMagnetic Resonance ImagingMaleMendelian Randomization AnalysisPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID40209151
PMCPMC12048161

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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.