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dc.contributor.authorStefanucci, L
dc.contributor.authorMoslemi, C
dc.contributor.authorTomé, AR
dc.contributor.authorVirtue, S
dc.contributor.authorBidault, G
dc.contributor.authorGleadall, NS
dc.contributor.authorWatson, LPE
dc.contributor.authorKwa, JE
dc.contributor.authorBurden, F
dc.contributor.authorFarrow, S
dc.contributor.authorChen, J
dc.contributor.authorVõsa, U
dc.contributor.authorBurling, K
dc.contributor.authorWalker, L
dc.contributor.authorOrd, J
dc.contributor.authorBarker, P
dc.contributor.authorWarner, J
dc.contributor.authorFrary, A
dc.contributor.authorRenhstrom, K
dc.contributor.authorAshford, SE
dc.contributor.authorPiper, J
dc.contributor.authorBiggs, G
dc.contributor.authorErber, WN
dc.contributor.authorHoffman, GJ
dc.contributor.authorSchoenmakers, N
dc.contributor.authorErikstrup, C
dc.contributor.authorRieneck, K
dc.contributor.authorDziegiel, MH
dc.contributor.authorUllum, H
dc.contributor.authorAzzu, V
dc.contributor.authorVacca, M
dc.contributor.authorAparicio, HJ
dc.contributor.authorHui, Q
dc.contributor.authorCho, K
dc.contributor.authorSun, YV
dc.contributor.authorWilson, PW
dc.contributor.authorBayraktar, OA
dc.contributor.authorVidal-Puig, A
dc.contributor.authorOstrowski, SR
dc.contributor.authorAstle, WJ
dc.contributor.authorOlsson, ML
dc.contributor.authorStorry, JR
dc.contributor.authorPedersen, OB
dc.contributor.authorOuwehand, WH
dc.contributor.authorChatterjee, K
dc.contributor.authorVuckovic, D
dc.contributor.authorFrontini, M
dc.date.accessioned2024-06-04T12:37:17Z
dc.date.issued2024-06-20
dc.date.updated2024-06-04T10:59:17Z
dc.description.abstractBackground Obesity rates have nearly tripled in the past 50 years, and by 2030, more than one billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are aetiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments. Methods We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in SMIM1 and the general population, leveraging data from 5 cohorts. Metabolic characterization of SMIM1-/- individuals was performed using plasma biochemistry, calorimetric chamber and DEXA scan. Findings We found that individuals homozygous for a loss-of-function genetic variant in the Small Integral Membrane Protein 1 (SMIM1) gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin-adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure. Conclusion This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them.en_GB
dc.description.sponsorshipNational Institute for Health and Care Research (NIHR)en_GB
dc.description.sponsorshipBritish Heart Foundationen_GB
dc.description.sponsorshipNHS Blood and Transplanten_GB
dc.identifier.citationPublished online 20 June 2024en_GB
dc.identifier.doi10.1016/j.medj.2024.05.015
dc.identifier.urihttp://hdl.handle.net/10871/136120
dc.identifierORCID: 0000-0001-8074-6299 (Frontini, Mattia)
dc.language.isoenen_GB
dc.publisherCell Pressen_GB
dc.relation.urlhttps://zenodo.org/records/10685501en_GB
dc.relation.urlhttps://github.com/stefanucci-luca/vel_ko_analysisen_GB
dc.rights© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)en_GB
dc.titleSMIM1 absence is associated with reduced energy expenditure and excess weighten_GB
dc.typeArticleen_GB
dc.date.available2024-06-04T12:37:17Z
dc.descriptionThis is the final version. Available on open access from Cell Press via the DOI in this recorden_GB
dc.descriptionData and code availability; Participants’ phenotypes and SMIM1 locus genotypes are accessible via the relevant cohort environments: UK Biobank (https://www.ukbiobank.ac.uk/) and MVP (https://www.mvp.va.gov/pwa/discover-mvp-data). Access to these cohorts requires an active project application. All the data generated for this study are available in an anonymized version in supplementary tables or in the Zenodo repository at: https://zenodo.org/records/10685501. The code used to analyze the cohorts is available at https://github.com/stefanucci-luca/vel_ko_analysis. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.en_GB
dc.identifier.eissn2666-6340
dc.identifier.journalMeden_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2024-05-29
dcterms.dateSubmitted2023-08-07
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2024-05-29
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-06-04T10:59:20Z
refterms.versionFCDAM
refterms.dateFOA2024-07-05T14:23:07Z
refterms.panelAen_GB
exeter.rights-retention-statementNo


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© 2024 The Author(s). Published by Elsevier Inc.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Except where otherwise noted, this item's licence is described as © 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)