2021
DOI: 10.1126/sciadv.abg0108
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Linking the FTO obesity rs1421085 variant circuitry to cellular, metabolic, and organismal phenotypes in vivo

Abstract: Variants in FTO have the strongest association with obesity; however, it is still unclear how those noncoding variants mechanistically affect whole-body physiology. We engineered a deletion of the rs1421085 conserved cis-regulatory module (CRM) in mice and confirmed in vivo that the CRM modulates Irx3 and Irx5 gene expression and mitochondrial function in adipocytes. The CRM affects molecular and cellular phenotypes in an adipose depot–dependent manner and affects organismal phenotypes that are relevant for ob… Show more

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Cited by 20 publications
(15 citation statements)
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“…In mice, studies have shown that FTO can regulate fasting and feeding, and therefore variation in FTO can result in changes of feeding behaviour and obesity 47 . Recently, it has been shown that engineered deletion in the rs1421085 (r 2 > 0.9 with rs1121980 in Europeans) conserved cis-regulatory module can affect organismal phenotypes relevant to obesity in mouse 48 . MC4R deficiency is known to be the most common cause of monogenic obesity 49 , and gain-of-function variants in MC4R is associated with lower risk of obesity, type 2 diabetes, and coronary artery disease 50 .…”
Section: Resultsmentioning
confidence: 99%
“…In mice, studies have shown that FTO can regulate fasting and feeding, and therefore variation in FTO can result in changes of feeding behaviour and obesity 47 . Recently, it has been shown that engineered deletion in the rs1421085 (r 2 > 0.9 with rs1121980 in Europeans) conserved cis-regulatory module can affect organismal phenotypes relevant to obesity in mouse 48 . MC4R deficiency is known to be the most common cause of monogenic obesity 49 , and gain-of-function variants in MC4R is associated with lower risk of obesity, type 2 diabetes, and coronary artery disease 50 .…”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, expression quantitative trait loci (eQTL) analysis revealed significantly higher expression levels of IRX3 and IRX5 in human brain, human hypothalamic arcuate-like neurons derived from human induced pluripotent stem cells (hiPSCs) and human adipocyte progenitor cells from risk-allele carriers, compared to non-risk allele carriers, whereas risk and non-risk carriers did not show significant difference of FTO expression ( Figure 1A ). Gene editing experiments in human adipocytes showed that an obesity-risk intronic variant of FTO results in higher expression of both IRX3 and IRX5 specifically in adipocyte progenitor cells ( Claussnitzer et al, 2015 ), and deletion of a cis-regulatory module (CRM) harboring the FTO risk variant in mice results in lower Irx3 and Irx5 gene expression in adipocyte progenitors to roughly 70% of control levels ( Laber et al, 2021 ). Furthermore, ∼20k-bp deletion spanning the orthologous obesity-associated interval of Fto in mice leads to down-regulation of both Irx3 and Irx5 in preadipocytes and developing hypothalamus ( Sobreira et al, 2021 ).…”
Section: Irx3 and Irx5 Homeobox Genes Are Effectors Of Fto Obesity-risk Variantsmentioning
confidence: 99%
“…To circumvent this, a mouse line harboring cis -heterozygous mutant allele of Irx3 and Irx5 ( Irx3 + Irx5 + / Irx3 Δ Irx5 eGFP ; Irx3/5 dHet ) was employed to study the effects of half-reduction of the expression of Irx3 and Irx5 on energy homeostasis ( Son et al, 2021a ). As obesity-risk variants of FTO affect the expression levels of both IRX3 and IRX5 ( Claussnitzer et al, 2015 ; Laber et al, 2021 ; Sobreira et al, 2021 ), Irx3/5 dHet mice serve as a preclinical model mimicking lower IRX3 and IRX5 expression levels in humans. Unlike Irx3 tLZ / tLZ and Irx5 eGFP / eGFP mice, Irx3/5 dHet mice do not show a runty phenotype and develop with a normal body length at weaning ( Son et al, 2021a ).…”
Section: The Importance Of Irx3 and Irx5 In Metabolic Regulationmentioning
confidence: 99%
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“…Because each edge has a corresponding absolute change of metabolite formulas (addition or subtraction), the formula assignment of an entire network component can be made from a single reliably annotated node through formula propagation (Breitling et al, 2006;Tziotis et al, 2011;Moritz et al, 2017;Amara et al, 2022). As a few examples, MDiNs have been used in this way in studies on mouse cecal samples (Walker et al, 2014), yeast (Liu et al, 2016), and mouse adipose tissue and human blood plasma (Laber et al, 2021), among others (Moritz et al, 2015;Willkommen et al, 2018). Furthermore, other methods similar to MDiNs that use mass differences for formula annotation have been developed (Weber and Viant, 2010;Morreel et al, 2014).…”
Section: Introductionmentioning
confidence: 99%