2020
DOI: 10.7554/elife.55851
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Genetic mapping of etiologic brain cell types for obesity

Abstract: The underlying cell types mediating predisposition to obesity remain largely obscure. Here, we integrated recently published single-cell RNA-sequencing (scRNA-seq) data from 727 peripheral and nervous system cell types spanning 17 mouse organs with body mass index (BMI) genome-wide association study (GWAS) data from >457,000 individuals. Developing a novel strategy for integrating scRNA-seq data with GWAS data, we identified 26, exclusively neuronal, cell types from the hypothalamus, subthalamus, midbrain, … Show more

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Cited by 102 publications
(126 citation statements)
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“…For both AFS and AFB, all SNPs with p <1×10 -5 in the pooled GWAS meta-analysis were used as input. Based on the results of the tissue enrichment analysis, we used CELLECT 88 to identify nervous system cell types that are enriched for expression of genes in loci reaching p <1×10 -5 in the GWAS, using RNAseq data from mouse brain. 29 A similar approach using tabula muris RNAseq data 87 helped prioritize additional central nervous system and pancreatic cell types for AFS.…”
Section: Methodsmentioning
confidence: 99%
“…For both AFS and AFB, all SNPs with p <1×10 -5 in the pooled GWAS meta-analysis were used as input. Based on the results of the tissue enrichment analysis, we used CELLECT 88 to identify nervous system cell types that are enriched for expression of genes in loci reaching p <1×10 -5 in the GWAS, using RNAseq data from mouse brain. 29 A similar approach using tabula muris RNAseq data 87 helped prioritize additional central nervous system and pancreatic cell types for AFS.…”
Section: Methodsmentioning
confidence: 99%
“…Additional insight could be obtained by performing cell prioritization analyses from human post-mortem brain samples and/or induced pluripotent stem cells from individuals with relevant genetic backgrounds using LDSC, MAGMA and DEPICT to identify genes that are predicted to be functionally similar to causal genes. Additionally, the recently developed computational toolkit CELLECT can provide additional insight in cell type enrichment 34 . CELLECT builds upon gene prioritization models, such as LDSC, DEPICT and MAGMA and subsequently performs cell type prioritization analyses using a continuous representation of cell type expression, rather than binary representation.…”
Section: Discussionmentioning
confidence: 99%
“…Hierarchical clustering and marker gene analysis for our 24 mouse VMH neuron clusters using CELLEX (Timshel, Thompson, and Pers 2020) revealed that many cell groups were highly related to other VMH neuron clusters (Fig. 2D, E; Table 3).…”
Section: A Simplified Parceling Scheme Defines Anatomically-distinct Vmh Neuron Populationsmentioning
confidence: 98%