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. 2016 Dec 22;17(Suppl 3):158.
doi: 10.1186/s12863-016-0466-2.

A Compendium of Human Genes Regulating Feeding Behavior and Body Weight, Its Functional Characterization and Identification of GWAS Genes Involved in Brain-Specific PPI Network

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Free PMC article

A Compendium of Human Genes Regulating Feeding Behavior and Body Weight, Its Functional Characterization and Identification of GWAS Genes Involved in Brain-Specific PPI Network

Elena V Ignatieva et al. BMC Genet. .
Free PMC article

Abstract

Background: Obesity is heritable. It predisposes to many diseases. The objectives of this study were to create a compendium of genes relevant to feeding behavior (FB) and/or body weight (BW) regulation; to construct and to analyze networks formed by associations between genes/proteins; and to identify the most significant genes, biological processes/pathways, and tissues/organs involved in BW regulation.

Results: The compendium of genes controlling FB or BW includes 578 human genes. Candidate genes were identified from various sources, including previously published original research and review articles, GWAS meta-analyses, and OMIM (Online Mendelian Inheritance in Man). All genes were ranked according to knowledge about their biological role in body weight regulation and classified according to expression patterns or functional characteristics. Substantial and overrepresented numbers of genes from the compendium encoded cell surface receptors, signaling molecules (hormones, neuropeptides, cytokines), transcription factors, signal transduction proteins, cilium and BBSome components, and lipid binding proteins or were present in the brain-specific list of tissue-enriched genes identified with TSEA tool. We identified 27 pathways from KEGG, REACTOME and BIOCARTA whose genes were overrepresented in the compendium. Networks formed by physical interactions or homological relationships between proteins or interactions between proteins involved in biochemical/signaling pathways were reconstructed and analyzed. Subnetworks and clusters identified by the MCODE tool included genes/proteins associated with cilium morphogenesis, signal transduction proteins (particularly, G protein-coupled receptors, kinases or proteins involved in response to insulin stimulus) and transcription regulation (particularly nuclear receptors). We ranked GWAS genes according to the number of neighbors in three networks and revealed 22 GWAS genes involved in the brain-specific PPI network. On the base of the most reliable PPIs functioning in the brain tissue, new regulatory schemes interpreting relevance to BW regulation are proposed for three GWAS genes (ETV5, LRP1B, and NDUFS3).

Conclusions: A compendium comprising 578 human genes controlling FB or BW was designed, and the most significant functional groups of genes, biological processes/pathways, and tissues/organs involved in BW regulation were revealed. We ranked genes from the GWAS meta-analysis set according to the number and quality of associations in the networks and then according to their involvement in the brain-specific PPI network and proposed new regulatory schemes involving three GWAS genes (ETV5, LRP1B, and NDUFS3) in BW regulation. The compendium is expected to be useful for pathology risk estimation and for design of new pharmacological approaches in the treatment of human obesity.

Keywords: Body weight regulation; Brain; Database; Feeding behavior; GWAS meta-analysis; Network; PPIs.

Figures

Fig. 1
Fig. 1
Venn diagram representing the numbers of genes in all gene sets Publications, OMIM, Syndromes, and GWAS meta-analysis used for creating the compendium of human genes controlling BW/FB. The red and blue dashed lines denote groups of genes obtained after ranking genes according to the knowledge of their biological role in body weight control
Fig. 2
Fig. 2
Distribution of functions of genes from the compendium. Panel a The fractions of protein-coding genes and other genes. Panel b Fractions of major functional groups of genes in the list of protein-coding genes
Fig. 3
Fig. 3
Association of genes from the compendium with major KEGG, REACTOME and BIOCARTA pathways. Pathways with fold enrichment > 1.5 and BH adjusted p-value < 5*10−2 are presented. Only genes from Rank_1: genes with biological interpretation were involved in analysis
Fig. 4
Fig. 4
The fractions of genes classified according to tissue expression patterns and calculated for all protein-coding genes (Genome) or for all genes from the compendium (578_all_Compendium) and gene sets Publications, OMIM_allelic_variants, OMIM_all_text, GWAS meta-analysis, Syndromes. Panel a presents the fractions of genes classified into all six expression categories described in [42] and the category Not found. Panel b presents the fractions of genes belonging to three consolidated groups: (1) Expressed in all + Mixed; (2) Not detected + Not found; (3) Tissue elevated. The significances of the Chi-square test comparing the fractions of genes in test groups with the fractions in the whole-genome dataset are indicated with one (p-value < 0.05), two (p-value < 0.01), or three (p-value < 0.001) asterisks. The red and blue dotted lines in panel a and the orange dotted line in panel b denote the levels observed in the whole genome set of protein-coding genes
Fig. 5
Fig. 5
The heat map depicts the results of tissue-specific expression analysis performed with TSEA. Only tissues with overrepresented (p-value <0.05) cell-specific lists of tissue-enriched genes identified at the overlap with genes from the compendium or seven sets (Rank_1: genes with biological interpretation, Rank_2: genes without biological interpretation, Publications, OMIM_allelic_variants, OMIM_all_text, GWAS meta-analysis, and Syndromes) are shown. P-values derived by Fisher’s exact test with the Benjamini-Hochberg correction were obtained from the TSEA tool
Fig. 6
Fig. 6
The number of genes from the compendium found with TSEA tool at the overlap with the cell-specific lists of transcripts expressed in a tissue-enriched manner. The lists of tissue-enriched transcripts were identified at pSI threshold = 0.05. Organs or tissues with Benjamini-Hochberg corrected p-values < 0.05 are presented
Fig. 7
Fig. 7
Venn diagrams representing the numbers of genes involved in three networks Experimental, Knowledge, and Homology. Panel a shows the total number of genes in each network. Panel b the lists of 20 genes that had the highest numbers of neighbors in each network
Fig. 8
Fig. 8
Unconnected subnetworks from the network formed by associations between homologous proteins (Homology). The colors of nodes indicate expression categories of genes (see legend) assigned according to data from the Human Protein Atlas [42] (see Gene expression analysis section). Thicker lines represent the stronger associations. Names of genes/proteins from the GWAS meta analysis set are shown in blue. Subnetworks with three or more nodes are outlined by dotted line. TFs – transcription factors
Fig. 9
Fig. 9
Three extended clusters revealed in the network Experimental formed by physical interactions between proteins from the compendium. Dashed lines denote the initial three clusters comprising 10, 4, and 4 proteins, which were identified with the MCODE tool. For Cluster 1: red check marks denote nine proteins annotated by GO term cilium morphogenesis; four genes marked by blue check marks are localized in primary cilia according to [56]. For Cluster 3: blue lozenges mark proteins associated with GO term response to insulin stimulus. Thicker lines represent stronger associations. The color legend and other designations follow Fig. 8
Fig. 10
Fig. 10
Genes from the GWAS meta-analysis set that are involved in three networks (Experimental, Knowledge and Homology). Red numerals indicate the numbers of genes that were found in three, two, or one networks. The colors of nodes correspond to RNA expression categories according to data obtained from the Human Protein Atlas [42] (see Gene expression analysis section). An edge width is proportional to the number of neighbors for the corresponding individual gene/protein in each network
Fig. 11
Fig. 11
Venn diagram representing intersections between the GWAS meta-analysis set and two groups of genes Brain-specific gene according to TSEA and DEG according to [49] that gave rise to the Brain-specific sublist of genes from the compendium (see Sublist of proteins expressed in brain section). Callout rectangles show genes that were found at the intersections of the gene set and two gene groups. Genes belonging to the group Rank_2: genes without interpretation are underlined
Fig. 12
Fig. 12
The Experimental_brain-specific network formed by physical interactions between genes/proteins from the sublist Brain-specific (see Sublist of proteins expressed in brain section). Ellipses denote proteins/genes from the Rank_1: genes with biological interpretation group, lozenges denote proteins/genes from Rank_2: genes without biological interpretation. Names of genes/proteins from the GWAS meta analysis set are shown in blue. Dashed rectangles denote associations that involve genes/proteins from the group Rank_2: genes without biological interpretation. Blue numerals denote the ranks of nodes calculated according to their weight (the number of first neighbors). The color legend and other designations are the same as in Figs. 8, 9, and 10
Fig. 13
Fig. 13
Putative regulatory pathways involving physical interactions revealed within the network Experimental_brain-specific: Panel a. Interactions between ETV5 and AR. Panel b. Interactions between LRP1B and SERPINE1. Panel c. The regulatory scheme involving NDUFS3, PARK2, and ADRB2. Ellipses indicate proteins/genes from the group Rank_1: genes with biological interpretation. Lozenges indicate proteins/genes from the group Rank_2: genes without biological interpretation. Genes/proteins from the GWAS meta-analysis set are shown in blue
Fig. 14
Fig. 14
A catalog of functional characteristics of genes regulating BW and FB revealed in the current study. Here we present only the most important molecular functions, biochemical/signaling pathways, organs/tissues, and biological processes: (1) non-overlapping functional groups of genes that were overrepresented in the compendium; (2) the classification of enriched pathways performed using the hierarchical scheme provided by the KEGG pathway database (the full list of pathways is presented in Fig. 3 and Additional file 2: Figure S1); (3) TSEA organs and tissues with the cell-specific lists of tissue-enriched transcripts/genes that were overrepresented with genes from the group Rank_1: genes with biological interpretation; (4) homologous groups of proteins including more than three proteins; (5) extended clusters with scores of initial clusters exceeding 3.3
Fig. 15
Fig. 15
Ranking and classification of GWAS genes from the compendium according to various criteria. For ranking based on the number of neighbors in three networks, we present three top genes for each network. For GWAS genes involved in the brain-specific network, three top genes (selected according to the number of neighbors) are presented

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