{"type": "root", "children": [{"type": "t", "text": "<head>\n <meta charset=\"UTF-8\">\n <title>Summary of FAM163B Function</title>\n </head>\n \n "}, {"type": "p", "children": [{"type": "t", "text": "\n Recent large‐scale genetic studies have focused on dissection of the biological basis of complex traits such as smoking behavior and metabolic regulation. In one investigation of smoking phenotypes that included meta‐analyses of cohorts exceeding 200,000 individuals, several novel loci were uncovered that contribute to the variance in cigarette consumption and related behaviors (see"}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": "and."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": " Although FAM163B was not the central focus of these studies, its genomic region emerged from analyses that combined genetic association statistics despite missing data, and it has been highlighted as one of the candidate genes warranting follow‐up.\n "}]}, {"type": "t", "text": "\n "}, {"type": "p", "children": [{"type": "t", "text": "\n FAM163B is now considered a putative contributor to the genetic architecture underlying tobacco use. Its association with smoking‐related outcomes suggests that the gene may be involved in the cellular signaling pathways that regulate neural circuits implicated in addictive behaviors. Moreover, related work addressing insulin resistance in skeletal muscle—which explored mechanisms of type 2 diabetes—hints that FAM163B might also, directly or indirectly, interface with pathways involved in metabolic regulation."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "3"}]}, {"type": "t", "text": " \n "}]}, {"type": "t", "text": "\n "}, {"type": "p", "children": [{"type": "t", "text": "\n Even though its exact molecular function remains to be fully elucidated, the converging evidence from meta-analyses and fine-mapping studies supports the idea that FAM163B could modulate both neural and metabolic physiology. In studies applying novel statistical approaches for multi-variant analysis, the signal attributed to FAM163B was part of a pattern of allelic heterogeneity at known loci for tobacco use"}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": ", and further gene identification efforts have continued to implicate FAM163B as deserving of additional functional characterization."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "4"}]}, {"type": "t", "text": "\n "}]}, {"type": "t", "text": "\n "}, {"type": "p", "children": [{"type": "t", "text": "\n In summary, FAM163B appears to be a candidate gene that may influence smoking behavior through regulation of neural signaling, and it might also play a role in metabolic pathways that are relevant to insulin resistance. These multifaceted associations underscore the need for continued research to clarify its molecular mechanisms and physiological impact.\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Unknown Authors "}, {"type": "b", "children": [{"type": "t", "text": "Genome-wide meta-analyses identify multiple loci associated with smoking behavior."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Nat Genet (2010)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1038/ng.571"}], "href": "https://doi.org/10.1038/ng.571"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "20418890"}], "href": "https://pubmed.ncbi.nlm.nih.gov/20418890"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Yu Jiang, Sai Chen, Daniel McGuire, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "PLoS Genet (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1371/journal.pgen.1007452"}], "href": "https://doi.org/10.1371/journal.pgen.1007452"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30016313"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30016313"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "Qiuju Ding, Amelia Li Min Tan, E J Parra, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Genome-wide meta-analysis associates GPSM1 with type 2 diabetes, a plausible gene involved in skeletal muscle function."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "J Hum Genet (2020)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1038/s10038-019-0720-3"}], "href": "https://doi.org/10.1038/s10038-019-0720-3"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "31959871"}], "href": "https://pubmed.ncbi.nlm.nih.gov/31959871"}]}, {"type": "r", "ref": 4, "children": [{"type": "t", "text": "Hiroyuki Miwa, Nobuyuki Itoh "}, {"type": "b", "children": [{"type": "t", "text": "Unknown genes, "}, {"type": "a", "children": [{"type": "t", "text": "i"}], "href": "i"}, {"type": "t", "text": "Cebelin"}, {"type": "a", "children": [{"type": "t", "text": "/i"}], "href": "/i"}, {"type": "t", "text": " and "}, {"type": "a", "children": [{"type": "t", "text": "i"}], "href": "i"}, {"type": "t", "text": "Cebelin-like"}, {"type": "a", "children": [{"type": "t", "text": "/i"}], "href": "/i"}, {"type": "t", "text": ", predominantly expressed in mouse brain."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Heliyon (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1016/j.heliyon.2018.e00773"}], "href": "https://doi.org/10.1016/j.heliyon.2018.e00773"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30294689"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30294689"}]}]}]}