{"entity": "publication", "iuid": "6d7d266081f34129a0c2cf298f226f39", "timestamp": "2026-04-19T02:05:30.433Z", "links": {"self": {"href": "https://publications.scilifelab.se/publication/6d7d266081f34129a0c2cf298f226f39.json"}, "display": {"href": "https://publications.scilifelab.se/publication/6d7d266081f34129a0c2cf298f226f39"}}, "title": "A Genetic Risk Score Is Associated with Weight Loss Following Roux-en Y Gastric Bypass Surgery.", "authors": [{"family": "Bandstein", "given": "Marcus", "initials": "M"}, {"family": "Voisin", "given": "Sarah", "initials": "S"}, {"family": "Nilsson", "given": "Emil K", "initials": "EK"}, {"family": "Schultes", "given": "Bernd", "initials": "B"}, {"family": "Ernst", "given": "Barbara", "initials": "B"}, {"family": "Thurnheer", "given": "Martin", "initials": "M"}, {"family": "Benedict", "given": "Christian", "initials": "C"}, {"family": "Mwinyi", "given": "Jessica", "initials": "J"}, {"family": "Schi\u00f6th", "given": "Helgi B", "initials": "HB"}], "type": "journal article", "published": "2016-09-00", "journal": {"volume": "26", "issn": "1708-0428", "issue": "9", "pages": "2183-2189", "title": "Obes Surg", "issn-l": "0960-8923"}, "abstract": "Currently, Roux-en Y gastric bypass (RYGB) is the most efficient therapy for severe obesity. Weight loss after surgery is, however, highly variable and genetically influenced. Genome-wide association studies have identified several single nucleotide polymorphisms (SNP) associated with body mass index (BMI) and waist-hip ratio (WHR). We aimed to identify two genetic risk scores (GRS) composed of weighted BMI and WHR-associated SNPs to estimate their impact on excess BMI loss (EBMIL) after RYGB surgery.\n\nTwo hundred and thirty-eight obese patients (BMI 45.1\u2009\u00b1\u20096.2\u00a0kg/m(2), 74\u00a0% women), who underwent RYGB, were genotyped for 35 BMI and WHR-associated SNPs and were followed up after 2\u00a0years. SNPs with high impact on post-surgical weight loss were filtered out using a random forest model. The filtered SNPs were combined into a GRS and analyzed in a linear regression model.\n\nAn up to 11\u00a0% lower EBMIL with higher risk score was estimated for two GRS models (P\u2009=\u20090.026 resp. P\u2009=\u20090.021) composed of seven BMI-associated SNPs (closest genes: MC4R, TMEM160, PTBP2, NUDT3, TFAP2B, ZNF608, MAP2K5, GNPDA2, and MTCH2) and of three WHR-associated SNPs (closest genes: HOXC13, LYPLAL1, and DNM3-PIGC). Patients within the lowest GRS quartile had higher EBMIL compared to patients within the other three quartiles in both models.\n\nWe identified two GRSs composed of BMI and WHR-associated SNPs with significant impact on weight loss after RYGB surgery using random forest analysis as a SNP selection tool. The GRS may be useful to pre-surgically evaluate the risks for patients undergoing RYGB surgery.", "doi": "10.1007/s11695-016-2072-9", "pmid": "26832135", "labels": {"National Genomics Infrastructure": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "10.1007/s11695-016-2072-9"}, {"db": "pmc", "key": "PMC4985537"}], "notes": [], "created": "2017-05-03T12:59:48.137Z", "modified": "2024-01-16T13:48:49.594Z"}