11 research outputs found
Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin
Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loc
New genetic loci link adipose and insulin biology to body fat distribution.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms
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GOG 8020/210: Risk stratification of lymph node metastasis, disease progression and survival using single nucleotide polymorphisms in endometrial cancer: An NRG oncology/gynecologic oncology group study
ObjectivesThe ability to stratify a patient's risk of metastasis and survival permits more refined care. A proof of principle study was undertaken to investigate the relationship between single nucleotide polymorphisms (SNPs) in literature based candidate cancer genes and the risk of nodal metastasis and clinical outcome in endometrioid endometrial cancer (EEC) patients.MethodsSurgically-staged EEC patients from the Gynecologic Oncology Group or Washington University School of Medicine with germline DNA available were eligible. Fifty-four genes represented by 384 SNPs, were evaluated by Illumina Custom GoldenGate array. Association with lymph node metastases was the primary outcome. Progression-free survival (PFS) and overall survival (OS) was also evaluated.Results361 SNPs with high quality genotype data were evaluated in 337 patients with outcome data. Five SNPs in CXCR2 had an odds ratio (OR) between 0.68 and 0.70 (p-value ≤ 0.025). The A allele rs946486 in ABL had an OR of 1.5 (p-value = 0.01) for metastasis. The G allele in rs7795743 in EGFR had an OR for metastasis of 0.68 (p-value = 0.02) and hazard ratio (HR) for progression of 0.66 (p-value = 0.004). Importantly, no SNP met genome wide significance after adjusting for multiple test correcting and clinical covariates. The A allele in rs2159359 SNP in NME1 and the G allele in rs13222385 in EGFR were associated with worse OS. Both exhibited genome wide significance; rs13222385 remained significant after adjusting for prognostic clinical variables.ConclusionSNPs in cancer genes including rs2159359 SNP in NME1 and rs13222385 in EGFR may stratify risk in EEC and are prioritized for further investigation
Chemotherapy Response Rates Among Patients With Endometrial Cancer Who Have Elevated Serum Platelets
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Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin
Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci