RESUMO
Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.
Assuntos
Diabetes Mellitus Tipo 2 , Diabetes Gestacional , Diabetes Mellitus Tipo 2/epidemiologia , Diabetes Mellitus Tipo 2/genética , Diabetes Gestacional/genética , Feminino , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Glucose , Humanos , Polimorfismo de Nucleotídeo Único/genética , GravidezRESUMO
Adiponectin, a protein secreted by the adipose tissue, is an endogenous insulin sensitizer with circulating levels that are decreased in obese and diabetic subjects. Recently, circulating levels of adiponectin have been correlated with breast cancer risk. Our previous work showed that polymorphisms of the adiponectin pathway are associated with breast cancer risk. We conducted the first study of adiponectin pathways in African Americans and Hispanics in the Women's Health Initiative SNP Health Association Resource cohort of 3,642 self-identified Hispanic women and 8,515 self-identified African American women who provided consent for DNA analysis. Single nucleotide polymorphisms (SNPs) from three genes were included in this analysis: ADIPOQ, ADIPOR1, and ADIPOR2. The genome-wide human SNP array 6.0 (909,622 SNPs) ( www.affymetrix.com ) was used. We found that rs1501299, a functional SNP of ADIPOQ that we previously reported was associated with breast cancer risk in a mostly Caucasian population, was also significantly associated with breast cancer incidence (HR for the GG/TG genotype: 1.23; 95 % CI 1.059-1.43) in African American women. We did not find any other SNPs in these genes to be associated with breast cancer incidence. This is the first study assessing the role of adiponectin pathway SNPs in breast cancer risk in African Americans and Hispanics. RS1501299 is significantly associated with breast cancer risk in African American women. As the rates of obesity and diabetes increase in African Americans and Hispanics, adiponectin and its functional SNPs may aid in breast cancer risk assessment.
Assuntos
Adiponectina/genética , Adiponectina/metabolismo , Negro ou Afro-Americano , Neoplasias da Mama/metabolismo , Hispânico ou Latino , Polimorfismo Genético , Transdução de Sinais , Idoso , Alelos , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/genética , Feminino , Predisposição Genética para Doença , Genótipo , Humanos , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , Risco , Fatores de RiscoRESUMO
OBJECTIVES: Infant mortality rates (IMR) and under-five mortality rates (U5MR) in Tuvalu (2010 population 11,149) for 1990-2011 were evaluated to determine best estimates of levels and trends. METHODS: Estimates were graphed over time to identify trends/inconsistencies, and censored for reliability/plausibility. Where possible, 95% confidence intervals (CIs) and tests for linear trend were calculated. RESULTS: Ministry of Health (MoH) data indicates IMR and U5MR (per 1,000 live births) declined over 1990-2008: IMR 62 (95%CI 46-81) for 1991-93 (51 deaths) to 19 (95%CI 10-33) for 2006-08 (12 deaths); U5MR 67 (95%CI 50-87) for 1991-93 (55 deaths) to 19 (95%CI 10-33) for 2006-08 (12 deaths). The 2007 Demographic and Health Survey (DHS) suggests recent trends are increasing: IMR 24 for 1998-2002 to 31 (95%CI 20-42) for 2003-07; U5MR 29 for 1998-2002 to 36 (95%CI 30-43) for 2003-07 (deaths not provided). Tests for linear trend and 95%CIs indicate MoH declines are statistically significant, but recent increased estimates from DHS are not, and could be affected by recall bias. CONCLUSIONS: Small populations provide challenges in interpretation of IMR/U5MR trends. To ensure the correct interpretation of rates, CIs (95%) and tests for trend should be calculated. Tuvalu has experienced steady decline in IMR/U5MR over the past 20 years.
Assuntos
Mortalidade Infantil , Pré-Escolar , Demografia/estatística & dados numéricos , Feminino , Objetivos , Humanos , Lactente , Recém-Nascido , Masculino , Micronésia/epidemiologia , Reprodutibilidade dos TestesRESUMO
Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of complex disease. Regardless of context, the practical utility of this information will ultimately depend upon the quality of the original data. Quality control (QC) procedures for GWAS are computationally intensive, operationally challenging, and constantly evolving. Here we enumerate some of the challenges in QC of GWAS data and describe the approaches that the electronic MEdical Records and Genomics (eMERGE) network is using for quality assurance in GWAS data, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of GWAS data, including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We propose best practices and discuss areas of ongoing and future research.