Dataset Information

FTO Genotype and Type 2 Diabetes Mellitus: Spatial Analysis and Meta-Analysis of 62 Case-Control Studies from Different Regions.

ABSTRACT: Type 2 diabetes mellitus (T2DM) is a global health problem that results from the interaction of environmental factors with genetic variants. Although a number of studies have suggested that genetic polymorphisms in the fat mass and obesity-associated (FTO) gene are associated with T2DM risk, the results have been inconsistent. To investigate whether FTO polymorphisms associate with T2DM risk and whether this association is region-related, we performed this spatial analysis and meta-analysis. More than 60,000 T2DM patients and 90,000 controls from 62 case-control studies were included in this study. Odds ratios (ORs), 95% confidence intervals (CIs) and Moran's I statistic were used to estimate the association between FTO rs9939609, rs8050136, rs1421085, and rs17817499, and T2DM risk in different regions. rs9939609 (OR = 1.15, 95% CI 1.11-1.19) and rs8050136 (OR = 1.14, 95% CI 1.10-1.18) conferred a predisposition to T2DM. After adjustment for body mass index (BMI), the association remained statistically significant for rs9939609 (OR = 1.11, 95% CI 1.05-1.17) and rs8050136 (OR = 1.08, 95% CI 1.03-1.12). In the subgroup analysis of rs9939609 and rs8050136, similar results were observed in East Asia, while no association was found in North America. In South Asia, an association for rs9939609 was revealed but not for rs8050136. In addition, no relationship was found with rs1421085 or rs17817499 regardless of adjustment for BMI. Moran's I statistic showed that significant positive spatial autocorrelations existed in rs9939609 and rs8050136. Studies on rs9939609 and rs8050136 focused on East Asia and South Asia, whereas studies on rs1421085 and rs17817499 were distributed in North America and North Africa. Our data suggest that the associations between FTO rs9939609, rs8050136 and T2DM are region-related, and the two single-nucleotide polymorphisms contribute to an increased risk of T2DM. Future studies should investigate this issue in more regions.

SUBMITTER: Yang Y

PROVIDER: S-EPMC5333059 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

FTO Genotype and Type 2 Diabetes Mellitus: Spatial Analysis and Meta-Analysis of 62 Case-Control Studies from Different Regions.

Yang Ying Y Liu Boyang B Xia Wei W Yan Jing J Liu Huan-Yu HY Hu Ling L Liu Song-Mei SM

Genes 20170211 2

Type 2 diabetes mellitus (T2DM) is a global health problem that results from the interaction of environmental factors with genetic variants. Although a number of studies have suggested that genetic polymorphisms in the fat mass and obesity-associated (<i>FTO</i>) gene are associated with T2DM risk, the results have been inconsistent. To investigate whether <i>FTO</i> polymorphisms associate with T2DM risk and whether this association is region-related, we performed this spatial analysis and meta ...[more]

PMID: 28208657

Similar Datasets

Project description:Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM.

Project description:Purpose RPGR is the most common cause of X-linked retinitis pigmentosa (RP), of which female carriers are also frequently affected. The aim of the current study was to explore the RPGR variation spectrum and associated phenotype based on the data from our lab and previous studies. Methods Variants in RPGR were selected from exome sequencing data of 7,092 probands with different eye conditions. The probands and their available family members underwent comprehensive ocular examinations. Similar data were collected from previous reports through searches in PubMed, Web of Science, and Google Scholar. Systematic analyses of genotypes, phenotypes and their correlations were performed. Results A total of 46 likely pathogenic variants, including nine missense and one in-frame variants in RCC1-like domain and 36 truncation variants, in RPGR were detected in 62 unrelated families in our in-house cohort. In addition, a total of 585 variants, including 491 (83.9%) truncation variants, were identified from the literature. Systematic analysis of variants from our in-house dataset, literature, and gnomAD suggested that most of the pathogenic variants of RPGR were truncation variants while pathogenic missense and in-frame variants were enriched in the RCC1-like domain. Phenotypic variations were present between males and female carriers, including more severe refractive error but better best corrected visual acuity (BCVA) in female carriers than those in males. The male patients showed a significant reduction of BCVA with increase of age and males with exon1-14 variants presented a better BCVA than those with ORF15 variants. For female carriers, the BCVA also showed significant reduction with increase of age, but BCVA in females with exon1-14 variants was not significant difference compared with those with ORF15 variants. Conclusion Most pathogenic variants of RPGR are truncations. Missense and in-frame variants located outside of the RCC1-like domain might be benign and the pathogenicity criteria for these variants should be considered with greater caution. The BCVA and refractive error are different between males and female carriers. Increase of age and location of variants in ORF15 contribute to the reduction of BCVA in males. These results are valuable for understanding genotypes and phenotypes of RPGR.

Project description:Background: Current evidence suggests that the information needs of people with diabetes mellitus differ across patient groups. With a view to being able to provide individualized information, this study aims to identify (i) the diabetes-related information needs of people with diabetes mellitus; (ii) different subgroups of people with specific information needs; and (iii) associated characteristics of the identified subgroups, such as sociodemographic characteristics, diabetes-related comorbidities, and well-being.Methods: This cross-sectional study was based on data from 837 respondents with diabetes mellitus who participated in the population-based KORA (Cooperative Health Research in the Augsburg Region) Health Survey 2016 in Southern Germany (KORA GEFU 4 study) (45.6% female, mean age 71.1?years, 92.8% Type 2 diabetes). Diabetes-related information needs were assessed with a questionnaire asking about patients' information needs concerning 11 diabetes-related topics, e.g. 'long-term complications' and 'treatment/therapy'. Subgroups of people with different information needs and associated characteristics were identified using latent class analysis.Results: We identified the following four classes of people with different information needs: 'high needs on all topics', 'low needs on all topics', 'moderate needs with a focus on complications and diabetes in everyday life', and 'advanced needs with a focus on social and legal aspects and diabetes research'. The classes differed significantly in age, years of education, type of diabetes, diabetes duration, diabetes-related comorbidities, smoking behaviour, diabetes education, current level of information, and time preference.Conclusions: Knowledge about different patient subgroups can be useful for tailored information campaigns or physician-patient interactions. Further research is needed to analyse health care needs in these groups, changes in information needs over the course of the disease, and prospective health outcomes.

Dataset Information

FTO Genotype and Type 2 Diabetes Mellitus: Spatial Analysis and Meta-Analysis of 62 Case-Control Studies from Different Regions.

Publications

FTO Genotype and Type 2 Diabetes Mellitus: Spatial Analysis and Meta-Analysis of 62 Case-Control Studies from Different Regions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets