69 research outputs found

    Joint Effect of Genetic and Lifestyle Risk Factors on Type 2 Diabetes Risk among Chinese Men and Women

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    More than 40 genetic susceptibility loci have been reported for type 2 diabetes (T2D). Recently, the combined effect of genetic variants has been investigated by calculating a genetic risk score. We evaluated 36 genome-wide association study (GWAS) identified SNPs in 2,679 T2D cases and 3322 controls in middle-age Han Chinese. Fourteen SNPs were significantly associated with T2D in analysis adjusted for age, sex and BMI. We calculated two genetic risk scores (GRS) (GRS1 with all the 36 SNPs and GRS2 with the 14 SNPs significantly associated with T2D). The odds ratio for T2D with each GRS point (per risk allele) was 1.08 (95% CI: 1.06–1.09) for GRS1 and 1.15 (95% CI: 1.13–1.18) for GRS2. The OR for quintiles were 1.00, 1.26, 1.69, 1.95 and 2.18 (P\u3c0.0001) for GRS1 and 1.00, 1.33, 1.60, 2.03 and 2.80 (P\u3c0.001) for GRS2. Participants in the higher tertile of GRS1 and the higher BMI category had a higher risk of T2D compared to those on the lower tertiles of the GRS1 and of BMI (OR = 11.08; 95% CI: 7.39–16.62). We found similar results when we investigated joint effects between GRS1 and WHR terciles and exercise participation. We finally investigated the joint effect between tertiles of GRSs and a composite high risk score (no exercise participation and high BMI and WHR) on T2D risk. We found that compared to participants with low GRS1 and no high risk factors for T2D, those with high GRS1 and three high risk factors had a higher risk of T2D (OR = 13.06; 95% CI: 8.65–19.72) but the interaction factor was of marginal significance. The association was accentuated when we repeated analysis with the GRS2. In conclusion we found an association between GRS and lifestyle factors, alone and in combination, contributed to the risk of and T2D among middle age Chinese

    Effect of a non-dieting lifestyle randomised control trial on psychological well-being and weight management in morbidly obese pre-menopausal women.

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    Objective This study examined the effects of a non-dieting lifestyle intervention approach for morbidly obese women designed in the framework of the self-determination theory (SDT) and Health at Every Size on weight maintenance and psychological functioning. Participants and design Predominantly white (97%), morbidly obese (BMI ≥ 35 kg m-2 with at least one co-morbid condition or a BMI ≥ 40 kg m-2) pre-menopausal women (N = 62), aged between 24 and 55 years were initially randomly assigned to 12 weeks of lifestyle intervention (IIG) or delayed start control group (DSCG). The program consisted of 3 months intensive lifestyle intervention followed by 9 month maintenance phase. The DSCG group commenced the program after 3 months. Results and conclusions Initially, the IIG showed a significant decrease in body weight (baseline to end of the RCT phase) compared with a significant increase in the DSCG group. However, no significant changes in weight status were evident in either group at 12 months compared with baseline. The 3-month intensive intervention resulted in significantly improved psychological functioning in both groups, which were maintained at 12 months. The study provides additional support for a non-dieting, theory-based, lifestyle approach to weight management and psychological well-being among morbidly obese females

    Genome-Wide Association Study in East Asians Identifies Novel Susceptibility Loci for Breast Cancer

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    Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. We aimed to discover novel genetic susceptibility loci for breast cancer. We conducted a four-stage genome-wide association study (GWAS) in 19,091 cases and 20,606 controls of East-Asian descent including Chinese, Korean, and Japanese women. After analyzing 690,947 SNPs in 2,918 cases and 2,324 controls, we evaluated 5,365 SNPs for replication in 3,972 cases and 3,852 controls. Ninety-four SNPs were further evaluated in 5,203 cases and 5,138 controls, and finally the top 22 SNPs were investigated in up to 17,423 additional subjects (7,489 cases and 9,934 controls). SNP rs9485372, near the TGF-β activated kinase (TAB2) gene in chromosome 6q25.1, showed a consistent association with breast cancer risk across all four stages, with a P-value of 3.8×10−12 in the combined analysis of all samples. Adjusted odds ratios (95% confidence intervals) were 0.89 (0.85–0.94) and 0.80 (0.75–0.86) for the A/G and A/A genotypes, respectively, compared with the genotype G/G. SNP rs9383951 (P = 1.9×10−6 from the combined analysis of all samples), located in intron 5 of the ESR1 gene, and SNP rs7107217 (P = 4.6×10−7), located at 11q24.3, also showed a consistent association in each of the four stages. This study provides strong evidence for a novel breast cancer susceptibility locus represented by rs9485372, near the TAB2 gene (6q25.1), and identifies two possible susceptibility loci located in the ESR1 gene and 11q24.3, respectively

    Additional file 1: of Integrative genomic analysis reveals functional diversification of APOBEC gene family in breast cancer

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    Tables S1 and S2. Table S1. Data characteristics in this study. Table S2. Expression levels of APOBEC family genes across ten breast cell lines. (XLSX 14 kb

    Additional file 2: Figures S1–S6. of Integrative genomic analysis reveals functional diversification of APOBEC gene family in breast cancer

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    Figure S1. Expression profiles of APOBEC family genes in breast tumor tissues and adjacent normal tissues in relation to ER status. Figure S2. Comparison of chromatin states in APOBEC1 (A), APOBEC2 (B), APOBEC4 (C), and AICDA (D) genes in ER+ (MCF-7), ER− (HCC1954) breast cancer cells, and normal cells (HMEC). Chromatin states characterized by the ChromHMM algorithm are represented by different colors shown in the bottom. Figure S3. Kaplan-Meier curve for overall survival of four patient groups with higher (top 50 %) or lower (bottom 50 %) expression of APOBEC3B and APOBEC3C genes in breast cancer. Figure S4. Distribution of the number of somatic mutations (A) and C>T/G>A mutations (B) per tumor exome. The red curve is a kernel density estimate. Figure S5. Relationship between mRNA levels of APOBEC3B (upper panel) and APOBEC3C (lower panel) and number of somatic SNVs per tumor exome stratified by the ER status. The black lines and red curves are drawn from the linear regression model and local regression smoothing, respectively. Figure S6. Expression profiles of APOBEC family genes in breast tumor tissues in relation with copy numbers of APOBEC3B. (ZIP 559 kb
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