METHODS: We carried out a systematic search of all available RCTs up to June 2019 in the following electronic databases: PubMed, Scopus, Web of Science and Google Scholar. Pooled weight mean difference (WMD) of the included studies was estimated using random-effects model.
RESULTS: A total of 27 articles were included in this meta-analysis, with walnuts dosage ranging from 15 to 108 g/d for 2 wk to 2 y. Overall, interventions with walnut intake did not alter waist circumference (WC) (WMD: -0.193 cm, 95 % CI: -1.03, 0.64, p = 0.651), body weight (BW) (0.083 kg, 95 % CI: -0.032, 0.198, p = 0.159), body mass index (BMI) (WMD: -0.40 kg/m,295 % CI: -0.244, 0.164, p = 0.703), and fat mass (FM) (WMD: 0.28 %, 95 % CI: -0.49, 1.06, p = 0.476). Following dose-response evaluation, reduced BW (Coef.= -1.62, p = 0.001), BMI (Coef.= -1.24, p = 0.041) and WC (Coef.= -5.39, p = 0.038) were significantly observed through walnut intake up to 35 g/day. However, the number of studies can be limited as to the individual analysis of the measures through the dose-response fashion.
CONCLUSIONS: Overall, results from this meta-analysis suggest that interventions with walnut intake does not alter BW, BMI, FM, and WC. To date, there is no discernible evidence to support walnut intake for improving anthropometric indicators of weight loss.
METHODS: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.
FINDINGS: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P