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Sökning: WFRF:(Willett Walter)

  • Resultat 51-60 av 69
  • Föregående 12345[6]7Nästa
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51.
  • Huang, Tao, et al. (författare)
  • Dairy Consumption and Body Mass Index Among Adults : Mendelian Randomization Analysis of 184802 Individuals from 25 Studies
  • 2018
  • Ingår i: Clinical Chemistry. - 0009-9147 .- 1530-8561. ; 64:1, s. 183-191
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined.METHODS: We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies.RESULTS: Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15 × 10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11 × 10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0 × 10−4).CONCLUSIONS: The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.
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52.
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53.
  • Joshi, Amit D., et al. (författare)
  • Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium
  • 2014
  • Ingår i: American Journal of Epidemiology. - : Oxford University Press. - 0002-9262 .- 1476-6256. ; 180:10, s. 1018-1027
  • Tidskriftsartikel (refereegranskat)abstract
    • Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 x 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
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54.
  • Lindstroem, Sara, et al. (författare)
  • Common genetic variants in prostate cancer risk prediction-results from the NCI breast and prostate cancer cohort consortium (BPC3)
  • 2012
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:3, s. 437-444
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent single-nucleotide polymorphism markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer, and age.Methods: We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data.Results: The best risk model (C-statistic = 0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P = 0.009), with highest accuracy in men younger than 60 years (C-statistic = 0.679). The absolute ten-year risk for 50-year-old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile).Conclusions: Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from prostate-specific antigen screening.Impact: Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
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55.
  • Lindstroem, Sara, et al. (författare)
  • Replication of five prostate cancer loci identified in an Asian population-results from the NCI breast and prostate cancer cohort consortium (BPC3)
  • 2012
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 21:1, s. 212-216
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: A recent genome-wide association study (GWAS) of prostate cancer in a Japanese population identified five novel regions not previously discovered in other ethnicities. In this study, we attempt to replicate these five loci in a series of nested prostate cancer case-control studies of European ancestry. Methods: We genotyped five single-nucleotide polymorphism (SNP): rs13385191 (chromosome 2p24), rs12653946 (5p15), rs1983891 (6p21), rs339331 (6p22), and rs9600079 (13q22), in 7,956 prostate cancer cases and 8,148 controls from a series of nested case-control studies within the National cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3). We tested each SNP for association with prostate cancer risk and assessed whether associations differed with respect to disease severity and age of onset. Results: Four SNPs (rs13385191, rs12653946, rs1983891, and rs339331) were significantly associated with prostate cancer risk (P values ranging from 0.01 to 1.1 x 10(-5)). Allele frequencies and ORs were overall lower in our population of European descent than in the discovery Asian population. SNP rs13385191 (C2orf43) was only associated with low-stage disease (P = 0.009, case-only test). No other SNP showed association with disease severity or age of onset. We did not replicate the 13q22 SNP, rs9600079 (P = 0.62). Conclusions: Four SNPs associated with prostate cancer risk in an Asian population are also associated with prostate cancer risk in men of European descent. Impact: This study illustrates the importance of evaluation of prostate cancer risk markers across ethnic groups. Cancer Epidemiol Biomarkers Prev; 21(1); 212-16. (C) 2011 AACR.
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56.
  • Livesey, Geoffrey, et al. (författare)
  • Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes : A Systematic Review and Updated Meta-Analyses of Prospective Cohort Studies
  • 2019
  • Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 11:6
  • Forskningsöversikt (refereegranskat)abstract
    • Published meta-analyses indicate significant but inconsistent incident type-2 diabetes(T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is nowover a decade ago that a published meta-analysis used a predefined standard to identify validstudies. Considering valid studies only, and using random effects dose-response meta-analysis(DRM) while withdrawing spurious results (p < 0.05), we ascertained whether these relationswould support nutrition guidance, specifically for an RR > 1.20 with a lower 95% confidence limit>1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). Thecombined T2D-GI RR was 1.27 (1.15-1.40) (p < 0.001, n = 10 studies) per 10 units GI, while that forthe T2D-GL RR was 1.26 (1.15-1.37) (p < 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet.The corresponding global DRM using restricted cubic splines were 1.87 (1.56-2.25) (p < 0.001, n =10) and 1.89 (1.66-2.16) (p < 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GLwere robustly associated with incident T2D. Together with mechanistic and other data, thissupports that consideration should be given to these dietary risk factors in nutrition advice.Concerning the public health relevance at the global level, our evidence indicates that GI and GLare substantial food markers predicting the development of T2D worldwide, for persons ofEuropean ancestry and of East Asian ancestry.
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57.
  • Livesey, Geoffrey, et al. (författare)
  • Dietary Glycemic Index and Load and the Risk of Type 2 Diabetes : Assessment of Causal Relations
  • Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 11:6
  • Forskningsöversikt (refereegranskat)abstract
    • While dietary factors are important modifiable risk factors for type 2 diabetes (T2D), the causal role of carbohydrate quality in nutrition remains controversial. Dietary glycemic index (GI) and glycemic load (GL) have been examined in relation to the risk of T2D in multiple prospective cohort studies. Previous meta-analyses indicate significant relations but consideration of causality has been minimal. Here, the results of our recent meta-analyses of prospective cohort studies of 4 to 26-y follow-up are interpreted in the context of the nine Bradford-Hill criteria for causality, that is: (1) Strength of Association, (2) Consistency, (3) Specificity, (4) Temporality, (5) Biological Gradient, (6) Plausibility, (7) Experimental evidence, (8) Analogy, and (9) Coherence. These criteria necessitated referral to a body of literature wider than prospective cohort studies alone, especially in criteria 6 to 9. In this analysis, all nine of the Hill's criteria were met for GI and GL indicating that we can be confident of a role for GI and GL as causal factors contributing to incident T2D. In addition, neither dietary fiber nor cereal fiber nor wholegrain were found to be reliable or effective surrogate measures of GI or GL. Finally, our cost-benefit analysis suggests food and nutrition advice favors lower GI or GL and would produce significant potential cost savings in national healthcare budgets. The high confidence in causal associations for incident T2D is sufficient to consider inclusion of GI and GL in food and nutrient-based recommendations.
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58.
  • McKay, James D., et al. (författare)
  • Vitamin D Receptor Polymorphisms and Breast Cancer Risk: Results from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium
  • 2009
  • Ingår i: Cancer Epidemiology Biomarkers & Prevention. - : American Association for Cancer Research. - 1538-7755. ; 18:1, s. 297-305
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Vitamin D is hypothesized to lower the risk of breast cancer by inhibiting cell proliferation via the nuclear vitamin D receptor (VDR). Two common single nucleotide polymorphisms (SNP) in the VDR gene (VDR), rs154441.0 (BsmI), and rs2228570 (FokI), have been inconsistently associated with breast cancer risk. Increased risk has been reported for the FokIff genotype, which encodes a less transcriptionally active isoform of VDR, and reduced risk has been reported for the BsmI BB genotype, a SNP in strong linkage disequilibrium with a 3'-untranslated region, which may influence VDR mRNA stability. Methods: We pooled data from 6 prospective studies in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium to examine associations between these SNPs and breast cancer among >6,300 cases and 8,100 controls for each SNP using conditional logistic regression. Results: The odds ratio (OR) for the rs2228570 (FokI) ff versus FF genotype in the overall population was statistically significantly elevated [OR, 1-1.6; 95% confidence interval (95% CI), 1.04-1.28] but was weaker once data from the cohort with previously published positive findings were removed (OR, 1.1.0; 95% CI, 0.981.24). No association was noted between rs1544410 (Bsm I) BB and breast cancer risk overall (OR, 0.98; 95% CI, 0.89-1.09), but the BB genotype was associated with a significantly lower risk of advanced breast cancer (OR, 0.74; 95% CI, 0.60-0.92). Conclusions: Although the evidence for independent contributions of these variants to breast cancer susceptibility remains equivocal, future large studies should integrate genetic variation in VDR with biomarkers of vitamin D status. (Cancer Epidemiol Biomarkers Prev 2009;18(1):297-305)
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59.
  • Risérus, Ulf, et al. (författare)
  • Dietary fats and prevention of type 2 diabetes
  • 2009
  • Ingår i: Progress in lipid research. - 0163-7827 .- 1873-2194. ; 48:1, s. 44-51
  • Forskningsöversikt (refereegranskat)abstract
    • Although type 2 diabetes is determined primarily by lifestyle and genes, dietary composition may affect both its development and complications. Dietary fat is of particular interest because fatty acids influence glucose metabolism by altering cell membrane function, enzyme activity, insulin signaling, and gene expression. This paper focuses on the prevention of type 2 diabetes and summarizes the epidemiologic literature on associations between types of dietary fat and diabetes risk. It also summarizes controlled feeding studies on the effects of dietary fats on metabolic mediators, such as insulin resistance. Taken together, the evidence suggests that replacing saturated fats and trans fatty acids with unsaturated (polyunsaturated and/or monounsaturated) fats has beneficial effects on insulin sensitivity and is likely to reduce risk of type 2 diabetes. Among polyunsaturated fats, linoleic acid from the n-6 series improves insulin sensitivity. On the other hand, long-chain n-3 fatty acids do not appear to improve insulin sensitivity or glucose metabolism. In dietary practice, foods rich in vegetable oils, including non-hydrogenated margarines, nuts, and seeds, should replace foods rich in saturated fats from meats and fat-rich dairy products. Consumption of partially hydrogenated fats should be minimized. Additional controlled, long-term studies are needed to improve our knowledge on the optimal proportion of different types of fats to prevent diabetes.
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60.
  • Romieu, Isabelle, et al. (författare)
  • Energy balance and obesity : what are the main drivers?
  • Ingår i: Cancer Causes and Control. - : Springer. - 0957-5243. ; 28:3, s. 247-258
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: The aim of this paper is to review the evidence of the association between energy balance and obesity. Methods: In December 2015, the International Agency for Research on Cancer (IARC), Lyon, France convened a Working Group of international experts to review the evidence regarding energy balance and obesity, with a focus on Low and Middle Income Countries (LMIC). Results: The global epidemic of obesity and the double burden, in LMICs, of malnutrition (coexistence of undernutrition and overnutrition) are both related to poor quality diet and unbalanced energy intake. Dietary patterns consistent with a traditional Mediterranean diet and other measures of diet quality can contribute to long-term weight control. Limiting consumption of sugar-sweetened beverages has a particularly important role in weight control. Genetic factors alone cannot explain the global epidemic of obesity. However, genetic, epigenetic factors and the microbiota could influence individual responses to diet and physical activity. Conclusion: Energy intake that exceeds energy expenditure is the main driver of weight gain. The quality of the diet may exert its effect on energy balance through complex hormonal and neurological pathways that influence satiety and possibly through other mechanisms. The food environment, marketing of unhealthy foods and urbanization, and reduction in sedentary behaviors and physical activity play important roles. Most of the evidence comes from High Income Countries and more research is needed in LMICs.
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