Dietary glycemic index and load and the risk of type 2 diabetes: A systematic review and updated meta‐analyses of prospective cohort studies

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 now over a decade ago that a published meta-analysis used a predefined standard to identify valid studies. Considering valid studies only, and using random effects dose-response meta-analysis (DRM) while withdrawing spurious results (p < 0.05), we ascertained whether these relations would 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). The combined T2D-GI RR was 1.27 (1.15-1.40) (p < 0.001, n = 10 studies) per 10 units GI, while that for the 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 2000 kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GL were robustly associated with incident T2D. Together with mechanistic and other data, this supports 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 GL are substantial food markers predicting the development of T2D worldwide, for persons of European ancestry and of East Asian ancestry

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.Peer Reviewe

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies

The effect of wheat bran particle size and wheat protein on serum lipids and colonic health

grantor: University of TorontoBackground. Wheat bran is the major source of dietary fiber yet the optimum particle size is not clearly defined. Objective. To determine the effect of wheat bran particle size and wheat protein on serum lipids and colonic health. Design. In one-month metabolic (n = 24) and two-week ad-libitum diets (n = 24) subjects took 19g/d dietary fiber as fine or coarse-wheat bran in randomized crossover studies with low-fiber controls. In the metabolic study 10% of energy was provided as wheat gluten. Results. Wheat bran had no effect on serum lipids but gluten reduced triglycerides (P = 0.005). Wheat bran particle size did not affect fecal bulking. However, fine bran increased fecal butyrate concentrations (P $<$ 0.007) and breath CH\sb4 levels (P = 0.025) suggesting increased bacterial fermentation. Conclusions. Wheat bran regardless of particle size does not lower serum lipids although gluten may reduce serum triglycerides. Fine bran is an effective fecal bulking agent and may promote colonic mucosal health.M.Sc

Glycemic Index, Glycemic Load and Cancer Risk: An Updated Meta-Analysis

Diets high in glycemic index (GI) and glycemic load (GL) have been related to an increased risk of selected cancers, but additional quantification is required. We updated a systematic review and meta-analysis published in 2015 to May 2019 to provide quantitative information on GI/GL and cancer risk. Relative risks (RR) and the corresponding 95 % confidence intervals (CI) for the highest versus the lowest categories of GI and GL were extracted from selected studies and pooled using random-effects models. Twenty reports (&gt;22,000 cancer cases) have become available after January 2015, and 15 were added to the meta-analyses by cancer sites, which considered a total of 88 investigations. The five additional reports were reviewed, but not included in the meta-analyses, since data were inadequate to be pooled. For hormone-related cancers, summary RRs for the highest versus lowest GI and GL intakes were moderately increased. They ranged from 1.04 (breast) to 1.12 (endometrium) for GI and from 1.03 (prostate) to 1.22 (ovary) for GL, of borderline significance. High GI was associated with small increased risks of colorectal (summary RR for GI: 1.20, 95% CI, 1.07&ndash;1.34&mdash;GL: 1.09, 95% CI, 0.97&ndash;1.22, 19 studies), bladder (GI: 1.25, 95% CI, 1.11&ndash;1.41&mdash;GL: 1.10, 95% CI, 0.85&ndash;1.42, four studies) and kidney cancers (GI: 1.16, 95% CI, 1.02&ndash;1.32&mdash;GL: 1.14, 95% CI, 0.81&ndash;1.60, five studies). GL was not significantly related to those cancer sites. Stomach, prostate and lung cancers were not associated with GI and GL. The present analysis, based on an updated comprehensive evaluation of the epidemiological literature, indicates moderate unfavorable effects of high versus low GI on colorectal, and possibly bladder and kidney cancers, and a possible moderate positive association between GL and endometrial cancer

Identification of Modulated MicroRNAs Associated with Breast Cancer, Diet, and Physical Activity

Background: Several studies have shown that healthy lifestyles prevent the risk of breast cancer (BC) and are associated with better prognosis. It was hypothesized that lifestyle strategies induce microRNA (miRNA) modulation that, in turn, may lead to important epigenetic modifications. The identification of miRNAs associated with BC, diet, and physical activity may give further insights into the role played by lifestyle interventions and their efficacy for BC patients. To predict which miRNAs may be modulated by diet and physical activity in BC patients, the analyses of different miRNA expression datasets were performed. Methods: The GEO DataSets database was used to select miRNA expression datasets related to BC patients, dietary interventions, and physical exercise. Further bioinformatic approaches were used to establish the value of selected miRNAs in BC development and prognosis. Results: The analysis of datasets allowed the selection of modulated miRNAs associated with BC development, diet, and physical exercise. Seven miRNAs were also associated with the overall survival of BC patients. Conclusions: The identified miRNAs may play a role in the development of BC and may have a prognostic value in patients treated with integrative interventions including diet and physical activity. Validation of such modulated miRNAs on BC patients undergoing lifestyle strategies will be mandatory

Identification of Modulated MicroRNAs Associated with Breast Cancer, Diet, and Physical Activity

Background: Several studies have shown that healthy lifestyles prevent the risk of breast cancer (BC) and are associated with better prognosis. It was hypothesized that lifestyle strategies induce microRNA (miRNA) modulation that, in turn, may lead to important epigenetic modifications. The identification of miRNAs associated with BC, diet, and physical activity may give further insights into the role played by lifestyle interventions and their efficacy for BC patients. To predict which miRNAs may be modulated by diet and physical activity in BC patients, the analyses of different miRNA expression datasets were performed. Methods: The GEO DataSets database was used to select miRNA expression datasets related to BC patients, dietary interventions, and physical exercise. Further bioinformatic approaches were used to establish the value of selected miRNAs in BC development and prognosis. Results: The analysis of datasets allowed the selection of modulated miRNAs associated with BC development, diet, and physical exercise. Seven miRNAs were also associated with the overall survival of BC patients. Conclusions: The identified miRNAs may play a role in the development of BC and may have a prognostic value in patients treated with integrative interventions including diet and physical activity. Validation of such modulated miRNAs on BC patients undergoing lifestyle strategies will be mandatory

Diabetes Risk Reduction Diet and Endometrial Cancer Risk

Diabetes increases endometrial cancer risk. We investigated the role of a diabetes risk reduction diet (DRRD) on the risk of endometrial cancer using data from a multicentric, Italian hospital-based case–control study (1992–2006) enrolling 454 histologically confirmed cases of endometrial cancer and 908 controls matched by age and center. We derived a DRRD score assigning higher scores for higher intakes of cereal fiber, fruit, coffee, polyunsaturated:saturated fatty acid ratio, and nuts and for lower glycemic load and lower intakes of red/processed meat and sugar-sweetened beverages/fruit juices. The odds ratios (OR) of endometrial cancer according to the DRRD score were derived by multiple conditional logistic regression models. The OR for high (DRRD score &gt;24, i.e., third tertile) versus medium–low adherence to the DRRD was 0.73 (95% confidence interval, CI, 0.55–0.97). Similar results were observed after the exclusion of diabetic women (OR 0.75; 95% CI, 0.56–1.00) and allowance for total vegetable consumption (OR 0.80; 95% CI, 0.60–1.07). Inverse associations were observed in most of the analyzed subgroups. The OR for high DRRD combined with high vegetable consumption was 0.45 (95% CI, 0.28–0.73). Our results suggest that diets able to reduce diabetes risk may also reduce endometrial cancer risk. High vegetable consumption combined with high adherence to the DRRD may provide additional benefit in endometrial cancer prevention