Gut microbiota composition in relation to intake of added sugar, sugar-sweetened beverages and artificially sweetened beverages in the Malmö Offspring Study

Purpose It has been suggested that a high intake of sugar or sweeteners may result in an unfavorable microbiota composition; however, evidence is lacking. Hence, in this exploratory epidemiological study, we aim to examine if intake of added sugar, sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) associate with the gut microbiota composition. Methods Participants (18–70 years) in the Malmö Offspring Study have provided blood, urine, and fecal samples and completed both web-based 4 day food records and short food frequency questionnaires. The gut microbiota was assessed by 16S rRNA sequencing, processed in QIIME and matched to Greengenes (v.13.8), giving 64 included genera after filtering. Intake of added sugar (n = 1371) (also supported by the overnight urinary sugar biomarker in a subgroup n = 577), SSBs (n = 1086) and ASBs (n = 1085) were examined as exposures in negative binomial regressions. Results Various genera nominally associated with intake of added sugar, SSBs, and ASBs. Only the negative association between SSB intake and Lachnobacterium remained significant after multiple testing correction. A positive association between SSB intake and the Firmicutes:Bacteroidetes ratio was also observed. Conclusion In this wide population, the cross-sectional associations between added sugar and sweet beverage intake and the gut microbiota are modest, but the results suggest that SSB intake is associated negatively with the genus Lachnobacterium and positively with the Firmicutes:Bacteroidetes ratio. Larger studies, preferably using metagenomic sequencing, are needed to further evaluate if a link exists between intake of sugars and sweeteners and the human gut microbiota

Hrk1 Plays Both Hog1-Dependent and -Independent Roles in Controlling Stress Response and Antifungal Drug Resistance in Cryptococcus neoformans

The HOG (High Osmolarity Glycerol response) pathway plays a central role in controlling stress response, ergosterol biosynthesis, virulence factor production, and differentiation of Cryptococcus neoformans, which causes fatal fungal meningoencephalitis. Recent transcriptome analysis of the HOG pathway discovered a Hog1-regulated gene (CNAG_00130.2), encoding a putative protein kinase orthologous to Rck1/2 in Saccharomyces cerevisiae and Srk1 in Schizosaccharomyces pombe. Its function is not known in C. neoformans. The present study functionally characterized the role of Hrk1 in C. neoformans. Northern blot analysis confirmed that HRK1 expression depends on the Hog1 MAPK. Similar to the hog1Δ mutant, the hrk1Δ mutant exhibited almost complete resistance to fludioxonil, which triggers glycerol biosynthesis via the HOG pathway. Supporting this, the hrk1Δ mutant showed reduced intracellular glycerol accumulation and swollen cell morphology in response to fludioxonil, further suggesting that Hrk1 works downstream of the HOG pathway. However, Hrk1 also appeared to have Hog1-independent functions. Mutation of HRK1 not only further increased osmosensitivity of the hog1Δ mutant, but also suppressed increased azole-resistance of the hog1Δ mutant in an Erg11-independent manner. Furthermore, unlike the hog1Δ mutant, Hrk1 was not involved in capsule biosynthesis. Hrk1 was slightly involved in melanin production but dispensable for virulence of C. neoformans. These findings suggest that Hrk1 plays both Hog1-dependent and –independent roles in stress and antifungal drug susceptibility and virulence factor production in C. neoformans. Particularly, the finding that inhibition of Hrk1 substantially increases azole drug susceptibility provides a novel strategy for combination antifungal therapy

Soft drink and juice consumption and renal cell carcinoma incidence and mortality in the European Prospective Investigation into Cancer and Nutrition

Background: Renal cell carcinoma (RCC) accounts for more than 80% of kidney cancers in adults, and obesity is a known risk factor. Regular consumption of sweetened beverages has been linked to obesity and several chronic diseases, including some types of cancer. It is uncertain whether soft drink and juice consumption is associated with risk of RCC. We investigated the associations of soft drink and juice consumption with RCC incidence and mortality in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: A total of 389,220 EPIC participants with median age of 52 years at recruitment (1991–2000) were included. Cox regression yielded adjusted HRs and 95% confidence intervals (CI) for RCC incidence and mortality in relation to intakes of juices and total, sugar-sweetened, and artificially sweetened soft drinks. Results: A total of 888 incident RCCs and 356 RCC deaths were identified. In models including adjustment for body mass index and energy intake, there was no higher risk of incident RCC associated with consumption of juices (HR per 100 g/day increment = 1.03; 95% CI, 0.97–1.09), total soft drinks (HR = 1.01; 95% CI, 0.98–1.05), sugar-sweetened soft drinks (HR = 0.99; 95% CI, 0.94–1.05), or artificially sweetened soft drinks (HR = 1.02; 95% CI, 0.96–1.08). In these fully adjusted models, none of the beverages was associated with RCC mortality (HR, 95% CI per 100 g/day increment 1.06, 0.97–1.16; 1.03, 0.98–1.09; 0.97, 0.89–1.07; and 1.06, 0.99–1.14, respectively). Conclusions: Consumption of juices or soft drinks was not associated with RCC incidence or mortality after adjusting for obesity

Evaluation of protein and amino acid intake estimates from the EPIC dietary questionnaires and 24-h dietary recalls using different food composition databases

Background and aims This study aimed to expand the European Prospective Investigation into Cancer and Nutrition (EPIC) nutrient database (ENDB) by adding amino acid (AA) values, using the U.S. nutrient database (USNDB). Additionally, we aimed to evaluate these new protein and AA intake estimates from the EPIC dietary questionnaires (DQ) and 24-h dietary recalls (24-HDR) using different matching procedures. Methods and results Dietary energy, protein and AA intakes were assessed via DQ and 24-HDR by matching with the USNDB food composition table. Energy and protein intakes calculated using USNDB matching were compared with those calculated using ENDB, that uses country specific food composition tables. Pearson correlations, Cohen's weighted kappa statistic and Bland–Altman plots were used to compare data resulting from USNDB matching with our reference from ENDB matching. Very high correlations were found when comparing daily energy (r = 0.99) and dietary protein intakes (r = 0.97) assessed via USNDB with those obtained via ENDB (matching for DQ and 24-HDR). Significant positive correlations were also found with energy and protein intakes acquired via 24-HDRs in the EPIC calibration sample. Conclusion Very high correlations between total energy and protein intake obtained via the USDA matching and those available in ENDB suggest accuracy in the food matching. Individual AA have been included in the extended EPIC Nutrient database that will allow important analyses on AA disease prospective associations in the EPIC study

Dietary intake of advanced glycation endproducts and risk of hepatobiliary cancers: A multinational cohort study

Advanced glycation endproducts (AGEs) may contribute to liver carcinogenesis because of their proinflammatory and prooxidative properties. Diet is a major source of AGEs, but there is sparse human evidence on the role of AGEs intake in liver cancer etiology. We examined the association between dietary AGEs and the risk of hepatobiliary cancers in the European Prospective Investigation into Cancer and Nutrition prospective cohort (n = 450 111). Dietary intake of three AGEs, Nε-[carboxymethyl]lysine (CML), Nε-[1-carboxyethyl]lysine (CEL) and Nδ-[5-hydro-5-methyl-4-imidazolon-2-yl]-ornithine (MG-H1), was estimated using country-specific dietary questionnaires linked to an AGEs database. Cause-specific hazard ratios (HR) and their 95% confidence intervals (CI) for associations between dietary AGEs and risk of hepatocellular carcinoma (HCC), gallbladder and biliary tract cancers were estimated using multivariable Cox proportional hazard regression. After a median follow-up time of 14.9 years, 255 cases of HCC, 100 cases of gallbladder cancer and 173 biliary tract cancers were ascertained. Higher intakes of dietary AGEs were inversely associated with the risk of HCC (per 1 SD increment, HR-CML = 0.87, 95% CI: 0.76-0.99, HR-CEL = 0.84, 95% CI: 0.74-0.96 and HR-MH-G1 = 0.84, 95% CI: 0.74-0.97). In contrast, positive associations were observed with risk of gallbladder cancer (per 1 SD, HR-CML = 1.28, 95% CI: 1.05-1.56, HR-CEL = 1.17; 95% CI: 0.96-1.40, HR-MH-G1 = 1.27, 95% CI: 1.06-1.54). No associations were observed for cancers of the intra and extrahepatic bile ducts. Our findings suggest that higher intakes of dietary AGEs are inversely associated with the risk of HCC and positively associated with the risk of gallbladder cancer

Evaluation of protein and amino acid intake estimates from the EPIC dietary questionnaires and 24-hour dietary recalls using different food composition databases

Background and aims This study aimed to expand the European Prospective Investigation into Cancer and Nutrition (EPIC) nutrient database (ENDB) by adding amino acid (AA) values, using the U.S. nutrient database (USNDB). Additionally, we aimed to evaluate these new protein and AA intake estimates from the EPIC dietary questionnaires (DQ) and 24-hour dietary recalls (24-HDR) using different matching procedures. Methods and results Dietary energy, protein and AA intakes were assessed via DQ and 24-HDR by matching with the USNDB food composition table. Energy and protein intakes calculated using USNDB matching were compared with those calculated using ENDB, that uses country specific food composition tables. Pearson correlations, Cohen’s weighted kappa statistic and Bland-Altman plots were used to compare data resulting from USNDB matching with our reference from ENDB matching. Very high correlations were found when comparing daily energy (r=0.99) and dietary protein intakes (r=0.97) assessed via USNDB with those obtained via ENDB (matching for DQ and 24-HDR). Significant positive correlations were also found with energy and protein intakes acquired via 24-HDRs in the EPIC calibration sample. Conclusion Very high correlations between total energy and protein intake obtained via the USDA matching and those available in ENDB suggest accuracy in the food matching. Individual AA have been included in the extended EPIC Nutrient database that will allow important analyses on AA disease prospective associations in the EPIC study

Consumption of ultra-processed foods associated with weight gain and obesity in adults: A multi-national cohort study

Background There is a worldwide shift towards increased consumption of ultra-processed foods (UPF) with concurrent rising prevalence of obesity. We examined the relationship between the consumption of UPF and weight gain and risk of obesity. Methods This prospective cohort included 348 748 men and women aged 25–70 years. Participants were recruited between 1992 and 2000 from 9 European countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Two body weight measures were available, at baseline and after a median follow-up time of 5 years. Foods and drinks were assessed at baseline by dietary questionnaires and classified according to their degree of processing using NOVA classification. Multilevel mixed linear regression was used to estimate the association between UPF consumption and body weight change (kg/5 years). To estimate the relative risk of becoming overweight or obese after 5 years we used Poisson regression stratified according to baseline body mass index (BMI). Results After multivariable adjustment, higher UPF consumption (per 1 SD increment) was positively associated with weight gain (0·12 kg/5 years, 95% CI 0·09 to 0·15). Comparing highest vs. lowest quintile of UPF consumption was associated with a 15% greater risk (95% CI 1·11, 1·19) of becoming overweight or obese in normal weight participants, and with a 16% greater risk (95% CI 1·09, 1·23) of becoming obese in participants who were overweight at baseline. Conclusions These results are supportive of public health campaigns to substitute UPF for less processed alternatives for obesity prevention and weight management

Soft drink and juice consumption and renal cell carcinoma incidence and mortality in the european prospective investigation into cancer and nutrition

Background: Renal cell carcinoma (RCC) accounts for more than 80% of kidney cancers in adults, and obesity is a known risk factor. Regular consumption of sweetened beverages has been linked to obesity and several chronic diseases, including some types of cancer. It is uncertain whether soft drink and juice consumption is associated with risk of RCC. We investigated the associations of soft drink and juice consumption with RCC incidence and mortality in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: A total of 389,220 EPIC participants with median age of 52 years at recruitment (1991-2000) were included. Cox regression yielded adjusted HRs and 95% confidence intervals (CI) for RCC incidence and mortality in relation to intakes of juices and total, sugar-sweetened, and artificially sweetened soft drinks. Results: A total of 888 incident RCCs and 356 RCC deaths were identified. In models including adjustment for body mass index and energy intake, there was no higher risk of incident RCC associated with consumption of juices (HR per 100 g/day increment ¼ 1.03; 95% CI, 0.97-1.09), total soft drinks (HR ¼ 1.01; 95% CI, 0.98-1.05), sugar-sweetened soft drinks (HR ¼ 0.99; 95% CI, 0.94-1.05), or artificially sweetened soft drinks (HR ¼ 1.02; 95% CI, 0.96-1.08). In these fully adjusted models, none of the beverages was associated with RCC mortality (HR, 95% CI per 100 g/day increment 1.06, 0.97-1.16; 1.03, 0.98-1.09; 0.97, 0.89-1.07; and 1.06, 0.99-1.14, respectively). Conclusions: Consumption of juices or soft drinks was not associated with RCC incidence or mortality after adjusting for obesity. Impact: Soft drink and juice intakes are unlikely to play an independent role in RCC development or mortality

Replacement of red and processed meat with other food sources of protein and the risk of type 2 diabetes in European populations: The epic-interact study

OBJECTIVE There is sparse evidence for the association of suitable food substitutions for red and processed meat on the risk of type 2 diabetes. We modeled the association between replacing red and processed meat with other protein sources and the risk of type 2 diabetes and estimated its population impact. RESEARCH DESIGN AND METHODS The European Prospective Investigation into Cancer (EPIC)-InterAct case cohort included 11,741 individuals with type 2 diabetes and a subcohort of 15,450 participants in eight countries. We modeled the replacement of self-reported red and processed meat with poultry, fish, eggs, legumes, cheese, cereals, yogurt, milk, and nuts. Country-specific hazard ratios (HRs) for incident type 2 diabetes were estimated by Prentice-weighted Cox regression and pooled using random-effects meta-analysis. RESULTS There was a lower hazard for type 2 diabetes for the modeled replacement of red and processed meat (50 g/day) with cheese (HR 0.90, 95% CI 0.83–0.97) (30 g/day), yogurt (0.90, 0.86–0.95) (70 g/day), nuts (0.90, 0.84–0.96) (10 g/day), or cereals (0.92, 0.88–0.96) (30 g/day) but not for replacements with poultry, fish, eggs, legumes, or milk. If a causal association is assumed, replacing red and processed meat with cheese, yogurt, or nuts could prevent 8.8%, 8.3%, or 7.5%, respectively, of new cases of type 2 diabetes. CONCLUSIONS Replacement of red and processed meat with cheese, yogurt, nuts, or cereals was associated with a lower rate of type 2 diabetes. Substituting red and processed meat by other protein sources may contribute to the prevention of incident type 2 diabetes in European populations