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The associations between grains and carbohydrate intake and type 2 diabetes mellitus are controversial. This study aimed to evaluate the relationship between grains, carbohydrate intakes and the risk of type 2 diabetes mellitus in China.
Materials and Methods
This was a 1:2 (sex/age) matched case-control study, participants were adults. Cases were diabetics diagnosed within 3 months and the controls were without disorder of glucose metabolism. Face-to-face interviews were conducted to collect information on their socio-demographic characteristics, lifestyle factors, and dietary intakes using structured questionnaires. Grains were divided into whole, refined and common grain, and the carbohydrate intake was also calculated. The study participants were divided into quartiles (Q1 (lowest), Q2, Q3, and Q4) by food and nutrients intakes separately. Multivariable conditional logistic regression was used to explore the association of foods and nutrients with type 2 diabetes mellitus after adjusting for potential confounders. Trend test were performed by treating quartiles variables as continuous variables.
Results and Discussion
Our study enrolled 384 type 2 diabetes mellitus patients (males 162, females 222) and 768 controls (males 324, females 444). Multivariable conditional logistic regression analysis(Ver. 21.0; PSS Inc.,Chicago,IL,USA) showed that moderate amount intake of total cereals was inversely associated with type 2 diabetes mellitus. The adjusted OR of the second quartile (Q2, 223g/d) and the third quartile (Q3, 255g/d) were 0.60(95%CI:0.38–0.93) and 0.51(95%CI:0.33–0.79), respectively, compared with the lowest quartile (Q1, 165g/d), but this inverse association was not found in the highest quartile (Q4, 307g/d) and the OR was 0.74(95%CI:0.47–1.15). There was significant negative association between whole grains intake and type 2 diabetes mellitus with the OR of the highest intake 0.48(95%CI:0.31–0.77) compared with the lowest intake(Ptrend = 0.001).No association was found between refined grains intake intake and type 2 diabetes mellitus, and neither did common grain intake. Higher carbohydrate intake may have a beneficial effect on type 2 diabetes mellitus. The best effect was found in the second quartile intake (Q2, 264g/d), with an adjusted OR of 0.56 (95%CI:0.37–0.84) compared with the lowest quartile intake (Q1, 220g/d).The OR of Q3 (285g/d) and Q4 (334g/d) were 0.69 (95%CI:0.48–1.00) and 0.66 (95CI:0.44–1.00) respectively(Ptrend p = 0.017).
Moderate amount of total cereals intake may benefit to type 2 diabetes mellitus, however, much lower and higher intake can increase the risk. Higher intake of whole grains was associated with a lower risk of type 2 diabetes mellitus. Carbohydrate intake was negative associated with type 2 diabetes mellitus.
The microbiota–gut–brain axis, especially the microbial tryptophan (Trp) biosynthesis and metabolism pathway (MiTBamp), may play a critical role in the pathogenesis of major depressive disorder (MDD). However, studies on the MiTBamp in MDD are lacking. The aim of the present study was to analyze the gut microbiota composition and the MiTBamp in MDD patients.
We performed shotgun metagenomic sequencing of stool samples from 26 MDD patients and 29 healthy controls (HCs). In addition to the microbiota community and the MiTBamp analyses, we also built a classification based on the Random Forests (RF) and Boruta algorithm to identify the gut microbiota as biomarkers for MDD.
The Bacteroidetes abundance was strongly reduced whereas that of Actinobacteria was significantly increased in the MDD patients compared with the abundance in the HCs. Most noteworthy, the MDD patients had increased levels of Bifidobacterium, which is commonly used as a probiotic. Four Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K01817, K11358, K01626, K01667) abundances in the MiTBamp were significantly lower in the MDD group. Furthermore, we found a negative correlation between the K01626 abundance and the HAMD scores in the MDD group. Finally, RF classification at the genus level can achieve an area under the receiver operating characteristic curve of 0.890.
The present findings enabled a better understanding of the changes in gut microbiota and the related Trp pathway in MDD. Alterations of the gut microbiota may have the potential as biomarkers for distinguishing MDD patients form HCs.
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