BackgroundVegetarian diets exclude all animal flesh and are being widely adopted by an increasing number of people; however, effects on blood lipid concentrations remain unclear. This meta‐analysis aimed to quantitatively assess the overall effects of vegetarian diets on blood lipids.Methods and ResultsWe searched PubMed, Scopus, Embase, ISI Web of Knowledge, and the Cochrane Library through March 2015. Studies were included if they described the effectiveness of vegetarian diets on blood lipids (total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, and triglyceride). Weighted mean effect sizes were calculated for net changes by using a random‐effects model. We performed subgroup and univariate meta‐regression analyses to explore sources of heterogeneity. Eleven trials were included in the meta‐analysis. Vegetarian diets significantly lowered blood concentrations of total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, and non–high‐density lipoprotein cholesterol, and the pooled estimated changes were −0.36 mmol/L (95% CI −0.55 to −0.17; P<0.001), −0.34 mmol/L (95% CI −0.57 to −0.11; P<0.001), −0.10 mmol/L (95% CI −0.14 to −0.06; P<0.001), and −0.30 mmol/L (95% CI −0.50 to −0.10; P=0.04), respectively. Vegetarian diets did not significantly affect blood triglyceride concentrations, with a pooled estimated mean difference of 0.04 mmol/L (95% CI −0.05 to 0.13; P=0.40).ConclusionsThis systematic review and meta‐analysis provides evidence that vegetarian diets effectively lower blood concentrations of total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, and non–high‐density lipoprotein cholesterol. Such diets could be a useful nonpharmaceutical means of managing dyslipidemia, especially hypercholesterolemia.

1The COVID-19 pandemic is spreading globally with high disparity in the 2 susceptibility of the disease severity. Identification of the key underlying factors for 3 this disparity is highly warranted. Here we describe constructing a proteomic risk 4 score based on 20 blood proteomic biomarkers which predict the progression to 5 severe COVID-19. We demonstrate that in our own cohort of 990 individuals without 6 infection, this proteomic risk score is positively associated with proinflammatory 7 cytokines mainly among older, but not younger, individuals. We further discovered 8 that a core set of gut microbiota could accurately predict the above proteomic 9 biomarkers among 301 individuals using a machine learning model, and that these gut 10 microbiota features are highly correlated with proinflammatory cytokines in another 11 set of 366 individuals. Fecal metabolomic analysis suggested potential amino 12 acid-related pathways linking gut microbiota to inflammation. This study suggests 13 that gut microbiota may underlie the predisposition of normal individuals to severe : medRxiv preprint ( Figure S1). Gut microbiota data were collected and measured during a follow-up 107 visit of the cohort participants, with a cross-sectional subset of the individuals (n=132) 108 having blood proteomic data at the same time point as the stool collection and another 109 independent prospective subset of the individuals (n=169) having proteomic data at a 110 next follow-up visit ~3 years later than the stool collection. 111 112 Among the cross-sectional subset, using a machine learning-based method: 113 LightGBM and a very conservative and strict tenfold cross-validation strategy, we 114 identified 20 top predictive operational taxonomic units (OTUs), and this subset of 115 core OTUs explained an average 21.5% of the PRS variation (mean out-of-sample 116 R 2 =0.215 across ten cross-validations). The list of these core OTUs along with their 117 taxonomic classification is provided inTable S3. These OTUs were mainly assigned 118 to Bacteroides genus, Streptococcus genus, Lactobacillus genus, Ruminococcaceae 119 family, Lachnospiraceae family and Clostridiales order.120 121To test the verification of the core OTUs, the Pearson correlation analysis showed the 122 coefficient between the core OTUs-predicted PRS and actual PRS reached 0.59 123 (p<0.001), substantially outperforming the predictive capacity of other demographic 124 characteristics and laboratory tests including age, BMI, sex, blood pressure and blood 125 lipids (Pearson's r =0.154, p=0.087) ( Figure 3A). Additionally, we used co-inertia 126 analysis (CIA) to further test co-variance between the 20 identified core OTUs and 20 127 predictive proteomic biomarkers of severe COVID-19, outputting a RV coefficient 128 (ranged from 0 to 1) to quantify the closeness. The results indicated a close 129 association of these OTUs with the proteomic biomarkers (RV=0.12, p<0.05) (Figure 130 S3A). When replicating this analysis stratified by age, significant association was 131 observed...

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BackgroundProspective cohort studies in relation to the associations between n-3 polyunsaturated fatty acids (PUFA) and risk of type 2 diabetes (T2D) were inconsistent. Differences in tissue n-3 PUFA compositions in subjects with and without T2D were also inconsistent in both cohort and case-control studies. We conducted a systematic review and meta-analysis of prospective cohort studies to examine the associations of fish and n-3 PUFA intake with T2D risk. The differences in tissue n-3 PUFA compositions in subjects with and without T2D were investigated based on cohort and case-control studies.Methods and FindingsPubMed, Embase, Cochrane library, China National Knowledge Infrastructure (CNKI) and Chinese VIP database up to January 2012 was used to identify relevant studies, and reference lists from retrieved studies were reviewed. Two authors independently extracted the data. Random-effects models were used to pool the summary relative risk (RR). Twenty-four studies including 24,509 T2D patients and 545,275 participants were identified. For cohort studies, the summary RR of T2D for the highest vs lowest categories of total fish, marine n-3 PUFA and alpha-linolenic acid intake was 1.07 (95% CI: 0.91, 1.25), 1.07 (95% CI: 0.95, 1.20) and 0.93 (95% CI: 0.81, 1.07), respectively. Subgroup analyses indicated that summary RR (highest vs lowest category) of T2D for fish and marine n-3 PUFA intake was 0.89 (95% CI: 0.81, 0.98) and 0.87 (95% CI: 0.79, 0.96) for Asian populations, and 1.20 (95% CI: 1.01, 1.44) and 1.16 (95% CI: 1.04, 1.28) for Western populations. Asian subjects with T2D had significantly lower tissue compositions of C22∶6n-3 (SMD: −1.43; 95% CI: −1.75, −1.12) and total n-3 PUFA (SMD: −1.41; 95% CI: −2.23, −0.59) compared with those without T2D.ConclusionThis systematic review and meta-analysis provides evidence that marine n-3 PUFA have beneficial effects on the prevention of T2D in Asian populations.