Effects of Sjogren's Syndrome on essential hypertension: a two-sample mendelian randomization study.

BACKGROUND: Sjogren's Syndrome (SS) plays important roles in the development of essential hypertension. Nevertheless, with the limitation of reverse causality and confounder in observational studies, such a relationship remains unclear. We aimed to assess the causal relationship of SS and hypertension by the Mendelian randomization (MR) approach. METHODS: We used MR to investigate a causal association between SS and essential hypertension. Inverse variance weighted (IVW), MR Egger regression, Maximum likelihood, Weighted median, and MR pleiotropy residual sum and outlier test (MR-PRESSO) were used in this MR analysis. RESULTS: In this study, we found that the ratio of IVW is 1.00024 (95% CI: 1.00013- 1.00036, P=0.0387), This result was also confirmed by sensitivity analysis methods such as Maximum likelihood is 1.00025 (95% CI: 1.00013-1.00037, P=0.036), MR Egger is 1.00071 (95% CI: 1.00047-1.00095, P=0.0045), and Weighted median is 1.00040 (95% CI: 1.00021- 1.00059, P=0.0322). And MR-Egger intercept method revealed the absence of horizontal pleiotropy in this investigation (P>0.05). The Cochran's Q Test indicated an absence of heterogeneity among them (P>0.05). Heterogeneity and horizontal pleiotropy tests further demonstrate that the results of MR are relatively stable. The above results all suggest that pSS may promote the risk of hypertension. CONCLUSIONS: Our study provides evidence of a causal relationship of SS and hypertension. It is suggested to pay attention to early screening for hypertension, reduce disability and mortality rates, and improve patient prognosis in patients with SS.

Microecosystem of yak rumen on the Qinghai-Tibetan Plateau is stable and is unaffected by soil or grass microbiota.

The rumen of livestock grazing on the Qinghai-Tibetan Plateau (QTP) acts as a transfer station for the circulation of soil, grass, faecal mineral elements and nutrients. Whether the microorganisms from the soil and grass could circulate through livestock rumen and excreted faeces. We studied the structural composition and interactive networks of microbiomes (bacteria and fungi) in soil, grass, and grazing yaks (rumen and faeces) on the QTP by using 16S rRNA gene and internally transcribed spacer (ITS) sequencing technology and to calculate the contribution rate of microorganisms from one habitat to another habitat using SourceTracker analysis. The meta-co-occurrence network revealed that soil, grass, rumen, and faeces comprise four independent habitats. The bacterial and fungal composition was significantly different in these four habitats. Soil microbiota showed the highest alpha diversity and microbial network complexity. Rumen microbiota demonstrated the highest microbial network stability and synergy, while grass endophytes showed the lowest microbial network complexity, stability, and synergy. According to the SourceTracker model, grass contributes 0.02% to the rumen microbes of yaks, while soil microorganisms do not circulate in the rumen. The soil and grass microbiota originating from faeces were 4.5% and 1.2%, respectively. The contribution of soil to grass was found to be 1.1%. Overall, the rumen microbiota of yaks is relatively stable and is only minimally influenced by the microbiota inhabiting the environment under natural grazing conditions. However, the contribution of yaks to soil and grass microbiota is relatively high when compared with the contribution of soil and grass to yaks microbiota.

Localized intensification of arsenic methylation within landfill leachate-saturated zone.

Leachate-saturated zone (LSZ) of landfills is a complicated biogeochemical hotspot due to the continuous input of electron donors and acceptors from the top refuse layer with leachate migration. In this study, the methylation behavior of the arsenic (As) was investigated. The results indicate that As-methylation processes are influenced by temperature fields in LSZ. The dimethylarsinic acid biotransformation capability can be enhanced with an increase in temperature. Microbial diversity, quantification of functional gene (arsM), and co-occurrence network analysis further characterized the drivers of As methylation in LSZ. As-biogeochemical cycle pathways, as well as As-functional gene distribution among different temperature fields, were modeled on the basis of KEGG annotation. Binning analysis was further employed to assemble As-methylated metagenomes, enabling the identification of novel species for As methylation in landfills. Then, 87 high-quality draft metagenome-assembled genomes (MAGs) were reconstructed from LSZ refuse samples; nearly 15 % (13 of 87) belonged to putative As-methylates functional MAGs. Combined with the model of the As-biogeochemical cycle, nine putative functional species could complete methylation processes alone. The findings of this study highlighted the temperature influence on the As-methylation behavior in LSZ and could facilitate the management of As contamination in landfills.