Exploring the causal relationship between gut microbiota and multiple myeloma risk based on Mendelian randomization and biological annotation.

Introduction: The microbial genome-wide association studies (mbGWAS) have highlighted significant host-microbiome interactions based on microbiome heritability. However, establishing causal relationships between particular microbiota and multiple myeloma (MM) remains challenging due to limited sample sizes. Methods: Gut microbiota data from a GWAS with 18,340 participants and MM summary statistics from 456,348 individuals. The inverse variance-weighted (IVW) method was used as the main bidirectional Mendelian randomization (MR) analysis. To assess the robustness of our results, we further performed supplementary analyses, including MR pleiotropy residual sum and outlier (MR-PRESSO) test, MR-Egger, Weighted median, Simple mode, and Weighted mode. Moreover, a backward MR analysis was conducted to investigate the potential for reverse causation. Finally, gene and gene-set-based analyses were then conducted to explore the common biological factors connecting gut microbiota and MM. Results: We discovered that 10 gut microbial taxa were causally related to MM risk. Among them, family Acidaminococcaceae, Bacteroidales family S24-7, family Porphyromonadaceae, genus Eubacterium ruminantium group, genus Parabacteroides, and genus Turicibacter were positively correlated with MM. Conversely, class Verrucomicrobia, family Verrucomicrobiaceae, genus Akkermansia, and order Verrucomicrobiales were negatively correlated with MM. The heterogeneity test revealed no Heterogeneity. MR-Egger and MR-PRESSO tests showed no significant horizontal pleiotropy. Importantly, leave-one-out analysis confirmed the robustness of MR results. In the backward MR analysis, no statistically significant associations were discovered between MM and 10 gut microbiota taxa. Lastly, we identified novel host-microbiome shared genes (AUTS2, CDK2, ERBB3, IKZF4, PMEL, SUOX, and RAB5B) that are associated with immunoregulation and prognosis in MM through biological annotation. Discussion: Overall, this study provides evidence supporting a potential causal relationship between gut microbiota and MM risk, while also revealing novel host-microbiome shared genes relevant to MM immunoregulation and clinical prognosis.

Regional differences of high-quality development level for manufacturing industry in China.

The development of China's manufacturing industry is still facing the challenge of regional imbalance. To solve the problem of development imbalance, it is necessary to realize regional development. First, we must analyze the development characteristics of different regions. To this end, we consider the requirements of the new development era and design an evaluation index system for the high-quality development level of the manufacturing industry from the dimensions of innovation, green, and efficiency. Then construct a novel hybrid model which combines the grey incidence clustering model and AP algorithm for panel data in this paper. According to the statistical data from 2014 to 2018, we find out the high-quality development of China's manufacturing industry is characterized by obvious regional differences, different development stages and different constraints.