Department of Clinical Laboratory Science, Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan.
Institute of Liberal Arts and Science, Kanazawa University, Kanazawa, Japan.
Front Cell Infect Microbiol. 2022 Sep 2;12:908997. doi: 10.3389/fcimb.2022.908997. eCollection 2022.
Dyslipidemia (DL) is one of the most common lifestyle-related diseases. There are few reports showing the causal relationship between gut microbiota (GM) and DL. In the present study, we used a linear non-Gaussian acyclic model (LiNGAM) to evaluate the causal relationship between GM and DL. A total of 79 men and 82 women aged 40 years or older living in Shika-machi, Ishikawa Prefecture, Japan were included in the analysis, and their clinical information was investigated. DNA extracted from the GM was processed to sequence the 16S rRNA gene using next-generation sequencing. Participants were divided into four groups based on sex and lipid profile information. The results of one-way analysis of covariance, linear discriminant analysis effect size, and least absolute value reduction and selection operator logistic regression model indicated that several bacteria between men and women may be associated with DL. The LiNGAM showed a presumed causal relationship between different bacteria and lipid profiles in men and women. In men, and were shown to be potentially associated with changes in low- and high-density lipoprotein cholesterol levels. In women, the LiNGAM results showed two bacteria, and , had a presumptive causal relationship with lipid profiles. These results may provide a new sex-based strategy to reduce the risk of developing DL and to treat DL through the regulation of the intestinal environment using specific GM.
血脂异常（DL）是最常见的与生活方式相关的疾病之一。很少有报道显示肠道微生物群（GM）与 DL 之间存在因果关系。在本研究中，我们使用线性非高斯无环模型（LiNGAM）来评估 GM 与 DL 之间的因果关系。共有 79 名年龄在 40 岁或以上的男性和 82 名女性居住在日本石川县的 Shika-machi，对他们的临床信息进行了调查。从 GM 中提取的 DNA 经过处理，使用下一代测序对 16S rRNA 基因进行测序。根据性别和血脂谱信息，将参与者分为四组。协方差的单向分析、线性判别分析效应大小、最小绝对值缩减和选择算子逻辑回归模型的结果表明，男性和女性之间的几种细菌可能与 DL 有关。LiNGAM 显示了不同细菌与男性和女性血脂谱之间的假定因果关系。在男性中，和被显示为可能与低和高密度脂蛋白胆固醇水平的变化有关。在女性中，LiNGAM 结果显示两种细菌和与血脂谱存在假定的因果关系。这些结果可能为通过调节肠道环境使用特定的 GM 来降低 DL 发病风险和治疗 DL 提供一种新的基于性别的策略。
