Associations of gut microbiota with dyslipidemia based on sex differences in subjects from Northwestern China
The gut microbiota (GM) has been proven to play a role in the regulation of host lipid metabolism, which provides a new theory about the pathogenesis of dyslipidemia. However, the associations of GM with dyslipidemia based on sex differences remain unclear and warrant elucidation.BACKGROUNDThe gut m...
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| Vydané v: | World journal of gastroenterology : WJG Ročník 28; číslo 27; s. 3455 |
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| Hlavní autori: | , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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21.07.2022
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| ISSN: | 2219-2840, 2219-2840 |
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| Abstract | The gut microbiota (GM) has been proven to play a role in the regulation of host lipid metabolism, which provides a new theory about the pathogenesis of dyslipidemia. However, the associations of GM with dyslipidemia based on sex differences remain unclear and warrant elucidation.BACKGROUNDThe gut microbiota (GM) has been proven to play a role in the regulation of host lipid metabolism, which provides a new theory about the pathogenesis of dyslipidemia. However, the associations of GM with dyslipidemia based on sex differences remain unclear and warrant elucidation.To investigate the associations of GM features with serum lipid profiles based on sex differences in a Chinese population.AIMTo investigate the associations of GM features with serum lipid profiles based on sex differences in a Chinese population.This study ultimately recruited 142 participants (73 females and 69 males) at Honghui Hospital, Xi'an Jiaotong University. The anthropometric and blood metabolic parameters of all participants were measured. According to their serum lipid levels, female and male participants were classified into a high triglyceride (H_TG) group, a high total cholesterol (H_CHO) group, a low high-density lipoprotein cholesterol (L_HDL-C) group, and a control (CON) group with normal serum lipid levels. Fresh fecal samples were collected for 16S rRNA gene sequencing. UPARSE software, QIIME software, the RDP classifier and the FAPROTAX database were used for sequencing analyses.METHODSThis study ultimately recruited 142 participants (73 females and 69 males) at Honghui Hospital, Xi'an Jiaotong University. The anthropometric and blood metabolic parameters of all participants were measured. According to their serum lipid levels, female and male participants were classified into a high triglyceride (H_TG) group, a high total cholesterol (H_CHO) group, a low high-density lipoprotein cholesterol (L_HDL-C) group, and a control (CON) group with normal serum lipid levels. Fresh fecal samples were collected for 16S rRNA gene sequencing. UPARSE software, QIIME software, the RDP classifier and the FAPROTAX database were used for sequencing analyses.The GM composition at the phylum level included Firmicutes and Bacteroidetes as the core GM. Different GM features were identified between females and males, and the associations between GM and serum lipid profiles were different in females and males. The GM features in different dyslipidemia subgroups changed in both female patients and male patients. Proteobacteria, Lactobacillaceae, Lactobacillus and Lactobacillus_salivarius were enriched in H_CHO females compared with CON females, while Coriobacteriia were enriched in L_HDL-C females. In the comparison among the three dyslipidemia subgroups in females, Lactobacillus_salivarius were enriched in H_CHO females, and Prevotellaceae were enriched in L_HDL-C females. Compared with CON or H_TG males, Prevotellaceae, unidentified_Ruminococcaceae, Roseburia and Roseburia_inulinivorans were decreased in L_HDL-C males (P value < 0.05), and linear discriminant analysis effect size analysis indicated an enrichment of the above GM taxa in H_TG males compared with other male subgroups. Additionally, Roseburia_inulinivorans abundance was positively correlated with serum TG and total cholesterol levels, and Roseburia were positively correlated with serum TG level. Furthermore, Proteobacteria (0.724, 95%CI: 0.567-0.849), Lactobacillaceae (0.703, 95%CI: 0.544-0.832), Lactobacillus (0.705, 95%CI: 0.547-0.834) and Lactobacillus_salivarius (0.706, 95%CI: 0.548-0.835) could distinguish H_CHO females from CON females, while Coriobacteriia (0.710, 95%CI: 0.547-0.841), Coriobacteriales (0.710, 95%CI: 0.547-0.841), Prevotellaceae (0.697, 95%CI: 0.534-0.830), Roseburia (0.697, 95%CI: 0.534-0.830) and Roseburia_inulinivorans (0.684, 95%CI: 0.520-0.820) could discriminate H_TG males from CON males. Based on the predictions of GM metabolic capabilities with the FAPROTAX database, a total of 51 functional assignments were obtained in females, while 38 were obtained in males. This functional prediction suggested that cellulolysis increased in L_HDL-C females compared with CON females, but decreased in L_HDL-C males compared with CON males.RESULTSThe GM composition at the phylum level included Firmicutes and Bacteroidetes as the core GM. Different GM features were identified between females and males, and the associations between GM and serum lipid profiles were different in females and males. The GM features in different dyslipidemia subgroups changed in both female patients and male patients. Proteobacteria, Lactobacillaceae, Lactobacillus and Lactobacillus_salivarius were enriched in H_CHO females compared with CON females, while Coriobacteriia were enriched in L_HDL-C females. In the comparison among the three dyslipidemia subgroups in females, Lactobacillus_salivarius were enriched in H_CHO females, and Prevotellaceae were enriched in L_HDL-C females. Compared with CON or H_TG males, Prevotellaceae, unidentified_Ruminococcaceae, Roseburia and Roseburia_inulinivorans were decreased in L_HDL-C males (P value < 0.05), and linear discriminant analysis effect size analysis indicated an enrichment of the above GM taxa in H_TG males compared with other male subgroups. Additionally, Roseburia_inulinivorans abundance was positively correlated with serum TG and total cholesterol levels, and Roseburia were positively correlated with serum TG level. Furthermore, Proteobacteria (0.724, 95%CI: 0.567-0.849), Lactobacillaceae (0.703, 95%CI: 0.544-0.832), Lactobacillus (0.705, 95%CI: 0.547-0.834) and Lactobacillus_salivarius (0.706, 95%CI: 0.548-0.835) could distinguish H_CHO females from CON females, while Coriobacteriia (0.710, 95%CI: 0.547-0.841), Coriobacteriales (0.710, 95%CI: 0.547-0.841), Prevotellaceae (0.697, 95%CI: 0.534-0.830), Roseburia (0.697, 95%CI: 0.534-0.830) and Roseburia_inulinivorans (0.684, 95%CI: 0.520-0.820) could discriminate H_TG males from CON males. Based on the predictions of GM metabolic capabilities with the FAPROTAX database, a total of 51 functional assignments were obtained in females, while 38 were obtained in males. This functional prediction suggested that cellulolysis increased in L_HDL-C females compared with CON females, but decreased in L_HDL-C males compared with CON males.This study indicates associations of GM with serum lipid profiles, supporting the notion that GM dysbiosis may participate in the pathogenesis of dyslipidemia, and sex differences should be considered.CONCLUSIONThis study indicates associations of GM with serum lipid profiles, supporting the notion that GM dysbiosis may participate in the pathogenesis of dyslipidemia, and sex differences should be considered. |
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| AbstractList | The gut microbiota (GM) has been proven to play a role in the regulation of host lipid metabolism, which provides a new theory about the pathogenesis of dyslipidemia. However, the associations of GM with dyslipidemia based on sex differences remain unclear and warrant elucidation.BACKGROUNDThe gut microbiota (GM) has been proven to play a role in the regulation of host lipid metabolism, which provides a new theory about the pathogenesis of dyslipidemia. However, the associations of GM with dyslipidemia based on sex differences remain unclear and warrant elucidation.To investigate the associations of GM features with serum lipid profiles based on sex differences in a Chinese population.AIMTo investigate the associations of GM features with serum lipid profiles based on sex differences in a Chinese population.This study ultimately recruited 142 participants (73 females and 69 males) at Honghui Hospital, Xi'an Jiaotong University. The anthropometric and blood metabolic parameters of all participants were measured. According to their serum lipid levels, female and male participants were classified into a high triglyceride (H_TG) group, a high total cholesterol (H_CHO) group, a low high-density lipoprotein cholesterol (L_HDL-C) group, and a control (CON) group with normal serum lipid levels. Fresh fecal samples were collected for 16S rRNA gene sequencing. UPARSE software, QIIME software, the RDP classifier and the FAPROTAX database were used for sequencing analyses.METHODSThis study ultimately recruited 142 participants (73 females and 69 males) at Honghui Hospital, Xi'an Jiaotong University. The anthropometric and blood metabolic parameters of all participants were measured. According to their serum lipid levels, female and male participants were classified into a high triglyceride (H_TG) group, a high total cholesterol (H_CHO) group, a low high-density lipoprotein cholesterol (L_HDL-C) group, and a control (CON) group with normal serum lipid levels. Fresh fecal samples were collected for 16S rRNA gene sequencing. UPARSE software, QIIME software, the RDP classifier and the FAPROTAX database were used for sequencing analyses.The GM composition at the phylum level included Firmicutes and Bacteroidetes as the core GM. Different GM features were identified between females and males, and the associations between GM and serum lipid profiles were different in females and males. The GM features in different dyslipidemia subgroups changed in both female patients and male patients. Proteobacteria, Lactobacillaceae, Lactobacillus and Lactobacillus_salivarius were enriched in H_CHO females compared with CON females, while Coriobacteriia were enriched in L_HDL-C females. In the comparison among the three dyslipidemia subgroups in females, Lactobacillus_salivarius were enriched in H_CHO females, and Prevotellaceae were enriched in L_HDL-C females. Compared with CON or H_TG males, Prevotellaceae, unidentified_Ruminococcaceae, Roseburia and Roseburia_inulinivorans were decreased in L_HDL-C males (P value < 0.05), and linear discriminant analysis effect size analysis indicated an enrichment of the above GM taxa in H_TG males compared with other male subgroups. Additionally, Roseburia_inulinivorans abundance was positively correlated with serum TG and total cholesterol levels, and Roseburia were positively correlated with serum TG level. Furthermore, Proteobacteria (0.724, 95%CI: 0.567-0.849), Lactobacillaceae (0.703, 95%CI: 0.544-0.832), Lactobacillus (0.705, 95%CI: 0.547-0.834) and Lactobacillus_salivarius (0.706, 95%CI: 0.548-0.835) could distinguish H_CHO females from CON females, while Coriobacteriia (0.710, 95%CI: 0.547-0.841), Coriobacteriales (0.710, 95%CI: 0.547-0.841), Prevotellaceae (0.697, 95%CI: 0.534-0.830), Roseburia (0.697, 95%CI: 0.534-0.830) and Roseburia_inulinivorans (0.684, 95%CI: 0.520-0.820) could discriminate H_TG males from CON males. Based on the predictions of GM metabolic capabilities with the FAPROTAX database, a total of 51 functional assignments were obtained in females, while 38 were obtained in males. This functional prediction suggested that cellulolysis increased in L_HDL-C females compared with CON females, but decreased in L_HDL-C males compared with CON males.RESULTSThe GM composition at the phylum level included Firmicutes and Bacteroidetes as the core GM. Different GM features were identified between females and males, and the associations between GM and serum lipid profiles were different in females and males. The GM features in different dyslipidemia subgroups changed in both female patients and male patients. Proteobacteria, Lactobacillaceae, Lactobacillus and Lactobacillus_salivarius were enriched in H_CHO females compared with CON females, while Coriobacteriia were enriched in L_HDL-C females. In the comparison among the three dyslipidemia subgroups in females, Lactobacillus_salivarius were enriched in H_CHO females, and Prevotellaceae were enriched in L_HDL-C females. Compared with CON or H_TG males, Prevotellaceae, unidentified_Ruminococcaceae, Roseburia and Roseburia_inulinivorans were decreased in L_HDL-C males (P value < 0.05), and linear discriminant analysis effect size analysis indicated an enrichment of the above GM taxa in H_TG males compared with other male subgroups. Additionally, Roseburia_inulinivorans abundance was positively correlated with serum TG and total cholesterol levels, and Roseburia were positively correlated with serum TG level. Furthermore, Proteobacteria (0.724, 95%CI: 0.567-0.849), Lactobacillaceae (0.703, 95%CI: 0.544-0.832), Lactobacillus (0.705, 95%CI: 0.547-0.834) and Lactobacillus_salivarius (0.706, 95%CI: 0.548-0.835) could distinguish H_CHO females from CON females, while Coriobacteriia (0.710, 95%CI: 0.547-0.841), Coriobacteriales (0.710, 95%CI: 0.547-0.841), Prevotellaceae (0.697, 95%CI: 0.534-0.830), Roseburia (0.697, 95%CI: 0.534-0.830) and Roseburia_inulinivorans (0.684, 95%CI: 0.520-0.820) could discriminate H_TG males from CON males. Based on the predictions of GM metabolic capabilities with the FAPROTAX database, a total of 51 functional assignments were obtained in females, while 38 were obtained in males. This functional prediction suggested that cellulolysis increased in L_HDL-C females compared with CON females, but decreased in L_HDL-C males compared with CON males.This study indicates associations of GM with serum lipid profiles, supporting the notion that GM dysbiosis may participate in the pathogenesis of dyslipidemia, and sex differences should be considered.CONCLUSIONThis study indicates associations of GM with serum lipid profiles, supporting the notion that GM dysbiosis may participate in the pathogenesis of dyslipidemia, and sex differences should be considered. |
| Author | Dai, Kun Yang, Yan-Jie Lv, Jing Wang, Ji-Han Wang, Yang-Yang Guo, Lei Yu, Yan Wang, Guo-Dong Zhao, He-Ping Yan, Yu-Zhu |
| Author_xml | – sequence: 1 givenname: Lei surname: Guo fullname: Guo, Lei – sequence: 2 givenname: Yang-Yang surname: Wang fullname: Wang, Yang-Yang – sequence: 3 givenname: Ji-Han surname: Wang fullname: Wang, Ji-Han – sequence: 4 givenname: He-Ping surname: Zhao fullname: Zhao, He-Ping – sequence: 5 givenname: Yan surname: Yu fullname: Yu, Yan – sequence: 6 givenname: Guo-Dong surname: Wang fullname: Wang, Guo-Dong – sequence: 7 givenname: Kun surname: Dai fullname: Dai, Kun – sequence: 8 givenname: Yu-Zhu surname: Yan fullname: Yan, Yu-Zhu – sequence: 9 givenname: Yan-Jie surname: Yang fullname: Yang, Yan-Jie – sequence: 10 givenname: Jing surname: Lv fullname: Lv, Jing |
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