探討血液透析患者中腸胃道菌相之變化

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趙盈婷(Ying-Ting Chao) 查詢紙本館藏

畢業系所

系統生物與生物資訊研究所

論文名稱

探討血液透析患者中腸胃道菌相之變化
(Role o f T he G ut M icrobiota and I ts A ssociate d M etabolites in H emo dialysis P atients)

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摘要(中)

心血管疾病為慢性腎病及末期腎病患者中相當常見的併發及死亡原因之一，其中血管鈣化為一個重要的危險因子。本研究探討腸道微生物群對於血管鈣化對於末期腎病患者心血管疾病的影響。實驗材料使用之糞便檢體，分別來自於健康對照組、控制良好鈣磷乘積產物的血液透析患者(HD)以及具有高鈣磷乘積產物的血液透析患者(HDHCP)，並對這些組別進行了16S片段定序再進行後續腸道微生物組成分析。結果顯示，腸道微生物組成在健康對照組和血液透析患者中存在著顯著差異。在血液透析患者的菌相中，厚壁菌門、放線菌門以及變形菌門在豐度上有明顯增加。而在高鈣磷乘積產物組中，厚壁菌門中的一種菌屬Lachnospiraceae_FCS020_group，比起其他組別，則有顯著的增加。除了偵測腸道微生物組成變化外，我們利用PICRUSt軟體來預測功能性分析，發現HDHCP組中有幾個與血管鈣化相關的代謝途徑明顯差異，包括糖醣磷酸途徑、類固醇及萜烯骨架生物合成途徑與脂肪酸鏈的延長合成的上調。我們的研究結果證明了腸道微生物菌相的改變以及其代謝物，在末期腎病患者血管鈣化過程中扮演著重要角色，並對鈣磷乘積產物的生成具有潛在影響。某些微生物的增加和特定代謝途徑可能會影響末期腎病患者中的血管鈣化程度。

摘要(英)

This study investigated the impact of gut microbiota on vascular calcification (VC), a cardiovascular risk factor in end-stage renal disease (ESRD). Fecal samples were collected from healthy controls, dialysis patients with controlled Ca x P, and dialysis patients with higher Ca x P (HDHCP). The samples were subjected to 16S amplicon sequencing to analyze the gut microbial composition. The results showed significant differences in gut microbial composition between hemodialysis patients and healthy controls. Three phyla (Firmicutes, Actinobacteria, and Proteobacteria) were notably more abundant in hemodialysis patients. Within the group with higher Ca x P, a specific genus called Lachnospiraceae_FCS020_group was significantly increased. Serval metabolic pathway, as predicted by the PICRUSt software, including the pentose phosphate pathway, the steroid biosynthesis pathway, the terpenoid backbone biosynthesis pathway and fatty acid elongation pathway, were found to be upregulated in the higher Ca x P group. Our research highlights the significance of dysbiosis in the gut microbiome of hemodialysis patients and its potential influence on Ca x P levels. We observed an elevated presence of specific microbial taxa and the upregulation of certain metabolic pathways. These findings suggest that these factors may play a role in the development of VC, a known cardiovascular risk factor in individuals with ESRD.

關鍵字(中)

★ 鈣磷積產物
★ 慢性腎臟疾病
★ 腸道微生物
★ 菌群失調

關鍵字(英)

★ calcium-phosphorus product
★ chronic kidney disease
★ gut microbiota
★ dysbiosis

論文目次

中文摘要 I
ABSTRACT II
謝辭 III
Contents IV
List of Figures V
List of Tables VI
Chapter II Materials and methods 9
2-1 Patients and Controls 9
2-2 Stool DNA extraction and 16S rRNA gene amplification 10
2-3 16S rRNA Gene Amplicon Sequencing 11
2-4 Bioinformatics and statistical analysis 12
Chapter III Results 15
3-1 Characteristics of the participants in the clinical study 15
3-2 Comparison of gut microbial diversity between healthy controls and hemodialysis patients 16
3-3 Comparison of the gut microbiome composition in healthy controls and hemodialysis patients 18
3-4 Potential bacterial species associated with higher Ca xP levels in hemodialysis patients 20
3-5 Correlation between the gut microbiome and clinical indicators in hemodialysis patients 22
3-6 Identification of crucial microbial functions associated with Ca xP levels in dialysis patients 22
Chapter IV Discussion 24
Chapter V Conclusion 33
Chapter VI Bibliography 34
Chapter VII Tables 44
Chapter VIII Figures 49
Appendix 58

參考文獻

1 Kovesdy, C. P. Epidemiology of chronic kidney disease: an update 2022. Kidney International Supplements 12, 7-11, doi:https://doi.org/10.1016/j.kisu.2021.11.003 (2022).
2 Foreman, K. J. et al. Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories. Lancet 392, 2052-2090, doi:10.1016/S0140-6736(18)31694-5 (2018).
3 Tsai, H. J., Wu, P. Y., Huang, J. C. & Chen, S. C. Environmental Pollution and Chronic Kidney Disease. Int J Med Sci 18, 1121-1129, doi:10.7150/ijms.51594 (2021).
4 Chen, Y. C. et al. Genome-Wide Association Study for eGFR in a Taiwanese Population. Clin J Am Soc Nephrol 17, 1598-1608, doi:10.2215/CJN.02180222 (2022).
5 Collins, A. J. et al. US Renal Data System 2013 Annual Data Report. Am J Kidney Dis 63, A7, doi:10.1053/j.ajkd.2013.11.001 (2014).
6 DeFronzo, R. A. & Bakris, G. L. Modifying chronic kidney disease progression with the mineralocorticoid receptor antagonist finerenone in patients with type 2 diabetes. Diabetes Obes Metab 24, 1197-1205, doi:10.1111/dom.14696 (2022).
7 Muntner, P. et al. Hypertension awareness, treatment, and control in adults with CKD: results from the Chronic Renal Insufficiency Cohort (CRIC) Study. Am J Kidney Dis 55, 441-451, doi:10.1053/j.ajkd.2009.09.014 (2010).
8 Ceja-Galicia, Z. A. et al. The Development of Dyslipidemia in Chronic Kidney Disease and Associated Cardiovascular Damage, and the Protective Effects of Curcuminoids. Foods 12, doi:10.3390/foods12050921 (2023).
9 Wang, M., Lin, X., Yang, X. & Yang, Y. Research progress on related mechanisms of uric acid activating NLRP3 inflammasome in chronic kidney disease. Ren Fail 44, 615-624, doi:10.1080/0886022X.2022.2036620 (2022).
10 Yamamoto, R. et al. A Dose-Dependent Association between Alcohol Consumption and Incidence of Proteinuria and Low Glomerular Filtration Rate: A Systematic Review and Meta-Analysis of Cohort Studies. Nutrients 15, doi:10.3390/nu15071592 (2023).
11 Seidu, S. et al. Physical activity and risk of chronic kidney disease: systematic review and meta-analysis of 12 cohort studies involving 1,281,727 participants. Eur J Epidemiol 38, 267-280, doi:10.1007/s10654-022-00961-7 (2023).
12 Lamb, E. J., Levey, A. S. & Stevens, P. E. The Kidney Disease Improving Global Outcomes (KDIGO) guideline update for chronic kidney disease: evolution not revolution. Clin Chem 59, 462-465, doi:10.1373/clinchem.2012.184259 (2013).
13 Kraus, M. A., Kalra, P. A., Hunter, J., Menoyo, J. & Stankus, N. The prevalence of vascular calcification in patients with end-stage renal disease on hemodialysis: a cross-sectional observational study. Ther Adv Chronic Dis 6, 84-96, doi:10.1177/2040622315578654 (2015).
14 Zhu, H. et al. Machine Learning for the Prevalence and Severity of Coronary Artery Calcification in Nondialysis Chronic Kidney Disease Patients: A Chinese Large Cohort Study. J Thorac Imaging 37, 401-408, doi:10.1097/RTI.0000000000000657 (2022).
15 Haarhaus, M., Brandenburg, V., Kalantar-Zadeh, K., Stenvinkel, P. & Magnusson, P. Alkaline phosphatase: a novel treatment target for cardiovascular disease in CKD. Nature Reviews Nephrology 13, 429-442, doi:10.1038/nrneph.2017.60 (2017).
16 Sarnak, M. J. et al. Chronic Kidney Disease and Coronary Artery Disease: JACC State-of-the-Art Review. J Am Coll Cardiol 74, 1823-1838, doi:10.1016/j.jacc.2019.08.1017 (2019).
17 Foley, R. N. & Parfrey, P. S. Cardiovascular disease and mortality in ESRD. J Nephrol 11, 239-245 (1998).
18 Matsushita, K. et al. Epidemiology and risk of cardiovascular disease in populations with chronic kidney disease. Nat Rev Nephrol 18, 696-707, doi:10.1038/s41581-022-00616-6 (2022).
19 Matsushita, K., Ballew, S. H. & Coresh, J. Cardiovascular risk prediction in people with chronic kidney disease. Curr Opin Nephrol Hypertens 25, 518-523, doi:10.1097/MNH.0000000000000265 (2016).
20 Ogata, H. et al. Effect of Treating Hyperphosphatemia With Lanthanum Carbonate vs Calcium Carbonate on Cardiovascular Events in Patients With Chronic Kidney Disease Undergoing Hemodialysis: The LANDMARK Randomized Clinical Trial. JAMA 325, 1946-1954, doi:10.1001/jama.2021.4807 (2021).
21 Foley, R. N., Parfrey, P. S. & Sarnak, M. J. Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis 32, S112-119, doi:10.1053/ajkd.1998.v32.pm9820470 (1998).
22 Lau, W. L., Festing, M. H. & Giachelli, C. M. Phosphate and vascular calcification: Emerging role of the sodium-dependent phosphate co-transporter PiT-1. Thromb Haemost 104, 464-470, doi:10.1160/TH09-12-0814 (2010).
23 Strauss, H. W., Nakahara, T., Narula, N. & Narula, J. Vascular calcification: the evolving relationship of vascular calcification to major acute coronary events. Journal of Nuclear Medicine 60, 1207-1212 (2019).
24 Jablonski, K. L. & Chonchol, M. Vascular calcification in end-stage renal disease. Hemodial Int 17 Suppl 1, S17-21, doi:10.1111/hdi.12084 (2013).
25 Yin, L. et al. Role of gut microbiota-derived metabolites on vascular calcification in CKD. J Cell Mol Med 25, 1332-1341, doi:10.1111/jcmm.16230 (2021).
26 Lynch, S. V. & Pedersen, O. The Human Intestinal Microbiome in Health and Disease. N Engl J Med 375, 2369-2379, doi:10.1056/NEJMra1600266 (2016).
27 Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59-65, doi:10.1038/nature08821 (2010).
28 Korem, T. et al. Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples. Science 349, 1101-1106, doi:10.1126/science.aac4812 (2015).
29 Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210-215, doi:10.1038/nature25973 (2018).
30 Eckburg, P. B. et al. Diversity of the human intestinal microbial flora. Science 308, 1635-1638, doi:10.1126/science.1110591 (2005).
31 Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174-180, doi:10.1038/nature09944 (2011).
32 Moore, W. E. & Holdeman, L. V. Human fecal flora: the normal flora of 20 Japanese-Hawaiians. Appl Microbiol 27, 961-979, doi:10.1128/am.27.5.961-979.1974 (1974).
33 Mizrahi-Man, O., Davenport, E. R. & Gilad, Y. Taxonomic classification of bacterial 16S rRNA genes using short sequencing reads: evaluation of effective study designs. PLoS One 8, e53608, doi:10.1371/journal.pone.0053608 (2013).
34 Luo, D. et al. The Effects of Hemodialysis and Peritoneal Dialysis on the Gut Microbiota of End-Stage Renal Disease Patients, and the Relationship Between Gut Microbiota and Patient Prognoses. Front Cell Infect Microbiol 11, 579386, doi:10.3389/fcimb.2021.579386 (2021).
35 Dai, L. et al. Sevelamer Use in End-Stage Kidney Disease (ESKD) Patients Associates with Poor Vitamin K Status and High Levels of Gut-Derived Uremic Toxins: A Drug-Bug Interaction? Toxins (Basel) 12, doi:10.3390/toxins12060351 (2020).
36 Witkowski, M., Weeks, T. L. & Hazen, S. L. Gut Microbiota and Cardiovascular Disease. Circ Res 127, 553-570, doi:10.1161/CIRCRESAHA.120.316242 (2020).
37 Spychala, M. S. et al. Age-related changes in the gut microbiota influence systemic inflammation and stroke outcome. Ann Neurol 84, 23-36, doi:10.1002/ana.25250 (2018).
38 Tanase, D. M. et al. Role of Gut Microbiota on Onset and Progression of Microvascular Complications of Type 2 Diabetes (T2DM). Nutrients 12, doi:10.3390/nu12123719 (2020).
39 Onal, E. M., Afsar, B., Covic, A., Vaziri, N. D. & Kanbay, M. Gut microbiota and inflammation in chronic kidney disease and their roles in the development of cardiovascular disease. Hypertens Res 42, 123-140, doi:10.1038/s41440-018-0144-z (2019).
40 Velasquez, M. T., Centron, P., Barrows, I., Dwivedi, R. & Raj, D. S. Gut Microbiota and Cardiovascular Uremic Toxicities. Toxins (Basel) 10, doi:10.3390/toxins10070287 (2018).
41 Shin, N. R., Whon, T. W. & Bae, J. W. Proteobacteria: microbial signature of dysbiosis in gut microbiota. Trends Biotechnol 33, 496-503, doi:10.1016/j.tibtech.2015.06.011 (2015).
42 Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and environmental microbiology 75, 7537-7541 (2009).
43 Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79, 5112-5120, doi:10.1128/AEM.01043-13 (2013).
44 Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194-2200, doi:10.1093/bioinformatics/btr381 (2011).
45 Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41, D590-596, doi:10.1093/nar/gks1219 (2013).
46 Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature methods 7, 335-336 (2010).
47 Oksanen, J. et al. Vegan: community ecology package http://CRAN. R-project. org/package= vegan (2013).
48 Warnes, G. R. et al. gplots: Various R programming tools for plotting data. R package version 2, 1 (2009).
49 Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol 12, R60, doi:10.1186/gb-2011-12-6-r60 (2011).
50 Jonsson, V., Osterlund, T., Nerman, O. & Kristiansson, E. Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics. BMC Genomics 17, 78, doi:10.1186/s12864-016-2386-y (2016).
51 Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15, 550, doi:10.1186/s13059-014-0550-8 (2014).
52 Langille, M. G. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature biotechnology 31, 814-821 (2013).
53 Bao, W. H. et al. Relationship between gut microbiota and vascular calcification in hemodialysis patients. Ren Fail 45, 2148538, doi:10.1080/0886022X.2022.2148538 (2023).
54 Merino-Ribas, A. et al. Vascular Calcification and the Gut and Blood Microbiome in Chronic Kidney Disease Patients on Peritoneal Dialysis: A Pilot Study. Biomolecules 12, doi:10.3390/biom12070867 (2022).
55 Sumida, K., Yamagata, K. & Kovesdy, C. P. Constipation in CKD. Kidney Int Rep 5, 121-134, doi:10.1016/j.ekir.2019.11.002 (2020).
56 Chung, S., Barnes, J. L. & Astroth, K. S. Gastrointestinal Microbiota in Patients with Chronic Kidney Disease: A Systematic Review. Adv Nutr 10, 888-901, doi:10.1093/advances/nmz028 (2019).
57 Liu, S. et al. Effect of probiotics on the intestinal microbiota of hemodialysis patients: a randomized trial. Eur J Nutr 59, 3755-3766, doi:10.1007/s00394-020-02207-2 (2020).
58 Ren, Z. et al. Alterations of the Human Gut Microbiome in Chronic Kidney Disease. Adv Sci (Weinh) 7, 2001936, doi:10.1002/advs.202001936 (2020).
59 Wu, I.-W. et al. Gut microbiota as diagnostic tools for mirroring disease progression and circulating nephrotoxin levels in chronic kidney disease: discovery and validation study. International journal of biological sciences 16, 420 (2020).
60 De Angelis, M. et al. Microbiota and metabolome associated with immunoglobulin A nephropathy (IgAN). PLoS One 9, e99006, doi:10.1371/journal.pone.0099006 (2014).
61 Vaziri, N. D. et al. Chronic kidney disease alters intestinal microbial flora. Kidney Int 83, 308-315, doi:10.1038/ki.2012.345 (2013).
62 Joffe, Y. T., Collins, M. & Goedecke, J. H. The relationship between dietary fatty acids and inflammatory genes on the obese phenotype and serum lipids. Nutrients 5, 1672-1705, doi:10.3390/nu5051672 (2013).
63 Matsumoto, N. et al. Relationship between Nutrient Intake and Human Gut Microbiota in Monozygotic Twins. Medicina (Kaunas) 57, doi:10.3390/medicina57030275 (2021).
64 Ferguson, J. F. et al. High dietary salt-induced dendritic cell activation underlies microbial dysbiosis-associated hypertension. JCI Insight 5, doi:10.1172/jci.insight.126241 (2019).
65 Seldin, M. M. et al. Trimethylamine N-Oxide Promotes Vascular Inflammation Through Signaling of Mitogen-Activated Protein Kinase and Nuclear Factor-κB. J Am Heart Assoc 5, doi:10.1161/jaha.115.002767 (2016).
66 Gao, J. et al. Gut microbial taxa as potential predictive biomarkers for acute coronary syndrome and post-STEMI cardiovascular events. Scientific Reports 10, 2639, doi:10.1038/s41598-020-59235-5 (2020).
67 Vojinovic, D. et al. Relationship between gut microbiota and circulating metabolites in population-based cohorts. Nat Commun 10, 5813-5813, doi:10.1038/s41467-019-13721-1 (2019).
68 Tang, C. et al. Effects of polysaccharides from purple sweet potatoes on immune response and gut microbiota composition in normal and cyclophosphamide treated mice. Food Funct 9, 937-950, doi:10.1039/c7fo01302g (2018).
69 Zou, X. Y. et al. Bacillus subtilis inhibits intestinal inflammation and oxidative stress by regulating gut flora and related metabolites in laying hens. Animal 16, 100474, doi:10.1016/j.animal.2022.100474 (2022).
70 Jovanovich, A., Isakova, T. & Stubbs, J. Microbiome and Cardiovascular Disease in CKD. Clin J Am Soc Nephrol 13, 1598-1604, doi:10.2215/CJN.12691117 (2018).
71 Gupte, S. A. et al. Vascular Signaling by Free Radicals Pentose phosphate pathway coordinates multiple redox-controlled relaxing mechanisms in bovine coronary arteries. Am J Physiol Heart Circ Physiol 285, H2316-H2326 (2003).
72 Peiró, C. et al. Inflammation, glucose, and vascular cell damage: the role of the pentose phosphate pathway. Cardiovascular diabetology 15, 1-15 (2016).
73 Zhu, Y. et al. Advanced glycation end products accelerate calcification in VSMCs through HIF-1α/PDK4 activation and suppress glucose metabolism. Scientific reports 8, 1-12 (2018).
74 Colhoun, H. M. et al. Lipoprotein subclasses and particle sizes and their relationship with coronary artery calcification in men and women with and without type 1 diabetes. Diabetes 51, 1949-1956 (2002).
75 Prenner, S. B. et al. Very low density lipoprotein cholesterol associates with coronary artery calcification in type 2 diabetes beyond circulating levels of triglycerides. Atherosclerosis 236, 244-250, doi:10.1016/j.atherosclerosis.2014.07.008 (2014).
76 Xie, X. et al. Association of very low-density lipoprotein cholesterol with all-cause and cardiovascular mortality in peritoneal dialysis. Kidney and Blood Pressure Research 42, 52-61 (2017).
77 Ren, J. et al. Long-term coronary heart disease risk associated with very-low-density lipoprotein cholesterol in Chinese: the results of a 15-Year Chinese Multi-Provincial Cohort Study (CMCS). Atherosclerosis 211, 327-332, doi:10.1016/j.atherosclerosis.2010.02.020 (2010).
78 Aarsland, A. & Wolfe, R. R. Hepatic secretion of VLDL fatty acids during stimulated lipogenesis in men. J Lipid Res 39, 1280-1286 (1998).
79 Kageyama, A. et al. Palmitic acid induces osteoblastic differentiation in vascular smooth muscle cells through ACSL3 and NF-κB, novel targets of eicosapentaenoic acid. PLoS One 8, e68197 (2013).
80 Huang, J. M., Xian, H. & Bacaner, M. Long-chain fatty acids activate calcium channels in ventricular myocytes. Proceedings of the National Academy of Sciences of the United States of America 89, 6452-6456, doi:10.1073/pnas.89.14.6452 (1992).
81 Liu, T. et al. Bioaccumulation of blood long-chain fatty acids during hemodialysis. Metabolites 12, 269 (2022).
82 Block, G. A., Kilpatrick, R. D., Lowe, K. A., Wang, W. & Danese, M. D. CKD-mineral and bone disorder and risk of death and cardiovascular hospitalization in patients on hemodialysis. Clin J Am Soc Nephrol 8, 2132-2140, doi:10.2215/CJN.04260413 (2013).
83 Danese, M. D., Belozeroff, V., Smirnakis, K. & Rothman, K. J. Consistent control of mineral and bone disorder in incident hemodialysis patients. Clin J Am Soc Nephrol 3, 1423-1429, doi:10.2215/CJN.01060308 (2008).
84 Viegas, C., Araújo, N., Marreiros, C. & Simes, D. The interplay between mineral metabolism, vascular calcification and inflammation in Chronic Kidney Disease (CKD): challenging old concepts with new facts. Aging (Albany NY) 11, 4274 (2019).

指導教授

許藝瓊(Yi-Chiung Hsu)

審核日期

2023-7-24

推文