journal article·2024-10Open access

Integrated Microbiome and Metabolome Analysis Reveals Hypothalamic‐Comorbidities Related Signatures in Craniopharyngioma

Ben Lin, Zhen Ye, Zhan Cao, Zhao Ye, Yifei Yu, Weiliang Jiang, Sichen Guo, Vladimir Melnikov, Peng Zhou, Chenxing Ji, Chengzhang Shi, Zerui Wu, Zhengyuan Chen, Yihua Xu, Qilin Zhang, Zengyi Ma, Nidan Qiao, Long Chen, Xuefei Shou, Xiaoyun Cao, Xiang Zhou, Li Zhang, Min He, Yongfei Wang, Hongying Ye, Yiming Li, Zhaoyun Zhang, Meng Wang, Renyuan Gao, Yichao Zhang

Advanced Science· Volume 11· Issue 39

Abstract

Abstract Craniopharyngioma (CP) is an intracranial tumor with high mortality and morbidity. Though biologically benign, CP will damage the hypothalamus, inducing comorbidities such as obesity, metabolic syndrome, and cognitive impairments. The roles of gut microbiome and serum metabolome in CP‐associated hypothalamic comorbidities are aimed to be explored. Patients with CP are characterized by increased Shannon diversity, Eubacterium, Clostridium, and Roseburia, alongside decreased Alistipes and Bacteroides. CP‐enriched taxa are positively correlated with dyslipidemia and cognitive decline, while CP‐depleted taxa are negatively associated with fatty liver. Subsequent serum metabolomics identified notably up‐regulated purine metabolism, and integrative analysis indicated an association between altered microbiota and elevated hypoxanthine. Phenotypic study and multi‐omics analysis in the Rax‐CreERT2::BrafV600E/+::PtenFlox/+ mouse model validated potential involvement of increased Clostridium and dysregulated purine metabolism in hypothalamic comorbidities. To further consolidate this, intervention experiments are performed and it is found that hypoxanthine co‐variated with the severity of hypothalamic comorbidities and abundance of Clostridium, and induced dysregulated purine metabolism along with redox imbalance in target organs (liver and brain cortex). Overall, the study demonstrated the potential of increased Clostridium and up‐regulated purine metabolism as signatures of CP‐associated hypothalamic‐comorbidities, and unveiled that elevated Clostridium, dysregulated purine metabolism, and redox imbalance may mediate the development and progression of CP‐associated hypothalamic‐comorbidities.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Diet and metabolism studies · Gut microbiota and health · Metabolomics and Mass Spectrometry Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Neurosurgery Huashan Hospital Fudan University Shanghai 200040 China

Department of General Surgery Shanghai Tenth People's Hospital School of Medicine Tongji University Shanghai 200072 China

Institute of Gut Microbiota Research and Engineering Development Shanghai Tenth People's Hospital Tongji University School of Medicine Shanghai 200072 China

Department of Endocrinology and Metabolism Huashan Hospital Fudan University Shanghai 200040 China

Department of Gastroenterology Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai 200080 China

Shanghai Key Laboratory of Pancreatic Disease Institute of Pancreatic Disease, Shanghai Jiao Tong University School of Medicine Shanghai 201620 China

Shanghai Medical College Fudan University Shanghai 200032 China

Department of Cardiology Huashan Hospital Fudan University Shanghai 200040 China

National Center for Neurological Disorders Shanghai 200040 China

Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration Shanghai 200040 China

Neurosurgical Institute of Fudan University Fudan University Shanghai 200040 China

Shanghai Clinical Medical Center of Neurosurgery Shanghai 200040 China

Funding

National Natural Science Foundation of China · Shanghai Science and Technology Development Foundation · Natural Science Foundation of Shanghai Municipality

References (76)

Show source-provided references
1. 10.1530/EJE-17-070710.1530/EJE-17-0707 ↗
2. 10.1038/s41572-019-0125-910.1038/s41572-019-0125-9 ↗
3. 10.1159/00050451210.1159/000504512 ↗
4. Liu H. · Neural Regen. Res. · 2012 · 7 · 601
5. 10.1007/s11102-006-0413-810.1007/s11102-006-0413-8 ↗
6. 10.1038/nrendo.2016.21710.1038/nrendo.2016.217 ↗
7. 10.1097/JNN.0b013e3181f8a59d10.1097/JNN.0b013e3181f8a59d ↗
8. 10.1210/endrev/bnac03510.1210/endrev/bnac035 ↗
9. 10.1021/acs.jafc.1c0076910.1021/acs.jafc.1c00769 ↗
10. 10.1038/nrmicro308910.1038/nrmicro3089 ↗
11. 10.3390/nu1304122810.3390/nu13041228 ↗
12. 10.1111/bph.1551210.1111/bph.15512 ↗
13. 10.1016/j.arr.2021.10134710.1016/j.arr.2021.101347 ↗
14. 10.1038/nrmicro198210.1038/nrmicro1982 ↗
15. 10.1073/pnas.081287410610.1073/pnas.0812874106 ↗
16. 10.1126/science.122547510.1126/science.1225475 ↗
17. 10.1111/cns.1408110.1111/cns.14081 ↗
18. 10.1186/s13293-023-00576-x10.1186/s13293-023-00576-x ↗
19. 10.1016/j.nbd.2024.10646010.1016/j.nbd.2024.106460 ↗
20. 10.1002/advs.20230301510.1002/advs.202303015 ↗
21. 10.1152/ajpendo.00281.202310.1152/ajpendo.00281.2023 ↗
22. 10.1016/j.jhazmat.2024.13357010.1016/j.jhazmat.2024.133570 ↗
23. 10.1002/hep.2843110.1002/hep.28431 ↗
24. 10.1530/EJE-15-042210.1530/EJE-15-0422 ↗
25. 10.1002/hep.2014010.1002/hep.20140 ↗
26. 10.1177/140349481039581710.1177/1403494810395817 ↗
27. Jin H. · Chin. J. Nerv. Ment. Dis. · 1986 · 12 · 260
28. 10.1038/nature0541410.1038/nature05414 ↗
29. 10.1038/ismej.2012.14610.1038/ismej.2012.146 ↗
30. 10.1111/j.1462-2920.2007.01281.x10.1111/j.1462-2920.2007.01281.x ↗
31. 10.1038/oby.2009.16710.1038/oby.2009.167 ↗
32. 10.1016/j.nut.2021.11129310.1016/j.nut.2021.111293 ↗
33. 10.1038/s41564-023-01355-510.1038/s41564-023-01355-5 ↗
34. 10.1016/j.jpsychires.2024.01.03610.1016/j.jpsychires.2024.01.036 ↗
35. 10.1007/s00253-023-12754-310.1007/s00253-023-12754-3 ↗
36. 10.1016/j.ijbiomac.2024.13062210.1016/j.ijbiomac.2024.130622 ↗
37. 10.1016/j.cell.2020.08.00710.1016/j.cell.2020.08.007 ↗
38. 10.1111/jdi.1320710.1111/jdi.13207 ↗
39. 10.1172/jci.insight.14476210.1172/jci.insight.144762 ↗
40. 10.1007/s12035-016-9866-610.1007/s12035-016-9866-6 ↗
41. 10.3389/fphys.2021.64774310.3389/fphys.2021.647743 ↗
42. 10.1007/s40618-018-0987-910.1007/s40618-018-0987-9 ↗
43. 10.1111/jne.1284210.1111/jne.12842 ↗
44. 10.1159/00050961610.1159/000509616 ↗
45. 10.1016/0378-1119(93)90652-J10.1016/0378-1119(93)90652-J ↗
46. 10.1074/jbc.274.8.456110.1074/jbc.274.8.4561 ↗
47. 10.1016/S0891-5849(98)00154-310.1016/S0891-5849(98)00154-3 ↗
48. 10.2174/092986732366616072509191510.2174/0929867323666160725091915 ↗
49. Sarnesto A. · Lab Invest. · 1996 · 74 · 48
50. Friedl H. P. · Am. J. Pathol. · 1990 · 136 · 491
51. 10.1161/01.ATV.0000170827.16296.6e10.1161/01.ATV.0000170827.16296.6e ↗
52. 10.1096/fasebj.9.11.764941510.1096/fasebj.9.11.7649415 ↗
53. 10.3390/ijms1911359810.3390/ijms19113598 ↗
54. 10.1016/j.jare.2016.11.00410.1016/j.jare.2016.11.004 ↗
55. 10.1074/jbc.R90001020010.1074/jbc.R900010200 ↗
56. 10.1039/D1FO01830B10.1039/D1FO01830B ↗
57. 10.1038/s41580-023-00645-410.1038/s41580-023-00645-4 ↗
58. 10.2165/00003088-200746080-0000110.2165/00003088-200746080-00001 ↗
59. 10.1016/j.semarthrit.2014.05.00710.1016/j.semarthrit.2014.05.007 ↗
60. 10.1074/jbc.M117.81678510.1074/jbc.M117.816785 ↗
61. 10.1002/hep.3097810.1002/hep.30978 ↗
62. 10.1016/j.bbrc.2017.10.00410.1016/j.bbrc.2017.10.004 ↗
63. 10.1002/pbc.2849310.1002/pbc.28493 ↗
64. 10.1186/s40168-018-0520-610.1186/s40168-018-0520-6 ↗
65. 10.1128/spectrum.00425-2110.1128/spectrum.00425-21 ↗
66. 10.1371/journal.pcbi.100944210.1371/journal.pcbi.1009442 ↗
67. 10.1101/gr.097261.10910.1101/gr.097261.109 ↗
68. 10.1093/nar/gkl72310.1093/nar/gkl723 ↗
69. 10.1093/bioinformatics/bts56510.1093/bioinformatics/bts565 ↗
70. 10.1038/nature1356810.1038/nature13568 ↗
71. 10.1101/gr.22920210.1101/gr.229202 ↗
72. 10.1210/clinem/dgaa01410.1210/clinem/dgaa014 ↗
73. 10.1093/nar/gkv38010.1093/nar/gkv380 ↗
74. 10.1002/imt2.1010.1002/imt2.10 ↗
75. 10.1093/bioinformatics/btac00310.1093/bioinformatics/btac003 ↗
76. 10.1038/s41467-021-22640-z10.1038/s41467-021-22640-z ↗