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Open Access 01.12.2023 | Research

Integrative analysis of purine metabolites and gut microbiota in patients with neuromyelitis optica spectrum disorders after mycophenolate mofetil treatment

verfasst von: Gong Li, Xiaoyu Ma, Lijuan Xia, Ran Wei, Xiran Wang, Cang Li, Yuge Wang, Limin He, Hao Ren, Jian Sun, Wei Qiu

Erschienen in: BMC Neurology | Ausgabe 1/2023

Abstract

Background

Neuromyelitis optica spectrum disorder (NMOSD) is a recurring inflammatory demyelinating disease that is commonly observed in Asian countries like China. Prior investigations have shown that mycophenolate mofetil (MMF) with better biocompatibility compared to azathioprine (AZA), and can prevent relapses of NMOSD, but the efficacy was controversially reported in different NMOSD cases. We aimed to explore the factors that weaken efficacy of MMF in NMOSD.

Methods

A total of 34 NMOSD patients treated with MMF were prospectively enrolled and grouped according to the therapeutic efficacy as effective group (EG, n = 23) versus less-effective group (LEG, n = 11). The purine metabolites were profiled in serum samples and gut microbiota was analyzed using 16S rRNA sequencing with stool samples from the same patients.

Results

Purine salvage pathway (PSP) metabolites (inosine, hypoxanthine, xanthine, guanine and uric acid) in the serum of NMOSD patients were elevated in the LEG compared to EG (p < 0.05). Additionally, the richness and microbial diversity of gut microbiota was found to be similar between EG and LEG patients. However, LEG patients had increased presence of Clostridium and Synergistes but decreased abundance of the Coprococcus genus.

Conclusions

The PSP metabolites and composition of the gut microbiota were changed between patients with or without optimal clinical response after MMF treatment. This may help us to understand the pharmacodynamics of MMF in NMOSD.

Gong Li and Xiaoyu Ma are co-first authors of the article.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

MMF

Mycophenolate Mofetil

NMOSD

Neuromyelitis Optica Spectrum Disorders

Effective Group

LEG

Less-Effective Group

PSP

Purine Salvage Pathway

MPA

Mycophenolic Acid

AQP4-IgG

Anti-Aquaporin-4 Antibodies

EDSS

Expanded Disability Status Scale

SNPs

Single Nucleotide Polymorphisms:UGT1A9:UDP-Glucuronosyltransferase 1–9

IMPDH

Inosine Monophosphate Dehydrogenase

SNP

Single Nucleotide Polymorphisms

GUS

β-glucuronidase

CNS

Central Nervous System

Introduction

Neuromyelitis optica spectrum disorders (NMOSD) is a severe, disabling autoimmune disease of the central nervous system (CNS) characterized by its association with serum anti-aquaporin-4 antibodies (AQP4-IgG) [1‐4]. Clinically, NMOSD results in a range of syndromes of varied severities including recurrent paralysis, blindness and brain syndromes [5]. Immunosuppressive therapies including administration of azathioprine (AZA) and mycophenolate mofetil (MMF) in addition to the new B cell- and complement-targeted therapies are the current NMOSD treatments aimed at relapse prevention [6, 7], with MMF demonstrating better tolerability compared to AZA [8]. MMF is a prodrug whose active metabolite mycophenolic acid (MPA) inhibits inosine monophosphate dehydrogenase (IMPDH) and suppresses the de novo synthesis of guanine nucleotides in rapidly-proliferating cells such as T and B lymphocytes [9, 10]. MMF/MPA treatments significantly and comprehensively lower the levels of baseline purine metabolites in intestinal cell models as well as in patients [11, 12]. However, previous studies have shown mixed efficacy of MMF in treating NMOSD, the proportion of recurrence-free patients in NMOSD is 46–73%, the Expanded Disability Status Scale (EDSS) score decreased or stabilized in 83–91% of patients [6, 13‐15].

Our laboratory recently demonstrated that the gut microbiomes of healthy individuals can be distinguished from NMOSD patients. In particular, the degree of Streptococcus spp. colonization was significantly and positively correlated with disease severity [16]. Other studies have demonstrated strong associations between several Clostridium spp. and NMOSD development [17, 18]. These studies linked dynamic interactions of the host gut microbiota to NMOSD. However, it is not known whether NMOSD therapies such as MMF administration are also influenced by the gut microbiota and whether the gut microbiota has a role in the efficacy of these therapies.

In the current study, we performed metabolic profiling and microbiome analysis on samples collected from NMOSD patients. This may not only help us to understand the pharmacodynamics of MMF but may also reveal the reasons of therapeutic effect.

Materials and methods

Reagents and chemicals

Inosine, hypoxanthine, xanthine, guanine and uric acid were obtained from MedChemExpress (Shanghai, China) and were prepared as 1000 ppm methanol stocks. NaOH 10 mM was used as necessary to increase solubility. Acetonitrile was purchased from Macklin (Shanghai, China).

Patient enrollment

The study group included 34 NMOSD patients who had received MMF therapy (0.5 g MMF orally, twice a day for long term therapy) at the Third Affiliated Hospital of Sun Yat-sen University (Guangzhou, China). The primary inclusion criteria were (1) clinical diagnosis of NMOSD and seropositive for AQP4-IgG [19, 20]; (2) patients aged 15–65 and (3) an Kurtzke Expanded Disability Status Scale (EDSS) score ≤ 8.0. Patients who met any of the following key criteria were excluded: (1) treatment with antibiotics or probiotics within the last 3 months; (2) emergency treatment such as plasmapheresis or intravenous methylprednisolone for acute recurrence within the last 1 month; (3) Concurrent disease with diabetes mellitus, systemic autoimmune diseases or other neurological diseases.

Stool and serum samples were taken from the patient that received MMF treatment at least for 3 months. Stool samples were taken in the morning. Serum samples were taken for 0.5, 1 and 2 h after receiving MMF in the early morning. Clinical data was collected included relapses, follow-up time and EDSS score. The 34 participants were divided into two groups: patients with no relapse were classified into the effective group (EG). Patients who relapsed after 3 months of MMF treatment were treated as the less-effective group (LEG). This study was approved by the ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University ([2020]02-016-01) and all patients signed informed consent.

HPLC-MS/MS analysis

Serum sample processing and HPLC-UV–MS/MS analysis were performed as previously described with minor modifications [21]. In brief, chromatographic separations were conducted using a Shimadzu LC-30AD series HPLC system (Shimadzu, Kyoto, Japan) with an Frulic N column (AZYP, LLC, Arlington, USA). Analytes were eluted at a flow rate of 0.4 mL/min using a gradient of phase A (0.2% formic acid) and phase B (0.2% formic acid in acetonitrile) as follows: 0–0.5 min, 80% B; 0.5–4.5 min, 50% B; 4.5–8 min, 80% B. The eluates were monitored by UV at 254 nm and MS detection in parallel. The injection volume as 5 µL, and the column temperature was maintained at 23 °C. MS detection was performed using an AB Sciex Triple Quad 5500 (AB Sciex, Toronto, Canada).

Microbiome 16S rRNA gene sequencing, alignment and analysis

Microbial DNA was extracted from fecal samples of NMOSD patients using the E.Z.N.A. Stool DNA Kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s protocol. Extracted DNA was qualitatively and quantitatively analyzed by gel electrophoresis and ultraviolet spectroscopy before sequencing. Thereafter, bacterial 16S rDNA V3–V4 regions were amplified using primers 341 F and 806R (Illumina, San Diego, CA, USA). The resulting amplicons were sequenced using the Illumina NovaSeq 6000 platform (Guangdong Longsee Biomedical, Foshan, China).

Statistical analyses

The data were expressed as the mean ± standard deviation (SD). A unpaired parametric t-test was performed for comparison of the two groups using Prism v8.0 software (GraphPad, San Diego, CA, USA). A p value of 0.05 was considered to be statistically significant.

Results

Clinical characteristics

A total of 34 NMOSD patients who had received MMF therapy were recruited. All patients were diagnosed with NMOSD according to clinical diagnosis and seropositive for AQP4-IgG [19]. Immunotherapies such as MMF or AZA typically require 3–6 months to reach a milestone of stable effectiveness [22]. Hence, all the recurrences we recorded in this study occurred after 6 months of MMF use. The acute treatment guideline for NMOSD involves high-dose steroid therapy, follow with a gradual reduction in steroid usage and long-term maintenance [22‐25]. Throughout the steroid treatment process, patients were gradually tapered to a maintenance dose of 8 mg methylprednisolone or 10 mg prednisone every other day or 5 mg prednisone once daily during the remission phase. As 4 mg methylprednisolone is equal to 5 mg prednisone, they all use similar doses of steroids. And in the remission stage, they all didn’t use other immunotherapy to prevent relapse currently and previously.

Our group of NMOSD patients were analyzed according to their clinical responses to MMF therapies and grouped according to responders (EG) and less-responders (LEG). The clinical characteristics of the patients are shown in Table 1. Significant differences in relapse times (p < 0.001) and EDSS after MMF (p = 0.005) were observed between EG and LEG patients.

Table 1

Clinical parameters in NMOSD patients according to response to MMF

Variables	EG (n = 23)	LEG (n = 11)	p value
Relapse times	0	2.00 ± 0.89	< 0.001
Age (years)	39.95 ± 12.20	47.45 ± 11.76	0.106
Gender (male: female)	5:18	1:10	0.638
Follow-up time (months)	21.00 ± 14.34	37 ± 20.27	0.060
EDSS before MMF	4.00 ± 0.86	3.5 ± 1.06	0.228
EDSS after MMF	3.00 ± 1.06	4.0 ± 1.30	0.005

Purine salvage pathway metabolites are maintained at high levels in LEG patients

We examined purine metabolites whose biosynthesis is targeted by MMF(MPA) in the serum of recruited patients (Fig. 1A-B). Interestingly, we found distinct differences in the abundance of the purine salvage pathway (PSP) metabolites inosine, hypoxanthine, xanthine, guanine and uric acid (UA) for the patients that responded to MMF therapy (EG) and non-responders (LEG). These 5 PSP metabolites were all elevated in the serum of LEG patients. In particular, inosine, hypoxanthine, xanthine and guanine were significantly (p < 0.05) decreased in EG patients 1 h after receiving the MMF. At 2 h following MMF intervention, inosine levels reached the level of significance (p < 0.05) and were also lower in EG patients (Fig. 1C-G). The observations indicated a negative correlation between the MMF therapeutic response and PSP metabolite levels in serum of patients.

Altered gut microbiota in NMOSD patients by their responses to MMF therapy

Previous studies have indicated that the gut microbiota participates in the development and pathogenesis of NMOSD [16‐18, 26]. The gut microbiota was profiled for each patient using 16 S rRNA sequencing. The microbial richness (operational taxonomic units, OTUs and Chao1 indices) and microbial diversity (Shannon and Simpson indices) were similar between EG and LEG patients (Fig. 2A-D). β diversity was assessed using principal-coordinate analysis (PCA) based on weighted UniFrac metrics and the results again indicated no compositional alterations between the microbiota of the patients in the two groups (Fig. 2E).

Since no structural shifts were observed among the patients in the response to MMF, we extended our taxonomic comparisons. The microbial compositions of each group were compared using the 20 most-abundant operational taxonomic units OUT at the genus level. Overall, Bacteroides dominated in both EG and LEG patients while the other dominate genera including Faecalibacterium, Roseburia and Megamonas, rarely exceeded 30% of all sequences (Fig. 2F). Interestingly, LEfSe analysis indicated that the abundance of Clostridium and Synergistes had significantly increased for EG and corresponded to a significant decline in abundance of the Coprococcus genus in LEG (Fig. 2G). These results indicated that overall, the gut microbiota stayed compositionally stable in the MMF therapy while the abundance of 3 bacterial genera were significantly altered.

Discussion

NMOSD pathogenesis has been linked to the activity of microbiota [26, 27]. Long-term MMF therapy is widely used in immunological and NMOSD diseases although not all patients display the optimal clinical response. Whether the microbiota is also involved in the therapeutic response to the drugs against NMOSD has not been previously investigated. In this study, our findings first showed that the purine metabolites and composition of the gut microbiota were changed.

The NMOSD patients may experience pathogenesis of different level that influenced by various factors such as disease duration, comorbidities, prior disease-modifying treatment (DMT), and their baseline magnetic resonance imaging (MRI) status. However, NMOSD exacerbation is often reported to be associated with recurrences rather than a gradual progression, typically manifesting as a “cliff-like” exacerbation followed by incomplete recovery [6]. Consequently, the worsening of NMOSD appears to have little correlation with disease duration [7]. Based on our pre-survey, all patients recruited in our study had no histories for other DMT. Since the MMF has been primarily considered to target the relapses of NMOSD, we assessed failed responses of patients to MMF by examining recurrences and the EDSS.

The assessment of the effectiveness of MMF primarily relies on the area under the plasma concentration-time curve from 0 to 12 h (AUC_0 − 12) as the principal parameter. However, while the AUC_0 − 12 of the MPA concentration-time curve exhibits a strong correlation with pharmacological effects, its measurement proves to be arduous in a clinical setting. Several clinical trials have demonstrated that the predicted value of the AUC from 0 to 2 h (AUC_0 − 2) can effectively evaluate the AUC from 0 to 12 h [28, 29]. Considering the challenges associated with sampling during clinical practice, we have chosen to employ three specific time points (0.5, 1, and 2 h) to represent the aforementioned parameter. We found that the levels of four PSP metabolites, including inosine, hypoxanthine, xanthine and guanine were significantly decreased in EG patients 1 h after receiving the MMF compared to LEG patients. MMF was originally designed to inhibit GMP and GTP synthesis. However, GTP synthesis is also coupled to purine de novo synthesis via PRPP availability that is regulated by the rapamycin complex 1 (mTORC1) [30]. Thus, other purines and in particular the PSP metabolites should be suppressed by the presence of MMF. In support of this, previous studies have demonstrated that levels of PSP metabolites levels in serum or plasma elevated in patients with CNS disease [31, 32]. Similarly, UA levels were mildly elevated in NMOSD patients during relapse compared with patients with a good prognosis [33].These findings coupled with our results potentially indicated that selected PSP metabolites might be used to distinguish the therapeutic efficacy of MMF in NMOSD patients.

A key factor for the poor response to MMF therapy in NMOSD patients has been linked to host genetic polymorphisms. For instance, single nucleotide polymorphisms (SNPs) in the genes encoding the MPA metabolizing enzyme UDP-glucuronosyltransferase 1–9 (UGT1A9) or the molecular targets (IMPDH1 and IMPDH2) are linked to a weakened drug responsiveness of individual patients [19, 30, 34]. In addition to SNP differences, the metabolic capacity of gut microbiota also actively participates in the utilization and metabolism of MMF e.g. through β-glucuronidase (GUS) enzymes expressed by gut commensals [35‐37]. We profiled the microbiomes of NMOSD patients that were grouped according to their therapeutic responses to MMF therapy. Out of expectation, significant changes were not found in the microbial richness and diversity in the MMF non-responders compared to responders in this study. This implied a minor impact of the established host microbiome on the therapeutic response to MMF.

Currently, numerous studies have demonstrated that patients with NMOSD undergo substantial alterations in the composition of their gut microbiota following administration of immunotherapy drugs. Cree et al. observed a noteworthy proliferation of Clostridium perfringens in NMOSD patients treated with rituximab, in comparison to a control group [38]. In a separate study, Junli Gong et al. revealed a decrease in the relative abundance of the Streptococcus genus following treatment with immunosuppressants (MMF and AZA), when compared to an untreated group [39]. These findings suggest a potential association between the enrichment of C. perfringens and Streptococcus in NMOSD and the development of the disease. In this study, the abundance of Clostridium and Synergistes had significantly increased for EG patients and corresponded to a significant decline in abundance of the Coprococcus genus in LEG patients. Clostridium in the Firmicutes phylum was related to the AQP4-IgG–associated NMOSD [17, 18]. Moreover, the genus Coprococcus includes species that are strong butyrate producers [40‐42] so that one possible explanation for our results is that they alleviate the syndromes of NMOSD by butyrate-dependent anti-inflammatory effects as well as having a negative effect on IL-17 A expression [43, 44]. A recent study also spotlighted this genus, whose abundance sharply reduced in NMOSD patients in comparison with the health control [45]. Hence, the existing Coprococcus species might be beneficial microbes to patients with NMOSD and ameliorate its symptoms by curtailing the levels of pro-inflammatory cytokines. This is an encouraging finding, and further investigation is needed to identify the mechanism adopted by Coprococcus couple with MMF to suppress the process of NMOSD development.

However, there are several limitations for this study. First, the absence of criteria for assessing the effectiveness of NMOSD treatment may weaken our conclusion. Our analysis based on relapse frequency and EDSS as criteria may introduce inherent bias into our findings. Second, the limited sampling size restricts our capacity to establish comprehensive conclusive remarks. Also, this precluded the consideration of baseline MRI status and general complications.

Future investigations would incorporate a comprehensive categorization of patients’ conditions, which is beneficial to better understand NMOSD.

Conclusions

In this study, altered PSP metabolites and composition of the gut microbiota were observed between NMOSD patients with or without optimal clinical response after MMF treatment. Poor clinical response might be the increased abundance of Clostridium and Synergistes and decreased relative abundances of the genera Coprococcus. Our data might help to understand the pharmacodynamics of MMF in the aspect of the gut-brain axis. Furthermore, in view of the fact that MMF is so widely used in NMOSD, further studies investigating the mechanism of this Coprococcus in NMOSD are needed.

Acknowledgements

We thank Hangzhou Zhongmei Huadong Pharmaceutical for their help with grant support.

Declarations

All procedures performed in studies involving human participants were in accordance with the ethical standards and with the Helsinki declaration. And this study was approved by the ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University ([2020]02-016-01). Written informed consent was obtained from all of patients or their relatives and healthy controls (or their parent or legal guardian in the case of children under 18).

Not applicable.

Competing interests

The authors declare no competing interests.

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Lucchinetti C, Guo Y, Popescu B, Fujihara K, Itoyama Y, Misu T. The pathology of an autoimmune astrocytopathy: lessons learned from neuromyelitis optica. Brain Pathol. 2014;24 1:83–97. https://doi.org/10.1111/bpa.12099.CrossRef

Mader S, Kümpfel T, Meinl E. Novel insights into pathophysiology and therapeutic possibilities reveal further differences between AQP4-IgG- and MOG-IgG-associated Diseases. Curr Opin Neurol. 2020;33 3:362–71. https://doi.org/10.1097/wco.0000000000000813.CrossRef

Bennett JL, Costello F, Chen JJ, Petzold A, Biousse V, Newman NJ, et al. Optic neuritis and autoimmune optic neuropathies: advances in diagnosis and treatment. Lancet Neurol. 2023;22 1:89–100. https://doi.org/10.1016/s1474-4422(22)00187-9.CrossRef

Fu Y, Bi J, Yan Y, Sun X, Li K, Kim SY, et al. Rapid Immunodot AQP4 assay for Neuromyelitis Optica Spectrum Disorder. JAMA Neurol. 2023;80 10:1105–12. https://doi.org/10.1001/jamaneurol.2023.2974.CrossRef

Wingerchuk DM, Banwell B, Bennett JL, Cabre P, Carroll W, Chitnis T, et al. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology. 2015;85(2):177–89. https://doi.org/10.1212/wnl.0000000000001729.CrossRefPubMedPubMedCentral

Huang Q, Wang J, Zhou Y, Yang H, Wang Z, Yan Z, et al. Low-dose mycophenolate mofetil for Treatment of Neuromyelitis Optica Spectrum Disorders: a prospective Multicenter Study in South China. Front Immunol. 2018;9:2066. https://doi.org/10.3389/fimmu.2018.02066.CrossRefPubMedPubMedCentral

Wingerchuk D, Weinshenker B. Neuromyelitis Optica. Curr Treat Options Neurol. 2008;10(1):55–66. https://doi.org/10.1007/s11940-008-0007-z.CrossRefPubMed

Yong HYF, Burton JM. A Clinical Approach to existing and emerging therapeutics in Neuromyelitis Optica Spectrum Disorder. Curr Neurol Neurosci Rep. 2023;23 9:489–506. https://doi.org/10.1007/s11910-023-01287-x.CrossRef

Allison A. Mechanisms of action of mycophenolate mofetil. Lupus. 2005;2–8. https://doi.org/10.1191/0961203305lu2109oa.

10.

Allison AC, Eugui EM. The design and development of an immunosuppressive drug, mycophenolate mofetil. Springer Semin Immunopathol. 1993;14 4:353–80. https://doi.org/10.1007/bf00192309.CrossRef

11.

Moreno Planas J, Cuervas-Mons Martinez V, Rubio Gonzalez E, Gomez Cruz A, Lopez-Monclus J, Sánchez-Turrion V et al. Mycophenolate mofetil can be used as monotherapy late after liver transplantation. American journal of transplantation: official journal of the American Society of Transplantation and the American Society of Transplant Surgeons. 2004;4 10:1650–5; https://doi.org/10.1111/j.1600-6143.2004.00556.x.

12.

Heischmann S, Dzieciatkowska M, Hansen K, Leibfritz D, Christians U. The immunosuppressant mycophenolic acid alters nucleotide and lipid metabolism in an intestinal cell model. Sci Rep. 2017;7:45088. https://doi.org/10.1038/srep45088.CrossRefPubMedPubMedCentral

13.

Montcuquet A, Collongues N, Papeix C, Zephir H, Audoin B, Laplaud D, et al. Effectiveness of mycophenolate mofetil as first-line therapy in AQP4-IgG, MOG-IgG, and seronegative neuromyelitis optica spectrum disorders. Mult Scler. 2017;23 10:1377–84. https://doi.org/10.1177/1352458516678474.CrossRef

14.

Huh SY, Kim SH, Hyun JW, Joung AR, Park MS, Kim BJ, et al. Mycophenolate mofetil in the treatment of neuromyelitis optica spectrum disorder. JAMA Neurol. 2014;71 11:1372–8. https://doi.org/10.1001/jamaneurol.2014.2057.CrossRef

15.

Jacob A, Matiello M, Weinshenker BG, Wingerchuk DM, Lucchinetti C, Shuster E, et al. Treatment of neuromyelitis optica with mycophenolate mofetil: retrospective analysis of 24 patients. Arch Neurol. 2009;66 9:1128–33. https://doi.org/10.1001/archneurol.2009.175.CrossRef

16.

Gong J, Qiu W, Zeng Q, Liu X, Sun X, Li H et al. Lack of short-chain fatty acids and overgrowth of opportunistic pathogens define dysbiosis of neuromyelitis optica spectrum disorders: a Chinese pilot study. Multiple sclerosis (Houndmills, Basingstoke, England). 2019;25 9:1316–25; https://doi.org/10.1177/1352458518790396.

17.

Pandit L, Cox L, Malli C, D’Cunha A, Rooney T, Lokhande H, et al. Clostridium bolteae is elevated in neuromyelitis optica spectrum disorder in India and shares sequence similarity with AQP4. Neurology(R) Neuroimmunol Neuroinflammation. 2021;8(1). https://doi.org/10.1212/nxi.0000000000000907.

18.

Cree B, Spencer C, Varrin-Doyer M, Baranzini S, Zamvil S. Gut microbiome analysis in neuromyelitis optica reveals overabundance of Clostridium perfringens. Ann Neurol. 2016;80 3:443–7. https://doi.org/10.1002/ana.24718.CrossRef

19.

Wingerchuk D, Banwell B, Bennett J, Cabre P, Carroll W, Chitnis T, et al. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology. 2015;85(2):177–89. https://doi.org/10.1212/wnl.0000000000001729.CrossRefPubMedPubMedCentral

20.

Benard-Seguin E, Costello F. Optic neuritis: current challenges in diagnosis and management. Curr Opin Neurol. 2023;36 1:10–8. https://doi.org/10.1097/wco.0000000000001128.CrossRef

21.

Lu JJ, Jia BJ, Yang L, Zhang W, Dong X, Li P, et al. Ultra-high performance liquid chromatography with ultraviolet and tandem mass spectrometry for simultaneous determination of metabolites in purine pathway of rat plasma. J Chromatogr B Analyt Technol Biomed Life Sci. 2016;1036–1037:84–92. https://doi.org/10.1016/j.jchromb.2016.09.023.CrossRefPubMed

22.

Trebst C, Jarius S, Berthele A, Paul F, Schippling S, Wildemann B, et al. Update on the diagnosis and treatment of neuromyelitis optica: recommendations of the Neuromyelitis Optica Study Group (NEMOS). J Neurol. 2014;261(1):1–16. https://doi.org/10.1007/s00415-013-7169-7.CrossRefPubMed

23.

Sellner J, Boggild M, Clanet M, Hintzen RQ, Illes Z, Montalban X, et al. EFNS guidelines on diagnosis and management of neuromyelitis optica. Eur J Neurol. 2010;17 8:1019–32. https://doi.org/10.1111/j.1468-1331.2010.03066.x.CrossRef

24.

Kimbrough DJ, Fujihara K, Jacob A, Lana-Peixoto MA, Leite MI, Levy M, et al. Treatment of Neuromyelitis Optica: review and recommendations. Mult Scler Relat Disord. 2012;1 4:180–7. https://doi.org/10.1016/j.msard.2012.06.002.CrossRef

25.

Wingerchuk DM, Lennon VA, Lucchinetti CF, Pittock SJ, Weinshenker BG. The spectrum of neuromyelitis optica. Lancet Neurol. 2007;6 9:805 – 15; doi: 10.1016/s1474-4422(07)70216-8.

26.

Carnero Contentti E, Correale J. Association between Infections, the microbiome, vaccination, and neuromyelitis optica spectrum disorder. Mult Scler. 2023;29(4–5):492–501. https://doi.org/10.1177/13524585221113272.CrossRefPubMed

27.

Cui C, Ruan Y, Qiu W. Potential role of the gut microbiota in neuromyelitis optica spectrum disorder: implication for intervention. J Clin Neuroscience: Official J Neurosurgical Soc Australasia 2020;82 Pt B:193–9; https://doi.org/10.1016/j.jocn.2020.11.011.

28.

Pawinski T, Durlik M, Szlaska I, Urbanowicz A, Majchrnak J, Gralak B. Comparison of mycophenolic acid pharmacokinetic parameters in kidney transplant patients within the first 3 months post-transplant. J Clin Pharm Ther. 2006;31 1:27–34. https://doi.org/10.1111/j.1365-2710.2006.00713.x.CrossRef

29.

Pillans PI, Rigby RJ, Kubler P, Willis C, Salm P, Tett SE, et al. A retrospective analysis of mycophenolic acid and cyclosporin concentrations with acute rejection in renal transplant recipients. Clin Biochem. 2001;34 1:77–81. https://doi.org/10.1016/s0009-9120(00)00196-x.CrossRef

30.

Emmanuel N, Ragunathan S, Shan Q, Wang F, Giannakou A, Huser N, et al. Purine nucleotide availability regulates mTORC1 activity through the Rheb GTPase. Cell Rep. 2017;19 13:2665–80. https://doi.org/10.1016/j.celrep.2017.05.043.CrossRef

31.

Lazzarino G, Amorini A, Petzold A, Gasperini C, Ruggieri S, Quartuccio M, et al. Serum compounds of Energy Metabolism Impairment are related to disability, Disease Course and Neuroimaging in multiple sclerosis. Mol Neurobiol. 2017;54 9:7520–33. https://doi.org/10.1007/s12035-016-0257-9.CrossRef

32.

Kuračka L, Kalnovičová T, Kucharská J, Turčáni P. Multiple sclerosis: evaluation of purine nucleotide metabolism in central nervous system in association with serum levels of selected fat-soluble antioxidants. Multiple Scler Int. 2014;2014:759808. https://doi.org/10.1155/2014/759808.CrossRef

33.

Shu Y, Li H, Zhang L, Wang Y, Long Y, Li R, et al. Elevated cerebrospinal fluid uric acid during relapse of neuromyelitis optica spectrum disorders. Brain and Behavior. 2017;7(1):e00584. https://doi.org/10.1002/brb3.584.CrossRefPubMed

34.

Wei Y, Wu D, Chen Y, Dong C, Qi J, Wu Y, et al. Population pharmacokinetics of mycophenolate mofetil in pediatric patients early after liver transplantation. Front Pharmacol. 2022;13:1002628. https://doi.org/10.3389/fphar.2022.1002628.CrossRefPubMedPubMedCentral

35.

Taylor M, Flannigan K, Rahim H, Mohamud A, Lewis I, Hirota S, et al. Vancomycin relieves mycophenolate mofetil-induced gastrointestinal toxicity by eliminating gut bacterial β-glucuronidase activity. Sci Adv. 2019;5 8:eaax2358. https://doi.org/10.1126/sciadv.aax2358.CrossRef

36.

Simpson JB, Sekela JJ, Graboski AL, Borlandelli VB, Bivins MM, Barker NK, et al. Metagenomics combined with activity-based proteomics point to gut bacterial enzymes that reactivate mycophenolate. Gut Microbes. 2022;14(1:2107289). https://doi.org/10.1080/19490976.2022.2107289.

37.

Khan MH, Onyeaghala GC, Rashidi A, Holtan SG, Khoruts A, Israni A, et al. Fecal β-glucuronidase activity differs between hematopoietic cell and kidney transplantation and a possible mechanism for disparate dose requirements. Gut Microbes. 2022;14(1:2108279). https://doi.org/10.1080/19490976.2022.2108279.

38.

Cree BA, Spencer CM, Varrin-Doyer M, Baranzini SE, Zamvil SS. Gut microbiome analysis in neuromyelitis optica reveals overabundance of Clostridium perfringens. Ann Neurol. 2016;80 3:443–7. https://doi.org/10.1002/ana.24718.CrossRef

39.

Gong J, Qiu W, Zeng Q, Liu X, Sun X, Li H, et al. Lack of short-chain fatty acids and overgrowth of opportunistic pathogens define dysbiosis of neuromyelitis optica spectrum disorders: a Chinese pilot study. Mult Scler. 2019;25 9:1316–25. https://doi.org/10.1177/1352458518790396.CrossRef

40.

Liu C, Du P, Cheng Y, Guo Y, Hu B, Yao W, et al. Study on fecal fermentation characteristics of aloe polysaccharides in vitro and their predictive modeling. Carbohydr Polym. 2021;256:117571. https://doi.org/10.1016/j.carbpol.2020.117571.CrossRefPubMed

41.

Maier L, Pruteanu M, Kuhn M, Zeller G, Telzerow A, Anderson EE, et al. Extensive impact of non-antibiotic Drugs on human gut bacteria. Nature. 2018;555 7698:623–8. https://doi.org/10.1038/nature25979.CrossRef

42.

Nikolova VL, Smith MRB, Hall LJ, Cleare AJ, Stone JM, Young AH. Perturbations in Gut Microbiota Composition in Psychiatric disorders: a review and Meta-analysis. JAMA Psychiatry. 2021;78 12:1343–54. https://doi.org/10.1001/jamapsychiatry.2021.2573.CrossRef

43.

Huang S, Mao J, Zhou L, Xiong X, Deng Y. The imbalance of gut microbiota and its correlation with plasma inflammatory cytokines in pemphigus vulgaris patients. Scand J Immunol. 2019;90 3:e12799. https://doi.org/10.1111/sji.12799.CrossRef

44.

Yeh N, Hsu C, Tsai T, Chiu H. Gut Microbiome in Psoriasis is perturbed differently during secukinumab and Ustekinumab Therapy and Associated with response to treatment. Clin Drug Investig. 2019;39 12:1195–203. https://doi.org/10.1007/s40261-019-00849-7.CrossRef

45.

Shi Z, Qiu Y, Wang J, Fang Y, Zhang Y, Chen H, et al. Dysbiosis of gut microbiota in patients with neuromyelitis optica spectrum disorders: a cross sectional study. J Neuroimmunol. 2020;339:577126. https://doi.org/10.1016/j.jneuroim.2019.577126.CrossRefPubMed

Titel: Integrative analysis of purine metabolites and gut microbiota in patients with neuromyelitis optica spectrum disorders after mycophenolate mofetil treatment
verfasst von: Gong Li
Xiaoyu Ma
Lijuan Xia
Ran Wei
Xiran Wang
Cang Li
Yuge Wang
Limin He
Hao Ren
Jian Sun
Wei Qiu
Publikationsdatum: 01.12.2023
Verlag: BioMed Central
Erschienen in: BMC Neurology / Ausgabe 1/2023
Elektronische ISSN: 1471-2377
DOI: https://doi.org/10.1186/s12883-023-03500-3

Neu in den Fachgebieten Neurologie und Psychiatrie

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Springer Medizin

Integrative analysis of purine metabolites and gut microbiota in patients with neuromyelitis optica spectrum disorders after mycophenolate mofetil treatment