Sodium oligomannate therapeutically remodels gut microbiota and suppresses gut bacterial amino acids-shaped neuroinflammation to inhibit Alzheimer's disease progression
Authors: Changrong Ge
Chen Du
Wen Lian
Shuaishuai Chang
Haiyan Zhang
Huan Wang
Tao Wang
Jia Liu
Guangqiang Sun
Meiyu Geng
Jian Ding
Zuoquan Xie
Feifei Lin
Yanxue Gong
Dabing Yang
Shifu Xiao
Teng Feng
Xinyi Wang
Xun Huang
Guanqun Zhang
Jing Zhang
Lingfei Ruan
Qingli Zhang
Jun Yang
Xingkun Chu
Siyuan Yan
Journal: Cell research (2019)
Discipline: MOLECULAR BIOLOGY & GENETICS
Keywords: gut dysbiosis; Alzheimer's disease; neuroinflammation; microbiota composition; phenylalanine
Affiliations: Shanghai Green Valley Pharmaceutical Co., Ltd, Shanghai, 201203, China., State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China., Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, 200025, China., Institutional Technology Service Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China., State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China. .

Abstract:  Recently, increasing evidence has suggested the association between gut dysbiosis and Alzheimer's disease (AD) progression, yet the role of gut microbiota in AD pathogenesis remains obscure. Herein, we provide a potential mechanistic link between gut microbiota dysbiosis and neuroinflammation in AD progression. Using AD mouse models, we discovered that, during AD progression, the alteration of gut microbiota composition leads to the peripheral accumulation of phenylalanine and isoleucine, which stimulates the differentiation and proliferation of pro-inflammatory T helper 1 (Th1) cells. The brain-infiltrated peripheral Th1 immune cells are associated with the M1 microglia activation, contributing to AD-associated neuroinflammation. Importantly, the elevation of phenylalanine and isoleucine concentrations and the increase of Th1 cell frequency in the blood were also observed in two small independent cohorts of patients with mild cognitive impairment (MCI) due to AD. Furthermore, GV-971, a sodium oligomannate that has demonstrated solid and consistent cognition improvement in a phase 3 clinical trial in China, suppresses gut dysbiosis and the associated phenylalanine/isoleucine accumulation, harnesses neuroinflammation and reverses the cognition impairment. Together, our findings highlight the role of gut dysbiosis-promoted neuroinflammation in AD progression and suggest a novel strategy for AD therapy by remodelling the gut microbiota. 

Retracted: No

PubPeer comments:
 Within Supplemental Figure 1, there appears to be image duplication between panel (A) 7M and panel (h) 7M . I would appreciate pubpeer readers comments on this. The red boxes circling the 7M image of panels (a) and (h) are mine, and provided to clearly indicate to the reader which images appear duplicated. ![file] ![file] I ve also included the legends for reader convenience respective for each panel. , 
 #1 I did a comparison of the 2 7M images and they do look like highly likely from the same image slide. I read their IHC section in Methods. They didn t say that they did staining for anti-Au03b242 and anti-IBA1 on neighboring sections. Could the authors help clarify the methods here? ![file] , 
 #1 Obviously, those staining results of Iba1 is not correct. If you have been studying microglia, you would know that the activated microglia is like ameboid. Here is a correct example of Iba1 staining in an Alzheimeru2019s disease model of another Nature paper https: www.nature.com articles s41467-019-09118-9 figures 1 ![file] , 
 So this paper is talking about neuroinflammation in Alzheimeru2019s disease, but the authors even don t know the correct morphology of activated microglia. And in fact, IHC or IF of Iba1 staining is very easy in activated microglia. , 
 The tables below are Supplemental Tables 1 and 3. My area of expertise is not statistics. Is it normal that the corrected p-value can 1) be so frequently the same between so many measures and 2) can the corrected p-value be the same value up to 6 decimal places between two different uncorrected p-values? (what I mean by the last question, if itu2019s not clear, please see the red arrows for one example where the corrected p-value is 0.003063 for the uncorrected p-values of 0.000795 and 0.00146) ![file] ![file] , 
 I think this is common for BH adjustment. I have many such values in my publication https: peerj.com articles cs-67 ![file] , 
 Figure 2 b vs Figure 2 e: why are Th1 frequency values in Tg group so different? in 2b, Tg + - antibiotics. In 2e, Tg, WT, co-house. So the Tg group should be similar in both experiments. You say that 5.5% (Tg) vs 3.8% (Tg + antibiotics) is significantly different, but how come the Tg in B is 5.5% vs Tg in E is about 12% (value estimated from figure)? If you run statistics, you will conclude that your Tg groups in both experiments are significantly different (p 0.0001). But they are supposed to be same, correct? So if you repeat your experiment on different days, and got such big difference with your control groups, how do you trust the comparison with other groups? ![file] , 
 I don t think it an important problem, may be they are simple variations around normal range, just like ranges in well-known serum biochemical biomarkers: ![file] The question is what s the normal range of Th1 cells in those mice, if there is no common knowledge, then I think it s totally acceptable in this paper. , 
 #2 Actually when I look at those two pictures in much greater detail, they are not exactly the same images. Some fluorescent points are not in the same place. Thus those 2 images may be selected from serial sections, instead of duplicate images. Better for the journal to clarify these problems. ,