Gut microbiome alterations in Alzheimer’s disease

Scientific Reports - Tập 7 Số 1
N. Vogt1, Robert L. Kerby2, Kimberly A. Dill‐McFarland2, Sandra Harding1, Andrew P. Merluzzi1, Sterling C. Johnson1, Cynthia M. Carlsson1, Sanjay Asthana3, Henrik Zetterberg4, Kaj Blennow4, Barbara B. Bendlin5, Federico E. Rey2
1Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue J5/1 Mezzanine, Madison, WI 53792, USA
2Department of Bacteriology, University of Wisconsin-Madison, 1550 Linden Drive, Madison, WI 53706, USA
3Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
4Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
5Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, WARF Building, 610 Walnut Street, 9th Floor, Suite 957, Madison, WI 53726, USA

Tóm tắt

AbstractAlzheimer’s disease (AD) is the most common form of dementia. However, the etiopathogenesis of this devastating disease is not fully understood. Recent studies in rodents suggest that alterations in the gut microbiome may contribute to amyloid deposition, yet the microbial communities associated with AD have not been characterized in humans. Towards this end, we characterized the bacterial taxonomic composition of fecal samples from participants with and without a diagnosis of dementia due to AD. Our analyses revealed that the gut microbiome of AD participants has decreased microbial diversity and is compositionally distinct from control age- and sex-matched individuals. We identified phylum- through genus-wide differences in bacterial abundance including decreased Firmicutes, increased Bacteroidetes, and decreased Bifidobacterium in the microbiome of AD participants. Furthermore, we observed correlations between levels of differentially abundant genera and cerebrospinal fluid (CSF) biomarkers of AD. These findings add AD to the growing list of diseases associated with gut microbial alterations, as well as suggest that gut bacterial communities may be a target for therapeutic intervention.

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Tài liệu tham khảo

Selkoe, D. J. & Hardy, J. The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Mol. Med. 8, 595–608 (2016).

Hill, J. M. et al. Pathogenic microbes, the microbiome, and Alzheimer’s disease (AD). Front. Aging. Neurosci. 6, 1–5 (2014).

Zhao, Y., Dua, P. & Lukiw, W. J. Microbial sources of amyloid and relevance to amyloidogenesis and Alzheimer’s disease (AD). J. Alzheimers Dis. Parkinsonism 5, 177 (2015).

Bhattacharjee, S. & Lukiw, W. J. Alzheimer’s disease and the microbiome. Front. Cell. Neurosci. 7, 1–4 (2013).

Ghaisas, S., Maher, J. & Kanthasamy, A. Gut microbiome in health and disease: Linking the microbiome-gut-brain axis and environmental factors in the pathogenesis of systemic and neurodegenerative diseases. Pharmacol. Ther. 158, 52–62 (2016).

Chow, J., Lee, S. M., Shen, Y., Khosravi, A. & Mazmanian, S. K. Host-bacterial symbiosis in health and disease. Adv. Immunol. 107, 243–274 (2010).

Koenig, J. E. et al. Succession of microbial consortia in the developing infant gut microbiome. Proc. Natl. Acad. Sci. USA 108(Suppl 1), 4578–4585 (2011).

Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

Claesson, M. J. et al. Composition, variability, and temporal stability of the intestinal microbiota of the elderly. Proc. Natl. Acad. Sci. USA 108(Suppl 1), 4586–4591 (2011).

Clemente, J. C., Ursell, L. K., Parfrey, L. W. & Knight, R. The impact of the gut microbiota on human health: an integrative view. Cell 148, 1258–1270 (2012).

Fung, T. C., Olson, C. A. & Hsiao, E. Y. Interactions between the microbiota, immune and nervous systems in health and disease. Nat. Neurosci. 20, 145–155 (2017).

Scheperjans, F. et al. Gut microbiota are related to Parkinson’s disease and clinical phenotype. Mov. Disord. 30, 350–358 (2015).

Keshavarzian, A. et al. Colonic bacterial composition in Parkinson’s disease. Mov. Disord. 30, 1351–1360 (2015).

Cattaneo, A. et al. Association of brain amyloidosis with pro-inflammatory gut bacterial taxa and peripheral inflammation markers in cognitively impaired elderly. Neurobiol. Aging 49, 60–68 (2017).

Minter, M. R. et al. Antibiotic-induced perturbations in gut microbial diversity influences neuro-inflammation and amyloidosis in a murine model of Alzheimer’s disease. Sci. Rep. 6, 1–12 (2016).

Harach, T. et al. Reduction of Abeta amyloid pathology in APPPS1 transgenic mice in the absence of gut microbiota. Sci. Rep. 7, 41802 (2017).

Morris, M. C. et al. MIND diet associated with reduced incidence of Alzheimer’s disease. Alzheimers Dement. 11, 1007–1014 (2015).

Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821 (2013).

Blennow, K. & Zetterberg, H. The past and the future of Alzheimer’s disease CSFbiomarkers - a journey toward validated biochemical tests covering the whole spectrum of molecular events. Front. Neurosci. 9, 1–8 (2015).

Hellwig, K. et al. Neurogranin and YKL-40: independent markers of synaptic degeneration and neuroinflammation in Alzheimer’s disease. Alz. Res. Therapy 7, 74 (2015).

Craig-Schapiro, R. et al. YKL-40: a novel prognostic fluid biomarker for preclinical Alzheimer’s disease. Biol. Psychiatry 68, 903–912 (2010).

Rosén, C. et al. Increased Levels of Chitotriosidase and YKL-40 in Cerebrospinal Fluid from Patients with Alzheimer’s disease. Dement. Geriatr. Cogn. Dis. Extra 4, 297–304 (2014).

Pistollato, F. et al. Role of gut microbiota and nutrients in amyloid formation and pathogenesis of Alzheimer disease. Nutr. Rev. 74, 624–634 (2016).

Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).

Larsen, N. et al. Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS ONE 5, 1–10 (2010).

Dicksved, J. et al. Molecular analysis of the gut microbiota of identical twins with Crohn’s disease. ISME J. 2, 716–727 (2008).

DuPont, A. W. & DuPont, H. L. The intestinal microbiota and chronic disorders of the gut. Nat. Rev. Gastroenterol. Hepatol. 8, 523–531 (2011).

Cryan, J. F. & Dinan, T. G. Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat. Rev. Neurosci. 13, 701–712 (2012).

Schwiertz, A. et al. Microbiota and SCFA in lean and overweight healthy subjects. Obesity 18, 190–195 (2009).

Ley, R. E. et al. Obesity alters gut microbial ecology. Proc. Natl. Acad. Sci. USA 102, 11070–11075 (2005).

Rawlings, A. M. et al. Diabetes in midlife and cognitive change over 20 years: a cohort study. Ann. Intern. Med. 161, 785–793 (2014).

Ott, A. et al. Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology 53, 1937–1942 (1999).

la Monte de, S. M. & Wands, J. R. Review of insulin and insulin-like growth factor expression, signaling, and malfunction in the central nervous system: relevance to Alzheimer’s disease. J. Alzheimers Dis. 7, 45–61 (2005).

Willette, A. A. et al. Association of insulin resistance with cerebral glucose uptake in late middle-aged adults at risk for Alzheimer disease. JAMA Neurol. 72, 1013–1020 (2015).

Willette, A. A. et al. Insulin resistance predicts brain amyloid deposition in late middle-aged adults. Alzheimers Dement. 11, 504–510 (2015).

Rajilić-Stojanović, M. & de Vos, W. M. The first 1000 cultured species of the human gastrointestinal microbiota. FEMS Microbiol. Rev. 38, 996–1047 (2014).

Cani, P. D. et al. Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes 56, 1761–1772 (2007).

Asti, A. & Gioglio, L. Can a bacterial endotoxin be a key factor in the kinetics of amyloid fibril formation? J. Alzheimers Dis. 39, 169–179 (2014).

Sheng, J. G. et al. Lipopolysaccharide-induced-neuroinflammation increases intracellular accumulation of amyloid precursor protein and amyloid beta peptide in APPswe transgenic mice. Neurobiol. Dis. 14, 133–145 (2003).

Kahn, M. S. et al. Prolonged elevation in hippocampal Aβ and cognitive deficits following repeated endotoxin exposure in the mouse. Behav. Brain. Res. 229, 176–184 (2012).

Kitazawa, M., Oddo, S., Yamasaki, T. R., Green, K. N. & LaFerla, F. M. Lipopolysaccharide-induced inflammation exacerbates tau pathology by a cyclin-dependent kinase 5-mediated pathway in a transgenic model of Alzheimer’s disease. J. Neurosci. 25, 8843–8853 (2005).

Sy, M. et al. Inflammation induced by infection potentiates tau pathological features in transgenic mice. Am. J. Pathol. 178, 2811–2822 (2011).

Man, A. L. et al. Age-associated modifications of intestinal permeability and innate immunity in human small intestine. Clin. Sci. 129, 515–527 (2015).

Stehle, J. R. et al. Lipopolysaccharide-binding protein, a surrogate marker of microbial translocation, is associated with physical function in healthy older adults. J. Gerontol. Ser. A-Biol. Sci. Med. Sci. 67, 1212–1218 (2012).

Zhan, X. et al. Gram-negative bacterial molecules associate with Alzheimer disease pathology. Neurology 87, 2324–2332 (2016).

O’Callaghan, A. & van Sinderen, D. Bifidobacteria and their role as members of the human gut microbiota. Front. Microbiol. 7, 1–23 (2016).

Arboleya, S., Watkins, C., Stanton, C. & Ross, R. P. Gut bifidobacteria populations in human health and aging. Front. Microbiol. 7, 1–9 (2016).

Underwood, M. A., German, J. B., Lebrilla, C. B. & Mills, D. A. Bifidobacterium longum subspecies infantis: champion colonizer of the infant gut. Pediatr. Res. 77, 229–235 (2015).

Wang, Z. et al. The role of bifidobacteria in gut barrier function after thermal injury in rats. J. Trauma 61, 650–657 (2006).

Griffiths, E. A. et al. In vivo effects of bifidobacteria and lactoferrin on gut endotoxin concentration and mucosal immunity in Balb/c mice. Dig. Dis. Sci. 49, 579–589 (2004).

Romond, M.-B. et al. Does the intestinal bifidobacterial colonisation affect bacterial translocation? Anaerobe 14, 43–48 (2008).

Akbari, E. et al. Effect of probiotic supplementation on cognitive function and metabolic status in Alzheimer’s disease: a randomized, double-blind and controlled trial. Front. Aging. Neurosci. 8, 1–8 (2016).

Shen, L., Liu, L. & Ji, H.-F. Alzheimer’s disease histological and behavioral manifestations in transgenic mice correlate with specific gut microbiome state. J. Alzheimers Dis. 56, 385–390 (2017).

Nguyen, T. L. A., Vieira-Silva, S., Liston, A. & Raes, J. How informative is the mouse for human gut microbiota research? Dis. Model. Mech. 8, 1–16 (2015).

Hansen, R. A. et al. Efficacy and safety of donepezil, galantamine, and rivastigmine for the treatment of Alzheimer’s disease: a systematic review and meta-analysis. Clin. Interv. Aging 3, 211–225 (2008).

Sager, M. A., Hermann, B. & La Rue, A. Middle-aged children of persons with Alzheimer’s disease: APOE genotypes and cognitive function in the Wisconsin Registry for Alzheimer’s Prevention. J. Geriatr. Psychiatry Neurol. 18, 245–249 (2005).

Johnson, S. C. et al. The effect of TOMM40 poly-T length on gray matter volume and cognition in middle-aged persons with APOE ε3/ε3 genotype. Alzheimers Dement. 7, 456–465 (2011).

McKhann, G. M. et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7, 263–269 (2011).

Lewis, S. J. & Heaton, K. W. Stool form scale as a useful guide to intestinal transit time. Scand. J. Gastroenterol. 32, 920–924 (1997).

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 (2013).

Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009).

Westcott, S. L. & Schloss, P. D. OptiClust, an improved method for assigning amplicon-based sequence data to operational taxonomic units. mSphere 2, 1–11 (2017).

Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59 (2013).

Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq. 2. Genome Biol. 15, 31–21 (2014).

McMurdie, P. J. & Holmes, S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, 1–12 (2014).

White, J. R., Nagarajan, N. & Pop, M. Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Comput. Biol. 5, 1–11 (2009).

Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12(R60), 1–18 (2011).

Lewczuk, P., Lelental, N., Spitzer, P., Maler, J. M. & Kornhuber, J. Amyloid-β 42/40 cerebrospinal fluid concentration ratio in the diagnostics of Alzheimer’s disease: validation of two novel assays. J. Alzheimers Dis. 43, 183–191 (2015).

Racine, A. M. et al. Associations between performance on an abbreviated CogState battery, other measures of cognitive function, and biomarkers in people at risk for Alzheimer’s sisease. J. Alzheimers Dis. 54, 1395–1408 (2016).

Racine, A. M. et al. Association of longitudinal white matter degeneration and cerebrospinal fluid biomarkers of neurodegeneration, inflammation and Alzheimer’s disease in late-middle-aged adults. Brain Imaging Behav. 59, 306 (2017).

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Scientific Reports

Tập 7 Số 1

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