Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease
Open accessAbstract
Increasing evidence suggests Alzheimer's disease (AD) pathophysiology is influenced by primary and secondary bile acids, the end product of cholesterol metabolism. We analyze 2,114 post-mortem brain transcriptomes and identify genes in the alternative bile acid synthesis pathway to be expressed in the brain. A targeted metabolomic analysis of primary and secondary bile acids measured from post-mortem brain samples of 111 individuals supports these results. Our metabolic network analysis suggests that taurine transport, bile acid synthesis, and cholesterol metabolism differ in AD and cognitively normal individuals. We also identify putative transcription factors regulating metabolic genes and influencing altered metabolism in AD. Intriguingly, some bile acids measured in brain tissue cannot be explained by the presence of enzymes responsible for their synthesis, suggesting that they may originate from the gut microbiome and are transported to the brain. These findings motivate further research into bile acid metabolism in AD to elucidate their possible connection to cognitive decline.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Studies in AD patients report a consistent pattern of reduced levels of primary bile acids and elevated levels of secondary bile acids.
“Although studies in AD patients have yielded slightly heterogeneous results in BA composition, they have reported a consistent pattern of reduced levels of primary BAs and elevated levels of secondary BAs.”
From Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases (2024) · cites this paper as [355]
Secondary bile acids associated with AD and cognitive impairments include DCA, LCA, glycodeoxycholic acid, taurodeoxycholic acid, glycolithocholic acid, and taurolithocholic acid.
“Secondary BAs associated with AD and cognitive impairments include DCA, LCA, glycodeoxycholic acid, taurodeoxycholic acid, glycolithocholic acid, and taurolithocholic acid.355–358”
From Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases (2024) · cites this paper as [355]
BA receptors are present in the brain, and BAs can be synthesized locally or actively transported across the BBB by BA transporters from circulation.
“BA receptors are present in the brain, and BAs can either be synthesized locally or actively transported across the BBB by BA transporters from circulation (297, 301, 302).”
From Signalling cognition: The gut microbiota and hypothalamic-pituitary-adrenal axis (2023) · cites this paper as [302]
Altered bile acid profiles are observed in several neuropathologies associated with cognitive decline, such as Alzheimer's disease.
“Altered BA profiles have been observed in several neuropathologies associated with cognitive decline, such as Alzheimer’s disease (302, 324).”
From Signalling cognition: The gut microbiota and hypothalamic-pituitary-adrenal axis (2023) · cites this paper as [302]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works
Tissue-based map of the human proteome
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286 · see citing works
SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver
Horton, J. D., Goldstein, J. L., & Brown, M. S. (2002) · Journal of Clinical Investigation · doi:10.1172/jci15593 · Cited by 4,285 · see citing works
SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver
Horton, J. D., Goldstein, J. L., & Brown, M. S. (2002) · Journal of Clinical Investigation · doi:10.1172/jci0215593 · Cited by 4,092 · see citing works
The blood-brain barrier: Bottleneck in brain drug development
Pardridge, W. M. (2005) · NeuroRX · doi:10.1602/neurorx.2.1.3 · Cited by 2,798 · see citing works
Single-cell transcriptomic analysis of Alzheimer’s disease
Mathys, H., Davila-Velderrain, J., Peng, Z., Gao, F., Mohammadi, S., Young, J. Z., Menon, M., He, L., Abdurrob, F., Jiang, X., et al. (2019) · Nature · doi:10.1038/s41586-019-1195-2 · Cited by 2,568 · see citing works
The Enzymes, Regulation, and Genetics of Bile Acid Synthesis
Russell, D. W. (2003) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.72.121801.161712 · Cited by 2,069 · see citing works
Bile Acid Metabolism and Signaling
Chiang, J. Y. L. (2013) · Comprehensive physiology · doi:10.1002/cphy.c120023 · Cited by 1,390 · see citing works
Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A., Haraldsdóttir, H. S., Wachowiak, J., Keating, S., Vlasov, V., et al. (2019) · Nature Protocols · doi:10.1038/s41596-018-0098-2 · Cited by 1,253 · see citing works
Self-citationHallmarks of Brain Aging: Adaptive and Pathological Modification by Metabolic States
Mattson, M. P., & Arumugam, T. V. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.05.011 · Cited by 1,242 · see citing works
Consequences of bile salt biotransformations by intestinal bacteria
Ridlon, J. M., Harris, S. C., Bhowmik, S., Kang, D.-J., & Hylemon, P. B. (2016) · Gut Microbes · doi:10.1080/19490976.2015.1127483 · Cited by 1,097 · see citing works
Linking lipids to Alzheimer's disease: cholesterol and beyond
Di Paolo, G., & Kim, T.-W. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3012 · Cited by 972 · see citing works
The Gut Microbiota and Alzheimer’s Disease
Jiang, C., Li, G., Huang, P., Liu, Z., & Zhao, B. (2017) · Journal of Alzheimer's Disease · doi:10.3233/jad-161141 · Cited by 852 · see citing works
Brain-Gut-Microbiota Axis in Alzheimer’s Disease
Kowalski, K., & Mulak, A. (2019) · Journal of Neurogastroenterology and Motility · doi:10.5056/jnm18087 · Cited by 826 · see citing works
Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota
Magnúsdóttir, S., Heinken, A., Kutt, L., Ravcheev, D. A., Bauer, E., Noronha, A., Greenhalgh, K., Jäger, C., Baginska, J., Wilmes, P., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3703 · Cited by 798 · see citing works
Self-citationRecon3D enables a three-dimensional view of gene variation in human metabolism
Brunk, E., Sahoo, S., Zielinski, D. C., Altunkaya, A., Dräger, A., Mih, N., Gatto, F., Nilsson, A., Preciat, G., Aurich, M. K., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4072 · Cited by 755 · see citing works
Self-citationMahmoudianDehkordi, S., Arnold, M., Nho, K., Ahmad, S., Jia, W., Xie, G., Louie, G., Kueider‐Paisley, A., Moseley, M. A., Thompson, J. W., et al. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.07.217 · Cited by 706 · see citing works
Self-citationA multi-omic atlas of the human frontal cortex for aging and Alzheimer’s disease research
De Jager, P. L., Ma, Y., McCabe, C., Xu, J., Vardarajan, B. N., Felsky, D., Klein, H.-U., White, C. C., Peters, M. A., Lodgson, B., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.142 · Cited by 598 · see citing works
Self-citationEndocrine functions of bile acids
Houten, S. M., 渡辺, 光., & Auwerx, J. H. (2006) · The EMBO Journal · doi:10.1038/sj.emboj.7601049 · Cited by 583 · see citing works
The gut microbiome in human neurological disease: A review
Tremlett, H., Bauer, K. C., Appel‐Cresswell, S., Finlay, B. B., & Waubant, E. (2017) · Annals of Neurology · doi:10.1002/ana.24901 · Cited by 535 · see citing works
Ghaisas, S., Maher, J. M., & Kanthasamy, A. G. (2015) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2015.11.012 · Cited by 519 · see citing works
Wang, M., Beckmann, N. D., Roussos, P., Wang, E., Zhou, X., Wang, Q., Ming, C., Neff, R., Ma, W., Fullard, J. F., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.185 · Cited by 502 · see citing works
Self-citationTransport of Glutamate and Other Amino Acids at the Blood-Brain Barrier
Smith, Q. R. (2000) · Journal of Nutrition · doi:10.1093/jn/130.4.1016s · Cited by 381 · see citing works
F-Seq: a feature density estimator for high-throughput sequence tags
Boyle, A. P., Guinney, J., Crawford, G. E., & Furey, T. S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn480 · Cited by 363 · see citing works
Computationally efficient flux variability analysis
Guðmundsson, S., & Thiele, I. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-489 · Cited by 360 · see citing works
Self-citationiMAT: an integrative metabolic analysis tool
Zur, H., Ruppin, E., & Shlomi, T. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq602 · Cited by 357 · see citing works
Nho, K., Kueider‐Paisley, A., MahmoudianDehkordi, S., Arnold, M., Risacher, S. L., Louie, G., Blach, C., Baillie, R., Han, X., Kastenmüller, G., et al. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.08.012 · Cited by 343 · see citing works
Self-citationMetabolic Dysfunction in Alzheimers Disease and Related Neurodegenerative Disorders
Cai, H., Cong, W., Ji, S., Rothman, S. M., Maudsley, S. R., & Martin, B. (2012) · Current Alzheimer Research · doi:10.2174/156720512799015064 · Cited by 308 · see citing works
Braissant, O., McLin, V. A., & Cudalbu, C. (2012) · Journal of Inherited Metabolic Disease · doi:10.1007/s10545-012-9546-2 · Cited by 288 · see citing works
Bile acid signaling pathways from the enterohepatic circulation to the central nervous system
Mertens, K. L., Kalsbeek, A., Soeters, M. R., & Eggink, H. M. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00617 · Cited by 287 · see citing works
Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE
Wang, Y., Eddy, J. A., & Price, N. D. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-153 · Cited by 277 · see citing works
Self-citationLarge-scale in silico modeling of metabolic interactions between cell types in the human brain
Lewis, N. E., Schramm, G., Bordbar, A., Schellenberger, J., Andersen, M. P., Cheng, J. K., Patel, N., Yee, A., Lewis, R. A., Eils, R., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1711 · Cited by 261 · see citing works
Quinn, M., McMillin, M., Galindo, C., Frampton, G., Pae, H. Y., & DeMorrow, S. (2014) · Digestive and Liver Disease · doi:10.1016/j.dld.2014.01.159 · Cited by 259 · see citing works
The microbiome modulating activity of bile acids
Tian, Y., Gui, W., Koo, I., Smith, P. B. W., Allman, E. L., Nichols, R. G., Rimal, B., Cai, J., Liu, Q., & Patterson, A. D. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1732268 · Cited by 251 · see citing works
Loss of astrocyte cholesterol synthesis disrupts neuronal function and alters whole-body metabolism
Ferris, H. A., Perry, R. J., Moreira, G. V., Shulman, G. I., Horton, J. D., & Kahn, C. R. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620506114 · Cited by 246 · see citing works
Cholesterol metabolism and transport in the pathogenesis of Alzheimer’s disease
Martins, I., Berger, T. R., Sharman, M., Verdile, G., Fuller, S., & Martins, R. (2009) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2009.06408.x · Cited by 237 · see citing works
Faster and More Accurate Sequence Alignment with SNAPPreprint
Zaharia, M., Bolosky, W. J., Curtis, K., Fox, A., Patterson, D. A., Shenker, S. J., Stoica, I. G., Karp, R. M., & Sittler, T. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1111.5572 · Cited by 219 · see citing works
Shah, S. A., Yoon, G. H., Chung, S. S., Abid, M. N., Kim, T. H., Lee, H. Y., & Kim, M. O. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.23 · Cited by 206 · see citing works
Alterations in metabolic pathways and networks in Alzheimer’s disease
Kaddurah‐Daouk, R., Zhu, H., Sharma, S., Bogdanov, M. B., Rozen, S., Matson, W. R., Oki, N. O., Motsinger‐Reif, A. A., Churchill, E., Lei, Z., et al. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.18 · Cited by 205 · see citing works
Self-citationConvergent genetic and expression data implicate immunity in Alzheimer's disease
International Genomics of Alzheimer's Disease Consortium (IGAP), Jones, L., Lambert, J., Wang, L., Choi, S., Harold, D., Vedernikov, A., Escott‐Price, V., Stone, T., Richards, A., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.05.1757 · Cited by 199 · see citing works
Self-citationPiper, J., Elze, M. C., Cauchy, P., Cockerill, P. N., Bonifer, C., & Ott, S. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt850 · Cited by 194 · see citing works
Effects of bile acids on neurological function and disease
McMillin, M., & DeMorrow, S. (2016) · The FASEB Journal · doi:10.1096/fj.201600275r · Cited by 192 · see citing works
Apolipoprotein E metabolism and functions in brain and its role in Alzheimer's disease
Liao, F., Yoon, H., & Kim, J. (2017) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000383 · Cited by 191 · cited 1× · see citing works
“pathway activation increases ABCA1 levels, which in turn led to APOE lipidation and amyloid b clearance.(43) We also identified the transport of taurine as an important factor from themetabolic analysis.”
BackgroundAmino acid catabolism in Alzheimer’s disease brain: Friend or foe?
Griffin, J. W. D., & Bradshaw, P. C. (2017) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2017/5472792 · Cited by 185 · see citing works
Alteration of bile acid metabolism in the rat induced by chronic ethanol consumption
Xie, G., Zhong, W., Li, H., Li, Q., Qiu, Y.-P., Zheng, X.-J., Chen, H., Zhao, X., Zhang, S., Zhou, Z.-X., et al. (2013) · The FASEB Journal · doi:10.1096/fj.13-231860 · Cited by 182 · see citing works
Self-citationRecent advances in understanding bile acid homeostasis
Chiang, J. Y. L. (2017) · F1000Research · doi:10.12688/f1000research.12449.1 · Cited by 182 · see citing works
Bile acids: analysis in biological fluids and tissues
Griffiths, W. J., & Sjövall, J. (2009) · Journal of Lipid Research · doi:10.1194/jlr.r001941-jlr200 · Cited by 178 · see citing works
Self-citationKondo, S., Saito, A., Hino, S., Murakami, T., Ogata, M., Kanemoto, S., Nara, S., Yamashita, A., Yoshinaga, K., Hara, H., et al. (2006) · Molecular and Cellular Biology · doi:10.1128/mcb.01552-06 · Cited by 172 · see citing works
Retinoic Acid Actions through Mammalian Nuclear Receptors
Huang, P., Chandra, V., & Rastinejad, F. (2013) · Chemical Reviews · doi:10.1021/cr400161b · Cited by 167 · see citing works
Profiling of Serum Bile Acids in a Healthy Chinese Population Using UPLC–MS/MS
Xie, G., Wang, Y., Wang, X., Zhao, A., Chen, T., Ni, Y., Wong, L. L., Zhang, H., Zhang, J., Liu, C., et al. (2015) · Journal of Proteome Research · doi:10.1021/pr500920q · Cited by 162 · see citing works
Self-citationMarksteiner, J., Blasko, I., Kemmler, G., Koal, T., & Humpel, C. (2017) · Metabolomics · doi:10.1007/s11306-017-1297-5 · Cited by 158 · see citing works
Fatty Acid Transport Through the Blood‐Brain Barrier
Spector, R. (1988) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1988.tb02958.x · Cited by 155 · see citing works
Metabolomic Profiling of Bile Acids in Clinical and Experimental Samples of Alzheimer’s Disease
Pan, X., Elliott, C. T., McGuinness, B., Passmore, P., Kehoe, P. G., Hölscher, C., McClean, P. L., Graham, S. F., & Green, B. D. (2017) · Metabolites · doi:10.3390/metabo7020028 · Cited by 153 · see citing works
Bile acids: analysis in biological fluids and tissues
Griffiths, W. J., & Sjövall, J. (2009) · Journal of Lipid Research · doi:10.1194/jlr.r001941 · Cited by 152 · see citing works
Self-citationCorbett, G. T., Gonzalez, F. J., & Pahan, K. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1504890112 · Cited by 151 · see citing works
Conserved brain myelination networks are altered in Alzheimer’s and other neurodegenerative diseases
Allen, M., Wang, X., Burgess, J. D., Watzlawik, J., Serie, D. J., Younkin, C. S., Nguyen, T., Malphrus, K. G., Lincoln, S., Carrasquillo, M. M., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2017.09.012 · Cited by 143 · see citing works
Self-citationPalmitate and Cholesterol Transport Through the Blood‐Brain Barrier
Pardridge, W. M., & Mietus, L. J. (1980) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1980.tb06621.x · Cited by 137 · see citing works
Redzic, Z. B. (2011) · Fluids and Barriers of the CNS · doi:10.1186/2045-8118-8-3 · Cited by 128 · see citing works
Bordbar, A., Yurkovich, J. T., Paglia, G., Rolfsson, Ó., Sigurjónsson, Ó. E., & Palsson, B. Ø. (2017) · Scientific Reports · doi:10.1038/srep46249 · Cited by 128 · see citing works
Self-citationKang, Y., Ohtsuki, S., Takanaga, H., Tomi, M., Hosoya, K., & Terasaki, T. (2002) · Journal of Neurochemistry · doi:10.1046/j.1471-4159.2002.01223.x · Cited by 122 · see citing works
Alteration of transcription factors NF-κB and STAT1 in Alzheimer's disease brains
Kitamura, Y., Shimohama, S., Ota, T., Matsuoka, Y., Nomura, Y., & Taniguchi, T. (1997) · Neuroscience Letters · doi:10.1016/s0304-3940(97)00797-0 · Cited by 113 · see citing works
Cholesterol and statins in Alzheimer's disease: Current controversies
Fonseca, A. C. R. G., Resende, R., Oliveira, C. R., & Pereira, C. (2009) · Experimental Neurology · doi:10.1016/j.expneurol.2009.09.013 · Cited by 112 · see citing works
Transport of nutrients and hormones through the blood-brain barrier
Pardridge, W. M. (1981) · Diabetologia · doi:10.1007/bf00254490 · Cited by 102 · see citing works
Gusmao, E. G., Dieterich, C., Zenke, M., & Costa, I. G. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu519 · Cited by 90 · see citing works
Xie, G., Wang, X., Jiang, R., Zhao, A., Yan, J., Zheng, X., Huang, F., Liu, X., Panee, J., Rajani, C., et al. (2018) · EBioMedicine · doi:10.1016/j.ebiom.2018.10.030 · Cited by 84 · see citing works
Self-citationTranscriptional regulatory networks underlying gene expression changes in Huntington's disease
Ament, S. A., Pearl, J. R., Cantle, J. P., Bragg, R. M., Skene, P. J., Coffey, S. R., Bergey, D. E., Wheeler, V. C., MacDonald, M. E., Baliga, N. S., et al. (2018) · Molecular Systems Biology · doi:10.15252/msb.20167435 · Cited by 78 · see citing works
Self-citationBjörkhem, I., Araya, Z., Rudling, M., Angelin, B., Einarsson, C., & Wikvall, K. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m202343200 · Cited by 76 · see citing works
Reconstruction of Cell-type-Specific Interactomes at Single-Cell Resolution
Mohammadi, S., Davila-Velderrain, J., & Kellis, M. (2019) · Cell Systems · doi:10.1016/j.cels.2019.10.007 · Cited by 73 · see citing works
Pearl, J. R., Colantuoni, C., Bergey, D. E., Funk, C. C., Shannon, P. T., Basu, B., Casella, A. M., Oshone, R. T., Hood, L., Price, N. D., et al. (2019) · Cell Systems · doi:10.1016/j.cels.2019.01.002 · Cited by 60 · see citing works
Self-citationThe Role of ABCA1 Gene Sequence Variants on Risk of Alzheimer's Disease
Lupton, M. K., Proitsi, P., Lin, K., Hamilton, G., Daniilidou, M., Tsolaki, M., & Powell, J. F. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-131121 · Cited by 55 · see citing works
Koldamova, R. P., & Lefterov, I. M. (2007) · Current Alzheimer Research · doi:10.2174/156720507780362227 · Cited by 55 · see citing works
Griffiths, W. J., Abdel‐Khalik, J., Yutuc, E., Morgan, A. H., Gilmore, I. S., Hearn, T., & Wang, Y. (2017) · Analytical Biochemistry · doi:10.1016/j.ab.2017.01.009 · Cited by 55 · see citing works
Self-citationBrain properties predict proximity to symptom onset in sporadic Alzheimer’s disease
Vogel, J. W., Vachon‐Presseau, É., Binette, A. P., Tam, A., Orban, P., Joie, R. L., Savard, M., Picard, C., Poirier, J., Bellec, P., et al. (2018) · Brain · doi:10.1093/brain/awy093 · Cited by 50 · see citing works
STAT1 Negatively Regulates Spatial Memory Formation and Mediates the Memory-Impairing Effect of Aβ
Hsu, W., Ma, Y., Hsieh, D., Liu, Y., & Lee, E. H. Y. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2013.263 · Cited by 49 · see citing works
Bile Acids in Hepatic Encephalopathy
DeMorrow, S. (2018) · Journal of Clinical and Experimental Hepatology · doi:10.1016/j.jceh.2018.04.011 · Cited by 47 · see citing works
Satoh, J.-I., Yamamoto, Y., Asahina, N., Kitano, S., & Kino, Y. (2014) · Disease Markers · doi:10.1155/2014/123165 · Cited by 46 · see citing works
Logsdon, B. A., Perumal, T. M., Swarup, V., Wang, M., Funk, C. C., Gaiteri, C., Allen, M., Wang, X. B., Dammer, E. B., Srivastava, G. P., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/510420 · Cited by 46 · see citing works
Self-citationPeripheral serum metabolomic profiles inform central cognitive impairment
Wang, J., Wei, R., Xie, G., Arnold, M., Kueider‐Paisley, A., Louie, G., Dehkordi, S. M., Blach, C., Baillie, R., Han, X., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-70703-w · Cited by 38 · see citing works
Self-citationConcentrations of bile acid precursors in cerebrospinal fluid of Alzheimer's disease patients
Griffiths, W. J., Abdel‐Khalik, J., Yutuc, E., et al. (2018) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2018.12.020 · Cited by 34 · see citing works
Self-citationFunk, C. C., Casella, A. M., Jung, S. C., Richards, M. A., Rodriguez, A., Shannon, P. T., Donovan-Maiye, R., Heavner, B., Chard, K., Xiao, Y., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108029 · Cited by 34 · see citing works
Self-citationGenome-Scale Reconstruction of the Human Astrocyte Metabolic Network
Martín-Jiménez, C., Salazar-Barreto, D., Barreto, G. E., & González, J. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00023 · Cited by 33 · see citing works
Physiological characteristics of allo-cholic acid
Mendoza, M. E., Monte, M. J., Serrano, M. A., et al. (2003) · Journal of Lipid Research · doi:10.1194/jlr.m200220-jlr200 · Cited by 28 · see citing works
Heinken, A., Ravcheev, D. A., Baldini, F., Heirendt, L., Fleming, R. M. T., & Thiele, I. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/229138 · Cited by 28 · see citing works
Self-citationWhen metabolism meets physiology: Harvey and HarvettaPreprint
Thiele, I., Sahoo, S., Heinken, A., Heirendt, L., Aurich, M. K., Noronha, A., & Fleming, R. M. T. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/255885 · Cited by 23 · see citing works
Self-citationFowler, K. D., Funt, J. M., Artyomov, M. N., Zeskind, B. J., Kolitz, S. E., & Towfic, F. (2015) · Scientific Reports · doi:10.1038/srep14324 · Cited by 20 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Microbiota–gut–brain axis and its therapeutic applications in neurodegenerative diseases
Loh, J. S., Mak, W. Q., Tan, L. K. S., Ng, C. X., Chan, H. H., Yeow, S. H., Foo, J. B., Ong, Y. S., How, C. W., & Khaw, K. Y. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01743-1 · Cited by 1,193 · see citing works
Microbiota-derived metabolites as drivers of gut–brain communication
Ahmed, H., Leyrolle, Q., Koistinen, V., Kärkkäinen, O., Layé, S., Delzenne, N., & Hanhineva, K. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2102878 · Cited by 462 · see citing works
Signalling cognition: The gut microbiota and hypothalamic-pituitary-adrenal axis
Rusch, J. A., Layden, B. T., & Dugas, L. R. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1130689 · Cited by 415 · see citing works
Microbial-derived metabolites as a risk factor of age-related cognitive decline and dementia
Connell, E., Le Gall, G., Pontifex, M. G., Sami, S., Cryan, J. F., Clarke, G., Müller, M., & Vauzour, D. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00548-6 · Cited by 208 · see citing works
Varma, V. R., Büşra Lüleci, H., Oommen, A. M., Varma, S., Blackshear, C. T., Griswold, M. E., An, Y., Roberts, J. A., O’Brien, R., Pletnikova, O., et al. (2021) · npj Aging and Mechanisms of Disease · doi:10.1038/s41514-021-00064-9 · Cited by 153 · see citing works
Bile acids as key modulators of the brain-Gut-Microbiota axis in alzheimer’s disease
Mulak, A. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-210608 · Cited by 114 · see citing works
Varma, V. R., Wang, Y., An, Y., Varma, S., Bilgel, M., Doshi, J., Legido-Quigley, C., Delgado, J. C., Oommen, A. M., Roberts, J. A., et al. (2021) · PLOS Medicine · doi:10.1371/journal.pmed.1003615 · Cited by 97 · see citing works
Self-citationMahmoudianDehkordi, S., Bhattacharyya, S., Brydges, C. R., Jia, W., Fiehn, O., Rush, A. J., Dunlop, B. W., & Kaddurah-Daouk, R. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.937906 · Cited by 75 · see citing works
Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer’s disease
Meng, L., Jin, H., Yulug, B., Altay, O., Li, X., Hanoglu, L., Cankaya, S., Coskun, E., Idil, E., Nogaylar, R., et al. (2024) · Alzheimer's Research & Therapy · doi:10.1186/s13195-024-01578-6 · Cited by 49 · see citing works
[Retracted] A Review of Bile Acid Metabolism and Signaling in Cognitive Dysfunction‐Related Diseases
Weng, Z.-B., Chen, Y.-R., Lv, J.-T., Wang, M.-X., Chen, Z.-Y., Zhou, W., Shen, X.-C., Zhan, L.-B., & Wang, F. (2022) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2022/4289383 · Cited by 32 · see citing works
RetractedUzuner Odongo, D., İlgün, A., Bozkurt, F. B., & Çakır, T. (2025) · Communications Biology · doi:10.1038/s42003-025-07941-z · Cited by 4 · see citing works
- Authors
- Baloni, P., Funk, C. C., Yan, J., Yurkovich, J. T., Kueider-Paisley, A., Nho, K., Heinken, A., Jia, W., Mahmoudiandehkordi, S., Louie, G., Saykin, A. J., Arnold, M., Kastenmüller, G., Griffiths, W. J., Thiele, I., Kaddurah-Daouk, R., Kueider-Paisley, A., Louie, G., Doraiswamy, P. M., Blach, C., Moseley, A., Thompson, J. W., Mahmoudiandehkhordi, S., Welsh-Balmer, K., Plassman, B., Saykin, A., Nho, K., Kastenmüller, G., Arnold, M., Bhattacharyya, S., Han, X., Baillie, R., Fiehn, O., Barupal, D., Meikle, P., Mazmanian, S., Kling, M., Shaw, L., Trojanowski, J., Toledo, J., van Duijin, C., Hankemier, T., Thiele, I., Heinken, A., Price, N., Funk, C., Baloni, P., Jia, W., Wishart, D., Brinton, R., Chang, R., Farrer, L., Au, R., Qiu, W., Würtz, P., Mangravite, L., Krumsiek, J., Newman, J., Zhang, B., Moreno, H., Kaddurah-Daouk, R., & Price, N. D.
- Affiliations
- Indiana University Indianapolis (US)
- Institute for Systems Biology (US)
- Duke University (US)
- Swansea University (GB)
- Helmholtz Munich (DE)
- University of Hawaii Cancer Center (US)
- ORCID
- Yan, Jingwen
- Yurkovich, James T.
- Mahmoudiandehkordi, Siamak
- Griffiths, William J.
- Doraiswamy, P. Murali
- Blach, Colette
- Plassman, Brenda
- Bhattacharyya, Sudeepa
- Han, Xianlin
- Baillie, Rebecca
- Fiehn, Oliver
- Barupal, Dinesh
- Meikle, Peter
- Mazmanian, Sarkis
- Shaw, Leslie
- Trojanowski, John
- Toledo, Jon
- Wishart, David
- Brinton, Roberta
- Chang, Rui
- Farrer, Lindsay
- Au, Rhoda
- Würtz, Peter
- Mangravite, Lara
- Krumsiek, Jan
- Newman, John
- Zhang, Bin
- Moreno, Herman
- Venue
- Cell Reports Medicine
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 1
- Issue
- 8
- Pages
- 100138
- ISSN
- 2666-3791 (ISSN-L)
- PMC
- PMC7691449
- OpenAlex
- W3099584915
- Cited by
- 211
- References
- 85
- Citations by year
- 2026: 30 · 2025: 36 · 2024: 47 · 2023: 39 · 2022: 30 · 2021: 27 · 2019: 1
- FWCI
- 14.43
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cell Reports Medicine (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc-nd)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by-nc-nd)
- IUScholarWorks (Indiana University) (submittedVersion, cc-by-nc-nd)
- Funders
- Biotechnology and Biological Sciences Research Council (BB/I001735/1, BB/N015932/1)
- National Institute on Aging (RF1 AG0151550, R01AG046171, U01AG46152, R01 AG057452, RF1 AG058942, R01AG17917, P30AG10161, R01AG15819)
- Engineering and Physical Sciences Research Council
- National Institutes of Health (R01 CA129769, R01 AG019771, P30 AG010133)
- Qatar National Research Fund (NLM R01 LM012535, NPRP8-061-3-011, R03 AG054936)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Surgery › Cholesterol and Lipid Metabolism
- Keywords
- Alzheimer's disease, bile acid synthesis, bile acid metabolism, cholesterol metabolism, taurine transport, metabolic network analysis, gut microbiota, transcription factors, cognitive decline, brain metabolomics
- MeSH terms
- Alzheimer Disease, Bile Acids and Salts, Brain, Cholesterol, Humans, Lipogenesis, Lipid Metabolism, Metabolic Networks and Pathways, Metabolomics, Transcriptome, Cognitive Dysfunction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
