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Schweickart A, Batra R, Neth BJ, Martino C, Shenhav L, Zhang AR, Shi P, Karu N, Huynh K, Meikle PJ, Schimmel L, Dilmore AH, Blennow K, Zetterberg H, Blach C, Dorrestein PC, Knight R, Craft S, Kaddurah-Daouk R, Krumsiek J. Serum and CSF metabolomics analysis shows Mediterranean Ketogenic Diet mitigates risk factors of Alzheimer's disease. NPJ METABOLIC HEALTH AND DISEASE 2024; 2:15. [PMID: 38962750 PMCID: PMC11216994 DOI: 10.1038/s44324-024-00016-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 05/16/2024] [Indexed: 07/05/2024]
Abstract
Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean Ketogenic Diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.
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Affiliation(s)
- Annalise Schweickart
- Tri-Institutional Program in Computational Biology & Medicine, Weill Cornell Medicine, New York, NY USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY USA
| | - Richa Batra
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY USA
| | - Bryan J. Neth
- Department of Neurology, Mayo Clinic, Rochester, MN USA
| | - Cameron Martino
- Department of Pediatrics, University of California San Diego, La Jolla, CA USA
| | - Liat Shenhav
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY USA
| | - Anru R. Zhang
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC USA
| | - Pixu Shi
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC USA
| | - Naama Karu
- Tasmanian Independent Metabolomics and Analytical Chemistry Solutions (TIMACS), Hobart, TAS Australia
| | - Kevin Huynh
- Baker Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, VIC Australia
| | - Peter J. Meikle
- Baker Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, VIC Australia
| | - Leyla Schimmel
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC USA
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC USA
| | - Pieter C. Dorrestein
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA USA
| | - Rob Knight
- Departments of Pediatrics, Computer Science and Engineering, Bioengineering, University of California San Diego, La Jolla, CA USA
| | - Alzheimer’s Gut Microbiome Project Consortium
- Tri-Institutional Program in Computational Biology & Medicine, Weill Cornell Medicine, New York, NY USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY USA
- Department of Neurology, Mayo Clinic, Rochester, MN USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA USA
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY USA
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC USA
- Tasmanian Independent Metabolomics and Analytical Chemistry Solutions (TIMACS), Hobart, TAS Australia
- Baker Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, VIC Australia
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC USA
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Duke Molecular Physiology Institute, Duke University, Durham, NC USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA USA
- Departments of Pediatrics, Computer Science and Engineering, Bioengineering, University of California San Diego, La Jolla, CA USA
- Department of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston Salem, NC USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC USA
- Department of Medicine, Duke University, Durham, NC USA
| | - Suzanne Craft
- Department of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston Salem, NC USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC USA
- Department of Medicine, Duke University, Durham, NC USA
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY USA
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Dilmore AH, Kuplicki R, McDonald D, Kumar M, Estaki M, Youngblut N, Tyakht A, Ackermann G, Blach C, MahmoudianDehkordi S, Dunlop BW, Bhattacharyya S, Guinjoan S, Mandaviya P, Ley RE, Kaddaruh-Dauok R, Paulus MP, Knight R. Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585820. [PMID: 38562901 PMCID: PMC10983923 DOI: 10.1101/2024.03.19.585820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.
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Affiliation(s)
- Amanda Hazel Dilmore
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, California, USA
| | - Rayus Kuplicki
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Megha Kumar
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Mehrbod Estaki
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Nicholas Youngblut
- Department of Microbiome Science, Max Planck Institute for Biology, Tübingen, Germany
| | - Alexander Tyakht
- Department of Microbiome Science, Max Planck Institute for Biology, Tübingen, Germany
| | - Gail Ackermann
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Colette Blach
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, USA
- Department of Medicine, Duke University, Durham, North Carolina, USA
- Duke Institute of Brain Sciences, Duke University, Durham, North Carolina, USA
| | | | - Boadie W. Dunlop
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Sudeepa Bhattacharyya
- Department of Biological Sciences, Arkansas Biosciences Institute, Arkansas State University, Jonesboro, AR, USA
| | | | - Pooja Mandaviya
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ruth E. Ley
- Department of Microbiome Science, Max Planck Institute for Biology, Tübingen, Germany
| | - Rima Kaddaruh-Dauok
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, USA
- Department of Medicine, Duke University, Durham, North Carolina, USA
- Duke Institute of Brain Sciences, Duke University, Durham, North Carolina, USA
| | | | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
- Department of Computer Science & Engineering, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
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Schweickart A, Batra R, Neth BJ, Martino C, Shenhav L, Zhang AR, Shi P, Karu N, Huynh K, Meikle PJ, Schimmel L, Dilmore AH, Blennow K, Zetterberg H, Blach C, Dorrestein PC, Knight R, Craft S, Kaddurah-Daouk R, Krumsiek J. A Modified Mediterranean Ketogenic Diet mitigates modifiable risk factors of Alzheimer's Disease: a serum and CSF-based metabolic analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.27.23298990. [PMID: 38076824 PMCID: PMC10705656 DOI: 10.1101/2023.11.27.23298990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean-ketogenic diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.
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Affiliation(s)
- Annalise Schweickart
- Tri-Institutional Program in Computational Biology & Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY 10021, USA
| | - Richa Batra
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY 10021, USA
| | | | - Cameron Martino
- Department of Pediatrics, University of California San Diego, La Jolla, CA
| | - Liat Shenhav
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Anru R. Zhang
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Pixu Shi
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Naama Karu
- Tasmanian Independent Metabolomics and Analytical Chemistry Solutions (TIMACS), Hobart, 7008 Tasmania, Australia
| | - Kevin Huynh
- Baker Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, VIC, Australia
| | - Peter J. Meikle
- Baker Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, VIC, Australia
| | - Leyla Schimmel
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Pieter C Dorrestein
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA
| | - Rob Knight
- Departments of Pediatrics, Computer Science and Engineering, Bioengineering, University of California San Diego, La Jolla, CA
| | | | - Suzanne Craft
- Department of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Weill Cornell Medicine, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, New York, NY 10021, USA
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Hughes RL, Frankenfeld CL, Gohl DM, Huttenhower C, Jackson SA, Vandeputte D, Vogtmann E, Comstock SS, Kable ME. Methods in Nutrition & Gut Microbiome Research: An American Society for Nutrition Satellite Session [13 October 2022]. Nutrients 2023; 15:nu15112451. [PMID: 37299414 DOI: 10.3390/nu15112451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/14/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023] Open
Abstract
The microbial cells colonizing the human body form an ecosystem that is integral to the regulation and maintenance of human health. Elucidation of specific associations between the human microbiome and health outcomes is facilitating the development of microbiome-targeted recommendations and treatments (e.g., fecal microbiota transplant; pre-, pro-, and post-biotics) to help prevent and treat disease. However, the potential of such recommendations and treatments to improve human health has yet to be fully realized. Technological advances have led to the development and proliferation of a wide range of tools and methods to collect, store, sequence, and analyze microbiome samples. However, differences in methodology at each step in these analytic processes can lead to variability in results due to the unique biases and limitations of each component. This technical variability hampers the detection and validation of associations with small to medium effect sizes. Therefore, the American Society for Nutrition (ASN) Nutritional Microbiology Group Engaging Members (GEM), sponsored by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS), hosted a satellite session on methods in nutrition and gut microbiome research to review currently available methods for microbiome research, best practices, as well as tools and standards to aid in comparability of methods and results. This manuscript summarizes the topics and research discussed at the session. Consideration of the guidelines and principles reviewed in this session will increase the accuracy, precision, and comparability of microbiome research and ultimately the understanding of the associations between the human microbiome and health.
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Affiliation(s)
| | | | - Daryl M Gohl
- University of Minnesota Genomics Center, Minneapolis, MN 55455, USA
- Department of Genetics, Cell Biology, and Developmental Biology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Curtis Huttenhower
- Department of Biostatistics and Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Chan Microbiome in Public Health Center, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Scott A Jackson
- Complex Microbial Systems Group, Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
| | - Doris Vandeputte
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
| | - Emily Vogtmann
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sarah S Comstock
- Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI 48824, USA
| | - Mary E Kable
- USDA-ARS Western Human Nutrition Research Center, University of California-Davis, Davis, CA 95616, USA
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