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Winchester LM, Newby D, Ghose U, Hu P, Green H, Chien S, Ranson J, Faul J, Llewellyn D, Lee J, Bauermeister S, Nevado-Holgado A. Anemia, hemoglobin concentration and cognitive function in the Longitudinal Ageing Study in India-Harmonized Diagnostic Assessment of Dementia (LASI-DAD) and the Health and Retirement Study. medRxiv 2024:2024.01.22.24301583. [PMID: 38343823 PMCID: PMC10854337 DOI: 10.1101/2024.01.22.24301583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
Background In India, anemia is widely researched in children and women of reproductive age, however, studies in older populations are lacking. Given the adverse effect of anemia on cognitive function and dementia this older population group warrants further study. The Longitudinal Ageing Study in India - Harmonized Diagnostic Assessment of Dementia (LASI-DAD) dataset contains detailed measures to allow a better understanding of anaemia as a potential risk factor for dementia. Method 2,758 respondents from the LASI-DAD cohort, aged 60 or older, had a complete blood count measured from venous blood as well as cognitive function tests including episodic memory, executive function and verbal fluency. Linear regression was used to test the associations between blood measures (including anemia and hemoglobin concentration (g/dL)) with 11 cognitive domains. All models were adjusted for age and gender with the full model containing adjustments for rural location, years of education, smoking, region, BMI and population weights.Results from LASI-DAD were validated using the USA-based Health and Retirement Study (HRS) cohort (n=5720) to replicate associations between blood cell measures and global cognition. Results In LASI-DAD, we showed an association between anemia and poor memory (p=0.0054). We found a positive association between hemoglobin concentration and ten cognitive domains tested (β=0.041-0.071, p<0.05). The strongest association with hemoglobin was identified for memory-based tests (immediate episodic, delayed episodic and broad domain memory, β=0.061-0.071, p<0.005). Positive associations were also shown between the general cognitive score and the other red blood count tests including mean corpuscular hemoglobin concentration (MCHC, β=0.06, p=0.0001) and red cell distribution width (RDW, β =-0.11, p<0.0001). In the HRS cohort, positive associations were replicated between general cognitive score and other blood count tests (Red Blood Cell, MCHC and RDW, p<0.05). Conclusion We have established in a large South Asian population that low hemoglobin and anaemia are associated with low cognitive function, therefore indicating that anaemia could be an important modifiable risk factor. We have validated this result in an external cohort demonstrating both the variability of this risk factor cross-nationally and its generalizable association with cognitive outcomes.
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Affiliation(s)
| | - Danielle Newby
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | | | - Peifeng Hu
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Hunter Green
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA 90089
| | - Sandy Chien
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA 90089
| | - Janice Ranson
- College of Medicine and Health, University of Exeter, UK
| | - Jessica Faul
- Survey Research Center, Institute for Social Research, University of Michigan
| | | | - Jinkook Lee
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA 90089
- Department of Economics, University of Southern California, Los Angeles, CA, USA 90089
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2
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Bettencourt C, Skene N, Bandres-Ciga S, Anderson E, Winchester LM, Foote IF, Schwartzentruber J, Botia JA, Nalls M, Singleton A, Schilder BM, Humphrey J, Marzi SJ, Toomey CE, Kleifat AA, Harshfield EL, Garfield V, Sandor C, Keat S, Tamburin S, Frigerio CS, Lourida I, Ranson JM, Llewellyn DJ. Artificial intelligence for dementia genetics and omics. Alzheimers Dement 2023; 19:5905-5921. [PMID: 37606627 PMCID: PMC10841325 DOI: 10.1002/alz.13427] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/23/2023]
Abstract
Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.
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Affiliation(s)
- Conceicao Bettencourt
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
| | - Nathan Skene
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Emma Anderson
- Department of Mental Health of Older People, Division of Psychiatry, University College London, London, UK
| | | | - Isabelle F Foote
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Jeremy Schwartzentruber
- Open Targets, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
- Illumina Artificial Intelligence Laboratory, Illumina Inc, Foster City, California, USA
| | - Juan A Botia
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Mike Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International LLC, Washington, DC, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Brian M Schilder
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Jack Humphrey
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Sarah J Marzi
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Christina E Toomey
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
- The Francis Crick Institute, London, UK
| | - Ahmad Al Kleifat
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Eric L Harshfield
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Cynthia Sandor
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Samuel Keat
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, Neurology Section, University of Verona, Verona, Italy
| | - Carlo Sala Frigerio
- UK Dementia Research Institute, Queen Square Institute of Neurology, University College London, London, UK
| | | | | | - David J Llewellyn
- University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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3
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Marzi SJ, Schilder BM, Nott A, Frigerio CS, Willaime-Morawek S, Bucholc M, Hanger DP, James C, Lewis PA, Lourida I, Noble W, Rodriguez-Algarra F, Sharif JA, Tsalenchuk M, Winchester LM, Yaman Ü, Yao Z, Ranson JM, Llewellyn DJ. Artificial intelligence for neurodegenerative experimental models. Alzheimers Dement 2023; 19:5970-5987. [PMID: 37768001 DOI: 10.1002/alz.13479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 08/11/2023] [Accepted: 08/14/2023] [Indexed: 09/29/2023]
Abstract
INTRODUCTION Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. HIGHLIGHTS There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery.
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Affiliation(s)
- Sarah J Marzi
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Brian M Schilder
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Alexi Nott
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | | | | | - Magda Bucholc
- School of Computing, Engineering & Intelligent Systems, Ulster University, Derry, UK
| | - Diane P Hanger
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Patrick A Lewis
- Royal Veterinary College, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | | | - Wendy Noble
- Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | | | - Jalil-Ahmad Sharif
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Maria Tsalenchuk
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | | | - Ümran Yaman
- UK Dementia Research Institute at UCL, London, UK
| | | | | | - David J Llewellyn
- University of Exeter Medical School, Exeter, UK
- Alan Turing Institute, London, UK
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4
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Winchester LM, Harshfield EL, Shi L, Badhwar A, Khleifat AA, Clarke N, Dehsarvi A, Lengyel I, Lourida I, Madan CR, Marzi SJ, Proitsi P, Rajkumar AP, Rittman T, Silajdžić E, Tamburin S, Ranson JM, Llewellyn DJ. Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia. Alzheimers Dement 2023; 19:5860-5871. [PMID: 37654029 PMCID: PMC10840606 DOI: 10.1002/alz.13390] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/13/2023] [Accepted: 06/19/2023] [Indexed: 09/02/2023]
Abstract
With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice. HIGHLIGHTS: Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real-world validation, and interdisciplinary collaboration are required.
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Affiliation(s)
| | - Eric L Harshfield
- Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, Cambridge, UK
| | - Liu Shi
- Novo Nordisk Research Centre Oxford (NNRCO), Headington, UK
| | - AmanPreet Badhwar
- Département de Pharmacologie et Physiologie, Institut de Génie Biomédical, Faculté de Médecine, Université de Montréal, Montreal, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada
| | - Ahmad Al Khleifat
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Natasha Clarke
- Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada
| | - Amir Dehsarvi
- School of Medicine, Medical Sciences, and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Imre Lengyel
- Wellcome-Wolfson Institute of Experimental Medicine, Queen's University, Belfast, UK
| | - Ilianna Lourida
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
| | | | - Sarah J Marzi
- UK Dementia Research Institute at Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Petroula Proitsi
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anto P Rajkumar
- Institute of Mental Health, Mental Health and Clinical Neurosciences academic unit, University of Nottingham, Nottingham, UK, Mental health services of older people, Nottinghamshire healthcare NHS foundation trust, Nottingham, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Edina Silajdžić
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Janice M Ranson
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
| | - David J Llewellyn
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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5
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Ranson JM, Khleifat AA, Lyall DM, Newby D, Winchester LM, Proitsi P, Veldsman M, Rittman T, Marzi S, Yao Z, Skene N, Bettencourt C, Kormilitzin A, Foote IF, Golborne C, Lourida I, Bucholc M, Tang E, Oxtoby NP, Bagshaw P, Walker Z, Everson R, Ballard CG, van Duijn CM, Langa KM, MacLeod M, Rockwood K, Llewellyn DJ. The Deep Dementia Phenotyping (DEMON) Network: A global platform for innovation using data science and artificial intelligence. Alzheimers Dement 2022. [DOI: 10.1002/alz.067873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | - Sarah Marzi
- UK Dementia Research Institute London United Kingdom
- Imperial College London London United Kingdom
| | - Zhi Yao
- LifeArc London United Kingdom
| | - Nathan Skene
- UK Dementia Research Institute London United Kingdom
- Imperial College London London United Kingdom
| | | | | | | | | | | | | | - Eugene Tang
- Newcastle University Newcastle United Kingdom
| | | | - Peter Bagshaw
- Somerset Clinical Commissioning Group Yeovil United Kingdom
| | | | - Richard Everson
- University of Exeter Exeter United Kingdom
- Alan Turing Institute London United Kingdom
| | | | | | | | | | | | - David J Llewellyn
- University of Exeter Exeter United Kingdom
- Alan Turing Institute London United Kingdom
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6
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van Duijn CM, Amin N, Liu J, Bonnechere B, MahmoudianDehkordi S, Arnold M, Batra R, Chiou Y, Fernandes M, Ikram MA, Kraaij R, Krumsiek J, Newby D, Nho K, Radjabzadeh D, Saykin AJ, Shi L, Sproviero W, Winchester LM, Yang Y, Nevado‐Holgado AJ, Kastenmüller G, Kaddurah‐Daouk R. Interplay of the human exposome, metabolome and gut microbiome in dementia and major depression. Alzheimers Dement 2022. [DOI: 10.1002/alz.067261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Cornelia M van Duijn
- Nuffield Department of Population Health, University of Oxford Oxford United Kingdom
| | - Najaf Amin
- University of Oxford Oxford United Kingdom
| | - Jun Liu
- University of Oxford Oxford United Kingdom
| | | | - Siamak MahmoudianDehkordi
- Bioinformatics Research Center, Department of Statistics, North Carolina State University Raleigh NC USA
| | | | - Richa Batra
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine New York NY USA
| | - Yu‐Jie Chiou
- Nuffield Department of Population Health, Oxford University Oxford United Kingdom
| | | | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC Rotterdam Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam Netherlands
| | - Jan Krumsiek
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine New York NY USA
| | | | - Kwangsik Nho
- Indiana Alzheimer’s Disease Research Center Indianapolis IN USA
| | - Djawad Radjabzadeh
- Department of Internal Medicine, Erasmus University Medical Center Rotterdam Netherlands
| | - Andrew J. Saykin
- Department of Radiology and Imaging Services, Indiana University School of Medicine Indianapolis IN USA
| | - Liu Shi
- Department of Psychiatry, University of Oxford Oxford United Kingdom
| | | | | | - Yang Yang
- Department of Computer Science and Engineering Shanghai China
| | | | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health Neuherberg Germany
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7
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Ranson JM, Khleifat AA, Lyall DM, Newby D, Winchester LM, Proitsi P, Veldsman M, Rittman T, Marzi S, Yao Z, Skene N, Bettencourt C, Kormilitzin A, Foote IF, Golborne C, Lourida I, Bucholc M, Tang E, Oxtoby NP, Bagshaw P, Walker Z, Everson R, Ballard CG, van Duijn CM, Langa KM, MacLeod M, Rockwood K, Llewellyn DJ. The Deep Dementia Phenotyping (DEMON) Network: A global platform for innovation using data science and artificial intelligence. Alzheimers Dement 2022; 18 Suppl 2:e067308. [DOI: 10.1002/alz.067308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | - Sarah Marzi
- UK Dementia Research Institute London United Kingdom
- Imperial College London London United Kingdom
| | - Zhi Yao
- LifeArc London United Kingdom
| | - Nathan Skene
- UK Dementia Research Institute London United Kingdom
- Imperial College London London United Kingdom
| | | | | | | | | | | | | | - Eugene Tang
- Newcastle University Newcastle United Kingdom
| | | | - Peter Bagshaw
- Somerset Clinical Commissioning Group Yeovil United Kingdom
| | | | - Richard Everson
- University of Exeter Exeter United Kingdom
- Alan Turing Institute London United Kingdom
| | | | | | | | | | | | - David J Llewellyn
- University of Exeter Exeter United Kingdom
- Alan Turing Institute London United Kingdom
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Newby D, Winchester LM, Sproviero W, Fernandes M, Ghose U, Li QS, Launer LJ, Nevado‐Holgado AJ. The association between isolated hypertension and brain volumes in UK Biobank. Alzheimers Dement 2021. [DOI: 10.1002/alz.050742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | | | | | - Qingqin S Li
- Janssen Research & Development, LLC Titusville NJ USA
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9
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Winchester LM, Lawton M, Barber IS, Evetts S, Ryan B, Wade‐Martins R, Ben‐Shlomo Y, Hu M, Grosset DG, Nevado‐Holgado AJ, Lovestone S. Proteomic analysis of Parkinson’s disease patient cohorts show similarities in mechanism to Alzheimer’s disease. Alzheimers Dement 2021. [DOI: 10.1002/alz.057727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | | | | | - Samuel Evetts
- Oxford Parkinson's Disease Centre Oxford United Kingdom
| | - Brent Ryan
- Oxford Parkinson's Disease Centre Oxford United Kingdom
| | | | | | - Michele Hu
- University of Oxford Oxford United Kingdom
| | | | | | - Simon Lovestone
- Department of Psychiatry, University of Oxford Oxford United Kingdom
- Janssen‐Cilag UK Ltd Oxford United Kingdom
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10
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Liu J, Amin N, Arnold M, Nho K, Saykin AJ, Newby D, Winchester LM, Nevado‐Holgado AJ, Kastenmüller G, Kaddurah‐Daouk RF, Van Duijn CM. Profiling the metabolome of patients with dementia in the UK Biobank. Alzheimers Dement 2021. [DOI: 10.1002/alz.056147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jun Liu
- University of Oxford Oxford United Kingdom
| | - Najaf Amin
- University of Oxford Oxford United Kingdom
| | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University Durham NC USA
- Duke University Durham NC USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine Indianapolis IN USA
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11
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Shi L, Winchester LM, Westwood S, Baird AL, Anand SN, Buckley NJ, Hye A, Ashton NJ, Bos I, Vos SJB, Kate MT, Scheltens P, Teunissen CE, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lléo A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Legido-Quigley C, Barkhof F, Andreasson U, Blennow K, Zetterberg H, Streffer J, Lill CM, Bertram L, Visser PJ, Kolb HC, Narayan VA, Lovestone S, Nevado-Holgado AJ. Replication study of plasma proteins relating to Alzheimer's pathology. Alzheimers Dement 2021; 17:1452-1464. [PMID: 33792144 DOI: 10.1002/alz.12322] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/26/2020] [Accepted: 02/05/2021] [Indexed: 12/16/2022]
Abstract
INTRODUCTION This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis. METHODS Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively. RESULTS Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis. DISCUSSION Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.
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Affiliation(s)
- Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - Sarah Westwood
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Alison L Baird
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Sneha N Anand
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Noel J Buckley
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Abdul Hye
- Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Nicholas J Ashton
- Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK.,Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Isabelle Bos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands.,Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Mara Ten Kate
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Charlotte E Teunissen
- Neurochemistry lab, Department of Clinical Chemistry, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | | | - Silvy Gabel
- University Hospital Leuven, Leuven, Belgium.,Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Karen Meersmans
- University Hospital Leuven, Leuven, Belgium.,Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.,Department of Neurology, UZ Brussel and Center for Neurociences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Ellen E De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Kristel Sleegers
- Complex Genetics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.,Institute Born-Bunge, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Giovanni B Frisoni
- University of Geneva, Geneva, Switzerland.,IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- AIX marseille university, INS, Ap-hm, Marseille, France
| | | | - Régis Bordet
- Inserm, University of Lille, CHU Lille, Lille, France
| | - José L Molinuevo
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hopsital Clínic-IDIBAPS, Barcelona, Spain.,Barcelona Beta Brain Research Center, Unversitat Pompeu Fabra, Barcelona, Spain
| | - Lorena Rami
- Barcelona Beta Brain Research Center, Unversitat Pompeu Fabra, Barcelona, Spain
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Petronella Kettunen
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Makedonia, Thessaloniki, Greece
| | - Frans Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Alberto Lléo
- Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Isabel Sala
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Julius Popp
- University Hospital of Lausanne, Lausanne, Switzerland.,Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | | | | | | | - Peter Johannsen
- Danish Dementia Research Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Yvonne Freund-Levi
- Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK.,Karolinska Institutet Center for Alzheimer Research, Division of Clinical Geriatrics, School of Medical Sciences Örebro University and Department of Neurobiology, Caring Sciences and Society (NVS), Stockholm, Sweden
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, University of Heidelberg, Mannheim, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Cristina Legido-Quigley
- Kings College London, London, UK.,The Systems Medicine Group, Steno Diabetes Center, Gentofte, Denmark
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherland.,UCL Institutes of Neurology and Healthcare Engineering, London, UK
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,UK Dementia Research Institute at UCL, London, UK.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Johannes Streffer
- Complex Genetics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.,UCB, Braine-l'Alleud, Belgium, formerly Janssen R&D, LLC Beerse, Beerse, Belgium
| | - Christina M Lill
- Section for Translational Surgical Oncology and Biobanking, Department of Surgery, University of Lübeck and University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.,Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands.,Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | | | | | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, UK.,Janssen R&D, Beerse, UK
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12
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Shi L, Winchester LM, Liu BY, Killick R, Ribe EM, Westwood S, Baird AL, Buckley NJ, Hong S, Dobricic V, Kilpert F, Franke A, Kiddle S, Sattlecker M, Dobson R, Cuadrado A, Hye A, Ashton NJ, Morgan AR, Bos I, Vos SJ, ten Kate M, Scheltens P, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lleó A, Alcolea D, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Teunissen CE, Freund-Levi Y, Frölich L, Legido-Quigley C, Barkhof F, Blennow K, Rasmussen KL, Nordestgaard BG, Frikke-Schmidt R, Nielsen SF, Soininen H, Vellas B, Kloszewska I, Mecocci P, Zetterberg H, Morgan BP, Streffer J, Visser PJ, Bertram L, Nevado-Holgado AJ, Lovestone S. Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology. J Alzheimers Dis 2020; 77:1353-1368. [PMID: 32831200 PMCID: PMC7683080 DOI: 10.3233/jad-200208] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/15/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. OBJECTIVE We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. METHODS We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). RESULTS We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. CONCLUSIONS Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.
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Affiliation(s)
- Liu Shi
- Department of Psychiatry, University of Oxford, UK
| | | | | | - Richard Killick
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
| | | | | | | | | | - Shengjun Hong
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Fabian Kilpert
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Steven Kiddle
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, UK
| | - Martina Sattlecker
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, UK
| | - Richard Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Institute of Health Informatics, University College London, London, UK
| | - Antonio Cuadrado
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Investigación Sanitaria La Paz (IdiPaz), Instituto de Investigaciones Biomédicas Alberto Sols UAM-CSIC, and Department of Biochemistry, Faculty of Medicine, Autonomous University of Madrid, Madrid, Spain
- ”Victor Babes” National Institute of Pathology, Bucharest, Romania
| | - Abdul Hye
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
| | - Nicholas J. Ashton
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | | | - Isabelle Bos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Stephanie J.B. Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Mara ten Kate
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | | | - Silvy Gabel
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium
| | - Karen Meersmans
- University Hospital Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium
| | - Sebastiaan Engelborghs
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology, UZ Brussel, Brussels, Belgium
| | - Ellen E. De Roeck
- Center for Neurosciences, Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Kristel Sleegers
- Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Belgium
| | - Giovanni B. Frisoni
- University of Geneva, Geneva, Switzerland
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- AIX Marseille University, INS, Ap-hm, Marseille, France
| | | | | | - José L. Molinuevo
- Alzheimer’s disease & other cognitive disorders unit, Hospital Clínic, Barcelona, Spain
- BarcelonaBeta Brain Research Center, Universitat Pompeu Fabra, Barcelona, Spain
| | - Lorena Rami
- BarcelonaBeta Brain Research Center, Universitat Pompeu Fabra, Barcelona, Spain
| | - Anders Wallin
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Memory Clinic at Department of Neuropsychiatry, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Petronella Kettunen
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, school of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Makedonia, Greece
| | - Frans Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Alberto Lleó
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Daniel Alcolea
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Julius Popp
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
- Geriatric Psychiatry, Department of Psychiatry, Geneva University Hospitals, and University of Geneva, Geneva, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | | | - Mikel Tainta
- CITA-Alzheimer Foundation, San Sebastian, Spain
- Organización Sanitaria Integrada Goierri – Alto Urola, Osakidetza, Spain
| | - Peter Johannsen
- Danish Dementia Research Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory, dept of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Yvonne Freund-Levi
- School of Medical Sciences, Örebro University, Örebro, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institute, Stockholm, Sweden
- Department of Old Age Psychiatry, Psychology and Neuroscience, King’s College London, UK
- Department of Psychiatry, Örebro Universitetssjukhus, Örebro, Sweden
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, University of Heidelberg, Mannheim, Germany
| | - Cristina Legido-Quigley
- Kings College London, London, UK
- The Systems Medicine Group, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherland
- UCL Institutes of Neurology and Healthcare Engineering, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Katrine Laura Rasmussen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Børge Grønne Nordestgaard
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Frederiksberg, Denmark
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sune Fallgaard Nielsen
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Hilkka Soininen
- Neurology / Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Bruno Vellas
- Toulouse Gerontopole University Hospital, Univeriste Paul Sabatier, INSERM U 558, France
| | | | - Patrizia Mecocci
- Section of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, United Kingdom
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
| | - B. Paul Morgan
- Dementia Research Institute Cardiff, Cardiff University, Cardiff, UK
| | - Johannes Streffer
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- UCB, Braine-l’Alleud, Belgium, formerly Janssen R&D, LLC. Beerse, Belgium at the time of study conduct
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Simon Lovestone
- Department of Psychiatry, University of Oxford, UK
- Currently at Janssen-Cilag UK, formerly at Department of Psychiatry, University of Oxford, UK at the time of the study conduct
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Winchester LM, Powell J, Lovestone S, Nevado-Holgado AJ. Red blood cell indices and anaemia as causative factors for cognitive function deficits and for Alzheimer's disease. Genome Med 2018; 10:51. [PMID: 29954452 PMCID: PMC6022699 DOI: 10.1186/s13073-018-0556-z] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 06/07/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Studies have shown that low haemoglobin and anaemia are associated with poor cognition, and anaemia is known to be associated with Alzheimer's disease (AD), but the mechanism of this risk is unknown. Here, we first seek to confirm the association between cognition and anaemia and secondly, in order to further understand the mechanism of this association, to estimate the direction of causation using Mendelian randomisation. METHODS Two independent cohorts were used in this analysis: AddNeuroMed, a longitudinal study of 738 subjects including AD and age-matched controls with blood cell measures, cognitive assessments and gene expression data from blood; and UK Biobank, a study of 502,649 healthy participants, aged 40-69 years with cognitive test measures and blood cell indices at baseline. General linear models were calculated using cognitive function as the outcome with correction for age, sex and education. In UK Biobank, SNPs with known blood cell measure associations were analysed with Mendelian randomisation to estimate direction of causality. In AddNeuroMed, gene expression data was used in pathway enrichment analysis to identify associations reflecting biological function. RESULTS Both sample sets evidence a reproducible association between cognitive performance and mean corpuscular haemoglobin (MCH), a measure of average mass of haemoglobin per red blood cell. Furthermore, in the AddNeuroMed cohort, where longitudinal samples were available, we showed a greater decline in red blood cell indices for AD patients when compared to controls (p values between 0.05 and 10-6). In the UK Biobank cohort, we found lower haemoglobin in participants with reduced cognitive function. There was a significant association for MCH and red blood cell distribution width (RDW, a measure of cell volume variability) compared to four cognitive function tests including reaction time and reasoning (p < 0.0001). Using Mendelian randomisation, we then showed a significant effect of MCH on the verbal-numeric and numeric traits, implying that anaemia has causative effect on cognitive performance. CONCLUSIONS Lower haemoglobin levels in blood are associated to poor cognitive function and AD. We have used UK Biobank SNP data to determine the relationship between cognitive testing and haemoglobin measures and suggest that haemoglobin level and therefore anaemia does have a primary causal impact on cognitive performance.
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Affiliation(s)
| | - John Powell
- Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
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14
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Haider S, McIntyre A, van Stiphout RGPM, Winchester LM, Wigfield S, Harris AL, Buffa FM. Genomic alterations underlie a pan-cancer metabolic shift associated with tumour hypoxia. Genome Biol 2016; 17:140. [PMID: 27358048 PMCID: PMC4926297 DOI: 10.1186/s13059-016-0999-8] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 06/06/2016] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Altered metabolism is a hallmark of cancer. However, the role of genomic changes in metabolic genes driving the tumour metabolic shift remains to be elucidated. Here, we have investigated the genomic and transcriptomic changes underlying this shift across ten different cancer types. RESULTS A systematic pan-cancer analysis of 6538 tumour/normal samples covering ten major cancer types identified a core metabolic signature of 44 genes that exhibit high frequency somatic copy number gains/amplifications (>20 % cases) associated with increased mRNA expression (ρ > 0.3, q < 10(-3)). Prognostic classifiers using these genes were confirmed in independent datasets for breast and kidney cancers. Interestingly, this signature is strongly associated with hypoxia, with nine out of ten cancer types showing increased expression and five out of ten cancer types showing increased gain/amplification of these genes in hypoxic tumours (P ≤ 0.01). Further validation in breast and colorectal cancer cell lines highlighted squalene epoxidase, an oxygen-requiring enzyme in cholesterol biosynthesis, as a driver of dysregulated metabolism and a key player in maintaining cell survival under hypoxia. CONCLUSIONS This study reveals somatic genomic alterations underlying a pan-cancer metabolic shift and suggests genomic adaptation of these genes as a survival mechanism in hypoxic tumours.
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Affiliation(s)
- Syed Haider
- />Computational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK
- />Molecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Alan McIntyre
- />Molecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Ruud G. P. M. van Stiphout
- />Computational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK
| | - Laura M. Winchester
- />Computational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK
- />Molecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Simon Wigfield
- />Molecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Adrian L. Harris
- />Molecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Francesca M. Buffa
- />Computational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK
- />Molecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
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15
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Haider S, McIntyre A, van Stiphout RGPM, Winchester LM, Wigfield S, Harris AL, Buffa FM. Abstract 3750: Genomic alterations underlie a pan-cancer metabolic transcriptome shift. Cancer Res 2015. [DOI: 10.1158/1538-7445.am2015-3750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background
Hypoxia is a key physiological and microenvironmental difference between tumour and normal tissues. Hypoxia induces DNA damage, genomic aberrations and reprogramming of DNA repair mechanisms. A crucial mechanism in a highly dynamic hypoxic tumour microenvironment is metabolic reprogramming of tumour cells. Genome-wide multi-modal molecular profiles have been generated, however it remains unclear whether upregulation of metabolic genes is substantially enriched with somatically acquired alterations. To answer this, we performed a pan-cancer integrative analysis of genomic and transcriptomic profiles of 10 TCGA tumour types (n = 5,500).
Methods
2,750 metabolic genes were extracted from KEGG pathways, and differentially upregulated genes were identified for each tumour type. High-ranking (10%) upregulated genes were assessed for correlation between mRNA abundance and DNA copy-number changes, and subsequently tested for metabolic-enrichment using genome-wide permutation analysis. For each tumour type, highly correlated genesets were subsequently examined for their potential as drug targets and biomarkers of disease relapse.
Results
Integrative analysis of mRNA and copy-number data revealed clusters of tumours that exhibit similar landscape of metabolic gene profiles, and those having unique metabolic copy number aberrations. Within these profiles, we identify a core set of genes that exhibit strong correlation (Spearman's ρ>0.3; q<0.001) between DNA and RNA profiles (candidate drivers) across a range of tumour types. Compared to genome-wide correlation patterns, the correlated genes were significantly over-represented in breast, glioblastoma multiforme and ovarian cancers (p<0.05). Of note, the correlation analysis uncovered breast cancer subtype-specific heterogeneity in altered metabolic profiles with aggressive breast cancers (Basal and HER2-enriched) demonstrating higher number of candidate drivers. mRNA correlation analysis performed on the top candidate drivers revealed an overall trend of positive correlation between hypoxia signature and metabolic genes. This highlights hypoxia as a potential cause of metabolic dysregulation. Further in-vitro analysis of one of the top candidate drivers, SQLE amplification, showed a marked sensitivity to inhibition in hypoxia compared to normoxia, highlighting hypoxia dependence of genetic and metabolic reprograming in aggressive breast cancers (Basal and HER2-enriched) and colon cancer.
Conclusions
We isolate tumour-type specific and core pan-cancer metabolic gene signatures revealing within and cross disease heterogeneity in metabolic profiles. We highlight a core set of pan-cancer metabolic candidate drivers which are recurrently over-expressed due to genomic amplifications induced by hypoxia.
Citation Format: Syed Haider, Alan McIntyre, Ruud GPM van Stiphout, Laura M. Winchester, Simon Wigfield, Adrian L. Harris, Francesca M. Buffa. Genomic alterations underlie a pan-cancer metabolic transcriptome shift. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3750. doi:10.1158/1538-7445.AM2015-3750
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Affiliation(s)
- Syed Haider
- University of Oxford, Oxford, United Kingdom
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