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Li Z, Ma Q, Zhang J, Yin R, You J, Hao Q, Wu X, Kang J, Wang L, Deng Y, Li Y, Shen C, Wu B, Feng J, Tu Y, Xiao X, Yu J, Cheng W. Large-Scale Plasma Proteomics to Profile Pathways and Prognosis of Chronic Pain. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2410160. [PMID: 40048323 PMCID: PMC12021123 DOI: 10.1002/advs.202410160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 01/10/2025] [Indexed: 04/26/2025]
Abstract
While increasing peripheral mechanisms related to chronic pain, the plasma proteomics profile associated with it and its prognosis remains elusive. This study utilizes 2923 plasma proteins and chronic pain of 51 644 participants from UK Biobank and finds 474 proteins linked to chronic pain in six sites: head, neck or shoulder, back, stomach or abdominal, hip, and knee, with 11 proteins sharing across pain sites. The identified proteins are largely enriched in immune and metabolic pathways and highly expressed in tissues like lungs and small intestines. Phenome-wide analysis highlights the significance of pain-related proteome on diverse facets of human health, and in-depth Mendelian randomization validates 10 proteins (CD302, RARRES2, TNFRSF1B, BTN2A1, TNFRSF9, COL18A1, TNF, CD74, TNFRSF4, and BTN2A1) as markers of chronic pain. Furthermore, protein sets capable of classifying pain patients and healthy participants, particularly performing best in hip pain (area under curve, AUC = 0.725), are identified. Interestingly, the prediction of pain spreading over ten years achieves an AUC of 0.715, with leptin identified as a crucial predictor. This study delineates proteins associated with various pain conditions and identifies proteins capable of classifying pain and predicting pain spreading, offering benefits for both research and clinical practice.
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Affiliation(s)
- Ze‐Yu Li
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Qing Ma
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive ScienceEast China Normal UniversityShanghai200062China
| | - Jie Zhang
- Department of NeurosurgeryHuashan Hospital, Shanghai Medical CollegeFudan UniversityShanghai200040China
- National Center for Neurological DisordersShanghai200040China
| | - Rui‐Ying Yin
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Jia You
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Qi‐Zheng Hao
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Xin‐Rui Wu
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
| | - Ju‐Jiao Kang
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Lin‐Bo Wang
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Yue‐Ting Deng
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
| | - Yu‐Zhu Li
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Chun Shen
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
| | - Bang‐Sheng Wu
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
| | - Jian‐Feng Feng
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
- Department of Computer ScienceUniversity of WarwickCoventryCV4 7ALUK
- Fudan ISTBI–ZJNU Algorithm Centre for Brain‐inspired IntelligenceZhejiang Normal UniversityZhejiang321004China
| | - Yi‐Heng Tu
- CAS Key Laboratory of Mental Health, Institute of PsychologyChinese Academy of SciencesBeijing100101China
| | - Xiao Xiao
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
| | - Jin‐Tai Yu
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
| | - Wei Cheng
- Institute of Science and Technology for Brain‐Inspired IntelligenceDepartment of NeurologyHuashan HospitalState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai200433China
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University)Ministry of EducationShanghai200433China
- Fudan ISTBI–ZJNU Algorithm Centre for Brain‐inspired IntelligenceZhejiang Normal UniversityZhejiang321004China
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Popp J, Kressig RW, Bieler-Aeschlimann M, Rabl M, Ienca M, Monsch AU, Pihan H, Klöppel S, Meyer-Heim T, Becker S. Conference report: Trends, new technologies and implications for dementia diagnostics, treatment and care in Switzerland. Swiss Med Wkly 2025; 155:4017. [PMID: 40134375 DOI: 10.57187/s.4017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2025] Open
Abstract
Dementia diseases represent a major burden for the directly affected people, their relatives and modern society. Despite considerable efforts in recent years, early and accurate disease diagnosis and monitoring is still a challenge while no cure is available in most cases. New drugs, in particular disease-modifying therapies, and recent technological advancements offer promising perspectives. The integration of novel biomarkers, artificial intelligence and digital health tools has the potential to transform dementia care, making it more personalised, efficient and adapted to the living conditions and needs of older people. In November 2023, the 7th Dementia Summit convened a panel of experts from geriatrics, neurology, neuropsychology, psychiatry, ethics as well as general medicine to discuss interdisciplinary challenges, advancements and their implications for the future of dementia care in Switzerland. The conference underscored the importance of a multidisciplinary approach to successfully integrate new technologies in both clinical-translational research and dementia prevention, diagnosis and care. While recent innovations represent major steps forward, their implementation also comes with important challenges including questions on healthcare system preparedness and adaptation, ethical aspects, technology literacy, acceptance and appropriate use.
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Affiliation(s)
- Julius Popp
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich and University of Zurich, Zurich, Switzerland
- Department of Old Age Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Reto W Kressig
- University Department of Geriatric Medicine Felix Platter, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Mélanie Bieler-Aeschlimann
- Leenaards Memory Centre, Department of Clinical Neurosciences, and Infections Disease Service, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | - Miriam Rabl
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Marcello Ienca
- Institute for History and Ethics of Medicine, School of Medicine and Health, Technical University of Munich, Munich, Germany
- College of Humanities, Swiss Federal Institute of Technology in Lausanne, Lausanne, Switzerland
| | | | - Hans Pihan
- Neurology Clinic and Memory Clinic, Biel Hospital Centre, Biel, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Tatjana Meyer-Heim
- Zurichs Municipal Hospital, Waid, University Geriatric Clinic, Zurich, Switzerland
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Rabl M, Clark C, Dayon L, Popp J. Neuropsychiatric symptoms in cognitive decline and Alzheimer's disease: biomarker discovery using plasma proteomics. J Neurol Neurosurg Psychiatry 2025; 96:370-382. [PMID: 39288961 PMCID: PMC12015082 DOI: 10.1136/jnnp-2024-333819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 08/07/2024] [Indexed: 09/19/2024]
Abstract
BACKGROUND AND OBJECTIVES Neuropsychiatric symptoms (NPS) are common in older people with cognitive impairment and Alzheimer's disease (AD). No biomarkers to detect the related pathology or predict the clinical evolution of NPS are available yet. This study aimed to identify plasma proteins that may serve as biomarkers for NPS and NPS-related clinical disease progression. METHODS A panel of 190 plasma proteins was quantified using Luminex xMAP in the Alzheimer's Disease Neuroimaging Initiative cohort. NPS and cognitive performance were assessed at baseline and after 1 and 2 years. Logistic regression, receiver operating characteristic analysis and cross-validation were used to address the relations of interest. RESULTS A total of 507 participants with mild cognitive impairment (n=396) or mild AD dementia (n=111) were considered. Selected plasma proteins improved the prediction of NPS (area under the curve (AUC) from 0.61 to 0.76, p<0.001) and future NPS (AUC from 0.63 to 0.80, p<0.001) when added to a reference model. Distinct protein panels were identified for single symptoms. Among the selected proteins, ANGT, CCL1 and IL3 were associated with NPS at all three time points while CCL1, serum glutamic oxaloacetic transaminase and complement factor H were also associated with cognitive decline. The associations were independent of the presence of cerebral AD pathology as assessed using cerebrospinal fluid biomarkers. CONCLUSIONS Plasma proteins are associated with NPS and improve prediction of future NPS.
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Affiliation(s)
- Miriam Rabl
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Psychiatric University Hospital, Zurich, Switzerland
| | - Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Psychiatric University Hospital, Zurich, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, Lausanne, Switzerland
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Psychiatric University Hospital, Zurich, Switzerland
- Old-Age Psychiatry Service, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
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Rabl M, Zullo L, Lewczuk P, Kornhuber J, Karikari TK, Blennow K, Zetterberg H, Bavato F, Quednow BB, Seifritz E, von Gunten A, Clark C, Popp J. Plasma neurofilament light, glial fibrillary acid protein, and phosphorylated tau 181 as biomarkers for neuropsychiatric symptoms and related clinical disease progression. Alzheimers Res Ther 2024; 16:165. [PMID: 39054505 PMCID: PMC11270946 DOI: 10.1186/s13195-024-01526-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS One hundred and fifty-one participants with normal cognition (n = 76) or mild cognitive impairment (n = 75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Different regression and ROC analyses were used to address the associations of interest. RESULTS None of the three plasma biomarker was associated with NPS at baseline. Higher GFAP levels were associated with the presence of NPS at follow-up (OR = 2.8, p = .002) and both, higher NfL and higher GFAP with an increase in the NPI-Q severity score over time (β = 0.25, p = .034 and β = 0.30, p = .013, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.72 to 0.88, p = .002) and AD pathology (AUC 0.78 to 0.87, p = .010), but not of cognitive decline (AUC 0.79 to 0.85, p = .081). CONCLUSION Plasma NfL and GFAP are both associated with future NPS and NPS severity change. Considering the presence of NPS along with blood-based AD-biomarkers may improve the prediction of clinical progression of NPS over time and inform clinical decision-making in non-demented older people.
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Affiliation(s)
- Miriam Rabl
- Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Lenggstrasse 31, Zurich, 8032, Switzerland.
| | - Leonardo Zullo
- Old-Age Psychiatry Service, Department of Psychiatry, Lausanne University Hospital, Lausanne, 1005, Switzerland
- Leenaards Memory Clinic, Lausanne University Hospital, Lausanne, 1005, Switzerland
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, 91054, Erlangen, Germany
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, Białystok, 15-269, Poland
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, 91054, Erlangen, Germany
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 41, Sweden
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15219, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 41, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 41, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1E 6BT, UK
- UK Dementia Research Institute at University College London, London, W1T 7NF, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, 999077, China
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Francesco Bavato
- Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Lenggstrasse 31, Zurich, 8032, Switzerland
- Experimental and Clinical Pharmacopsychology, Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, 8032, Switzerland
| | - Boris B Quednow
- Experimental and Clinical Pharmacopsychology, Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, 8032, Switzerland
- Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, 8057, Switzerland
| | - Erich Seifritz
- Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Lenggstrasse 31, Zurich, 8032, Switzerland
| | - Armin von Gunten
- Old-Age Psychiatry Service, Department of Psychiatry, Lausanne University Hospital, Lausanne, 1005, Switzerland
| | - Christopher Clark
- Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Lenggstrasse 31, Zurich, 8032, Switzerland
| | - Julius Popp
- Department of Adult Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Lenggstrasse 31, Zurich, 8032, Switzerland
- Old-Age Psychiatry Service, Department of Psychiatry, Lausanne University Hospital, Lausanne, 1005, Switzerland
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Chen Z, Wang X, Teng Z, Liu M, Liu F, Huang J, Liu Z. Modifiable lifestyle factors influencing psychiatric disorders mediated by plasma proteins: A systemic Mendelian randomization study. J Affect Disord 2024; 350:582-589. [PMID: 38246286 DOI: 10.1016/j.jad.2024.01.169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 01/13/2024] [Accepted: 01/16/2024] [Indexed: 01/23/2024]
Abstract
BACKGROUND Psychiatric disorders are emerging as a serious public health hazard, influencing an increasing number of individuals worldwide. However, the effect of modifiable lifestyle factors on psychiatric disorders remains unclear. METHODS Genome-wide association studies (GWAS) summary statistics were obtained mainly from Psychiatric Genomics Consortium and UK Biobank, with sample sizes varying between 10,000 and 1,200,000. The two-sample Mendelian randomization (MR) method was applied to investigate the causal associations between 45 lifestyle factors and 13 psychiatric disorders, and screen potential mediator proteins from 2992 candidate plasma proteins. We implemented a four-step framework with step-by-step screening incorporating two-step, univariable, and multivariable MR. RESULTS We found causal effects of strenuous sports or other exercise on Tourette's syndrome (OR [95%CI]: 0.0047 [5.24E-04-0.042]); lifelong smoking index on attention-deficit hyperactivity disorder (10.53 [6.96-15.93]), anxiety disorders (3.44 [1.95-6.05]), bipolar disorder (BD) (2.25 [1.64-3.09]), BD II (2.89 [1.81-4.62]), and major depressive disorder (MDD) (2.47 [1.90-3.20]); and educational years on anorexia nervosa (AN) (1.47 [1.22-1.76]), and MDD (0.74 [0.66-0.83]). Five proteins were found to have causal associations with psychiatric disorders, namely ADH1B, GHDC, STOM, CD226, and TP63. STOM, a membrane protein deficient in the erythrocytes of hereditary stomatocytosis patients, may mediate the effect of educational attainment on AN. LIMITATIONS The mechanisms underlying the effects of lifestyle factors on psychiatric disorders require further investigation. CONCLUSIONS These findings could help assess the risk of psychiatric disorders based on lifestyle factors and also support lifestyle interventions as a prevention strategy for mental illness.
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Affiliation(s)
- Zhuohui Chen
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hypothalamic Pituitary Research Centre, Xiangya Hospital, Central South University, Changsha, China
| | - Xiang Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hypothalamic Pituitary Research Centre, Xiangya Hospital, Central South University, Changsha, China
| | - Ziwei Teng
- National Clinical Research Centre for Mental Disorders, Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Psychiatry, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Mengdong Liu
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Fangkun Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hypothalamic Pituitary Research Centre, Xiangya Hospital, Central South University, Changsha, China
| | - Jing Huang
- National Clinical Research Centre for Mental Disorders, Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Psychiatry, Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hypothalamic Pituitary Research Centre, Xiangya Hospital, Central South University, Changsha, China.
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Rabl M, Zullo L, Lewczuk P, Kornhuber J, Karikari TK, Blennow K, Zetterberg H, Bavato F, Quednow BB, Seifritz E, von Gunten A, Clark C, Popp J. Plasma neurofilament light, glial fibrillary acid protein, and phosphorylated tau 181 as biomarkers for neuropsychiatric symptoms and related clinical disease progression. RESEARCH SQUARE 2024:rs.3.rs-4116836. [PMID: 38562890 PMCID: PMC10984087 DOI: 10.21203/rs.3.rs-4116836/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS One hundred and fifty-one participants with normal cognition (n=76) or mild cognitive impairment (n=75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Linear regression and ROC analyses were used to address the associations of interest. RESULTS Higher GFAP levels were associated with NPS at baseline (β=0.23, p=.008). Higher NfL and GFAP levels were associated with the presence of NPS at follow-up (β=0.29, p=.007 and β=0.28, p=.007, respectively) and with an increase in the NPI-Q severity score over time (β=0.23, p=.035 and β=0.27, p=.011, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.73 to 0.84, p=.007) and AD pathology (AUC 0.79 to 0.86, p=.006), but not of cognitive decline (AUC 0.79 to 0.84, p=.068). CONCLUSION Plasma GFAP is associated with NPS while NfL and GFAP are both associated with future NPS and NPS severity. Considering the presence of NPS along with blood-based AD-biomarkers may improve diagnosis and prediction of clinical progression of NPS and inform clinical decision-making in non-demented older people.
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Affiliation(s)
- Miriam Rabl
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich
| | - Leonardo Zullo
- Department of Psychiatry, Old Age Psychiatry Service, Lausanne University Hospital
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg
| | - Francesco Bavato
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich
| | - Boris B Quednow
- Experimental and Clinical Pharmacopsychology, Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich
| | - Erich Seifritz
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich
| | - Armin von Gunten
- Department of Psychiatry, Old Age Psychiatry Service, Lausanne University Hospital
| | - Christopher Clark
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich
| | - Julius Popp
- Department of Adult Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich
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Ouanes S, Rabl M, Clark C, Kirschbaum C, Popp J. Persisting neuropsychiatric symptoms, Alzheimer's disease, and cerebrospinal fluid cortisol and dehydroepiandrosterone sulfate. Alzheimers Res Ther 2022; 14:190. [PMID: 36529757 PMCID: PMC9762003 DOI: 10.1186/s13195-022-01139-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 12/06/2022] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Neuropsychiatric symptoms are important treatment targets in the management of dementia and can be present at very early clinical stages of neurodegenerative diseases. Increased cortisol has been reported in Alzheimer's disease (AD) and has been associated with faster cognitive decline. Elevated cortisol output has been observed in relation to perceived stress, depression, and anxiety. Dehydroepiandrosterone sulfate (DHEAS) has known anti-glucocorticoid effects and may counter the effects of cortisol. OBJECTIVES We aimed to examine whether CSF cortisol and DHEAS levels were associated with (1) neuropsychiatric symptoms at baseline, (2) changes in neuropsychiatric symptoms over 3 years, and (3) whether these associations were related to or independent of AD pathology. METHODS One hundred and eighteen participants on a prospective study in a memory clinic setting, including patients with cognitive impairment (n = 78), i.e., mild cognitive impairment or mild dementia, and volunteers with normal cognition (n = 40), were included. Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q). CSF cortisol and DHEAS, as well as CSF AD biomarkers, were obtained at baseline. Neuropsychiatric symptoms were re-assessed at follow-up visits 18 and 36 months from baseline. We constructed linear regression models to examine the links between baseline neuropsychiatric symptoms, the presence of AD pathology as indicated by CSF biomarkers, and CSF cortisol and DHEAS. We used repeated-measures mixed ANCOVA models to examine the associations between the neuropsychiatric symptoms' changes over time, baseline CSF cortisol and DHEAS, and AD pathology. RESULTS Higher CSF cortisol was associated with higher NPI-Q severity scores at baseline after controlling for covariates including AD pathology status (B = 0.085 [0.027; 0.144], p = 0.027; r = 0.277). In particular, higher CSF cortisol was associated with higher baseline scores of depression/dysphoria, anxiety, and apathy/indifference. Elevated CSF cortisol was also associated with more marked increase in NPI-Q scores over time regardless of AD status (p = 0.036, η2 = 0.207), but this association was no longer significant after controlling for BMI and the use of psychotropic medications. CSF DHEAS was associated neither with NPI-Q scores at baseline nor with their change over time. Cortisol did not mediate the association between baseline NPI-Q and changes in clinical dementia rating sum of boxes over 36 months. CONCLUSION Higher CSF cortisol may reflect or contribute to more severe neuropsychiatric symptoms at baseline, as well as more pronounced worsening over 3 years, independently of the presence of AD pathology. Our findings also suggest that interventions targeting the HPA axis may be helpful to treat neuropsychiatric symptoms in patients with dementia.
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Affiliation(s)
- Sami Ouanes
- grid.8515.90000 0001 0423 4662Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland ,grid.413548.f0000 0004 0571 546XDepartment of Psychiatry, Hamad Medical Corporation, PO BOX 3050, Doha, Qatar
| | - Miriam Rabl
- grid.412004.30000 0004 0478 9977Centre for Gerontopsychiatric Medicine, Department of Geriatric Psychiatry, University Hospital of Psychiatry, Minervastrasse 145, P.O. Box 341, 8032 Zurich, Switzerland
| | - Christopher Clark
- grid.412004.30000 0004 0478 9977Centre for Gerontopsychiatric Medicine, Department of Geriatric Psychiatry, University Hospital of Psychiatry, Minervastrasse 145, P.O. Box 341, 8032 Zurich, Switzerland
| | - Clemens Kirschbaum
- grid.4488.00000 0001 2111 7257Biopsychology, Technische Universität Dresden, Andreas Schubert Bau, Dresden, Germany
| | - Julius Popp
- grid.8515.90000 0001 0423 4662Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977Centre for Gerontopsychiatric Medicine, Department of Geriatric Psychiatry, University Hospital of Psychiatry, Minervastrasse 145, P.O. Box 341, 8032 Zurich, Switzerland
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Clark C, Rabl M, Dayon L, Popp J. The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease. Front Aging Neurosci 2022; 14:1065904. [PMID: 36570537 PMCID: PMC9768448 DOI: 10.3389/fnagi.2022.1065904] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022] Open
Abstract
Beyond the core features of Alzheimer's disease (AD) pathology, i.e. amyloid pathology, tau-related neurodegeneration and microglia response, multiple other molecular alterations and pathway dysregulations have been observed in AD. Their inter-individual variations, complex interactions and relevance for clinical manifestation and disease progression remain poorly understood, however. Heterogeneity at both pathophysiological and clinical levels complicates diagnosis, prognosis, treatment and drug design and testing. High-throughput "omics" comprise unbiased and untargeted data-driven methods which allow the exploration of a wide spectrum of disease-related changes at different endophenotype levels without focussing a priori on specific molecular pathways or molecules. Crucially, new methodological and statistical advances now allow for the integrative analysis of data resulting from multiple and different omics methods. These multi-omics approaches offer the unique advantage of providing a more comprehensive characterisation of the AD endophenotype and to capture molecular signatures and interactions spanning various biological levels. These new insights can then help decipher disease mechanisms more deeply. In this review, we describe the different multi-omics tools and approaches currently available and how they have been applied in AD research so far. We discuss how multi-omics can be used to explore molecular alterations related to core features of the AD pathologies and how they interact with comorbid pathological alterations. We further discuss whether the identified pathophysiological changes are relevant for the clinical manifestation of AD, in terms of both cognitive impairment and neuropsychiatric symptoms, and for clinical disease progression over time. Finally, we address the opportunities for multi-omics approaches to help discover novel biomarkers for diagnosis and monitoring of relevant pathophysiological processes, along with personalised intervention strategies in AD.
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Affiliation(s)
- Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zürich, Switzerland,Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,*Correspondence: Christopher Clark,
| | - Miriam Rabl
- Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,University of Lausanne, Lausanne, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zürich, Switzerland,Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
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