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Daniilidou M, Eroli F, Alanko V, Goikolea J, Latorre-Leal M, Rodriguez-Rodriguez P, Griffiths WJ, Wang Y, Pacciarini M, Brinkmalm A, Zetterberg H, Blennow K, Rosenberg A, Bogdanovic N, Winblad B, Kivipelto M, Ibghi D, Cedazo-Minguez A, Maioli S, Matton A. Alzheimer's disease biomarker profiling in a memory clinic cohort without common comorbidities. Brain Commun 2023; 5:fcad228. [PMID: 37680670 PMCID: PMC10481253 DOI: 10.1093/braincomms/fcad228] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 05/17/2023] [Accepted: 08/24/2023] [Indexed: 09/09/2023] Open
Abstract
Alzheimer's disease is a multifactorial disorder with large heterogeneity. Comorbidities such as hypertension, hypercholesterolaemia and diabetes are known contributors to disease progression. However, less is known about their mechanistic contribution to Alzheimer's pathology and neurodegeneration. The aim of this study was to investigate the relationship of several biomarkers related to risk mechanisms in Alzheimer's disease with the well-established Alzheimer's disease markers in a memory clinic population without common comorbidities. We investigated 13 molecular markers representing key mechanisms underlying Alzheimer's disease pathogenesis in CSF from memory clinic patients without diagnosed hypertension, hypercholesterolaemia or diabetes nor other neurodegenerative disorders. An analysis of covariance was used to compare biomarker levels between clinical groups. Associations were analysed by linear regression. Two-step cluster analysis was used to determine patient clusters. Two key markers were analysed by immunofluorescence staining in the hippocampus of non-demented control and Alzheimer's disease individuals. CSF samples from a total of 90 participants were included in this study: 30 from patients with subjective cognitive decline (age 62.4 ± 4.38, female 60%), 30 with mild cognitive impairment (age 65.6 ± 7.48, female 50%) and 30 with Alzheimer's disease (age 68.2 ± 7.86, female 50%). Angiotensinogen, thioredoxin-1 and interleukin-15 had the most prominent associations with Alzheimer's disease pathology, synaptic and axonal damage markers. Synaptosomal-associated protein 25 kDa and neurofilament light chain were increased in mild cognitive impairment and Alzheimer's disease patients. Grouping biomarkers by biological function showed that inflammatory and survival components were associated with Alzheimer's disease pathology, synaptic dysfunction and axonal damage. Moreover, a vascular/metabolic component was associated with synaptic dysfunction. In the data-driven analysis, two patient clusters were identified: Cluster 1 had increased CSF markers of oxidative stress, vascular pathology and neuroinflammation and was characterized by elevated synaptic and axonal damage, compared with Cluster 2. Clinical groups were evenly distributed between the clusters. An analysis of post-mortem hippocampal tissue showed that compared with non-demented controls, angiotensinogen staining was higher in Alzheimer's disease and co-localized with phosphorylated-tau. The identification of biomarker-driven endophenotypes in cognitive disorder patients further highlights the biological heterogeneity of Alzheimer's disease and the importance of tailored prevention and treatment strategies.
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Affiliation(s)
- Makrina Daniilidou
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 83 Huddinge, Sweden
| | - Francesca Eroli
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
| | - Vilma Alanko
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 83 Huddinge, Sweden
| | - Julen Goikolea
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
| | - Maria Latorre-Leal
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
| | - Patricia Rodriguez-Rodriguez
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
| | | | - Yuqin Wang
- Swansea University Medical School, Swansea SA2 8PP, UK
| | | | - Ann Brinkmalm
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 413 90 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 90 Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 413 90 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 90 Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London WC1N3AR, UK
- UK Dementia Research Institute at UCL, London WC1N3AR, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 413 90 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 90 Mölndal, Sweden
| | - Anna Rosenberg
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, FI-70029 Kuopio, Finland
| | - Nenad Bogdanovic
- Theme Inflammation and Aging, Karolinska University Hospital, 141 83 Huddinge, Sweden
| | - Bengt Winblad
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 141 83 Huddinge, Sweden
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 83 Huddinge, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 141 83 Huddinge, Sweden
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London SW7 2AZ, UK
| | - Delphine Ibghi
- Neurodegeneration Cluster, Rare and Neurologic Disease Research Sanofi R&D, F-91380 Chilly-Mazarin, France
| | - Angel Cedazo-Minguez
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
- Neurodegeneration Cluster, Rare and Neurologic Disease Research Sanofi R&D, F-91380 Chilly-Mazarin, France
| | - Silvia Maioli
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
| | - Anna Matton
- Division of Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 64 Solna, Sweden
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 83 Huddinge, Sweden
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London SW7 2AZ, UK
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Liang Y, Ngandu T, Laatikainen T, Soininen H, Tuomilehto J, Kivipelto M, Qiu C. Cardiovascular health metrics from mid- to late-life and risk of dementia: A population-based cohort study in Finland. PLoS Med 2020; 17:e1003474. [PMID: 33320852 PMCID: PMC7737898 DOI: 10.1371/journal.pmed.1003474] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 11/09/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Very few studies have explored the patterns of cardiovascular health (CVH) metrics in midlife and late life in relation to risk of dementia. We examined the associations of composite CVH metrics from midlife to late life with risk of incident dementia. METHODS AND FINDINGS This cohort study included 1,449 participants from the Finnish Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) study, who were followed from midlife (baseline from1972 to 1987; mean age 50.4 years; 62.1% female) to late life (1998), and then 744 dementia-free survivors were followed further into late life (2005 to 2008). We defined and scored global CVH metrics based on 6 of the 7 components (i.e., smoking, physical activity, and body mass index [BMI] as behavioral CVH metrics; fasting plasma glucose, total cholesterol, and blood pressure as biological CVH metrics) following the modified American Heart Association (AHA)'s recommendations. Then, the composite global, behavioral, and biological CVH metrics were categorized into poor, intermediate, and ideal levels. Dementia was diagnosed following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. Data were analyzed with Cox proportional hazards and the Fine and Gray competing risk regression models. During the follow-up examinations, dementia was diagnosed in 61 persons in 1998 and additional 47 persons in 2005 to 2008. The fully adjusted hazard ratio (HR) of dementia was 0.71 (95% confidence interval [CI]: 0.43, 1.16; p = 0.174) and 0.52 (0.29, 0.93; p = 0.027) for midlife intermediate and ideal levels (versus poor level) of global CVH metrics, respectively; the corresponding figures for late-life global CVH metrics were 0.60 (0.22, 1.69; p = 0.338) and 0.91 (0.34, 2.41; p = 0.850). Compared with poor global CVH metrics in both midlife and late life, the fully adjusted HR of dementia was 0.25 (95% CI: 0.08, 0.86; p = 0.028) for people with intermediate global CVH metrics in both midlife and late life and 0.14 (0.02, 0.76; p = 0.024) for those with midlife ideal and late-life intermediate global CVH metrics. Having an intermediate or ideal level of behavioral CVH in both midlife and late life (versus poor level in both midlife and late life) was significantly associated with a lower dementia risk (HR range: 0.03 to 0.26; p < 0.05), whereas people with midlife intermediate and late-life ideal biological CVH metrics had a significantly increased risk of dementia (p = 0.031). Major limitations of this study include the lack of data on diet and midlife plasma glucose, high rate of attrition, as well as the limited power for certain subgroup analyses. CONCLUSIONS In this study, we observed that having the ideal CVH metrics, and ideal behavioral CVH metrics in particular, from midlife onwards is associated with a reduced risk of dementia as compared with people having poor CVH metrics. Maintaining life-long health behaviors may be crucial to reduce late-life risk of dementia.
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Affiliation(s)
- Yajun Liang
- Aging Research Center & Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Tiia Ngandu
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Clinical Geriatrics & Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden
| | - Tiina Laatikainen
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Joint Municipal Authority for North Karelia Social and Health Services (Siun Sote), Joensuu, Finland
| | - Hilkka Soininen
- Neurocenter, Department of Neurology, Kuopio University Hospital, Kuopio, Finland
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jaakko Tuomilehto
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Saudi Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia and Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Miia Kivipelto
- Division of Clinical Geriatrics & Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Neuroepidemiology and Ageing Research Unit, School of Public Health, Imperial College London, London, United Kingdom
- Stockholms Sjukhem, Research and Development Unit, Stockholm, Sweden
- * E-mail: (MK); (CQ)
| | - Chengxuan Qiu
- Aging Research Center & Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet and Stockholm University, Stockholm, Sweden
- * E-mail: (MK); (CQ)
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