Low blood carotenoid status in dementia and mild cognitive impairment: A systematic review and meta-analysis

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Abstract

Background

Given their potent antioxidation properties, carotenoids play a role in delaying and preventing dementia and mild cognitive impairment (MCI). However, observational studies have found inconsistent results regarding the associations between blood carotenoid levels and the risk of dementia and MCI. We conducted this systematic review and meta-analysis to investigate the relationship between blood carotenoid levels and the risk of dementia and MCI.

Methods

A systematic search was performed in the Web of Science, PubMed, Embase, and Cochrane Library electronic databases to retrieve relevant English articles published from their inception until February 23, 2023. Study quality was assessed by the Newcastle-Ottawa scale. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were pooled using random-effect meta-analyses. Ultimately, 23 studies (n = 6610) involving 1422 patients with dementia, 435 patients with MCI, and 4753 controls were included.

Results

Our meta-analysis showed that patients with dementia had lower blood lycopene (SMD: -0.521; 95%CI: -0.741, -0.301), α-carotene (SMD: -0.489; 95%CI: -0.697, -0.281), β-carotene (SMD: -0.476; 95%CI: -0.784, -0.168), lutein (SMD: -0.516; 95%CI: -0.753, -0.279), zeaxanthin (SMD: -0.571; 95%CI: -0.910, -0.232) and β-cryptoxanthin (SMD: -0.617; 95%CI: -0.953, -0.281) than the controls. Our results indicated that blood carotenoid levels were significantly lower in patients with dementia than in controls, despite high heterogeneity across the studies. Owing to insufficient data, we did not observe a similar and stable relationship between blood carotenoid levels and MCI.

Conclusions

Our meta-analysis indicated that lower blood carotenoid levels may be a risk factor for dementia and MCI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-023-03900-7.

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Most cited references 56

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Quantifying heterogeneity in a meta-analysis.

Julian P T Higgins, Simon G Thompson (2002)

The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.

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Is Open Access

NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

Clifford R. Jack, David Bennett, Kaj Blennow … (2018)

In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

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Author and article information

Contributors

Qinghua Jiang: lnzyjqh2002@163.com

Journal

Journal ID (nlm-ta): BMC Geriatr

Journal ID (iso-abbrev): BMC Geriatr

Title: BMC Geriatrics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2318

Publication date (Electronic): 30 March 2023

Publication date PMC-release: 30 March 2023

Publication date Collection: 2023

Volume: 23

Electronic Location Identifier: 195

Affiliations

[1 ]GRID grid.412449.e, ISNI 0000 0000 9678 1884, School of Pharmacy, , China Medical University, ; Shenyang, China

[2 ]GRID grid.412467.2, ISNI 0000 0004 1806 3501, Department of Pharmacy, , Shengjing Hospital of China Medical University, ; Shenyang, China

Article

Publisher ID: 3900

DOI: 10.1186/s12877-023-03900-7

PMC ID: 10064563

PubMed ID: 36997905

SO-VID: b8b45a7d-bbd9-46a7-9069-8c2d8fffa932

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 8 August 2022

Date accepted : 16 March 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 81703405

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ScienceOpen disciplines: Geriatric medicine

Keywords: blood carotenoid levels,dementia,mild cognitive impairment,meta-analysis,systematic review

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ScienceOpen disciplines: Geriatric medicine

Keywords: blood carotenoid levels, dementia, mild cognitive impairment, meta-analysis, systematic review

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Low blood carotenoid status in dementia and mild cognitive impairment: A systematic review and meta-analysis

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Abstract

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Supplementary Information

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Karger: Neurology and Neuroscience

Most cited references 56

Bias in meta-analysis detected by a simple, graphical test

Quantifying heterogeneity in a meta-analysis.

NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

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