Cited by 46Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsCerebrospinal fluid and hydrocephalus

Matrix metalloproteinase 10 is linked to the risk of progression to dementia of the Alzheimer’s type

Open access
Martino Adami, Pamela V, Orellana, Adelina, García, Pablo, Kleineidam, Luca, Alarcón-Martín, Emilio, Montrreal, Laura, Aguilera, Nuria, Espinosa, Ana +38 more·2022·Brain

Abstract

Alzheimer’s disease has a long asymptomatic phase that offers a substantial time window for intervention. Using this window of opportunity will require early diagnostic and prognostic biomarkers to detect Alzheimer’s disease pathology at predementia stages, thus allowing identification of patients who will most probably progress to dementia of the Alzheimer’s type and benefit from specific disease-modifying therapies. Consequently, we searched for CSF proteins associated with disease progression along with the clinical disease staging. We measured the levels of 184 proteins in CSF samples from 556 subjective cognitive decline and mild cognitive impairment patients from three independent memory clinic longitudinal studies (Spanish ACE, n = 410; German DCN, n = 93; German Mannheim, n = 53). We evaluated the association between protein levels and clinical stage, and the effect of protein levels on the progression from mild cognitive impairment to dementia of the Alzheimer’s type. Mild cognitive impairment subjects with increased CSF level of matrix metalloproteinase 10 (MMP-10) showed a higher probability of progressing to dementia of the Alzheimer’s type and a faster cognitive decline. CSF MMP-10 increased the prediction accuracy of CSF amyloid-β 42 (Aβ42), phospho-tau 181 (P-tau181) and total tau (T-tau) for conversion to dementia of the Alzheimer’s type. Including MMP-10 to the [A/T/(N)] scheme improved considerably the prognostic value in mild cognitive impairment patients with abnormal Aβ42, but normal P-tau181 and T-tau, and in mild cognitive impairment patients with abnormal Aβ42, P-tau181 and T-tau. MMP-10 was correlated with age in subjects with normal Aβ42, P-tau181 and T-tau levels. Our findings support the use of CSF MMP-10 as a prognostic marker for dementia of the Alzheimer’s type and its inclusion in the [A/T/(N)] scheme to incorporate pathologic aspects beyond amyloid and tau. CSF level of MMP-10 may reflect ageing and neuroinflammation.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/brain/awac024

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Previous studies found increased levels of CSF MMP-10 in AD, as well as increased rates of disease progression in those with high CSF MMP-10 levels at baseline.

    “Regarding the role of MMP‐10 (matrix metalloproteinase 10) in preclinical AD, we note that previous studies found increased levels of CSF MMP‐10 in AD, as well as increased rates of disease progression in those with high CSF MMP‐10 levels at baseline (Martino Adami et al, 2022).”

    From The genetic regulation of protein expression in cerebrospinal fluid (2023) · cites this paper as Martino Adami et al, 2022

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 26

  1. Hampel H, O'Bryant SE, Molinuevo JL, et al. Blood-based biomar- kers for Alzheimer disease: Mapping the road to the clinic. Nat Rev Neurol. 2018;14(11):639-652.
  2. Zetterberg H, Bendlin BB. Biomarkers for Alzheimer's disease- Preparing for a new era of disease-modifying therapies. Mol Psychiatry. 2020;26:296-308.
  3. Jessen F, Amariglio RE, van Boxtel M, et al. A conceptual frame- work for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimers Dement. 2014;10(6):844-852.
  4. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: Clinical characterization and outcome. Arch Neurol. 1999;56:303-308.
  5. Mckhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: Recommendations from the national institute on aging-Alzheimer's association work- groups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7:263-269.
  6. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA work group under the auspices of de- partment of health and human services task force on Alzheimer's disease. Neurology. 1984;34:939-944.
  7. Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impair- ment-Beyond controversies, towards a consensus: report of the international working group on mild cognitive impairment. J Intern Med. 2004;256(3):240-246.
  8. Philipps V, Amieva H, Andrieu S, et al. Normalized mini-mental state examination for assessing cognitive change in population- based brain aging studies. Neuroepidemiology. 2014;43(1):15-25.
  9. Palmqvist S, Hertze J, Minthon L, et al. Comparison of brief cog- nitive tests and CSF biomarkers in predicting Alzheimer's dis- ease in mild cognitive impairment: Six-year follow-up study. PLoS ONE. 2012;7:e38639.
  10. Glorioso CA, Pfenning AR, Lee SS, et al. Rate of brain aging and APOE ɛ4 are synergistic risk factors for Alzheimer's disease. Life Sci Alliance. 2019;2(3):e201900303.
  11. Jack CR, Hampel HJ, Universities S, Cu M, Petersen RC. A new classification system for AD, independent of cognition A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology. 2016;87:539-547.
  12. Sternlicht MD, Werb Z. How matrix metalloproteinases regulate cell behavior. Annu Rev Cell Dev Biol. 2001;17:463-516.
  13. Thorns V, Walter GF, Thorns C. Expression of MMP-2. MMP;7, MMP-9, MMP-10 and MMP-11 in human astrocytic and oligo- dendroglial gliomas. Anticancer Res. 2003;23:3937-3944.
  14. Nuttall RK, Silva C, Hader W, et al. Metalloproteinases are en- riched in microglia compared with leukocytes and they regulate cytokine levels in activated microglia. Glia. 2007;55:516-526.
  15. Yan P, Hu X, Song H, et al. Matrix metalloproteinase-9 degrades amyloid-β fibrils in vitro and compact plaques in situ. J Biol Chem. 2006;281(34):24566-24574.
  16. Bjerke M, Zetterberg H, Edman Å, Blennow K, Wallin A, Andreasson U. Cerebrospinal fluid matrix metalloprotei- nases and tissue inhibitor of metalloproteinases in combin- ation with subcortical and cortical biomarkers in vascular dementia and Alzheimer's disease. J Alzheimers Dis. 2011; 27:665-676.
  17. Craig-Schapiro R, Kuhn M, Xiong C, et al. Multiplexed immuno- assay panel identifies novel CSF biomarkers for Alzheimer's dis- ease diagnosis and prognosis. PLoS ONE. 2011;6:e18850.
  18. Duits FH, Hernandez-Guillamon M, Montaner J, et al. Matrix me- talloproteinases in Alzheimer's disease and concurrent cere- bral microbleeds. J Alzheimers Dis. 2015;48(3):711-720.
  19. Lago JC, Puzzi MB. The effect of aging in primary human dermal fibroblasts. PLoS ONE. 2019;14(7):e0219165.
  20. Mora-Gutiérrez JM, Rodríguez JA, Fernández-Seara MA, et al. MMP-10 is increased in early stage diabetic kidney disease and can be reduced by renin-angiotensin system blockade. Sci Rep. 2020;10(1):1-12.
  21. Montero I, Orbe J, Varo N, et al. C-reactive protein induces matrix metalloproteinase-1 and -10 in human endothelial cells: Implications for clinical and subclinical atherosclerosis. J Am Coll Cardiol. 2006;47(7):1369-1378.
  22. Santaella A, Kuiperij HB, Van Rumund A, et al. Inflammation biomarker discovery in Parkinson's disease and atypical parkin- sonisms. BMC Neurol. 2020;20(1):26.
  23. Tchkonia T, Zhu Y, Van Deursen J, Campisi J, Kirkland JL. Cellular senescence and the senescent secretory phenotype: Therapeutic opportunities. J Clin Invest. 2013;123(3):966-972.
  24. Lye JJ, Latorre E, Lee BP, et al. Astrocyte senescence may drive al- terations in GFAPα. CDK:N2A. p14 ARF, and TAU3 transcript ex- pression and contribute to cognitive decline. GeroScience. 2019; 41(5):561-573.
  25. Heneka MT, McManus RM, Latz E. Inflammasome signalling in brain function and neurodegenerative disease. Nat Rev Neurosci. 2018;19(10):610-621.
  26. Sidoryk-Wegrzynowicz M, Wegrzynowicz M, Lee E, Bowman AB, Aschner M. Role of astrocytes in brain function and disease. Toxicol Pathol. 2011;39(1):115-123.

Cited by

Sorted by citations

Authors
Martino Adami, P. V., Orellana, A., García, P., Kleineidam, L., Alarcón-Martín, E., Montrreal, L., Aguilera, N., Espinosa, A., Abdelnour, C., Rosende-Roca, M., Pablo Tartari, J., Vargas, L., Mauleón, A., Esteban-De Antonio, E., López-Cuevas, R., Dalmasso, M. C., Campos Martin, R., Parveen, K., Andrade Fuentes, V. M., Amin, N., Ahmad, S., Ikram, M. A., Lewczuk, P., Kornhuber, J., Peters, O., Frölich, L., Rüther, E., Wiltfang, J., Tarraga, L., Boada, M., Maier, W., de Rojas, I., Cano, A., Sanabria, A., Alegret, M., Hernández, I., Marquié, M., Valero, S., van Duijn, C. M., Wagner, M., Jessen, F., Schneider, A., Sáez Goñi, M. E., González Pérez, A., Ruiz, A., & Ramírez, A.
Affiliations
  • Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne , 50937 Cologne , Germany
  • Instituto de Salud Carlos III (ES)
  • Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, International University of Catalonia , 8029 Barcelona , Spain
  • University of Bonn (DE)
  • Universitat Internacional de Catalunya (ES)
  • University of Cologne (DE)
  • University of Oxford (GB)
  • Erasmus MC (NL)
  • Medical University of Białystok (PL)
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
  • Charité – Universitätsmedizin Berlin (DE)
  • Heidelberg University (DE)
  • Universitätsmedizin Göttingen (DE)
  • German Center for Neurodegenerative Diseases (DE)
  • Department of Epidemiology, Erasmus MC , 3015 GD Rotterdam , The Netherlands
  • Andalusian Bioinformatics Research Centre (CAEBi) , 41013 Seville , Spain
Venue
Brain
Published
2022-01-27
Volume
145
Issue
7
Pages
2507-2517
ISSN
  • 0006-8950 (ISSN-L)
  • 1460-2156
OpenAlex
W4210274422
Cited by
46
References
7
Citations by year
2026: 13 · 2025: 12 · 2024: 7 · 2023: 12 · 2022: 2
FWCI
5.26
Type
journal article
Language
en
Open access
Locations
  • Brain (publishedVersion)
  • PubMed (publishedVersion)
  • Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • DZNE Pub (submittedVersion)
Funders
  • German Federal Ministry of Education and Research (01GI0102, 01GI0420, 01GI0422, 01GI0423, 01GI0429, 01GI0431, 01GI0433, 01GI0434, 01ED2007A)
  • European Union’s Horizon 2020 (115975)
  • Grifols, Life Molecular Imaging, Araclon Biotech, Alkahest, Laboratorio de análisis Echevarne and IrsiCaixa
  • ISCIII (PI13/02434, PI16/01861, PI19/01301)
  • Fondo Europeo de Desarrollo Regional
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Cerebrospinal fluid and hydrocephalus
Keywords
matrix metalloproteinase-10, Alzheimer's disease, mild cognitive impairment, subjective cognitive decline, cerebrospinal fluid biomarkers, conversion to dementia, amyloid-beta 42, total tau, cognitive decline, neuroinflammation, aging, disease-modifying therapy
MeSH terms
Alzheimer Disease, Humans, Longitudinal Studies, Peptide Fragments, Biomarkers, Amyloid beta-Peptides, tau Proteins, Disease Progression, Matrix Metalloproteinase 10, Cognitive Dysfunction

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review