Transition rates between amyloid and neurodegeneration biomarker states and to dementia: a population-based, longitudinal cohort study
Open accessAbstract
Background In a 2014 cross-sectional analysis, we showed that amyloid and neurodegeneration biomarker states in participants with no clinical impairment varied greatly with age, suggesting dynamic within-person processes. In this longitudinal study, we aimed to estimate rates of transition from a less to a more abnormal biomarker state by age in individuals without dementia, as well as to assess rates of transition to dementia from an abnormal state.Methods Participants from the Mayo Clinic Study of Aging (Olmsted County, MN, USA) without dementia at baseline were included in this study, a subset of whom agreed to multimodality imaging. Amyloid PET (with (11)C-Pittsburgh compound B) was used to classify individuals as amyloid positive (A(+)) or negative (A(-)). (18)F-fluorodeoxyglucose ((18)F-FDG)-PET and MRI were used to classify individuals as neurodegeneration positive (N(+)) or negative (N(-)). We used all observations, including those from participants who did not have imaging results, to construct a multistate Markov model to estimate four different age-specific biomarker state transition rates: A(-)N(-) to A(+)N(-); A(-)N(-) to A(-)N(+) (suspected non-Alzheimer's pathology); A(+)N(-) to A(+)N(+); and A(-)N(+) to A(+)N(+). We also estimated two age-specific rates to dementia: A(+)N(+) to dementia and A(-)N(+) to dementia. Using these state-to-state transition rates, we estimated biomarker state frequencies by age.Findings At baseline (between Nov 29, 2004, to March 7, 2015), 4049 participants did not have dementia (3512 [87%] were clinically normal and 537 [13%] had mild cognitive impairment). 1541 individuals underwent imaging between March 28, 2006, to April 30, 2015. Transition rates were low at age 50 years and, with one exception, exponentially increased with age. At age 85 years compared with age 65 years, the rate was nearly 11-times higher (17.2 vs 1.6 per 100 person-years) for the transition from A(-)N(-) to A(-)N(+), three-times higher (20.8 vs 6.1) for A(+)N(-) to A(+)N(+), and five-times higher (13.2 vs 2.6) for A(-)N(+) to A(+)N(+). The rate of transition was also increased at age 85 years compared with age 65 years for A(+)N(+) to dementia (7.0 vs 0.8) and for A(-)N(+) to dementia (1.7 vs 0.6). The one exception to an exponential increase with age was the transition rate from A(-)N(-) to A(+)N(-), which increased from 4.0 transitions per 100 person-years at age 65 years to 6.9 transitions per 100 person-years at age 75 and then plateaued beyond that age. Estimated biomarker frequencies by age from the multistate model were similar to cross-sectional biomarker frequencies.Interpretation Our transition rates suggest that brain ageing is a nearly inevitable acceleration toward worse biomarker and clinical states. The one exception is the transition to amyloidosis without neurodegeneration, which is most dynamic from age 60 years to 70 years and then plateaus beyond that age. We found that simple transition rates can explain complex, highly interdependent biomarker state frequencies in our population.Funding National Institute on Aging, Alexander Family Professorship of Alzheimer's Disease Research, the GHR Foundation.
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Multi-state modeling can estimate Alzheimer's disease duration from stage progression and mortality rates without requiring very long follow-up.
“We estimated disease duration by applying a multi-state modeling approach, which has been previously used in AD research [22-25], and can offer an estimate of disease duration based on stage progression and mortality rates in the absence of very long follow-up duration.”
From Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and <i>APOE</i> genotype (2019) · cites this paper as [22]
The potential violation of the independence assumption was addressed by taking age as a time-dependent covariate.
“This was addressed by taking age as the time-dependent covariate, which has been applied before to overcome this issue [22, 47].”
From Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and <i>APOE</i> genotype (2019) · cites this paper as [22]
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- Authors
- Jack, C. R., Therneau, T. M., Wiste, H. J., Weigand, S. D., Knopman, D. S., Lowe, V. J., Mielke, M. M., Vemuri, P., Roberts, R. O., Machulda, M. M., Senjem, M. L., Gunter, J. L., Rocca, W. A., & Petersen, R. C.
- Affiliations
- Mayo Clinic (US)
- Corresponding author
- Jack, Clifford R
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 15
- Issue
- 1
- Pages
- 56-64
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC4784263
- OpenAlex
- W2178393107
- Cited by
- 129
- References
- 36
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 8 · 2023: 4 · 2022: 9 · 2021: 9 · 2020: 13 · 2019: 13 · 2018: 24 · 2017: 21 · 2016: 16 · 2015: 1
- FWCI
- 16.68
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- Funders
- Mayo Clinic
- National Institutes of Health (5u01ag024904-10)
- National Institute on Aging (U01-AG-024904, R01AG034676, P50AG044170, R01AG043392, R21AG045228, U01AG006786, U01AG24904, R01AG011378, R01AG031750, R01AG037551, R01AG041851, P50AG016574)
- National Heart, Lung, and Blood Institute (R01HL120859, U01HL096917)
- National Cancer Institute (R01CA163803, R01CA107476, R01CA168762, P30CA015083)
- National Institute of Nursing Research (R01NR015259)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR027065, R01AR046849)
- National Institute of Biomedical Imaging and Bioengineering (R01EB016966)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
- Keywords
- amyloid PET, neurodegeneration biomarkers, dementia risk, multi-state Markov model, Alzheimer's disease, mild cognitive impairment, 11C-Pittsburgh compound B, 18F-FDG PET, brain MRI, Mayo Clinic Study of Aging, preclinical Alzheimer's disease
- MeSH terms
- Aged, Aged, 80 and over, Cross-Sectional Studies, Dementia, Female, Humans, Longitudinal Studies, Male, Middle Aged, Population Surveillance, Cohort Studies, Biomarkers, Disease Progression, Neurodegenerative Diseases, Plaque, Amyloid, Cognitive Dysfunction
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