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Transition rates between amyloid and neurodegeneration biomarker states and to dementia: a population-based, longitudinal cohort study

Overview of attention for article published in Lancet Neurology, November 2015
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45

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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

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5 news outlets
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10 X users
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1 patent

Citations

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108 Dimensions

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251 Mendeley
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1 CiteULike
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Title
Transition rates between amyloid and neurodegeneration biomarker states and to dementia: a population-based, longitudinal cohort study
Published in
Lancet Neurology, November 2015
DOI 10.1016/s1474-4422(15)00323-3
Pubmed ID
Authors

Clifford R Jack, Terry M Therneau, Heather J Wiste, Stephen D Weigand, David S Knopman, Val J Lowe, Michelle M Mielke, Prashanthi Vemuri, Rosebud O Roberts, Mary M Machulda, Matthew L Senjem, Jeffrey L Gunter, Walter A Rocca, Ronald C Petersen

Abstract

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. 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. 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. 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. National Institute on Aging, Alexander Family Professorship of Alzheimer's Disease Research, the GHR Foundation.

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Geographical breakdown

Country Count As %
United States 4 2%
United Kingdom 2 <1%
Germany 1 <1%
Austria 1 <1%
France 1 <1%
Italy 1 <1%
Australia 1 <1%
Unknown 240 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 20%
Researcher 45 18%
Student > Master 27 11%
Student > Bachelor 22 9%
Other 19 8%
Other 45 18%
Unknown 42 17%
Readers by discipline Count As %
Medicine and Dentistry 61 24%
Neuroscience 38 15%
Psychology 28 11%
Agricultural and Biological Sciences 15 6%
Biochemistry, Genetics and Molecular Biology 9 4%
Other 41 16%
Unknown 59 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 45. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 June 2020.
All research outputs
#923,523
of 25,547,904 outputs
Outputs from Lancet Neurology
#583
of 4,040 outputs
Outputs of similar age
#15,166
of 393,447 outputs
Outputs of similar age from Lancet Neurology
#9
of 79 outputs
Altmetric has tracked 25,547,904 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,040 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.6. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,447 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.