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Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease
Franzmeier N, Dewenter A, Frontzkowski L, Dichgans M, Rubinski A, Neitzel J, Smith R, Strandberg O et al.. Science advances, 2020-11-27
Topic: Plasma and spinal-fluid biomarkers
In Alzheimer's disease (AD), the Braak staging scheme suggests a stereotypical tau spreading pattern that does, however, not capture interindividual variability in tau deposition. This complicates the prediction of tau spreading, which may become critical for defining individualized tau-PET readouts in clinical trials. Since tau is assumed to spread throughout connected regions, we used functional connectivity to improve tau spreading predictions over Braak staging methods. We included two samples with longitudinal tau-PET from controls and AD patients. Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences. Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters. A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage-specific readouts and reduced sample sizes by ~40% in simulated tau-targeting interventions. Thus, connectivity-based tau spreading models may show utility in clinical trials.
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APA 7th
Franzmeier, N., Dewenter, A., Frontzkowski, L., Dichgans, M., Rubinski, A., Neitzel, J., et al. (2020). Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease. Science advances. https://doi.org/10.1126/sciadv.abd1327
Vancouver
Franzmeier N, Dewenter A, Frontzkowski L, Dichgans M, Rubinski A, Neitzel J, et al. Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease. Science advances. 2020. doi:10.1126/sciadv.abd1327. PMID: 33246962.
BibTeX
@article{franzmeier2020-33246962,
author = {Franzmeier, N. and Dewenter, A. and Frontzkowski, L. and Dichgans, M. and Rubinski, A. and Neitzel, J. and Smith, R. and Strandberg, O. and others},
title = {{Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer's disease}},
journal = {Science advances},
year = {2020},
doi = {10.1126/sciadv.abd1327},
pmid = {33246962},
url = {https://doi.org/10.1126/sciadv.abd1327}
}
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Key findings
- Cross-sectionally, we found connectivity of tau epicenters (i.e., regions with earliest tau) to predict estimated tau spreading sequences.
- Longitudinally, we found tau accumulation rates to correlate with connectivity strength to patient-specific tau epicenters.
- A connectivity-based, patient-centered tau spreading model improved the assessment of tau accumulation rates compared to Braak stage-specific readouts and reduced sample sizes by ~40% in simulated tau-targeting interventions.
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Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 57/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 33 of the 58 points we could judge it on, which is 57 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Science advances) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2020 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 33246962) |
| Free to read | 2 / 2 | Free to read |
| Points | 33 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 33 of the 58 points we could judge it on is 57 out of 100. |
| Total | 57 / 100 | — |
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