This page is alzhub.org's plain-English summary of a published study, not the paper itself. It is generated from the record we hold for this study, sourced and linked below — check the original for the full text and methods.

54/100

✓ Peer-reviewed alzhub usefulness score 54 out of 100. Long-term cohort studies

Topic: Amyloid, tau and blood-test diagnosis

Individuals with Alzheimer's disease (AD) dementia exhibit significant heterogeneity across clinical symptoms, atrophy patterns, and spatial distribution of Tau deposition. Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain regions and cognitive tests. Here, we considered a data-driven hierarchical Bayesian model to identify latent factors from atrophy patterns and cognitive deficits simultaneously, thus exploiting the rich dimensionality within each modality.

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

APA 7th

Sun, N., Mormino, E. C., Chen, J., Sabuncu, M. R., Yeo, B. T. T., & Alzheimer’s Disease Neuroimaging Initiative. (2019). Multi-modal latent factor exploration of atrophy, cognitive and tau heterogeneity in Alzheimer's disease. NeuroImage. https://doi.org/10.1016/j.neuroimage.2019.116043

Vancouver

Sun N, Mormino EC, Chen J, Sabuncu MR, Yeo BTT, Alzheimer’s Disease Neuroimaging Initiative. Multi-modal latent factor exploration of atrophy, cognitive and tau heterogeneity in Alzheimer's disease. NeuroImage. 2019. doi:10.1016/j.neuroimage.2019.116043. PMID: 31344486.

BibTeX

@article{sun2019-31344486,
  author  = {Sun, N. and Mormino, E. C. and Chen, J. and Sabuncu, M. R. and Yeo, B. T. T. and {Alzheimer’s Disease Neuroimaging Initiative}},
  title   = {{Multi-modal latent factor exploration of atrophy, cognitive and tau heterogeneity in Alzheimer's disease}},
  journal = {NeuroImage},
  year    = {2019},
  doi     = {10.1016/j.neuroimage.2019.116043},
  pmid    = {31344486},
  url     = {https://doi.org/10.1016/j.neuroimage.2019.116043}
}

Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.

Key findings

Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain regions and cognitive tests.
Here, we considered a data-driven hierarchical Bayesian model to identify latent factors from atrophy patterns and cognitive deficits simultaneously, thus exploiting the rich dimensionality within each modality.
Unlike most previous studies, our model allows each factor to be expressed to varying degrees within an individual, in order to reflect potential multiple co-existing pathologies.
By applying our model to ADNI-GO/2 AD dementia participants, we found three atrophy-cognitive factors.

Why it matters

This study used a data-driven model to identify latent factors from atrophy patterns and cognitive deficits in people with Alzheimer's disease dementia. It is an observational study of disease heterogeneity, so it does not treat, cure, or prevent Alzheimer's disease.

Study details

Study designlongitudinal study
Evidence strengthModerate

How this study scored 54/100

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.

Component	Points	Why
Journal tier	7 / 10	Tier 3 — peer-reviewed journal (NeuroImage)
Journal's citation record	4 / 4	NeuroImage: journal h-index 523 (OpenAlex, 2026-10-29)
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	2019 — 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	4 / 7	Cited 47 times (OpenAlex, 2026-10-10)
Citations per year	2 / 5	5.2 citations a year over 9 year(s) since 2019
Impact for its field and year	3 / 6	Cited 5.4× the average for papers of its field and year (OpenAlex FWCI)
Cited by studies here	1 / 6	Cited by 1 other studies in this library
Still being cited	1 / 4	Cited 11 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record	3 / 4	Last-listed author B.T. Thomas Yeo: h-index 77 (OpenAlex, whole career)
Institution's track record	3 / 3	Stanford University: institution h-index 2,684 (OpenAlex)
Multi-centre collaboration	2 / 3	OpenAlex lists 7 institution(s) in 2 countries
Indexed in PubMed	2 / 2	Indexed in PubMed (PMID 31344486)
Free to read	0 / 2	Behind a paywall — scores zero
Total	54 / 100	—

What each of these 20 components measures, and what this score is not →

Read the original

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

Studies this one cites

Referenced by this study and also in the alzhub library, so you can read them here. Showing 12 of 29.

Later studies that cite this one

1 study in the alzhub library lists this one in its references.

Related studies in Long-term cohort studies

Also tagged “phosphorylated”

732 studies in the library carry the topic tag “phosphorylated”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 732 tagged studies.

Similar studies

More on Long-term cohort studies

See all studies in Long-term cohort studies →