Topic: Brain proteins, microglia and lab models
Previous studies have prioritized trait-relevant cell types by looking for an enrichment of genome-wide association study (GWAS) signal within functional regions. However, these studies are limited in cell resolution by the lack of functional annotations from difficult-to-characterize or rare cell populations. Measurement of single-cell gene expression has become a popular method for characterizing novel cell types, and yet limited work has linked single-cell RNA sequencing (RNA-seq) to phenotypes of interest. To address this deficiency, we present RolyPoly, a regression-based polygenic model that can prioritize trait-relevant cell types and genes from GWAS summary statistics and gene expression data. RolyPoly is designed to use expression data from either bulk tissue or single-cell RNA-seq. In this study, we demonstrated RolyPoly's accuracy through simulation and validated previously known tissue-trait associations. We discovered a significant association between microglia and late-onset Alzheimer disease and an association between schizophrenia and oligodendrocytes and replicating fetal cortical cells. Additionally, RolyPoly computes a trait-relevance score for each gene to reflect the importance of expression specific to a cell type. We found that differentially expressed genes in the prefrontal cortex of individuals with Alzheimer disease were significantly enriched with genes ranked highly by RolyPoly gene scores. Overall, our method represents a powerful framework for understanding the effect of common variants on cell types contributing to complex traits.
Key findings
- In this study, we demonstrated RolyPoly's accuracy through simulation and validated previously known tissue-trait associations.
- We discovered a significant association between microglia and late-onset Alzheimer disease and an association between schizophrenia and oligodendrocytes and replicating fetal cortical cells.
- We found that differentially expressed genes in the prefrontal cortex of individuals with Alzheimer disease were significantly enriched with genes ranked highly by RolyPoly gene scores.
- Overall, our method represents a powerful framework for understanding the effect of common variants on cell types contributing to complex traits.
Why it matters
Using a new method called RolyPoly, the researchers found a significant association between microglia and late-onset Alzheimer's disease. Genes differentially expressed in the prefrontal cortex of people with Alzheimer's disease were significantly enriched with genes ranked highly by the method.
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Study details
- Evidence strengthLow
How this study scored 48/100
Published in a peer-reviewed journal. Scored zero for study design, 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 (American journal of human genetics) |
| Journal's citation record | 3 / 4 | The American Journal of Human Genetics: journal h-index 385 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2017 — 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 | 5 / 7 | Cited 127 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 11.5 citations a year over 11 year(s) since 2017 |
| Impact for its field and year | 3 / 6 | Cited 6.9× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 2 other studies in this library |
| Still being cited | 2 / 4 | Cited 34 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Jonathan K. Pritchard: h-index 116 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | Stanford University: institution h-index 2,684 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 6 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 29106824) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 48 / 100 | — |
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Read the original
Full text: free to read — PubMed Central lists this copy as free to read: the link above (checked 10 Oct 2026).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Calderon, D., Bhaskar, A., Knowles, D. A., Golan, D., Raj, T., Fu, A. Q., et al. (2017). Inferring Relevant Cell Types for Complex Traits by Using Single-Cell Gene Expression. American journal of human genetics. https://doi.org/10.1016/j.ajhg.2017.09.009
Vancouver
Calderon D, Bhaskar A, Knowles DA, Golan D, Raj T, Fu AQ, et al. Inferring Relevant Cell Types for Complex Traits by Using Single-Cell Gene Expression. American journal of human genetics. 2017. doi:10.1016/j.ajhg.2017.09.009. PMID: 29106824.
BibTeX
@article{calderon2017-29106824,
author = {Calderon, D. and Bhaskar, A. and Knowles, D. A. and Golan, D. and Raj, T. and Fu, A. Q. and Pritchard, J. K.},
title = {{Inferring Relevant Cell Types for Complex Traits by Using Single-Cell Gene Expression}},
journal = {American journal of human genetics},
year = {2017},
doi = {10.1016/j.ajhg.2017.09.009},
pmid = {29106824},
url = {https://doi.org/10.1016/j.ajhg.2017.09.009}
}
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