Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform
Mischa Lundberg, Letitia M F Sng, Piotr Szul, Rob Dunne, Arash Bayat, Samantha C Burnham, Denis C Bauer, Natalie A Twine. Scientific reports, 2023-10-17
Topic: Genetics and APOE
Alzheimer's disease (AD) is a complex genetic disease, and variants identified through genome-wide association studies (GWAS) explain only part of its heritability. Epistasis has been proposed as a major contributor to this 'missing heritability', however, many current methods are limited to only modelling additive effects. We use VariantSpark, a machine learning approach to GWAS, and BitEpi, a tool for epistasis detection, to identify AD associated variants and interactions across two independent cohorts, ADNI and UK Biobank. By incorporating significant epistatic interactions, we captured 10.41% more phenotypic variance than logistic regression (LR). We validate the well-established AD loci, APOE, and identify two novel genome-wide significant AD associated loci in both cohorts, SH3BP4 and SASH1, which are also in significant epistatic interactions with APOE. We show that the SH3BP4 SNP has a modulating effect on the known pathogenic APOE SNP, demonstrating a possible protective mechanism against AD. SASH1 is involved in a triplet interaction with pathogenic APOE SNP and ACOT11, where the SASH1 SNP lowered the pathogenic interaction effect between ACOT11 and APOE. Finally, we demonstrate that VariantSpark detects disease associations with 80% fewer controls than LR, unlocking discoveries in well annotated but smaller cohorts.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Lundberg, M., Sng, L. M. F., Szul, P., Dunne, R., Bayat, A., Burnham, S. C., et al. (2023). Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform. Scientific reports. https://doi.org/10.1038/s41598-023-44378-y
Vancouver
Lundberg M, Sng LMF, Szul P, Dunne R, Bayat A, Burnham SC, et al. Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform. Scientific reports. 2023. doi:10.1038/s41598-023-44378-y. PMID: 37848535.
BibTeX
@article{lundberg2023-37848535,
author = {Lundberg, Mischa and Sng, Letitia M F and Szul, Piotr and Dunne, Rob and Bayat, Arash and Burnham, Samantha C and Bauer, Denis C and Twine, Natalie A},
title = {{Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform}},
journal = {Scientific reports},
year = {2023},
doi = {10.1038/s41598-023-44378-y},
pmid = {37848535},
url = {https://doi.org/10.1038/s41598-023-44378-y}
}
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Key findings
- By incorporating significant epistatic interactions, we captured 10.41% more phenotypic variance than logistic regression (LR).
- We validate the well-established AD loci, APOE, and identify two novel genome-wide significant AD associated loci in both cohorts, SH3BP4 and SASH1, which are also in significant epistatic interactions with APOE.
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Study details
- Effect size10.41%
- Evidence strengthLow
How this study scored 45/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, 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, multi-centre collaboration and free to read, so those were left out: it earned 25 of the 56 points we could judge it on, which is 45 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Scientific reports) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| 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 | 3 / 5 | 2023 — within 6 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 | 2 / 3 | Effect reported as a number, without an interval or test |
| 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 37848535) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 25 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 25 of the 56 points we could judge it on is 45 out of 100. |
| Total | 45 / 100 | — |
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