Author

Aaron Day-Williams

Biogen (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 3 Genomics· 2

Signature Assays, Organisms & Methods

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Assay:GWAS summary statistics· 4 Organism:human· 4 Approach:statistical model· 4 Research Focus:GWAS / association mapping· 3 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Andrew SingletoniD· 2 shared Christopher S. Franklin· 2 shared Cornelis BlauwendraatiD· 2 shared Faraz FaghriiD· 2 shared Hampton L. LeonardiD· 2 shared Heiko RunziD· 2 shared Hirotaka IwakiiD· 2 shared Mike A. NallsiD· 2 shared

Activity by Year

2017-2019 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersGenomics

Andrew SingletonORCID

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Author profile →

5 papers

Recent·Most cited

Genetic variability and potential effects on clinical trial outcomes: perspectives in Parkinson’s disease

Hampton L. Leonard, Cornelis Blauwendraat, Lynne Krohn, Faraz Faghri, Hirotaka Iwaki, G. D. Ferguson, Aaron Day-Williams, David J. Stone, Andrew Singleton, Mike A. Nalls, Ziv Gan‐Or

This study simulates clinical trials to show genetic differences between trial arms can lead to false negatives and positives, especially in small samples, and suggests genetic balancing improves outcomes.

Journal of Medical Genetics · Nov 29, 2019Peer-reviewedGenomics

Genome-wide association study of Parkinsons disease progression biomarkers in 12 longitudinal patients cohorts

Hirotaka Iwaki, Cornelis Blauwendraat, Hampton L. Leonard, Jonggeol Jeffrey Kim, Ganqiang Liu, Jodi Maple‐Grødem, Jean‐Christophe Corvol, Lasse Pihlstrøm, Marlies van Nimwegen, Samantha J. Hutten, H. Nguyen Khanh-Dung, Jacqueline H. Rick, Shirley W. Eberly, Faraz Faghri, Peggy Auinger, , Mike A. Nalls

This study identifies two genome-wide significant variants associated with Parkinson's disease progression and replicates known risk variants' effects on motor and cognitive decline.

bioRxiv · Mar 27, 2019 · PreprintGenetics

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

Simon J. Haworth, Chin Yang Shapland, Caroline Hayward, Bram Peter Prins, Janine F. Felix, Carolina Medina‐Gómez, Fernando Rivadeneira, Carol A. Wang, Tarunveer S. Ahluwalia, Martine Vrijheid, Mònica Guxens, Jordi Sunyer, Ioanna Tachmazidou, Klaudia Walter, Valentina Iotchkova, , David K. Jackson

The paper identifies 9 novel genetic loci, including low-frequency variants in TP53, associated with head circumference and intracranial volume in up to 46,000 individuals.

Nature Communications · Jan 21, 2019Peer-reviewedGenetics

Phenotype-specific information improves prediction of functional impact for noncoding variants

Corneliu Alexandru Bodea, Adele A. Mitchell, Alex Bloemendal, Aaron Day-Williams, Heiko Runz, Shamil R. Sunyaev

PINES improves noncoding variant functional impact prediction by integrating phenotype-dependent epigenetic annotations.

bioRxiv · May 3, 2018 · PreprintGenomics

Phenome-wide association studies (PheWAS) across large "real-world data" population cohorts support drug target validation

Dorothée Diogo, Chao Tian, Christopher S. Franklin, Mervi Alanne-Kinnunen, Michael March, Chris C. A. Spencer, Ciara Vangjeli, Michael E. Weale, Hannele Mattsson, Elina Kilpeläinen, Patrick M. Abou‐Sleiman, Dermot F. Reilly, Joshua J. McElwee, Joseph Maranville, Arnaub K. Chatterjee, , Heiko Runz

The paper uses PheWAS across large cohorts to identify genetic associations with drug targets and predict drug safety and efficacy.

bioRxiv · Nov 13, 2017 · PreprintGenetics