Author

Maya Lowe

23andMe (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

Click to filter author papers

Genetic & Genomic Medicine· 4 Genetics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:GWAS summary statistics· 6 Organism:human· 5 Approach:statistical model· 5 Research Focus:GWAS / association mapping· 3 Research Focus:polygenic risk· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Adam AutoniD· 6 shared Anjali J. Shastri· 6 shared Catherine H. Weldon· 6 shared Daniella CokeriD· 6 shared Janie F. Shelton· 6 shared Jessica BielenbergiD· 6 shared Kipper Fletez‐BrantiD· 6 shared Stella W. AslibekyaniD· 6 shared

Activity by Year

2022-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

6 shared papersGenetic & Genomic Medicine

Adam AutonORCID

Mutual co-authors in cluster

Author profile →

6 papers

Recent·Most cited

Insights into Ancestral Diversity in Parkinsons Disease Risk: A Comparative Assessment of Polygenic Risk Scores

Paula Saffie Awad, Spencer M. Grant, Mary B. Makarious, Inas Elsayed, Arinola O. Sanyaolu, Peter Wild Crea, Artur Francisco Schumacher Schuh, Kristin S. Levine, Dan Vitale, Mathew J. Koretsky, Jeffrey Kim, Thiago Peixoto Leal, María Teresa Periñán, Sumit Dey, Alastair John Noyce, , Edward A. Fon

This study compares polygenic risk scores for Parkinson's disease across seven ancestries, finding varying predictive accuracy and highlighting the need for ancestry-specific models.

npj Parkinson s Disease · Jul 3, 2025Peer-reviewedGenetic & Genomic Medicine

MUSSEL: Enhanced Bayesian Polygenic Risk Prediction Leveraging Information across Multiple Ancestry Groups

Jin Jin, Jianan Zhan, Jingning Zhang, Ruzhang Zhao, Jared O’Connell, Yunxuan Jiang, Stella W. Aslibekyan, Adam Auton, Elizabeth Babalola, Robert K. Bell, Jessica Bielenberg, Katarzyna Bryc, Emily Bullis, Daniella Coker, Gabriel Cuéllar-Partida, , Nilanjan Chatterjee

MUSSEL improves polygenic risk prediction across populations by integrating GWAS summary statistics and using Bayesian hierarchical modeling with ensemble learning.

Cell Genomics · Apr 1, 2024Peer-reviewedGenetics

Multi-ancestry genome-wide meta-analysis in Parkinson's disease

Jonggeol Jeffrey Kim, Dan Vitale, Diego Véliz Otani, Michelle Mulan Lian, Karl Heilbron, Stella W. Aslibekyan, Adam Auton, Elizabeth Babalola, Robert K. Bell, Jessica Bielenberg, Katarzyna Bryc, Emily Bullis, Paul Cannon, Daniella Coker, Gabriel Cuéllar-Partida, , Piu Chan

This paper conducts a multi-ancestry genome-wide meta-analysis of Parkinson's disease, identifying 78 independent loci and 23 genes associated with PD risk.

Nature Genetics · Dec 28, 2023Peer-reviewedGenetic & Genomic Medicine

A new method for multi-ancestry polygenic prediction improves performance across diverse populations

Haoyu Zhang, Jianan Zhan, Jin Jin, Jingning Zhang, Wenxuan Lu, Ruzhang Zhao, Thomas U. Ahearn, Zhi Yu, Jared O’Connell, Yunxuan Jiang, Tony Chen, Dayne Y. Okuhara, Stella W. Aslibekyan, Adam Auton, Elizabeth Babalola, , Nilanjan Chatterjee

The paper introduces CT-SLEB, a method for multi-ancestry polygenic prediction that improves performance in non-European populations using GWAS summary statistics and simulation studies.

Nature Genetics · Sep 25, 2023Peer-reviewedGenetics

Discovery of genomic loci associated with sleep apnoea risk through multi-trait GWAS analysis with snoring

Adrián I. Campos, Nathan Ingold, Yunru Huang, Brittany L. Mitchell, Pik Fang Kho, Xikun Han, Luis M. García‐Marín, Jue‐Sheng Ong, Michelle Agee, Stella Aslibekyan, Adam Auton, Elizabeth Babalola, Robert K. Bell, Jessica Bielenberg, Katarzyna Bryc, , Miguel E. Rentería

This study identifies 49 genetic loci associated with sleep apnoea risk using multi-trait GWAS, with 29 replicated in a large cohort, and finds genetic correlations with several complex traits.

SLEEP · Dec 16, 2022Peer-reviewedGenetic & Genomic Medicine

The UGT2A1/UGT2A2 locus is associated with COVID-19-related anosmia

Janie F. Shelton, Anjali J. Shastri, Kipper Fletez‐Brant, The 23andMe COVID-19 Team, Adam Auton, Adrian Chubb, Alison Fitch, Alison Kung, Amanda Altman, Andy Kill, Antony Symons, Catherine H. Weldon, Daniella Coker, Jason Tan, Jeff Pollard, , Yiwen Zheng

The paper identifies a genetic association between the UGT2A1/UGT2A2 locus and COVID-19-related anosmia using a trans-ethnic GWAS.

Nature Genetics · Jan 17, 2022Peer-reviewedGenetic & Genomic Medicine