Startseite Potential application of elastic nets for shared polygenicity detection with adapted threshold selection
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Potential application of elastic nets for shared polygenicity detection with adapted threshold selection

  • Majnu John ORCID logo EMAIL logo und Todd Lencz ORCID logo
Veröffentlicht/Copyright: 3. November 2022
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The International Journal of Biostatistics
Aus der Zeitschrift The International Journal of Biostatistics Band 19 Heft 2

Abstract

Current research suggests that hundreds to thousands of single nucleotide polymorphisms (SNPs) with small to modest effect sizes contribute to the genetic basis of many disorders, a phenomenon labeled as polygenicity. Additionally, many such disorders demonstrate polygenic overlap, in which risk alleles are shared at associated genetic loci. A simple strategy to detect polygenic overlap between two phenotypes is based on rank-ordering the univariate p-values from two genome-wide association studies (GWASs). Although high-dimensional variable selection strategies such as Lasso and elastic nets have been utilized in other GWAS analysis settings, they are yet to be utilized for detecting shared polygenicity. In this paper, we illustrate how elastic nets, with polygenic scores as the dependent variable and with appropriate adaptation in selecting the penalty parameter, may be utilized for detecting a subset of SNPs involved in shared polygenicity. We provide theory to better understand our approaches, and illustrate their utility using synthetic datasets. Results from extensive simulations are presented comparing the elastic net approaches with the rank ordering approach, in various scenarios. Results from simulations studies exhibit one of the elastic net approaches to be superior when the correlations among the SNPs are high. Finally, we apply the methods on two real datasets to illustrate further the capabilities, limitations and differences among the methods.

Keywords: elastic nets; GWAS; Lasso; polygenic scores
Corresponding author: Majnu John, Institute of Behavioral Science, Feinstein Institutes of Medical Research, 350 Community Drive, Manhasset, NY 11030, USA; Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health System, Glen Oaks, NY, USA; and Departments of Psychiatry and of Mathematics, Hofstra University, Hempstead, NY, USA, E-mail:

Funding source: National Institute of Mental Health

Award Identifier / Grant number: R01MH120313

Award Identifier / Grant number: R01MH120594

Award Identifier / Grant number: P50 MH080173

Award Identifier / Grant number: R01 MH095458

Award Identifier / Grant number: R01 MH117646

Acknowledgments

We appreciate very much the comments by two anonymous reviewers and the Associate Editor Dr. Vivian Viallon, which led to substantial improvement of the manuscript. We also sincerely thank the Editor-in-Chief Dr. Antoine Chambaz for his patience, and for providing us extended time to complete the revisions. The authors thank John Cholewa and Eugene Kats for help with computational resources and computer systems, and Dr. Max Lam for assistance with obtaining data used in an earlier version of the paper.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: M.J’s work was supported in part by the following grants from the National Institute of Mental Health (NIMH) awarded to PI: Deligiannides, K (R01MH120313), PIs: Kane, J and Robinson, D (R01MH120594), and PI: Malhotra AK (P50 MH080173) and both authors’ work was supported by two project grants to T.L. (R01 MH095458 and R01 MH117646).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/ijb-2020-0108).

Received: 2020-01-28
Revised: 2022-09-28
Accepted: 2022-10-05
Published Online: 2022-11-03

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Part-1: SMAC 2021 Webconference
  3. Statistics, philosophy, and health: the SMAC 2021 webconference
  4. Part-2: Regular Articles
  5. “Show me the DAG!”
  6. Causal inference for oncology: past developments and current challenges
  7. The EBM+ movement
  8. Bayesianism from a philosophical perspective and its application to medicine
  9. Bayesian inference for optimal dynamic treatment regimes in practice
  10. Agent-based modeling in medical research, virtual baseline generator and change in patients’ profile issue
  11. Agent based modeling in health care economics: examples in the field of thyroid cancer
  12. A copula-based set-variant association test for bivariate continuous, binary or mixed phenotypes
  13. Detection of atypical response trajectories in biomedical longitudinal databases
  14. Potential application of elastic nets for shared polygenicity detection with adapted threshold selection
  15. Error analysis of the PacBio sequencing CCS reads
  16. A SIMEX approach for meta-analysis of diagnostic accuracy studies with attention to ROC curves
  17. Statistical modelling of COVID-19 and drug data via an INAR(1) process with a recent thinning operator and cosine Poisson innovations
  18. The balanced discrete triplet Lindley model and its INAR(1) extension: properties and COVID-19 applications
https://doi.org/10.1515/ijb-2020-0108
Schlagwörter für diesen Artikel
elastic nets; GWAS; Lasso; polygenic scores

Artikel in diesem Heft

  1. Frontmatter
  2. Part-1: SMAC 2021 Webconference
  3. Statistics, philosophy, and health: the SMAC 2021 webconference
  4. Part-2: Regular Articles
  5. “Show me the DAG!”
  6. Causal inference for oncology: past developments and current challenges
  7. The EBM+ movement
  8. Bayesianism from a philosophical perspective and its application to medicine
  9. Bayesian inference for optimal dynamic treatment regimes in practice
  10. Agent-based modeling in medical research, virtual baseline generator and change in patients’ profile issue
  11. Agent based modeling in health care economics: examples in the field of thyroid cancer
  12. A copula-based set-variant association test for bivariate continuous, binary or mixed phenotypes
  13. Detection of atypical response trajectories in biomedical longitudinal databases
  14. Potential application of elastic nets for shared polygenicity detection with adapted threshold selection
  15. Error analysis of the PacBio sequencing CCS reads
  16. A SIMEX approach for meta-analysis of diagnostic accuracy studies with attention to ROC curves
  17. Statistical modelling of COVID-19 and drug data via an INAR(1) process with a recent thinning operator and cosine Poisson innovations
  18. The balanced discrete triplet Lindley model and its INAR(1) extension: properties and COVID-19 applications
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