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Polygenic Risk Scores for Complex Traits in the Genome-Wide Association Study (GWAS) Era

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 29 April 2024 | Viewed by 838

Special Issue Editor

Dr. Giovanni Malerba

E-Mail Website
Guest Editor
GM Lab, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy
Interests: genomics and transcriptomics of Mendelian and complex traits; association and Linkage analyses; statistical genetics and bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Genetic and polygenic risk scores from genome studies are becoming reliable predictors for the assessment of the genetic risk of complex traits/diseases. In the era of precision medicine, there is a compelling interest in building novel and more precise computational models to predict the intricate network of gene–gene and gene–environment interactions underlying the etiopathological pathways of complex traits. The introduction of polygenic risk scores represents a relatively novel field of genetic research that has its roots in the present-day ability to determine individual genomic profiles at low cost. Such profiles can be arranged into complex models to synthesize the association of new composite genetic factors with many complex diseases.  In this Special Issue, we welcome contributions focusing on genetic and polygenic risk scores, comprising their development and implementation and their application in human traits and diseases.

Dr. Giovanni Malerba
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precision medicine
  • genetic
  • gene–gene
  • gene–environment

Published Papers (1 paper)

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Research

15 pages, 3186 KiB  
Article
Evaluating the Efficacy of Type 2 Diabetes Polygenic Risk Scores in an Independent European Population
by Monta Brīvība, Ivanna Atava, Raitis Pečulis, Ilze Elbere, Laura Ansone, Maija Rozenberga, Ivars Silamiķelis and Jānis Kloviņš
Int. J. Mol. Sci. 2024, 25(2), 1151; https://doi.org/10.3390/ijms25021151 - 17 Jan 2024
Viewed by 617
Abstract
Numerous type 2 diabetes (T2D) polygenic risk scores (PGSs) have been developed to predict individuals’ predisposition to the disease. An independent assessment and verification of the best-performing PGS are warranted to allow for a rapid application of developed models. To date, only 3% [...] Read more.
Numerous type 2 diabetes (T2D) polygenic risk scores (PGSs) have been developed to predict individuals’ predisposition to the disease. An independent assessment and verification of the best-performing PGS are warranted to allow for a rapid application of developed models. To date, only 3% of T2D PGSs have been evaluated. In this study, we assessed all (n = 102) presently published T2D PGSs in an independent cohort of 3718 individuals, which has not been included in the construction or fine-tuning of any T2D PGS so far. We further chose the best-performing PGS, assessed its performance across major population principal component analysis (PCA) clusters, and compared it with newly developed population-specific T2D PGS. Our findings revealed that 88% of the published PGSs were significantly associated with T2D; however, their performance was lower than what had been previously reported. We found a positive association of PGS improvement over the years (p-value = 8.01 × 10−4 with PGS002771 currently showing the best discriminatory power (area under the receiver operating characteristic (AUROC) = 0.669) and PGS003443 exhibiting the strongest association PGS003443 (odds ratio (OR) = 1.899). Further investigation revealed no difference in PGS performance across major population PCA clusters and when compared with newly developed population-specific PGS. Our findings revealed a positive trend in T2D PGS performance, consistently identifying high-T2D-risk individuals in an independent European population. Full article
(This article belongs to the Special Issue Polygenic Risk Scores for Complex Traits in the Genome-Wide Association Study (GWAS) Era)
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