Robust Bioinformatics Approaches Result in the First Polygenic Risk Score for BMI in Greek Adults

Maria Kafyra; Ioanna Panagiota Kalafati; Maria Dimitriou; Effimia Grigoriou; Alexandros Kokkinos; Loukianos Rallidis; Genovefa Kolovou; Georgios Trovas; Eirini Marouli; Panos Deloukas; Panagiotis Moulos; George V Dedoussis

doi:10.3390/jpm13020327

Robust Bioinformatics Approaches Result in the First Polygenic Risk Score for BMI in Greek Adults

J Pers Med. 2023 Feb 14;13(2):327. doi: 10.3390/jpm13020327.

Authors

Affiliations

¹ Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece.
² Department of Nutrition and Dietetics, School of Physical Education, Sport Science and Dietetics, University of Thessaly, 42132 Trikala, Greece.
³ Department of Nutritional Science and Dietetics, School of Health Science, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece.
⁴ First Department of Propaedeutic and Internal Medicine, Laiko General Hospital, Athens University Medical School, 11527 Athens, Greece.
⁵ Second Department of Cardiology, Medical School, National and Kapodistrian University of Athens, Attikon Hospital, 12462 Athens, Greece.
⁶ Cardiometabolic Center, Metropolitan Hospital, 18547 Piraeus, Greece.
⁷ Laboratory for the Research of Musculoskeletal System "Th. Garofalidis", School of Medicine, National and Kapodistrian University of Athens, KAT General Hospital, Athinas 10th Str., 14561 Athens, Greece.
⁸ William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.
⁹ Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center 'Alexander Fleming', 16672 Vari, Greece.
¹⁰ Genome Analysis, 17671 Athens, Greece.

Abstract

Quantifying the role of genetics via construction of polygenic risk scores (PRSs) is deemed a resourceful tool to enable and promote effective obesity prevention strategies. The present paper proposes a novel methodology for PRS extraction and presents the first PRS for body mass index (BMI) in a Greek population. A novel pipeline for PRS derivation was used to analyze genetic data from a unified database of three cohorts of Greek adults. The pipeline spans various steps of the process, from iterative dataset splitting to training and test partitions, calculation of summary statistics and PRS extraction, up to PRS aggregation and stabilization, achieving higher evaluation metrics. Using data from 2185 participants, implementation of the pipeline enabled consecutive repetitions in splitting training and testing samples and resulted in a 343-single nucleotide polymorphism PRS yielding an R² = 0.3241 (beta = 1.011, p-value = 4 × 10^-193) for BMI. PRS-included variants displayed a variety of associations with known traits (i.e., blood cell count, gut microbiome, lifestyle parameters). The proposed methodology led to creation of the first-ever PRS for BMI in Greek adults and aims at promoting a facilitating approach to reliable PRS development and integration in healthcare practice.

Keywords: Greek adults; bioinformatics; body mass index (BMI); polygenic risk score (PRS).

Abstract

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