TY - JOUR
T1 - Prediction of parkinson’s disease risk based on genetic profile and established risk factors
AU - Chairta, Paraskevi P.
AU - Hadjisavvas, Andreas
AU - Georgiou, Andrea N.
AU - Loizidou, Maria A.
AU - Yiangou, Kristia
AU - Demetriou, Christiana A.
AU - Christou, Yiolanda P.
AU - Pantziaris, Marios
AU - Michailidou, Kyriaki
AU - Zamba-Papanicolaou, Eleni
N1 - Funding Information:
The authors would like to thank all the participants and the Cyprus Institute of Neurology and Genetics and the Cyprus School of Molecular Medicine for the support.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/8
Y1 - 2021/8
N2 - Background: Parkinson’s disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk score (PRS) in combination with already established PD-environmental/lifestyle factors. Methods: Genotypic and lifestyle/environmental data on 235 PD-patients and 464 controls were obtained from a previous study carried out in the Cypriot population. A PRS was calculated for each individual. Univariate logistic-regression analysis was used to assess the association of PRS and each risk factor with PD-status. Stepwise-regression analysis was used to select the best predictive model for PD combining genetic and lifestyle/environmental factors. Results: The 12-SNPs PRS was significantly increased in PD-cases compared to controls. Furthermore, univariate analyses showed that age, head injury, family history, depression, and Body Mass Index (BMI) were significantly associated with PD-status. Stepwise-regression suggested that a model which includes PRS and seven other independent lifestyle/environmental factors is the most predictive of PD in our population. Conclusions: These results suggest an association between both genetic and environmental factors and PD, and highlight the potential for the use of PRS in combination with the classical risk factors for risk prediction of PD.
AB - Background: Parkinson’s disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk score (PRS) in combination with already established PD-environmental/lifestyle factors. Methods: Genotypic and lifestyle/environmental data on 235 PD-patients and 464 controls were obtained from a previous study carried out in the Cypriot population. A PRS was calculated for each individual. Univariate logistic-regression analysis was used to assess the association of PRS and each risk factor with PD-status. Stepwise-regression analysis was used to select the best predictive model for PD combining genetic and lifestyle/environmental factors. Results: The 12-SNPs PRS was significantly increased in PD-cases compared to controls. Furthermore, univariate analyses showed that age, head injury, family history, depression, and Body Mass Index (BMI) were significantly associated with PD-status. Stepwise-regression suggested that a model which includes PRS and seven other independent lifestyle/environmental factors is the most predictive of PD in our population. Conclusions: These results suggest an association between both genetic and environmental factors and PD, and highlight the potential for the use of PRS in combination with the classical risk factors for risk prediction of PD.
KW - Case-control study
KW - Cypriot population
KW - Environmental factors
KW - Genetic variants
KW - Parkinson’s disease
KW - Polygenic risk score
KW - Predictive model
KW - PRS
KW - SNPs
UR - http://www.scopus.com/inward/record.url?scp=85113548624&partnerID=8YFLogxK
U2 - 10.3390/genes12081278
DO - 10.3390/genes12081278
M3 - Article
C2 - 34440451
AN - SCOPUS:85113548624
SN - 2073-4425
VL - 12
JO - Genes
JF - Genes
IS - 8
M1 - 1278
ER -