Genetics in Parkinson's Disease: From Better Disease Understanding to Machine Learning Based Precision Medicine

Overview

Journal Front Mol Med

Date 2024 Aug 1

PMID 39086979

Authors

Mohamed Aborageh

Peter Krawitz

Holger Frohlich

Affiliations

Soon will be listed here.

Abstract

Parkinson's Disease (PD) is a neurodegenerative disorder with highly heterogeneous phenotypes. Accordingly, it has been challenging to robustly identify genetic factors associated with disease risk, prognosis and therapy response via genome-wide association studies (GWAS). In this review we first provide an overview of existing statistical methods to detect associations between genetic variants and the disease phenotypes in existing PD GWAS. Secondly, we discuss the potential of machine learning approaches to better quantify disease phenotypes and to move beyond disease understanding towards a better-personalized treatment of the disease.

References

Krauthammer M, Kaufmann C, Gilliam T, Rzhetsky A . Molecular triangulation: bridging linkage and molecular-network information for identifying candidate genes in Alzheimer's disease. Proc Natl Acad Sci U S A. 2004; 101(42):15148-53. PMC: 523448. DOI: 10.1073/pnas.0404315101. View

Ibanez L, Dube U, Saef B, Budde J, Black K, Medvedeva A . Parkinson disease polygenic risk score is associated with Parkinson disease status and age at onset but not with alpha-synuclein cerebrospinal fluid levels. BMC Neurol. 2017; 17(1):198. PMC: 5688622. DOI: 10.1186/s12883-017-0978-z. View

Lee S, Emond M, Bamshad M, Barnes K, Rieder M, Nickerson D . Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies. Am J Hum Genet. 2012; 91(2):224-37. PMC: 3415556. DOI: 10.1016/j.ajhg.2012.06.007. View

Lambert S, Gil L, Jupp S, Ritchie S, Xu Y, Buniello A . The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation. Nat Genet. 2021; 53(4):420-425. PMC: 11165303. DOI: 10.1038/s41588-021-00783-5. View

Li B, Leal S . Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am J Hum Genet. 2008; 83(3):311-21. PMC: 2842185. DOI: 10.1016/j.ajhg.2008.06.024. View

Hoffmann T, Marini N, Witte J . Comprehensive approach to analyzing rare genetic variants. PLoS One. 2010; 5(11):e13584. PMC: 2972202. DOI: 10.1371/journal.pone.0013584. View

Schork N, Murray S, Frazer K, Topol E . Common vs. rare allele hypotheses for complex diseases. Curr Opin Genet Dev. 2009; 19(3):212-9. PMC: 2914559. DOI: 10.1016/j.gde.2009.04.010. View

Ahmadi Rastegar D, Ho N, Halliday G, Dzamko N . Parkinson's progression prediction using machine learning and serum cytokines. NPJ Parkinsons Dis. 2019; 5:14. PMC: 6658482. DOI: 10.1038/s41531-019-0086-4. View

Jimenez-Jimenez F, Alonso-Navarro H, Garcia-Martin E, Agundez J . NAT2 polymorphisms and risk for Parkinson's disease: a systematic review and meta-analysis. Expert Opin Drug Metab Toxicol. 2016; 12(8):937-46. DOI: 10.1080/17425255.2016.1192127. View

10.

Price A, Kryukov G, de Bakker P, Purcell S, Staples J, Wei L . Pooled association tests for rare variants in exon-resequencing studies. Am J Hum Genet. 2010; 86(6):832-8. PMC: 3032073. DOI: 10.1016/j.ajhg.2010.04.005. View

11.

Collins L, Williams-Gray C . The Genetic Basis of Cognitive Impairment and Dementia in Parkinson's Disease. Front Psychiatry. 2016; 7:89. PMC: 4873499. DOI: 10.3389/fpsyt.2016.00089. View

12.

Li C, Ou R, Chen Y, Gu X, Wei Q, Cao B . Mutation Analysis of DNAJC Family for Early-Onset Parkinson's Disease in a Chinese Cohort. Mov Disord. 2020; 35(11):2068-2076. DOI: 10.1002/mds.28203. View

13.

Bland J, Altman D . Multiple significance tests: the Bonferroni method. BMJ. 1995; 310(6973):170. PMC: 2548561. DOI: 10.1136/bmj.310.6973.170. View

14.

Ryu H, Park K, Choi N, Kim J, Park Y, Jo S . Genomic Analysis Identifies New Loci Associated With Motor Complications in Parkinson's Disease. Front Neurol. 2020; 11:570. PMC: 7358548. DOI: 10.3389/fneur.2020.00570. View

15.

Titova N, Chaudhuri K . Personalized medicine in Parkinson's disease: Time to be precise. Mov Disord. 2017; 32(8):1147-1154. PMC: 5575483. DOI: 10.1002/mds.27027. View

16.

Zawistowski M, Gopalakrishnan S, Ding J, Li Y, Grimm S, Zollner S . Extending rare-variant testing strategies: analysis of noncoding sequence and imputed genotypes. Am J Hum Genet. 2010; 87(5):604-17. PMC: 2978957. DOI: 10.1016/j.ajhg.2010.10.012. View

17.

Hamza T, Zabetian C, Tenesa A, Laederach A, Montimurro J, Yearout D . Common genetic variation in the HLA region is associated with late-onset sporadic Parkinson's disease. Nat Genet. 2010; 42(9):781-5. PMC: 2930111. DOI: 10.1038/ng.642. View

18.

Choi S, OReilly P . PRSice-2: Polygenic Risk Score software for biobank-scale data. Gigascience. 2019; 8(7). PMC: 6629542. DOI: 10.1093/gigascience/giz082. View

19.

Saad M, Lesage S, Saint-Pierre A, Corvol J, Zelenika D, Lambert J . Genome-wide association study confirms BST1 and suggests a locus on 12q24 as the risk loci for Parkinson's disease in the European population. Hum Mol Genet. 2010; 20(3):615-27. DOI: 10.1093/hmg/ddq497. View

20.

Blauwendraat C, Reed X, Krohn L, Heilbron K, Bandres-Ciga S, Tan M . Genetic modifiers of risk and age at onset in GBA associated Parkinson's disease and Lewy body dementia. Brain. 2019; 143(1):234-248. PMC: 6935749. DOI: 10.1093/brain/awz350. View