Poster No:
857
Submission Type:
Abstract Submission
Authors:
Natalia Ogonowski1,2, Santiago Diaz-Torres1,2, Luis M. Garcia Marin1,2, Xochitl Diaz1, Zuriel Ceja1,3, Miguel Renteria1,2
Institutions:
1Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia, 2School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia, 3School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, Australia
First Author:
Natalia Ogonowski
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute|School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
Brisbane, QLD, Australia|Brisbane, QLD, Australia
Co-Author(s):
Santiago Diaz-Torres
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute|School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
Brisbane, QLD, Australia|Brisbane, QLD, Australia
Luis M. Garcia Marin
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute|School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
Brisbane, QLD, Australia|Brisbane, QLD, Australia
Xochitl Diaz
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute
Brisbane, QLD, Australia
Zuriel Ceja
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute|School of Biomedical Sciences, The University of Queensland
Brisbane, QLD, Australia|Brisbane, QLD, Australia
Miguel Renteria
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute|School of Biomedical Sciences, Faculty of Medicine, The University of Queensland
Brisbane, QLD, Australia|Brisbane, QLD, Australia
Introduction:
Introduction: Parkinson's disease (PD) is the second most common neurodegenerative disorder, characterised by motor symptoms (resting tremor, rigidity, and bradykinesia), as well as non-motor symptoms, such as cognitive impairment and sleep disturbances. Its etiology is multifactorial, encompassing genetic, environmental, and age-related factors. Despite recent progress in elucidating the genetic aetiology of PD, considerable gaps remain in understanding the genetic architecture of the disease. Further investigation into the genetic underpinnings of PD could significantly advance our comprehension of its biological mechanisms. In this study, we used summary statistics from genome-wide association studies (GWAS) of brain morphometry and PD to increase our knowledge about the genetic basis of PD.
Methods:
Methods: We performed a meta-analysis of GWAS for PD using summary statistics from the Nalls et al. 2019 and FinnGen release 9, followed by a Multi-Trait Analysis of GWAS (mTAG) between PD and neuroimaging phenotypes (intracranial volume and the volumes of the accumbens, brainstem, caudate, pallidum, putamen, thalamus, and ventral diencephalon), yielding a combined effective sample size of 62,294 PD cases and 1,938,001 controls. Our results identified genetic variants associated with PD. We also conducted conditional and joint analyses to identify the genetic variants that best account for heritable variation. Finally, we performed functional annotation and pathway analyses to gain insights into the biological mechanisms underlying the observed associations.
Results:
Results: Our study identified 206 independent genome-wide significant risk signals across 83 genomic regions, of which 99 were novel. Gene-based association tests revealed 226 genes associated with PD. Additionally, we identified three biological pathways involved in the development of PD: regulation of axon extension in axon guidance, signalling to p38 via RIT and RIN, and genes down-regulated in hypertrophic hearts (due to the expression of a constitutively active form of PPP3CA) that are predicted to be targets of the miR-1 microRNA.
Conclusions:
Conclusion: Our findings advance the understanding of the genetic basis of PD by combining genetic results from neuroimaging traits. Additionally, prioritising genes involved in PD aetiology provides new avenues to understand biological mechanisms associated with PD risk and offers new avenues for treatment development.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Genetics:
Genetic Association Studies 1
Genetic Modeling and Analysis Methods
Keywords:
Computational Neuroscience
Degenerative Disease
Sub-Cortical
Other - Multitrait analysis of GWAS, Parkinson's disease
1|2Indicates the priority used for review
Provide references using author date format
Nalls MA, et al (2019). 'Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies'. Lancet Neurol, 18(12):1091-1102.
Turley P, et al (2018). 'Multi-trait analysis of genome-wide association summary statistics using MTAG'. Nat Genet, 50(2):229-237.
Xu H, et al (2023). 'Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study'. Addiction,18(10):1942-1952.