Functional characterisation of the amyotrophic lateral sclerosis risk locus GPX3/TNIP1
Restuadi, Restuadi; Steyn, Frederik J; Kabashi, Edor; Ngo, Shyuan T; Cheng, Fei-Fei; Nabais, Marta F; Thompson, Mike J; Qi, Ting; Wu, Yang; Henders, Anjali K; Wallace, Leanne; Bye, Chris R; Turner, Bradley J; Ziser, Laura; Mathers, Susan; McCombe, Pamela A; Needham, Merrilee; Schultz, David; Kiernan, Matthew C; van Rheenen, Wouter; van den Berg, Leonard H; Veldink, Jan H; Ophoff, Roel; Gusev, Alexander; Zaitlen, Noah; McRae, Allan F; Henderson, Robert D; Wray, Naomi R; Giacomotto, Jean; Garton, Fleur C
(2022) Genome Medicine, volume 14, issue 1, pp. 1 - 22
(Article)
Abstract
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a complex, late-onset, neurodegenerative disease with a genetic contribution to disease liability. Genome-wide association studies (GWAS) have identified ten risk loci to date, including the TNIP1/GPX3 locus on chromosome five. Given association analysis data alone cannot determine the most plausible risk gene for this
... read more
locus, we undertook a comprehensive suite of in silico, in vivo and in vitro studies to address this. METHODS: The Functional Mapping and Annotation (FUMA) pipeline and five tools (conditional and joint analysis (GCTA-COJO), Stratified Linkage Disequilibrium Score Regression (S-LDSC), Polygenic Priority Scoring (PoPS), Summary-based Mendelian Randomisation (SMR-HEIDI) and transcriptome-wide association study (TWAS) analyses) were used to perform bioinformatic integration of GWAS data (Ncases = 20,806, Ncontrols = 59,804) with 'omics reference datasets including the blood (eQTLgen consortium N = 31,684) and brain (N = 2581). This was followed up by specific expression studies in ALS case-control cohorts (microarray Ntotal = 942, protein Ntotal = 300) and gene knockdown (KD) studies of human neuronal iPSC cells and zebrafish-morpholinos (MO). RESULTS: SMR analyses implicated both TNIP1 and GPX3 (p < 1.15 × 10-6), but there was no simple SNP/expression relationship. Integrating multiple datasets using PoPS supported GPX3 but not TNIP1. In vivo expression analyses from blood in ALS cases identified that lower GPX3 expression correlated with a more progressed disease (ALS functional rating score, p = 5.5 × 10-3, adjusted R2 = 0.042, Beffect = 27.4 ± 13.3 ng/ml/ALSFRS unit) with microarray and protein data suggesting lower expression with risk allele (recessive model p = 0.06, p = 0.02 respectively). Validation in vivo indicated gpx3 KD caused significant motor deficits in zebrafish-MO (mean difference vs. control ± 95% CI, vs. control, swim distance = 112 ± 28 mm, time = 1.29 ± 0.59 s, speed = 32.0 ± 2.53 mm/s, respectively, p for all < 0.0001), which were rescued with gpx3 expression, with no phenotype identified with tnip1 KD or gpx3 overexpression. CONCLUSIONS: These results support GPX3 as a lead ALS risk gene in this locus, with more data needed to confirm/reject a role for TNIP1. This has implications for understanding disease mechanisms (GPX3 acts in the same pathway as SOD1, a well-established ALS-associated gene) and identifying new therapeutic approaches. Few previous examples of in-depth investigations of risk loci in ALS exist and a similar approach could be applied to investigate future expected GWAS findings.
show less
Download/Full Text
Keywords: Computational biology, Disease progression, Genes, Genome-wide association study, MND, Motor neurone disease, Neurodegenerative diseases, Quantitative trait loci, Regulator, Zebrafish, Molecular Medicine, Molecular Biology, Genetics, Genetics(clinical)
ISSN: 1756-994x
Publisher: BioMed Central
Note: Funding Information: Funding and support from the National Health and Medical Research Council Australia (NHMRC grant numbers 1078901 (to NW), 1113400 (to NW), 1087889 (to NW), 1121962 (to FCG), 1132524 (to MCK), 1153439 (to MCK), 1156093 (to MCK), 1165850 (to JG) and 1174145 (to JG)), the University of Queensland (Postgraduate scholarship to RR and Dr Jian Zhou Memorial Scholarship to FC), the Scott Sullivan Fellowship (with the MND and Me Foundation and Royal Brisbane and Women’s Hospital) (to STN 2015-2020), the FightMND Mid-Career Research Fellowship (to STN 2020-2023), the QUEX scholarship (with University of Exeter) (to MN), the National Institute of Health (Training Grant in Genomic Analysis and Interpretation T32HG002536 (MJT)), the European Research Council (ERC) European Union’s Horizon 2020 research and innovation programme (772376 – EScORIAL to JV), the National Institute of Mental Health (R01-MH115676 to AG) and Rebecca L. Cooper Medical Research Project Grant (PG2019405 to JG) Publisher Copyright: © 2021, The Author(s).
(Peer reviewed)