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Functional characterisation of the amyotrophic lateral sclerosis risk locus GPX3/TNIP1

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 ana...

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Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767698/
https://www.ncbi.nlm.nih.gov/pubmed/35042540
http://dx.doi.org/10.1186/s13073-021-01006-6
Descripción
Sumario: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 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 (N(cases) = 20,806, N(controls) = 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 N(total) = 942, protein N(total) = 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 R(2) = 0.042, B(effect) = 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-021-01006-6.