Genome Medicine (Jan 2022)

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

  • Restuadi Restuadi,
  • Frederik J. Steyn,
  • Edor Kabashi,
  • Shyuan T. Ngo,
  • Fei-Fei Cheng,
  • Marta F. Nabais,
  • Mike J. Thompson,
  • Ting Qi,
  • Yang Wu,
  • Anjali K. Henders,
  • Leanne Wallace,
  • Chris R. Bye,
  • Bradley J. Turner,
  • Laura Ziser,
  • Susan Mathers,
  • Pamela A. McCombe,
  • Merrilee Needham,
  • David Schultz,
  • Matthew C. Kiernan,
  • Wouter van Rheenen,
  • Leonard H. van den Berg,
  • Jan H. Veldink,
  • Roel Ophoff,
  • Alexander Gusev,
  • Noah Zaitlen,
  • Allan F. McRae,
  • Robert D. Henderson,
  • Naomi R. Wray,
  • Jean Giacomotto,
  • Fleur C. Garton

DOI
https://doi.org/10.1186/s13073-021-01006-6
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 22

Abstract

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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 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.

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