Validation of genetic modifiers for Duchenne muscular dystrophy: a multicentre study assessing SPP1 and LTBP4 variants

van den Bergen JC, Hiller M, Böhringer S,Vijfhuizen L, Ginjaar HB, Chaouch A, Bushby K, Straub V, Scoto M, Cirak S, Humbertclaude V, Claustres M, Scotton C, Passarelli C, Lochmüller H, Muntoni F,Tuffery-Giraud S, Ferlini A, Aartsma-Rus AM, Verschuuren J J G M, ’t Hoen PAC, Spitali P


Journal of Neurology, Neurosurgery and Psychiatry, December 2014
DOI: 10.1136/jnnp-2014-308409

Abstract

Objective: Duchenne muscular dystrophy (DMD) is characterised by progressive muscle weakness. It has recently been reported that single nucleotide polymorphisms (SNPs) located in the SPP1 and LTBP4 loci can account for some of the inter-individual variability observed in the clinical disease course. The validation of genetic association in large independent cohorts is a key process for rare diseases in order to qualify prognostic biomarkers and stratify patients in clinical trials.
Methods: Duchenne patients from five European neuromuscular centres were included. Information about age at wheelchair dependence and steroid use was gathered. Melting curve analysis of PCR fragments or Sanger sequencing were used to genotype SNP rs28357094 in the SPP1 gene in 336 patients. The genotype of SNPs rs2303729, rs1131620, rs1051303 and rs10880 in the LTBP4 locus was determined in 265 patients by mass spectrometry. For both loci, a multivariate analysis was performed, using genotype/haplotype, steroid use and cohort as covariates.
Results: We show that corticosteroid treatment and the IAAM haplotype of the LTBP4 gene are significantly associated with prolonged ambulation in patients with DMD. There was no significant association between the SNP rs28357094 in the SPP1 gene and the age of ambulation loss. Conclusions This study underlines the importance of replicating genetic association studies for rare diseases in large independent cohorts to identify the most robust associations. We anticipate that genotyping of validated genetic associations will become important for the design and interpretation of clinical trials.

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