Single Nucleotide Variants of Candidate Genes in Aggrecan Metabolic Pathway Are Associated with Lumbar Disc Degeneration and Modic Changes
INTRODUCTION
Lumbar disc degeneration (LDD) is genetically determined and severity of LDD is associated with Modic changes. Aggrecan is a major proteoglycan in the intervertebral disc and end plate. Progressive reduction of aggrecan is a main feature of LDD and Modic changes.


OBJECTIVES
The study investigated the associations of single nucleotide variants (SNVs) of candidate genes in the aggrecan metabolic pathway with the severity of LDD and Modic changes. In-silico functional analysis of significant SNVs was also assessed.


METHODS
A descriptive cross sectional study was carried out on 106 patients with chronic mechanical low back pain. T1, T2 sagittal lumbar MRI scans were used to assess the severity of LDD and Modic changes. 62 SNVs in ten candidate genes (ACAN, IL1A, IL1B, IL6, MMP3, ADAMTS4, ADAMTS5, TIMP1, TIMP2 and TIMP3) were genotyped on Sequenom MassARRAY iPLEX platform. Multiple linear regression analysis was carried out using PLINK 1.9 in accordance with additive genetic model. In-silico functional analysis was carried out using Provean, SIFT, PolyPhen and Mutation Taster.


RESULTS
Mean age was 52.42±9.42 years. 74 (69.8%) were females. The rs2856836, rs1304037, rs17561 and rs1800587 variants of the IL1A gene were associated with the severity of LDD and Modic changes. The rs41270041 variant of the ADAMTS4 gene and the rs226794 variant of the ADAMTS5 gene were associated with severity of LDD while the rs34884997 variant of the ADAMTS4 gene, the rs55933916 variant of the ADAMTS5 gene and the rs9862 variant of the TIMP3 gene were associated with severity of Modic changes. The rs17561 variant of the IL1A gene was predicted as pathogenic by the PolyPhen prediction tool.


CONCLUSIONS
SNVs of candidate genes in ACAN metabolic pathway are associated with severity of LDD and Modic changes in patients with chronic mechanical low back pain. Predictions of in-silico functional analysis of significant SNVs are inconsistent.