Introduction: Chronic low back pain (cLBP) is a heterogeneous condition defined as low back pain that has been present for greater than 3 months and has been an ongoing problem for at least half the days in the past 6 months1. Individuals differ in their experience of pain, and it has been suggested that these differences may be related to genetic variations between individuals2. Human genetic variations are reflected in the differences in DNA sequence that occur naturally between individuals in a given population. Variants primarily include single nucleotide polymorphisms (SNPs), insertions and deletions, copy number variations, structural variations like inversions and translocations, tandem repeats, and other chromosomal rearrangements3. The aim of this study was to identify the most frequently occurring genetic variations/variants present in a cLBP population.
Methods: Saliva samples were collected from 1000 cLBP patients. After DNA extraction from the saliva, whole genome sequencing (WGS) was performed using the Illumina NovaSeq 6000. The data generated on the NovaSeq 6000 was converted to FASTQ files using Illumina’s bcltofastq conversion software. The quality of each paired FASTQ file was checked using FASTQC. 31 samples were not able to be sequenced and were therefore excluded from the analysis. NVIDIA Parabricks was used to run the standard Genome Analysis Toolkit (GATK) Mutect2 pipeline for the analysis of WGS data. This pipeline includes alignment to the GRCh38 human reference genome, somatic variant calling with Mutect2 using both the germline resource as well as the panel of normals provided by GATK, and variant filtering using FilterMutectCalls. Identified somatic variants were annotated with Variant Effect Predictor. Variants occurring within the top 20 FrequentLy mutAted GeneS (FLAGS) were omitted4, and the resulting set of somatic variants were subsequently plotted using maftools.
Results: Several types of genetic variants were detected in the cLBP cohort including SNPs, insertions, and deletions. Nonsynonymous variants were classified using the Sequence Ontology terms for all variants that Ensembl defines as having a moderate to high disruptive impact on the resulting proteins. The top 5 nonsynonymous genetic variants identified in 969 patient samples were associated with the following genes: MUC5AC (87%), EPPK1 (81%), MUC19 (70%), NBPF9 (68%), and CCDC187 (65%). These genes are involved in pathways that regulate neuronal development, immune response and inflammation.
Discussion: Study of genetic variants provides insights into possible contributors to the biological processes involved in chronic low back pain and helps to identify potential targets for treatments. Our results indicate that a significant number of genetic variants are present in the cLBP population. The identification of these variants has potential diagnostic and prognostic utility in cLBP research. For example, with the complex nature of pain involving various mechanisms, genetic variants could serve as promising biomarkers to identify individuals with cLBP who may have differential response to treatment. Future studies will explore the relationship of these genetic variants, the experience of cLBP and its outcomes.