TranSNPs: A class of functional SNPs affecting mRNA translation potential revealed by fraction-based allelic imbalance

Toll-like receptors and IL-7 as potential biomarkers for immune-mediated necrotizing myopathies

We aimed to verify whether the immune system may represent a source of potential biomarkers for the stratification of immune-mediated necrotizing myopathies (IMNMs) subtypes. A group of 22 patients diagnosed with IMNM [7 with autoantibodies against signal recognition particle (SRP) and 15 against 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR)] and 12 controls were included. A significant preponderance of M1 macrophages was observed in both SRP+ and HMGCR+ muscle samples (p < 0.0001 in SRP+ and p = 0.0316 for HMGCR+ ), with higher values for SRP+ (p = 0.01). Despite the significant increase observed in the expression of TLR4 and all endosomal Toll-like receptors (TLRs) at protein level in IMNM muscle tissue, only TLR7 has been shown considerably upregulated compared to controls at transcript level (p = 0.0026), whereas TLR9 was even decreased (p = 0.0223). Within IMNM subgroups, TLR4 (p = 0.0116) mRNA was significantly increased in SRP+ compared to HMGCR+ patients. Within IMNM group, only IL-7 was differentially expressed between SRP+ and HMGCR+ patients, with higher values in SRP+ patients (p = 0.0468). Overall, innate immunity represents a key player in pathological mechanisms of IMNM. TLR4 and the inflammatory cytokine IL-7 represent potential immune biomarkers able to differentiate between SRP+ and HMGCR+ patients.

OUP accepted manuscript

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.