The non-coding genome in genetic brain disorders: new targets for therapy?

Abstract

The non-coding genome, consisting of more than 98% of all genetic information in humans and once judged as ‘Junk DNA’, is increasingly moving into the spotlight in the field of human genetics. Non-coding regulatory elements (NCREs) are crucial to ensure correct spatio-temporal gene expression. Technological advancements have allowed to identify NCREs on a large scale, and mechanistic studies have helped to understand the biological mechanisms underlying their function. It is increasingly becoming clear that genetic alterations of NCREs can cause genetic disorders, including brain diseases. In this review, we concisely discuss mechanisms of gene regulation and how to investigate them, and give examples of non-coding alterations of NCREs that give rise to human brain disorders. The cross-talk between basic and clinical studies enhances the understanding of normal and pathological function of NCREs, allowing better interpretation of already existing and novel data. Improved functional annotation of NCREs will not only benefit diagnostics for patients, but might also lead to novel areas of investigations for targeted therapies, applicable to a wide panel of genetic disorders. The intrinsic complexity and precision of the gene regulation process can be turned to the advantage of highly specific treatments. We further discuss this exciting new field of ‘enhancer therapy’ based on recent examples.

Genetic regulation of lncRNA expression in the whole human brain

“…Furthermore, 29 significantly SNP-enriched neurological disease-brain region pairs including six neurological diseases (about 6.4% of all neurological diseases) were identified: insomnia (mean OR = 27.73), MDD (mean OR = 19.49), Parkinson’s disease (PD) (mean OR = 35.07), schizophrenia (mean OR = 15.21), depression (mean OR = 18.45), and bipolar (mean OR = 23.27) ( Figure 6a ). Conversely, only ten such non-neurological disease-brain region pairs (involving about 1.9% non-neurological diseases) showed a close correlation between the lncRNA eSNPs identified in brain tissues and neurological diseases with respect to the diseases ( OR = 3.47, P = 2.82 ×10 -2 ) and the disease-brain region pairs ( OR = 13.23, P = 3.15 ×10 -14 ) ( Figure 6b ). Figure 6c shows that the SNP-enriched neurological diseases encompass more brain regions than the non-neurological diseases.…”

“…Particularly enriched in the human brain, lncRNAs are key regulators in brain development, neuronal regeneration, synaptic plasticity maintenance, and CNS disorder pathogenesis [4][5][6][7][8] . Many of the variants associated with brain-related traits identified by GWAS are localized in the noncoding genome and regulate lncRNA expression [11][12][13][14][15][16][17][18] . Understanding the genetic regulation of lncRNAs in the brain is crucial for deciphering neuronal functions and CNS disorder mechanisms.…”

“…The genome-wide association studies (GWAS) have identified a large number of SNPs significantly associated with brain development and CNS disorders 11 . They exhibit marked tissue specificity 12 and are mainly located in the non-coding regions of the genome (approximately 93%), especially the lncRNA sequences [13][14][15] . Importantly, most of these non-coding SNPs play key roles in the regulation of lncRNA expression, which is a prerequisite for acting on proximal protein-coding target genes indirectly, further contributing to the pathogenesis of many CNS disorders [16][17][18] .…”

Solving the unsolved genetic epilepsies: Current and future perspectives

“…As complex as the gene regulatory mechanisms are, so too are the mechanisms that lead to their dysfunction. Although few studies have addressed these mechanisms on a large scale, 44,45 it is clear from the many published examples that virtually any conceivable mechanism for perturbing gene regulation is likely to be associated with disease 46 . To identify these mechanisms, WGS analysis needs to be combined with knowledge of where regulatory elements are located, for example, obtained from large‐scale computational studies that integrate multiple layers of omics data to predict the location of regulatory elements 39 .…”

Neighborhood based computational approaches for the prediction of lncRNA-disease associations

“…More than of the human genome consists of non-coding regions, considered in the past as “junk” DNA. However, in the last decades evidence has been shown that non-coding genome elements often play an important role in regulating various critical biological processes [ 1 ]. An important class of non-coding molecules which have started to receive great attention in the last few years is represented by long non-coding RNAs (lncRNAs), that is, RNAs not translated into functional proteins, and longer than 200 nucleotides.…”