Available online 29 February 2024, 101937

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Systemic Lupus Erythematosus (SLE) is a multifactorial autoimmune disease that arises from a dynamic interplay between genetics and environmental triggers. The advent of sophisticated genomics technology has catalyzed a shift in our understanding of disease etiology, spotlighting the pivotal role of non-coding DNA variants in SLE pathogenesis. In this review, we present a comprehensive examination of the non-coding variants associated with SLE, shedding light on their role in influencing disease risk and progression. We discuss the latest methodological advancements that have been instrumental in the identification and functional characterization of these genomic elements, with a special focus on the transformative power of CRISPR-based gene-editing technologies. Additionally, the review probes into the therapeutic opportunities that arise from modulating non-coding regions associated with SLE. Through an exploration of the complex network of non-coding DNA, this review aspires to decode the genetic puzzle of SLE and set the stage for groundbreaking gene-based therapeutic interventions and the advancement of precision medicine strategies tailored to SLE management.

Section snippetsSLE is the disease with genetic predisposition

Systemic Lupus Erythematosus (SLE), a paradigm of autoimmune disorders, is distinguished by its multifactorial nature, where genetic predisposition plays a cardinal role. This complex disease is marked by a dysregulated immune response, leading to rampant autoantibody production, immune complex formation, and subsequent multi-organ damage. Currently, SLE impacts more than 3 million individuals globally, presenting a significant health burden [1]. The disease's etiology, while still not fully

Most SLE risk variants are located in the non-coding region of the genome

The ascent of genomics has dramatically reshaped our comprehension of the intricate tapestry of the human genome [10,11]. At the forefront of this enlightenment, particularly in relation to complex disorders like SLE, are the critical investigations of genetic variants via genome-wide association studies (GWAS). These studies have systematically pinpointed a myriad of single nucleotide polymorphisms (SNPs) associated with an increased susceptibility to SLE [[12], [13], [14], [15]](Table 1). By

Identification the function of non-coding variants is challenging

Deciphering the specific roles of non-coding genomic variants remains a formidable scientific challenge. Non-coding regions, once dubbed the“dark matter”of the genome due to their mysterious and seemingly inert nature, have shed this misnomer as contemporary research reveals their considerable functional potential. The advent of various analytical techniques, such as transcription factor binding assays, histone modification profiling, and studies of three-dimensional (3D) genome conformation,

Traditional methods to study the function of non-coding variants in SLE

The elucidation of non-coding genetic variants and their impact on systemic lupus erythematosus (SLE) is pivotal in comprehending the genetic underpinnings of this complex autoimmune disorder. Diverse techniques have been developed to investigate these variants, each providing distinct and valuable perspectives on their influence on SLE pathogenesis.

Expression Quantitative Trait Loci (eQTL) analysis stands out as a fundamental approach. It serves as a predictive model that links genetic

Unraveling non-coding variant functions using CRISPR-based methods

Traditional methodologies have been instrumental in the exploration of non-coding genetic variations, providing valuable insights into their association with gene function. However, these methods do not address the biggest challenge of exploring the function of genetic variation in non-coding regions: elucidating the function of non-coding variants in situ, against a cell-specific background. The traditional methods are constrained by their intrinsic inability to replicate the sophisticated

Therapeutic potential of non-coding regions associated with SLE

The therapeutic exploitation of non-coding genomic regions, particularly enhancers, presents compelling potential in the realm of disease treatment, specifically for autoimmune conditions SLE. Enhancers, as pivotal regulatory elements, exhibit remarkable cell-type specificity; an attribute that positions them as promising candidates for targeted gene therapy. The maturation of CRISPR gene-editing technology has fast-tracked this potential, enabling precision modification of enhancers to

Perspectives

SLE is a multifaceted and polygenic autoimmune disease characterized by diverse genetic factors contributing to its etiology. Pioneering developments in genetics and molecular biology have significantly enhanced our capacity to “observe” associations between genetic variants and SLE phenotypes through GWAS. Yet, as we delve deeper into the genetic landscape of SLE, we are confronted by an intriguing paradox — “The more we watch, the less we know.” This conundrum arises from the fact that the

Practice points●

SLE is a genetically predisposed disease, but the mechanisms of genetic mediates SLE risk is not yet fully defined.

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It is noteworthy that since SLE is a highly genetically heterogenous disease, disease-related genetic testing is helpful for individualized and effective treatment after SLE individuals are diagnosed.

Research agenda●

GWAS suggests genetic variants associated with SLE, but the underlying causal variants need to be ascertained thoroughly and systematically.

●

The genetic participation in the pathogenesis of SLE still needs to be intensively investigated, although there are many approaches to separate the effects of coding and non-coding region variants on the pathogenesis of SLE, how to comprehend the synergistic effect between coding and non-coding region variants organically and systematically needs to be

CRediT authorship contribution statement

Yutong Zhang: Writing – original draft. Guojun Hou: Writing – original draft, Writing – review & editing. Nan Shen: Conceptualization.

Declaration of competing interest

None.

Acknowledgements

The research underpinning the work presented has received funding from the following sources: National Natural Science Foundation of China (31930037, 32141004 and 82302024), Shanghai Science and Technology Innovation Plan (21Y31900200).

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