KC's hyperproliferation, is correlated with its promoter's hypermethylation [70] (Figure 1). The Wnt pathway plays a key role in PsO by regulating the proliferation and differentiation of KCs [71]. Additional evidence exists regarding the non-malignant effect of specialized promoters' methylation status in a human malady. The promoter of the SHP-1 isoform was found to be hypomethylated in psoriatic lesions, indicating that the methylation of *SHP-1*'s promoter in PsO might be related to the STAT3's binding affinity, due to the upregulation of the latter in the lesional skin [72] (Figure 1). The same group also studied ID4, a protein that participates in cell proliferation, differentiation and apoptosis, as well as in tumorigenesis (cholangiocarcinoma, breast cancer, lymphoma). *ID4* promoter hypermethylation promoter was linked with parakeratosis, which refers to deficient development of KCs, and skin-related cellular differentiation in PsO cases [73] (Figure 1). The promoter of the *p16INK4a* gene, which is involved in hyperproliferative skin diseases, was found to be hypermethylated in psoriatic skin [74]. Sheng et al. investigated the hypomethylation of *CYP2S1* and further identified the hypomethylation of two extra loci within the *CYP2S1* region, leading to its upregulation in psoriatic tissues [75] (Figure 1). Members of the growth arrest and DNA damage-inducible gene family, such as *GADD45a* and *GADD45b*, exhibit low expression in psoriatic lesional skin [76]. Specifically the expression *GADD45a*, which has a demethylase activity, was found to be positively correlated with IFN-γ and TNFα expression. Its depletion leads to hypermethylation of *UCHL1* promoter in PsO cases [77]. The expression of *WIF1*, an inhibitor of Wnt signaling, is linked to its promoter's demethylation, which is a result of *DNMT1* silencing, while its hypermethylation is a consequence of *DNMT1* overexpression. Indirubin, a traditional medicine utilized for treating various inflammatory diseases, inhibits the expression of *DNMT1* and the methylation of *WIF1* promoter, as well as the expression of Wnt-pathway core genes, such as *FZD2*, *FZD5*, and β-catenin [78].

#### *3.2. DNA Methylation in Immune Cells*

Despite the predominant role of KCs in the pathogenesis of cutaneous diseases, PsO, as an autoimmune disorder, is driven by the substantial activation of multiple immune cell types, which further stimulate KCs' proliferation through the secretion of pro-inflammatory cytokines. Moreover, PsO is considered to be a T-cell-mediated autoimmune disease, since the role of Th cells, as well as their secretome, has been extensively studied and targeted therapeutically [79]. Immune cells can be isolated either from lesional skin or PBMCs. The latter is a non-invasive approach and has therefore been established as the standard method for studying PsO-related immune cells.

PBMCs from psoriatic patients have been shown to exhibit aberrant DNA methylation, for example, hypermethylation of *p14ARF*, *MBD2*, *MeCP2* and hypomethylation of *DNMT1* [69] (Figure 1). Genome-wide DNA methylation profiling of CD4+ T cells unveiled the significantly hypermethylated promoters of immune-related X chromosome genes, such as *SLITRK4*, *EMD*, *ZIC3*, *CXorf40A*, *HDAC6*, *IKBKG*, *SH3KBP1*, *OTUD5*, *NDUFA1*, *WNK3* and *MSL3* [80]. Recent studies uncovered the hypermethylated profile of genes that are implicated in the TGFβ pathway, including *SNX25, STAD3* and *BRG1*, from whole blood samples of monozygotic twins [81] (Figure 1). Additional comparison of CD8+ T cells in monozygotic twins from psoriatic samples and healthy controls identified 110 hypermethylated and 224 hypomethylated loci. DNA methylation analyses of CD8+ T cells between PsO, psoriatic arthritis cases and healthy controls revealed numerous differences, indicating that DNA methylation screening in these cell subtypes could act as a potential diagnostic biomarker [82]. Furthermore, genome-wide DNA methylation profiling from peripheral whole blood displayed that *FOXP3* is hypermethylated, leading to reduced Treg levels in patients with PsO [83] (Figure 1).

Bisulfite-sequencing on a targeted gene panel revealed the low methylation levels of *p15* and *p21* promoters in hematopoietic stem cells; *p15*, *p21* and *p16* exhibit similar methylation patterns and play a well-established role in controlling cell cycle [84,85] (Figure 1). Research conducted in CD4+ T cells of monozygotic twins with PsO showed the promoter

hypomethylation of transcription-regulator *ZNF99* gene. In CD8+ T cells associated with PsO, hypomethylation of the serine/threonine MAST3 and MTOR kinases, and hypermethylation of the *PM20D1* peptidase gene was shown [86] (Figure 1).

#### **4. Histone Modifications**

The post-translational histone modification (PTM) process is an important mechanism of gene expression regulation since these proteins directly participate in DNA organization and accessibility. Briefly, nucleosomes are the fundamental subunit of chromatin and are composed of histone octamers. Each histone (H2A, H2B, H3 and H4) is represented twice in the nucleosome structure that forms a binding scaffold for 147 DNA base pairs [87]. PTMs usually occur in the overhanging N-terminal tails of histones, resulting in either enhanced transcriptional activity through nucleosome unwinding and euchromatin formation, or strengthened DNA-histone interactions that form heterochromatin and suppress gene expression. Several types of histone modifications, implicated in both gene silencing and enhanced transcription, have been described, including adenylation, methylation, phosphorylation, ADP ribosylation and sumoylation among others [88].

#### *4.1. Histone Modifications in KCs*

Epigenetic regulation of KCs is an essential part of chronic skin inflammation. Recent research demonstrated that decreased H3K9 dimethylation leads to increased IL-23 expression in KCs; H3K9me2 levels play a key role in regulating basal and TNF-induced IL-23A expression [89]. H3K27me3 and *EZH2*, a histone methyl-transferase enzyme, were significantly enriched in cutaneous biopsies from individuals with PsO when compared to healthy controls. *EZH2* is implicated in cell proliferation and tumorigenesis [90] and thus its transcriptional silencing affects the proliferation and differentiation of KCs.

Sirtuin (SIRT) is a family of (NAD+)-dependent deacetylases, involved in cell apoptosis, gene transcription, tumor development, autoimmune inflammation and epigenetic modification processes. Specifically, *SIRT1* regulates inflammation-associated signaling pathways [91,92]. Hwang et al. showed that *HDAC-1* is overexpressed and *SIRT1* displays a decreased expression in skin biopsies of patients with PsO [93]. GLS1-mediated glutaminolysis induces proliferation of KCs in PsO and promotes Th17 and γδ T17 cell differentiation through the acetylation of H3 on Il17a promoter [94]. The first whole-genome study for histone modifications showed that H3K27 is hyperacetylated in 60% of the overexpressed gene promoters in cutaneous lesions and binding sites of overexpressed TFs in lesional skin, such as *GRHL* [95] (Figure 1). *WT1*, a TF implicated in cell proliferation and apoptosis, is highly expressed in psoriatic skin lesions and has two binding sites in the IL-1β gene promoter. IL-1β is produced by KCs, with its gene promoter showing considerably high histone acetylation levels that positively correlate with histone acetyltransferases p300 (P300) expression [96]. H3K27 hyperacetylation of *RPL22* promoter in PsO lesional skin leads to overexpression of *RPL22*, which is linked to CyclinD1 upregulation, inducing KC proliferation. *RLP22* also prevents KC apoptosis and is involved in CD4+ T cell chemotaxis [97].

#### *4.2. Histone Modifications in Immune Cells*

PBMCs from PsO patients exhibit higher H3K4 methylation levels when compared to healthy individuals. Responders and non-responders in biological therapies tend to have different H3K27 and H3K4 methylation profiles [98] (Figure 1). Regulation of Th17 cell differentiation can be achieved by TCR-induced H3K27 demethylase Jmjd3, which is overexpressed and decreases H3K27me3 levels. Jmjd3 controls chromatin accessibility of numerous Th17-related loci, such as Th17-specific gene promoters, and induces Th17 cell differentiation by decreasing H3K27me3 enrichment [99]. Zhang et al. unveiled decreased H4 acetylation in psoriatic PBMCs, downregulation of *P300*, *CBP* and *SIRT1* as well as increased HDAC1 levels [100] (Figure 1).

#### **5. Non-Coding RNAs**

Non-coding RNAs (ncRNAs) are RNA molecules that are not translated into functional proteins. They are typically grouped into distinct families according to their size and function. Most ncRNA families play a key role in directly or indirectly affecting gene expression at the transcriptional and post-transcriptional level. The microRNA (miRNA) family consists of small (~18–23 nucleotides), single-stranded RNA molecules that are loaded on and guide the RNA-induced silencing complex (RISC) to mediate mRNA degradation and/or translation suppression [101]. Circular RNAs (cirRNAs) form a continuous loop through their linkage on the 5 and 3 termini, establishing them as stable, exonuclease-proof RNA molecules with numerous roles in transcriptional and translational regulation [102]. Long non-coding RNAs (lncRNAs) are defined as longer than 200 nucleotides transcripts with an emerging role in the pathogenesis of autoimmune diseases [91]. LncRNAs and circRNAs can regulate gene expression by participating in processes that alter chromatic conformation, forming triplexes with DNA as well as interfering with transcription enzymes [103].

Due to the abundance of the ncRNAs implicated and studied in the context of PsO, we conducted an exhaustive literature search regarding the differential expression of ncRNAs in cutaneous biopsies, serum levels as well as PBMCs. We filtered the screened studies according to the importance of the ncRNAs under study, evaluated through their statistically significant differential expression in contrast to healthy controls as well as their identified, direct or indirect target genes. Non-coding RNAs screened by more than one study were also identified as important regulators of the psoriatic transcriptome.

#### *5.1. MiRNAs in KCs*

The immortalized nontumorigenic human epidermal (HaCaT) cell line and KCs have been widely used in PsO studies as they are easy to isolate and provide reliable results regarding the transcriptome and proteome profile of the disease [104]. Fibronectin 1 (*FN1*) and integrin subunit α9 (*ITGA9*) signaling pathways are both implicated in cell motility and direct targets of miR-4516, which was found to be downregulated in cutaneous PsO biopsies (Figure 1). Specifically, Chowdhari et al. found significant overexpression of both *FN1 and ITGA9* as well as STAT3 in PsO, which could be partly responsible for the KCs activated state in lesional skin since it induces proliferation and terminal differentiation [105]. MiR-424 has been also investigated as a potential biomarker in PsO given its regulatory role in signaling pathways that orchestrate differentiation and cell cycle regulation in KCs [106] (Figure 1). The decreased miR-424 expression has been associated with the overexpression of *MEK1* and *CCNE1*, members of the metabolic pathways responsible for the abnormal KC proliferation observed in the clinical manifestation of the disease; however, the exact regulatory mechanism has yet to be defined. Another miRNA whose down-regulation has been associated with PsO is miR-145, a molecule that has been widely studied in immunemediated inflammatory diseases due to its inhibitory role in cell proliferation and immune responses [107] (Figure 1). It has been observed that miR-145 downregulation promotes proliferation and chemokine expression in the lesional skin, as it directly targets *MLK3*, which in turn regulates STAT3 and NF-κB TFs. Increased expression of miR-21 has been associated with the epidermal downregulation of *TIMP-3*, leading to the activation of *TACE*, which subsequently induces TNFα overexpression and a psoriasis-like phenotype [108] (Figure 1).

MiR-200c, a miRNA involved in apoptosis and senescence of KCs, was found to be upregulated in lesional skin compared to non-lesional skin biopsies and healthy controls [109] (Figure 1). MiR-200c is also known to directly repress *SIRT1*, which has a key role in oxidative stress and the regulation of skin inflammation, as well as *eNOS* and *FOXO1,* which have a significant role in regulating the function and preservation of endothelial cells. MiR-200c expression also shows a positive correlation, without being a direct regulator of molecules involved in inflammation such as *IL-6* and *COX-2*, and plaque destabilization such as *MMP-1* and *MMP-9*. Table 1 presents further deregulated miRNAs in KCs from PsO patients.

**Table 1.** Deregulated ncRNAs in PsO in keratinocytes.

Abbreviations: ncRNA, non-coding RNA; miR, microRNA; HEK, human embryonic kidney cell line; HaCaT, human epidermal keratinocyte cell line.

#### *5.2. MiRNAs in Immune Cells and Serum*

Fu et al. showed that miR-138, whose expression levels regulate the balance between Th1 and Th2 cells by targeting RUNX3, was found downregulated in PBMCs of Pso patients [125] (Figure 1). RUNX3 is an important TF regulating cell proliferation and apoptosis, and its increased expression in PsO classifies it as a key gene for PsO susceptibility. MiR-143 downregulation exhibits a significant correlation with PsO severity; specifically, patients with stable disease stages showed higher miR-143 expression levels, while patients in progressive stages had lower expression levels [126] (Figure 1). *BCL2*, which is thought to be responsible for shortening the lifetime of cortical cells, has been proven a direct target of miR-143 [126]. Additionally, García-Rodríguez et al. showed that the upregulation of miR-155 in PsO plasma samples is an important regulator of *SOCS1*, a susceptibility locus of PsO [127]. The miRNA-155/SOCS1 pathway is targeted in macrophages by Vitamin D or Vitamin D Receptor (VDR) signaling to reduce the inflammatory response [128] (Figure 1). The upregulation of miR-210 in CD4+ T cells has also been found to significantly correlate with PsO onset and progression, mainly by targeting *FOXP3* [129] (Figure 1). *FOXP3* displays a central role in the development and diverse functionality of Treg cells, as it appears to facilitate their differentiation through genetic programming [129], thus establishing it as an important contributor to the pathogenesis of the disease. In normal CD4+ T cells, overexpression of miR-210 can indirectly, contribute to the expression of inflammatory cytokines such as IFN-γ and IL-17 while suppressing other cytokines such as IL-10 and TGF-β, which are secreted by Tregs. Table 2 presents further deregulated miRNAs in PBMCs and plasma from PsO patients.

**Table 2.** Deregulated ncRNAs in PsO in immune cells and plasma.

Abbreviations: ncRNA, non-coding RNA; miR, microRNA; PBMCs, peripheral blood mononuclear cells.

#### *5.3. LncRNAs in PsO*

Despite the established regulatory role of lncRNAs, there is still limited evidence regarding their participation in PsO pathogenesis. The maternally expressed gene 3 (*MEG3*), a downregulated lncRNA in HaCaT cells, has an identified miR-21 binding site, thus acting as a sponge or decoy for miR-21. It is postulated that *MEG3* participates in the regulation of PsO KCs proliferation and apoptosis as well as the expression of *CASP8* through its interplay with miR-21 [135]. By utilizing a luciferase reporter assay, it was confirmed that MSX2P1, a lncRNA overexpressed in HaCaT and KCs, is a direct target of miR-6731, thus negatively affecting its function on other RNAs. Further research in IL-22-stimulated KCs revealed MSX2P1's indirect role in increasing the protein levels of S100A7, IL-23, NFκB, TNFα, IL-12β, HLA-C, and CCHCR [136]. Psoriasis-susceptibility-related RNA Gene Induced by Stress (PRINS) [137] and GAS5 [138] are lncRNAs displaying an under- and over-expression pattern, respectively, in the serum levels of patients with PsO. Specifically, plasma levels of PRINS transcripts were found to be down-regulated in patients with PsO, similar to its direct target *G1P3* and interacting partner *NPM*, while PRINS' miRNA targets that function as decoys, consisting of miR-124, miR-203a, miR-129, miR-146a and miR-9, were overexpressed, thus indicating a possible lncRNA–miRNA–mRNA axis of diagnostic value.

While the role of circRNAs in PsO progression remains obscure, CDR1as, a ciRNA significantly downregulated in cutaneous PsO biopsies, has been associated with numerous genes that are involved in the pathogenesis of the disease, such as *EGR3, GATA6, GATA3* and *FOXN3* [139]. However, the direct regulatory mechanism remains unclear (Figure 1). Xiaoxin Liu et al. also showed that circRNA hsa\_skin\_088763 was down-regulated in lesional skin compared to normal controls. It is postulated that this circRNA is indirectly associated with several PsO-related genes such as *GATA6*, *SIK2*, *IL17RD*, *EGR3*, *FAS*, *LRIG1*, and *PPARGC1A*, due to their shared regulatory ncRNAs (Figure 1), thus characterizing it as a competing endogenous RNA (ceRNA). A comprehensive list of all deregulated lncRNAs is presented in Tables 3 and 4, stratified based on the cell type under study.

**Table 3.** Deregulated lncRNAs in psoriasis in keratinocytes. In this table, miRNAs, which are targets of lncRNAs that function as decoys, are highlighted in bold.

Abbreviations: circRNA, circular RNA; lncRNA, long non-coding RNA; HEKs, human embryonic kidney cell line; HaCaT, human epidermal keratinocyte cell line; NHEK, normal human epidermal keratinocyte.

**Table 4.** Deregulated lncRNAs in psoriasis in serum. In this table, miRNAs, which are targets of lncRNAs that function as decoys, are highlighted in bold.

#### **6. Therapeutic Approaches Targeting the Epigenetic Mechanisms**

In recent years, biologic drugs targeting TNF, IL-23 and IL-17 and small-molecule drugs such as phosphodiesterase-4 (apremilast) and Janus kinase (JAK) inhibitors have been effective in plaque psoriasis clinical management. The predominant role of epigenetic modifications in the pathogenesis of complex diseases, as analyzed in the framework of PsO, establishes the therapeutic interventions targeting the epigenome, a promising clinical field. Numerous inhibitors of molecules that participate in the epigenetic reprogramming, including DNMTs and HDAC, have been extensively utilized in clinical trials. Recently FDA-approved agents, combined with cytotoxic chemotherapies, show promising results despite their limited implementation, mostly on hematologic malignancies [146]. Such repurposing approaches, already applicable in cancer, might prove beneficial in PsO considering the diverse cell subtypes that are involved in its pathogenesis.

Reservatol, a polyphenol with anti-inflammatory properties, was shown to stimulate the expression of *SIRT1* leading HaCaT cells to death [147]. Recently, trichostatin A (TSA), a class I and II HDAC inhibitor (HDACi), significantly decreased KC's proliferative phenotype, both in vitro and in vivo [148]. These results are in accordance with previous studies examining the effect of TSA on human Tregs and the prevention of their differentiation into IL-17A producing cells through the overexpression of *FOXP3* [149,150]. Another example of an epigenetic-driven therapeutic intervention is peroxisome proliferator-activated receptor gamma (PPARγ) and/or alpha (PPARα) antagonists, which inhibit *AQP3* expression in KCs, while agonists induce the differentiation of the latter, establishing them as a topical treatment for cutaneous diseases such as PsO. AQP3 is a water channel protein that regulates multiple aspects of KCs [151,152], with its expression induced by HDACs, particularly HDAC3, via acetylated transcription factors such as the family of p53 and PPARs.

MiRNA-mediated gene expression regulation is another approach in the anti-PsO therapeutic arsenal. MiRNAs exhibit a diverse role through their interaction with numerous transcripts and can therefore affect multiple pathways implicated in PsO. Imiquimodinduced psoriasis-like murine models were treated with a miR-210 antisense moleculecontaining topical gel. Based on the predominant role of miR-210 in the regulation of multiple genes expressed in CD4+ T cells, as analyzed before, cellular markers of cell proliferation were significantly decreased in KCs, while the imbalance of CD4+ T cells was reversed to a non-pathological state [153]. Another topical-application approach referred to the usage of quaternized starch (Q-starch) as a miRNA-197 delivery system in lesionalxenotransplantated mice, alongside ultrasound for increased cutaneous permeability. The Q-starch/miRNA-197 complex was able to alleviate the psoriatic symptoms through the targeting of IL-22RA1 and IL-17RA transcripts, nevertheless without a homogeneous effect along the transplanted psoriatic skin sample [154]. Locked nucleid acid (LNA) *anti-miR-21* oligonucleotides were also assessed for their efficacy as a therapeutic approach in a doubleknockout PsO murine model, displaying an important amelioration in the histopathological symptoms of the disease [108], further highlighting the role of miR-21 overexpression in PsO. Additionally, Qiao et al. inhibited miR-6731 in IL-22-stimulated HaCaT cells, showing an increased proliferative activity of the IL-22-induced KCs, while protein expression levels of therapeutic targets of PsO, including TNFα, IL-23, HLA-C as well as inflammatory molecules such as NF-κB and the PSORS1 locus were significantly overexpressed. These results imply a protective role of miR-21 in the pathogenesis of PsO [135].

#### **7. Discussion**

The etiopathology of PsO lies in the complex interactions between genetic, immunological and environmental factors, including but not limited to the imbalance in the gut and skin microbiome, as well as lifestyle and stress-inducing factors. The effect of genome– environment interactions can extend to the epigenome with direct and indirect modulation of DNA methylation and histone modifications in PsO-related loci. These cascading effects are further amplified by the function of ncRNAs, which in numerous ways regulate the expression of PsO-associated genes and pathways. However, epigenetic modifications and deregulation of ncRNA molecules occur in the spectrum of both KCs and immune cells, while the polygenicity of PsO aggravates candidate-gene approaches, thus obscuring the characterization of the exact mechanisms that alter the disease predisposition in individuals. Furthermore, skin tissue and immune cells consist of abundant and heterogeneous cellular populations, where each cell type exhibits a distinct epigenomic and, thus, transcriptomic profile. This diversity dramatically increases the complexity of research conducted in the field. The secretome of implicated cell types is affected by the distinct epigenetic and regulatory profiles of each sub-population, which is triggered by stress-inducing factors and the disease progression (Figure 1). Nevertheless, with the advent of next-generation sequencing, modern flow cytometry techniques and genome-wide analyses, the epigenetic reprogramming that participates in homeostasis disruption and the cutaneous inflammatory cascade is gradually elucidated, leading to the clarification of PsO pathogenesis.

Even though the epigenetic modifications cannot be utilized as clinical biomarkers for the disease progression, shedding light upon the molecular mechanisms governing their development and maintenance can potentially uncover novel therapeutic targets associated with the induced epigenetic changes. In contrast, ncRNAs and especially miRNAs have a rich history of being used as disease biomarkers and targets of therapeutic intervention, despite the difficulties imposed by the off-target effects due to the wide spectrum of pathways affected by miRNAs.

Future studies should focus on developing methods for reversing DNA methylation in the context of PsO therapeutic interventions, as a way to understand the molecular discrepancies between responders and non-responders to therapy. Additionally, the catalogue of ncRNAs implicated in PsO should be significantly enriched to provide an extensive view of the targeted genes set and an accurate description of the vast interactome that underlies

PsO. The gene regulatory networks that will emerge from the combination of epigenetic and ncRNA meta-analyses, as well as the genetic predisposition to PsO, will facilitate the development of a new generation of highly precise therapeutic approaches with minimum adverse effects and maximum impact.

**Author Contributions:** Conceptualization, C.A. and Y.V.; resources, C.A., P.A., P.X. and P.N.; data curation, C.A., P.A., P.X., P.N., G.K.G. and Y.V.; writing—original draft preparation, C.A., P.A., P.X., P.N. and G.K.G.; writing—review and editing, C.A., K.G., P.A., P.X., P.N., G.K.G., S.G. and Y.V.; visualization, C.A, P.X. and Y.V.; supervision, Y.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** The publication of this article has been financed by the Research Committee of the University of Patras.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The datasets generated or analyzed during the current study are available from the corresponding author on reasonable request.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

**Lucia Martin-Gutierrez 1, Robert Wilson 2, Madhura Castelino 2, Elizabeth C. Jury 1 and Coziana Ciurtin 3,\***

**Abstract:** Sjögren's syndrome (SS) is a heterogeneous autoimmune rheumatic disease (ARD) characterised by dryness due to the chronic lymphocytic infiltration of the exocrine glands. Patients can also present other extra glandular manifestations, such as arthritis, anaemia and fatigue or various types of organ involvement. Due to its heterogenicity, along with the lack of effective treatments, the diagnosis and management of this disease is challenging. The objective of this review is to summarize recent multi-omic publications aiming to identify biomarkers in tears, saliva and peripheral blood from SS patients that could be relevant for their better stratification aiming at improved treatment selection and hopefully better outcomes. We highlight the relevance of pro-inflammatory cytokines and interferon (IFN) as biomarkers identified in higher concentrations in serum, saliva and tears. Transcriptomic studies confirmed the upregulation of IFN and interleukin signalling in patients with SS, whereas immunophenotyping studies have shown dysregulation in the immune cell population frequencies, specifically CD4+and C8+T activated cells, and their correlations with clinical parameters, such as disease activity scores. Lastly, we discussed emerging findings derived from different omic technologies which can provide integrated knowledge about SS pathogenesis and facilitate personalised medicine approaches leading to better patient outcomes in the future.

**Keywords:** Sjogren's syndrome; patient stratification; clinical relevance; multi-omics

#### **1. Introduction**

Sjögren's syndrome (SS) is an autoimmune rheumatic disease (ARD) characterised by a chronic inflammatory process associated with lymphocytic infiltrate affecting the exocrine glands. The disease has significant heterogeneity in clinical presentation according to age at disease onset, type of organ involvement, as well as serological features and response to therapy [1,2]. When the disease occurs on its own, it is called primary SS (pSS), while when it accompanies other autoimmune conditions, it is defined as secondary SS (sSS). Various classification criteria have been used to define pSS and exclude mimicking pathology, with the most recent ones being the data and consensus-driven American College of Rheumatology/European League Against Rheumatism Classification Criteria proposed in 2016 [3].

There are currently no universally accepted classification criteria for sSS and some experts argue that making a distinction between pSS and sSS is not adequate anymore, as both phenotypes represent the same disease [4]. Moreover, the classification criteria validated in adults have minimal utility in SS with childhood-onset (defined as disease onset before the age of 18 years), as the disease presentation in children and young people, although rare, is different [5]. This, in addition to the lack of validated classification criteria

**Citation:** Martin-Gutierrez, L.; Wilson, R.; Castelino, M.; Jury, E.C.; Ciurtin, C. Multi-Omic Biomarkers for Patient Stratification in Sjogren's Syndrome—A Review of the Literature. *Biomedicines* **2022**, *10*, 1773. https://doi.org/10.3390/ biomedicines10081773

Academic Editor: Marianna Christodoulou

Received: 22 June 2022 Accepted: 20 July 2022 Published: 22 July 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

for childhood-onset SS, further limits the research opportunities for younger people affected by this disease [6].

The disease manifestations vary among patients; some have predominant exocrine glandular involvement leading to dryness, which is the hallmark symptom of the disease. Glandular involvement manifests as dry mouth (xerostomia), dry eyes (xerophthalmia), dry skin (xerosis cutis), as well as vaginal dryness, dry cough, pancreatic dysfunction, salivary gland inflammation/enlargement (e.g., parotitis), etc., while patients with extraglandular involvement can experience frequent musculoskeletal, haematological, and rarely hepatic, renal, pulmonary, cardiac, peripheral or central nervous system manifestations, as well as less specific symptoms of fatigue (common) or fever and lymphadenopathy (less common) [7]. Clinical presentation usually guides the disease management, which is largely symptomatic for glandular manifestations and involves the use of immunosuppressive treatment approaches in patients with more severe organ involvement [8]. The evidence for the efficacy of various therapies currently recommended for the management of SS is modest overall [9,10], emphasising the need for better research.

As a direct consequence of the disease pathogenesis being centred around the process of autoimmune epithelitis, powered by the interplay between the cells of the innate and adaptive immune systems, and activated by interferons and other pro-inflammatory cytokines leading to chronic immune activation in a host with genetic susceptibility [11], various disease fingerprints can be identified from the peripheral blood, as well as serum, saliva, tears and salivary gland biopsies.

Significant progress has been achieved recently in clinical research in terms of better patient clinical and molecular characterisation [12], but despite this, the management of this condition remains challenging because of patient heterogeneity and various limitations of the way the disease activity and response to treatment are measured. These aspects very likely contribute to the lack of significant treatment advances in SS, despite preliminary signals of the efficacy of various biologic agents in clinical trials [13–15]. Better research into disease pathogenesis and distinct clinical and molecular phenotypes will hopefully enable better patient selection for available therapies as well as new target discoveries.

#### **2. Materials and Methods**

This review aimed as identifying the main papers published since 2000 investigating multi-omics (cytokine profiling in serum, tears, saliva, immunophenotyping, genomic, transcriptomic and metabolomic) studies in SS in an effort to identify distinct patient groups (endotypes) which can inform meaningful stratification for better disease characterisation and improved treatment strategies. Publications selected for this review followed these inclusion criteria: Sample size higher than 10, the inclusion of age and gender-matched healthy controls, and data on at least one omic analysis in any biologic sample relevant to SS (blood, serum, tears, saliva, salivary gland biopsy) and published in English. We presented the most informative papers found in the literature in tables, summarising the study design, sample size, control groups, main findings and their clinical relevance.

#### **3. Results**

#### *3.1. Multi-Omic Biomarkers for Patient Stratification*

#### 3.1.1. Tear Biomarkers

One of the main symptoms of pSS is dry eye (xeropththalmia) as a result of lymphocytic infiltration of the lacrimal glands. Tears represent a valuable biological sample resource because of their proximity to the site of glandular inflammation and they might contain biomarkers that could help us to understand the pathogenesis of pSS, improve its diagnosis and have therapeutic implications.

Recently, several studies have concentrated their efforts on identifying those biomarkers through either cytokine, metabolomic or proteomic tear profiling (Table 1).

In this context, Chen et al. [16] determined the cytokine profile of tears, measured by a 27-plexcytokine assay in 29 pSS patients and 20 gender/age matched controls (non-SS sicca subjects and healthy controls—HCs). Elevated levels of pro-inflammatory cytokines, such as interleukin (IL)-1 receptor agonist (ra), IL-2, IL-17A, interferon (IFN)-γ, Macrophage inflammatory protein-1-β (MIP-1b), and Rantes (Regulated upon Activation, Normal T Cell Expressed and Presumably Secreted) and anti-inflammatory interleukin 4 IL-4, were found in pSS patients compared to controls. Interestingly, higher cytokine levels correlated positively with eye dryness severity and negatively with Schirmer's test which measures the volume of tears secreted over 5 min [16]. These findings are validated by another study Willems et al., which also found an increased concentration of IFN-γ, tumor necrosis factor alfa (TNF-α), IL-2, IL-4, IL-6, IL-10, IL-12p70 and IL-5 in tears of pSS patients compared to HCs [17]. Moreover, they also verified the negative correlation between the Schirmer test and the concentration of IL-2, IL-4, IL-10 and IL-12p70 in tears.

Tears are composed of water, electrolytes, mucins and hundreds of different proteins and metabolites. Urbanski et al. identified a metabolic signature of tears comprising nine metabolites specific to pSS, compared to patients with non-immune dry eye disease [18]. Metabolomic quantification by mass spectrometry and liquid chromatography showed that three metabolites, serine, aspartate and dopamine, had lower concentrations whereas six lipids (including pro-inflammatory lysophosphatidylcholine [19], sphingomyelin, and phoshatidylcholine diacyl) had increased concentrations in pSS patients compared to the non-pSS Sicca controls. Moreover, age, sex, use of anticholinergic drugs, or the presence of anti-Ro/SSA antibodies did not influence the association between the metabolomic signature and the pSS status, suggesting that it is a true disease signature.

Tear proteomic analysis by Das et al. [20] using high performance liquid chromatography (HPLC) and mass spectrometry revealed the upregulation of 83 proteins and downregulation of 112 proteins in pSS patients compared to HCs. Enrichment pathway analysis of upregulated proteins included leukocyte trans-endothelial migration, protein-lipid complex remodelling and collagen catabolic pathway. On the other hand, the analysis of downregulated proteins indicated that pathways, such as glycolysis and amino acid metabolism, were diminished in tears from pSS patients. The relationship between proteomic biomarkers and clinical outcomes was not explored.

#### 3.1.2. Saliva Biomarkers

Dry mouth (xerostomia) is a key symptom of pSS occurring in more than 95% of patients as a consequence of autoimmune destruction of salivary glands [21,22]. Salivary gland pathology detected by salivary gland biopsy is included in the classification criteria for pSS, and in many patients, this is an essential diagnostic and prognostic tool. However, this is an invasive procedure that could lead to local complications in a minority of cases, [23] whereas the collection of saliva for research purposes is, in contrast, a noninvasive procedure. Biomarkers found in saliva could potentially reflect the pathogenesis of this disease. Therefore, many researchers have been aiming to identify those lately (Table 2).

One of the few studies examining the cytokine profile of unstimulated saliva of pSS patients using the Luminex platform found an increase in IFN-γ, IL-1, IL-4, IL-10, IL-12p40, IL-17, and TNF-α levels in pSS patients compared to non-SS and HCs [24]. Moreover, IL-6 levels were higher in pSS compared to HCs. Notably, unstimulated saliva flow rate correlated with INF-γ/IL-4 ratio and salivary gland biopsy focus score (the number of inflammatory infiltrates of at least 50 cells present in 4 mm2 of salivary gland area) correlated with TNF-α/IL-4 ratio in pSS, suggesting a predominant Th1 saliva signature. Years later, Chen et al. [16] reported enhanced levels of IP-10 (Interferon gamma-induced protein 10 or C-X-C motif chemokine ligand 10, CXCL10) and MIP-1α in saliva samples from pSS compared to HCs and a negative correlation between MIP-1α levels and both unstimulated whole saliva as well as the stimulated whole saliva flow rates.

**Table 1.** *Cont.*

**Table 2.** Examples of studies investigating potential Sjögren's Syndrome biomarkers in saliva/salivary

 glands.

**Table 2.** *Cont.*

**Table 2.** *Cont.*

Metabolomics analysis of saliva identified a total of 41 metabolites reduced in pSS patients compared to HCs [25]. Principal component analysis (PCA) revealed that saliva from pSS patients had less biological diversity compared to HCs. Two distinct groups of pSS patients were identified based on their metabolomic profile: the only clinical differences between the groups were older age and the presence of major salivary gland glanditis in one group compared to the other. Recently, a longitudinal study by Herrala et al. [26] investigated changes in the levels of salivary metabolites in pSS and HCs using proton nuclear magnetic resonance (NMR) spectroscopy over 20 weeks. Choline, taurine, alanine, and glycine were the most significantly different metabolites, all of them were found in higher concentrations in saliva samples from pSS patients than in HCs. Compared to the baseline of the HCs, choline was significantly elevated at each time point, taurine and glycine were significantly higher at weeks 1, 10 and 20, whereas alanine was higher at weeks 10 and 20, suggesting that the distinct saliva metabolic signature is relatively stable over time.

Saliva proteomic analysis by Delaleu et al. [27] using a multiplex capture antibodybased assay identified 61 differentially expressed proteins in pSS vs. non-SS controls including rheumatoid arthritis (RA) and HCs samples. Interestingly only one protein, fibroblast growth factor (FGF)-4, was found at a lower concentration in pSS while 60 different proteins were present at higher concentrations compared to controls. This comprehensive analysis recognised a proteomic signature based on the following proteins: clusterin, IL-5, FGF-4 and IL-4. The proteomic signature could correctly identify pSS patients with an accuracy of 93.8% and non-SS patients with an accuracy of 100%. However, none of the protein biomarkers correlated with saliva flow rates in pSS. A more recent study by Das et al. [20] identified the upregulation of 104 proteins and downregulation of 42 proteins in pSS compared to controls. Some enriched pathways in patients' saliva included JAK-STAT signalling after IL-12 stimulation, superoxide metabolic process and phagocytosis.

#### 3.1.3. Potential pSS Biomarkers in Peripheral Blood

It is well known that pSS is characterised by an imbalance of immune cell types, including a loss of T cell tolerance and autoreactivity, increased infiltration of exocrine gland tissues, contributing to the inflammatory microenvironment, as well as B cell activation, which is crucial for ectopic lymphoid structure and germinal centre formation, which eventually leads to the irreversible glandular damage [29]. Table 3.

Mingueneau et al. [30] published a fascinating study whereby, using mass spectrometry and immunochemistry in paired blood and salivary gland biopsies, a SS disease signature was uncovered. These findings highlighted the presence of activated CD8+ T cells, terminally differentiated plasma cells, and activated epithelial cells in biopsies, whereas in blood samples they observed a cell signature of low numbers of CD4+ T cells, memory B cells, plasmacytoid dendritic cells and high numbers of activated CD4+, CD8+ T cells and plasmablasts. The blood signature observed correlated with clinical parameters and enabled patient stratification into different endotypes with distinct disease activity and degrees of glandular inflammation. In line with this result, Van der Kroef et al. [31] also observed reduced frequencies of memory B cells and plasmacytoid dendritic cells and increased frequencies of activated HLA-DR CD4+ and CD8+ T cells in pSS patients compared to HCs.

In 2021, Szabó et al. [32] published an article whose aim was to investigate whether the distribution of B cells in pSS could be affected by a change in the balance of circulating T follicular helper (Tfh) cell subsets and follicular regulatory T cells. Utilising multicolour flow cytometry, they discovered that pSS patients had a significant increase in activated Tfh cells compared to HCs. Interestingly, anti-La/SSB-positive patients had a higher frequency of T follicular regulatory cells compared to seronegative patients. In the B-cell compartment, they observed that memory B cells were decreased, and transitional and naïve B cells were significantly increased. Lastly, they identified a positive correlation between the proportion of activated Tfh cells and both the levels of anti-La/SSB autoantibody and the serum IgA

titre. Moreover, they demonstrated the frequency of pro-inflammatory Tfh1 cells correlated positively with levels of serum IgG and anti-LA/SSB autoantibody, suggesting the potential implication of various immune cell subsets in the disease pathogenesis through correlations with serological markers.

Martin-Gutierrez et al. [33] identified an immune signature derived from the analysis of 29 different cell subsets including B and T cells, which was driven by five distinct cell subsets: transitional Bm2 cells, late memory Bm5 cells, IgD-CD27-B cells, and CD8+ naive and CD8+ Tem which differentiated between pSS patients and matched HCs. Moreover, they identified a shared immunological profile across three disease phenotypes: systemic lupus erythematosus (SLE), pSS and SLE associated with SS. By applying machine learning approaches, they identified two patient endotypes based on immune cell alterations, irrespective of the underlying diagnosis, suggesting significant pathogenic commonalities between these three disease groups. Notably, correlations were found between clinical manifestations and the frequencies of the immune cell subsets driving the stratification. CD8+ and CD4+ T cell subsets and B cell populations correlated with the erythrocyte sedimentation rate (ESR) in pSS patients whereas haemoglobin levels correlated with the frequency of CD8+central memory T cells. Disease damage scores also correlated with the frequency of CD8+ TEMRA (effector memory T cells re-expresses CD45RA)cells, CD8+ responder cells (CD25-CD127+) and CD8+CD25-CD127-T cells.

Single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) identified the expansion of CD4+ cytotoxic T lymphocytes and a population of CD4+ T cells highly expressing the T cell receptor Alpha Variable 13-2gene, in pSS patients compared to HCs [34]. Pathway enrichment analysis revealed upregulation of genes involved with type I and II interferon signalling, TNF family signalling and antigen processing and presentation in pSS patients. Using flow cytometry, it was confirmed the percentages of CD4+ Granzyme B+ T cells in the CD4+ T cell populations were significantly higher in pSS patients compared to the HCs. No correlations were found between the frequencies of CD4+ T cells and clinical or serological parameters, including the disease activity index ESSDAI (EULAR Sjögren's syndrome (SS) disease activity index), ESR levels, or the presence of anti-Ro antibodies.

Disease-associated biomarkers can be detected in serum through proteomic or metabolomic technologies. Serum concentrations of proteins in pSS patients and HCs were measured by a high-throughput proteomic assay in a recent publication [35]. Using this complex assay 1110 proteins were quantified and, from those, 82 were found to be differentially expressed in pSS patients. Significant correlations between nine differently expressed serum proteins and the ESSDAI score were found. Using a second cohort of pSS patients, five proteins including CXCL13, TNF-receptor 2, CD48, B-cell activating factor (BAFF), and PD-L2 (Programmed cell death ligand 2) were validated as pSS-associated biomarkers. Another study investigated which serum protein biomarkers, measured by Bio-Plex, could distinguish pSS from other autoimmune diseases, such as SLE and RA [36]. Out of 63 proteins, they were able to identify eight and four proteins that could differentiate pSS from SLE and RA, respectively. A combination of four different proteins: BDNF (Brain Derived Neurotrophic Factor), I-TAC/CXCL11, soluble (s) CD163 and Fractalkine/CX3CL1 was identified as a pSS protein signature as it could discern pSS from other autoimmune diseases. A negative correlation between ESSDAI score and serum sCD163 concentrations was found.

Different reports [37–39] have also focused on analysing changes in serum metabolites by different techniques, such as mass spectrometry to find new molecules that could play a role in the pathogenesis of pSS and could become new drug targets [39]. Using a nontargeted gas chromatography-mass spectrometry (GC-MS) serum metabolic profile, the authors detected 21 metabolites that differentiated between pSS patients and controls, with 18 out of 21 metabolites further validated in another cohort. Two metabolites, stearic acid and linoleic acid had the adequate discriminatory capacity to separate pSS patients from HCs and correlated with clinical parameters, such as C-Reactive Protein (CRP), ESR, IgG, anti-Ro/SSA, anti-La/SSB, antinuclear antibodies, IgA and rheumatoid factor.

**Table 3.**

Examples of studies

investigating

 potential Sjögren's Syndrome biomarkers

 in saliva.

**Table 3.** *Cont.*

**Table 3.** *Cont.*

#### 3.1.4. Genetic and Epigenetic Studies

Although the aetiology of SS is unknown, it is considered that different factors, such as environmental, genetic and epigenetic, contribute to the disease pathogenesis. In this context, several studies [40–43], have focused on finding genetic and epigenetic factors that could be associated with SS. Transcriptomics, genome-wide association studies (GWAS) to identify genomic variants that are statistically associated with a risk of suffering the disease and epigenetic studies to determine whether gene expression is active or inactive based on DNA methylation are widely used nowadays.

#### Multi-omic pSS Signatures

It is well known that the diagnosis and treatment of SS, is challenging due to the existing molecular and clinical heterogenicity, which reflects different disease stages, variable types of organ involvement, disease severity and treatment, as well as patient-specific factors, such as age, environmental exposures and comorbidities. Thus, recent research (Table 4) has been focused on integrating genomic/epigenomic, transcriptomic, proteomic, metabolomic and immunophenotype characterisation and clinical data to gain more knowledge about the disease pathogenesis as well as being able to classify patients into groups defined by their molecular pattern.

Integrated transcriptomic and serum proteomic data with an immune signature comprising 24 different cell populations highlighted the presence of a pSS gene signature driven by interferon genes as well as ADAMs (a disintegrin and metalloprotease) substrates [44]. Interestingly, the genomic regions coding the genes identified as part of the disease signature were predominantly hypomethylated, therefore, transcriptionally activated. In addition, the proteomic analysis revealed some correlations between ADAMs substrates and ESSDAI scores. Relevantly, the authors confirmed that CD8+ T cells, especially TEMRA, produced the signature observed. Similarly, transcriptomic and cytokine profiling of pSS patients allowed the stratification of pSS patients into three distinct clusters, defined by IFN-responsive and inflammation-associated genes [45]. Interestingly, patients belonging to the cluster with the strongest IFN and inflammation gene signature also had high ESSDAI scores and elevated levels of anti-Ro/SSA and La/SSB autoantibodies. This cluster was also defined by a high serum concentration of cytokines, such as LIGHT and Blys and chemokine CXCL13 [45]. Soret et al. [46] and Barturen et al. [47] independently validated some of these findings, by showing a pSS patient transcriptomic stratification also driven by IFN-related pathways. Interestingly, in both studies, a cluster of patients with low disease activity was identified, characterised by a transcriptomic profile similar to that of HCs. Soret et al. [46] did not detect any differentially expressed genes, single nucleotide polymorphisms (SNPs) or differences in B and T cells, monocytes, basophils, eosinophils and neutrophils frequencies in pSS patients with low disease activity when compared to HCs.

**Table 4.**

Examples of studies

investigating

 potential Sjögren's Syndrome biomarkers

 using multi-omic

 approaches.

**Table 4.** *Cont.*

signature, IFN—interferon, CXCL-C-X-C motif ligand, SNPs—Single nucleotide polymorphisms, Notch—Neurogenic locus notch homolog protein, MX1myxovirus resistance protein 1,NLRC5—NLR Family CARD Domain Containing 5, CCL8/MCP2—monocyte chemotactic protein-2, SLEDAI—Systemic LupusErythematosus Disease Activity Index, ESSDAI—EULAR Sjögren's syndrome (SS) disease activity index.

#### **4. Discussion**

The significant progress made by high-throughput technologies, increased effort for large-scale academic and industry research collaborations to facilitate external validation, and advancement of computer algorithms for big data integration and cluster analysis provide unprecedented opportunities for better patient classification, improved pathogenic characterisation, prediction and therapeutic opportunities across all autoimmune diseases. It is increasingly recognised the need for better quality research, including both pre-clinical and clinical validation to enable meeting the ultimate goal of achieving clinical utility and patient benefit. Despite the impressive therapeutic advances leading to licensing of many new targeted therapies in autoimmune rheumatic disease (ARDs), such as inflammatory arthritis or SLE [48], patients with SS do not benefit from the same range of therapeutic options available for other conditions, despite shared pathogenesis [49]. Many of the signals of efficacy from early phase clinical trials of various biologics investigated in SS have not been replicated in larger studies and research is ongoing [50,51].

Efforts have been made in improving the way the response to treatment in clinical trials of patients with SS is assessed [52], while current treatment recommendations expanded to targeted biologic treatment options despite of lack of large phase 3 clinical trials [10]. In addition, novel approaches, such as advocating for a molecular classification of SS to drive precision medicine strategies have been proposed [46], which suggests that the future of clinical research in SS will likely involve multi-omic characterisation of patients (Figure 1). In this respect, good quality, reproducible research involving large cohort collaborations to capture the disease heterogeneity, as well as facilitate the validation of disease signatures, is required to improve knowledge about SS pathogenesis and facilitate the much-needed therapeutic advances.

**Figure 1.** Potential multi-omic approaches taken in clinical research.

It is widely recognised that SS is associated with a genetic predisposition, similar to other ARDs, which has been confirmed in large GWAS studies which validated the associations with HLA, IRF5, STAT4 and BLK genetic loci, while also detecting novel susceptible loci [53]. The best characterised are the HLA genes, associated with an increased disease risk ranging from 1.85 to 3.41 as per a large meta-analysis [54]. Various non-HLA genes associated with the disease have also been described but very few have been validated across studies [11].

Research into the role of environmental factors and epigenetics currently supports the old hypothesis that a ubiquitous virus is a potential trigger for the mechanism of autoimmunity, with most data potentially implicating Epstein–Barr Virus (EBV), Human T cell Leukemia Virus-1 (HTLV-1), or Coxsackie virus in the development of SS [55], despite the lack of conclusive evidence for their causal role. The most well-defined epigenetic mechanisms likely to play a role in the pathogenesis of SS have been described as DNA methylation, histone modifications and non-coding RNAs [42].

SS is characterised by a pro-inflammatory environment and cytokine profiling of serum, tears and saliva identified a predominance of pro-inflammatory cytokines, such as MIP, IL-1, IFN-γ, TNF-α, IL-6, IL-12 or IL17 in various proportions, as well as increased anti-inflammatory molecules, such as IL-4 or IL-10. Some of these data have been validated across studies, while some of the biomarkers, including cytokine ratios suggesting a Th1 signature also correlated with clinically meaningful parameters, such as tear and saliva secretion [16,17,24].

Dysregulation of various immune cell populations has been hypothesised as one of the key factors implicated in disease pathogenesis. Immune profiling of patients with SS found distinct immune signatures in the salivary gland tissue compared to peripheral blood, as expected. The main players seem to be activated CD8+ T cells, terminally differentiated plasma cells, and activated epithelial cells in biopsies, whereas the peripheral blood signatures comprised high numbers of activated CD4+, CD8+ T cells. Although these signatures were not perfectly validated across various studies [30,33], some correlated with serological and clinical parameters, suggesting a potential clinical utility.

Proteomic analysis revealed distinct signatures in tears and saliva compared to the serum of patients SS, with the majority of signatures being able to differentiate, with high accuracy, SS patients from controls, and a few correlating with clinical meaningful parameters. Enriched pathway analysis also overlapped with some cytokine signature findings, such as the upregulation of the JAK-STAT signalling after IL-12 stimulation in saliva [27]. The protein patterns identified in saliva were associated with B cell immune responses, macrophage differentiation and T cell chemotaxis, which showed similarities with salivary gland histopathological features [27], suggesting a potential role for saliva analysis as a proxy measure of glandular inflammation.

Transcriptomic profiling of salivary gland tissue was characterised by the upregulation of IFN-α and IL-12/IL-18 signalling, as well as CD3/CD28 T cell activation, CD40 signalling in B-cells, as well as significant correlation with the IFN-α score in PBMCs [28], which shows similarities with proteomic profiles of saliva. IFN response genes were also upregulated in most cell subsets when assessed by single-cell blood transcriptomic analysis, highlighting the role of the IFN activation pathway in the pathogenesis of the disease. In terms of potential clinical implications, the IFNγ/IFNα mRNA ratio in salivary gland tissue was shown to have the best discriminative capacity for lymphoma development in patients with pSS [56]. Patient stratification based on transcriptomic signatures identified distinct clusters driven by IFN and B cell activation, as well as SNPs in HLA genes and epigenetic modifications including gene hypomethylation [46], all processes recognised as involved in the disease pathogenesis, although the clinical significance of patient stratification was less clear.

Metabolomic characterisation of serum, tears and saliva of patients with pSS identified distinct signatures with almost no overlap between various biologic fluids [18,26,39]. Further research exploring the inter-individual variability and its stability over time is required [26].

The power of integrating several omic technologies in the investigation of the disease fingerprints harnessed evidence for the role of cytotoxic CD8 T cells in the disease pathogenesis [44] as well as enabled the identification of inflammatory, lymphoid and IFN-driven patient clusters generated by a combination of the transcriptome, methylome and cytokine profilin [45,47]. Patient clusters driven by high IFN and pro-inflammatory signatures were

also associated with high disease activity suggesting that these pathways are relevant to the disease pathogenesis.

#### **5. Conclusions**

Omic investigation of SS provides a valuable insight into the disease pathogenesis and patient molecular heterogeneity which has implications for SS prognosis and better management strategies to address the unmet patient needs. Further research into standardising technologies and validating findings across large patient populations, as well as further exploration of potential correlations with clinical significance, are required to establish which are the strongest molecular signals that could be potentially translated into research with patient benefit. Ultimately, integrating data provided by multiple omics analysis can provide the much-required complementary knowledge related to the interplay between genes, environment, immune cell activation and pro-inflammatory milieu which all sustain the pathogenic processes associated with SS.

Understanding how the disease's natural course or treatment impacts these molecular signatures, as well as which pathways can be targeted by available and novel treatments will open a new era for research in SS.

**Author Contributions:** L.M.-G. and C.C. conceptualised the paper search strategy. All authors reviewed the literature and contributed to data collection. L.M.-G. and C.C. wrote the first draft of the manuscript. All authors reviewed the manuscript, provided intellectual input in the presentation of findings, conclusions, discussions, and limitations. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by grants from the MRC EMINENT project grant (MR/X004694/1), NIHR UCLH Biomedical Research Centre grant BRC772/III/EJ/101350, BRC773/III/CC/101350. This work was performed within the Centre for Adolescent Rheumatology Versus Arthritis at UCL UCLH and GOSH supported by grants from Versus Arthritis (21593, 22908 and 20164). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

**Institutional Review Board Statement:** No institutional review board was required as this is a literature review.

**Informed Consent Statement:** Not required as this study is a literature review.

**Conflicts of Interest:** The authors declare that the perspective was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

#### **References**

**Zahra Alghoul 1,2, Chunhua Yang 1,3,\* and Didier Merlin 1,3**

	- 3 Atlanta Veterans Affairs Medical Center, Decatur, GA 30033, USA

**Abstract:** Diagnosis and prognosis of inflammatory bowel disease (IBD)—a chronic inflammation that affects the gastrointestinal tract of patients—are challenging, as most clinical symptoms are not specific to IBD, and are often seen in other inflammatory diseases, such as intestinal infections, druginduced colitis, and monogenic diseases. To date, there is no gold-standard test for monitoring IBD. Endoscopy and imaging are essential diagnostic tools that provide information about the disease's state, location, and severity. However, the invasive nature and high cost of endoscopy make it unsuitable for frequent monitoring of disease activity in IBD patients, and even when it is possible to replace endoscopy with imaging, high cost remains a concern. Laboratory testing of blood or feces has the advantage of being non-invasive, rapid, cost-effective, and standardizable. Although the specificity and accuracy of laboratory testing alone need to be improved, it is increasingly used to monitor disease activity or to diagnose suspected IBD cases in combination with endoscopy and/or imaging. The literature survey indicates a dearth of summarization of biomarkers for IBD testing. This review introduces currently available non-invasive biomarkers of clinical importance in laboratory testing for IBD, and discusses the trends and challenges in the IBD biomarker studies.

**Keywords:** proteomics; epigenetics; endoscopy; imaging; laboratory testing

#### **1. Introduction**

Inflammatory bowel disease (IBD) is a set of chronic and idiopathic inflammatory conditions that affect more than 3.5 million patients worldwide. The two major forms of IBD are Crohn's disease (CD), in which inflammation affects any segment of the gastrointestinal (GI) tract [1], and ulcerative colitis (UC), in which inflammation affects the inner lining of the colon or rectum [2]. Patients with IBD are up to six times more likely to develop colorectal cancer than the general population [3,4]. In addition to the molecular alterations (such as chromosomal instability, microsatellite instability, and hypermethylation) that contribute to sporadic colorectal cancer, IBD-related colorectal cancer is linked to inflammation that induces the transcription of mutated cancer genes [5]. Loss-of-function mutations in tumor-suppressor protein p53 occur in both sporadic and IBD-related colorectal cancer, but they occur earlier in the non-dysplastic mucosa of IBD-related colorectal cancer than in sporadic colorectal cancer [4,5]. Another mutation observed in both types of cancer is the nonfunctional adenomatous polyposis coli (APC) gatekeeper gene. Unlike the p53 mutation, APC mutation occurs just prior to carcinoma in IBD-related colorectal cancer, but at a much earlier stage in sporadic colorectal cancer [4]. Other gene mutations linked to IBD-related colorectal cancer include p27, k-Ras (12p12) oncogene, human mismatch repair genes (e.g., hMLH1, hMSH2), and p16 [4].

CD and UC are both characterized by mucosal inflammation, with occasional flares and remittance. Inflammation in CD can affect any segment of the GI tract, and spreads in a non-continuous pattern [1,6]. CD commonly involves the formation of strictures,

**Citation:** Alghoul, Z.; Yang, C.; Merlin, D. The Current Status of Molecular Biomarkers for Inflammatory Bowel Disease. *Biomedicines* **2022**, *10*, 1492. https://doi.org/10.3390/ biomedicines10071492

Academic Editor: Marianna Christodoulou

Received: 24 May 2022 Accepted: 21 June 2022 Published: 24 June 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

abscesses, and fistulas [6]. Its histological features include thickened submucosa, fissuring ulceration, transmural inflammation, and non-caseating granulomas [6]. Inflammation in UC affects the inner lining of the colon or rectum, and spreads in a continuous pattern [2,6]. It shows superficial inflammatory changes in the mucosa and submucosa, and involves the formation of cryptitis and crypt abscesses [6]. The clinical symptoms of IBD include abdominal pain, diarrhea, rectal bleeding, weight loss, nausea, intestinal pain and, in some cases, fever [7,8]. As these symptoms are not specific to IBD, the clinical diagnostic process must consist of using a combination of endoscopic, radiological, clinical, histological, and laboratory tests [9]; a single technique is often insufficient for the diagnosis.

Endoscopy and imaging are essential techniques for the diagnosis, management, and treatment of IBD. They are used in the initial evaluation of patients with suspected IBD, as well as in making a differential diagnosis of UC versus CD in confirmed IBD cases [10]. The strength of endoscopy as a diagnostic tool lies primarily in its ability to visually observe different bowel segments, allowing clinicians to assess disease severity and monitor disease activity over time. Ileocolonoscopy has traditionally been the most used form of endoscopy in IBD. The initial evaluation of patients presenting with clinical symptoms suggestive of IBD should be carried out with ileocolonoscopy, as recommended by the American Society for Gastrointestinal Endoscopy (ASGE) Standards of Practice Committee [11]. In addition to providing a visual of the colon and the terminal ileum, ileocolonoscopy can be used to obtain biopsy specimens for further analysis. The ASGE suggests obtaining at least two biopsy specimens from five sites throughout the bowel during the initial evaluation [12]. However, the invasiveness and high cost of ileocolonoscopy are major drawbacks that have limited its frequent use for monitoring disease activity.

New, less-invasive endoscopic techniques that can more accurately diagnose IBD, while also providing a differential diagnosis of CD and UC, have emerged in the past few years. These include video capsule endoscopy (VCE), confocal laser endomicroscopy (CLE), and single- or double-balloon-assisted enteroscopy (SBE and DBE, respectively). VCE provides imaging of the whole bowel via ingestion of a wireless capsule endoscope [13]. This technique is particularly useful for inspecting areas in the GI tract that cannot be visualized by colonoscopy [14]. Although the risk of capsule retention is low, it remains the primary concern in patients with suspected or known IBD [15]. VCE is less invasive and more cost-effective than ileocolonoscopy, but it cannot be used in performing biopsies. In CLE, a confocal laser microscope is used in vivo to obtain living tissue images during colonoscopy [16]. CLE has the advantage of offering a faster diagnosis than a traditional colonoscopy. Enteroscopy in both of its forms (SBE and DBE) allows access to small bowel areas that standard endoscopy cannot reach. Additionally, enteroscopy can be used in performing histological analysis. However, due to its technical complexity and time-consuming preparation, enteroscopy is not recommended for the initial evaluation of suspected IBD cases [17].

In confirmed IBD cases, clinical symptoms alone are insufficient for clinicians to determine the extent of mucosal inflammation, or to make a differential diagnosis between UC and CD. There has been a growing interest in the use of cross-sectional imaging modalities such as magnetic resonance enterography (MRE), ultrasonography (US), and computed tomography (CT) as tools to supplement endoscopy in the diagnosis and monitoring of IBD [18]. These techniques are instrumental in detecting mural and extramural complications and assessing laminal inflammation in areas affected by CD in the small bowel that are beyond the reach of colonoscopy [19]. Due to their ability to diagnose CD with high accuracy, cross-sectional imaging modalities are used to make differential diagnoses in suspected cases of UC [20]. This aspect is critical because these diseases differ in their prognosis and required treatments.

Although imaging techniques offer highly accurate IBD diagnosis, they require experienced personnel, sophisticated instruments, and high costs, hampering their routine application. Laboratory testing's advantage lies in the fact that these tests can be standardized, rapid, and cost-effective, but they can also be applied to the already established

patient sample libraries to process independent investigations. An increasing number of laboratory tests, combined with endoscopy or imaging, are used to monitor disease activity or diagnose suspected IBD cases. As good laboratory test results rely on the proper use of molecular biomarkers from the patients' tissue, blood (serum), or fecal samples, this review summarizes currently available biomarkers of clinical importance in laboratory testing of IBD, discusses the possible involved genetic and epigenetic factors, and envisions the trends and challenges of biomarker discovery in IBD.

#### **2. Non-Invasive Molecular Biomarkers of IBD: Serum Proteins, Serological Antibodies, and Fecal Proteins**

Biomarkers play critical roles in the early detection and monitoring of disease progression and therapeutic responses (Figure 1). Disease activity can be monitored with laboratory tests that measure circulating biomarkers in the blood (serum or plasma), tissue, or feces. A biomarker is defined as "a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention" [21]. Identifying a biomarker or several biomarkers of a given condition's pathologies might help to diagnose, prognose, and assess therapeutic responses. For a biomarker to be effective, it should possess several attributes, such as being non-invasive, inexpensive, convenient for sampling, reproducible, and disease-specific (i.e., accurate and precise). An ideal biomarker also needs to have a rapid test-to-result turnaround time, be standardizable to provide comparable test results across different assays, be widely available and stable for storage, have a wide dynamic range, use defined thresholds to determine the absence/presence or extent of inflammation, and be responsive to changes in the state of inflammation [22].

**Figure 1.** The potential role of biomarker assays in the care of patients with suspected or established IBD: Biomarkers may be used in all phases of the care. For patients with suspected IBD, biomarkers can be used to select which patients are unlikely to have IBD and could forgo further testing. Once patients are diagnosed, biomarkers can determine which patients have CD or UC and predict the disease course. Biomarkers can be used to determine which patients are most likely to respond to therapies, determine prognosis, and identify those who require more aggressive therapies. In patients with recurrent symptoms, biomarkers can differentiate patients with active inflammation from those likely to have symptoms from other causes. Adapted from James D. Lewis's review [23]; *Gastroenterology*, Volume 140 Issue 6, Pages 1817–1826.e2; https://doi.org/10.1053/j.gastro.2010.11.058.

Several molecular biomarkers have been established as reliable measures for disease activity in IBD [22,24]. They are minimally invasive and relatively inexpensive compared to colonoscopy and imaging techniques. They can also assist in identifying patients who require diagnosis with endoscopy and biopsies. However, many of these biomarkers have limitations in terms of their specificity, sensitivity, responsiveness, and/or other desirable attributes of IBD biomarkers [22]. There are currently three major types of molecular biomarkers available for IBD: serum biomarkers, serological antibodies, and fecal biomarkers.

#### *2.1. Serum Biomarkers*

Several inflammatory serum biomarkers have become part of routine laboratory testing for the diagnosis of IBD. Although they are not specific to IBD, these serum biomarkers are commonly used for initial diagnosis due to their ease of use, low cost, and well-established protocols. The most common of these tests are those for C-reactive protein (CRP) and the erythrocyte sedimentation rate (ESR).

CRP is a pentameric protein that is produced in the liver by hepatocytes. It is found in serum at <1 mg/L under physiological conditions. Its concentration increases during an acute-phase response, as pro-inflammatory cytokines such as IL-6, tumor necrosis factor α (TNF-α), and IL-1β stimulate its production in the hepatocytes [25–27]. CRP has a relatively short half-life (about 19 h) [28], making it a better indicator of inflammation than most acute-phase proteins. Elevated CRP levels are observed in most active CD cases, whereas the CRP levels of UC patients show little-to-no increase in the case of active disease [27,29]. This may reflect the production of CRP by mesenteric adipocytes in patients with CD [30]. Although CRP is widely used as a biomarker for IBD, it lacks specificity; elevated CRP levels are also observed in autoimmune disorders, infections, and malignancies [25].

ESR is a measure of how quickly erythrocytes sediment through plasma in a column, with a higher rate taken as indicating more inflammation. ESR values are affected by physiological factors such as pregnancy, age, and gender, as well as changes in hematocrit levels in patients with anemia and polycythemia [31]. Medications that cause changes in the size of erythrocytes can also affect ESR values [32]. Changes in ESR values are not specific to IBD, and can be due to any inflammatory stimulus. Unlike CRP, ESR values are altered in both UC and CD, and we cannot distinguish them. ESR values peak more slowly than CRP, and take longer to return to normal after the end of an inflammatory flare [28].

CRP and ESR have been studied long enough to become established in IBD diagnosis. While both tests lack the specificity and accuracy to be considered a gold-standard diagnosis, CRP has some advantages over ESR. For example, the CRP concentration changes faster than the ESR value upon a change in disease activity, CRP has a broader range of abnormal values than ESR, and (unlike ESR) CRP does not show age-related variation [33].

Leucine-rich alpha-2 glycoprotein (LRG) is a 50 kD protein that is secreted by hepatocytes, neutrophils, macrophages, and intestinal epithelial cells [34–36]. It has recently emerged as a novel serological biomarker for IBD and rheumatoid arthritis. Studies have found that levels of LRG are elevated in patients with active UC, and decrease with a decline in disease activity [37,38]. Notably, elevated levels of LRG correlate better than CRP with clinical and endoscopic scores in patients with active UC and CD [38–40]. LRG has been also found to predict mucosal healing in both UC and CD patients with normal CRP levels [41].

#### *2.2. Serological Antibodies*

Serological testing is a well-established diagnostic tool for a variety of immune diseases. Its use in IBD has been mainly focused on patients with a confirmed diagnosis; little work has been done on its potential as a primary diagnostic tool in patients with suspected IBD. Perinuclear anti-neutrophil cytoplasmic antibodies (p-ANCAs) and anti-*Saccharomyces cerevisiae* antibodies (ASCAs) are the two primary antibodies currently examined in IBD studies. ANCAs are a group of antibodies produced against antigens in the cytoplasm of

neutrophils. ASCAs are produced against mannan and other yeast cell wall components. Both have been reported to provide clinically useful positive or negative predictive values: p-ANCA+/ASCA− is reported in patients with UC, while p-ANCA−/ASCA+ is seen in patients with CD. Although each of these biomarker antibodies can be used to discriminate UC from CD, they both have low accuracy and sensitivity [42]. Positive results for either antibody are not unique to IBD, and may be related to several other GI and inflammatory conditions, such as celiac disease, Behcet's disease, cystic fibrosis, and rheumatoid arthritis [42,43].

#### *2.3. Fecal Biomarkers*

Fecal biomarkers are the proteins that are explicitly found in stool samples of patients with IBD. The fecal biomarkers for IBD reported to date are mainly fecal leukocyte proteins. These include calprotectin, calgranulin C, lactoferrin, and lipocalin-2. They have several advantages over blood biomarkers, including the ease of sample accessibility, high biomarker concentration due to the direct contact of the fecal sample with the site of inflammation, and higher specificity for IBD because they reflect GI inflammation (unlike serum biomarkers, which are increased by various types of inflammation) [44].

Calprotectin is the most widely used fecal biomarker for IBD. It is a calcium- and zincbinding protein that is abundant in neutrophils, eosinophils, and macrophages. Changes in its concentration are observed in various secretory and excretory products in the body upon activation of granulocytes and mononuclear phagocytes [45]. Elevated fecal calprotectin levels are expected in patients with active IBD, due to the presence of a high number of neutrophils in the GI tract, which is characteristic of the disease [28]. Calprotectin is resistant to degradation, and is stable for 7 days in fecal samples stored at room temperature [46]. Changes in fecal calprotectin levels are not exclusive to IBD; alterations are also observed in various colon and intestine diseases [47].

Calgranulin C (S100A12) belongs to the S100 family of low-molecular-weight calciumbinding proteins, which activate the NF-κB pathway and increase cytokine release during pro-inflammatory processes [31]. The serum concentration of calgranulin C is high in IBD [48], but the fecal concentration is higher, making the fecal assay more sensitive to IBD. Elevated levels of calgranulin C have been reported in other inflammatory conditions, such as arthritis [49].

Lactoferrin is another biomarker whose levels are significantly elevated in active IBD. It is an iron-binding glycoprotein that is found specifically in neutrophils; in this respect, it contrasts with calprotectin, which is found in several types of cells. Lactoferrin has high specificity and sensitivity for diagnosing active IBD [50].

Lipocalin-2 (LCN-2), also known as neutrophil gelatinase-associated lipocalin (NGAL) or siderocalin (Scn), is a bacteriostatic protein stored in neutrophil granules [51,52]. LCN-2 is involved in innate immunity by secluding iron from pathogenic bacteria, limiting their invasion. It is a highly stable protein whose elevated expression by gut epithelial cells has been demonstrated in colonic biopsies from inflamed areas of patients with IBD. Serum LCN-2 has been proven to be an active biomarker in UC patients, and it is widely used as a fecal biomarker of acute inflammation in the animal model of UC, indicating that it can potentially be used as a fecal biomarker of human UC. Upregulation of LCN-2 is believed to be induced by IL-22 and IL-17A [53].

#### *2.4. Diagnostic/Prognostic Accuracy*

The major concern about diagnosis and prognosis of IBD that solely rely on singular molecular biomarkers is their detection accuracy. A study showed that the biomarkers' correlation coefficients with endoscopy could vary from 0.48 to 0.83 (for calprotectin) and from 0.19 to 0.87 (for lactoferrin) in IBD patients [23] (Table 1). IBD detection methods that combine endoscopy with histopathology biomarkers can be highly accurate, such as in the context of oncostatin M (OSM) or oncostatin M receptor (OSMR), which are found to be highly overexpressed in the inflamed intestinal tissue of active IBD patients, with a

*p*-value < 0.001 for OSM (*n* = 42) and a *p*-value < 0.05 for OSMR (*n* = 86) at a false discovery rate (FDR) of 1% [54].

**Table 1.** Correlation of biomarkers with disease activity, determined by endoscopy.

\* CDEIS, Crohn's Disease Endoscopic Index of Severity; \*\* SES-CD, Simple Endoscopic Score for Crohn's Disease. Adapted from James D. Lewis's review [23]; *Gastroenterology*, Volume 140 Issue 6 Pages 1817–1826.e2; https://doi.org/10.1053/j.gastro.2010.11.058.

To date, C-reactive protein and fecal calprotectin are considered reliable markers of disease activity, with demonstrated utility in IBD management [55]. However, singlebiomarker-based detections often present a larger ambiguous "grey zone" than detections made using composite biomarkers (Figure 2). Composite biomarkers are defined as "a combination of ≥2 biomarkers", and are selected using an optimized algorithm to render a single interpretive output. The combination of different biomarkers has shown higher accuracy, and is expected to reduce the "grey zone" of each biomarker and replace singlemarker approaches in the future of research and clinical practice [55] (Figure 2).

**Figure 2.** Improvements are provided by composite biomarkers. Careful selection of markers and their integration can optimize the diagnostic accuracy of single biomarkers of disease activity and drastically reduce the blind spot resulting from the "grey zone". Adapted from Dragoni G. et al.'s review [55]; *Digestive Diseases*, https://doi.org/10.1159/000511641.

#### **3. Trends in IBD Biomarker Discovery**

#### *3.1. Proteomics*

Proteomics, the study of the set of gene-encoded proteins known as the proteome, uses a range of techniques for separating, identifying, and structurally characterizing proteins. Proteomics goes beyond the study of proteins in a given cell, including their isoforms, post-translational modifications, and protein–protein interactions [56]. Depending on the

analysis method, proteomic approaches can be bottom-up or top-down. In bottom-up proteomics, proteolytic digestion breaks the extracted proteins into peptides, which are then analyzed by mass spectrometry (MS). In top-down proteomics, intact proteins are analyzed. The samples used in IBD-related studies are usually obtained from blood (serum or plasma) or colonic biopsies. Liquid chromatography coupled with electrospray tandem mass spectrometry (LC–ESI-MS/MS) is the most widely used proteomic technique in IBD research. Other commonly used techniques include two-dimensional gel electrophoresis coupled with matrix-assisted laser desorption/ionization (MALDI)-MS screening and immunofluorescence microscopy.

Due to the strong connections between protein expression and disease activity, the application of proteomics in biomarker discovery is a promising emerging field. Advances in LC–MS instrumentation, such as the combination of ultrahigh-performance liquid chromatography (UPLC) with nano-electrospray ionization and high-resolution mass spectrometry (HRMS), have revealed the potential of MS-based proteomics to compete with or even replace traditional immunoassay techniques. It is hoped that proteomics may help to develop personalized and precision medicine [57]. Instead of focusing on finding a single biomarker, current proteomic biomarker research aims to identify protein biomarker panels representing an individual's disease state. In this context, three approaches have emerged over the past few years: (1) Proteotyping—a multiprotein approach used to determine an individual's unique proteome [58]. (2) Proteogenomics—a multi-omics approach in which genomic and proteomic analyses are performed on the same sample; data obtained from this pairing contain information that would not be obtained using either technique alone [59,60]. (3) Proteoforms—protein variants that result from post-translational modifications of proteins, genetic mutations, or truncations. MS immunoassays are often used to map a specific protein's proteoforms to distinguish between normal and clinical fluctuations [61,62].

To date, the use of proteomics in IBD has focused on three areas: identifying novel protein biomarkers for diagnosis, understanding the pathological mechanisms underlying disease activity, and monitoring the response to treatment. Berndt et al. pioneered the use of proteomics in IBD by performing proteomic analysis of normal and inflamed intestinal mucosa using multi-epitope ligand cartography immunofluorescence microscopy. The authors found that different T-cell populations in the mucosa expressed distinct proteins in each form of IBD [63]. An experimental approach based on combining discovery proteomics with targeted verification experiments successfully assessed transmural intestinal complications in CD, with 70% sensitivity and 72.5% specificity. This approach, which used label-free LC–MS/MS, identified a serological biomarker panel that could discriminate complicated CD from uncomplicated CD, rheumatoid arthritis, UC, and healthy controls [64]. Another study that used LC–MS identified a panel of four proteins that could distinguish active pediatric IBD from non-IBD with high sensitivity and specificity.

Additionally, the study found that two of the identified proteins were elevated in IBD stool samples, demonstrating that fecal samples can be used for measuring these biomarkers [65]. Several studies attempted to identify differentially expressed proteins in patients with UC and CD through proteomic profiling of serum or colonic biopsies. Proteomic profiling of colon biopsies using MALDI-MS identified distinct protein peaks for UC and CD specimens, indicating that it could be possible to differentially diagnose these IBD forms using protein profiles [66–68]. In a study that compared the proteomic spectra of submucosal samples from inflamed UC versus CD and uninflamed UC versus CD, two distinct peaks were identified in the first case, and three in the second [66]. Another study identified a set of 25 proteins as differentiators for UC and CD in colonic mucosal tissue samples obtained from 62 patients with confirmed UC/CD [67]. Screening of mucosal biopsies obtained from children with suspected IBD identified two distinct biomarker panels: one consisted of 5 proteins that were reported to discriminate IBD from control patients, while the other consisted of 12 proteins reported to allow the differential diagnosis of CD and UC patients [68]. Protein profiling of 120 serum samples from patients with

CD or UC and inflammatory and healthy controls was performed using surface-enhanced laser desorption/ionization–time-of-flight mass spectrometry (SELDI-TOF-MS). This work identified four diagnostic protein biomarkers for IBD, one of which could reportedly discriminate UC from CD with accuracies similar to or higher than those of the ANCA and ASCA serological tests [69]. Proteomic profiling of stricturing CD, non-stricturing CD, and UC patients identified a smaller set of peptides for differentiating stricture versus non-stricture CD in IBD [70].

In addition to diagnostic biomarkers, several studies have used proteomics to identify biomarkers that could be used to assess treatment responses in IBD. One study monitored the treatment response to infliximab in IBD patients by measuring the levels of circulating chemokines and monocyte activation using LC–nano-ESI-MS/MS. The study found that 2 weeks from the start of treatment, decreases were evident in the levels of macrophage-derived CD14 and CD86, as well as the chemokine, CCL2 potentially providing a mechanistic explanation for why not all patients respond to this treatment [71]. Another study investigated the treatment response to infliximab and prednisone in children with IBD. The study identified 18 proteins and 3 miRNAs that were responsive to both drugs; some were downregulated with inflammation, while others were upregulated as the inflammation was resolved [72].

#### *3.2. Genetics*

Pathological studies of IBD and its two subtypes suggest a genetic risk factor behind the immune response to the intestinal microbiota. Genome-wide association studies (GWASs) have identified approximately 240 gene loci associated with susceptibility to IBD [73]. Several studies have used genetic profiling of blood samples to identify gene panels that may help to differentiate IBD from healthy controls [74], active from inactive CD [75], and CD from UC [76–78]. Distinct gene panels were also identified in peripheral blood samples from pediatric IBD patients in clinical remission compared to healthy controls [79]. Other studies performed gene expression analysis on mucosal biopsies from IBD patients, and identified distinct gene panels for IBD versus healthy controls [80] and UC versus healthy controls [81]. The use of genetics to identify loci associated with IBD can potentially define causal disease mechanisms, which could, in turn, advance the biomarker discovery process [82].

#### *3.3. Epigenetics*

Epigenetics, which describes changes in gene function caused by gene–environment interactions rather than changes in the DNA sequence, is gaining research interest among scientists seeking to study the pathogenesis and diagnosis of IBD [83,84]. DNA methylation and RNA interference are the two most heavily researched areas in IBD epigenetic studies.

DNA methylation refers to adding a methyl group to cytosine residues in the CpG dinucleotide sequence [85]. Early studies of DNA methylation changes in the mucosa of IBD patients focused primarily on their use as predictors of malignancy [86]. Recent studies have shown that the DNA methylation of specific genes plays a role in the pathogenesis of IBD, suggesting that they could be useful as biomarkers [87,88]. A genome-wide methylation profiling conducted on rectal biopsies identified panels of genes (e.g., *THRAP2*, *FANCC*, *GBGT1*, *DOK2*, *TNFSF4*, *TNFSF12*, and *FUT7*) that showed evidence of differential methylation in CD and UC specimens in comparison to those from healthy controls [88]. Another study identified seven differentially methylated CpG sites in the diseased intestinal tissue of IBD patients compared to normal intestinal tissue from the same patients [89]. Genome-wide changes in DNA methylation have also been analyzed using the peripheral blood of patients with IBD. Analysis of the DNA methylation changes using peripheral blood from CD patients identified 50 genes that showed significant differential methylation compared to that in healthy controls [87]. Site-specific DNA methylation changes in genes associated with IBD pathways have also been identified, with the results showing a 45% overlap of the differentially methylated positions in UC and CD [90].

MicroRNAs (miRNAs) are non-coding, single-stranded RNA species that consist of 18–25 nucleotides. Disruptions in their expression profiles and function are observed in human diseases such as cancer and neurological, cardiovascular, and autoimmune diseases [91]. The potential of miRNAs as diagnostic biomarkers and treatment options in IBD has garnered growing interest in the past few years. Colonic tissue and circulating miRNAs (e.g., serum, feces) are the two types of samples used in most of these studies.

Several studies have successfully identified distinct miRNA profiles reflecting the upor downregulation of one or more miRNAs in colonic biopsy specimens of IBD patients [92] (Table 2). One of the pioneering studies in this area identified the differential expression of 11 miRNAs in the mucosal tissue samples of patients with active UC [93]. Other studies that examined the colonic mucosa of patients with active UC reported upregulation of one or more miRNAs (such as miR-21 [94], miR-150 [95], and miR-155 [94]) and downregulation of others (such as miR-143 and miR-145 [96]), in comparison to healthy controls. Similarly, some studies compared the colonic mucosa of patients with active CD to healthy controls, and reported upregulation of miR-196 [97] and downregulation of miR-7 [98]. Other studies assayed the expression of hundreds of miRNAs, and identified panels differentially expressed in the colonic tissues of patients with UC and CD versus controls [99–101].

**Table 2.** A summary of microRNAs that are correlated with ulcerative colitis (UC#1–12) or Crohn's disease (CD, #13–22).

**Table 2.** *Cont.*

HC: healthy controls, RT-qPCR: quantitative real-time polymerase chain reaction, Biopsy: colon tissue biopsy, ISH: in situ hybridization, PBMCs: peripheral blood mononuclear cells, DSS: dextran sodium sulfate, TNF: Tumor necrosis factor alpha. Adapted and modified from Jaslin P. James et al.'s review [92]; *Int. J. Mol. Sci*. 2020, 21, 7893; doi:10.3390/ijms21217893.

Distinct profiles of circulating miRNAs have also been identified in blood samples of IBD patients. Several studies identified many upregulated or downregulated miRNAs in peripheral blood samples from patients with IBD. Samples were obtained from patients with UC or CD versus healthy controls [101–104] and pediatric CD versus healthy controls [105]. Distinct panels of miRNAs have also been identified in fecal samples of IBD patients [106–108]. More investigation into the specificity of miRNAs for IBD is required before they can be used as diagnostic tools, as some miRNAs are known to be associated with other conditions. For example, miR-21 is significantly high in the blood of UC patients [103], but is also upregulated in patients with colorectal cancer [109]. One study examined the differential expression of miRNAs between UC and CD in saliva, in addition to blood and colon tissue samples [110]. The study identified several miRNAs (i.e., miR-21, miR-31, miR-142-3p, miR-142-5p) whose expression levels in all three types of samples were significantly altered between IBD and non-IBD patients.

#### **4. Challenges and Future Directions**

#### *4.1. Proteomic Biomarker Discovery*

The typical protein biomarker discovery and validation process consists of six phases: discovery, qualification, verification, assay optimization, clinical evaluation/validation, and commercialization [111]. During the discovery phase, researchers identify a list of 20 to several hundred proteins that are differentially expressed between healthy and diseaseconfirmed samples. This identification process is based on an unbiased, semi-quantitative assessment of peptide abundances in both samples. In the next phase, qualification, this unbiased approach is replaced with a targeted analysis to confirm the differential expression of the candidate proteins identified in the discovery phase. In the verification phase, a more significant number of samples are used to account for the variations in the proteomes of the different studied sets. At this stage, specificity and sensitivity acquire particular importance when the researchers select the few protein biomarkers used in the assay optimization and clinical evaluation phases. In the assay optimization phase, an antibody is selected for each biomarker candidate and used to develop an immunoassay to replace the MS step in protein quantification. During the evaluation/validation phase, the assay is evaluated for

analytical parameters, such as accuracy and precision. If clinical validation is successful, the protein biomarker moves to the commercialization state [111].

The path to successful protein biomarker discovery through this multistage process faces several challenges. As a result, the introduction of new protein biomarkers has been slow, and has not met the clinical need for proteomic tests [112]. Some relevant challenges include the low number of samples under study and the lack of well-designed study methods and standard protocols [113]. These variables can be optimized through more careful choices of sample types and sizes. Sample selection and processing require special consideration when performing a proteomic analysis. For example, human plasma contains tens of thousands of proteins that differ in their structures and abundances [114]. It is not always possible to identify a single or multiple disease-specific proteins that could be used as markers for a particular disease. The proteins selected in the discovery phase are often classified as false positives. This is primarily due to the low frequency of selecting low-abundance proteins and limitations in their detection [111]. Even using other biofluids—such as urine, cerebrospinal fluid, cell line homogenates, or tissue lysates has not eliminated this complexity [111]. There are also considerations more specific to the study of IBD. Intestinal mucosal biopsies are widely used in IBD studies. Protein degradation during and after extraction might lead to the under- or over-representation of specific proteins [115]. The use of protease inhibitors that minimize protein degradation can keep this variable under control. Cell heterogeneity of the mucosal specimens is another variable that could lead to an inaccurate proteome analysis [115]. Enriching samples for specific cell types and/or organelles can lower the sample's complexity and improve the protein identification efficiency [115,116]. The statistical power of a proteomic study is another factor that requires special attention in the biomarker discovery pipeline, especially in the discovery and verification stages. Skates et al. proposed a statistical framework for increasing the probability of identifying a biomarker that can reach the clinical validation stage [117]. According to their framework, the success of a biomarker in reaching clinical validation depends on the number of candidate proteins examined at each stage, the separation in biomarker signal between cases and controls (as measured by standard deviation), and the percentage of cases in which the biomarker is expressed. The authors provided probability tables that can be used in determining the proper sample size for a given study.

Although significant progress has been achieved in the instrumentation and sample preparation of proteomic techniques, proteomics in biomarker discovery is still in its early stages. Compared to molecular biomarkers, significant work is required to prove the utility of any protein panel as a new biomarker for IBD.

#### *4.2. Epigenetics in Diagnostic Biomarkers*

Epigenetic signatures are tissue- and cell-type-specific. A major challenge in IBD epigenetic studies using peripheral blood or mucosal biopsies is the cell-type heterogeneity of these specimens. Additional non-disease-specific cell types can lead to complications in interpreting the data due to interference from the different individual epigenetic features. Thus, disease-specific cell types should be purified from the mixed cell or tissue samples before analysis. However, several cell types have been linked to the pathogenesis of IBD, making the selection of disease-specific cell types in IBD a challenge. Although the techniques used in epigenetic studies are well established, they also have their limitations. Most microRNA studies use real-time quantitative PCR followed by microarrays. Although these techniques can identify a wide number of miRNAs, they are not sensitive to functionally distinct microRNA variants and slight nucleotide variations between microRNAs in the same families. They also have a low dynamic range, and cannot detect miRNAs with low expression levels [118]. Next-generation sequencing (NGS) is a high-throughput and fast method that has emerged lately as a more effective technique for identifying novel microRNAs [119].

Other challenges emerge from environmental factors, such as age, diet, and smoking, which can affect the epigenome. Hence, a well-designed study seeking to identify diseasespecific variations selectively would require a careful selection of patients and controls.

#### **5. Conclusions**

The role of endoscopy and inflammatory biomarkers in the diagnosis of IBD has been extensively studied over the years, improving our understanding of the utility and limitations of each diagnostic tool in clinical settings. Although the combination of endoscopy and molecular tests has become a well-established diagnostic tool for IBD, there is continuing effort to find an ideal diagnostic tool that can overcome the challenges limiting the current tools. Lately, there has been growing interest in switching from using a single biomarker to the biomarker panel approach, in an effort to identify biomarkers that, together, are specific to IBD and can enable differential diagnosis of UC versus CD. This shift in research focus is evident from the increasing number of studies looking into the use of proteomics and genomics for identifying biomarker signatures. As the causes of IBD are still undetermined, with immunological, genetic, and environmental triggers having been found to contribute to disease progression [120–123], researchers also continue to search for new molecular biomarkers that are associated with these factors—especially in the context of new fecal biomarkers and serological antibodies.

**Author Contributions:** C.Y. and D.M. developed the concept, and Z.A. wrote the draft. The manuscript was then critically revised by D.M. and C.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Department of Veterans Affairs (Merit Award BX002526 to D. Merlin) and by the National Institute of Diabetes and Digestive and Kidney Diseases (RO1-DK-116306 and RO1-DK-107739 to D. Merlin). D. Merlin is a recipient of a Senior Research Career Scientist Award (BX004476) from the Department of Veterans Affairs.

**Data Availability Statement:** No new data were generated or analyzed in support of this research.

**Acknowledgments:** The authors appreciate the support from the Elsevier for reusing the Figure and table from Gastroenterology (Volume 140, Issue 6, pages 1817–1826.e2) for our review's Figure 1 and Table 1. We also appreciate the S. Karger AG, Basel publishers for reusing the Figure for our review's Figure 2 from the journal Digestive Diseases (2021; 39: 190–203, https://doi.org/10.1159/000511641), and thank the MDPI for reusing table unit from Int. J. Mol. Sci. (2020, 21, 7893; doi:10.3390/ijms21217893) for our review's Table 2.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**

### *Review* **Cell Death-Related Ubiquitin Modifications in Inflammatory Syndromes: From Mice to Men**

**Nieves Peltzer 1,2,3,\*,† and Alessandro Annibaldi 1,\*,†**

**Abstract:** Aberrant cell death can cause inflammation and inflammation-related diseases. While the link between cell death and inflammation has been widely established in mouse models, evidence supporting a role for cell death in the onset of inflammatory and autoimmune diseases in patients is still missing. In this review, we discuss how the lessons learnt from mouse models can help shed new light on the initiating or contributing events leading to immune-mediated disorders. In addition, we discuss how multiomic approaches can provide new insight on the soluble factors released by dying cells that might contribute to the development of such diseases.

**Keywords:** cell death; apoptosis; necroptosis; pyroptosis; ubiquitin; LUBAC; OTULIN; A20; inflammation; autoimmunity; human genetics

#### **1. Introduction**

The field of cell death has undergone quite a substantial evolution over the past three decades. During the 1990s and the first years of the new century, scientists were mainly focused on how the knowledge of cell death pathways could have helped improve cancer therapy, to eliminate as many cancer cells as possible, with little interest for the pathophysiological roles of cell death [1,2]. In the last decade or so, the field has moved towards a new direction, with the purpose to understand how the decision between life and death regulates tissue homeostasis and inflammatory responses during tissue damage or pathogen infection [3,4]. It became increasingly clear that cell death-regulating molecules are not always programmed to kill and can fulfil cell death-independent functions [5,6]. In addition, cell death is not a biological end point and, in the process of dying or after their death, cells can still emit signals in a programmed manner [7]. These signals evoke inflammatory programs that are essential for the ability of tissues to recover from different types of insults and restore homeostasis [8]. However, aberrantly regulated cell death can exacerbate inflammatory processes that can in turn cause tissue failure and inflammatory disorders and autoimmunity [9]. Therefore, the magnitude of cell death processes is always fine-tuned by multiple control mechanisms that are in place to prevent the detrimental effects of uncontrolled cell death [10].

Cytokines of the tumour necrosis factor (TNF) family are crucial regulators of cell death, inflammation and autoimmunity [11]. TNF receptor 1 (TNFR1) is a member of the death receptor (DR) family. These receptors are characterised by the presence, in their intracellular portion, of a death domain (DD) that is able to initiate cell death cascades [11]. Other well-studied members of this family are CD95 (Fas/APO-1), TNF-related apoptosisinducing ligand (TRAIL)-R1 (DR4) and TRAIL-R2 (DR5) [12]. It is the research conducted on the TNF-TNFR1 system during the past two decades that allowed scientists to discover the

**Citation:** Peltzer, N.; Annibaldi, A. Cell Death-Related Ubiquitin Modifications in Inflammatory Syndromes: From Mice to Men. *Biomedicines* **2022**, *10*, 1436. https://doi.org/10.3390/ biomedicines10061436

Academic Editor: Marianna Christodoulou

Received: 20 May 2022 Accepted: 15 June 2022 Published: 17 June 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

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previously unappreciated link between cell death and inflammation. Indeed, the numerous mouse models developed in the past 10 years, bearing inactivating mutation in players on the TNFR1-signalling pathway, revealed that cell death could be the triggering event in inflammatory and autoimmune diseases [9]. In this review, we focus on different mouse models that led to the discovery of the relationship between cell death and inflammation, how they contributed to establish the link between cell death and inflammation-related disorders and how these disorders resemble human autoinflammatory and autoimmune diseases. In addition, we review the latest omic-based approaches adopted to elucidate the inflammatory potential of dying cells.

#### **2. TNFR1-Signalling Pathway**

Upon binding to its cognate ligand, TNF, TNFR1 trimerizes and initiates the formation of a receptor-bound complex called complex-I or TNFR1-associated signalling complex (TNFR1-RSC) [13]. The first event for complex-I formation is the recruitment of the adaptor protein TRADD, and the kinase RIPK1, via DD-interaction [14]. Subsequently, TRADD recruits TRAF2 that in turn binds to the E3 ligases cIAP1 and cIAP2 [15]. These cIAPs synthesise ubiquitin chains of different topologies (i.e., K63, K48 and K11) on different components of complex-I, including themselves and RIPK1 [16,17]. These ubiquitin chains serve as a scaffold to recruit another E3 ligase, the linear ubiquitin chain assembly complex, LUBAC [18]. LUBAC is a tripartite E3 ligase complex formed of HOIP, HOIL-1 and SHARPIN [19,20]. LUBAC conjugates linear ubiquitin chains, also called methionine (M) 1 chains, to several complex-I components, including RIPK1 and TNFR1 [21]. The ubiquitin chains formed by cIAP1/2 and LUBAC stabilise complex-I and favour the recruitment of different kinase complexes: TAB2/TAB3/TAK1 [22–24], NEMO/IKKα/IKKβ and NEMO/TANK1/NAP1/TBK1/IKKε [25]. The TAK1 and IKKα/IKKβ kinases are required for the activation of NF-κB and MAPKs for the expression of pro-survival and pro-inflammatory genes that are required to mount an innate immune response [26]. TAK1 also controls MK2 activation. The M1 chains synthesised by LUBAC also serve to recruit deubiquitinating enzymes (DUBs), namely A20 and CYLD, this last via the adapter SPATA2, which have opposing effects in complex-I [21,27]. While CYLD hydrolyses ubiquitin chains, prevalently K63 chains [28], to control the extent of NF-κB activation, A20 shields them and prevents their removal, ensuring complex-I stability [21] (Figure 1).

The TNF-signalling pathway is tightly controlled by a number of checkpoints that rely on ubiquitination-, phosphorylation-, gene-expression-dependent and proteolytic events [10,29]. In conditions where any of these checkpoints is disabled, there is the formation of a secondary cytoplasmic complex, referred to as complex-II, which is composed of FADD, Caspase-8, cFLIP, RIPK1 and RIPK3, and that has cytotoxic activity [10,13,29]. Complex II can induce (i) apoptosis, via the activation of the initiator Caspase-8, which, in turn, cleaves and activates the executioner Caspase-3 and Caspase-7 [30]; (ii) necroptosis, mediated by the kinase activity of RIPK1 and RIPK3 and the pseudokinase MLKL, which, following RIPK3-mediated activation, forms pores in the plasma membrane [31–33]; and (iii) pyroptosis, following Caspase-8-mediated cleavage of Gasdermin D that, similarly to MLKL, has the ability to form pores on the plasma membrane, leading to a lytic type of death [34,35]. While in non-immune cells Caspase-8 activation mainly leads to apoptosis, in innate immune cells, such as macrophages, Caspase-8 activation can induce both caspase-dependent apoptosis and Gasdermin D-mediated pyroptosis-like death [35] (Figure 1).

**Figure 1.** TNFR1-induced-signalling pathway. Cartoon depicting the TNFR1-induced-signalling pathway. Upon binding of TNF to TNFR1, a membrane-bound complex referred to as complex-I forms. This complex is characterised by the presence of adaptor proteins (e.g., TRADD, TRAF2, SPATA2, TAB1/2 and NAP1/TANK1), E3 ligases (e.g., cIAP1/2 and LUBAC), which conjugate poly-ubiquitin chains of different topology (i.e., K63, K48, K11 and M1) to different proteins of the complex, the deubiquitinases (DUBs) A20 and CYLD, and protein kinases such as RIPK1, IKK1/2, TAK1 and TBK1/IKKε. Complex-I promotes the activation of NF-κB and MAPKs that in turn mediate the expression of pro-survival as well as pro-inflammatory genes. Under certain circumstances, a secondary cytoplasmic complex originates in the cytosol from complex-I, referred to as complex-II. This complex is composed of FADD, cFLIP, Caspase-8, RIPK1 and RIPK3. Caspase-8 can trigger apoptosis via activation of Caspase-3 or, in some cell type, pyroptosis, via cleavage of Gasdermin D. Upon Caspase-8 inhibition by the means of synthetic- or viral-encoded caspase inhibitor, RIPK1 activates RIPK3 that in turn phosphorylates MLKL that undergoes activation and executes necroptosis. Of note, OTULIN, XIAP and MK2, have important regulatory functions in the TNFR1-signalling pathway, despite they are not directly recruited to complex-I or complex-II. OTULIN regulates the availability of the LUBAC components for their recruitment to complex-I. XIAP controls RIPK1 ubiquitination status outside complex-II and potentially its cytotoxic activity. MK2, by phosphorylating RIPK1, modulates its killing activity.

Both the conjugation and hydrolysis of ubiquitin moieties represent one of the most studied checkpoint mechanisms that control complex-II formation and restrain TNF cytotoxicity [36]. Amongst the key proteins and protein complexes responsible for these ubiquitin-system-mediated control mechanisms, are LUBAC (E3 ligase complex) [37], XIAP (X-linked IAP) [38], A20 and OTULIN (DUBs) [21] (Figure 2). In the next sections we focus on the pathological consequences of mutations disrupting the activity of the above indicated E3s and DUBs in genetically modified mice and human patients, and highlight the similarities and differences between the two systems.

**Figure 2.** A20, LUBAC, OTULIN and XIAP regulate the balance between cell death and inflammation in mice. Cartoons illustrating how A20 (**a**), LUBAC (**b**), OTULIN (**c**) and XIAP (**d**) control the balance between NF-κB-mediated gene activation and complex-II-mediated cell death in mouse cells. A20 deletion results in the deregulation of both NF-κB response and RIPK1/RIPK3/MLKL-induced necroptosis, which, in turn, triggers inflammasome activation (**a**). Individual deletion of the LUBAC components causes an attenuation of NF-κB response, but an exacerbation of complex-II-mediated cell death, which can result in embryonic lethality or cell death-dependent inflammation in adult mice (**b**). OTULIN deletion leads to hyperactivation of NF-κB and, at the same time, can unleash complex-II-mediated cell death. This can in turn cause embryonic lethality or cell death-dependent inflammation in adult mice (**c**). XIAP deletion causes both Caspase-8-dependent apoptosis and RIPK3-dependent inflammasome activation, which eventually triggers inflammation (**d**).

#### **3. LUBAC**

Genetic deletion of any of the three LUBAC components causes either absence of linear chains (HOIP and HOIL-1) or reduction in linear chains (SHARPIN) in TNFR1 induced complex-I [39]. The phenotype of mice bearing a naturally occurring mutation in the SHARPIN gene, referred to as *cpdm* (chronic proliferative dermatitis mice) (Table 1), which causes its deletion, initially puzzled scientists of the cell death field [40]. Although SHARPIN deletion caused reduced NF-κB-mediated gene activation in vitro, *cpdm* mice developed chronic dermatitis and multiorgan inflammation [20]. This conundrum was solved by findings showing that (i) attenuation of linear ubiquitination in complex-I on the one side impairs NF-κB activation and reduces gene expression, but on the other side causes cell death by favouring complex-II formation in response to TNF stimulation [20]; and (ii) TNF-mediated cell death can be a potent trigger of inflammation. The latter was supported by the evidence that genetic deletion of TNF rescues *cpdm* mice from developing dermatitis and represented a watershed in the cell death field [20]. Indisputable evidence

confirming that cell death was the cause of inflammation in *cpdm* mice came from the fact that combined deletion of FADD in keratinocytes or Caspase-8, to suppress apoptosis, and RIPK3 or MLKL to suppress necroptosis, prevented the inflammatory phenotype of SHARPIN mutant-mice [41,42]. Around the same years, animal models of cell deathinduced inflammation, some of which we discuss here, boomed, further corroborating the notion that cell death can be the etiological agent of inflammatory syndromes. Differently from mice bearing the SHARPIN mutation, mice lacking HOIP or HOIL-1 are embryonically lethal due to exacerbated endothelial cell death and heart defects [39,43] (Table 1). Yet, the selective deletion of HOIP or HOIL-1 in keratinocyte causes severe skin inflammation, which is cell death dependent [44,45]. However, differently from *cpdm*, lethal dermatitis was found to be only partially TNF-driven [44]. Indeed, while concomitant deletion of RIPK3 and Caspase-8 completely prevents the inflammatory lesions, loss of TNFR1 delays the onset of dermatitis, but mutant mice still succumb later in life due to severe skin inflammation [44]. What triggers cell death in the absence of linear ubiquitination beyond TNF? It was reported that the inflammatory phenotype occurring as a consequence of HOIL-1 deficiency could be significantly delayed by the simultaneous deletion of TNFR1 and the DD of CD95 and TRAIL-R. This indicates that these three death receptors act in concert to induce cell death in the skin when LUBAC activity is completely abrogated [44]. In the liver, HOIP deletion causes hepatocellular carcinoma that arises from inflammation caused by hepatocyte death [46]. The role of LUBAC in immune cells has also been described. T cellspecific deletion of HOIP or HOIL-1 leads to an almost complete depletion of CD4/CD8+ T cells in mice [47]. HOIP- and HOIL-1-deficient T cells exhibited delayed NF-κB activation upon TCR and TNFR1 stimulation, consistently with a role for LUBAC in the activation of NF-κB. However, enforced NF-κB activation via the overexpression of a constitutively active version of IKKβ (IKKβca), does not restore normal T cell numbers [47]. Equally intriguing was the fact that T cell developmental defects also seem to be independent of cell death activation. Similarly, loss of LUBAC in B cells impairs signalling via the TNFR superfamily member CD40, highlighting an important role of linear ubiquitination in B cell activation [48]. Notably, mice with full body deficiency in HOIP or HOIL-1 displayed severe defects in haematopoietic progenitors, which affected erythropoiesis, and this was independent of cell death [39,49] (Table 1). This evidence would suggest that, differently from keratinocytes or other cell types, LUBAC activity does not primarily inhibit cell death in immune cells, but it rather plays an important role in coordinating different signals required for cell development or differentiation.

Last, although HOIL-1 also bears E3 ligase activity, it is not essential for LUBAC activity as E3 catalytic inactive mice are viable [18,50,51]. Instead, HOIL-1 catalytic activity limits linear ubiquitination. Indeed, mouse embryonic fibroblasts (MEFs) expressing catalytically inactive HOIL-1 are protected from cell death and have enhanced NF-κB activation in response to TNF due to increased levels of linear ubiquitin chains [39,51]. As a consequence, HOIL-1 catalytic inactive mice are protected from hepatocyte death in a model of liver damage and are also protected from dermatitis in a *cpdm* background [51]. Intriguingly, mice harbouring HOIL-1 catalytic inactivity displayed increased glycogen deposition in muscle [52].

To date, only a limited number of patients bearing LUBAC mutations have ever been reported. The amino acid sequence similarity between human and mouse is 91.6% for HOIL-1, 86.5% for HOIP and 73.6% for SHARPIN. The first reported LUBAC-mutant patients, in 2012, were two sisters from a non-consanguineous marriage, with compound heterozygous mutation of HOIL-1, consisting of deletion and nonsense mutation (p.Q185X) and one boy from a consanguineous marriage, with homozygous deletion of two nucleotides (c.121\_122delCT) in HOIL-1 [53]. Few weeks after their birth, they started developing a series of disorders including autoinflammation (e.g., abdominal pain), immunodeficiency, which rendered the three patients susceptible to bacterial infections, amylopectin-like deposits in muscle and cardiomyopathy [53]. They all died by the age of eight years [53]. Immune cells, in particular the monocytes, lacking HOIL-1 are hyperresponsive to IL-1β stimulation, with exaggerated

cytokine production, including IL-6 and IL-8. On the other hand, non-immune cells, such as fibroblasts, exhibited a delayed NF-κB response following IL-1β and TNF stimulation and severely impaired cytokine and chemokine production [53] (Table 1). This dichotomy most likely explains the paradoxical clinical phenotype observed in the three HOIL-1 mutant patients. Indeed, while the hyperresponsiveness of monocytes is the underlying cause of autoinflammation, the refractoriness of non-immune cells to mount an innate immune response could explain the immunodeficiency and susceptibility to bacterial infections. One year later, two independent studies reported a few more cases of patients with homozygous or heterozygous compound truncating or missense mutations of HOIL-1 [54]. These patients suffered from progressive muscular weakness, abnormal accumulation of glycogen in muscles and cardiomyopathy. Intriguingly, they presented no sign of autoinflammation and immunodeficiency [54]. Even more intriguingly was the discovery of two more patients, in 2018, carrying HOIL-1 mutations with both autoinflammatory/immunodeficiency and myopathic features [55]. At present, it is not known what determines whether HOIL-1 mutant patients preponderantly have one or the other phenotype, or both. It is also difficult to understand whether the mutations present in these patients would result in reduced HOIL-1 E3 ligase activity or whether they would rather behave as a linear ubiquitin-null mutant.

The first HOIP homozygous missense mutation (L72P) patient was reported in 2015 [56]. This patient was born from consanguineous parents. The second one, born from nonconsanguineous parents, carrying biallelic variants, was identified in 2019 [57]. In both cases, the authors reported that, similarly to some HOIL-1 mutant patients, fibroblasts have impaired NF-κB activation upon TNF and IL-1β stimulation while monocytes are hyperresponsive to IL-1β stimulation [56]. In both cases, patients presented clinical features characteristic of multiorgan autoinflammation and immunodeficiency (recurrent bacterial infection). Lymphopenia (T cell depletion) was only present in the first observed patient [56]. The similar clinical manifestations between HOIL-1 and HOIP mutant patients can probably be attributed to the loss of linear ubiquitination, which is a common feature of loss of these two proteins, at least in mice [39] (Table 1).

**Table 1.** Overview of the pathological consequences of the deletion or mutation of the indicated genes in mice and human patients.

#### **Table 1.** *Cont.*

Very recently, a non-synonymous variant of SHARPIN was identified as genetic risk factor for LOAD (late-onset Alzheimer's disease) in a cohort of 202 Japanese individuals [58]. This variant has an amino acid substitution (G186R) that seemingly affects its subcellular localisation and NF-κB activation. In a follow-up study, six more SHARPIN variants were identified from a cohort of 180 patients with LOAD and 184 patients with mild cognitive impairment (Table 1). This, at present, is the only reported association between SHARPIN mutation and human diseases [59].

The different LUBAC mutant mouse models described above have been instrumental in unveiling the physiological role of linear ubiquitination and how linear ubiquitin chains orchestrate inflammatory programs. Equally important was the fact that they allowed to unravel the link between cell death and inflammation and the potent inflammatory potential of cell death activation. Mouse work revealed that the individual LUBAC components contribute to optimal gene activation following stimulation of immune receptors, including TNFR1, but, most importantly, they limit the killing activity of TNF. Therefore, the predominant phenotypic effect triggered in mice by their absence is cell death and cell death-induced inflammation. However, the phenotypic similarities between LUBAC mutant mice and patients are limited to some features of glycogen deposition and heart defects. In the human setting, loss of function mutations of HOIP, HOIL-1 or SHARPIN do not only result in autoinflammation, but also in immunodeficiency, glycogen storage disorders (HOIP and HOIL-1) and neurodegeneration (SHARPIN). This might indicate that (i) in humans, the gene activatory functions of LUBAC are as or more predominant than its cell death inhibitory functions, although the occurrence of cell death has not been fully analysed in patients; and (ii) those individuals carrying LUBAC mutations that escape lethality in utero, might have backup systems in place to regulate cell death and inflammation that are not completely dependent on LUBAC. An extensive cell death analysis in LUBAC mutant patients, using classical cell death markers might help elucidate the role of LUBAC in controlling organism homeostasis, and find therapeutic strategies to improve the care of LUBAC mutant patients.

#### **4. OTULIN**

OTULIN is the only known linear chain-specific deubiquitinase [81]. The amino acid sequence similarity between human and mouse OTULIN is 90.1%. In 2016, homozygous missense mutation of OTULIN was identified in three siblings, from a consanguineous family, affected by a severe sterile form of autoinflammation, which was named OTULIN-related autoinflammatoy syndrome (ORAS) [61]. In the same year, another group identified three more patients, from three different consanguineous families, carrying OTULIN biallelic mutations and symptoms of systemic sterile inflammation (e.g., prolonged fevers and diarrhoea) that they called Otulipenia [63] (Table 1). Few more patients carrying compound heterozygous mutations on OTULIN were identified, with similar clinical manifestations [62]. This prompted different groups of scientists to investigate the molecular basis of this mutant OTULIN-driven inflammatory disorder using mouse models. The most intuitive explanation as to why OTULIN-mutant patients suffered from a severe inflammatory disease was that, without functional OTULIN, there would be an excess of linear chains that would in turn exacerbate NF-κB responses and the consequent production of pro-inflammatory factors. Indeed, both OTULIN-mutant patients and OTULIN-deficient mice (conditional full body and myeloid cell-specific) exhibited linear chains accumulation, increased NF-κB activation and excessive cytokine production [61,63]. The fact that Infliximab (TNF-neutralising antibody) drastically reduced the inflammatory syndrome in patients and mice [61] indicated that the main instigator of the excessive NF-κB activation and cytokine production observed in absence of functional OTULIN (patients) and full-length protein (mice) is TNF (Table 1). Intriguingly, it was concluded that, differently from LUBAC deficient mice, it was the gene activation ability of TNF rather than its cell death-promoting potential that caused the inflammatory phenotype in mice lacking OTULIN.