The Hippo signaling pathway is required for salivary gland development and its dysregulation is associated with Sjogren's-like disease

Sjogren's syndrome (SS) is a complex autoimmune disease that primarily affects salivary and lacrimal glands and is associated with high morbidity. Although the prevailing dogma is that immune system pathology drives SS, increasing evidence points to structural defects, including defective E-cadherin adhesion, to be involved in its etiology. We have shown that E-cadherin plays pivotal roles in the development of the mouse salivary submandibular gland (SMG) by organizing apical-basal polarity in acinar and ductal progenitors and by signaling survival for differentiating duct cells. Recently, E-cadherin junctions have been shown to interact with effectors of the Hippo signaling pathway, a core pathway regulating organ size, cell proliferation and differentiation. We now show that Hippo signaling is required for SMG branching morphogenesis and is involved in the pathophysiology of SS. During SMG development, a Hippo pathway effector, TAZ, becomes increasingly phosphorylated and associated with E-cadherin and α-catenin, consistent with the activation of Hippo signaling. Inhibition of Lats2, an upstream kinase that promotes TAZ phosphorylation, results in dysmorphogenesis of the SMG and impaired duct formation. SMGs from NOD mice, a mouse model for SS, phenocopy the Lats2-inhibited SMGs and exhibit a reduction in E-cadherin junctional components, including TAZ. Importantly, labial specimens from human SS patients display mislocalization of TAZ from junctional regions to the nucleus, coincident with accumulation of extracellular matrix components, fibronectin and CTGF, known downstream targets of TAZ. Our studies show that Hippo signaling plays a crucial role in SMG branching morphogenesis and provide evidence that defects in this pathway are associated with SS in humans

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death

Genome-wide association study identifies Sjögren’s risk loci with functional implications in immune and glandular cells

Sjögren’s disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjögren’s cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands.Research reported in this publication was supported by the National Institutes of Health (NIH): R01AR073855 (C.J.L.), R01AR065953 (C.J.L.), R01AR074310 (A.D.F.), P50AR060804 (K.L.S.), R01AR050782 (K.L.S), R01DE018209 (K.L.S.), R33AR076803 (I.A.), R21AR079089 (I.A.); NIDCR Sjögren’s Syndrome Clinic and Salivary Disorders Unit were supported by NIDCR Division of Intramural Research at the National Institutes of Health funds - Z01-DE000704 (B.W.); Birmingham NIHR Biomedical Research Centre (S.J.B.); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2155 – Projektnummer 390874280 (T.W.); Research Council of Norway (Oslo, Norway) – Grant 240421 (TR.R.), 316120 (M.W-H.); Western Norway Regional Health Authority (Helse Vest) – 911807, 912043 (R.O.); Swedish Research Council for Medicine and Health (L.R., G.N., M.W-H.); Swedish Rheumatism Association (L.R., G.N., M.W-H.); King Gustav V’s 80-year Foundation (G.N.); Swedish Society of Medicine (L.R., G.N., M.W-H.); Swedish Cancer Society (E.B.); Sjögren’s Syndrome Foundation (K.L.S.); Phileona Foundation (K.L.S.). The Stockholm County Council (M.W-H.); The Swedish Twin Registry is managed through the Swedish Research Council - Grant 2017-000641. The French ASSESS (Atteinte Systémique et Evolution des patients atteints de Syndrome de Sjögren primitive) was sponsored by Assistance Publique-Hôpitaux de Paris (Ministry of Health, PHRC 2006 P060228) and the French society of Rheumatology (X.M.).publishedVersio

Genome-wide association study identifies Sjögren's risk loci with functional implications in immune and glandular cells.

Sjögren’s disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjögren’s cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands.We thank all the research and clinical staff, consortium investigators, and study participants (detailed in Supplementary Information), and funding agencies who made this study possible. The content of this publication is solely the responsibility of the authors and does not represent the official views of the funding agencies listed below. Research reported in this publication was supported by the National Institutes of Health (NIH): R01AR073855 (C.J.L.), R01AR065953 (C.J.L.), R01AR074310 (A.D.F.), P50AR060804 (K.L.S.), R01AR050782 (K.L.S), R01DE018209 (K.L.S.), R33AR076803 (I.A.), R21AR079089 (I.A.); NIDCR Sjögren’s Syndrome Clinic and Salivary Disorders Unit were supported by NIDCR Division of Intramural Research at the National Institutes of Health funds - Z01-DE000704 (B.W.); Birmingham NIHR Biomedical Research Centre (S.J.B.); Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2155 – Projektnummer 390874280 (T.W.); Research Council of Norway (Oslo, Norway) – Grant 240421 (TR.R.), 316120 (M.W-H.); Western Norway Regional Health Authority (Helse Vest) – 911807, 912043 (R.O.); Swedish Research Council for Medicine and Health (L.R., G.N., M.W-H.); Swedish Rheumatism Association (L.R., G.N., M.W-H.); King Gustav V’s 80-year Foundation (G.N.); Swedish Society of Medicine (L.R., G.N., M.W-H.); Swedish Cancer Society (E.B.); Sjögren’s Syndrome Foundation (K.L.S.); Phileona Foundation (K.L.S.). The Stockholm County Council (M.W-H.); FOREUM Foundation for Research in Rheumatology (R.J., M.W-H). The Swedish Twin Registry is managed through the Swedish Research Council - Grant 2017-000641. The French ASSESS (Atteinte Systémique et Evolution des patients atteints de Syndrome de Sjögren primitive) was sponsored by Assistance Publique-Hôpitaux de Paris (Ministry of Health, PHRC 2006 P060228) and the French society of Rheumatology (X.M.). We want to acknowledge the following invesigators who recruited patients: Jacques-Eric Gottenberg, Valerie Devauchelle-Pensec, Jean Jacques Dubost, Anne-Laure Fauchais, Vincent Goeb, Eric Hachulla, Claire Larroche, Véronique Le Guern, Jacques Morel, Aleth Perdriger, Emmanuelle Dernis, Stéphanie Rist, Damien Sene, Olivier Vittecoq. We also thank Sarah Tubiana and all staff members of the Bichat Hospital Biological Resource Center (Paris) for centralizing and managing biological collection. We also thank Rezvan Kiani Dehkordi, Karolina Tandre, Käth Nilsson, Marianne Eidsheim, Kjerstin Jacobsen, Ingeborg Kvivik and Kjetil Bårdsen for collecting patient blood samples. We acknowledge the SNP&SEQ Technology Platform, Uppsala, part of National Genomics Infrastructure (NGI) Sweden, for genotyping of Scandinavian samples, and the Swedish Twin Registry for access to data. The SNP&SEQ Technology Platform was supported by Science for Life Laboratory, Uppsala University, the Knut and Alice Wallenberg Foundation and the Swedish Research Council. Last, we thank the investigators for the following dbGaP studies: Phs000428.v2.p2: This study used control data from the Health and Retirement Study in dbGaP (phs000428.v2.p2) submitted by David Weir, PhD at the University of Michigan and funded by the National Institute of Aging RC2 AG036495 and RC4 AG039029. Phs000672.v1.p1: Genotype data from the Sjögren’s International Collaborative Clinical Alliance (SICCA) Registry was obtained through dbGAP accession number phs000672.v1.p1. This study was supported by the National Institute of Dental and Craniofacial Research (NIDCR), the National Eye Institute, and the Office of Research on Women’s Health through contract number N01-DE-32636. Genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health (NIH) to the Johns Hopkins University (contract numbers HHSN268200782096C, HHSN268201100011I, HHSN268201200008I). Funds for genotyping were provided by the NIDCR through CIDR’s NIH contract. Assistance with data cleaning and imputation was provided by the University of Washington. We thank investigators from the following studies that provided DNA samples for genotyping: the Genetic Architecture of Smoking and Smoking Cessation, Collaborative Genetic Study of Nicotine Dependence (phs000404.v1.p1); Age-Related Eye Disease Study (AREDS) - Genetic Variation in Refractive Error Substudy (phs000429.v1.p1); and National Institute of Mental Health’s Human Genetics Initiative (phs000021.v3.p2, phs000167.v1.p1). We thank the many clinical collaborators and research participants who contributed to this research. Phs000196.v3.p1: Investigators and Parkinson Disease patients that contributed to this Genome-wide Association Study of Parkinson Disease. phs000187.v1.p1: Research support to collect data and develop an application to support the High Density SNP Association Analysis of Melanoma project was provided by 3P50CA093459, 5P50CA097007, 5R01ES011740, and 5R01CA133996

Indole-3-carbinol-induced death in cancer cells involves EGFR downregulation and is exacerbated in a 3D environment

Indole-3-carbinol-induced death in cancer cells involves EGFR downregulation and is exacerbated in a 3D environmen

Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction

Abstract Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in complex data. This study applied machine learning to classify levels of meibomian gland dysfunction from tear proteins. The aim was to investigate proteomic changes between groups with different severity levels of meibomian gland dysfunction, as opposed to only separating patients with and without this condition. An established feature importance method was used to identify the most important proteins for the resulting models. Moreover, a new method that can take the uncertainty of the models into account when creating explanations was proposed. By examining the identified proteins, potential biomarkers for meibomian gland dysfunction were discovered. The overall findings are largely confirmatory, indicating that the presented machine learning approaches are promising for detecting clinically relevant proteins. While this study provides valuable insights into proteomic changes associated with varying severity levels of meibomian gland dysfunction, it should be noted that it was conducted without a healthy control group. Future research could benefit from including such a comparison to further validate and extend the findings presented here

Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence

Meibomian gland dysfunction is the most common cause of dry eye disease and leads to significantly reduced quality of life and social burdens. Because meibomian gland dysfunction results in impaired function of the tear film lipid layer, studying the expression of tear proteins might increase the understanding of the etiology of the condition. Machine learning is able to detect patterns in complex data. This study applied machine learning to classify levels of meibomian gland dysfunction from tear proteins. The aim was to investigate proteomic changes between groups with different severity levels of meibomian gland dysfunction, as opposed to only separating patients with and without this condition. An established feature importance method was used to identify the most important proteins for the resulting models. Moreover, a new method that can take the uncertainty of the models into account when creating explanations was proposed. By examining the identified proteins, potential biomarkers for meibomian gland dysfunction were discovered. The overall findings are largely conirmatory, indicating that the presented machine learning approaches are promising for detecting clinically relevant proteins. While this study provides valuable insights into proteomic changes associated with varying severity levels of meibomian gland dysfunction, it should be noted that it was conducted without a healthy control group. Future research could benefit from including such a comparison to further validate and extend the findings presented here

Gene expression alterations in salivary gland epithelia of Sjögren’s syndrome patients are associated with clinical and histopathological manifestations

Abstract Sjögren’s syndrome (SS) is a complex autoimmune disease associated with lymphocytic infiltration and secretory dysfunction of salivary and lacrimal glands. Although the etiology of SS remains unclear, evidence suggests that epithelial damage of the glands elicits immune and fibrotic responses in SS. To define molecular changes underlying epithelial tissue damage in SS, we laser capture microdissected (LCM) labial salivary gland epithelia from 8 SS and 8 non-SS controls for analysis by RNA sequencing (RNAseq). Computational interrogation of gene expression signatures revealed that, in addition to a division of SS and non-SS samples, there was a potential intermediate state overlapping clustering of SS and non-SS samples. Differential expression analysis uncovered signaling events likely associated with distinct SS pathogenesis. Notable signals included the enrichment of IFN-γ and JAK/STAT-regulated genes, and the induction of genes encoding secreted factors, such as LTF, BMP3, and MMP7, implicated in immune responses, matrix remodeling and tissue destruction. Identification of gene expression signatures of salivary epithelia associated with mixed clinical and histopathological characteristics suggests that SS pathology may be defined by distinct molecular subtypes. We conclude that gene expression changes arising in the damaged salivary epithelia may offer novel insights into the signals contributing to SS development and progression

Proteomic and histopathological characterisation of sicca subjects and primary Sjögren’s syndrome patients reveals promising tear, saliva and extracellular vesicle disease biomarkers

Background Mononuclear cell infiltration of exocrine glands, production of Ro/SSA and La/SSB autoantibodies, along with oral and ocular dryness, are characteristic features of primary Sjögren’s syndrome (pSS). Non-SS sicca subjects, an underexplored group in relation to pSS, display similar sicca symptoms, with possible mild signs of inflammation in their salivary glands, yet with no serological detection of autoantibody production. In this study, we investigated inflammatory manifestations in the salivary gland tissue, tear fluid and saliva of non-SS subjects, as compared to pSS patients and healthy individuals. Methods Fifteen non-SS, 10 pSS and 10 healthy subjects were included in the analyses. Histological evaluation of salivary gland biopsies was performed. Liquid chromatography-mass spectrometry (LC-MS) was conducted on tear fluid and stimulated whole saliva, and proteomic biomarker profiles were generated. Extracellular vesicle (EVs) isolation and characterisation from both fluids were also combined with LC-MS. The LC-MS data were analysed for quantitative differences between patient and control groups using Scaffold. Database for Annotation, Visualization and Integrated Discovery (DAVID) and Functional Enrichment Analysis Tool (FunRich) were applied for functional analyses. Results Histopathological evaluation of salivary gland biopsies showed implications of milder inflammation in non-SS subjects through mononuclear cell infiltration, fibrosis and fatty replacement, as compared to pSS patients. Although unaffected in the non-SS group, upregulation of proinflammatory pathways and proteins involved in ubiquitination (LMO7 and HUWE1) and B cell differentiation (TPD52) were detected in tear fluid of pSS patients. Moreover, overexpression of proteins STOM, ANXA4 and ANXA1, regulating cellular innate and adaptive immunological pathways, were further identified in EVs from tear fluid of pSS patients. Finally, whole saliva and EVs isolated from whole saliva of pSS patients expressed proteins vital for innate MHC class I cellular regulation (NGAL) and T cell activation (CD44). Conclusions Non-SS sicca subjects may show implications of mild inflammation in their glandular tissue, while their protein profile was strikingly more similar to healthy controls than to pSS patients. Hence, the tear and salivary biomarkers identified could be implemented as potential non-invasive diagnostic tools that may aid in increasing diagnostic accuracy when evaluating non-SS subjects and pSS patients and monitoring disease progression

Tear and Saliva Metabolomics in Evaporative Dry Eye Disease in Females

Accurate diagnosis of dry eye disease (DED) is challenging, and even today there is no gold standard biomarker of DED. Hypothesis-free global metabolomic studies of tears from DED patients have great potential to discover metabolites and pathways affected in the pathophysiology of DED, and to identify possible future biomarkers. These metabolites and biomarkers could be important for diagnosing and monitoring disease as well as for new therapeutic targets and strategies. As DED is associated with dry mouth, this study aimed to perform metabolomic analyses of tears and saliva from patients with decreased tear film break-up time but normal Schirmer test, and age-matched controls with both tear production and stability within physiological range. We applied strict inclusion criteria to reduce sampling bias in the metabolomic analyses and selected only age-matched females with Schirmer test values between 10–15 mm/5 min. The tear film analysis arm included 19 patients (with tear film break-up time 0–5 s) and 12 controls (with tear film break-up time 10–30 s), while the salivary analysis arm consisted of a subset which included 18 patients and six controls. Metabolomic analyses were performed using liquid chromatography and high-resolution mass spectrometry. Analyses using a global database search detected a total of 56 metabolites in tear samples that were significantly different between the groups. Of these, several have known associations with DED. These metabolites are present in meibum and have anti-oxidative characteristics or associations with the ocular microbiome, and altered concentrations suggest that they may play a significant role in DED associated with decreased tear film stability. In saliva, hypotaurine levels were lower among patients with tear film instability. In this pilot study, we found different levels of several metabolites in patients with decreased tear film break-up time that may have associations with DED. Future studies are required to replicate our findings and clarify the exact roles of these metabolites