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Objective: Systemic inflammatory autoimmune diseases (SIADs) such as systemic lupus erythematosus (SLE), primary Sjögren disease (pSS), and idiopathic inflammatory myopathies (myositis) are complex conditions characterized by shared circulating autoantibodies and clinical manifestations, including skin rashes, among others. This study was aimed at elucidating the genetics underlying these common features.

Methods: We performed targeted DNA sequencing of coding and regulatory regions from approximately 1,900 immune-related genes in a large cohort of 2,292 well-characterized Scandinavian patients with SIADs with SLE, pSS, and myositis as well as 1,252 controls. A gene-based functionally weighted genetic score for aggregate testing of all genetic variants, including rare variants, was complemented by in silico functional analyses and in vitro reporter experiments.

Results: Case–control association analysis detected known and potentially novel genetic loci in agreement with previous genetic and transcriptomics findings linked to the SIAD autoimmune background. Intriguingly, case–case comparisons between patient subgroups with and without specific autoantibodies revealed that the subgroups defined by antinuclear antibodies and anti–double-stranded DNA antibodies have unique genetic profiles reflecting their heterogeneity. When focusing on clinical features, we overall showed that dual-specificity phosphatase 1 (DUSP1) protective genetic variants lead to increased gene expression and potentially to anti-inflammatory effects on the SIAD-associated skin phenotype. This is consistent with recent genetic findings on eczema and with the previously reported down-regulation of the MAPK signaling-related gene DUSP1 in other skin disorders.

Conclusion: Together, this suggests common molecular mechanisms potentially underlying overlapping clinical manifestations shared among different disorders and informs clinical heterogeneity, which could be translated to improve disease diagnostic and treatment, also in more generalized disease frameworks.

In the 1980s, my research career begun with microbial DNA diagnostics at Orion Pharmaceutica in Helsinki, Finland, where I was part of an innovative team that developed novel methods based on the polymerase chain reaction (PCR) and the biotin-avidin interaction. One of our key achievements during this time was the invention of the solid-phase minisequencing method for genotyping single nucleotide polymorphisms (SNPs). In the 1990s, I shifted focus to human genetics, investigating mutations of the'Finnish disease heritage'. During this period, I also developed quantitative methods using PCR and minisequencing of mitochondrial mutations and for forensic analyses. In the late 1990s and early 2000s, microarray-based SNP genotyping became a major topic for my research, first in Helsinki and later with my research group at Uppsala University in Sweden. By the mid-2000s, I began collaborating with leading clinicians on genetics of autoimmune disease, specifically systemic lupus erythematosus and later worked on the classification and clinical outcome of pediatric acute lymphoblastic leukemia, when large-scale genomics and epigenomics emerged.These collaborations, which focused on integrating genomics into clinical practice, lasted almost two decades until I retired from research in 2022. In parallel with my research activities, I led the SNP/ DNA Technology Platform in the Wallenberg Consortium North program from 2001 to 2006. I continued as Director of the SNP&SEQ Technology Platform, which expanded rapidly during the 2010s, and became part of Science for Life Laboratory in 2013. Today (in 2024), the SNP&SEQ Technology Platform is one of the largest units of the Swedish National Genomics Infrastructure hosted by SciLifeLab. The present article provides a personal perspective on nearly four decades of research, highlighting projects and methods I found particularly exciting or important.

OBJECTIVE: B cells are important in the pathogenesis of primary Sjögren's syndrome (pSS). Patients positive for SSA/SSB autoantibodies are more prone to systemic disease manifestations and adverse outcomes. We aimed to determine the role of B cell composition, gene expression and B cell receptor (BCR) usage in pSS subgroups stratified for SSA/SSB antibodies.

METHODS: Over 230 000 B cells were isolated from peripheral blood of pSS patients (n = 6 SSA-, n = 8 SSA+ single positive and n = 10 SSA/SSB+ double positive) and four healthy controls, and processed for single cell RNA and VDJ sequencing.

RESULTS: We show that SSA/SSB+ patients present the highest and lowest proportion of naïve and memory B cells respectively, and the highest upregulation of interferon-induced genes across all B cell subtypes. Differential usage of IGHV showed that IGHV1-69 and IGHV4-30-4 were more often used in all pSS subgroups compared with controls. Memory B cells from SSA/SSB+ patients displayed a higher proportion of cells with unmutated VDJ transcripts compared to other pSS patient groups and controls, indicating altered somatic hypermutation processes. Comparison with previous studies revealed heterogeneous clonotype pools, with little overlap in CDR3 sequences. Joint analysis using scRNA-seq and scVDJ-seq data allowed unsupervised stratification pSS patients, and identified novel parameters that correlated to disease manifestations and antibody status.

CONCLUSION: We describe heterogeneity and molecular characteristics in B cells from pSS patients, providing clues to intrinsic differences in B cells that affect the phenotype and outcome, allowing stratification of pSS patients at improved resolution. This article is protected by copyright. All rights reserved.

Background In patients with idiopathic inflammatory myopathies (IIM), autoantibodies are associated with specific clinical phenotypes suggesting a pathogenic role of adaptive immunity. We explored if autoantibody profiles are associated with specific HLA genetic variants and clinical manifestations in IIM. Methods We included 1348 IIM patients and determined the occurrence of 14 myositis-specific or-associated autoantibodies. We used unsupervised cluster analysis to identify autoantibody-defined subgroups and logistic regression to estimate associations with clinical manifestations, HLA-DRB1, HLA-DQA1, HLA-DQB1 alleles, and amino acids imputed from genetic information of HLA class II and I molecules. Findings We identified eight subgroups with the following dominant autoantibodies: anti-Ro52, -U1RNP, -PM/Scl,-Mi2,-Jo1,-Jo1/Ro52,-TIF1 gamma or negative for all analysed autoantibodies. Associations with HLA-DRB1*11, HLA-DRB1*15, HLA-DQA1*03, and HLA-DQB1*03 were present in the anti-U1RNP-dominated subgroup. HLA-DRB1*03, HLA-DQA1*05, and HLA-DQB1*02 alleles were overrepresented in the anti-PM/Scl and anti-Jo1/ Ro52-dominated subgroups. HLA-DRB1*16, HLA-DRB1*07 alleles were most frequent in anti-Mi2 and HLA- DRB1*01 and HLA-DRB1*07 alleles in the anti-TIF1 gamma subgroup. The HLA-DRB1*13, HLA-DQA1*01 and HLA-DQB1*06 alleles were overrepresented in the negative subgroup. Significant signals from variations in class I molecules were detected in the subgroups dominated by anti-Mi2, anti-Jo1/Ro52, anti-TIF1 gamma, and the negative subgroup. Interpretation Distinct HLA class II and I associations were observed for almost all autoantibody-defined subgroups. The associations support autoantibody profiles use for classifying IIM which would likely reflect underlying pathogenic mechanisms better than classifications based on clinical symptoms and/or histopathological features. Funding See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript. Copyright (c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Introduction The suitability of whole-genome sequencing (WGS) as the sole method to detect clinically relevant genomic aberrations in B-cell acute lymphoblastic leukemia (ALL) was investigated with the aim of replacing current diagnostic methods.

Methods For this purpose, we assessed the analytical performance of 150 bp paired-end WGS (90x leukemia/30x germline). A set of 88 retrospective B-cell ALL samples were selected to represent established ALL subgroups as well as ALL lacking stratifying markers by standard-of-care (SoC), so-called B-other ALL.

Results Both the analysis of paired leukemia/germline (L/N)(n=64) as well as leukemia-only (L-only)(n=88) detected all types of aberrations mandatory in the current ALLTogether trial protocol, i.e., aneuploidies, structural variants, and focal copy-number aberrations. Moreover, comparison to SoC revealed 100% concordance and that all patients had been assigned to the correct genetic subgroup using both approaches. Notably, WGS could allocate 35 out of 39 B-other ALL samples to one of the emerging genetic subgroups considered in the most recent classifications of ALL. We further investigated the impact of high (90x; n=58) vs low (30x; n=30) coverage on the diagnostic yield and observed an equally perfect concordance with SoC; low coverage detected all relevant lesions.

Discussion The filtration of the WGS findings with a short list of genes recurrently rearranged in ALL was instrumental to extract the clinically relevant information efficiently. Nonetheless, the detection of DUX4 rearrangements required an additional customized analysis, due to multiple copies of this gene embedded in the highly repetitive D4Z4 region. We conclude that the diagnostic performance of WGS as the standalone method was remarkable and allowed detection of all clinically relevant genomic events in the diagnostic setting of B-cell ALL.

Genomic analyses have redefined the molecular subgrouping of pediatric acute lymphoblastic leukemia (ALL). Molecular subgroups guide risk-stratification and targeted therapies, but outcomes of recently identified subtypes are often unclear, owing to limited cases with comprehensive profiling and cross-protocol studies. We developed a machine learning tool (ALLIUM) for the molecular subclassification of ALL in retrospective cohorts as well as for up-front diagnostics. ALLIUM uses DNA methylation and gene expression data from 1131 Nordic ALL patients to predict 17 ALL subtypes with high accuracy. ALLIUM was used to revise and verify the molecular subtype of 281 B-cell precursor ALL (BCP-ALL) cases with previously undefined molecular phenotype, resulting in a single revised subtype for 81.5% of these cases. Our study shows the power of combining DNA methylation and gene expression data for resolving ALL subtypes and provides a comprehensive population-based retrospective cohort study of molecular subtype frequencies in the Nordic countries.

Objective Copy number variation of the C4 complement components, C4A and C4B, has been associated with systemic inflammatory autoimmune diseases. This study was undertaken to investigate whether C4 copy number variation is connected to the autoimmune repertoire in systemic lupus erythematosus (SLE), primary Sjogren's syndrome (SS), or myositis.

Methods Using targeted DNA sequencing, we determined the copy number and genetic variants of C4 in 2,290 well-characterized Scandinavian patients with SLE, primary SS, or myositis and 1,251 healthy controls.

Results A prominent relationship was observed between C4A copy number and the presence of SSA/SSB autoantibodies, which was shared between the 3 diseases. The strongest association was detected in patients with autoantibodies against both SSA and SSB and 0 C4A copies when compared to healthy controls (odds ratio [OR] 18.0 [95% confidence interval (95% CI) 10.2-33.3]), whereas a weaker association was seen in patients without SSA/SSB autoantibodies (OR 3.1 [95% CI 1.7-5.5]). The copy number of C4 correlated positively with C4 plasma levels. Further, a common loss-of-function variant in C4A leading to reduced plasma C4 was more prevalent in SLE patients with a low copy number of C4A. Functionally, we showed that absence of C4A reduced the individuals' capacity to deposit C4b on immune complexes.

Conclusion We show that a low C4A copy number is more strongly associated with the autoantibody repertoire than with the clinically defined disease entities. These findings may have implications for understanding the etiopathogenetic mechanisms of systemic inflammatory autoimmune diseases and for patient stratification when taking the genetic profile into account.

By performing whole-genome sequencing in a Swedish cohort of 71 parent-offspring trios, in which the child in each family is affected by systemic lupus erythematosus (SLE, OMIM 152700), we investigated the contribution of de novo variants to risk of SLE. We found de novo single nucleotide variants (SNVs) to be significantly enriched in gene promoters in SLE patients compared with healthy controls at a level corresponding to 26 de novo promoter SNVs more in each patient than expected. We identified 12 de novo SNVs in promoter regions of genes that have been previously implicated in SLE, or that have functions that could be of relevance to SLE. Furthermore, we detected three missense de novo SNVs, five de novo insertion-deletions, and three de novo structural variants with potential to affect the expression of genes that are relevant for SLE. Based on enrichment analysis, disease-affecting de novo SNVs are expected to occur in one-third of SLE patients. This study shows that de novo variants in promoters commonly contribute to the genetic risk of SLE. The fact that de novo SNVs in SLE were enriched to promoter regions highlights the importance of using whole-genome sequencing for identification of de novo variants.

Primary Sjogren's syndrome (pSS) is an autoimmune inflammatory disease with profound clinical heterogeneity, where excessive activation of the type I interferon (IFN) system is considered one of the key mechanisms in disease pathogenesis. Here we present a DNA methylation-based IFN system activation score (DNAm IFN score) and investigate its potential associations with sub-phenotypes of pSS. The study comprised 100 Swedish patients with pSS and 587 Swedish controls. For replication, 48 patients with pSS from Stavanger, Norway, were included. IFN scores were calculated from DNA methylation levels at the IFN-induced genes RSAD2, IFIT1 and IFI44L. A high DNAm IFN score, defined as > mean(controls) +2SD(controls) (IFN score > 4.4), was observed in 59% of pSS patients and in 4% of controls (p=1.3x10(-35)). Patients with a high DNAm IFN score were on average seven years younger at symptom onset (p=0.017) and at diagnosis (p=3x10(-3)). The DNAm IFN score levels were significantly higher in pSS positive for both SSA and SSB antibodies compared to SSA/SSB negative patients (p(discovery)=1.9x10(-8), p(replication)=7.8x10(-4)). In patients positive for both SSA subtypes Ro52 and Ro60, an increased score was identified compared to single positive patients (p=0.022). Analyzing the discovery and replication cohorts together, elevated DNAm IFN scores were observed in pSS with hypergammaglobulinemia (p=2x10(-8)) and low C4 (p=1.5x10(-3)) compared to patients without these manifestations. Patients < 70 years with ongoing lymphoma at DNA sampling or lymphoma at follow-up (n=7), presented an increased DNAm IFN score compared to pSS without lymphoma (p=0.025). In conclusion, the DNAm-based IFN score is a promising alternative to mRNA-based scores for identification of patients with activation of the IFN system and may be applied for patient stratification guiding treatment decisions, monitoring and inclusion in clinical trials.

Objective To investigate how genetics influence the risk of smoking-related systemic lupus erythematosus (SLE) manifestations. Methods Patients with SLE (n(discovery cohort)=776, n(replication cohort)=836) were genotyped using the 200K Immunochip single nucleotide polymorphisms (SNP) Array (Illumina) and a custom array. Sixty SNPs with SLE association (p<5.0x10(-8)) were analysed. Signal transducer and activator of transcription 4 (STAT4) activation was assessed in in vitro stimulated peripheral blood mononuclear cells from healthy controls (n= 45). Results In the discovery cohort, smoking was associated with myocardial infarction (MI) (OR 1.96 (95% CI 1.09 to 3.55)), with a greater effect in patients carrying any rs11889341 STAT4 risk allele (OR 2.72 (95% CI 1.24 to 6.00)) or two risk alleles (OR 8.27 (95% CI 1.48 to 46.27)). Smokers carrying the risk allele also displayed an increased risk of nephritis (OR 1.47 (95% CI 1.06 to 2.03)). In the replication cohort, the high risk of MI in smokers carrying the risk allele and the association between the STAT4 risk allele and nephritis in smokers were confirmed (OR 6.19 (95% CI 1.29 to 29.79) and 1.84 (95% CI 1.05 to 3.29), respectively). The interaction between smoking and the STAT4 risk allele resulted in further increase in the risk of MI (OR 2.14 (95% CI 1.01 to 4.62)) and nephritis (OR 1.53 (95% CI 1.08 to 2.17)), with 54% (MI) and 34% (nephritis) of the risk attributable to the interaction. Levels of interleukin-12-induced phosphorylation of STAT4 in CD8+ T cells were higher in smokers than in non-smokers (mean geometric fluorescence intensity 1063 vs 565, p=0.0063). Lastly, the IL12A rs564799 risk allele displayed association with MI in both cohorts (OR 1.53 (95% CI 1.01 to 2.31) and 2.15 (95% CI 1.08 to 4.26), respectively). Conclusions Smoking in the presence of the STAT4 risk gene variant appears to increase the risk of MI and nephritis in SLE. Our results also highlight the role of the IL12-STAT4 pathway in SLE-cardiovascular morbidity.