To Örebro University

OBJECTIVES: Diagnostic delay is common in pediatric inflammatory bowel disease (PIBD), and fecal calprotectin (FCP) is often limited by challenges with sample collection. Therefore, we aimed to identify and validate a blood-based diagnostic protein signature of PIBD.

METHODS: Proteins were analyzed using proximity extension assay in plasma samples from treatment-naïve pediatric patients in a Swedish inception cohort referred for suspected IBD and validated in an independent Norwegian population-based pediatric inception cohort. Diagnostic performance was estimated by the area under the curve (AUC) with 95% confidence intervals (CIs).

RESULTS: The discovery cohort included 58 patients with PIBD and 36 symptomatic controls without evidence of IBD, while the validation cohort consisted of 79 patients with PIBD and 37 symptomatic controls. In total, 154 proteins were examined. Univariable analyses identified 26 differentially regulated proteins for PIBD versus symptomatic controls in the discovery cohort (q < 0.05), whereas 29 proteins were differentially regulated in the validation cohort. Using regularized logistic regression, we identified a diagnostic model of 31 proteins that differentiated PIBD from symptomatic controls in the discovery cohort (AUC = 0.83; 95% CI: 0.74-0.90). The protein signature was further reduced to a clinically relevant biomarker consisting of high-sensitivity C-reactive protein (hsCRP) and seven other proteins with diagnostic capacity (AUC = 0.85, 95% CI: 0.78-0.92) outperforming hsCRP in the validation cohort (p = 0.006).

CONCLUSIONS: We identified and validated a blood-based protein signature for PIBD with superior diagnostic performance compared to hsCRP. Given the challenges of fecal sample collection, further assay development may enable integration of these biomarkers into diagnostic pathways for PIBD.

TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02727959.

Background: The disease course of patients with newly diagnosed ulcerative colitis (UC) is highly uncertain, and there is a lack of validated prognostic biomarkers that could aid in clinical decision making.

Methods: Newly diagnosed, mainly treatment naïve patients with UC from three large inception cohorts were used to develop and validate a serum proteomics-based risk score for prognostication of disease course during the first year from diagnosis. In the discovery cohort (n = 161) and validation cohort 1 (n = 186) an aggressive disease course was defined as the presence of any IBD-related surgery, hospital admission for active disease, treatment refractoriness towards targeted therapies (i.e. biologics, JAK-inhibitors or S1P receptor modulators), and >2 courses or high cumulative doses of systemic corticosteroids. In validation cohort 2 (n = 120), an aggressive disease course was defined as the need for a biologic, ciclosporin or surgery. 178 proteins were measured on Olink platforms, and a machine learning algorithm (i.e. regularised regression) was applied to the discovery cohort to develop an UC risk score comprising 23 proteins. The performance of the UC risk score was assessed in the two external validation cohorts. For validation cohort 2, a condensed version of the UC risk score was applied, as only 14 of the original 23 proteins were available. Cox regression estimated hazard ratios (HR) for the association between the UC risk score at diagnosis, time to escalation to targeted therapy (validation cohort I) and time to the defining episode of an aggressive disease course (validation cohort II).

Results: Based on univariate analyses, we identified 59 proteins associated with an aggressive disease course in the discovery cohort (PFDR <0.10; Figure 1A). Twenty could be validated in validation cohort 1, and nine remained in validation cohort 2 (PFDR <0.10; Figure 1B-C).

In the discovery cohort, the machine learning model showed a high predictive capacity, with an area under the curve (AUC) of 0.81 (Figure 1D) and was numerically superior compared with a clinical model comprising sex, age and CRP (AUC = 0.72). Next, the performance of the UC risk score was confirmed in the two external validation cohorts, displaying AUC:s of 0.77 (Figure 1E-F). Patients with a higher UC risk score at diagnosis had increased risk of initiating targeted therapy (HR 4.26, 95% CI 1.91–9.49; Figure 2A). The HR for having an aggressive disease course was 9.12 (95% CI 3.04–27.3; Figure 2B).

Conclusion: We develop a UC risk score for prognostication of disease course and confirmed its high predictive performance by external validation in two independent cohorts. The risk score is a promising tool for quantifying the risk of having an aggressive disease course in UC.

Background: The clinical course of inflammatory bowel disease (IBD) is highly heterogeneous. Previously we identified a protein-based prognostic signature in serum using the proximity extension assay (PEA). To enable clinical translation, further assay development is required, including the establishment of standard curves and clinically actionable cut-offs. Therefore, we aimed to develop, optimise and validate a serum-based assay that quantifies absolute protein concentrations at diagnosis to identify individuals at higher risk of an aggressive course of IBD.

Methods: Proteins were selected from the commercially available Olink inflammation and oncology II panels as well as from five custom-made multiplex panels comprising 460 proteins based on genes in 163 IBD-risk loci (the IBD Character project1). Serum from 71 newly diagnosed IBD patients (Crohn’s disease, n = 29; ulcerative colitis, n = 42) (SIC-IBD) was analysed. Proteins associated with an aggressive course: I) need for biologics, ciclosporin, or surgery for flare after initial induction or II) hospitalisation, refractoriness to targeted therapy, excessive corticosteroid use or surgery within one year, were identified using penalised logistic regression. From these proteins a focused prognostic panel was developed and analytically optimized for absolute quantification. Model performance was evaluated by nested cross-validation (area under the curve [AUC]) and externally validated in 329 treatment-naïve IBD patients from the population-based IBSEN III cohort. Time to the composite outcome was analysed by estimating hazard rations (HR) using Cox regression.

Results: Thirteen proteins (CCL19, XPNPEP2, TGFα, VGFA, DLL1, PSGL1, OSM, CSF1, FURIN, IL-18, EpCAM, and TNFRSF9) met the pre-defined criteria and formed the final prognostic signature. In the discovery cohort, the model achieved an AUC of 0.76, with no interaction with age, sex or IBD subtype. External validation in the IBSEN III cohort yielded an AUC of 0.66 (95%CI 0.57-0.75), sensitivity 49% and specificity 70% at the discovery cohort derived optimal cut-off. Among patients classified as high risk, compared to low risk, the HR for the composite endpoint of aggressive disease course was 1.81 (P = 0.0002, Figure 1).

Conclusion: We developed and validated the first PEA-based serum panel enabling absolute quantitation of prognostic proteins for clinical use. At diagnosis, IBD-patients classified as high risk based on the 13-protein signature had an 81% higher relative risk of an aggressive disease course, supporting further evaluation.

BACKGROUND: 16S rRNA gene sequencing is widely used for bacterial community profiling in both clinical and research contexts. The expanding availability of library preparation protocols and bioinformatic pipelines increases analytical flexibility but may also introduce method-dependent biases that affect inferred microbial composition and relative abundance estimates. The relative impact of library preparation protocol, amplicon region, and bioinformatic pipeline on species-level taxonomic inference and compositional agreement remains insufficiently characterised. We therefore compared the Illumina 16S Metagenomic Sequencing Library Preparation protocol (V3-V4) and the Zymo Quick-16S Plus NGS Library Prep Kit (V1-V2 and V3-V4) in combination with two bioinformatic pipelines, nf-core/ampliseq and TRANA. Performance was assessed using defined microbial community standards and human faecal and colonic biopsy samples.

RESULTS: Pipeline choice was the dominant driver of variation in inferred community composition, exceeding the effects of amplicon regions and library preparation protocols. Genus-level profiles were broadly concordant across methods. Species-level resolution and agreement with expected community composition differed systematically between pipelines, with TRANA demonstrating lower Bray-Curtis dissimilarities to expected compositions than nf-core/ampliseq. Amplicon region had a secondary, pipeline-dependent effect, while protocol differences were minor. In clinical samples, inter-individual biological variation exceeded technical variation.

CONCLUSIONS: Bioinformatic processing substantially influenced species-level inference in short-read 16S sequencing, highlighting the importance of pipeline selection for microbiome study design and cross-study comparability.

Background: Limited statistical power has hampered previous estimates of concordance between relatives and heritability in inflammatory bowel diseases (IBD). To examine the genetic component of Crohn’s disease and ulcerative colitis, we established the largest nationwide IBD twin cohort to date and assessed estimates of concordance and heritability.

Methods: We used the Swedish Twin Registry to identify all twins from complete pairs with known zygosity born between 1886 and 2004. The Swedish National Patient Register was used to identify all patients diagnosed with IBD. We calculated proband concordance rates and fitted a model estimating explained variance in diseases due to genetics (i.e., the heritability), environment shared between twins, and environment unique to each twin.

Results: A cohort of 111,080 twins was followed until a median age of 62.2 years, during which 964 individuals were diagnosed with IBD (Table 1). The proband concordance rate for Crohn’s disease was 0.30 in monozygotic pairs and 0.02 in dizygotic pairs (Table 2). The corresponding rates for ulcerative colitis were 0.15 and 0.03. After adjusting for sex and birth year, heritability was estimated to be 0.78 (95% CI: 0.68–0.87) for Crohn’s disease and 0.57 (95% CI: 0.46–0.69) for ulcerative colitis.

Conclusion: In this large population-based twin study, the heritability of Crohn’s disease was 0.78 and 0.57 for ulcerative colitis. These findings highlight the disparity between heritability estimates from twin studies and those inferred from genome-wide association studies, underscoring the need for continued exploration of the genetic basis of IBD.

High-throughput sequencing has transformed clinical diagnostics of rare diseases (RD), cancer and infectious diseases by enabling the identification of disease-causing genetic alterations and facilitating individualised treatment and care. In response to these advances, Genomic Medicine Sweden (GMS) was established in 2017 as a national collaborative effort to accelerate implementation of genomics-based precision medicine within Sweden's regionally organized, publicly funded healthcare system. GMS brings together the seven university healthcare regions and their associated medical faculties, in collaboration with healthcare regions across Sweden, Science for Life Laboratory, patient organizations, industry and governmental agencies. Activities are coordinated through national disease-specific expert groups, supported by cross-cutting functions in bioinformatics, health economics, ethics, education and patient engagement. At the operational level, seven Genomic Medicine Centres, embedded at university hospitals, develop and deliver harmonised genomic diagnostics nationwide. The National Genomics Platform provides secure infrastructure for large-scale data storage, analysis, and national and international data sharing. Following initial project-based funding, GMS now receives long-term governmental support. This review describes the national implementation of genomic-based precision diagnostics, discusses challenges and lessons learnt, and highlights key milestones across disease areas, including whole-genome sequencing in RD and paediatric cancer, comprehensive genomic profiling of haematological malignancies and solid tumours, pathogen genomics in microbiology, pharmacogenomic testing and emerging applications of polygenic risk scores in complex diseases. Collectively, these efforts have contributed to more than 500,000 genomic tests being performed within Swedish healthcare between 2017 and 2025. Finally, we outline future diagnostic needs and priority areas to ensure sustainable, scalable and equitable access to precision medicine.

BACKGROUND AND AIMS: Limited statistical power has hampered previous estimates of concordance between relatives and heritability in inflammatory bowel diseases (IBD). To examine the genetic component of Crohn's disease and ulcerative colitis, we established the largest nationwide IBD twin cohort to date and assessed estimates of concordance and heritability.

METHODS: We used the Swedish Twin Registry to identify all twins from complete pairs with known zygosity born between 1886 and 2004. The Swedish National Patient Register was used to identify all patients diagnosed with IBD. We calculated proband concordance rates and fitted a model estimating explained variance in diseases due to genetics (ie, the heritability), environment shared between twins, and environment unique to each twin.

RESULTS: A cohort of 111 080 twins was followed until a median age of 62.2 years, during which 964 individuals were diagnosed with IBD. The proband concordance rate for Crohn's disease was 0.30 in monozygotic pairs and 0.02 in dizygotic pairs. The corresponding rates for ulcerative colitis were 0.15 and 0.03. After adjusting for sex and birth year, heritability was estimated to be 0.78 (95% CI: 0.68-0.87) for Crohn's disease and 0.57 (95% CI: 0.46-0.69) for ulcerative colitis.

CONCLUSION: In this large population-based twin study, the heritability of Crohn's disease was 0.78 and 0.57 for ulcerative colitis. These findings highlight the disparity between heritability estimates from twin studies and those inferred from genome-wide association studies, underscoring the need for continued exploration of the genetic basis of IBD.

Background: Minimally invasive biomarkers that can reliably distinguish adults with inflammatory bowel disease (IBD) from symptomatic controls are still lacking. We investigated whether serum lipidomics can provide a reproducible diagnostic signature for IBD and how such a signature performs in relation to relevant inflammatory markers.

Methods: Untargeted lipidomic profiling was conducted on serum from the Swedish SIC-IBD inception cohort, comprising adults referred for suspected IBD, symptomatic controls, as well as healthy controls. Candidate diagnostic lipids were identified using supervised machine-learning models in the discovery cohort and then evaluated in the independent, population-based Norwegian IBSEN III inception cohort of treatment-naïve adults. We examined the diagnostic performance of the lipidomic signature in combination with high-sensitivity C-reactive protein (hs-CRP) and fecal calprotectin (FCP).

Results: The discovery cohort included 96 IBD patients, 66 non-IBD symptomatic controls, and 48 healthy controls, whereas the validation cohort comprised 349 patients with IBD and 198 symptomatic controls (Table 1). In the discovery cohort, a serum signature of hs-CRP and the two top lipids, lactosyl ceramide (d18:1/16:0) and phosphatidylcholine (O-44:5), demonstrated a high diagnostic performance (area under the curve [AUC] 0.80, 95% CI 0.73-0.87) compared with hs-CRP alone (AUC 0.70, 95% CI 0.63-0.79). When applied to the validation cohort, hs-CRP combined with the serum lipid signature significantly enhanced discrimination between IBD and symptomatic controls (AUC 0.79, 95% CI 0.75-0.83) compared with hs-CRP alone (AUC 0.68, 95% CI 0.64-0.73; P < 0.0001). As illustrated in Figure 1, among patients with available stool samples, combining FCP with hs-CRP and the lipid signature numerically improved diagnostic accuracy (AUC 0.89, 95% CI 0.86-0.92) compared with FCP alone (AUC 0.86, 95% CI 0.83–0.90).

Conclusion: We identified and externally validated a serum lipidomic signature that improves the diagnostic prediction of IBD when combined with hs-CRP. Although the blood-based model of hs-CRP, lactosyl ceramide (d18:1/16:0), and phosphatidylcholine (O-44:5) did not outperform FCP alone, it approached its diagnostic performance and further enhanced accuracy when integrated with FCP. These findings support added value these lipids and may offer insights into lipid-related pathways underlying IBD pathogenesis.

Background: IgG autoantibodies against integrin αvβ6 have been associated with preclinical ulcerative colitis (UC),1,2 but data on their emergence and validation are still scarce. Therefore, we aimed to establish and validate a cutoff of anti-αvβ6 for predicting future UC across two independent preclinical cohorts. Additionally, we examined their development in early-life, assessed the influence of genetic-, environmental risk factors and inflammation on anti-αvβ6.

Methods: Within large population-based cohorts (n > 180,000), prediagnostic blood samples from individuals who later in life were diagnosed with UC were compared with age- and sex-matched controls who remained UC-free during follow-up (Figure 1). To explore early-life presence and genetic and shared environmental influences, we analysed serum from ABIS, a population-based birth cohort (n = 17,055) and the Swedish Twin Registry (n > 97,000). Anti-αvβ6 levels were measured using an in-house automated fluorescence enzyme immunoassay. Relative estimates of proteins were measured on the Olink platform3.

Results: In the discovery cohort (Table 1), anti-αvβ6 antibodies differentiated preclinical UC from controls (area under the curve [AUC]=0.68). Applying the model to the validation cohort yielded an AUC of 0.79, with a sensitivity of 46% and a specificity of 93%, at the optimal cut-off (109 UA/l) derived from the discovery cohort. Predictive capacity increased closer to diagnosis but remained significant for samples collected ≥20 years before UC diagnosis (AUC=0.67). In the birth cohort, anti-αvβ6 levels at birth appeared elevated in children who later developed UC (OR = 2.13; 95%CI, 0.84-5.38), likely reflecting transplacental antibody transfer, but also after 5 years (OR = 2.58; 95%CI, 0.83-8.03) and 8 years (OR = 2.50; 95%CI, 0.30-21.00). When assessing the level of agreement within twin pairs, low intra-class correlation coefficients were observed irrespective of zygosity and disease status, suggesting limited influence of genetic and shared environmental exposures. However, anti-αvβ6 levels differed across smoking categories in the preclinical cohorts, but inclusion of smoking status added little to model performance (AUC=0.82). By calculating a composite proteomic score, a progressive increase in the score was observed from the lowest to highest quartile of αvβ6 levels in preclinical UC, whereas most controls were found in the lowest quartiles for both the proteomic score and autoantibody levels.

Conclusion: Anti-αvβ6 autoantibodies represent a reproducible biomarker for preclinical UC. Their early-life presence, environmental modulation, and correlation with immuno-inflammatory proteins highlight their potential utility for risk stratification.

BACKGROUND AND AIMS: The diagnostic and prognostic properties of anti-integrin αvβ6 IgG autoantibodies in ulcerative colitis (UC) are poorly understood. We aimed to assess the diagnostic performance of anti-integrin αvβ6 autoantibodies and examine their association with disease outcomes.

METHODS: Serum samples from a Swedish inception cohort of patients with suspected inflammatory bowel disease (IBD, n=473) were analysed using an in-house fluorescence enzyme immunoassay based on EliA™technology. Findings were validated in a Norwegian population-based inception cohort (n=570). Diagnostic performance was assessed by calculating the area under the curve (AUC) with 95% confidence intervals (CIs) and determining sensitivity and specificity. Reclassification was evaluated using the net reclassification index.

RESULTS: In the discovery cohort, patients with UC, IBD-unclassified, or colonic Crohn's disease exhibited higher median autoantibody levels compared to symptomatic and healthy controls. In the validation cohort, the autoantibody demonstrated 79% sensitivity and 94% specificity for UC vs symptomatic controls at a cut-off of 400 UA/l. Its diagnostic performance (AUC=0.92, 95%CI 0.89-0.95) was superior to hs-CRP (AUC=0.65, 95%CI 0.60-0.70, P<0.001) and faecal calprotectin (fcalpro) (AUC=0.88, 95%CI 0.84-0.92, P=0.09). Combining the autoantibody with fcalpro further improved diagnostic accuracy (AUC=0.97, 95%CI 0.95-0.98) and patient reclassification (P<0.001). Autoantibody positivity was associated with a severe phenotype of UC, characterised by increased inflammatory activity and higher IL-17A and granzyme B levels. Higher autoantibody levels were linked to an aggressive disease course, remaining stable in aggressive UC but decreasing in indolent disease (P=0.003).

CONCLUSIONS: Anti-integrin αvβ6 is a reliable diagnostic and prognostic marker for UC, with potential clinical implementation.