Predominantly antibody deficiency and the association with celiac disease in Sweden: A nationwide case-control study.

BACKGROUND: Predominantly antibody deficiency (PAD) is associated with noninfectious inflammatory gastrointestinal disease. Population estimates of celiac disease (CeD) risk in those with PAD are limited. OBJECTIVE: To estimate population risk of PAD in individuals with CeD. METHODS: We conducted a nationwide case-control study in Swedish individuals who received a diagnosis of CeD between 1997 and 2017 (n = 34,980), matched to population comparators by age, sex, calendar year, and county. The CeD was confirmed through the Epidemiology Strengthened by histopathology Reports in Sweden study, which provided information on biopsy specimens from each of Sweden's pathology departments. PAD was identified using International Classification of Diseases, 10th Revision coding and categorized according to the International Union of Immunologic Societies. Logistic regression was used to calculate adjusted odds ratios (aORs) and 95% CIs. RESULTS: PAD was more prevalent in CeD than in population controls (n = 105 [0.3%] vs n = 57 [0.033%], respectively). This translated to an aOR of 8.23 (95% CI 5.95-11.48). The association was strongest with common variable immunodeficiency (aOR 17.25; 95% CI 6.86-52.40), and slightly lower in other PAD (aOR 8.39; 95% CI 5.79-12.32). The risk of CeD remained increased at least 5 years after diagnosis of PAD (aOR 4.79; 95% CI 2.89-7.97, P-heterogeneity ≤ 0.001). CONCLUSION: PAD was associated with an increased risk of CeD. A particularly strong association was seen in those with CVID, although this should be interpreted cautiously given the limited understanding of the mechanisms of histopathologic changes in these patients.

Towards Improved XAI-Based Epidemiological Research into the Next Potential Pandemic.

By applying AI techniques to a variety of pandemic-relevant data, artificial intelligence (AI) has substantially supported the control of the spread of the SARS-CoV-2 virus. Along with this, epidemiological machine learning studies of SARS-CoV-2 have been frequently published. While these models can be perceived as precise and policy-relevant to guide governments towards optimal containment policies, their black box nature can hamper building trust and relying confidently on the prescriptions proposed. This paper focuses on interpretable AI-based epidemiological models in the context of the recent SARS-CoV-2 pandemic. We systematically review existing studies, which jointly incorporate AI, SARS-CoV-2 epidemiology, and explainable AI approaches (XAI). First, we propose a conceptual framework by synthesizing the main methodological features of the existing AI pipelines of SARS-CoV-2. Upon the proposed conceptual framework and by analyzing the selected epidemiological studies, we reflect on current research gaps in epidemiological AI toolboxes and how to fill these gaps to generate enhanced policy support in the next potential pandemic.

Avoidant/restrictive food intake disorder symptoms are not as frequent as other eating disorder symptoms when ulcerative colitis is in remission.

BACKGROUND AND AIM: Recent studies have shown that up to 53% of patients with inflammatory bowel disease (IBD) screen positive for avoidant/restrictive food intake disorder (ARFID). There is however concern that ARFID screening rates are over-inflated in patients with active disease. We aimed to evaluate the frequency and characteristics of ARFID symptoms using the Nine Item ARFID Screen (NIAS), and to use another eating disorder measure, the Eating Disorder Examination-Questionnaire 8 (EDE-Q8), to rule-out/characterize other eating disorder cognitive and behavioral symptoms. METHODS: Participants included adults with UC who are enrolled in an in an ongoing cohort study with quiescent UC (SCCAI ≤2 or fecal calprotectin <150 µg/g with corticosteroid-free clinical remission for ≥ 3 months) at baseline. We used self-reported data on demographics, gastrointestinal medications, medical comorbidities, NIAS scores, and other eating disorder symptom scores (8-item Eating Disorder Examination-Questionnaire; EDE-Q-8). RESULTS: We included 101 participants who completed the NIAS at their baseline cohort assessment (age 49.9±16.5 years; 55% female). Eleven participants (11%) screened positively for ARFID on at least one NIAS subscale (n=8 male). Up to thirty participants (30%) screened positive for other eating disorder symptoms (EDE-Q-8 Global ≥2.3). Overall score distributions on the EDE-Q-8 showed that participants scored highest on the Weight Concern and Shape Concern subscales. CONCLUSIONS: Among adults with UC in remission, we found a low rate of ARFID symptoms by the NIAS but a high rate of positive screens for other eating disorder symptoms.

A natural language processing algorithm accurately classifies steatotic liver disease pathology to estimate the risk of cirrhosis.

BACKGROUND: Histopathology remains the gold standard for diagnosing and staging metabolic dysfunction-associated steatotic liver disease (MASLD). The feasibility of studying MASLD progression in electronic medical records based on histological features is limited by the free-text nature of pathology reports. Here we introduce a natural language processing (NLP) algorithm to automatically score MASLD histology features. METHODS: From the Mass General Brigham health care system electronic medical record, we identified all patients (1987-2021) with steatosis on index liver biopsy after excluding excess alcohol use and other etiologies of liver disease. An NLP algorithm was constructed in Python to detect steatosis, lobular inflammation, ballooning, and fibrosis stage from pathology free-text and manually validated in >1200 pathology reports. Patients were followed from the index biopsy to incident decompensated liver disease accounting for covariates. RESULTS: The NLP algorithm demonstrated positive and negative predictive values from 93.5% to 100% for all histologic concepts. Among 3134 patients with biopsy-confirmed MASLD followed for 20,604 person-years, rates of the composite endpoint increased monotonically with worsening index fibrosis stage (p for linear trend <0.005). Compared to simple steatosis (incidence rate, 15.06/1000 person-years), the multivariable-adjusted HRs for cirrhosis were 1.04 (0.72-1.5) for metabolic dysfunction-associated steatohepatitis (MASH)/F0, 1.19 (0.92-1.54) for MASH/F1, 1.89 (1.41-2.52) for MASH/F2, and 4.21 (3.26-5.43) for MASH/F3. CONCLUSIONS: The NLP algorithm accurately scores histological features of MASLD from pathology free-text. This algorithm enabled the construction of a large and high-quality MASLD cohort across a multihospital health care system and disclosed an accelerating risk for cirrhosis based on the index MASLD fibrosis stage.

Single-cell transcriptomic analyses reveal distinct immune cell contributions to epithelial barrier dysfunction in checkpoint inhibitor colitis.

Immune checkpoint inhibitor (ICI) therapy has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). Little is understood about the pathogenic mechanisms driving irColitis, which does not readily occur in model organisms, such as mice. To define molecular drivers of irColitis, we used single-cell multi-omics to profile approximately 300,000 cells from the colon mucosa and blood of 13 patients with cancer who developed irColitis (nine on anti-PD-1 or anti-CTLA-4 monotherapy and four on dual ICI therapy; most patients had skin or lung cancer), eight controls on ICI therapy and eight healthy controls. Patients with irColitis showed expanded mucosal Tregs, ITGAEHi CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs and recirculating ITGB2Hi CD8 T cells. Cytotoxic GNLYHi CD4 T cells, recirculating ITGB2Hi CD8 T cells and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 therapy compared to anti-PD-1 therapy. Luminal epithelial cells in patients with irColitis expressed PCSK9, PD-L1 and interferon-induced signatures associated with apoptosis, increased cell turnover and malabsorption. Together, these data suggest roles for circulating T cells and epithelial-immune crosstalk critical to PD-1/CTLA-4-dependent tolerance and barrier function and identify potential therapeutic targets for irColitis.