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GAD-alum given into lymph nodes to Type 1 diabetes (T1D) patients participating in a multicenter, randomized, placebo-controlled double-blind study seemed to have a positive effect for patients with DR3DQ2 haplotype, who showed better preservation of C-peptide than the placebo group. Here we compared the immunomodulatory effect of GAD-alum administered into lymph nodes of patients with T1D versus placebo with focus on patients with DR3DQ2 haplotype. MethodsGAD autoantibodies, GADA subclasses, GAD(65)-induced cytokine secretion (Luminex panel) and proliferation of peripheral mononuclear cells were analyzed in T1D patients (n=109) who received either three intra-lymphatic injections (one month apart) with 4 mu g GAD-alum and oral vitamin D supplementation (2000 IE daily for 120 days), or placebo. ResultsHigher GADA, GADA subclasses, GAD(65)-induced proliferation and cytokine secretion was observed in actively treated patients after the second injection of GAD-alum compared to the placebo group. Following the second injection of GAD-alum, actively treated subjects with DR3DQ2 haplotype had higher GAD(65)-induced secretion of several cytokine (IL4, IL5, IL7, IL10, IL13, IFN gamma, GM-CSF and MIP1 beta) and proliferation compared to treated individuals without DR3DQ2. Stratification of samples from GAD-alum treated patients according to C-peptide preservation at 15 months revealed that "good responder" individuals with better preservation of C-peptide secretion, independently of the HLA haplotype, had increased GAD(65)-induced proliferation and IL13 secretion at 3 months, and a 2,5-fold increase of IL5 and IL10 as compared to "poor responders". The second dose of GAD-alum also induced a more pronounced cytokine secretion in "good responders" with DR3DQ2, compared to few "good responders" without DR3DQ2 haplotype. ConclusionPatients with DR3DQ2 haplotype had a distinct early cellular immune response to GAD-alum injections into the lymph node, and predominant GAD(65)-induc

Objectives To identify factors affecting early childhood sleep, and investigate the relationship between sleep and overweight/obesity in childhood. Study Design Data were collected using parental-completed questionnaires from N = 10.840 one-year-old children in the prospective ABIS-study (All Babies in Southeast Sweden), followed up until 8 years of age. Chi-squared test and Pearson Correlation were used to assess the relationship between covariates affecting the childrens sleep. Subsequently, longitudinal mixed model analyses were used to predict the effect of different sleep dimensions (bedtime, sleep duration, sleep quality, and the number of awakenings) on BMI Z-scores. Results Children to parents born in Sweden, parents with higher education, non-single parents, non-smoking mothers during pregnancy, and children with fewer siblings, were more likely to have appropriate sleep habits at 1 year age. A greater number of awakenings and nocturnal feeds, and particularly later bedtime (beta = -0.544, p < 0.0001) were linked to shorter sleep duration. Sleep duration early in life was negatively associated with BMI Z-scores (adjusted effect estimate [95% CI]: beta = -0.09, [(-0.15) - (-0.03)], p = 0.005) later. In addition, higher birth weight, small size for gestational age, unhealthy food habits, children of mothers who smoked during pregnancy, and higher parental BMI resulted in higher BMI Z-scores. Conclusion The childs BMI Z-score increases by 0.09 units with every hour shorter sleep duration, indicating that short sleep duration might increase the risk of overweight and obesity in children. Parental educational interventions advising appropriate sleeping patterns should be considered when implementing strategies to combat the development of childhood obesity., Funding Agencies|ALF Region Ostergotland [0000]; Barndiabetesfonden (The Swedish Child Diabetes Foundation); Swedish Council for Working Life and Social Research [FAS2004-1775]; Medical Research Council of Southeast Sweden; JDRF Wallenberg Foundation [K98-99D-12813-01A]; Swedish Research Council [K2008-69X-20826-01-4, K2005-72X-11242-11A]

IntroductionIn several of the Low and Middle Income countries , many patients with Type 1 diabetes (T1D) are most probably not diagnosed at all which may contribute to their low incidence. As an example of a country with low income and poor resources, we have chosen to study T1D in children/young people in Tanzania. MethodsAnalyses of casebooks and statistics at several Tanzanian hospitals treating young patients with insulin dependent diabetes, usually Type 1 diabetes, and collection of information from different organisations such a Tanzanian Diabetes Association, Life for a Child, Changing Diabetes in Children and World Diabetes Foundation. ResultsThe incidence in several areas is low. However, a lot of data are often missing at studied clinics and therefore the incidence might be higher, and with increased awareness in recent years the number of patients has increased many-folds. Most patients present with typical symptoms and signs of T1D, and a high proportion with plausible ketoacidosis , although this proportion has decreased from about 90% to about 40% in recent decades. Many patients have poor blood glucose control, and complications often develop already after short diabetes duration. In recent years resources have increased, awareness has increased and diabetes clinics started where staff has got training. ConclusionsThere are problems with diabetes care in Tanzania but several facts give hope for the future.

Aims: Between 1985 and 1996, Sweden experienced an "epidemic" of celiac disease with a fourfold increase in incidence in young children. Timing and amount of gluten introduced during infancy have been thought to explain this "epidemic". We aimed to study whether the cumulative incidence of type 1 diabetes differs between children born during the "epidemic" compared to children born after. Methods: This is a national register study in Sweden comparing the cumulative incidence of type 1 diabetes in two birth cohorts of 240 844 children 0-17 years old born 1992-1993, during the "epidemic", and 179 530 children born 1997-1998, after the "epidemic". Children diagnosed with type 1 diabetes were identified using three national registers. Results: The cumulative incidence of type 1 diabetes by the age of 17 was statistically significantly higher in those born after the "epidemic" 0.77% than in those born during the "epidemic" 0.68% (p < 0.001). Conclusion: The incidence of type 1 diabetes is higher in those born after the epidemic compared to those born during the epidemic, which does not support the hypothesis that gluten introduction increases the incidence of T1D. Changes in gluten introduction did not halt the increased incidence of type 1 diabetes in Sweden.

During the COVID-19 pandemic, Sweden was among the few countries that did not enforce strict lockdown measures but instead relied more on voluntary and sustainable mitigation recommendations. While supported by the majority of Swedes, this approach faced rapid and continuous criticism. Unfortunately, the respectful debate centered around scientific evidence often gave way to mudslinging. However, the available data on excess all-cause mortality rates indicate that Sweden experienced fewer deaths per population unit during the pandemic (2020–2022) than most high-income countries and was comparable to neighboring Nordic countries through the pandemic. An open, objective scientific dialogue is essential for learning and preparing for future outbreaks.

BackgroundBirth cohort studies with linked register-based data on inflammatory bowel disease (IBD) provide opportunities to prospectively study early-life determinants of the disease. However, register-based data often lack information on clinical characteristics and rely on diagnostic algorithms. Within the All Babies in Southeast Sweden (ABIS) cohort, we examined the validity of a register-based definition of IBD, its incidence, and clinical and therapeutic characteristics at diagnosis.MethodsWe followed 16,223 children from birth (1997-1999) until the end of 2020 for the diagnosis of IBD as defined by a minimum of two diagnostic codes for IBD in the Swedish National Patient Register (NPR). We described the incidence and cumulative incidence of IBD. Through a medical record review of cases diagnosed by the end of 2017, we examined the positive predictive value (PPV) for IBD and described its clinical characteristics and treatment.ResultsBy 2020, at an average age of 22.2 years, 113 participants (0.74%, 95% confidence interval [CI] = 0.61-0.89) had a register-based diagnosis of IBD, corresponding to an incidence of 31.3 per 100,000 person-years of follow-up; the incidence for Crohns disease (CD) was 11.1 per 100,000 person-years and 15.8 for ulcerative colitis (UC). Of 77 participants with a register-based definition of IBD by the end of 2017, medical records were identified for 61 participants, of whom 57 had true IBD (PPV = 93%; 95%CI = 0.87-1.00). While oral 5-aminosalicylic acid treatment was equally common in newly diagnosed CD and UC patients, biologics were more often used for newly diagnosed CD. The median faecal calprotectin levels were 1206 mg/kg at diagnosis and 93 mg/kg at the last follow-up (P < 0.001).ConclusionsIn this population-based sample of Swedish children and young adults the cumulative IBD incidence was 0.74. The validity of register-based definition of IBD was high and supports using such data to identify IBD patients in cohort studie

The objective of this paper was to investigate if socioeconomic status (SES), measured by maternal education and household income, influenced the risk of developing autoimmune disease (Type 1 Diabetes, Celiac disease, Juvenile Idiopathic Arthritis, Crohns disease, Ulcerative colitis, and autoimmune thyroid disease), or age at diagnosis, and to analyse pathways between SES and autoimmune disease. We used data from the All Babies in Southeast Sweden (ABIS) study, a population-based prospective birth cohort, which included children born 1997-1999. Diagnoses of autoimmune disease was collected from the Swedish National Patient Register Dec 2020. In 16,365 individuals, low maternal education, but not household income, was associated with increased risk of Type 1 Diabetes; middle education RR 1.54, 95% CI 1.06, 2.23; P 0.02, low education RR 1.81, 95% CI 1.04, 3.18; P 0.04. Maternal education and household income was not associated with any other autoimmune disease and did not influence the age at diagnosis. Part of the increased risk of Type 1 Diabetes by lower maternal education was mediated by the indirect pathway of higher BMI and higher risk of Serious Life Events (SLE) at 5 years of age. The risk of developing Type 1 Diabetes associated to low maternal education might be reduced by decreasing BMI and SLE during childhood., Funding Agencies|Linkoeping University; County Council of Ostergot-land, Forskningsradet i Sydoestra Sverige, Vetenskapsradet [K2005-72X-11242-11A]; Knut och Alice Wallenbergs Stiftelse [K 98-99D-12813-01A]; Forskningsradet foer Arbetsliv och Socialvetenskap [FAS20041775]; Barndiabetesfonden; Juvenile Diabetes Research Foundation International; Ostgota Brandstodsbolag

OBJECTIVE Type 2 diabetes is an established risk factor for hospitalization and death in COVID-19 infection, while findings with respect to type 1 diabetes have been diverging. RESEARCH DESIGN AND METHODS Using nationwide health registries, we identified all patients aged >= 18 years with type 1 and type 2 diabetes in Sweden. Odds ratios (ORs) describe the general and age-specific risk of being hospitalized, need for intensive care, or dying, adjusted for age, socioeconomic factors, and coexisting conditions, compared with individuals without diabetes. Machine learning models were used to find predictors of outcomes among individuals with diabetes positive for COVID-19. RESULTS Until 30 June 2021, we identified 365 (0.71%) and 11,684 (2.31%) hospitalizations in 51,402 and 504,337 patients with type 1 and 2 diabetes, respectively, with 67 (0.13%) and 2,848 (0.56%) requiring intensive care unit (ICU) care and 68 (0.13%) and 4,020 (0.80%) dying (vs 7,824,181 individuals without diabetes [41,810 hospitalizations (0.53%), 8,753 (0.11%) needing ICU care, and 10,160 (0.13%) deaths). Although those with type 1 diabetes had moderately raised odds of being hospitalized (multiple-adjusted OR 1.38 [95% CI 1.24-1.53]), there was no independent effect on ICU care or death (OR of 1.21 [95% CI 0.94-1.52] and 1.13 [95% CI 0.88-1.48], respectively). Age and socioeconomic factors were the dominating features for predicting hospitalization and death in both types of diabetes. CONCLUSIONS Type 2 diabetes was associated with increased odds for all outcomes, whereas patients with type 1 diabetes had moderately increased odds of hospitalization but not ICU care and death., Funding Agencies|Swedish state under an agreement concerning research and education of doctors [ALFGBG-966211]; Swedish Heart and Lung Foundation [2021-0345]; Swedish Research Council [2018-02527, 2020-05792, 2021-06525]

Combining and comparing microbiome data from distinct infant cohorts has been challenging because such data are inherently multidimensional and complex. Here, we used an ensemble of machine-learning (ML) models and studied 16S rRNA amplicon sequencing data from 4,099 gut microbiome samples representing 12 prospectively collected infant cohorts. We chose the childbirth delivery mode as a starting point for such analysis because it has previously been associated with alterations in the gut microbiome in infants. In cross-study ensemble models, Bacteroides was the most important feature in all machine-learning models. The predictive capacity by taxonomy varied with age. At the age of 1-2 months, gut microbiome data were able to predict delivery mode with an area under the curve of 0.72 to 0.83. In contrast, ML models trained on taxa were not able to differentiate between the modes of delivery, in any of the cohorts, when the infants were between 3 and 12 months of age. Moreover, no ML model, alternately trained on the functional pathways of the infant gut microbiome, could consistently predict mode of delivery at any infant age. This study shows that infant gut microbiome data sets can be effectively combined with the application of ML analysis across different study populations. IMPORTANCE There are challenges in merging microbiome data from diverse research groups due to the intricate and multifaceted nature of such data. To address this, we utilized a combination of machine-learning (ML) models to analyze 16S sequencing data from a substantial set of gut microbiome samples, sourced from 12 distinct infant cohorts that were gathered prospectively. Our initial focus was on the mode of delivery due to its prior association with changes in infant gut microbiomes. Through ML analysis, we demonstrated the effective merging and comparison of various gut microbiome data sets, facilitating the identification of robust microbiome biomarkers applicable across vari

Combining and comparing microbiome data from distinct infant cohorts has been challenging because such data are inherently multidimensional and complex. Here, we used an ensemble of machine-learning (ML) models and studied 16S rRNA amplicon sequencing data from 4,099 gut microbiome samples representing 12 prospectively collected infant cohorts. We chose the childbirth delivery mode as a starting point for such analysis because it has previously been associated with alterations in the gut microbiome in infants. In cross-study ensemble models, Bacteroides was the most important feature in all machine-learning models. The predictive capacity by taxonomy varied with age. At the age of 1-2 months, gut microbiome data were able to predict delivery mode with an area under the curve of 0.72 to 0.83. In contrast, ML models trained on taxa were not able to differentiate between the modes of delivery, in any of the cohorts, when the infants were between 3 and 12 months of age. Moreover, no ML model, alternately trained on the functional pathways of the infant gut microbiome, could consistently predict mode of delivery at any infant age. This study shows that infant gut microbiome data sets can be effectively combined with the application of ML analysis across different study populations.IMPORTANCEThere are challenges in merging microbiome data from diverse research groups due to the intricate and multifaceted nature of such data. To address this, we utilized a combination of machine-learning (ML) models to analyze 16S sequencing data from a substantial set of gut microbiome samples, sourced from 12 distinct infant cohorts that were gathered prospectively. Our initial focus was on the mode of delivery due to its prior association with changes in infant gut microbiomes. Through ML analysis, we demonstrated the effective merging and comparison of various gut microbiome data sets, facilitating the identification of robust microbiome biomarkers applicable across varied study popula, Funding Agencies|All authors declare no conflict of interest relevant to this article.

Background We aimed to investigate whether early-life hygiene-related factors influenced the risk of inflammatory bowel disease (IBD) in a Scandinavian population and test the associations consistency across cohorts.Methods This study followed 117 493 participants in the All Babies in Southeast Sweden study and the Norwegian Mother, Father, and Child Cohort Study. IBD diagnoses were defined by national registers. Comprehensive data on hygiene-related exposures, such as having pets, rural living, daycare attendance, and siblings, were retrieved from questionnaires administered from pregnancy until childs age of 36 months. A multivariable Cox regression model yielded adjusted hazard ratios (aHRs) for IBD accounting for socioeconomic status and perinatal factors. Cohort-specific estimates were pooled using a random-effects model.Results In over 2 024 299 person-years of follow-up 451 participants developed IBD. In pooled estimates children attending daycare up to 36 months of life vs not attending daycare were less likely to develop Crohns disease (aHR, 0.60; 95% confidence interval [CI], 0.37- 0.98). Children having 1 or more siblings had a modestly increased risk of IBD (aHR, 1.17; 95% CI, 0.96-1.42; aHR for each sibling, 1.12; 95% CI, 1.01-1.24). The other hygiene factors were not significantly linked to later IBD. In the Norwegian Mother, Father, and Child Cohort Study cohort, bed sharing was associated with an increased risk of IBD, most notably for ulcerative colitis (aHR, 1.67; 95% CI, 1.01-2.78).Conclusions In this birth cohort study from 2 high-income Scandinavian countries, some early-life hygiene-related exposures were associated with IBD risk. The generalizability of these results to countries of other socioeconomic level is unknown. Exposure to some hygiene factors during early childhood seems to be associated with the risk of later inflammatory bowel disease. The direction and magnitude of the associations need to be further studied before any clinical im, Funding Agencies|The authors are grateful to all the families in Sweden and Norway who participated in these ongoing cohort studies. In addition, they acknowledge Leslie Shaps, PhD, at Proofreading, Editing amp; Translation Global Services for language editing.