The Lectin Pathway of Complement Activation Is a Critical Component of the Innate Immune Response to Pneumococcal Infection

The complement system plays a key role in host defense against pneumococcal infection. Three different pathways, the classical, alternative and lectin pathways, mediate complement activation. While there is limited information available on the roles of the classical and the alternative activation pathways of complement in fighting streptococcal infection, little is known about the role of the lectin pathway, mainly due to the lack of appropriate experimental models of lectin pathway deficiency. We have recently established a mouse strain deficient of the lectin pathway effector enzyme mannan-binding lectin associated serine protease-2 (MASP-2) and shown that this mouse strain is unable to form the lectin pathway specific C3 and C5 convertases. Here we report that MASP-2 deficient mice (which can still activate complement via the classical pathway and the alternative pathway) are highly susceptible to pneumococcal infection and fail to opsonize Streptococcus pneumoniae in the none-immune host. This defect in complement opsonisation severely compromises pathogen clearance in the lectin pathway deficient host. Using sera from mice and humans with defined complement deficiencies, we demonstrate that mouse ficolin A, human L-ficolin, and collectin 11 in both species, but not mannan-binding lectin (MBL), are the pattern recognition molecules that drive lectin pathway activation on the surface of S. pneumoniae. We further show that pneumococcal opsonisation via the lectin pathway can proceed in the absence of C4. This study corroborates the essential function of MASP-2 in the lectin pathway and highlights the importance of MBL-independent lectin pathway activation in the host defense against pneumococci

Lack of association between PCK1 polymorphisms and obesity, physical activity, and fitness in European Youth Heart Study (EYHS)

Phosphoenolpyruvate carboxykinase-1 (PCK1) is the rate-limiting enzyme in the hepatic gluconeogenic pathway. Studies have shown that overexpression of Pck1 in mice results in obesity-related traits and higher levels of physical activity (PA). Therefore, our aims were to investigate whether common genetic variation in the PCK1 gene influences obesity-related traits, PA, and fitness, and to examine whether PA and fitness attenuate the influence of the PCK1 polymorphisms on obesity in children. Analyses were undertaken on data from Danish and Estonian children (958 boys and 1,104 girls) from the European Youth Heart Study (EYHS), a school-based, cross-sectional study of children (mean ± s.d. age: 9.6 ± 0.4 years) and adolescents (15.5 ± 0.5 years). We genotyped eight polymorphisms that captured the common genetic variations in the PCK1 gene. The association between the PCK1 polymorphisms and BMI, waist circumference (WC), sum of four skinfolds, PA, and fitness was tested using an additive model adjusted for age, age-group, gender, maturity, and country. Interactions were tested by including interaction terms in the model. None of the polymorphisms were significantly associated with BMI, WC, sum of four skinfolds, PA, and fitness, and also with the risk of being overweight or obese (P > 0.05). The interactions between the polymorphisms and age-group, gender, PA, and fitness were not statistically significant. This is the first study to comprehensively examine the association of PCK1 polymorphisms with obesity, PA, and fitness. Despite strong evidence from animal studies, our study in the EYHS cohort failed to identify an association of PCK1 polymorphisms with obesity, PA, and fitness

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes : an IMI-DIRECT study

Background The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. Conclusions Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.Peer reviewe

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities. [Abstract copyright: © 2023. The Author(s).

Gene × Physical Activity Interactions in Obesity: Combined Analysis of 111,421 Individuals of European Ancestry

Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal

Practical consensus guidelines for the management of enuresis

Despite the high prevalence of enuresis, the professional training of doctors in the evaluation and management of this condition is often minimal and/or inconsistent. Therefore, patient care is neither optimal nor efficient, which can have a profound impact on affected children and their families. Once comprehensive history taking and evaluation has eliminated daytime symptoms or comorbidities, monosymptomatic enuresis can be managed efficaciously in the majority of patients. Non-monosymptomatic enuresis is often a more complex condition; these patients may benefit from referral to specialty care centers. We outline two alternative strategies to determine the most appropriate course of care. The first is a basic assessment covering only the essential components of diagnostic investigation which can be carried out in one office visit. The second strategy includes several additional evaluations including completion of a voiding diary, which requires extra time during the initial consultation and two office visits before treatment or specialty referral is provided. This should yield greater success than first-line treatment. Conclusion: This guideline, endorsed by major international pediatric urology and nephrology societies, aims to equip a general pediatric practice in both primary and secondary care with simple yet comprehensive guidelines and practical tools (i.e., checklists, diary templates, and quick-reference flowcharts) for complete evaluation and successful treatment of enuresis

COLEC10 is mutated in 3MC patients and regulates early craniofacial development

3MC syndrome is an autosomal recessive heterogeneous disorder with features linked to developmental abnormalities. The main features include facial dysmorphism, craniosynostosis and cleft lip/palate; skeletal structures derived from cranial neural crest cells (cNCC). We previously reported that lectin complement pathway genes COLEC11 and MASP1/3 are mutated in 3MC syndrome patients. Here we define a new gene, COLEC10, also mutated in 3MC families and present novel mutations in COLEC11 and MASP1/3 genes in a further five families. The protein products of COLEC11 and COLEC10, CL-K1 and CL-L1 respectively, form heteromeric complexes. We show COLEC10 is expressed in the base membrane of the palate during murine embryo development. We demonstrate how mutations in COLEC10 (c.25C>T; p.Arg9Ter, c.226delA; p.Gly77Glufs*66 and c.528C>G p.Cys176Trp) impair the expression and/or secretion of CL-L1 highlighting their pathogenicity. Together, these findings provide further evidence linking the lectin complement pathway and complement factors COLEC11 and COLEC10 to morphogenesis of craniofacial structures and 3MC etiology.New life Fundation for Disabled Childre

No interactions between previously associated 2-hour glucose gene variants and physical activity or BMI on 2-hour glucose levels.

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions