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While microRNAs (miRs) like miR-9 are crucial for neurogenesis and neuronal differentiation, their regulatory mechanisms are not well understood. miR-9 is highly expressed in the brain and plays a significant role in neurogenesis. Using the Collaborative Cross resource, we identified significant quantitative trait loci (QTL) through genetic analyses. We then characterized over 130 candidate genes within these QTL regions using RNA interference, qPCR, and neuronal differentiation assays, narrowing them down to 13 promising candidates. Among these, Panx2, Polr1c, and Mgea5 were found to colocalize in the neurogenic niches of the SVZ and DG regions, as shown by immunofluorescence. Further ChIP-seq and Co-IP analyses revealed their interaction and binding to the miR-9 locus, forming a DNA-protein regulatory complex we termed 'miRSome-9.' A 3C/ChIP-loop assay confirmed the chromatin organization of miRSome-9 at the miR-9 locus, shedding light on the upstream mechanisms regulating miR-9 expression during neurogenesis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

The humoral response is complex and involves multiple cellular populations and signaling pathways. Bacterial and viral infections, as well as immunization regimens, can trigger this type of response, promoting the formation of microanatomical cellular structures called germinal centers (GCs). GCs formed in secondary lymphoid organs support the differentiation of high-affinity plasma cells and memory B cells. There is growing evidence that the quality of the humoral response is influenced by genetic variants. Using 12 genetically divergent mouse strains, we assessed the impact of genetics on GC cellular traits. At steady state, in the spleen, lymph nodes and Peyer's patches, we quantified GC B cells, plasma cells and follicular helper T cells. These traits were also quantified in the spleen of mice following immunization with a foreign antigen, namely, sheep red blood cells, in addition to the number and size of GCs. We observed both strain- and organ-specific variations in cell type abundance, as well as for GC number and size. Moreover, we find that some of these traits are highly heritable. Importantly, the results of this study inform on the impact of genetic diversity in shaping the GC response and identify the traits that are the most impacted by genetic background., (© 2024 The Author(s). Immunology & Cell Biology published by John Wiley & Sons Australia, Ltd on behalf of the Australian and New Zealand Society for Immunology, Inc.)

Mesothelioma is a lethal cancer. Despite promising outcomes associated with immunotherapy, durable responses remain restricted to a minority of patients, highlighting the need for improved strategies that better predict outcome. Here, we described the development of a mesothelioma-specific gene signature that accurately predicts survival. Comprehensive gene expression analysis of asbestos exposed MexTAg Collaborative Cross mouse tumors revealed distinct tumor clusters characterized by epithelial mesenchymal transition/extracellular matrix, or immune infiltrate related gene expression profiles. Weighted gene co-expression network analysis (WGCNA) identified 20 hub genes that drove differential gene expression. Human homologues of these 20 hub genes were refined through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to identify a six-gene mesothelioma-specific prognostic signature that accurately predicted patient survival across four independent human mesothelioma datasets. Furthermore, this six-gene signature demonstrated the potential to predict treatment response, thus advancing the management of this challenging malignancy., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

Background: Weight loss can improve the metabolic complications of obesity. However, it is unclear whether insulin resistance persists despite weight loss and whether any protective benefits are preserved following weight regain (weight cycling). The impact of genetic background on weight cycling is undocumented. We aimed to investigate the effects of weight loss and weight cycling on metabolic outcomes and sought to clarify the role of genetics in this relationship., Method: Both C57BL/6 J and genetically heterogeneous Diversity Outbred Australia (DOz) mice were alternately fed high fat Western-style diet (WD) and a chow diet at 8-week intervals. Metabolic measures including body composition, glucose tolerance, pancreatic beta cell activity, liver lipid levels and adipose tissue insulin sensitivity were determined., Results: After diet switch from WD (8-week) to chow (8-week), C57BL/6 J mice displayed a rapid normalisation of body weight, adiposity, hyperinsulinemia, liver lipid levels and glucose uptake into adipose tissue comparable to chow-fed controls. In response to the same dietary intervention, genetically diverse DOz mice conversely maintained significantly higher fat mass and insulin levels compared to chow-fed controls and exhibited much more profound interindividual variability than C57BL/6 J mice. Weight cycled (WC) animals were re-exposed to WD (8-week) and compared to age-matched controls fed 8-week WD for the first time (LOb). In C57BL/6 J but not DOz mice, WC animals had significantly higher blood insulin levels than LOb controls. All WC animals exhibited significantly greater beta cell activity than LOb controls despite similar fat mass, glucose tolerance, liver lipid levels and insulin-stimulated glucose uptake in adipose tissue., Conclusion: Following weight loss, metabolic outcomes return to baseline in C57BL/6 J mice with obesity. However, genetic diversity significantly impacts this response. A period of weight loss does not provide lasting benefits after weight regain, and weight cycling is detrimental and associated with hyperinsulinemia and elevated basal insulin secretion., (© 2024. The Author(s).)

Introduction: The Environmental Determinants of Islet Autoimmunity (ENDIA) Study is an ongoing Australian prospective cohort study investigating how modifiable prenatal and early-life exposures drive the development of islet autoimmunity and type 1 diabetes (T1D) in children. In this profile, we describe the cohort's parental demographics, maternal and neonatal outcomes and human leukocyte antigen (HLA) genotypes., Research Design and Methods: Inclusion criteria were an unborn child, or infant aged less than 6 months, with a first-degree relative (FDR) with T1D. The primary outcome was persistent islet autoimmunity, with children followed until a T1D diagnosis or 10 years of age. Demographic data were collected at enrollment. Lifestyle, clinical and anthropometric data were collected at each visit during pregnancy and clinical pregnancy and birth data were verified against medical case notes. Data were compared between mothers with and without T1D. HLA genotyping was performed on the ENDIA child and all available FDRs., Results: The final cohort comprised 1473 infants born to 1214 gestational mothers across 1453 pregnancies, with 80% enrolled during pregnancy. The distribution of familial T1D probands was 62% maternal, 28% paternal and 11% sibling. The frequency of high-risk HLA genotypes was highest in T1D probands, followed by ENDIA infants, and lowest among unaffected family members. Mothers with T1D had higher rates of pregnancy complications and perinatal intervention, and larger babies of shorter gestation. Parent demographics were comparable to the Australian population for age, parity and obesity. A greater percentage of ENDIA parents were Australian born, lived in a major city and had higher socioeconomic advantage and education., Conclusions: This comprehensive profile provides the context for understanding ENDIA's scope, methodology, unique strengths and limitations. Now fully recruited, ENDIA will provide unique insights into the roles of early-life factors in the development of islet autoimmunity and T1D in the Australian environment., Trial Registration Number: ACTRN12613000794707., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: To identify N-glycan structures on immunoglobulin A related to type 1 diabetes mellitus among children at the disease onset and adults with type 1 diabetes mellitus., Methods: Human polyclonal IgA N-glycans were profiled using hydrophilic interaction ultra performance liquid chromatography in two cohorts. The first cohort consisted of 62 children at the onset of type 1 diabetes mellitus and 86 of their healthy siblings. The second cohort contained 84 adults with the disease and 84 controls. Associations between N-glycans and type 1 diabetes mellitus were tested using linear mixed model for the paediatric cohort, or general linear model for the adult cohort. False discovery rate was controlled by Benjamini-Hochberg method modified by Li and Ji., Results: In children, an increase in a single oligomannose N-glycan was associated with type 1 diabetes mellitus (B = 0.529, p = 0.0067). N-glycome of the adults displayed increased branching (B = 0.466, p = 0.0052), trigalactosylation (B = 0.466, p = 0.0052), trisialylation (B = 0.629, p < 0.001), and mannosylation (B = 0.604, p < 0.001). The strongest association with the disease was a decrease in immunoglobulin A core fucosylation (B = -0.900, p < 0.001)., Conclusions: Changes in immunoglobulin N-glycosylation patterns in type 1 diabetes point to disruptions in immunoglobulin A catabolism and dysregulated inflammatory capabilities of the antibody, potentially impacting immune responses and inflammation., Competing Interests: The authors declare they have no known competing financial interests or personal relationships that could influence the work reported in this research paper., (© 2024 The Authors.)

Context: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Measures to prevent and treat DKD require better identification of patients most at risk. In this systematic review, we summarize the existing evidence of genetic risk scores (GRSs) and their utility for predicting DKD in people with type 1 or type 2 diabetes., Evidence Acquisition: We searched MEDLINE, Embase, Web of Science, and Cochrane Reviews in June 2022 to identify all existing and relevant literature. Main data items sought were study design, sample size, population, single nucleotide polymorphisms of interest, DKD-related outcomes, and relevant summary measures of result. The Critical Appraisal Skills Programme checklist was used to evaluate the methodological quality of studies., Evidence Synthesis: We identified 400 citations of which 15 are included in this review. Overall, 7 studies had positive results, 5 had mixed results, and 3 had negative results. Most studies with the strongest methodological quality (n = 9) reported statistically significant and favourable findings of a GRS's association with at least 1 measure of DKD., Conclusion: This systematic review presents evidence of the utility of GRSs to identify people with diabetes that are at high risk of developing DKD. In practice, a robust GRS could be used at the first clinical encounter with a person living with diabetes in order to stratify their risk of complications. Further prospective research is needed., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society.)

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes ( CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12 ) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Fisher, Patrick, Hoang, Marcq, Behrouzfar, Young, Miller, Robinson, Bueno, Nowak, Lesterhuis, Morahan and Lake.)

This family-based study was conducted in a group of Iranians with Type 1 diabetes (T1D) to investigate the transmission from parents of risk and non-risk HLA alleles and haplotypes, and to estimate the genetic risk score for this disease within this population. A total of 240 T1D subjects including 111 parent-child trios (111 children with T1D, 133 siblings, and 222 parents) and 330 ethnically matched healthy individuals were recruited. High-resolution HLA typing for DRB1/DQB1 loci was performed for all study subjects (n = 925) using polymerase chain reaction-sequence-specific oligonucleotide probe method. The highest predisposing effect on developing T1D was conferred by the following haplotypes both in all subjects and in probands compared to controls: DRB1*04:05-DQB1*03:02 (Pc = 2.97e-06 and Pc = 6.04e-10, respectively), DRB1*04:02-DQB1*03:02 (Pc = 5.94e-17 and Pc = 3.86e-09, respectively), and DRB1*03:01-DQB1*02:01 (Pc = 8.26e-29 and Pc = 6.56e-16, respectively). Conversely, the major protective haplotypes included DRB1*13:01-DQB1*06:03 (Pc = 6.99e-08), DRB1*15:01-DQB1*06:02 (Pc = 2.97e-06) in the cases versus controls. Also, DRB1*03:01-DQB1*02:01/DRB1*04:02|05-DQB1*03:02 and DRB1*03:01-DQB1*02:01/DRB1*03:01-DQB1*02:01 diplotypes conferred the highest predisposing effect in the cases (Pc = 8.65e-17 and Pc = 6.26e-08, respectively) and in probands (Pc = 5.4e-15 and Pc = 0.001, respectively) compared to controls. Transmission disequilibrium test showed that the highest risk was conferred by DRB1*04:02-DQB1*03:02 (Pc = 3.26e-05) and DRB1*03:01-DQB1*02:01 (Pc = 1.78e-12) haplotypes and the highest protection by DRB1*14:01-DQB1*05:03 (Pc = 8.66e-05), DRB1*15:01-DQB1*06:02 (Pc = 0.002), and DRB1*11:01-DQB1*03:01 (Pc = 0.0003) haplotypes. Based on logistic regression analysis, carriage of risk haplotypes increased the risk of T1D development 24.5 times in the Iranian population (p = 5.61e-13). Also, receiver operating characteristic curve analysis revealed a high predictive power of those risk haplotypes in discrimination of susceptible from healthy individuals (area under curve: 0.88, p = 5.5e-32). Our study highlights the potential utility of genetic risk assessment based on HLA diplotypes for predicting T1D risk in individuals, particularly among family members of affected children in our population., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)