DNA methylation as a new tool for the differential diagnosis between T-LBL and lymphocyte-rich thymoma.

T-lymphoblastic lymphoma (T-LBL) and thymoma are two rare primary tumors of the thymus deriving either from T-cell precursors or from thymic epithelial cells, respectively. Some thymoma subtypes (AB, B1, and B2) display numerous reactive terminal deoxynucleotidyl transferase-positive (TdT+) T-cell precursors masking epithelial tumor cells. Therefore, the differential diagnosis between T-LBL and TdT+ T-lymphocyte-rich thymoma could be challenging, especially in the case of needle biopsy. To distinguish between T-LBL and thymoma-associated lymphoid proliferations, we analyzed the global DNA methylation using two different technologies, namely MeDIP array and EPIC array, in independent samples series [17 T-LBLs compared with one TdT+ lymphocyte-rich thymoma (B1 subtype) and three normal thymi, and seven lymphocyte-rich thymomas compared with 24 T-LBLs, respectively]. In unsupervised principal component analysis (PCA), T-LBL and thymoma samples clustered separately. We identified differentially methylated regions (DMRs) using MeDIP-array and EPIC-array datasets and nine overlapping genes between the two datasets considering the top 100 DMRs including ZIC1, TSHZ2, CDC42BPB, RBM24, C10orf53, and MACROD2. In order to explore the DNA methylation profiles in larger series, we defined a classifier based on these six differentially methylated gene promoters, developed an MS-MLPA assay, and demonstrated a significant differential methylation between thymomas (hypomethylated; n = 48) and T-LBLs (hypermethylated; n = 54) (methylation ratio median 0.03 versus 0.66, respectively; p < 0.0001), with MACROD2 methylation status the most discriminating. Using a machine learning strategy, we built a prediction model trained with the EPIC-array dataset and defined a cumulative score taking into account the weight of each feature. A score above or equal to 0.4 was predictive of T-LBL and conversely. Applied to the MS-MLPA dataset, this prediction model accurately predicted diagnoses of T-LBL and thymoma. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

CADPS functional mutations in patients with bipolar disorder increase the sensitivity to stress.

Bipolar disorder is a severe and chronic psychiatric disease resulting from a combination of genetic and environmental risk factors. Here, we identified a significant higher mutation rate in a gene encoding the calcium-dependent activator protein for secretion (CADPS) in 132 individuals with bipolar disorder, when compared to 184 unaffected controls or to 21,070 non-psychiatric and non-Finnish European subjects from the Exome Aggregation Consortium. We found that most of these variants resulted either in a lower abundance or a partial impairment in one of the basic functions of CADPS in regulating neuronal exocytosis, synaptic plasticity and vesicular transporter-dependent uptake of catecholamines. Heterozygous mutant mice for Cadps+/- revealed that a decreased level of CADPS leads to manic-like behaviours, changes in BDNF level and a hypersensitivity to stress. This was consistent with more childhood trauma reported in families with mutation in CADPS, and more specifically in mutated individuals. Furthermore, hyperactivity observed in mutant animals was rescued by the mood-stabilizing drug lithium. Overall, our results suggest that dysfunction in calcium-dependent vesicular exocytosis may increase the sensitivity to environmental stressors enhancing the risk of developing bipolar disorder.

Two polygenic mouse models of major depressive disorders identify TMEM161B as a potential biomarker of disease in humans.

Treatments are only partially effective in major depressive disorders (MDD) but no biomarker exists to predict symptom improvement in patients. Animal models are essential tools in the development of antidepressant medications, but while recent genetic studies have demonstrated the polygenic contribution to MDD, current models are limited to either mimic the effect of a single gene or environmental factor. We developed in the past a model of depressive-like behaviors in mice (H/Rouen), using selective breeding based on behavioral reaction after an acute mild stress in the tail suspension test. Here, we propose a new mouse model of depression (H-TST) generated from a more complex genetic background and based on the same selection process. We first demonstrated that H/Rouen and H-TST mice had similar phenotypes and were more sensitive to glutamate-related antidepressant medications than selective serotonin reuptake inhibitors. We then conducted an exome sequencing on the two mouse models and showed that they had damaging variants in 174 identical genes, which have also been associated with MDD in humans. Among these genes, we showed a higher expression level of Tmem161b in brain and blood of our two mouse models. Changes in TMEM161B expression level was also observed in blood of MDD patients when compared with controls, and after 8-week treatment with duloxetine, mainly in good responders to treatment. Altogether, our results introduce H/Rouen and H-TST as the two first polygenic animal models of MDD and demonstrate their ability to identify biomarkers of the disease and to develop rapid and effective antidepressant medications.

Risperidone response in patients with schizophrenia drives DNA methylation changes in immune and neuronal systems.

Background: The choice of efficient antipsychotic therapy for schizophrenia relies on a time-consuming trial-and-error approach, whereas the social and economic burdens of the disease call for faster alternatives. Material & methods: In a search for predictive biomarkers of antipsychotic response, blood methylomes of 28 patients were analyzed before and 4 weeks into risperidone therapy. Results: Several CpGs exhibiting response-specific temporal dynamics were identified in otherwise temporally stable methylomes and noticeable global response-related differences were observed between good and bad responders. These were associated with genes involved in immunity, neurotransmission and neuronal development. Polymorphisms in many of these genes were previously linked with schizophrenia etiology and antipsychotic response. Conclusion: Antipsychotic response seems to be shaped by both stable and medication-induced methylation differences.

The most common way to treat schizophrenia is antipsychotic medication. However, not all antipsychotics work for all patients. The only way to find a suitable antipsychotic is to prescribe one and wait, sometimes for months, to see if it works. Finding an alternative to this trial-and-error method would help reduce patient suffering and costs for healthcare systems. The idea is to look in the DNA of our blood cells for specific marks that can change in response to our lifestyle or health condition. These marks could help us predict how patients will react to the drug. In other words, they can serve as biomarkers of antipsychotic response. The current work examined the blood of schizophrenia patients before and 4 weeks after starting medication. The patients who did not respond well to the drug had different marks on the genes involved in immune defense and nervous system functioning. Some of these genes also play roles in the development of schizophrenia, whereas others can directly affect what happens to the drug in the patient's body. Although marks that predict how patients will react were not identified with certainty, valuable targets for future research were identified.

Dense mapping of the region of insulin gene VNTR in polycystic ovary syndrome in a population of women from Central Europe.

INTRODUCTION: Insulin gene VNTR was associated with polycystic ovary syndrome (PCOS) in some studies but not in others. This couldb be due to the heterogeneity of the definition of PCOS and/or the use of inappropriate gene mapping strategies. MATERIAL AND METHODS: In this investigation, the association of VNTR with PCOS was explored in a population of women from Central Europe (377 cases and 105 controls) in whom PCOS was diagnosed according to Rotterdam criteria. Seven SNPs: rs3842756 (G/A), rs3842755 (G/T), rs3842754 (C/T), rs3842753 (A/C), rs3842752 (C/T), rs3842748 (G/C), and rs689 (T/A) were genotyped in a portion of the population (160 cases and 95 controls) by sequencing or by SSO-PCR. Analysis of linkage disequilibrium (LD) pattern allowed selecting three tagSNPs (rs3842754, rs3842748, and rs689), which were genotyped in the rest of the population by KASPar. RESULTS: Six haplotypes were reconstructed, among which three (h1, h2 and h6) were more frequent. Statistical analysis allowed observation of the association of the SNP rs3842748, through its GC genotype, with obesity in PCOS (P = 0.049; OR CI95% 1,59 [1.00-2.51]) and in classical PCOS (YPCOS) (P = 0.010), as well as the correlation of the SNP rs689 and the pair of haplotypes h1/h1 with higher levels of testosteronaemia in the PCOS group, although this was at the limit of significance (P = 0.054) CONCLUSION: These results are in accordance with some studies in literature and highlight the role of insulin gene VNTR in complex metabolic disorders.