The role of genes of the second phase of detoxification of xenobiotics in the pathogenesis of multifactorial diseases

The genetic status of a person is currently assigned a major role in the pathogenesis, diagnosis and treatment of various diseases. The most important genetic factors that have been attached great importance to are the genes of the glutathione-S-transferase family (GSTs). The genes of the glutathione-S-transferase family belong to the second phase of detoxification of xenobiotics and their altered activity leads to the development of many pathological conditions. GSTM, GSTT, GSTP are considered to be the most polymorphic. The issues of the participation of polymorphic GSTs in the development of infectious, allergic and oncological diseases, disorders of the reproductive system, as well as in the development of Alzheimer's disease are discussed in the article.

IOTG-01. Computational Neurosurgery in Brain Tumors: A paradigm shift on the use of Artificial Intelligence and Connectomics in pre- and intra-operative imaging

Computational Neurosurgery is a novel field where computational modeling and artificial intelligence (AI) are used to analyze diseases of neurosurgical interest. Our aim is to apply AI models to brain tumor (BT) images to a) automatically segment BTs on pre-operative MRI, b) predict the genetic subtype of glioma on intra- and post-operative histological specimens; and c) predict the extent of resection according to connectomics data. For the segmentation task, we used 510 BT images to train a deep learning (DL) model for automatic segmentation of the tumors’ edges and comparison of the AI-generated masks versus experts’ consensus (quantified by means of the dice score). For the histopathology task, we digitalized 266 hematoxylin/eosin slides of gliomas (including 130 IDH-wildtype and 136 IDH-mutant) and applied a DL architecture to predict the IDH genetic status, then validated by immunohistochemistry and genetic sequencing. The datasets were also augmented by generating synthetic glioma images by means of a Generative Adversarial Network methodology. The resection of 10 BTs was also customized according to connectomics data. In the segmentation experiment, we reached a dice score of ~0.9 (out of 1.0), while further demonstrating that only the T1, T1 after gadolinium, and FLAIR sequences are necessary for accurate automatic segmentation. In the histopathology task, we were able to predict the genetic status with accuracy between 76% and 95% using the DL model. The machine learning-based connectome analysis allowed us to perform safe supramaximal resection. We have shown the robustness of applying AI methodology or the automatic segmentation of BTs in MR imaging. Moreover, we have also shown that AI can be used to predict the genetic status, specifically, IDH, in histopathology images of gliomas. Our results support the use of AI in the clinical scenario for a fast and objective computerized characterization of patients affected by BTs.

Association between CSF alpha-synuclein seeding activity and genetic status in Parkinson’s disease and dementia with Lewy bodies

The clinicopathological heterogeneity in Lewy-body diseases (LBD) highlights the need for pathology-driven biomarkers in-vivo. Misfolded alpha-synuclein (α-Syn) is a lead candidate based on its crucial role in disease pathophysiology. Real-time quaking-induced conversion (RT-QuIC) analysis of CSF has recently shown high sensitivity and specificity for the detection of misfolded α-Syn in patients with Parkinson's disease (PD) and dementia with Lewy bodies (DLB). In this study we performed the CSF RT-QuIC assay in 236 PD and 49 DLB patients enriched for different genetic forms with mutations in GBA, parkin, PINK1, DJ1, and LRRK2. A subgroup of 100 PD patients was also analysed longitudinally. We correlated kinetic seeding parameters of RT-QuIC with genetic status and CSF protein levels of molecular pathways linked to α-Syn proteostasis. Overall, 85% of PD and 86% of DLB patients showed positive RT-QuIC α-Syn seeding activity. Seeding profiles were significantly associated with mutation status across the spectrum of genetic LBD. In PD patients, we detected positive α-Syn seeding in 93% of patients carrying severe GBA mutations, in 78% with LRRK2 mutations, in 59% carrying heterozygous mutations in recessive genes, and in none of those with bi-allelic mutations in recessive genes. Among PD patients, those with severe GBA mutations showed the highest seeding activity based on RT-QuIC kinetic parameters and the highest proportion of samples with 4 out of 4 positive replicates. In DLB patients, 100% with GBA mutations showed positive α-Syn seeding compared to 79% of wildtype DLB. Moreover, we found an association between α-Syn seeding activity and reduced CSF levels of proteins linked to α-Syn proteostasis, specifically lysosome-associated membrane glycoprotein 2 and neurosecretory protein VGF.These findings highlight the value of α-Syn seeding activity as an in-vivo marker of Lewy-body pathology and support its use for patient stratification in clinical trials targeting α-Syn.

Genetic status of Centella asiatica (L.) Urb. (Indian pennywort): A review

In recent years, demand for medicinal plants increased due to the rise in attraction towards herbal products which are safer compared to modern drugs. Centella asiatica (L.) Urb is known as an important medicinal plant in herbal medicinal systems. It also used as an active ingredient for many products in the pharmaceutical and cosmetic industry. So far, review on this plant concerns mainly on medicinal, cosmetology and photochemical works reported. This review presents the genetic studies conducted in this herb along with a mention on conservation. Since documenting and studying genetic variation and its composition has an important connection for the understanding of evolution and improving the conservation of this species.

MiRNAs Correlate with HLA Expression in Uveal Melanoma: Both Up- and Downregulation Are Related to Monosomy 3

MicroRNAs are known to play a role in the regulation of inflammation. As a high HLA Class I expression is associated with a bad prognosis in UM, we set out to determine whether any miRNAs were related to a high HLA Class I expression and inflammation. We also determined whether such miRNAs were related to the UM’s genetic status. The expression of 125 miRNAs was determined in 64 primary UM from Leiden. Similarly, the mRNA expression of HLA-A, HLA-B, TAP1, BAP1, and immune cell markers was obtained. Expression levels of 24 of the 125 miRNAs correlated with expression of at least three out of four HLA Class I probes. Four miRNAs showed a positive correlation with HLA expression and infiltration with leukocytes, 20 a negative pattern. In the first group, high miRNA levels correlated with chromosome 3 loss/reduced BAP1 mRNA expression, in the second group low miRNA levels. The positive associations between miRNA-22 and miRNA-155 with HLA Class I were confirmed in the TCGA study and Rotterdam cohort, and with TAP1 in the Rotterdam data set; the negative associations between miRNA-125b2 and miRNA-211 and HLA-A, TAP1, and CD4 were confirmed in the Rotterdam set. We demonstrate two patterns: miRNAs can either be related to a high or a low HLA Class I/TAP1 expression and the presence of infiltrating lymphocytes and macrophages. However, both patterns were associated with chromosome 3/BAP1 status, which suggests a role for BAP1 loss in the regulation of HLA expression and inflammation in UM through miRNAs.