TENM2

Last update 08 May 2025

Basic Info

Synonyms

KIAA1127, ODZ2, Protein Odd Oz/ten-m homolog 2

+ [11]

Introduction

Involved in neural development, regulating the establishment of proper connectivity within the nervous system. Promotes the formation of filopodia and enlarged growth cone in neuronal cells. Induces homophilic cell-cell adhesion (By similarity). May function as a cellular signal transducer. Induces gene transcription inhibition. Acts as a ligand of the ADGRL1 receptor. Mediates axon guidance and heterophilic cell-cell adhesion.

100 Clinical Results associated with TENM2

100 Translational Medicine associated with TENM2

0 Patents (Medical) associated with TENM2

Literatures (Medical) associated with TENM2

01 Apr 2025·Immunology

Renal and Peripheral Blood Transcriptome Signatures That Predict Treatment Response in Proliferative Lupus Nephritis—A Prospective Study

Article

Author: Thabah, Molly Mary ; Shah, Sanket ; Kommoju, Vallayyachari ; Vembar, Shruthi Sridhar ; Mariaselvam, Christina Mary ; Bavikatte, Anitha Nagaraj ; Kavadichanda, Chengappa ; Bulusu, Sree Nethra ; Negi, Vir Singh ; Murthy, Sneha Surya Narayana

ABSTRACTMechanisms contributing to non‐response to treatment in lupus nephritis (LN) are unclear. We characterised the transcriptome of paired peripheral blood mononuclear cells (PBMCs) and renal tissues in LN before and after cyclophosphamide (CYC) treatment and identified markers that predicted treatment response. Total RNA isolated from paired PBMCs (n = 32) and renal tissues (n = 25) of 16 proliferative LN before CYC treatment, 6 months post‐treatment, and during renal flare, was sequenced on Illumina Novaseq‐6000 platform. Post‐treatment, eight patients were clinical responders (CR), of whom four flared (FL), and eight were non‐responders (NR). Comparative transcriptomic analyses before and after treatment within CR, NR, and FL groups was performed using DESeq2. Weighted gene co‐expression network analysis (WGCNA) and ROC analysis was performed to identify and validate hub genes predictive of treatment response. Based on this, we observed that pathways such as degradation of cell cycle proteins, expression of G0 and G1 phase proteins, and apoptosis, were upregulated in CR PBMCs post‐treatment, while IFN‐γ signalling and ECM organisation were downregulated. In NR PBMCs, ECM molecules, neddylation and BCR signalling were upregulated post‐CYC treatment, while in NR renal tissue, TLR, IFN and NF‐κB signalling pathways were upregulated. In FL PBMCs, neutrophil degranulation and ROS and RNS production in phagocytes were downregulated following treatment, whereas, in the corresponding renal tissue, cell‐ECM interactions and ISG15 antiviral mechanism were downregulated. After WGCNA and subsequent ROC analysis, TENM2, NLGN1 and AP005230.1 from PBMCs each predicted NR (AUC‐0.91; p = 0.03), while combined model improved prediction (AUC‐0.94; p = 0.02). AP005230.1 from renal tissue also predicted non‐response (AUC‐0.94; p = 0.01) and AC092436.3 from PBMCs predicted renal flare (AUC‐0.81; p = 0.04). Our study identified significant DEGs/pathways specific to different treatment outcomes and hub genes that predicted non‐response and renal flare.

01 Jan 2025·Veterinary Medicine International

Comparative Transcriptome Analysis of Hens’ Livers in Conventional Cage vs. Cage‐Free Egg Production Systems

Article

Author: Rondón-Barragán, Iang Schroniltgen ; Herrera-Sánchez, María Paula ; Rodríguez-Hernández, Roy

Different conditions of production systems including stocking density, thermal conditions, and behavior restriction can have a significant detrimental effect on the health and performance of laying hens. The conventional cage system is one of the systems that have been reported to cause stress problems in birds, due to social and behavioral stress. Emerging technologies have facilitated a deeper understanding of animal responses to various scenarios and can be an additional tool to conventional ones to assess animal welfare, where transcriptomic analysis has the potential to show the genetic changes that occur in response to stress. According to this, the aim of this work was to characterize the liver transcriptome of hens housed under two egg production systems (conventional cage and cage‐free). Liver tissue from Hy‐Line Brown hens housed in conventional cage (n = 3) and cage‐free (n = 3) production systems at week 80 of age was processed using the Illumina platform to identify differentially expressed genes with a padj < 0.05. Regarding the differentially expressed genes, 138 genes were found, of which 81 were upregulated and 57 downregulated. Some of the genes of interest were TENM2, GRIN2C, and ACACB, which would indicate greater fat synthesis in the liver of caged hens. The enriched KEGG pathways were DNA replication and the cell cycle. In conclusion, it was identified that the cage production system may influence DNA replication and the cell cycle since the genes related to these terms were found suppressed, which would indicate cellular instability.

01 Aug 2024·European Neuropsychopharmacology

Lithium response in bipolar disorder: Epigenome-wide DNA methylation signatures and epigenetic aging

Article

Author: Gavín, Patrícia ; Jiménez, Ester ; Barrot-Feixat, Carme ; Giménez-Palomo, Anna ; Acosta-Díez, Miriam ; Mitjans, Marina ; Vieta, Eduard ; Benabarre, Antoni ; García-Portilla, María Paz ; Bobes, Julio ; Papiol, Sergi ; Schulze, Thomas G ; González-Blanco, Leticia ; Zafrilla-López, Marina ; Saiz, Pilar A ; Ruiz, Victoria ; Arias, Bárbara

Lithium (Li) is the first-line treatment for bipolar disorder (BD) even though only 30 % of BD patients are considered excellent responders. The mechanisms by which Li exerts its action are not clearly understood, but it has been suggested that specific epigenetic mechanisms, such as methylation processes, may play a role. In this regard, DNA methylation patterns can be used to estimate epigenetic age (EpiAge), which is accelerated in BD patients and reversed by Li treatment. Our first aim was to compare the DNA methylation profile in peripheral blood between BD patients categorized as excellent responders to Li (Ex-Rp) and non-responders (N-Rp). Secondly, EpiAge was estimated to detect differential age acceleration between the two groups. A total of 130 differentially methylated positions (DMPs) and 16 differentially methylated regions (DMRs) between Ex-Rp (n = 26) and N-Rp (n = 37) were identified (FDR adjusted p-value < 0.05). We found 122 genes mapping the DMPs and DMRs, nine of which (HOXB6, HOXB3, HOXB-AS3, TENM2, CACNA1B, ANK3, EEF2K, CYP1A1, and SORCS2) had previously been linked to Li response. We found genes related to the GSK3β pathway to be highly represented. Using FUMA, we found enrichment in Gene Ontology Cell Component for the synapse. Gene network analysis highlighted functions related to the cell cycle, nervous system development and function, and gene expression. No significant differences in age acceleration were found between Ex-Rp and N-Rp for any of the epigenetic clocks analysed. Our findings indicate that a specific methylation pattern could determine the response to Li in BD patients. We also found that a significant portion of the differentially methylated genes are closely associated with the GSK3β pathway, reinforcing the role of this system in Li response. Future longitudinal studies with larger samples will help to elucidate the epigenetic mechanisms underlying Li response.

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TENM2

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