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1.
Bioinformatics ; 40(6)2024 Jun 03.
Article in English | MEDLINE | ID: mdl-38889282

ABSTRACT

MOTIVATION: Integrative Biomedicl Informatics, Research Program on Biomedical Informatics (IBI - GRIB), Hospital Del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF) C/ del Dr. Aiguader 88 Barcelona 08003 Spain.Understanding the genetic basis of complex diseases is one of the main challenges in modern genomics. However, current tools often lack the versatility to efficiently analyze the intricate relationships between genetic variations and disease outcomes. To address this, we introduce Genopyc, a novel Python library designed for comprehensive investigation of how the variants associated to complex diseases affects downstream pathways. Genopyc offers an extensive suite of functions for heterogeneous data mining and visualization, enabling researchers to delve into and integrate biological information from large-scale genomic datasets. RESULTS: In this work, we present the Genopyc library through application to real-world genome wide association studies variants. Using Genopyc to investigate the functional consequences of variants associated to intervertebral disc degeneration enabled a deeper understanding of the potential dysregulated pathways involved in the disease, which can be explored and visualized by exploiting the functionalities featured in the package. Genopyc emerges as a powerful asset for researchers, facilitating the investigation of complex diseases paving the way for more targeted therapeutic interventions. AVAILABILITY AND IMPLEMENTATION: Genopyc is available on pip https://pypi.org/project/genopyc/.The source code of Genopyc is available at https://github.com/freh-g/genopyc. A tutorial notebook is available at https://github.com/freh-g/genopyc/blob/main/tutorials/Genopyc_tutorial_notebook.ipynb. Finally, a detailed documentation is available at: https://genopyc.readthedocs.io/en/latest/.


Subject(s)
Genome-Wide Association Study , Genomics , Software , Humans , Genomics/methods , Data Mining/methods , Genetic Variation , Databases, Genetic , Computational Biology/methods
2.
NAR Genom Bioinform ; 6(2): lqae049, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38745993

ABSTRACT

Knowledge graph embeddings (KGE) are a powerful technique used in the biomedical domain to represent biological knowledge in a low dimensional space. However, a deep understanding of these methods is still missing, and, in particular, regarding their applications to prioritize genes associated with complex diseases with reduced genetic information. In this contribution, we built a knowledge graph (KG) by integrating heterogeneous biomedical data and generated KGE by implementing state-of-the-art methods, and two novel algorithms: Dlemb and BioKG2vec. Extensive testing of the embeddings with unsupervised clustering and supervised methods showed that KGE can be successfully implemented to predict genes associated with diseases and that our novel approaches outperform most existing algorithms in both scenarios. Our findings underscore the significance of data quality, preprocessing, and integration in achieving accurate predictions. Additionally, we applied KGE to predict genes linked to Intervertebral Disc Degeneration (IDD) and illustrated that functions pertinent to the disease are enriched within the prioritized gene set.

4.
JOR Spine ; 6(4): e1294, 2023 Dec.
Article in English | MEDLINE | ID: mdl-38156054

ABSTRACT

The cartilaginous endplates (CEP) are key components of the intervertebral disc (IVD) necessary for sustaining the nutrition of the disc while distributing mechanical loads and preventing the disc from bulging into the adjacent vertebral body. The size, shape, and composition of the CEP are essential in maintaining its function, and degeneration of the CEP is considered a contributor to early IVD degeneration. In addition, the CEP is implicated in Modic changes, which are often associated with low back pain. This review aims to tackle the current knowledge of the CEP regarding its structure, composition, permeability, and mechanical role in a healthy disc, how they change with degeneration, and how they connect to IVD degeneration and low back pain. Additionally, the authors suggest a standardized naming convention regarding the CEP and bony endplate and suggest avoiding the term vertebral endplate. Currently, there is limited data on the CEP itself as reported data is often a combination of CEP and bony endplate, or the CEP is considered as articular cartilage. However, it is clear the CEP is a unique tissue type that differs from articular cartilage, bony endplate, and other IVD tissues. Thus, future research should investigate the CEP separately to fully understand its role in healthy and degenerated IVDs. Further, most IVD regeneration therapies in development failed to address, or even considered the CEP, despite its key role in nutrition and mechanical stability within the IVD. Thus, the CEP should be considered and potentially targeted for future sustainable treatments.

5.
Eur Spine J ; 32(10): 3379-3386, 2023 10.
Article in English | MEDLINE | ID: mdl-37555954

ABSTRACT

PURPOSE: Low back pain (LBP) is one of the largest causes of morbidity worldwide. The aetiology of LBP is complex, and many factors contribute to the onset. Bone marrow lesions within the vertebra adjacent to an intervertebral degenerate disc named Modic change (MC) have been suggested as a diagnostic subgroup of LBP. Autoimmune response has been proposed to be one of the causes that promote the development of MC. The aim of the current investigation is to assess prevalence and severity of MC and LBP in participants with an autoimmune disease diagnosis in a well-documented cohort of adult twin volunteers. METHODS: Multivariate generalized mixed linear models (GLMM) were implemented in order to calculate the association between having an autoimmune disorder and MC prevalence, width and severe and disabling LBP. The model was corrected for family structure as well as for covariates such as age, BMI and smoking. RESULTS: No association was found between diagnosis of autoimmune disorder and MC. Interestingly, BMI was independently associated with MC width but not to MC prevalence. These results help to shed light on the relationship between MC and autoimmunity as well as the role of BMI in the development of the lesions. CONCLUSION: This study is the first to examine autoimmune disorders and MC prevalence in a large, population-based female cohort. The study was well powered to detect a small effect. No association was found between having a diagnosis of one or more autoimmune conditions and MC prevalence, width or LBP.


Subject(s)
Autoimmune Diseases , Intervertebral Disc Degeneration , Low Back Pain , Adult , Humans , Female , Intervertebral Disc Degeneration/pathology , Lumbar Vertebrae/pathology , Body Mass Index , Magnetic Resonance Imaging/methods , Low Back Pain/epidemiology , Low Back Pain/etiology , Low Back Pain/pathology , Autoimmune Diseases/epidemiology , Autoimmune Diseases/complications , Autoimmune Diseases/pathology
6.
Front Cell Dev Biol ; 10: 924692, 2022.
Article in English | MEDLINE | ID: mdl-35846355

ABSTRACT

Low back pain is a highly prevalent, chronic, and costly medical condition predominantly triggered by intervertebral disc degeneration (IDD). IDD is often caused by structural and biochemical changes in intervertebral discs (IVD) that prompt a pathologic shift from an anabolic to catabolic state, affecting extracellular matrix (ECM) production, enzyme generation, cytokine and chemokine production, neurotrophic and angiogenic factor production. The IVD is an immune-privileged organ. However, during degeneration immune cells and inflammatory factors can infiltrate through defects in the cartilage endplate and annulus fibrosus fissures, further accelerating the catabolic environment. Remarkably, though, catabolic ECM disruption also occurs in the absence of immune cell infiltration, largely due to native disc cell production of catabolic enzymes and cytokines. An unbalanced metabolism could be induced by many different factors, including a harsh microenvironment, biomechanical cues, genetics, and infection. The complex, multifactorial nature of IDD brings the challenge of identifying key factors which initiate the degenerative cascade, eventually leading to back pain. These factors are often investigated through methods including animal models, 3D cell culture, bioreactors, and computational models. However, the crosstalk between the IVD, immune system, and shifted metabolism is frequently misconstrued, often with the assumption that the presence of cytokines and chemokines is synonymous to inflammation or an immune response, which is not true for the intact disc. Therefore, this review will tackle immunomodulatory and IVD cell roles in IDD, clarifying the differences between cellular involvements and implications for therapeutic development and assessing models used to explore inflammatory or catabolic IVD environments.

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