The Human Extracellular Matrix Diseasome Reveals Genotype-Phenotype Associations with Clinical Implications for Age-Related Diseases

Synergizing drug repurposing and target identification for neurodegenerative diseases

Despite dedicated research efforts, the absence of disease-curing remedies for neurodegenerative diseases (NDDs) continues to jeopardize human society and stands as a challenge. Drug repurposing is an attempt to find new functionality of existing drugs and take it as an opportunity to discourse the clinically unmet need to treat neurodegeneration. However, despite applying this approach to rediscover a drug, it can also be used to identify the target on which a drug could work. The primary objective of target identification is to unravel all the possibilities of detecting a new drug or repurposing an existing drug. Lately, scientists and researchers have been focusing on specific genes, a particular site in DNA, a protein, or a molecule that might be involved in the pathogenesis of the disease. However, the new era discusses directing the signaling mechanism involved in the disease progression, where receptors, ion channels, enzymes, and other carrier molecules play a huge role. This review aims to highlight how target identification can expedite the whole process of drug repurposing. Here, we first spot various target-identification methods and drug-repositioning studies, including drug-target and structure-based identification studies. Moreover, we emphasize various drug repurposing approaches in NDDs, namely, experimental-based, mechanism-based, and in silico approaches. Later, we draw attention to validation techniques and stress on drugs that are currently undergoing clinical trials in NDDs. Lastly, we underscore the future perspective of synergizing drug repurposing and target identification in NDDs and present an unresolved question to address the issue.

Emerging applications of machine learning in genomic medicine and healthcare

The integration of artificial intelligence technologies has propelled the progress of clinical and genomic medicine in recent years. The significant increase in computing power has facilitated the ability of artificial intelligence models to analyze and extract features from extensive medical data and images, thereby contributing to the advancement of intelligent diagnostic tools. Artificial intelligence (AI) models have been utilized in the field of personalized medicine to integrate clinical data and genomic information of patients. This integration allows for the identification of customized treatment recommendations, ultimately leading to enhanced patient outcomes. Notwithstanding the notable advancements, the application of artificial intelligence (AI) in the field of medicine is impeded by various obstacles such as the limited availability of clinical and genomic data, the diversity of datasets, ethical implications, and the inconclusive interpretation of AI models' results. In this review, a comprehensive evaluation of multiple machine learning algorithms utilized in the fields of clinical and genomic medicine is conducted. Furthermore, we present an overview of the implementation of artificial intelligence (AI) in the fields of clinical medicine, drug discovery, and genomic medicine. Finally, a number of constraints pertaining to the implementation of artificial intelligence within the healthcare industry are examined.

Secreted ADAMTS-like proteins as regulators of connective tissue function

The extracellular matrix (ECM) determines functional properties of connective tissues through structural components, such as collagens, elastic fibers, or proteoglycans. The ECM also instructs cell behavior through regulatory proteins, including proteases, growth factors, and matricellular proteins, which can be soluble or tethered to ECM scaffolds. The secreted a disintegrin and metalloproteinase with thrombospondin type 1 repeats/motifs-like (ADAMTSL) proteins constitute a family of regulatory ECM proteins that are related to ADAMTS proteases but lack their protease domains. In mammals, the ADAMTSL protein family comprises seven members, ADAMTSL1-6 and papilin. ADAMTSL orthologs are also present in the worm, Caenorhabditis elegans, and the fruit fly, Drosophila melanogaster. Like other matricellular proteins, ADAMTSL expression is characterized by tight spatiotemporal regulation during embryonic development and early postnatal growth and by cell type- and tissue-specific functional pleiotropy. Although largely quiescent during adult tissue homeostasis, reexpression of ADAMTSL proteins is frequently observed in the context of physiological and pathological tissue remodeling and during regeneration and repair after injury. The diverse functions of ADAMTSL proteins are further evident from disorders caused by mutations in individual ADAMTSL proteins, which can affect multiple organ systems. In addition, genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) in ADAMTSL genes to complex traits, such as lung function, asthma, height, body mass, fibrosis, or schizophrenia. In this review, we summarize the current knowledge about individual members of the ADAMTSL protein family and highlight recent mechanistic studies that began to elucidate their diverse functions.

En route towards a personalized medicine approach: Innovative therapeutic modalities for connective tissue disorders

Connective tissue disorders can be caused by pathogenic variants (mutations) in genes encoding extracellular matrix (ECM) proteins. Such disorders typically manifest during development or postnatal growth and result in significant morbidity and mortality. The development of curative treatments for connective tissue disorders is hampered in part by the inability of many mature connective tissues to efficiently regenerate. To be most effective, therapeutic strategies designed to preserve or restore tissue function will likely need to be initiated during phases of significant endogenous connective tissue remodeling and organ sculpting postnatally and directly target the underlying ECM protein mutations. With recent advances in whole exome sequencing, in-vitro and in-vivo disease modeling, and the development of mutation-specific molecular therapeutic modalities, it is now feasible to directly correct disease-causing mutations underlying connective tissue disorders and ameliorate their pathogenic consequences. These technological advances may lead to potentially curative personalized medicine approaches for connective tissue disorders that have previously been considered incurable. In this review, we highlight innovative therapeutic modalities including gene replacement, exon skipping, DNA/mRNA editing, and pharmacological approaches that were used to preserve or restore tissue function in the context of connective tissue disorders. Inherent to a successful application of these approaches is the need to deepen the understanding of mechanisms that regulate ECM formation and homeostasis, and to decipher how individual mutations in ECM proteins compromise ECM and connective tissue development and function.

Strategic outline of interventions targeting extracellular matrix for promoting healthy longevity

The extracellular matrix (ECM), composed of interlinked proteins outside of cells, is an important component of the human body that helps maintain tissue architecture and cellular homeostasis. As people age, the ECM undergoes changes that can lead to age-related morbidity and mortality. Despite its importance, ECM aging remains understudied in the field of geroscience. In this review, we discuss the core concepts of ECM integrity, outline the age-related challenges and subsequent pathologies and diseases, summarize diagnostic methods detecting a faulty ECM, and provide strategies targeting ECM homeostasis. To conceptualize this, we built a technology research tree to hierarchically visualize possible research sequences for studying ECM aging. This strategic framework will hopefully facilitate the development of future research on interventions to restore ECM integrity, which could potentially lead to the development of new drugs or therapeutic interventions promoting health during aging.