**Preface to "Understanding Neuromuscular Health and Disease: Advances in Genetics, Omics, and Molecular Function"**

Recently, the field of neuromuscular research has seen considerable advances in the molecular and cellular understanding of muscle biology, and the treatment of neuro-muscular disease. These advances are at the forefront of modern molecular methodologies, often integrating across wet-lab cell and tissue models, dry-lab computational approaches, and clinical studies. The continuing development and application of multi-omics methods offer particular challenges and opportunities, not least in the potential for personalized medicine.

This compilation, entitled "Understanding Neuromuscular Health and Disease: Advances in Genetics, Omics, and Molecular Function", encompasses some 15 publications from colleagues working on diverse aspects of neuromuscular health and disease. It is structured according to the following broad themes:


More than 500 different genes are known to be associated with neuromuscular disorders (Buscara et al.), and the identification of causative mutations has allowed the development of personalized therapies (Buscara et al., Smeriglio et al.). However, even if great progress has been made during the past two decades in different subgroups of neuromuscular disorders, there are still numerous challenges to resolve, such as the optimization of therapeutic knock-down strategies (Joubert et al.), targeting specific muscles or tissues of the nervous system (Buscara et al.), identifying genetic modifiers that can impair a therapeutic strategy (Smeriglio et al.), targeting common pathways being affected in different patient subgroups for a given disease (Le Gall et al., Connolly et al.), or understanding the impact of neuromuscular disorders on other tissues that could be affected but may be understudied.

The neuromuscular pathologies considered in this book include Duchenne muscular dystrophy (Anwar et al., Lim et al., Tawalbeh et al., Sheikh et al.), facioscapulohumeral dystrophy (Joubert et al., Heier et al., Sidlauskaite et al.), amyotrophic lateral sclerosis (Le Gall et al., Connolly et al., Vasilopoulou et al.), spinal muscular atrophy (Smeriglio et al.), Emery–Dreifuss muscular dystrophy (Vignier et al.), and rheumatoid arthritis (D'Cruz et al.). Looking across diseases, several themes are recurrent, such as the efforts to identify genotype–phenotype correlations in DMD (Anwar et al., Lim et al., Sheikh et al.) and ALS (Le Gall et al., Connolly et al.), the quest for effective biomarkers in many neuromuscular conditions (Smeriglio et al., Tawalbeh et al., Heier et al., D'Cruz et al.), and the use of genomic and multi-omic approaches towards better ways to identify biomarkers and to understand disease (Heier et al., Vasilopoulou et al., Vignier et al.).

The search for genotype–phenotype correlations can be aimed at the improved understanding of disease (Le Gall et al., Connolly et al., Lim et al., Sheikh et al.), but may also be relevant to potential therapeutic outcomes (Anwar et al.). Of relevance to this are genotype–phenotype correlations in DMD (Anwar et al., Lim et al., Sheikh et al.) and in ALS (Le Gall et al., Connolly et al.). It is interesting to contrast the state of investigations in these two conditions, differences which are related to the underlying genetics: DMD being due to mutations at a single gene, and, therefore, correlations being sought between clinical outcomes and specific mutation patterns within that gene (Anwar et al., Lim et al., Sheikh et al.); ALS being a disease of unclear aetiology for the majority of patients and the focus of these genotype–phenotype investigations thus being on the relationship of different genes and their functional roles to the implicated mechanisms (Le Gall et al.) or clinical outcomes of the condition (Connolly et al.).

The use of genomics and multi-omics approaches is a theme which itself cuts across the aims of current research, from the overlay of multiple omics data to achieve a global perspective and new understanding of Emery–Dreifuss muscular dystrophy (Vignier et al.), to the identification of novel circulating miRNA and protein biomarkers for FSHD using multi-omics (Heier et al.), through to the application of machine learning to the genomics of ALS, which is aimed at understanding the molecular basis of this disease (and is also relevant to genotype–phenotype correlations) (Vasilopoulou et al.). Deciphering the pathways and gene mutations involved in neuromuscular diseases may allow for the development of computational models helping our understanding of muscle pathologies, which could enable preclinical studies of neuromuscular diseases in the context of personalized medicine (Speciale et al.).

Aside from therapeutic strategy development, the use of biomarkers may be critical as disease trackers for the development of effective therapeutics (for example, in FSHD, Heier et al.), but also to the personalized tailoring of existing treatments (such as in DMD, Tawalbeh et al., and in rheumatoid arthritis, D'Cruz et al.), and may prove useful in a broad sense for improved stratification, diagnosis, and treatment (e.g., in adult SMA, Smeriglio et al.).

We hope that studies such as these, that integrate modern molecular methodologies across cell and tissue models, computational approaches, and clinical studies, will continue to drive progress towards improved neuromuscular health and treatments for these often severe diseases.

> **William Duddy, Stephanie Duguez** *Editors*
