Immune Dysregulation Disorders in the Bioinformatics Paradigm

Immune dysregulation is an entity that consists of primary immunodeficiency disorders (PIDs), autoimmune diseases (adaptive immunity dysregulation), and autoinflammatory syndromes (innate immunity dysregulation). It reflects inadequate immune function, which leads to exaggerated chronic inflammatory responses and so tissue damage [1]. Immune dysregulation disorders are clinically and genetically heterogenous disorders. The clinical phenotypes derived from distinct genotype can overlap, and different disorders can share the same phenotype. Thus, in many cases, a precise diagnosis and effective management are difficult to achieve. Over the last decade, remarkable progress has been made particularly in finding disease-causing genes for a number of rare monogenic immune dysregulatory disorders. With the explosion of multi-omics technologies, such as genomics, proteomics, and transcriptomics, high throughput sequencing approaches have been widely applied in the immune dysregulation studies. This has led to increase awareness and a quantum jumb in the number of these monogenic immune dysregulation disorders, as well as pathways that underlie their pathogenesis. Moreover, this has facilitated the identification of new biomarkers that can help in early diagnosis, prognosis, spectacular novel therapeutic successes in the clinic and prediction of therapeutic responses [2]. Given the complexity of our immune system, diversity of immune dysregulation disorders, the heterogenous phenotypes, and advent of next-generation sequencing (NGS) data that is becoming increasingly available, putting all of these together and moving these big data to the clinic is becoming ever more critical. In a recent study by Stray-Pedersen and colleagues, the authors sought to investigate the ability of whole exome sequencing (WES) to detect disease-causing variants in patients with PIDs. They used computational copy number variant prediction pipelines. A likely molecular diagnosis was achieved in 40% of unrelated probands. Clinical diagnosis was revised in nearly half, and management was directly altered in nearly a quarter of families based on molecular findings [3]. This approach will lead to timely diagnosis, alter medical management; provide accurate information about recurrence risks for family planning, and may result in healthcare savings by ending diagnostic odysseys. Despite these many successes, there are some challenges and obstacles we face with the big data created in the last decade. We, as physicians, have to choose the right patient to do the genetic testing on to get the highest yield. This can be done with the focus on the phenotypes and clinical manifestations. These days, many phenotype databases, such as PHO have made this process easier. Another challenge is that clinical NGS technology has evolved rapidly, outpacing resources for generating guidelines, standards, and resources such as data storage. Bioinformatics and NGS-based precision medicine has mainly focused on cancer and remains under-utilized in rare diseases such as immune dysregulation disorders. Our goal is to encourage the use of immunoinformatics to accelerate immune system research. There have been several bio-tools to study Immune disorders, such as patients' registries, genomic databases, phenotype ontologies, and decision support systems. Genome-Phenome mapping can be very helpful in studying genotype-phenotype correlation and in determining the presence of gene variants in asymptomatic family members. In summary, with the recent breakthroughs in rare monogenic immune dysregulatory disorders, there have been renaissance in the field of immune dysregulation. Future clinical initiatives that incorporate NGS into medical care (NGS-based precision medicine), in addition to decision supporting systems, will help to shape the trajectory of broader incorporation. This will establish a firm foundation for investigating more complex immune disorders, and will facilitate the field of precision medicine in a world of bioinformatics paradigm. Given the rapid pace, all medical providers will have to keep a weather eye open for changes in this transformative field.