Exciting progress in Amyotrophic Lateral Sclerosis (ALS) in the last few years has been made with the identification of new genetic causes of this disease. In addition, induced pluripotent cells (iPSC), which are adult somatic cells reprogrammed to a pluripotent stem cell-like state, can be derived from ALS patients and subsequently differentiated into the affected neurons and glia. Since the discovery of the first ALS gene 25 years ago and the creation of the first ALS mouse model, much has been learned about the disease. Yet despite these discoveries and critical research tools, truly effective therapies and good biomarkers absolutely required to make progress have not been forthcoming. It is clear that single research labs and simple animal models are not sufficient in finding the root cause of ALS in the vast majority of patients, identifying subtypes of disease and defining the pathophysiological pathways and drug targets along with highly relevant biomarkers. Only a large scale, concerted, and coordinated collaborative effort will make a difference in a timely manner. The proposed plan will bring together investigators across many disciplines needed to tackle ALS: iPSC technologies, cell biology, drug screening, genomics, proteomics, clinical observation, big data and machine learning. Of note, there is tremendous clinical heterogeneity within ALS, and there are many clinical forms fruste of ALS, and closely related neurodegenerative motor neuron diseases. Because the pathological relationship of these diseases is uncertain, this study will include ALS and related motor neuron diseases (MND). By creating a very large repository of iPSC, bio-fluid samples, gene sequencing, and carefully collected clinical phenotype information, this project will have a transformative effect on the landscape of ALS research. Until now, individual ALS researchers have labored to use small datasets to shed light on this uncommon disease and attempted to develop targeted therapies, often using rodent models– ultimately with slow progress, mixed results and little to change our clinical and therapeutic approach to the disease. Meanwhile, medical discoveries and drug development for common diseases, such as breast cancer, hypertension and hypercholesterolemia, have blossomed. One major driver of these successes in common disease is the access of researchers to true human samples of the disease as large datasets for biochemical molecular and clinical information. In aggregate, these large clinical population approaches along with real human tissue very effectively allows sub-grouping of patients to develop more effective therapies, to determine which drug should be used for which patient, to discover new drugs effective in patient subgroups (e.g. breast cancer), and to provide large sample repositories for use by academic institutions and companies worldwide. The extremely large data sets of relevant biological and clinical information and the human iPSC sample repository established by this project has the potential to move ALS discovery onto an even playing field with other far more common diseases. The unprecedented dataset generated from this approach will serve as foundation for academics and pharmaceutical companies to identify new ALS targets and candidate biomarkers. What has become clear is that the vast majority of ALS patients, those with sporadic disease, familial ALS, and related MND, have heterogeneity with regard to timing of disease onset, temporal disease progression, site of disease onset, and either a predominance o
|Effective start/end date||1/1/18 → 12/31/21|
- Johns Hopkins University (AGMT 5/8/18)
- Les Turner Amyotrophic Lateral Sclerosis Foundation, Ltd. (AGMT 5/8/18)
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