Dataset Information

Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.

ABSTRACT: Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics.

SUBMITTER: Baxi EG

PROVIDER: S-EPMC8825283 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.

Baxi Emily G EG Thompson Terri T Li Jonathan J Kaye Julia A JA Lim Ryan G RG Wu Jie J Ramamoorthy Divya D Lima Leandro L Vaibhav Vineet V Matlock Andrea A Frank Aaron A Coyne Alyssa N AN Landin Barry B Ornelas Loren L Mosmiller Elizabeth E Thrower Sara S Farr S Michelle SM Panther Lindsey L Gomez Emilda E Galvez Erick E Perez Daniel D Meepe Imara I Lei Susan S Mandefro Berhan B Trost Hannah H Pinedo Louis L Banuelos Maria G MG Liu Chunyan C Moran Ruby R Garcia Veronica V Workman Michael M Ho Richie R Wyman Stacia S Roggenbuck Jennifer J Harms Matthew B MB Stocksdale Jennifer J Miramontes Ricardo R Wang Keona K Venkatraman Vidya V Holewenski Ronald R Sundararaman Niveda N Pandey Rakhi R Manalo Danica-Mae DM Donde Aneesh A Huynh Nhan N Adam Miriam M Wassie Brook T BT Vertudes Edward E Amirani Naufa N Raja Krishna K Thomas Reuben R Hayes Lindsey L Lenail Alex A Cerezo Aianna A Luppino Sarah S Farrar Alanna A Pothier Lindsay L Prina Carolyn C Morgan Todd T Jamil Arish A Heintzman Sarah S Jockel-Balsarotti Jennifer J Karanja Elizabeth E Markway Jesse J McCallum Molly M Joslin Ben B Alibazoglu Deniz D Kolb Stephen S Ajroud-Driss Senda S Baloh Robert R Heitzman Daragh D Miller Tim T Glass Jonathan D JD Patel-Murray Natasha Leanna NL Yu Hong H Sinani Ervin E Vigneswaran Prasha P Sherman Alexander V AV Ahmad Omar O Roy Promit P Beavers Jay C JC Zeiler Steven S Krakauer John W JW Agurto Carla C Cecchi Guillermo G Bellard Mary M Raghav Yogindra Y Sachs Karen K Ehrenberger Tobias T Bruce Elizabeth E Cudkowicz Merit E ME Maragakis Nicholas N Norel Raquel R Van Eyk Jennifer E JE Finkbeiner Steven S Berry James J Sareen Dhruv D Thompson Leslie M LM Fraenkel Ernest E Svendsen Clive N CN Rothstein Jeffrey D JD

Nature neuroscience 20220203 2

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, includi ...[more]

PMID: 35115730

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Project description:Our understanding of Alzheimer's disease pathogenesis is currently limited by difficulties in obtaining live neurons from patients and the inability to model the sporadic form of the disease. It may be possible to overcome these challenges by reprogramming primary cells from patients into induced pluripotent stem cells (iPSCs). Here we reprogrammed primary fibroblasts from two patients with familial Alzheimer's disease, both caused by a duplication of the amyloid-? precursor protein gene (APP; termed APP(Dp)), two with sporadic Alzheimer's disease (termed sAD1, sAD2) and two non-demented control individuals into iPSC lines. Neurons from differentiated cultures were purified with fluorescence-activated cell sorting and characterized. Purified cultures contained more than 90% neurons, clustered with fetal brain messenger RNA samples by microarray criteria, and could form functional synaptic contacts. Virtually all cells exhibited normal electrophysiological activity. Relative to controls, iPSC-derived, purified neurons from the two APP(Dp) patients and patient sAD2 exhibited significantly higher levels of the pathological markers amyloid-?(1-40), phospho-tau(Thr?231) and active glycogen synthase kinase-3? (aGSK-3?). Neurons from APP(Dp) and sAD2 patients also accumulated large RAB5-positive early endosomes compared to controls. Treatment of purified neurons with ?-secretase inhibitors, but not ?-secretase inhibitors, caused significant reductions in phospho-Tau(Thr?231) and aGSK-3? levels. These results suggest a direct relationship between APP proteolytic processing, but not amyloid-?, in GSK-3? activation and tau phosphorylation in human neurons. Additionally, we observed that neurons with the genome of one sAD patient exhibited the phenotypes seen in familial Alzheimer's disease samples. More generally, we demonstrate that iPSC technology can be used to observe phenotypes relevant to Alzheimer's disease, even though it can take decades for overt disease to manifest in patients.

Dataset Information

Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.

Publications

Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.

Similar Datasets

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