Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia

Spontaneous entry into an offline state during wakefulness: A mechanism of memory consolidation

This OSF publication contains open resources from the following publication: Wamsley, E. J., & Summer, T. (2020). Spontaneous Entry into an “Offline” State during Wakefulness: A Mechanism of Memory Consolidation? Journal of Cognitive Neuroscience, 1–21. Documentation of our methods, our primary data files, and analysis code are included. Disclaimer: We are attempting to follow the "just post it!" philosophy, not allowing perfectionism to prevent us from openly sharing our materials. As a result, I apologize that these materials may not be optimally curated, organized, and documented. I am happy to answer what questions I can ([email protected]), however, extensive technical support won't be possible given our limited resources. We hope that these materials may be useful despite this

Resting states and memory consolidation: A preregistered replication and meta-analysis

This OSF project contains the preregistration and study data associated with the following publication: Humiston, G., Tucker, M. A., Summer, T., & Wamsley, E. J. (2019). Resting States and Memory consolidation: A preregistered Replication and Meta-Analysis. Scientific Reports, 9(1), 1–9. Included in the files posted: 1. "Humiston 2019 OSF Repository.sav" is an SPSS file containing the data for the study. 2. "exclusion criteria final.sps" is an SPSS syntax file containing code to execute the participant exclusions as described in the manuscript and pre-registration. 3. "WRRR-Study_1_Manualv3.docx" is the procedures manual that research assistants used during data collection. 4. The preregistration can be found by clicking on "Registrations", above. Questions about these materials can be direct to [email protected]

Resting state EEG correlates of memory consolidation

This project archives methods and data for the study described in this manuscript: Brokaw, K., Tishler, W., Manceor, S., Hamilton, K., Gaulden, A., Parr, E., & Wamsley, E. J. (2016). Resting state EEG correlates of memory consolidation. Neurobiology of Learning and Memory, 130, 17–25. https://doi.org/10.1016/j.nlm.2016.01.008 The aim of this project was to determine the conditions under which memory is optimally enhanced across a short period of resting wakefulness. To accomplish this goal, we examined changes in memory across a brief interval filled with either quiet resting or active wakefulness, while brain activity was monitored using EEG

Data

SPSS format data file used for analysis

Participant Forms

Here we archive copies of questionnaires used in this research study

Modeling district heating and cooling systems with URBANopt, GeoJSON to Modelica Translator, and the Modelica Buildings Library

The URBANopt project has successfully leveraged OpenStudio/EnergyPlus to model buildings and electrical systems at an urban scale; however, URBANopt has lacked the ability to model district thermal energy systems until recently. This paper will present the modeling infrastructure that was developed specifically for the analysis of district heating and cooling systems, and how it is integrated into the existing URBANopt framework. The paper also discusses the development of new models added to the Modelica Buildings Library to model various district energy system components including loads, energy transfer stations (ETS), distribution networks, and central plants. The paper describes how different building loads can be modeled including time series, TEASER reduced-order models, or Spawn of EnergyPlus models. URBANopt District Energy Systems allows the user to switch between the various configurations