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Center for Alzheimer’s and Related Dementias

Stimulating and Accelerating Alzheimer's and Related Dementias Research at NIH

Through the NIH Center for Alzheimer's and Related Dementias (CARD), researchers work across scientific domains and disease boundaries to bridge basic, preclinical, and clinical research with the goal of accelerating translational research on these devastating diseases.

Mission & Philosophy

CARD is a collaborative NIA/NINDS initiative that supports basic, translational, and clinical research on Alzheimer’s disease and related dementias. CARD’s central mission is to initiate, stimulate, accelerate, and support research that will lead to the development of improved treatments and preventions for these diseases.

Our vision is to stimulate and accelerate Alzheimer’s and related dementias research through a data-driven and collaborative approach that emphasizes robust, replicable findings and cooperative progress over individual success. CARD scientists engage and collaborate with researchers in government, academia, and industry to create foundational resources and expertise that add broad value to the Alzheimer’s and related dementias field. We work across scientific domains and disease boundaries to bridge basic, preclinical, and clinical research with the goal of accelerating translational research on these devastating diseases.

Our scientific themes include:

  • Molecular pathogenesis anchored in genetics
  • Disease subtyping, prediction, and progression
  • De-risking of Alzheimer's and related dementias therapeutic targets
  • Precision therapeutics

Our structural priorities include:

  • Diversity in research and researchers
  • Democratization of data
  • Transparency and reproducibility
  • Collaboration and cooperation
  • Foundational resource generation
  • Spanning the translational divide

About CARD

Oversight and Leadership

CARD is overseen by the center director, who provides scientific and administrative oversight to create and implement the long-term vision. The director reports to the CARD Leadership Board as well as NIA and NINDS leadership.

CARD Investigators

CARD investigators work on critical research projects or initiatives relevant to the CARD mission. These can be intramural investigators with a secondary or temporary appointment at CARD, or extramural or industry scientists with a visiting appointment at CARD.

Independent Research Scholars

Independent Research Scholars are early-stage research fellows with term-limited appointments at CARD. Fellows apply for the CARD Independent Research Scholars Program within the first 1 to 4 years of their postdoctoral fellowship and focus on Alzheimer’s and related dementias themes aligned with the CARD mission.

Expert Groups

CARD Expert Groups are collaboration-oriented cores and facilities that provide expertise to CARD investigators through their resources and skills. These groups assist in the execution of projects outside of the skill set of CARD investigators.

Training

Data Science Master’s Degree Fellowship

CARD has partnered with the NIH’s Foundation for Advanced Education in the Sciences (FAES) and the University of Maryland at Baltimore (UMBC) to offer a unique high-quality master’s level program to enable healthcare researchers to grow their data science skills. The CARD/FAES/UMBC program offers a virtual 30-credit Masters in Professional Studies (MPS) in Data Science with a focus on application to the biomedical and healthcare fields. With the creation of this program, our goal is to cultivate the next generation of data science and bioinformatics professionals at NIH.

This program is a non-thesis, 30-credit professional graduate degree that requires 30 credit hours. Each course typically carries 2-3 credits and requires approximately 3 hours of classes per week via internet-based class interaction and approximately 6 additional hours per week of study time. This degree program allows qualified students who take specified FAES Data Science and Bioinformatics courses to transfer up to 15 credits to UMBC’s Master’s of Professional Studies in Data Science. A minimum of 15 credits are required for UMBC. This master’s degree can be earned in 1-3 consecutive years.

Why enroll staff in this program?

Fellowship awardees will gain foundational knowledge in data analysis and management through collaborative online instruction and direct consultation with experts in the field. Fellows will also have the opportunity to utilize and refine the skills they learn by working with real data curated at CARD and its partner initiatives and ICs. However, the use of CARD data, or employment by CARD, is not required for participation.

Application process

All students must apply for evaluation through FAES and meet the graduate requirements through the regular admission process of UMBC and the MPS in Data Science. FAES’ application requirements will consist of student information, degree transcripts, curriculum vitae or resume and a statement of purpose. Admission decisions for the MPS are made by CARD/FAES/UMBC data science staff. The number of openings per academic year will be 12. In 2021, these will be spread across a staggered start in Spring (4 openings) and Fall (8 openings) semesters. Later cohorts will be launched in following Fall semesters through 2023.

Timeline

  • CARD/FAES Fall 2021 application deadline: May 25, 2021
  • UMBC Fall 2021 application deadline: June 7, 2021
  • Fellows’ Admission Notifications: no later than July 6, 2021
  • UMBC Fall 2021 Semester begins: August 31, 2021
  • FAES Fall 2021 Semester begins: August 30, 2021

Admission requirements

  • Bachelor’s degree in any subject with a GPA of 3.0 or higher, preferably in a computational or biomedical field
  • Prospective students must have completed at least one of the following undergraduate or graduate level courses, which can be substituted for equivalent professional experience of online training academies:
    • Statistics
    • Calculus
    • Programming
  • Online Application Form
  • Transcripts from each college/university attended (undergraduate and graduate)
  • CV or Resume
  • Statement of Purpose
  • GRE scores are not required for admission.

This unique partnership reduces costs and offers flexibility to qualified students. The per fellow cost to sponsors for the first cohort degree program is approximately $18,000.

Visit this FAES portal for the application and additional information.

Jobs

Check back here for CARD career opportunities.

Projects

iPSC Neurodegenerative Disease Initiative

Researchers have identified more than 50 regions of the genome (called loci) that contain variants that may increase risk for the disease. To develop effective treatments for Alzheimer’s and related dementias, we must identify how individual mutations impact cellular pathways and contribute to Alzheimer’s and related dementias pathology. However, this requires readily available, disease-relevant cellular models of Alzheimer’s and related dementias and phenotypic datasets of the effects of gene mutations on cellular pathways, which are not currently available in the field.

We will create a foundational repository of isogenic induced pluripotent stem cell (iPSC) lines using CRISPR/Cas9-based genetic engineering. Our target goals are 132 variants across 72 AD/ADRD genes, 8 of which are known AD-related genes, 15 are genes linked to Dementia with Lewy Bodies/Parkinson’s Disease, 28 genes are associated with Frontotemporal Dementia/Amyotrophic Lateral Sclerosis, and 21 are genes associated with other neurodegenerative disorders.

For each gene variant, we plan to engineer:

  • Heterozygous clones for the disease-associated single nucleotide variant
  • Homozygous clones for the disease-associated single nucleotide variant
  • Reverent clones
  • Gene knockout clones
  • Halotag knock-in clones

Each of these lines will undergo rigorous quality control and be made publicly available to the research community. These lines will be distributed by Jackson Laboratories with an anticipated distribution start date of June 2021.

The iNDI team includes:

  • Mark R. Cookson: principal investigator (NIA)
  • Michael Ward: principal investigator (NINDS)
  • Lirong Peng: scientist, informatics
  • Andy Qi: scientist, proteomics
  • Daniel Ramos: scientist, functional genomics
  • Erika Lara-Flores: scientist, cell culture and microscopy
  • Julia Stadler: technical laboratory manager
  • Luke Reilly: postbaccalaureate IRTA fellow
  • Kailyn Anderson: postbaccalaureate IRTA fellow

Contact: Caroline Pantazis, scientific project manager
Email Caroline Pantazis.

Data Science

Our data science team supported by researchers from Data Tecnica International builds innovative technology products to support CARD researchers and collaborators in their data science needs. This group prepares, analyzes, and interprets large, complex scientific data to eliminate barriers in data processing and accelerate research in Alzheimer's disease and related dementias and other neurodegenerative diseases (NDD). Through their work, this group aims to cultivate an open source / open science data ecosystem for CARD and the greater Alzheimer's disease and related dementias research community while helping to build a stronger, more diverse data science community at CARD and the broader NIH.

Several resources generated by the team include:

  • GenoML: A repository for democratized genomics and automated machine learning workflows.
  • Gravity: A collaborative efforts to bring together all available Alzheimer's disease and related dementias and NDD data silos with cloud-based computing power and secure, safe connections to harmonized data.
  • OmicSynth: Artificial intelligence-driven network models and causal inferences derived from diverse sets of summary statistics. Knowledge exploration and synthesis in Alzheimer's disease and related dementias multiomics.
  • Spectrum: A collaboration to build better data harmonization tools and more accurate representations of Alzheimer's disease and related dementias and NDD diagnoses. This work sees Alzheimer's disease and related dementias and NDD as a continuum, not discrete units.
  • CRISPRbrain: An open-science data commons for functional genomics screens in edited, differentiated human cell types, in collaboration with the Kampmann Lab at University of California-San Francisco.

The leadership of the data science team includes:

  • Mike Nalls: lead for general data science
  • Faraz Faghri: lead for computer science
  • Hirotaka Iwaki: lead for clinical-translational applications
  • Hampton Leonard: lead for collaborative research

Contact: Mike Nalls
Email Mike Nalls

Long-read Sequencing

To date, most large-scale genetic sequencing efforts for Alzheimer's disease and related dementias have been performed using short-read DNA sequencing. Although these approaches can identify single nucleotide changes and small indels, they are not optimized to identify large structural variations or repeat expansions. Furthermore, many areas of the genome cannot be accurately sequenced with this technology, like homologous elements, highly GC-rich regions, centromeric regions, and telomeres.

Long-read sequencing enables us to generate accurate genetic sequencing data for challenging genomic regions to identify structural variants driving Alzheimer's disease and related dementias pathology. A greater understanding of the genetic architecture of the Alzheimer's disease and related dementias genome will lead to further insight into the disease and pathway mechanisms underlying them and new potential therapeutic targets for these diseases.

With this research, we will build a public resource consisting of long-read genome sequencing data from a large number of confirmed people with Alzheimer's disease and related dementias and healthy individuals. We will make both the raw and processed data publicly available to the community, along with our analysis pipeline, algorithms, and optimized DNA isolation protocols.

The long-read sequencing team:

  • Adam Phillippy, NHGRI
  • Benedict Paten, UCSC
  • Bryan Traynor, NIA
  • Cornelis Blauwendraat, NIA
  • Fritz Sedlazeck, Baylor College of Medicine
  • Sonja Scholz, NINDS

AutoTAC

Through this project, CARD scientists aim to de-risk a therapeutic strategy for Alzheimer’s and related dementias through preclinical development in the NIH Intramural Research Program. One of the most rigorous neuroanatomical signatures of Alzheimer’s is the presence of intracellular Tau protein aggregates. These insoluble protein aggregates are susceptible to autophagic elimination. We have developed a strategy to engulf and eliminate these intracellular structures by targeting them for autophagic removal. Our goal is to use this strategy in collaboration with industry to develop therapeutic targets for protein clearance in neurodegenerative diseases.

The AutoTAC team:

  • Richard Youle: principal investigator (NINDS)
  • Chunxin Wang: staff scientist
  • Peng-peng Zhu: staff scientist
  • William Rosencrans: graduate student

Contact: Caroline Pantazis, scientific project manager
Email Caroline Pantazis

CARD News

Visit these announcements to learn more about CARD:

If you are a member of the media, please contact the NIA Office of Communications and Public Liaison or call (301) 496-1752 for more information about CARD.