Engineered 3D immuno-glial-neurovascular human miBrain model

A Alice E. Stanton (Koch Institute, Massachusetts Institute of Technology) A Adele Bubnys (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) E Emre Agbas (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) B Benjamin James (Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology) D Dong Shin Park (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) A Alan Jiang (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) R Rebecca L. Pinals (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) L Liwang Liu N Nhat Truong (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) A Anjanet Loon (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) C Colin Staab O Oyku Cerit (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) H Hsin-Lan Wen (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) D David Mankus (Koch Institute, Massachusetts Institute of Technology) M Margaret E. Bisher (Koch Institute, Massachusetts Institute of Technology) A Abigail K. R. Lytton-Jean (Koch Institute, Massachusetts Institute of Technology) M Manolis Kellis J Joel W. Blanchard (Picower Institute for Learning and Memory, Massachusetts Institute of Technology) R Robert Langer L Li-Huei Tsai

Abstract

Patient-specific, human-based cellular models integrating a biomimetic blood–brain barrier, immune, and myelinated neuron components are critically needed to enable accelerated, translationally relevant discovery of neurological disease mechanisms and interventions. To construct a human cell-based model that includes these features and all six major brain cell types needed to mimic disease and dissect pathological mechanisms, we have constructed, characterized, and utilized a multicellular integrated brain (miBrain) immuno-glial-neurovascular model by engineering a brain-inspired 3D hydrogel and identifying conditions to coculture these six brain cell types, all differentiated from patient induced pluripotent stem cells. miBrains recapitulate in vivo – like hallmarks inclusive of neuronal activity, functional connectivity, barrier function, myelin-producing oligodendrocyte engagement with neurons, multicellular interactions, and transcriptomic profiles. We implemented the model to study Alzheimer’s Disease pathologies associated with APOE4 genetic risk. APOE4 miBrains differentially exhibit amyloid aggregation, tau phosphorylation, and astrocytic glial fibrillary acidic protein. Unlike the coemergent fate specification of glia and neurons in other organoid approaches, miBrains integrate independently differentiated cell types, a feature we harnessed to identify that APOE4 in astrocytes promotes neuronal tau pathogenesis and dysregulation through crosstalk with microglia.

Article Details

Volume / Issue Vol. 122, Issue 42
Published October 21, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (20)

A

Alice E. Stanton

Koch Institute, Massachusetts Institute of Technology

A

Adele Bubnys

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

E

Emre Agbas

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

B

Benjamin James

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology

D

Dong Shin Park

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

A

Alan Jiang

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

R

Rebecca L. Pinals

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

L

Liwang Liu

N

Nhat Truong

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

A

Anjanet Loon

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

C

Colin Staab

O

Oyku Cerit

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

H

Hsin-Lan Wen

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

D

David Mankus

Koch Institute, Massachusetts Institute of Technology

M

Margaret E. Bisher

Koch Institute, Massachusetts Institute of Technology

A

Abigail K. R. Lytton-Jean

Koch Institute, Massachusetts Institute of Technology

M

Manolis Kellis

J

Joel W. Blanchard

Picower Institute for Learning and Memory, Massachusetts Institute of Technology

R

Robert Langer

L

Li-Huei Tsai