Evidence map›Paper›PMID 34750588›Full record

ReviewNature reviews. Neurology2022

Dissecting the complexities of Alzheimer disease with in vitro models of the human brain.

Joel W Blanchard, Matheus B Victor, Li-Huei Tsai

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 72 citations in OpenAlex.

  1. Pooled it
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  17. Research on Alzheimer's Disease (AD) Involving the Use ofCentral nervous system agents in medicinal chemistry · 2025
    Review
  18. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Joel W Blanchard *Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Matheus B Victor *Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Li-Huei TsaiPicower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA. lhtsai@mit.edu.ORCID http://orcid.org/0000-0003-1262-0592
Massachusetts Institute of Technology · USBroad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer disease (AD) is the most prevalent type of dementia. It is marked by severe memory loss and cognitive decline, and currently has limited effective treatment options. Although individuals with AD have common neuropathological hallmarks, emerging data suggest that the disease has a complex polygenic aetiology, and more than 25 genetic loci have been linked to an elevated risk of AD and dementia. Nevertheless, our ability to decipher the cellular and molecular mechanisms that underlie genetic susceptibility to AD, and its progression and severity, remains limited. Here, we discuss ongoing efforts to leverage genomic data from patients using cellular reprogramming technologies to recapitulate complex brain systems and build in vitro discovery platforms. Much attention has already been given to methodologies to derive major brain cell types from pluripotent stem cells. We therefore focus on technologies that combine multiple cell types to recreate anatomical and physiological properties of human brain tissue in vitro. We discuss the advances in the field for modelling four domains that have come into view as key contributors to the pathogenesis of AD: the blood-brain barrier, myelination, neuroinflammation and neuronal circuits. We also highlight opportunities for the field to further interrogate the complex genetic and environmental factors of AD using in vitro models.

Indexed as

Models, AnatomicModels, NeurologicalAlzheimer DiseaseAnimalsBrainGenetic Predisposition to DiseaseHumans

Identifiers

PMID34750588
OpenAlexW3213357147

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.