Evidence map›Paper›PMID 36061149›Full record

ReviewStem cells international2022

Human Brain Organoid: A Versatile Tool for Modeling Neurodegeneration Diseases and for Drug Screening.

Cuili Ma, Hwanwook Seong, Xiaowei Li, Xiao Yu, Shunliang Xu, Yujing Li

Abstract readReview
In one paragraph

Review in Stem cells international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Human brain organoids for understanding substance use disorders.Drug metabolism and pharmacokinetics · 2025
    Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Article
  10. In Vitro 3D Modeling of Neurodegenerative Diseases.Bioengineering (Basel, Switzerland) · 2023
    Review
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

6 authors.

Cuili MaDepartment of Internal Medicine, Qingdao Agricultural University Associated Hospital, Qingdao 266109, Shandong Province, China.
Hwanwook SeongDepartment of Human Genetics, Emory University School of Medicine, 615 Michael St, Atlanta, GA30322, USA.
Xiaowei LiSchool of Life Sciences, Nanjing University, 163 Xianlindadao Rd, Nanjing 210023, China.
Xiao YuDepartment of Neurology and Department of Nutrition, The Second Hospital Cheeloo College of Medicine, Shandong University, 247 Beiyuan Road, Jinan 250033, Shandong Province, China.
Shunliang XuDepartment of Neurology, The Second Hospital Cheeloo College of Medicine, Shandong University, 247 Beiyuan Road, Jinan 250033, Shandong Province, China.ORCID https://orcid.org/0000-0001-6516-723X
Yujing LiDepartment of Human Genetics, Emory University School of Medicine, 615 Michael St, Atlanta, GA30322, USA.ORCID https://orcid.org/0000-0002-4363-2484

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical trials serve as the fundamental prerequisite for clinical therapy of human disease, which is primarily based on biomedical studies in animal models. Undoubtedly, animal models have made a significant contribution to gaining insight into the developmental and pathophysiological understanding of human diseases. However, none of the existing animal models could efficiently simulate the development of human organs and systems due to a lack of spatial information; the discrepancy in genetic, anatomic, and physiological basis between animals and humans limits detailed investigation. Therefore, the translational efficiency of the research outcomes in clinical applications was significantly weakened, especially for some complex, chronic, and intractable diseases. For example, the clinical trials for human fragile X syndrome (FXS) solely based on animal models have failed such as mGluR5 antagonists. To mimic the development of human organs more faithfully and efficiently translate in vitro biomedical studies to clinical trials, extensive attention to organoids derived from stem cells contributes to a deeper understanding of this research. The organoids are a miniaturized version of an organ generated in vitro, partially recapitulating key features of human organ development. As such, the organoids open a novel avenue for in vitro models of human disease, advantageous over the existing animal models. The invention of organoids has brought an innovative breakthrough in regeneration medicine. The organoid-derived human tissues or organs could potentially function as invaluable platforms for biomedical studies, pathological investigation of human diseases, and drug screening. Importantly, the study of regeneration medicine and the development of therapeutic strategies for human diseases could be conducted in a dish, facilitating in vitro analysis and experimentation. Thus far, the pilot breakthrough has been made in the generation of numerous types of organoids representing different human organs. Most of these human organoids have been employed for in vitro biomedical study and drug screening. However, the efficiency and quality of the organoids in recapitulating the development of human organs have been hindered by engineering and conceptual challenges. The efficiency and quality of the organoids are essential for downstream applications. In this article, we highlight the application in the modeling of human neurodegenerative diseases (NDDs) such as FXS, Alzheimer's disease (AD), Parkinson's disease (PD), and autistic spectrum disorders (ASD), and organoid-based drug screening. Additionally, challenges and weaknesses especially for limits of the brain organoid models in modeling late onset NDDs such as AD and PD., and future perspectives regarding human brain organoids are addressed.

Identifiers

PMID36061149
PMCPMC9436613

What OpenQuestion holds

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Registered trials

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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.