ReviewGenes2022
Human Induced Pluripotent Stem Cell Phenotyping and Preclinical Modeling of Familial Parkinson's Disease.
Review in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Advancements in differentiation of induced pluripotent stem cells into specialized neuronal subtypes.Neural regeneration research · 2026Article
- Mitochondrial Dysfunction as a Driver of Neurodegeneration in Parkinson's and Huntington's Disease: Molecular Insights and Emerging Interventions.Molecular neurobiology · 2026Review
- Preclinical models of stem cell-mediated analgesia and tissue repair: mechanisms, challenges, and future directions.Frontiers in cellular neuroscience · 2026Review
- Stem cells strike back: advancements in Alzheimer's and Parkinson's disease treatment and modeling efforts from 2019 to 2024.Journal of molecular medicine (Berlin, Germany) · 2025Review
- Preclinical biodistribution and safety evaluation of human iPSC-derived dopaminergic neural progenitor cells for Parkinson's disease.Frontiers in cell and developmental biology · 2025Article
- Clinical, mechanistic, biomarker, and therapeutic advances in GBA1-associated Parkinson's disease.Translational neurodegeneration · 2024Review
- Article
- Genetic Evidence for Endolysosomal Dysfunction in Parkinson's Disease: A Critical Overview.International journal of molecular sciences · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Parkinson's disease (PD) is primarily idiopathic and a highly heterogenous neurodegenerative disease with patients experiencing a wide array of motor and non-motor symptoms. A major challenge for understanding susceptibility to PD is to determine the genetic and environmental factors that influence the mechanisms underlying the variations in disease-associated traits. The pathological hallmark of PD is the degeneration of dopaminergic neurons in the substantia nigra pars compacta region of the brain and post-mortem Lewy pathology, which leads to the loss of projecting axons innervating the striatum and to impaired motor and cognitive functions. While the cause of PD is still largely unknown, genome-wide association studies provide evidence that numerous polymorphic variants in various genes contribute to sporadic PD, and 10 to 15% of all cases are linked to some form of hereditary mutations, either autosomal dominant or recessive. Among the most common mutations observed in PD patients are in the genes LRRK2, SNCA, GBA1, PINK1, PRKN, and PARK7/DJ-1. In this review, we cover these PD-related mutations, the use of induced pluripotent stem cells as a disease in a dish model, and genetic animal models to better understand the diversity in the pathogenesis and long-term outcomes seen in PD patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.