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Important Datasets on Adverse Reactions

Shraddha Dumawat, Deepthi Das
January 20, 2023

An adverse reaction can be defined as an undesired effect of a drug or other type of treatment, such as surgery. The Thalidomide tragedy is a classic example of the same. You can read about it here-


Even though much focus and attention has gone into verifying adverse reactions, more recent examples like-

  • Serious heart rhythm problems in Covid -19 patients treated with chloroquine/ hydroxychloroquine- particularly when taken at high doses or in combination with the antibiotic azithromycin.
  • Perforation of the uterus and/or fallopian tubes, migration of inserts to the abdominal or pelvic cavity, persistent pain and suspected allergic or hypersensitivity reactions in women using Essure, a permanent contraception device.  

-show that we are far from solving this problem. A significant roadblock comes in the form of finding available relevant data and connecting the dots between the disease, drugs, drug interactions and long-term/short-term adverse effects.

Where to Find Datasets on Adverse Reactions?

Research data on adverse reactions can be found in publications, and repositories like GEO, TCGA, etc. It is mostly present as part of the information about the patient sample and might be scattered across the publication or metadata. Here, we present two important datasets that can help find adverse reactions of various drugs on neonatal outcomes and in children. A user can explore many more such curated datasets using Polly, which streamlines the data findability by standardizing the data, harmonizing the metadata, and using knowledge graphs to make context-driven connections between the data. This allows one to find relevant datasets even if the details about adverse reactions are present in the data description text or as a character column in a data table.


Dataset ID: GSE145357_GPL23479_raw
Source: GEO
Data type: RNA-Seq
Published on: Jun 04, 2020
Article: Regulatory T Cells Play a Central Role in a Subset of Idiopathic Preterm Birth and Adverse Neonatal Outcomes

Researchers can utilize the following study as a benchmark for checking Treg depletory drugs.  

Regulatory T cells (Tregs) have been exhaustively investigated during early pregnancy; however, their role later in gestation is poorly understood. This study reports that functional Tregs are reduced at the maternal-fetal interface in a subset of women with idiopathic preterm labor/birth (PTB), which is accompanied by a concomitant increase in Tc17 cells. In mice, depletion of functional Tregs during late gestation induced PTB and adverse neonatal outcomes, which were rescued by the adoptive transfer of such cells. Treg depletion did not alter obstetrical parameters in the mother; yet, it increased susceptibility to endotoxin-induced PTB. The mechanisms whereby the loss of Tregs induces adverse perinatal outcomes involved tissue-specific immune responses and mild systemic maternal inflammation together with dysregulation of developmental and cellular processes in the placenta, in the absence of intra-amniotic inflammation. These findings provide mechanistic evidence supporting a central role for Tregs in the pathophysiology of idiopathic PTB and adverse neonatal outcomes.

Sample distribution - A partial Treg depletory agent (diphtheria toxin) was used in the study
PCA plot shows a good correlation (80.24%) between PBS (control) and treated cells.

Language Development Disorders

Dataset ID: GSE171566_GPL11154_raw
Source: GEO, RNA-Seq
Published on: Feb 23, 2022
Article: From cohorts to molecules: adverse impacts of endocrine disrupting mixtures.

Convergent evidence associates exposure to endocrine-disrupting chemicals (EDCs) with major human diseases, even at regulation-compliant concentrations. This might be because humans are exposed to EDC mixtures, whereas chemical regulation is based on a risk assessment of individual compounds. Here, the authors developed a mixture-centered risk assessment strategy that integrates epidemiological and experimental evidence. They identified that exposure to an EDC mixture in early pregnancy is associated with language delay in offspring.  

At human-relevant concentrations, this mixture disrupted hormone-regulated and disease-relevant regulatory networks in human brain organoids and in the model organisms Xenopus leavis and Danio rerio, as well as behavioral responses. In human fetal primary neural stem cells and three-dimensional cortical brain organoids differentiated from human pluripotent stem cells, the transcriptomic analysis showed that the mix interferes with hormonal pathways and dysregulates the expression of genes and biological pathways that are causally linked to autism spectrum disorders.

Reinterrogating epidemiological data, the authors found that up to 54% of the children had prenatal exposures above experimentally derived levels of concern, reaching, for the upper decile compared with the lowest decile of exposure, a 3.3 times higher risk of language delay.

Sample distribution describes the source used and the mutation across the datasets. The drug used is that of bisphenol to understand the effect EDC
The PCA plot represents the group based on genetic modification, showcasing a significant difference in the samples
Differential expression plotted for CD4 for the mentioned groups and subgroups of the genetic mutation.

Polly allows complex queries and generates accurate search results on bulk and single-cell RNA-seq data because of its structured and harmonized repositories. Take a look at various python notebooks for examples of the consumption of your data here.

Connect with us to accelerate your journey of finding relevant biomedical datasets, creating cohorts, visualizing & analyzing the data, thereby deriving actionable insights and probable targets.

References :

  1. Gomez-Lopez N, Arenas-Hernandez M, Romero R, Miller D et al. Regulatory T Cells Play a Role in a Subset of Idiopathic Preterm Labor/Birth and Adverse Neonatal Outcomes. Cell Rep 2020 Jul 7;32(1):107874
  2. Caporale N, Leemans M, Birgersson L, Germain PL et al. From cohorts to molecules: Adverse impacts of endocrine disrupting mixtures. Science 2022 Feb 18;375(6582):eabe8244

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