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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06130683
Other study ID # 2023-NHLHCRF-YYPPLC-ZR-08
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date November 8, 2023
Est. completion date July 31, 2025

Study information

Verified date February 2024
Source China-Japan Friendship Hospital
Contact Chunyu Li
Phone 86 18031662801
Email seonjuk@foxmail.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

This project intends to select cases that meet the research requirements, take secondary hyperparathyroidism, primary hyperparathyroidism and normal human parathyroid tissue, a total of three groups, 4 cases in each group, through the method of single-cell transcription and sequencing, construct a map of human parathyroid function types, reveal the gene structure and gene expression status of cells, and visualize the expression characteristics, intercellular heterogeneity, and heterogeneity of cell subsets of secondary hyperparathyroid cells in a hierarchical manner, draw a single-cell map, and compare the differences between groups. To explore the pathogenesis of secondary hyperparathyroidism. Secondary hyperparathyroidism, parathyroid tissue of primary hyperparathyroidism and normal parathyroid tissue obtained by accident were collected, frozen and preserved, frozen tissue thawed, single-cell suspension was prepared and each cell was specifically labeled by the Mozhuo Genomics system, after oil breaking, polymerase chain reaction amplification, reverse transcription to obtain complementary DNA, and a library of complementary DNA that passed quality inspection was constructed to obtain high-quality data of parathyroid cells. Cell Ranger, R Seurat package, and t-SNE dimensionality reduction diagram were used to reduce the dimensionality, cluster, and visualize the data. In order to construct a single-cell atlas of parathyroid glands, investigators performed cluster analysis of similar cells according to the gene expression profile, and then visualized the data by t-SNE. According to the results of cell clustering, the specific and highly expressed genes in each cell cluster were identified. Cell populations were identified according to the expression of landmark genes, and the differences in cell types and proportions between groups were compared.


Recruitment information / eligibility

Status Recruiting
Enrollment 12
Est. completion date July 31, 2025
Est. primary completion date November 8, 2024
Accepts healthy volunteers No
Gender All
Age group 18 Years to 80 Years
Eligibility Inclusion Criteria: - Study participants with a diagnosis of secondary hyperparathyroidism who underwent surgical treatment - Study participants with a diagnosis of primary hyperparathyroidism who underwent surgical treatment - Study participants who have obtained informed consent Exclusion Criteria: - Other non-secondary hyperparathyroidism conditions such as primary hyperparathyroidism were excluded at the time of inclusion of study participants with essential hyperparathyroidism. - Other non-primary hyperparathyroid conditions such as secondary hyperparathyroidism were excluded at the time of inclusion of study participants with essential hyperparathyroidism. - Refusal of informed consent.

Study Design


Intervention

Other:
Single-cell sequencing
Single-cell sequencing technology can reveal the gene structure and gene expression status of individual cells, reflecting the heterogeneity between cells.

Locations

Country Name City State
China China and Japan Friendship Hospital Beijing

Sponsors (1)

Lead Sponsor Collaborator
China-Japan Friendship Hospital

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Construct the single-cell atlas A single-cell atlas of normal parathyroid, primary hyperparathyroidism, and secondary hyperparathyroidism was constructed.
Differential analysis is performed to explore differences in gene expression. Next step is to perform kegg and analyze the pathway information. Cell populations are used to explore changes in cell state during population progression. Quasi-temporal analysis is designed to delineate the dynamic trajectory of cell differentiation and the dynamic process of gene expression. SCENIC is a network for inferring gene co-expression.
Investigators will use software such as CellRanger and the Seurat package in R word to implement this.
One year
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