Single-Cell Sequence Technology Used to Reveal Heterogeneity of Secondary Hyperparathyroidism

Active, not recruiting

• Conditions: Secondary Hyperparathyroidism
• Interventions: Other: Single-cell sequencing

• Registration Number: NCT06130683
• Lead Sponsor: China-Japan Friendship Hospital

Brief 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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2023-11-03
• Study Start: 2023-11-10
• Study First Submitted QC: 2023-11-12
• Study First Posted: 2023-11-14
• Status Verified: 2024-12
• Primary Completion: 2024-12-08
• Last Update Submitted: 2024-12-25
• Last Update Posted: 2024-12-27
• Study Completion: 2025-07-31

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 12

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

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Secondary Hyperparathyroidism	Single-cell sequencing	Patients who were diagnosed as secondary hyperparathyroidism
Normal group	Single-cell sequencing	Parathyroid tissue obtained incidentally during other neck surgeries, derived from people without parathyroid disease.
Primary Hyperparathyroidism	Single-cell sequencing	Patients who were diagnosed as primary hyperparathyroidism

Primary Outcome Measures

Name	Time	Method
Construct the single-cell atlas	One year	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.

Trial Locations

Locations (1)

China and Japan Friendship Hospital; 🇨🇳 Beijing, China