ArticleFrontiers in cell and developmental biology2021
Identifying Thyroid Carcinoma-Related Genes by Integrating GWAS and eQTL Data.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Biomarkers in Ataxia-Telangiectasia: a Systematic Review.Journal of neurology · 2025Pooled it
- Considering hormone-sensitive cancers as a single disease in the UK biobank reveals shared aetiology.Communications biology · 2022Article
- The Emerging Landscapes of Long Noncoding RNA in Thyroid Carcinoma: Biological Functions and Clinical Significance.Frontiers in oncology · 2021Review
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Thyroid carcinoma (TC) is the most common endocrine malignancy. The incidence rate of thyroid cancer has increased rapidly in recent years. The occurrence and development of thyroid cancers are highly related to the massive genetic and epigenetic changes. Therefore, it is essential to explore the mechanism of thyroid cancer pathogenesis. Genome-Wide Association Studies (GWAS) have been widely used in various diseases. Researchers have found multiple single nucleotide polymorphisms (SNPs) are significantly related to TC. However, the biological mechanism of these SNPs is still unknown. In this paper, we used one GWAS dataset and two eQTL datasets, and integrated GWAS with expression quantitative trait loci (eQTL) in both thyroid and blood to explore the mechanism of mutations and causal genes of thyroid cancer. Finally, we found rs1912998 regulates the expression of IGFALS (
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