인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The tumour immune microenvironment (TIME) is critical for lymphoma progression and therapy resistance, yet causal relationships between specific immune cell types and lymphoma subtypes remain poorly defined. In this study, using bidirectional Mendelian randomization (MR), genetic correlation (LDSC), and expression-QTL integration (SMR), we systematically evaluated causal relationships and genetic correlation between immune cells and various lymphomas. Additionally, we utilised the Mendelian randomization-based method of summary data-based MR (SMR), which incorporated genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) data from immune cells to identify genes associated with lymphoma. Furthermore, colocalization analysis and genetic correlation analysis were conducted for further validation of our findings. The two-sample mendelian randomization approach was employed to identify the immune cell types that exhibit a causal relationship with different lymphomas. Additionally, the genetic correlation between these immune cells and lymphomas was further analysed using the linked disequilibrium score regression method, thereby enhancing the reliability of our findings. The SMR and colocalisation analyses revealed several genes associated with these immune cells, thereby providing additional support for their putative role in the pathogenesis of lymphoma. Our study elucidates the intricate interplay between immune cells by employing genetic methodologies, thus suggesting novel therapeutic candidates that warrant experimental validation and risk predictors in different subtypes of lymphoma treatments.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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