Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma

被引:1
|
作者
Dutta, Diptavo [2 ]
Guo, Xinyu [1 ]
Winter, Timothy D. [3 ]
Jahagirdar, Om [2 ]
Ha, Eunji [4 ]
Susztak, Katalin [4 ]
Machiela, Mitchell J. [2 ]
Chanock, Stephen J. [3 ]
Purdue, Mark P. [5 ]
机构
[1] Univ Southern Calif, Dept Quantitat & Computat Biol, Los Angeles, CA USA
[2] NCI, Integrat Tumor Epidemiol Branch, Div Canc Epidemiol & Genet, Rockville, MD 20850 USA
[3] NCI, Lab Genet Susceptibil, Div Canc Epidemiol & Genet, Rockville, MD USA
[4] Univ Penn, Perelman Sch Med, Delphia, PA USA
[5] NCI, Occupat & Environm Epidemiol Branch, Div Canc Epidemiol & Genet, Rockville, MD 20850 USA
基金
美国国家卫生研究院;
关键词
RISK; CAUCHY; ATLAS;
D O I
10.1016/j.ajhg.2024.07.012
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Univariate and Mmultivariate Proteome-wide Association Studies to Identify Causal Proteins for Alzheimer's Disease in the Presence of Invalid Instruments with GWAS Summary Data
    Fang, Lei
    Xue, Haoran
    Lin, Zhaotong
    Pan, Wei
    GENETIC EPIDEMIOLOGY, 2024, 48 (07) : 353 - 354
  • [42] Identification of Human Brain Proteins for Bitter-Sweet Taste Perception: A Joint Proteome-Wide and Transcriptome-Wide Association Study
    Wei, Wenming
    Cheng, Bolun
    He, Dan
    Zhao, Yijing
    Qin, Xiaoyue
    Cai, Qingqing
    Zhang, Na
    Chu, Xiaoge
    Shi, Sirong
    Zhang, Feng
    NUTRIENTS, 2022, 14 (10)
  • [43] Brain Proteome-Wide Association Study Identifies Candidate Genes that Regulate Protein Abundance Associated with Post-Traumatic Stress Disorder
    Zhang, Zhen
    Meng, Peilin
    Zhang, Huijie
    Jia, Yumeng
    Wen, Yan
    Zhang, Jingxi
    Chen, Yujing
    Li, Chun'e
    Pan, Chuyu
    Cheng, Shiqiang
    Yang, Xuena
    Yao, Yao
    Liu, Li
    Zhang, Feng
    GENES, 2022, 13 (08)
  • [44] Association of KRAS Mutation and Gene Pathways in Colorectal Carcinoma: A Transcriptome- and Methylome-Wide Study and Potential Implications for Therapy
    Jasmine, Farzana
    Almazan, Armando
    Khamkevych, Yuliia
    Bissonnette, Marc
    Ahsan, Habibul
    Kibriya, Muhammad G.
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2024, 25 (15)
  • [45] The application of an in-cell proteome-wide structural biology method to identify drug-induced interactome changes
    Jones, Lisa M.
    Mallis, Christopher S.
    BIOPHYSICAL JOURNAL, 2022, 121 (03) : 299A - 299A
  • [46] Multi-ancestry fine-mapping improves precision to identify causal genes in transcriptome-wide association studies
    Lu, Zeyun
    Gopalan, Shyamalika
    Yuan, Dong
    Conti, David, V
    Pasaniuc, Bogdan
    Gusev, Alexander
    Mancuso, Nicholas
    AMERICAN JOURNAL OF HUMAN GENETICS, 2022, 109 (08) : 1388 - 1404
  • [47] Accounting for nonlinear effects of gene expression identifies additional associated genes in transcriptome-wide association studies
    Lin, Zhaotong
    Xue, Haoran
    Malakhov, Mykhaylo M.
    Knutson, Katherine A.
    Pan, Wei
    HUMAN MOLECULAR GENETICS, 2022, 31 (14) : 2462 - 2470
  • [48] Identify clear cell renal cell carcinoma related genes by gene network
    Yan, Fangrong
    Wang, Yue
    Liu, Chunhui
    Zhao, Huiling
    Zhang, Liya
    Lu, Xiaofan
    Chen, Chen
    Wang, Yaoyan
    Lu, Tao
    Wang, Fei
    ONCOTARGET, 2017, 8 (66) : 110358 - 110366
  • [49] Transcriptome network analysis reveals candidate genes for renal cell carcinoma
    Zhai, Wei
    Xu, Yun-Fei
    Liu, Min
    Zheng, Jun-Hua
    JOURNAL OF CANCER RESEARCH AND THERAPEUTICS, 2012, 8 (01) : 28 - 33
  • [50] Identification of genes associated with testicular germ cell tumor susceptibility through a transcriptome-wide association study
    Ugalde-Morales, Emilio
    Wilf, Rona
    Pluta, John
    Ploner, Alexander
    Fan, Mengyao
    Damra, Mohammad
    Aben, Katja K.
    Anson-Cartwright, Lynn
    Chen, Chu
    Cortessis, Victoria K.
    Daneshmand, Siamak
    Ferlin, Alberto
    Gamulin, Marija
    Gietema, Jourik A.
    Gonzalez-Niera, Anna
    Grotmol, Tom
    Hamilton, Robert J.
    Harland, Mark
    Haugen, Trine B.
    Hauser, Russ
    Hildebrandt, Michelle A. T.
    Karlsson, Robert
    Kiemeney, Lambertus A.
    Kim, Jung
    Lessel, Davor
    Lothe, Ragnhild A.
    Loveday, Chey
    Chanock, Stephen J.
    Mcglynn, Katherine A.
    Meijer, Coby
    Nead, Kevin T.
    Nsengimana, Jeremie
    Popovic, Maja
    Rafnar, Thorunn
    Richiardi, Lorenzo
    Rocca, Maria S.
    Schwartz, Stephen M.
    Skotheim, Rolf I.
    Stefansson, Kari
    Stewart, Douglas R.
    Turnbull, Clare
    Vaughn, David J.
    Winge, Sofia B.
    Zheng, Tongzhang
    Monteiro, Alvaro N.
    Almstrup, Kristian
    Kanetsky, Peter A.
    Nathanson, Katherine L.
    Wiklund, Fredrik
    AMERICAN JOURNAL OF HUMAN GENETICS, 2025, 112 (03)