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@ARTICLE{Bien:143007,
author = {S. A. Bien and Y.-R. Su and D. V. Conti and T. A. Harrison
and C. Qu and X. Guo and Y. Lu and D. Albanes and P. L. Auer
and B. L. Banbury and S. I. Berndt and S. Bézieau and H.
Brenner$^*$ and D. D. Buchanan and B. J. Caan and P. T.
Campbell and C. S. Carlson and A. T. Chan and J.
Chang-Claude$^*$ and S. Chen and C. M. Connolly and D. F.
Easton and E. J. M. Feskens and S. Gallinger and G. G. Giles
and M. J. Gunter and J. Hampe and J. R. Huyghe and M.
Hoffmeister$^*$ and T. J. Hudson and E. J. Jacobs and M. A.
Jenkins and E. Kampman and H. M. Kang and T. Kühn$^*$ and
S. Küry and F. Lejbkowicz and L. Le Marchand and R. L.
Milne and L. Li and C. I. Li and A. Lindblom and N. M.
Lindor and V. Martín and C. E. McNeil and M. Melas and V.
Moreno and P. A. Newcomb and K. Offit and P. D. P. Pharaoh
and J. D. Potter and C. Qu and E. Riboli and G. Rennert and
N. Sala and C. Schafmayer and P. C. Scacheri and S. L.
Schmit and G. Severi and M. L. Slattery and J. D. Smith and
A. Trichopoulou and R. Tumino and C. M. Ulrich and F. J. B.
van Duijnhoven and B. Van Guelpen and S. J. Weinstein and E.
White and A. Wolk and M. O. Woods and A. H. Wu and G. R.
Abecasis and G. Casey and D. A. Nickerson and S. B. Gruber
and L. Hsu and W. Zheng and U. Peters},
title = {{G}enetic variant predictors of gene expression provide new
insight into risk of colorectal cancer.},
journal = {Human genetics},
volume = {138},
number = {4},
issn = {1432-1203},
address = {Heidelberg},
publisher = {Springer},
reportid = {DKFZ-2019-00632},
pages = {307-326},
year = {2019},
note = {138(4):307-326},
abstract = {Genome-wide association studies have reported 56
independently associated colorectal cancer (CRC) risk
variants, most of which are non-coding and believed to exert
their effects by modulating gene expression. The
computational method PrediXcan uses cis-regulatory variant
predictors to impute expression and perform gene-level
association tests in GWAS without directly measured
transcriptomes. In this study, we used reference datasets
from colon (n = 169) and whole blood (n = 922)
transcriptomes to test CRC association with genetically
determined expression levels in a genome-wide analysis of
12,186 cases and 14,718 controls. Three novel associations
were discovered from colon transverse models at
FDR ≤ 0.2 and further evaluated in an independent
replication including 32,825 cases and 39,933 controls.
After adjusting for multiple comparisons, we found
statistically significant associations using colon
transcriptome models with TRIM4 (discovery
P = 2.2 × 10- 4, replication P = 0.01), and
PYGL (discovery P = 2.3 × 10- 4, replication
P = 6.7 × 10- 4). Interestingly, both genes
encode proteins that influence redox homeostasis and are
related to cellular metabolic reprogramming in tumors,
implicating a novel CRC pathway linked to cell growth and
proliferation. Defining CRC risk regions as one megabase up-
and downstream of one of the 56 independent risk variants,
we defined 44 non-overlapping CRC-risk regions. Among these
risk regions, we identified genes associated with CRC
(P < 0.05) in 34/44 CRC-risk regions. Importantly, CRC
association was found for two genes in the previously
reported 2q25 locus, CXCR1 and CXCR2, which are potential
cancer therapeutic targets. These findings provide strong
candidate genes to prioritize for subsequent laboratory
follow-up of GWAS loci. This study is the first to implement
PrediXcan in a large colorectal cancer study and findings
highlight the utility of integrating transcriptome data in
GWAS for discovery of, and biological insight into, risk
loci.},
cin = {C070 / C120 / C020 / L101},
ddc = {610},
cid = {I:(DE-He78)C070-20160331 / I:(DE-He78)C120-20160331 /
I:(DE-He78)C020-20160331 / I:(DE-He78)L101-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:30820706},
doi = {10.1007/s00439-019-01989-8},
url = {https://inrepo02.dkfz.de/record/143007},
}