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- Schmit, Stephanie L, et al.
(author)
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Novel Common Genetic Susceptibility Loci for Colorectal Cancer.
- 2019
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 111:2, s. 146-157
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Journal article (peer-reviewed)abstract
- Background: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.Methods: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.Results: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.Conclusions: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.
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- Huyghe, Jeroen R., et al.
(author)
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Discovery of common and rare genetic risk variants for colorectal cancer
- 2019
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:1, s. 76-
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Journal article (peer-reviewed)abstract
- To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 x 10(-8), bringing the number of known independent signals for CRC to similar to 100. New signals implicate lower-frequency variants, Kruppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.
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- Bien, Stephanie A., et al.
(author)
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Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer
- 2019
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In: Human Genetics. - : Springer. - 0340-6717 .- 1432-1203. ; 138:4, s. 307-326
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Journal article (peer-reviewed)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 FDR0.2 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=2.2x10(-4), replication P=0.01), and PYGL (discovery P=2.3x10(-4), replication P=6.7x10(-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.
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- Gottschalk, L, et al.
(author)
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Scale aggregation - comparison of flux estimates from NOPEX
- 1999
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In: AGRICULTURAL AND FOREST METEOROLOGY. - : ELSEVIER SCIENCE BV. - 0168-1923. ; 98-9, s. 103-119
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Journal article (peer-reviewed)abstract
- The NOPEX two concentrated field efforts (CFEs) (June 1994 and April-July 1995) provide high quality data sets for the Boreal environment. The analysis of these data with traditional meteorological and hydrological approaches allow estimations of fluxes o
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| 9. |
- Kononoff, J, et al.
(author)
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Adolescent cannabinoid exposure induces irritability-like behavior and cocaine cross-sensitization without affecting the escalation of cocaine self-administration in adulthood
- 2018
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1, s. 13893-
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Journal article (peer-reviewed)abstract
- Cannabis use is typically initiated during adolescence and is a significant risk factor for the development of cocaine use in adulthood. However, no preclinical studies have examined the effects of adolescent cannabinoid exposure on cocaine dependence in adulthood using the escalation model of cocaine self-administration and the assessment of negative emotional states. In the present study, we found that exposure to the cannabinoid receptor agonist WIN55,212-2 (WIN) in adolescence produced irritability-like behavior and psychomotor cross-sensitization to cocaine in adolescence. In adulthood, rats were allowed to self-administer cocaine. The acquisition of cocaine self-administration was lower in rats with adolescent WIN exposure compared with controls. However, both WIN-exposed and control rats escalated their cocaine intake at the same rate, had similar responding under a progressive-ratio schedule of reinforcement, and had similar psychomotor responses to cocaine. Interestingly, the increase in irritability-like behavior that was previously observed in adolescence after WIN exposure persisted into adulthood. Whether the persisting increase in irritability-like behavior after WIN exposure has translational relevance remains to be studied. In summary, these results suggest that psychoactive cannabinoid exposure during adolescence is unlikely to have a major effect on the escalation of cocaine intake or the development of compulsive-like responding per se in adulthood in a rat model of cocaine self-administration. However, whether the persisting irritability-like behavior may predispose an individual to mood-related impairments in adulthood or predict such impairments warrants further investigation.
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| 10. |
- Kotelnikova, E, et al.
(author)
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Signaling networks in MS: a systems-based approach to developing new pharmacological therapies
- 2015
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In: Multiple sclerosis (Houndmills, Basingstoke, England). - : SAGE Publications. - 1477-0970 .- 1352-4585. ; 21:2, s. 138-146
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Journal article (peer-reviewed)abstract
- The pathogenesis of multiple sclerosis (MS) involves alterations to multiple pathways and processes, which represent a significant challenge for developing more-effective therapies. Systems biology approaches that study pathway dysregulation should offer benefits by integrating molecular networks and dynamic models with current biological knowledge for understanding disease heterogeneity and response to therapy. In MS, abnormalities have been identified in several cytokine-signaling pathways, as well as those of other immune receptors. Among the downstream molecules implicated are Jak/Stat, NF-Kb, ERK1/3, p38 or Jun/Fos. Together, these data suggest that MS is likely to be associated with abnormalities in apoptosis/cell death, microglia activation, blood-brain barrier functioning, immune responses, cytokine production, and/or oxidative stress, although which pathways contribute to the cascade of damage and can be modulated remains an open question. While current MS drugs target some of these pathways, others remain untouched. Here, we propose a pragmatic systems analysis approach that involves the large-scale extraction of processes and pathways relevant to MS. These data serve as a scaffold on which computational modeling can be performed to identify disease subgroups based on the contribution of different processes. Such an analysis, targeting these relevant MS-signaling pathways, offers the opportunity to accelerate the development of novel individual or combination therapies.
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