Circadian pathway genes in relation to glioma risk and outcome
Purpose: There is growing evidence that circadian disruption may alter risk and aggressiveness of cancer. We evaluated common genetic variants in the circadian gene pathway for associations with glioma risk and patient outcome in a US clinic-based case–control study. Methods: Subjects were genotyped...
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description | Purpose: There is growing evidence that circadian disruption may alter risk and aggressiveness of cancer. We evaluated common genetic variants in the circadian gene pathway for associations with glioma risk and patient outcome in a US clinic-based case–control study. Methods: Subjects were genotyped for 17 candidate single nucleotide polymorphisms in ARNTL, CRY1, CRY2, CSNK1E, KLHL30, NPAS2, PER1, PER3, CLOCK, and MYRIP. Unconditional logistic regression was used to estimate age and gender-adjusted odds ratios (OR) and 95 % confidence intervals (CI) for glioma risk under three inheritance models (additive, dominant, and recessive). Proportional hazards regression was used to estimate hazard ratios for glioma-related death among 441 patients with high-grade tumors. Survival associations were validated using The Cancer Genome Atlas (TCGA) dataset. Results: A variant in PER1 (rs2289591) was significantly associated with overall glioma risk (per variant allele OR 0.80; 95 % CI 0.66–0.97; ptrend = 0.027). The variant allele for CLOCK rs11133391 under a recessive model increased risk of oligodendroglioma (OR 2.41; 95 % CI 1.31–4.42; p = 0.005), though not other glioma subtypes (p for heterogeneity = 0.0033). The association remained significant after false discovery rate adjustment (p = 0.008). Differential associations by gender were observed for MYRIP rs6599077 and CSNK1E rs1534891 though differences were not significant after adjustment for multiple testing. No consistent mortality associations were identified. Several of the examined genes exhibited differential expression in glioblastoma multiforme versus normal brain in TCGA data (MYRIP, ARNTL, CRY1, KLHL30, PER1, CLOCK, and PER3), and expression of NPAS2 was significantly associated with a poor patient outcome in TCGA patients. Conclusion: This exploratory analysis provides some evidence supporting a role for circadian genes in the onset of glioma and possibly the outcome of glioma. |
doi_str_mv | 10.1007/s10552-013-0305-y |
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Burton ; Olson, Jeffrey J. ; Browning, James E. ; Monteiro, Alvaro N. ; Egan, Kathleen M.</creator><creatorcontrib>Madden, Melissa H. ; Anic, Gabriella M. ; Thompson, Reid C. ; Nabors, L. Burton ; Olson, Jeffrey J. ; Browning, James E. ; Monteiro, Alvaro N. ; Egan, Kathleen M.</creatorcontrib><description>Purpose: There is growing evidence that circadian disruption may alter risk and aggressiveness of cancer. We evaluated common genetic variants in the circadian gene pathway for associations with glioma risk and patient outcome in a US clinic-based case–control study. Methods: Subjects were genotyped for 17 candidate single nucleotide polymorphisms in ARNTL, CRY1, CRY2, CSNK1E, KLHL30, NPAS2, PER1, PER3, CLOCK, and MYRIP. Unconditional logistic regression was used to estimate age and gender-adjusted odds ratios (OR) and 95 % confidence intervals (CI) for glioma risk under three inheritance models (additive, dominant, and recessive). Proportional hazards regression was used to estimate hazard ratios for glioma-related death among 441 patients with high-grade tumors. Survival associations were validated using The Cancer Genome Atlas (TCGA) dataset. Results: A variant in PER1 (rs2289591) was significantly associated with overall glioma risk (per variant allele OR 0.80; 95 % CI 0.66–0.97; ptrend = 0.027). The variant allele for CLOCK rs11133391 under a recessive model increased risk of oligodendroglioma (OR 2.41; 95 % CI 1.31–4.42; p = 0.005), though not other glioma subtypes (p for heterogeneity = 0.0033). The association remained significant after false discovery rate adjustment (p = 0.008). Differential associations by gender were observed for MYRIP rs6599077 and CSNK1E rs1534891 though differences were not significant after adjustment for multiple testing. No consistent mortality associations were identified. Several of the examined genes exhibited differential expression in glioblastoma multiforme versus normal brain in TCGA data (MYRIP, ARNTL, CRY1, KLHL30, PER1, CLOCK, and PER3), and expression of NPAS2 was significantly associated with a poor patient outcome in TCGA patients. Conclusion: This exploratory analysis provides some evidence supporting a role for circadian genes in the onset of glioma and possibly the outcome of glioma.</description><identifier>ISSN: 0957-5243</identifier><identifier>EISSN: 1573-7225</identifier><identifier>DOI: 10.1007/s10552-013-0305-y</identifier><identifier>PMID: 24135790</identifier><identifier>CODEN: CCCNEN</identifier><language>eng</language><publisher>Dordrecht: Springer</publisher><subject>Adolescent ; Adult ; Aged ; Aged, 80 and over ; Alleles ; Apoptosis ; Biomedical and Life Sciences ; Biomedicine ; Brain cancer ; Breast cancer ; Cancer Research ; Case-Control Studies ; Cell cycle ; Circadian rhythm ; Circadian Rhythm - genetics ; Clinical outcomes ; Epidemiology ; Female ; Gene expression ; Genes ; Genomes ; Genomics ; Genotype ; Glioma ; Glioma - etiology ; Glioma - genetics ; Glioma - mortality ; Hematology ; Humans ; Male ; Middle Aged ; Mortality ; Oligodendroglioma ; Oncology ; Original Paper ; Patients ; Polymorphism, Single Nucleotide - genetics ; Prostate ; Proxy reporting ; Proxy statements ; Public Health ; Risk ; Tumors ; Young Adult</subject><ispartof>Cancer causes & control, 2014-01, Vol.25 (1), p.25-32</ispartof><rights>Springer Science+Business Media Dordrecht 2013</rights><rights>Springer Science+Business Media Dordrecht 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c525t-ceecb797b11356aa10f437d1d978b364f3d85a89302c0327789db147399a76353</citedby><cites>FETCH-LOGICAL-c525t-ceecb797b11356aa10f437d1d978b364f3d85a89302c0327789db147399a76353</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/24717126$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/24717126$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,780,784,803,885,27924,27925,41488,42557,51319,58017,58250</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24135790$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Madden, Melissa H.</creatorcontrib><creatorcontrib>Anic, Gabriella M.</creatorcontrib><creatorcontrib>Thompson, Reid C.</creatorcontrib><creatorcontrib>Nabors, L. Burton</creatorcontrib><creatorcontrib>Olson, Jeffrey J.</creatorcontrib><creatorcontrib>Browning, James E.</creatorcontrib><creatorcontrib>Monteiro, Alvaro N.</creatorcontrib><creatorcontrib>Egan, Kathleen M.</creatorcontrib><title>Circadian pathway genes in relation to glioma risk and outcome</title><title>Cancer causes & control</title><addtitle>Cancer Causes Control</addtitle><addtitle>Cancer Causes Control</addtitle><description>Purpose: There is growing evidence that circadian disruption may alter risk and aggressiveness of cancer. We evaluated common genetic variants in the circadian gene pathway for associations with glioma risk and patient outcome in a US clinic-based case–control study. Methods: Subjects were genotyped for 17 candidate single nucleotide polymorphisms in ARNTL, CRY1, CRY2, CSNK1E, KLHL30, NPAS2, PER1, PER3, CLOCK, and MYRIP. Unconditional logistic regression was used to estimate age and gender-adjusted odds ratios (OR) and 95 % confidence intervals (CI) for glioma risk under three inheritance models (additive, dominant, and recessive). Proportional hazards regression was used to estimate hazard ratios for glioma-related death among 441 patients with high-grade tumors. Survival associations were validated using The Cancer Genome Atlas (TCGA) dataset. Results: A variant in PER1 (rs2289591) was significantly associated with overall glioma risk (per variant allele OR 0.80; 95 % CI 0.66–0.97; ptrend = 0.027). The variant allele for CLOCK rs11133391 under a recessive model increased risk of oligodendroglioma (OR 2.41; 95 % CI 1.31–4.42; p = 0.005), though not other glioma subtypes (p for heterogeneity = 0.0033). The association remained significant after false discovery rate adjustment (p = 0.008). Differential associations by gender were observed for MYRIP rs6599077 and CSNK1E rs1534891 though differences were not significant after adjustment for multiple testing. No consistent mortality associations were identified. Several of the examined genes exhibited differential expression in glioblastoma multiforme versus normal brain in TCGA data (MYRIP, ARNTL, CRY1, KLHL30, PER1, CLOCK, and PER3), and expression of NPAS2 was significantly associated with a poor patient outcome in TCGA patients. Conclusion: This exploratory analysis provides some evidence supporting a role for circadian genes in the onset of glioma and possibly the outcome of glioma.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Alleles</subject><subject>Apoptosis</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Brain cancer</subject><subject>Breast cancer</subject><subject>Cancer Research</subject><subject>Case-Control Studies</subject><subject>Cell cycle</subject><subject>Circadian rhythm</subject><subject>Circadian Rhythm - genetics</subject><subject>Clinical outcomes</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotype</subject><subject>Glioma</subject><subject>Glioma - etiology</subject><subject>Glioma - genetics</subject><subject>Glioma - mortality</subject><subject>Hematology</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Oligodendroglioma</subject><subject>Oncology</subject><subject>Original Paper</subject><subject>Patients</subject><subject>Polymorphism, Single Nucleotide - genetics</subject><subject>Prostate</subject><subject>Proxy reporting</subject><subject>Proxy statements</subject><subject>Public Health</subject><subject>Risk</subject><subject>Tumors</subject><subject>Young Adult</subject><issn>0957-5243</issn><issn>1573-7225</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNqFkcFu1DAQhi1ERZfCA3AAWeqll5SxHWfiSyW0ooBUiQucLcfxbr0k9mInVPv2uKRUCwc4-TDffOOZn5BXDC4ZAL7NDKTkFTBRgQBZHZ6QFZMoKuRcPiUrUBIryWtxSp7nvAMA2XB4Rk55zYREBStytfbJmt6bQPdmur0zB7p1wWXqA01uMJOPgU6RbgcfR0OTz9-oCT2N82Tj6F6Qk40Zsnv58J6Rr9fvv6w_VjefP3xav7uprORyqqxztkOFHStzG2MYbGqBPesVtp1o6o3oW2laJYBbEByxVX3HahRKGWyEFGfkavHu5250vXVhSmbQ--RHkw46Gq__rAR_q7fxhxaqWFhbBBcPghS_zy5PevTZumEwwcU5ayZF3XLFG_F_tFaAIJpf6Plf6C7OKZRLFApryZuSRqHYQtkUc05u8_hvBvo-SL0EqUuQ-j5IfSg9b44Xfuz4nVwB-ALkUgpbl45G_8P6emna5SmmIykyZGX3n_GvsP4</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Madden, Melissa H.</creator><creator>Anic, Gabriella M.</creator><creator>Thompson, Reid C.</creator><creator>Nabors, L. 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Burton</creatorcontrib><creatorcontrib>Olson, Jeffrey J.</creatorcontrib><creatorcontrib>Browning, James E.</creatorcontrib><creatorcontrib>Monteiro, Alvaro N.</creatorcontrib><creatorcontrib>Egan, Kathleen M.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancer causes & control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Madden, Melissa H.</au><au>Anic, Gabriella M.</au><au>Thompson, Reid C.</au><au>Nabors, L. Burton</au><au>Olson, Jeffrey J.</au><au>Browning, James E.</au><au>Monteiro, Alvaro N.</au><au>Egan, Kathleen M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Circadian pathway genes in relation to glioma risk and outcome</atitle><jtitle>Cancer causes & control</jtitle><stitle>Cancer Causes Control</stitle><addtitle>Cancer Causes Control</addtitle><date>2014-01-01</date><risdate>2014</risdate><volume>25</volume><issue>1</issue><spage>25</spage><epage>32</epage><pages>25-32</pages><issn>0957-5243</issn><eissn>1573-7225</eissn><coden>CCCNEN</coden><abstract>Purpose: There is growing evidence that circadian disruption may alter risk and aggressiveness of cancer. We evaluated common genetic variants in the circadian gene pathway for associations with glioma risk and patient outcome in a US clinic-based case–control study. Methods: Subjects were genotyped for 17 candidate single nucleotide polymorphisms in ARNTL, CRY1, CRY2, CSNK1E, KLHL30, NPAS2, PER1, PER3, CLOCK, and MYRIP. Unconditional logistic regression was used to estimate age and gender-adjusted odds ratios (OR) and 95 % confidence intervals (CI) for glioma risk under three inheritance models (additive, dominant, and recessive). Proportional hazards regression was used to estimate hazard ratios for glioma-related death among 441 patients with high-grade tumors. Survival associations were validated using The Cancer Genome Atlas (TCGA) dataset. Results: A variant in PER1 (rs2289591) was significantly associated with overall glioma risk (per variant allele OR 0.80; 95 % CI 0.66–0.97; ptrend = 0.027). The variant allele for CLOCK rs11133391 under a recessive model increased risk of oligodendroglioma (OR 2.41; 95 % CI 1.31–4.42; p = 0.005), though not other glioma subtypes (p for heterogeneity = 0.0033). The association remained significant after false discovery rate adjustment (p = 0.008). Differential associations by gender were observed for MYRIP rs6599077 and CSNK1E rs1534891 though differences were not significant after adjustment for multiple testing. No consistent mortality associations were identified. Several of the examined genes exhibited differential expression in glioblastoma multiforme versus normal brain in TCGA data (MYRIP, ARNTL, CRY1, KLHL30, PER1, CLOCK, and PER3), and expression of NPAS2 was significantly associated with a poor patient outcome in TCGA patients. Conclusion: This exploratory analysis provides some evidence supporting a role for circadian genes in the onset of glioma and possibly the outcome of glioma.</abstract><cop>Dordrecht</cop><pub>Springer</pub><pmid>24135790</pmid><doi>10.1007/s10552-013-0305-y</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Aged Aged, 80 and over Alleles Apoptosis Biomedical and Life Sciences Biomedicine Brain cancer Breast cancer Cancer Research Case-Control Studies Cell cycle Circadian rhythm Circadian Rhythm - genetics Clinical outcomes Epidemiology Female Gene expression Genes Genomes Genomics Genotype Glioma Glioma - etiology Glioma - genetics Glioma - mortality Hematology Humans Male Middle Aged Mortality Oligodendroglioma Oncology Original Paper Patients Polymorphism, Single Nucleotide - genetics Prostate Proxy reporting Proxy statements Public Health Risk Tumors Young Adult |
title | Circadian pathway genes in relation to glioma risk and outcome |
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