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11.
  • Locke, Adam E, et al. (author)
  • Genetic studies of body mass index yield new insights for obesity biology.
  • 2015
  • In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
  • Journal article (peer-reviewed)abstract
    • Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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12.
  • Machiela, Mitchell J., et al. (author)
  • Characterization of Large Structural Genetic Mosaicism in Human Autosomes
  • 2015
  • In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 96:3, s. 487-497
  • Journal article (peer-reviewed)abstract
    • Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 x 3 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.
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13.
  • McKay, James D., et al. (author)
  • Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes
  • 2017
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 49:7, s. 1126-1132
  • Journal article (peer-reviewed)abstract
    • Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genomewide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.
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14.
  • Sampson, Joshua N., et al. (author)
  • Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
  • 2015
  • In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
  • Journal article (peer-reviewed)abstract
    • Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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15.
  • Shungin, Dmitry, et al. (author)
  • New genetic loci link adipose and insulin biology to body fat distribution.
  • 2015
  • In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
  • Journal article (peer-reviewed)abstract
    • Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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16.
  • Thomas, Minta, et al. (author)
  • Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations
  • 2023
  • In: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
  • Journal article (peer-reviewed)abstract
    • Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.
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17.
  • Zhang, Mingfeng, et al. (author)
  • Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21
  • 2016
  • In: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 7:41, s. 66328-66343
  • Journal article (peer-reviewed)abstract
    • Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10(-15)), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10(-9)) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10(-8)). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 (NR5A2), chr8q24.21 (MYC) and chr5p15.33 (CLPTM1L-TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal (n = 10) and tumor (n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10(-8)). This finding was validated in a second set of paired (n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10(-4)-2.0x10(-3)). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.
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18.
  • Ahn, Jiyoung, et al. (author)
  • Quantitative trait loci predicting circulating sex steroid hormones in men from the NCI-Breast and Prostate Cancer Cohort Consortium (BPC3).
  • 2009
  • In: Human molecular genetics. - : Oxford University Press (OUP). - 1460-2083 .- 0964-6906. ; 18:19, s. 3749-57
  • Journal article (peer-reviewed)abstract
    • Twin studies suggest a heritable component to circulating sex steroid hormones and sex hormone-binding globulin (SHBG). In the NCI-Breast and Prostate Cancer Cohort Consortium, 874 SNPs in 37 candidate genes in the sex steroid hormone pathway were examined in relation to circulating levels of SHBG (N = 4720), testosterone (N = 4678), 3 alpha-androstanediol-glucuronide (N = 4767) and 17beta-estradiol (N = 2014) in Caucasian men. rs1799941 in SHBG is highly significantly associated with circulating levels of SHBG (P = 4.52 x 10(-21)), consistent with previous studies, and testosterone (P = 7.54 x 10(-15)), with mean difference of 26.9 and 14.3%, respectively, comparing wild-type to homozygous variant carriers. Further noteworthy novel findings were observed between SNPs in ESR1 with testosterone levels (rs722208, mean difference = 8.8%, P = 7.37 x 10(-6)) and SRD5A2 with 3 alpha-androstanediol-glucuronide (rs2208532, mean difference = 11.8%, P = 1.82 x 10(-6)). Genetic variation in genes in the sex steroid hormone pathway is associated with differences in circulating SHBG and sex steroid hormones.
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19.
  • Barrdahl, Myrto, et al. (author)
  • Association of breast cancer risk loci with breast cancer survival
  • 2015
  • In: International Journal of Cancer. - : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 137:12, s. 2837-2845
  • Journal article (peer-reviewed)abstract
    • The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele=0.70; 95% CI: 0.58-0.85; ptrend=2.84 x 10-4; HRheterozygotes=0.71; 95% CI: 0.55-0.92; HRhomozygotes=0.48; 95% CI: 0.31-0.76; p2DF=1.45 x 10-3). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend=6.6 x 10-4; HRheterozygotes=0.96 95% CI: 0.90-1.03; HRhomozygotes=1.21; 95% CI: 1.09-1.35; p2DF=1.25 x 10-4). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.What's new? Genetic factors are known to influence the risk of breast cancer, but inherited genetic variation may also affect disease prognosis and response to treatment. In this study, the we investigated whether single nucleotide polymorphisms (SNPs) that are known to be associated with breast cancer risk might also influence the survival of breast-cancer patients. While two of the investigated SNPs may influence survival, there was otherwise no indication that SNP alleles related to breast cancer risk also play a role in the survival of breast cancer patients.
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20.
  • Barrdahl, Myrto, et al. (author)
  • Post-G WAS gene-environment interplay in breast cancer : results from the Breast and Prostate Cancer Cohort Consortium and a meta-analysis on 79 000 women
  • 2014
  • In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:19, s. 5260-5270
  • Journal article (peer-reviewed)abstract
    • We studied the interplay between 39 breast cancer (BC) risk SNPs and established BC risk (body mass index, height, age at menarche, parity, age at menopause, smoking, alcohol and family history of BC) and prognostic factors (TNM stage, tumor grade, tumor size, age at diagnosis, estrogen receptor status and progesterone receptor status) as joint determinants of BC risk. We used a nested case-control design within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), with 16 285 BC cases and 19 376 controls. We performed stratified analyses for both the risk and prognostic factors, testing for heterogeneity for the risk factors, and case-case comparisons for differential associations of polymorphisms by subgroups of the prognostic factors. We analyzed multiplicative interactions between the SNPs and the risk factors. Finally, we also performed a meta-analysis of the interaction ORs from BPC3 and the Breast Cancer Association Consortium. After correction for multiple testing, no significant interaction between the SNPs and the established risk factors in the BPC3 study was found. The meta-analysis showed a suggestive interaction between smoking status and SLC4A7-rs4973768 (P-interaction = 8.84 x 10(-4)) which, although not significant after considering multiple comparison, has a plausible biological explanation. In conclusion, in this study of up to almost 79 000 women we can conclusively exclude any novel major interactions between genome-wide association studies hits and the epidemiologic risk factors taken into consideration, but we propose a suggestive interaction between smoking status and SLC4A7-rs4973768 that if further replicated could help our understanding in the etiology of BC.
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  • Result 11-20 of 65
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