Displaying publications 81 - 100 of 112 in total

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  1. Barnes DR, Rookus MA, McGuffog L, Leslie G, Mooij TM, Dennis J, et al.
    Genet Med, 2020 10;22(10):1653-1666.
    PMID: 32665703 DOI: 10.1038/s41436-020-0862-x
    PURPOSE: We assessed the associations between population-based polygenic risk scores (PRS) for breast (BC) or epithelial ovarian cancer (EOC) with cancer risks for BRCA1 and BRCA2 pathogenic variant carriers.

    METHODS: Retrospective cohort data on 18,935 BRCA1 and 12,339 BRCA2 female pathogenic variant carriers of European ancestry were available. Three versions of a 313 single-nucleotide polymorphism (SNP) BC PRS were evaluated based on whether they predict overall, estrogen receptor (ER)-negative, or ER-positive BC, and two PRS for overall or high-grade serous EOC. Associations were validated in a prospective cohort.

    RESULTS: The ER-negative PRS showed the strongest association with BC risk for BRCA1 carriers (hazard ratio [HR] per standard deviation = 1.29 [95% CI 1.25-1.33], P = 3×10-72). For BRCA2, the strongest association was with overall BC PRS (HR = 1.31 [95% CI 1.27-1.36], P = 7×10-50). HR estimates decreased significantly with age and there was evidence for differences in associations by predicted variant effects on protein expression. The HR estimates were smaller than general population estimates. The high-grade serous PRS yielded the strongest associations with EOC risk for BRCA1 (HR = 1.32 [95% CI 1.25-1.40], P = 3×10-22) and BRCA2 (HR = 1.44 [95% CI 1.30-1.60], P = 4×10-12) carriers. The associations in the prospective cohort were similar.

    CONCLUSION: Population-based PRS are strongly associated with BC and EOC risks for BRCA1/2 carriers and predict substantial absolute risk differences for women at PRS distribution extremes.

  2. Breast Cancer Association Consortium, Dorling L, Carvalho S, Allen J, González-Neira A, Luccarini C, et al.
    N Engl J Med, 2021 02 04;384(5):428-439.
    PMID: 33471991 DOI: 10.1056/NEJMoa1913948
    BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

    METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

    RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

    CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

  3. Baxter JS, Johnson N, Tomczyk K, Gillespie A, Maguire S, Brough R, et al.
    Am J Hum Genet, 2021 Jul 01;108(7):1190-1203.
    PMID: 34146516 DOI: 10.1016/j.ajhg.2021.05.013
    A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).
  4. Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, et al.
    Cancer Discov, 2016 Sep;6(9):1052-67.
    PMID: 27432226 DOI: 10.1158/2159-8290.CD-15-1227
    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.

    SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

  5. Zeng C, Guo X, Long J, Kuchenbaecker KB, Droit A, Michailidou K, et al.
    Breast Cancer Res, 2016 06 21;18(1):64.
    PMID: 27459855 DOI: 10.1186/s13058-016-0718-0
    BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk.

    METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation.

    RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P 

  6. Ghoussaini M, Edwards SL, Michailidou K, Nord S, Cowper-Sal Lari R, Desai K, et al.
    Nat Commun, 2014 Sep 23;4:4999.
    PMID: 25248036 DOI: 10.1038/ncomms5999
    GWAS have identified a breast cancer susceptibility locus on 2q35. Here we report the fine mapping of this locus using data from 101,943 subjects from 50 case-control studies. We genotype 276 SNPs using the 'iCOGS' genotyping array and impute genotypes for a further 1,284 using 1000 Genomes Project data. All but two, strongly correlated SNPs (rs4442975 G/T and rs6721996 G/A) are excluded as candidate causal variants at odds against >100:1. The best functional candidate, rs4442975, is associated with oestrogen receptor positive (ER+) disease with an odds ratio (OR) in Europeans of 0.85 (95% confidence interval=0.84-0.87; P=1.7 × 10(-43)) per t-allele. This SNP flanks a transcriptional enhancer that physically interacts with the promoter of IGFBP5 (encoding insulin-like growth factor-binding protein 5) and displays allele-specific gene expression, FOXA1 binding and chromatin looping. Evidence suggests that the g-allele confers increased breast cancer susceptibility through relative downregulation of IGFBP5, a gene with known roles in breast cell biology.
  7. Glubb DM, Maranian MJ, Michailidou K, Pooley KA, Meyer KB, Kar S, et al.
    Am J Hum Genet, 2015 Jan 08;96(1):5-20.
    PMID: 25529635 DOI: 10.1016/j.ajhg.2014.11.009
    Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival.
  8. Orr N, Dudbridge F, Dryden N, Maguire S, Novo D, Perrakis E, et al.
    Hum Mol Genet, 2015 May 15;24(10):2966-84.
    PMID: 25652398 DOI: 10.1093/hmg/ddv035
    We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.
  9. Lin WY, Camp NJ, Ghoussaini M, Beesley J, Michailidou K, Hopper JL, et al.
    Hum Mol Genet, 2015 Jan 01;24(1):285-98.
    PMID: 25168388 DOI: 10.1093/hmg/ddu431
    Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.
  10. Johnson N, Dudbridge F, Orr N, Gibson L, Jones ME, Schoemaker MJ, et al.
    Breast Cancer Res, 2014 May 26;16(3):R51.
    PMID: 24887515 DOI: 10.1186/bcr3662
    INTRODUCTION: We have previously shown that a tag single nucleotide polymorphism (rs10235235), which maps to the CYP3A locus (7q22.1), was associated with a reduction in premenopausal urinary estrone glucuronide levels and a modest reduction in risk of breast cancer in women age ≤50 years.

    METHODS: We further investigated the association of rs10235235 with breast cancer risk in a large case control study of 47,346 cases and 47,570 controls from 52 studies participating in the Breast Cancer Association Consortium. Genotyping of rs10235235 was conducted using a custom Illumina Infinium array. Stratified analyses were conducted to determine whether this association was modified by age at diagnosis, ethnicity, age at menarche or tumor characteristics.

    RESULTS: We confirmed the association of rs10235235 with breast cancer risk for women of European ancestry but found no evidence that this association differed with age at diagnosis. Heterozygote and homozygote odds ratios (ORs) were OR = 0.98 (95% CI 0.94, 1.01; P = 0.2) and OR = 0.80 (95% CI 0.69, 0.93; P = 0.004), respectively (P(trend) = 0.02). There was no evidence of effect modification by tumor characteristics. rs10235235 was, however, associated with age at menarche in controls (P(trend) = 0.005) but not cases (P(trend) = 0.97). Consequently the association between rs10235235 and breast cancer risk differed according to age at menarche (P(het) = 0.02); the rare allele of rs10235235 was associated with a reduction in breast cancer risk for women who had their menarche age ≥15 years (OR(het) = 0.84, 95% CI 0.75, 0.94; OR(hom) = 0.81, 95% CI 0.51, 1.30; P(trend) = 0.002) but not for those who had their menarche age ≤11 years (OR(het) = 1.06, 95% CI 0.95, 1.19, OR(hom) = 1.07, 95% CI 0.67, 1.72; P(trend) = 0.29).

    CONCLUSIONS: To our knowledge rs10235235 is the first single nucleotide polymorphism to be associated with both breast cancer risk and age at menarche consistent with the well-documented association between later age at menarche and a reduction in breast cancer risk. These associations are likely mediated via an effect on circulating hormone levels.

  11. Michailidou K, Beesley J, Lindstrom S, Canisius S, Dennis J, Lush MJ, et al.
    Nat Genet, 2015 Apr;47(4):373-80.
    PMID: 25751625 DOI: 10.1038/ng.3242
    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
  12. Baker TR, Adu-Bredu S, Affum-Baffoe K, Aiba SI, Akite P, Alexiades M, et al.
    Sci Rep, 2025 Feb 08;15(1):4695.
    PMID: 39922807 DOI: 10.1038/s41598-024-84367-3
    Understanding how the traits of lineages are related to diversification is key for elucidating the origin of variation in species richness. Here, we test whether traits are related to species richness among lineages of trees from all major biogeographical settings of the lowland wet tropics. We explore whether variation in mortality rate, breeding system and maximum diameter are related to species richness, either directly or via associations with range size, among 463 genera that contain wet tropical forest trees. For Amazonian genera, we also explore whether traits are related to species richness via variation among genera in mean species-level range size. Lineages with higher mortality rates-faster life-history strategies-have larger ranges in all biogeographic settings and have higher mean species-level range sizes in Amazonia. These lineages also have smaller maximum diameters and, in the Americas, contain dioecious species. In turn, lineages with greater overall range size have higher species richness. Our results show that fast life-history strategies influence species richness in all biogeographic settings because lineages with these ecological strategies have greater range sizes. These links suggest that dispersal has been a key process in the evolution of the tropical forest flora.
  13. Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, et al.
    Nat Genet, 2015 Feb;47(2):164-71.
    PMID: 25581431 DOI: 10.1038/ng.3185
    Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.
  14. Rebbeck TR, Mitra N, Wan F, Sinilnikova OM, Healey S, McGuffog L, et al.
    JAMA, 2015 Apr 07;313(13):1347-61.
    PMID: 25849179 DOI: 10.1001/jama.2014.5985
    IMPORTANCE: Limited information about the relationship between specific mutations in BRCA1 or BRCA2 (BRCA1/2) and cancer risk exists.

    OBJECTIVE: To identify mutation-specific cancer risks for carriers of BRCA1/2.

    DESIGN, SETTING, AND PARTICIPANTS: Observational study of women who were ascertained between 1937 and 2011 (median, 1999) and found to carry disease-associated BRCA1 or BRCA2 mutations. The international sample comprised 19,581 carriers of BRCA1 mutations and 11,900 carriers of BRCA2 mutations from 55 centers in 33 countries on 6 continents. We estimated hazard ratios for breast and ovarian cancer based on mutation type, function, and nucleotide position. We also estimated RHR, the ratio of breast vs ovarian cancer hazard ratios. A value of RHR greater than 1 indicated elevated breast cancer risk; a value of RHR less than 1 indicated elevated ovarian cancer risk.

    EXPOSURES: Mutations of BRCA1 or BRCA2.

    MAIN OUTCOMES AND MEASURES: Breast and ovarian cancer risks.

    RESULTS: Among BRCA1 mutation carriers, 9052 women (46%) were diagnosed with breast cancer, 2317 (12%) with ovarian cancer, 1041 (5%) with breast and ovarian cancer, and 7171 (37%) without cancer. Among BRCA2 mutation carriers, 6180 women (52%) were diagnosed with breast cancer, 682 (6%) with ovarian cancer, 272 (2%) with breast and ovarian cancer, and 4766 (40%) without cancer. In BRCA1, we identified 3 breast cancer cluster regions (BCCRs) located at c.179 to c.505 (BCCR1; RHR = 1.46; 95% CI, 1.22-1.74; P = 2 × 10(-6)), c.4328 to c.4945 (BCCR2; RHR = 1.34; 95% CI, 1.01-1.78; P = .04), and c. 5261 to c.5563 (BCCR2', RHR = 1.38; 95% CI, 1.22-1.55; P = 6 × 10(-9)). We also identified an ovarian cancer cluster region (OCCR) from c.1380 to c.4062 (approximately exon 11) with RHR = 0.62 (95% CI, 0.56-0.70; P = 9 × 10(-17)). In BRCA2, we observed multiple BCCRs spanning c.1 to c.596 (BCCR1; RHR = 1.71; 95% CI, 1.06-2.78; P = .03), c.772 to c.1806 (BCCR1'; RHR = 1.63; 95% CI, 1.10-2.40; P = .01), and c.7394 to c.8904 (BCCR2; RHR = 2.31; 95% CI, 1.69-3.16; P = .00002). We also identified 3 OCCRs: the first (OCCR1) spanned c.3249 to c.5681 that was adjacent to c.5946delT (6174delT; RHR = 0.51; 95% CI, 0.44-0.60; P = 6 × 10(-17)). The second OCCR spanned c.6645 to c.7471 (OCCR2; RHR = 0.57; 95% CI, 0.41-0.80; P = .001). Mutations conferring nonsense-mediated decay were associated with differential breast or ovarian cancer risks and an earlier age of breast cancer diagnosis for both BRCA1 and BRCA2 mutation carriers.

    CONCLUSIONS AND RELEVANCE: Breast and ovarian cancer risks varied by type and location of BRCA1/2 mutations. With appropriate validation, these data may have implications for risk assessment and cancer prevention decision making for carriers of BRCA1 and BRCA2 mutations.

  15. Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, et al.
    Sci Data, 2020 07 09;7(1):225.
    PMID: 32647314 DOI: 10.1038/s41597-020-0534-3
    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
  16. Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, et al.
    Sci Data, 2021 Feb 25;8(1):72.
    PMID: 33633116 DOI: 10.1038/s41597-021-00851-9
  17. Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, et al.
    Nat Genet, 2020 01;52(1):56-73.
    PMID: 31911677 DOI: 10.1038/s41588-019-0537-1
    Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
  18. Zhang H, Ahearn TU, Lecarpentier J, Barnes D, Beesley J, Qi G, et al.
    Nat Genet, 2020 06;52(6):572-581.
    PMID: 32424353 DOI: 10.1038/s41588-020-0609-2
    Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P 
  19. Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, et al.
    Eur J Hum Genet, 2022 Jan 14.
    PMID: 35027648 DOI: 10.1038/s41431-021-00987-7
    Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
  20. Dareng EO, Tyrer JP, Barnes DR, Jones MR, Yang X, Aben KKH, et al.
    Eur J Hum Genet, 2022 May;30(5):630-631.
    PMID: 35314806 DOI: 10.1038/s41431-022-01085-y
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