Mikael Hartman

Dr. Mikael Hartman

orcid

Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 March 2013 in Nature Genetics
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TCThe Breast and Ovarian Cancer Susceptibility Collaboration
The Breast and Ovarian Cancer Susceptibility Collaboration
KMKyriaki Michailidou
Kyriaki Michailidou
H(Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON)
Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON)
KIkConFab Investigators
kConFab Investigators
AGAustralian Ovarian Cancer Study Group
Australian Ovarian Cancer Study Group
DEDouglas F Easton
Douglas F Easton

5 January 2016 in JAMA
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LMLorelei A. Mucci
Lorelei A. Mucci
JHJacob Hjelmborg
Jacob Hjelmborg
JHJennifer R. Harris
Jennifer R. Harris
KCKamila Czene
Kamila Czene
DHDavid J. Havelick
David J. Havelick
JKJaakko Kaprio
Jaakko Kaprio
The global burden of cancer is considerable, with an estimated 12 million new cases and 8 million cancer deaths each year.1 In 2015 in the United States, 1.7 million individuals will be diagnosed with cancer and 590 000 will die of cancer, accounting for 1 in 4 deaths.2 In the Nordic countries, cancer is the leading cause of mortality, accounting for 30% of all deaths. Refinement of primary and secondary prevention strategies (ie, factors that would have the greatest influence on reducing cancer incidence and mortality) requires a detailed understanding of the contribution of genetic and environmental factors to disease pathogenesis.

9 March 2015 in Nature Genetics
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BOBocs
Bocs
KMKyriaki Michailidou
Kyriaki Michailidou
KIkConFab Investigators
kConFab Investigators
AGAOCS Group
AOCS Group
NBNbcs
Nbcs
DEDouglas F Easton
Douglas F Easton
Doug Easton and colleagues report the results of a large-scale genome-wide association study of breast cancer. They discover 15 new susceptibility loci and highlight likely target genes in several of the newly associated regions. 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.

27 March 2013 in Nature Genetics
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SBStig E Bojesen
Stig E Bojesen
KPKaren A Pooley
Karen A Pooley
SJSharon E Johnatty
Sharon E Johnatty
JBJonathan Beesley
Jonathan Beesley
KMKyriaki Michailidou
Kyriaki Michailidou
ADAlison M Dunning
Alison M Dunning
Stig Bojesen, Georgia Chenevix-Trench, Alison Dunning and colleagues report common variants at the TERT-CLPTM1L locus associated with mean telomere length measured in whole blood. They also identify associations at this locus to breast or ovarian cancer susceptibility and report functional studies in breast and ovarian cancer tissue and cell lines. TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 × 10−7), lower risks for estrogen receptor (ER)-negative (P = 1.0 × 10−8) and BRCA1 mutation carrier (P = 1.1 × 10−5) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 × 10−14), higher risk of low-malignant-potential ovarian cancer (P = 1.3 × 10−15) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 × 10−12) and BRCA1 mutation carrier (P = 1.6 × 10−14) breast and invasive ovarian (P = 1.3 × 10−11) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.

27 March 2013 in Nature Genetics
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TNThe Gene Environmental Interaction And Breast Cancer (Genica) Network
The Gene Environmental Interaction And Breast Cancer (Genica) Network
MGMontserrat Garcia-Closas
Montserrat Garcia-Closas
KIkConFab Investigators
kConFab Investigators
F(Familial Breast Cancer Study (FBCS)
Familial Breast Cancer Study (FBCS)
AIAustralian Breast Cancer Tissue Bank (ABCTB) Investigators
Australian Breast Cancer Tissue Bank (ABCTB) Investigators
PKPeter Kraft
Peter Kraft

10 May 2014 in JNCI: Journal of the National Cancer Institute
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APAndreas Pettersson
Andreas Pettersson
RGRebecca E. Graff
Rebecca E. Graff
GUGiske Ursin
Giske Ursin
ISIsabel dos Santos Silva
Isabel dos Santos Silva
VMValerie McCormack
Valerie McCormack
RTRulla M. Tamimi
Rulla M. Tamimi
Fibroglandular breast tissue appears dense on mammogram, whereas fat appears nondense. It is unclear whether absolute or percentage dense area more strongly predicts breast cancer risk and whether absolute nondense area is independently associated with risk. We conducted a meta-analysis of 13 case–control studies providing results from logistic regressions for associations between one standard deviation (SD) increments in mammographic density phenotypes and breast cancer risk. We used random-effects models to calculate pooled odds ratios and 95% confidence intervals (CIs). All tests were two-sided with P less than .05 considered to be statistically significant. Among premenopausal women (n = 1776 case patients; n = 2834 control subjects), summary odds ratios were 1.37 (95% CI = 1.29 to 1.47) for absolute dense area, 0.78 (95% CI = 0.71 to 0.86) for absolute nondense area, and 1.52 (95% CI = 1.39 to 1.66) for percentage dense area when pooling estimates adjusted for age, body mass index, and parity. Corresponding odds ratios among postmenopausal women (n = 6643 case patients; n = 11187 control subjects) were 1.38 (95% CI = 1.31 to 1.44), 0.79 (95% CI = 0.73 to 0.85), and 1.53 (95% CI = 1.44 to 1.64). After additional adjustment for absolute dense area, associations between absolute nondense area and breast cancer became attenuated or null in several studies and summary odds ratios became 0.82 (95% CI = 0.71 to 0.94; Pheterogeneity = .02) for premenopausal and 0.85 (95% CI = 0.75 to 0.96; Pheterogeneity < .01) for postmenopausal women. The results suggest that percentage dense area is a stronger breast cancer risk factor than absolute dense area. Absolute nondense area was inversely associated with breast cancer risk, but it is unclear whether the association is independent of absolute dense area.