Publications by authors named "Kyriaki Michailidou"

143 Publications

Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.

Nat Commun 2021 07 7;12(1):4198. Epub 2021 Jul 7.

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants.
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http://dx.doi.org/10.1038/s41467-021-24327-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8263739PMC
July 2021

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

Am J Hum Genet 2021 Jul 18;108(7):1190-1203. Epub 2021 Jun 18.

Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany.

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).
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http://dx.doi.org/10.1016/j.ajhg.2021.05.013DOI Listing
July 2021

Gene-Environment Interactions Relevant to Estrogen and Risk of Breast Cancer: Can Gene-Environment Interactions Be Detected Only among Candidate SNPs from Genome-Wide Association Studies?

Cancers (Basel) 2021 May 14;13(10). Epub 2021 May 14.

Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, 2730 Herlev, Denmark.

In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (-2df = 1.2 × 10). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (-2df = 1.1 × 10). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.
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http://dx.doi.org/10.3390/cancers13102370DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156547PMC
May 2021

Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels.

BMC Bioinformatics 2021 Apr 28;22(1):218. Epub 2021 Apr 28.

Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, 2371, Nicosia, Cyprus.

Background: Next-generation sequencing (NGS) represents a significant advancement in clinical genetics. However, its use creates several technical, data interpretation and management challenges. It is essential to follow a consistent data analysis pipeline to achieve the highest possible accuracy and avoid false variant calls. Herein, we aimed to compare the performance of twenty-eight combinations of NGS data analysis pipeline compartments, including short-read mapping (BWA-MEM, Bowtie2, Stampy), variant calling (GATK-HaplotypeCaller, GATK-UnifiedGenotyper, SAMtools) and interval padding (null, 50 bp, 100 bp) methods, along with a commercially available pipeline (BWA Enrichment, Illumina®). Fourteen germline DNA samples from breast cancer patients were sequenced using a targeted NGS panel approach and subjected to data analysis.

Results: We highlight that interval padding is required for the accurate detection of intronic variants including spliceogenic pathogenic variants (PVs). In addition, using nearly default parameters, the BWA Enrichment algorithm, failed to detect these spliceogenic PVs and a missense PV in the TP53 gene. We also recommend the BWA-MEM algorithm for sequence alignment, whereas variant calling should be performed using a combination of variant calling algorithms; GATK-HaplotypeCaller and SAMtools for the accurate detection of insertions/deletions and GATK-UnifiedGenotyper for the efficient detection of single nucleotide variant calls.

Conclusions: These findings have important implications towards the identification of clinically actionable variants through panel testing in a clinical laboratory setting, when dedicated bioinformatics personnel might not always be available. The results also reveal the necessity of improving the existing tools and/or at the same time developing new pipelines to generate more reliable and more consistent data.
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http://dx.doi.org/10.1186/s12859-021-04144-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080428PMC
April 2021

Evaluating Polygenic Risk Scores for Breast Cancer in Women of African Ancestry.

J Natl Cancer Inst 2021 Mar 26. Epub 2021 Mar 26.

Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.

Background: Polygenic risk scores (PRS) have been demonstrated to identify women of European, Asian and Latino ancestry at elevated risk of developing breast cancer (BC). We evaluated the performance of existing PRSs trained in European ancestry populations among women of African ancestry.

Methods: We assembled genotype data for women of African ancestry, including 9,241 cases and 10,193 controls. We evaluated associations of 179- and 313-variant PRSs with overall and subtype-specific BC risk. PRS discriminatory accuracy was assessed using area under the receiver operating characteristic curve (AUC). We also evaluated a recalibrated PRS, replacing the index variant with variants in each region that better captured risk in women of African ancestry, and estimated lifetime absolute risk of BC in African Americans by PRS category.

Results: For overall BC, the odds ratios per standard deviation of PRS313 was 1.27 (95%CI = 1.23 to 1.31), with an AUC of 0.571 (95%CI = 0.562 to 0.579). Compared to women with average risk (40th-60th PRS percentile), women in the top decile of PRS313 had a 1.54-fold increased risk (95% CI = 1.38 to 1.72). By age 85 years, the absolute risk of overall BC was 19.6% for African American women in the top 1% of PRS313 and 6.7% for those in the lowest 1%. The recalibrated PRS did not improve BC risk prediction.

Conclusion: The PRSs stratify BC risk in women of African ancestry, with attenuated performance compared to that reported in European, Asian and Latina populations. Future work is needed to improve BC risk stratification for women of African ancestry.
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http://dx.doi.org/10.1093/jnci/djab050DOI Listing
March 2021

Implementation of multigene panel NGS diagnosis in the national primary ciliary dyskinesia cohort of Cyprus: An island with a high disease prevalence.

Hum Mutat 2021 Jun 25;42(6):e62-e77. Epub 2021 Mar 25.

Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.

We aimed to determine a genetic diagnosis in the national primary ciliary dyskinesia (PCD) cohort of Cyprus, an island with a high disease prevalence. We used targeted next-generation sequencing (NGS) of 39 PCD genes in 48 patients of Greek-Cypriot and other ancestries. We achieved a molecular diagnosis in 74% of the unrelated families tested. We identified 24 different mutations in 11 genes, 12 of which are novel. Homozygosity was more common in Greek-Cypriot than non-Greek-Cypriot patients (88% vs. 46.2%, p = .016). Four mutations (DNAH11:c.5095-2A>G, CFAP300:c.95_103delGCCGGCTCC, TTC25:c.716G>A, RSPH9:c.670+2T>C) were found in 74% of the diagnosed Greek-Cypriot families. Patients with RSPH9 mutations demonstrated higher nasal nitric oxide (57 vs. 15 nl/min, p <.001), higher forced expiratory volume in 1 s (-0.89 vs. -2.37, p = .018) and forced vital capacity (-1.00 vs. -2.16, p = .029) z scores than the rest of the cohort. Targeted multigene-panel NGS is an efficient tool for early diagnosis of PCD, providing insight into genetic disease epidemiology and improved patient stratification.
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http://dx.doi.org/10.1002/humu.24196DOI Listing
June 2021

Impact of the COVID-19 Pandemic on the Mental Health of Healthcare Workers.

Int J Environ Res Public Health 2021 02 3;18(4). Epub 2021 Feb 3.

Medical School, University of Cyprus, Nicosia 1678, Cyprus.

The coronavirus disease 2019 (COVID-19) has a great impact on healthcare workers (HCWs) that includes negative mental health outcomes, such as post-traumatic stress, anxiety and depressive symptoms. In this cross-sectional study, we report on mental health outcomes among HCWs in Cyprus. Data were collected between 3 May and 27 May 2020, with the use of an online questionnaire that included demographics (sex, age, occupation, education, work sector, years of work experience), the 9-item Patient Health Questionnaire (PHQ-9) which assesses depressive symptoms, the Impact of Events Scale Revised (IES-R), which measures post-traumatic stress disorder (PTSD) symptoms, and the-10 item Perceived Stress Scale (PSS-10) which quantifies stress responses. Participants (42% physicians, 24% nurses, 18% physiotherapists, 16% classified as "other") were 58% of female gender and aged 21-76. A total of 79 (18.6%) and 62 HCWs (14.6%) reported clinically significant depressive (PHQ-9 ≥ 10) and post-traumatic stress (IES-R > 33) symptoms respectively. Nurses were more likely than physicians to suffer from depression (adjusted prevalence ratio 1.7 (1.06-2.73); = 0.035) and PTSD (adjusted prevalence ratio 2.51 (1.49-4.23); = 0.001). Even in a country with a rather low spread of the COVID-19, such as Cyprus, HCWs reported a substantial mental health burden, with nurses reporting increased depressive and PTSD symptoms compared to other HCWs.
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http://dx.doi.org/10.3390/ijerph18041435DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913751PMC
February 2021

Muscle-derived exosomes encapsulate myomiRs and are involved in local skeletal muscle tissue communication.

FASEB J 2021 02;35(2):e21279

Department of Molecular Genetics, Function & Therapy, Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus.

Exosomes are extracellular vesicles that are released from most cell types encapsulating specific molecular cargo. Exosomes serve as mediators of cell-to-cell and tissue-to-tissue communications under normal and pathological conditions. It has been shown that exosomes carrying muscle-specific miRNAs, myomiRs, are secreted from skeletal muscle cells in vitro and are elevated in the blood of muscle disease patients. The aim of this study was to investigate the secretion of exosomes encapsulating the four myomiRs from skeletal muscle tissues and to assess their role in inter-tissue communication between neighboring skeletal muscles in vivo. We demonstrate, for the first time, that isolated, intact skeletal muscle tissues secrete exosomes encapsulating the four myomiRs, miR-1, miR-133a, miR-133b, and miR-206. Notably, we show that the sorting of the four myomiRs within exosomes varies between skeletal muscles of different muscle fiber-type composition. miR-133a and miR-133b downregulation in TA muscles caused a reduction of their levels in neighboring skeletal muscles and in serum exosomes. In conclusion, our results reveal that skeletal muscle-derived exosomes encapsulate the four myomiRs, some of which enter the blood, while a portion is used for the local communication between proximal muscle tissues. These findings provide important evidence regarding novel pathways implicated in skeletal muscle function.
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http://dx.doi.org/10.1096/fj.201902468RRDOI Listing
February 2021

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

N Engl J Med 2021 02 20;384(5):428-439. Epub 2021 Jan 20.

The authors' affiliations are as follows: the Centre for Cancer Genetic Epidemiology, Departments of Public Health and Primary Care (L.D., S. Carvalho, J.A., K.A.P., Q.W., M.K.B., J.D., B.D., N. Mavaddat, K. Michailidou, A.C.A., P.D.P.P., D.F.E.) and Oncology (C.L., P.A.H., C. Baynes, D.M.C., L.F., V.R., M. Shah, P.D.P.P., A.M.D., D.F.E.), University of Cambridge, Cambridge, the Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine (A. Campbell, D.J.P.), and the Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology (D.J.P.), University of Edinburgh, the Cancer Research UK Edinburgh Centre (D.A.C., J.F.), and the Usher Institute of Population Health Sciences and Informatics, University of Edinburgh Medical School (A. Campbell, J.F.), Edinburgh, the Divisions of Informatics, Imaging, and Data Sciences (E.F.H.), Cancer Sciences (A. Howell), Population Health, Health Services Research, and Primary Care (A. Lophatananon, K. Muir), and Evolution and Genomic Sciences, School of Biological Sciences (W.G.N., E.M.V., D.G.E.), University of Manchester, the NIHR Manchester Biomedical Research Unit (E.F.H.) and the Nightingale Breast Screening Centre, Wythenshawe Hospital (E.F.H., H.I.), Academic Health Science Centre and North West Genomics Laboratory Hub, and the Manchester Centre for Genomic Medicine, St. Mary's Hospital, Manchester University NHS Foundation Trust (W.G.N., E.M.V., D.G.E.), Manchester, the School of Cancer and Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy's Campus, King's College London, London (E.J.S.), the Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham (I.T.), and the Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford (I.T.) - all in the United Kingdom; the Human Genotyping-CEGEN Unit, Human Cancer Genetic Program (A.G.-N., M.R.A., N.Á., B.H., R.N.-T.), and the Human Genetics Group (V.F., A.O., J.B.), Spanish National Cancer Research Center, Centro de Investigación en Red de Enfermedades Raras (A.O., J.B.), Servicio de Oncología Médica, Hospital Universitario La Paz (M.P.Z.), and Molecular Oncology Laboratory, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (M. de la Hoya), Madrid, the Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela, Complejo Hospitalario Universitario de Santiago (A. Carracedo, M.G.-D.), and Centro de Investigación en Red de Enfermedades Raras y Centro Nacional de Genotipado, Universidad de Santiago de Compostela (A. Carracedo), Santiago de Compostela, the Oncology and Genetics Unit, Instituto de Investigacion Sanitaria Galicia Sur, Xerencia de Xestion Integrada de Vigo-Servizo Galeo de Saúde, Vigo (J.E.C.), and Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo (J.I.A.P.) - all in Spain; the Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund (C. Wahlström, J.V., M.L., T. Törngren, Å.B., A.K.), the Department of Oncology, Örebro University Hospital, Örebro (C. Blomqvist), and the Departments of Medical Epidemiology and Biostatistics (K.C., M.E., M.G., P. Hall, W.H., K.H.), Oncology, Södersjukhuset (P. Hall, S. Margolin), Molecular Medicine and Surgery (A. Lindblom), and Clinical Science and Education, Södersjukhuset (S. Margolin, C. Wendt), Karolinska Institutet, and the Department of Clinical Genetics, Karolinska University Hospital (A. Lindblom), Stockholm - all in Sweden; the Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD (M.T.P., C.F., G.C.-T., A.B.S.), the Cancer Epidemiology Division, Cancer Council Victoria (G.G.G., R.J.M., R.L.M.), the Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (G.G.G., R.J.M., R.L.M.), and the Department of Clinical Pathology (M.C.S.), University of Melbourne, Anatomical Pathology, Alfred Hospital (C.M.), and the Cancer Epidemiology Division, Cancer Council Victoria (M.C.S.), Melbourne, VIC, and Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC (G.G.G., M.C.S., R.L.M.) - all in Australia; the Division of Molecular Pathology (R.K., S. Cornelissen, M.K.S.), Family Cancer Clinic (F.B.L.H., L.E.K.), Department of Epidemiology (M.A.R.), and Division of Psychosocial Research and Epidemiology (M.K.S.), the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, Division Laboratories, Pharmacy and Biomedical Genetics, Department of Genetics, University Medical Center, Utrecht (M.G.E.M.A.), the Department of Clinical Genetics, Erasmus University Medical Center (J.M.C., A.M.W.O.), and the Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute (B.A.M.H.-G., A. Hollestelle, M.J.H.), Rotterdam, the Department of Clinical Genetics, Maastricht University Medical Center, Maastricht (E.B.G.G.), the Departments of Human Genetics (I.M.M.L., M.P.G.V., P.D.), Clinical Genetics (C.J.A.), and Pathology (P.D.), Leiden University Medical Center, Leiden, the Department of Human Genetics, Radboud University Medical Center, Nijmegen (A.R.M.), and the Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen (J.C.O.) - all in the Netherlands; the Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute (B.D.), and the Division of Cancer Epidemiology and Genetics, National Cancer Institute (T.A., S.J.C., X.R.Y., M.G.-C.), National Institutes of Health, Bethesda, MD; the Department of Pathology, Brigham and Women's Hospital, Harvard Medical School (B.D.), and the Department of Nutrition, Harvard T.H. Chan School of Public Health (R.M.V.D.), Boston; the Departments of Clinical Genetics (K.A.), Oncology (C. Blomqvist), and Obstetrics and Gynecology (H.N., M. Suvanto), Helsinki University Hospital, University of Helsinki, Helsinki, and the Unit of Clinical Oncology, Kuopio University Hospital (P. Auvinen), the Institute of Clinical Medicine, Oncology (P. Auvinen), the Translational Cancer Research Area (J.M.H., V.-M.K., A. Mannermaa), and the Institute of Clinical Medicine, Pathology, and Forensic Medicine (J.M.H., V.-M.K., A. Mannermaa), University of Eastern Finland, and the Biobank of Eastern Finland, Kuopio University Hospital (V.-M.K., A. Mannermaa), Kuopio - both in Finland; the N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus (N.N.A., N.V.B.); the Department of Gynecology and Obstetrics and Institute of Clinical Molecular Biology, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, Kiel (N.A.), the Institute of Medical Biometry and Epidemiology (H. Becher) and Cancer Epidemiology Group (T.M., J.C.-C.), University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, the Department of Gynecology and Obstetrics (M.W.B., P.A.F., L.H.) and Institute of Human Genetics (A.B.E.), University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-European Metropolitan Region of Nuremberg, Erlangen, the Division of Cancer Epidemiology (S.B., A. Jung, P.M.K., J.C.-C.), Molecular Epidemiology Group, C080 (B. Burwinkel, H.S.), Division of Pediatric Neurooncology (A.F.), and Molecular Genetics of Breast Cancer (U.H., M.M., M.U.R., D.T.), German Cancer Research Center, Molecular Biology of Breast Cancer, University Women's Clinic Heidelberg, University of Heidelberg (B. Burwinkel, A.S., H.S.), Hopp Children's Cancer Center (A.F.), Faculty of Medicine, University of Heidelberg (P.M.K.), and National Center for Tumor Diseases, University Hospital and German Cancer Research Center (A.S., C.S.), Heidelberg, the Department of Radiation Oncology (N.V.B., M. Bremer, H.C.) and the Gynecology Research Unit (N.V.B., T.D., P. Hillemanns, T.-W.P.-S., P.S.), Hannover Medical School, Hannover, the Institute of Human Genetics, University of Münster, Münster (N.B.-M.), Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart (H. Brauch, W.-Y.L.), iFIT-Cluster of Excellence, University of Tübingen, and the German Cancer Consortium, German Cancer Research Center, Partner Site Tübingen (H. Brauch), and the University of Tübingen (W.-Y.L.), Tübingen, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum (T.B.), Institute for Medical Informatics, Statistics, and Epidemiology, University of Leipzig, Leipzig (C.E.), Center for Hereditary Breast and Ovarian Cancer (E.H., R.K.S.) and Center for Integrated Oncology (E.H., R.K.S.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, the Department of Internal Medicine, Evangelische Kliniken Bonn, Johanniter Krankenhaus, Bonn (Y.-D.K.), the Department of Gynecology and Obstetrics, University of Munich, Campus Großhadern, Munich (A. Meindl), and the Institute of Pathology, Städtisches Klinikum Karlsruhe, Karlsruhe (T.R.) - all in Germany; the Gynecological Cancer Registry, Centre Georges-François Leclerc, Dijon (P. Arveux), and the Center for Research in Epidemiology and Population Health, Team Exposome and Heredity, INSERM, University Paris-Saclay, Villejuif (E.C.-D., P.G., T. Truong) - both in France; the Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences (M. Bermisheva, E.K.), the Department of Genetics and Fundamental Medicine, Bashkir State University (E.K., D.P., Y.V.), and the Ufa Research Institute of Occupational Health and Human Ecology (Y.V.), Ufa, Russia; the Department of Genetics and Pathology (K.B., A. Jakubowska, J. Lubiński, K.P.) and the Independent Laboratory of Molecular Biology and Genetic Diagnostics (A. Jakubowska), Pomeranian Medical University, Szczecin, Poland; the Copenhagen General Population Study, the Department of Clinical Biochemistry (S.E.B., B.G.N.), and the Department of Breast Surgery (H.F.), Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, and the Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen (S.E.B., B.G.N.) - both in Denmark; the Division of Cancer Prevention and Genetics, European Institute of Oncology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) (B. Bonanni), the Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano (S. Manoukian), the Genome Diagnostics Program, FIRC Institute of Molecular Oncology (P.P.), and the Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (P.R.), Milan; the Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet (A.-L.B.-D., G.I.G.A., V.N.K.), and the Institute of Clinical Medicine, Faculty of Medicine, University of Oslo (A.-L.B.-D., V.N.K.), Oslo; Medical Faculty, Universidad de La Sabana (I.B.), and the Clinical Epidemiology and Biostatistics Department (F.G.) and Institute of Human Genetics (D.T.), Pontificia Universidad Javeriana, Bogota, Colombia; the Department of Internal Medicine and Huntsman Cancer Institute, University of Utah (N.J.C., M.J.M., J.A.W.), and the Intermountain Healthcare Biorepository and Department of Pathology, Intermountain Healthcare (M.H.C.), Salt Lake City; the David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California, Los Angeles (P.A.F.), and Moores Cancer Center (M.G.-D., M.E.M.) and the Department of Family Medicine and Public Health (M.E.M.), University of California San Diego, La Jolla; the Departments of Medical Oncology (V.G., D.M.) and Pathology (M.T.), University Hospital of Heraklion, Heraklion, and the Department of Oncology, University Hospital of Larissa, Larissa (E.S.) - both in Greece; the Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital (G.G., I.L.A.), the Departments of Laboratory Medicine and Pathobiology (A.M.M.) and Molecular Genetics (I.L.A.), University of Toronto, and the Laboratory Medicine Program, University Health Network (A.M.M.), Toronto, and the Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Québec City, QC (J.S.) - both in Canada; the Department of Electron Microscopy and Molecular Pathology (A. Hadjisavvas, K.K., M.A.L.), the Cyprus School of Molecular Medicine (A. Hadjisavvas, K.K., M.A.L., K. Michailidou), and the Biostatistics Unit (K. Michailidou), Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus; the Saw Swee Hock School of Public Health (M. Hartman, R.M.V.D.) and the Department of Medicine, Yong Loo Lin School of Medicine (R.M.V.D.), National University of Singapore, the Department of Surgery, National University Health System (M. Hartman, J. Li), and the Human Genetics Division, Genome Institute of Singapore (J. Li), Singapore; the Department of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia (W.K.H.), and the Breast Cancer Research Programme, Cancer Research Malaysia (W.K.H., P.S.N., S.-Y.Y., S.H.T.), Selangor, and the Breast Cancer Research Unit, Cancer Research Institute (N.A.M.T.), and the Department of Surgery, Faculty of Medicine (N.A.M.T., P.S.N., S.H.T.), University Malaya, Kuala Lumpur - both in Malaysia; Surgery, School of Medicine, National University of Ireland, Galway (M.J.K., N. Miller); the Department of Surgery, Daerim Saint Mary's Hospital (S.-W.K.), the Department of Surgery, Ulsan University College of Medicine and Asan Medical Center (J.W.L.), the Department of Surgery, Soonchunhyang University College of Medicine and Soonchunhyang University Hospital (M.H.L.), Integrated Major in Innovative Medical Science, Seoul National University College of Medicine (S.K.P.), and the Cancer Research Institute, Seoul National University (S.K.P.), Seoul, South Korea; the Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Center, Lahore, Pakistan (M.U.R.); and the National Cancer Institute, Ministry of Public Health, Nonthaburi, Thailand (S.T.).

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 (, , , , and ) 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 (, , , and ) 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 and , odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in , , , , , and , odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in , , and were associated with a risk of breast cancer overall with a P value of less than 0.001. For , , and , 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.).
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http://dx.doi.org/10.1056/NEJMoa1913948DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611105PMC
February 2021

NGS Panel Testing of Triple-Negative Breast Cancer Patients in Cyprus: A Study of -Negative Cases.

Cancers (Basel) 2020 Oct 27;12(11). Epub 2020 Oct 27.

Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, 6 Iroon Avenue, 2371 Agios Dhometios, Nicosia, Cyprus.

In Cyprus, approximately 9% of triple-negative (estrogen receptor-negative, progesterone receptor-negative, and human epidermal growth factor receptor 2-negative) breast cancer (TNBC) patients are positive for germline pathogenic variants (PVs) in . However, the contribution of other genes has not yet been determined. To this end, we aimed to investigate the prevalence of germline PVs in -negative TNBC patients in Cyprus, unselected for family history of cancer or age of diagnosis. A comprehensive 94-cancer-gene panel was implemented for 163 germline DNA samples, extracted from the peripheral blood of TNBC patients. Identified variants of uncertain clinical significance were evaluated, using extensive in silico investigation. Eight PVs (4.9%) were identified in two high-penetrance TNBC susceptibility genes. Of these, seven occurred in (87.5%) and one occurred in (12.5%). Interestingly, 50% of the patients carrying PVs were diagnosed over the age of 60 years. The frequency of non- PVs (4.9%) and especially PVs (4.3%) in TNBC patients in Cyprus appears to be higher compared to other populations. Based on these results, we believe that and along with genetic testing could be beneficial for a large proportion of TNBC patients in Cyprus, irrespective of their age of diagnosis.
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http://dx.doi.org/10.3390/cancers12113140DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7692082PMC
October 2020

Detecting rare copy number variants from Illumina genotyping arrays with the CamCNV pipeline: Segmentation of z-scores improves detection and reliability.

Genet Epidemiol 2021 Apr 5;45(3):237-248. Epub 2020 Oct 5.

Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK.

The intensities from genotyping array data can be used to detect copy number variants (CNVs) but a high level of noise in the data and overlap between different copy-number intensity distributions produces unreliable calls, particularly when only a few probes are covered by the CNV. We present a novel pipeline (CamCNV) with a series of steps to reduce noise and detect more reliably CNVs covering as few as three probes. The pipeline aims to detect rare CNVs (below 1% frequency) for association tests in large cohorts. The method uses the information from all samples to convert intensities to z-scores, thus adjusting for variance between probes. We tested the sensitivity of our pipeline by looking for known CNVs from the 1000 Genomes Project in our genotyping of 1000 Genomes samples. We also compared the CNV calls for 1661 pairs of genotyped replicate samples. At the chosen mean z-score cut-off, sensitivity to detect the 1000 Genomes CNVs was approximately 85% for deletions and 65% for duplications. From the replicates, we estimate the false discovery rate is controlled at ∼10% for deletions (falling to below 3% with more than five probes) and ∼28% for duplications. The pipeline demonstrates improved sensitivity when compared to calling with PennCNV, particularly for short deletions covering only a few probes. For each called CNV, the mean z-score is a useful metric for controlling the false discovery rate.
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http://dx.doi.org/10.1002/gepi.22367DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005414PMC
April 2021

European polygenic risk score for prediction of breast cancer shows similar performance in Asian women.

Nat Commun 2020 07 31;11(1):3833. Epub 2020 Jul 31.

Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore, Singapore.

Polygenic risk scores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asian women is unclear. Here we evaluate the best performing PRSs for European-ancestry women using data from 17,262 breast cancer cases and 17,695 controls of Asian ancestry from 13 case-control studies, and 10,255 Chinese women from a prospective cohort (413 incident breast cancers). Compared to women in the middle quintile of the risk distribution, women in the highest 1% of PRS distribution have a ~2.7-fold risk and women in the lowest 1% of PRS distribution has ~0.4-fold risk of developing breast cancer. There is no evidence of heterogeneity in PRS performance in Chinese, Malay and Indian women. A PRS developed for European-ancestry women is also predictive of breast cancer risk in Asian women and can help in developing risk-stratified screening programmes in Asia.
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http://dx.doi.org/10.1038/s41467-020-17680-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395776PMC
July 2020

Effect of HBB genotype on survival in a cohort of transfusion-dependent thalassemia patients in Cyprus.

Haematologica 2020 07 30. Epub 2020 Jul 30.

Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, UK.

Initiation of regular transfusion in transfusion-dependent thalassemia (TDT) is based on the assessment of clinical phenotype. Pathogenic HBB variants causing β-thalassemia are important determinants of phenotype and could be used to aid decision making. We investigated the association of HBB genotype with survival in a cohort study in the four thalassemia centres in Cyprus. HBB genotype was classified as severe (β0/β0 or β+/β0), moderate (β+/β+), or mild (β0/β++ or β+/β++). Risk factors for mortality were evaluated using multivariate Cox proportional-hazards regression. 537 subjects were followed for a total of 20,963 person years. 80.4% (95% CI 76.4-84.7) of individuals survived to 50 years of age with increasing rates of liver, infection and malignancy-related deaths observed during recent follow-up. We evaluated non-modifiable risk factors and found worse outcomes associated with male sex (Hazard ratio 1.9, 95% CI 1.1-3.0, p=0.01) and milder genotype (Hazard ratio 1.6, 95% CI 1.1-2.3, p=0.02). The effect of genotype was confirmed in a second model, which included treatment effects. Patients with a milder genotype initiated transfusion significantly later and had reduced blood requirements compared to those with moderate or severe genotypes, although pre-transfusion hemoglobin levels did not differ between genotypes. Our results suggest that early treatment decisions to delay transfusion and different long-term treatment strategies in milder genotypes have led to adverse long-term effects of under-treated thalassemia and worse survival. We propose that HBB genotype determination and use of this information to aid in decision making can improve long-term outcomes of thalassaemia patients.
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http://dx.doi.org/10.3324/haematol.2020.260224DOI Listing
July 2020

Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers.

Nat Commun 2020 07 3;11(1):3353. Epub 2020 Jul 3.

Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.
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http://dx.doi.org/10.1038/s41467-020-16483-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335068PMC
July 2020

Identification of novel splice mutation in SMAD3 in two Cypriot families with nonsyndromic thoracic aortic aneurysm. Two case reports.

Mol Genet Genomic Med 2020 09 29;8(9):e1378. Epub 2020 Jun 29.

Department of Cardiovascular Genetics and The Laboratory of Forensic Genetics, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.

Background: Thoracic aortic aneurysm and dissection (TAA/D) represents a potentially lethal disease group characterized by an increased risk of dissection or rupture. Only a small percentage (approximately 30%) of individuals with nonsyndromic familial TAA/D have a pathogenic variant in one of the genes that have been found to be associated with the disease.

Methods: A targeted sequencing panel and direct sequencing approach were used to identify causative mutations in the index patients and other family members.

Results: In this study we report two apparently unrelated Cypriot families with nonsyndromic familial TAA/D. The proband A is a female patient diagnosed with TAA/D and intracranial aneurysm and opted for an elective intervention. The proband B is a male patient who was diagnosed with TAA/D and underwent cardiac surgery. Sequencing analysis identified a novel splice site variant (c.871+1G>A) in SMAD3 which is shown to be associated with the disease. Analysis of mRNA from the patient's tissue confirmed aberrant splicing and exon 6 skipping.

Conclusion: Our findings expand the mutation spectrum of variants that have been shown to be associated with nonsyndromic familial TAA/D. This study demonstrates the importance of a comprehensive clinical and genetic evaluation aiming at early diagnosis and intervention.
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http://dx.doi.org/10.1002/mgg3.1378DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507478PMC
September 2020

Proteomic analysis in lupus mice identifies Coronin-1A as a potential biomarker for lupus nephritis.

Arthritis Res Ther 2020 06 18;22(1):147. Epub 2020 Jun 18.

Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, Iroon Avenue 6, Agios Dometios, 2371, P.O. Box 23462 / 1683, Nicosia, Cyprus.

Background: Approximately 50% of systemic lupus erythematosus (SLE) patients develop nephritis, which is among the most severe and frequent complications of the disease and a leading cause of morbidity and mortality. Despite intensive research, there are still no reliable lupus nephritis (LN) markers in clinical use that can assess renal damage and activity with a high sensitivity and specificity. To this end, the aim of this study was to identify new clinically relevant tissue-specific protein biomarkers and possible underlying molecular mechanisms associated with renal involvement in SLE, using mass spectrometry (MS)-based proteomics.

Methods: Kidneys were harvested from female triple congenic B6.NZMsle1/sle2/sle3 lupus mice model, and the respective sex- and age-matched C57BL/6 control mice at 12, 24 and 36 weeks of age, representing pre-symptomatic, established and end-stage LN, respectively. Proteins were extracted from kidneys, purified, reduced, alkylated and digested by trypsin. Purified peptides were separated by liquid chromatography and analysed by high-resolution MS. Data were processed by the Progenesis QIp software, and functional annotation analysis was performed using DAVID bioinformatics resources. Immunofluorescence and multiple reaction monitoring (MRM) MS methods were used to confirm prospective biomarkers in SLE mouse strains as well as human serum samples.

Results: Proteomic profiling of kidney tissues from SLE and control mice resulted in the identification of more than 3800 unique proteins. Pathway analysis revealed a number of dysregulated molecular pathways that may be mechanistically involved in renal pathology, including phagosome and proximal tubule bicarbonate reclamation pathways. Proteomic analysis supported by human transcriptomic data and pathway analysis revealed Coronin-1A, Ubiquitin-like protein ISG15, and Rho GDP-dissociation inhibitor 2, as potential LN biomarkers. These results were further validated in other SLE mouse strains using MRM-MS. Most importantly, experiments in humans showed that measurement of Coronin-1A in human sera using MRM-MS can segregate LN patients from SLE patients without nephritis with a high sensitivity (100%) and specificity (100%).

Conclusions: These preliminary findings suggest that serum Coronin-1A may serve as a promising non-invasive biomarker for LN and, upon validation in larger cohorts, may be employed in the future as a screening test for renal disease in SLE patients.
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http://dx.doi.org/10.1186/s13075-020-02236-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7301983PMC
June 2020

Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk.

Sci Rep 2020 06 16;10(1):9688. Epub 2020 Jun 16.

Department of Gynecology and Obstetrics, University of Tübingen, Tübingen, Germany.

In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.
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http://dx.doi.org/10.1038/s41598-020-65665-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297796PMC
June 2020

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Nat Genet 2020 06 18;52(6):572-581. Epub 2020 May 18.

Molecular Medicine Unit, Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. 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 < 5.0 × 10), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
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http://dx.doi.org/10.1038/s41588-020-0609-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808397PMC
June 2020

Clustering of known low and moderate risk alleles rather than a novel recessive high-risk gene in non-BRCA1/2 sib trios affected with breast cancer.

Int J Cancer 2020 11 30;147(10):2708-2716. Epub 2020 May 30.

Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands.

Breast cancer risk is approximately twice as high in first-degree relatives of female breast cancer cases than in women in the general population. Less than half of this risk can be attributed to the currently known genetic risk factors. Recessive risk alleles represent a relatively underexplored explanation for the remainder of familial risk. To address this, we selected 19 non-BRCA1/2 breast cancer families in which at least three siblings were affected, while no first-degree relatives of the previous or following generation had breast cancer. Germline DNA from one of the siblings was subjected to exome sequencing, while all affected siblings were genotyped using SNP arrays to assess haplotype sharing and to calculate a polygenic risk score (PRS) based on 160 low-risk variants. We found no convincing candidate recessive alleles among exome sequencing variants in genomic regions for which all three siblings shared two haplotypes. However, we found two families in which all affected siblings carried the CHEK2*1100delC. In addition, the average normalized PRS of the "recessive" family probands (0.81) was significantly higher than that in both general population cases (0.35, P = .026) and controls (P = .0004). These findings suggest that the familial aggregation is, at least in part, explained by a polygenic effect of common low-risk variants and rarer intermediate-risk variants, while we did not find evidence of a role for novel recessive risk alleles.
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http://dx.doi.org/10.1002/ijc.33039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540545PMC
November 2020

Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk.

J Natl Cancer Inst 2021 Mar;113(3):329-337

Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
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http://dx.doi.org/10.1093/jnci/djaa056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936056PMC
March 2021

Genetic Susceptibility to Systemic Sclerosis in the Greek-Cypriot Population: A Pilot Study.

Genet Test Mol Biomarkers 2020 May 21;24(5):309-317. Epub 2020 Apr 21.

Neurogenetics Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.

Systemic Sclerosis (SSc), also known as scleroderma, is an autoimmune rheumatic disease, which is clinically subdivided into two major subgroups; limited (lcSSc) and diffuse cutaneous scleroderma (dcSSc). Even though the SSc etiologies remains unclear, some HLA and non-HLA genetic variants have been associated with the disease. This study was designed to evaluate the associations between several HLA-related genetic variants and SSc in the Greek-Cypriot population. Forty-one SSc patients and 164 controls were genotyped at 18 selected single nucleotide polymorphisms (SNPs) using restriction fragment length polymorphism analyses, Sanger sequencing, and a multiplex SNaPshot minisequencing assay. Logistic regression analysis under the log-additive model was used to evaluate all possible associations between these SNPs and SSc; nominal statistical significance was assumed at  < 0.05. Associations of SSc with SNPs rs3117230, rs3128930, and rs3128965 within the and regions were observed in the Greek-Cypriot population at the level of  < 0.05. However, none of these associations survived a Bonferroni correction. The direction of the effect is consistent with the direction reported in previous studies. In addition, allele frequencies of the majority of the selected SNPs in the Greek-Cypriot population are similar to those reported in the European population. This study initiates the genetic investigation of SSc in the Greek-Cypriot population, a relatively small newly investigated population. Further investigation with a larger sample size and/or additional SSc susceptibility loci may confirm the association of some of these variants with SSc in the Greek-Cypriot population that could potentially be used for predictive testing.
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http://dx.doi.org/10.1089/gtmb.2019.0255DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232649PMC
May 2020

Transcriptome-wide association study of breast cancer risk by estrogen-receptor status.

Genet Epidemiol 2020 07 1;44(5):442-468. Epub 2020 Mar 1.

Department of Radiation Oncology, Hannover Medical School, Hannover, Germany.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.
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http://dx.doi.org/10.1002/gepi.22288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987299PMC
July 2020

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Nat Genet 2020 01 7;52(1):56-73. Epub 2020 Jan 7.

Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.

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.
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http://dx.doi.org/10.1038/s41588-019-0537-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974400PMC
January 2020

Chromatin interactome mapping at 139 independent breast cancer risk signals.

Genome Biol 2020 01 7;21(1). Epub 2020 Jan 7.

Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.

Background: Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression.

Results: We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region.

Conclusions: Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.
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http://dx.doi.org/10.1186/s13059-019-1877-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947858PMC
January 2020

A Mendelian randomization analysis of circulating lipid traits and breast cancer risk.

Int J Epidemiol 2020 08;49(4):1117-1131

Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA.

Background: Conventional epidemiologic studies have evaluated associations between circulating lipid levels and breast cancer risk, but results have been inconsistent. As Mendelian randomization analyses may provide evidence for causal inference, we sought to evaluate potentially unbiased associations between breast cancer risk and four genetically predicted lipid traits.

Methods: Previous genome-wide association studies (GWAS) have identified 164 discrete variants associated with high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), triglycerides and total cholesterol. We used 162 of these unique variants to construct weighted genetic scores (wGSs) for a total of 101 424 breast cancer cases and 80 253 controls of European ancestry from the Breast Cancer Association Consortium (BCAC). Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between per standard deviation increase in genetically predicted lipid traits and breast cancer risk. Additional Mendelian randomization analysis approaches and sensitivity analyses were conducted to assess pleiotropy and instrument validity.

Results: Corresponding to approximately 15 mg/dL, one standard deviation increase in genetically predicted HDL-C was associated with a 12% increased breast cancer risk (OR: 1.12, 95% CI: 1.08-1.16). Findings were consistent after adjustment for breast cancer risk factors and were robust in several sensitivity analyses. Associations with genetically predicted triglycerides and total cholesterol were inconsistent, and no association for genetically predicted LDL-C was observed.

Conclusions: This study provides strong evidence that circulating HDL-C may be associated with an increased risk of breast cancer, whereas LDL-C may not be related to breast cancer risk.
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http://dx.doi.org/10.1093/ije/dyz242DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750975PMC
August 2020

Vaccine confidence among parents: Large scale study in eighteen European countries.

Vaccine 2020 02 14;38(6):1505-1512. Epub 2019 Dec 14.

Pediatric Clinic, Maccabi Healthcare Services, Tel Aviv, Israel. Electronic address:

Background: Despite the fact that vaccines save 2-3 million lives worldwide every year, a percentage of children are not getting appropriately vaccinated, thus leading to disease outbreaks. One of the major reasons of low vaccine uptake in Europe is vaccine hesitancy, contributing to the recent measles outbreaks. Monitoring of vaccine hesitancy is valuable in early identification of vaccine concerns.

Methods: We performed an eighteen country European survey on parents' attitudes and behaviors regarding their children's immunization. Parents having at least one child 1-4 years old were mostly recruited by primary care paediatricians to reply to a web-based questionnaire. The questionnaire was developed by the European Academy of Paediatrics Research in Ambulatory Setting Network steering committee, based on similar surveys. An individual level hesitancy score was constructed using the answers to 21 questions, and correlations of the score with socio-demographic characteristics and types of providers were explored. To assess inter country differences, a country level self -reported confidence was defined.

Results: Fifty six percent and 24% of 5736 respondents defined themselves as "not at all hesitant", and "somewhat hesitant", respectively. Parents who consulted general practitioners were more hesitant than parents who consulted pediatricians (p < 0.05). Consultation with homeopathists was associated with the highest reported hesitancy (p < 0.05). Vaccine confidence was highest in Portugal and Cyprus, and lowest in Bulgaria and Poland.

Conclusion: The majority of parents in Europe believe in the importance of childhood vaccination. However, significant lack of confidence was found in certain European countries, highlighting the need for continuous monitoring, awareness and response plans. The possible influence of different types of healthcare providers on parental decisions demonstrated for the first time in our survey, calls for further research. Monitoring and continuous medical education efforts aimed mostly at those professionals who might not be likely to recommend vaccination are suggested.
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http://dx.doi.org/10.1016/j.vaccine.2019.11.068DOI Listing
February 2020

The :p.Arg658* truncating variant is associated with risk of triple-negative breast cancer.

NPJ Breast Cancer 2019 1;5:38. Epub 2019 Nov 1.

25University of Texas MD Anderson Cancer Center, Department of Breast Medical Oncology, Houston, TX USA.

Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes , , , , and are associated with breast cancer risk. , which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants :p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of or . These three variants were also studied functionally by measuring survival and chromosome fragility in patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that :p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44,  = 0.034 and OR = 3.79;  = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for :p.Arg658* and found that also :p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96;  = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with :p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat -associated tumors.
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http://dx.doi.org/10.1038/s41523-019-0127-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825205PMC
November 2019

Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry.

EBioMedicine 2019 Oct 16;48:203-211. Epub 2019 Oct 16.

Department of Epidemiology, Cancer Prevention Institute of California, Fremont, CA, USA; Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.

Background: We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets.

Methods: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.

Findings: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P < 2·19 × 10. The associations for four variants reached P < 5 × 10 and have been reported by previous GWAS, including rs6435074 and rs6723097 (CASP8), rs17879961 (CHEK2) and rs2853669 (TERT). The remaining eight variants were rs676387 (HSD17B1), rs762551 (CYP1A2), rs1045485 (CASP8), rs9340799 (ESR1), rs7931342 (CHR11), rs1050450 (GPX1), rs13010627 (CASP10) and rs9344 (CCND1). Further investigating these 10 genes identified associations for two additional variants at P < 5 × 10, including rs4793090 (near HSD17B1), and rs9210 (near CYP1A2), which have not been identified by previous GWAS.

Interpretation: Though most candidate gene variants were not associated with breast cancer risk, we found 14 variants showing an association. Our findings warrant further functional investigation of these variants. FUND: National Institutes of Health.
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http://dx.doi.org/10.1016/j.ebiom.2019.09.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6838373PMC
October 2019

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium.

Int J Epidemiol 2020 02;49(1):216-232

Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Background: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.

Methods: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.

Results: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.

Conclusions: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.
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http://dx.doi.org/10.1093/ije/dyz193DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426027PMC
February 2020