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Kyriaki Michailidou

Researcher at The Cyprus Institute of Neurology and Genetics

Publications -  196
Citations -  15678

Kyriaki Michailidou is an academic researcher from The Cyprus Institute of Neurology and Genetics. The author has contributed to research in topics: Breast cancer & Genome-wide association study. The author has an hindex of 53, co-authored 173 publications receiving 12306 citations. Previous affiliations of Kyriaki Michailidou include University of South Florida & University of Copenhagen.

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Large-scale genotyping identifies 41 new loci associated with breast cancer risk

Kyriaki Michailidou, +220 more
- 01 Apr 2013 - 
TL;DR: A meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, and identified 29,807 SNPs for further genotyping suggests that more than 1,000 additional loci are involved in breast cancer susceptibility.
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Association analysis identifies 65 new breast cancer risk loci

Kyriaki Michailidou, +396 more
- 02 Nov 2017 - 
TL;DR: A genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry finds that heritability of Breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome- wide average.
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RAD51B in Familial Breast Cancer

Liisa M. Pelttari, +115 more
- 05 May 2016 - 
TL;DR: It is suggested that loss-of-function mutations in RAD 51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk.
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MicroRNA related polymorphisms and breast cancer risk

Sofia Khan, +161 more
- 12 Nov 2014 - 
TL;DR: Five miRNA binding site SNPs associated significantly with breast cancer risk are located in the 3′ UTR of CASP8, HDDC3, DROSHA, MUSTN1, and MYCL1, respectively, which belongs to miRNA machinery genes and has a central role in initial miRNA processing.
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Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Nasim Mavaddat, +310 more
TL;DR: This PRS, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset is developed and empirically validated and is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.