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Evelin Mihailov

Evelin Mihailov

D-Index & Metrics

Genetics

D-Index
85
Citations
56439
World Ranking
1276
National Ranking
5

Overview

Evelin Mihailov is affiliated with the University of Tartu in Estonia. Their research primarily spans the fields of Medicine and Biochemistry, Genetics and Molecular Biology, with significant contributions to Genetics, Molecular Biology, Psychiatry and Mental Health, Pediatrics, Perinatology and Child Health, and Hematology.

Their scholarly output includes investigations into various topics such as Genetic Associations and Epidemiology, Birth, Development, and Health, Migraine and Headache Studies, Epigenetics and DNA Methylation, Bioinformatics and Genomic Networks, Neuroscience of Respiration and Sleep, and Genetic and Phenotypic Traits in Livestock.

Recent publications reflect a focus on large-scale genetic analyses and epidemiological studies. Notable papers include:

  • Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals (2022, Nature Genetics)
  • Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank (2020, Molecular Psychiatry)
  • Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability (2021, Nature Communications)
  • A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank (2020, Nature Communications)
  • Cross-trait analyses with migraine reveal widespread pleiotropy and suggest a vascular component to migraine headache (2020, International Journal of Epidemiology)

Their frequent collaborators include Reedik Mägi, Tõnu Esko, Jouke-Jan Hottenga, Lili Milani, and Mark J. Adams.

Publication venues where they have appeared regularly comprise UNC Libraries, Nature Communications, Molecular Psychiatry, Nature Genetics, and the International Journal of Epidemiology.

Best Publications

  • Discovery and refinement of loci associated with lipid levels

    Cristen J. Willer;Ellen M. Schmidt;Sebanti Sengupta;Gina M. Peloso;Gina M. Peloso;Gina M. Peloso

  • Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

    Naomi R. Wray;Stephan Ripke;Stephan Ripke;Stephan Ripke;Manuel Mattheisen;MacIej Trzaskowski

  • Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

    James J. Lee;Robbee Wedow;Aysu Okbay;Edward Kong

  • A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease

    M Nikpay;A Goel;Won H-H.;L M Hall

  • Defining the role of common variation in the genomic and biological architecture of adult human height

    Andrew R. Wood;Tonu Esko;Jian Yang;Sailaja Vedantam

  • Large-scale association analysis identifies new risk loci for coronary artery disease

    Panos Deloukas;Stavroula Kanoni;Christina Willenborg;Martin Farrall

  • Genetic studies of body mass index yield new insights for obesity biology

    Adam E. Locke;Bratati Kahali;Sonja I. Berndt;Anne E. Justice

  • Genome-wide association study identifies 74 loci associated with educational attainment

    Aysu Okbay;Jonathan P. Beauchamp;Mark Alan Fontana;James J. Lee

  • The genetic architecture of type 2 diabetes

    Christian Fuchsberger;Christian Fuchsberger;Jason A. Flannick;Jason A. Flannick;Tanya M. Teslovich;Anubha Mahajan

  • Modulation of genetic associations with serum urate levels by body-mass-index in humans

    Jennifer E. Huffman;Eva Albrecht;Alexander Teumer;Massimo Mangino

  • Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

    Aysu Okbay;Bart M L Baselmans;Jan-Emmanuel De Neve;Patrick Turley

  • Common variants associated with plasma triglycerides and risk for coronary artery disease

    Ron Do;Cristen J. Willer;Ellen M. Schmidt;Sebanti Sengupta

  • Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

    Anubha Mahajan;Min Jin Go;Weihua Zhang;Jennifer E. Below

  • Identification of seven loci affecting mean telomere length and their association with disease

    Veryan Codd;Christopher P Nelson;Eva Albrecht;Massimo Mangino

  • Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    Robert A Scott;Vasiliki Lagou;Ryan P Welch;Eleanor Wheeler

  • A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

    Majid Nikpay;Anuj Goel;Hong-Hee Won;Leanne M. Hall

  • Genome-wide association study identifies 74 loci associated with educational attainment

    Aysu Okbay;Jonathan P. Beauchamp;Mark Alan Fontana;James J. Lee

  • The genetic architecture of type 2 diabetes

    Christian Fuchsberger;Jason Flannick;Tanya M. Teslovich;Anubha Mahajan

  • Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

    Anubha Mahajan;Min Jin Go;Weihua Zhang;Jennifer E. Below

  • Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

    Aysu Okbay;Bart M. L. Baselmans;Jan-Emmanuel De Neve;Patrick Turley

Frequent Co-Authors

Tonu Esko
Tonu Esko University of Tartu
Andres Metspalu
Andres Metspalu University of Tartu
Panos Deloukas
Panos Deloukas Queen Mary University of London
Markus Perola
Markus Perola Finnish Institute for Health and Welfare
Kari Stefansson
Kari Stefansson deCODE Genetics (Iceland)
Veikko Salomaa
Veikko Salomaa Finnish Institute for Health and Welfare
Erik Ingelsson
Erik Ingelsson Stanford University
Albert Hofman
Albert Hofman Harvard University
Reedik Mägi
Reedik Mägi University of Tartu
Christian Gieger
Christian Gieger Helmholtz Zentrum München

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