Author

Dimitris Dikeos

National and Kapodistrian University of Athens

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetic & Genomic Medicine· 5 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 6 Approach:statistical model· 6 Research Focus:GWAS / association mapping· 5 Assay:GWAS summary statistics· 4 Research Focus:fine-mapping· 3 Research Focus:gene regulatory network inference· 2 Approach:Bayesian inference· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Ditte DemontisiD· 6 shared Srdjan DjuroviciD· 6 shared David CoheniD· 5 shared Esben AgerboiD· 5 shared Farooq Amin M. D· 5 shared Frank DudbridgeiD· 5 shared Franziska DegenhardtiD· 5 shared Giulio GenoveseiD· 5 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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6 shared papersGenetic & Genomic Medicine

Ditte DemontisORCID

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6 papers

Recent·Most cited

Genome-wide association studies identify 77 loci for suicidality and provide novel biological insights

Sarah M. C. Colbert, Maria Koromina, Alexander S Hatoum, Mallory Stephenson, Alexis C. Edwards, Emma C. Johnson, Xuejun Qin, Andrey A Shabalin, Lucas T Ito, Kevin S O’Connell, Arvid Harder, Jens Hjerling-Leffler, Min Ji Kim, Ikuo Otsuka, Laura Vilar‐Ribó, , Bharath Holla

This study identifies 77 genetic loci associated with suicidality through genome-wide association analyses across multiple cohorts and provides biological insights into its genetic architecture.

medRxiv · Oct 22, 2025 · PreprintGenetic & Genomic Medicine

Distinct genetic liability profiles define clinically relevant patient strata across common diseases

Lucia Trastulla, Georgii V. Dolgalev, Sylvain Moser, Laura T. Jiménez-Barrón, Till F. M. Andlauer, Moritz von Scheidt, Douglas M. Ruderfer, Stephan Ripke, Andrew McQuillin, Eli A. Stahl, Enrico Domenici, Rolf Adolfsson, Ingrid Agartz, Esben Agerbo, Margot Albus, , Thomas Folkmann Hansen

The paper identifies genetically distinct patient subgroups across diseases by analyzing polygenic risk and pathway convergence.

Nature Communications · Jul 1, 2024Peer-reviewedGenetic & Genomic Medicine

Using brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia

Yu-Han H. Hsu, Greta Pintacuda, Ruize Liu, Eugeniu Nacu, April Kim, Kalliopi Tsafou, Natalie Petrossian, William J. Crotty, Jung Min Suh, Jackson Riseman, Jacqueline M. Martín, Julia C. Biagini, Daya Mena, Joshua K.T. Ching, Edyta Małolepsza, , Ina Giegling

The paper uses brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia and identifies enriched networks and genes associated with the disease.

iScience · Apr 18, 2023Peer-reviewedGenetic & Genomic Medicine

Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia

Vassily Trubetskoy, Antonio F. Pardiñas, Ting Qi, Georgia Panagiotaropoulou, Swapnil Awasthi, Tim B. Bigdeli, Julien Bryois, Chia‐Yen Chen, Charlotte A. Dennison, Lynsey S. Hall, Max Lam, Kyoko Watanabe, Oleksandr Frei, Tian Ge, Janet C Harwood, , Elliot S. Gershon

A genome-wide association study of 69,369 schizophrenia cases and 236,642 controls identifies 270 risk loci, prioritizes 130 genes, and links common and rare risk variants to neuronal synaptic biology.

Nature · Apr 8, 2022Peer-reviewedGenetic & Genomic Medicine✦ In-depth digest

Sex-Dependent Shared and Non-Shared Genetic Architecture Across Mood and Psychotic Disorders

Gabriëlla A.M. Blokland, Jakob Grove, Chia‐Yen Chen, Chris J. Cotsapas, Stuart A. Tobet, Robert J. Handa, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James Walters, Kai-How Farh, Peter Holmans, Phil Lee, Brendan K Bulik-Sullivan, David Andrew Collier, , Joel N. Hirschhorn

This study identifies sex-dependent genetic risk loci shared and specific to mood and psychotic disorders using genome-wide interaction analysis.

Biological Psychiatry · Jan 1, 2022Peer-reviewedGenetics

A comparison of ten polygenic score methods for psychiatric disorders applied across multiple cohorts

Guiyan Ni, Jian Zeng, Joana A. Revez, Ying Wang, Zhili Zheng, Tian Ge, Restuadi Restuadi, Jacqueline Kiewa, Dale R. Nyholt, Jonathan R. I. Coleman, Jordan W. Smoller, Stephan Ripke, Benjamin M. Neale, Aiden Peter Corvin, James Walters, , Vahram H. Haroutunian

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

Biological Psychiatry · May 3, 2021Peer-reviewedGenetic & Genomic Medicine