Author

Katharina Schramm

Helmholtz MunichORCID 0000-0002-8809-3170Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 8 Organism:human· 7 Assay:GWAS summary statistics· 5 Research Focus:GWAS / association mapping· 4 Assay:bulk RNA-seq· 3 Research Focus:eQTL / molecular QTL mapping· 3 Research Focus:benchmarking· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Holger ProkischiD· 7 shared Anand Kumar AndiappaniD· 6 shared Johannes KettuneniD· 6 shared Markus PerolaiD· 6 shared Martina Müller‐NurasyidiD· 6 shared Mika A. P. KähöneniD· 6 shared Olli Tuomas RaitakariiD· 6 shared Samuli RipattiiD· 6 shared

Activity by Year

2014-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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7 shared papersGenetics

Holger ProkischORCID

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8 papers

Recent·Most cited

OTTERS: A powerful TWAS framework leveraging summary-level reference data

Qile Dai, Geyu Zhou, Hongyu Zhao, Urmo Võsa, Lude Franke, Alexis J. Battle, Alexander Teumer, Terho J. Lehtimäki, Olli Tuomas Raitakari, Tõnu Esko, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Wibowo Arindrarto, , Jingjing Yang

OTTERS is a TWAS framework that uses summary-level eQTL reference data to estimate eQTL weights and perform omnibus TWAS, showing improved power and applicability.

Nature Communications · Mar 7, 2023Peer-reviewedGenetics

Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis

Urmo Võsa, Annique Claringbould, Harm-Jan Westra, Marc Jan Bonder, Patrick Deelen, Biao Zeng, Holger Kirsten, Ashis Saha, Roman Kreuzhuber, Seyhan Yazar, Harm Brugge, Roy Oelen, Dylan H. de Vries, Monique G.P. van der Wijst, Silva Kasela, , Bruce M. Psaty

The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.

Nature Genetics · Sep 1, 2021Peer-reviewedGenomics

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying cardiac conduction

Ιωάννα Ντάλλα, Lu-Chen C Weng, James Cartwright, Amelia Weber Hall, Garðar Sveinbjörnsson, Nathan R. Tucker, Seung Hoan Choi, Mark D. Chaffin, Carolina Roselli, Michael R. Barnes, Borbála Mifsud, Helen R. Warren, Caroline Hayward, Jonathan Marten, James J. Cranley, , Dan M. Roden

This study identifies 210 genetic loci associated with the PR interval through multi-ancestry GWAS, highlighting their role in cardiac conduction and cardiovascular disease.

bioRxiv · Jul 30, 2019 · PreprintGenetics

Mendelian Randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Eleonora Porcu, Sina Rüeger, Kaido Lepik, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Wibowo Arindrarto, Philip Awadalla, Alexis J. Battle, Frank Beutner, Marc Jan Bonder, Dorret Irene Boomsma, Mark W. Christiansen, Annique Claringbould, , René Luijk

This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.

Nature Communications · Jul 24, 2019Peer-reviewedGenetics

Novel susceptibility loci and genetic regulation mechanisms for type 2 diabetes

Angli Xue, Yang Wu, Zhihong Zhu, Futao Zhang, Kathryn E. Kemper, Zhili Zheng, Loïc Yengo, Luke R. Lloyd‐Jones, Julia Sidorenko, Yeda Wu, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Philip Awadalla, , Jian Yang

This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.

Nature Communications · Jul 23, 2018Peer-reviewedGenetics

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Ting Qi, Yang Wu, Jian Zeng, Futao Zhang, Angli Xue, Longda Jiang, Zhihong Zhu, Kathryn E. Kemper, Loïc Yengo, Zhili Zheng, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Philip Awadalla, , Jian Yang

The paper identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.

Nature Communications · Jun 5, 2018Peer-reviewedGenetics

Genetic architecture of early childhood growth phenotypes gives insights into their link with later obesity

N. Maneka G. De Silva, Sylvain P Sebert, Alexessander Couto Alves, Ulla Sovio, Shikta Das, Hendrik Rob Taal, Nicole M. Warrington, Alex Lewin, Marika Kaakinen, Diana L. Cousminer, Elisabeth Thiering, Nicholas John Timpson, Ville Karhunen, Tom A. Bond, Xavier Estivill, , Marjo‐Riitta Järvelin

This study identifies genetic loci associated with early childhood growth phenotypes and links them to later adiposity traits, suggesting potential targets for obesity prevention.

bioRxiv · Jun 16, 2017 · PreprintGenomics

Cell specific eQTL analysis without sorting cells

Harm-Jan Westra, Danny Arends, Tõnu Esko, Marjolein J. Peters, Claudia Schurmann, Katharina Schramm, Johannes Kettunen, Hanieh Yaghootkar, Benjamin Fairfax, Anand Kumar Andiappan, Yang Li, Jingyuan Fu, Juha Karjalainen, Mathieu Platteel, Marijn Visschedijk, , Dena

The paper introduces a method for cell-specific eQTL analysis without cell sorting, showing that Crohn's disease-associated SNPs mainly affect neutrophil gene expression in whole blood data.

bioRxiv · Feb 12, 2014Genetics