Morten Krebs

Jun 12, 2024 | nature.com | Joeri J. Meijsen |Kejia Hu |Morten Krebs |Georgios Athanasiadis |Sarah Washbrook |Richard Zetterberg | +14 more

AbstractMental disorders are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders. Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and near-complete genealogies of Denmark and Sweden (n = 17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six mental disorders and 15 cardiometabolic disorders.

Feb 29, 2024 | medrxiv.org | Joeri J. Meijsen |Kejia Hu |Morten Krebs |Georgios Athanasiadis

NM receives an honorarium to serve as associate editor on the European Eating Disorders Review board. OAA is a consultant to Corteechs.ai and received speaker's honorarium from Janssen, Sunovion and Lundbeck. UAV declares receiving support from EPA2023, ISTSS2022 as keynote speaker, and serves on a NordForsk expert committee on Long COVID.

Nov 29, 2023 | nature.com | Clare Palmer |Morten Krebs |Vivek Appadurai |Esben Agerbo |Anders D. Børglum |David M. Hougaard | +7 more

AbstractAttention deficit hyperactivity disorder (ADHD) is a complex disorder that manifests variability in long-term outcomes and clinical presentations. The genetic contributions to such heterogeneity are not well understood. Here we show several genetic links to clinical heterogeneity in ADHD in a case-only study of 14,084 diagnosed individuals. First, we identify one genome-wide significant locus by comparing cases with ADHD and autism spectrum disorder (ASD) to cases with ADHD but not ASD.

Nov 20, 2023 | nature.com | Andrew Dahl |Ulzee An |Morten Krebs |Vivek Appadurai |Silviu-Alin Bacanu |Thomas Werge | +3 more

AbstractBiobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each.