In 2022, it has been 15 years since the first well-designed genome-wide association study (GWAS). Abdel Abdellaoui and Karin Verweij from Amsterdam UMC together with Loic Yengo and Peter Visscher from the University of Queensland celebrate this with an extensive review in American Journal of Human Genetics titled “15 years of GWAS discovery: Realizing the promise”. They review how GWAS facilitated an impressive range of discoveries impacting multiple fields, including complex trait genetics, population genetics, epidemiology, social science, and medicine. They discuss a wide range of topics, including the evolution of complex traits and disease risk, increasingly predictive polygenic scores, mate choice, clinical applications such as embryo selection and gene editing, and the expansion of genomics to more global populations and rare genetic variants. Read more on 15 years since the advent of the revolutionary GWAS design here: https://authors.elsevier.com/a/1gPIVgeX2XVG
In a study published in Nature Genetics, Cato Romero, Mats Nagel, and Sophie van der Sluis teamed up with colleagues from the Complex Trait Genetics department and the Million Veteran Program to scrutinize the genetic similarity of twelve psychiatric disorders.
Comorbidity among psychiatric disorders could be due to different disorders sharing the same genetic risk factors. Pinpointing genetic variants and biological processes shared between psychiatric disorders is essential to improve treatment of these debilitating disorders and can potentially even lead to genetically informed therapy (e.g., drug development, drug repurposing) and genetically informed adaptation of our diagnostic system.
In the paper by Romero et al., considerable genetic overlap was detected between psychiatric disorders in the form genetic variants (SNPs), genes, and genomic regions, to overlapping functional annotations; however, the majority of overlap was between pairs of psychiatric disorders. Only genomic regions related to evolutionary conservation were associated to most (9 out of 12) psychiatric disorders, which suggests genetic variation in essential biological processes as a common feature of psychiatric disorders.
Beyond the degree of genetic overlap, Romero et al. showed that variation in statistical power and genetic architecture crucially determines the potential success of future cross-trait genetic research. As more and more genetic data is being collected and shared, it is a matter of time before circumstances for genetic comorbidity research improve to live up to its potential.
Global genetic correlations between the twelve psychiatric disorders.
Individuals with a mental illness are much more likely to also experience other health problems. Two of the most important such ‘comorbidities’ of mental illness are the (mis)use of addictive substances and cardiovascular disease. Combined, substance use and cardiovascular disease play a driving role in decreasing quality and duration of life of individuals with mental illness. Jorien Treur, member of GENE Amsterdam, has received a Starting grant from the European Research Council (ERC) to investigate precisely how mental illness, substance use, and cardiovascular disease are connected.
What is particularly unclear, is whether there are causal effects of mental illness with substance use and cardiovascular disease. Identifying causal effects is challenging due to the multifactorial outcomes that are involved. Dr. Treur will apply several innovative epidemiological and genetic causal methods and carefully compare their results to come to reliable answers. Using the resulting information, Dr. Treur will then test how this causal knowledge affects clinical decision-making among psychiatrists.
Finally, an important focal point is ethnic diversity. Individuals of non-European ancestry are hugely underrepresented in (psychiatric) research, while they are affected by a greater disease burden. By including powerful multi-ethnic samples Jorien Treur hopes to help fill this important knowledge gap.
Induced pluripotent stem cells (iPSCs) greatly facilitate the investigation of human disease mechanisms, the characterization of patient-specific cellular phenotypes, and the development of new, personalized treatments. For brain disorders, iPSC-based disease modelling is particularly advantageous as access to primary tissue is highly restricted. However, optimal study designs with sufficient statistical power were poorly defined.
To address this problem, the research team generated immunocytochemical, electrophysiological, and proteomic data from iPSC-derived neurons of five healthy subjects, analysed variation in these data, and used this information to set up realistic power simulations. These simulations demonstrate that published case-control iPSC studies are generally underpowered.
To reach higher statistical power, isogenic designs, where mutations are generated or corrected within the same genetic background, can be used. However, these designs are limited in their generalizability. Instead, studying multiple isogenic pairs in parallel increases absolute power up to 60% or requires up to 5-fold fewer lines, while allowing generalization of the findings to the larger patient population.
To optimize statistically rigorous iPSC-based studies that will yield robust and replicable results, the research team generated a free web tool that can be used to a priori explore the power of different study designs, using any (pilot) data: https://jessiebrunner.shinyapps.io/App_PowerCurves/