| Autor: |
Liam Cotter, Girish N. Nadkarni, Eric D. Achtyes, Noam D. Beckmann, Douglas S. Lehrer, Deepak Kaji, Ayman H. Fanous, Carlos N. Pato, Michael Preuss, Eric E. Schadt, Gillian M. Belbin, Alexander W. Charney, Isotta Landi, Steve McCarroll, Mark Hyman Rapaport, Tim B. Bigdeli, M. T. Pato, Loos R, Van Vleck T, Peter F. Buckley, Dolores Malaspina, Eimear E. Kenny, Benjamin S. Glicksberg |
| Rok vydání: |
2021 |
| Předmět: |
|
| Popis: |
Schizophrenia (SCZ) is the archetypal severe mental illness and one of the most deeply characterized human genetic traits. Like most common diseases SCZ is highly polygenic, and as such its genetic liability can be summarized at the individual level by a polygenic risk score (PRS). Polygenic risk scores are a cornerstone of the precision medicine vision, as it is widely anticipated they will come to serve as biomarkers of disease and poor outcomes in real-world clinical practice. However, to date, few studies have assessed their actual prognostic value relative to current standards-of-care. SCZ is an ideal test case towards this end because the predictive power of the SCZ PRS exceeds that of most other common diseases. Here, we analyzed clinical and genetic data from two multi-ethnic cohorts totaling 8,541 adults with SCZ and related psychotic disorders, assessing whether the SCZ PRS improves poor outcome prediction relative to clinical features captured in a standard psychiatric interview. For all outcomes investigated, the SCZ PRS did not improve the performance of predictive models, an observation that was generally robust to divergent case definitions and ancestral backgrounds of study participants. These findings demonstrate the limited potential of even the most powerful contemporary polygenic risk scores as a tool for individualized outcome prediction. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
