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Approved Research

Complex trait analysis from genotype, and low-pass cell-free and ancient DNA sequence data in structured populations.

Principal Investigator: Professor Toomas Kivisild
Approved Research ID: 95216
Approval date: March 28th 2023

Lay summary

Complex traits are influenced both by environmental and genetic factors. Typically, the genetic component of a complex trait consists of many genetic variants, which each have a small effect on the trait. A polygenic risk score combines the effect of these variants into a single genetic risk score, thus representing someone's genetic risk to develop the disease or show a particular trait. As such, these scores are promising tools to be used in clinic and precision medicine. A polygenic risk score is most commonly calculated from high quality SNP array data.  Low-coverage sequence data, such as maternal cell-free DNA from non-invasive prenatal testing (NIPT, typically performed to detect fetal abnormalities such as trisomy 21 in early pregnancy) or ancient DNA would however be an important alternative source. Since both the maternal cfDNA and ancient DNA are of very low concentration, missing genotypes need to be imputed. It is not clear, however, what impact sequence coverage and damage, fetal fraction and other factors affecting imputation accuracy altogether have on the PRS estimation of different phenotypic traits in the presence of different levels of population stratification. In this project we will use both genotype and low-pass sequence data from NIPT and ancient DNA samples of different genetic ancestries to assess the performance of different imputation and polygenic risk score estimation tools. Complex traits with different genetic architecture represented in the UK Biobank data will be used to evaluate the accuracy and potential biases in inference of polygenic risk scores. Our main clinically relevant focus will be on pregnancy related complex traits such as preeclampsia, SLE, gestational diabetes. In addition, other clinical phenotypes of interest, such as cancer (e.g. breast cancer), neurological diseases (e.g. Alzheimer's disease), immune disorders (e.g. inflammatory bowel disease)  will also be considered.