Janahi, Mohammed;
(2025)
Polygenic Scores for Normative Models: Development and Applications.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Normative modeling considers disease as an outlier in a distribution of healthy con- trols. Genetics account for a significant portion of variability in both healthy and diseased subjects. This thesis demonstrates that accounting for genetics in nor- mative models through a novel Multi-Threshold polygenic score (Multi-Threshold- PGS) method improves their accuracy and clinical utility. It also establishes that the Multi-Threshold-PGS is useful outside the context of normative models and in both disease and quantitative traits. I first determine that stratifying normative models (nomograms) of Hippocam- pal Volume (HV) using a HV Polygenic Score (PGS) computed at a single p-value threshold shifts nomograms significantly in both UKBB and ADNI as predicted by the PGS. The magnitude of the shift corresponded to ∼three years of normal aging for a 65-year-old. I found that HV PGS independently correlated to HV across thresholds, with the order in one score being unpredictive of the score in an- other. I next showed that compounding PGS increased the nomogram shift. Across 12,720 models, summing any 2 PGSs increased separation by 22%, and Multi- Threshold-PGS by 60%. Multi-Threshold-PGS provided significant correlations to 9 neurocognitive assessments both cross-sectionally and longitudinally in three out- of-sample datasets. Next, I showed that MAF-based PGSs were well correlated to each other and proved an inferior basis for Multi-Threshold-PGS compared to their p-value coun- terparts. I finally showed that Multi-Threshold-PGS provided benefits in disease traits and outside the context of normative modeling. Multi-Threshold-PGSs of Alzheimer’s Disease (AD) provided significantly better results in four different experimental setups and in out-of-sample data. Overall, Multi-Threshold-PGS provided improvements in a broad range of applications. My results show that PGS and normative modeling can be developed to provide significant utility in both the clinic and clinical trials. Future work will explore the benefits of Multi-Threshold-PGS in other neurocognitive applications and improve this PGS further with pathway-informed construction.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Polygenic Scores for Normative Models: Development and Applications |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10205131 |
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