University of California San Francisco
Neurology

Author Of 1 Presentation

Genetics and Epigenetics Oral Presentation

PS08.04 - Polygenic Risk Score Analysis in Multiple Sclerosis

Speakers
Presentation Number
PS08.04
Presentation Topic
Genetics and Epigenetics
Lecture Time
13:27 - 13:39

Abstract

Background

The International Multiple Sclerosis Genetics Consortium (IMSGC) uncovered the contribution of inherited variants to multiple sclerosis (MS) in 115,801 individuals. Polygenic risk profiling intends to summarize and represent the genetic architecture of complex disorders and identify groups of individuals who can benefit from the knowledge of their increased susceptibility. In this context, it is important to explore the relationships between polygenic risk scores (PRS) in MS with disease status and severity in population-level and familial cohorts, in order to leverage potential clinical utilities.

Objectives

To develop and assess quantifiable measures of MS susceptibility and examine their association with phenotypic variability.

Methods

We employed both the Bayesian LDPred algorithm and Pruning and Thresholding to develop multiple MS-PRS from a multi-cohort GWAS comprising 41,505 participants. Models were validated in the UK Biobank phase 1 dataset and tested in both the UK Biobank phase 2 and the Kaiser Permanente Northern California (KPNC) MS datasets. PRS of families was tested in a cohort of 34 families with one affected parent and at least one affected child. Clinical phenotype data was used in the UCSF EPIC cohort including 742 MS patients. Standard quality control of the base (IMSGC) and target datasets was performed prior to final analyses.

Results

We observed a statistically significant difference between PRS distributions of cases and controls in both the UK Biobank and KPNC cohorts (P < 1e-70), and identified individuals at greater risk versus the rest of the population (OR > 3). We confirmed that an increased PRS in siblings of disease discordant parents is associated with a higher risk of MS and showed an enhanced power for disease prediction among siblings in a small cohort of 152 individuals. These results suggest that PRS metric shows promise for prediction of MS within sibships, but needs to be further tested in larger familial cohorts. The predictive prognostic value of PRS for selected MRI metrics and disability scores suggests that PRS modestly explain phenotypic variations.

Conclusions

Polygenic risk scores are currently the best estimate of the complex genetic architecture of MS and, when clinically implemented, could facilitate recognition and management of MS in early stages of the disease. These results provide a direction for translation of MS-GWAS studies into relevant biology and clinically meaningful outcomes.

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Presenter Of 1 Presentation

Genetics and Epigenetics Oral Presentation

PS08.04 - Polygenic Risk Score Analysis in Multiple Sclerosis

Speakers
Presentation Number
PS08.04
Presentation Topic
Genetics and Epigenetics
Lecture Time
13:27 - 13:39

Abstract

Background

The International Multiple Sclerosis Genetics Consortium (IMSGC) uncovered the contribution of inherited variants to multiple sclerosis (MS) in 115,801 individuals. Polygenic risk profiling intends to summarize and represent the genetic architecture of complex disorders and identify groups of individuals who can benefit from the knowledge of their increased susceptibility. In this context, it is important to explore the relationships between polygenic risk scores (PRS) in MS with disease status and severity in population-level and familial cohorts, in order to leverage potential clinical utilities.

Objectives

To develop and assess quantifiable measures of MS susceptibility and examine their association with phenotypic variability.

Methods

We employed both the Bayesian LDPred algorithm and Pruning and Thresholding to develop multiple MS-PRS from a multi-cohort GWAS comprising 41,505 participants. Models were validated in the UK Biobank phase 1 dataset and tested in both the UK Biobank phase 2 and the Kaiser Permanente Northern California (KPNC) MS datasets. PRS of families was tested in a cohort of 34 families with one affected parent and at least one affected child. Clinical phenotype data was used in the UCSF EPIC cohort including 742 MS patients. Standard quality control of the base (IMSGC) and target datasets was performed prior to final analyses.

Results

We observed a statistically significant difference between PRS distributions of cases and controls in both the UK Biobank and KPNC cohorts (P < 1e-70), and identified individuals at greater risk versus the rest of the population (OR > 3). We confirmed that an increased PRS in siblings of disease discordant parents is associated with a higher risk of MS and showed an enhanced power for disease prediction among siblings in a small cohort of 152 individuals. These results suggest that PRS metric shows promise for prediction of MS within sibships, but needs to be further tested in larger familial cohorts. The predictive prognostic value of PRS for selected MRI metrics and disability scores suggests that PRS modestly explain phenotypic variations.

Conclusions

Polygenic risk scores are currently the best estimate of the complex genetic architecture of MS and, when clinically implemented, could facilitate recognition and management of MS in early stages of the disease. These results provide a direction for translation of MS-GWAS studies into relevant biology and clinically meaningful outcomes.

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