Author Of 1 Presentation
PS08.04 - Polygenic Risk Score Analysis in Multiple Sclerosis
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.
To develop and assess quantifiable measures of MS susceptibility and examine their association with phenotypic variability.
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.
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.
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.
Author Of 3 Presentations
P0063 - Development of a Custom Multivariate Proteomic Serum Based Assay for Association with Radiographic and Clinical Endpoints in MS (ID 833)
Multiple Sclerosis (MS) is a complex and heterogeneous disease. Investigating the biological pathways and cell types involved in MS pathophysiology as represented by protein biomarker expression can help inform the development of tools to monitor disease activity, disease progression, identify early evidence of relapse, and monitor treatment response.
To develop a blood based multiplex proteomic assay that associates with clinical and radiographic endpoints in patients with MS. These endpoints include the presence of gadolinium-enhanced (Gd+) lesions, Annualized Relapse Rate (ARR) and clinically defined relapse status (active versus stable).
Serum samples (n=690 in total) from multiple deeply-phenotyped cohorts (ACP, CLIMB and EPIC) were tested in immunoassays for the measurement of 1196 proteins using Proximity Extension Assays (PEA) from OlinkTM and for 215 proteins using xMAPTM immunoassays from Myriad RBM, Inc. (RBM). Associated radiographic and clinical endpoints at the time of the blood draw were correlated with the protein levels. Twenty-one proteins were selected for inclusion in a custom assay based on their performance in univariate and multivariate statistical models, and replication across independent cohorts. Biological pathway modeling and network analysis were performed to ensure comprehensive representation of MS neurophysiology. Area under the curve (AUC) was selected as the key metric for model performance evaluation.
Multivariate statistical ensembles restricted to the expression levels of the biomarkers selected for the custom assay achieved AUC performance of 0.827 for classification of the presence of Gd+ lesions, 0.802 for classification of clinically defined relapse status, and 0.930 for the classification of patients with Low ARR (≤0.2 relapses) vs High ARR (≥1.0 relapses). A multivariate model utilizing shifts in biomarker expression in longitudinally paired samples achieved the highest observed performance of 0.950 for classification of Gd+ lesion presence. In each case, the multivariate models significantly outperformed (p-value <0.05) the AUC of the highest performing univariate biomarker.
Multivariate models restricted to the 21 selected proteins effectively classified several radiographic and clinical endpoints with stronger performance than any single biomarker. A 21-plex custom assay panel is being developed for further investigation and validation using additional cohorts.
P0671 - Exploring the gut microbiome in multiple sclerosis via the international MS Microbiome Study (iMSMS) (ID 1532)
- S. Singh
- M. Mendoza
- R. Baumann
- J. Landefeld
- P. Casaccia
- I. Katz Sand
- Z. Xia
- H. Weiner
- T. Chitnis
- S. Chandran
- P. Connick
- D. Oteagui
- T. Castillo-Trivino
- S. Caillier
- A. Santaniello
- G. Ackermann
- G. Humphrey
- L. Negrotto
- M. Farez
- R. Hohlfeld
- A. Pröbstel
- X. Jia
- J. Graves
- A. Bar-Or
- H. Wekerle
- J. Oksenberg
- T. West
- J. Correale
- B. Cree
- S. Hauser
- R. Knight
- S. Baranzini
The gut microbiota is emerging as a critical regulator of immune responses and appears to play an important role in MS. The International Multiple Sclerosis Microbiome study (iMSMS) is a global collaboration aimed at elucidating the role of commensal gut bacteria in MS by acquiring and analyzing samples from 2000 patients and 2000 household healthy controls.
The iMSMS focuses on identifying the microbes, genes and pathways that are involved in MS pathogenesis and on investigating how the microbiome changes response to treatment.
A total of 576 case and household healthy control pairs were recruited from 7 centers located in the US (West and East coasts), Europe and South America. Stool samples were collected and evaluated by both 16S and shallow whole metagenome shotgun sequencing. Univariate and multivariate linear regression analyses were conducted to understand patterns of variation on gut microbiome.
This is the largest MS microbiome study reported to date. Our results showed a statistically significant difference of beta diversity between MS and healthy controls for the first time in MS. Intriguingly, multiple species of Akkermansia, including the known mucin-degrading bacterium Akkermansia muciniphila, were significantly enriched in untreated MS patients after adjusting for confounding factors, but the difference was not detected in treated MS group versus control. Ruminococcus torques and Eisenbergiella tayi were also among the top significantly enriched bacteria in MS. Inversely, a main butyrate producer, Faecalibacterium prausnitzii, was significantly decreased in the untreated MS group. Functional pathways of L-tryptophan biosynthesis and L-threonine biosynthesis were slightly increased in untreated MS patients, while 5-aminoimidazole ribonucleotide biosynthesis I was increased in the treated group.
Our large household-controlled study allowed us to identify modest but statistically robust MS-associated changes in bacterial composition and functions. It provides the foundation for all future studies of the gut microbiota in MS. The strain-level genomic variation and microbiome-derived molecules need to be further explored for understanding microbial adaptation and pathogenicity.
P1005 - An electronic, unsupervised Patient Reported Expanded Disability Status Scale for Multiple Sclerosis (ID 1921)
In persons with multiple sclerosis (MS), the Expanded Disability Status Scale (EDSS) is the criterion standard for assessing disability, but its in-person nature constrains patient participation in research and clinical assessments.
To develop and validate a scalable, electronic, unsupervised patient-reported EDSS (ePR-EDSS) that would capture MS-related disability across the spectrum of severity.
We enrolled 136 adult MS patients, split into a preliminary testing Cohort 1 (n=50), and a validation Cohort 2 (n=86), which was evenly distributed across EDSS groups. Each patient completed an ePR-EDSS either immediately before or after a MS clinician’s Neurostatus EDSS (NS-EDSS) evaluation. The final ePR-EDSS version includes 23 questions, takes between 7-12 minutes to complete (based on time measured for Cohort 2 participants), and can be accessed at https://openmsbioscreen.ucsf.edu/predss/about.
In Cohort 2, mean age was 50.6 years (range 26-80) and median EDSS was 3.5 (IQR 1.5, 5.5). The ePR-EDSS and EDSS agreed within 1-point for 86% of examinations; kappa for agreement within 1-point was 0.85 (p<0.001). The correlation coefficient between the two measures was 0.91 (<0.001). For individual functional systems, complete agreement was highest for the brainstem score (55.8%) and lowest for the sensory score (31.4%). In sensitivity analyses adjusted for NS-EDSS, the absolute difference between ePR-EDSS and NS-EDSS was not significantly related to age, sex, disease duration, years of education, or the timepoint at which the ePR-EDSS tool was assessed (before/after neurological exam).
The ePR-EDSS is unique compared to other published tools - it can be accessed and performed by the patient without any supervision, is freely and openly available, has built-in logic to calculate functional system and total scores, and is validated over a wide NS-EDSS range. It demonstrated high correlation with NS-EDSS, with good agreement even at lower EDSS levels. For clinical care, the ePR-EDSS could enable the longitudinal monitoring of a patient’s disability. For research, it provides a valid and rapid measure across the entire spectrum of disability and permits broader participation with fewer in-person assessments.