Polygenic risk score prediction of multiple sclerosis in individuals of South Asian ancestry

Polygenic susceptibility for multiple sclerosis is associated with working memory in low-performing young adults

BACKGROUND

Multiple sclerosis (MS) is a complex disease with substantial heritability estimates. Besides typical clinical manifestations such as motor and sensory deficits, MS is characterized by structural and functional brain abnormalities, and by cognitive impairment such as decreased working memory (WM) performance.

OBJECTIVES

We investigated the possible link between the polygenic risk for MS and WM performance in healthy adults (18-35 years). Additionally, we addressed the relationship between polygenic risk for MS and white matter fractional anisotropy (FA).

METHODS

We generated a polygenic risk score (PRS) of MS susceptibility and investigated its association with WM performance in 3282 healthy adults (two subsamples, N1 = 1803, N2 = 1479). The association between MS-PRS and FA was studied in the second subsample. MS severity PRS associations were also investigated for the WM and FA measurements.

RESULTS

MS-PRS was significantly associated with WM performance within the 10% lowest WM-performing individuals (p = 0.001; pFDR = 0.018). It was not significantly associated with any of the investigated FA measurements. MS severity PRS was significantly associated with brain-wide mean FA (p = 0.041) and showed suggestive associations with additional FA measurements.

CONCLUSIONS

By identifying a genetic link between MS and WM performance this study contributes to the understanding of the genetic complexity of MS, and hopefully to the possible identification of molecular pathways linked to cognitive deficits in MS. It also contributes to the understanding of genetic associations with MS severity, as these associations seem to involve distinct biological pathways compared to genetic variants linked to the overall risk of developing MS.

Shifting our attention earlier in the multiple sclerosis disease course

PURPOSE OF REVIEW

Revisions of multiple sclerosis (MS) diagnostic criteria enable clinicians to diagnose patients earlier in the biologic disease course. Prompt initiation of therapy correlates with improved clinical outcomes. This has led to increased attention on the earliest stages of MS, including the MS prodrome and radiologically isolated syndrome (RIS). Here, we review current understanding and approach to patients with preclinical MS.

RECENT FINDINGS

MS disease biology often begins well before the onset of typical MS symptoms, and we are increasingly able to recognize preclinical and prodromal stages of MS. RIS represents the best characterized aspect of preclinical MS, and its diagnostic criteria were recently revised to better capture patients at highest risk of conversion to clinical MS. The first two randomized control trials evaluating disease modifying therapy use in RIS also found that treatment could delay or prevent onset of clinical disease.

SUMMARY

Despite progress in our understanding of the earliest stages of the MS disease course, additional research is needed to systematically identify patients with preclinical MS as well as capture those at risk for developing clinical disease. Recent data suggests that preventive immunomodulatory therapies may be beneficial for high-risk patients with RIS; though management remains controversial.

Applying a genetic risk score model to enhance prediction of future multiple sclerosis diagnosis at first presentation with optic neuritis

Optic neuritis (ON) is associated with numerous immune-mediated inflammatory diseases, but 50% patients are ultimately diagnosed with multiple sclerosis (MS). Differentiating MS-ON from non-MS-ON acutely is challenging but important; non-MS ON often requires urgent immunosuppression to preserve vision. Using data from the United Kingdom Biobank we showed that combining an MS-genetic risk score (GRS) with demographic risk factors (age, sex) significantly improved MS prediction in undifferentiated ON; one standard deviation of MS-GRS increased the Hazard of MS 1.3-fold (95% confidence interval 1.07-1.55, P < 0.01). Participants stratified into quartiles of predicted risk developed incident MS at rates varying from 4% (95%CI 0.5-7%, lowest risk quartile) to 41% (95%CI 33-49%, highest risk quartile). The model replicated across two cohorts (Geisinger, USA, and FinnGen, Finland). This study indicates that a combined model might enhance individual MS risk stratification, paving the way for precision-based ON treatment and earlier MS disease-modifying therapy.

Multiple Sclerosis Pathogenesis and Updates in Targeted Therapeutic Approaches

PURPOSE OF REVIEW

In this review, we provide a comprehensive update on current scientific advances and emerging therapeutic approaches in the field of multiple sclerosis.

RECENT FINDINGS

Multiple sclerosis (MS) is a common disorder characterized by inflammation and degeneration within the central nervous system (CNS). MS is the leading cause of non-traumatic disability in the young adult population. Through ongoing research, an improved understanding of the disease underlying mechanisms and contributing factors has been achieved. As a result, therapeutic advancements and interventions have been developed specifically targeting the inflammatory components that influence disease outcome. Recently, a new type of immunomodulatory treatment, known as Bruton tyrosine kinase (BTK) inhibitors, has surfaced as a promising tool to combat disease outcomes. Additionally, there is a renewed interested in Epstein-Barr virus (EBV) as a major potentiator of MS. Current research efforts are focused on addressing the gaps in our understanding of the pathogenesis of MS, particularly with respect to non-inflammatory drivers. Significant and compelling evidence suggests that the pathogenesis of MS is complex and requires a comprehensive, multilevel intervention strategy. This review aims to provide an overview of MS pathophysiology and highlights the most recent advances in disease-modifying therapies and other therapeutic interventions.

Decision trees to evaluate the risk of developing multiple sclerosis

Introduction

Multiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS.

Methods

This paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors.

Results

The study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease.

Discussion

Given its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease.

ADAMS project: a genetic Association study in individuals from Diverse Ancestral backgrounds with Multiple Sclerosis based in the UK

PURPOSE

Genetic studies of multiple sclerosis (MS) susceptibility and severity have focused on populations of European ancestry. Studying MS genetics in other ancestral groups is necessary to determine the generalisability of these findings. The genetic Association study in individuals from Diverse Ancestral backgrounds with Multiple Sclerosis (ADAMS) project aims to gather genetic and phenotypic data on a large cohort of ancestrally-diverse individuals with MS living in the UK.

PARTICIPANTS

Adults with self-reported MS from diverse ancestral backgrounds. Recruitment is via clinical sites, online (https://app.mantal.co.uk/adams) or the UK MS Register. We are collecting demographic and phenotypic data using a baseline questionnaire and subsequent healthcare record linkage. We are collecting DNA from participants using saliva kits (Oragene-600) and genotyping using the Illumina Global Screening Array V.3.

FINDINGS TO DATE

As of 3 January 2023, we have recruited 682 participants (n=446 online, n=55 via sites, n=181 via the UK MS Register). Of this initial cohort, 71.2% of participants are female, with a median age of 44.9 years at recruitment. Over 60% of the cohort are non-white British, with 23.5% identifying as Asian or Asian British, 16.2% as Black, African, Caribbean or Black British and 20.9% identifying as having mixed or other backgrounds. The median age at first symptom is 28 years, and median age at diagnosis is 32 years. 76.8% have relapsing-remitting MS, and 13.5% have secondary progressive MS.

FUTURE PLANS

Recruitment will continue over the next 10 years. Genotyping and genetic data quality control are ongoing. Within the next 3 years, we aim to perform initial genetic analyses of susceptibility and severity with a view to replicating the findings from European-ancestry studies. In the long term, genetic data will be combined with other datasets to further cross-ancestry genetic discoveries.