A Risk Score for Predicting Multiple Sclerosis

ObjectiveMultiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI.Methods78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals.ResultsThere was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75–0.88).InterpretationsThe risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies.     

Risk Acceptance in Multiple Sclerosis Patients on Natalizumab Treatment

Objective

We aimed to investigate the ability of natalizumab (NTZ)-treated patients to assume treatment-associated risks and the factors involved in such risk acceptance.

Methods

From a total of 185 patients, 114 patients on NTZ as of July 2011 carried out a comprehensive survey. We obtained disease severity perception scores, personality traits’ scores, and risk-acceptance scores (RAS) so that higher RAS indicated higher risk acceptance. We recorded JC virus status (JCV+/-), prior immunosuppression, NTZ treatment duration, and clinical characteristics. NTZ patients were split into subgroups (A-E), depending on their individual PML risk. Some 22 MS patients on first-line drugs (DMD) acted as controls.

Results

No differences between treatment groups were observed in disease severity perception and personality traits. RAS were higher in NTZ than in DMD patients (p<0.01). Perception of the own disease as a more severe condition tended to predict higher RAS (p=0.07). Higher neuroticism scores predicted higher RAS in the NTZ group as a whole (p=0.04), and in high PML-risk subgroups (A-B) (p=0.02). In low PML-risk subgroups (C-E), higher RAS were associated with a JCV+ status (p=0.01). Neither disability scores nor pre-treatment relapse rate predicted RAS in either group.

Conclusions

Risk acceptance is a multifactorial phenomenon, which might be partly explained by an adaptive process, in light of the higher risk acceptance amongst NTZ-treated patients and, especially, amongst those who are JCV seropositive but still have low PML risk, but which seems also intimately related to personality traits.     

Decision Analysis: A Method for Taking Uncertainties into Account in Risk-Based Decision Making

The assessment of human and ecological risks and associated risk-management decisions are characterized by only partial knowledge of the relevant systems. Typically, large variability and measurement errors in data create challenges for estimating risks and identifying appropriate management strategies. The formal quantitative method of decision analysis can help deal with these challenges because it takes uncertainties into account explicitly and quantitatively. In recent years, research in several areas of natural resource management has demonstrated that decision analysis can identify policies that are appropriate in the presence of uncertainties. More importantly, the resulting optimal decision is often different from the one that would have been chosen had the uncertainties not been taken into account quantitatively. However, challenges still exist to effective implementation of decision analysis.     

Trait Anxiety Has Effect on Decision Making under Ambiguity but Not Decision Making under Risk

Previous studies have reported that trait anxiety (TA) affects decision making. However, results remain largely inconsistent across studies. The aim of the current study was to further address the interaction between TA and decision making. 304 subjects without depression from a sample consisting of 642 participants were grouped into high TA (HTA), medium TA (MTA) and low TA (LTA) groups based on their TA scores from State Trait Anxiety Inventory. All subjects were assessed with the Iowa Gambling Task (IGT) that measures decision making under ambiguity and the Game of Dice Task (GDT) that measures decision making under risk. While the HTA and LTA groups performed worse on the IGT compared to the MTA group, performances on the GDT between the three groups did not differ. Furthermore, the LTA and HTA groups showed different individual deck level preferences in the IGT: the former showed a preference for deck B indicating that these subjects focused more on the magnitude of rewards, and the latter showed a preference for deck A indicating significant decision making impairment. Our findings suggest that trait anxiety has effect on decision making under ambiguity but not decision making under risk and different levels of trait anxiety related differently to individual deck level preferences in the IGT.     

Hippocampal Theta-Gamma Coupling Reflects State-Dependent Information Processing in Decision Making

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Metabolic State Alters Economic Decision Making under Risk in Humans

Background

Animals'' attitudes to risk are profoundly influenced by metabolic state (hunger and baseline energy stores). Specifically, animals often express a preference for risky (more variable) food sources when below a metabolic reference point (hungry), and safe (less variable) food sources when sated. Circulating hormones report the status of energy reserves and acute nutrient intake to widespread targets in the central nervous system that regulate feeding behaviour, including brain regions strongly implicated in risk and reward based decision-making in humans. Despite this, physiological influences per se have not been considered previously to influence economic decisions in humans. We hypothesised that baseline metabolic reserves and alterations in metabolic state would systematically modulate decision-making and financial risk-taking in humans.

Methodology/Principal Findings

We used a controlled feeding manipulation and assayed decision-making preferences across different metabolic states following a meal. To elicit risk-preference, we presented a sequence of 200 paired lotteries, subjects'' task being to select their preferred option from each pair. We also measured prandial suppression of circulating acyl-ghrelin (a centrally-acting orexigenic hormone signalling acute nutrient intake), and circulating leptin levels (providing an assay of energy reserves). We show both immediate and delayed effects on risky decision-making following a meal, and that these changes correlate with an individual''s baseline leptin and changes in acyl-ghrelin levels respectively.

Conclusions/Significance

We show that human risk preferences are exquisitely sensitive to current metabolic state, in a direction consistent with ecological models of feeding behaviour but not predicted by normative economic theory. These substantive effects of state changes on economic decisions perhaps reflect shared evolutionarily conserved neurobiological mechanisms. We suggest that this sensitivity in human risk-preference to current metabolic state has significant implications for both real-world economic transactions and for aberrant decision-making in eating disorders and obesity.     

Identification and Prioritization of Important Attributes of Disease-Modifying Drugs in Decision Making among Patients with Multiple Sclerosis: A Nominal Group Technique and Best-Worst Scaling

ObjectivesUnderstanding the preferences of patients with multiple sclerosis (MS) for disease-modifying drugs and involving these patients in clinical decision making can improve the concordance between medical decisions and patient values and may, subsequently, improve adherence to disease-modifying drugs. This study aims first to identify which characteristics–or attributes–of disease-modifying drugs influence patients´ decisions about these treatments and second to quantify the attributes’ relative importance among patients.MethodsFirst, three focus groups of relapsing-remitting MS patients were formed to compile a preliminary list of attributes using a nominal group technique. Based on this qualitative research, a survey with several choice tasks (best-worst scaling) was developed to prioritize attributes, asking a larger patient group to choose the most and least important attributes. The attributes’ mean relative importance scores (RIS) were calculated.ResultsNineteen patients reported 34 attributes during the focus groups and 185 patients evaluated the importance of the attributes in the survey. The effect on disease progression received the highest RIS (RIS = 9.64, 95% confidence interval: [9.48–9.81]), followed by quality of life (RIS = 9.21 [9.00–9.42]), relapse rate (RIS = 7.76 [7.39–8.13]), severity of side effects (RIS = 7.63 [7.33–7.94]) and relapse severity (RIS = 7.39 [7.06–7.73]). Subgroup analyses showed heterogeneity in preference of patients. For example, side effect-related attributes were statistically more important for patients who had no experience in using disease-modifying drugs compared to experienced patients (p < .001).ConclusionsThis study shows that, on average, patients valued effectiveness and unwanted effects as most important. Clinicians should be aware of the average preferences but also that attributes of disease-modifying drugs are valued differently by different patients. Person-centred clinical decision making would be needed and requires eliciting individual preferences.     

Cannabinoids and Multiple Sclerosis

This review discusses clinical and preclinical evidence that supports the use of cannabinoid receptor agonists for the management of multiple sclerosis. In addition, it considers preclinical findings that suggest that as well as ameliorating signs and symptoms of multiple sclerosis, cannabinoid CB₁ and/or CB₂ receptor activation may suppress some of the pathological changes that give rise to these signs and symptoms. Evidence that the endocannabinoid system plays a protective role in multiple sclerosis is also discussed as are potential pharmacological strategies for enhancing such protection in the clinic.     

Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study

BackgroundObservational studies have demonstrated an association between decreased vitamin D level and risk of multiple sclerosis (MS); however, it remains unclear whether this relationship is causal. We undertook a Mendelian randomization (MR) study to evaluate whether genetically lowered vitamin D level influences the risk of MS.ConclusionsA genetically lowered 25OHD level is strongly associated with increased susceptibility to MS. Whether vitamin D sufficiency can delay, or prevent, MS onset merits further investigation in long-term randomized controlled trials.     

An Updated Meta-Analysis of Risk of Multiple Sclerosis following Infectious Mononucleosis

Background

Multiple sclerosis (MS) appears to develop in genetically susceptible individuals as a result of environmental exposures. Epstein-Barr virus (EBV) infection is an almost universal finding among individuals with MS. Symptomatic EBV infection as manifested by infectious mononucleosis (IM) has been shown in a previous meta-analysis to be associated with the risk of MS, however a number of much larger studies have since been published.

Methods/Principal Findings

We performed a Medline search to identify articles published since the original meta-analysis investigating MS risk following IM. A total of 18 articles were included in this study, including 19390 MS patients and 16007 controls. We calculated the relative risk of MS following IM using a generic inverse variance with random effects model. This showed that the risk of MS was strongly associated with IM (relative risk (RR) 2.17; 95% confidence interval 1.97–2.39; p<10⁻⁵⁴).

Discussion

Our results establish firmly that a history of infectious mononucleosis significantly increases the risk of multiple sclerosis. Future work should focus on the mechanism of this association and interaction with other risk factors.     

Lymphocyte Transformation in Multiple Sclerosis

Lymphocytes in cultures of peripheral blood cells from patients with multiple sclerosis showed significant blastogenic transformation in the presence of human brain extract, encephalitogenic myelin basic protein, or human cerebrospinal fluid, but not in the presence of kidney extract. There was no correlation between the degree of activity of the patients'' disease and the percentage transformation of their lymphocytes.     

Progress in Multiple Sclerosis Genetics

A genetic component in the susceptibility to multiple sclerosis (MS) has long been known, and the first and major genetic risk factor, the HLA region, was identified in the 1970’s. However, only with the advent of genome-wide association studies in the past five years did the list of risk factors for MS grow from 1 to over 50. In this review, we summarize the search for MS risk genes and the latest results. Comparison with data from other autoimmune and neurological diseases and from animal models indicates parallels and differences between diseases. We discuss how these translate into an improved understanding of disease mechanisms, and address current challenges such as genotype-phenotype correlations, functional mechanisms of risk variants and the missing heritability.