Stressful life events are associated with the risk of multiple sclerosis

An analytical review on the use of artificial intelligence and machine learning in diagnosis, prediction, and risk factor analysis of multiple sclerosis

Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurological disorder damages nerve cell sheaths, with treatments focusing on symptom relief. Manual MS detection is time-consuming and error prone. Though MS lesion detection has been studied, limited attention has been paid to clinical analysis and computational risk factor prediction. Artificial intelligence (AI) techniques and Machine Learning (ML) methods offer accurate and effective alternatives to mapping MS progression. However, there are challenges in accessing clinical data and interdisciplinary collaboration. By analyzing 103 papers, we recognize the trends, strengths and weaknesses of AI, ML, and statistical methods applied to MS diagnosis. AI/ML-based approaches are suggested to identify MS risk factors, select significant MS features, and improve the diagnostic accuracy, such as Rule-based Fuzzy Logic (RBFL), Adaptive Fuzzy Inference System (ANFIS), Artificial Neural Network methods (ANN), Support Vector Machine (SVM), and Bayesian Networks (BNs). Meanwhile, applications of the Expanded Disability Status Scale (EDSS) and Magnetic Resonance Imaging (MRI) can enhance MS diagnostic accuracy. By examining established risk factors like obesity, smoking, and education, some research tackled the issue of disease progression. The performance metrics varied across different aspects of MS studies: Diagnosis: Sensitivity ranged from 60 % to 98 %, specificity from 60 % to 98 %, and accuracy from 61 % to 97 %. Prediction: Sensitivity ranged from 76 % to 98 %, specificity from 65 % to 98 %, and accuracy from 62 % to 99 %. Segmentation: Accuracy ranged up to 96.7 %. Classification: Sensitivity ranged from 78 % to 97.34 %, specificity from 65 % to 99.32 %, and accuracy from 71 % to 97.94 %. Furthermore, the literature shows that combining techniques can improve efficiency, exploiting their strengths for better overall performance.

Psycho-Neuroendocrinology in the Rehabilitation Field: Focus on the Complex Interplay between Stress and Pain

Chronic stress and chronic pain share neuro-anatomical, endocrinological, and biological features. However, stress prepares the body for challenging situations or mitigates tissue damage, while pain is an unpleasant sensation due to nociceptive receptor stimulation. When pain is chronic, it might lead to an allostatic overload in the body and brain due to the chronic dysregulation of the physiological systems that are normally involved in adapting to environmental challenges. Managing stress and chronic pain (CP) in neurorehabilitation presents a significant challenge for healthcare professionals and researchers, as there is no definitive and effective solution for these issues. Patients suffering from neurological disorders often complain of CP, which significantly reduces their quality of life. The aim of this narrative review is to examine the correlation between stress and pain and their potential negative impact on the rehabilitation process. Moreover, we described the most relevant interventions used to manage stress and pain in the neurological population. In conclusion, this review sheds light on the connection between chronic stress and chronic pain and their impact on the neurorehabilitation pathway. Our results emphasize the need for tailored rehabilitation protocols to effectively manage pain, improve treatment adherence, and ensure comprehensive patient care.

Adverse Childhood Experiences and the Risk of Multiple Sclerosis Development: A Review of Potential Mechanisms

Adverse childhood experiences (ACEs), such as abuse, neglect, and household dysfunction, contribute to long-term systemic toxic stress and inflammation that may last well into adulthood. Such early-life stressors have been associated with increased susceptibility to multiple sclerosis (MS) in observational studies and with the development of experimental autoimmune encephalomyelitis in animal models. In this review, we summarize the evidence for an ACE-mediated increase in MS risk, as well as the potential mechanisms for this association. ACEs dysregulate neurodevelopment, stress responses, and immune reactivity; they also alter the interplay between the immune system and neural networks. All of this may be relevant for MS risk. We further discuss how ACEs induce epigenetic changes and how the toxic stress caused by ACEs may reactivate the Epstein-Barr Virus (EBV), a key risk factor for MS. We conclude by suggesting new initiatives to obtain further insights into this topic.

Effects of Psychological Stress on Multiple Sclerosis via HPA Axis-mediated Modulation of Natural Killer T Cell Activity

The involvement of psychological stress and Natural Killer T (NKT) cells in the pathophysiology of multiple sclerosis has been identified in the progression of this disease. Psychological stress can impact disease occurrence, relapse, and severity through its effects on the Hypothalamic- Pituitary-Adrenal (HPA) axis and immune responses. NKT cells are believed to play a pivotal role in the pathogenesis of multiple sclerosis, with recent evidence suggesting their distinct functional alterations following activation of the HPA axis under conditions of psychological stress. This review summarizes the associations between psychological stress, NKT cells, and multiple sclerosis while discussing the potential mechanism for how NKT cells mediate the effects of psychological stress on this disease.

The social readjustment rating scale: Updated and modernised

The Social Readjustment Rating Scale, originally devised in 1967 by Holmes and Rahe, measures the impact of life events stress. At the time, the SRRS advanced its field of research by standardising the impact of stress with a set of independently derived weights called 'life change units' (LCUs) for 43 life events found to predict illness onset. The scale has been criticised for being outdated, e.g. "Mortgage over $10,000" and biased, e.g. "Wife begin or stop work". The aim of this cross-sectional survey study is to update and improve the SRRS whilst allowing backwards compatibility. We successfully updated the SRRS norms/LCUs using the ratings of 540 predominantly UK adults aged 18 to 84. Moreover, we also updated wording of 12 SRRS items and evaluated the impact of demographics, personal experience and loneliness. Using non-parametric frequentist and Bayesian statistics we found that the updated weights were higher but broadly consistent with those of the original study. Furthermore, changes to item wording did not affect raters' evaluations relative to the original thereby ensuring cross-comparability with the original SRRS. The raters were not unduly influenced by their personal experiences of events nor loneliness. The target sample was UK rather than US-based and was proportionately representative regarding age, sex and ethnicity. Moreover, the age range was broader than the original SRRS. In addition, we modernised item wording, added one optional extra item to the end of the scale to evaluate the readjustment to living alone and identified 3 potential new items proposed by raters. Backwards-compatibility is maintained.

Impact of the first Gulf war on multiple sclerosis risk in Kuwait: a quasi-experimental study

OBJECTIVE

It has been reasoned that stressful life events tend to alter immune function thereby increasing the susceptibility to autoimmune diseases including multiple sclerosis (MS). Using the database of Kuwait National MS Registry, this quasi-experimental study assessed the impact of the first Gulf War (Iraqi invasion of Kuwait in 1990) on MS risk in Kuwait.

METHODS

MS incidence data from 1980 to 2019 were obtained from the Kuwait National MS Registry. Annual age-standardized incidence rates (ASIRs) (per 10⁵ person-years) were computed using the World Standard Population as a reference. Interrupted time series analysis with the option of autoregressive order (1) was used to evaluate the impact of the first Gulf War on MS risk by treating 1990 as an intervention year.

RESULTS

Estimated baseline annual ASIR (per 10⁵ person-years) was 0.38 (95% CI: -1.02, 1.78; p = 0.587). MS ASIRs (per 10⁵ person-years) tended to increase significantly every year prior to 1990 by 0.45 (ASIR per 10⁵ person-years = 0.45; 95% CI: 0.15, 0.76; p = 0.005). During the first year of the first Gulf War, there seemed to be a non-significant increase (step change) in ASIRs (per 10⁵ person-years) of MS (ASIR per 10⁵ person-years = 0.85; 95% CI: - 5.16, 6.86; p = 0.775) followed by a non-significant increase in the annual trend in MS ASIRs per 10⁵ person-years (relative to the preintervention trend i.e., the difference between the pre-first Gulf War versus the post-first Gulf War trends) by 0.65 (ASIR per 10⁵ person-years = 0.65; 95% CI: - 0.22, 1.52; p = 0.138). However, a postestimation measure of the post-first Gulf War trend was statistically significant (ASIR per 10⁵ person-years = 1.10; 95% CI: 0.40, 1.80; p = 0.003), which implies that the post-first Gulf War trend in the annual ASIRs (per 10⁵ person-years) inclined to be the same as was the pre-first Gulf War (i.e., counterfactual of the pre-first Gulf War trend in annual ASIRs (per 10⁵ person-years) as if no first Gulf War took place).The Durbin-Watson test statistic (d = 1.89) showed almost non-significant autocorrelations across the time series observations on ASIRs (per 10⁵ person-years).

CONCLUSIONS

This study suggests that the first Gulf War was not significantly associated with the increasing trend in MS risk at population level in Kuwait neither with any short-term change nor with secular trend. Future studies may consider confirming the role of conflict-related stress or other stressful life events in potential exacerbation of MS risk along with unraveling biologically plausible mechanistic pathways.

Abuse and revictimization in adulthood in multiple sclerosis: a cross-sectional study during pregnancy

BACKGROUND

Knowledge concerning exposure to abuse in adulthood and in pregnancy in people with multiple sclerosis (MS) is sparse.

OBJECTIVE

To determine the occurrence of adult abuse and abuse in relation to pregnancy in women with MS and their risk of revictimization (repeated abuse as adults after childhood abuse).

METHODS

This cross-sectional study comprised pregnant women from the Norwegian Mother, Father and Child Cohort study. Information on abuse was acquired through self-completed questionnaires. We used logistic regression to estimate adjusted odds ratios (aORs) with 95% confidence intervals (CIs).

RESULTS

We identified 106 women with MS at enrollment through linkage with national health registries. The reference group consisted of 77,278 women without MS. Twenty-seven women (26%) with MS reported any adult abuse compared to 15,491 women (20%) without MS, aOR 1.33 (0.85-2.09). Twenty-two (21%) women with MS reported systematic emotional abuse compared to 13% without MS, aOR 1.75 (1.08-2.83). Ten women (10%) with MS reported sexual abuse, compared to 6% without MS, aOR 1.72 (0.89-3.33). More women with MS reported rape as an adult, aOR 2.37 (1.02-5.49). Women with MS had higher risk of revictimization as adults, after childhood abuse, aOR 2.23 (1.22-4.10). The risk of abuse during pregnancy or 6 months preceding pregnancy was similar between the groups.

CONCLUSIONS

Women with MS had increased occurrence of systematic emotional abuse, rape, and revictimization as adults, compared to women without MS.

Association of adverse childhood experiences with the development of multiple sclerosis

OBJECTIVE

To study whether exposure to childhood emotional, sexual or physical abuse is associated with subsequent multiple sclerosis (MS) development.

METHODS

A nationwide, prospective cohort study based on participants in the Norwegian Mother, Father and Child cohort study. Enrolment took place 1999-2008, with follow-up until 31 December 2018. Childhood abuse before age 18 years was obtained from self-completed questionnaires. We identified MS diagnoses through data-linkage with national health registries and hospital records. The Cox model was used to estimate HRs for MS with 95% CIs, adjusting for confounders and mediators.

RESULTS

In this prospective cohort study, 14 477 women were exposed to childhood abuse and 63 520 were unexposed. 300 women developed MS during the follow-up period. 71 of these (24%) reported a history of childhood abuse, compared with 14 406 of 77 697 (19%) women that did not develop MS. Sexual abuse (HR 1.65, 95% CI 1.13 to 2.39) and emotional abuse (HR 1.40, 95% CI 1.03 to 1.90) in childhood were both associated with an increased risk of developing MS. The HR of MS after exposure to physical abuse was 1.31 (95% CI 0.83 to 2.06). The risk of MS was further increased if exposed to two (HR 1.66, 95% CI 1.04 to 2.67) or all three abuse categories (HR 1.93, 95% CI 1.02 to 3.67).

INTERPRETATION

Childhood sexual and emotional abuse were associated with an increased risk of developing MS. The risk was higher when exposed to several abuse categories, indicating a dose-response relationship. Further studies are needed to identify underlying mechanisms.

Demand with low supply: A pipeline for personalized integrative medicine in multiple sclerosis

Timely personalized medicine is an unmet, critical need in multiple sclerosis (MS). A major barrier to providing individualized care is the lack of information on which interventions are most appropriate for whom. In this viewpoint, we submit a rationale and three-step roadmap to personalized integrative medicine. This multidisciplinary team approach requires that we (1) comprehensively assess whole health at diagnosis, (2) appropriately integrate data within electronic health record systems and leverage machine learning to analyze big data, and (3) design, test, and deliver multimodal interventions. Using a whole-person approach to assessment and intervention, we will be better informed to provide personalized care at the level of the individual.

Genetic, Environmental and Lifestyle Determinants of Accelerated Telomere Attrition as Contributors to Risk and Severity of Multiple Sclerosis

Telomeres are protective structures at the ends of linear chromosomes. Shortened telomere lengths (TL) are an indicator of premature biological aging and have been associated with a wide spectrum of disorders, including multiple sclerosis (MS). MS is a chronic inflammatory, demyelinating and neurodegenerative disease of the central nervous system. The exact cause of MS is still unclear. Here, we provide an overview of genetic, environmental and lifestyle factors that have been described to influence TL and to contribute to susceptibility to MS and possibly disease severity. We show that several early-life factors are linked to both reduced TL and higher risk of MS, e.g., adolescent obesity, lack of physical activity, smoking and vitamin D deficiency. This suggests that the mechanisms underlying the disease are connected to cellular aging and senescence promoted by increased inflammation and oxidative stress. Additional prospective research is needed to clearly define the extent to which lifestyle changes can slow down disease progression and prevent accelerated telomere loss in individual patients. It is also important to further elucidate the interactions between shared determinants of TL and MS. In future, cell type-specific studies and advanced TL measurement methods could help to better understand how telomeres may be causally involved in disease processes and to uncover novel opportunities for improved biomarkers and therapeutic interventions in MS.

Stressful life events and the risk of primary progressive multiple sclerosis: A population-based case-control study

BACKGROUND

The onset and presentation of primary progressive multiple sclerosis (PPMS) like any other autoimmune diseases can be triggered by unexpected lifetime stressful events, which require to be assessed in order to minimize our exposure to such events as much as possible.

OBJECTIVE

The aim of the present study was to determine the possible role of socioeconomic status (SES) and stressful events in PPMS development METHODS: The present population-based case-control study recruited PPMS cases and healthy controls from the general population during 2019-2020 in Tehran, Iran. Clinical diagnosis of cases was based on the 2017 McDonald criteria and confirmed by a neurologist. The selection of sex-matched controls from the same source population of cases was performed using the standard method of Random Digit Dialing (RDD). The study questionnaire was filled out over telephone interviews. Matched logistic regression was administered to estimate the adjusted and unadjusted odds ratio (OR) at 95% confidence intervals (CIs) adjusted for sex, age, and marital status using SPSS 23.

RESULTS

This study examined 146 PPMS cases and 294 controls. Mean ages (SD) for cases and controls were 46.97 (9.4) and 37.67 (6.12), respectively (P < 0.001). No stressful events over five years prior to the disease onset were associated with an increased risk of PPMS. Marriage (OR: 0.04; 95% CI (0.01- 0.37), P = 0.004), close family members' serious disease (OR: 0.10; 95% CI (0.02-0.60), P = 0.01), and being in debt (OR: 0.03; 95% CI (0-0.37), P = 0.006) were found to have a negative association with the risk of disease occurrence. Death of a loved one, family disruption, jail term, homelessness period, Conquer(national university entrance exam), death of spouse, getting fired from a job, joblessness, divorce, migration, close family members' suicide, and retirement were not associated with the risk of PPMS (P > 0.05). History of depression before the PPMS presentation was considerably associated with the incidence of PPMS (P < 0.001). Self-rated health status was scored noticeably lower by cases as compared with controls (P < 0.001). Participants with the paternal educational degree of guidance school showed a higher risk of PPMS by 2.83 time (OR: 2.83; 95% CI (1.02 - 7.80), P = 0.04) than participants with university educated fathers. In total, SES during adolescence did not indicate any association with the risk of PPMS (with the exception of levels 2 (P = 0.02) and 7 (P = 0.05)).

CONCLUSION

No stressful life events were identified as possible increasing risk factors for PPMS. Marriage, close family members' serious disease, and being in debt had a negative association with the disease risk. The history of depression may elevate the risk of PPMS. While the highest and lowest SES levels in adolescence were not remarkable determiners for PPMS, levels 2 and 7 had a positive association with the risk of PPMS. The maternal educational level was not an important factor; however, the paternal educational degree of guidance school as compared to university degree made individuals more susceptible to PPMS. Self-rated health status score was higher in controls.

Current review and next steps for artificial intelligence in multiple sclerosis risk research

In the last few decades, the prevalence of multiple sclerosis (MS), a chronic inflammatory disease of the nervous system, has increased, particularly in Northern European countries, the United States, and United Kingdom. The promise of artificial intelligence (AI) and machine learning (ML) as tools to address problems in MS research has attracted increasing interest in these methods. Bayesian networks offer a clear advantage since they can integrate data and causal knowledge allowing for visualizing interactions between dependent variables and potential confounding factors. A review of AI/ML research methods applied to MS found 216 papers using terms "Multiple Sclerosis", "machine learning", "artificial intelligence", "Bayes", and "Bayesian", of which 90 were relevant and recently published. More than half of these involve the detection and segmentation of MS lesions for quantitative analysis; however clinical and lifestyle risk factor assessment and prediction have largely been ignored. Of those that address risk factors, most provide only association studies for some factors and often fail to include the potential impact of confounding factors and bias (especially where these have causal explanations) that could affect data interpretation, such as reporting quality and medical care access in various countries. To address these gaps in the literature, we propose a causal Bayesian network approach to assessing risk factors for MS, which can address deficiencies in current epidemiological methods of producing risk measurements and makes better use of observational data.