António Martins da Silva

Epilepsy, hippocampal sclerosis and febrile seizures linked by common genetic variation around SCN1A

Epilepsy comprises several syndromes, amongst the most common being mesial temporal lobe epilepsy with hippocampal sclerosis. Seizures in mesial temporal lobe epilepsy with hippocampal sclerosis are typically drug-resistant, and mesial temporal lobe epilepsy with hippocampal sclerosis is frequently associated with important co-morbidities, mandating the search for better understanding and treatment. The cause of mesial temporal lobe epilepsy with hippocampal sclerosis is unknown, but there is an association with childhood febrile seizures. Several rarer epilepsies featuring febrile seizures are caused by mutations in SCN1A, which encodes a brain-expressed sodium channel subunit targeted by many anti-epileptic drugs. We undertook a genome-wide association study in 1018 people with mesial temporal lobe epilepsy with hippocampal sclerosis and 7552 control subjects, with validation in an independent sample set comprising 959 people with mesial temporal lobe epilepsy with hippocampal sclerosis and 3591 control subjects. To dissect out variants related to a history of febrile seizures, we tested cases with mesial temporal lobe epilepsy with hippocampal sclerosis with (overall n = 757) and without (overall n = 803) a history of febrile seizures. Meta-analysis revealed a genome-wide significant association for mesial temporal lobe epilepsy with hippocampal sclerosis with febrile seizures at the sodium channel gene cluster on chromosome 2q24.3 [rs7587026, within an intron of the SCN1A gene, P = 3.36 × 10−9, odds ratio (A) = 1.42, 95% confidence interval: 1.26–1.59]. In a cohort of 172 individuals with febrile seizures, who did not develop epilepsy during prospective follow-up to age 13 years, and 6456 controls, no association was found for rs7587026 and febrile seizures. These findings suggest SCN1A involvement in a common epilepsy syndrome, give new direction to biological understanding of mesial temporal lobe epilepsy with hippocampal sclerosis with febrile seizures, and open avenues for investigation of prognostic factors and possible prevention of epilepsy in some children with febrile seizures.

Protective role of the HLA-A*02 allele in Portuguese patients with multiple sclerosis.

Background Multiple sclerosis (MS) is associated with human leukocyte antigen (HLA) HLA–DRB1*15. Recent evidence that CD8 T cells are implicated in MS suggests that HLA class I may also contribute. An association of HLA–A*02 and A*03 alleles has been described. Objectives We examined the influence of HLA–A*02 and HLA–A*03 in Portuguese patients with MS, independently of HLA–DRB1*15 using a logistic regression model. Conclusions DRB1*15 increased the risk of developing MS and HLA–A*02 decreased the risk. A*03 had no effect. To analyze if HLA–A*02 association was independent from DRB1*15, an interaction between these two alleles was introduced in the model; no significant interaction was found.

Psychosocial factors as predictors of quality of life in chronic portuguese patients

BackgroundChronic illnesses are diseases of long duration and generally of slow progression. They cause significant quality of life impairment. The aim of this study was to analyse psychosocial predictors of quality of life and of subjective well-being in chronic Portuguese patients.MethodsChronic disease patients (n = 774) were recruited from central Portuguese Hospitals. Participants completed self-reported questionnaires assessing socio-demographic, clinical, psychosocial and outcome variables: quality of life (HRQL) and subjective well-being (SWB). MANCOVA analyses were used to test psychosocial factors as determinants of HRQL and SWB.ResultsAfter controlling for socio-demographic and clinical variables, results showed that dispositional optimism, positive affect, spirituality, social support and treatment adherence are significant predictors of HRQL and SWB. Similar predictors of quality of life, such as positive affect, treatment adherence and spirituality, were found for subgroups of disease classified by medical condition.ConclusionsThe work identifies psychosocial factors associated with quality of life. The predictors for the entire group of different chronic diseases are similar to the ones found in different chronic disease subgroups: positive affect, social support, treatment adherence and spirituality. Patients with more positive affect, additional social support, an adequate treatment adherence and a feel-good spirituality, felt better with the disease conditions and consequently had a better quality of life. This study contributes to understanding and improving the processes associated with quality of life, which is relevant for health care providers and chronic diseases support.

Immunogenetic Predisposing Factors for Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis

ABSTRACT Purpose: Neuroinflammation appears as an important epileptogenic mechanism. Experimental and clinical studies have demonstrated an upregulation of pro-inflammatory cytokines such as IL-1β and TNF-α, in mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). Expression of these cytokines can be modulated by polymorphisms such as rs16944 and rs1800629, respectively, both of which have been associated with febrile seizures (FS) and MTLE-HS development. The human leukocyte antigen (HLA) system has also been implicated in diverse epileptic entities, suggesting a variable role of this system in epilepsy. Our aim was to analyse the association between immunogenetic factors and MTLE-HS development. For that rs16944 (-511 T>C, IL-1β), rs1800629 (-308 G>A, TNF-α) polymorphisms and HLA-DRB1 locus were genotyped in a Portuguese Population. Methods: We studied 196 MTLE-HS patients (108 females, 88 males, 44.7 ± 12.0 years, age of onset = 13.6 ± 10.3 years, 104 with FS antecedents) and 282 healthy controls in a case–control study. Results: The frequency of rs16944 TT genotype was higher in MTLE-HS patients compared to controls (14.9% in MTLE-HS vs. 7.7% in controls, p = 0.021, OR [95% CI] = 2.20 [1.13–4.30]). This association was independent of FS antecedents. No association was observed between rs1800629 genotypes or HLA-DRB1 alleles and MTLE-HS susceptibility. Also, no correlation was observed between the studied polymorphisms and disease age of onset. Conclusion: The rs16944 TT genotype is associated with MTLE-HS development what may be explained by the higher IL-1β levels produced by this genotype. High IL-1β levels may have neurotoxic effects or imbalance neurotransmission leading to seizures.

Brain expression of inflammatory mediators in Mesial Temporal Lobe Epilepsy patients

Neuroinflammation may be central in epileptogenesis. In this study we analysed inflammatory reaction markers in brain tissue of Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis (MTLE-HS) patients. TLR4, IL-1β and IL-10 gene expression as well as the presence of activated HLA-DR+ microglia was evaluated in 23 patients and 10 cadaveric controls. Inflammation characterized by the presence of HLA-DR+ microglia and TLR4, IL-1β overexpression was evident in hippocampus and anterior temporal cortex of MTLE-HS patients. Anti-inflammatory IL-10 was also overexpressed in MTLE-HS patients. Our results show that hippocampal neuroinflammation extends beyond lesional limits, as far as the anterior temporal cortex.

Age of onset of mesial temporal lobe epilepsy with hippocampal sclerosis: the effect of apolipoprotein E and febrile seizures

ABSTRACT Purpose: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is the most frequent pharmaco-resistant epilepsy. It has been associated with febrile seizures (FS) in childhood. Its aetiology remains unclear but genetic factors are involved. Apolipoprotein E (ApoE) is the main lipoprotein secreted in brain. It has a critical immunomodulatory function, influences neurotransmission and it is involved in repairing damaged neurons. ApoE ϵ4 is an isoform of ApoE with altered protein function, previously associated with refractoriness and early onset epilepsy. This study was undertaken to determine if ApoE isoforms are risk factors for MTLE-HS and influence clinical characteristics.Methods: A group of 188 MTLE-HS patients (101 F, 87 M, mean age = 44.7 ± 11.6 years, 100 with FS antecedents) was studied and compared with a group of 342 healthy individuals in a case-control genetic association study. Data were analysed with Pearson Chi-squared Test or Students t test, as appropriated.Results: No differences in ApoE ϵ4 allelic frequencies between MTLE-HS patients and controls or between MTLE-HS subgroups were observed. Nevertheless, ApoE ϵ4 carriers had an earlier MTLE-HS onset (11.0 ± 7.9 years in ApoE ϵ4 carriers vs. 14.4 ± 11.2 years in ApoE ϵ4 non-carriers p < 0.05). Additionally, we observed that MTLE-HS patients with FS antecedents had a statistically significant early disease onset (11.5 ± 8.7 years in FS+ vs. 16.0 ± 12.1 years in FS−, p < 0.01).Conclusions: Our data show that ApoE ϵ4 and FS may not participate directly in etiopathogenic mechanisms of MTLE-HS but could hasten the disease development in predisposed individuals.

General Discussion of the Assessment and Representation of the Elements Seizure Frequency and Seizure Severity

When we are constructing scales we must decide on their various objectives; what is the role and function the scale is going to play? Do we intend to use a severity scale on its own, or do we want a seizure severity scale to be used as a component of a model to assess the severity of epilepsy? Seizure severity has a different meaning for patients and doctors. While neurologists emphasize the clinical and electroencephalographic manifestations as clinical markers, the patients emphasize some of the clinical aspects they are aware of and those with greater impact on their quality of life (QOL). Which of these concepts are we going to use? Which is the definition of seizure severity we are going to measure? Do we want a scale based only on clinical judgments or do we want a severity scale to measure patient’s perception of severity? Can we decide upon a scale that can be used in various contexts, or has each of the available scales (VA, Chalfont, Liverpool) its own objective and its own role to play?

Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning

Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of poorly defined diseases with excessive daytime sleepiness as a core feature. Due to the considerable overlap of symptoms and the rarity of the diseases, it is difficult to identify distinct phenotypes of CH. Machine learning (ML) can help to identify phenotypes as it learns to recognize clinical features invisible for humans. Here we apply ML to data from the huge European Narcolepsy Network (EU-NN) that contains hundreds of mixed features of narcolepsy making it difficult to analyze with classical statistics. Stochastic gradient boosting, a supervised learning model with built-in feature selection, results in high performances in testing set. While cataplexy features are recognized as the most influential predictors, machine find additional features, e.g. mean rapid-eye-movement sleep latency of multiple sleep latency test contributes to classify NT1 and NT2 as confirmed by classical statistical analysis. Our results suggest ML can identify features of CH on machine scale from complex databases, thus providing ‘ideas’ and promising candidates for future diagnostic classifications.

An Application of Structural Equation Modeling of Test Dispositional Optimism as Mediator or Moderator in Quality of Life in Patients with Chronic Disease

The aim of the present study was to test a hypothetical model to examine if dispositional optimism exerts a moderating or a mediating effect between personality traits and quality of life, in Portuguese patients with chronic diseases. A sample of 540 patients was recruited from central hospitals in various districts of Portugal. All patients completed self-reported questionnaires assessing socio-demographic and clinical variables, personality, dispositional optimism, and quality of life. Structural equation modeling (SEM) was used to analyze the moderating and mediating effects. Results suggest that dispositional optimism exerts a mediator rather than a moderator role between personality traits and quality of life, suggesting that “the expectation that good things will happen” contributes to a better general well-being and better mental functioning.

General Discussion of the Part Played by Health Status, Adverse Effects of Treatment and Psychosocial Factors in the Construction of indexes

I have not heard a definition of what health is, we are speaking about health status, but what is health? Did we use the definition that health is a lack of disease or a lack of signs and symptoms, or is health a state of physical, social and mental well-being? If we are speaking about well-being, this is a much more subjective impression of people and needs a patient-based scale. We know the type of patient who reacts to seizure suppression by saying “the treatment robbed me of my epilepsy.” For him it was not a good result that he had no seizures as his pattern of life had completely depended on his seizures and now life felt empty. Another remark I have to make is: we discussed seizure frequency, and then severity of seizures, now we add a third component, health status. The topic becomes more and more complicated. In fact in most clinical trials of anti-epileptic drugs we do not admit patients with other diseases or pregnant women. If indexes are only to be used in research it seems there would be no place to discuss the health aspect.