Multiple Sclerosis (MS) is a chronic disabling neuroinflammatory disease. Psychiatric manifestations have a high prevalence in MS patients and may worsen the illness progression and the patients’ quality of life (QoL). Depression is a highly prevalent condition in MS patients, associated with poorer adherence to treatment, decreased functional status and QoL, and increased suicide risk. Diagnosis and treatment of this disorder is challenging because of symptom overlap. Other prevalent psychiatric comorbidities are anxiety disorders, bipolar disorder, psychotic disorders, substance misuse and personality disorders. As the illness progresses, personality changes can happen, as well as affect abnormalities. Cognitive changes occur frequently in MS patients, and affect features like processing speed, attention, learning, memory, visual spatial capabilities, and some language deficits. Disease-modifying treatments may reduce cognitive impairment because of their container action on the brain’s lesion burden. Other QoL determinants such as fatigue, pain, sexual dysfunction, exercise, resilience and social support should be taken into account, in order to promote the individuals’ well-being. Further studies are needed in order to elucidate the effectiveness of pharmacotherapy and more neuroimaging studies are required to clarify the relationship between structural changes and psychiatric comorbidities.

In recent years, evidence supporting a link between inflammation and neuropsychiatric disorders has been mounting. Autism spectrum disorders (ASD) and schizophrenia share some clinical similarities which we hypothesize might reflect the same biological basis, namely, in terms of inflammation. However, the diagnosis of ASD and schizophrenia relies solely on clinical symptoms, and to date, there is no clinically useful biomarker to diagnose or monitor the course of such illnesses. The focus of this review is the central role that inflammation plays in ASD and schizophrenia. It spans from pre-clinical animal models to clinical research and excludes in vitro studies. Four major areas are covered: (1) microglia, the inflammatory brain resident myeloid cells, (2) biomarkers, including circulating cytokines, oxidative stress markers, and microRNA players, known to influence cellular processes at brain and immune levels, (3) effect of anti-psychotics on biomarkers and other predictors of response, and (4) impact of gender on response to immune activation, biomarkers, and response to anti-psychotic treatments.

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BackgroundRecent research has documented the association between attachment and cortisol rhythms. During pregnancy, when attachment patterns are likely to be activated, elevated levels of cortisol are associated with negative effects for the mother and the foetus. The aim of the present study was to examine the association of adult attachment style and cortisol rhythms in pregnant women.MethodsEighty women in the third trimester of pregnancy participated in the study. Adult attachment was assessed using the Adult Attachment Scale – Revised (AAS-R). Participants collected 4 samples of salivary cortisol at two different days; 3 samples were collected in the morning immediately after wakeup and one sample was collected by bedtime.ResultsResults found group significant differences in the cortisol diurnal oscillation (F(1,71) = 26.46, p < .001,), with secure women reporting a steep decrease in cortisol from awakening to bedtime, while women with fearful avoidant attachment reported no changes. No group differences were found regarding the cortisol awakening response.ConclusionsThese results highlight the importance of considering attachment patterns during pregnancy, suggesting fearful avoidant attachment style as a possible risk factor for emotional difficulties and dysregulation of the neuroendocrine rhythms.

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Gender specifics in cardiovascular risk factors should be considered in prevention strategies. Women reported significantly worse quality of life, putting them at higher risk for cardiovascular morbidity and mortality. Therefore, gender differences in predictors of quality of life warrant further investigation.