7 research outputs found
The polygenic basis of relapse after a first episode of schizophrenia
Little is known about genetic predisposition to relapse. Previous studies have linked cognitive and psychopathological (mainly schizophrenia and bipolar disorder) polygenic risk scores (PRS) with clinical manifestations of the disease. This study aims to explore the potential role of PRS from major mental disorders and cognition on schizophrenia relapse. 114 patients recruited in the 2EPs Project were included (56 patients who had not experienced relapse after 3 years of enrollment and 58 patients who relapsed during the 3-year follow-up). PRS for schizophrenia (PRS-SZ), bipolar disorder (PRS-BD), education attainment (PRS-EA) and cognitive performance (PRS-CP) were used to assess the genetic risk of schizophrenia relapse.Patients with higher PRS-EA, showed both a lower risk (OR=0.29, 95% CI [0.11–0.73]) and a later onset of relapse (30.96± 1.74 vs. 23.12± 1.14 months, p=0.007. Our study provides evidence that the genetic burden of neurocognitive function is a potentially predictors of relapse that could be incorporated into future risk prediction models. Moreover, appropriate treatments for cognitive symptoms appear to be important for improving the long-term clinical outcome of relapse
Epigenetic clocks in relapse after a first episode of schizophrenia
The main objective of the present study was to investigate the association between several epigenetic clocks, covering different aspects of aging, with schizophrenia relapse evaluated over a 3-year follow-up period in a cohort of ninety-one first-episode schizophrenia patients. Genome-wide DNA methylation was profiled and four epigenetic clocks, including epigenetic clocks of chronological age, mortality and telomere length were calculated. Patients that relapsed during the follow-up showed epigenetic acceleration of the telomere length clock (p = 0.030). Shorter telomere length was associated with cognitive performance (working memory, r = 0.31 p = 0.015; verbal fluency, r = 0.28 p = 0.028), but no direct effect of cognitive function or symptom severity on relapse was detected. The results of the present study suggest that epigenetic age acceleration could be involved in the clinical course of schizophrenia and could be a useful marker of relapse when measured in remission stages
Influence of clinical and neurocognitive factors in psychosocial functioning after a first episode non-affective psychosis: differences between males and females
BackgroundDeficits in psychosocial functioning are present in the early stages of psychosis. Several factors, such as premorbid adjustment, neurocognitive performance, and cognitive reserve (CR), potentially influence functionality. Sex differences are observed in individuals with psychosis in multiple domains. Nonetheless, few studies have explored the predictive factors of poor functioning according to sex in first-episode psychosis (FEP). This study aimed to explore sex differences, examine changes, and identify predictors of functioning according to sex after onset.Materials and methodsThe initial sample comprised 588 individuals. However, only adults with non-affective FEP (n = 247, 161 males and 86 females) and healthy controls (n = 224, 142 males and 82 females) were included. A comprehensive assessment including functional, neuropsychological, and clinical scales was performed at baseline and at 2-year follow-up. A linear regression model was used to determine the predictors of functioning at 2-year follow-up.ResultsFEP improved their functionality at follow-up (67.4% of both males and females). In males, longer duration of untreated psychosis (β = 0.328, p = 0.003) and worse premorbid adjustment (β = 0.256, p = 0.023) were associated with impaired functioning at 2-year follow-up, while in females processing speed (β = 0.403, p = 0.003), executive function (β = 0.299, p = 0.020) and CR (β = −0.307, p = 0.012) were significantly associated with functioning.ConclusionOur data indicate that predictors of functioning at 2-year follow-up in the FEP group differ according to sex. Therefore, treatment and preventative efforts may be adjusted taking sex into account. Males may benefit from functional remediation at early stages. Conversely, in females, early interventions centered on CR enhancement and cognitive rehabilitation may be recommended
Search for schizophrenia and bipolar biotypes using functional network properties
Abstract Introduction Recent studies support the identification of valid subtypes within schizophrenia and bipolar disorder using cluster analysis. Our aim was to identify meaningful biotypes of psychosis based on network properties of the electroencephalogram. We hypothesized that these parameters would be more altered in a subgroup of patients also characterized by more severe deficits in other clinical, cognitive, and biological measurements. Methods A clustering analysis was performed using the electroencephalogram‐based network parameters derived from graph‐theory obtained during a P300 task of 137 schizophrenia (of them, 35 first episodes) and 46 bipolar patients. Both prestimulus and modulation of the electroencephalogram were included in the analysis. Demographic, clinical, cognitive, structural cerebral data, and the modulation of the spectral entropy of the electroencephalogram were compared between clusters. Data from 158 healthy controls were included for further comparisons. Results We identified two clusters of patients. One cluster presented higher prestimulus connectivity strength, clustering coefficient, path‐length, and lower small‐world index compared to controls. The modulation of clustering coefficient and path‐length parameters was smaller in the former cluster, which also showed an altered structural connectivity network and a widespread cortical thinning. The other cluster of patients did not show significant differences with controls in the functional network properties. No significant differences were found between patients´ clusters in first episodes and bipolar proportions, symptoms scores, cognitive performance, or spectral entropy modulation. Conclusion These data support the existence of a subgroup within psychosis with altered global properties of functional and structural connectivity
Non-invasive oxygenation support in acutely hypoxemic COVID-19 patients admitted to the ICU : a multicenter observational retrospective study
Background: Non-invasive oxygenation strategies have a prominent role in the treatment of acute hypoxemic respiratory failure during the coronavirus disease 2019 (COVID-19). While the efficacy of these therapies has been studied in hospitalized patients with COVID-19, the clinical outcomes associated with oxygen masks, high-flow oxygen therapy by nasal cannula and non-invasive mechanical ventilation in critically ill intensive care unit (ICU) patients remain unclear. Methods: In this retrospective study, we used the best of nine covariate balancing algorithms on all baseline covariates in critically ill COVID-19 patients supported with > 10 L of supplemental oxygen at one of the 26 participating ICUs in Catalonia, Spain, between March 14 and April 15, 2020. Results: Of the 1093 non-invasively oxygenated patients at ICU admission treated with one of the three stand-alone non-invasive oxygenation strategies, 897 (82%) required endotracheal intubation and 310 (28%) died during the ICU stay. High-flow oxygen therapy by nasal cannula (n = 439) and non-invasive mechanical ventilation (n = 101) were associated with a lower rate of endotracheal intubation (70% and 88%, respectively) than oxygen masks (n = 553 and 91% intubated), p < 0.001. Compared to oxygen masks, high-flow oxygen therapy by nasal cannula was associated with lower ICU mortality (hazard ratio 0.75 [95% CI 0.58-0.98), and the hazard ratio for ICU mortality was 1.21 [95% CI 0.80-1.83] for non-invasive mechanical ventilation. Conclusion: In critically ill COVID-19 ICU patients and, in the absence of conclusive data, high-flow oxygen therapy by nasal cannula may be the approach of choice as the primary non-invasive oxygenation support strategy
Epigenetic clocks in relapse after a first episode of schizophrenia
The main objective of the present study was to investigate the association between several epigenetic clocks, covering different aspects of aging, with schizophrenia relapse evaluated over a 3-year follow-up period in a cohort of ninety-one first-episode schizophrenia patients. Genome-wide DNA methylation was profiled and four epigenetic clocks, including epigenetic clocks of chronological age, mortality and telomere length were calculated. Patients that relapsed during the follow-up showed epigenetic acceleration of the telomere length clock (p = 0.030). Shorter telomere length was associated with cognitive performance (working memory, r = 0.31 p = 0.015; verbal fluency, r = 0.28 p = 0.028), but no direct effect of cognitive function or symptom severity on relapse was detected. The results of the present study suggest that epigenetic age acceleration could be involved in the clinical course of schizophrenia and could be a useful marker of relapse when measured in remission stages
Discovering HIV related information by means of association rules and machine learning
Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts