Brain morphometry points to emerging patterns of psychosis, depression, and anxiety vulnerability over a 2-year period in childhood

Background Gray matter morphometry studies have lent seminal insights into the etiology of mental illness. Existing research has primarily focused on adults and then, typically on a single disorder. Examining brain characteristics in late childhood, when the brain is preparing to undergo significant adolescent reorganization and various forms of serious psychopathology are just first emerging, may allow for a unique and highly important perspective of overlapping and unique pathogenesis. Methods A total of 8645 youth were recruited as part of the Adolescent Brain and Cognitive Development study. Magnetic resonance imaging scans were collected, and psychotic-like experiences (PLEs), depressive, and anxiety symptoms were assessed three times over a 2-year period. Cortical thickness, surface area, and subcortical volume were used to predict baseline symptomatology and symptom progression over time. Results Some features could possibly signal common vulnerability, predicting progression across forms of psychopathology (e.g. superior frontal and middle temporal regions). However, there was a specific predictive value for emerging PLEs (lateral occipital and precentral thickness), anxiety (parietal thickness/area and cingulate), and depression (e.g. parahippocampal and inferior temporal). Conclusion Findings indicate common and distinct patterns of vulnerability for varying forms of psychopathology are present during late childhood, before the adolescent reorganization, and have direct relevance for informing novel conceptual models along with early prevention and intervention efforts.

Susceptibility of Some Corylus avellana L. Cultivars to Xanthomonas arboricola pv. corylina

Bacterial blight of hazelnut (Corylus avellana L.) is caused by Xanthomonas arboricola pv. corylina (Xac). In the past, bacterial blight has been a key disease impacting the Oregon hazelnut industry where 99% of the United States hazelnut crop is grown. The disease is re-emerging in young orchards, as acreage of newly released hazelnut cultivars rapidly increases. This increase in hazelnut acreage is accompanied by renewed interest in developing control strategies for bacterial blight. Information on susceptibility of hazelnut cultivars to Xac is limited, partially due to lack of verified methods to quantify hazelnut cultivar response to artificial inoculation. In this research, Xac inoculation protocols were adapted to two hazelnut growing environments to evaluate cultivar susceptibility: in vitro tissue culture under sterile and controlled conditions, and in vivo potted tree conditions. Five hazelnut cultivars were evaluated using the in vitro inoculation protocol and seven hazelnut cultivars were evaluated using the in vivo inoculation protocol. Under in vitro conditions, there were severe bacterial blight symptoms on each cultivar consistent with those seen in the field, but no significant differences in the susceptibility of the newly released cultivars were observed compared to known Xac-susceptible cultivar (“Barcelona”). Under in vivo conditions, the proportion of necrotic buds were significantly higher in “Jefferson” and “Dorris” compared to all of the other tested cultivars, including “Barcelona.” The symptom progression seen in vivo mirrored the timing and symptom progression of bacterial blight reported from field observations. The in vitro conditions significantly reduced the amount of time required to measure the inoculation efficiency compared to the in vivo environment and allowed for greater replication. Further studies on the effects of Xac can use the results of these experiments to establish a dose–response model for bacterial blight, a wider range of germplasm can be tested under in vitro conditions, and management strategies that can be evaluated on large populations of new cultivars using the in vivo methods.

Inhibitory Immune Checkpoint Molecules and Exhaustion of T cells in COVID-19

COVID-19 (Coronavirus Disease) is an infectious disease caused by the coronavirus SARS-CoV-2 (Severe acute respiratory syndrome Coronavirus 2), which belongs to the genus Betacoronavirus. It was first identified in patients with severe respiratory disease in December 2019 in Wuhan, China. It mainly affects the respiratory system, and in severe cases causes serious lung infection or pneumonia, which can lead to the death of the patient. Clinical studies show that SARS-CoV-2 infection in critical cases causes acute tissue damage due to a pathological immune response. The immune response to a new coronavirus is complex and involves many processes of specific and non-specific immunity. Analysis of available studies has shown various changes, especially in the area of specific cellular immunity, including lymphopenia, decreased T cells (CD3+, CD4+ and CD8+), changes in the T cell compartment associated with symptom progression, deterioration of the condition and development of lung damage. We provide a detailed review of the analyses of immune checkpoint molecules PD-1, TIM-3, LAG-3 CTLA-4, TIGIT, BTLA, CD223, IDO-1 and VISTA on exhausted T cells in patients with asymptomatic to symptomatic stages of COVID-19 infection. Furthermore, this review may help to better understand the pathological T cell immune response and improve the design of therapeutic strategies for patients with SARS-CoV-2 infection.

Patient and Caregiver Symptom Trajectory: The Last 2 Months of Cancer Home Hospice

Patient symptom management is a fundamental goal of cancer home hospice care. However, informal family caregivers, who are primarily responsible for daily patient care, also experience negative symptoms, especially at the end of the patient’s life. While research has attended to patient symptom progression in home hospice, little research focuses on caregiver symptoms. To address this, we examined the frequency of both patient and caregiver symptoms to determine how these symptoms change in the last two months of the patient’s life. Sixty-three cancer hospice caregivers from 4 US states prospectively reported daily patient and caregiver symptoms via an Interactive Voice Response phone system. We analyzed data from up to the last 60 days of the patient’s life. Most caregivers were female (71.4%), Caucasian (88.9%), spouses of the patient (46%); average age was 59 years old (SD=13). Patients were mostly female (54%), with diverse solid tumor cancer diagnoses, and 72 years old (SD=11) on average. Most commonly reported moderate-to-severe patient symptoms were fatigue (67%), pain (47.5%), and loss in appetite (42.3%). Most common moderate-to-severe caregiver symptoms were fatigue (57.8%), trouble sleeping (45.1%), anxiety (52%), and depression (40.4%). Patient and caregiver symptoms were significantly correlated (Pearson r = .51, p<.001). Mixed-effects models found that both patient and caregiver symptoms (collapsed by week) worsened as patient death approached (ps <.01). Researchers and clinicians who are aware of the strong relationship between patient and caregiver symptoms are best able to address caregiver symptoms as part of hospice care, particularly as patient death approaches.

Stochastic Epigenetic Mutations Influence Parkinson’s Disease Risk, Progression, and Mortality

Background: Stochastic epigenetic mutations (SEM) reflect a deviation from normal site-specific methylation patterns. Epigenetic mutation load (EML) captures the accumulation of SEMs across an individual’s genome and may reflect dysfunction of the epigenetic maintenance system in response to epigenetic challenges. Objective: We investigate whether EML is associated with PD risk and time to events (i.e., death and motor symptom decline). Methods: We employed logistic regression and Cox proportional hazards regression to assess the association between EML and several outcomes. Our analyses are based on 568 PD patients and 238 controls from the Parkinson’s disease, Environment and Genes (PEG) study, for whom blood-based methylation data was available. Results: We found an association for PD onset and EML in all genes (OR = 1.90; 95%CI 1.52-2.37) and PD-related genes (OR = 1.87; 95%CI 1.50-2.32). EML was also associated with time to a minimum score of 35 points on the motor UPDRS exam (OR = 1.28; 95%CI 1.06-1.56) and time to death (OR = 1.29, 95%CI 1.11-1.49). An analysis of PD related genes only revealed five intragenic hotspots of high SEM density associated with PD risk. Conclusion: Our findings suggest an enrichment of methylation dysregulation in PD patients in general and specifically in five PD related genes. EML may also be associated with time to death and motor symptom progression in PD patients.

Evaluation of treatment response and symptom progression in 400 patients with visual snow syndrome

AimsTo gather information on useful medications to treat visual snow syndrome (VSS) as well as to validate an instrument to assess its clinical severity and the course of the disorder over time.MethodsFour hundred patients with VSS were included in this web-based prospective questionnaire study. All subjects completed a treatment questionnaire and a clinical diary. The first allowed evaluation of the effects of previous medications on visual snow, while the second measured VSS symptoms daily over the course of 30 days.ResultsPatients commonly reported previous use of medications such as antidepressants, antiepileptics, antibiotics and benzodiazepines. However, none of these drug classes was beneficial for the majority of patients. Recreational drugs and alcohol worsened visual snow symptoms in several reports. Vitamins and benzodiazepines had high therapeutic ratios, although in most cases they did not change the course of VSS.The monthly diary confirmed that the static in VSS is a consistent symptom over time. It also showed that indoor and fluorescent lights have a worse effect on symptoms when compared with natural outdoor lighting.ConclusionsThe study confirms clinical experience that medications are generally ineffective in VSS, with the exception of vitamins and perhaps benzodiazepines, which could be beneficial in some patients. The 30-day diary represents a useful tool to measure symptom progression over time, which could be used in future trials on VSS.

Tumour Treating Fields in Glioblastoma: Is the treatment tolerable, effective, and practical in UK Patients?

Aims Tumour Treating Fields (TTF) in combination with standard therapy, prolongs survival in patients with Glioblastoma (GBM). The aim of the current study was to assess the feasibility of integrating TTF into a standard UK neuro-oncology service with a focus on patient tolerability, compliance, and treatment delivery. Method A prospective study was performed of UK patients with IDH 1 Wild Type, MGMT Unmethylated GBM treated with TTF, in conjunction with conventional therapy. Patient compliance data, device-specific tolerability questions, and an evaluation of disease progression and survival were collected. Monthly quality of life (QoL) questionnaires (EORTC QLQ-C30 with BN-20) examined the trend of global health, psychosocial function and symptom progression. Results Nine patients were enrolled with a median age of 47 (7 males; 2 females). Overall, compliance with TTF was 89% (range 16% - 97%). Only one patient failed to comply with treatment. Patients tolerated the device with minimal side effects. Eight patients described mild to moderate skin irritation, whilst all patients were keen to recommend the device to other patients (100%). Most patients found the weight and size of the device to be its biggest drawback (72%). Progression-free survival was 5.5 months and median overall survival 14.9 months. Conclusion TTF was well tolerated amongst a small cohort of UK patients, who were able to comply with treatment without any significant complication. QoL questionnaires showed no sustained deterioration in global health, physical and emotional function until the final months of life, when disease burden was greatest.

Stroke recovery phenotyping through network trajectory approaches and graph neural networks

Stroke is a leading cause of neurological injury characterized by impairments in multiple neurological domains including cognition, language, sensory and motor functions. Clinical recovery in these domains is tracked using a wide range of measures that may be continuous, ordinal, interval or categorical in nature, which presents challenges for standard multivariate regression approaches. This has hindered stroke researchers’ ability to achieve an integrated picture of the complex time-evolving interactions amongst symptoms. Here we use tools from network science and machine learning that are particularly well-suited to extracting underlying patterns in such data, and may assist in prediction of recovery patterns. To demonstrate the utility of this approach, we analyzed data from the NINDS tPA trial using the Trajectory Profile Clustering (TPC) method to identify distinct stroke recovery patterns for 11 different neurological domains at 5 discrete time points. Our analysis identified 3 distinct stroke trajectory profiles that align with clinically relevant stroke syndromes, characterized both by distinct clusters of symptoms, as well as differing degrees of symptom severity. We then validated our approach using graph neural networks to determine how well our model performed predictively for stratifying patients into these trajectory profiles at early vs. later time points post-stroke. We demonstrate that trajectory profile clustering is an effective method for identifying clinically relevant recovery subtypes in multidimensional longitudinal datasets, and for early prediction of symptom progression subtypes in individual patients. This paper is the first work introducing network trajectory approaches for stroke recovery phenotyping, and is aimed at enhancing the translation of such novel computational approaches for practical clinical application.

Lateralization of Motor Signs Affects Symptom Progression in Parkinson Disease

Background: Asymmetry of motor signs is a cardinal feature of Parkinson disease which may impact phenotypic expression.Objective: To investigate the relationship between lateralization of motor signs and symptom progression and severity during longitudinal observation for up to 4 years in a naturalistic study.Methods: We analyzed data prospectively collected during the NINDS Parkinson Disease Biomarker Project (PDBP). We defined the Movement Disorder Society Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) part II as the primary measure of symptom progression. Left side predominant subjects were those whose lateralized motor scores on the MDS-UPDRS part III were ≥2 points higher on the left side than on the right side of the body. Multiple regression models (controlled for age, gender, education years, ethnicity, levodopa equivalent daily dose (LEDD) at baseline, and years with PD) were used to estimate the rate of symptom progression comparing left predominant (LPD) with non-left predominant (NLPD) subjects. A sensitivity analysis was performed using the same multiple regression models in the subgroups of low (0–26) or high (>27) MDS-UPDRS II score at baseline to determine if PD severity influenced the results.Results: We included 390 participants, 177 LPD and 213 NLPD. We found that MDS-UPDRS part II progression from baseline to 48 months was faster in LPD compared to NLPD (0.6 points per year faster in LPD, p = 0.05). Additionally, the LPD group was statistically significantly worse at baseline and at 48 months in several subparts of the MDS-UPDRS and the Parkinson's Disease Questionnaire-39 (PDQ-39) mobility score. Significantly slower progression (difference of −0.8, p = 0.01) and lower score at 48 months (difference of −3.8, p = 0.003) was seen for NLPD vs. LPD in the group with lower baseline MDS-UPDRS part II score.Conclusion: Left side lateralization was associated with faster symptom progression and worse outcomes in multiple clinical domains in our cohort. Clinicians should consider using motor predominance in their counseling regarding prognosis.