Iron has been increasingly implicated in the pathology of neurodegenerative diseases. In the past decade, development of the new magnetic resonance imaging technique, quantitative susceptibility mapping (QSM), has enabled for the more comprehensive investigation of iron distribution in the brain. The aim of this systematic review was to provide a synthesis of the findings from existing QSM studies in neurodegenerative diseases. We identified 80 records by searching MEDLINE, Embase, Scopus, and PsycInfo databases. The disorders investigated in these studies included Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Wilson's disease, Huntington's disease, Friedreich's ataxia, spinocerebellar ataxia, Fabry disease, myotonic dystrophy, pantothenate-kinase-associated neurodegeneration, and mitochondrial membrane protein-associated neurodegeneration. As a general pattern, QSM revealed increased magnetic susceptibility (suggestive of increased iron content) in the brain regions associated with the pathology of each disorder, such as the amygdala and caudate nucleus in Alzheimer's disease, the substantia nigra in Parkinson's disease, motor cortex in amyotrophic lateral sclerosis, basal ganglia in Huntington's disease, and cerebellar dentate nucleus in Friedreich's ataxia. Furthermore, the increased magnetic susceptibility correlated with disease duration and severity of clinical features in some disorders. Although the number of studies is still limited in most of the neurodegenerative diseases, the existing evidence suggests that QSM can be a promising tool in the investigation of neurodegeneration.

Introduction: Many patients with cognitive and neuropsychiatric symptoms face diagnostic delay and misdiagnosis. We investigated whether cerebrospinal fluid (CSF) neurofilament light (NfL) and total-tau (t-tau) could assist in the clinical scenario of differentiating neurodegenerative (ND) from psychiatric disorders (PSY), and rapidly progressive disorders.Methods: Biomarkers were examined in patients from specialist services (ND and PSY) and a national Creutzfeldt-Jakob registry (Creutzfeldt-Jakob disease [CJD] and rapidly progressive dementias/atypically rapid variants of common ND, RapidND).

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Objective: Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuroprogressive or neurodegenerative component to schizophrenia, remain largely unknown. Examining fluid biomarkers of diverse types of neuronal damage could increase our understanding of these processes, as well as potentially provide clinically useful biomarkers, for example with assisting with differentiation from progressive neurodegenerative disorders such as Alzheimer and frontotemporal dementias. Methods: This study measured plasma neurofilament light chain protein (NfL) using ultrasensitive Simoa technology, to investigate the degree of neuronal injury in a well-characterised cohort of people with treatment-resistant schizophrenia on clozapine ( n = 82), compared to first-degree relatives (an at-risk group, n = 37), people with schizophrenia not treated with clozapine ( n = 13), and age- and sex-matched controls ( n = 59). Results: We found no differences in NfL levels between treatment-resistant schizophrenia (mean NfL, M = 6.3 pg/mL, 95% confidence interval: [5.5, 7.2]), first-degree relatives (siblings, M = 6.7 pg/mL, 95% confidence interval: [5.2, 8.2]; parents, M after adjusting for age = 6.7 pg/mL, 95% confidence interval: [4.7, 8.8]), controls (M = 5.8 pg/mL, 95% confidence interval: [5.3, 6.3]) and not treated with clozapine (M = 4.9 pg/mL, 95% confidence interval: [4.0, 5.8]). Exploratory, hypothesis-generating analyses found weak correlations in treatment-resistant schizophrenia, between NfL and clozapine levels (Spearman’s r = 0.258, 95% confidence interval: [0.034, 0.457]), dyslipidaemia ( r = 0.280, 95% confidence interval: [0.064, 0.470]) and a negative correlation with weight ( r = −0.305, 95% confidence interval: [−0.504, −0.076]). Conclusion: Treatment-resistant schizophrenia does not appear to be associated with neuronal, particularly axonal degeneration. Further studies are warranted to investigate the utility of NfL to differentiate treatment-resistant schizophrenia from neurodegenerative disorders such as behavioural variant frontotemporal dementia, and to explore NfL in other stages of schizophrenia such as the prodome and first episode.

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Introduction Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia. Methods A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient’s symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data. Results Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual’s symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = −5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05). Conclusion Symptom network structure varies over the course of schizophrenia: symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia.

Background Our objective was to explore what people receiving and providing care consider to be ‘good’ in-home care for people living with dementia. Methods We conducted 36 in-depth interviews and two focus groups with key stakeholders in Australia in the first quarter of 2018. Participants included those receiving care (4 people living with dementia, 15 family carers) or providing care (9 case managers, 5 service managers, 10 home care workers). Qualitative thematic analysis was guided by Braun and Clarke’s six-step approach. Results Consensus was reached across all groups on five themes considered as important for good in-home dementia care: 1) Home care workers’ understanding of dementia and its impact; 2) Home care workers’ demonstrating person-centred care and empathy in their care relationship with their client; 3) Good relationships and communication between care worker, person with dementia and family carers; 4) Home care workers’ knowing positive practical strategies for changed behaviours; 5) Effective workplace policies and workforce culture. The results contributed to the co-design of a dementia specific training program for home care workers. Conclusions It is crucial to consider the views and opinions of each stakeholder group involved in providing/receiving dementia care from home care workers, to inform workforce training, education program design and service design. Results can be used to inform and empower home care providers, policy, and related decision makers to guide the delivery of improved home care services. Trial registration ACTRN 12619000251123.