Cross-national variations in reported discrimination among people treated for major depression worldwide: The ASPEN/INDIGO international study

Background: No study has so far explored differences in discrimination reported by people with major depressive disorder (MDD) across countries and cultures. Aims: To (a) compare reported discrimination across different countries, and (b) explore the relative weight of individual and contextual factors in explaining levels of reported discrimination in people with MDD. Method: Cross-sectional multisite international survey (34 countries worldwide) of 1082 people with MDD. Experienced and anticipated discrimination were assessed by the Discrimination and Stigma Scale (DISC). Countries were classified according to their rating on the Human Development Index (HDI). Multilevel negative binomial and Poisson models were used. Results: People living in 'very high HDI' countries reported higher discrimination than those in 'medium/low HDI' countries. Variation in reported discrimination across countries was only partially explained by individual-level variables. The contribution of country-level variables was significant for anticipated discrimination only. Conclusions: Contextual factors play an important role in anticipated discrimination. Country-specific interventions should be implemented to prevent discrimination towards people with MDD

The UNC-45 Chaperone Is Critical for Establishing Myosin-Based Myofibrillar Organization and Cardiac Contractility in the Drosophila Heart Model

UNC-45 is a UCS (UNC-45/CRO1/She4P) class chaperone necessary for myosin folding and/or accumulation, but its requirement for maintaining cardiac contractility has not been explored. Given the prevalence of myosin mutations in eliciting cardiomyopathy, chaperones like UNC-45 are likely to be equally critical in provoking or modulating myosin-associated cardiomyopathy. Here, we used the Drosophila heart model to examine its role in cardiac physiology, in conjunction with RNAi-mediated gene silencing specifically in the heart in vivo. Analysis of cardiac physiology was carried out using high-speed video recording in conjunction with movement analysis algorithms. unc-45 knockdown resulted in severely compromised cardiac function in adults as evidenced by prolonged diastolic and systolic intervals, and increased incidence of arrhythmias and extreme dilation; the latter was accompanied by a significant reduction in muscle contractility. Structural analysis showed reduced myofibrils, myofibrillar disarray, and greatly decreased cardiac myosin accumulation. Cardiac unc-45 silencing also dramatically reduced life-span. In contrast, third instar larval and young pupal hearts showed mild cardiac abnormalities, as severe cardiac defects only developed during metamorphosis. Furthermore, cardiac unc-45 silencing in the adult heart (after metamorphosis) led to less severe phenotypes. This suggests that UNC-45 is mostly required for myosin accumulation/folding during remodeling of the forming adult heart. The cardiac defects, myosin deficit and decreased life-span in flies upon heart-specific unc-45 knockdown were significantly rescued by UNC-45 over-expression. Our results are the first to demonstrate a cardiac-specific requirement of a chaperone in Drosophila, suggestive of a critical role of UNC-45 in cardiomyopathies, including those associated with unfolded proteins in the failing human heart. The dilated cardiomyopathy phenotype associated with UNC-45 deficiency is mimicked by myosin knockdown suggesting that UNC-45 plays a crucial role in stabilizing myosin and possibly preventing human cardiomyopathies associated with functional deficiencies of myosin

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions