Accelerating the in vitro emulation of Alzheimer's disease-associated phenotypes using a novel 3D blood-brain barrier neurosphere co-culture model.

High failure rates in clinical trials for neurodegenerative disorders such as Alzheimer's disease have been linked to an insufficient predictive validity of current animal-based disease models. This has created an increasing demand for alternative, human-based models capable of emulating key pathological phenotypes in vitro. Here, a three-dimensional Alzheimer's disease model was developed using a compartmentalized microfluidic device that combines a self-assembled microvascular network of the human blood-brain barrier with neurospheres derived from Alzheimer's disease-specific neural progenitor cells. To shorten microfluidic co-culture times, neurospheres were pre-differentiated for 21 days to express Alzheimer's disease-specific pathological phenotypes prior to the introduction into the microfluidic device. In agreement with post-mortem studies and Alzheimer's disease in vivo models, after 7 days of co-culture with pre-differentiated Alzheimer's disease-specific neurospheres, the three-dimensional blood-brain barrier network exhibited significant changes in barrier permeability and morphology. Furthermore, vascular networks in co-culture with Alzheimer's disease-specific microtissues displayed localized ß-amyloid deposition. Thus, by interconnecting a microvascular network of the blood-brain barrier with pre-differentiated neurospheres the presented model holds immense potential for replicating key neurovascular phenotypes of neurodegenerative disorders in vitro.

A consistent pattern of slide effects in Illumina DNA methylation BeadChip array data.

Background: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical powerResults: We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content.Conclusions: Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.

Benchmarking omics-based prediction of asthma development in children.

BACKGROUND: Asthma is a heterogeneous disease with high morbidity. Advancement in high-throughput multi-omics approaches has enabled the collection of molecular assessments at different layers, providing a complementary perspective of complex diseases. Numerous computational methods have been developed for the omics-based patient classification or disease outcome prediction. Yet, a systematic benchmarking of those methods using various combinations of omics data for the prediction of asthma development is still lacking. OBJECTIVE: We aimed to investigate the computational methods in disease status prediction using multi-omics data. METHOD: We systematically benchmarked 18 computational methods using all the 63 combinations of six omics data (GWAS, miRNA, mRNA, microbiome, metabolome, DNA methylation) collected in The Vitamin D Antenatal Asthma Reduction Trial (VDAART) cohort. We evaluated each method using standard performance metrics for each of the 63 omics combinations. RESULTS: Our results indicate that overall Logistic Regression, Multi-Layer Perceptron, and MOGONET display superior performance, and the combination of transcriptional, genomic and microbiome data achieves the best prediction. Moreover, we find that including the clinical data can further improve the prediction performance for some but not all the omics combinations. CONCLUSIONS: Specific omics combinations can reach the optimal prediction of asthma development in children. And certain computational methods showed superior performance than other methods.

The neuroimmune axis of Alzheimer's disease.

Alzheimer's disease (AD) is a genetically complex and heterogeneous disorder with multifaceted neuropathological features, including ß-amyloid plaques, neurofibrillary tangles, and neuroinflammation. Over the past decade, emerging evidence has implicated both beneficial and pathological roles for innate immune genes and immune cells, including peripheral immune cells such as T cells, which can infiltrate the brain and either ameliorate or exacerbate AD neuropathogenesis. These findings support a neuroimmune axis of AD, in which the interplay of adaptive and innate immune systems inside and outside the brain critically impacts the etiology and pathogenesis of AD. In this review, we discuss the complexities of AD neuropathology at the levels of genetics and cellular physiology, highlighting immune signaling pathways and genes associated with AD risk and interactions among both innate and adaptive immune cells in the AD brain. We emphasize the role of peripheral immune cells in AD and the mechanisms by which immune cells, such as T cells and monocytes, influence AD neuropathology, including microglial clearance of amyloid-ß peptide, the key component of ß-amyloid plaque cores, pro-inflammatory and cytotoxic activity of microglia, astrogliosis, and their interactions with the brain vasculature. Finally, we review the challenges and outlook for establishing immune-based therapies for treating and preventing AD.

Genetic and functional analyses implicate microRNA 499A in bipolar disorder development.

Bipolar disorder (BD) is a complex mood disorder with a strong genetic component. Recent studies suggest that microRNAs contribute to psychiatric disorder development. In BD, specific candidate microRNAs have been implicated, in particular miR-137, miR-499a, miR-708, miR-1908 and miR-2113. The aim of the present study was to determine the contribution of these five microRNAs to BD development. For this purpose, we performed: (i) gene-based tests of the five microRNA coding genes, using data from a large genome-wide association study of BD; (ii) gene-set analyses of predicted, brain-expressed target genes of the five microRNAs; (iii) resequencing of the five microRNA coding genes in 960 BD patients and 960 controls and (iv) in silico and functional studies for selected variants. Gene-based tests revealed a significant association with BD for MIR499A, MIR708, MIR1908 and MIR2113. Gene-set analyses revealed a significant enrichment of BD associations in the brain-expressed target genes of miR-137 and miR-499a-5p. Resequencing identified 32 distinct rare variants (minor allele frequency < 1%), all of which showed a non-significant numerical overrepresentation in BD patients compared to controls (p = 0.214). Seven rare variants were identified in the predicted stem-loop sequences of MIR499A and MIR2113. These included rs142927919 in MIR2113 (pnom = 0.331) and rs140486571 in MIR499A (pnom = 0.297). In silico analyses predicted that rs140486571 might alter the miR-499a secondary structure. Functional analyses showed that rs140486571 significantly affects miR-499a processing and expression. Our results suggest that MIR499A dysregulation might contribute to BD development. Further research is warranted to elucidate the contribution of the MIR499A regulated network to BD susceptibility.

Whole-exome sequencing of 81 individuals from 27 multiply affected bipolar disorder families.

Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of depression and mania. Research suggests that the cumulative impact of common alleles explains 25-38% of phenotypic variance, and that rare variants may contribute to BD susceptibility. To identify rare, high-penetrance susceptibility variants for BD, whole-exome sequencing (WES) was performed in three affected individuals from each of 27 multiply affected families from Spain and Germany. WES identified 378 rare, non-synonymous, and potentially functional variants. These spanned 368 genes, and were carried by all three affected members in at least one family. Eight of the 368 genes harbored rare variants that were implicated in at least two independent families. In an extended segregation analysis involving additional family members, five of these eight genes harbored variants showing full or nearly full cosegregation with BD. These included the brain-expressed genes RGS12 and NCKAP5, which were considered the most promising BD candidates on the basis of independent evidence. Gene enrichment analysis for all 368 genes revealed significant enrichment for four pathways, including genes reported in de novo studies of autism (padj < 0.006) and schizophrenia (padj = 0.015). These results suggest a possible genetic overlap with BD for autism and schizophrenia at the rare-sequence-variant level. The present study implicates novel candidate genes for BD development, and may contribute to an improved understanding of the biological basis of this common and often devastating disease.