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Abstract
The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a complex public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N=9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|rg|=0.21-1, pFDR<0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer’s disease, bipolar disorder, and Tourette’s syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1, that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings underscore the complex genetic landscape of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.
Highlights
Local genetic correlations found even in the absence of global correlations.
Both positive and negative local correlations found for IR-neuropsychiatric pairs.
Enrichment for immune, and insulin signalling pathways, among others.
Pinpointed shared likely causal variants within 10 genomic regions.
Identified therapeutic targets, e.g., SLC39A8 and HLA-DRB1, for drug repurposing.
High-resolution mapping of cell cycle dynamics during T-cell development and regeneration in vivo
(2024)
Control of cell proliferation is critical for the lymphocyte life cycle. However, little is known on how stage-specific alterations in cell cycle behavior drive proliferation dynamics during T-cell development. Here, we employed in vivo dual-nucleoside pulse labeling combined with determination of DNA replication over time as well as fluorescent ubiquitination-based cell cycle indicator mice to establish a quantitative high-resolution map of cell cycle kinetics of thymocytes. We developed an agent-based mathematical model of T-cell developmental dynamics. To generate the capacity for proliferative bursts, cell cycle acceleration followed a ‘stretch model’, characterized by simultaneous and proportional contraction of both G1 and S phase. Analysis of cell cycle phase dynamics during regeneration showed tailored adjustments of cell cycle phase dynamics. Taken together, our results highlight intrathymic cell cycle regulation as an adjustable system to maintain physiologic tissue homeostasis and foster our understanding of dysregulation of the T-cell developmental program.
The hippocampus (HPC) supports spatial working memory (SWM) through its interactions with the prefrontal cortex (PFC). However, it is not clear whether and how the dorsal (dHPC) and ventral (vHPC) poles of the HPC make distinct contributions to SWM and whether they differentially influence the PFC. To address this question, we optogenetically silenced the dHPC or the vHPC while simultaneously recording from the PFC of mice performing a SWM task. We found that whereas both HPC subregions were necessary during the encoding phase of the task, only the dHPC was necessary during the choice phase. Silencing of either subregion altered the spatial firing patterns of PFC neurons. However, only silencing of the vHPC affected their coding of spatial goals. These results thus reveal distinct contributions of the dorsal and ventral HPC poles to SWM and the coding of behaviorally-relevant spatial information by PFC neurons.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
Background: Trauma-related guilt and shame are crucial for the development and maintenance of PTSD (posttraumatic stress disorder). We developed an intervention combining cognitive techniques with loving-kindness meditations (C-METTA) that specifically target these emotions. C-METTA is an intervention of six weekly individual treatment sessions followed by a four-week practice phase.
Objective: This study examined C-METTA in a proof-of-concept study within a randomized wait-list controlled trial.
Method: We randomly assigned 32 trauma-exposed patients with a DSM-5 diagnosis to C-METTA or a wait-list condition (WL). Primary outcomes were clinician-rated PTSD symptoms (CAPS-5) and trauma-related guilt and shame. Secondary outcomes included psychopathology, self-criticism, well-being, and self-compassion. Outcomes were assessed before the intervention phase and after the practice phase.
Results: Mixed-design analyses showed greater reductions in C-METTA versus WL in clinician-rated PTSD symptoms (d = −1.09), guilt (d = −2.85), shame (d = −2.14), psychopathology and self-criticism.
Conclusion: Our findings support positive outcomes of C-METTA and might contribute to improved care for patients with stress-related disorders. The study was registered in the German Clinical Trials Register (DRKS00023470).
HIGHLIGHTS
C-METTA is an intervention that addresses trauma-related guilt and shame and combines cognitive interventions with loving-kindness meditations.
A proof-of-concept study was conducted examining C-METTA in a wait-list randomized controlled trial
C-METTA led to reductions in trauma-related guilt and shame and PTSD symptoms.
The MICOS complex subunit MIC13 is essential for mitochondrial cristae organization. Mutations in MIC13 cause severe mitochondrial hepato-encephalopathy displaying defective cristae morphology and loss of the MIC10-subcomplex. Here we identified SLP2 as a novel interacting partner of MIC13 and decipher a critical role of SLP2 for MICOS assembly at distinct steps. SLP2 provides a large interaction hub for MICOS subunits and loss of SLP2 imparted YME1L-mediated proteolysis of MIC26 and drastic alterations in cristae morphology. We further identified a MIC13-specific role in stabilizing the MIC10-subcomplex via a MIC13-YME1L axis. SLP2 together with the stabilized MIC10-subcomplex promotes efficient assembly of the MIC60-subcomplex forming the MICOS-MIB complex. Consistently, super-resolution nanoscopy showed a dispersed distribution of the MIC60 in cells lacking SLP2 and MIC13. Our study reveals converging and interdependent assembly pathways for the MIC10- and MIC60-subcomplexes which are controlled in two ways, the MIC13-YME1L and the SLP2-YME1L axes, revealing mechanistic insights of these factors in cristae morphogenesis. These results will be helpful in understanding the human pathophysiology linked to mutations in MIC13 or its interaction partners.
Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.