Whole genome analyses reveal significant convergence in obsessive-compulsive disorder between humans and dogs

Transcriptomic and intervention evidence reveals domestic dogs as a promising model for anti-inflammatory investigation

Domestic dogs have great potential to expand our understanding of the determinants of aging. To understand the aging pattern of domestic dogs and evaluate whether they can be used as an aging model, we performed RNA sequencing on white blood cells from domestic dogs aged 1-9 years and treated aged dogs with classical antiaging approaches. We obtained 30 RNA sequencing libraries and identified 61 age-associated genes with dynamic changes, the majority of which were related to metabolism and immune function, which may be predominant biomarkers for aging in dogs. We next treated aged dogs with canine mesenchymal stem cells (cMSCs), nicotinamide mononucleotide, and rapamycin to determine whether and how they responded to the antiaging interventions. The results showed that these treatments can significantly reduce the level of inflammatory factors (IL-6 and TNF-α). MSCs effectively improved the heart functions of aged dogs. Three key potential age-related genes (PYCR1, CCRL2, and TOX) were reversed by MSC treatment, two of which (CCRL2 and TOX) are implicated in immunity. Overall, we profiled the transcriptomic pattern of domestic dogs and revealed that they may be a good model of aging, especially in anti-inflammatory investigations.

Pathological Networking of Gray Matter Dendritic Density With Classic Brain Morphometries in OCD

Importance

The pathogenesis of obsessive-compulsive disorder (OCD) may involve altered dendritic morphology, but in vivo imaging of neurite morphology in OCD remains limited. Such changes must be interpreted functionally within the context of the multimodal neuroimaging approach to OCD.

Objective

To examine whether dendritic morphology is altered in patients with OCD compared with healthy controls (HCs) and whether such alterations are associated with other brain structural metrics in pathological networks.

Design, Setting, and Participants

This case-control study used cross-sectional data, including multimodal brain images and clinical symptom assessments, from 108 patients with OCD and 108 HCs from 2014 to 2017. Patients with OCD were recruited from Shanghai Mental Health Center, Shanghai, China, and HCs were recruited via advertisements. The OCD group comprised unmedicated adults with a Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) diagnosis of OCD, while the HCs were adults without any DSM-IV diagnosis, matched for age, sex, and education level. Data were analyzed from September 2019 to April 2023.

Exposure

DSM-IV diagnosis of OCD.

Main Outcomes and Measures

Multimodal brain imaging was used to compare neurite microstructure and classic morphometries between patients with OCD and HCs. The whole brain was searched to identify regions exhibiting altered morphology in patients with OCD and explore the interplay between the brain metrics representing these alterations. Brain-symptom correlations were analyzed, and the performance of different brain metric configurations were evaluated in distinguishing patients with OCD from HCs.

Results

Among 108 HCs (median [IQR] age, 26 [23-31] years; 50 [46%] female) and 108 patients with OCD (median [IQR] age, 26 [24-31] years; 46 [43%] female), patients with OCD exhibited deficient neurite density in the right lateral occipitoparietal regions (peak t = 3.821; P ≤ .04). Classic morphometries also revealed widely-distributed alterations in the brain (peak t = 4.852; maximum P = .04), including the prefrontal, medial parietal, cingulate, and fusiform cortices. These brain metrics were interconnected into a pathological brain network associated with OCD symptoms (global strength: HCs, 0.253; patients with OCD, 0.941; P = .046; structural difference, 0.572; P < .001). Additionally, the neurite density index exhibited high discriminatory power in distinguishing patients with OCD from HCs (accuracy, ≤76.85%), and the entire pathological brain network also exhibited excellent discriminative classification properties (accuracy, ≤82.87%).

Conclusions and Relevance

The findings of this case-control study underscore the utility of in vivo imaging of gray matter dendritic density in future OCD research and the development of neuroimaging-based biomarkers. They also endorse the concept of connectopathy, providing a potential framework for interpreting the associations among various OCD symptom-related morphological anomalies.

Differential effects of social isolation on oligodendrocyte development in different brain regions: insights from a canine model

Social isolation (SI) exerts diverse adverse effects on brain structure and function in humans. To gain an insight into the mechanisms underlying these effects, we conducted a systematic analysis of multiple brain regions from socially isolated and group-housed dogs, whose brain and behavior are similar to humans. Our transcriptomic analysis revealed reduced expression of myelin-related genes specifically in the white matter of prefrontal cortex (PFC) after SI during the juvenile stage. Despite these gene expression changes, myelin fiber organization in PFC remained unchanged. Surprisingly, we observed more mature oligodendrocytes and thicker myelin bundles in the somatosensory parietal cortex in socially isolated dogs, which may be linked to an increased expression of ADORA2A, a gene known to promote oligodendrocyte maturation. Additionally, we found a reduced expression of blood-brain barrier (BBB) structural components Aquaporin-4, Occludin, and Claudin1 in both PFC and parietal cortices, indicating BBB disruption after SI. In agreement with BBB disruption, myelin-related sphingolipids were increased in cerebrospinal fluid in the socially isolated group. These unexpected findings show that SI induces distinct alterations in oligodendrocyte development and shared disruption in BBB integrity in different cortices, demonstrating the value of dogs as a complementary animal model to uncover molecular mechanisms underlying SI-induced brain dysfunction.

A single-nucleus transcriptomic atlas of the dog hippocampus reveals the potential relationship between specific cell types and domestication

The process of domestication has led to dramatic differences in behavioral traits between domestic dogs and gray wolves. Whole-genome research found that a class of putative positively selected genes were related to various aspects of learning and memory, such as long-term potentiation and long-term depression. In this study, we constructed a single-nucleus transcriptomic atlas of the dog hippocampus to illustrate its cell types, cell lineage and molecular features. Using the transcriptomes of 105 057 nuclei from the hippocampus of a Beagle dog, we identified 26 cell clusters and a putative trajectory of oligodendrocyte development. Comparative analysis revealed a significant convergence between dog differentially expressed genes (DEGs) and putative positively selected genes (PSGs). Forty putative PSGs were DEGs in glutamatergic neurons, especially in Cluster 14, which is related to the regulation of nervous system development. In summary, this study provides a blueprint to understand the cellular mechanism of dog domestication.

Genome-Wide Analyses Reveal Genetic Convergence of Prolificacy between Goats and Sheep

The litter size of domestic goats and sheep is an economically important trait that shows variation within breeds. Strenuous efforts have been made to understand the genetic mechanisms underlying prolificacy in goats and sheep. However, there has been a paucity of research on the genetic convergence of prolificacy between goats and sheep, which likely arose because of similar natural and artificial selection forces. Here, we performed comparative genomic and transcriptomic analyses to identify the genetic convergence of prolificacy between goats and sheep. By combining genomic and transcriptomic data for the first time, we identified this genetic convergence in (1) positively selected genes (CHST11 and SDCCAG8), (2) differentially expressed genes (SERPINA14, RSAD2, and PPIG at follicular phase, and IGF1, GPRIN3, LIPG, SLC7A11, and CHST15 at luteal phase), and (3) biological pathways (genomic level: osteoclast differentiation, ErbB signaling pathway, and relaxin signaling pathway; transcriptomic level: the regulation of viral genome replication at follicular phase, and protein kinase B signaling and antigen processing and presentation at luteal phase). These results indicated the potential physiological convergence and enhanced our understanding of the overlapping genetic makeup underlying litter size in goats and sheep.