Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma.

We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation.

Identifying unique subgroups in suicide risks among psychiatric outpatients.

BACKGROUND: The presence of psychiatric disorders is widely recognized as one of the primary risk factors for suicide. A significant proportion of individuals receiving outpatient psychiatric treatment exhibit varying degrees of suicidal behaviors, which may range from mild suicidal ideations to overt suicide attempts. This study aims to elucidate the transdiagnostic symptom dimensions and associated suicidal features among psychiatric outpatients. METHODS: The study enrolled patients who attended the psychiatry outpatient clinic at a tertiary hospital in South Korea (n = 1, 849, age range = 18-81; 61% women). A data-driven classification methodology was employed, incorporating a broad spectrum of clinical symptoms, to delineate distinctive subgroups among psychiatric outpatients exhibiting suicidality (n = 1189). A reference group of patients without suicidality (n = 660) was included for comparative purposes to ascertain cluster-specific sociodemographic, suicide-related, and psychiatric characteristics. RESULTS: Psychiatric outpatients with suicidality (n = 1189) were subdivided into three distinctive clusters: the low-suicide risk cluster (Cluster 1), the high-suicide risk externalizing cluster (Cluster 2), and the high-suicide risk internalizing cluster (Cluster 3). Relative to the reference group (n = 660), each cluster exhibited distinct attributes pertaining to suicide-related characteristics and clinical symptoms, covering domains such as anxiety, externalizing and internalizing behaviors, and feelings of hopelessness. Cluster 1, identified as the low-suicide risk group, exhibited less frequent suicidal ideation, planning, and multiple attempts. In the high-suicide risk groups, Cluster 2 displayed pronounced externalizing symptoms, whereas Cluster 3 was primarily defined by internalizing and hopelessness symptoms. Bipolar disorders were most common in Cluster 2, while depressive disorders were predominant in Cluster 3. DISCUSSION: Our findings suggest the possibility of differentiating psychiatric outpatients into distinct, clinically relevant subgroups predicated on their suicide risk. This research potentially paves the way for personalizing interventions and preventive strategies that address cluster-specific characteristics, thereby mitigating suicide-related mortality among psychiatric outpatients.

A Comparative Study of Endoscopic versus Percutaneous Epidural Neuroplasty in Lower Back Pain: Outcomes at Six-Month Follow Up.

Background and Objectives: Endoscopic epidural neuroplasty (EEN) facilitates adhesiolysis through direct epiduroscopic visualization, offering more precise neural decompression than that exhibited by percutaneous epidural neuroplasty (PEN). We aimed to compare the effects of EEN and PEN for 6 months after treatment with lower back and radicular pain in patients. Methods: This retrospective study compared the visual analog scale (VAS) and Oswestry disability index (ODI) scores in patients with low back and radicular pain who underwent EEN or PEN with a steering catheter. The medical records of 107 patients were analyzed, with 73 and 34 undergoing EEN and PEN, respectively. Results: The VAS and ODI scores decreased at all time points after EEN and PEN. VAS and ODI scores decreased more in the EEN group than those in the PEN group at 1 day and 1- and 6-months post-procedure, indicating superior pain relief for both lower back and radicular pain through EEN. Conclusions: EEN is a superior treatment of pain control than PEN in lower back and radicular pain patients.

Brain Age Prediction Using Multi-Hop Graph Attention Combined with Convolutional Neural Network.

Convolutional neural networks (CNNs) have been used widely to predict biological brain age based on brain magnetic resonance (MR) images. However, CNNs focus mainly on spatially local features and their aggregates and barely on the connective information between distant regions. To overcome this issue, we propose a novel multi-hop graph attention (MGA) module that exploits both the local and global connections of image features when combined with CNNs. After insertion between convolutional layers, MGA first converts the convolution-derived feature map into graph-structured data by using patch embedding and embedding-distance-based scoring. Multi-hop connections between the graph nodes are modeled by using the Markov chain process. After performing multi-hop graph attention, MGA re-converts the graph into an updated feature map and transfers it to the next convolutional layer. We combined the MGA module with sSE (spatial squeeze and excitation)-ResNet18 for our final prediction model (MGA-sSE-ResNet18) and performed various hyperparameter evaluations to identify the optimal parameter combinations. With 2788 three-dimensional T1-weighted MR images of healthy subjects, we verified the effectiveness of MGA-sSE-ResNet18 with comparisons to four established, general-purpose CNNs and two representative brain age prediction models. The proposed model yielded an optimal performance with a mean absolute error of 2.822 years and Pearson's correlation coefficient (PCC) of 0.968, demonstrating the potential of the MGA module to improve the accuracy of brain age prediction.

Impact of sleep disturbance in shift workers on hippocampal volume and psychomotor speed.

STUDY OBJECTIVES: Shift work interferes with circadian rhythms, affecting sleep quality and cognitive function. Poor sleep quality in shift workers can impair psychomotor performance due to fatigue and sleepiness, increasing the risk of errors, accidents, and reduced productivity. Given the potential for atrophic changes in the hippocampus due to sleep disturbances, our study investigates how poor sleep quality correlates with hippocampal structural alterations and impacts psychomotor performance among shift workers. METHODS: We recruited 100 shift workers, classifying them based on sleep quality into two groups: good sleep-SW group (n = 59) and poor sleep-SW group (n = 41). Sleep quality was assessed using both 7-day actigraphy for sleep efficiency and the Pittsburgh Sleep Quality Index. A control group of 106 non-shift workers without sleep problems (non-SW group) was also included for comparison. The outcome measures were psychomotor speed and hippocampal volumes, both total and by subfield. RESULTS: The poor sleep-SW group showed significantly smaller hippocampal volumes than both the good sleep-SW group (P<0.001) and the non-SW group (P=0.003). Longer shift work years correlated with greater reductions in hippocampal volume in this group (r=-0.42, P=0.009), unlike in the good sleep-SW group (r=0.08, P=0.541). Furthermore, they demonstrated declines in psychomotor speed relative to the non-SW group (P=0.006), which correlated with smaller hippocampal volumes (r=0.37, P=0.020). CONCLUSIONS: Shift workers with poor sleep quality exhibit significant hippocampal volume reductions and psychomotor speed decline, underscoring the importance of early intervention and support for sleep issues in this population.

Alterations in Brain Morphometric Networks and Their Relationship with Memory Dysfunction in Patients with Type 2 Diabetes Mellitus.

Cognitive dysfunction, a significant complication of type 2 diabetes mellitus (T2DM), can potentially manifest even from the early stages of the disease. Despite evidence of global brain atrophy and related cognitive dysfunction in early-stage T2DM patients, specific regions vulnerable to these changes have not yet been identified. The study enrolled patients with T2DM of less than five years' duration and without chronic complications (T2DM group, n=100) and demographically similar healthy controls (control group, n=50). High-resolution T1-weighted magnetic resonance imaging data were subjected to independent component analysis to identify structurally significant components indicative of morphometric networks. Within these networks, the groups' gray matter volumes were compared, and distinctions in memory performance were assessed. In the T2DM group, the relationship between changes in gray matter volume within these networks and declines in memory performance was examined. Among the identified morphometric networks, the T2DM group exhibited reduced gray matter volumes in both the precuneus (Bonferroni-corrected p=0.003) and insular-opercular (Bonferroni-corrected p=0.024) networks relative to the control group. Patients with T2DM demonstrated significantly lower memory performance than the control group (p=0.001). In the T2DM group, reductions in gray matter volume in both the precuneus (r=0.316, p=0.001) and insular-opercular (r=0.199, p=0.047) networks were correlated with diminished memory performance. Our findings indicate that structural alterations in the precuneus and insular-opercular networks, along with memory dysfunction, can manifest within the first 5 years following a diagnosis of T2DM.

Changes in Structural Covariance among Olfactory-related Brain Regions in Anosmia Patients.

Anosmia, characterized by the loss of smell, is associated not only with dysfunction in the peripheral olfactory system but also with changes in several brain regions involved in olfactory processing. Specifically, the orbitofrontal cortex is recognized for its pivotal role in integrating olfactory information, engaging in bidirectional communication with the primary olfactory regions, including the olfactory cortex, amygdala, and entorhinal cortex. However, little is known about alterations in structural connections among these brain regions in patients with anosmia. In this study, high-resolution T1-weighted images were obtained from participants. Utilizing the volumes of key brain regions implicated in olfactory function, we employed a structural covariance approach to investigate brain reorganization patterns in patients with anosmia (n=22) compared to healthy individuals (n=30). Our structural covariance analysis demonstrated diminished connectivity between the amygdala and entorhinal cortex, components of the primary olfactory network, in patients with anosmia compared to healthy individuals (z=-2.22, FDR-corrected p=0.039). Conversely, connectivity between the orbitofrontal cortex-a major region in the extended olfactory network-and amygdala was found to be enhanced in the anosmia group compared to healthy individuals (z=2.32, FDR-corrected p=0.039). However, the structural connections between the orbitofrontal cortex and entorhinal cortex did not differ significantly between the groups (z=0.04, FDR-corrected p=0.968). These findings suggest a potential structural reorganization, particularly of higher-order cortical regions, possibly as a compensatory effort to interpret the limited olfactory information available in individuals with olfactory loss.