The Association for Jewish Studies (AJS) is a scholarly organization in the United States that promotes academic Jewish Studies. The AJS was founded in 1969 and held its first annual conference that year at Brandeis University. In 1976, the AJS began to publish a scholarly journal, the AJS Review. The AJS is the largest academic Jewish Studies organization in the world.
Transcriptomics can routinely identify genes that are overexpressed, have splicing defects, or exhibit aberrant allele-specific expression. Yet, gene misexpression, also known as ectopic expression, has been less well characterized despite its demonstrated importance in some rare diseases, including congenital limb malformations, congenital hyperinsulinism, and monogenic severe childhood obesity. To gain a wider view of how frequently misexpression occurs and the mechanisms that cause it, Vanderstichele et al. analyzed bulk whole-blood RNA-seq data in more than 4,500 healthy blood donors from the INTERVAL study. Although the frequency for any particular misexpression event was very low, in total, 96% of individuals exhibited at least one instance. Misexpression was also not limited to a handful of genes—rather, slightly more than a third of inactive protein-coding genes were affected at least once in the sample. These genes were less likely to contain variants associated with developmental diseases and were significantly enriched for the presence of rare structural variants in cis. Overall, the authors identified a putative mechanism for 42% of events with a misexpression-associated structural variant, with transcript fusion leading to the highest levels of misexpression, followed by transcript readthrough and gene inversion. Thus, this work demonstrates the impact of rare structural variants on misexpression and adds another type of outlier analysis to the transcriptomics toolkit.
Background: Radiomic features provide quantitative information about lesions morphology and texture on medical images. Recent studies have shown that intracerebral hemorrhage (ICH) radiomics on admission non-contrast head CT are associated with severity of symptoms at baseline and clinical outcomes - providing prognostic information beyond hematoma volume. In this study, we determined hematoma radiomic markers of post-ICH survival on admission head CT. Methods: Using the ATACH-2 trial dataset, we manually segmented ICH on admission head CTs and extracted 1130 radiomic features. Univariate and multivariate survival analyses were performed using the Cox Proportional Hazards model, Kaplan Meier Analysis, and logistic regression. Results: We split our dataset (n=871) to training (n=580) and testing (n=291) cohorts. Increased “original first order Energy” radiomic feature was associated with a higher probability of death (Hazard Ratio=1.64, p <0.0001). LASSO Cox Proportional Hazards modeling also identified “original first order Energy” alongside age, NIHSS, and baseline INR as significant predictors of death. The ROC analysis confirmed the prognostic capability of this feature at 7 days, 30 days, and 90 days post-ICH in training and test cohorts. Kaplan Meier analysis demonstrated that increased “original first order Energy” is associated with a higher probability of death (p < 0.05 at all time points). Logistic regression also showed that this feature is an independent predictor of post-ICH mortality (Odds ratios=2.04, p < 0.001). Conclusions: The “original first order Energy” radiomic feature of hematoma on admission non-contrast head CT scans is a main predictor of survival in supratentorial ICH. This radiomic feature represents the magnitude of voxel values confounded with lesion volume - i.e. brighter larger hematomas on head CT have higher " original first order Energy ", and are associated with higher mortality rates after supratentorial ICH.
The omnigenic hypothesis, which contextualizes the highly polygenic nature of complex traits, proposes that a broad, interconnected gene regulatory network coalesces on a set of core effector genes in relevant tissues. Most heritability, therefore, can be attributed to so-called peripheral pathways comprising the additive trans-effects of many common variants. In this issue, Iakovliev et al. explore a key component of the omnigenic hypothesis by seeking to identify core (or, per the authors’ terminology, sparse effector) genes for type 1 diabetes. The authors propose that core genes can be identified by testing disease association with trans-scores, which represent the aggregation of trans-eQTL and trans-pQTL results. Somewhat reassuringly from a biological standpoint, the putative core genes, which would not be detected through traditional genome-wide association analyses, all function in the immune system. Although the approach put forth by the authors will need to be tested in the context of other complex traits and diseases, it is tempting to begin to speculate how the search for core genes might influence the design and interpretation of future research. As an example, one could envision a shift from fine-mapping approaches aimed at identifying discrete functional variants to those that evaluate trans-scores to identify crucial regulatory networks.
