Search

Background Gene-set analyses measure the association between a disease of interest and a "set" of genes related to a biological pathway. These analyses often incorporate gene network properties to account for differential contributions of each gene. We extend this concept further—defining gene contributions based on biophysical properties—by leveraging mathematical models of biology to predict the effects of genetic perturbations on a particular downstream function. Results We present a method that combines gene weights from model predictions and gene ranks from genome-wide association studies into a weighted gene-set test. We demonstrate in simulation how such a method can improve statistical power. To this effect, we identify a gene set, weighted by model-predicted contributions to intracellular calcium ion concentration, that is significantly related to bipolar disorder in a small dataset (P = 0.04; n = 544). We reproduce this finding using publicly available summary data from the Psychiatric Genomics Consortium (P = 1.7 × 10−4; n = 41,653). By contrast, an approach using a general calcium signaling pathway did not detect a significant association with bipolar disorder (P = 0.08). The weighted gene-set approach based on intracellular calcium ion concentration did not detect a significant relationship with schizophrenia (P = 0.09; n = 65,967) or major depression disorder (P = 0.30; n = 500,199). Conclusions Together, these findings show how incorporating math biology into gene-set analyses might help to identify biological functions that underlie certain polygenic disorders. [ABSTRACT FROM AUTHOR]

Forecasting how climate change will impact biological systems represents a grand challenge for biologists. However, climate change biology lacks an effective framework for anticipating and resolving uncertainty. Here, we introduce the concept of climate change wildcards: biological or bioclimatic processes with a high degree of uncertainty and a large impact on our ability to address the biotic consequences of climate change. Wildcards may occur at multiple points in the progression of research—from understanding, to predicting, to forecasting biological responses. Our understanding of biological responses is limited by the components and processes we exclude to make research tractable. Our ability to predict biological responses often requires integration between biological levels of organization, across multiple stressors, and from specific cases to general systems. However, these types of integration can be dramatically affected by, respectively, differences between biological levels in their critical points, nonadditivity of the effects of different stressors, and historical and geographic contingency. Finally, our ability to forecast biological responses to climate change requires incorporating climatic projections in bioclimatic models. Such forecasts are vulnerable to the compounding of biological and climatic uncertainty, especially when biological responses occur in novel areas of bioclimatic parameter space. Both biological responses and climate change are dynamic processes; the potential of biological systems to be buffered against or rescued from the effects of climate change depends on the relative timing of biological and climatic effects—one of the least predictable aspects of both systems. In sum, our framework identifies stress points in the research process where we should anticipate and forestall wildcards. Focusing on universal currencies, like energy and elements, and universal structures, like functional traits and ecological networks, will improve our ability to generalize results. Most importantly, by modeling and communicating uncertainty, climate change biology can identify critical foci for future research. [ABSTRACT FROM AUTHOR]

Pediatric extrarenal malignant rhabdoid tumors (MRTs) are rare, aggressive tumors with a poor prognosis (20% 5-year survival). There are currently fewer than 10 published case reports of primary MRT of the bladder. We report the case of an 18-month-old female with an isolated MRT of the bladder which was initially misdiagnosed as an inflammatory myofibroblastic tumor on biopsy. We review the history, tumor biology, histology, and current management of extrarenal MRT, along with lessons learned from the difficulty with the patient's initial diagnosis. [ABSTRACT FROM AUTHOR]

Circulating tumor DNA (ctDNA) analysis may improve early-stage breast cancer treatment via non-invasive tumor burden assessment. To investigate subtype-specific differences in the clinical significance and biology of ctDNA shedding, we perform serial personalized ctDNA analysis in hormone receptor (HR)-positive/HER2-negative breast cancer and triple-negative breast cancer (TNBC) patients receiving neoadjuvant chemotherapy (NAC) in the I-SPY2 trial. ctDNA positivity rates before, during, and after NAC are higher in TNBC than in HR-positive/HER2-negative breast cancer patients. Early clearance of ctDNA 3 weeks after treatment initiation predicts a favorable response to NAC in TNBC only. Whereas ctDNA positivity associates with reduced distant recurrence-free survival in both subtypes. Conversely, ctDNA negativity after NAC correlates with improved outcomes, even in patients with extensive residual cancer. Pretreatment tumor mRNA profiling reveals associations between ctDNA shedding and cell cycle and immune-associated signaling. On the basis of these findings, the I-SPY2 trial will prospectively test ctDNA for utility in redirecting therapy to improve response and prognosis. [Display omitted] • Early clearance of ctDNA in triple-negative patients associates with good response • ctDNA dynamics during neoadjuvant chemotherapy predict clinical outcomes • ctDNA negativity associates with improved survival despite having residual cancer • Expression analysis reveals pathways associated with ctDNA shedding Magbanua et al. examine the dynamics of ctDNA in plasma of high-risk early-stage breast cancer patients receiving neoadjuvant chemotherapy. Understanding the predictive and prognostic value of ctDNA and biology of ctDNA shedding in different breast cancer subtypes can inform the use of ctDNA for treatment selection to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Brazilian free-tailed bats (Tadarida brasiliensis) are one of the most widely distributed bat species in the Americas, often engaging in rapid, long-distance dispersals. Here, we document that, since ca. 2007, these bats have expanded their range into western North Carolina, eastern Tennessee and Virginia. Reports from wildlife control professionals, wildlife rehabilitators, regional submissions of bats for rabies testing, acoustic monitoring and the presence of T. brasiliensis in buildings and bat houses indicate that these bats are now established in year-round colonies in areas previously thought outside their range limits. The geographic distributions of many organisms are currently shifting to higher latitudes in response to changing climate. We hypothesize that a coldtolerant thermal physiology that allows these largely tropical bats to enter extended torpor contributes to the ability of T. brasiliensis to establish populations in formerly cooler regions and propose that their rapid northward expansion is facilitated by climate change and their tendency to explore new habitats and use a wide diversity of roost sites. Because of their abundance and use of man-made structures, we anticipate that the range expansion of T. brasiliensis will have implications for public health, ecosystem services and bat conservation. [ABSTRACT FROM AUTHOR]