Information about individual-level genetic ancestry is central to population genetics, forensics and genomic medicine. So far, studies have typically considered genetic ancestry on a broad continental level, and there is much less understanding of how more detailed genetic ancestry profiles can be generated and how accurate and reliable they are. Here, we assess these questions by developing a framework for individual-level ancestry estimation within a single European country, Finland, and we apply the framework to track changes in the fine-scale genetic structure throughout the 20th century. We estimate the genetic ancestry for 18,463 individuals from the National FINRISK Study with respect to up to 10 genetically and geographically motivated Finnish reference groups and illustrate the annual changes in the fine-scale genetic structure over the decades from 1920s to 1980s for 12 geographic regions of Finland. We detected major changes after a sudden, internal migration related to World War II from the region of ceded Karelia to the other parts of the country as well as the effect of urbanization starting from the 1950s. We also show that while the level of genetic heterogeneity in general increases towards the present day, its rate of change has considerable differences between the regions. To our knowledge, this is the first study that estimates annual changes in the fine-scale ancestry profiles within a relatively homogeneous European country and demonstrates how such information captures a detailed spatial and temporal history of a population. We provide an interactive website for the general public to examine our results.

Motivation Biobank scale genetic associations results over thousands of traits can be difficult to visualize and navigate. Results We have created LAVAA, a visualization web-application to generate genetic volcano plots for simultaneously considering the p-value, effect size, case counts, trait class and fine-mapping posterior probability at a single SNP across a range of traits from a large set of GWAS. We find that user interaction with association results in LAVAA can enrich and enhance the biological interpretation of individual loci. Availability LAVAA is available as a stand-alone web service (https://geneviz.aalto.fi/LAVAA/) and will be available in future releases of the finngen.fi website starting with release 10 in late 2023.

Although network visualizations are becoming increasingly common, designing such visualizations can be challenging due to the number of visual elements and non-linear relations that they need to display. The main design challenge faced is finding the right trade-off between providing a sufficient level of information detail while keeping the visual complexity of the visualization as low as possible. One way of overcoming this challenge is to rely on the use of mental models that are familiar to the users of network visualizations. In this paper, we propose the use of a mental interaction model similar to that of map visualizations -generally based on geographical maps -as the basis for visual design of network diagrams. We argue that such a mental model would foster a set of network interaction tasks that can be defined broadly as wayfinding. We present the process of wayfinding from a semiotic standpoint, and match its main key points to those of interaction tasks with network diagrams. As a case study for this analysis, we also present a prototype network diagram visualization tool, called Colocalization Network Explorer, which we have developed to support the exploration of the relationships between various diseases and the portion of the human genome that is potentially involved in their onset. Additionally, we describe how the design process has benefited from the adoption of the wayfinding mental model.

TPS754 Background: Collecting duct carcinoma (CDC) is a rare type of non-clear cell renal cell carcinoma with an aggressive course and poor prognosis. The treatment of metastatic disease remains unsatisfactory as no standard-of-care has been established yet. The gap in the clinical management is certainly linked to the poor molecular characterization. To date, a comprehensive biological characterization of CDC and the identification of predictive biomarker is still lacking. Our previous studies proved that CDC is a molecularly heterogeneous disease composed of at least two subtypes distinguished by cell signalling, metabolic and immune-related alterations and featured by a prognostic signature associating T cell immunity and angiogenesis with good clinical outcome and sensitivity to cabozantinib (Gargiuli et al, Cancers 2021 Jun 10;13(12):2903; Todoerti et al, J Clin Oncol 40, no. 16_suppl (June 01, 2022) e16507-e16507; Verzoni et al, Ann Oncol 33:S1218-S121). The aim of CICERONE trial is to change the paradigm of CDC management providing therapies in a biologically informed manner starting from our previous findings. Methods: First, we will define a molecular taxonomy of CDC through comprehensive transcriptomic profiling of 100 CDC samples retrospectively collected within 12 months from the Italian Group of Uropathology Network and the European Union Hub Center. Pathologic review by genitourinary pathologist was required. RNA-Seq will be performed. Results will be merged to that already obtained by the same methodology from the BONSAI dataset (NCT03354884) and evaluated by unsupervised clustering analysis. We will identify differentially expressed genes and pathways. The immune and angiogenic signatures will be searched validating our preliminary results to identify predictive signatures for the subsequent prospective phase II trial. RNA-seq data will be also explored to detect fusion transcripts, as potential source of novel CDC oncogenic drivers, and study immune tumor content through Cybersort deconvolution. RT-qPCR on RNA derived from tumor and normal tissue will be performed to determine tumor specific origin of the fusion transcripts. Immune infiltrate will be also characterized by IHC, together with PDL-1 scoring. Subsequently we will conduct a prospective phase II trial in order to optimize treatment choice and validate prospectively the biological data. In this phase, previously untreated patients with metastatic CDC will be treated according to baseline tumor signature. Moreover, we will assess whether a new concept of immune liquid biopsy that includes the assessment of immunosuppressive vs antitumor immune cells may represent an accessible and compliant tool to test systemic immunity and its implications in response to treatment. This study was supported by the Italian Ministry of health (RF-2019-12369602). Clinical trial information: NCT05372302 .