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Single-cell data combined with phenotypes improves variant interpretation

Whole genome sequencing offers significant potential to improve the diagnosis and treatment of rare diseases by enabling the identification of thousands of rare, potentially pathogenic variants. Existing variant prioritisation tools can be complemented by approaches that incorporate phenotype specificity and provide contextual biological information, such as tissue or cell-type specificity. 

Study Protocol for a Stepped-Wedge Cluster (Nested) Randomized Controlled Trial of Antenatal Colostrum Expression (ACE) Instruction in First-Time Mothers: The ACE Study

Although many mothers initiate breastfeeding, supplementation with human-milk substitutes (formula) during the birth hospitalization is common and has been associated with early breastfeeding cessation. Colostrum hand expressed in the last few weeks before birth, known as antenatal colostrum expression (ACE), can be used instead of human-milk substitutes. However, evidence is lacking on the efficacy of ACE on breastfeeding outcomes and in non-diabetic mothers. 

Gene editing and cardiac disease modelling for the interpretation of genetic variants of uncertain significance in congenital heart disease

Genomic sequencing in congenital heart disease (CHD) patients often discovers novel genetic variants, which are classified as variants of uncertain significance (VUS). Functional analysis of each VUS is required in specialised laboratories, to determine whether the VUS is disease causative or not, leading to lengthy diagnostic delays.

Pushing the boundaries of rare disease diagnostics with the help of the first Undiagnosed Hackathon

Timo Lassmann BSc (Hons) MSc PhD Feilman Fellow; Head, Precision Health Research and Head, Translational Intelligence timo.lassmann@thekids.org.au

Coupling of response biomarkers between tumor and peripheral blood in patients undergoing chemoimmunotherapy

Platinum-based chemotherapy in combination with anti-PD-L1 antibodies has shown promising results in mesothelioma. However, the immunological mechanisms underlying its efficacy are not well understood and there are no predictive biomarkers to guide treatment decisions.

Mining single-cell data for cell type-disease associations

A robust understanding of the cellular mechanisms underlying diseases sets the foundation for the effective design of drugs and other interventions. The wealth of existing single-cell atlases offers the opportunity to uncover high-resolution information on expression patterns across various cell types and

Functional characterization of the MED12 p.Arg1138Trp variant in females: implications for neural development and disease mechanism

Seven female individuals with multiple congenital anomalies, developmental delay and/or intellectual disability have been found to have a genetic variant of uncertain significance in the mediator complex subunit 12 gene. The functional consequence of this genetic variant in disease is undetermined, and insight into disease mechanism is required.

Preclinical efficacy of azacitidine and venetoclax for infant KMT2A-rearranged acute lymphoblastic leukemia reveals a new therapeutic strategy

Infants with KMT2A-rearranged B-cell acute lymphoblastic leukemia (ALL) have a dismal prognosis. Survival outcomes have remained static in recent decades despite treatment intensification and novel therapies are urgently required.

Time-course RNAseq data of murine AB1 mesothelioma and Renca renal cancer following immune checkpoint therapy

Time-critical transcriptional events in the immune microenvironment are important for response to immune checkpoint blockade (ICB), yet these events are difficult to characterise and remain incompletely understood. Here, we present whole tumor RNA sequencing data in the context of treatment with ICB in murine models of AB1 mesothelioma and Renca renal cell cancer. 

An evaluation of GPT models for phenotype concept recognition

Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field.