Understanding the Role of Rare Genetic Variants
Recent research on the UK Biobank cohort, a large-scale genetic data set, has shed light on the significant role of rare genetic variants (RVs) in complex trait heritability. The study confirms that these RVs account for a substantial portion of the complex trait heritability and their aggregation at the gene level leads to a significant loss of information. This insight emphasizes the need for more extensive research on RVs and their impact on health and diseases.
Research Design and Methodology
The study utilized two main genetic datasets from the UK Biobank: Whole Exome Sequencing (WES) data and imputed genotype data. The research employed a method called RARity to compute heritability estimates based on aggregating linear regression models over large genetic regions, encompassing thousands of variants. The study also evaluated pathogenicity scores such as CADD, M-CAP, and REVEL to classify deleterious RVs. These steps were complemented by extensive quality control of genetic data and simulation studies to identify suitable linkage disequilibrium (LD) pruning parameters for accurate heritability estimation.
Exploring the Influence of Sex, Gene Length, and Evolutionary Constraint
The exploration of sex-stratified analyses and the influence of gene length and evolutionary constraint on RV heritability added another layer of depth to the research. Such analyses provided valuable insights into the role of rare genetic variants in heritability and disease risk, opening up new avenues for gene discovery and the prediction of variant-level functionality.
Bridging the Gap in Diagnosing Indigenous Rare Diseases
In a related development, the International Rare Disease Research Consortium (IRDiRC) has convened a global Task Force to address health inequity faced by Indigenous people. The Task Force aims to bridge the gap in diagnosing Indigenous rare diseases, a critical step towards equitable healthcare. The initiative is supported by the Scientific Secretariat of IRDiRC, funded by the European Union through the European Joint Programme on Rare Disease under the European Union’s Horizon 2020 Research and Innovation Programme.
Uncovering New Drivers of Heart Disease and Brain Vessel Disorders
Another groundbreaking approach developed by Harvard Medical School scientists has established a way to connect genetic changes to biologic function and dysfunction. The technique combines several tools of genetic analysis to reveal how changes in gene structure can alter the biology and function of epithelial cells lining the blood vessels, leading to cardiovascular disease and brain vessel malformations. This innovative approach, known as V2G2P, could be a powerful strategy for studying many other diseases where genetic risk factors remain to be discovered.
Identifying Genetic Associations Related to Kidney Function
A large-scale study part of the international CKDGen consortium for research into the genetics of kidney disease has identified 23 genetic associations related to kidney function. The research also developed a method for analyzing the X chromosome in detail and identifying sex-specific differences, which can be used in future studies.
A New Genetic Disorder Causing Severe Lung Diseases
Recently, a never-before-documented genetic disorder that causes severe lung diseases and recurrent infections in children has been identified. Caused by the absence of a chemical receptor called CCR2, the disorder affects the ability of immune cells called alveolar macrophages to respond to infections and maintain proper levels of surfactant in the lungs.
Mapping CAD Variants and Biological Pathways
New research has discovered biological drivers of heart disease risk by mapping the relationship between known CAD variants and the biological pathways they impact. The researchers used the V2G2P approach to match CAD loci previously identified through genome-wide association studies to genes impacted by these genetic variants. This study focused on endothelial cells lining blood vessels and examined endothelial mechanisms unrelated to lipid metabolism, uncovering new mechanisms driving CAD risk for which therapies may yet be developed.
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