Hasil untuk "Genetics"

Giacomo Cavalli, E. Heard

R. Loos, G. Yeo

The prevalence of obesity has tripled over the past four decades, imposing an enormous burden on people’s health. Polygenic (or common) obesity and rare, severe, early-onset monogenic obesity are often polarized as distinct diseases. However, gene discovery studies for both forms of obesity show that they have shared genetic and biological underpinnings, pointing to a key role for the brain in the control of body weight. Genome-wide association studies (GWAS) with increasing sample sizes and advances in sequencing technology are the main drivers behind a recent flurry of new discoveries. However, it is the post-GWAS, cross-disciplinary collaborations, which combine new omics technologies and analytical approaches, that have started to facilitate translation of genetic loci into meaningful biology and new avenues for treatment. In this Review, Loos and Yeo summarize our current understanding of the genetic underpinnings of monogenic and polygenic obesity. They highlight the commonalities revealed by recent studies and discuss the implications for treatment and prediction of obesity risk.

A. Boehme, Charles C. Esenwa, M. Elkind

C. Kenyon

Nicholas A. Sinnott-Armstrong, Yosuke Tanigawa, D. Amar et al.

Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 5,794 independent loci associated with at least one trait (p 0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build ‘multi-PRS’ models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases. Genetic analysis of 35 blood and urine laboratory measurements from 363,228 individuals identifies 1,857 loci associated with at least one laboratory value.

Tim Postmus

M. Beaumont, Jinlian Wang

▶ Provides a forum for data and ideas, aiding the further development of conservation genetics ▶ Topics include population genetics, molecular ecology and biology, evolutionary biology, and systematics and more ▶ Offers full research papers, review papers, short communications, and methodological notes ▶ Widely indexed and abstracted ▶ 96% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again

E. Mardis

The COVID-19 Host Genetics Initiative

The COVID-19 pandemic is a global crisis creating severe disruptions across the economy and health system. Insights into how to better understand and treat COVID-19 are desperately needed. Early studies have focused on the clinical characteristics [1–3], epidemiology [1, 4, 5], and genomic characterization [6–8] of SARS-CoV-2 infection. These studies have also highlighted the value and importance of transparent data sharing across countries, which have enabled the live tracking of the disease widespread worldwide [9, 10]. The role of host genetics in impacting susceptibility and severity of COVID-19 has been less studied. Previous work has supported the role of human leukocyte antigen (HLA) in susceptibility [11] and severity [12] for several viral infections. Moreover, a synonymous variant in the IFN-induced transmembrane protein-3 gene has been reported to cause severe clinical outcomes in patients infected with H7N9 and H1N1 influenza viruses [13, 14], although results did not reach established P value thresholds (P < 5 × 10). In addition, candidate variant studies have suggested host factors that are critical for severe disease in other coronavirus infections, such as infections due to the related SARS-CoV [15]. Given the importance and urgency of exploring the role of the host genome in conjunction with COVID-19 clinical and genomic variability, and the recognition that this can only be achieved with the combined effort of the scientific community, we launched the ‘COVID-19 Host Genetics Initiative’. This initiative brings together the human genetics community to generate, share, and analyze data to learn the genetic determinants of COVID-19 susceptibility, severity, and outcomes. Such discoveries could help to identify individuals at unusually high or low risk, generate hypotheses for drug repurposing, and contribute to global knowledge of the biology of SARS-CoV-2 infection and disease. The initiative has three main goals:

F. Furnari, T. Fenton, R. Bachoo et al.

Malignant astrocytic gliomas such as glioblastoma are the most common and lethal intracranial tumors. These cancers exhibit a relentless malignant progression characterized by widespread invasion throughout the brain, resistance to traditional and newer targeted therapeutic approaches, destruction of normal brain tissue, and certain death. The recent confluence of advances in stem cell biology, cell signaling, genome and computational science and genetic model systems have revolutionized our understanding of the mechanisms underlying the genetics, biology and clinical behavior of glioblastoma. This progress is fueling new opportunities for understanding the fundamental basis for development of this devastating disease and also novel therapies that, for the first time, portend meaningful clinical responses.

D. Graham, R. Xavier

Brenda Winkel-Shirley

M. E. Davey, G. O’Toole

D. Falconer

M. Lynch, B. Walsh

F. Allendorf, G. Luikart

S. Manel, M. Schwartz, G. Luikart et al.

R. Frankham

M. Claussnitzer, Judy H. Cho, R. Collins et al.

M. Ghoussaini, Edward Mountjoy, M. Carmona et al.

Abstract Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.