Изменивший правила игры в раскрытии генетической предрасположенности к COVID-19

Используя недавно разработанный инструмент под названием GASPACHO, ученые обнаружили вариант гена, связанный с повышенной восприимчивостью к вирусам.

” data-gt-translate-атрибуты = “[{” attribute=””>COVID-19. The tool allows them to track gene expression changes in the innate immune response, aiding in the identification of potential therapeutic targets.

Researchers have discovered a mechanism for COVID-19 susceptibility using a newly created tool. The tool, GASPACHO, captures dynamic changes in gene expression along the innate immune response, allowing researchers to identify genes and molecular pathways associated with disease risk that have previously been too complex to detect or interpret.

Using GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), researchers at the Wellcome Sanger Institute, the National Center for Child Health and Development in Japan, Tel Aviv University and their collaborators have identified a gene variant that affects COVID-19 susceptibility. Understanding genetic factors contributing to COVID-19 infection and severity may provide new biological insights into disease pathogenesis and identify therapeutic targets. It is hoped the tool can be applied to discover further susceptibility mechanisms across other human disorders.

The study, published in Nature Genetics on June 12, helps to unpick the relationship between specific genes, their expression levels, and their potential connection in disease susceptibility. The team highlights the utility of the tool with a COVID-19 case study.

There exists a wide variation in how people respond to COVID-19. Around 80 percent of infected people experience a mild-to-moderate bout of illness, while some will experience mainly respiratory symptoms that are much more severe, requiring hospitalization and even intensive care. Part of this variation may be down to differences in our genes, specifically differences in our genetic regulation of gene expression.

The regions that affect gene expression are called expression quantitative trait loci (eQTLs). These are like signposts in our

Researchers from the Wellcome Sanger Institute and their collaborators in Japan and at Tel Aviv University triggered an antiviral response in human fibroblast cells from 68 healthy donors, then profiled them using single-cell transcriptomics to put GASPACHO to the test.

The tool uses non-linear regression modeling^[1] для регистрации динамических изменений в eQTL, происходящих на разных стадиях иммунного ответа. В отличие от предыдущих попыток картирования eQTL, которые объединяли данные по отдельным ячейкам — измеряя среднюю экспрессию генов во многих клетках, — GASPACHO обеспечивает разрешение для конкретных клеток для отслеживания изменений во времени и в отдельных ячейках.

Команда идентифицировала 1275 eQTL в геноме, которые изменяют экспрессию генов во время врожденного иммунного ответа между людьми, что имеет значение для 40 иммунных заболеваний, таких как болезнь Крона и диабет.

Исследователи обнаружили, что при применении инструмента для изучения вариаций исходов COVID-19 более низкая экспрессия ОАС1 изменение генов произошло у тех, кто с большей вероятностью заразится COVID-19. ОАС1 ген кодирует белок, участвующий в элиминации вируса.

” data-gt-translate-атрибуты = “[{” attribute=””>RNA from the cell.

In COVID-19 patients, the team found lower OAS1 expression in nasal epithelial cells as well as monocytes in blood — both viral target cell types — compared to a reference genotype group. Their findings suggest that OAS1 expression can be modulated by a common splicing variant, OAS1 splicing QTL, at these target cell types. This is a genetic alteration in the DNA sequence at the boundary of an exon and intron. In these cells, the splicing variant will likely directly influence the efficacy of viral RNA clearance in the individual, explaining the impaired clinical outcome in the COVID-19 patient group.

While this genetic alteration needs to be explored further to fully understand the role it plays, it offers insights into the molecular mechanisms underlying susceptibility to COVID-19 and other immune-related diseases, providing a basis for developing potential therapies harnessing these genetic mechanisms.

Dr. Natsuhiko Kumasaka, first author of the study from the National Center for Child Health and Development in Japan, said: “We may in the future be able to use OAS1 and other genes on the same cascade in drug discovery or as therapeutic targets, but more research is needed to understand the specific mechanisms by which OAS1 or related genes may contribute to COVID-19.”

Dr. Tzachi Hagai, co-lead author of the study from Tel Aviv University, said: “It’s remarkable how small differences in our genetic makeup can affect our health and susceptibility to disease, just by influencing how active our genes are. While host-specific genetic factors are only one part of the puzzle, our work sheds light on the molecular mechanisms underlying various traits, diseases, and drug responses and how these may interact among wider environmental, clinical, and social factors. The findings here underscore the importance of ongoing scientific investigations to unravel the complex interactions between human genetics and the outcome of pathogen infection, including by emerging viruses such as

Notes

1. Non-linear regression modeling is a statistical approach used to analyze and describe relationships between variables that do not follow a straight line. It allows for more flexible representations of complex patterns and trends in the data.

Reference: “Mapping interindividual dynamics of innate immune response at single-cell resolution” by Natsuhiko Kumasaka, Raghd Rostom, Ni Huang, Krzysztof Polanski, Kerstin B. Meyer, Sharad Patel, Rachel Boyd, Celine Gomez, Sam N. Barnett, Nikolaos I. Panousis, Jeremy Schwartzentruber, Maya Ghoussaini, Paul A. Lyons, Fernando J. Calero-Nieto, Berthold Göttgens, Josephine L. Barnes, Kaylee B. Worlock, Masahiro Yoshida, Marko Z. Nikolic, Emily Stephenson, Gary Reynolds, Muzlifah Haniffa, John C. Marioni, Oliver Stegle, Tzachi Hagai and Sarah A. Teichmann, 12 June 2023, Nature Genetics.
DOI: 10.1038/s41588-023-01421-y