NEW YORK – A team from the National Library of Medicine, Broad Institute, and Massachusetts Institute of Technology has started tallying the genetic features that distinguish pathogenic coronaviruses — particularly the SARS-CoV-2 virus behind the ongoing COVID-19 pandemic and the Middle Eastern respiratory syndrome-causing MERS-CoV — from less dangerous coronaviruses.

“We were able to identify several features that are not found in less virulent coronaviruses and that could be relevant for pathogenicity in humans. The actual demonstration of the relevance of these findings will come from direct experiments that are currently getting under way,” senior author Eugene Koonin, a biotechnology information researcher at the National Library of Medicine, said in a statement.

For a paper published in the Proceedings of the National Academy of Sciences on Wednesday, the researchers relied on comparative genomics, phylogenetic analyses, and support vector-based machine learning to narrow in on suspicious features shared by the SARS-CoV-2 and MERS-CoV coronaviruses, which they classified as viruses with “high case fatality rate” (high-CFR) coronaviruses. They noted that the machine-learning strategy selected made it possible to pick up differences between these high-CFR viruses and “low-CFR” human coronaviruses that might be missed with genome alignment-based comparisons alone.

“[W]e trained multiple support vector machines across a sliding window to detect regions that confer clean separation between high- and low-CFR virus genomes,” the authors explained. “We evaluated the performance of each [support vector machine] via cross-validation and filtered for genomic regions that significantly distinguish the high- and low-CFR genomes.”

Based on analyses of more than 900 available coronavirus genomes, the team uncovered 11 seemingly distinct sites in the high-CFR SARS-CoV-2 and MERS-CoV genomes, including sequences coding for the nucleocapsid protein and the spike glycoprotein that interacts with host cell receptors.

When they took a closer look at these changes, the researchers saw signs that the high-CFR viruses produce a version of the nucleocapsid protein with an enhanced nuclear localization signal, while the spike protein for the potentially deadly SARS and MERS coronaviruses shared insertions not found in more mild-mannered, low-CFR coronaviruses.

“The enhancement of the NLS in the high-CFR coronaviruses nucleocapsids implies an important role of the sub-cellular localization of the nucleocapsid protein in coronavirus pathogenicity,” the authors suggested, adding that “insertions in the spike protein appear to have been acquired independently by the SARs and MERS clades of the high-CFR coronaviruses, in both the domain involved in virus-cell fusion and the domain mediating receptor recognition.”

While functional studies are needed to dig into the potential connections identified in their new analysis, the authors suggested that the features found so far “could be crucial contributors to coronavirus pathogenicity and possible targets for diagnostics, prognostication, and interventions.”

“These features correlate with the high fatality rate of these coronaviruses as well as their ability to switch hosts from animals to humans,” Koonin and co-authors explained. “The identified features could represent crucial elements of coronavirus virulence and allow for detecting animal coronaviruses that have the potential to make the jump to humans in the future.”

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July 31, 2019 – Improving collaboration between specialists and integrating multiple datasets to leverage big data will be key for advancing research for dry age-related macular degeneration (AMD), according to a new report from a National Institute of Health (NIH) working group.

Over 11 million people in the United States are diagnosed with AMD, an eye disease that ultimately results in blindness. It is the leading cause of blindness among individuals 65 years of age and older.

The disease can manifest in one of two forms: neovascular (wet) or non-neovascular (dry). While the neovascular form progresses more rapidly, there are several known and proven treatments for the disease. There are no preventive measures for dry AMD nor treatment options.

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“The working group thoroughly assessed what is known about dry AMD pathobiology, and the recommendations will be informative for considering future NEI research priorities to align with promising pathways for discovering therapeutic targets,” said Director of National Eye Institute (NEI), Paul Sieving, MD, PhD, in an earlier news release.

The working group recommended a systems biology approach to disease treatment, an integration of genomic, preclinical, medical, pharmacological, and clinical data to inform modeling of the disease progression. Synthesizing big data from all these areas including tissue samples from clinical trials will help inform predictive modeling which can then be used to inform individual patient care.

A personalized approach to disease management may also be helpful, the working group recommended. Such an approach should consider the disease stage, progression, and individual risk factors to provide preventive and treatment strategies specific to the patient, the report said. Collaborating will all points of care will allow a multidisciplinary team to use a patient’s unique clinical, imaging, and genomic data to treat the disease.

“We propose that researchers utilize a systems biology approach, integrating the big data available from clinical registries and various fields of biology known as ‘omics’ to develop better models and ultimately treatments for patients with this blinding disease,” stated report co-author Joan W. Miller, MD.

Due to a lack of preventive strategies and treatment options for dry AMD, the working group noted the need for improved understanding of the disease pathology and promoted clinical trial investigations to do so. Previous research has shown a genetic link to the disease as well as several lifestyle factors including smoking, but there is no work examining the effects these factors have on dry AMD.

A better understanding of how these factors impact the disease will help providers be better informed to watch for risk factors and promote inventive preventive strategies. Such understanding only comes from examining data and promoting the use of big, integrated data sources to help investigators use multiple sources to answer their questions.

Effective disease management will need multiple targets that differ based on the disease stage progression, the report notes. A strategy overhaul needs to take place that focuses on large-scale, collaborative, systems biology in order to effectively treat the disease.

“This approach would integrate basic, genomic, pre-clinical, medical, pharmacological, and clinical data into mathematical models of pathological processes at different stages of dry AMD in order to ask how relevant individual components act together within the living system,” Miller said.

The working group was appointed by the National Advisory Eye Council, a 12-member panel that establishes guidelines for the NEI under the NIH. The group was charged with a multilayered goal: to raise public health awareness about the impact of dry AMD, review the current state of research about the disease for a better understanding of its pathology, propose future research directions, encourage scientists to focus on AMD, and promote collaboration among a network of specialized providers.

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