Covariance Network Analysis Predicts Hepatitis Outcomes

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Covariance Network Analysis Predicts Hepatitis Outcomes

Differences in network connections identify hepatitis C patients who respond to

antiviral therapyPublish date: Dec 26, 2008

FRIDAY, Dec. 26 (HealthDay News) -- In patients with hepatitis C infection,

analyzing genome-wide virus amino acid covariance networks can predict response

to treatment with interferon-alpha and ribavirin, according to a report

published online Dec. 22 in the Journal of Clinical Investigation.

Rajeev Aurora, Ph.D., of the Saint Louis University School of Medicine, and

colleagues analyzed amino acid covariance within the full viral coding region of

virus sequences obtained from 94 patients who subsequently underwent treatment.

The researchers found the existence of genome-wide networks of covarying amino

acids, and found that the connections within the networks differed in responders

and non-responders, with non-responders having three times as many hydrophobic

amino acid pairs. After detecting patterns within the networks, they were able

to predict treatment outcomes with greater than 95 percent coverage and 100

percent accuracy.

" Furthermore, the hub positions in the networks are attractive antiviral targets

because of their genetic linkage with many other positions that we predict would

suppress evolution of resistant variants, " the authors conclude. " Finally,

covariance network analysis could be applicable to any virus with sufficient

genetic variation, including most human RNA viruses. "

[Guest guest]

http://www.modernmedicine.com/modernmedicine/Pathology/Covariance-Network-Analys\

is-Predicts-Hepatitis-Out/ArticleNewsFeed/Article/detail/573190?contextCategoryI\

d=40142

Covariance Network Analysis Predicts Hepatitis Outcomes

Differences in network connections identify hepatitis C patients who respond to

antiviral therapyPublish date: Dec 26, 2008

FRIDAY, Dec. 26 (HealthDay News) -- In patients with hepatitis C infection,

analyzing genome-wide virus amino acid covariance networks can predict response

to treatment with interferon-alpha and ribavirin, according to a report

published online Dec. 22 in the Journal of Clinical Investigation.

Rajeev Aurora, Ph.D., of the Saint Louis University School of Medicine, and

colleagues analyzed amino acid covariance within the full viral coding region of

virus sequences obtained from 94 patients who subsequently underwent treatment.

The researchers found the existence of genome-wide networks of covarying amino

acids, and found that the connections within the networks differed in responders

and non-responders, with non-responders having three times as many hydrophobic

amino acid pairs. After detecting patterns within the networks, they were able

to predict treatment outcomes with greater than 95 percent coverage and 100

percent accuracy.

" Furthermore, the hub positions in the networks are attractive antiviral targets

because of their genetic linkage with many other positions that we predict would

suppress evolution of resistant variants, " the authors conclude. " Finally,

covariance network analysis could be applicable to any virus with sufficient

genetic variation, including most human RNA viruses. "