The Current Hepatitis C Virus Prevalence in China May Have Resulted Mainly from an Officially Encouraged Plasma Campaign in the 1990s: a Coalescence Inference with Genetic Sequences

Abstract

In this study, we investigated hepatitis C virus (HCV) molecular epidemiology and evolutionary dynamics. Both E1 and NS5B sequences were characterized in 379 of 433 patients in southern China and classified into five major subtypes: 1b in 256 patients, 6a in 67 patients, 2a in 29 patients, 3a in 14 patients, and 3b in 13 patients. Using the E1 sequences obtained, along with those from other studies using samples from China, we inferred the HCV epidemic history by means of coalescence strategies. Five Bayesian skyline plots (BSPs) were estimated for the five subtypes. They concurrently highlighted the rapid growth in the HCVinfected population size from 1993 to 2000, followed by an abrupt slowing. Although flanked on both sides by variable population sizes, the plots showed distinct patterns of rapid HCV growth. Coincidently, 1993 to 2000 was a period when contaminated blood transfusions were common in China due to a procedural error in an officially encouraged plasma campaign. The abrupt slowing in 1998 to 2000 corresponded to the central government outlawing paid blood donations in 1998. Using a parametric model, the HCV population growth rates were estimated during 1993 to 2000. It was revealed that the 6a rate was the highest, followed by those of 1b, 2a, 3b, and 3a. Because these rates differed significantly (P < 1e؊9) from each other, they may help explain why 6a is increasingly prevalent in southern China and 1b is predominant nationwide. These rates are approximately 10-fold higher than those reported elsewhere. These findings suggested that during the plasma campaign, certain barriers to efficient viral transmission were removed, allowing wide HCV dissemination.

Migration Patterns of Hepatitis C Virus in China Characterized for Five Major Subtypes Based on Samples from 411 Volunteer Blood Donors from 17 Provinces and Municipalities

“…This corresponds to a period during which contaminated blood transfusions were common, largely due to a procedural error in an officially encouraged plasma campaign. Using a parametric model, we estimated the HCV population growth rates during this period and suggested that certain barriers to efficient viral transmission were removed, allowing nationwide dissemination (20). Although these findings support the belief that the plasma campaign founded the high HCV prevalence in China, the current HCV genotype distribution patterns could also have been affected by subsequent human migrations.…”

A Unique Pattern of HCV Genotype Distribution on Hainan Island in China Revealed by Evolutionary Analysis

“…Four clusters were identified. Clusters I, II, and III are the same as those we have reported previously [13,15,17,30], each having a full posterior probability of 1.00. In contrast, the fourth cluster is not as robust as these three; it has a probability of only 0.51 and is thus unnamed.…”

“…Surprisingly, this time frame was much later than that we estimated for other HCV subtypes. Although we should bear in mind that the time frames of other HCV subtypes correspond to a period during which a procedural error occurred in an officially encouraged plasma campaign in China [17], a delayed time frame for subtype 1a may indicate its unique epidemic history. A better interpretation was provided by a BSP, which estimated the rapid population growth of subtype 1a occurred during 1998~2005.…”

“…Although there was a clear slowing down of the growth rate around 2005, the growth continued through to the present time. After comparison with the BSPs we recently described for subtypes 1b, 2a, 3a, 3b, and 6a [17], two important features of the BSP for 1a become evident: (1) its rapid growth occurred later than that of the other HCV subtypes; and (2) there has been no constant phase in the population size in the near recent past.…”

“…Therefore, to analyze the various HCV subtypes, we used the exponential clock model in combination with the GTR+I+Г substitution model and the Bayesian skyline model. However, prior evolutionary rates differed among HCV subtypes, as we have recently described [13,17]. MCMC chains were run for 300 million states and a tree was generated for every 10,000 states.…”