Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
1st Department of Medicine, Laikon General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
Infect Genet Evol. 2021 Jul;91:104799. doi: 10.1016/j.meegid.2021.104799. Epub 2021 Mar 4.
Improving HIV diagnosis, access to care and effective antiretroviral treatment provides our global strategy to reduce HIV incidence. To reach this goal we need to increase our knowledge about local epidemics. HIV infection dates would be an important information towards this goal, but they are largely unknown. To date, methods to estimate the dates of HIV infection are based mainly on laboratory or molecular methods. Our aim was to validate molecular clock inferred infection dates that were estimated by analysing sequences from 145 people living with HIV (PLHIV) with known transmission dates (clinically estimated infection dates).
All HIV sequences were obtained by Sanger sequencing and were previously found to belong to well-established molecular transmission clusters (MTCs).
Our analysis showed that the molecular clock inferred infection dates were correlated with the clinically estimated ones (Spearman's Correlation coefficient = 0.93, p < 0.001) and that there was an agreement between them (Lin's concordance correlation coefficient = 0.92, p < 0.001). For the 61.4% of cases the molecular clock inferred preceded the clinically estimated infection dates. The median difference between clinically and molecularly estimated dates of infection was of 0.18 (IQR: -0.21, 0.89) years. The lowest differences were identified in people who inject drugs of our study population.
The estimated time to more recent common ancestor (t) of nodes within clusters provides a reliable approximation of HIV infections for PLHIV infected within MTCs. Next-generation sequencing data and molecular clock estimates based on heterochronous sequences provide, probably, more reliable methods for inferring infection dates. However, since these data are not available in most of the HIV clinical laboratories, our approach, under specific conditions, can provide a reliable estimation of HIV infection dates and can be used for HIV public health interventions.
提高 HIV 诊断、获得医疗服务和有效的抗逆转录病毒治疗，是我们降低 HIV 发病率的全球战略。为了实现这一目标，我们需要更多地了解当地的流行情况。HIV 感染日期是实现这一目标的重要信息，但目前尚不清楚。迄今为止，估计 HIV 感染日期的方法主要基于实验室或分子方法。我们的目的是验证通过分析具有已知传播日期（临床估计的感染日期）的 145 名 HIV 感染者（PLHIV）的序列而推断出的分子钟感染日期。
所有 HIV 序列均通过 Sanger 测序获得，并且先前发现它们属于成熟的分子传播簇（MTC）。
我们的分析表明，分子钟推断的感染日期与临床估计的感染日期相关（Spearman 相关系数= 0.93，p < 0.001），并且两者之间存在一致性（Lin 的一致性相关系数= 0.92，p < 0.001）。对于 61.4%的病例，分子钟推断的感染日期早于临床估计的感染日期。感染日期的临床和分子估计之间的中位数差异为 0.18 年（IQR：-0.21，0.89）。在我们研究人群中，吸毒者的差异最小。
簇内节点的更近共同祖先（t）的估计时间为感染 MTC 内的 PLHIV 提供了 HIV 感染的可靠近似值。基于异时序列的下一代测序数据和分子钟估计可能为推断感染日期提供更可靠的方法。但是，由于大多数 HIV 临床实验室都无法获得这些数据，因此在特定条件下，我们的方法可以提供 HIV 感染日期的可靠估计，并可用于 HIV 公共卫生干预措施。
