Priority Intervention Targets Identified Using an In-Depth Sampling HIV Molecular Network in a Non-Subtype B Epidemics Area

Abstract

Molecular network analysis based on the genetic similarity of HIV-1 is increasingly used to guide targeted interventions. Nevertheless, there is a lack of experience regarding molecular network inferences and targeted interventions in combination with epidemiological information in areas with diverse epidemic strains of HIV-1.We collected 2,173 pol sequences covering 84% of the total newly diagnosed HIV-1 infections in Shenyang city, Northeast China, between 2016 and 2018. Molecular networks were constructed using the optimized genetic distance threshold for main subtypes obtained using sensitivity analysis of plausible threshold ranges. The transmission rates (TR) of each large cluster were assessed using Bayesian analyses. Molecular clusters with the characteristics of ≥5 newly diagnosed cases in 2018, high TR, injection drug users (IDUs), and transmitted drug resistance (TDR) were defined as priority clusters. Several HIV-1 subtypes were identified, with a predominance of CRF01_AE (71.0%, 1,542/2,173), followed by CRF07_BC (18.1%, 393/2,173), subtype B (4.5%, 97/2,173), other subtypes (2.6%, 56/2,173), and unique recombinant forms (3.9%, 85/2,173). The overall optimal genetic distance thresholds for CRF01_AE and CRF07_BC were both 0.007 subs/site. For subtype B, it was 0.013 subs/site. 861 (42.4%) sequences of the top three subtypes formed 239 clusters (size: 2-77 sequences), including eight large clusters (size ≥10 sequences). All the eight large clusters had higher TR (median TR = 52.4/100 person-years) than that of the general HIV infections in Shenyang (10.9/100 person-years). A total of ten clusters including 231 individuals were determined as priority clusters for targeted intervention, including eight large clusters (five clusters with≥5 newly diagnosed cases in 2018, one cluster with IDUs, and two clusters with TDR (K103N, Q58E/V179D), one cluster with≥5 newly diagnosed cases in 2018, and one IDUs cluster. In conclusion, a comprehensive analysis combining in-depth sampling HIV-1 molecular networks construction using subtype-specific optimal genetic distance thresholds, and baseline epidemiological information can help to identify the targets of priority intervention in an area epidemic for non-subtype B.

Molecular Network Analysis Reveals Transmission of HIV-1 Drug-Resistant Strains Among Newly Diagnosed HIV-1 Infections in a Moderately HIV Endemic City in China

“…Molecular networks were inferred based on pairwise nucleotide genetic distance (Tamura-Nei 93 substitution model) using HIV-TRACE (Kosakovsky Pond et al, 2018). Similar to the previous analysis, the optimal genetic distance threshold was identified to construct the molecular network through sensitivity analysis because the maximum number of molecular clusters could be generated at this threshold (Zhao et al, 2021). Only clusters containing ≥3 individuals with the same TDR mutation were selected for the HIVDR transmission cluster.…”

“…To explore TDR spread, we constructed CRF01_AE and CRF07_BC molecular networks as they harbored nearly all (n > 3) of the detected high-frequency TDR mutations (89.7%, 236/263) (Zhao et al, 2021). We inferred 232 CRF01_AE clusters (size range: 2-99) and 55 CRF07_BC clusters (size range: 2-70) (Figure 4).…”

“…Molecular network analysis based on pol gene sequences from HIVDR detection can be used to reconstruct the viral transmission network, which can clarify the pattern of HIV transmission and guide the development of prevention and control measures (Wertheim et al, 2014;Zhao et al, 2021). However, molecular network technology has rarely been used to explore HIVDR transmission in China.…”

Transmission and Drug Resistance Characteristics of Human Immunodeficiency Virus-1 Strain Using Medical Information Data Retrieval System

“…Among the free antiviral treatment formulas, there are 6 kinds of imitation antiviral drugs (didanosine (DDI), azidothymidine (AZT), 2′,3′-didehydro-3′-deoxythymidine (D4T), lamivudine (3TC), nevirapine (NVP), and efavirenz (EFV)) to compose 6 formulas such as AZT/DDI/NVP and AZT/3CT/NVP. Antiviral therapy can reduce the speed of virus replication for HIV patients and improve the body's immunity [ 23 ].…”

Practice and Prospect: HIV-1 Molecular Network-Based Studies in China

“…74 Interventions on individuals in these networks can effectively prevent networks from further rapid expansion. A new report from Shenyang (Liaoning Province) obtained the optimal threshold for constructing molecular networks by applying sensitivity analysis, 75 which means that the maximum number (not size) of clusters can be identified under this threshold. After constructing molecular networks, the study defined a molecular network with either a high transmission rate, rapid growth (more than five newly diagnosed infections), or presence of TDR as priority intervention networks, 75 providing a new way to leverage molecular networks for targeted intervention.…”