Designing a Genome-Based HIV Incidence Assay with High Sensitivity and Specificity

• Activity Number: 145
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Sung Yong Park and Tanzy Love*+ and Sally W. Thurston and Alan S. Perelson and Ha Youn Lee
• Companies: University of Southern California and University of Rochester and University of Rochester and Los Alamos National Laboratory and University of Southern California
• Keywords: AIDS ; discrimination ; Hamming distance ; time of infection ; incidence rate

Abstract

Considerable inaccuracy in identifying HIV incidence has been a serious obstacle to the development of efficient HIV/AIDS prevention and interventions. Accurately distinguishing recent or incident infections from chronic infections enables one to monitor epidemics and evaluate the impact of HIV prevention/intervention trials. Our study designed a novel scheme for identifying incident infections in a highly accurate manner, based on the characteristics of HIV gene diversification within an infected individual. We devised a binary classification test based on the tail characteristics of the Hamming distance distribution of sequences and identified a clear signature of incident infections. The presence of closely related strains in the sampled HIV gene sequences identify recent infections in both single-variant and multivariant transmissions. This criteria, used as a biomarker, is found to have greater than 95% specificity and sensitivity and is robust to viral and host-specific factors. Because of rapid and continuing improvements in sequencing technology and cost, sequence-based incidence assays hold great promise as a means of quantifying HIV incidence from a single blood test.