Comparison of Plasma, Dried Blood Spots, and Peripheral Blood Mononuclear Cells as Biosamples for HIV-1 Genotypic...

The collection, storage, and transport of plasma, the ideal specimen for HIV-1 genotyping, is plagued by technical difficulties in resource-limited settings. We aimed to compare corresponding bio-samples for HIV-1 genotypic drug resistance testing. A total of 87 matched specimens of plasma, dried blood spots (DBS), and peripheral blood mononuclear cells (PBMCs) collected from 29 persons living with HIV (PLWH) in clinical, immunological, and/or virological failure were included. Drug resistance genotyping was done by nested PCR amplification and Sanger sequencing of the HIV-1 pol gene. The clinical reporting was based on the Stanford University HIV Drug Resistance Database. Amplification and genotyping success rates from the three sample types were compared. The level of agreement between the sample types was assessed using Cohen's kappa coefficient. In total, 89.7% (n = 26) of samples were amplified in plasma, 69% (n = 20) in DBS, and 100% (n = 29) in PBMC. In samples with plasma viral load >1,000 copies/mL, 96.2% were amplified in plasma, 73.1% in DBS, and 100% in PBMCs. The median number of mutations detected in plasma, DBS, and PBMCs was 6.5 (interquartile range [IQR]: 2-8.25), 5 (IQR: 0-6), and 5 (IQR: 2-7), respectively. The difference in the number of mutations across the three sample types was not statistically significant (p = 0.221). The agreement between the sample types was calculated based on susceptibility and resistance to different antivirals. The kappa values for nucleoside reverse transcriptase inhibitors and non-nucleoside reverse transcriptase inhibitors ranged from 0.70 to 0.88 and 0.75 to 0.87, respectively. Six samples showed discordance in HIV-1 drug resistance profiles when compared across the three compartments. DBS is a promising alternative to plasma for HIV-1 genotypic testing in resource-limited settings owing to the ease of sampling, storage, transportation, human resource efficiency, and cost-effectiveness. However, no single specimen type can satisfy all requirements and purposes. Selecting an appropriate specimen for a setting requires careful consideration of the practical constraints, logistical capacity, and application needs.