Diagnosis of paediatric HIV/AIDS.

(East African Medical Journal: 2002 79(3): 109-110

Host genetics and viral load in primary HIV-1 infection: clear evidence for gene by sex interactions

© 2014, The Author(s).Research in the past two decades has generated unequivocal evidence that host genetic variations substantially account for the heterogeneous outcomes following human immunodeficiency virus type 1 (HIV-1) infection. In particular, genes encoding human leukocyte antigens (HLA) have various alleles, haplotypes, or specific motifs that can dictate the set-point (a relatively steady state) of plasma viral load (VL), although rapid viral evolution driven by innate and acquired immune responses can obscure the long-term relationships between HLA genotypes and HIV-1-related outcomes. In our analyses of VL data from 521 recent HIV-1 seroconverters enrolled from eastern and southern Africa, HLA-A*03:01 was strongly and persistently associated with low VL in women (frequency = 11.3 %, P  0.50). In a reduced multivariable model, age, sex, geography (clinical sites), previously identified HLA factors (HLA-B*18, B*45, B*53, and B*57), and the interaction term for female sex and HLA-A*03:01 collectively explained 17.0 % of the overall variance in geometric mean VL over a 3-year follow-up period (P < 0.0001). Multiple sensitivity analyses of longitudinal and cross-sectional VL data yielded consistent results. These findings can serve as a proof of principle that the gap of “missing heritability” in quantitative genetics can be partially bridged by a systematic evaluation of sex-specific associations

Population-Based Biochemistry, Immunologic and Hematological Reference Values for Adolescents and Young Adults in a Rural Population in Western Kenya

BACKGROUND: There is need for locally-derived age-specific clinical laboratory reference ranges of healthy Africans in sub-Saharan Africa. Reference values from North American and European populations are being used for African subjects despite previous studies showing significant differences. Our aim was to establish clinical laboratory reference values for African adolescents and young adults that can be used in clinical trials and for patient management. METHODS AND FINDINGS: A panel of 298, HIV-seronegative individuals aged 13-34 years was randomly selected from participants in two population-based cross-sectional surveys assessing HIV prevalence and other sexually transmitted infections in western Kenya. The adolescent (/=18 years) ratio and the male-to-female ratio was 1ratio1. Median and 95% reference ranges were calculated for immunohematological and biochemistry values. Compared with U.S-derived reference ranges, we detected lower hemoglobin (HB), hematocrit (HCT), red blood cells (RBC), mean corpuscular volume (MCV), neutrophil, glucose, and blood urea nitrogen values but elevated eosinophil and total bilirubin values. Significant gender variation was observed in hematological parameters in addition to T-bilirubin and creatinine indices in all age groups, AST in the younger and neutrophil, platelet and CD4 indices among the older age group. Age variation was also observed, mainly in hematological parameters among males. Applying U.S. NIH Division of AIDS (DAIDS) toxicity grading to our results, 40% of otherwise healthy study participants were classified as having an abnormal laboratory parameter (grade 1-4) which would exclude them from participating in clinical trials. CONCLUSION: Hematological and biochemistry reference values from African population differ from those derived from a North American population, showing the need to develop region-specific reference values. Our data also show variations in hematological indices between adolescent and adult males which should be considered when developing reference ranges. This study provides the first locally-derived clinical laboratory reference ranges for adolescents and young adults in western Kenya

Cerebrospinal Fluid Viral Load and Intrathecal Immune Activation in Individuals Infected with Different HIV-1 Genetic Subtypes

Background: HIV-1 exhibits a high degree of genetic diversity and is presently divided into 3 distinct HIV-1 genetic groups designated major (M), non-M/non-O (N) and outlier (O). Group M, which currently comprises 9 subtypes (A-D, F-H, J and K), at least 34 circulating recombinant forms (CRFs) and several unique recombinant forms (URFs) is responsible for most of the HIV-1 epidemic. Most of the current knowledge of HIV-1 central nervous system (CNS) infection is based on subtype B. However, subtypes other than subtype B account for the majority of global HIV-1 infections. Therefore, we investigated whether subtypes have any influence on cerebrospinal fluid (CSF) markers of HIV-1 CNS infection. Methodology/Principal Findings: CSF HIV-1 RNA, CSF neopterin and CSF white blood cell (WBC) count were measured in patients infected with different HIV-1 subtypes. Using multivariate regression analysis, no differences in the CSF WBC count, neopterin and viral load were found between various HIV-1 subtypes

Does rapid HIV disease progression prior to combination antiretroviral therapy hinder optimal CD4 + T-cell recovery once HIV-1 suppression is achieved?

Objective: This article compares trends in CD4+ T-cell recovery and proportions achieving optimal restoration (>=500 cells/µl) after viral suppression following combination antiretroviral therapy (cART) initiation between rapid and nonrapid progressors. Methods: We included HIV-1 seroconverters achieving viral suppression within 6 months of cART. Rapid progressors were individuals experiencing at least one CD4+ less than 200 cells/µl within 12 months of seroconverters before cART. We used piecewise linear mixed models and logistic regression for optimal restoration. Results: Of 4024 individuals, 294 (7.3%) were classified as rapid progressors. At the same CD4+ T-cell count at cART start (baseline), rapid progressors experienced faster CD4+ T-cell increases than nonrapid progressors in first month [difference (95% confidence interval) in mean increase/month (square root scale): 1.82 (1.61; 2.04)], which reversed to slightly slower increases in months 1–18 [-0.05 (-0.06; -0.03)] and no significant differences in 18–60 months [-0.003 (-0.01; 0.01)]. Percentage achieving optimal restoration was significantly lower for rapid progressors than nonrapid progressors at months 12 (29.2 vs. 62.5%) and 36 (47.1 vs. 72.4%) but not at month 60 (70.4 vs. 71.8%). These differences disappeared after adjusting for baseline CD4+ T-cell count: odds ratio (95% confidence interval) 0.86 (0.61; 1.20), 0.90 (0.38; 2.17) and 1.56 (0.55; 4.46) at months 12, 36 and 60, respectively. Conclusion: Among people on suppressive antiretroviral therapy, rapid progressors experience faster initial increases of CD4+ T-cell counts than nonrapid progressors, but are less likely to achieve optimal restoration during the first 36 months after cART, mainly because of lower CD4+ T-cell counts at cART initiation