Altered Maternal Antibody Profiles in Women With Human Immunodeficiency Virus Drive Changes in Transplacental Antibody Transfer

Abstract

Background HIV-exposed, uninfected (HEU) children have a higher risk of severe infection than HIV-unexposed children, though the causes are poorly understood. Emerging data point to altered antibody transfer in women with HIV (WHIV), however, specific perturbations and the influence of ART and viremia remain unclear. Methods We evaluated antigen-specific transplacental antibody transfer across 14 antigens in paired maternal and umbilical cord plasma from 352 Ugandan women; 176 were WHIV taking ART. We measured antigen-specific IgG subclass (IgG1, 2, 3, 4) levels and antibody Fcγ receptor (FcγRn, 2a, 2b, 3a, 3b) binding profiles. We used Partial Least Squares Discriminant Analysis to define antigen-specific transplacental antibody transfer features. Results Global antibody transfer patterns were similar by maternal HIV serostatus, pointing to effective placental function in WHIV on ART. However, HEU umbilical cord antibody profiles were altered, driven by perturbed maternal seroprofiles. WHIV and paired HIV-exposed umbilical cord plasma had higher levels of chronic herpesvirus antibodies (P<0.01 for EBV, HSV) and lower levels of classic vaccine-induced antibodies (P<0.01 for tetanus, polio, HiB), suggesting that umbilical cord antibody profile differences arise from imbalanced WHIV immunity. Multivariate regression analysis demonstrated abnormal WHIV antibody profiles were associated with HIV viremia, lower CD4 count and post-conception ART initiation (P=0.01). Conclusions Preserved placental antibody transfer and perturbed immune-dominance profiles in WHIV shift the balance of immunity delivered to neonates, pointing to HIV-associated changes in maternal antibody profiles as a key determinant of compromised neonatal immunity. Maternal vaccination interventions may promote transfer of relevant, effective antibodies to protect HEU children against early-life infections.

Quantitative mechanistic model reveals key determinants of placental IgG transfer and informs prenatal immunization strategies

“…Parameter estimation was performed using CaliPro as described elsewhere (32,33) (see Methods). With this optimized parameter set, the model recapitulated dynamics of both bulk and subclass-specific IgG transfer, predicting the IgG subclass transfer hierarchy most frequently reported in literature ( (11)(12)(13)32,(34)(35)(36).…”

Research news in clinical context

“…This study analysed antibodies to 14 antigens in paired maternal and umbilical cord samples from 352 Ugandan women, including 176 (50%) women living with HIV and receiving antiretroviral therapy (ART). 4 The ratio of umbilical to maternal antigenspecific IgG levels were similar regardless of HIV status, indicative of intact placental transfer function. However, individual antibodies showed significant differences: women with HIV had lower levels of antibodies to tetanus, Haemophilus influenzae type b and polio and higher levels of antibodies to herpesviruses.…”

“…HIV-negative infants exposed to HIV are at increased risk of severe infections, but the causes are not known. This study analysed antibodies to 14 antigens in paired maternal and umbilical cord samples from 352 Ugandan women, including 176 (50%) women living with HIV and receiving antiretroviral therapy (ART) 4. The ratio of umbilical to maternal antigen-specific IgG levels were similar regardless of HIV status, indicative of intact placental transfer function.…”

Distinct Type 1 Immune Networks Underlie the Severity of Restrictive Lung Disease after COVID-19

“…98 Supervised multivariate statistical models were built using a previously described analysis pipeline. 99 MATLAB computing environment (version R2022a, Mathworks, Natick, MA, USA) was used for multivariate analysis, and codes are available on GitHub (https://github.com/Dolatshahi-Lab/PLSR-DA; https://github.com/Dolatshahi-Lab/Elastic-Net-for-PLSR-DA). Feature Selection: A minimal set of measurements was selected using elastic net regularization, in order to down-select features and prevent overfitting 36,37 Elastic net was performed on each dataset individually to enable inclusion of as many samples as possible.…”