Fourteen vaginal bacterial species and the presence of a protein that promotes inflammation were associated with increased odds of HIV acquisition in a study of more than 500 cisgender women in African countries with high HIV incidence. The study was the largest to date to prospectively analyze the relationship between both the vaginal microbiome and vaginal tissue inflammation and the likelihood of acquiring HIV among cisgender women in this population. The NIAID-sponsored research was published in The Journal of Infectious Diseases.

Research is limited regarding the potential impacts of vaginal bacteria and inflammatory markers on HIV acquisition. Only one previous study has characterized both factors in women before they had HIV to investigate their odds of acquiring the virus, but the number of HIV acquisition events in that study was low, potentially limiting their ability to detect associations.

To increase understanding of these issues, researchers analyzed vaginal swab samples from 586 cisgender women participating a large biomedical HIV prevention clinical trial in South Africa, Uganda and Zimbabwe, and compared the bacterial and inflammatory profiles of samples from 150 participants who acquired HIV during the study with the samples of 436 participants who did not. The team identified 14 bacterial species associated with HIV acquisition and noted that participants whose samples contained most or all of those bacteria had the highest odds of acquiring HIV, while the presence of none or few of the identified bacteria was associated with the lowest odds of HIV acquisition. They similarly identified six inflammatory cytokines and chemokines—proteins that communicate with other cells to prompt the body to fight infections through inflammatory processes—associated with HIV acquisition, and identified the highest odds of HIV acquisition in participants whose samples contained all six of those proteins. Furthermore, they identified a single chemokine called interferon gamma-induced protein 10 associated with the highest odds of HIV acquisition out of the six.

These results suggest that strategies to reduce concentrations of the 14 identified bacterial species and inflammatory proteins could help prevent HIV acquisition, according to the authors. They also recommended that additional studies be conducted to understand the mechanisms by which these factors contribute to biological susceptibility to HIV.

Reference: Srinivasan, S et al. Vaginal Bacteria and Proinflammatory Host Immune Mediators as Biomarkers of HIV Acquisition 3 Risk among African Women. Journal of Infectious Diseases. DOI 10.1093/infdis/jiae406 (2024).

This blog is the second in a series about the future of NIAID's HIV clinical research enterprise. For more information, please visit the HIV Clinical Research Enterprise page.

The impact of clinical research is often measured by its outcomes. From trials that provide groundbreaking evidence of efficacy to those stopped early for futility, the end results of clinical trials shape practice and future research priorities. However, years of effort from scientists, study teams and study participants while a trial is underway are sometimes overshadowed by final study outcomes. In this regard, trial implementation requires clinical research sites’ operational excellence for the duration of a study. Access to relevant populations depends on the location of each clinical research site as well as investigators' and clinical care providers’ engagement with the local community and understanding of their needs and preferences. A high-functioning clinical research site anchored in the communities it works in and comprised of cohesive, well-integrated components is essential to producing high-quality outputs. 

Currently, NIAID supports four research networks as part of its HIV clinical research enterprise. The networks are made up of more than 100 clinical research sites, each with local experts, robust research infrastructure, and well-trained, cross-functional staff who maintain standardized procedures and quality controls aligned with their network.

Every seven years, NIAID engages research partners, community representatives, and other public health stakeholders in a multidisciplinary evaluation of network progress toward short- and long-term scientific goals. This process takes account of knowledge gained since the networks were last funded and identifies essential course corrections based on the latest scientific and public health evidence. Subsequent NIAID HIV research investments build on the conclusions of these discussions. This process includes examining the networks’ infrastructure model, which the Institute updates and refines to stay aligned with its scientific priorities. 

The HIV clinical trials network sites have made tremendous contributions to NIH’s scientific priorities by offering direct access to and consultation with populations most affected by HIV globally, and by delivering high-quality clinical research with strong connections to trusted community outreach platforms. Their approach to community engagement anchors clinical research sites beyond the scope of any individual study, and when possible, aligns scientific questions and study protocols based on local context. 

Since the start of the 2020 research network grant cycle, HIV clinical research sites have enrolled about 93,000 participants across 78 clinical trials in 25 countries. The networks were able to quickly pivot to support NIAID’s emerging infectious disease priority areas, including COVID-19 and mpox. Of the 93,000 participants since 2020, approximately 78,000 were enrolled into COVID-19 clinical trials sponsored by NIAID’s Division of AIDS. 

Clinical trials sites currently operate with a hub-and-spoke model, with each hub providing centralized support to their linked clinical research sites. This model leverages shared resources where possible and practical, and ensures robust oversight to promote high-quality clinical trial operations. Hubs provide infrastructure and services including laboratory, pharmacy, regulatory, data management, and training to support execution of NIAID-sponsored clinical research. 

Future networks will need to maintain core strengths of current models while expanding capacity in areas vital to further scientific progress. These include operations that inform pandemic responses and extending our reach within communities impacted by HIV, including populations historically underrepresented in clinical research. Additionally, there may be opportunities for clinical research sites and other partners to conduct implementation science research based on their capacity and access to relevant populations in the context of specific scientific questions. 

Make seamless progress on established and emerging scientific priorities

Our goals include maintaining the strength and flexibility of our current network model and infrastructure to support established scientific priorities that improve the practice of medicine, including high-impact registrational trials to identify new biomedical interventions and support changes to product labelling. The networks also must remain capable of directing operations to generate evidence on interventions for pandemic responses. 

Engage underserved populations for more representative studies 

Building on its current reach, NIAID and its partners have identified opportunities to expand or strengthen our connections to medically underserved populations affected by HIV, and to increase representation of geographic areas with limited access to current clinical trials sites. We also are seeking clinical research sites with longstanding community relationships and experience conducting randomized clinical trials that include Black gay, bisexual, and other men who have sex with men, transgender people, people who sell sex, people who use drugs, and adolescent girls and young women, as well as populations in African countries with a high HIV prevalence. 

Integrate implementation science within clinical research practice

Implementation science is the scientific study of methods and strategies that facilitate the uptake of evidence-based practice and research into regular use by practitioners and policymakers. As biomedical HIV prevention, treatment, and diagnostic options expand, our scientific questions must expand to address not only whether an intervention works, but how it can be delivered to offer health care choices that people need, want and are able to use. This expanded scientific scope calls for research sites to have a diverse reach and skill sets, including experience and capacity for conducting implementation science research and fostering and maintaining partnerships with organizations that conduct implementation science research on key topics and interventions on which implementers seek stronger evidence.

The research community plays an essential role in shaping NIAID’s scientific direction and research enterprise operations. We want to hear from you. Please share your questions and comments at NextNIAIDHIVNetworks@mail.nih.gov.

About NIAID’s HIV Clinical Trials Networks

The clinical trials networks are supported through grants from NIAID, with co-funding from and scientific partnerships with NIH’s National Institute of Mental Health, National Institute on Drug Abuse, National Institute on Aging, and other NIH institutes and centers. There are four networks—Advancing Clinical Therapeutics Globally for HIV/AIDS and Other Infections, the HIV Vaccine Trials Network, the HIV Prevention Trials Network, and the International Maternal Pediatric Adolescent AIDS Clinical Trials Network.

This blog is the first in a series about the future of NIAID's HIV clinical research enterprise. For more information, please visit the HIV Clinical Research Enterprise page.

NIAID supports four research networks as part of its HIV clinical research enterprise. Every seven years, the Institute engages research partners, community representatives, and other public health stakeholders in a multidisciplinary evaluation of network progress toward short- and long-term scientific goals. This process takes account of knowledge gained since the networks were last funded and identifies essential course corrections based on the latest scientific and public health evidence. Subsequent NIAID HIV research investments build on the conclusions of these discussions.

Pregnancy, childbirth and the postnatal period are a key focus of NIAID HIV research and call for measures to support the health of people who could become pregnant as well as their infants. Biological changes and social dynamics such as gender inequality, intimate partner violence, and discrimination can increase the likelihood of HIV acquisition during all natal stages. Of note, breastfeeding/chestfeeding is emerging as the predominant mode of vertical HIV transmission. NIAID is committed to optimizing HIV treatment and prevention options for people who might become pregnant, people who are pregnant and lactating, newborns, and young children who are still nursing or are living with HIV. Our goals are to offer safe, effective, acceptable, and accessible tools that provide evidence-based HIV prevention choices throughout the period of reproductive potential; prevent vertical HIV transmission to infants; and enable infants born with HIV to experience long periods of HIV remission or complete HIV clearance. We think these goals can be reached with discovery and development studies to advance biomedical interventions, and implementation science to rapidly introduce state-of-the-art interventions where they are needed most urgently.

In the current evaluation of our clinical trials networks, NIAID and other stakeholders are assessing novel interventions to interrupt the unacceptably high rate of new pediatric HIV diagnoses that persist in high burden countries. Recent research is rapidly expanding the evidence base for treatment for children and pregnant people with HIV, as well as biomedical prevention tools for pregnant people and people of reproductive potential who stand to benefit from their use. Some key advances include: 

• Expanded evidence to support a cascade of multiple regulatory approvals making new therapeutic agents available to the youngest children with HIV;
• Demonstrated safety of prevention products and antiretroviral therapy (ART) throughout pregnancy, including long-acting cabotegravir for HIV pre-exposure prophylaxis (PrEP); the controlled-release vaginal ring for HIV PrEP; and integrase strand transfer inhibitor-based ART for viral suppression in people with HIV; and
• Rigorous examination of the potential of treatment initiation within hours of birth to enable ART-free HIV remission in children in a research setting.

Together, these advances open doors to improved tools for HIV prevention and treatment and help define remaining evidence gaps and research needs.

Biomedical research to accelerate evidence responsive to pediatric and perinatal needs 

As noted above, a NIAID-sponsored clinical trial led by the International Maternal Pediatric Adolescent AIDS Clinical Trials Network (IMPAACT), called IMPAACT P1115, found that four children surpassed a year of HIV remission after pausing ART. The protocol remains active with subsequent iterations of the trial in children receiving more advanced ART regimens and novel broadly neutralizing antibody-based therapy. Further research is planned to identify biomarkers to predict the likelihood of HIV remission or rebound following ART interruption. Additional studies also are needed to better understand the mechanisms by which neonatal immunity and very early ART initiation limited the formation of latent HIV reservoirs to drive the original P1115 results.

Additional research priorities include developing early infant HIV testing assays that can promptly detect vertical HIV acquisition through breastfeeding/chestfeeding; wider examination of the safety and efficacy of presumptive ART pending an HIV diagnosis; administration of very early neonatal and pediatric formulations of the latest and future generations of long-acting ARVs for prevention and treatment and antibody-based therapy; and optimization of long-acting HIV treatment regimens to support health through periods of reproductive potential, pregnancy, and lactation.    

Implementation science to strengthen delivery 

Improving HIV prevention and care through reproductive years and intense early-life HIV intervention for infants will require an unprecedented level of reproductive health, prenatal, postnatal and pediatric HIV service integration. Several key clinical and operational questions warrant investigation through implementation science. The first is assuring availability of acceptable HIV testing modalities pre-conception, as well as universal HIV testing as part of routine obstetric care, and then supporting access to a person’s preferred PrEP method or ART based on HIV status. For infants whose birthing parent has HIV, we need evidence-based models for offering very early point-of-care infant HIV diagnosis and treatment, including presumptive ART for infants exposed to HIV in utero pending confirmatory testing. We also need to understand how to better support continued engagement in care to maintain viral suppression for childbearing people with HIV through the end of the lactating period and life course. We will provide special consideration for the preferences of adolescent and young adult cisgender women who are disproportionately affected by HIV in high burden settings globally. Defining local and contextually appropriate adaptations of successful models will be paramount for successful uptake. 

The research community plays an essential role in shaping NIAID’s scientific direction and research enterprise operations. We want to hear from you. Please share your questions and comments at NextNIAIDHIVNetworks@mail.nih.gov.

About NIAID Clinical Trials Networks and Pediatric HIV

The IMPAACT Network examines prevention and treatment interventions for HIV, HIV-associated complications, and related pathogens in infants, children, and adolescents, and during pregnancy and postpartum periods. The Network is supported through grants from NIAID, with co-funding and scientific partnership from the NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development and the NIH National Institute of Mental Health. Three other networks—the HIV Vaccine Trials Network, HIV Prevention Trials Network, and Advancing Clinical Therapeutics Globally for HIV/AIDS and Other Infections—generate complementary evidence and provide research infrastructure where needed when rapidly evolving prevention and treatment science has implications for IMPAACT priority populations. 

Editorial note: NIAID encourages the use of inclusive language in all communications. The terms related to lactation and pregnancy in this blog reflect the diverse gender identities and experiences of all people who stand to benefit from HIV prevention and cure research. For more information on inclusive language related to pregnancy and family, please visit the NIAID HIV Language Guide.  

The immune system senses and responds to changes in physiologic health, and a new tool called the immune health metric (IHM) can measure and even predict some of these changes, an NIAID study has found. If doctors could use the IHM to detect health problems long before symptoms appear, they could potentially act early to prevent disease, the investigators suggest. Their findings are published in the journal Nature Medicine. 

The researchers developed the IHM starting with extensive analyses of biological samples from nearly 230 people who have one of 22 rare, severe immune disorders caused by a mutation in just one gene. The scientists also included samples from 42 healthy people matched to the others by age and sex. The analyses involved many elements, including gene transcripts in immune cells, blood-based proteins, and the frequency of various blood cells, all related to the immune system. The initial goal was to learn if there were immune-system similarities among people with the diverse array of diseases.

To the researchers’ surprise, the disparate diseases had many similar features when viewed through the lens of the immune system as a whole, rather than only the mutated gene and its effects. The primary source of immune variation came from aspects of the individual, irrespective of their disease or the medication they were taking. 

To explore this observation further, the scientists fed their gene-transcript and blood-based protein data into artificial intelligence (AI) tools. The first tool assessed differences among the people in the study without knowing their disease or symptoms. This analysis yielded a numeric measurement called jPC1 that was based on a specific combination of key gene transcripts and proteins. jPC1 correlated negatively with inflammation and related markers, and positively with parameters not linked to inflammation. This suggested that jPC1 could be used to measure immune health. Further supporting this finding, the group of healthy participants had a significantly higher mean jPC1 score than people grouped by severe immune disorder. 

The second AI tool the researchers tested is a machine-learning model that they taught to distinguish between healthy people and those with severe immune disorders. The investigators did this using the gene transcripts, blood-based proteins, and blood cells from the original biological samples. The scientists used their model to compute the probability that a person belonged to the immunologically healthy group. Each person received a score based on that probability. The researchers called this scoring system the immune health metric, or IHM. The IHM scores correlated highly with the jPC1 scores, suggesting that the gene transcripts and proteins key to jPC1 drive immune health differences among individuals.

When the scientists applied the IHM to the healthy people in their study and data from an independent study of healthy aging conducted by NIH’s National Institute on Aging, the one variable the metric correlated with was age. There was an inverse relationship between IHM score and age, with ages ranging from 22 to 93. This indicated that aging, like disease, distances people from optimal immune health. 

The authors validated the IHM by showing it could reflect immune health status and treatment outcomes and even predict some health outcomes when applied to gene transcript data, blood-based protein data, or both from studies previously conducted by other scientists. For instance, IHM and jPC1 scores accurately distinguished people with common autoimmune and inflammatory diseases from healthy people. IHM scores also reflected variability in disease activity among people with lupus, an autoimmune disease, during periods with symptoms of differing severity and periods without symptoms. Among people with rheumatoid arthritis, IHM scores reflected differences in the immune health of people whose symptoms responded to treatment compared to those whose symptoms did not. In vaccine studies and a heart failure study, people with higher baseline IHM scores had better antibody responses to vaccines and better future heart health than people with lower baseline scores. Finally, there was an inverse relationship between IHM score and body-mass index (BMI) in a study of sedentary adults, even after controlling for age, sex, race, and levels of C-reactive protein, which the liver releases in response to inflammation. 

While there are many tools available to measure physiologic and organ-system function and health, few tools measure immune-system health. The IHM could help fill this gap. The investigators hope that clinicians will one day be able to use the predictive capacity of the IHM to detect diseases early enough for preventive medicine to halt disease progression and preserve health.

John S. Tsang, Ph.D., and Rachel Sparks, M.D., M.P.H., led the study. Dr. Tsang was co-director of the NIH Center for Human Immunology at NIAID and chief of the Multiscale Systems Biology Section in the NIAID Laboratory of Immune System Biology when most of the research was conducted. He is now the founding director of the Yale Center for Systems and Engineering Immunology, a professor of immunobiology and biomedical engineering at Yale University, and an adjunct investigator in the NIAID Laboratory of Immune System Biology. 

Dr. Sparks was an assistant clinical investigator in the NIAID Laboratory of Immune System Biology and an attending physician at the NIH Clinical Center when she conducted the research. She is now an experimental medicine physician at Astra Zeneca in Gaithersburg, Maryland, and a special volunteer in the NIAID Laboratory of Immune System Biology. 

Reference: R Sparks et al. A unified metric of human immune health. Nature Medicine DOI: 10.1038/s41591-024-03092-6 (2024).     

Malaria, one of the deadliest infectious diseases on the planet, has had a profound impact on humanity throughout history. This disease has even left its mark in our DNA: Many scientists believe it has had a strong selective pressure on the human genome over time. Because malaria is often fatal in children, babies born with some degree of resistance to the parasite that causes malaria have a better likelihood of growing up and passing those traits along to their own children. Unfortunately, some of these traits may come at a price: For more than 50 years, scientists have documented that malaria infection is associated with high levels of autoantibodies—antibodies that recognize and attack the person’s own tissues and are associated with autoimmune disorders.

To investigate the link between autoantibodies and malaria immunity, NIAID researchers, along with their colleagues, have studied the molecular mechanisms of these malaria defense systems. Their findings, recently published in Immunity, reveal the associations between malaria, human resistance to it, and autoantibodies that are linked to certain autoimmune disorders—specifically, systemic lupus erythematosus (SLE).

The researchers began by examining a collection of blood samples collected during a longitudinal study of 602 people, aged three months to 25 years, in the West African country of Mali. Malaria transmission is highly seasonal in Mali: the parasite which causes malaria, Plasmodium falciparum, is transmitted by mosquitoes, which need certain conditions to reproduce. During the dry season, which ends in May, malaria transmission rates are low. The researchers tested for autoantibodies in blood samples that were collected in May and then linked this with whether the participant had symptomatic malaria that needed treatment during the ensuing malaria season.

Participants who had very high levels of autoantibodies had a 41 percent lower risk of getting sick with malaria than people who had low levels of autoantibodies. To investigate how autoantibodies might protect from malaria, the researchers took blood samples with high levels of autoantibodies and isolated the autoantibodies. They then exposed malaria parasites to the autoantibodies in the laboratory and found that parasite growth was inhibited. The autoantibodies bound to proteins that the parasite uses to invade human red blood cells. The researchers believe that something similar may have happened to the participants of this study—their autoantibodies reduced the parasite’s ability to invade and grow in their blood cells, increasing their chances of remaining free of malaria symptoms.

Although this adaptation seems beneficial, it may come with a catch. Very similar autoantibodies can be found in the blood of people with SLE. This chronic autoimmune disorder can affect almost any organ system, but it often manifests as a rash, joint pain, and persistent fatigue. In its worst forms, it can be debilitating. While the causes of SLE are still unknown, it does appear to have a genetic component—for example, in the U.S., SLE is more common in some ethnic groups than others, including people with African ancestry. However, for unclear reasons, SLE and other autoimmune disorders are less common in Africa, suggesting that other factors alter the immune system to decrease the risk of autoimmune disorders there. Participants in the Mali study with high levels of autoantibodies had no symptoms of SLE or other autoimmune disorders.

When the researchers tested autoantibodies from people in the United States with SLE, they reacted to malaria parasites similar to the autoantibodies from the Malian study participants. These findings suggest that the overactive immune response that contributes to SLE may have evolved to defend against malaria. Even though many people with SLE today will never encounter a malaria-carrying mosquito, they still produce the antibodies that may have helped their ancestors survive malaria.

Reference:

Hagadorn, K et al. Autoantibodies inhibit Plasmodium falciparum growth and are associated with protection from clinical malaria. Immunity. DOI: https://doi.org/10.1016/j.immuni.2024.05.024 (2024)