Towards personalized medicine in maternal and child health: integrating biologic and social determinants

Solving the Puzzle of Preterm Birth

Solving the puzzle of preterm birth has been challenging and will require novel integrative solutions as preterm birth likely arises from many etiologies. It has been demonstrated that many sociodemographic and psychological determinants of preterm birth relate to its complex biology. It is this understanding that has enabled the development of a novel preventative strategy, which integrates the omics profile (genome, epigenome, transcriptome, proteome, metabolome, microbiome) with sociodemographic, environmental, and psychological determinants of individual pregnant people to solve the puzzle of preterm birth.

Computational Approaches for Predicting Preterm Birth and Newborn Outcomes

Preterm birth (PTB) and its associated morbidities are a leading cause of infant mortality and morbidity. Accurate predictive models and a better biological understanding of PTB-associated morbidities are critical in reducing their adverse effects. Increasing availability of multimodal high-dimensional data sets with concurrent advances in artificial intelligence (AI) have created a rich opportunity to gain novel insights into PTB, a clinically complex and multifactorial disease. Here, the authors review the use of AI to analyze 3 modes of data: electronic health records, biological omics, and social determinants of health metrics.

Promoting advanced medical services in the framework of 3PM-a proof-of-concept by the "Centro" Region of Portugal

Multidisciplinary team from three universities based in the "Centro" Region of Portugal developed diverse approaches as parts of a project dedicated to enhancing and expanding Predictive, Preventive, and Personalized Medicine (3PM) in the Region. In a sense, outcomes acted as a proof-of-concept, in that they demonstrated the feasibility, but also the relevance of the approaches. The accomplishments comprise defining a new regional strategy for implementing 3PM within the Region, training of human resources in genomic sequencing, and generating good practices handbooks dedicated to diagnostic testing via next-generation sequencing, to legal and ethical concerns, and to knowledge transfer and entrepreneurship, aimed at increasing literacy on 3PM approaches. Further approaches also included support for entrepreneurship development and start-ups, and diverse and relevant initiatives aimed at increasing literacy relevant to 3PM. Efforts to enhance literacy encompassed citizens across the board, from patients and high school students to health professionals and health students. This focus on empowerment through literacy involved a variety of initiatives, including the creation of an illustrated book on genomics and the production of two theater plays centered on genetics. Additionally, authors stressed that genomic tools are relevant, but they are not the only resources 3PM is based on. Thus, they defend that other initiatives intended to enable citizens to take 3PM should include multi-omics and, having in mind the socio-economic burden of chronic diseases, suboptimal health status approaches in the 3PM framework should also be considered, in order to anticipate medical intervention in the subclinical phase.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00353-9.

Unraveling the Role of Maternal Serum Ferritin Levels in Preterm Delivery: A Comprehensive Review

Preterm delivery remains a critical global health concern, with numerous adverse consequences for both neonate and healthcare systems. Understanding the relationship between maternal ferritin levels, as a marker of iron status, and the risk of preterm birth is the focal point of this comprehensive review. We provide insights into the multifaceted nature of this connection, highlighting factors that influence maternal ferritin levels, including dietary intake, genetic and physiological variations, comorbidities, and iron supplementation. While evidence suggests an association between low maternal ferritin levels and preterm birth, causality remains elusive, necessitating further research with robust study designs. The potential mechanisms linking maternal iron status to preterm birth, such as inflammation, infection, and oxidative stress, are explored, underscoring the need for in-depth investigations. This comprehensive review emphasizes the clinical importance of assessing and monitoring maternal ferritin levels in prenatal care and advocates for public health initiatives to raise awareness and provide targeted interventions, particularly in high-risk populations. As we strive to address these unanswered questions and embark on innovative research directions, the aim is to ultimately enhance our understanding of the complex relationship between maternal iron status and preterm birth, leading to improved maternal and child health outcomes.

Associations Between Direct and Indirect Forms of Racism Exposure and Stress-Induced Inflammatory Response and Health in Pregnancy

Theory and research suggest chronic direct and indirect exposures to racism impact health, and stress-responsive inflammation may play a role in these paths. This study examines links between forms of racism-related stress, salivary markers of inflammation during acute psychosocial stress, and perinatal mental and physical health in a racially heterogenous sample. Pregnant people (n = 108, 27% non-white) self-reported personal and vicarious exposure to racism (racial microaggressions, online racism, overt racial/ethnic discrimination) and racial collective self-esteem, as well as affective symptoms and general physical health. Five saliva samples collected before and after the Trier Social Stress Test were assayed for pro-inflammatory cytokines and C-reactive protein. Results revealed associations between racism-related stress and greater inflammatory reactivity/delayed recovery to acute stress, between racial collective self-esteem and lower levels of inflammation, and between profiles of inflammatory responses to stress and mental and physical symptoms. We discuss implications for understanding perinatal health disparities.

Noninvasive Prenatal Testing Using Circulating DNA and RNA: Advances, Challenges, and Possibilities

Prenatal screening using sequencing of circulating cell-free DNA has transformed obstetric care over the past decade and significantly reduced the number of invasive diagnostic procedures like amniocentesis for genetic disorders. Nonetheless, emergency care remains the only option for complications like preeclampsia and preterm birth, two of the most prevalent obstetrical syndromes. Advances in noninvasive prenatal testing expand the scope of precision medicine in obstetric care. In this review, we discuss advances, challenges, and possibilities toward the goal of providing proactive, personalized prenatal care. The highlighted advances focus mainly on cell-free nucleic acids; however, we also review research that uses signals from metabolomics, proteomics, intact cells, and the microbiome. We discuss ethical challenges in providing care. Finally, we look to future possibilities, including redefining disease taxonomy and moving from biomarker correlation to biological causation.

Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries

Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate proteomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.

Maternal factors during pregnancy influencing maternal, fetal, and childhood outcomes

Enhancing pregnancy health is known to improve the mother's and offspring's life-long well-being. The maternal environment, encompassing genetic factors, impacts of social determinants, the nutritional/metabolic milieu, and infections and inflammation, have immediate consequences for the in utero development of the fetus and long-term programming into childhood and adulthood. Moreover, adverse pregnancy outcomes such as preterm birth or preeclampsia, often attributed to the maternal environmental factors listed above, have been associated with poor maternal cardiometabolic health after pregnancy. In this BMC Medicine article collection, we explore a broad spectrum of maternal characteristics across pregnancy and postnatal phenotypes, anticipating substantial cross-fertilization of new understanding and shared mechanisms around diverse outcomes. Advances in the ability to leverage 'omics across different platforms (genome, transcriptome, proteome, metabolome, microbiome, lipidome), large high-dimensional population databases, and unique cohorts are generating exciting new insights: The first articles in this collection highlight the role of placental biomarkers of preterm birth, metabolic influences on fetal and childhood growth, and the impact of common pre-existing maternal disorders, obesity and smoking on pregnancy outcomes, and the child's health. As the collection grows, we look forward to seeing the connections emerge across maternal, fetal, and childhood outcomes that will foster new insights and preventative strategies for women.

Single center blind testing of a US multi-center validated diagnostic algorithm for Kawasaki disease in Taiwan

Background

Kawasaki disease (KD) is the leading cause of acquired heart disease in children. The major challenge in KD diagnosis is that it shares clinical signs with other childhood febrile control (FC) subjects. We sought to determine if our algorithmic approach applied to a Taiwan cohort.

Methods

A single center (Chang Gung Memorial Hospital in Taiwan) cohort of patients suspected with acute KD were prospectively enrolled by local KD specialists for KD analysis. Our previously single-center developed computer-based two-step algorithm was further tested by a five-center validation in US. This first blinded multi-center trial validated our approach, with sufficient sensitivity and positive predictive value, to identify most patients with KD diagnosed at centers across the US. This study involved 418 KDs and 259 FCs from the Chang Gung Memorial Hospital in Taiwan.

Findings

Our diagnostic algorithm retained sensitivity (379 of 418; 90.7%), specificity (223 of 259; 86.1%), PPV (379 of 409; 92.7%), and NPV (223 of 247; 90.3%) comparable to previous US 2016 single center and US 2020 fiver center results. Only 4.7% (15 of 418) of KD and 2.3% (6 of 259) of FC patients were identified as indeterminate. The algorithm identified 18 of 50 (36%) KD patients who presented 2 or 3 principal criteria. Of 418 KD patients, 157 were infants younger than one year and 89.2% (140 of 157) were classified correctly. Of the 44 patients with KD who had coronary artery abnormalities, our diagnostic algorithm correctly identified 43 (97.7%) including all patients with dilated coronary artery but one who found to resolve in 8 weeks.

Interpretation

This work demonstrates the applicability of our algorithmic approach and diagnostic portability in Taiwan.

Cohort profile: Colombian Cohort for the Early Prediction of Preterm Birth (COLPRET): early prediction of preterm birth based on personal medical history, clinical characteristics, vaginal microbiome, biophysical characteristics of the cervix and maternal serum biochemical markers

PURPOSE

Preterm birth (PTB) is a public health issue. Interventions to prolong the length of gestation have not achieved the expected results, as the selection of population at risk of PTB is still a challenge. Cervical length (CL) is the most accepted biomarker, however in the best scenario the CL identifies half of the patients. It is unlikely that a single measure identifies all pregnant women who will deliver before 37 weeks of gestation, considering the multiple pathways theory. We planned this cohort to study the link between the vaginal microbiome, the proteome, metabolome candidates, characteristics of the cervix and the PTB.

PARTICIPANTS

Pregnant women in the first trimester of a singleton pregnancy are invited to participate in the study. We are collecting biological samples, including vaginal fluid and blood from every patient, also performing ultrasound measurement that includes Consistency Cervical Index (CCI) and CL. The main outcome is the delivery of a neonate before 37 weeks of gestation.

FINDINGS TO DATE

We have recruited 244 pregnant women. They all have measurements of the CL and CCI. A vaginal sample for microbiome analysis has been collected in the 244 patients. Most of them agreed to blood collection, 216 (89%). By August 2021, 100 participants had already delivered. Eleven participants (11 %) had a spontaneous PTB.

FUTURE PLANS

A reference value chart for the first trimester CCI will be created. We will gather information regarding the feasibility, reproducibility and limitations of CCI. Proteomic and metabolomic analyses will be done to identify the best candidates, and we will validate their use as predictors. Finally, we plan to integrate clinical data, ultrasound measurements and biological profiles into an algorithm to obtain a multidimensional biomarker to identify the individual risk for PTB.

Stress and Its Consequences-Biological Strain

Understanding the role of stress in pregnancy and its consequences is important, particularly given documented associations between maternal stress and preterm birth and other pathological outcomes. Physical and psychological stressors can elicit the same biological responses, known as biological strain. Chronic stressors, like poverty and racism (race-based discriminatory treatment), may create a legacy or trajectory of biological strain that no amount of coping can relieve in the absence of larger-scale socio-behavioral or societal changes. An integrative approach that takes into consideration simultaneously social and biological determinants of stress may provide the best insights into the risk of preterm birth. The most successful computational approaches and the most predictive machine-learning models are likely to be those that combine information about the stressors and the biological strain (for example, as measured by different omics) experienced during pregnancy.

Data-Driven Modeling of Pregnancy-Related Complications

A healthy pregnancy depends on complex interrelated biological adaptations involving placentation, maternal immune responses, and hormonal homeostasis. Recent advances in high-throughput technologies have provided access to multiomics biological data that, combined with clinical and social data, can provide a deeper understanding of normal and abnormal pregnancies. Integration of these heterogeneous datasets using state-of-the-art machine-learning methods can enable the prediction of short- and long-term health trajectories for a mother and offspring and the development of treatments to prevent or minimize complications. We review advanced machine-learning methods that could: provide deeper biological insights into a pregnancy not yet unveiled by current methodologies; clarify the etiologies and heterogeneity of pathologies that affect a pregnancy; and suggest the best approaches to address disparities in outcomes affecting vulnerable populations.

Innate Immune Responses to Acute Viral Infection During Pregnancy

Immunological adaptations in pregnancy allow maternal tolerance of the semi-allogeneic fetus but also increase maternal susceptibility to infection. At implantation, the endometrial stroma, glands, arteries and immune cells undergo anatomical and functional transformation to create the decidua, the specialized secretory endometrium of pregnancy. The maternal decidua and the invading fetal trophoblast constitute a dynamic junction that facilitates a complex immunological dialogue between the two. The decidual and peripheral immune systems together assume a pivotal role in regulating the critical balance between tolerance and defense against infection. Throughout pregnancy, this equilibrium is repeatedly subjected to microbial challenge. Acute viral infection in pregnancy is associated with a wide spectrum of adverse consequences for both mother and fetus. Vertical transmission from mother to fetus can cause developmental anomalies, growth restriction, preterm birth and stillbirth, while the mother is predisposed to heightened morbidity and maternal death. A rapid, effective response to invasive pathogens is therefore essential in order to avoid overwhelming maternal infection and consequent fetal compromise. This sentinel response is mediated by the innate immune system: a heritable, highly evolutionarily conserved system comprising physical barriers, antimicrobial peptides (AMP) and a variety of immune cells—principally neutrophils, macrophages, dendritic cells, and natural killer cells—which express pattern-receptors that detect invariant molecular signatures unique to pathogenic micro-organisms. Recognition of these signatures during acute infection triggers signaling cascades that enhance antimicrobial properties such as phagocytosis, secretion of pro-inflammatory cytokines and activation of the complement system. As well as coordinating the initial immune response, macrophages and dendritic cells present microbial antigens to lymphocytes, initiating and influencing the development of specific, long-lasting adaptive immunity. Despite extensive progress in unraveling the immunological adaptations of pregnancy, pregnant women remain particularly susceptible to certain acute viral infections and continue to experience mortality rates equivalent to those observed in pandemics several decades ago. Here, we focus specifically on the pregnancy-induced vulnerabilities in innate immunity that contribute to the disproportionately high maternal mortality observed in the following acute viral infections: Lassa fever, Ebola virus disease (EVD), dengue fever, hepatitis E, influenza, and novel coronavirus infections.