The intellectual foundations of this shift reach back nearly two decades. The term exposome was coined to mirror the genome: if genetics describes the internal blueprint of disease risk, the exposome describes everything external that acts upon it. As the review recounts, the concept matured through landmark papers in epidemiology, including Christopher Wild’s influential 2012 articulation of the exposome’s path from concept to utility, and later work framing the exposome as the science of social-to-biological transitions. What has changed most dramatically, the authors emphasize, is not the idea but the feasibility. A decade ago, measuring even a handful of environmental exposures across thousands of children seemed daunting. Today, large-scale cohorts, wearable sensors, satellite data, and high-throughput chemistry have made a genuinely comprehensive accounting possible, and recent analyses estimate that unhealthy environments remain a major contributor to the global burden of disease.

Why children, specifically? The review is emphatic that pediatric populations are not simply small adults. Development unfolds through a sequence of critical windows, extending from preconception through fetal life, infancy, and childhood, during which tissues and organ systems are exquisitely sensitive to external signals. The historical record offers sobering proof of how consequential these windows can be. The review highlights the tragic case of diethylstilbestrol, a synthetic estrogen prescribed to pregnant women in the mid-twentieth century, whose effects rippled into the second and even third generations of exposed families. Modern research on endocrine-disrupting chemicals suggests that such developmental sensitivity is not an anomaly but a general principle: hormones, brain architecture, immune programming, and metabolism are all calibrated by environmental inputs during precisely the periods when measurement has historically been weakest.

Measuring that totality demands an equally diverse toolkit, and the review provides a detailed inventory of the current state of the art. Questionnaires and surveys remain indispensable for capturing behaviors, diets, and housing conditions that no sensor can detect, though they carry well-known limitations in recall and precision. Biomarkers offer a complementary window: chemicals and their metabolites measured in urine, blood, hair, saliva, and even meconium can integrate exposure over hours, weeks, or months. Innovative sampling strategies are extending this reach to the youngest children, including methods that collect infant and toddler urine using cotton pads and disposable diapers, and microsampling approaches that reduce the burden of repeated blood collection. Hair analysis can reveal exposure to tobacco smoke and metals over extended periods, while archived dried blood spots and even deciduous teeth are emerging as time capsules of past exposure, allowing researchers to reconstruct the chemical history of a childhood long after it has passed.

Beyond the body, the review catalogs the technologies now monitoring the environments children actually inhabit. Low-cost personal sensors can track particulate matter in real time as children move through streets, classrooms, and homes, revealing exposure patterns that fixed monitoring stations inevitably miss. Silicone wristbands, worn like a watch, passively absorb hundreds of chemicals from the surrounding air, providing an integrative record of personal chemical exposure that has been validated against urinary biomarkers for compounds such as phthalates. House dust, tap water, and hand wipes serve as sentinels for indoor contamination by flame retardants, endocrine-disrupting compounds, and heavy metals. Geospatial indicators, derived from satellite imagery and administrative databases, add the dimension of place, linking addresses to traffic density, green space, noise, temperature, and neighborhood deprivation. Longitudinal personal monitoring studies have shown just how dynamic an individual’s chemical environment can be, fluctuating dramatically from day to day in ways that a single snapshot could never reveal.

The analytical challenge, once all these data streams exist, is formidable. Children are exposed not to single agents but to complex mixtures, in which chemicals interact with physical stressors like heat and noise, with built-environment features, and with social conditions such as poverty and family stress. The review describes the statistical machinery being developed to cope with this high-dimensional reality: methods for examining hundreds of exposures simultaneously, for identifying exposure clusters that travel together, for weighting mixtures to determine which components drive harm, and for pinpointing critical windows when an exposure matters most. Simulation studies and exposome data challenge events have systematically compared these approaches, establishing best practices for a field that is, in effect, inventing its own statistics. Causal inference remains the hardest problem of all, since environmental exposures correlate with each other and with socioeconomic circumstances in ways that can easily masquerade as causation.

Multi-omics integration is the review’s most forward-looking theme. By layering genomics, epigenomics, transcriptomics, metabolomics, and even microbiome data onto exposure measurements, researchers can trace the molecular pathways through which environment becomes biology. The European HELIX project, one of the pioneering exposome cohorts, demonstrated that early-life exposures leave detectable multi-omic signatures in children, and follow-up analyses have linked these signatures to biological age markers and developmental outcomes. Other findings from the exposome literature illustrate the power of this approach: prenatal mercury exposure has been associated with heightened susceptibility to liver inflammation in childhood, maternal exposures have been tied to shifts in the infant gut microbiome, and family affluence has been connected to cortisol production and telomere length, a cellular marker of biological aging. These are not isolated curiosities; together they sketch the mechanisms by which the social and chemical worlds of early life are inscribed into physiology.

The scale of the enterprise now underway is genuinely global. The review surveys major birth cohorts on several continents, including the ECHO Program in the United States, the Japan Environment and Children’s Study, the GUSTO cohort in Singapore, the PIPA project in Rio de Janeiro, and the Drakenstein Child Health Study in South Africa, alongside European initiatives such as HELIX, ATHLETE, Equal-Life, and ENDOMIX. Harmonization efforts like HBM4EU have aligned human biomonitoring across multiple countries, producing comparable data on chemical exposure in children, teenagers, and adults. This convergence matters because it allows patterns observed in one population to be tested in another, strengthening the inference that an association reflects a real biological relationship rather than a local confound. It also creates the data infrastructure needed for the next frontier: predictive models that could estimate an individual child’s exposure profile and risk trajectory.

Perhaps the most striking message of the review is its insistence that exposome science is no longer merely descriptive. Intervention studies are beginning to close the loop between measurement and prevention. Randomized trials have tested housing interventions to reduce endocrine-disrupting chemical exposures in children, perinatal environmental health education programs aimed at lowering exposure to harmful compounds, and low-plastic diets shown to reduce urinary levels of phthalates and bisphenols. Research into personal care products has identified practical levers for decreasing chemical exposure in everyday life. These studies transform the exposome from an academic mapping exercise into a source of actionable advice, demonstrating that when exposures are accurately measured, they can also be meaningfully reduced, often with simple changes available to families and clinicians.

The review closes with a call that gives the exposome a distinctly clinical face: pediatricians, it argues, should stand at the center of translating this science into practice. Because so many environmental determinants of health act during early development, the pediatric visit represents a unique point of intervention, and the authors envision exposome-informed consultations in which modifiable environmental, biological, and social risks are identified and addressed before they compound. The remaining challenges are real, including the cost and complexity of exposure assessment, the need for better causal methods, and the difficulty of communicating mixture risks to families and regulators. But the trajectory is unmistakable. What began as a provocative analogy to the genome has matured into a rigorous, data-rich discipline with cohorts spanning the globe, molecular tools capable of reading environment in the body, and early evidence that its insights can change outcomes. For a generation of children growing up amid unprecedented chemical, climatic, and social change, the exposome offers something medicine has long lacked: a complete map of the terrain on which their health will be built.

Subject of Research: Comprehensive exposome approaches for assessing environmental exposures and their health effects in children

Article Title: Assessing environmental exposures in children: toward a comprehensive exposome approach

Article References: Portefaix, A., & Maitre, L. (2026). Assessing environmental exposures in children: toward a comprehensive exposome approach. Pediatric Research. https://doi.org/10.1038/s41390-026-05460-z

Image Credits: AI Generated

DOI: 10.1038/s41390-026-05460-z

Keywords: exposome, children's health, environmental exposures, pediatric research, biomarkers, multi-omics, birth cohorts, endocrine-disrupting chemicals, air pollution, exposure assessment, public health, critical windows of development

The new effort, known as the NorthMom Study, was described in a study protocol published in BMC Public Health. It is an observational, population-based cohort nested within NorthPop, designed to follow women from their pregnancies into the age at which routine breast cancer screening begins. Rather than waiting decades to count cancer diagnoses, the investigators are focusing on intermediate markers—most importantly mammographic breast density—that are strongly associated with future breast cancer risk and can be measured at scale through Sweden’s national screening program.

The scientific rationale rests on a concept that cancer biologists call windows of susceptibility. Breast tissue does not respond uniformly to environmental insults throughout a woman’s life; instead, there are discrete periods—prenatal development, puberty, pregnancy, and menopause—when the mammary gland is undergoing rapid structural and hormonal change and is correspondingly more vulnerable. During pregnancy in particular, breast tissue undergoes dramatic maturation driven by surges of hormones, making it sensitive to compounds that can interact with hormone receptors, including endocrine-disrupting chemicals. An exposure that perturbs these processes, the hypothesis goes, could trigger biological effects such as alterations in breast density, shortened breastfeeding duration, or persistent changes in gene expression and metabolism that mediate the path from exposure to eventual disease.

Breast density itself—the proportion of fibroglandular tissue within the breast—is one of the strongest known independent risk factors for breast cancer, and it also complicates screening by masking underlying tumors on mammograms. Density is shaped by hormonal, genetic, and environmental influences, yet surprisingly few studies have examined how environmental exposures, particularly those occurring during windows of susceptibility, relate to density measured later in life. NorthMom is explicitly designed to fill this gap by linking prospectively collected pregnancy exposures to density measurements taken when participants turn 40 and attend their first screening mammograms.

The exposure data available to the researchers are unusually rich. During pregnancy, NorthPop collected detailed questionnaire information on diet, physical activity, medication use, mental health, and home and work environments. For all participants, the cohort holds geospatial estimates of ambient air pollution, traffic noise, and residential access to green spaces. For subsets of women, levels of persistent organic pollutants were measured in plasma samples banked during pregnancy, and the team plans eventually to perform comprehensive chemical exposomics analyses on plasma from all enrolled women. Because these data were collected before any outcomes existed, the study avoids the recall bias that plagues much of environmental epidemiology.

Recruitment into NorthMom follows a straightforward protocol. Every woman enrolled in NorthPop is invited to participate in the year after her 40th birthday, provided she still lives in Västerbotten, has not withdrawn from the parent cohort, and is not currently pregnant. Those who agree visit the Clinical Research Center at the University Hospital of Umeå, where a nurse draws a venous blood sample that is separated into plasma, buffy coat, and erythrocyte fractions and stored at minus 80 degrees Celsius in the regional biobank. Participants also undergo dual-energy X-ray absorptiometry, or DXA, a scan that quantifies body fat percentage and distribution far more precisely than body mass index, and they complete a short questionnaire on reproductive history and hormone therapy or contraceptive use.

Breast density is assessed two ways. Screening mammograms obtained through Sweden’s national program are classified by a consultant breast radiologist using both the fourth and fifth editions of the Breast Imaging Reporting and Data System, and independently analyzed with LIBRA, an open-source software tool that produces automated measures of percent density and dense area in square centimeters. Using both subjective and automated methods allows the team to cross-validate the software and to express density as a continuous variable, which boosts statistical power. For women with multiple screening occasions, the study will also track how density changes over time using mixed-effects models, testing whether pregnancy exposures are associated not just with density at a single point but with the rate at which density evolves through the menopausal transition.

The statistical planning is already in place. Based on pilot data showing a standard deviation of roughly 19.7 percentage points for breast density, the investigators calculate that 1,049 women would give the study 80 percent power to detect a 1.7-percentage-point difference in density per one-standard-deviation increase in exposure, at a two-sided significance level of 0.05. Analyses will employ linear regression for continuous density, ordinal and logistic regression for BI-RADS categories, and repeated-measures models for longitudinal trajectories. Early recruitment figures show 36.6 percent of invited women enrolling—442 of 1,207 in the first year—and ongoing funding is expected to carry recruitment at least through 2028, by which time more than 3,000 NorthPop mothers will have turned 40 and around 1,000 participants should be enrolled.

The study’s design offers several distinctive strengths. DXA scans capture adiposity with a granularity that BMI cannot match, addressing a persistent weakness in breast cancer epidemiology where crude proxies often obscure the true role of body fat. The link to NorthPop means exposure data and biobanked pregnancy samples already exist, dramatically reducing costs and enabling biomarker analyses of the internal exposome—proteomic, metabolomic, and epigenetic signatures that may reveal how environmental chemicals leave durable biological footprints. Sweden’s comprehensive national registers, including those covering cancer diagnoses, prescribed drugs, causes of death, and family relationships, allow deep longitudinal follow-up, and linkage with the long-running Northern Sweden Health and Disease Study could eventually provide exposure and blood sample data spanning pregnancy, perimenopause, menopause, and beyond for a substantial share of participants.

The investigators are candid about limitations. The cohort’s ultimate size, likely around a thousand women, is too small to use breast cancer diagnoses themselves as a primary outcome. But because studies of environmental effects on breast cancer intermediates such as density are scarce, the researchers argue that this unusual setting is precisely what makes new discoveries possible, with density serving as a defensible surrogate for cancer-specific effects. If the hypothesis holds—that chemical and physical exposures during pregnancy leave measurable imprints on breast tissue decades later—NorthMom will have helped expose one of the most overlooked chapters in the environmental history of breast cancer, and it will have done so by following the mothers of a birth cohort every bit as carefully as their children.

Subject of Research: A population-based cohort study examining how environmental exposures during pregnancy affect breast cancer risk factors, particularly mammographic breast density, in women over 40

Article Title: The NorthMom study: population-based follow-up of women in a birth cohort to assess pregnancy exposures and effects on breast cancer risk factors

Article References: Fredriksson, A., Lundberg-Ulfsdotter, R., Vinnars, M.-T., Oudin, A., Van Guelpen, B., West, C. E., Domellöf, M., Wu, W. Y.-Y., Dembrower, K., & Harlid, S. (2026). The NorthMom study: population-based follow-up of women in a birth cohort to assess pregnancy exposures and effects on breast cancer risk factors. BMC Public Health, 26(1), Article 2670. https://doi.org/10.1186/s12889-026-29622-0

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29622-0

Keywords: breast cancer, breast density, pregnancy, environmental exposures, endocrine-disrupting chemicals, air pollution, birth cohort, mammography, epidemiology, exposome, women's health, PFAS

Sickle cell disease is a single-gene disorder that affects hemoglobin, the oxygen-carrying molecule in red blood cells. A single mutation causes hemoglobin molecules to polymerize under certain conditions, deforming red cells into rigid, crescent shapes that lodge in small blood vessels. The consequences are cascading: vaso-occlusion triggers episodes of excruciating pain, chronic hemolytic anemia, inflammation, and progressive damage to organs including the kidneys, lungs, brain, and spleen. The disease is among the costliest chronic conditions in medicine, measured in both direct health care expenditure and lost human potential, and it disproportionately affects people of African, Mediterranean, Middle Eastern, and South Asian ancestry. Yet for all its molecular simplicity—one gene, one known mutation—the disease behaves with bewildering variability. Some patients endure frequent crises and early organ failure while others, carrying the same genotype, live comparatively well for decades. The reason for this divergence has remained one of the field’s most stubborn mysteries.

The Mount Sinai team, led by principal investigator Sarah McCuskee, MD, Assistant Professor of Emergency Medicine and of Global Health and Health Systems Design, believes the answer may lie substantially outside the genome—in the “exposome,” the cumulative measure of every environmental exposure an individual encounters from moment to moment across a lifetime. “We have heard time and time again from our patients: their lives impact their disease, and vice versa,” Dr. McCuskee said in announcing the award. “But until now, how daily life impacts sickle cell disease hasn’t been studied very much. We are excited to partner with people living with sickle cell disease to understand this better, while applying rigorous scientific methods to make sure our conclusions are impactful.” Her framing captures the project’s central ambition: to treat patient experience not as anecdote but as a valid signal that can be rigorously quantified, measured, and validated.

The biological logic behind the hypothesis is grounded in what preliminary work has already hinted at. Neighborhood and personal exposures are known to activate inflammatory pathways, alter vascular tone, and shift metabolic states—all processes directly implicated in sickle cell pathogenesis. Chronic psychosocial stress elevates cortisol and sympathetic nervous system activity, which can promote vasoconstriction and heighten the likelihood of vaso-occlusive events. Elevated ambient temperature is suspected of influencing blood viscosity and dehydration status, both critical variables in a disease where red cells sickle more readily when blood flow slows or plasma volume falls. Airborne particulate matter, particularly fine particles smaller than 2.5 micrometers, known as PM2.5, penetrates deep into the lungs and drives systemic inflammation through oxidative stress, an especially concerning mechanism for patients whose vasculature is already prone to inflammatory damage. Poor access to nutritious food may compromise the antioxidant defenses and hydration status that help keep sickling episodes at bay. Substandard housing—with inadequate heating, cooling, ventilation, or pest exposure—compounds all of these risks simultaneously.

The new study is among the first prospective investigations of exposures in sickle cell disease ever undertaken, and its methodology reflects the sophistication that such a claim demands. The researchers will pursue two complementary strategies. The first links blood samples previously donated by people with sickle cell disease for research to geospatial data on the exposures those individuals experience, drawing on advanced satellite-based models. These models can estimate ambient concentrations of fine particulate matter, neighborhood-level temperatures, and other environmental variables at fine resolution, allowing investigators to connect each participant’s residential history with molecular readouts of their disease state. The second strategy moves into real time: participants will carry portable air-quality sensors that directly measure the particles they breathe, and they will report on diet and stress levels as they occur. These moment-to-moment exposure data will then be linked to measurements of the body’s energy metabolism and inflammatory markers, giving researchers a dynamic picture of how a specific exposure on a specific day translates into molecular changes in the blood.

This pairing of satellite modeling and personal sensing is methodologically significant. Satellite data offers population-scale coverage and historical depth, but it estimates exposure at the ambient level and can miss what individuals actually encounter indoors, in transit, or in microenvironments like subway platforms and workplaces. Portable sensors capture the true inhaled dose but are limited in duration and cohort size. By triangulating the two approaches and anchoring both to biochemical endpoints—energy metabolism and inflammation—the study can distinguish between exposures that merely correlate with disease activity and those that plausibly drive it. If, for example, a spike in personally measured PM2.5 is followed within days by a rise in inflammatory cytokines and markers of hemolysis, the causal chain becomes far harder to dismiss. That kind of evidence, replicated across participants and seasons, is what regulatory policy and clinical guidance ultimately require.

The collaborative architecture of the project is equally deliberate. The research will be conducted in partnership with the Human Immune Monitoring Center at Mount Sinai, which provides deep immunophenotyping capability; the Institute for Exposomic Research at the Icahn School of Medicine, one of the first institutions in the world organized specifically around exposomic science; and the Center for Sickle Cell Disease, which anchors the clinical and community dimensions of the work. Exposomics—the systematic study of non-genetic drivers of health—has gained momentum in cancer, cardiovascular disease, and neurology, but its application to a monogenic disease like sickle cell is comparatively novel and potentially transformative, because it addresses the variability that the gene itself cannot explain.

Community partnership is not an afterthought in this design but a stated structural principle. When the study concludes, the researchers intend to share results widely, including through publicly available maps of neighborhood exposures co-developed with the New York City sickle cell community. That commitment matters for a disease whose patients have historically faced well-documented barriers in health care—under-treatment of pain, delayed emergency care, and skepticism about the severity of their symptoms. By giving the community access to the same exposure data that researchers use, the project aims to convert an academic finding into an advocacy tool, one that residents, clinicians, and policymakers can use to argue for cooler housing, cleaner air, and better food environments in the neighborhoods where sickle cell patients live.

The translational endpoint is clinical. Dr. McCuskee and her colleagues plan to develop tools based on their findings that will help clinicians counsel patients concretely—not in vague exhortations to “stay healthy,” but with specific, evidence-based guidance about which environmental conditions appear to elevate risk for a given individual, and what mitigations may help. Beyond sickle cell disease, the investigators hope the methods themselves—linking personal sensing, geospatial modeling, and molecular biomarkers—could form a template for investigating other chronic and genetic illnesses in which outcomes vary inexplicably from patient to patient, including cystic fibrosis, certain autoimmune conditions, and cardiovascular disease.

The grant will be distributed over five years, a duration long enough to capture seasonal variation in temperature, air quality, and stress exposures, and to observe whether exposure-driven molecular changes translate into clinical events such as pain crises, emergency department visits, or hospitalizations. If the study delivers on its promise, it could mark a turning point in how medicine understands a disease long defined by its genetics. The mutation in the hemoglobin gene has been known since the middle of the twentieth century; the environmental and social conditions that determine how severely that mutation expresses itself have, by comparison, barely been examined. Mount Sinai’s new program sets out to close that gap, grounded in the conviction that where people live is not background noise to their biology but part of it—and that understanding the two together may finally explain why one gene can produce so many different lives.