For 60 years, the Child Health and Development Studies (CHDS) has produced groundbreaking discoveries linking prenatal exposures to diseases like breast cancer and multigenerational obesity. Today, revolutionary AI and mass spectrometry advances have created an unprecedented opportunity: we can now digitize CHDS's irreplaceable three-generation biological archive and health outcomes into a real-time, globally accessible resource. This $51M initiative will accelerate preventative medicine and treatment research on a scale never before possible.
Sixty years of CHDS research have reshaped what we know about how prenatal exposures drive disease—but each breakthrough was built on one chemical, one disease, one painstaking lab study at a time. Full digitization would multiply these discoveries by orders of magnitude, creating three capabilities that do not yet exist in medicine.
From single-chemical proof to a whole-exposome prediction engine
CHDS has proven, one chemical at a time, that what a mother is exposed to during pregnancy predicts her child’s cancer risk decades later. Pesticide exposure in the womb triples breast cancer risk. A common anti-nausea drug triples colorectal cancer risk. A widely used hormone injection increases risk of colorectal, prostate, and brain cancers up to 35-fold. Antihistamines prescribed for morning sickness raise liver cancer risk nearly 5-fold. A class of antibiotics quadruples colorectal cancer risk. Each finding took years of work on a single compound—but a pilot using modern mass spectrometry on archived CHDS blood has already discovered entirely new suspect carcinogens that no one was even looking for. Digitizing all 50,000+ samples would measure thousands of exposures at once across three generations, cross-referenced against 60 years of cancer outcomes—building a comprehensive prenatal fingerprint that predicts lifetime cancer risk from a single pregnancy blood draw.
From grandmother’s blood to granddaughter’s diagnosis—decoded at the molecular level
The CHDS is the only cohort in the world with stored blood samples, health records, and outcome data spanning three generations—grandmothers, mothers, and grandchildren. It has already proven that disease risk passes across generations through mechanisms beyond DNA: a grandmother’s pesticide exposure in the 1960s predicts her granddaughter’s obesity (2.6× risk) and early puberty (2.1× risk) fifty years later. Scientists have begun to explain how—showing that prenatal chemical exposure flips molecular switches on breast cancer genes still detectable in daughters’ blood at age 49, and that archived newborn blood carries molecular signatures of autism risk that differ by sex. Digitizing all three generations of samples would create the world’s first molecular atlas of inherited environmental disease—revealing which banned chemicals from decades ago are still driving disease in young people today, and where to intervene to break the chain.
One blood draw that predicts disease across two lives
CHDS has built the most compelling evidence base in the world that pregnancy is a stress test revealing future disease—for both mother and child. Combinations of pregnancy complications predict cardiovascular death at 4–7× the normal rate; severe preeclampsia alone carries a 10-fold risk. Hormone levels in the third trimester predict breast cancer up to 38 years later. The same blood reveals the child’s future: inflammation during pregnancy predicts teenage depression; maternal obesity doubles the child’s colorectal cancer risk; undiagnosed celiac markers predict impaired infant growth; even heavy coffee drinking reduces a son’s fertility by 25% four decades later. Today, each of these is tested in isolation. Full digitization would turn a single prenatal blood draw into a comprehensive screening platform for the mother’s lifetime risk of heart disease, breast cancer, and metabolic disease—and the child’s risk of cancer, obesity, autism, depression, and reproductive problems. No such tool exists. The CHDS archive is the only dataset that could build and validate one.
These three concepts share a single bottleneck:
the biological archive remains analog.
153 studies have each unlocked one narrow window. Full digitization would open them all at once—creating a real-time, AI-queryable resource that transforms prenatal medicine from reactive diagnosis to predictive prevention across generations.
Fund the $51M Digitization InitiativePrenatal exposures have a massive impact on human health. The CHDS cohort is the key to proving this link, but its physical samples are finite and require costly, labor-intensive assay analysis. Moreover, data access relies on slow, fragmented, and old-fashioned methods. We are building a modern, AI-driven platform to unlock this invaluable resource and accelerate scientific discovery.
Why now?
Longitudinal data indicates an alarming rise in early-onset cancer diagnoses (patients under 50) across several regions. This trend highlights a failure in current diagnostics and necessitates immediate, innovative action in detection and preventative research. The Exposome Atlas is designed to provide the predictive engine necessary to address this challenge.
— Referenced findings from major peer-reviewed reports; please consult the project's bibliography for exact citations.
For over 60 years, the CHDS has been a cornerstone of public health research, producing landmark findings that connect early-life exposures to lifelong health outcomes.
A seminal CHDS study revealed that women exposed to high levels of the pesticide DDT in utero were nearly four times more likely to be diagnosed with breast cancer as adults. This groundbreaking finding reshaped our understanding of environmental carcinogens.
Read the ReportResearch demonstrated that a grandmother's exposure to PCBs during pregnancy could increase obesity risk across generations, revealing multigenerational metabolic disruption.
Explore the StudyBy analyzing stored serum samples, CHDS investigators found steroid hormone levels during pregnancy were associated with future maternal breast cancer risk.
View PublicationA CHDS study found a link between paternal occupation and an increased risk of colorectal cancer in adult offspring, suggesting paternal exposures can have downstream effects.
See Dr. Cohn's ProfileRodin, a Python-based tool for high-resolution mass spectrometry, streamlines metabolomics analysis, making cohort data more accessible to modern researchers.
Learn about RodinThis is not just data preservation; it's the creation of a permanent, AI-powered engine for discovery. The funding will build the infrastructure, execute the analysis, and staff the initiative for permanent disease prevention on a global scale.
| Initiative | Cost |
|---|---|
| Mass Spectrometry Digitization (50,000+ Samples) | $25,000,000 |
| Custom LLM Development & Data Harmonization (3 Years) | $6,000,000 |
| Expert Bioinformatics, AI Staffing & Executive Leadership | $6,000,000 |
| Future-Generation Data Collection | $5,000,000 |
| 10-Year Data Hosting, Storage & Operations | $7,500,000 |
| Global Access Front-End Platform & Outreach | $1,500,000 |
| TOTAL FUNDING REQUIRED | $51,000,000 |
Whether you're a potential investor, researcher, or partner, we'd love to hear from you. Let's build the future of preventative medicine together.