Explore the scientific evidence supporting beta cell biology, metabolic disease interception, liquid biopsy, and molecular diagnostics. This library includes Kihealth publications alongside foundational peer-reviewed research from leading academic institutions around the world.
Supporting materials from Kihealth's clinical, research, and validation programs.
Peer-facing technical writing on assay design, analytical validity, and clinical utility.
A curated library of foundational studies from Nature, Cell, Science, NEJM, Diabetes, JCI, PNAS, and other leading journals — the scientific record underlying Kihealth Labs' work in beta cell biology, cfDNA, and precision diagnostics.
IDF Diabetes Atlas 10th edition — global diabetes prevalence figures widely cited across the metabolic disease literature.
CCGA study establishing methylation-based multi-cancer detection — a defining reference for scalable cfDNA methylation screening.
Continuous multi-omic monitoring uncovering biological rhythms — methodological precedent for longitudinal cfDNA surveillance.
TrialNet study showing that a single course of teplizumab delayed clinical T1D onset by ~2 years — a landmark for disease interception.
DELFI framework demonstrating disease-specific fragmentation patterns in cfDNA — a template widely referenced in cfDNA precision diagnostics.
Widely cited review of deep learning applications in clinical medicine — provides the framing for AI-enabled precision diagnostics.
Demonstrated the value of longitudinal multi-omic monitoring for detecting sub-clinical disease transitions — directly informs interception-grade biomarker strategy.
Established genome-wide cfDNA methylation profiling as a sensitive approach to tissue-of-origin inference — technology principles broadly applied to non-oncology interception.
Demonstrated that short cfDNA fragments preferentially carry tumor signal — key evidence supporting size-selective liquid biopsy approaches.
Defining review of liquid biopsy technology and clinical translation — foundational framework used broadly in cfDNA-based diagnostics.
Framework paper on the convergence of molecular diagnostics, longitudinal monitoring, and analytics — the intellectual foundation for disease interception.
Landmark demonstration that tissue-specific methylation signatures in cfDNA can identify the cellular origin of cell death, including β-cells, hepatocytes, brain, and pancreatic exocrine tissue.
Foundational fragmentomics work showing that cfDNA fragment length distributions carry tissue- and disease-of-origin information.
Defined functional β-cell subpopulations within adult human islets — foundational for interpreting molecular signals of β-cell health.
Landmark single-cell atlas of the human endocrine pancreas across T2D — a reference resource for β-cell biology and biomarker development.
Single-cell RNA-seq of human islets identifying T2D-associated transcriptional changes — key reference for β-cell stress biology.
Demonstrated elevated unmethylated INS DNA in plasma at diagnosis of T1D and its decline over the first year, validating cfDNA methylation as a β-cell death biomarker.
Showed that β-cell-derived cfDNA rises in autoantibody-positive at-risk individuals before clinical onset of T1D, supporting the disease interception paradigm.
Definitive Nature primer on T2D pathophysiology, integrating β-cell failure with insulin resistance and multi-organ dysfunction.
Established the 3-stage model of presymptomatic T1D used to define clinical interception windows.
Landmark policy paper defining the precision medicine agenda, now foundational to biomarker-driven early detection.
Established a droplet digital PCR (ddPCR) assay for demethylated INS cfDNA — the technical foundation for high-sensitivity blood-based β-cell death monitoring.
ADA/EASD consensus report on β-cell failure mechanisms in T2D and priorities for prevention — a canonical citation in metabolic disease interception.
Highly cited work on transcription factor control of islet cell identity, relevant to β-cell regeneration strategies.
Combined analysis of >13,000 children showing that seroconversion to multiple islet autoantibodies predicts near-inevitable progression to T1D — the risk-stratification foundation used by Kihealth's T1D program.
Head-to-head demonstration of ddPCR's precision advantage over qPCR for rare-event detection — directly relevant to β-cell cfDNA assays.
Demonstrated that β-cell dedifferentiation — not just death — underlies loss of insulin secretion in diabetes, reshaping models of β-cell decline.
Widely cited synthesis of T1D natural history and the multi-stage disease model that underlies modern interception research.
Duplex sequencing — one of the technical breakthroughs enabling ultra-sensitive detection of rare cfDNA variants.
Demonstrated genome-wide fetal profiling from maternal plasma cfDNA — a defining early success of clinical liquid biopsy.
First demonstration that methylation-specific PCR of circulating insulin DNA can quantify β-cell death in vivo, establishing the molecular basis for INS cfDNA assays.
Defining review of the UPR — a central pathway in β-cell stress responses relevant to both T1D and T2D pathogenesis.
Original ddPCR platform paper — the technical basis for high-sensitivity absolute quantification used in cfDNA assays including demethylated INS DNA.
Comprehensive review of INS mutations, β-cell stress, and their contribution to monogenic and complex diabetes phenotypes.
Early proof-of-concept that circulating tumor DNA can be measured dynamically — a paradigm that generalized to cfDNA in metabolic disease.
Long-term evidence for the durable benefit of early glycemic control — reinforcing the value of earlier detection windows.
Foundational comparative analysis of β-cell death mechanisms across T1D and T2D — cited across the disease interception literature.
The Diabetes Prevention Program — the defining evidence that T2D can be prevented, and the clinical rationale for earlier biomarker-driven interception.
Finnish Diabetes Prevention Study — foundational evidence for prevention in high-risk individuals identified by early biomarkers.
