Projects

Our research spans these areas:

Chronic illness and pain conditions

Lyme disease is the most common vector-borne illness in the United States and is rapidly growing in both incidence and range. We study the causes, consequences, and treatments for Lyme disease and other chronic illnesses, including fibromyalgia, ME/CFS and long COVID, as well as tick-borne diseases of both humans and livestock.

CARE for Lyme is our remote sampling and biospecimen collection study. Participants receive at-home kits and surveys over a year, and we test the ticks that bit them, linking infection in the tick to biomarkers and outcomes in the person.

CARE for Lyme pairs tick samples with longitudinal prospective participant samples.

A tick bite transmits *Borrelia burgdorferi*, which can infect the uterus. From Lyme disease increases risk for multiple gynecological conditions.

Genome-wide associations with fibromyalgia across 2.5 million people, from Kerrebijn et al. 2026.

Genetics and gene-environment interactions of biomarkers

Biomarker levels vary widely throughout the day and year, but these are rarely accounted for in clinical or research models of disease. We are developing approaches to do so, with a particular focus on cholesterol and related steroid hormones.

Glucose variation across the day stratified by *MTNR1B* genotype. The same variant that raises glucose in the morning also lowers it in the evening. From Sinnott-Armstrong et al. 2026.

Human adipocytes packed with lipid droplets, from our study of a non-coding variant near *COBLL1* that alters actin remodelling.

Lyme-free risk curves from our work on cholesterol and Lyme disease.

Open lab automation

The open hardware ecosystem for laboratory automation has a number of individual successful tools, but little integration. We’re developing the hardware and software to integrate these, including OLIVE (Online Learning of In Vitro Experiments), our system for automated high throughput experimentation.

OLIVE’s architecture pairs algorithmic experimental design with automated testing.

Biomedical metascience

Artificial intelligence is rapidly becoming a medical diagnostic aid, despite bias, privacy, and other concerns. We study these and develop methods to incorporate medical and community feedback into AI systems. We also design systems to help us understand and address ethical and methodological shortcomings of the field more broadly.