André Rendeiro

Our research group focuses on spatial and computational biology to understand how cells interact to form complex human physiology—and how these interactions change over the human lifespan and contribute to disease. We develop and apply advanced computational methods for the analysis of spatial data, including spatial transcriptomics and highly multiplexed imaging, and integrate this with other molecular data modalities such as transcriptomics, proteomics, metabolomics, and most importantly, clinical data across different stages of life.

Our goal is to reveal how molecular activity at the cellular level leads to higher-order tissue architecture and how disruptions in these processes contribute to disease development. Core research questions include:

• How can we define robust patterns of tissue architecture across tissues and organs?
• Are there undiscovered recurring spatial patterns that distinguish health from disease?
• Do specific tissue architecture patterns influence treatment accessibility and therapy response?
• What large-scale patterns of immune cell distribution exist within and across human organs?
• Can we quantify tissue integrity across the human body and track it throughout the lifespan?
• What is the connection between tissue integrity, aging, and disease onset? 

Computational Pathology and Tissue Micro-Anatomy

The spatial organization of tissues into micro-anatomical domains—including cell size, shape, and extracellular matrix composition—can shift significantly in pathological conditions. With cutting-edge technologies like multiplexed imaging and spatial transcriptomics, we can directly observe cellular phenotypes and cell-cell interactions within the native tissue environment. These tools allow us to uncover the fundamental organizing principles of human tissue architecture and organ-specific physiology.

Our research aims to:

• Define tissue integrity across healthy human tissues and age groups
• Detect early pre-cancerous lesions and signs of cancer invasion
• Investigate age-related diseases involving cell degeneration and loss of tissue structure 

Aging, Tissue Integrity, and Lifespan Extension

Aging is linked to the decline of tissue integrity and is a major driver of chronic diseases that reduce quality of life. We hypothesize that previously overlooked spatial patterns in tissue organization play a key role in the loss of cellular identity and tissue function associated with aging. These patterns may be influenced by proximity to anatomical structures, extracellular matrix changes, or local metabolic activity—factors that contribute to inflammation, cellular senescence, and tissue breakdown.

By studying these spatial relationships, we aim to:

• Understand how tissue integrity changes with age
• Explore how these changes lead to disease
• Develop strategies to delay or prevent aging-related decline
• Contribute to lifespan extension and healthy aging

André Rendeiro is a Principal Investigator at CeMM since June 2022. He leads a group studying how cells interact to generate complex physiology in the human body, and how these interactions changes over the lifespan of individuals and give rise to disease. To do that, his group develops computational methods for the analysis of spatial data (spatial transcriptomics, highly multiplexed imaging, histopathological images)—its integration with various modalities of molecular, demographic, and clinical data of individuals throughout their lifespan.

Prior to starting his group, Rendeiro studied in Portugal, Austria, and Norway and earned his PhD in molecular medicine at CeMM in Vienna. During his PhD he developed methods for high-throughput cellular profiling and perturbation at single-cell resolution, applying them to leukemia, in the lab of Christoph Bock at CeMM. Between 2020 and 2022 he was a postdoctoral associate at the Institute for Precision Medicine and the Institute for Computational Biomedicine at Weill Cornell Medicine in New York. There, in the lab of Olivier Elemento, he developed computational methods for the analysis of highly multiplexed imaging that incorporate expression, morphology, microanatomy, and clinical covariates. He led efforts resulting in the first tissue-level, single-cell resolution maps of lung pathology during COVID-19 and also contributed to the study of cancer, lung development, and disease, as well as COVID-19 immunology.