An atlas of human histological diversity

Abstract

Descriptions of tissues by histopathologists rest on verbal statements limited by quantitative inaccuracies and personal cognitive biases. Here we propose an unsupervised computational framework that transposes to histology the concepts and methods of RNA-seq gene expression analysis, setting histology on an unbiased quantitative ground. Leveraging this framework and the GTEx dataset, we built an atlas surveying the histological diversity of 40 organs from 946 non-diseased individuals and documenting 11,125,747 associations between 2,560 morphemes--the histological analogs of genes in our framework--and 9 layers of patho-clinical and multi-omic molecular data, providing a rich context to interpret histology. In contrast with the ideally healthy normal specimens depicted in histology textbooks, the atlas reveals the influence of age, sex, genetics and sub-clinical pathologies on tissue structures. For example, we report that female eccrine sweat glands are surrounded by more adipocytes than their male counterparts, and that distinct calcification-associated aorta morphemes are driven by either smoking or genetic polymorphisms. Cross-organ analyses also delineate the systemic histological impact of diabetes and other conditions and establish the power of blood gene expression to predict disease-related morphemes. The atlas is released as an interactive web resource aimed at researchers.