Perturbational phenotyping of human blood cells reveals genetically determined latent traits associated with subsets of common diseases

Abstract

Although genome-wide association studies (GWAS) have successfully linked genetic risk loci to various disorders, identifying underlying cellular biological mechanisms remains challenging due to the complex nature of common diseases. We established a framework using human peripheral blood cells, physical, chemical and pharmacological perturbations, and flow cytometry-based functional readouts to reveal latent cellular processes and performed GWAS based on these evoked traits in up to 2,600 individuals. We identified 119 genomic loci implicating 96 genes associated with these cellular responses and discovered associations between evoked blood phenotypes and subsets of common diseases. We found a population of pro-inflammatory anti-apoptotic neutrophils prevalent in individuals with specific subsets of cardiometabolic disease. Multigenic models based on this trait predicted the risk of developing chronic kidney disease in type 2 diabetes patients. By expanding the phenotypic space for human genetic studies, we could identify variants associated with large effect response differences, stratify patients and efficiently characterize the underlying biology.

Main

Precision medicine strives to reclassify complex heterogeneous diseases into distinct biologically defined groups, thereby enabling targeted therapies and improved outcomes. Examples include the subdivision of common cancers by somatic driver mutations¹, the discovery of eosinophilic variants of asthma² and the recognition that some presentations of heart failure may arise from the accumulation of amyloidogenic proteins, which can be subdivided further based on the aggregating protein³. The realization of precision medicine has been hindered by the lack of readily available measures of the activities of discrete biological pathways in most common diseases. Historical approaches have focused on mining large patient biobanks combining archived DNA, RNA and serum or plasma samples with clinical records⁴. Although such strategies have identified common genetic variants associated with clinical outcomes, they have typically not been successful at capturing the underlying cell biology, limiting their utility in producing mechanistic insights into therapeutic implications^5,6.

We aimed to establish a framework that bridges genetic variants and complex diseases through standardized phenotyping of primary human cells. We used live human blood cells, as these reflect physiological processes, disease states and environmental factors, including active therapies. For example, dysregulation of hematopoietic processes can result in disease progression via mechanisms such as the contribution of inflammation to atherosclerosis and insulin resistance^7,8,9 or hyperactive coagulation in pathological thrombosis^10,11,12. In addition to circulating cells with their repertoire of responses, blood plasma contains hormones, secreted proteins, metabolites, cell-free DNA, microparticles and extracellular vesicles that can carry signals to blood cells or other cell types. Peripheral blood may offer a diagnostic window into multiple organ systems and integrative physiology^13,14,15.

Previous genome-wide association studies (GWAS) on whole blood primarily focused on complete blood counts (CBCs); clinical parameters describing numbers; volumes and distribution of leukocytes; erythrocytes and platelets; and the genetic architecture of hematopoiesis and blood diseases have been mapped in detail^16,17,18. A recent study expanded measured phenotypes to include flow cytometry-derived parameters with the aim of better describing cellular function¹⁹. The Human Functional Genomics Project profiled cytokine production and baseline immune parameters in response to pathogen challenges²⁰. Other studies have revealed the genetic basis of platelet aggregation in response to known agonists^21,22. However, these studies did not consider the dynamic responses of blood cells to environmental conditions, which likely contribute to their effects on disease development, progression and prevention.

We hypothesized that treating whole blood ex vivo with diverse stressors or stimuli would enable the identification of latent differential cellular responses and new disease-associated endophenotypes. We anticipated that this expansion of phenotypic space would evoke traits determined by large effect size common alleles, enabling efficient target identification and improving the prediction of incident events. Moreover, given that biological pathways are reused across diverse tissues and organ systems, insights into whole blood may be relevant to a range of conditions originating in different tissues. By identifying intermediate cellular phenotypes, we sought to define subcategories of disease and specific pathophysiologic mechanisms that can be targeted more directly.

Results

Chemical perturbations expand the phenotypic space of blood profiles

In clinical settings, whole blood cytometry is used to quantify circulating cells as part of standardized diagnostic tests. We adapted a widely-used whole-blood cytometry analyzer (Sysmex XN-1000) to systematically profile peripheral blood from over 4,700 study participants (donors) under 37 conditions (36 perturbations and baseline), genotyped more than 2,600 donors and performed GWAS for all blood perturbation profiles (Fig. 1a). We recorded side scatter (SSC), forward scatter (FSC) and side fluorescence (SFL) of blood cells using four fluorescence dyes (white cell differential channel by fluorescence (WDF), white count and nucleated red blood cells (WNR), reticulocyte (RET) and platelet F (PLT-F)) that quantify morphological and intracellular properties. Chemical stressors evoked distinct cellular states for blood cells that were not typically observed under baseline conditions, enabling the detection of new cell populations in three-dimensional cytometry measurements (Extended Data Fig. 1). We determined cellular gates based on empiric distributions of blood cells under perturbation conditions and defined parameter sets for all observed cell populations (Fig. 1b and Extended Data Fig. 2). The perturbation conditions represented discrete classes of exposure likely to contribute to blood cell responses as follows: (1) simulated physiological stressors; (2) chemical stressors; (3) gut microbiome metabolites; and (4) drugs with known mechanisms of action (Supplementary Table 1). We recorded up to 37 condition-specific blood responses for each donor and calculated quantitative profiles characterizing each cell population using cell counts, as well as median and s.d. for SSC, FSC and SFL parameters for each blood cell population (Fig. 1c and Supplementary Table 2). Compared to the baseline, each perturbation evoked particular changes in the characteristics of different blood lineages, resulting in a series of distinct cellular profiles (Extended Data Figs. 1 and 2 and Supplementary Fig. 1). With these chemical perturbations, we expanded quantification for each donor from 278 parameters to more than 4,000 parameters on average, greatly expanding the phenotypic space that could be interrogated.