A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.
Introduction Type 2 Diabetes (T2D) affects more than 415 million people and is a leading cause of morbidity and mortality worldwide. While T2D is influenced by environmental factors, it is also a highly heritable disorder, with genetic variation contributing to a disparity in T2D prevalence across populations. An example of this disparity is observed within American populations, where the prevalence of diabetes in individuals of Mexican or Latin American descent is approximately twice that of US non‐Hispanic whites. Through a genome‐wide association study, we recently identified a variant haplotype in SLC16A11 that explains ~20% of the increased T2D prevalence in Mexico. Objective To follow up on the genetic association at SLC16A11 , in order to delineate mechanisms underlying T2D risk at this locus. Results Using a combination of molecular, biochemical, cellular, and physiological approaches we identify two distinct mechanisms that lead to reduced SLC16A11 function. First, we observe a significant reduction in SLC16A11 expression ‐ in a dose‐dependent manner ‐ in carriers of the T2D risk haplotype, in human liver. Second, we demonstrate that T2D risk‐associated coding variants in SLC16A11 attenuate activity by disrupting a key interaction with an ancillary protein, thereby reducing plasma membrane localization. These two independent mechanisms by which T2D‐associated coding and non‐coding variants impact SLC16A11 expression levels and subcellular localization implicate perturbation of SLC16A11 as causal at this locus, and suggest reduced SLC16A11 activity as the T2D‐relevant direction‐of‐effect. To gain insight into how disruption of SLC16A11 function impacts T2D risk, we investigate the activity of this previously uncharacterized transporter and establish that SLC16A11 functions as an H + ‐coupled monocarboxylate transporter. Conclusion Our findings illustrate the path from genetic association to therapeutic hypothesis, through defining the molecular mechanisms by which genetic variation affects SLC16A11 action, and suggest that increasing SLC16A11 function could be therapeutically beneficial for people with T2D. Support or Funding Information This work was conducted as part of the Slim Initiative for Genomic Medicine, a project funded by the Carlos Slim Foundation in Mexico
