The nuclear receptor PPARγ is the master regulator of adipocyte differentiation, distribution, and function. In addition, PPARγ induces terminal differentiation of several epithelial cell lineages, including colon epithelia. Loss-of-function mutations in PPARG result in familial partial lipodystrophy subtype 3 (FPDL3), a rare condition characterized by aberrant adipose tissue distribution and severe metabolic complications, including diabetes. Mutations in PPARG have also been reported in sporadic colorectal cancers, but the significance of these mutations is unclear. Studying these natural PPARG mutations provides valuable insights into structure-function relationships in the PPARγ protein. We functionally characterized a novel FPLD3-associated PPARγ L451P mutation in helix 9 of the ligand binding domain (LBD). Interestingly, substitution of the adjacent amino acid K450 was previously reported in a human colon carcinoma cell line.

Adipose tissue plays a crucial role in maintaining metabolic homeostasis by storing lipids and glucose from circulation as intracellular fat. As peripheral tissues like adipose tissue become insulin resistant, decompensation of blood glucose levels occurs causing type 2 diabetes (T2D). Currently, modulating the glycocalyx, a layer of cell-surface glycans, is an underexplored pharmacological treatment strategy to improve glucose homeostasis in T2D patients. Here, we show a novel role for cell-surface heparan sulfate (HS) in establishing glucose uptake capacity and metabolic utilization in differentiated adipocytes. Using a combination of chemical and genetic interventions, we identified that HS modulates this metabolic phenotype by attenuating levels of Wnt signaling during adipogenesis. By engineering, the glycocalyx of pre-adipocytes with exogenous synthetic HS mimetics, we were able to enhance glucose clearance capacity after differentiation through modulation of Wnt ligand availability. These findings establish the cellular glycocalyx as a possible new target for therapeutic intervention in T2D patients by enhancing glucose clearance capacity independent of insulin secretion.

Impaired expansion of peripheral fat contributes to the pathogenesis of insulin resistance and Type 2 Diabetes (T2D). We aimed to identify novel disease-gene interactions during adipocyte differentiation.

Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs.

Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.

The seven-transmembrane superfamily member 3 protein (TM7SF3) is a p53-regulated homeostatic factor that attenuates cellular stress and the unfolded protein response. Here we show that TM7SF3 localizes to nuclear speckles; eukaryotic nuclear bodies enriched in splicing factors. This unexpected location for a trans -membranal protein enables formation of stable complexes between TM7SF3 and pre-mRNA splicing factors including DHX15, LARP7, HNRNPU, RBM14, and HNRNPK. Indeed, TM7SF3 regulates alternative splicing of >330 genes, mainly at the 3'end of introns by directly modulating the activity of splicing factors such as HNRNPK. These effects are observed both in cell lines and primary human pancreatic islets. Accordingly, silencing of TM7SF3 results in differential expression of 1465 genes (about 7% of the human genome); with 844 and 621 genes being up- or down-regulated, respectively. Our findings implicate TM7SF3, as a resident protein of nuclear speckles and suggest a role for seven-transmembrane proteins as regulators of alternative splicing.

Continuous glucose monitoring (CGM) is approved for insulin dosing decisions in the ambulatory setting, but not currently for inpatients. CGM has the capacity to reduce patient-provider contact in inpatients with coronavirus disease 2019 (COVID-19), thus potentially reducing in hospital virus transmission. However, there are sparse data on the accuracy and efficacy of CGM to titrate insulin doses in inpatients.

Type 2 diabetes (T2D) is a multifactorial, heritable syndrome characterized by dysregulated glucose homeostasis that results from impaired insulin secretion and insulin resistance. Genetic association studies have successfully identified hundreds of T2D risk loci implicating many genes in disease pathogenesis. In this review, we provide an overview of the recent T2D genetic studies from the past 3 years with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discuss recent work on the use and limitations of genetic risk scores (GRS) for T2D risk prediction.