Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes.

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

Identification of mammalian transcription factors that bind to inaccessible chromatin.

Transcription factors (TFs) are proteins that affect gene expression by binding to regulatory regions of DNA in a sequence specific manner. The binding of TFs to DNA is controlled by many factors, including the DNA sequence, concentration of TF, chromatin accessibility and co-factors. Here, we systematically investigated the binding mechanism of hundreds of TFs by analysing ChIP-seq data with our explainable statistical model, ChIPanalyser. This tool uses as inputs the DNA sequence binding motif; the capacity to distinguish between strong and weak binding sites; the concentration of TF; and chromatin accessibility. We found that approximately one third of TFs are predicted to bind the genome in a DNA accessibility independent fashion, which includes TFs that can open the chromatin, their co-factors and TFs with similar motifs. Our model predicted this to be the case when the TF binds to its strongest binding regions in the genome, and only a small number of TFs have the capacity to bind dense chromatin at their weakest binding regions, such as CTCF, USF2 and CEBPB. Our study demonstrated that the binding of hundreds of human and mouse TFs is predicted by ChIPanalyser with high accuracy and showed that many TFs can bind dense chromatin.

RISING STARS: Liver sinusoidal endothelial transcription factors in metabolic homeostasis and disease.

Liver sinusoidal endothelial cells (LSECs) are highly specialised endothelial cells that form the liver microvasculature. LSECs maintain liver homeostasis, scavenging bloodborne molecules, regulating immune response, and actively promoting hepatic stellate cell quiescence. These diverse functions are underpinned by a suite of unique phenotypical attributes distinct from other blood vessels. In recent years, studies have begun to reveal the specific contributions of LSECs to liver metabolic homeostasis and how LSEC dysfunction associates with disease aetiology. This has been particularly evident in the context of non-alcoholic fatty liver disease (NAFLD), the hepatic manifestation of metabolic syndrome, which is associated with the loss of key LSEC phenotypical characteristics and molecular identity. Comparative transcriptome studies of LSECs and other endothelial cells, together with rodent knockout models, have revealed that loss of LSEC identity through disruption of core transcription factor activity leads to impaired metabolic homeostasis and to hallmarks of liver disease. This review explores the current knowledge of LSEC transcription factors, covering their roles in LSEC development and maintenance of key phenotypic features, which, when disturbed, lead to loss of liver metabolic homeostasis and promote features of chronic liver diseases, such as non-alcoholic liver disease.