Induced pluripotent stem cells (iPSCs) are an essential tool for modeling how causal genetic variants impact cellular function in disease, as well as an emerging source of tissue for regenerative medicine. The preparation of somatic cells, their reprogramming and the subsequent verification of iPSC pluripotency are laborious, manual processes limiting the scale and reproducibility of this technology. Here we describe a modular, robotic platform for iPSC reprogramming enabling automated, high-throughput conversion of skin biopsies into iPSCs and differentiated cells with minimal manual intervention. We demonstrate that automated reprogramming and the pooled selection of polyclonal pluripotent cells results in high-quality, stable iPSCs. These lines display less line-to-line variation than either manually produced lines or lines produced through automation followed by single-colony subcloning. The robotic platform we describe will enable the application of iPSCs to population-scale biomedical problems including the study of complex genetic diseases and the development of personalized medicines.

Wolfram syndrome is an autosomal recessive disorder caused by mutations in WFS1 and is characterized by insulin-dependent diabetes mellitus, optic atrophy, and deafness. To investigate the cause of β-cell failure, we used induced pluripotent stem cells to create insulin-producing cells from individuals with Wolfram syndrome. WFS1-deficient β-cells showed increased levels of endoplasmic reticulum (ER) stress molecules and decreased insulin content. Upon exposure to experimental ER stress, Wolfram β-cells showed impaired insulin processing and failed to increase insulin secretion in response to glucose and other secretagogues. Importantly, 4-phenyl butyric acid, a chemical protein folding and trafficking chaperone, restored normal insulin synthesis and the ability to upregulate insulin secretion. These studies show that ER stress plays a central role in β-cell failure in Wolfram syndrome and indicate that chemical chaperones might have therapeutic relevance under conditions of ER stress in Wolfram syndrome and other forms of diabetes.

The exchange of the oocyte's genome with the genome of a somatic cell, followed by the derivation of pluripotent stem cells, could enable the generation of specific cells affected in degenerative human diseases. Such cells, carrying the patient's genome, might be useful for cell replacement. Here we report that the development of human oocytes after genome exchange arrests at late cleavage stages in association with transcriptional abnormalities. In contrast, if the oocyte genome is not removed and the somatic cell genome is merely added, the resultant triploid cells develop to the blastocyst stage. Stem cell lines derived from these blastocysts differentiate into cell types of all three germ layers, and a pluripotent gene expression program is established on the genome derived from the somatic cell. This result demonstrates the feasibility of reprogramming human cells using oocytes and identifies removal of the oocyte genome as the primary cause of developmental failure after genome exchange.

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters human host cells via angiotensin-converting enzyme 2 (ACE2) and causes coronavirus disease 2019 (COVID-19). Here, through a genome-wide association study, we identify a variant (rs190509934, minor allele frequency 0.2–2%) that downregulates ACE2 expression by 37% (P = 2.7 × 10−8) and reduces the risk of SARS-CoV-2 infection by 40% (odds ratio = 0.60, P = 4.5 × 10−13), providing human genetic evidence that ACE2 expression levels influence COVID-19 risk. We also replicate the associations of six previously reported risk variants, of which four were further associated with worse outcomes in individuals infected with the virus (in/near LZTFL1, MHC, DPP9 and IFNAR2). Lastly, we show that common variants define a risk score that is strongly associated with severe disease among cases and modestly improves the prediction of disease severity relative to demographic and clinical factors alone.