The human homologue of unc-93 maps to chromosome 6q27 – characterisation and analysis in sporadic epithelial ovarian cancer

BACKGROUND: In sporadic ovarian cancer, we have previously reported allele loss at D6S193 (62%) on chromosome 6q27, which suggested the presence of a putative tumour suppressor gene. Based on our data and that from another group, the minimal region of allele loss was between D6S264 and D6S149 (7.4 cM). To identify the putative tumour suppressor gene, we established a physical map initially with YACs and subsequently with PACs/BACs from D6S264 to D6S149. To accelerate the identification of genes, we sequenced the entire contig of approximately 1.1 Mb. Seven genes were identified within the region of allele loss between D6S264 and D6S149. RESULTS: The human homologue of unc-93 (UNC93A) in C. elegans was identified to be within the interval of allele loss centromeric to D6S149. This gene is 24.5 kb and comprises of 8 exons. There are two transcripts with the shorter one due to splicing out of exon 4. It is expressed in testis, small intestine, spleen, prostate, and ovary. In a panel of 8 ovarian cancer cell lines, UNC93A expression was detected by RT-PCR which identified the two transcripts in 2/8 cell lines. The entire coding sequence was examined for mutations in a panel of ovarian tumours and ovarian cancer cell lines. Mutations were identified in exons 1, 3, 4, 5, 6 and 8. Only 3 mutations were identified specifically in the tumour. These included a c.452G>A (W151X) mutation in exon 3, c.676C>T (R226X) in exon 5 and c.1225G>A(V409I) mutation in exon 8. However, the mutations in exon 3 and 5 were also present in 6% and 2% of the normal population respectively. The UNC93A cDNA was shown to express at the cell membrane and encodes for a protein of 60 kDa. CONCLUSIONS: These results suggest that no evidence for UNC93A as a tumour suppressor gene in sporadic ovarian cancer has been identified and further research is required to evaluate its normal function and role in the pathogenesis of ovarian cancer

Fetus-derived DLK1 is required for maternal metabolic adaptations to pregnancy and is associated with fetal growth restriction.

Pregnancy is a state of high metabolic demand. Fasting diverts metabolism to fatty acid oxidation, and the fasted response occurs much more rapidly in pregnant women than in non-pregnant women. The product of the imprinted DLK1 gene (delta-like homolog 1) is an endocrine signaling molecule that reaches a high concentration in the maternal circulation during late pregnancy. By using mouse models with deleted Dlk1, we show that the fetus is the source of maternal circulating DLK1. In the absence of fetally derived DLK1, the maternal fasting response is impaired. Furthermore, we found that maternal circulating DLK1 levels predict embryonic mass in mice and can differentiate healthy small-for-gestational-age (SGA) infants from pathologically small infants in a human cohort. Therefore, measurement of DLK1 concentration in maternal blood may be a valuable method for diagnosing human disorders associated with impaired DLK1 expression and to predict poor intrauterine growth and complications of pregnancy.M.A.M.C. was supported by a PhD studentship from the Cambridge Centre for Trophoblast Research. Research was supported by grants from the MRC (MR/J001597/1 and MR/L002345/1), the Medical College of Saint Bartholomew's Hospital Trust, a Wellcome Trust Investigator Award, EpigeneSys (FP7 Health-257082), EpiHealth (FP7 Health-278414), a Herchel Smith Fellowship (N.T.) and NIH grant RO1 DK89989. The contents are the authors' sole responsibility and do not necessarily represent official NIH views. We thank G. Burton for invaluable support, and M. Constância and I. Sandovici (University of Cambridge) for the Meox2-cre mice. We are extremely grateful to all of the participants in the Pregnancy Outcome Prediction study. This work was supported by the NIHR Cambridge Comprehensive Biomedical Research Centre (Women's Health theme) and project grants from the MRC (G1100221) and Sands (Stillbirth and Neonatal Death Charity). The study was also supported by GE Healthcare (donation of two Voluson i ultrasound systems for this study) and by the NIHR Cambridge Clinical Research Facility, where all research visits took place.This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/ng.369

Human pregnancy zone protein stabilizes misfolded proteins including preeclampsia- and Alzheimer\u27s- associated amyloid beta peptide

Protein misfolding underlies the pathology of a large number of human disorders, many of which are age-related. An exception to this is preeclampsia, a leading cause of pregnancy-associated morbidity and mortality in which misfolded proteins accumulate in body fluids and the placenta. We demonstrate that pregnancy zone protein (PZP), which is dramatically elevated in maternal plasma during pregnancy, efficiently inhibits in vitro the aggregation of misfolded proteins, including the amyloid beta peptide (Aβ) that is implicated in preeclampsia as well as with Alzheimer\u27s disease. The mechanism by which this inhibition occurs involves the formation of stable complexes between PZP and monomeric Aβ or small soluble Aβ oligomers formed early in the aggregation pathway. The chaperone activity of PZP is more efficient than that of the closely related protein alpha-2-macroglobulin (α2M), although the chaperone activity of α2M is enhanced by inducing its dissociation into PZP-like dimers. By immunohistochemistry analysis, PZP is found primarily in extravillous trophoblasts in the placenta. In severe preeclampsia, PZP-positive extravillous trophoblasts are adjacent to extracellular plaques containing Aβ, but PZP is not abundant within extracellular plaques. Our data support the conclusion that the up-regulation of PZP during pregnancy represents a major maternal adaptation that helps to maintain extracellular proteostasis during gestation in humans. We propose that overwhelming or disrupting the chaperone function of PZP could underlie the accumulation of misfolded proteins in vivo. Attempts to characterize extracellular proteostasis in pregnancy will potentially have broad-reaching significance for understanding disease-related protein misfolding

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease