Birthdating studies reshape models for pituitary gland cell specification

AbstractThe intermediate and anterior lobes of the pituitary gland are derived from an invagination of oral ectoderm that forms Rathke's pouch. During gestation proliferating cells are enriched around the pouch lumen, and they appear to delaminate as they exit the cell cycle and differentiate. During late mouse gestation and the postnatal period, anterior lobe progenitors re-enter the cell cycle and expand the populations of specialized, hormone-producing cells. At birth, all cell types are present, and their localization appears stratified based on cell type. We conducted a birth dating study of Rathke's pouch derivatives to determine whether the location of specialized cells at birth is correlated with the timing of cell cycle exit. We find that all of the anterior lobe cell types initiate differentiation concurrently with a peak between e11.5 and e13.5. Differentiation of intermediate lobe melanotropes is delayed relative to anterior lobe cell types. We discovered that specialized cell types are not grouped together based on birth date and are dispersed throughout the anterior lobe. Thus, the apparent stratification of specialized cells at birth is not correlated with cell cycle exit. Thus, the currently popular model of cell specification, dependent upon timing of extrinsic, directional gradients of signaling molecules, needs revision. We propose that signals intrinsic to Rathke's pouch are necessary for cell specification between e11.5 and e13.5 and that cell–cell communication likely plays an important role in regulating this process

PROP1 triggers epithelial-mesenchymal transition-like process in pituitary stem cells

Mutations in PROP1 are the most common cause of hypopituitarism in humans; therefore, unraveling its mechanism of action is highly relevant from a therapeutic perspective. Our current understanding of the role of PROP1 in the pituitary gland is limited to the repression and activation of the pituitary transcription factor genes Hesx1 and Pou1f1, respectively. To elucidate the comprehensive PROP1-dependent gene regulatory network, we conducted genome wide analysis of PROP1 DNA binding and effects on gene expression in mutant mice, mouse isolated stem cells and engineered mouse cell lines. We determined that PROP1 is essential for stimulating stem cells to undergo an epithelial to mesenchymal transition-like process necessary for cell migration and differentiation. Genomic profiling reveals that PROP1 binds to genes expressed in epithelial cells like Claudin 23, and to EMT inducer genes like Zeb2, Notch2 and Gli2. Zeb2 activation appears to be a key step in the EMT process. Our findings identify PROP1 as a central transcriptional component of pituitary stem cell differentiation.Fil: Pérez Millán, María Inés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Brinkmeier, Michelle. University of Michigan; Estados UnidosFil: Mortensen, Amanda H. University of Michigan; Estados UnidosFil: Camper, Sally. University of Michigan; Estados Unido

Genetics of combined pituitary hormone deficiency: Roadmap into the genome era

The genetic basis for combined pituitary hormone deficiency (CPHD) is complex, involving 30 genes in a variety of syndromic and nonsyndromic presentations. Molecular diagnosis of this disorder is valuable for predicting disease progression, avoiding unnecessary surgery, and family planning. Weexpect that the application of high throughput sequencing will uncover additional contributing genes and eventually become a valuable tool for molecular diagnosis. For example, in the last 3 years, six new genes have been implicated in CPHD using whole-exome sequencing. In this review, we present a historical perspective on gene discovery for CPHD and predict approaches that may facilitate future gene identification projects conducted by clinicians and basic scientists. Guidelines for systematic reporting of genetic variants and assigning causality are emerging. We apply these guidelines retrospectively to reports of the genetic basis of CPHD and summarize modes of inheritance and penetrance for each of the known genes. In recent years, there have been great improvements in databases of genetic information for diverse populations. Some issues remain that make molecular diagnosis challenging in some cases. These include the inherent genetic complexity of this disorder, technical challenges like uneven coverage, differing results from variant calling and interpretation pipelines, the number of tolerated genetic alterations, and imperfect methods for predicting pathogenicity.Wediscuss approaches for future research in the genetics of CPHD.Fil: Fang, Qing. University of Michigan; Estados UnidosFil: George, Akima S.. University of Michigan; Estados UnidosFil: Brinkmeier, Michelle L.. University of Michigan; Estados UnidosFil: Mortensen, Amanda H.. University of Michigan; Estados UnidosFil: Gergics, Peter. University of Michigan; Estados UnidosFil: Cheung, Leonard Y.M.. University of Michigan; Estados UnidosFil: Daly, Alexandre Z.. University of Michigan; Estados UnidosFil: Ajmal, Adnan. University of Michigan; Estados UnidosFil: Pérez Millán, María Inés. University of Michigan; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Bilge Ozel, A.. University of Michigan; Estados UnidosFil: Kitzman, Jacob. University of Michigan; Estados UnidosFil: Mills, Ryan E.. University of Michigan; Estados UnidosFil: Li, Jun Z.. University of Michigan; Estados UnidosFil: Camper, Sally. University of Michigan; Estados Unido

Aged PROP1 Deficient Dwarf Mice Maintain ACTH Production

Humans with PROP1 mutations have multiple pituitary hormone deficiencies (MPHD) that typically advance from growth insufficiency diagnosed in infancy to include more severe growth hormone (GH) deficiency and progressive reduction in other anterior pituitary hormones, eventually including adrenocorticotropic hormone (ACTH) deficiency and hypocortisolism. Congenital deficiencies of GH, prolactin, and thyroid stimulating hormone have been reported in the Prop1null (Prop1-/-) and the Ames dwarf (Prop1df/df) mouse models, but corticotroph and pituitary adrenal axis function have not been thoroughly investigated. Here we report that the C57BL6 background sensitizes mutants to a wasting phenotype that causes approximately one third to die precipitously between weaning and adulthood, while remaining homozygotes live with no signs of illness. The wasting phenotype is associated with severe hypoglycemia. Circulating ACTH and corticosterone levels are elevated in juvenile and aged Prop1 mutants, indicating activation of the pituitary-adrenal axis. Despite this, young adult Prop1 deficient mice are capable of responding to restraint stress with further elevation of ACTH and corticosterone. Low blood glucose, an expected side effect of GH deficiency, is likely responsible for the elevated corticosterone level. These studies suggest that the mouse model differs from the human patients who display progressive hormone loss and hypocortisolism

One-step generation of conditional and reversible gene knockouts

Loss-of-function studies are key for investigating gene function, and CRISPR technology has made genome editing widely accessible in model organisms and cells. However, conditional gene inactivation in diploid cells is still difficult to achieve. Here, we present CRISPR-FLIP, a strategy that provides an efficient, rapid and scalable method for biallelic conditional gene knockouts in diploid or aneuploid cells, such as pluripotent stem cells, 3D organoids and cell lines, by co-delivery of CRISPR-Cas9 and a universal conditional intronic cassette.A.A.-R. and K.T. are supported by the Medical Research Council, A.M. is supported by Wntsapp, Marie Curie ITN. J.F. and J.C.R.S. are supported by the Wellcome Trust. W.C.S. received core grant support from the Wellcome Trust to the Wellcome Trust Sanger Institute. B.-K.K. and R.C.M. are supported by a Sir Henry Dale Fellowship from the Wellcome Trust and the Royal Society (101241/Z/13/Z) and receive a core support grant from the Wellcome Trust and MRC to the WT–MRC Cambridge Stem Cell Institute

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping on the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C8197/A16565), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combination of the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative, grant 1 U19 CA148065-01 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.324

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe