Kallmann's syndrome (KS) is a genetically heterogeneous disorder consisting of congenital hypogonadotropic hypogonadism (CHH) with anosmia or hyposmia.Our objective was to compare the reproductive phenotypes of men harboring KAL1 and FGFR1/KAL2 mutations.We studied the endocrine features reflecting gonadotropic-testicular axis function in 39 men; 21 had mutations in KAL1 and 18 in FGFR1/KAL2, but none had additional mutations in PROK-2 or PROKR-2 genes.Puberty failed to occur in the patients with KAL1 mutations, all of whom had complete CHH. Three patients with FGFR1/KAL2 mutations had normal puberty, were eugonadal, and had normal testosterone and gonadotropin levels. Cryptorchidism was more frequent (14 of 21 vs. 3 of 15; P<00.1) and testicular volume (2.4+/-1.1 vs. 5.4+/-2.4 ml; P<0.001) was smaller in CHH subjects with KAL1 mutations than in subjects with FGFR1/KAL2 mutations. The mean basal plasma FSH level (0.72+/-0.47 vs. 1.48+/-0.62 IU/liter; P<0.05), serum inhibin B level (19.3+/-10.6 vs. 39.5+/-19.3 pg/ml; P<0.005), basal LH plasma level (0.57+/-0.54 vs. 1.0+/-0.6 IU/liter; P<0.01), and GnRH-stimulated LH plasma level (1.2+/-1.0 vs. 4.1+/-3.5 IU/liter; P<0.01) were significantly lower in the subjects with KAL1 mutations. LH pulsatility was studied in 13 CHH subjects with KAL1 mutations and seven subjects with FGFR1/KAL2 mutations; LH secretion was nonpulsatile in all the subjects, but mean LH levels were lower in those with KAL1 mutations.KAL1 mutations result in a more severe reproductive phenotype than FGFR1/KAL2 mutations. The latter are associated with a broader spectrum of pubertal development and with less severe impairment of gonadotropin secretion.
Improvements in diagnostic imaging techniques during the past several years have led to an increasing recognition of asymptomatic lesions in the pituitary. The management of these “pituitary incidentalomas” is controversial. Some lesions may increase in size, causing impaired pituitary hormone production or compressed optic chiasm, whereas others will remain unchanged in size and will never produce tumoral or hormonal symptoms. The type of initial endocrinological assessment and the required frequency and length of follow-up need to be carefully determined, taking cost-effectiveness into account. In this setting, it is crucial to obtain precise information about the natural history of each type of pituitary lesion. Incidental discovery of an intrapituitary cyst is frequent and needs careful examination of magnetic resonance (MR) images to differentiate between craniopharyngiomas (in which association with solid component and calcification is more likely) and Rathkes cleft cyst (in which cyst size is generally less than 20 mm and which is less frequently associated with hypopituitarism on hormonal evaluation). Incidental microadenomas (≤10 mm) raise the issue of the importance of the hormonal evaluation, given the high prevalence of lesions less than 10 mm in size and the rarity of hormone secretion by these microincidentalomas. If a careful history and physical examination rules out acromegaly and Cushings disease, the hormonal work-up can probably be limited to prolactin measurement for diagnosis of prolactinoma. Thereafter, given the natural history of these nonsecreting microadenomas and the fact that they very rarely increase in size, a “wait-and-see” attitude may be recommended. The incidental discovery of a macroadenoma (> 10 mm) requires an extensive work-up. If the lesion compresses the optic nerves, surgical removal is obviously indicated. If the lesion causes hypersecretion of prolactin, growth hormone or corticotropin, patients may be offered tumor-subtype directed therapy. On the contrary, if no hormonal hypersecretion (or secretion limited to gonadotropins and/or their subunits) is found, and if the macroadenoma is some distance from the optic chiasm, routine surgical removal of the tumor may not be necessary. Indeed, in prospective studies of incidental macroadenomas, only 25% increased in size and less than 5% required an operation. If expectant management is elected, yearly MRI surveillance may be recommended, at least during the first 5 years. Another frequent incidentaloma is the normal pituitary hypertrophy found in young women. Careful examination of MR images may help to distinguish it from pituitary tumors and infiltrating lesions and to avoid unnecessary surgery.
In the human adrenal gland, serotonin (5‐HT) stimulates cortisol production through a paracrine mechanism involving 5‐HT4 receptors positively‐coupled to adenylyl cyclase. A hyperresponsiveness of adrenocortical tissue to 5‐HT has also been described in several cases of ACTH‐independent bilateral macronodular adrenal hyperplasias (AIMAHs) and adenomas causing Cushing's syndrome. In the present study, we report two cases of cortisol‐producing adrenocortical lesions, i.e. one AIMAH (case 1) and one adenoma (case 2), whose secretory activity was inhibited in vitro by 5‐HT. The potencies (pIC50) and efficacies (Emax) of 5‐HT to inhibit cortisol secretion were 8.2 ± 0.4 and − 64.1% ± 7.5% in case 1, and 9.2 ± 0.5 and − 32.3% ± 3.8% in case 2. The specific 5‐HT4 antagonist GR 113808 failed to influence the 5‐HT‐induced decrease in cortisol production by the two tissues, indicating that the paradoxical inhibitory effect of 5‐HT could not be accounted for by activation of eutopic 5‐HT4 receptors. These results suggest that the tissues expressed aberrant 5‐HT receptors. In conclusion, the present study provides the first evidence for an inhibitory effect of 5‐HT on cortisol secretion in adrenocortical lesions causing Cushing's syndrome. Our data also suggest that expression of illegitimate membrane receptors by cortisol‐producing adrenal hyperplasias and/or adenomas may convert a paracrine stimulatory factor into an inhibitory signal.
The measurement of parathyroid hormone(PTH) in situ (PTHis) by fine-needle aspiration (FNA) has been proposed as a tool to preoperatively help localize parathyroid glands detected on ultrasound. However, the accuracy of PTHis is highly variable according to the few available studies.We aimed to develop and validate the PTHis procedure and assessed the performance of PTHis in a large series of patients with hyperparathyroidism and/or undetermined cervical lesions.The technique set-up consisted of PTHis measurement in thyroid samples from patients with thyroid nodules and patients with high circulating PTH levels (tertiary hyperparathyroidism). Consecutive patients were recruited at one tertiary referral centre from 2017 to 2020 and submitted to ultrasound-guided FNA-PTHis determination.During the method set-up, we obtained undetectable PTHis levels in all non-parathyroid tissues after sample dilutions. PTHis was higher in patients with hyperparathyroidism (n = 145; 1817 ± 3739 ng/L; range: <4.6-31 140) than in those with thyroid or undetermined cervical lesions (n= 34; <4.6 ng/mL; P < 0.0001). When evaluating PTHis performance in histologically proven samples (158 lesions from 121 patients), PTHis was detectable in 85/97 parathyroid lesions (87%; range: 22-31;140 ng/L) and undetectable in all non-parathyroid lesions (n = 61; P < 0.0001). The specificity and positive predictive value were 100%, and the sensitivity was 87.6%. False-negative lesions (n= 12) were smaller (9.4 ± 5.9 mm) and more often consisted of hyperplasias (75%) than true-positive lesions (16.1 ± 8.4 mm and 33%, P = 0.009 and P = 0.0089, respectively). The method was safe and well tolerated. Four educational cases are also provided.PTHis determination is a safe and well-tolerated procedure that enhances the specificity of ultrasound-detected lesions. If accurately set-up, it confirms the parathyroid origin of uncharacterized cervical lesions.
Research Article13 April 2016Open Access Source DataTransparent process IGSF10 mutations dysregulate gonadotropin-releasing hormone neuronal migration resulting in delayed puberty Sasha R Howard Sasha R Howard Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Leonardo Guasti Leonardo Guasti Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Gerard Ruiz-Babot Gerard Ruiz-Babot Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Alessandra Mancini Alessandra Mancini Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Alessia David Alessia David Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK Search for more papers by this author Helen L Storr Helen L Storr Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Lousie A Metherell Lousie A Metherell Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Michael JE Sternberg Michael JE Sternberg Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK Search for more papers by this author Claudia P Cabrera Claudia P Cabrera Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK Search for more papers by this author Helen R Warren Helen R Warren NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University of London, London, UK Search for more papers by this author Michael R Barnes Michael R Barnes Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK Search for more papers by this author Richard Quinton Richard Quinton Institute of Genetic Medicine University of Newcastle-upon-Tyne, Newcastle-upon-Tyne, UK Search for more papers by this author Nicolas de Roux Nicolas de Roux Unité Mixte de Recherche 1141, Institut National de la Santé et de la Recherche Médicale, Paris, France Université Paris Diderot, Sorbonne Paris Cité, Hôpital Robert Debré, Paris, France Laboratoire de Biochimie, Assistance Publique-Hôpitaux de Paris, Hôpital Robert Debré, Paris, France Search for more papers by this author Jacques Young Jacques Young Univ Paris-Sud, Le Kremlin Bicêtre, France INSERM UMR-1185, Le Kremlin Bicêtre, France Assistance Publique-Hôpitaux de Paris, Bicêtre Hospital, Le Kremlin-Bicêtre, France Department of Reproductive Endocrinology, Bicêtre Hospital, Le Kremlin-Bicêtre, France Search for more papers by this author Anne Guiochon-Mantel Anne Guiochon-Mantel Univ Paris-Sud, Le Kremlin Bicêtre, France INSERM UMR-1185, Le Kremlin Bicêtre, France Assistance Publique-Hôpitaux de Paris, Bicêtre Hospital, Le Kremlin-Bicêtre, France Search for more papers by this author Karoliina Wehkalampi Karoliina Wehkalampi Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland Search for more papers by this author Valentina André Valentina André Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy Search for more papers by this author Yoav Gothilf Yoav Gothilf Department of Neurobiology, The George S. Wise Faculty of Life Sciences and Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv, Israel Search for more papers by this author Anna Cariboni Anna Cariboni Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy Institute of Ophthalmology, University College London (UCL), London, UK Search for more papers by this author Leo Dunkel Corresponding Author Leo Dunkel orcid.org/0000-0003-4008-8521 Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Sasha R Howard Sasha R Howard Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Leonardo Guasti Leonardo Guasti Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Gerard Ruiz-Babot Gerard Ruiz-Babot Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Alessandra Mancini Alessandra Mancini Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Alessia David Alessia David Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK Search for more papers by this author Helen L Storr Helen L Storr Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Lousie A Metherell Lousie A Metherell Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Michael JE Sternberg Michael JE Sternberg Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK Search for more papers by this author Claudia P Cabrera Claudia P Cabrera Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK Search for more papers by this author Helen R Warren Helen R Warren NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University of London, London, UK Search for more papers by this author Michael R Barnes Michael R Barnes Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK Search for more papers by this author Richard Quinton Richard Quinton Institute of Genetic Medicine University of Newcastle-upon-Tyne, Newcastle-upon-Tyne, UK Search for more papers by this author Nicolas de Roux Nicolas de Roux Unité Mixte de Recherche 1141, Institut National de la Santé et de la Recherche Médicale, Paris, France Université Paris Diderot, Sorbonne Paris Cité, Hôpital Robert Debré, Paris, France Laboratoire de Biochimie, Assistance Publique-Hôpitaux de Paris, Hôpital Robert Debré, Paris, France Search for more papers by this author Jacques Young Jacques Young Univ Paris-Sud, Le Kremlin Bicêtre, France INSERM UMR-1185, Le Kremlin Bicêtre, France Assistance Publique-Hôpitaux de Paris, Bicêtre Hospital, Le Kremlin-Bicêtre, France Department of Reproductive Endocrinology, Bicêtre Hospital, Le Kremlin-Bicêtre, France Search for more papers by this author Anne Guiochon-Mantel Anne Guiochon-Mantel Univ Paris-Sud, Le Kremlin Bicêtre, France INSERM UMR-1185, Le Kremlin Bicêtre, France Assistance Publique-Hôpitaux de Paris, Bicêtre Hospital, Le Kremlin-Bicêtre, France Search for more papers by this author Karoliina Wehkalampi Karoliina Wehkalampi Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland Search for more papers by this author Valentina André Valentina André Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy Search for more papers by this author Yoav Gothilf Yoav Gothilf Department of Neurobiology, The George S. Wise Faculty of Life Sciences and Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv, Israel Search for more papers by this author Anna Cariboni Anna Cariboni Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy Institute of Ophthalmology, University College London (UCL), London, UK Search for more papers by this author Leo Dunkel Corresponding Author Leo Dunkel orcid.org/0000-0003-4008-8521 Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK Search for more papers by this author Author Information Sasha R Howard1,‡, Leonardo Guasti1,‡, Gerard Ruiz-Babot1, Alessandra Mancini1, Alessia David2, Helen L Storr1, Lousie A Metherell1, Michael JE Sternberg2, Claudia P Cabrera3,4, Helen R Warren4,5, Michael R Barnes3,4, Richard Quinton6, Nicolas Roux7,8,9, Jacques Young10,11,12,13, Anne Guiochon-Mantel10,11,12, Karoliina Wehkalampi14, Valentina André15, Yoav Gothilf16, Anna Cariboni15,17 and Leo Dunkel 1 1Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK 2Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, UK 3Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK 4NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, UK 5Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University of London, London, UK 6Institute of Genetic Medicine University of Newcastle-upon-Tyne, Newcastle-upon-Tyne, UK 7Unité Mixte de Recherche 1141, Institut National de la Santé et de la Recherche Médicale, Paris, France 8Université Paris Diderot, Sorbonne Paris Cité, Hôpital Robert Debré, Paris, France 9Laboratoire de Biochimie, Assistance Publique-Hôpitaux de Paris, Hôpital Robert Debré, Paris, France 10Univ Paris-Sud, Le Kremlin Bicêtre, France 11INSERM UMR-1185, Le Kremlin Bicêtre, France 12Assistance Publique-Hôpitaux de Paris, Bicêtre Hospital, Le Kremlin-Bicêtre, France 13Department of Reproductive Endocrinology, Bicêtre Hospital, Le Kremlin-Bicêtre, France 14Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland 15Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy 16Department of Neurobiology, The George S. Wise Faculty of Life Sciences and Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv, Israel 17Institute of Ophthalmology, University College London (UCL), London, UK ‡These authors contributed equally to this work *Corresponding author. Tel: +44 207 882 6235; Fax: +44 207 882 6197; E-mail: [email protected] EMBO Mol Med (2016)8:626-642https://doi.org/10.15252/emmm.201606250 Correction added on 1 June 2016: In the last sentence of the abstract the word "casual" was corrected to "causal". PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Early or late pubertal onset affects up to 5% of adolescents and is associated with adverse health and psychosocial outcomes. Self-limited delayed puberty (DP) segregates predominantly in an autosomal dominant pattern, but the underlying genetic background is unknown. Using exome and candidate gene sequencing, we have identified rare mutations in IGSF10 in 6 unrelated families, which resulted in intracellular retention with failure in the secretion of mutant proteins. IGSF10 mRNA was strongly expressed in embryonic nasal mesenchyme, during gonadotropin-releasing hormone (GnRH) neuronal migration to the hypothalamus. IGSF10 knockdown caused a reduced migration of immature GnRH neurons in vitro, and perturbed migration and extension of GnRH neurons in a gnrh3:EGFP zebrafish model. Additionally, loss-of-function mutations in IGSF10 were identified in hypothalamic amenorrhea patients. Our evidence strongly suggests that mutations in IGSF10 cause DP in humans, and points to a common genetic basis for conditions of functional hypogonadotropic hypogonadism (HH). While dysregulation of GnRH neuronal migration is known to cause permanent HH, this is the first time that this has been demonstrated as a causal mechanism in DP.2 Synopsis Self-limited delayed puberty (DP) has strong familial inheritance, but the underlying genetic determinants are unknown. IGSF10 deficiency is found to affect embryonic GnRH neuronal migration and results in DP in humans. Pathogenic mutations in IGSF10 are found in patients with self-limited delayed puberty. IGSF10 is a gene of previously unclear function with no known human mutations. IGSF10 is expressed within the nasal mesenchyme during fetal development, in a pattern similar to known chemokines that direct migrational GnRH neurons to the hypothalamus. Knockdown of IGSF10 led to a reduced migration of GnRH neurons in vitro and in a transgenic zebrafish model. IGSF10 loss-of-function mutations were also identified in patients with hypothalamic amenorrhea, suggesting an overlapping genetic and mechanistic basis between different types of functional hypogonadotropic hypogonadism, including DP and hypothalamic amenorrhea. Introduction Puberty is the critical developmental stage during which reproductive capacity is attained. The onset of puberty is driven by the reactivation of the hypothalamic–pituitary–gonadal (HPG) axis after relative quiescence during childhood, with an increase in the pulsatile release of gonadotropin-releasing hormone (GnRH). While the timing of pubertal onset varies within and between different populations, it is a highly heritable trait, suggesting strong genetic determinants (Wehkalampi et al, 2008b). Previous epidemiological studies estimate that 60–80% of the variation in pubertal onset is under genetic regulation (Parent et al, 2003; Gajdos et al, 2009; Morris et al, 2011). However, despite this strong heritability, little is known about the genetic control of human puberty (Palmert & Dunkel, 2012). Abnormal pubertal timing affects up to 5% of adolescents and is associated with adverse health and psychosocial outcomes (He et al, 2010; Ritte et al, 2012; Widen et al, 2012; Day et al, 2015). Our lack of understanding of the factors that trigger pubertal onset is a barrier both to diagnosis and to the management of patients with pubertal disorders, and also hampers attempts to comprehend the population-wide trend toward an earlier age of pubertal onset in the developed world (DiVall & Radovick, 2008; Mouritsen et al, 2010). Attempts to identify key genetic regulators of the timing of puberty have ranged from genome-wide association studies of age at menarche (Ong et al, 2009; Elks et al, 2010) to next-generation sequencing approaches. Together, these studies suggest that pubertal timing in the general population may be controlled by hundreds of genetic regulators, while loss-of-function mutations in one gene can produce the phenotypic features of complete GnRH deficiency. In patients with hypogonadotropic hypogonadism (HH), up to 30 separate genes resulting in severely delayed or absent puberty have been identified (Bianco & Kaiser, 2009; Gajdos et al, 2009). These genes control GnRH neuronal migration and differentiation, GnRH secretion, or its downstream pathways (Karges & de Roux, 2005; Beate et al, 2012). Evidence for digenic inheritance of HH, with synergistic effects of two gene defects together producing a more severe phenotype, has also been established (Pitteloud et al, 2007). At the extreme end of the normal range of pubertal onset, self-limited delayed puberty (DP) is a common condition (Sedlmeyer, 2002a). Self-limited DP is defined as the absence of testicular enlargement in boys or breast development in girls at an age that is 2–2.5 standard deviations (SD) later than the population mean (Palmert & Dunkel, 2012). DP segregates within families, with the majority of families displaying an autosomal dominant pattern of inheritance (Sedlmeyer, 2002b; Wehkalampi et al, 2008b). Recently, variants in HH genes have been identified in some cases of self-limited DP (Zhu et al, 2015). However, in the majority of patients with DP, the neuroendocrine pathophysiology and its genetic regulation remain unclear. Our large, well-phenotyped cohort with self-limited DP from the relatively homogenous Finnish population provides invaluable familial data with which to investigate this question (Kristiansson et al, 2008; Wehkalampi et al, 2008b). We hypothesized that such families will be enriched for low-frequency, high- or moderate-effect alleles that are amenable to discovery through exome sequencing. Results Rare, potentially pathogenic variants in the IGSF10 gene found in 10 families with DP Initial whole exome sequencing performed in the 18 most extensive families from our cohort (111 individuals: a total of 76 individuals with DP, male = 53 and female = 23; and 35 controls, male = 13 and female = 22) identified 2,474,145 variants after quality control (Fig 1). Following filtering through our in-house pipeline to identify rare, predicted deleterious mutations, segregating with trait in an autosomal dominant inheritance pattern in multiple families and with potential biological relevance, 28 top candidate genes were identified. These 28 genes were then put forward for targeted resequencing in a further 42 families from the same cohort (178 individuals with DP and 110 controls, Fig 1), and the filtered results were analyzed by applying statistical thresholds for enrichment of rare, pathogenic variants in our cohort via rare variant burden testing with multiple comparison adjustment (Benjamini et al, 2001). Figure 1. Flowchart of exome sequencing filtering outcomesWhole exome sequencing was initially performed on DNA extracted from the peripheral blood leukocytes of 111 individuals from the 18 most extensive families from our cohort (76 with DP and 35 controls). The exome sequences were aligned to the UCSC hg19 reference genome. Picard tools and the genome analysis toolkit were used to mark PCR duplicates, realign around indels, recalibrate quality scores, and call variants. Variants were analyzed further and filtered for potential causal variants using filters for quality control, predicted functional annotation, minor allele frequency (MAF), segregation with trait, variants in multiple families, and biological relevance (see Materials and Methods and Appendix Table S1 for further information on filtering criteria). Targeted exome sequencing using a Fluidigm array of 28 candidate genes identified post-filtering was then performed in a further 42 families from the same cohort (288 individuals, 178 with DP and 110 controls). Variants post-targeted resequencing were filtered using the same criteria as the whole exome sequencing data. Rare variant burden testing was performed for all genes selected for targeted resequencing, in order to rank candidate genes post-targeted resequencing. A multiple comparison adjustment was applied to the set of 28 P-values post hoc (Benjamini et al, 2001). Screening of 100 further cohort controls was via conventional Sanger sequencing. Functional annotation of the variants as described elsewhere in Materials and Methods. DP, delayed puberty. *data unpublished. Download figure Download PowerPoint The candidate gene, immunoglobulin superfamily member 10, IGSF10 (ENSG00000152580, gene identification number 285313), was identified after rare variant burden testing (adjusted P-value = 0.020) and screening of a further 100 controls from our cohort (Fig 1). Four genes had initially passed the P < 0.025 threshold after rare variant burden testing, and potentially pathogenic variants in these genes were further analyzed to determine their presence in controls from our cohort and for segregation with trait (Appendix Table S1 and Fig 1). Following this analysis, IGSF10 was found to be the most promising candidate, with four potentially pathogenic variants in 10 probands from our cohort. The other 9 of 13 rare and potentially pathogenic variants that had been identified in IGSF10 from targeted exome sequencing results were discarded in our post-sequencing analysis, as they were present in multiple controls from our cohort. Four variants in IGSF10 identified in 31 individuals from 10 families (NM_178822.4: c.467G>T (rs138756085) p.Arg156Leu, NM_178822.4: c.481G>A (rs114161831) p.Glu161Lys, NM_178822.4: c.6791A>G p.Glu2264Gly and NM_178822.4: c.7840G>A (rs112889898) p.Asp2614Asn) were found in ≤ 1 control subject (Table 1, Figs 2A and EV1). Table 1. Minor allele frequency of IGSF10 variants in study population and control cohorts Nucleotide change Amino acid change Exon MAF from DP patients (%) (n = 215) MAF from controls (%) (n = 210) MAF (%) Finnish/European/All c.467G>T p.Arg156Leu 3 2.8 0 0/0.5/0.4 c.481G>A p.Glu161Lys 3 5.6 0.5 2.0/0.7/1.0 c.6791A>G p.Glu2264Gly 6 0.5 0 not seen c.7840G>A p.Asp2614Asn 6 3.3 0 0/0.8/0.8 Minor allele frequency (MAF) data for the Finnish population were retrieved from The Sequencing Initiative Suomi (The SISu project) (http://www.sisuproject.fi/, release 3.0, accessed September 2015). European and other MAF data were retrieved from the ExAC Browser (Exome Aggregation Consortium (ExAC), Cambridge, MA: http://exac.broadinstitute.org, accessed September 2015). Figure 2. Pedigrees of the families with N-terminal IGSF10 mutations with typical growth charts Squares indicate male family members, and circles female family members. Black symbols represent clinically affected, gray symbols represent unknown phenotype, and clear symbols represent unaffected individuals. The arrow with "P" indicates the proband in each family and "us" indicates unsequenced due to the lack of DNA from that individual. The mutation in each family is given next to the family number; a horizontal black line above an individual's symbol indicates that they are heterozygous for that mutation as identified by either whole exome sequencing (family 3 and 4) or Fluidigm array (family 1, 2, 5, and 6), and verified by Sanger sequencing. Growth charts of 2 probands each showing typical growth patterns of self-limited DP, without compromised linear growth before puberty. Solid horizontal black lines connect green dots representing bone age to red dots at the equivalent chronological age. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Pedigrees of the families with two Further Potentially Pathogenic IGSF10 mutationsSquares indicate male family members; circles female family members. Black symbols represent clinically affected, gray symbols represent unknown phenotype, and clear symbols represent unaffected individuals. The arrow with "P" indicates the proband in each family, and "us" indicates unsequenced due to the lack of DNA from that individual. The mutation in each family is given next to the family number; a horizontal black line above an individual's symbol indicates they are heterozygous for that mutation as confirmed by either whole exome sequencing or Fluidigm array, and verified by Sanger sequencing. Download figure Download PowerPoint Although three of the four variants were present in public databases, they were highly enriched in our cohort (Table 1). Analysis of self-limited DP families is complicated by the fact that this phenotype represents the tail of a normally distributed trait within the population, so it is anticipated that variants that govern the inheritance of this condition will also be present in the general population at a low level. Indeed, it is expected that up to 5% of the individuals sequenced in population databases will have abnormal pubertal timing, either early or delayed. Thus, the absence of these variants in population databases cannot be used as an exclusion criterion, and instead, a comparison of prevalence of such variants must be made to identify those that are enriched in patients compared to the ethnically matched general population. All four IGSF10 variants are heterozygous missense variants predicted to be deleterious, damaging, or possibly damaging by ≥ 3/5 prediction tools (Table 2). All variants affect amino acids that are highly conserved among homologues, as revealed by PhyloP or GERP score, and multiple sequence alignment (Table 2 and Appendix Fig S1). Table 2. Prediction of IGSF10 variants according to web-based prediction software programs and conservation across species AA Change dbSNP137 ID PhyloP (Pollard et al, 2010) Pred SIFT (Kumar et al, 2009) Pred PolyPhen-2 (Adzhubei et al, 2010) Pred LRT (Chun & Fay, 2009) Pred MutationTaster (Schwarz et al, 2014) Pred FATHMM (Shihab et al, 2013) Pred GERP (Cooper et al, 2005) ++ p.R156L rs138756085 C D D D N D 5.18 p.E161K rs114161831 C D D D D T 4.94 p.E2264G n/a C D P N D T 3.71 p.D2614N rs112889898 C D D D D T 5.24 C, conserved; D, deleterious, disease causing or damaging; P, possibly damaging; N, neutral; T, tolerated. Families with IGSF10 variants display autosomal dominant inheritance and classical self-limited DP Two N-terminal variants in IGSF10 (p.Arg156Leu and p.Glu161Lys) were identified in 20 individuals from six families (Figs 2A and 3A). Perfect segregation with the expected autosomal dominant pattern of inheritance was seen in all but one individual (family3.III.3), who was found to have DP without carrying the variant. Of note given the known association between BMI and pubertal timing, this individual was very lean (weight 13% below median weight for height) at 13 years (Kaplowitz, 2008). The two C-terminal variants (p.Glu2264Gly and p.Asp2614Asn), identified in 11 individuals from four families, in contrast demonstrated incomplete penetrance in family 7 and a possible de novo mutation in family 10 (Fig EV1). Figure 3. IGSF10 protein structure and position of N-terminal mutations IGSF10 domains and N-terminal mutations identified in the study. Region I contains leucine-rich repeats (LRR) 1-7 flanked by a LRR N-terminal (LRR Nt) and C-terminal (LRR Ct) cap. Region II is structurally disordered. Region III contains two Ig-like domains (Ig). Region IV is structurally disordered. Region V contains 10 Ig-like domains (Ig). Protein tertiary structure as predicted by in silico analysis. Biological consequences of the 2 identified N-terminal mutations. Both WT and mutant N-terminal protein fragments (p.Arg156Leu and p.Glu161Lys) were expressed in HEK293 cells as demonstrated by Western blotting. The GFP-tagged protein products of both were not detected in the conditioned media of mammalian cells, as compared to wild type (WT), and appear to be retained in the intracellular compartment (mean ± SEM; n = 3). Ponceau red staining is shown to demonstrate equal protein loading for conditioned media. UT, untransfected negative control; nd, not detected; two-tailed t-test, n = 3 for each group, *P = 0.01094 (WT vs. p.Arg156Leu) and P = 0.04408 (WT vs. p.Glu161Lys). It has to date not been possible to test cytoplasmic retention for the two C-terminal mutations due to difficulty expressing the full-length or C-terminal protein fragment in mammalian cells. Source data are available online for this figure. Source Data for Figure 3 [emmm201606250-sup-0003-SDataFig3C.tiff] Download figure Download PowerPoint The affected individuals from these 10 families have classical clinical and biochemical features of "simple" DP, with delayed onset of Tanner stage 2 and delayed peak height velocity (Table 3). All probands had low gonadotropins with low or undetectable sex steroids and delayed bone age at presentation. In addition, these 10 probands displayed a t
L'axe hypothalamo-hypophyso-surrenalien est un determinant majeur de la reponse au stress. Dans une etude prospective conduite entre 1991 et 1995 dans deux hopitaux universitaires francais, 189 patients presentant un choc septique ont ete inclus. Un test au Synacthene Immediat (0,250 mg) avec mesure du cortisol 30 et 60 minutes apres a ete effectue a l'arrivee en Reanimation. La mortalite a 1 mois a ete correlee a la cortisolemie basale et apres synacthene. 58 % des patients sont decedes dans ce delai : le temps moyen entre l'admission et le deces etait de 17 jours. En analyse multivariee, les predicteurs du deces etaient : un score de McCabe superieur a 0, un score de defaillance multiviscerale superieur a 2, un taux de lactate superieur a 2,8, un rapport PO2/fraction d'oxygene inspire ne depassant pas 160 mmHg, mais egalement une cortisolemie basale superieure a 34 µg/dl et un delta maximal entre le cortisol basal et le cortisol apres synacthene, inferieur a 9 µg/dl. Trois groupes ont ete distingues. Le test au Synacthene semble donc avoir une valeur pronostique interessante lors d'un choc septique. Djillali A et al. 2000. 3-level prognostic classification in septic shock based on cortisol levels and cortisol responses to corticotropin. JAMA 283 : 1038-1045.
