The syndrome of central hypothyroidism and macroorchidism: IGSF1 controls TRHR and FSHB expression by differential modulation of pituitary TGFβ and Activin pathways

IGSF1 (Immunoglobulin Superfamily 1) gene defects cause central hypothyroidism and macroorchidism. However, the pathogenic mechanisms of the disease remain unclear. Based on a patient with a full deletion of IGSF1 clinically followed from neonate to adulthood, we investigated a common pituitary origin for hypothyroidism and macroorchidism, and the role of IGSF1 as regulator of pituitary hormone secretion. The patient showed congenital central hypothyroidism with reduced TSH biopotency, over-secretion of FSH at neonatal minipuberty and macroorchidism from 3 years of age. His markedly elevated inhibin B was unable to inhibit FSH secretion, indicating a status of pituitary inhibin B resistance. We show here that IGSF1 is expressed both in thyrotropes and gonadotropes of the pituitary and in Leydig and germ cells in the testes, but at very low levels in Sertoli cells. Furthermore, IGSF1 stimulates transcription of the thyrotropin-releasing hormone receptor (TRHR) by negative modulation of the TGFβ1-Smad signaling pathway, and enhances the synthesis and biopotency of TSH, the hormone secreted by thyrotropes. By contrast, IGSF1 strongly down-regulates the activin-Smad pathway, leading to reduced expression of FSHB, the hormone secreted by gonadotropes. In conclusion, two relevant molecular mechanisms linked to central hypothyroidism and macroorchidism in IGSF1 deficiency are identified, revealing IGSF1 as an important regulator of TGFβ/Activin pathways in the pituitary

Log-Ratio and Parallel Factor Analysis: An Approach to Analyze Three-Way Compositional Data

For the exploratory analysis of three-way data, Parafac/Candecomp model (CP) is one of the most\ud applied models to study three-way arrays when the data are approximately trilinear. It is a three-way\ud generalization of PCA (Principal Component Analysis). CP model is a common name for low-rank\ud decomposition of three-way arrays. In this approach, the three-dimensional data are decomposed into a\ud series of factors, each relating to one of the three physical ways. When the data are particular ratios, as in\ud the case of compositional data, this model should consider the special problems that compositional data\ud pose. The principal aim of this paper is to describe how an analysis of compositional data by CP is possible\ud and how the results should be interpreted