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      Rapid Proteasomal Degradation of Mutant Proteins Is the Primary Mechanism Leading to Tumorigenesis in Patients With Missense AIP Mutations

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          The pathogenic effect of mutations in the aryl hydrocarbon receptor interacting protein ( AIP) gene ( AIPmuts) in pituitary adenomas is incompletely understood. We have identified the primary mechanism of loss of function for missense AIPmuts.


          This study sought to analyze the mechanism/speed of protein turnover of wild-type and missense AIP variants, correlating protein half-life with clinical parameters.

          Design and Setting:

          Half-life and protein–protein interaction experiments and cross-sectional analysis of AIPmut positive patients' data were performed in a clinical academic research institution.


          Data were obtained from our cohort of pituitary adenoma patients and literature-reported cases.


          Protein turnover of endogenous AIP in two cell lines and fifteen AIP variants overexpressed in HEK293 cells was analyzed via cycloheximide chase and proteasome inhibition. Glutathione-S-transferase pull-down and quantitative mass spectrometry identified proteins involved in AIP degradation; results were confirmed by coimmunoprecipitation and gene knockdown. Relevant clinical data was collected.

          Main Outcome Measures:

          Half-life of wild-type and mutant AIP proteins and its correlation with clinical parameters.


          Endogenous AIP half-life was similar in HEK293 and lymphoblastoid cells (43.5 and 32.7 h). AIP variants were divided into stable proteins (median, 77.7 h; interquartile range [IQR], 60.7–92.9 h), and those with short (median, 27 h; IQR, 21.6–28.7 h) or very short (median, 7.7 h; IQR, 5.6–10.5 h) half-life; proteasomal inhibition rescued the rapid degradation of mutant proteins. The experimental half-life significantly correlated with age at diagnosis of acromegaly/gigantism (r = 0.411 ; P = .002). The FBXO3-containing SKP1–CUL1–F-box protein complex was identified as the E3 ubiquitin-ligase recognizing AIP.


          AIP is a stable protein, driven to ubiquitination by the SKP1–CUL1–F-box protein complex. Enhanced proteasomal degradation is a novel pathogenic mechanism for AIPmuts, with direct implications for the phenotype.


          We determined that protein instability, leading to shortened protein half-life, is a novel pathogenic mechanism for mutations in the AIP gene with clinical significance for pituitary adenoma patients.

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          Most cited references 50

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          An integrated map of genetic variation from 1,092 human genomes

          Summary Through characterising the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help understand the genetic contribution to disease. We describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methodologies to integrate information across multiple algorithms and diverse data sources we provide a validated haplotype map of 38 million SNPs, 1.4 million indels and over 14 thousand larger deletions. We show that individuals from different populations carry different profiles of rare and common variants and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways and that each individual harbours hundreds of rare non-coding variants at conserved sites, such as transcription-factor-motif disrupting changes. This resource, which captures up to 98% of accessible SNPs at a frequency of 1% in populations of medical genetics focus, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.
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            Global quantification of mammalian gene expression control.

            Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here we simultaneously measured absolute mRNA and protein abundance and turnover by parallel metabolic pulse labelling for more than 5,000 genes in mammalian cells. Whereas mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Using a quantitative model we have obtained the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stability shared functional properties, indicating that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression provides a rich resource and helps to provide a greater understanding of the underlying design principles.
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              Guidelines for investigating causality of sequence variants in human disease

              The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.

                Author and article information

                J Clin Endocrinol Metab
                J. Clin. Endocrinol. Metab
                The Journal of Clinical Endocrinology and Metabolism
                Endocrine Society (Washington, DC )
                August 2016
                2 June 2016
                2 June 2016
                : 101
                : 8
                : 3144-3154
                Centre for Endocrinology (L.C.H.-R., F.M., G.T., D.T., N.R.-G., D.I., M.K.), and Centre for Biochemical Pharmacology (F.D.), William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University of London, London, EC1M 6BQ, United Kingdom; Genome Damage and Stability Centre (R.M.L.M., C.P.), University of Sussex, Brighton, Falmer, BN1 9RQ, United Kingdom
                Author notes
                Address all correspondence and requests for reprints to: Márta Korbonits, MD, PhD, Professor of Endocrinology and Metabolism, Centre for Endocrinology, William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, United Kingdom. E-mail: m.korbonits@ .

                This article has been published under the terms of the Creative Commons Attribution License (CC-BY;, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s).

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                Endocrinology & Diabetes


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