Cushing's disease, also known as adrenocorticotropic hormone (ACTH)-secreting pituitary adenomas (PAs) that cause excess cortisol production, accounts for up to 85% of corticotrophin-dependent Cushing's syndrome cases. However, the genetic alterations in this disease are unclear. Here, we performed whole-exome sequencing of DNA derived from 12 ACTH-secreting PAs and matched blood samples, which revealed three types of somatic mutations in a candidate gene, USP8 (encoding ubiquitin-specific protease 8), exclusively in exon 14 in 8 of 12 ACTH-secreting PAs. We further evaluated somatic USP8 mutations in additional 258 PAs by Sanger sequencing. Targeted sequencing further identified a total of 17 types of USP8 variants in 67 of 108 ACTH-secreting PAs (62.04%). However, none of these mutations was detected in other types of PAs (n = 150). These mutations aggregate within the 14-3-3 binding motif of USP8 and disrupt the interaction between USP8 and 14-3-3 protein, resulting in an elevated capacity to protect EGFR from lysosomal degradation. Accordingly, PAs with mutated USP8 display a higher incidence of EGFR expression, elevated EGFR protein abundance and mRNA expression levels of POMC, which encodes the precursor of ACTH. PAs with mutated USP8 are significantly smaller in size and have higher ACTH production than wild-type PAs. In surgically resected primary USP8-mutated tumor cells, USP8 knockdown or blocking EGFR effectively attenuates ACTH secretion. Taken together, somatic gain-of-function USP8 mutations are common and contribute to ACTH overproduction in Cushing's disease. Inhibition of USP8 or EGFR is promising for treating USP8-mutated corticotrophin adenoma. Our study highlights the potentially functional mutated gene in Cushing's disease and provides insights into the therapeutics of this disease.
Establishing baseline MRI biomarkers for normal brain aging is significant and valuable for separating normal changes in the brain structure and functioning from different neurological diseases. In this paper for the first time we have simultaneously measured a variety of tissue specific contributions defining R2* relaxation of the gradient recalled echo (GRE) MRI signal in human brains of healthy adults (ages 22 to 74 years) and related these measurements to tissue structural and functional properties. This was accomplished by separating tissue (R2t*) and extravascular BOLD contributions to the total tissue specific GRE MRI signal decay (R2*) using an advanced version of previously developed Gradient Echo Plural Contrast Imaging (GEPCI) approach and the acquisition and post-processing methods that allowed the minimization of artifacts related to macroscopic magnetic field inhomogeneities, and physiological fluctuations. Our data (20 healthy subjects) show that in most cortical regions R2t* increases with age while tissue hemodynamic parameters, i.e. relative oxygen extraction fraction (OEFrel), deoxygenated cerebral blood volume (dCBV) and tissue concentration of deoxyhemoglobin (Cdeoxy) remain practically constant. We also found the important correlations characterizing the relationships between brain structural and hemodynamic properties in different brain regions. Specifically, thicker cortical regions have lower R2t* and these regions have lower OEF. The comparison between GEPCI-derived tissue specific structural and functional metrics and literature information suggests that (a) regions in a brain characterized by higher R2t* contain higher concentration of neurons with less developed cellular processes (dendrites, spines, etc.), (b) regions in a brain characterized by lower R2t* represent regions with lower concentration of neurons but more developed cellular processes, (c) the age-related increases in the cortical R2t* mostly reflect the age-related increases in the cellular packing density. The baseline GEPCI-based biomarkers obtain herein could serve to help distinguishing age-related changes in brain cellular and hemodynamic properties from changes which occur due to the neurodegenerative diseases.
The meta-QTL and candidate genes will facilitate the elucidation of molecular bases underlying agriculturally important traits and open new avenues for functional markers development and elite alleles introgression in maize breeding program. A large number of QTLs attributed to grain productivity and other agriculturally important traits have been identified and deposited in public repositories. The integration of fruitful QTL becomes a major issue in current plant genomics. To this end, we first collected QTL for six agriculturally important traits in maize, including yield, plant height, ear height, leaf angle, stay-green, and maize rough dwarf disease resistance. The meta-analysis method was then employed to retrieve 113 meta-QTL. Additionally, we also isolated candidate genes for target traits by the bioinformatic technique. Several candidates, including some well-characterized genes, GA3ox2 for plant height, lg1 and lg4 for leaf angle, zfl1 and zfl2 for flowering time, were co-localized with established meta-QTL intervals. Intriguingly, in a relatively narrow meta-QTL region, the maize ortholog of rice yield-related gene GW8/OsSPL16 was believed to be a candidate for yield. Leveraging results presented in this study will provide further insights into the genetic architecture of maize agronomic traits. Moreover, the meta-QTL and candidate genes reported here could be harnessed for the enhancement of stress tolerance and yield performance in maize and translation to other crops.
Background Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals. Methods Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer’s Disease Research Center at Washington University in St. Louis. Cognitive status was operationalized with the Clinical Dementia Rating (CDR) scale. The participants, assessed as cognitively normal (CDR = 0; n = 23) or with mild AD dementia (CDR = 0.5 or 1; n = 11) underwent GEPCI MRI, a collection of cognitive performance tests and CSF amyloid (Aβ) biomarker Aβ42. A subset of 19 participants also underwent PET PiB studies to assess their brain Aβ burden. According to the Aβ status, cognitively normal participants were divided into normal (Aβ negative; n = 13) and preclinical (Aβ positive; n = 10) groups. Results GEPCI quantitative measurements demonstrated significant differences between all the groups: normal and preclinical, normal and mild AD, and preclinical and mild AD. GEPCI quantitative metrics characterizing tissue cellular integrity in the hippocampus demonstrated much stronger correlations with psychometric tests than the hippocampal atrophy. Importantly, GEPCI-determined changes in the hippocampal tissue cellular integrity were detected even in the hippocampal areas not affected by the atrophy. Our studies also uncovered strong correlations between GEPCI brain tissue metrics and beta-amyloid (Aβ) burden defined by positron emission tomography (PET) - the current in vivo gold standard for detection of cortical Aβ, thus supporting GEPCI as a potential surrogate marker for Aβ imaging – a known biomarker of early AD. Remarkably, the data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in some areas of medial temporal lobe (e.g. parahippocampal cortex), where Aβ accumulation is relatively low. Conclusion We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies.
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