scholarly journals Assessment of Molecular Measures in Non-FXTAS Male Premutation Carriers

2018 ◽  
Vol 9 ◽  
Author(s):  
Reem R. Al Olaby ◽  
Hiu-Tung Tang ◽  
Blythe Durbin-Johnson ◽  
Andrea Schneider ◽  
David Hessl ◽  
...  
Keyword(s):  
Author(s):  
Marissa Robinson ◽  
Jessica Klusek ◽  
Michele D. Poe ◽  
Deborah D. Hatton ◽  
Jane E. Roberts

Abstract Effortful control, or the ability to suppress a dominant response to perform a subdominant response, is an early-emerging temperament trait that is linked with positive social-emotional development. Fragile X syndrome (FXS) is a single-gene disorder characterized by hallmark regulatory impairments, suggesting diminished effortful control. This study compared the development of effortful control in preschool boys with FXS (n = 97) and typical development (n = 32). Unlike their typical peers, the boys with FXS did not exhibit growth in effortful control over time, which could not be accounted for by adaptive impairments, FMR1 molecular measures, or autism symptoms. These results contribute to our understanding of the childhood phenotype of FXS that may be linked to the poor social-emotional outcomes seen in this group.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e21048-e21048
Author(s):  
Eric M. Ellsworth ◽  
C. Max Schmidt ◽  
Jamie F. Bleicher ◽  
Dennis M. Smith ◽  
Sydney D. Finkelstein

e21048 Background: Pancreatic cysts pose a challenge in patient management primarily due to difficulties distinguishing non-mucinous cysts from potentially pre-malignant mucinous ones, and in determining the malignant potential of mucinous cysts. Mutations to the GNAS gene have been identified as a marker for intraductal papillary mucinous neoplasm (IPMN). [1,2] We evaluated the significance of GNAS mutation in diagnosis of pancreatic cysts. Methods: We retrieved archival DNA from 237 cyst fluids. 200 specimens were chosen with 100 KRAS mutant and 100 KRAS wild type in a range of CEA values. 37 specimens were chosen with a molecular diagnosis of aggressive biological behavior, to enrich for malignant IPMNs. We sequenced each fluid’s DNA from for codon 201 of GNAS. Molecular criteria for mucinous cysts included KRAS mutation, elevated DNA, or ≥2 high clonality LOH mutations. Results: Of the 237 specimens, 25 were not amplifiable due to degraded DNA, 52 (25%) had a GNAS mutation, and 160 had no GNAS mutation. Of the 52 GNAS mutated specimens, 5 were diagnosed as biologically aggressive based on significant associated mutations, 28 as statistically indolent based on associated molecular changes, and 19 as benign (no accompanying mutations). The proportion of GNAS mutations decreased with increasing molecular changes linked to malignancy. Data from [1] shows no statistical difference in frequency of GNAS mutation in side branch vs. main vs. mixed IPMNs (p= 0.46). Similarly, in our cohort, 6 cases had clear imaging features of a side branch IPMN, and of these 2 (33%) had a mutation in GNAS. Using molecular criteria for identification of mucinous cysts, 166 were mucinous and 71 non-mucinous. Incorporation of GNAS into the molecular determination of mucinous etiology identified 13 additional cases (7%). Conclusions: Use of GNAS increases sensitivity for detection of mucinous lesions. GNAS does not appear to correlate with molecular measures of biological aggressiveness. These findings confirm those in [1], that GNAS should be used in conjunction with a panel of molecular markers for evaluating the malignant potential of pancreatic cystic lesions. References 1. Sci Transl Med. 2011 Jul 20; 3:92ra66. 2. PNAS 2011 Dec 27; 108:21188-93.


2020 ◽  
Vol 49 (4) ◽  
pp. 1075-1081
Author(s):  
Jussi Ekholm ◽  
Pauli Ohukainen ◽  
Antti J Kangas ◽  
Johannes Kettunen ◽  
Qin Wang ◽  
...  

Abstract Motivation An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming. Implementation EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser. General features Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000). Availability The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].


2019 ◽  
Vol 3 (4) ◽  
pp. 411-421 ◽  
Author(s):  
Sara Hägg ◽  
Daniel W. Belsky ◽  
Alan A. Cohen

Abstract The field of molecular epidemiology of aging involves the application of molecular methods to measure aging processes and their genetic determinants in human cohorts. Over the last decade, the field has undergone rapid progress with a dramatic increase in the number of papers published. The aim of this review is to give an overview of the research field, with a specific focus on new developments, opportunities, and challenges. Aging occurs at multiple hierarchical levels. There is increasing consensus that aging-related changes at the molecular level cause declines in physiological integrity, functional capacity, and ultimately lifespan. Molecular epidemiology studies seek to quantify this process. Telomere length, composite scores integrating clinical biomarkers, and omics clocks are among the most well-studied metrics in molecular epidemiology studies. New developments in the field include bigger data and hypothesis-free analysis together with new modes of collaborations in interdisciplinary teams and open access norms around data sharing. Key challenges facing the field are the lack of a gold standard by which to evaluate molecular measures of aging, inconsistency in which metrics of aging are measured and analyzed across studies, and a need for more longitudinal data necessary to observe change over time.


2001 ◽  
Vol 158 (7) ◽  
pp. 1040-1051 ◽  
Author(s):  
Hower Kwon ◽  
Vinod Menon ◽  
Stephan Eliez ◽  
Ilana S. Warsofsky ◽  
Christopher D. White ◽  
...  

2015 ◽  
Author(s):  
Andrew Dhawan ◽  
Trevor A Graham ◽  
Alexander G Fletcher

The lack of effective biomarkers for predicting cancer risk in premalignant disease is a major clinical problem. There is a near-limitless list of candidate biomarkers and it remains unclear how best to sample the tissue in space and time. Practical constraints mean that only a few of these candidate biomarker strategies can be evaluated empirically and there is no framework to determine which of the plethora of possibilities is the most promising. Here we have sought to solve this problem by developing a theoretical platform for in silico biomarker development. We construct a simple computational model of carcinogenesis in premalignant disease and use the model to evaluate an extensive list of tissue sampling strategies and different molecular measures of these samples. Our model predicts that: (i) taking more biopsies improves prognostication, but with diminishing returns for each additional biopsy; (ii) longitudinally-collected biopsies provide slightly more prognostic information than a single biopsy collected at the latest possible time-point; (iii) measurements of clonal diversity are more prognostic than measurements of the presence or absence of a particular abnormality and are particularly robust to confounding by tissue sampling; and (iv) the spatial pattern of clonal expansions is a particularly prognostic measure. This study demonstrates how the use of a mechanistic framework provided by computational modelling can diminish empirical constraints on biomarker development.


1991 ◽  
Vol 180 (1) ◽  
pp. 249-254 ◽  
Author(s):  
Rumiko Shimazawa ◽  
Sayaka Hibino ◽  
Hidetoshi Mizoguchi ◽  
Yuichi Hashimoto ◽  
Shigeo Iwasaki ◽  
...  

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