scholarly journals Next-generation sequencing identifies monogenic diabetes in 16% of patients with late adolescence/adult-onset diabetes selected on a clinical basis: a cross-sectional analysis

BMC Medicine ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Xavier Donath ◽  
◽  
Cécile Saint-Martin ◽  
Danièle Dubois-Laforgue ◽  
Ramanan Rajasingham ◽  
...  
2021 ◽  
Author(s):  
Ling-hui Qu ◽  
Xin Jin ◽  
Chao Zeng ◽  
Nian-gou Zhou ◽  
Yan-hong Liu ◽  
...  

Background: Stargardt disease (STGD) is the most common form of juvenile macular dystrophy associated with progressive central vision loss, and is agenetically and clinically heterogeneous disease. Molecular diagnosis is of great significance in aiding the clinical diagnosis, helping to determine the phenotypic severity and visual prognosis. In this study, we determined the clinical and genetic features of seven childhood-onset and three adult-onset Chinese STGD families. We performed capture next generation sequencing (NGS) of the probands and searched for potentially disease-causing genetic variants in previously identified retinal or macular dystrophy genes.  Methods: In all, 10unrelated Chinese families were enrolled. Panel based NGS was performed to identify potentially disease-causing genetic variants in previously identified retinal or macular dystrophy genes, including the five known STGD genes (ABCA4, PROM1, PRPH2, VMD2 and ELOVL4). Variant analysis, Sanger validation, and segregation tests were utilized to validate the disease-causing mutations inthese families. Results: Using systematic data analysis with an established bioinformatics pipeline and segregation analysis, 17 pathogenic mutations in ABCA4 were identified in the ten STGD families. Four of these mutations were novel: c.371delG, c.681T > G, c.5509C > T and EX37del. Childhood-onset STGD was associated with severe visual loss, generalized retinal dysfunction and was due to more severe variants in ABCA4 than those found in adult-onset disease. Conclusions: We expand the existing spectrum of STGD and reveal the genotype-phenotype relationships of the ABCA4 mutations in Chinese patients. Childhood-onset STGD lies at the severe end of the spectrum of ABCA4-associated retinal phenotypes.


2017 ◽  
Vol 135 (3) ◽  
pp. 266-269
Author(s):  
James Yarmolinsky ◽  
Bruce Bartholow Duncan ◽  
Sandhi Maria Barreto ◽  
Maria de Fátima Sander Diniz ◽  
Dora Chor ◽  
...  

ABSTRACT CONTEXT AND OBJECTIVE: It has been reported that earlier age at first childbirth may increase the risk of adult-onset diabetes among postmenopausal women, a novel finding with important public health implications. To date, however, no known studies have attempted to replicate this finding. We aimed to test the hypothesis that age at first childbirth is associated with the risk of adult-onset diabetes among postmenopausal women. DESIGN AND SETTING: Cross-sectional analysis using baseline data from 2919 middle-aged and elderly postmenopausal women in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). METHODS: Age at first childbirth was determined from self-reporting and newly diagnosed diabetes through a 2-hour 75-g oral glucose tolerance test and/or glycated hemoglobin. Logistic regression was performed to examine associations between age at first childbirth and newly diagnosed diabetes among postmenopausal women. RESULTS: We did not find any association between age at first childbirth and diabetes, either when minimally adjusted for age, race and study center (odds ratio, OR [95% confidence interval, CI]: ≤ 19 years: 1.15 [0.82-1.59], 20-24 years: 0.90 [0.66-1.23] and ≥ 30 years: 0.86 [0.63-1.17] versus 25-29 years; P = 0.36) or when fully adjusted for childhood and adult factors (OR [95% CI]: ≤ 19 years: 0.95 [0.67-1.34], 20-24 years: 0.78 [0.56-1.07] and ≥ 30 years: 0.84 [0.61-1.16] versus 25-29 years; P = 0.40). CONCLUSION: Our current analysis does not support the existence of an association between age at first childbirth and adult-onset diabetes among postmenopausal women, which had been reported previously.


2020 ◽  
Author(s):  
Susanne Gerber ◽  
Stephan Weißbach ◽  
Stanislav Jur`Evic Sys ◽  
Charlotte Hewel ◽  
Hristo Todorov ◽  
...  

Abstract Background Next Generation Sequencing (NGS) is the fundament of various studies providing insights into questions from biology and medicine. Nevertheless, integrating data from different experimental backgrounds can introduce strong biases. In order to methodically investigate the magnitude of systematic errors, we performed a cross-sectional observational study on a genomic cohort of 99 subjects each sequenced via (i) Illumina HiSeq X, (ii) Illumina HiSeq and (iii) Complete Genomics. Consequently, we systematically analyzed the heterogeneity between the sequencing cohorts with respect to genomic annotation and common filter criteria like minimum allele frequency (MAF). Results The number of detected variants/variant classes per individual was highly dependent on the sequencing technology. We observed a statistically significant overrepresentation of variants uniquely called by a single platform which indicates potential systematic biases. These variants were enriched in low complexity genomic regions and simple repeats. Furthermore, estimates of allele frequency were highly discrepant for a subset of variants in pairwise comparisons between different sequencing platforms. Applying common filters – such as MAF 5% and HWE- greatly reduced the heterogeneity between cohorts but still left discrepancies of several thousand variants after filtering.Conclusion We provide empirical evidence of systematic heterogeneity in variant calls between alternative experimental and data analysis setups. Our results highlight the potential benefit of reprocessing genomic data with harmonized pipelines when integrating data from different studies.


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