Influence of advanced age of maternal grandmothers on Down syndrome

BACKGROUND: Down syndrome (DS) is the most common chromosomal anomaly associated with mental retardation. This is due to the occurrence of free trisomy 21 (92–95%), mosaic trisomy 21 (2–4%) and translocation (3–4%). Advanced maternal age is a well documented risk factor for maternal meiotic nondisjunction. In India three children with DS are born every hour and more DS children are given birth to by young age mothers than by advanced age mothers. Therefore, detailed analysis of the families with DS is needed to find out other possible causative factors for nondisjunction. METHODS: We investigated 69 families of cytogenetically confirmed DS children and constructed pedigrees of these families. We also studied 200 randomly selected families belonging to different religions as controls. Statistical analysis was carried out using logistic regression. RESULTS: Out of the 69 DS cases studied, 67 were free trisomy 21, two cases were mosaic trisomy 21 and there were none with translocation. The number of DS births was greater for the young age mothers compared with the advanced age mothers. It has also been recorded that young age mothers (18 to 29 years) born to their mothers at the age 30 years and above produced as high as 91.3% of children with DS. The logistic regression of case- control study of DS children revealed that the odds ratio of age of grandmother was significant when all the four variables were used once at a time. However, the effect of age of mother and father was smaller than the effect of age of maternal grandmother. Therefore, for every year of advancement of age of the maternal grandmother, the risk (odds) of birth of DS baby increases by 30%. CONCLUSION: Besides the known risk factors, mother's age, father's age, the age of the maternal grandmother at the time of birth of the mother is a risk factor for the occurrence of Down syndrome

Dimethyl Sulfoxide Promotes the Multiple Functions of the Tumor Suppressor HLJ1 through Activator Protein-1 Activation in NSCLC Cells

Background: Dimethyl sulfoxide (DMSO) is an amphipathic molecule that displays a diversity of antitumor activities. Previous studies have demonstrated that DMSO can modulate AP-1 activity and lead to cell cycle arrest at the G1 phase. HLJ1 is a newly identified tumor and invasion suppressor that inhibits tumorigenesis and cancer metastasis. Its transcriptional activity is regulated by the transcription factor AP-1. However, the effects of DMSO on HLJ1 are still unknown. In the present study, we investigate the antitumor effects of DMSO through HLJ1 induction and demonstrate the mechanisms involved. Methods and Findings: Low-HLJ1-expressing highly invasive CL1–5 lung adenocarcinoma cells were treated with various concentrations of DMSO. We found that DMSO can significantly inhibit cancer cell invasion, migration, proliferation, and colony formation capabilities through upregulation of HLJ1 in a concentration-dependent manner, whereas ethanol has no effect. In addition, the HLJ1 promoter and enhancer reporter assay revealed that DMSO transcriptionally upregulates HLJ1 expression through an AP-1 site within the HLJ1 enhancer. The AP-1 subfamily members JunD and JunB were significantly upregulated by DMSO in a concentration-dependent manner. Furthermore, pretreatment with DMSO led to a significant increase in the percentage of UV-induced apoptotic cells. Conclusions: Our results suggest that DMSO may be an important stimulator of the tumor suppressor protein HLJ1 throug

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

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

This is the publisher’s final pdf. The published article is copyrighted by the Public Library of Science and can be found at: http://www.plosone.org/home.action.Background: Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. \ud \ud Methodology and Principal Findings: A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. \ud \ud Conclusion and Significance: Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level

Hypophosphatasia

Hypophosphatasia is a rare inherited disorder characterized by defective bone and teeth mineralization, and deficiency of serum and bone alkaline phosphatase activity. The prevalence of severe forms of the disease has been estimated at 1/100 000

The landscape of inherited and de novo copy number variants in a plasmodium falciparum genetic cross

<p>Abstract</p> <p>Background</p> <p>Copy number is a major source of genome variation with important evolutionary implications. Consequently, it is essential to determine copy number variant (CNV) behavior, distributions and frequencies across genomes to understand their origins in both evolutionary and generational time frames. We use comparative genomic hybridization (CGH) microarray and the resolution provided by a segregating population of cloned progeny lines of the malaria parasite, <it>Plasmodium falciparum</it>, to identify and analyze the inheritance of 170 genome-wide CNVs.</p> <p>Results</p> <p>We describe CNVs in progeny clones derived from both Mendelian (i.e. inherited) and non-Mendelian mechanisms. Forty-five CNVs were present in the parent lines and segregated in the progeny population. Furthermore, extensive variation that did not conform to strict Mendelian inheritance patterns was observed. 124 CNVs were called in one or more progeny but in neither parent: we observed CNVs in more than one progeny clone that were not identified in either parent, located more frequently in the telomeric-subtelomeric regions of chromosomes and singleton <it>de novo </it>CNVs distributed evenly throughout the genome. Linkage analysis of CNVs revealed dynamic copy number fluctuations and suggested mechanisms that could have generated them. Five of 12 previously identified expression quantitative trait loci (eQTL) hotspots coincide with CNVs, demonstrating the potential for broad influence of CNV on the transcriptional program and phenotypic variation.</p> <p>Conclusions</p> <p>CNVs are a significant source of segregating and <it>de novo </it>genome variation involving hundreds of genes. Examination of progeny genome segments provides a framework to assess the extent and possible origins of CNVs. This segregating genetic system reveals the breadth, distribution and dynamics of CNVs in a surprisingly plastic parasite genome, providing a new perspective on the sources of diversity in parasite populations.</p

Identification of Copy Number Variants Defining Genomic Differences among Major Human Groups

BACKGROUND:Understanding the genetic contribution to phenotype variation of human groups is necessary to elucidate differences in disease predisposition and response to pharmaceutical treatments in different human populations. METHODOLOGY/PRINCIPAL FINDINGS:We have investigated the genome-wide profile of structural variation on pooled samples from the three populations studied in the HapMap project by comparative genome hybridization (CGH) in different array platforms. We have identified and experimentally validated 33 genomic loci that show significant copy number differences from one population to the other. Interestingly, we found an enrichment of genes related to environment adaptation (immune response, lipid metabolism and extracellular space) within these regions and the study of expression data revealed that more than half of the copy number variants (CNVs) translate into gene-expression differences among populations, suggesting that they could have functional consequences. In addition, the identification of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with the copy number alleles allowed us to detect evidences of population differentiation and recent selection at the nucleotide variation level. CONCLUSIONS:Overall, our results provide a comprehensive view of relevant copy number changes that might play a role in phenotypic differences among major human populations, and generate a list of interesting candidates for future studies

Complete sequence of the 22q11.2 allele in 1,053 subjects with 22q11.2 deletion syndrome reveals modifiers of conotruncal heart defects

The 22q11.2 deletion syndrome (22q11.2DS) results from non-allelic homologous recombination between low-copy repeats termed LCR22. About 60%-70% of individuals with the typical 3 megabase (Mb) deletion from LCR22A-D have congenital heart disease, mostly of the conotruncal type (CTD), whereas others have normal cardiac anatomy. In this study, we tested whether variants in the hemizygous LCR22A-D region are associated with risk for CTDs on the basis of the sequence of the 22q11.2 region from 1,053 22q11.2DS individuals. We found a significant association (FDR p &lt; 0.05) of the CTD subset with 62 common variants in a single linkage disequilibrium (LD) block in a 350 kb interval harboring CRKL. A total of 45 of the 62 variants were associated with increased risk for CTDs (odds ratio [OR) ranges: 1.64-4.75). Associations of four variants were replicated in a meta-analysis of three genome-wide association studies of CTDs in affected individuals without 22q11.2DS. One of the replicated variants, rs178252, is located in an open chromatin region and resides in the double-elite enhancer, GH22J020947, that is predicted to regulate CRKL (CRK-like proto-oncogene, cytoplasmic adaptor) expression. Approximately 23% of patients with nested LCR22C-D deletions have CTDs, and inactivation of Crkl in mice causes CTDs, thus implicating this gene as a modifier. Rs178252 and rs6004160 are expression quantitative trait loci (eQTLs) of CRKL. Furthermore, set-based tests identified an enhancer that is predicted to target CRKL and is significantly associated with CTD risk (GH22J020946, sequence kernal association test (SKAT) p = 7.21&nbsp;× 10-5) in the 22q11.2DS cohort. These findings suggest that variance in CTD penetrance in the 22q11.2DS population can be explained in part by variants affecting CRKL expression