Air pollution and decreased bone mineral density among Women's Health Initiative participants

Background: Osteoporosis heavily affects postmenopausal women and is influenced by environmental exposures. Determining the impact of criteria air pollutants and their mixtures on bone mineral density (BMD) in postmenopausal women is an urgent priority. Methods: We conducted a prospective observational study using data from the ethnically diverse Women's Health Initiative Study (WHI) (enrollment, September 1994–December 1998; data analysis, January 2020 to August 2022). We used log-normal, ordinary kriging to estimate daily mean concentrations of PM10, NO, NO2, and SO2 at participants' geocoded addresses (1-, 3-, and 5-year averages before BMD assessments). We measured whole-body, total hip, femoral neck, and lumbar spine BMD at enrollment and follow-up (Y1, Y3, Y6) via dual-energy X-ray absorptiometry. We estimated associations using multivariable linear and linear mixed-effects models and mixture effects using Bayesian kernel machine regression (BKMR) models. Findings: In cross-sectional and longitudinal analyses, mean PM10, NO, NO2, and SO2 averaged over 1, 3, and 5 years before the visit were negatively associated with whole-body, total hip, femoral neck, and lumbar spine BMD. For example, lumbar spine BMD decreased 0.026 (95% CI: 0.016, 0.036) g/cm2/year per a 10% increase in 3-year mean NO2 concentration. BKMR suggested that nitrogen oxides exposure was inversely associated with whole-body and lumbar spine BMD. Interpretation: In this cohort study, higher levels of air pollutants were associated with bone damage, particularly on lumbar spine, among postmenopausal women. These findings highlight nitrogen oxides exposure as a leading contributor to bone loss in postmenopausal women, expanding previous findings of air pollution-related bone damage. Funding: US National Institutes of Health

Amplification ratio control system for copy number variation genotyping

We describe a generic design for ratiometric analysis suitable for determination of copy number variation (CNV) class of a gene. Following two initial sequence-specific PCR priming cycles, both ends of both amplicons (one test and one reference) in a duplex reaction, are all primed by the same universal primer (UP). Following each amplification denaturation step, the UP target and its reverse complement (UP′) in each strand form a hairpin. The bases immediately beyond the 3′-end of the UP and 5′ of UP′ are chosen such as not to base pair in the hairpin (otherwise priming is ablated). This hairpin creates a single constant environment for priming events and chaperones free 3′-ends of amplicon strands. The resultant ‘amplification ratio control system’ (ARCS) permits ratiometric representation of amplicons relative to the original template into PCR plateau phase. These advantages circumvent the need for real-time PCR for quantitation. Choice of different %(G+C) content for the target and reference amplicons allows liquid phase thermal melt discrimination and quantitation of amplicons. The design is generic, simple to set up and economical. Comparisons with real-time PCR and other techniques are made and CNV assays demonstrated for haptoglobin duplicon and ‘chemokine (C-C motif) ligand 3-like 1’ gene

Accuracy and differential bias in copy number measurement of CCL3L1 in association studies with three auto-immune disorders

Contains fulltext : 97604.pdf (publisher's version ) (Open Access)BACKGROUND: Copy number variation (CNV) contributes to the variation observed between individuals and can influence human disease progression, but the accurate measurement of individual copy numbers is technically challenging. In the work presented here we describe a modification to a previously described paralogue ratio test (PRT) method for genotyping the CCL3L1/CCL4L1 copy variable region, which we use to ascertain CCL3L1/CCL4L1 copy number in 1581 European samples. As the products of CCL3L1 and CCL4L1 potentially play a role in autoimmunity we performed case control association studies with Crohn's disease, rheumatoid arthritis and psoriasis clinical cohorts. RESULTS: We evaluate the PRT methodology used, paying particular attention to accuracy and precision, and highlight the problems of differential bias in copy number measurements. Our PRT methods for measuring copy number were of sufficient precision to detect very slight but systematic differential bias between results from case and control DNA samples in one study. We find no evidence for an association between CCL3L1 copy number and Crohn's disease, rheumatoid arthritis or psoriasis. CONCLUSIONS: Differential bias of this small magnitude, but applied systematically across large numbers of samples, would create a serious risk of false positive associations in copy number, if measured using methods of lower precision, or methods relying on single uncorroborated measurements. In this study the small differential bias detected by PRT in one sample set was resolved by a simple pre-treatment by restriction enzyme digestion

Genome-Wide Mapping of Copy Number Variation in Humans: Comparative Analysis of High Resolution Array Platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications

On Quality Control Measures in Genome-Wide Association Studies: A Test to Assess the Genotyping Quality of Individual Probands in Family-Based Association Studies and an Application to the HapMap Data

Allele transmissions in pedigrees provide a natural way of evaluating the genotyping quality of a particular proband in a family-based, genome-wide association study. We propose a transmission test that is based on this feature and that can be used for quality control filtering of genome-wide genotype data for individual probands. The test has one degree of freedom and assesses the average genotyping error rate of the genotyped SNPs for a particular proband. As we show in simulation studies, the test is sufficiently powerful to identify probands with an unreliable genotyping quality that cannot be detected with standard quality control filters. This feature of the test is further exemplified by an application to the third release of the HapMap data. The test is ideally suited as the final layer of quality control filters in the cleaning process of genome-wide association studies. It identifies probands with insufficient genotyping quality that were not removed by standard quality control filtering

Association analysis identifies ZNF750 regulatory variants in psoriasis

<p>Abstract</p> <p>Background</p> <p>Mutations in the <it>ZNF750 </it>promoter and coding regions have been previously associated with Mendelian forms of psoriasis and psoriasiform dermatitis. <it>ZNF750 </it>encodes a putative zinc finger transcription factor that is highly expressed in keratinocytes and represents a candidate psoriasis gene.</p> <p>Methods</p> <p>We examined whether <it>ZNF750 </it>variants were associated with psoriasis in a large case-control population. We sequenced the promoter and exon regions of <it>ZNF750 </it>in 716 Caucasian psoriasis cases and 397 Caucasian controls.</p> <p>Results</p> <p>We identified a total of 47 variants, including 38 rare variants of which 35 were novel. Association testing identified two <it>ZNF750 </it>haplotypes associated with psoriasis (p < 0.05). We also identified an excess of rare promoter and 5'untranslated region (UTR) variants in psoriasis cases compared to controls (p = 0.041), whereas there was no significant difference in the number of rare coding and rare 3' UTR variants. Using a promoter functional assay in stimulated human primary keratinocytes, we showed that four <it>ZNF750 </it>promoter and 5' UTR variants displayed a 35-55% reduction of <it>ZNF750 </it>promoter activity, consistent with the promoter activity reduction seen in a Mendelian psoriasis family with a <it>ZNF750 </it>promoter variant. However, the rare promoter and 5' UTR variants identified in this study did not strictly segregate with the psoriasis phenotype within families.</p> <p>Conclusions</p> <p>Two haplotypes of <it>ZNF750 </it>and rare 5' regulatory variants of <it>ZNF750 </it>were found to be associated with psoriasis. These rare 5' regulatory variants, though not causal, might serve as a genetic modifier of psoriasis.</p

A classification model for distinguishing copy number variants from cancer-related alterations

<p>Abstract</p> <p>Background</p> <p>Both somatic copy number alterations (CNAs) and germline copy number variants (CNVs) that are prevalent in healthy individuals can appear as recurrent changes in comparative genomic hybridization (CGH) analyses of tumors. In order to identify important cancer genes CNAs and CNVs must be distinguished. Although the Database of Genomic Variants (DGV) contains a list of all known CNVs, there is no standard methodology to use the database effectively.</p> <p>Results</p> <p>We develop a prediction model that distinguishes CNVs from CNAs based on the information contained in the DGV and several other variables, including segment's length, height, closeness to a telomere or centromere and occurrence in other patients. The models are fitted on data from glioblastoma and their corresponding normal samples that were collected as part of The Cancer Genome Atlas project and hybridized to Agilent 244 K arrays.</p> <p>Conclusions</p> <p>Using the DGV alone CNVs in the test set can be correctly identified with about 85% accuracy if the outliers are removed before segmentation and with 72% accuracy if the outliers are included, and additional variables improve the prediction by about 2-3% and 12%, respectively. Final models applied to data from ovarian tumors have about 90% accuracy with all the variables and 86% accuracy with the DGV alone.</p