Characteristics of participants who re-married and participants who were still widowed/single at 1 year (5 participants lost to follow up).

<p>Data reported as mean ± standard deviation (SD) or n(%); p-values for univariate tests derived from independent samples t-tests for continuous and Mann-Whitney U test for categorical variables; OR = odds ratio; CI = confidence interval.</p

Impact of successful cataract surgery on marital status and measures of poverty at follow up.

<p>OR = odds ratio, CI = confidence interval; controlling for age, gender, education and household size (no. of members) in logistic regression.</p

GA lesion growth rates for each individual in the combined study.

<p>The measured area of GA was square-root transformed. From the transformed area the growth rate was calculated per year in [mm/year]. Growth rates from each individual were then obtained by calculating the mean of all growth rates of the individual. If both eyes were affected, the mean of both eyes were calculated resulting in a single growth variable per individual. These individual growth rates were further transformed by the natural logarithm (ln) and were stratified either by (A) the genotype at ARMS2_rs10490924 or (B) the genotype at C3_rs2230199 or (C) the presence or absence of bilateral GA.</p

Forestplot representations of univariate linear regression models.

<p>Univariate linear regression models were fitted for variables ARMS2_rs10490924, C3_rs2230199 and bilateral GA for each study separately. Slope and standard errors obtained from the models of each study were combined by performing a meta-analysis assuming a random effects model. The combined estimates for slope and 95% confidence intervals (CI) were computed from the random effects model. In all analyses, no evidence was found for heterogeneity (P_{heterogeneity} > 0.05).</p

Summary characteristics of participating study populations.

<p>FAF = fundus autofluorescence.</p><p>Summary characteristics of participating study populations.</p

Multivariate linear regression analysis of factors significantly correlated to GA growth.

<p>^a P value of linear regression model vs. null model</p><p>^b combined effect sizes were estimated from random effects model (meta-analysis).</p><p>Multivariate linear regression analysis of factors significantly correlated to GA growth.</p

Increasing the Yield in Targeted Next-Generation Sequencing by Implicating CNV Analysis, Non-Coding Exons and the Overall Variant Load: The Example of Retinal Dystrophies

<div><p>Retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA) are major causes of blindness. They result from mutations in many genes which has long hampered comprehensive genetic analysis. Recently, targeted next-generation sequencing (NGS) has proven useful to overcome this limitation. To uncover “hidden mutations” such as copy number variations (CNVs) and mutations in non-coding regions, we extended the use of NGS data by quantitative readout for the exons of 55 RP and LCA genes in 126 patients, and by including non-coding 5′ exons. We detected several causative CNVs which were key to the diagnosis in hitherto unsolved constellations, e.g. hemizygous point mutations in consanguineous families, and CNVs complemented apparently monoallelic recessive alleles. Mutations of non-coding exon 1 of <i>EYS</i> revealed its contribution to disease. In view of the high carrier frequency for retinal disease gene mutations in the general population, we considered the overall variant load in each patient to assess if a mutation was causative or reflected accidental carriership in patients with mutations in several genes or with single recessive alleles. For example, truncating mutations in <i>RP1</i>, a gene implicated in both recessive and dominant RP, were causative in biallelic constellations, unrelated to disease when heterozygous on a biallelic mutation background of another gene, or even non-pathogenic if close to the C-terminus. Patients with mutations in several loci were common, but without evidence for di- or oligogenic inheritance. Although the number of targeted genes was low compared to previous studies, the mutation detection rate was highest (70%) which likely results from completeness and depth of coverage, and quantitative data analysis. CNV analysis should routinely be applied in targeted NGS, and mutations in non-coding exons give reason to systematically include 5′-UTRs in disease gene or exome panels. Consideration of all variants is indispensable because even truncating mutations may be misleading.</p></div

Mutational spectrum in RP and LCA patients.

<p>Percentages refer to patients with mutations in the respective gene that are considered causative. The distribution of causative mutations across many genes, each contributing a relatively small fraction to the mutational spectrum, confirms the extensive genetic heterogeneity of retinal dystrophies. Note that the three patients that were found to carry X-linked mutations are not contained in the schemes A – B. <b>A.</b> arRP. <b>B.</b> adRP. Note that the percentages refer to a relatively small adRP cohort in this study. <b>C.</b> LCA. <b>D.</b> Functional categorization of genes that were found to carry causative mutations in our study. Mutations in genes encoding components of the photoreceptor’s connecting cilium and associated structures were predominant.</p

Comparison of this study with previous NGS studies on retinal dystrophies.

*<p>Positive controls not included.</p>**<p>Additional samples from the same families not included. Gene numbers in brackets include additionally screened candidate genes that are not yet proven retinal disease genes. BBS, Bardet-Biedl syndrome; CRD, cone-rod dystrophy; CD, cone dystrophy; CSNB, congenital stationary night blindness; FA, fundus albipunctatus; STGD, Morbus Stargardt; USH, Usher syndrome.</p

Hemizygosity of a <i>CRX</i> mutation in a recessive consanguineous LCA family.

<p><b>A.</b> Compound-heterozygosity for a potentially protein-extending no-stop mutation (c.899A>G/p.(*300Trpext*118); here designated as Ext) abrogating the natural termination codon in exon 4 and a deletion of the same exon (delE4) <i>in trans</i> in patient 110 and her brother. <b>B.</b> Graphical view of the LOD score calculation from genomewide SNP mapping for this family previous to NGS testing: Genomewide homozygosity mapping prior to NGS did not identify a clear candidate locus. The combined maximum parametric LOD score of 2.4 was not obtained. <b>C.</b> Scheme of the <i>CRX</i> gene and coverage plots for CNV analysis from NGS data (Illumina MiSeq), indicating a heterozygous deletion of exon 4 (upper panel, absolute coverage based on read count; lower panel, SeqNext CNV analysis). See legend to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078496#pone-0078496-g002" target="_blank">Figure 2C</a>. <b>D.</b> Schematic representation of the mapped sequencing reads for the no-stop mutation (Integrative Genomics Viewer). The mutation (arrow) was present in all 65 reads covering this region of the gene and therefore appeared homozygous. <b>E.</b> Electropherograms from Sanger sequencing of the no-stop mutation with hemizygosity in patient 110 (upper panel) and heterozygosity in her mother (lower panel). <b>F.</b> Summary of the disease-causing genetic constellation in patient 110 and her brother (superimposition on parental alleles).</p