Ten‐Year Trends in Sleep‐Disordered Breathing After Ischemic Stroke: 2010 to 2019 Data From the BASIC Project

Background Despite good evidence that the prevalence of sleep‐disordered breathing (SDB) is increasing in the general population, no data are available about trends in poststroke SDB. We therefore sought to assess changes in poststroke SDB over a 10‐year period (2010–2019). Methods and Results Participants in the BASIC (Brain Attack Surveillance in Corpus Christi) project were offered a home sleep apnea test to assess for SDB after stroke. SDB assessment procedures remained unchanged throughout the study period. Respiratory event index was calculated as the sum of apneas and hypopneas per hour of recording. SDB was defined as respiratory event index ≥10/h for optimal sensitivity and specificity of the home sleep apnea test device compared with in‐laboratory polysomnography. Regression models were used to test associations between SDB prevalence and severity and time, with adjustment for multiple potential confounders. Among the 1215 participants who completed objective sleep apnea testing, the prevalence of SDB grew from 61% in the first year of the study to 76% in the last, with 1.1 times higher odds each year (95% CI, 1.07–1.19), after adjustment. A linear association was identified between time and respiratory event index (average annual respiratory event index increase of 0.56/h; 95% CI, 0.20/h–0.91/h), after adjustment. There was no difference in time trends by sex or ethnicity. Conclusions The prevalence and severity of SDB after ischemic stroke has increased over the past 10 years in this population‐based cohort. These data highlight the need to determine whether SDB treatment improves stroke outcomes

Novel metrics of sleep-disordered breathing are associated with outcome after ischemic stroke

OBJECTIVE/BACKGROUND: Standard measures of sleep-disordered breathing (SDB) that rely on count data may not sufficiently capture SDB severity or reflect downstream consequences of SDB. We hypothesized that novel metrics derived from pulse rate, oxygen saturation, and nasal pressure would be associated with stroke outcomes. PATIENTS/METHODS: Shortly after ischemic stroke, participants in a population-based study were offered ApneaLink Plus testing. Signal analysis was used to generate 166 metrics from the nasal pressure cannula and finger probe, categorized as: autonomic (based on pulse rate variability), oximetry-derived, nasal pressure-derived, and mixed oxygen and nasal pressure-derived measures. Three-month outcome assessments included functional and cognitive outcomes and stroke recurrence. Tobit regression and Cox proportional hazards models were used to examine associations between each sleep apnea metric and the three outcomes, unadjusted and adjusted for multiple potential confounders. Models were adjusted for multiple comparisons. RESULTS: Of the 530 participants, the median age was 65 (IQR: 57, 73), 49 % were female, and 64 % were Mexican American. Without covariate adjustment, 23 of 166 variables were associated with functional outcome, 43 were associated with cognitive outcome, and 1 was associated with stroke recurrence. After adjustment, 7 mixed, oximetry, or nasal pressure-based metrics and 1 autonomic metric were associated with functional outcome, but none was associated with cognitive outcome or stroke recurrence. CONCLUSIONS: Many novel metrics of SDB were associated with important stroke outcomes, and 8 novel metrics were associated with functional outcome in adjusted models. This raises hypotheses about pathways by which SDB may negatively impact stroke outcomes

A mega-analysis of expression quantitative trait loci in retinal tissue

Author summary The retina is a multilayered and highly specified neural tissue crucial for high-resolution visual perception and spatial orientation. Environmental and genetic insults to the retina result in many blinding diseases, such as age-related macular degeneration or glaucoma. Commonly, many of these diseases are age-related suggesting that minor changes are accumulating over a life-time, with little or no contribution of strong individual effects. Specifically, this is true for genetic factors known to underlie the etiology of complex diseases including the prevalent eye diseases. In our study, we searched for effects on gene expression due to genetic variation using 311 healthy post-mortem retinal tissue samples. We show that 3,007 of the 16,766 genes investigated are regulated in the retina by genetic variations. Of these, 80 genes are potentially associated to one or more of twelve complex eye diseases or retinal traits tested. Interestingly, 10 genes appear to be involved in the development of several eye traits suggesting that cellular mechanisms may act at a common point in the disease process. Consequently, our study provides the basis to further explore retinal disease pathways and is likely to highlight target molecules for future therapeutic applications. Significant association signals from genome-wide association studies (GWAS) point to genomic regions of interest. However, for most loci the causative genetic variant remains undefined. Determining expression quantitative trait loci (eQTL) in a disease relevant tissue is an excellent approach to zoom in on disease- or trait-associated association signals and hitherto on relevant disease mechanisms. To this end, we explored regulation of gene expression in healthy retina (n = 311) and generated the largest cis-eQTL data set available to date. Genotype- and RNA-Seq data underwent rigorous quality control protocols before FastQTL was applied to assess the influence of genetic markers on local (cis) gene expression. Our analysis identified 403,151 significant eQTL variants (eVariants) that regulate 3,007 genes (eGenes) (Q-Value < 0.05). A conditional analysis revealed 744 independent secondary eQTL signals for 598 of the 3,007 eGenes. Interestingly, 99,165 (24.71%) of all unique eVariants regulate the expression of more than one eGene. Filtering the dataset for eVariants regulating three or more eGenes revealed 96 potential regulatory clusters. Of these, 31 harbour 130 genes which are partially regulated by the same genetic signal. To correlate eQTL and association signals, GWAS data from twelve complex eye diseases or traits were included and resulted in identification of 80 eGenes with potential association. Remarkably, expression of 10 genes is regulated by eVariants associated with multiple eye diseases or traits. In conclusion, we generated a unique catalogue of gene expression regulation in healthy retinal tissue and applied this resource to identify potentially pleiotropic effects in highly prevalent human eye diseases. Our study provides an excellent basis to further explore mechanisms of various retinal disease etiologies

Gene Evolutionary Trajectories and GC Patterns Driven by Recombination in Zea mays

Recombination occurring during meiosis is critical for creating genetic variation and plays an essential role in plant evolution. In addition to creating novel gene combinations, recombination can affect genome structure through altering GC patterns. In maize (Zea mays) and other grasses, another intriguing GC pattern exists. Maize genes show a bimodal GC content distribution that has been attributed to nucleotide bias in the third, or wobble, position of the codon. Recombination may be an underlying driving force given that recombination sites are often associated with high GC content. Here we explore the relationship between recombination and genomic GC patterns by comparing GC gene content at each of the three codon positions (GC1, GC2, and GC3, collectively termed GCx) to instances of a variable GC-rich motif that underlies double strand break (DSB) hotspots and to meiocyte-specific gene expression. Surprisingly, GCx bimodality in maize cannot be fully explained by the codon wobble hypothesis. High GCx genes show a strong overlap with the DSB hotspot motif, possibly providing a mechanism for the high evolutionary rates seen in these genes. On the other hand, genes that are turned on in meiosis (early prophase I) are biased against both high GCx genes and genes with the DSB hotspot motif, possibly allowing important meiotic genes to avoid DSBs. Our data suggests a strong link between the GC-rich motif underlying DSB hotspots and high GCx genes

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

Abstract DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype–environment interaction in retina