Identification of novel biomarkers in obstructive sleep apnea via integrated bioinformatics analysis and experimental validation

Background

Obstructive sleep apnea (OSA) is a complex and multi-gene inherited disease caused by both genetic and environmental factors. However, due to the high cost of diagnosis and complex operation, its clinical application is limited. This study aims to explore potential target genes associated with OSA and establish a corresponding diagnostic model.

Methods

This study used microarray datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) related to OSA and perform functional annotation and pathway analysis. The study employed multi-scale embedded gene co-expression network analysis (MEGENA) combined with least absolute shrinkage and selection operator (LASSO) regression analysis to select hub genes and construct a diagnostic model for OSA. In addition, the study conducted correlation analysis between hub genes and OSA-related genes, immunoinfiltration, gene set enrichment analysis (GSEA), miRNA network analysis, and identified potential transcription factors (TFs) and targeted drugs for hub genes. Finally, the study used chronic intermittent hypoxia (CIH) mouse model to simulate OSA hypoxic conditions and verify the expression of hub genes in CIH mice.

Results

In this study, a total of 401 upregulated genes and 275 downregulated genes were identified, and enrichment analysis revealed that these differentially expressed genes may be associated with pathways such as vasculature development, cellular response to cytokine stimulus, and negative regulation of cell population proliferation. Through MEGENA combined with LASSO regression, seven OSA hub genes were identified, including C12orf54, FOS, GPR1, OR9A4, MYO5B, RAB39B, and KLHL4. The diagnostic model constructed based on these genes showed strong stability. The expression levels of hub genes were significantly correlated with the expression levels of OSA-related genes and mainly acted on pathways such as the JAK/STAT signaling pathway and the cytosolic DNA-sensing pathway. Drug-target predictions for hub genes were made using the Connectivity Map (CMap) database and the Drug-Gene Interaction database (Dgidb), which identified targeted therapeutic drugs for the hub genes. In vivo experiments showed that the hub genes were all decreasing in the OSA mouse model.

Conclusions

This study identified novel biomarkers for OSA and established a reliable diagnostic model. The transcriptional changes identified may help to reveal the pathogenesis, mechanisms, and sequelae of OSA.

Genome-wide association study of obstructive sleep apnoea in the Million Veteran Program uncovers genetic heterogeneity by sex

BACKGROUND

Genome-wide association studies (GWAS) for obstructive sleep apnoea (OSA) are limited due to the underdiagnosis of OSA, leading to misclassification of OSA, which consequently reduces statistical power. We performed a GWAS of OSA in the Million Veteran Program (MVP) of the U.S. Department of Veterans Affairs (VA) healthcare system, where OSA prevalence is close to its true population prevalence.

METHODS

We performed GWAS of 568,576 MVP participants, stratified by biological sex and by harmonized race/ethnicity and genetic ancestry (HARE) groups of White, Black, Hispanic, and Asian individuals. We considered both BMI adjusted (BMI-adj) and unadjusted (BMI-unadj) models. We replicated associations in independent datasets, and analysed the heterogeneity of OSA genetic associations across HARE and sex groups. We finally performed a larger meta-analysis GWAS of MVP, FinnGen, and the MGB Biobank, totalling 916,696 individuals.

FINDINGS

MVP participants are 91% male. OSA prevalence is 21%. In MVP there were 18 and 6 genome-wide significant loci in BMI-unadj and BMI-adj analyses, respectively, corresponding to 21 association regions. Of these, 17 were not previously reported in association with OSA, and 13 replicated in FinnGen (False Discovery Rate p-value < 0.05). There were widespread significant differences in genetic effects between men and women, but less so across HARE groups. Meta-analysis of MVP, FinnGen, and MGB biobank revealed 17 additional, previously unreported, genome-wide significant regions.

INTERPRETATION

Sex differences in genetic associations with OSA are widespread, likely associated with multiple OSA risk factors. OSA shares genetic underpinnings with several sleep phenotypes, suggesting shared aetiology and causal pathways.

FUNDING

Described in acknowledgements.

Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans

During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.

An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling

Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women's Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.

Association between symptoms of sleep apnea and problem behaviors in young adult twins and siblings

BACKGROUND

Sleep apnea is one of the most common sleep disorders and it is related to multiple negative health consequences. Previous studies have shown that sleep apnea is influenced by genetic factors. However, studies have not investigated the genetic and environmental influences of symptoms of sleep apnea in young adults. Furthermore, the underpinnings of the relationship between apnea symptoms and internalizing/externalizing problems are unknown. The objectives of this study were to estimate the magnitude of: (1) genetic and environmental influences on self-reported apnea symptoms; (2) the relationship between self-reported apnea symptoms and internalizing/externalizing traits; (3) genetic and environmental influences on the associations between self-reported apnea symptoms, internalizing behaviors and externalizing behaviors.

METHODS

In a twin/sibling study, univariate and multivariate models were fitted to estimate both individual variance and sources of covariance between symptoms of sleep apnea and internalizing/externalizing behaviors.

RESULTS

Our results show that genetic influences account for 40% of the variance in sleep apnea symptoms. Moreover, there are modest associations between depression, anxiety and externalizing behaviors with apnea symptoms (ranging from r = 0.22-0.29). However, the origins of these associations differ. For example, whereas most of the covariation between symptoms of depression and sleep apnea can be explained by genes (95%), there was a larger role for the environment (53%) in the association between symptoms of anxiety and sleep apnea.

CONCLUSIONS

Genetic factors explain a significant proportion of variance in symptoms of apnea and most of the covariance with depression.

Intermediate phenotypes of childhood obstructive sleep apnea

An intermediate phenotype of a disease is a trait in the path of pathogenesis from genetic predisposition to disease manifestation. Identifying intermediate phenotypes with high heritability is helpful in delineating the genetics of a disorder. In this study, we aimed to examine various traits with regards to obesity, cardiovascular risk and upper airway structure to identify potential intermediate phenotypes of childhood obstructive sleep apnea (OSA). Children aged between 6 and 18 years and their parents and siblings were recruited. All subjects underwent anthropometric measurements, cardiovascular risk assessment, sonographic measurement of lateral parapharyngeal wall (LPW) thickness, X-ray cephalometry and overnight polysomnography. A total of 34 phenotypes were examined. One hundred and one families consisting of 127 children (46 overweight) and 198 adults (84 overweight) were recruited. Heritability of obstructive apnea-hypopnea index (OAHI) was significant in overweight (h²  = 0.54) but not normal-weight individuals (h²  = 0.12). LPW thickness (h²  = 0.68) and resting blood pressure (h²  = 0.36 and 0.43 for systolic blood pressure [SBP] and diastolic blood pressure [DBP], respectively) were significantly heritable and associated with OAHI. Moreover, these traits were found to have shared genetic variance with OAHI in the overweight subgroup. Hyoid bone position also had significant heritability (h²  = 0.55) and association with OAHI but genetic correlation with OSA severity was not demonstrated. These findings suggest that LPW thickness and resting blood pressure are possible intermediate phenotypes of OSA independent of body mass index, especially in overweight patients. Identifying genes relevant to these phenotypes may help to elucidate the genetic susceptibility of OSA.

Genetic factors in sleep-disordered breathing

Sleep-disordered breathing (SDB) is characterized by repetitive episodes of decreased or arrested respiratory airflow during sleep. SDB is common and affects approximately 20% of the Japanese general population. Most traits of normal sleep and SDB show familial aggregation, suggesting significant effects of genetic factors. Obstructive sleep apnea (OSA) is the most common type of SDB and has a high heritability. Regardless of high heritability, no risk locus for OSA has reached a genome-wide level of significance (P < 5×10^-8) in linkage or candidate gene analysis. However, a recent genome-wide association study identified some genetic risks for OSA with P < 5×10^-8 for the first time. The identified genes are associated with inflammation, hypoxia signaling, and sleep pathways. The effects of genetic factors on the consequences of OSA has not been determined, although a correlation between OSA and cardiovascular disease may differ across races. Congenital central hypoventilation syndrome (CCHS) is a genetically inherited disorder caused by mutations in the paired-like homeobox 2B (PHOX2B) gene of polyalanine repeat mutations in the 20-alanine repeat or non-polyalanine repeat mutations. PHOX2B genotypes are also associated with clinical phenotypes of CCHS, including severity of hypoventilation. SDB, including obesity hypoventilation syndrome, is often seen in genetic obesity-associated disorders such as Prader-Willi syndrome. Although advances in genetics have resulted in identification of some genetic causes of SDB, further studies are required to elucidate the cellular and molecular mechanisms between genetic risks and clinical manifestations.

Cohort profile: the Baependi Heart Study-a family-based, highly admixed cohort study in a rural Brazilian town

PURPOSE

Cardiovascular disease (CVD) is a major challenge to global health. The same epidemiological transition scenario is replayed as countries develop, but with variations based on environment, culture and ethnic mixture. The Baependi Heart Study was set up in 2005 to develop a longitudinal family-based cohort study that reflects on some of the genetic and lifestyle-related peculiarities of the Brazilian populations, in order to evaluate genetic and environmental influences on CVD risk factor traits.

PARTICIPANTS

Probands were recruited in Baependi, a small rural town in the state of Minas Gerais, Brazil, following by first-degree and then increasingly more distant relatives. The first follow-up wave took place in 2010, and the second in 2016. At baseline, the study evaluated 1691 individuals across 95 families. Cross-sectional data have been collected for 2239 participants.

FINDINGS TO DATE

Environmental and lifestyle factors and measures relevant to cardiovascular health have been reported. Having expanded beyond cardiovascular health outcomes, the phenotype datasets now include genetics, biochemistry, anthropometry, mental health, sleep and circadian rhythms. Many of these have yielded heritability estimates, and a shared genetic background of anxiety and depression has recently been published. In spite of universal access to electricity, the population has been found to be strongly shifted towards morningness compared with metropolitan areas.

FUTURE PLANS

A new follow-up, marking 10 years of the study, is ongoing in 2016, in which data are collected as in 2010 (with the exception of the neuropsychiatric protocol). In addition to this, a novel questionnaire package collecting information about intelligence, personality and spirituality is being planned. The data set on circadian rhythms and sleep will be amended through additional questionnaires, actimetry, home sleep EEG recording and dim light melatonin onset (DLMO) analysis. Finally, the anthropometric measures will be expanded by adding three-dimensional facial photography, voice recording and anatomical brain MRI.