Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL

Crosstalk between gastrointestinal tract disorders and obstructive sleep apnea

PURPOSE

Clinical studies suggested associations between obstructive sleep apnea (OSA) and gastrointestinal tract disorders. This study aims to investigate the genetic causal relationship between OSA and gastrointestinal tract disorders, specifically gastroesophageal reflux disease (GERD) and inflammatory bowel disease (IBD).

METHODS

In this study, we employed two-sample Mendelian Randomization (MR) analysis to investigate the potential relationships between OSA and GERD, and between OSA and IBD. More specifically, the primary analysis utilized inverse variance weighting (IVW). Weighted median, MR Egger, and MR PRESSO were applied to complicate potential violations of MR assumptions. Also, sensitivity analysis was evaluated and similar analysis was performed again after outliers were removed. Additionally, multivariable MR (MVMR) was conducted for associated pairs to adjust for obesity.

RESULTS

Genetically predicted risk of GERD increased OSA risk by approximately 60% (ORIVW = 1.62, 95%CI = [1.43,1.84]) which was also stable by other complicated approaches, and even with BMI adjusted by MVMR (ORadjBMI[95%CI] = 1.26 [1.15,1.37]). Besides, OSA showed a mild causal effect on increased GERD risk after adjusting for obesity (ORadjBMI[95%CI] = 1.05 [1.02,1.08]). Additionally, OSA increased the risks for IBD (ORIVW[95%CI] = 1.36 [1.12,1.65]), including a higher risk of CD (ORIVW[95%CI] = 1.41 [1.08,1.83]), and a trend for increasing UC risk (ORIVW[95%CI] = 1.29 [0.99,1.67]).

CONCLUSION

GERD exerts a substantial causality on increasing the risk of OSA. Conversely, the potential for a causal relationship that OSA contributes to the development of GERD or IBD remains probable. These findings support the crosstalk between gastrointestinal tract disorders and OSA.

A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networks

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

Genome-wide association study and polygenic score assessment of insulin resistance

Insulin resistance (IR) and beta cell dysfunction are the major drivers of type 2 diabetes (T2D). Genome-Wide Association Studies (GWAS) on IR have been predominantly conducted in European populations, while Middle Eastern populations remain largely underrepresented. We conducted a GWAS on the indices of IR (HOMA2-IR) and beta cell function (HOMA2-%B) in 6,217 non-diabetic individuals from the Qatar Biobank (QBB; Discovery cohort; n = 2170, Replication cohort; n = 4047) with and without body mass index (BMI) adjustment. We also developed polygenic scores (PGS) for HOMA2-IR and compared their performance with a previously derived PGS for HOMA-IR (PGS003470). We replicated 11 loci that have been previously associated with HOMA-IR and 24 loci that have been associated with HOMA-%B, at nominal statistical significance. We also identified a novel locus associated with beta cell function near VEGFC gene, tagged by rs61552983 (P = 4.38 × 10-8). Moreover, our best performing PGS (Q-PGS4; Adj R2 = 0.233 ± 0.014; P = 1.55 x 10-3) performed better than PGS003470 (Adj R2 = 0.194 ± 0.014; P = 5.45 x 10-2) in predicting HOMA2-IR in our dataset. This is the first GWAS on HOMA2 and the first GWAS conducted in the Middle East focusing on IR and beta cell function. Herein, we report a novel locus in VEGFC that is implicated in beta cell dysfunction. Inclusion of under-represented populations in GWAS has potentials to provide important insights into the genetic architecture of IR and beta cell function.

The benefits of hypoglycemic therapy for patients with obstructive sleep apnea

PURPOSE

Obstructive sleep apnea (OSA) is often associated with glycemic abnormalities. This study is conducted to investigate the effects of hypoglycemic therapy on OSA-related indicators.

METHOD

We systematically searched Web of Science, PubMed, Embase, and the Cochrane Library for articles on OSA patients receiving any hypoglycemic drugs, published until December 25, 2022. Seven original studies were finally included. The proposal was registered with PROSPERO (CRD42022351206).

RESULTS

In summary, in addition to reduced glycosylated hemoglobin A1c (HbA1c), we found that hypoglycemic treatment can lower the apnea-hypopnea index (AHI) by 7.07/h (p = 0.0001). Although long-term treatment (> 12 weeks) achieved a more significant reduction in HbA1c (- 1.57% vs. - 0.30%) compared to short-term treatment (≤ 12 weeks), there was no significant difference between the two in terms of AHI (intergroup p-value = 0.27). We also found that patients using sodium glucose cotransporter 2 inhibitors (SGLT2i) experienced a greater reduction in AHI (- 11.00/h, p < 0.00001). Additionally, hypoglycemic treatment also showed certain improvements in related indicators like Epworth Sleepiness Scale, body mass index, and blood pressure.

CONCLUSIONS

Our results affirm the benefits of hypoglycemic treatment for OSA patients and highlight the notable effect of SGLT2i. Further researches are needed to help doctors gain a comprehensive understanding of the interaction between OSA and glycemic abnormalities.

Effect of different anti-cardiovascular disease treatments on the severity of obstructive sleep apnea

Obstructive sleep apnea (OSA) and cardiovascular co-morbidities have a mutually reinforcing effect, but existing studies have focussed only on the improvement of the associated co-morbidities by treatment for OSA. To provide fresh guidelines for the treatment of OSA from a co-morbidity standpoint, we conducted a systematic search of Web of Science, PubMed, EMBASE, and the Cochrane Library for articles published from inception up to 2 May 2023. Fourteen original studies of patients with OSA with cardiovascular co-morbidities and who received related treatment were included in the analysis. We found that diuretic treatment can reduce the apnea-hypopnea index in patients with OSA and hypertension (-19.41/h, p = 1.0 × 10-5 ), aldosterone-angiotensin inhibitors also have a 9.19/h reduction (p = 0.003), while the effect of renal sympathetic denervation is insignificant (-2.32/h, p = 0.19). The short-term treatment (<4 weeks) did not show an improvement (-2.72/h, p = 0.16), while long-term treatment (>4 weeks) produced surprising outcomes (-12.78/h, p = 0.002). Patients with milder disease (baseline AHI < 35/h) had insignificant improvements (-1.05/h, p = 0.46), whereas those with more severe disease (baseline AHI > 35/h) could achieve satisfactory outcomes (-14.74/h, p < 0.00001). In addition, it also showed some improvement in the oxygen desaturation index and blood oxygen. Our results support the additional benefit of antihypertensive treatment for OSA symptoms, and the efficacy can be affected by different therapy, treatment duration, and severity levels. It could be useful in developing clinical therapy, educating patients, and exploring interaction mechanisms. The proposal was registered with PROSPERO (CRD42022351206).

Effects of common lifestyle factors on obstructive sleep apnea: precautions in daily life based on causal inferences

Background

This study aimed to evaluate the causal impact of common modifiable lifestyles on obstructive sleep apnea (OSA), which is beneficial for recommendations to prevent and manage OSA.

Method

Published genome-wide association study (GWAS) summary statistics were used to perform two-sample Mendelian randomization (MR). Variants associated with each exposure of smoking, drinking, and leisure sedentary behaviors at the genetic level were used as instrumental variables (IVs). Then, inverse-variance weighting (IVW) was considered the primary result for causality. Moreover, several complimented approaches were also included to verify the observed associations. MR-PRESSO and MR-Egger intercept were applied to test the horizontal pleiotropy. To assess heterogeneity, Cochran's Q test by IVW and MR-Egger were applied.

Results

Regular smoking history increased OSA risk in all applied approaches [OR (95% CI)IVW = 1.28 (1.12, 1.45), p = 1.853 × 10-4], while the causality of lifetime smoking index [OR (95% CI)IVW = 1.39 (1.00, 1.91), p = 0.048], alcohol intake frequency [outliers removed OR (95% CI)IVW = 1.26 (1.08, 1.45), p = 0.002], and coffee intake behavior [OR (95% CI)IVW = 1.66 (1.03, 2.68), p = 0.039] on OSA risk were not always consistent in other approaches. In addition, no robust causal associations were observed for the effect of sedentary leisure behaviors on OSA risk. In sensitivity analysis, we observed no sign of horizontal pleiotropy or heterogeneity.

Conclusion

Ever regularly smoking has a robust causal role in increasing OSA risk, which should be discouraged as precautions from developing OSA.

Association of modifiable risk factors with obstructive sleep apnea: a Mendelian randomization study

BACKGROUND

The risk factors involved in obstructive sleep apnea (OSA) have not been clearly identified yet. We attempted to systematically investigate genetically predicted modifiable risk factors and lifestyle behaviors associated with OSA.

METHODS

The association between 34 risk factors and OSA was evaluated using the two-sample Mendelian randomization (MR). Genetic variants for risk factors were acquired from European-descent genome-wide studies. Data sources for OSA were extracted from FinnGen study with 16,761 cases and 201,194 controls. The primary analysis chosen was the inverse-variance weighted method.

RESULTS

MR analyses provide evidence of genetically predicted poor overall health rating (odds ratio (OR), 2.82; 95% confidence interval (CI), 1.95-4.08), nap during day (OR, 2.01; 95% CI, 1.37-2.93), high body mass index (BMI) (OR, 1.14; 95% CI, 1.09-1.19), increased body fat mass (OR, 1.83; 95% CI, 1.83-2.05), elevated body water mass (OR, 1.50; 95% CI, 1.31-1.70) and hypertension (OR, 1.81; 95% CI, 1.34-2.45) were associated with higher OSA risk, while high education level (OR, 0.55; 95% CI, 0.40-0.75) correlated with reduced OSA risk. Suggestive evidence was obtained for smoking and waist-to-hip ratio (WHR) with higher OSA odds, and vigorous physical activity, and HDL cholesterol with lower OSA odds. After adjusting for BMI using multivariable MR analysis, the effects of smoking, WHR, vigorous physical activity, and HDL-cholesterol were fully attenuated.

CONCLUSIONS

This MR study indicates that overall health rating, nap during day, BMI, body fat mass, body water mass, hypertension, and education are causally associated with the risk of OSA, which means that these modifiable risk factors are key targets for OSA prevention.

Lipid metabolism and neuromuscular junction as common pathways underlying the genetic basis of erectile dysfunction and obstructive sleep apnea

Erectile dysfunction (ED) incidence is higher in patients with obstructive sleep apnea (OSA). Studies have suggested that ED and OSA may activate similar pathways; however, few have investigated the links between their underlying genotypic profiles. Therefore, we conducted an in-silico analysis to test whether ED and OSA share genetic variants of risk and to identify any molecular, cellular and biological interactions between them. Two gene lists were manually curated through a literature review based on a PUBMED search, which resulted in one gene list associated with ED (total of 205 genes) and the other with OSA (total of 2622 genes). Between those gene sets, 35 were common for both lists (Fisher exact test, p-value = 0.027). The Protein-protein interaction (PPI) analysis using the intersect list as input showed that 3 of them had direct interactions (LPL, DGKB and PLCB1). In addition, the biological function of the genes contained in the intersect list suggested that pathways related to lipid metabolism and the neuromuscular junction were commonly found in the genetic basis of ED and OSA. From the shared genes between both conditions, the biological pathways highlighted in this study may serve as preliminary findings for future functional investigations on OSA and ED association.

Unraveling the associations and causalities between glucose metabolism and multiple sleep traits

Purpose

The aim of our study is to estimate the associations and causalities of glucose metabolism traits of fasting blood glucose (FBG), fasting insulin (FINS), glycosylated hemoglobin (HbA1c), and 2-h glucose post-challenge (2hGlu) with sleep traits consisting of excessive daytime sleepiness (EDS), insomnia, and sleep duration.

Methods

We employed standard quantitative analysis procedures to assess the associations between sleep traits and glucose metabolism. Moreover, we acquired published genome-wide association studies (GWAS) summary statistics for these traits and conducted Mendelian randomization (MR) analyses to estimate their causal directions and effects. Inverse variance weighting (IVW) was employed as the primary approach, followed by sensitivity analyses.

Results

A total of 116 studies with over 840,000 participants were included in the quantitative analysis. Our results revealed that participants with abnormal glucose metabolism had higher risks for EDS (OR [95% CI] = 1.37 [1.10,1.69]), insomnia (OR [95% CI] = 1.65 [1.24,2.20]), and both short and long sleep duration (OR [95% CI] = 1.35 [1.12,1.63]; OR [95% CI] = 1.38 [1.13,1.67] respectively). In addition, individuals with these sleep traits exhibited alterations in several glycemic traits compared with non-affected controls. In MR analysis, the primary analysis demonstrated causal effects of 2hGlu on risks of EDS (OR [95% CI] = 1.022 [1.002,1.042]) and insomnia (OR [95% CI] = 1.020[1.001,1.039]). Furthermore, FINS was associated with short sleep duration (OR [95% CI] = 1.043 [1.018,1.068]), which reversely presented a causal influence on HbA1c (β [95% CI] = 0.131 [0.022,0.239]). These results were confirmed by sensitivity analysis.

Conclusion

Our results suggested mutual risk and causal associations between the sleep traits and glycemic traits, shedding new light on clinical strategies for preventing sleep disorders and regulating glucose metabolism. Future studies targeting these associations may hold a promising prospect for public health.

A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically-determined protein-protein networks

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

The causal associations of altered inflammatory proteins with sleep duration, insomnia and daytime sleepiness

STUDY OBJECTIVES

Growing evidence linked inflammation with sleep. This study aimed to evaluate the associations and causal effects of sleep traits including insomnia, excessive daytime sleepiness (EDS), and sleep duration (short: <7 h; normal: 7-9 h; long: ≥9 h), with levels of C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), and interleukins.

METHODS

Standard procedures of quantitative analysis were applied to estimate the expression differences for each protein in compared groups. Then, a two-sample Mendelian randomization (MR) analysis was performed to explore their causal relationships with published genome-wide association study summary statistics. The inverse-variance weighted was used as the primary method, followed by several complementary approaches as sensitivity analyses.

RESULTS

A total of 44 publications with 51 879 participants were included in the quantitative analysis. Our results showed that the levels of CRP, interleukin-1β (IL-1β), IL-6, and TNF-α were higher from 0.36 to 0.58 (after standardization) in insomnia compared with controls, while there was no significant difference between participants with EDS and controls. Besides, there was a U/J-shaped expression of CRP and IL-6 with sleep durations. In MR analysis, the primary results demonstrated the causal effects of CRP on sleep duration (estimate: 0.017; 95% confidence intervals [CI], [0.003, 0.031]) and short sleep duration (estimate: -0.006; 95% CI, [-0.011, -0.001]). Also, IL-6 was found to be associated with long sleep duration (estimate: 0.006; 95% CI, [0.000, 0.013]). These results were consistent in sensitivity analyses.

CONCLUSIONS

There are high inflammatory profiles in insomnia and extremes of sleep duration. Meanwhile, elevated CRP and IL-6 have causal effects on longer sleep duration. Further studies can focus on related upstream and downstream mechanisms.

How is Obstructive Sleep Apnea Associated with High Blood Pressure and Diabetes Mellitus Type 2? Clues from a Two-Step Mendelian Randomized Study

Background

Obstructive sleep apnea (OSA), high blood pressure (HBP), and type 2 diabetes mellitus (T2DM) have a close clinical relationship, but whether and how OSA affects HBP and T2DM is unclear.

Study Design and Methods

Two-step, two-sample Mendelian randomization techniques were applied using single-nucleotide polymorphisms as genetic instruments for exposure and mediators, thus minimizing bias due to confounding factors and reverse causality. The total effect of OSA on HBP and T2DM was categorized into direct and mediating effects based on the mediating factors.

Results

Two-sample MR analysis showed that OSA increased the risk of HBP (odds ratio [OR] = 1.010, 95% confidence interval [CI], 1.002-1.018; P = 0.0121) and T2DM (OR = 1.140, 95% CI, 1.059-1.228; P = 0.0005). In the process of OSA caused by HBP, sex hormone-binding globulin (SHBG) (female, 4.47% mediation; male, 2.76% mediation), total testosterone (TT) (male, 3.72% mediation), bioavailable testosterone (BioT) (female, 7.74% mediation), high-density lipoprotein cholesterol (HDL-C) (3.25% mediation), and apolipoprotein A1 (ApoA1) (1.31% mediation) were individual contributors. SHBG (female, 4.10% mediation; male, 1.58% mediation), TT (male, 3.69% mediation), BioT (female, 2.58% mediation), HDL-C (3.32% mediation), ApoA1 (2.14% mediation), and omega-6 fatty acids (2.33% mediation) may have mediating roles to varying degrees in the process of OSA caused by T2DM.

Interpretation

This MR study showed that OSA is a risk factor for HBP and T2DM, and the evaluation of mediators may help further reveal the specific mechanism by which OSA causes HBP and T2DM.

Obstructive sleep apnoea heterogeneity and cardiovascular disease

Obstructive sleep apnoea (OSA), characterized by recurrent periods of upper airway obstruction and intermittent hypoxaemia, is prevalent in patients with cardiovascular disease (CVD), and is therefore important to consider in the prevention and management of CVD. Observational studies indicate that OSA is a risk factor for incident hypertension, poorly controlled blood pressure, stroke, myocardial infarction, heart failure, cardiac arrhythmias, sudden cardiac death and all-cause death. However, clinical trials have not provided consistent evidence that treatment with continuous positive airway pressure (CPAP) improves cardiovascular outcomes. These overall null findings might be explained by limitations in trial design and low levels of adherence to CPAP. Studies have also been limited by the failure to consider OSA as a heterogeneous disorder that consists of multiple subtypes resulting from variable contributions from anatomical, physiological, inflammatory and obesity-related risk factors, and resulting in different physiological disturbances. Novel markers of sleep apnoea-associated hypoxic burden and cardiac autonomic response have emerged as predictors of OSA-related susceptibility to adverse health outcomes and treatment response. In this Review, we summarize our understanding of the shared risk factors and causal links between OSA and CVD and emerging knowledge on the heterogeneity of OSA. We discuss the varied mechanistic pathways that result in CVD that also vary across subgroups of OSA, as well as the potential role of new biomarkers for CVD risk stratification.

Causal association between obstructive sleep apnea and gastroesophageal reflux disease: A bidirectional two-sample Mendelian randomization study

Objectives: Correlations between obstructive sleep apnea (OSA) and gastroesophageal reflux disease (GERD) have been detected in previous observational studies. However, this association remains uncertain due to the potential presence of selection and confounding biases. Therefore, this bidirectional two-sample Mendelian randomization (MR) study was conducted to evaluate the causal relationship between OSA and GERD.

Methods: In this study, instrumental variables (IVs) for OSA were selected from publicly available genetic summary data (27,207 cases and 280,720 controls). Summary statistics for GERD were obtained from a genome-wide association study of 602,604 individuals. The inverse variance weighted (IVW) method was used as the main MR method. The MR-Egger intercept test, MR pleiotropy residual sum and outlier, and leave-one-out analysis were used to detect pleiotropy. Heterogeneity was detected by Cochran’s Q test.

Results: The IVW results revealed that OSA [odds ratio (OR): 1.19, 95% confidence interval (CI): 1.11–1.28, p = 8.88E-07] was causally associated with the incidence of GERD. Moreover, there was evidence of GERD leading to OSA in the IVW analysis (OR: 1.44, 95%CI: 1.33–1.57, p = 7.74E-19). No directional pleiotropy was detected by the MR-Egger intercept test (all p &gt; 0.05).

Conclusion: This study found that OSA is linked to a higher incidence of GERD, and vice versa. This finding might be helpful for the screening and prevention of these two diseases.

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.

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.

Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of Latinos

BACKGROUND

Sleep phenotypes have been reported to be associated with cognitive ageing outcomes. However, there is limited research using genetic variants as proxies for sleep traits to study their associations. We estimated associations between Polygenic Risk Scores (PRSs) for sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnoea (OSA) and measures of cogntive ageing in Hispanic/Latino adults.

METHODS

We used summary statistics from published genome-wide association studies to construct PRSs representing the genetic basis of each sleep trait, then we studied the association of the PRSs of the sleep phenotypes with cognitive outcomes in the Hispanic Community Healthy Study/Study of Latinos. The primary model adjusted for age, sex, study centre, and measures of genetic ancestry. Associations are highlighted if their p-value <0.05.

FINDINGS

Higher PRS for insomnia was associated with lower global cognitive function and higher risk of mild cognitive impairment (MCI) (OR = 1.20, 95% CI [1.06, 1.36]). Higher PRS for daytime sleepiness was also associated with increased MCI risk (OR = 1.14, 95% CI [1.02, 1.28]). Sleep duration PRS was associated with reduced MCI risk among short and normal sleepers, while among long sleepers it was associated with reduced global cognitive function and with increased MCI risk (OR = 1.40, 95% CI [1.10, 1.78]). Furthermore, adjustment of analyses for the measured sleep phenotypes and APOE-ε4 allele had minor effects on the PRS associations with the cognitive outcomes.

INTERPRETATION

Genetic measures underlying insomnia, daytime sleepiness, and sleep duration are associated with MCI risk. Genetic and self-reported sleep duration interact in their effect on MCI.

FUNDING

Described in Acknowledgments.