Evidence for causal effects of sleep disturbances on risk for osteoarthritis: a univariable and multivariable Mendelian randomization study

Causal factors for osteoarthritis risk revealed by mendelian randomization analysis

Osteoarthritis (OA), a prevalent chronic disease among the elderly, presents a complex pathogenesis and currently lacks effective treatment. Traditional observational studies are time-consuming, labor-intensive, susceptible to confounding factors, and cannot establish causal relationships. Mendelian randomization (MR) analysis, leveraging genetic variation to assess causal associations between exposures and outcomes, offers a cost-effective and efficient alternative. Over the past decade, large-scale genome-wide association studies have identified numerous genetic variants linked to OA risk factors, facilitating MR study design. In this review, we systematically identified 52 MR studies meeting specific criteria and evaluated their quality, exploring the impact of lifestyle, nutrition, comorbidities, circulating metabolites, plasma proteins, and other health factors on OA risk. We discuss the results and potential mechanisms of MR findings, addressing conflicting evidence based on existing literature and our prior research. With the ongoing expansion of genome-wide association data, we anticipate MR's role in future OA studies to broaden, particularly in drug development research using targeted MR approaches. We thus aim for this paper to offer valuable insights for researchers and clinicians in related fields.

Major depressive disorder elevates the risk of dentofacial deformity: a bidirectional two-sample Mendelian randomization study

Background

The association between psychiatric disorders and dentofacial deformities has attracted widespread attention. However, their relationship is currently unclear and controversial.

Methods

A two-sample bidirectional MR analysis was performed to study the causal relationship between dentofacial deformity and eight psychiatric disorders, including major depressive disorder, panic disorder, schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, Alzheimer's disease, autism spectrum disorder, and neuroticism. Inverse variance weighted, weighted median, MR-Egger regression, weighted mode four methods, and further sensitivity analyses were conducted.

Results

The major depressive disorder affected dentofacial deformity, with an OR = 1.387 (95% CI = 1.181-1.629, P = 6.77×10-5). No other psychiatric disorders were found to be associated with dentofacial deformity. In turn, dentofacial deformity were associated with neuroticism, with an OR = 1.050 (95% CI = 1.008-1.093, P = 0.018). And there was no evidence that dentofacial deformity would increase the risk of other psychiatric disorders.

Conclusions

Major depressive disorder might elevate the risk of dentofacial deformities, and dentofacial deformity conditions would increase the risk of the incidence of neuroticism.

A clinical study based on bidirectional Mendelian randomization: Correlation between generalized anxiety disorder and weight-bearing joints osteoarthritis

Objectives

Bidirectional Mendelian randomization (MR) combined with clinical case analysis was used to elucidate the relationship between generalized anxiety disorder (GAD) caused by mental overload and the risk of weight-bearing joint (hip/knee) osteoarthritis (OA).

Methods

We performed MR analyses using publicly released genome-wide association study summary statistics to measure the causal effects between mental overload and weight-bearing joint OA risk. The primary MR analysis utilized the inverse-variance weighted (IVW) method, complemented by additional methods, including simple mode, weighted mode, MR-Egger regression, and weighted median. The leave-one-out method was used for sensitivity analysis. Concurrently, data from patients with OA (Kellgren-Lawrence grades III-IV) who needed total knee/hip arthroplasty were collected. Patient assessments were conducted utilizing the Western Ontario and McMaster Universities arthritis index, Penn State worry questionnaire, and visual analogue scale.

Results

Genetically predisposed GAD did not correlate with the risk of weight-bearing joint OA (IVW odds ratio [OR] = 0.840, 95 % confidence interval = 0.128, 5.50, P = 0.855). In reverse MR analyses, we detected no causal effect of weight-bearing OA on GAD (IVW OR = 1.00, 95 % CI = 0.985, 1.03, P = 0.687). In the clinical case evaluation, weight overload joint OA and GAD were highly correlated.

Conclusion

MR analysis indicated no bidirectional causal effect of GAD caused by mental overload on weight-bearing joint (hip or knee) OA. Clinical studies support the finding that GAD is highly correlated with weight-bearing joint OA. However, whether there is a causal relationship between GAD caused by mental overload and weight-overloading joint OA requires further investigation.

Sleep duration and the risk of new-onset arthritis in middle-aged and older adult population: results from prospective cohort study in China

Background

The pain and sleep disorders caused by arthritis are health issues that have been re-emphasized with the aging population. However, the majority of research on arthritis and sleep disorders has focused on cases that have already been diagnosed with arthritis. This research aims to explore the correlation between sleep duration and new-onset arthritis in middle-aged and older adult individuals.

Methods

Utilizing data from the China Health and Retirement Longitudinal Study from baseline (2011) to the Wave 3 follow-up (2018), we conducted a 7-year longitudinal investigation targeting populations with valid sleep questionnaire records and without arthritis. Sleep duration was assessed from nighttime sleep and daytime nap records. The new-onset of arthritis was determined based on self-reported diagnosis. We employed different logistic regression models to consider the potential impact of sleep duration on arthritis and conducted mediation analyses to assess the involvement of BMI in the association between sleep duration and the new-onset risk of arthritis.

Results

Out of the 6,597 individuals analyzed in the cohort, 586 (8.9%) were diagnosed with new-onset arthritis. Median sleep duration was notably shorter in the new-onset arthritis group (6.63 vs. 6.41 h, p < 0.05). There was a notable negative correlation found between new-onset risk of arthritis and sleep duration, with each Interquartile Range (IQR) increment in sleep leading to a 16% risk reduction (OR: 0.864; 95% CI: 0.784-0.954). Stratified analyses revealed BMI as a potential modifier in the sleep-arthritis relationship (P for interaction = 0.05). Mediation analyses further showed that about 3.5% of the association was mediated by BMI. Additionally, the inclusion of sleep duration improved the arthritis predictive power of our model, with an IDI of 0.105 (0.0203, 0.1898) and an NRI of 0.0013 (0.0004, 0.0022) after adding sleep duration to the basic model.

Conclusion

In the middle-aged and older adult demographic of China, increased sleep duration is associated with a decreased new-onset risk of arthritis, with BMI potentially playing a role in mediating this connection.

Causal relationship between sarcopenia with osteoarthritis and the mediating role of obesity: a univariate, multivariate, two-step Mendelian randomization study

BACKGROUND

Recent genetic evidence supports a causal role for sarcopenia in osteoarthritis, which may be mediated by the occurrence of obesity or changes in circulating inflammatory protein levels. Here, we leveraged publicly available genome-wide association study data to investigate the intrinsic causal relationship between sarcopenia, obesity, circulating inflammatory protein levels, and osteoarthritis.

METHODS

In this study, we used Mendelian randomization analyses to explore the causal relationship between sarcopenia phenotypes (Appendicular lean mass [ALM], Low hand-grip strength [LHG], and usual walking pace [UWP]) and osteoarthritis (Knee osteoarthritis [KOA], and Hip osteoarthritis [HOA]). Univariable Mendelian randomization (UVMR) analyses were performed using the inverse variance weighted (IVW) method, MR-Egger, weighted median method, simple mode, and weighted mode, with the IVW method being the primary analytical technique. Subsequently, the independent causal effects of sarcopenia phenotype on osteoarthritis were investigated using multivariate Mendelian randomization (MVMR) analysis. To further explore the mechanisms involved, obesity and circulating inflammatory proteins were introduced as the mediator variables, and a two-step Mendelian randomization analysis was used to explore the mediating effects of obesity and circulating inflammatory proteins between ALM and KOA as well as the mediating proportions.

RESULTS

UVMR analysis showed a causal relationship between ALM, LHG, UWP and KOA [(OR = 1.151, 95% CI: 1.087-1.218, P = 1.19 × 10-6, PFDR = 7.14 × 10-6) (OR = 1.215, 95% CI: 1.004-1.470; P = 0.046, PFDR = 0.055) (OR = 0.503, 95% CI: 0.292-0.867; P = 0.013, PFDR = 0.027)], and a causal relationship between ALM, UWP and HOA [(OR = 1.181, 95% CI: 1.103-1.265, P = 2.05 × 10-6, PFDR = 6.15 × 10-6) (OR = 0.438, 95% CI: 0.226-0.849, P = 0.014, PFDR = 0.022)]. In the MVMR analyses adjusting for confounders (body mass index, insomnia, sedentary behavior, and bone density), causal relationships were observed between ALM, LHG, UWP and KOA [(ALM: OR = 1.323, 95%CI: 1.224- 1.431, P = 2.07 × 10-12), (LHG: OR = 1.161, 95%CI: 1.044- 1.292, P = 0.006), (UWP: OR = 0.511, 95%CI: 0.290- 0.899, P = 0.020)], and between ALM and HOA (ALM: OR = 1.245, 95%CI: 1.149- 1.348, P = 7.65 × 10-8). In a two-step MR analysis, obesity was identified to play a potential mediating role in ALM and KOA (proportion mediated: 5.9%).

CONCLUSIONS

The results of this study suggest that decreased appendicular lean mass, grip strength, and walking speed increase the risk of KOA and decreased appendicular lean mass increases the risk of HOA in patients with sarcopenia in a European population. Obesity plays a mediator role in the occurrence of KOA due to appendicular lean body mass reduction.

Association between nighttime sleep duration and quality with knee osteoarthritis in middle-aged and older Chinese: A longitudinal cohort study

BACKGROUND

The association between nighttime sleep duration and sleep quality with the risk of knee osteoarthritis (OA) remains unclear. This study aimed to examine the longitudinal association among middle-aged and older adults in China.

METHODS

The data used in this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS) surveys conducted in 2011 and 2015. Nighttime sleep duration was categorized into five groups: <6 h, 6 to <7 h, 7 to <8 h, 8 to <9 h, and ≥9 h/night. Sleep quality was assessed by restless days in the past week (<1, 1-2, 3-4, and 5-7 days/week). Multivariate logistic regression models were used to assess the association between sleep duration and quality with incident knee OA.

RESULTS

A total of 11,114 participants who did not have knee OA at baseline were enrolled in this study. After 4 years of follow-up, the overall incidence of knee OA was 8.07 %. Compared to 7 to <8 h of sleep duration, short sleep duration (<6 h/night) was associated with a significantly increased risk of incident knee OA in the fully adjusted model [odds ratio (OR) =1.73, 95 % confidence interval (CI): 1.33-2.25]. Additionally, participants with 5-7 sleep restless days/week were associated with significantly increased risk of incident knee OA (OR = 1.88, 95 % CI: 1.48-2.38).

CONCLUSIONS

Short nighttime sleep duration and poor sleep quality are associated with increased risk of incident knee OA.

Causal Factors for Osteoarthritis: A Scoping Review of Mendelian Randomization Studies

OBJECTIVE

Mendelian randomization (MR) has increasingly been utilized as a tool for establishing causal relations between modifiable exposures and osteoarthritis (OA). The goal of this review was to summarize available MR studies of OA that evaluate the causal role of modifiable risk factors on OA.

METHODS

This review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews model. We performed a literature search for relevant studies published before December 2021 across multiple databases using the search terms "osteoarthritis" and ("Mendelian randomization" or "polygenic risk score"). We reported the MR estimates of causal associations between exposures and OA and then assessed methodologic quality of abstracted studies according to their efforts to validate the three key MR assumptions.

RESULTS

Our search identified 45 studies reporting on 141 exposure-association analyses. All studies performed a formal instrumental variable analysis to estimate the causal effect of exposure on OA. Causal associations (P < 0.05) were reported in 60 of these analyses representing 36 unique publications, and MR-Egger sensitivity analyses were performed in 45 of these analyses. MR studies provided support for causal associations of OA with increased levels of adiposity, coffee consumption, bone mineral density, and sleep disturbance, and decreased levels of serum calcium and low-density lipoprotein cholesterol.

CONCLUSION

These results highlight the potential benefits of weight reduction and improvement of sleep quality to reduce the risk of OA and call for a better understanding of the relations of coffee consumption and serum calcium to OA risk.

Association of Life's Essential 8 with osteoarthritis in United States adults: mediating effects of dietary intake of live microbes

Objective

Osteoarthritis (OA) is associated with cardiovascular disease and represents a persistent economic and physical burden on patients in the United States. This study evaluated the mediating effect of dietary live microbe intake on the association between cardiovascular health [based on Life's Essential 8 (LE8) scores] and osteoarthritis (OA) in adults.

Methods

This cross-sectional study included data from the National Health and Nutrition Examination Survey, 1999-2019 (from patients aged ≥20 years). LE8 scores (0-100) were measured according to the American Heart Association definition and categorized as low (0-49), moderate (50-79), or high (80-100). OA disease status was assessed using self-reported data from patients. The relationships were evaluated using multivariate logistic and restricted cubic spline models. Mediation analysis was used to evaluate the mediating effect of dietary live microbe intake on the association between LE8 and OA risk.

Results

The study included 23,213 participants aged ≥20 years. After adjusting for latent confounders, higher LE8 scores were found to be associated with a lower incidence of OA. The odds ratios (with 95% confidence intervals) for low, moderate, and high OA risk were 0.81 (0.69, 0.96) and 0.55 (0.44, 0.69), respectively; a non-linear dose-response relationship was observed (P-nonlinear = 0.012). Health behavior and health factor scores showed a similar pattern of correlation with OA risk. Low live microbe intake mediated the association between LE8, health behavior, and health factor scores with OA risk and did not appear to reduce OA risk.

Conclusion

Our findings suggest that although higher LE8 scores reduce the risk of developing OA, low live microbe intake may reduce the protective effect of higher scores. It is, therefore, essential to emphasize adherence to a lifestyle that confers high LE8 scores. Individuals should also be advised to reduce the intake of foods with low live microbe content.

Selection of genetic instruments in Mendelian randomisation studies of sleep traits

This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.

The Effect of Sleep on Metabolism, Musculoskeletal Disease, and Mortality in the General US Population: Analysis of Results From the National Health and Nutrition Examination Survey

BACKGROUND

Sleep is an important physiological behavior in humans that is associated with the occurrence and development of various diseases. However, the association of sleep duration with health-related outcomes, including obesity-related factors, musculoskeletal diseases, and mortality because of different causes, has not been systematically reported.

OBJECTIVE

This study aims to systematically investigate the effect of sleep duration on health-related outcomes.

METHODS

Overall, 54,664 participants with sleep information from 8 survey cycles of the National Health and Nutrition Examination Survey (2005-2020) were included in the analysis. Health-related outcomes comprised obesity-related outcomes (ie, BMI, obesity, waist circumference, and abdominal obesity), metabolism-related outcomes (ie, uric acid, hyperuricemia, and bone mineral density [BMD]), musculoskeletal diseases (ie, osteoarthritis [OA] and rheumatoid arthritis [RA]), and mortality because of different causes. The baseline information of participants including age, sex, race, educational level, marital status, total energy intake, physical activity, alcohol consumption, smoking, hypertension, and diabetes was also collected as covariates. Information about the metabolism index, disease status, and covariates was acquired from the laboratory, examination, and questionnaire data. Survival information, including survival status, duration, and cause of death, was obtained from the National Death Index records. Quantile regression models and Cox regression models were used for association analysis between sleep duration and health-related outcomes. In addition, the threshold effect analysis, along with smooth curve fitting method, was applied for the nonlinear association analysis.

RESULTS

Participants were divided into 4 groups with different sleep durations. The 4 groups showed significant differences in terms of baseline data (P<.001). The quantile regression analysis indicated that participants with increased sleep duration showed decreased BMI (β=-.176, 95% CI -.220 to -.133; P<.001), obesity (odds ratio [OR] 0.964, 95% CI 0.950-0.977; P<.001), waist circumference (β=-.219, 95% CI -.320 to -.117; P<.001), abdominal obesity (OR 0.975, 95% CI 0.960-0.990; P<.001), OA (OR 0.965, 95% CI 0.942-0.990; P=.005), and RA (OR 0.940, 95% CI 0.912-0.968; P<.001). Participants with increased sleep duration also showed increased BMD (β=.002, 95% CI .001-.003; P=.005), as compared with participants who slept <5.5 hours. A significant saturation effect of sleep duration on obesity, abdominal obesity, and hyperuricemia was detected through smooth curve fitting and threshold effect analysis (sleep duration>inflection point). In addition, a significant threshold effect of sleep duration on BMD (P<.001); OA (P<.001); RA (P<.001); and all-cause (P<.001), cardiovascular disease-cause (P<.001), cancer-cause (P=.005), and diabetes-cause mortality (P<.001) was found. The inflection point was between 6.5 hours and 9 hours.

CONCLUSIONS

The double-edged sword effect of sleep duration on obesity-related outcomes, embolism-related diseases, musculoskeletal diseases, and mortality because of different causes was detected in this study. These findings provided epidemiological evidence that proper sleep duration may be an important factor in the prevention of multisystem diseases.

Unravelling the liver-brain connection: A two-sample Mendelian randomization study investigating the causal relationship between NAFLD and cortical structure

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) has been linked to cognitive decline and neuropsychiatric conditions, implying a potential connection between NAFLD and brain health. However, the causal association between NAFLD and cortical changes remains uncertain. This study aimed to examine the causal impact of NAFLD on cortical structures using a two-sample Mendelian randomization (MR) approach.

METHODS

Summary data from genome-wide association studies (GWAS) for NAFLD were gathered from large-scale cohorts. Surface area (SA) and cortical thickness (TH) measurements were derived from Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium magnetic resonance imaging (MRI) data of 33,992 participants. Inverse-variance weighted (IVW) served as the primary method. Additional sensitivity analyses, including MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), MR-Egger, and weighted median procedures, were conducted to detect heterogeneity and pleiotropy.

RESULTS

Our MR analysis revealed that NAFLD led to notable alterations in cortical structures, particularly in the pars orbitalis gyrus. Specifically, genetically predicted NAFLD was linked to a decrease in TH (β = -0.008 mm, 95 % CI: -0.013 mm to -0.004 mm, P = 3.00 × 10-4) within this region. No significant heterogeneity and pleiotropy were identified.

CONCLUSION

The two-sample MR study supports the existence of a liver-brain axis by demonstrating a causal association between NAFLD and changes in cortical structures. These findings emphasize the potential association between NAFLD and brain health, which could have implications for preventing and treating cognitive deficits and neuropsychiatric conditions in patients with NAFLD.

Sleep disturbance and decrements in morning energy contribute to a higher symptom burden in oncology patients

OBJECTIVE/BACKGROUND

An emerging area of research is the relationship between sleep disturbance and decrements in energy. Given the paucity of research on the co-occurrence of these two symptoms, study purposes were to identify subgroups of oncology patients with distinct joint sleep disturbance AND morning energy profiles and evaluate for differences among the subgroups in demographic, clinical, and sleep disturbance characteristics, as well as the severity of other common symptoms and QOL outcomes.

PATIENTS/METHODS

Patients (n = 1336) completed measures of sleep disturbance and energy 6 times over two cycles of chemotherapy. All of the other measures were completed at enrollment. Latent profile analysis was used to identify the distinct joint sleep disturbance and morning energy profiles.

RESULTS

Three distinct profiles were identified (i.e., Low Sleep Disturbance and High Morning Energy (Normal, 20.6%), Moderate Sleep Disturbance and Low Morning Energy (Moderately Severe, 52.1%), Very High Sleep Disturbance and Very Low Morning Energy (Very Severe, 27.3%). Compared to Normal class, other two classes were more likely to be female, less likely to be employed, and had higher comorbidity burden and poorer functional status. Symptom scores and QOL outcomes exhibited a dose response effect (i.e., as the profile worsened, symptom scores increased and QOL scores decreased).

CONCLUSIONS

Given the associations between sleep disturbance and decrements in energy and a higher symptom burden, poorer QOL outcomes, and increased mortality, assessment of these two symptoms needs to be a high priority for clinicians and appropriate interventions initiated.

The interplay between symptoms of insomnia and pain in people with osteoarthritis: A narrative review of the current evidence

Osteoarthritis (OA) is a leading cause of disability worldwide and clinical pain is the major symptom of OA. This clinical OA-related pain is firmly associated with symptoms of insomnia, which are reported in up to 81% of people with OA. Since understanding the association between both symptoms is critical for their appropriate management, this narrative review synthesizes the existing evidence in people with OA on i) the mechanisms underlying the association between insomnia symptoms and clinical OA-related pain, and ii) the effectiveness of conservative non-pharmacological treatments on insomnia symptoms and clinical OA-related pain. The evidence available identifies depressive symptoms, pain catastrophizing and pain self-efficacy as mechanisms partially explaining the cross-sectional association between insomnia symptoms and pain in people with OA. Furthermore, in comparison to treatments without a specific insomnia intervention, the ones including an insomnia intervention appear more effective for improving insomnia symptoms, but not for reducing clinical OA-related pain. However, at a within-person level, treatment-related positive effects on insomnia symptoms are associated with a long-term pain reduction. Future longitudinal prospective studies offering fundamental insights into neurobiological and psychosocial mechanisms explaining the association between insomnia symptoms and clinical OA-related pain will enable the development of effective treatments targeting both symptoms.

Multidimensional Sleep Health Prior to SARS-CoV-2 Infection and Risk of Post-COVID-19 Condition

Importance

The association of multiple healthy sleep dimensions with post-COVID-19 condition (PCC), also known as long COVID, has not been investigated.

Objective

To examine whether multidimensional sleep health before and during the COVID-19 pandemic, prior to SARS-CoV-2 infection, was associated with the risk of PCC.

Design, Setting, and Participants

This prospective cohort study (2015-2021) included Nurses' Health Study II participants who reported testing positive (n = 2303) for SARS-CoV-2 infection in a substudy series of COVID-19-related surveys (n = 32 249) between April 2020 and November 2021. After exclusion for incomplete information about sleep health and nonresponse to a question about PCC, 1979 women were included in the analysis.

Exposures

Sleep health was measured both before (June 1, 2015, to May 31, 2017) and early (April 1 to August 31, 2020) in the COVID-19 pandemic. Prepandemic sleep score was defined according to 5 dimensions: morning chronotype (assessed in 2015), 7 to 8 hours of sleep per day, low insomnia symptoms, no snoring, and no frequent daytime dysfunction (all assessed in 2017). On the first COVID-19 substudy survey (returned between April and August 2020), average daily sleep duration and sleep quality for the past 7 days were queried.

Main Outcomes and Measures

SARS-CoV-2 infection and PCC (≥4 weeks of symptoms) were self-reported during 1 year of follow-up. Comparisons were examined between June 8, 2022, and January 9, 2023, using Poisson regression models.

Results

Of the 1979 participants reporting SARS-CoV-2 infection (mean [SD] age, 64.7 [4.6] years; 1979 [100%] female; and 1924 [97.2%] White vs 55 [2.8%] other races and ethnicities), 845 (42.7%) were frontline health care workers, and 870 (44.0%) developed PCC. Compared with women who had a prepandemic sleep score of 0 or 1 (least healthy), those who scored 5 (most healthy) had a 30% lower risk of developing PCC (multivariable-adjusted relative risk, 0.70; 95% CI, 0.52-0.94; P for trend <.001). Associations did not differ by health care worker status. No or little daytime dysfunction prepandemic and good sleep quality during the pandemic were independently associated with a lower risk of PCC (relative risk, 0.83 [95% CI, 0.71-0.98] and 0.82 [95% CI, 0.69-0.99], respectively). Results were similar when PCC was defined as having 8 or more weeks of symptoms or as having ongoing symptoms at the time of PCC assessment.

Conclusions and Relevance

The findings indicate that healthy sleep measured prior to SARS-CoV-2 infection, both before and during the COVID-19 pandemic, may be protective against PCC. Future research should investigate whether interventions on sleep health may prevent PCC or improve PCC symptoms.

Causal association of sleep disturbances and low back pain: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have shown that low back pain (LBP) often coexists with sleep disturbances, however, the causal relationship remains unclear. In the present study, the causal relationship between sleep disturbances and LBP was investigated and the importance of sleep improvement in the comprehensive management of LBP was emphasized.

METHODS

Genetic variants were extracted as instrumental variables (IVs) from the genome-wide association study (GWAS) of insomnia, sleep duration, short sleep duration, long sleep duration, and daytime sleepiness. Information regarding genetic variants in LBP was selected from a GWAS dataset and included 13,178 cases and 164,682 controls. MR-Egger, weighted median, inverse-variance weighted (IVW), penalized weighted median, and maximum likelihood (ML) were applied to assess the causal effects. Cochran's Q test and MR-Egger intercept were performed to estimate the heterogeneity and horizontal pleiotropy, respectively. Outliers were identified and eliminated based on MR-PRESSO analysis to reduce the effect of horizontal pleiotropy on the results. Removing each genetic variant using the leave-one-out analysis can help evaluate the stability of results. Finally, the reverse causal inference involving five sleep traits was implemented.

RESULTS

A causal relationship was observed between insomnia-LBP (OR = 1.954, 95% CI: 1.119-3.411), LBP-daytime sleepiness (OR = 1.011, 95% CI: 1.004-1.017), and LBP-insomnia (OR = 1.015, 95% CI: 1.004-1.026), however, the results of bidirectional MR analysis between other sleep traits and LBP were negative. The results of most heterogeneity tests were stable and specific evidence was not found to support the disturbance of horizontal multiplicity. Only one outlier was identified based on MR-PRESSO analysis.

CONCLUSION

The main results of our research showed a potential bidirectional causal association of genetically predicted insomnia with LBP. Sleep improvement may be important in comprehensive management of LBP.

Osteoarthritis is positively associated with self-reported sleep trouble in older adults

BACKGROUND

Osteoarthritis (OA) is a leading cause of disability in older adults. Most research has focused on minimizing pain and maximizing physical function so as to maintain patient mobility preceding joint arthroplasty. However, few studies have formally studied the relationship between OA and sleep trouble, although it is clinically recognized that OA may affect sleep.

METHODS

The study was based on the National Health and Nutrition Examination Survey (NHANES) database from 2011-2018. Participants were defined as adults aged 60 years or older with diagnoses of OA and self-reported sleep trouble. Multivariable regression analyses were applied to assess the association between OA and sleep trouble, adjusting for age, sex, body mass index, race/ethnicity, education level, marital status, income, depression level, etc. RESULTS: This study included 4154 participants, consisting of the control group (n = 2966) and the OA group (n = 1188). OA individuals were 2.11 (95% CI 1.79-2.47, p < 0.001) times more likely to have sleep trouble compared with those without OA. On subgroup analyses, there was lower odds ratio value of sleep trouble in men compared with women, and in the highest income group compared with the other income groups.

CONCLUSIONS

OA was positively associated with sleep trouble in older adults, with different odds ratio values among different subgroups. Our results suggest that older adults with OA should be aggressively screened for sleep problems.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

Association of insomnia and daytime sleepiness with low back pain: A bidirectional mendelian randomization analysis

Purpose: Observational research has indicated the presence of a causal relationship between sleep disturbances and low back pain (LBP). However, the link may have been biased by confounding factors. The purpose of this study was to examine the potential causal association of insomnia and daytime sleepiness with LBP by using mendelian randomization (MR). Methods: Genome-wide association study (GWAS) summary statistics of insomnia were obtained from a large-scale GWAS meta-analysis (n = 1,331,010; individuals from UK Biobank and 23andMe) or UK Biobank alone (n = 453,379). The summary statistics of daytime sleepiness were from UK Biobank (n = 452,071) and LBP were provided by the FinnGen Release 6 (210,645 individuals with 16,356 LBP cases and 194,289 controls) or UK Biobank (5,423 cases versus 355,771 controls). Linkage disequilibrium score (LDSC) regression and bidirectional MR analysis was employed to estimate genetic correlation and causal relationship. In the MR analysis, the inverse variance weighted method (IVW) was utilized as the main analysis procedure, while MR-Egger, Weighted median and Robust adjusted profile score (RAPS) were utilized for supplementary analyses. Results: LDSC analysis showed that LBP were significantly genetically correlated with insomnia (rg = 0.57, p = 2.26e-25) and daytime sleepiness (rg = 0.18, p = 0.001). The MR analysis revealed that genetically predicted insomnia was significantly associated with an increased risk of LBP (OR = 1.250, 95% CI: 1.186-1.318; p = 1.69e-16). However, the reverse causality was not confirmed. No evidence was identified supporting causality of daytime sleepiness and LBP. Conclusion: This study demonstrates a putative causal link of insomnia on LBP and a null causal effect of LBP on insomnia. Furthermore, a causal link between daytime sleepiness and LBP were not reported. This finding may stimulate new strategies for patient management in clinical practice, benefiting public health.