Causal association of genetically determined caffeine intake from tea or coffee with bone health: a two-sample Mendelian randomization study.

BACKGROUND: Relationship of caffeine intake and consumption of caffeinated beverages, such as tea and coffee, with bone health remains controversial. This study aimed to evaluate whether genetically determined caffeine intake from tea or coffee has causal effects on overall total body bone mineral density (TB-BMD) and fracture. We also assessed the association with TB-BMD in five age strata. METHODS: Using two-sample Mendelian randomization approach, summary statistics were retrieved from genome-wide association studies (GWAS)/GWAS meta-analyses of caffeine intake from tea (n = 395 866)/coffee (n = 373 522), TB-BMD (n = 66 628), and fracture (n = 426 795). Inverse variance weighted method was adopted as the main univariable analysis. Multivariable analysis was conducted to evaluate whether the causal effect is independent. RESULTS: In univariable analysis, genetically determined caffeine intake from tea had positive association with overall TB-BMD (per SD increase in genetically determined caffeine intake, beta of TB-BMD [in SD]: 0.166; 95% confidence interval (CI): 0.006-0.326) and inverse association with fracture (OR = 0.79; 95% CI: 0.654-0.954). Genetically determined caffeine intake from coffee was also positively associated with overall TB-BMD (beta = 0.231; 95% CI: 0.093-0.369). The association remained significant after adjustment for smoking in multivariable analysis. Genetically determined caffeine intake from tea or coffee was both positively associated with TB-BMD in the age strata of 45-60 years, but we lacked evidence of association in other strata. CONCLUSIONS: Genetically, caffeine intake from tea or coffee may be beneficial to bone health. Due to the ascertainment method of caffeine intake from tea, our study also implied genetically higher tea consumption may improve TB-BMD and lower fracture risk.

Prevalence, incidence, and survival analysis of interstitial lung diseases in Hong Kong: a 16-year population-based cohort study.

Background: Published data on the epidemiology of interstitial lung disease (ILD) in Asia is scarce. Understanding the epidemiology is important for authorities in the health management planning. This study aimed to estimate the prevalence, incidence, and survival of ILD in Hong Kong from 2005 to 2020 and evaluate the change of trend over time. Methods: In this retrospective cohort study, we identified ILD patients between 2005 and 2020 using a territory-wide electronic health record database. Prevalence, incidence rates, and age- and sex-standardised incidence rates with United Nations population in 2020 as a reference were estimated. Trends in prevalence and incidence were analysed using joinpoint regression and the average annual percent change (AAPC) was estimated. Median survival, and risk factors of mortality were evaluated using Cox proportional hazard regression. Findings: We identified 5924 patients and included 5884 of them for analysis. The prevalence of ILD increased from 24.7 to 33.6 per 100,000 population from 2005 to 2020 with an AAPC of 1.94 (95% confidence interval, CI: 1.69-2.34). The standardized incidence rate decreased from 5.36 to 2.57 per 100,000 person from 2005 to 2020 (AAPC -3.56, 95% CI, -4.95 to -1.78). The median survival of ILD was 2.50 (95% CI, 2.32-2.69) years. Male, older age, higher Charlson comorbidity index, and IIP subtype were associated with increased mortality with statistical significance. Interpretation: This study provided the first epidemiological evaluation of ILD in Hong Kong. Further studies on ILD in multiple Asian cities and countries are warranted. Funding: None.

Illicit drug use is associated with lower bone mineral density and bone strength.

Objectives: To evaluate the association of illicit drug use with bone mineral density (BMD) and hip geometric parameters at the narrow neck. Methods: This is a cross-sectional matched cohort study conducted in the Hong Kong Chinese population. Associations with illicit drug use were estimated using linear regression for BMD (lumbar spine and femoral neck) and hip geometrical parameters (cross-sectional area [CSA], cross-sectional moment of inertia [CSMI], section modulus [SM], average cortical thickness [ACT] and BMD at the narrow neck) after adjusting for age, body mass index (BMI), smoking status, drinking status, physical activity, and history of antipsychotic and antidepressant use. Mean difference and 95% confidence intervals (95% CI) were calculated between 108 illicit drug users and 108 controls using an adjusted linear model and cluster-robust standard errors after matching by age and sex. The false discovery rate was used to correct for multiple testing. Results: Illicit drug users had a significantly lower BMD (g/cm2) at the lumbar spine (mean difference: -0.062; 95% CI: -0.108 to -0.015), and femoral neck (mean difference: -0.058; 95% CI: -0.106 to -0.010) in the fully adjusted model. Illicit drug users also had a significantly lower CSA (mean difference: -0.238 cm2; 95% CI: -0.462 to -0.013), ACT (mean difference: -0.018 cm; 95% CI: -0.030 to -0.006) and BMD (mean difference: -0.070 g/cm2; 95% CI: -0.128 to -0.012) at the narrow neck. Conclusions: Illicit drug use is associated with lower BMD and bone strength. Future studies evaluating the risk of illicit drug use with fragility fracture are warranted.

Association of Bone Mineral Density and Bone Turnover Markers with the Risk of Diabetes: Hong Kong Osteoporosis Study and Mendelian Randomization.

Preclinical studies demonstrated that bone plays a central role in energy metabolism. However, how bone metabolism is related to the risk of diabetes in humans is unknown. We investigated the association of bone health (bone mineral density [BMD] and bone turnover markers) with incident type-2 diabetes mellitus (T2DM) based on the Hong Kong Osteoporosis Study (HKOS). A total of 993 and 7160 participants from the HKOS were studied for the cross-sectional and prospective analyses, respectively. The cross-sectional study evaluated the association of BMD and bone biomarkers with fasting glucose and glycated hemoglobin (HbA1c ) levels, whereas the prospective study examined the associations between BMD at study sites and the risk of T2DM by following subjects a median of 16.8 years. Body mass index (BMI) was adjusted in all full models. Mendelian randomization (MR) was conducted for causal inference. In the cross-sectional analysis, lower levels of circulating bone turnover markers and higher BMD were significantly associated with increased fasting glucose and HbA1c levels. In the prospective analysis, higher BMD (0.1 g/cm2 ) at the femoral neck and total hip was associated with increased risk of T2DM with hazard ratios (HRs) of 1.10 (95% confidence interval [CI], 1.03 to 1.18) and 1.14 (95% CI, 1.08 to 1.21), respectively. The presence of osteoporosis was associated with a 30% reduction in risk of T2DM compared to those with normal BMD (HR = 0.70; 95% CI, 0.55 to 0.90). The MR results indicate a robust genetic causal association of estimated BMD (eBMD) with 2-h glucose level after an oral glucose challenge test (estimate = 0.043; 95% CI, 0.007 to 0.079) and T2DM (odds ratio = 1.064; 95% CI, 1.036 to 1.093). Higher BMD and lower levels of circulating bone biomarkers were cross-sectionally associated with poor glycemic control. Moreover, higher BMD was associated with a higher risk of incident T2DM and the association is probably causal. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

COVID-19 and cognitive performance: a Mendelian randomization study.

Background: A substantial proportion of individuals with COVID-19 experienced cognitive impairment after resolution of SARS-CoV-2 infection. We aimed to evaluate whether genetic liability to SARS-CoV-2 infection per se, or more severe COVID-19, is causally linked to cognitive deficit. Methods: We firstly performed univariable Mendelian randomization (MR) analysis to examine whether genetic liability to SARS-CoV-2 infection, hospitalized and severe COVID-19 is causally associated with cognitive performance. To dissect the causal pathway, multivariable MR (MVMR) analysis was conducted by adjusting for five inflammatory markers [C-reactive protein, interleukin (IL)-1ß, IL-6, IL-8, and tumour necrosis factor α, as proxies of systemic inflammation]. Results: In univariable MR analysis, host genetic liability to SARS-CoV-2 infection was associated with lower cognitive performance [inverse variance weighted (IVW) analysis, estimate: -0.023; 95% Confidence Interval (CI): -0.038 to -0.009]. Such causal association was attenuated in MVMR analysis when we adjusted for the five correlated inflammatory markers in one analysis (IVW analysis, estimate: -0.022; 95% CI: -0.049 to 0.004). There was insufficient evidence of association for genetic liability to hospitalized and severe COVID-19 with cognitive performance. Conclusion: The causal effect of host genetic liability to SARS-CoV-2 infection on reduced cognitive performance may be mediated by systemic inflammation. Future studies examining whether anti-inflammatory agents could alleviate cognitive impairment in SARS-CoV-2-infected individuals are warranted.

Development and validation of sex-specific hip fracture prediction models using electronic health records: a retrospective, population-based cohort study.

Background: Hip fracture is associated with immobility, morbidity, mortality, and high medical cost. Due to limited availability of dual-energy X-ray absorptiometry (DXA), hip fracture prediction models without using bone mineral density (BMD) data are essential. We aimed to develop and validate 10-year sex-specific hip fracture prediction models using electronic health records (EHR) without BMD. Methods: In this retrospective, population-based cohort study, anonymized medical records were retrieved from the Clinical Data Analysis and Reporting System for public healthcare service users in Hong Kong aged ≥60 years as of 31 December 2005. A total of 161,051 individuals (91,926 female; 69,125 male) with complete follow-up from 1 January 2006 till the study end date on 31 December 2015 were included in the derivation cohort. The sex-stratified derivation cohort was randomly divided into 80% training and 20% internal testing datasets. An independent validation cohort comprised 3046 community-dwelling participants aged ≥60 years as of 31 December 2005 from the Hong Kong Osteoporosis Study, a prospective cohort which recruited participants between 1995 and 2010. With 395 potential predictors (age, diagnosis, and drug prescription records from EHR), 10-year sex-specific hip fracture prediction models were developed using stepwise selection by logistic regression (LR) and four machine learning (ML) algorithms (gradient boosting machine, random forest, eXtreme gradient boosting, and single-layer neural networks) in the training cohort. Model performance was evaluated in both internal and independent validation cohorts. Findings: In female, the LR model had the highest AUC (0.815; 95% Confidence Interval [CI]: 0.805-0.825) and adequate calibration in internal validation. Reclassification metrics showed the LR model had better discrimination and classification performance than the ML algorithms. Similar performance was attained by the LR model in independent validation, with high AUC (0.841; 95% CI: 0.807-0.87) comparable to other ML algorithms. In internal validation for male, LR model had high AUC (0.818; 95% CI: 0.801-0.834) and it outperformed all ML models as indicated by reclassification metrics, with adequate calibration. In independent validation, the LR model had high AUC (0.898; 95% CI: 0.857-0.939) comparable to ML algorithms. Reclassification metrics demonstrated that LR model had the best discrimination performance. Interpretation: Even without using BMD data, the 10-year hip fracture prediction models developed by conventional LR had better discrimination performance than the models developed by ML algorithms. Upon further validation in independent cohorts, the LR models could be integrated into the routine clinical workflow, aiding the identification of people at high risk for DXA scan. Funding: Health and Medical Research Fund, Health Bureau, Hong Kong SAR Government (reference: 17181381).

Unravelling genetic causality of haematopoiesis on bone metabolism in human.

Objective: Haematopoiesis was shown to regulate bone metabolism in in vivo studies. However, whether haematopoiesis has causal effects on bone health has never been investigated in humans. We aimed to evaluate the causal relationships of blood traits with bone mineral density (BMD) and fracture. Design and methods: Using two-sample Mendelian randomization, causal relationship of 29 blood traits with estimated BMD (eBMD), total body BMD (TBBMD), lumbar spine BMD (LSBMD), femoral neck BMD (FNBMD) and fracture were evaluated by inverse-variance weighted (IVW) method and multiple sensitivity analyses. Relevant genetic data were obtained from the largest possible publicly available genome-wide association studies. Results: Eight genetically determined red blood cell traits showed positive causal effects on eBMD, with beta estimates ranging from 0.009 (mean corpuscular haemoglobin) to 0.057 (haemoglobin concentration), while three white blood cell traits, including lymphocyte count (beta: -0.020; 95% CI: -0.033 to -0.007), neutrophil count (beta: -0.020; 95% CI: -0.035 to -0.006) and white blood cell count (beta: -0.027; 95% CI: -0.039 to -0.014), were inversely associated with eBMD. Causal effects for six of these blood traits were validated on TBBMD, LSBMD, FNBMD and/or fracture. The association of reticulocyte count (beta: 0.040; 95% CI: 0.016 to 0.063), haemoglobin (beta: 0.058; 95% CI: 0.021 to 0.094) and mean corpuscular haemoglobin concentration (beta: 0.030; 95% CI: 0.007 to 0.054) with eBMD remained significant in multivariable IVW analyses adjusted for other blood traits. Conclusion: This study provided evidence that haematopoietic system might regulate the skeletal system in humans and suggested the possible pathophysiology of bone diseases among people with haematological diseases. Significance statement: We conducted a novel Mendelian randomization study investigating the causal relationship of blood cells with bone mineral density. Red and white blood cell traits have positive and inverse causal relationship with bone mineral density, respectively, suggesting a potential link of haematopoietic system with the skeletal system in humans. Current findings suggest individuals with related haematological diseases, such as anaemia and leukocytosis, may have a lifelong increased risk of osteoporosis and/or fracture. Given that complete blood count is commonly performed in clinical setting, whether complete blood count can be used to predict fracture risk warrants further investigation.

COVID-19 and Thyroid Function: A Bi-Directional Two-Sample Mendelian Randomization Study.

Background: Thyroid dysfunction has been observed among some patients with coronavirus disease (COVID-19). It is unclear whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (or its severity) leads to the development of thyroid dysfunction, or vice versa. In this study, we examined the bi-directional causal relationship between host genetic liability to three COVID-19 phenotypes (including SARS-CoV-2 infection, hospitalized and severe COVID-19) and three thyroid dysfunction traits (including hyperthyroidism, hypothyroidism, and autoimmune thyroid disease [AITD]) and three continuous traits of thyroid hormones (including thyrotropin [TSH] and free thyroxine [fT4] within reference range, and TSH in full range). Methods: Summary statistics from the largest available meta-analyses of human genome-wide association studies were retrieved for the following variables: SARS-CoV-2 infection (n = 1,348,701), COVID-19 hospitalization (n = 1,557,411), severe COVID-19 (n = 1,059,456), hyperthyroidism (n = 51,823), hypothyroidism (n = 53,423), AITD (n = 755,406), TSH within reference range (n = 54,288), fT4 within reference range (n = 49,269), and TSH in full range (n = 119,715). Using a two-sample Mendelian randomization (MR) approach, the inverse-variance weighted (IVW) method was adopted as the main MR analysis. Weighted median, contamination mixture, MR-Egger, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods were applied as sensitivity analyses. Results: Host genetic susceptibility to SARS-CoV-2 infection was causally associated with hypothyroidism in the main IVW analysis (per doubling in prevalence of SARS-CoV-2 infection, odds ratio [OR] = 1.335; 95% confidence interval [CI]: 1.167-1.526; p = 2.4 × 10-5, surpassing the Bonferroni multiple-testing threshold). Similar causal estimates were observed in the sensitivity analyses (weighted median: OR = 1.296; CI: 1.066-1.575; p = 9 × 10-3; contamination mixture: OR = 1.356; CI: 1.095-1.818; p = 0.013; MR-Egger: OR = 1.712; CI: 1.202-2.439; p = 2.92 × 10-3, and MR-PRESSO: OR = 1.335; CI: 1.156-1.542; p = 5.73 × 10-4). Host genetic liability to hospitalized or severe COVID-19 was not associated with thyroid dysfunction or thyroid hormone levels. In the reverse direction, there was no evidence to suggest that genetic predisposition to thyroid dysfunction or genetically determined thyroid hormone levels altered the risk of the COVID-19 outcomes. Conclusions: This bi-directional MR study supports that host response to SARS-CoV-2 viral infection plays a role in the causal association with increased risk of hypothyroidism. Long-term follow-up studies are needed to confirm the expected increased hypothyroidism risk.

Osteoporosis is a novel risk factor of infections and sepsis: A cohort study.

Background: Accumulating evidence suggests the interaction of bone metabolism and the immune system, but how bone health is associated with the risk of infections remains unknown. Methods: This study aimed to investigate the relationship of bone mineral density (BMD) with the risk of common infections and sepsis in Hong Kong Osteoporosis Study (HKOS). A prospective cohort study, initiated in 1995 and followed until 31 December 2020, of 5,717 participants examined the association of BMD at three skeletal sites (lumbar spine, femoral neck, and total hip) with common infections - pneumonia, urinary tract infection (UTI), skin infection, and sepsis. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI). Findings: During the median follow-up of 17 years, higher BMD T-scores at the femoral neck and total hip were significantly associated with the reduced risk of pneumonia (HRs 0.89 and 0.87; 95% CIs 0.82 to 0.98 and 0.81 to 0.95), UTI (HRs 0.85 and 0.86; 95% CIs 0.76 to 0.94 and 0.78 to 0.95), skin infection (HRs 0.85 and 0.82; 95% CIs 0.74 to 0.97 and 0.73 to 0.93), and sepsis (HRs 0.83 and 0.82; 95% CIs 0.71 to 0.97 and 0.72 to 0.94). A significant association was observed for the lumbar spine BMD T-score with the risk of skin infection (HR 0.86; 95% CI: 0.78 to 0.95) but not with other infections and sepsis. Similarly, participants with osteoporosis, but not osteopenia, were significantly associated with an increased risk of infections and sepsis compared to those with normal BMD. Interpretation: BMD is a novel risk factor of infections and sepsis. People with low BMD, particularly those with osteoporosis, are at higher risk of infections and sepsis than those with normal BMD. Further studies on whether improving bone health can reduce the risk of infections and sepsis are warranted. Funding: None.

Validation of diagnostic coding for interstitial lung diseases in an electronic health record system in Hong Kong.

OBJECTIVE: Large electronic medical record (EMR) databases can facilitate epidemiology research into uncommon diseases such as interstitial lung disease (ILD). Given the rarity and diagnostic difficulty of ILD, the validity of the coding in EMR requires clarification. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD-9) code algorithms for identifying ILD in the territory-wide electronic medical health record system of Clinical Data Analysis and Reporting System (CDARS) in Hong Kong. METHOD: Patients who visited the Queen Mary Hospital in 2005-2018 with ILD were identified using the following ICD-9 codes: post-inflammatory pulmonary fibrosis (PPF; ICD-9: 515), idiopathic fibrosing alveolitis (IFA; ICD-9: 516.3), connective tissue disease-associated interstitial lung disease (CTD-ILD; ICD-9: 517.2, 517.8, 714.81), sarcoidosis (ICD-9: 135) and extrinsic allergic alveolitis (EAA; ICD-9: 495). A random selection was conducted in cases with diagnostic code of PPF and IFA, where a relative higher case number was identified. All the cases of CTD-ILD, sarcoidosis and EAA were included in validation for relatively small case number. RESULTS: Two hundred and sixty nine cases were validated using medical record review by a respiratory specialist. The overall positive predictive value (PPV) was 79% (95% CI, 74%-84%). In subgroup analysis, true positive case numbers of PPF, IFA, CTD-ILD, sarcoidosis and EAA were 74/100 (74%), 95/100 (95%), 11/15 (73%), 27/32 (84%) and 6/22 (27%), respectively. CONCLUSIONS: This was the first ICD-9 coding validation for ILD in Hong Kong CDARS. Our study demonstrated that using ICD-9 algorithms 515, 516.3, 517.2, 517.8, 714.81 and 135 enhanced identifications of ILDs with PPV that was reliable to support utility of CDARS database for further clinical research on ILDs. The validity is particularly high with 516.3.

Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study.

BACKGROUND: Depression and cardiovascular disease (CVD) are associated with each other but their relationship remains unclear. We aim to determine whether genetic predisposition to depression are causally linked to CVD [including coronary artery disease (CAD), myocardial infarction (MI), stroke and atrial fibrillation (AF)]. METHODS: Using summary statistics from the largest genome-wide association studies (GWAS) or GWAS meta-analysis of depression (primary analysis: n = 500 199), broad depression (help-seeking behavior for problems with nerves, anxiety, tension or depression; secondary analysis: n = 322 580), CAD (n = 184 305), MI (n = 171 875), stroke (n = 446 696) and AF (n = 1 030 836), genetic correlation was tested between two depression phenotypes and CVD [MI, stroke and AF (not CAD as its correlation was previously confirmed)]. Causality was inferred between correlated traits by Mendelian Randomization analyses. RESULTS: Both depression phenotypes were genetically correlated with MI (depression: rG = 0.169; p = 9.03 × 10-9; broad depression: rG = 0.123; p = 1 × 10-4) and AF (depression: rG = 0.112; p = 7.80 × 10-6; broad depression: rG = 0.126; p = 3.62 × 10-6). Genetically doubling the odds of depression was causally associated with increased risk of CAD (OR = 1.099; 95% CI 1.031-1.170; p = 0.004) and MI (OR = 1.146; 95% CI 1.070-1.228; p = 1.05 × 10-4). Adjustment for blood lipid levels/smoking status attenuated the causality between depression and CAD/MI. Null causal association was observed for CVD on depression. A similar pattern of results was observed in the secondary analysis for broad depression. CONCLUSIONS: Genetic predisposition to depression may have positive causal roles on CAD/MI. Genetic susceptibility to self-awareness of mood problems may be a strong causal risk factor of CAD/MI. Blood lipid levels and smoking may potentially mediate the causal pathway. Prevention and early diagnosis of depression are important in the management of CAD/MI.

Education Attainment, Intelligence and COVID-19: A Mendelian Randomization Study.

BACKGROUND: Evidence of socioeconomic inequality in COVID-19-related outcomes is emerging, with a higher risk of infection and mortality observed among individuals with lower education attainment. We aimed to evaluate the potential interventions against COVID-19 from the socioeconomic perspective, including improvement in education and intelligence. METHODS: With a two-sample Mendelian randomization approach using summary statistics from the largest genome-wide association meta-analysis, univariable analysis was adopted to evaluate the total causal effects of genetically determined education attainment and intelligence on COVID-19 outcomes. Multivariable analysis was performed to dissect the potential mechanisms. RESULTS: Genetic predisposition to higher education attainment by 1 SD (4.2 years) was independently associated with reduced risk of COVID-19 severity (OR = 0.508 [95% CI: 0.417-0.617]; p < 0.001). Genetically higher education attainment also lowered the risk of COVID-19 hospitalization (0.685 [0.593-0.791]; p < 0.001), but the association was attenuated after adjustment for beta estimates of intelligence in multivariable analysis. Genetically higher intelligence was associated with reduced risk of COVID-19 hospitalization (0.780 [0.655-0.930]; p = 0.006), with attenuation of association after adjustment for education attainment. Null association was observed for genetically determined education attainment and intelligence with SARS-CoV-2 infection. CONCLUSION: Education may act independently and jointly with intelligence in improving the COVID-19 outcomes. Improving education may potentially alleviate the COVID-19-related health inequality.

Genetically Determined TSH Level Within Reference Range Is Inversely Associated With Alzheimer Disease.

CONTEXT: Contradictory findings were reported in observational studies on the association of thyroid function (thyrotropin [TSH] and free thyroxine [FT4] levels) with Alzheimer disease (AD). OBJECTIVE: This work aims to determine whether genetically determined TSH/FT4 levels within reference range are causally associated with AD. METHODS: A bidirectional, 2-sample mendelian randomization (MR) study was conducted. With summary statistics from the largest genome-wide association studies (GWAS)/GWAS meta-analysis of TSH level(n ≥ 54 288), FT4 level(n = 49 269), and AD (71 880 cases; 383 378 controls), we used an MR approach to evaluate the bidirectional causal relationship between TSH/FT4 levels and AD. The inverse-variance weighted method was adopted as the main analysis. RESULTS: One SD increase in genetically determined TSH level within reference range was causally associated with a reduced risk of AD (odds ratio: 0.988; 95% CI, 0.977-0.998). A similar inverse association was observed in sex-specific analysis. The causal association was attenuated after adjustment for atrial fibrillation and blood pressure, suggesting they may mediate the causal pathway. A positive causal effect of AD on TSH level was detected only in male participants. This male-specific feedback loop may explain why the largest cohort study to date (Rotterdam Study) demonstrated a null observational association in men. Null association was observed between FT4 level and AD in both directions. CONCLUSION: Genetic predisposition to increased TSH level, even within reference range, may lower the risk of AD, with atrial fibrillation, systolic, and diastolic blood pressure as possible mediators. Given the higher magnitude of risk reduction observed in the Rotterdam Study, whether the causal estimates derived from this MR study are underestimated warrants further investigation.

The effect of different measurement modalities in the association of lean mass with mortality: A systematic review and meta-analysis.

OBJECTIVES: Lean mass is commonly measured by 3 modalities, dual energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), and computerized tomography (CT). CT is considered the most accurate, while lean mass measured by DXA and BIA often consists of non-muscle compartment, and hence considered less accurate when compared with CT. It remains unclear if the association of lean mass with mortality would differ using different measurement modalities. METHODS: A systematic review and meta-analysis of lean mass and mortality was conducted. The analysis was stratified by different measurement modalities and health conditions. Pooled hazard ratios were estimated using a random effects model. RESULTS: This meta-analysis included 188 studies with 98 468 participants. Reduced lean mass measured by BIA, DXA, and CT, was associated with increased risk of mortality with a hazard ratio (HR) of 1.35 (95% CI, 1.21-1.49), 1.18 (95% CI, 1.06-1.30), and 1.44 (95% CI, 1.32-1.57), respectively. Similarly, low lean mass defined by BIA-, DXA-, and CT-measurement was associated with increased risk of mortality, with an HR of 1.81 (95% CI, 1.56-2.10), 1.44 (95% CI, 1.29-1.60), and 1.78 (95% CI, 1.64-1.93). CONCLUSIONS: Reduced and low lean mass were robustly associated with increased mortality in studies using different measurement modalities.

Systematic review and meta-analysis of lean mass and mortality: Rationale and study description.

OBJECTIVES: Muscle mass is one of the key components in defining sarcopenia and is known to be important for locomotion and body homeostasis. Lean mass is commonly used as a surrogate of muscle mass and has been shown to be associated with increased mortality. However, the relationship of lean mass with mortality may be affected by different clinical conditions, modalities used, cut-off point to define low or normal lean mass, and even types of cancer among cancer patients. Thus, we aim to perform a comprehensive meta-analysis of lean mass with mortality by considering all these factors. METHODS: Systematic search was done in PubMed, Cochrane Library and Embase for articles related to lean mass and mortality. Lean mass measured by dual X-ray absorptiometry, bioelectrical impedance analysis, and computerized tomography were included. RESULTS: The number of relevant studies has increased continuously since 2002. A total of 188 studies with 98 468 people were included in the meta-analysis. The association of lean mass with mortality was most studied in cancer patients, followed by people with renal diseases, liver diseases, elderly, people with cardiovascular disease, lung diseases, and other diseases. The meta-analysis can be further conducted in subgroups based on measurement modalities, site of measurements, definition of low lean mass adopted, and types of cancer for studies conducted in cancer patients. CONCLUSIONS: This series of meta-analysis provided insight and evidence on the relationship between lean mass and mortality in all directions, which may be useful for further study and guideline development.

Sarcopenia and mortality in cancer: A meta-analysis.

OBJECTIVES: The aim of this meta-analysis is to comprehensively evaluate the effects of lean mass on all-cause mortality across different cancer types. METHODS: This is a meta-analysis. Cohort studies on lean mass and mortality published before December 20, 2017 were obtained by systematic search on PubMed, Cochrane Library, and Embase. Inclusion criteria were cohort studies reporting lean mass measurements by dual-energy X-ray absorptiometry, bioimpedance analysis or computed tomography, and with all-cause mortality as the study outcome. Exclusion criteria were studies using muscle mass surrogates, anthropometric measurement of muscle, rate of change in muscle mass, and sarcopenia defined by composite criteria. Hazard ratios (HRs) and 95% confidence intervals (CIs) of low/reduced lean mass on cancer mortality were pooled with a random-effects model. Subgroup analysis stratifying studies according to cancer type and measurement index was performed. RESULTS: Altogether 100 studies evaluated the association between lean mass and cancer mortality. The overall pooled HR on cancer mortality was 1.41 (95% CI, 1.24 to 1.59) for every standard deviation decrease in lean mass and 1.69 (95% CI, 1.56 to 1.83) for patients with sarcopenia (binary cutoffs). Overall mortality was also significantly associated with sarcopenia in across various cancer types, except for hematopoietic, breast, ovarian and endometrial, and prostate cancer. CONCLUSIONS: The robust association of decreased lean mass with increased mortality further justified the importance of developing clinical guidelines for managing sarcopenia in cancer patients. Public health initiatives aiming at promoting awareness of muscle health in susceptible individuals are urgently needed.

Different definition of sarcopenia and mortality in cancer: A meta-analysis.

OBJECTIVES: Sarcopenia has been an emerging theme in clinical oncology. Various definitions of sarcopenia have been proposed, but their prognostic performance have yet to be evaluated and compared. The aim of this meta-analysis is to comprehensively evaluate the performance of different cutoff definitions of sarcopenia in cancer mortality prognostication. METHODS: This is a meta-analysis. Cohort studies on lean mass and mortality published before December 20, 2017 were obtained by systematic search on PubMed, Cochrane Library, and Embase. Inclusion criteria were cohort studies reporting binary lean mass categorized according to clearly defined cutoffs, and with all-cause mortality as study outcome. Studies were stratified according to the cutoff(s) used in defining low lean mass. The cutoff-specific hazard ratios (HRs) and 95% confidence intervals (CIs) of low lean mass on cancer mortality were pooled with a random-effects model and compared. RESULTS: Altogether 81 studies that studied binary lean mass were included. The pooled HRs on cancer mortality using the 3 most used definitions were: 1.74 (95% CI, 1.46-2.07) using the definition proposed by International Consensus of Cancer Cachexia, 1.45 (95% CI, 1.21-1.75) using that by Martin, and 1.58 (95% CI, 1.35-1.84) using that by Prado. The associations between sarcopenia and cancer mortality using other definitions were all statistically significant, despite different estimates were observed. CONCLUSIONS: The association of low lean mass with increased mortality was consistent across different definitions; this provides further evidence on the poorer survival in cancer patients with sarcopenia. However, further studies evaluating the performance of each definition are warranted.

Evaluation of causality between ADHD and Parkinson's disease: Mendelian randomization study.

In a retrospective cohort study, patients with attention-deficit hyperactivity disorder (ADHD) and psychostimulant prescription were associated with increased risk of Parkinson's disease (PD). It is unclear whether ADHD per se or psychostimulant prescription is associated with PD. We aim to determine if genetic correlation or/and causal association exists between ADHD and PD using summary statistics obtained from the largest meta-analysis of genome-wide association studies of ADHD (20,183 cases; 35,191 controls) and PD (26,421 cases; 442,271 controls). Genetic correlation was tested between ADHD and PD by linkage disequilibrium score regression. Causal estimate was assessed by inverse-variance weighted (IVW) method as the main mendelian randomization analysis, with sensitivity analyses to detect horizontal pleiotropy. Weak and inverse genetic correlation existed between ADHD and PD (r=-0.100;SE=0.045;P = 0.026). Univariable IVW analysis with 10 and 77 genetic instruments respectively revealed null association for ADHD with PD (OR=0.930 per doubling in odds of ADHD; 95% CI:0.792-1.092) and PD with ADHD (OR=0.986 per doubling in odds of PD; 95% CI:0.956-1.015). Multivariable IVW analyses adjusted for BMI/smoking also revealed null association of ADHD with PD. Using 58 PD-associated genetic instruments, multivariable IVW analysis with/without adjustment for BMI/smoking suggested a weak and inverse causal association for PD on ADHD, but cautious interpretation is required. This well-powered study did not support causality between ADHD and PD. The observed positive association between ADHD and PD is more likely to be caused by unmeasured confounders. As psychostimulant use is associated with high risk of early-onset PD, future research should focus on this area.