A large-scale genome-wide association analysis of lung function in the Chinese population identifies novel loci and highlights shared genetic aetiology with obesity

Real-World Effectiveness of Single-Inhaler Triple Therapy for COPD: Impact of Diabetes Comorbidity

Type 2 diabetes is a frequent comorbidity in chronic obstructive pulmonary disease (COPD) patients, with the GOLD treatment recommendations asserting that the presence of diabetes be disregarded in the choice of treatment.

In a cohort of COPD patients with frequent exacerbations, initiators of single-inhaler triple therapy or dual bronchodilators were compared on the incidence of COPD exacerbation and pneumonia over one year, adjusted by propensity score weighting and stratified by type 2 diabetes.

The COPD cohort included 1,114 initiators of triple inhalers and 4,233 of dual bronchodilators (28% with type 2 diabetes). The adjusted hazard ratio (HR) of exacerbation with triple therapy was 1.04 (95% CI: 0.86-1.25) among COPD patients with type 2 diabetes and 0.74 (0.65-0.85) in those without. The incidence of severe pneumonia was elevated with triple therapy among patients with type 2 diabetes (HR 1.77; 1.14-2.75).

Triple therapy in COPD is effective among those without, but not those with, type 2 diabetes. Future therapeutic trials in COPD should consider diabetes comorbidity.

Exploiting meta-analysis of genome-wide interaction with serum 25-hydroxyvitamin D to identify novel genetic loci associated with pulmonary function

BACKGROUND

Higher 25-hydroxyvitamin D (25(OH)D) concentrations in serum has a positive association with pulmonary function. Investigating genome-wide interactions with 25(OH)D may reveal new biological insights into pulmonary function.

OBJECTIVES

We aimed to identify novel genetic variants associated with pulmonary function by accounting for 25(OH)D interactions.

METHODS

We included 211,264 participants from the observational United Kingdom Biobank study with pulmonary function tests (PFTs), genome-wide genotypes, and 25(OH)D concentrations from 4 ancestral backgrounds-European, African, East Asian, and South Asian. Among PFTs, we focused on forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) because both were previously associated with 25(OH)D. We performed genome-wide association study (GWAS) analyses that accounted for variant×25(OH)D interaction using the joint 2 degree-of-freedom (2df) method, stratified by participants' smoking history and ancestry, and meta-analyzed results. We evaluated interaction effects to determine how variant-PFT associations were modified by 25(OH)D concentrations and conducted pathway enrichment analysis to examine the biological relevance of our findings.

RESULTS

Our GWAS meta-analyses, accounting for interaction with 25(OH)D, revealed 30 genetic variants significantly associated with FEV1 or FVC (P2df <5.00×10-8) that were not previously reported for PFT-related traits. These novel variant signals were enriched in lung function-relevant pathways, including the p38 MAPK pathway. Among variants with genome-wide-significant 2df results, smoking-stratified meta-analyses identified 5 variants with 25(OH)D interactions that influenced FEV1 in both smoking groups (never smokers P1df interaction<2.65×10-4; ever smokers P1df interaction<1.71×10-5); rs3130553, rs2894186, rs79277477, and rs3130929 associations were only evident in never smokers, and the rs4678408 association was only found in ever smokers.

CONCLUSION

Genetic variant associations with lung function can be modified by 25(OH)D, and smoking history can further modify variant×25(OH)D interactions. These results expand the known genetic architecture of pulmonary function and add evidence that gene-environment interactions, including with 25(OH)D and smoking, influence lung function.

Using human genetics to understand the phenotypic association between chronotype and breast cancer

Little is known regarding the shared genetic influences underlying the observed phenotypic association between chronotype and breast cancer in women. Leveraging summary statistics from the hitherto largest genome-wide association study conducted in each trait, we investigated the genetic correlation, pleiotropic loci, and causal relationship of chronotype with overall breast cancer, and with its subtypes defined by the status of oestrogen receptor. We identified a negative genomic correlation between chronotype and overall breast cancer (r g  = -0.06, p = 3.00 × 10-4), consistent across oestrogen receptor-positive (r g  = -0.05, p = 3.30 × 10-3) and oestrogen receptor-negative subtypes (r g  = -0.05, p = 1.11 × 10-2). Five specific genomic regions were further identified as contributing a significant local genetic correlation. Cross-trait meta-analysis identified 78 loci shared between chronotype and breast cancer, of which 23 were novel. Transcriptome-wide association study revealed 13 shared genes, targeting tissues of the nervous, cardiovascular, digestive, and exocrine/endocrine systems. Mendelian randomisation demonstrated a significantly reduced risk of overall breast cancer (odds ratio 0.89, 95% confidence interval 0.83-0.94; p = 1.30 × 10-4) for genetically predicted morning chronotype. No reverse causality was found. Our work demonstrates an intrinsic link underlying chronotype and breast cancer, which may provide clues to inform management of sleep habits to improve female health.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

A genome-wide association study based on the China Kadoorie Biobank identifies genetic associations between snoring and cardiometabolic traits

Despite the high prevalence of snoring in Asia, little is known about the genetic etiology of snoring and its causal relationships with cardiometabolic traits. Based on 100,626 Chinese individuals, a genome-wide association study on snoring was conducted. Four novel loci were identified for snoring traits mapped on SLC25A21, the intergenic region of WDR11 and FGFR, NAA25, ALDH2, and VTI1A, respectively. The novel loci highlighted the roles of structural abnormality of the upper airway and craniofacial region and dysfunction of metabolic and transport systems in the development of snoring. In the two-sample bi-directional Mendelian randomization analysis, higher body mass index, weight, and elevated blood pressure were causal for snoring, and a reverse causal effect was observed between snoring and diastolic blood pressure. Altogether, our results revealed the possible etiology of snoring in China and indicated that managing cardiometabolic health was essential to snoring prevention, and hypertension should be considered among snorers.

Genome-wide association study of preserved ratio impaired spirometry (PRISm)

BACKGROUND

Preserved ratio impaired spirometry (PRISm) is defined as a forced expiratory volume in 1 s (FEV1) <80% predicted and FEV1/forced vital capacity ≥0.70. PRISm is associated with respiratory symptoms and comorbidities. Our objective was to discover novel genetic signals for PRISm and see if they provide insight into the pathogenesis of PRISm and associated comorbidities.

METHODS

We undertook a genome-wide association study (GWAS) of PRISm in UK Biobank participants (Stage 1), and selected single nucleotide polymorphisms (SNPs) reaching genome-wide significance for replication in 13 cohorts (Stage 2). A combined meta-analysis of Stage 1 and Stage 2 was done to determine top SNPs. We used cross-trait linkage disequilibrium score regression to estimate genome-wide genetic correlation between PRISm and pulmonary and extrapulmonary traits. Phenome-wide association studies of top SNPs were performed.

RESULTS

22 signals reached significance in the joint meta-analysis, including four signals novel for lung function. A strong genome-wide genetic correlation (rg) between PRISm and spirometric COPD (rg=0.62, p<0.001) was observed, and genetic correlation with type 2 diabetes (rg=0.12, p=0.007). Phenome-wide association studies showed that 18 of 22 signals were associated with diabetic traits and seven with blood pressure traits.

CONCLUSION

This is the first GWAS to successfully identify SNPs associated with PRISm. Four of the signals, rs7652391 (nearest gene MECOM), rs9431040 (HLX), rs62018863 (TMEM114) and rs185937162 (HLA-B), have not been described in association with lung function before, demonstrating the utility of using different lung function phenotypes in GWAS. Genetic factors associated with PRISm are strongly correlated with risk of both other lung diseases and extrapulmonary comorbidity.

Association between severe bronchiolitis in infancy and age 6-year lung function

BACKGROUND AND OBJECTIVES

Understanding early life risk factors for decreased lung function could guide prevention efforts and improve lung health throughout the lifespan. Our objective was to investigate the association between history of severe (hospitalized) bronchiolitis in infancy and age 6-year lung function.

METHODS

We analyzed data from two prospective cohort studies: infants hospitalized with bronchiolitis and a parallel cohort of healthy infants. Children were followed longitudinally, and spirometry was performed at age 6 years. To examine the relationship between history of severe bronchiolitis and primary outcomes - FEV1% predicted (pp) and FEV1/FVCpp - we used multivariable linear regression models adjusted for insurance status, perterm birth, secondhand smoke exposure, breastfeeding status, traffic-related air pollution and polygenic risk score. Secondary outcomes included FVCpp and bronchodilator responsiveness (BDR).

RESULTS

Age 6-year spirometry was available for 425 children with history of severe bronchiolitis in infancy and 48 controls. Unadjusted analysis revealed that while most children had normal range lung function, children with a history of severe bronchiolitis had lower FEV1pp and FEV1/FVCpp. In adjusted analyses, the same findings were observed: FEV1pp was 8% lower (p = 0.004) and FEV1/FVCpp was 4% lower (p = 0.007) in children with history of severe bronchiolitis versus controls. FVC and BDR did not differ between groups.

CONCLUSIONS

Children with severe bronchiolitis in infancy have decreased FEV1 and FEV1/FVC at age 6 years, compared to controls. These children may be at increased risk for chronic respiratory illness later in life.

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

BACKGROUND

Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.

METHODS

Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately.

RESULTS

In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model.

CONCLUSIONS

In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.

Epigenome-wide association analysis of infant bronchiolitis severity: a multicenter prospective cohort study

Bronchiolitis is the most common lower respiratory infection in infants, yet its pathobiology remains unclear. Here we present blood DNA methylation data from 625 infants hospitalized with bronchiolitis in a 17-center prospective study, and associate them with disease severity. We investigate differentially methylated CpGs (DMCs) for disease severity. We characterize the DMCs based on their association with cell and tissues types, biological pathways, and gene expression. Lastly, we also examine the relationships of severity-related DMCs with respiratory and immune traits in independent cohorts. We identify 33 DMCs associated with severity. These DMCs are differentially methylated in blood immune cells. These DMCs are also significantly enriched in multiple tissues (e.g., lung) and cells (e.g., small airway epithelial cells), and biological pathways (e.g., interleukin-1-mediated signaling). Additionally, these DMCs are associated with respiratory and immune traits (e.g., asthma, lung function, IgE levels). Our study suggests the role of DNA methylation in bronchiolitis severity.

Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese

BACKGROUND AND PURPOSE

Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population.

METHODS

Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH)).

RESULTS

In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HRSD) of PRSAS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HRSD of PRSIS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRSICH was positively associated with the risk of ICH (HRSD=1.07, 95% CI 1.01 to 1.14). PRSSAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification.

CONCLUSIONS

In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population.

Genotyping and population characteristics of the China Kadoorie Biobank

The China Kadoorie Biobank (CKB) is a population-based prospective cohort of >512,000 adults recruited from 2004 to 2008 from 10 geographically diverse regions across China. Detailed data from questionnaires and physical measurements were collected at baseline, with additional measurements at three resurveys involving ∼5% of surviving participants. Analyses of genome-wide genotyping, for >100,000 participants using custom-designed Axiom arrays, reveal extensive relatedness, recent consanguinity, and signatures reflecting large-scale population movements from recent Chinese history. Systematic genome-wide association studies of incident disease, captured through electronic linkage to death and disease registries and to the national health insurance system, replicate established disease loci and identify 14 novel disease associations. Together with studies of candidate drug targets and disease risk factors and contributions to international genetics consortia, these demonstrate the breadth, depth, and quality of the CKB data. Ongoing high-throughput omics assays of collected biosamples and planned whole-genome sequencing will further enhance the scientific value of this biobank.

Assessing causal relationships between gut microbiota and asthma: evidence from two sample Mendelian randomization analysis

Background

Accumulating evidence has suggested that gut microbiota dysbiosis is commonly observed in asthmatics. However, it remains unclear whether dysbiosis is a cause or consequence of asthma. We aimed to examine the genetic causal relationships of gut microbiota with asthma and its three phenotypes, including adult-onset asthma, childhood-onset asthma, and moderate-severe asthma.

Methods

To elucidate the causality of gut microbiota with asthma, we applied two sample Mendelian randomization (MR) based on the largest publicly available genome-wide association study (GWAS) summary statistics. Inverse variance weighting meta-analysis (IVW) was used to obtain the main estimates; and Weighted median, MR-Egger, Robust Adjusted Profile Score (MR-RAPS), Maximum likelihood method (ML), and MR pleiotropy residual sum and outlier (MR-PRESSO) methods were applied in sensitivity analyses. Finally, a reverse MR analysis was performed to evaluate the possibility of reverse causation.

Results

In the absence of heterogeneity and horizontal pleiotropy, the IVW method revealed that genetically predicted Barnesiella and RuminococcaceaeUCG014 were positively correlated with the risk of asthma, while the association between genetically predicted CandidatusSoleaferrea and asthma was negative. And for the three phenotypes of asthma, genetically predicted Akkermansia reduced the risk of adult-onset asthma, Collinsella and RuminococcaceaeUCG014 increased the risk of childhood-onset asthma, and FamilyXIIIAD3011group, Eisenbergiella, and Ruminiclostridium6 were correlated with the risk of moderate-severe asthma (all P<0.05). The reverse MR analysis didn't find evidence supporting the reverse causality from asthma and its three phenotypes to the gut microbiota genus.

Conclusion

This study suggested that microbial genera were causally associated with asthma as well as its three phenotypes. The findings deepened our understanding of the role of gut microbiota in the pathology of asthma, which emphasizes the potential of opening up a new vista for the prevention and diagnosis of asthma.

Genome-wide association studies: utility and limitations for research in physiology

Physiological systems are subject to interindividual variation encoded by genetics. Genome-wide association studies (GWAS) operate by surveying thousands of genetic variants from a substantial number of individuals and assessing their association to a trait of interest, be it a physiological variable, a molecular phenotype (e.g. gene expression), or even a disease or condition. Through a myriad of methods, GWAS downstream analyses then explore the functional consequences of each variant and attempt to ascertain a causal relationship to the phenotype of interest, as well as to delve into its links to other traits. This type of investigation allows mechanistic insights into physiological functions, pathological disturbances and shared biological processes between traits (i.e. pleiotropy). An exciting example is the discovery of a new thyroid hormone transporter (SLC17A4) and hormone metabolising enzyme (AADAT) from a GWAS on free thyroxine levels. Therefore, GWAS have substantially contributed with insights into physiology and have been shown to be useful in unveiling the genetic control underlying complex traits and pathological conditions; they will continue to do so with global collaborations and advances in genotyping technology. Finally, the increasing number of trans-ancestry GWAS and initiatives to include ancestry diversity in genomics will boost the power for discoveries, making them also applicable to non-European populations.

Genome-wide mapping of gene-microbe interactions in the murine lung microbiota based on quantitative microbial profiling

BACKGROUND

Mammalian lungs comprise a complex microbial ecosystem that interacts with host physiology. Previous research demonstrates that the environment significantly contributes to bacterial community structure in the upper and lower respiratory tract. However, the influence of host genetics on the makeup of lung microbiota remains ambiguous, largely due to technical difficulties related to sampling, as well as challenges inherent to investigating low biomass communities. Thus, innovative approaches are warranted to clarify host-microbe interactions in the mammalian lung.

RESULTS

Here, we aimed to characterize host genomic regions associated with lung bacterial traits in an advanced intercross mouse line (AIL). By performing quantitative microbial profiling (QMP) using the highly precise method of droplet digital PCR (ddPCR), we refined 16S rRNA gene amplicon-based traits to identify and map candidate lung-resident taxa using a QTL mapping approach. In addition, the two abundant core taxa Lactobacillus and Pelomonas were chosen for independent microbial phenotyping using genus-specific primers. In total, this revealed seven significant loci involving eight bacterial traits. The narrow confidence intervals afforded by the AIL population allowed us to identify several promising candidate genes related to immune and inflammatory responses, cell apoptosis, DNA repair, and lung functioning and disease susceptibility. Interestingly, one genomic region associated with Lactobacillus abundance contains the well-known anti-inflammatory cytokine Il10, which we confirmed through the analysis of Il10 knockout mice.

CONCLUSIONS

Our study provides the first evidence for a role of host genetic variation contributing to variation in the lung microbiota. This was in large part made possible through the careful curation of 16S rRNA gene amplicon data and the incorporation of a QMP-based methods. This approach to evaluating the low biomass lung environment opens new avenues for advancing lung microbiome research using animal models.

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Lung function and risk of incident dementia: A prospective cohort study of 431,834 individuals

BACKGROUND

Whether lung function prospectively affects cognitive brain health independent of their overlapping factors remains largely unknown. This study aimed to investigate the longitudinal association between decreased lung function and cognitive brain health and to explore underlying biological and brain structural mechanisms.

METHODS

This population-based cohort included 43,1834 non-demented participants with spirometry from the UK Biobank. Cox proportional hazard models were fitted to estimate the risk of incident dementia for individuals with low lung function. Mediation models were regressed to explore the underlying mechanisms driven by inflammatory markers, oxygen-carrying indices, metabolites, and brain structures.

FINDINGS

During a follow-up of 3,736,181 person-years (mean follow-up 8.65 years), 5,622 participants (1.30 %) developed all-cause dementia, which consisted of 2,511 Alzheimer's dementia (AD) and 1,308 Vascular Dementia (VD) cases. Per unit decrease in lung function measure was each associated with increased risk for all-cause dementia (forced expiratory volume in 1 s [liter]: hazard ratio [HR, 95 %CI], 1.24 [1.14-1.34], P = 1.10 × 10^-07; forced vital capacity [liter]: 1.16 [1.08-1.24], P = 2.04 × 10^-05; peak expiratory flow [liter/min]: 1.0013 [1.0010-1.0017], P = 2.73 × 10^-13). Low lung function generated similar hazard estimates for AD and VD risks. As underlying biological mechanisms, systematic inflammatory markers, oxygen-carrying indices, and specific metabolites mediated the effects of lung function on dementia risks. Besides, brain grey and white matter patterns mostly affected in dementia were substantially changed with lung function.

INTERPRETATION

Life-course risk for incident dementia was modulated by individual lung function. Maintaining optimal lung function is useful for healthy aging and dementia prevention.

Modeling biological age using blood biomarkers and physical measurements in Chinese adults

BACKGROUND

This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum.

METHODS

The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004-08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI).

FINDINGS

The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (-0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019).

INTERPRETATION

In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade.

FUNDING

This work was supported by National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01).

Application of Metabolomics in Obesity-Related Childhood Asthma Subtyping: A Narrative Scoping Review

Obesity-related asthma is a heterogeneous childhood asthma phenotype with rising prevalence. Observational studies identify early-life obesity or weight gain as risk factors for childhood asthma development. The reverse association is also described, children with asthma have a higher risk of being obese. Obese children with asthma have poor symptom control and an increased number of asthma attacks compared to non-obese children with asthma. Clinical trials have also identified that a proportion of obese children with asthma do not respond as well to usual treatment (e.g., inhaled corticosteroids). The heterogeneity of obesity-related asthma phenotypes may be attributable to different underlying pathogenetic mechanisms. Although few childhood obesity-related asthma endotypes have been described, our knowledge in this field is incomplete. An evolving analytical profiling technique, metabolomics, has the potential to link individuals' genetic backgrounds and environmental exposures (e.g., diet) to disease endotypes. This will ultimately help define clinically relevant obesity-related childhood asthma subtypes that respond better to targeted treatment. However, there are challenges related to this approach. The current narrative scoping review summarizes the evidence for metabolomics contributing to asthma subtyping in obese children, highlights the challenges associated with the implementation of this approach, and identifies gaps in research.

Multi-ancestry meta-analysis of asthma identifies novel associations and highlights the value of increased power and diversity

Asthma is a complex disease that varies widely in prevalence across populations. The extent to which genetic variation contributes to these disparities is unclear, as the genetics underlying asthma have been investigated primarily in populations of European descent. As part of the Global Biobank Meta-analysis Initiative, we conducted a large-scale genome-wide association study of asthma (153,763 cases and 1,647,022 controls) via meta-analysis across 22 biobanks spanning multiple ancestries. We discovered 179 asthma-associated loci, 49 of which were not previously reported. Despite the wide range in asthma prevalence among biobanks, we found largely consistent genetic effects across biobanks and ancestries. The meta-analysis also improved polygenic risk prediction in non-European populations compared with previous studies. Additionally, we found considerable genetic overlap between age-of-onset subtypes and between asthma and comorbid diseases. Our work underscores the multi-factorial nature of asthma development and offers insight into its shared genetic architecture.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

Relationship among genetic variants, obesity traits and asthma in the Taiwan Biobank

BACKGROUND AND OBJECTIVE

Obesity and asthma impose a heavy health and economic burden on millions of people around the world. The complex interaction between genetic traits and phenotypes caused the mechanism between obesity and asthma is still vague. This study investigates the relationship among obesity-related polygenic risk score (PRS), obesity phenotypes and the risk of having asthma.

METHODS

This is a matched case-control study, with 4 controls (8288 non-asthmatic) for each case (2072 asthmatic). Data were obtained from the 2008-2015 Taiwan Biobank Database and linked to the 2000-2016 National Health Insurance Research Database. All participants were ≥30 years old with no history of cancer and had a complete questionnaire, as well as physical examination, genome-wide single nucleotide polymorphisms and clinical diagnosis data. Environmental exposure, PM_2.5, was also considered. Multivariate adjusted ORs and 95% CIs were calculated using conditional logistic regression stratified by age and sex. Mediation analysis was also assessed, using a generalised linear model.

RESULTS

We found that the obese phenotype was associated with significantly increased odds of asthma by approximately 26%. Four obesity-related PRS, including body mass index (OR=1.07 (1.01-1.13)), waist circumference (OR=1.10 (1.04-1.17)), central obesity as defined by waist-to-height ratio (OR=1.09 (1.03-1.15)) and general-central obesity (OR=1.06 (1.00-1.12)), were associated with increased odds of asthma. Additional independent risk factors for asthma included lower educational level, family history of asthma, certain chronic diseases and increased PM_2.5 exposure. Obesity-related PRS is an indirect risk factor for asthma, the link being fully mediated by the trait of obesity.

CONCLUSIONS

Obese phenotypes and obesity-related PRS are independent risk factors for having asthma in adults in the Taiwan Biobank. Overall, genetic risk for obesity increases the risk of asthma by affecting the obese phenotype.

Prognostic value of GPC5 polymorphism rs2352028 and clinical characteristics in Chinese lung cancer patients

Background: GPC5 rs2352028 is associated with the risk of lung cancer, but its relationship with lung cancer prognosis is unclear. Materials & methods: The authors collected blood samples from 888 patients with lung cancer and used a Cox proportional hazards model to analyze the association between prognosis and GPC5 polymorphism rs2352028. Results: GPC5 rs2352028 C > T was associated with a better prognosis. Patients with CT genotype had longer overall survival than those with CC genotype. Additionally, older and early-stage patients with CT + TT genotype had a lower risk of death than those with CC genotype. Conclusion: GPC5 rs2352028 C > T may play a protective role in patients with lung cancer and GPC5 rs2352028 may be a potential genetic marker for lung cancer prognosis.

Mechanisms Linking COPD to Type 1 and 2 Diabetes Mellitus: Is There a Relationship between Diabetes and COPD?

Chronic obstructive pulmonary disease (COPD) patients frequently suffer from multiple comorbidities, resulting in poor outcomes for these patients. Diabetes is observed at a higher frequency in COPD patients than in the general population. Both type 1 and 2 diabetes mellitus are associated with pulmonary complications, and similar therapeutic strategies are proposed to treat these conditions. Epidemiological studies and disease models have increased our knowledge of these clinical associations. Several recent genome-wide association studies have identified positive genetic correlations between lung function and obesity, possibly due to alterations in genes linked to cell proliferation; embryo, skeletal, and tissue development; and regulation of gene expression. These studies suggest that genetic predisposition, in addition to weight gain, can influence lung function. Cigarette smoke exposure can also influence the differential methylation of CpG sites in genes linked to diabetes and COPD, and smoke-related single nucleotide polymorphisms are associated with resting heart rate and coronary artery disease. Despite the vast literature on clinical disease association, little direct mechanistic evidence is currently available demonstrating that either disease influences the progression of the other, but common pharmacological approaches could slow the progression of these diseases. Here, we review the clinical and scientific literature to discuss whether mechanisms beyond preexisting conditions, lifestyle, and weight gain contribute to the development of COPD associated with diabetes. Specifically, we outline environmental and genetic confounders linked with these diseases.