Age-of-onset information helps identify 76 genetic variants associated with allergic disease.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption.

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91,462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 × 10(-8)).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.

Loss of a co-twin at birth and subsequent risk of psychiatric disorders.

Twins suffering a co-twin loss at birth have reported feelings of loneliness and grief while it remains unexplored if they suffer increased risk of psychiatric disorders. We contrasted rate of first-onset psychiatric disorders among all Swedish-born twins whose co-twin died within 60 days after birth between 1973 and 2011 (n = 787) to that of 3935 matched unexposed twins, 3935 matched singletons (both matched to the exposed twins by birth year, sex, and birth characteristics), and 880 full siblings of the exposed twins. During a median of 19-year follow-up, exposed twins were at increased risk of first-onset psychiatric disorders (hazard ratio = 1.56, 95%CI 1.30-1.87) compared with unexposed twins. We observed the strongest association for emotional disorders and for psychiatric disorders diagnosed before the age of 25. Comparisons with matched singletons and the twin's full siblings rendered similar results, corroborating an association of loss of a co-twin at birth with subsequent risk of psychiatric disorders.

Clinical biomarkers and associations with healthspan and lifespan: Evidence from observational and genetic data.

BACKGROUND: Biomarker-disease relationships are extensively investigated. However, associations between common clinical biomarkers and healthspan, the disease-free lifespan, are largely unknown. We aimed to explore the predictive values of ten biomarkers on healthspan and lifespan, and to identify putative causal mechanisms. METHODS: Using data from 12,098 Swedish individuals aged 47-94 years, we examined both serum concentrations and genetically predicted levels of ten glycemic, lipid-, inflammatory, and hematological biomarkers. During a follow-up period of up to 16 years, 3681 incident cases of any chronic disease (i.e., end of healthspan) and 2674 deaths (i.e., end of lifespan) were documented. Cox regression models were applied to estimate the associations of a one standard deviation increase in biomarkers with healthspan and lifespan. FINDINGS: Seven out of ten serum biomarkers were significantly associated with risks of any chronic disease and death; elevated glycemic biomarkers and high-density lipoprotein-related biomarkers showed the strongest detrimental (hazard ratio [HR] 1·29 [95% CI 1·24-1·34]) and protective effects (HR 0·92 [95% CI 0·89-0·96]), respectively. Genetic predisposition to elevated fasting blood glucose (FBG) was associated with increased risks of any chronic disease (HR 1·05 [95% CI 1·02-1·09]); genetically determined higher C-reactive protein correlated with lower death risks (HR 0·91 [95% CI 0·87-0·95]). Notably, the genetically proxied FBG-healthspan association was largely explained by serum FBG concentration. INTERPRETATION: Circulating concentrations of glycemic, lipid-, and inflammatory biomarkers are predictive of healthspan and lifespan. Glucose control is a putative causal mechanism and a potential intervention target for healthspan maintenance. FUNDING: This study was supported by the Swedish Research Council (2015-03,255, 2018-02,077), FORTE (2013-2292), the Loo & Hans Osterman Foundation, the Foundation for Geriatric Diseases, the Magnus Bergwall Foundation, the Strategic Research Program in Epidemiology at Karolinska Institutet (SH, JJ), the China Scholarship Council, and the Swedish National Graduate School for Competitive Science on Ageing and Health. The Swedish Twin Registry is managed by Karolinska Institutet and receives funding as an infrastructure through the Swedish Research Council, 2017-00,641.

Long-term exposure to particulate air pollution and black carbon in relation to natural and cause-specific mortality: a multicohort study in Sweden.

OBJECTIVES: To estimate concentration-response relationships for particulate matter (PM) and black carbon (BC) in relation to mortality in cohorts from three Swedish cities with comparatively low pollutant levels. SETTING: Cohorts from Gothenburg, Stockholm and Umeå, Sweden. DESIGN: High-resolution dispersion models were used to estimate annual mean concentrations of PM with aerodynamic diameter ≤10 µm (PM10) and ≤2.5 µm (PM2.5), and BC, at individual addresses during each year of follow-up, 1990-2011. Moving averages were calculated for the time windows 1-5 years (lag1-5) and 6-10 years (lag6-10) preceding the outcome. Cause-specific mortality data were obtained from the national cause of death registry. Cohort-specific HRs were estimated using Cox regression models and then meta-analysed including a random effect of cohort. PARTICIPANTS: During the study period, 7 340 cases of natural mortality, 2 755 cases of cardiovascular disease (CVD) mortality and 817 cases of respiratory and lung cancer mortality were observed among in total 68 679 individuals and 689 813 person-years of follow-up. RESULTS: Both PM10 (range: 6.3-41.9 µg/m3) and BC (range: 0.2-6.8 µg/m3) were associated with natural mortality showing 17% (95% CI 6% to 31%) and 9% (95% CI 0% to 18%) increased risks per 10 µg/m3 and 1 µg/m3 of lag1-5 exposure, respectively. For PM2.5 (range: 4.0-22.4 µg/m3), the estimated increase was 13% per 5 µg/m3, but less precise (95% CI -9% to 40%). Estimates for CVD mortality appeared higher for both PM10 and PM2.5. No association was observed with respiratory mortality. CONCLUSION: The results support an effect of long-term air pollution on natural mortality and mortality in CVD with high relative risks also at low exposure levels. These findings are relevant for future decisions concerning air quality policies.

Risk of psychiatric disorders among the surviving twins after a co-twin loss.

Losing a co-twin by death is a severely stressful event yet with unknown impact on the surviving twin's risk of psychiatric disorders. We identified all Swedish-born twins who lost a co-twin by death between 1973 and 2013 (n = 4,528), their 4939 non-twin full siblings, together with 22,640 age- and sex-matched non-bereaved twins. Compared to the non-bereaved twins, exposed twins were at increased risk of receiving a first diagnosis of psychiatric disorders (hazard ratio = 1.65, 95% confidence interval1.48-1.83), particularly during the first month after loss. Similarly, compared to non-twin full siblings, the relative risks were significantly increased after loss of monozygotic co-twin (2.45-fold), and loss of a dizygotic co-twin (1.29-fold), with higher HR observed with greater age gaps between twins and non-twin siblings. As dizygotic twins share equal genetic relatedness to the deceased twin as their full siblings, this pattern suggests that beyond the contribution of genetic factors, shared early life experiences and attachment contribute to the risk of psychiatric disorders among surviving twins after co-twin loss.

Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up.

Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50-90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality.

Everyone ages, but how aging affects health varies from person to person. This means that how old someone seems or feels does not always match the number of years they have been alive; in other words, someone's "biological age" can often differ from their "chronological age". Scientists are now looking at the physiological changes related to aging to better predict who is at the greatest risk of age-related health problems. Several measurements of biological age have been put forward to capture information about various age-related changes. For example, some measurements look at changes to DNA molecules, while others measure signs of frailty, or deterioration in cognitive or physical abilities. However, to date, most studies into measures of biological age have looked at them individually and less is known about how these physiological changes interact, which is likely to be important. Now, Li et al. have looked at data on nine different measures of biological age in a group of 845 Swedish adults, aged between 50 and 90, that was collected several times over a follow-up period of about 20 years. The dataset also gave details of the individuals' birth year, sex, height, weight, smoking status, and education. The year of death was also collected from national registers for all individual in the group who had since died. Li et al. found that all nine biological age measures could be used to explain the risk of individuals in the group dying during the follow-up period. In other words, when comparing individuals with the same chronological age in the group under study, the person with a higher biological age measure was more likely to die earlier. The analysis also revealed that biological aging appears to accelerate as individuals approach 70 years old, and that there are noticeable differences in the aging process between men and women. Lastly, when combining all nine biological age measures, some of them worked better than others. Measurements of methylation groups added to DNA (known as DNA methylation age) and frailty (the frailty index) led to improved predictions for an individual's risk of death. Ultimately, if future studies confirm these results for measures from single individuals, DNA methylation and the frailty index may be used to help identify people who may benefit the most from interventions to prevent age-related health conditions.

Family history of coronary artery disease is associated with acute coronary syndrome in 28,188 chest pain patients.

BACKGROUND: The value of family history of coronary artery disease (CAD) in diagnosing acute coronary syndrome (ACS) in chest pain patients is uncertain, especially in relation to high-sensitivity assays for cardiac troponin T (hs-cTnT), which have improved ACS diagnostics. Our objective was to investigate the association between verified family history of CAD and ACS in chest pain patients, overall and in different strata of initial hs-cTnT. METHODS: Data on chest pain patients visiting four emergency departments in Sweden during 2013-2016 were cross-referenced with national registers of kinship, diseases and prescriptions. Family history of early CAD was defined as the occurrence of myocardial infarction or coronary revascularization before the age of 55 years in male and 65 years in female first-degree relatives. The outcome was combined including ACS and cardiovascular death within 30 days of presentation. RESULTS: Of 28,188 patients, 4.7% of patients had ACS. In total, 8.2% and 32.4% had a family history of early and ever-occurring CAD, respectively. Family history of CAD was positively associated with the outcome, independently of age, gender, cardiovascular risk factors and electrocardiogram findings. The strongest association was observed for family history of early CAD (odds ratio 1.62, 95% confidence interval 1.35-1.94). Stronger associations were observed in young patients (e.g. <65 years) and in patients with non-elevated initial hs-cTnT levels (p-value for interaction = 0.004 and 0.001, respectively). CONCLUSIONS: Family history of CAD is associated with ACS in chest pain patients, especially in patients of young age or with non-elevated initial hs-cTnT levels.

Profiles of histidine-rich glycoprotein associate with age and risk of all-cause mortality.

Despite recognizing aging as a common risk factor of many human diseases, little is known about its molecular traits. To identify age-associated proteins circulating in human blood, we screened 156 individuals aged 50-92 using exploratory and multiplexed affinity proteomics assays. Profiling eight additional study sets (N = 3,987), performing antibody validation, and conducting a meta-analysis revealed a consistent age association (P = 6.61 × 10-6) for circulating histidine-rich glycoprotein (HRG). Sequence variants of HRG influenced how the protein was recognized in the immunoassays. Indeed, only the HRG profiles affected by rs9898 were associated with age and predicted the risk of mortality (HR = 1.25 per SD; 95% CI = 1.12-1.39; P = 6.45 × 10-5) during a follow-up period of 8.5 yr after blood sampling (IQR = 7.7-9.3 yr). Our affinity proteomics analysis found associations between the particular molecular traits of circulating HRG with age and all-cause mortality. The distinct profiles of this multipurpose protein could serve as an accessible and informative indicator of the physiological processes related to biological aging.

Cardiovascular Diseases And Psychiatric Disorders During The Diagnostic Workup Of Suspected Hematological Malignancy.

BACKGROUND: Little attention has been given to the risk of cardiovascular and psychiatric comorbidities during the clinical evaluation of a suspected hematological malignancy. METHODS: Based on Skåne Healthcare Register, we performed a population-based cohort study of 1,527,449 individuals residing during 2005-2014 in Skåne, Sweden. We calculated the incidence rate ratios (IRRs) of cardiovascular diseases or psychiatric disorders during the diagnostic workup of 5495 patients with hematological malignancy and 18,906 individuals that underwent a bone marrow aspiration or biopsy or lymph node biopsy without receiving a diagnosis of any malignancy ("biopsied individuals"), compared to individuals without such experience (i.e., reference). RESULTS: There was a higher rate of cardiovascular diseases during the diagnostic workup of patients with hematological malignancy (overall IRR, 3.3; 95% CI, 2.9 to 3.8; greatest IRR for embolism and thrombosis, 8.1; 95% CI, 5.2 to 12.8) and biopsied individuals (overall IRR, 4.9; 95% CI, 4.6 to 5.3; greatest IRR for stroke, 37.5; 95% CI, 34.1 to 41.2), compared to reference. Similarly, there was a higher rate of psychiatric disorders during the diagnostic workup of patients with hematological malignancy (IRR, 2.1; 95% CI, 1.5 to 2.8) and biopsied individuals (IRR, 3.1; 95% CI, 2.9 to 3.4). The rate increases were greater around the time of diagnosis or biopsy, compared to thereafter, for both outcomes. CONCLUSION: There were higher rates of cardiovascular diseases and psychiatric disorders during the diagnostic workup of a suspected hematological malignancy, regardless of the final diagnosis.

Birth size and gestational age in opposite-sex twins as compared to same-sex twins: An individual-based pooled analysis of 21 cohorts.

It is well established that boys are born heavier and longer than girls, but it remains unclear whether birth size in twins is affected by the sex of their co-twin. We conducted an individual-based pooled analysis of 21 twin cohorts in 15 countries derived from the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), including 67,850 dizygotic twin individuals. Linear regression analyses showed that boys having a co-twin sister were, on average, 31 g (95% CI 18 to 45) heavier and 0.16 cm (95% CI 0.045 to 0.274) longer than those with a co-twin brother. In girls, birth size was not associated (5 g birth weight; 95% CI -8 to -18 and -0.089 cm birth length; 95% CI -0.202 to 0.025) with the sex of the co-twin. Gestational age was slightly shorter in boy-boy pairs than in boy-girl and girl-girl pairs. When birth size was standardized by gestational age, the magnitude of the associations was attenuated in boys, particularly for birth weight. In conclusion, boys with a co-twin sister are heavier and longer at birth than those with a co-twin brother. However, these differences are modest and partly explained by a longer gestation in the presence of a co-twin sister.

Genetic variants associated with angiotensin-converting enzyme inhibitor-induced cough: a genome-wide association study in a Swedish population.

AIM: We conducted a genome-wide association study on angiotensin-converting enzyme inhibitor-induced cough and used our dataset to replicate candidate genes identified in previous studies. PATIENTS & METHODS: A total of 124 patients and 1345 treated controls were genotyped using Illumina arrays. The genome-wide significance level was set to p < 5 × 10-8. RESULTS: We identified nearly genome-wide significant associations in CLASP1, PDE11A, KCNMB2, TGFA, SLC38A6 and MMP16. The strongest association was with rs62151109 in CLASP1 (odds ratio: 3.97; p = 9.44 × 10-8). All top hits except two were located in intronic or noncoding DNA regions. None of the candidate genes were significantly associated in our study. CONCLUSION: Angiotensin-converting enzyme inhibitor-induced cough is potentially associated with genes that are independent of bradykinin pathways.

SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population.

Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.