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Purpose: We sought to characterize the natural history of vascular Ehlers–Danlos syndrome in individuals with heterozygous COL3A1 mutations. Methods: We reviewed clinical records for details of vascular, bowel, and organ complications in 1,231 individuals (630 index cases and 601 relatives). Results: Missense and splice-site mutations accounted for more than 90% of the 572 alterations that we had identified in COL3A1 . Median survival was 51 years but was influenced by gender (lower in men) and by the type of mutation. Conclusion: Although vascular Ehlers–Danlos syndrome appears to be genetically homogeneous, allelic heterogeneity is marked, and the natural history varies with gender and type of mutation in COL3A1 . These findings indicate that when counseling families, confirmation of the presence of a COL3A1 mutation and its nature can help evaluate the risks of complications. These data are also important ingredients in both the selection and allocation of individuals to appropriate arms in clinical trials to assess the effects of interventions. Genet Med 16 12, 881–888.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2 , that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2 . Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes. ACE2 and TMPRSS2 have received recent attention as entry factors for SARS-CoV-2. Here the authors analyze nasal airway transcriptome data from 695 children determining ACE2 and TMPRSS2 expression is induced by viral and type2 inflammation, respectively, and both exhibit eQTLs that vary across world populations.

To identify genetic determinants of airway dysfunction, we performed a transcriptome-wide association study for asthma by combining RNA-seq data from the nasal airway epithelium of 681 children, with UK Biobank genetic association data. Our airway analysis identified 102 asthma genes, 58 of which were not identified by transcriptome-wide association analyses using other asthma-relevant tissues. Among these genes were MUC5AC , an airway mucin, and FOXA3 , a transcriptional driver of mucus metaplasia. Muco-ciliary epithelial cultures from genotyped donors revealed that the MUC5AC risk variant increases MUC5AC protein secretion and mucus secretory cell frequency. Airway transcriptome-wide association analyses for mucus production and chronic cough also identified MUC5AC . These cis-expression variants were associated with trans effects on expression; the MUC5AC variant was associated with upregulation of non-inflammatory mucus secretory network genes, while the FOXA3 variant was associated with upregulation of type-2 inflammation-induced mucus-metaplasia pathway genes. Our results reveal genetic mechanisms of airway mucus pathobiology. Understanding regulation of genes associated to disease can reveal insights into disease mechanisms. Here, the authors perform an airway epithelial transcriptome-wide association analysis to elucidate genetic determinants of airway dysfunction in asthma, identifying genetic mechanisms of mucus pathobiology.

Christopher Newton-Cheh and colleagues from the QTGEN consortium report genetic associations to the QT interval duration, a measure of cardiac repolarization which is a risk factor for sudden cardiac death, in three genome-wide association studies from the Framingham Heart Study, the Rotterdam Study and the Cardiovascular Health Study. QT interval duration, reflecting myocardial repolarization on the electrocardiogram, is a heritable risk factor for sudden cardiac death and drug-induced arrhythmias. We conducted a meta-analysis of three genome-wide association studies in 13,685 individuals of European ancestry from the Framingham Heart Study, the Rotterdam Study and the Cardiovascular Health Study, as part of the QTGEN consortium. We observed associations at P < 5 × 10 −8 with variants in NOS1AP , KCNQ1, KCNE1 , KCNH2 and SCN5A , known to be involved in myocardial repolarization and mendelian long-QT syndromes. Associations were found at five newly identified loci, including 16q21 near NDRG4 and GINS3 , 6q22 near PLN , 1p36 near RNF207 , 16p13 near LITAF and 17q12 near LIG3 and RFFL . Collectively, the 14 independent variants at these 10 loci explain 5.4–6.5% of the variation in QT interval. These results, together with an accompanying paper, offer insights into myocardial repolarization and suggest candidate genes that could predispose to sudden cardiac death and drug-induced arrhythmias.

Background Cox proportional hazards regression models are used to evaluate associations between exposures of interest and time-to-event outcomes in observational data. When exposures are measured on only a sample of participants, as they are in a case-cohort design, the sampling weights must be incorporated into the regression model to obtain unbiased estimating equations. Methods Robust Cox methods have been developed to better estimate associations when there are influential outliers in the exposure of interest, but these robust methods do not incorporate sampling weights. In this paper, we extend these robust methods, which already incorporate influence weights, so that they also accommodate sampling weights. Results Simulations illustrate that in the presence of influential outliers, the association estimate from the weighted robust method is closer to the true value than the estimate from traditional weighted Cox regression. As expected, in the absence of outliers, the use of robust methods yields a small loss of efficiency. Using data from a case-cohort study that is nested within the Multi-Ethnic Study of Atherosclerosis (MESA) longitudinal cohort study, we illustrate differences between traditional and robust weighted Cox association estimates for the relationships between immune cell traits and risk of stroke. Conclusions Robust weighted Cox regression methods are a new tool to analyze time-to-event data with sampling, e.g. case-cohort data, when exposures of interest contain outliers.

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits ( n  = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4 , CLDN2 , TSPAN6 and the female-specific DRP2 . Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R , and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1 . All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research. X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases such as chronic kidney disease (CKD). Here, the authors perform a sex-stratified, cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits, with results including identification of four novel loci associated with the CKD-defining trait eGFR.

Data are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting. We performed a two-stage GWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898 MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5×10-6 in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with total mortality in individuals who experienced MI during follow-up. In Stage I 15 loci passed the threshold of 5×10-6; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8×10-3) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2×10-9). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2×10-3). QKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders.

Objective Resting heart rate (RHR) is an established predictor of myocardial infarction (MI) and mortality, but the relationship between variation in RHR over a period of several years and health outcomes is unclear. We evaluated the relationship between long-term variation in RHR and the risks of incident MI and mortality among older adults. Methods 1991 subjects without cardiovascular disease from the Cardiovascular Health Study were included. RHR was taken from resting ECGs at the first five annual study visits. RHR mean, trend and variation were estimated with linear regression. Subjects were followed for incident MI and death until December 2010. HRs for RHR mean, trend and variation are reported for differences of 10 bpm, 2 bpm/year and 2 bpm, respectively. Results 262 subjects had an incident MI event (13%) and 1326 died (67%) during 12 years of median follow-up. In primary analyses adjusted for cardiovascular risk factors, RHR mean (HR 1.12; 95% CI 1.05 to 1.20) and variation (HR 1.08; 95% CI 1.03 to 1.13) were associated with the risk of death while trend was not. None of the RHR variables were significantly associated with the risk of incident MI events; however, CIs were wide and the MI associations with RHR variables were not significantly different from the mortality associations. Adjusting for additional variables did not affect estimates, and there were no significant interactions with sex. Conclusions Variation in RHR over a period of several years represents a potential predictor of long-term mortality among older persons free of cardiovascular disease.

Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 x 10.sup.-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) [greater than or equal to] 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.