Background

RNA-Sequencing (RNA-Seq) experiments have been optimized for library preparation, mapping, and gene expression estimation. These methods, however, have revealed weaknesses in the next stages of analysis of differential expression, with results sensitive to systematic sample stratification or, in more extreme cases, to outliers. Further, a method to assess normalization and adjustment measures imposed on the data is lacking.

Results

To address these issues, we utilize previously published eQTLs as a novel gold standard at the center of a framework that integrates DNA genotypes and RNA-Seq data to optimize analysis and aid in the understanding of genetic variation and gene expression. After detecting sample contamination and sequencing outliers in RNA-Seq data, a set of previously published brain eQTLs was used to determine if sample outlier removal was appropriate. Improved replication of known eQTLs supported removal of these samples in downstream analyses. eQTL replication was further employed to assess normalization methods, covariate inclusion, and gene annotation. This method was validated in an independent RNA-Seq blood data set from the GTEx project and a tissue-appropriate set of eQTLs. eQTL replication in both data sets highlights the necessity of accounting for unknown covariates in RNA-Seq data analysis.

Conclusion

As each RNA-Seq experiment is unique with its own experiment-specific limitations, we offer an easily-implementable method that uses the replication of known eQTLs to guide each step in one's data analysis pipeline. In the two data sets presented herein, we highlight not only the necessity of careful outlier detection but also the need to account for unknown covariates in RNA-Seq experiments.

Importance

Mitochondrial dysfunction is a core component of the aging process and may play a key role in atherosclerotic cardiovascular disease. Mitochondrial DNA copy number (mtDNA-CN), which represents the number of mitochondria per cell and number of mitochondrial genomes per mitochondrion, is an indirect biomarker of mitochondrial function.

Objective

To determine whether mtDNA-CN, measured in an easily accessible tissue (buffy coat/circulating leukocytes), can improve risk classification for cardiovascular disease (CVD) and help guide initiation of statin therapy for primary prevention of CVD.

Design, setting, and participants

Prospective, population-based cohort analysis including 21 870 participants (20 163 free from CVD at baseline) from 3 studies: Cardiovascular Health Study (CHS), Atherosclerosis Risk in Communities Study (ARIC), and Multiethnic Study of Atherosclerosis (MESA). The mean follow-up was 13.5 years. The study included 11 153 participants from ARIC, 4830 from CHS, and 5887 from MESA. Analysis of the data was conducted from March 10, 2014, to January 29, 2017.

Exposures

Mitochondrial DNA-CN measured from buffy coat/circulating leukocytes.

Main outcomes and measures

Incident CVD, which combines coronary heart disease, defined as the first incident myocardial infarction or death owing to coronary heart disease, and stroke, defined as the first nonfatal stroke or death owing to stroke.

Results

Of the 21 870 participants, the mean age was 62.4 years (ARIC, 57.9 years; MESA, 62.4 years; and CHS, 72.5 years), and 54.7% of participants were women. The hazard ratios for incident coronary heart disease, stroke, and CVD associated with a 1-SD decrease in mtDNA-CN were 1.29 (95% CI, 1.24-1.33), 1.11 (95% CI, 1.06-1.16), and 1.23 (95% CI, 1.19-1.26). The associations persisted after adjustment for traditional CVD risk factors. Addition of mtDNA-CN to the 2013 American College of Cardiology/American Heart Association Pooled Cohorts Equations for estimating 10-year hard atherosclerosis CVD risk was associated with improved risk classification (continuous net reclassification index, 0.194; 95% CI, 0.130-0.258; P < .001). Mitochondrial DNA-CN further improved sensitivity and specificity for the 2013 American College of Cardiology/American Heart Association recommendations on initiating statin therapy for primary prevention of ASCVD (net 221 individuals appropriately downclassified and net 15 individuals appropriately upclassified).

Conclusions and relevance

Mitochondrial DNA-CN was independently associated with incident CVD in 3 large prospective studies and may have potential clinical utility in improving CVD risk classification.

Aims

Sudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. We aim to identify potential loci associated with SCA and to identify risk factors causally associated with SCA.

Methods and results

We carried out a large genome-wide association study (GWAS) for SCA (n = 3939 cases, 25 989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization (MR) methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (i) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (ii) height and BMI, and (iii) electrical instability traits (QT and atrial fibrillation), suggesting aetiologic roles for these traits in SCA risk.

Conclusions

Our findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in high-risk populations and the general community.

Importance

The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

Objective

To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

Data sources

Genomewide association studies (GWAS) published up to January 15, 2015.

Study selection

GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

Data extraction and synthesis

Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

Main outcomes and measures

Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

Results

Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).

Conclusions and relevance

It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.