QALYs in cost-effectiveness analysis: an overview for cardiologists

In recent years, cost-effectiveness data have strongly influenced clinical practice guidelines for several cardiovascular treatments. Economic considerations are increasingly common as health systems are under mounting pressure to maximise value for money. The quality-adjusted life year (QALY)—an outcome measure that expresses the duration and quality of life—is the main pillar of cost-effectiveness analyses. It is widely used in assessments of the clinical and economic value of new cardiovascular treatments, but how the QALY is derived is often unclear to clinicians. In this article, we first explain how QALYs are defined and calculated. We then review a selected set of cost-effectiveness analyses of recently introduced cardiovascular treatments and outline how these studies derived their QALYs. Finally, we discuss the limitations of the QALY and how the presentation of the measure could be improved in cost-effectiveness studies

A flexible and parallelizable approach to genome-wide polygenic risk scores.

The heritability of most complex traits is driven by variants throughout the genome. Consequently, polygenic risk scores, which combine information on multiple variants genome-wide, have demonstrated improved accuracy in genetic risk prediction. We present a new two-step approach to constructing genome-wide polygenic risk scores from meta-GWAS summary statistics. Local linkage disequilibrium (LD) is adjusted for in Step 1, followed by, uniquely, long-range LD in Step 2. Our algorithm is highly parallelizable since block-wise analyses in Step 1 can be distributed across a high-performance computing cluster, and flexible, since sparsity and heritability are estimated within each block. Inference is obtained through a formal Bayesian variable selection framework, meaning final risk predictions are averaged over competing models. We compared our method to two alternative approaches: LDPred and lassosum using all seven traits in the Welcome Trust Case Control Consortium as well as meta-GWAS summaries for type 1 diabetes (T1D), coronary artery disease, and schizophrenia. Performance was generally similar across methods, although our framework provided more accurate predictions for T1D, for which there are multiple heterogeneous signals in regions of both short- and long-range LD. With sufficient compute resources, our method also allows the fastest runtimes

A genome-wide survey demonstrates widespread non-linear mRNA in expressed sequences from multiple species

We describe here the results of the first genome-wide survey of candidate exon repetition events in expressed sequences from human, mouse, rat, chicken, zebrafish and fly. Exon repetition is a rare event, reported in <10 genes, in which one or more exons is tandemly duplicated in mRNA but not in the gene. To identify candidates, we analysed database sequences for mRNA transcripts in which the order of the spliced exons does not follow the linear genomic order of the individual gene [events we term rearrangements or repetition in exon order (RREO)]. Using a computational approach, we have identified 245 genes in mammals that produce RREO events. RREO in mRNA occurs predominantly in the coding regions of genes. However, exon 1 is never involved. Analysis of the open reading frames suggests that this process may increase protein diversity and regulate protein expression via nonsense-mediated RNA decay. The sizes of the exons and introns involved around these events suggest a gene model structure that may facilitate non-linear splicing. These findings imply that RREO affects a significant subset of genes within a genome and suggests that non-linear information encoded within the genomes of complex organisms could contribute to phenotypic variation

Effects of size at birth, childhood growth patterns and growth hormone treatment on leukocyte telomere length

__Background__ Small size at birth and rapid growth in early life are associated with increased risk of cardiovascular disease in later life. Short children born small for gestational age (SGA) are treated with growth hormone (GH), inducing catch-up in length. Leukocyte telomere length (LTL) is a marker of biological age and shorter LTL is associated with increased risk of cardiovascular disease. __Objectives__ To investigate whether LTL is influenced by birth size, childhood growth and long-term GH treatment. __Methods__ We analyzed LTL in 545 young adults with differences in birth size and childhood growth patterns. Previously GH-treated young adults born SGA (SGA-GH) were compared to untreated short SGA (SGA-S), SGA with spontaneous catch-up to a normal body size (SGA-CU), and appropriate for gestational age with a normal body size (AGA-NS). LTL was measured using a quantitative PCR assay. __Results__ We found a positive association between birth length and LTL (p = 0.04), and a trend towards a positive association between birth weight and LTL (p = 0.08), after adjustments for gender, age, gestational age and adult body size. Weight gain during infancy and childhood and fat mass percentage were not as

A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size

Kidney DNA methylation as a driver of genetic change in the kidney

Objectives: Hypertension is associated with various physiological changes that result in an increased risk of stroke, cardiovascular events and chronic kidney disease. Here we conducted a genome-wide analysis of methylation changes in the human kidney to identify epigenetic signatures of hypertension using the largest collection of apparently healthy human renal tissue. As the first analysis of its kind in the human kidney we also determined whether these changes have functional consequences at the gene expression level. Methods: We examined DNA extracted from a total of 94 human kidneys to investigate methylation patterns in hypertension. We also examined RNA -sequencing to characterise the transcriptome of 180 human kidneys to uncover interactions between DNA methylation and gene expressi. Results: Our methylation analysis identified one hypertension-associated CpG site, three systolic blood pressure-associated CpG sites and 19 diastolic blood pressure -associated CpG sites; including four CpG sites previously identified in peripheral blood studies of hypertension. DNA methylation is a known regulator of gene expression; therefore, we investigated whether differential DNA methylation in proximity to hypertension-associated renal genes correlated with their renal expression. Methylation of two genes (FAM50B, PC) showed an association with renal expression. The transcriptome analysis of 180 kidneys revealed 14 hypertension-associated genes, 1 gene associated with systolic blood pressure and 6 genes associated with diastolic blood pressure; including those involved in smooth muscle response to blood pressure fluctuation and blood pressure response to salt intake in humans. Conclusion: Our study uncovered DNA methylation as a new regulatory mechanism underpinning hypertension-related changes in renal gene expression

Adult height and risk of 50 diseases : a combined epidemiological and genetic analysis

Funding FYL and SEH are funded by the National Institute for Health Research Leicester Biomedical Research Centre. CPN and NJS are funded by the British Heart Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Availability of data and materials The data reported in this paper are available via application directly to the UK Biobank.Peer reviewedPublisher PD