Epigenetic studies are commonly conducted on DNA from tissue samples. However, tissues are ensembles of cells that may each have their own epigenetic profile, and therefore inter-individual cellular ...heterogeneity may compromise these studies. Here, we explore the potential for such confounding on DNA methylation measurement outcomes when using DNA from whole blood. DNA methylation was measured using pyrosequencing-based methodology in whole blood (n = 50-179) and in two white blood cell fractions (n = 20), isolated using density gradient centrifugation, in four CGIs (CpG Islands) located in genes HHEX (10 CpG sites assayed), KCNJ11 (8 CpGs), KCNQ1 (4 CpGs) and PM20D1 (7 CpGs). Cellular heterogeneity (variation in proportional white blood cell counts of neutrophils, lymphocytes, monocytes, eosinophils and basophils, counted by an automated cell counter) explained up to 40% (p<0.0001) of the inter-individual variation in whole blood DNA methylation levels in the HHEX CGI, but not a significant proportion of the variation in the other three CGIs tested. DNA methylation levels in the two cell fractions, polymorphonuclear and mononuclear cells, differed significantly in the HHEX CGI; specifically the average absolute difference ranged between 3.4-15.7 percentage points per CpG site. In the other three CGIs tested, methylation levels in the two fractions did not differ significantly, and/or the difference was more moderate. In the examined CGIs, methylation levels were highly correlated between cell fractions. In summary, our analysis detects region-specific differential DNA methylation between white blood cell subtypes, which can confound the outcome of whole blood DNA methylation measurements. Finally, by demonstrating the high correlation between methylation levels in cell fractions, our results suggest a possibility to use a proportional number of a single white blood cell type to correct for this confounding effect in analyses.
Abstract
Summary
The sparse allele vectors file format is an efficient storage format for large-scale DNA variation data and is designed for high throughput association analysis by leveraging ...techniques for fast deserialization of data into computer memory. A command line interface has been developed to complement the storage format and supports basic features like importing, exporting and subsetting. Additionally, a C++ programming API is available allowing for easy integration into analysis software.
Availability and implementation
https://github.com/statgen/savvy.
Supplementary information
Supplementary data are available at Bioinformatics online.
Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new ...BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10
), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
We conducted a meta-analysis of genome-wide association data to detect genes influencing age at menarche in 17,510 women. The strongest signal was at 9q31.2 (P = 1.7 × 10−9), where the nearest genes ...include TMEM38B, FKTN, FSD1L, TAL2 and ZNF462. The next best signal was near the LIN28B gene (rs7759938; P = 7.0 × 10−9), which also influences adult height. We provide the first evidence for common genetic variants influencing female sexual maturation.
The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant ...calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.
Plasma low-density lipoprotein cholesterol (LDL-C) has been associated with aortic stenosis in observational studies; however, randomized trials with cholesterol-lowering therapies in individuals ...with established valve disease have failed to demonstrate reduced disease progression.
To evaluate whether genetic data are consistent with an association between LDL-C, high-density lipoprotein cholesterol (HDL-C), or triglycerides (TG) and aortic valve disease.
Using a Mendelian randomization study design, we evaluated whether weighted genetic risk scores (GRSs), a measure of the genetic predisposition to elevations in plasma lipids, constructed using single-nucleotide polymorphisms identified in genome-wide association studies for plasma lipids, were associated with aortic valve disease. We included community-based cohorts participating in the CHARGE consortium (n = 6942), including the Framingham Heart Study (cohort inception to last follow-up: 1971-2013; n = 1295), Multi-Ethnic Study of Atherosclerosis (2000-2012; n = 2527), Age Gene/Environment Study-Reykjavik (2000-2012; n = 3120), and the Malmö Diet and Cancer Study (MDCS, 1991-2010; n = 28,461).
Aortic valve calcium quantified by computed tomography in CHARGE and incident aortic stenosis in the MDCS.
The prevalence of aortic valve calcium across the 3 CHARGE cohorts was 32% (n = 2245). In the MDCS, over a median follow-up time of 16.1 years, aortic stenosis developed in 17 per 1000 participants (n = 473) and aortic valve replacement for aortic stenosis occurred in 7 per 1000 (n = 205). Plasma LDL-C, but not HDL-C or TG, was significantly associated with incident aortic stenosis (hazard ratio HR per mmol/L, 1.28; 95% CI, 1.04-1.57; P = .02; aortic stenosis incidence: 1.3% and 2.4% in lowest and highest LDL-C quartiles, respectively). The LDL-C GRS, but not HDL-C or TG GRS, was significantly associated with presence of aortic valve calcium in CHARGE (odds ratio OR per GRS increment, 1.38; 95% CI, 1.09-1.74; P = .007) and with incident aortic stenosis in MDCS (HR per GRS increment, 2.78; 95% CI, 1.22-6.37; P = .02; aortic stenosis incidence: 1.9% and 2.6% in lowest and highest GRS quartiles, respectively). In sensitivity analyses excluding variants weakly associated with HDL-C or TG, the LDL-C GRS remained associated with aortic valve calcium (P = .03) and aortic stenosis (P = .009). In instrumental variable analysis, LDL-C was associated with an increase in the risk of incident aortic stenosis (HR per mmol/L, 1.51; 95% CI, 1.07-2.14; P = .02).
Genetic predisposition to elevated LDL-C was associated with presence of aortic valve calcium and incidence of aortic stenosis, providing evidence supportive of a causal association between LDL-C and aortic valve disease. Whether earlier intervention to reduce LDL-C could prevent aortic valve disease merits further investigation.
Postsurgical pain is a key component of surgical recovery. However, the genetic drivers of postsurgical pain remain unclear. A broad review and meta-analyses of variants of interest will help ...investigators understand the potential effects of genetic variation.
This article is a systematic review of genetic variants associated with postsurgical pain in humans, assessing association with postsurgical pain scores and opioid use in both acute (0 to 48 h postoperatively) and chronic (at least 3 months postoperatively) settings. PubMed, Embase, and the Cochrane Central Register of Controlled Trials were searched from 2000 to 2022 for studies using search terms related to genetic variants and postsurgical pain in humans. English-language studies in adult patients examining associations of one or more genetic variants with postsurgical pain were included. The primary outcome was association of genetic variants with either acute or chronic postsurgical pain. Pain was measured by patient-reported pain score or analgesic or opioid consumption.
A total of 163 studies were included, evaluating 129 unique genes and 594 unique genetic variants. Many of the reported significant associations fail to be replicated in other studies. Meta-analyses were performed for seven variants for which there was sufficient data (OPRM1 rs1799971; COMT rs4680, rs4818, rs4633, and rs6269; and ABCB1 rs1045642 and rs2032582). Only two variants were associated with small differences in postsurgical pain: OPRM1 rs1799971 (for acute postsurgical opioid use standard mean difference = 0.25; 95% CI, 0.16 to 0.35; cohort size, 8,227; acute postsurgical pain score standard mean difference = 0.20; 95% CI, 0.09 to 0.31; cohort size, 4,619) and COMT rs4680 (chronic postsurgical pain score standard mean difference = 0.26; 95% CI, 0.08 to 0.44; cohort size, 1,726).
Despite much published data, only two alleles have a small association with postsurgical pain. Small sample sizes, potential confounding variables, and inconsistent findings underscore the need to examine larger cohorts with consistent outcome measures.
Observational studies have identified an association between body mass index (BMI) and incident atrial fibrillation (AF). Inferring causality from observational studies, however, is subject to ...residual confounding, reverse causation, and bias. The primary objective of this study was to evaluate the causal association between BMI and AF by using genetic predictors of BMI.
We identified 51 646 individuals of European ancestry without AF at baseline from 7 prospective population-based cohorts initiated between 1987 and 2002 in the United States, Iceland, and the Netherlands with incident AF ascertained between 1987 and 2012. Cohort-specific mean follow-up ranged from 7.4 to 19.2 years, over which period there was a total of 4178 cases of incident AF. We performed a Mendelian randomization with instrumental variable analysis to estimate a cohort-specific causal hazard ratio for the association between BMI and AF. Two genetic instruments for BMI were used:
genotype (rs1558902) and a BMI gene score comprising 39 single-nucleotide polymorphisms identified by genome-wide association studies to be associated with BMI. Cohort-specific estimates were combined by random-effects, inverse variance-weighted meta-analysis.
In age- and sex-adjusted meta-analysis, both genetic instruments were significantly associated with BMI (
: 0.43 95% confidence interval, 0.32-0.54 kg/m
per A-allele,
<0.001; BMI gene score: 1.05 95% confidence interval, 0.90-1.20 kg/m
per 1-U increase,
<0.001) and incident AF (
, hazard ratio, 1.07 1.02-1.11 per A-allele,
=0.004; BMI gene score, hazard ratio, 1.11 1.05-1.18 per 1-U increase,
<0.001). Age- and sex-adjusted instrumental variable estimates for the causal association between BMI and incident AF were hazard ratio, 1.15 (1.04-1.26) per kg/m
,
=0.005 (
) and 1.11 (1.05-1.17) per kg/m
,
<0.001 (BMI gene score). Both of these estimates were consistent with the meta-analyzed estimate between observed BMI and AF (age- and sex-adjusted hazard ratio 1.05 1.04-1.06 per kg/m
,
<0.001). Multivariable adjustment did not significantly change findings.
Our data are consistent with a causal relationship between BMI and incident AF. These data support the possibility that public health initiatives targeting primordial prevention of obesity may reduce the incidence of AF.
The HapMap Web site at http://www.hapmap.org is the primary portal to genotype data produced as part of the International Haplotype Map Project. In phase I of the project, >1.1 million SNPs were ...genotyped in 270 individuals from four worldwide populations. The HapMap Web site provides researchers with a number of tools that allow them to analyze the data as well as download data for local analyses. This paper presents step-by-step guides to using those tools, including guides for retrieving genotype and frequency data, picking tag-SNPs for use in association studies, viewing haplotypes graphically, and examining marker-to-marker LD patterns.
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