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Background DNA methylation is thought to be an important determinant of human phenotypic variation, but its inherent cell type specificity has impeded progress on this question. At exceptional genomic regions, interindividual variation in DNA methylation occurs systemically. Like genetic variants, systemic interindividual epigenetic variants are stable, can influence phenotype, and can be assessed in any easily biopsiable DNA sample. We describe an unbiased screen for human genomic regions at which interindividual variation in DNA methylation is not tissue-specific. Results For each of 10 donors from the NIH Genotype-Tissue Expression (GTEx) program, CpG methylation is measured by deep whole-genome bisulfite sequencing of genomic DNA from tissues representing the three germ layer lineages: thyroid (endoderm), heart (mesoderm), and brain (ectoderm). We develop a computational algorithm to identify genomic regions at which interindividual variation in DNA methylation is consistent across all three lineages. This approach identifies 9926 correlated regions of systemic interindividual variation (CoRSIVs). These regions, comprising just 0.1% of the human genome, are inter-correlated over long genomic distances, associated with transposable elements and subtelomeric regions, conserved across diverse human ethnic groups, sensitive to periconceptional environment, and associated with genes implicated in a broad range of human disorders and phenotypes. CoRSIV methylation in one tissue can predict expression of associated genes in other tissues. Conclusions In addition to charting a previously unexplored molecular level of human individuality, this atlas of human CoRSIVs provides a resource for future population-based investigations into how interindividual epigenetic variation modulates risk of disease. Electronic supplementary material The online version of this article (10.1186/s13059-019-1708-1) contains supplementary material, which is available to authorized users.

Previous studies have documented the primarily genetic aetiology for the stronger phenotypic covariance between reading disability and ADHD inattention symptoms, compared to hyperactivity-impulsivity symptoms. In this study, we examined to what extent this covariation could be attributed to "generalist genes" shared with general cognitive ability or to "specialist" genes which may specifically underlie processes linking inattention symptoms and reading difficulties. We used multivariate structural equation modeling on IQ, parent and teacher ADHD ratings and parent ratings on reading difficulties from a general population sample of 1312 twins aged 7.9-10.9 years. The covariance between reading difficulties and ADHD inattention symptoms was largely driven by genetic (45%) and child-specific environment (21%) factors not shared with IQ and hyperactivity-impulsivity; only 11% of the covariance was due to genetic effects common with IQ. Aetiological influences shared among all phenotypes explained 47% of the variance in reading difficulties. The current study, using a general population sample, extends previous findings by showing, first, that the shared genetic variability between reading difficulties and ADHD inattention symptoms is largely independent from genes contributing to general cognitive ability and, second, that child-specific environment factors, independent from IQ, also contribute to the covariation between reading difficulties and inattention symptoms.

Background Previous analysis clustered 1,238 individuals from the general population Genetics of Lipid Lowering Drugs Network (GOLDN) study by the size of their fasting very low-density, low-density and high-density lipoproteins (VLDL, LDL, HDL) using latent class analysis. From two of the eight identified groups (N = 251), ~75% of individuals met Adult Treatment Panel III criteria for the metabolic syndrome (MetS). Both showed small LDL diameter (mean = 19.9 nm); however, group 1 (N = 200) had medium VLDL diameter (mean = 53.1 nm) while group 2 had very large VLDL diameter (mean = 65.74 nm). Group 2 additionally showed significantly more insulin resistance (IR), and accompanying higher waist circumference and fasting glucose and triglycerides (all P < .01). Since lipoprotein lipase hydrolyzes triglyceride in the VLDL-LDL cascade, we examined whether these two patterns of lipoprotein diameter were associated with differences across two lipoprotein lipase (LPL) gene variants: D9N (rs1801177) and S447X (rs328). Findings Mixed linear models that controlled for age, sex, center of data collection, and family pedigree revealed no differences between the two groups for the D9N polymorphism (P = .36). However, group 2 contained significantly more carriers (25%) of the 447X variant than group 1 (14%; P = .04). Conclusions This was the first study this kind to show an association between LPL and large VLDL particle size within the MetS, a pattern associated with higher IR. Future work should extend this to larger samples to confirm these findings, and examine the long term outcomes of those with this lipoprotein diameter pattern.