Aptamer Proteomics for Biomarker Discovery in Heart Failure With Preserved Ejection Fraction: The PARAGON-HF Proteomic Substudy.

BACKGROUND: Prognostic markers and biological pathways linked to detrimental clinical outcomes in heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. METHODS AND RESULTS: We measured serum levels of 4123 unique proteins in 1117 patients with HFpEF enrolled in the PARAGON-HF (Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction) trial using a modified aptamer proteomic assay. Baseline circulating protein concentrations significantly associated with the primary end point and the timing and occurrence of total heart failure hospitalization and cardiovascular death were identified by recurrent events regression, accounting for multiple testing, adjusted for age, sex, treatment, and anticoagulant use, and compared with published analyses in 2515 patients with heart failure with reduced ejection fraction from the PARADIGM-HF (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) and ATMOSPHERE (Efficacy and Safety of Aliskiren and Aliskiren/Enalapril Combination on Morbidity-Mortality in Patients With Chronic Heart Failure) clinical trials. We identified 288 proteins that were robustly associated with the risk of heart failure hospitalization and cardiovascular death in patients with HFpEF. The baseline proteins most strongly related to outcomes included B2M (ß-2 microglobulin), TIMP1 (tissue inhibitor of matrix metalloproteinase 1), SERPINA4 (serpin family A member 4), and SVEP1 (sushi, von Willebrand factor type A, EGF, and pentraxin domain containing 1). Overall, the protein-outcome associations in patients with HFpEF did not markedly differ as compared with patients with heart failure with reduced ejection fraction. A proteomic risk score derived in patients with HFpEF was not superior to a previous proteomic score derived in heart failure with reduced ejection fraction nor to clinical risk factors, NT-proBNP (N-terminal pro-B-type natriuretic peptide), or high-sensitivity cardiac troponin. CONCLUSIONS: Numerous serum proteins linked to metabolic, coagulation, and extracellular matrix regulatory pathways were associated with worse HFpEF prognosis in the PARAGON-HF proteomic substudy. Our results demonstrate substantial similarities among serum proteomic risk markers for heart failure hospitalization and cardiovascular death when comparing clinical trial participants with heart failure across the ejection fraction spectrum. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique Identifiers: NCT01920711, NCT01035255, NCT00853658.

Relationship of Left Ventricular Mass to Lean Body Mass in the Obese Pediatric Population.

Our primary aim was to investigate the relationship between LVM and anthropometric measures including lean body mass (LBM) in obese pediatric subjects compared to normal weight controls. A retrospective chart review identified subjects 2-18 years old who were normotensive and had normal echocardiograms between 1995 and 2020 at Boston Children's Hospital. LVM was calculated with the 5/6 area length rule from 2D echocardiograms. LBM was calculated with equations derived from dual-energy X-ray absorptiometry. Of the 2217 subjects who met inclusion criteria, 203 were obese and 2014 had normal weight. The median age was 11.9 (2.0-18.9); 46% were female. The median LVM was 94.5 g (59.3-134.3) in obese subjects vs. 78.0 g (51.5-107.7) in controls. The median LBM was 37.2 kg (18.9-50.6) in obese subjects vs. 30.5 kg (17.6-40.8) in controls. In control and obese subjects, LBM had the strongest correlation to LVM (R2 0.86, P < 0.001) and (R2 0.87, P < 0.001), respectively. There was at most a modest correlation between tissue Doppler velocity z-scores and LV mass, and the largest was Septal E' z-score in obese subjects (r = - 0.31, P = 0.006). In this cohort, LBM was found to have the strongest relationship to LVM in obese subjects. The largest correlation between tissue Doppler velocity z-scores and LV mass was Septal E' z-score. Future studies will evaluate which measurements are more closely aligned with clinical outcomes in obese children.

A Unified, Scalable Framework for Neural Population Decoding.

Our ability to use deep learning approaches to decipher neural activity would likely benefit from greater scale, in terms of both model size and datasets. However, the integration of many neural recordings into one unified model is challenging, as each recording contains the activity of different neurons from different individual animals. In this paper, we introduce a training framework and architecture designed to model the population dynamics of neural activity across diverse, large-scale neural recordings. Our method first tokenizes individual spikes within the dataset to build an efficient representation of neural events that captures the fine temporal structure of neural activity. We then employ cross-attention and a PerceiverIO backbone to further construct a latent tokenization of neural population activities. Utilizing this architecture and training framework, we construct a large-scale multi-session model trained on large datasets from seven nonhuman primates, spanning over 158 different sessions of recording from over 27,373 neural units and over 100 hours of recordings. In a number of different tasks, we demonstrate that our pretrained model can be rapidly adapted to new, unseen sessions with unspecified neuron correspondence, enabling few-shot performance with minimal labels. This work presents a powerful new approach for building deep learning tools to analyze neural data and stakes out a clear path to training at scale.

Learning signatures of decision making from many individuals playing the same game.

Human behavior is incredibly complex and the factors that drive decision making-from instinct, to strategy, to biases between individuals-often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.

Clinical characteristics of heart failure with reduced ejection fraction patients with rare pathogenic variants in dilated cardiomyopathy-associated genes: A subgroup analysis of the PARADIGM-HF trial.

AIMS: To evaluate the prevalence of pathogenic variants in genes associated with dilated cardiomyopathy (DCM) in a clinical trial population with heart failure and reduced ejection fraction (HFrEF) and describe the baseline characteristics by variant carrier status. METHODS AND RESULTS: This was a post hoc analysis of the Phase 3 PARADIGM-HF trial. Forty-four genes, divided into three tiers, based on definitive, moderate or limited evidence of association with DCM, were assessed for rare predicted loss-of-function (pLoF) variants, which were prioritized using ClinVar annotations, measures of gene transcriptional output and evolutionary constraint, and pLoF confidence predictions. Prevalence was reported for pLoF variant carriers based on DCM-associated gene tiers. Clinical features were compared between carriers and non-carriers. Of the 1412 HFrEF participants with whole-exome sequence data, 68 (4.8%) had at least one pLoF variant in the 8 tier-1 genes (definitive/strong association with DCM), with Titin being most commonly affected. The prevalence increased to 7.5% when considering all 44 genes. Among patients with idiopathic aetiology, 10.0% (23/229) had tier-1 variants only and 12.6% (29/229) had tier-1, -2 or -3 variants. Compared to non-carriers, tier-1 carriers were younger (4 years; adjusted p-value [padj ] = 4 × 10-3 ), leaner (27.8 kg/m2 vs. 29.4 kg/m2 ; padj = 3.2 × 10-3 ), had lower ejection fraction (27.3% vs. 29.8%; padj = 5.8 × 10-3 ), and less likely to have ischaemic aetiology (37.3% vs. 67.4%; padj = 4 × 10-4 ). CONCLUSION: Deleterious pLoF variants in genes with definitive/strong association with DCM were identified in ∼5% of HFrEF patients from a PARADIGM-HF trial subset, who were younger, had lower ejection fraction and were less likely to have had an ischaemic aetiology.

Learning signatures of decision making from many individuals playing the same game.

Human behavior is incredibly complex and the factors that drive decision making--from instinct, to strategy, to biases between individuals--often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.

Transgelin: a new gene involved in LDL endocytosis identified by a genome-wide CRISPR-Cas9 screen.

A significant proportion of patients with elevated LDL and a clinical presentation of familial hypercholesterolemia do not carry known genetic mutations associated with hypercholesterolemia, such as defects in the LDL receptor. To identify new genes involved in the cellular uptake of LDL, we developed a novel whole-genome clustered regularly interspaced short palindromic repeat-Cas9 KO screen in HepG2 cells. We identified transgelin (TAGLN), an actin-binding protein, as a potentially new gene involved in LDL endocytosis. In silico validation demonstrated that genetically predicted differences in expression of TAGLN in human populations were significantly associated with elevated plasma lipids (triglycerides, total cholesterol, and LDL-C) in the Global Lipids Genetics Consortium and lipid-related phenotypes in the UK Biobank. In biochemical studies, TAGLN-KO HepG2 cells showed a reduction in cellular LDL uptake, as measured by flow cytometry. In confocal microscopy imaging, TAGLN-KO cells had disrupted actin filaments as well as an accumulation of LDL receptor on their surface because of decreased receptor internalization. Furthermore, TAGLN-KO cells exhibited a reduction in total and free cholesterol content, activation of SREBP2, and a compensatory increase in cholesterol biosynthesis. TAGLN deficiency also disrupted the uptake of VLDL and transferrin, other known cargoes for receptors that depend upon clathrin-mediated endocytosis. Our data suggest that TAGLN is a novel factor involved in the actin-dependent phase of clathrin-mediated endocytosis of LDL. The identification of novel genes involved in the endocytic uptake of LDL may improve the diagnosis of hypercholesterolemia and provide future therapeutic targets for the prevention of cardiovascular disease.

Dyslipidemia Among Adults With Congenital Heart Disease.

Background: Atherosclerotic disease is an important cause of morbidity among adults with congenital heart disease (CHD). Prevalence of dyslipidemia in this group is poorly described. Objectives: This study aimed to describe the prevalence of dyslipidemia among adults with CHD. Methods: A prospective, outpatient screening study was conducted among adults aged ≥18 years at 4 New England ambulatory congenital cardiology centers. Participants were surveyed regarding cardiovascular risk factors. Nonfasting fingerstick samples were obtained for analysis using a point-of-care lipid analyzer. Results: Lipid screening was completed on 186 participants (median age 30 [range 18-71] years, 50% female). Eighteen (10%) had simple CHD anatomy, and 63 (34%) had complex anatomy. Only 15% of 169 respondents reported history of high cholesterol. Eighty-five (46%) participants met National Cholesterol Education Program definition of dyslipidemia with 60 (32%), 62 (34%), and 37 (20%) having low high-density lipoprotein cholesterol (HDL-C <40 mg/dL), high non-HDL-C (≥130 mg/dL), and high total cholesterol (TC ≥200 mg/dL), respectively. TC was higher among participants with simple CHD than among those with moderate and complex lesions (mean 178.4 ± 48.7 vs 170.1 ± 35.0 vs 157.6 ± 34.5 mg/dL; P = 0.03). HDL-C was lower among participants with complex CHD than among those with simple and moderate lesions (mean 44.1 ± 13.5 vs 46.9 ± 12.5 vs 49.8 ± 15.3 mg/dL; P = 0.05). Conclusions: Dyslipidemia is highly prevalent among our cohort of adults with CHD, despite <15% reporting a prior diagnosis. Low HDL-C was more common in complex CHD, and high TC was more common in simple or moderate CHD. Lipid screening should be part of preventive health maintenance for all adults with CHD.

A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids.

Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.

Fontan-Associated Dyslipidemia.

Background Hypocholesterolemia is a marker of liver disease, and patients with a Fontan circulation may have hypocholesterolemia secondary to Fontan-associated liver disease or inflammation. We investigated circulating lipids in adults with a Fontan circulation and assessed the associations with clinical characteristics and adverse events. Methods and Results We enrolled 164 outpatients with a Fontan circulation, aged ≥18 years, in the Boston Adult Congenital Heart Disease Biobank and compared them with 81 healthy controls. The outcome was a combined outcome of nonelective cardiovascular hospitalization or death. Participants with a Fontan (median age, 30.3 [interquartile range, 22.8-34.3 years], 42% women) had lower total cholesterol (149.0±30.1 mg/dL versus 190.8±41.4 mg/dL, P<0.0001), low-density lipoprotein cholesterol (82.5±25.4 mg/dL versus 102.0±34.7 mg/dL, P<0.0001), and high-density lipoprotein cholesterol (42.8±12.2 mg/dL versus 64.1±16.9 mg/dL, P<0.0001) than controls. In those with a Fontan, high-density lipoprotein cholesterol was inversely correlated with body mass index (r=-0.30, P<0.0001), high-sensitivity C-reactive protein (r=-0.27, P=0.0006), and alanine aminotransferase (r=-0.18, P=0.02) but not with other liver disease markers. Lower high-density lipoprotein cholesterol was independently associated with greater hazard for the combined outcome adjusting for age, sex, body mass index, and functional class (hazard ratio [HR] per decrease of 10 mg/dL, 1.37; 95% CI, 1.04-1.81 [P=0.03]). This relationship was attenuated when log high-sensitivity C-reactive protein was added to the model (HR, 1.26; 95% CI, 0.95-1.67 [P=0.10]). Total cholesterol, low-density lipoprotein cholesterol, and triglycerides were not associated with the combined outcome. Conclusions The Fontan circulation is associated with decreased cholesterol levels, and lower high-density lipoprotein cholesterol is associated with adverse outcomes. This association may be driven by inflammation. Further studies are needed to understand the relationship between the severity of Fontan-associated liver disease and lipid metabolism.

Improving Cardiovascular Health in a Pediatric Preventive Cardiology Practice.

Poor childhood cardiovascular health translates into poor adult cardiovascular health. We hypothesized care in a preventive cardiology clinic would improve cardiovascular health after lifestyle counseling. Over a median of 3.9 months, mean cardiovascular health score (range 0-11) improved from 5.8 ± 2.2 to 6.3 ± 2.1 (P < .001) in 767 children.

Whole Blood DNA Methylation Signatures of Diet Are Associated With Cardiovascular Disease Risk Factors and All-Cause Mortality.

BACKGROUND: DNA methylation patterns associated with habitual diet have not been well studied. METHODS: Diet quality was characterized using a Mediterranean-style diet score and the Alternative Healthy Eating Index score. We conducted ethnicity-specific and trans-ethnic epigenome-wide association analyses for diet quality and leukocyte-derived DNA methylation at over 400 000 CpGs (cytosine-guanine dinucleotides) in 5 population-based cohorts including 6662 European ancestry, 2702 African ancestry, and 360 Hispanic ancestry participants. For diet-associated CpGs identified in epigenome-wide analyses, we conducted Mendelian randomization (MR) analysis to examine their relations to cardiovascular disease risk factors and examined their longitudinal associations with all-cause mortality. RESULTS: We identified 30 CpGs associated with either Mediterranean-style diet score or Alternative Healthy Eating Index, or both, in European ancestry participants. Among these CpGs, 12 CpGs were significantly associated with all-cause mortality (Bonferroni corrected P<1.6×10-3). Hypermethylation of cg18181703 (SOCS3) was associated with higher scores of both Mediterranean-style diet score and Alternative Healthy Eating Index and lower risk for all-cause mortality (P=5.7×10-15). Ten additional diet-associated CpGs were nominally associated with all-cause mortality (P<0.05). MR analysis revealed 8 putatively causal associations for 6 CpGs with 4 cardiovascular disease risk factors (body mass index, triglycerides, high-density lipoprotein cholesterol concentrations, and type 2 diabetes mellitus; Bonferroni corrected MR P<4.5×10-4). For example, hypermethylation of cg11250194 (FADS2) was associated with lower triglyceride concentrations (MR, P=1.5×10-14).and hypermethylation of cg02079413 (SNORA54; NAP1L4) was associated with body mass index (corrected MR, P=1×10-6). CONCLUSIONS: Habitual diet quality was associated with differential peripheral leukocyte DNA methylation levels of 30 CpGs, most of which were also associated with multiple health outcomes, in European ancestry individuals. These findings demonstrate that integrative genomic analysis of dietary information may reveal molecular targets for disease prevention and treatment.

Familial Cerebral Cavernous Malformation Syndrome with Concomitant Fourth Ventricular Ependymoma: True Association or Mere Coincidence?

Familial cerebral cavernous malformation syndromes are most commonly caused by mutations in one of three genes. The overlap of these genetic malformations with other acquired neoplastic lesions and congenital malformations is still under investigation. To the best of our knowledge, the concurrent occurrence of familial cavernous malformations and ependymoma has not been previously reported in the literature. Herein, we describe a patient with familial cerebral cavernous malformation syndrome and posterior fossa ependymoma. A 17-year-old asymptomatic male was referred to our outpatient neurosurgery clinic after genetic testing identified a familial KRIT1 (CCM1) mutation. The patient's sister had presented with a seizure disorder previously; multiple cavernous malformations were discovered, and a symptomatic large cavernous malformation required a craniotomy for resection. Two years later, she was diagnosed with follicular thyroid cancer due to HRAS (c.182A>G) mutation. The patient and his sister were found to have a novel germline KRIT1 disease-causing variant (c.1739deletion, p.ASN580Ilefs*2) and a variant of uncertain significance, potentially pathogenic (c.1988 A>G, p.Asn663Ser) in cis in CCM1 (KRIT1), of paternal inheritance. Due to the presence of genetic abnormalities, the patient underwent screening imaging of his neuraxis. Multiple cavernous malformations were identified, as was an incidental fourth ventricular mass. Resection of the fourth ventricular lesion was performed, and histopathological examination was consistent with ependymoma. We report a unique case of posterior fossa ependymoma in an individual with a familial cerebral cavernous malformation syndrome and a novel genetic abnormality in KRIT1. The association of these two findings may be valuable in determining a potential genetic association between the two pathologies and elucidating the pathogenesis of both cavernous malformations and ependymomas.

Endogenous oxidized phospholipids reprogram cellular metabolism and boost hyperinflammation.

Pathogen-associated molecular patterns (PAMPs) have the capacity to couple inflammatory gene expression to changes in macrophage metabolism, both of which influence subsequent inflammatory activities. Similar to their microbial counterparts, several self-encoded damage-associated molecular patterns (DAMPs) induce inflammatory gene expression. However, whether this symmetry in host responses between PAMPs and DAMPs extends to metabolic shifts is unclear. Here, we report that the self-encoded oxidized phospholipid oxPAPC alters the metabolism of macrophages exposed to lipopolysaccharide. While cells activated by lipopolysaccharide rely exclusively on glycolysis, macrophages exposed to oxPAPC also use mitochondrial respiration, feed the Krebs cycle with glutamine, and favor the accumulation of oxaloacetate in the cytoplasm. This metabolite potentiates interleukin-1ß production, resulting in hyperinflammation. Similar metabolic adaptions occur in vivo in hypercholesterolemic mice and human subjects. Drugs that interfere with oxPAPC-driven metabolic changes reduce atherosclerotic plaque formation in mice, thereby underscoring the importance of DAMP-mediated activities in pathophysiological conditions.

Epigenome-wide association study of DNA methylation and microRNA expression highlights novel pathways for human complex traits.

DNA methylation (DNAm) and microRNAs (miRNAs) have been implicated in a wide-range of human diseases. While often studied in isolation, DNAm and miRNAs are not independent. We analyzed associations of expression of 283 miRNAs with DNAm at >400K CpG sites in whole blood obtained from 3565 individuals and identified 227 CpGs at which differential methylation was associated with the expression of 40 nearby miRNAs (cis-miR-eQTMs) at FDR<0.01, including 91 independent CpG sites at r2 < 0.2. cis-miR-eQTMs were enriched for CpGs in promoter and polycomb-repressed state regions, and 60% were inversely associated with miRNA expression. Bidirectional Mendelian randomization (MR) analysis further identified 58 cis-miR-eQTMCpG-miRNA pairs where DNAm changes appeared to drive miRNA expression changes and opposite directional effects were unlikely. Integration of genetic variants in joint analyses revealed an average partial between cis-miR-eQTM CpGs and miRNAs of 2% after conditioning on site-specific genetic variation, suggesting that DNAm is an important epigenetic regulator of miRNA expression. Finally, two-step MR analysis was performed to identify putatively causal CpGs driving miRNA expression in relation to human complex traits. We found that an imprinted region on 14q32 that was previously identified in relation to age at menarche is enriched with cis-miR-eQTMs. Nine CpGs and three miRNAs at this locus tested causal for age at menarche, reflecting novel epigenetic-driven molecular pathways underlying this complex trait. Our study sheds light on the joint genetic and epigenetic regulation of miRNA expression and provides insights into the relations of miRNAs to their targets and to complex phenotypes.

Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study.

Epigenetic changes may contribute substantially to risks of diseases of aging. Previous studies reported seven methylation variable positions (MVPs) robustly associated with incident type 2 diabetes mellitus (T2DM). However, their causal roles in T2DM are unclear. In an incident T2DM case-cohort study nested within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk cohort, we used whole blood DNA collected at baseline, up to 11 years before T2DM onset, to investigate the role of methylation in the etiology of T2DM. We identified 15 novel MVPs with robust associations with incident T2DM and robustly confirmed three MVPs identified previously (near to TXNIP, ABCG1, and SREBF1). All 18 MVPs showed directionally consistent associations with incident and prevalent T2DM in independent studies. Further conditional analyses suggested that the identified epigenetic signals appear related to T2DM via glucose and obesity-related pathways acting before the collection of baseline samples. We integrated genome-wide genetic data to identify methylation-associated quantitative trait loci robustly associated with 16 of the 18 MVPs and found one MVP, cg00574958 at CPT1A, with a possible direct causal role in T2DM. None of the implicated genes were previously highlighted by genetic association studies, suggesting that DNA methylation studies may reveal novel biological mechanisms involved in tissue responses to glycemia.

Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease.

Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans-meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis-meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans-meQTL hotspots each targeting more than 30 CpGs and find that trans-meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases.