A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities

Background

Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse.

Methods

Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders.

Results

The mean annual exposure in Chennai and Delhi was 40 and 102 μg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi.

Conclusion

These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

The Tehran longitudinal family-based cardiometabolic cohort study sheds new light on dyslipidemia transmission patterns

Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28-9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

ADAMTS7: a Novel Therapeutic Target in Atherosclerosis

PURPOSE OF REVIEW

Genome-wide association studies have repeatedly linked the metalloproteinase ADAMTS7 to coronary artery disease. Here we aim to highlight recent findings surrounding the human genetics of ADAMTS7, novel mouse models that investigate ADAMTS7 function, and potential substrates of ADAMTS7 cleavage.

RECENT FINDINGS

Recent genome-wide association studies in coronary artery disease have replicated the GWAS signal for ADAMTS7 and shown that the signal holds true even across different ethnic groups. However, the direction of effect in humans remains unclear. A recent novel mouse model revealed that the proatherogenicity of ADAMTS7 is derived from its catalytic functions, while at the translational level, vaccinating mice against ADAMTS7 reduced atherosclerosis. Finally, in vitro proteomics approaches have identified extracellular matrix proteins as candidate substrates that may be causal for the proatherogenicity of ADAMTS7. ADAMTS7 represents an enticing target for therapeutic intervention. The recent studies highlighted here have replicated prior findings, confirming the genetic link between ADAMTS7 and atherosclerosis, while providing further evidence in mice that ADAMTS7 is a targetable proatherogenic enzyme.

A fast linkage method for population GWAS cohorts with related individuals

Linkage analysis, a class of methods for detecting co-segregation of genomic segments and traits in families, was used to map disease-causing genes for decades before genotyping arrays and dense SNP genotyping enabled genome-wide association studies in population samples. Population samples often contain related individuals, but the segregation of alleles within families is rarely used because traditional linkage methods are computationally inefficient for larger datasets. Here, we describe Population Linkage, a novel application of Haseman-Elston regression as a method of moments estimator of variance components and their standard errors. We achieve additional computational efficiency by using modern methods for detection of IBD segments and variance component estimation, efficient preprocessing of input data, and minimizing redundant numerical calculations. We also refined variance component models to account for the biases in population-scale methods for IBD segment detection. We ran Population Linkage on four blood lipid traits in over 70,000 individuals from the HUNT and SardiNIA studies, successfully detecting 25 known genetic signals. One notable linkage signal that appeared in both was for low-density lipoprotein (LDL) cholesterol levels in the region near the gene APOE (LOD = 29.3, variance explained = 4.1%). This is the region where the missense variants rs7412 and rs429358, which together make up the ε2, ε3, and ε4 alleles each account for 2.4% and 0.8% of variation in circulating LDL cholesterol. Our results show the potential for linkage analysis and other large-scale applications of method of moments variance components estimation.

Association of APP gene polymorphisms and promoter methylation with essential hypertension in Guizhou: a case-control study

BACKGROUND

Single-nucleotide polymorphisms (SNPs) and DNA methylation are crucial regulators of essential hypertension (EH). Amyloid precursor protein (APP) mutations are implicated in hypertension development. Nonetheless, studies on the association of APP gene polymorphism and promoter methylation with hypertension are limited. Therefore, this case-control aims to evaluate the genetic association of APP gene polymorphism and promoter methylation with EH in Guizhou populations.

OBJECTIVE AND METHODS

We conducted a case-control study on 343 EH patients and 335 healthy controls (including Miao, Buyi, and Han populations) in the Guizhou province of China to analyze 11 single-nucleotide polymorphisms (rs2040273, rs63750921, rs2211772, rs2830077, rs467021, rs368196, rs466433, rs364048, rs364051, rs438031, rs463946) in the APP gene via MassARRAY SNP. The MassARRAY EpiTYPER was employed to detect the methylation levels of the promoters.

RESULTS

In the Han population, the rs2211772 genotype distribution was significantly different between disease and control groups (χ² = 6.343, P = 0.039). The CC genotype reduced the risk of hypertension compared to the TT or TC genotype (OR 0.105, 95%CI 0.012-0.914, P = 0.041). For rs2040273 in the Miao population, AG or GG genotype reduced the hypertension risk compared with the AA genotype (OR 0.533, 95%CI 0.294-0.965, P = 0.038). Haplotype TCC (rs364051-rs438031-rs463946) increased the risk of EH in Guizhou (OR 1.427, 95%CI 1.020-1.996, P = 0.037). Each 1% increase in CpG_19 (- 613 bp) methylation level was associated with a 4.1% increase in hypertension risk (OR 1.041, 95%CI 1.002-1.081, P = 0.039). Each 1% increase in CpG_1 (- 296 bp) methylation level was associated with an 8% decrease in hypertension risk in women (OR 0.920, 95%CI 0.860-0.984, P = 0.015). CpG_19 significantly correlated with systolic blood pressure (r = 0.2, P = 0.03). The methylation levels of CpG_19 in hypertensive patients with rs466433, rs364048, and rs364051 minor alleles were lower than that with wild-type alleles (P < 0.05). Moreover, rs467021 and rs364051 showed strong synergistic interaction with EH (χ² = 7.633, P = 0.006). CpG_11, CpG_19, and rs364051 showed weak synergistic interaction with EH (χ² = 19.874, P < 0.001).

CONCLUSION

In summary, rs2211772 polymorphism and promoter methylation level of APP gene may be linked to EH in Guizhou populations. Our findings will provide novel insights for genetic research of hypertension and Alzheimer's disease.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Maternal lipid levels in early pregnancy as a predictor of childhood lipid levels: a prospective cohort study

Background

Maternal lipid levels in early pregnancy are associated with maternal health and foetal growth. It is however unclear if maternal lipids in early pregnancy can be used to predict childhood lipid levels. The aim of this study is to assess the association between maternal and offspring childhood lipid levels, and to investigate the influence of maternal BMI and diet on these associations.

Methods

This study included 2692 women participating in the Generation R study, an ongoing population-based prospective cohort study from early life onwards. Women with an expected delivery date between 2002 and 2006 living in Rotterdam, the Netherlands were included. Total cholesterol, triglycerides and high-density lipoprotein cholesterol (HDL-c) were measured in early pregnancy (median 13.2 weeks [90% range 10.6; 17.1]). Low-density lipoprotein cholesterol (LDL-c), remnant cholesterol and non-HDL-c were calculated. Corresponding lipid measurements were determined in 2692 children at the age of 6 (median 6.0 years [90% range 5.7; 7.5]) and 1673 children 10 years (median 9.7 years [90% range 9.5; 10.3]). Multivariate linear regression analysis was used to examine the association between maternal lipid levels in early pregnancy and the corresponding childhood lipid measurements at the ages of 6 and 10 years while adjusting for confounders.

Results

Maternal lipid levels in early pregnancy are positively associated with corresponding childhood lipid levels 6 and 10 years after pregnancy, independent of maternal body mass index and diet.

Conclusions

Maternal lipid levels in early pregnancy may provide an insight to the lipid profile of children years later. Gestational lipid levels may therefore be used as an early predictor of children’s long-term health. Monitoring of these gestational lipid levels may give a window-of-opportunity to start early interventions to decrease offspring’s lipid levels and possibly diminish their cardiovascular risk later in life. Future studies are warranted to investigate the genetic contribution on maternal lipid levels in pregnancy and lipid levels of their offspring years later.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04905-7.

Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study

While multiple factors are associated with cardiovascular disease (CVD), many environmental exposures that may contribute to CVD have not been examined. To understand environmental effects on cardiovascular health, we performed an exposome-wide association study (ExWAS), a hypothesis-free approach, using survey data on endogenous and exogenous exposures at home and work and data from health and medical histories from the North Carolina-based Personalized Environment and Genes Study (PEGS) (n = 5015). We performed ExWAS analyses separately on six cardiovascular outcomes (cardiac arrhythmia, congestive heart failure, coronary artery disease, heart attack, stroke, and a combined atherogenic-related outcome comprising angina, angioplasty, atherosclerosis, coronary artery disease, heart attack, and stroke) using logistic regression and a false discovery rate of 5%. For each CVD outcome, we tested 502 single exposures and built multi-exposure models using the deletion-substitution-addition (DSA) algorithm. To evaluate complex nonlinear relationships, we employed the knockoff boosted tree (KOBT) algorithm. We adjusted all analyses for age, sex, race, BMI, and annual household income. ExWAS analyses revealed novel associations that include blood type A (Rh-) with heart attack (OR[95%CI] = 8.2[2.2:29.7]); paint exposures with stroke (paint related chemicals: 6.1[2.2:16.0], acrylic paint: 8.1[2.6:22.9], primer: 6.7[2.2:18.6]); biohazardous materials exposure with arrhythmia (1.8[1.5:2.3]); and higher paternal education level with reduced risk of multiple CVD outcomes (stroke, heart attack, coronary artery disease, and combined atherogenic outcome). In multi-exposure models, trouble sleeping and smoking remained important risk factors. KOBT identified significant nonlinear effects of sleep disorder, regular intake of grapefruit, and a family history of blood clotting problems for multiple CVD outcomes (combined atherogenic outcome, congestive heart failure, and coronary artery disease). In conclusion, using statistics and machine learning, these findings identify novel potential risk factors for CVD, enable hypothesis generation, provide insights into the complex relationships between risk factors and CVD, and highlight the importance of considering multiple exposures when examining CVD outcomes.

Using Machine Learning to Identify Biomarkers Affecting Fat Deposition in Pigs by Integrating Multisource Transcriptome Information

Fat deposition in pigs is not only closely related to pig production efficiency and pork quality but also an ideal model for human obesity. Transcriptome sequencing is widely used to study fat deposition. However, due to small sample sizes, high false positive rates, and poor consistency of results from different studies, new strategies are urgently needed. Machine learning, a new analysis method, can effectively fit complex data and accurately identify samples and genes. In this study, 36 samples of adipose tissue, muscle tissue, and liver tissue were collected from Songliao black pigs and Landrace pigs, and the mRNA of all the samples was sequenced. In addition, we collected transcriptome data for 64 samples in the GEO database from four different sources. After standardization and imputation of missing values in the data set comprising 100 samples, traditional differential expression analysis was carried out, and different numbers of expressed genes were selected as features for the training model of eight machine learning methods. In the 1000 replications of fourfold cross validation with 100 samples, AdaBoost performed best, with an average prediction accuracy greater than 93% and the highest mean area under the curve in predicting the high- and low-fat content groups among the eight ML methods. According to their performance-based ranks inferred by AdaBoost, 12 genes related to fat deposition were identified; among them, FASN and APOD were specifically expressed in adipose tissue, and APOA1 was specifically expressed in the liver, which could be important candidate biomarkers affecting fat deposition.

Integrative analysis of multi-omics data to detect the underlying molecular mechanisms for obesity in vivo in humans

BACKGROUND

Obesity is a complex, multifactorial condition in which genetic play an important role. Most of the systematic studies currently focuses on individual omics aspect and provide insightful yet limited knowledge about the comprehensive and complex crosstalk between various omics levels.

SUBJECTS AND METHODS

Therefore, we performed a most comprehensive trans-omics study with various omics data from 104 subjects, to identify interactions/networks and particularly causal regulatory relationships within and especially those between omic molecules with the purpose to discover molecular genetic mechanisms underlying obesity etiology in vivo in humans.

RESULTS

By applying differentially analysis, we identified 8 differentially expressed hub genes (DEHGs), 14 differentially methylated regions (DMRs) and 12 differentially accumulated metabolites (DAMs) for obesity individually. By integrating those multi-omics biomarkers using Mendelian Randomization (MR) and network MR analyses, we identified 18 causal pathways with mediation effect. For the 20 biomarkers involved in those 18 pairs, 17 biomarkers were implicated in the pathophysiology of obesity or related diseases.

CONCLUSIONS

The integration of trans-omics and MR analyses may provide us a holistic understanding of the underlying functional mechanisms, molecular regulatory information flow and the interactive molecular systems among different omic molecules for obesity risk and other complex diseases/traits.

EHBP1, TUBB, and WWOX SNPs, Gene-Gene and Gene-Environment Interactions on Coronary Artery Disease and Ischemic Stroke

The associations among the EH domain-binding protein 1 (EHBP1), tubulin beta class I (TUBB), and WW domain-containing oxidoreductase (WWOX) single nucleotide polymorphisms (SNPs) and coronary artery disease (CAD) and ischemic stroke (IS) are not yet understood. This study aimed to detect the associations of these SNPs, gene-gene and gene-environment interactions and CAD and IS in the Guangxi Han population. A total of 1853 unrelated subjects were recruited into normal control (n = 638), CAD (n = 622), and IS (n = 593) groups. Related genotypes were determined by high-throughput sequencing. The genotypic and minor allelic frequencies of rs2278075 were different between the CAD and control groups, and those of rs2710642, rs3130685, and rs2278075 were also different between the IS and control groups. The rs2278075T allele, rs3130685-rs2222896-rs2278075, rs3130685-rs2222896-diabetes, rs3130685-rs2222896-drinking, and haplotype rs2710642A-rs10496099C-diabetes interactions were associated with increased risk, while G-T-G-C-G-A and G-T-T-T-G-T-drinking were associated with reduced risk of CAD. The rs2278075T and rs2710642G alleles, rs2710642G-rs10496099C haplotype, rs3130685-rs2278075-rs2222896, and rs2710642-rs2278075-hypertension interactions aggravated the association with IS, whereas the rs3130685T allele, rs2710642A-rs10496099C haplotype and the interactions of H1 (s2710642A-rs10496099C)-H2 (rs2710642G-rs10496099C)-drinking and I1 (A-C-G-C-A-A)-I3 (A-C-G-T-A-A)-I4 (A-C-G-T-G-A)-I5 (G-T-G-C-G-A) diminished the association with IS. Carrying WWOX rs2278075T was strongly associated with CAD or IS, while EHBP1 rs2710642 and TUBB rs3130685 might alter the association of IS by modifying the serum lipid profile. This study demonstrates that the EHBP1, TUBB, and WWOX SNPs, gene-gene and gene-environment interactions are associated with the risk of CAD and IS in the Guangxi Han population.

Notable paradoxical phenomena in associations between cardiovascular health score, subclinical and clinical cardiovascular disease in the community: The Framingham Heart Study

Importance

Cardiovascular Health (CVH) scores are inversely associated with prevalent subclinical (SubDz) and incident cardiovascular disease (CVD). However, the majority of people who develop CVD have intermediate or ideal CVH scores, while many with poor CVH profiles escape CVD development.

Objective

To describe the prevalence of paradoxical relations among CVH, SubDz, and CVD.

Design

Cohort study, Framingham Study data collected prospectively (1995–2016).

Setting

Population-based.

Participants

7,627 participants (mean age 49 years, 53% women) attending Offspring examinations 6/7 and Third Generation examinations 1/2.

Exposures

CVH score (range 0–14) constructed from poor, intermediate, or ideal status for each metric (smoking, diet, physical activity, blood pressure, body mass index, fasting glucose, total cholesterol); and prevalent SubDz (≥1 of: increased carotid intimal media thickness, CIMT; left ventricular hypertrophy, LVH; microalbuminuria, MA; elevated ankle brachial index, ABI; coronary artery calcium score ≥100,CAC).

Main outcome(s) and measure(s)

Ideal CVH (scores 12–14), intermediate CVH (scores 8–11), and poor CVH (0–7). We described three distinct paradoxical phenomena, involving combinations of CVH, SubDz, and CVD, and generated CVD incidence rates and predicted CVD probabilities for all combinations.

Results

We observed 842 CVD events (median follow-up 13.7 years); 1,663 participants had SubDz. Most individuals with poor CVH (78%) or SubDz (57% for CIMT to 77% for LVH) did not develop CVD on follow-up. Among participants with incident CVD, the majority had intermediate or ideal CVH (68%) or absent SubDz (46% for CAC to 96% for ABI) at baseline. We observed similar paradoxical results in relations between CVH and prevalent SubDz. Poor CVH and prevalent SubDz were each associated with higher CVD incidence rates compared to intermediate or ideal CVH and absent SubDz, respectively. The predicted CVD probability was nearly three-times greater among participants with poor (22%) versus intermediate or ideal CVH (8%). Mean CVD predicted probabilities were nearly three (26% vs. 10% for MA) to six-times (29% vs. 5% for CAC) greater among participants with SubDz versus without SubDz. Findings were consistent within age and sex strata.

Conclusions and relevance

Although poor CVH and SubDz presence are associated with CVD incidence, paradoxical phenomena involving CVH, SubDz, and CVD are frequently prevalent in the community. Further studies to elucidate biological mechanisms underlying these phenomena are warranted.

Combination of Genomic and Transcriptomic Approaches Highlights Vascular and Circadian Clock Components in Multiple Sclerosis

Aiming at exploring vascular components in multiple sclerosis (MS) with brain outflow disturbance, we combined transcriptome analysis in MS internal jugular vein (IJV) wall with WES in MS families with vertical transmission of disease. Main results were the differential expression in IJV wall of 16 MS-GWAS genes and of seven genes (GRIN2A, GRIN2B, IL20RB, IL26, PER3, PITX2, and PPARGC1A) not previously indicated by GWAS but encoding for proteins functionally interacting with MS candidate gene products. Strikingly, 22/23 genes have been previously associated with vascular or neuronal traits/diseases, nine encoded for transcriptional factors/regulators and six (CAMK2G, GRIN2A, GRIN2B, N1RD1, PER3, PPARGC1A) for circadian entrainment/rhythm components. Among the WES low-frequency (MAF ≤ 0.04) SNPs (n = 7) filtered in the 16 genes, the NR1D1 rs17616365 showed significantly different MAF in the Network for Italian Genomes affected cohort than in the 1000 Genome Project Tuscany samples. This pattern was also detected in five nonintronic variants (GRIN2B rs1805482, PER3 rs2640909, PPARGC1A rs2970847, rs8192678, and rs3755863) in genes coding for functional partners. Overall, the study proposes specific markers and low-frequency variants that might help (i) to understand perturbed biological processes in vascular tissues contributing to MS disease, and (ii) to characterize MS susceptibility genes for functional association with disease-pathways.

Gestational Age Dependence of the Maternal Circulating Long Non-Coding RNA Transcriptome During Normal Pregnancy Highlights Antisense and Pseudogene Transcripts

In the post-genomic era, our understanding of the molecular regulators of physiologic and pathologic processes in pregnancy is expanding at the whole-genome level. Longitudinal changes in the known protein-coding transcriptome during normal pregnancy, which we recently reported (Gomez-Lopez et al., 2019), have improved our definition of the major operant networks, yet pregnancy-related functions of the non-coding RNA transcriptome remain poorly understood. A key finding of the ENCODE (Encyclopedia of DNA Elements) Consortium, the successor of the Human Genome Project, was that the human genome contains approximately 60,000 genes, the majority of which do not encode proteins. The total transcriptional output of non-protein-coding RNA genes, collectively referred to as the non-coding transcriptome, is comprised mainly of long non-coding RNA (lncRNA) transcripts (Derrien et al., 2012). Although the ncRNA transcriptome eclipses its protein-coding counterpart in abundance, it has until recently lacked a comprehensive, unbiased, genome-scale characterization over the timecourse of normal human pregnancy. Here, we annotated, characterized, and selectively validated the longitudinal changes in the non-coding transcriptome of maternal whole blood during normal pregnancy to term. We identified nine long non-coding RNAs (lncRNAs), including long intergenic non-coding RNAs (lincRNAs) as well as lncRNAs antisense to or otherwise in the immediate vicinity of protein-coding genes, that were differentially expressed with advancing gestation in normal pregnancy: AL355711, BC039551 (expressed mainly in the placenta), JHDM1D-AS1, A2M-AS1, MANEA-AS1, NR_034004, LINC00649, LINC00861, and LINC01094. By cross-referencing our dataset against major public pseudogene catalogs, we also identified six transcribed pseudogenes that were differentially expressed over time during normal pregnancy in maternal blood: UBBP4, FOXO3B, two Makorin (MKRN) pseudogenes (MKRN9P and LOC441455), PSME2P2, and YBX3P1. We also identified three non-coding RNAs belonging to other classes that were modulated during gestation: the microRNA MIR4439, the small nucleolar RNA (snoRNA) SNORD41, and the small Cajal-body specific ncRNA SCARNA2. The expression profiles of most hits were broadly suggestive of functions in pregnancy. These time-dependent changes of the non-coding transcriptome during normal pregnancy, which may confer specific regulatory impacts on their protein-coding gene targets, will facilitate a deeper molecular understanding of pregnancy and lncRNA-mediated molecular pathways at the maternal-fetal interface and of how these pathways impact maternal and fetal health.

An emerging spectrum of variants and clinical features in KCNMA1-linked channelopathy

KCNMA1-linked channelopathy is an emerging neurological disorder characterized by heterogeneous and overlapping combinations of movement disorder, seizure, developmental delay, and intellectual disability. KCNMA1 encodes the BK K+ channel, which contributes to both excitatory and inhibitory neuronal and muscle activity. Understanding the basis of the disorder is an important area of active investigation; however, the rare prevalence has hampered the development of large patient cohorts necessary to establish genotype-phenotype correlations. In this review, we summarize 37 KCNMA1 alleles from 69 patients currently defining the channelopathy and assess key diagnostic and clinical hallmarks. At present, 3 variants are classified as gain-of-function with respect to BK channel activity, 14 loss-of-function, 15 variants of uncertain significance, and putative benign/VUS. Symptoms associated with these variants were curated from patient-provided information and prior publications to define the spectrum of clinical phenotypes. In this newly expanded cohort, seizures showed no differential distribution between patients harboring GOF and LOF variants, while movement disorders segregated by mutation type. Paroxysmal non-kinesigenic dyskinesia was predominantly observed among patients with GOF alleles of the BK channel, although not exclusively so, while additional movement disorders were observed in patients with LOF variants. Neurodevelopmental and structural brain abnormalities were prevalent in patients with LOF mutations. In contrast to mutations, disease-associated KCNMA1 single nucleotide polymorphisms were not predominantly related to neurological phenotypes but covered a wider set of peripheral physiological functions. Together, this review provides additional evidence exploring the genetic and biochemical basis for KCNMA1-linked channelopathy and summarizes the clinical repository of patient symptoms across multiple types of KCNMA1 gene variants.

The power of genetic diversity in genome-wide association studies of lipids

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

An integrative epi-transcriptomic approach identifies the human cartilage chitinase 3-like protein 2 (CHI3L2) as a potential mediator of B12 deficiency in adipocytes

Vitamin B12 has multiple biochemical functions including in the one-carbon cycle generating a methyl group for DNA methylation, and metabolism of fatty acids and amino acids to generate energy via the citric acid cycle. The aim of our study was to use a combined epigenomic and transcriptomic approach to identify novel genes mediating the effect of B12 on adipogenesis.Human pre-adipocytes (CHUB-S7) were treated with a range of B12 (0-500 nM) concentrations from the day of cell seeding until harvesting in discovery and validation experiments prior to genome-wide methylation analysis using the Illumina HumanMethylation 450Beadchip. For transcriptomic analysis, RNA-seq libraries were run on the Illumina HiSeq 2500. To further investigate the expression of any genes on human adipogenesis, a second human preadipocyte strain was studied (SGBS) by real-time quantitative PCR (qRT-PCR).A combined epigenetic and transcriptomic approach in differentiated human pre-adipocyte cell line, CHUB-S7, identified that the Human cartilage chitinase 3-like protein 2 (CHI3L2) gene was hypo-methylated and had increased expression in low B12 conditions. Furthermore, there was an approximately 1000-fold increase in CHI3L2 expression in the early days of adipocyte differentiation, which paralleled an increase of lipid droplets in differentiated SGBS cells and an increased expression level of markers of mature adipocytes.In summary, we have identified a potential role of the human cartilage chitinase 3-like protein 2 (CHI3L2) in adipocyte function in the presence of low B12 levels.

DNA methylation analyses identify an intronic ZDHHC6 locus associated with time to recurrent stroke in the Vitamin Intervention for Stroke Prevention (VISP) clinical trial

Aberrant DNA methylation profiles have been implicated in numerous cardiovascular diseases; however, few studies have investigated how these epigenetic modifications contribute to stroke recurrence. The aim of this study was to identify methylation loci associated with the time to recurrent cerebro- and cardiovascular events in individuals of European and African descent. DNA methylation profiles were generated for 180 individuals from the Vitamin Intervention for Stroke Prevention clinical trial using Illumina HumanMethylation 450K BeadChip microarrays, resulting in beta values for 470,871 autosomal CpG sites. Ethnicity-stratified survival analyses were performed using Cox Proportional Hazards regression models for associations between each methylation locus and the time to recurrent stroke or composite vascular event. Results were validated in the Vall d’Hebron University Hospital cohort from Barcelona, Spain. Network analyses of the methylation loci were generated using weighted gene coexpression network analysis. Primary analysis identified four significant loci, cg04059318, ch.2.81927627R, cg03584380, and cg24875416, associated with time to recurrent stroke. Secondary analysis identified three loci, cg00076998, cg16758041, and cg02365967, associated with time to composite vascular endpoint. Locus cg03584380, which is located in an intron of ZDHHC6, was replicated in the Vall d’Hebron University Hospital cohort. The results from this study implicate the degree of methylation at cg03584380 is associated with the time of recurrence for stroke or composite vascular events across two ethnically diverse groups. Furthermore, modules of loci were associated with clinical traits and blood biomarkers including previous number of strokes, prothrombin fragments 1 + 2, thrombomodulin, thrombin-antithrombin complex, triglyceride levels, and tissue plasminogen activator. Ultimately, these loci could serve as potential epigenetic biomarkers that could identify at-risk individuals in recurrence-prone populations.

Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank

We use UK Biobank data to train predictors for 65 blood and urine markers such as HDL, LDL, lipoprotein A, glycated haemoglobin, etc. from SNP genotype. For example, our Polygenic Score (PGS) predictor correlates ∼0.76 with lipoprotein A level, which is highly heritable and an independent risk factor for heart disease. This may be the most accurate genomic prediction of a quantitative trait that has yet been produced (specifically, for European ancestry groups). We also train predictors of common disease risk using blood and urine biomarkers alone (no DNA information); we call these predictors biomarker risk scores, BMRS. Individuals who are at high risk (e.g., odds ratio of >5× population average) can be identified for conditions such as coronary artery disease (AUC∼0.75), diabetes (AUC∼0.95), hypertension, liver and kidney problems, and cancer using biomarkers alone. Our atherosclerotic cardiovascular disease (ASCVD) predictor uses ∼10 biomarkers and performs in UKB evaluation as well as or better than the American College of Cardiology ASCVD Risk Estimator, which uses quite different inputs (age, diagnostic history, BMI, smoking status, statin usage, etc.). We compare polygenic risk scores (risk conditional on genotype: PRS) for common diseases to the risk predictors which result from the concatenation of learned functions BMRS and PGS, i.e., applying the BMRS predictors to the PGS output.

Mendelian Randomization of Dyslipidemia on Cognitive Impairment Among Older Americans

Background: Altered lipid metabolism may be a risk factor for dementia, and blood cholesterol level has a strong genetic component. We tested the hypothesis that dyslipidemia (either low levels of high-density lipoprotein cholesterol (HDL-C) or high total cholesterol) is associated with cognitive status and domains, and assessed causality using genetic predisposition to dyslipidemia as an instrumental variable. Methods: Using data from European and African genetic ancestry participants in the Health and Retirement Study, we selected observations at the first non-missing biomarker assessment (waves 2006-2012). Cognition domains were assessed using episodic memory, mental status, and vocabulary tests. Overall cognitive status was categorized in three levels (normal, cognitive impairment non-dementia, dementia). Based on 2018 clinical guidelines, we compared low HDL-C or high total cholesterol to normal levels. Polygenic scores for dyslipidemia were used as instrumental variables in a Mendelian randomization framework. Multivariable logistic regressions and Wald-type ratio estimators were used to examine associations. Results: Among European ancestry participants (n = 8,781), at risk HDL-C levels were associated with higher odds of cognitive impairment (OR = 1.20, 95% CI: 1.03, 1.40) and worse episodic memory, specifically. Using cumulative genetic risk for HDL-C levels as a valid instrumental variable, a significant causal estimate was observed between at risk low HDL-C levels and higher odds of dementia (OR = 2.15, 95% CI: 1.16, 3.99). No significant associations were observed between total cholesterol levels and cognitive status. No significant associations were observed in the African ancestry sample (n = 2,101). Conclusion: Our study demonstrates low blood HDL-C is a potential causal risk factor for impaired cognition during aging in non-Hispanic whites of European ancestry. Dyslipidemia can be modified by changing diets, health behaviors, and therapeutic strategies, which can improve cognitive aging. Studies on low density lipoprotein cholesterol, the timing of cholesterol effects on cognition, and larger studies in non-European ancestries are needed.

Identifying the Lipidomic Effects of a Rare Loss-of-Function Deletion in ANGPTL3

BACKGROUND

The identification and understanding of therapeutic targets for atherosclerotic cardiovascular disease is of fundamental importance given its global health and economic burden. Inhibition of ANGPTL3 (angiopoietin-like 3) has demonstrated a cardioprotective effect, showing promise for atherosclerotic cardiovascular disease treatment, and is currently the focus of ongoing clinical trials. Here, we assessed the genetic basis of variation in ANGPTL3 levels in the San Antonio Family Heart Study.

METHODS

We assayed ANGPTL3 protein levels in ≈1000 Mexican Americans from extended pedigrees. By drawing upon existing plasma lipidome profiles and genomic data we conducted analyses to understand the genetic basis to variation in ANGPTL3 protein levels, and accordingly the correlation with the plasma lipidome.

RESULTS

In a variance components framework, we identified that variation in ANGPTL3 was significantly heritable (h²=0.33, P=1.31×10^-16). To explore the genetic basis of this heritability, we conducted a genome-wide linkage scan and identified significant linkage (logarithm of odds =6.18) to a locus on chromosome 1 at 90 centimorgans, corresponding to the ANGPTL3 gene location. In the genomes of 23 individuals from a single pedigree, we identified a loss-of-function variant, rs398122988 (N121Kfs*2), in ANGPTL3, that was significantly associated with lower ANGPTL3 levels (β=-1.69 SD units, P=3.367×10^-13), and accounted for the linkage signal at this locus. Given the known role of ANGPTL3 as an inhibitor of endothelial and lipoprotein lipase, we explored the association of ANGPTL3 protein levels and rs398122988 with the plasma lipidome and related phenotypes, identifying novel associations with phosphatidylinositols.

CONCLUSIONS

Variation in ANGPTL3 protein levels is heritable and under significant genetic control. Both ANGPTL3 levels and loss-of-function variants in ANGPTL3 have significant associations with the plasma lipidome. These findings further our understanding of ANGPTL3 as a therapeutic target for atherosclerotic cardiovascular disease.

Challenges of Precision Medicine for Atherosclerotic Cardiovascular Disease Based on Human Genome Information

Precision or personalized medicine is currently gaining a lot of attention. Clinical evidence for its effectiveness has been established based on randomized clinical trials accounting for classical risk factors, such as hypertension, diabetes, and serum lipids. However, besides such classical risk factors, the genetic background should be considered, at least for heritable traits, including atherosclerotic cardiovascular disease (ASCVD). Such classical risk factors are almost always incidents that have already occurred in which it may be too late to start treatment, instead of indicators of presymptomatic state. Human genome information is associated with most traits, including ASCVD. Two methods of implementing precision medicine for ASCVD using human genome information are currently being investigated: the use of rare genetic variations that have large effect sizes and polygenic risk scores that are composed of multiple common genetic variations. This review article emphasizes the importance of clinical as well as genetic diagnoses when implementing precision medicine. Precision medicine should be considered based on comprehensive genetic analyses, encompassing rare to common genetic variations.

Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer

Metabolomics deals with multiple and complex chemical reactions within living organisms and how these are influenced by external or internal perturbations. It lies at the heart of omics profiling technologies not only as the underlying biochemical layer that reflects information expressed by the genome, the transcriptome and the proteome, but also as the closest layer to the phenome. The combination of metabolomics data with the information available from genomics, transcriptomics, and proteomics offers unprecedented possibilities to enhance current understanding of biological functions, elucidate their underlying mechanisms and uncover hidden associations between omics variables. As a result, a vast array of computational tools have been developed to assist with integrative analysis of metabolomics data with different omics. Here, we review and propose five criteria-hypothesis, data types, strategies, study design and study focus- to classify statistical multi-omics data integration approaches into state-of-the-art classes under which all existing statistical methods fall. The purpose of this review is to look at various aspects that lead the choice of the statistical integrative analysis pipeline in terms of the different classes. We will draw particular attention to metabolomics and genomics data to assist those new to this field in the choice of the integrative analysis pipeline.

Association of Circulating Metabolites in Plasma or Serum and Risk of Stroke: Meta-analysis From 7 Prospective Cohorts

OBJECTIVE

To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings.

METHODS

We investigated the association of metabolites with risk of stroke in 7 prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by nuclear magnetic resonance technology. The relationship between metabolites and stroke was assessed with Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately.

RESULTS

The analyses revealed 10 significant metabolite associations. Amino acid histidine (hazard ratio [HR] per SD 0.90, 95% confidence interval [CI] 0.85, 0.94; p = 4.45 × 10-5), glycolysis-related metabolite pyruvate (HR per SD 1.09, 95% CI 1.04, 1.14; p = 7.45 × 10-4), acute-phase reaction marker glycoprotein acetyls (HR per SD 1.09, 95% CI 1.03, 1.15; p = 1.27 × 10-3), cholesterol in high-density lipoprotein (HDL) 2, and several other lipoprotein particles were associated with risk of stroke. When focused on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD 1.12, 95% CI 1.05, 1.19; p = 4.13 × 10-4) and total and free cholesterol in large HDL particles.

CONCLUSIONS

We found association of amino acids, glycolysis-related metabolites, acute-phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding stroke.

Associations between TUBB-WWOX SNPs, their haplotypes, gene-gene, and gene-environment interactions and dyslipidemia

In this study, we investigated associations between single nucleotide polymorphisms (SNPs) in the tubulin beta class I (TUBB) and WW domain-containing oxidoreductase (WWOX) genes, gene-gene interactions, and gene-environment interactions and dyslipidemia in the Chinese Maonan ethnic group. Four SNPs (rs3132584, rs3130685, rs2222896, and rs2548861) were genotyped in unrelated subjects with normal lipid levels (864) or dyslipidemia (1129). While 5.0% of Maonan subjects carried the rs3132584TT genotype, none of the Chinese Han in Beijing subjects did. Allele and genotype frequencies differed between the normal and dyslipidemia groups for three SNPs (rs3132584, rs3130685, and rs2222896). rs2222896G allele carriers in the normal group had higher low-density lipoprotein cholesterol and lower high-density lipoprotein cholesterol levels. The rs3132584GG, rs3130685CC+TT, and rs2222896GG genotypes as well as the rs2222896G-rs2548861G and rs2222896G-rs2548861T haplotypes were associated with an elevated risk of dyslipidemia; the rs2222896A-rs2548861T and rs2222896A-rs2548861G haplotypes were associated with a reduced risk of dyslipidemia. Among the thirteen TUBB-WWOX interaction types identified, rs3132584T-rs3130685T-rs2222896G-rs2548861T increased the risk of dyslipidemia 1.371-fold. Fourteen two- to four-locus optimal interactive models for SNP-SNP, haplotype-haplotype, gene-gene, and gene-environment interactions exhibited synergistic or contrasting effects on dyslipidemia. Finally, the interaction between rs3132584 and rs2222896 increased the risk of dyslipidemia 2.548-fold and predicted hypertension.

Genetics of 35 blood and urine biomarkers in the UK Biobank

Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n = 363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1 s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build 'multi-PRS' models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n = 135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.

Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power

Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.

Association of the Duration of Ideal Cardiovascular Health Through Adulthood With Cardiometabolic Outcomes and Mortality in the Framingham Offspring Study

Importance

The American Heart Association ideal cardiovascular health (CVH) score is associated with the risk of cardiovascular disease (CVD) and mortality. However, it is unclear whether the number of years spent in ideal CVH is associated with morbidity or with mortality.

Objective

To evaluate whether living longer with a higher CVH score in midlife is associated with lower risk of hypertension, diabetes, chronic kidney disease, CVD and its subtypes (coronary heart disease, stroke, congestive heart failure, and peripheral artery disease), or all-cause mortality in later life.

Design, Setting, and Participants

This prospective cohort study used data from 1445 participants from 1991 to 2015 who participated in the community-based Framingham Heart Study Offspring investigation conducted in Massachusetts. The CVH scores of participants were assessed at examination cycles 5, 6, and 7 (1991-1995; 1995-1998; and 1998-2001, respectively). Individuals were excluded from analyses of the association between duration of CVH score and outcomes if they had the outcome of interest at the seventh examination. The median follow-up was approximately 16 years. Data were analyzed from April 2018 to October 2019. The CVH score categories were poor for scores 0 to 7, intermediate for scores 8 to 11, and ideal for scores 12 to 14. A composite score was derived based on smoking status, diet, physical activity, resting blood pressure levels, body mass index, fasting blood glucose levels, and total serum cholesterol levels.

Main Outcomes and Measures

Number of events and number at risk for each main outcome, including incident hypertension, diabetes, chronic kidney disease, CVD, and all-cause mortality, after the seventh examination.

Results

Of 1445 eligible participants, the mean (SD) age was 60 (9) years, and 751 (52%) were women. Number of events/number at risk for each main outcome after the seventh examination were 348/795 for incident hypertension, 104/1304 for diabetes, 198/918 for chronic kidney disease, 210/1285 for CVD, and 300/1445 for all-cause mortality. At the seventh examination, participants mostly had poor (568 [39%]) or intermediate (782 [54%]) CVH scores. For each antecedent (before examination cycle 7) 5-year duration that participants had intermediate or ideal CVH, they were less likely to develop adverse outcomes (hazards ratios of 0.67 [95% CI, 0.56-0.80] for incident hypertension, 0.73 [95% CI, 0.57-0.93] for diabetes, 0.75 [95% CI, 0.63-0.89] for chronic kidney disease, 0.73 [95% CI, 0.63-0.85] for CVD, and 0.86 [95% CI, 0.76-0.97] for all-cause mortality) relative to living the same amount of time in poor CVH (referent group). No effect modification was observed by age or by sex.

Conclusions and Relevance

These results suggest that more time spent in better CVH in midlife may have salutary cardiometabolic benefits and may be associated with lower mortality later in life.

Gene networks and pathways for plasma lipid traits via multitissue multiomics systems analysis

Genome-wide association studies (GWASs) have implicated ∼380 genetic loci for plasma lipid regulation. However, these loci only explain 17-27% of the trait variance, and a comprehensive understanding of the molecular mechanisms has not been achieved. In this study, we utilized an integrative genomics approach leveraging diverse genomic data from human populations to investigate whether genetic variants associated with various plasma lipid traits, namely, total cholesterol, high and low density lipoprotein cholesterol (HDL and LDL), and triglycerides, from GWASs were concentrated on specific parts of tissue-specific gene regulatory networks. In addition to the expected lipid metabolism pathways, gene subnetworks involved in "interferon signaling," "autoimmune/immune activation," "visual transduction," and "protein catabolism" were significantly associated with all lipid traits. In addition, we detected trait-specific subnetworks, including cadherin-associated subnetworks for LDL; glutathione metabolism for HDL; valine, leucine, and isoleucine biosynthesis for total cholesterol; and insulin signaling and complement pathways for triglyceride. Finally, by using gene-gene relations revealed by tissue-specific gene regulatory networks, we detected both known (e.g., APOH, APOA4, and ABCA1) and novel (e.g., F2 in adipose tissue) key regulator genes in these lipid-associated subnetworks. Knockdown of the F2 gene (coagulation factor II, thrombin) in 3T3-L1 and C3H10T1/2 adipocytes altered gene expression of Abcb11, Apoa5, Apof, Fabp1, Lipc, and Cd36; reduced intracellular adipocyte lipid content; and increased extracellular lipid content, supporting a link between adipose thrombin and lipid regulation. Our results shed light on the complex mechanisms underlying lipid metabolism and highlight potential novel targets for lipid regulation and lipid-associated diseases.

Associations between peroxisome proliferator-activated receptor γ (PPAR-γ) polymorphisms and serum lipids: Two cross-sectional studies of community-dwelling adults

Dyslipidemia is a well-established risk factor for cardiovascular disease. Experimental studies have reported that peroxisome proliferator-activated receptor γ (PPAR-γ) regulates adipocyte differentiation, lipid storage, and glucose metabolism. Therefore, we examined the associations between PPAR-γ polymorphisms (rs1801282, rs3856806, rs12497191, rs1151999, and rs1152003) and serum lipids in two cross-sectional studies. In the Shizuoka area of the Japan Multi-Institutional Collaborative Cohort Study, we examined 4,952 participants (3,356 men and 1,596 women) in a baseline survey and 2,245 participants (1,550 men and 695 women) in a second survey 5 years later. Outcome measures were the prevalence of dyslipidemia (low-density lipoprotein-cholesterol [LDL-C] ≥ 140 mg/dl, high-density lipoprotein-cholesterol < 40 mg/dl, triglycerides ≥ 150 mg/dl, and/or use of cholesterol-lowering drugs) and the prevalence of high LDL-C (LDL-C ≥ 140 mg/dl and/or use of cholesterol-lowering drugs). Multivariate odds ratios (ORs) were estimated by using unconditional logistic regression models. A total of 2,114 and 1,431 individuals (42.7% and 28.9%) had dyslipidemia and high LDL-C in the baseline survey, respectively, as did 933 and 716 (41.6% and 31.9%), respectively, in the second survey. In the baseline study, compared with major allele homozygotes, minor allele homozygotes of rs3856806 and rs12497191 had a 42% (OR, 0.58; 95% confidence interval (CI), 0.39-0.85) and 23% (OR, 0.77; 95% CI, 0.60-0.99) lower risk of dyslipidemia, respectively, after adjustment for potential confounding factors. In addition, minor allele homozygotes of rs3856806 had a 45% (OR, 0.55; 95% CI, 0.35-0.86) lower risk of high LDL-C. Similar risk reductions were found in the second survey. In conclusion, rs3856806 and rs12497191 polymorphisms may be related to a lower risk of dyslipidemia and high LDL-C.

Two robust tools for inference about causal effects with invalid instruments

Instrumental variables have been widely used to estimate the causal effect of a treatment on an outcome. Existing confidence intervals for causal effects based on instrumental variables assume that all of the putative instrumental variables are valid; a valid instrumental variable is a variable that affects the outcome only by affecting the treatment and is not related to unmeasured confounders. However, in practice, some of the putative instrumental variables are likely to be invalid. This paper presents two tools to conduct valid inference and tests in the presence of invalid instruments. First, we propose a simple and general approach to construct confidence intervals based on taking unions of well-known confidence intervals. Second, we propose a novel test for the null causal effect based on a collider bias. Our two proposals outperform traditional instrumental variable confidence intervals when invalid instruments are present and can also be used as a sensitivity analysis when there is concern that instrumental variables assumptions are violated. The new approach is applied to a Mendelian randomization study on the causal effect of low-density lipoprotein on globulin levels.

Epigenetic methylation in Eosinophilic Esophagitis: Molecular ageing and novel biomarkers for treatment response

BACKGROUND

Treatment failure in eosinophilic esophagitis (EoE) is common. We hypothesize that DNA methylation differs between patients by treatment response to topical steroids (oral viscous budesonide), thus offering the potential to inform targeting therapies.

OBJECTIVE

We sought to identify differentially methylated sites and affiliated genes in pre-treatment oesophageal cells between responders and non-responders and test for accelerated epigenetic ageing in oesophageal cells of EoE patients.

METHODS

DNA was extracted from prospectively collected and biobanked oesophageal biopsies from 36 Caucasian treatment naïve EoE patients at diagnosis. Methylation assays were completed using the Infinium HumanMethylation450 BeadChip. Normalized β values for each CpG site were tested (t test) for differential methylation. Further, 353 CpG probes were used to estimate epigenetic age for each patient and a linear regression model tested whether chronologic age and epigenetic age differed. Epigenetic age results were confirmed in an independent cohort of healthy controls.

RESULTS

Eighteen CpG sites were differentially methylated by treatment response (P < .00001). The mean epigenetic age and chronological age were 56.1 ± 11.1 and 36.7 ± 12.3 years, a mean age difference of 19.3 ± 5.2 years (P < .0001); accelerated ageing was not observed in the oesophageal cells of healthy controls.

CONCLUSIONS AND CLINICAL RELEVANCE

EoE patients that respond versus do not respond to treatment have differences in their methylation profile, including enrichment of genes in pathways consistent with cellular injury and repair due to environmental stress and cell adhesion and barrier integrity. EoE also appears to accelerate cellular ageing. Whether treatment can arrest or reverse accelerated epigenetic ageing and the implications for long-term disease progression is important areas for future research.

Transcriptomic Heterogeneity of Alzheimer's Disease Associated with Lipid Genetic Risk

Alzheimer's disease (AD) is a multifactorial disease that affects more than 5 million Americans. Multiple pathways might be involved in the AD pathogenesis. The implication of lipid genetic susceptibility on brain gene expression is yet to be investigated. The current study included 192 brain samples from AD patients who were enrolled in the ROSMAP study. The samples were genotyped and imputed to the HRC Reference Panel. Lipid polygenetic risk score was constructed from the weighted sum of genetic variants associated with low-density lipoprotein cholesterol (LDL-C). The gene expression was profiled by RNA sequencing, and the  association of gene expression with lipid polygenetic risk scores was tested by linear regression models adjusted for age, sex and APOE e4 alleles. Three genes were found to associate with lipid polygenetic risk scores, including HMCN2 (P = 3.6 × 10-7), PDLIM5 (P = 1.2 × 10-6), and FHL5 (P = 2.0 × 10-6). Network analysis revealed multiple related pathways, including dopaminergic synapse (P = 4.5 × 10-5), circadian entrainment (P = 1.1 × 10-4), and cholinergic synapse (P = 2.3 × 10-4). Our study underscores the importance of lipid regulation and metabolism to AD heterogeneity.

Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population

We performed a metabolome genome-wide association study for the Japanese population in the prospective cohort study of Tohoku Medical Megabank. By combining whole-genome sequencing and nontarget metabolome analyses, we identified a large number of novel associations between genetic variants and plasma metabolites. Of the identified metabolite-associated genes, approximately half have already been shown to be involved in various diseases. We identified metabolite-associated genes involved in the metabolism of xenobiotics, some of which are from intestinal microorganisms, indicating that the identified genetic variants also markedly influence the interaction between the host and symbiotic bacteria. We also identified five associations that appeared to be female-specific. A number of rare variants that influence metabolite levels were also found, and combinations of common and rare variants influenced the metabolite levels more profoundly. These results support our contention that metabolic phenotyping provides important insights into how genetic and environmental factors provoke human diseases.

MAPT haplotype-stratified GWAS reveals differential association for AD risk variants

INTRODUCTION

MAPT H1 haplotype is implicated as a risk factor for neurodegenerative diseases including Alzheimer's disease (AD).

METHODS

Using Alzheimer's Disease Genetics Consortium (ADGC) genome-wide association study (GWAS) data (n = 18,841), we conducted a MAPT H1/H2 haplotype-stratified association to discover MAPT haplotype-specific AD risk loci.

RESULTS

We identified 11 loci-5 in H2-non-carriers and 6 in H2-carriers-although none of the MAPT haplotype-specific associations achieved genome-wide significance. The most significant H2 non-carrier-specific association was with a NECTIN2 intronic (P = 1.33E-07) variant, and that for H2 carriers was near NKX6-1 (P = 1.99E-06). The GABRG2 locus had the strongest epistasis with MAPT H1/H2 variant rs8070723 (P = 3.91E-06). Eight of the 12 genes at these loci had transcriptome-wide significant differential expression in AD versus control temporal cortex (q < 0.05). Six genes were members of the brain transcriptional co-expression network implicated in "synaptic transmission" (P = 9.85E-59), which is also enriched for neuronal genes (P = 1.0E-164), including MAPT.

DISCUSSION

This stratified GWAS identified loci that may confer AD risk in a MAPT haplotype-specific manner. This approach may preferentially enrich for neuronal genes implicated in synaptic transmission.

Genome-Wide Selection Scan in an Arabian Peninsula Population Identifies a TNKS Haplotype Linked to Metabolic Traits and Hypertension

Despite the extreme and varying environmental conditions prevalent in the Arabian Peninsula, it has experienced several waves of human migrations following the out-of-Africa diaspora. Eventually, the inhabitants of the peninsula region adapted to the hot and dry environment. The adaptation and natural selection that shaped the extant human populations of the Arabian Peninsula region have been scarcely studied. In an attempt to explore natural selection in the region, we analyzed 662,750 variants in 583 Kuwaiti individuals. We searched for regions in the genome that display signatures of positive selection in the Kuwaiti population using an integrative approach in a conservative manner. We highlight a haplotype overlapping TNKS that showed strong signals of positive selection based on the results of the multiple selection tests conducted (integrated Haplotype Score, Cross Population Extended Haplotype Homozygosity, Population Branch Statistics, and log-likelihood ratio scores). Notably, the TNKS haplotype under selection potentially conferred a fitness advantage to the Kuwaiti ancestors for surviving in the harsh environment while posing a major health risk to present-day Kuwaitis.

Genomics of hypertriglyceridemia

With regard to heritability of phenotypes, the serum triglyceride level is considered to be highly heritable, with approximately 50% of its variability estimated to derive from parents. Thus, approximately 50% could be modifiable via environmental factors, including lifestyle and medications. Lipoproteins are definitive risk factors for atherosclerotic cardiovascular disease (ASCVD); among these, low-density lipoprotein (LDL) particles have been established as a causal factor for the development of ASCVD. Recently, triglyceride-rich lipoproteins have emerged as additional lipoproteins, which should be considered as residual targets for ASCVD risk reduction by LDL-lowering therapies. Compared with LDL particles, triglyceride-rich lipoproteins are significantly increased in the postprandial state, making it difficult to assess their clinical relevance. However, numerous pieces of evidence suggest that fasting and non-fasting triglycerides are associated with ASCVD. In addition, a recent meta-analysis of a Mendelian randomization study suggests that consideration of apolipoprotein B (APOB) might be better than considering LDL and triglyceride-rich lipoproteins separately. In this review, we examine (1) how triglyceride levels are determined by genetics, (2) lessons from extreme cases exhibiting severe hypertriglyceridemia, and (3) why triglycerides are important, by highlighting clinical and genetic evidence of their associations with ASCVD risk.

Genetic Affinities among Southern Africa Hunter-Gatherers and the Impact of Admixing Farmer and Herder Populations

Southern African indigenous groups, traditionally hunter-gatherers (San) and herders (Khoekhoe), are commonly referred to as “Khoe-San” populations and have a long history in southern Africa. Their ancestors were largely isolated up until ∼2,000 years ago before the arrival of pastoralists and farmers in southern Africa. Assessing relationships among regional Khoe-San groups has been challenging due to admixture with immigrant populations that obscure past population affinities and gene flow among these autochthonous communities. We re-evaluate a combined genome-wide data set of previously published southern Africa Khoe-San populations in conjunction with novel data from Khoe-San individuals collected in Xade (Central Kalahari Game Reserve, Botswana) prior to their resettlement outside the reserve. After excluding regions in the genome that trace their ancestry to recent migrant groups, the genetic diversity of 20 Khoe-San groups fitted an isolation-by-distance model. Even though isolation-by-distance explained most genetic affinities between the different autochthonous groups, additional signals of contact between Khoe-San groups could be detected. For instance, we found stronger genetic affinities, than what would be explained by isolation-by-distance gene flow, between the two geographically separated Khoe-San groups, who speak branches of the Kx’a-language family (ǂHoan and Ju). We also scanned the genome-wide data for signals of adaptive gene flow from farmers/herders into Khoe-San groups and identified a number of genomic regions potentially introduced by the arrival of the new groups. This study provides a comprehensive picture of affinities among Khoe-San groups, prior to the arrival of recent migrants, and found that these affinities are primarily determined by the geographic landscape.

Population history and genetic adaptation of the Fulani nomads: inferences from genome-wide data and the lactase persistence trait

Background

Human population history in the Holocene was profoundly impacted by changes in lifestyle following the invention and adoption of food-production practices. These changes triggered significant increases in population sizes and expansions over large distances. Here we investigate the population history of the Fulani, a pastoral population extending throughout the African Sahel/Savannah belt.

Results

Based on genome-wide analyses we propose that ancestors of the Fulani population experienced admixture between a West African group and a group carrying both European and North African ancestries. This admixture was likely coupled with newly adopted herding practices, as it resulted in signatures of genetic adaptation in contemporary Fulani genomes, including the control element of the LCT gene enabling carriers to digest lactose throughout their lives. The lactase persistence (LP) trait in the Fulani is conferred by the presence of the allele T-13910, which is also present at high frequencies in Europe. We establish that the T-13910 LP allele in Fulani individuals analysed in this study lies on a European haplotype background thus excluding parallel convergent evolution. We furthermore directly link the T-13910 haplotype with the Lactase Persistence phenotype through a Genome Wide Association study (GWAS) and identify another genomic region in the vicinity of the SPRY2 gene associated with glycaemic measurements after lactose intake.

Conclusions

Our findings suggest that Eurasian admixture and the European LP allele was introduced into the Fulani through contact with a North African population/s. We furthermore confirm the link between the lactose digestion phenotype in the Fulani to the MCM6/LCT locus by reporting the first GWAS of the lactase persistence trait. We also explored other signals of recent adaptation in the Fulani and identified additional candidates for selection to adapt to herding life-styles.

Regulation of glucose and lipid metabolism in health and disease

Glucose and fatty acids are the major sources of energy for human body. Cholesterol, the most abundant sterol in mammals, is a key component of cell membranes although it does not generate ATP. The metabolisms of glucose, fatty acids and cholesterol are often intertwined and regulated. For example, glucose can be converted to fatty acids and cholesterol through de novo lipid biosynthesis pathways. Excessive lipids are secreted in lipoproteins or stored in lipid droplets. The metabolites of glucose and lipids are dynamically transported intercellularly and intracellularly, and then converted to other molecules in specific compartments. The disorders of glucose and lipid metabolism result in severe diseases including cardiovascular disease, diabetes and fatty liver. This review summarizes the major metabolic aspects of glucose and lipid, and their regulations in the context of physiology and diseases.

Race-ethnic differences in the associations of maternal lipid trait genetic risk scores with longitudinal fetal growth

BACKGROUND

Fetal growth, an important predictor of cardiometabolic diseases in adults, is influenced by maternal and fetal genetic and environmental factors.

OBJECTIVE

We investigated the association between maternal lipid genetic risk score (GRS) and fetal growth among 4 US racial-ethnic populations (Whites, Blacks, Hispanics, and Asians).

METHODS

We extracted genotype data for 2008 pregnant women recruited in the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort with up to 6 standardized ultrasound examinations. GRS was calculated using 240 single-nucleotide polymorphisms previously associated with higher total cholesterol (GRSTChol), low-density lipoprotein cholesterol (GRSLDLc), and triglycerides (GRSTG) and lower high-density lipoprotein cholesterol (GRSHDLc).

RESULTS

At 40 weeks' gestation, a unit increase in GRSTG was associated with 11.4 g higher fetal weight (95% confidence interval [CI] 2.8-20.0 g) among normal-weight Whites, 26.3 g (95% CI 6.0-46.6 g) among obese Blacks, and 30.8 g (95% CI 6.3-55.3 g) among obese Hispanics. Higher GRSHDLc was associated with increased fetal weight across 36 to 40 weeks among normal-weight Whites and across 13 to 20 weeks among normal-weight Asians, but with decreased fetal weight across 26 to 40 weeks among normal-weight Hispanics. Higher GRSTChol was suggestively associated with increased fetal weight in males and decreased in females. Associations remained consistent after adjustment for serum lipids.

CONCLUSION

Associations between fetal weight and maternal lipid GRS appear to vary by maternal race-ethnic group, obesity status, and offspring sex. Genetic susceptibility to unfavorable lipid profiles contributes to fetal growth differences even among normal-weight women suggesting a potential future application in predicting aberrant fetal growth.

Rare DEGS1 variant significantly alters de novo ceramide synthesis pathway

The de novo ceramide synthesis pathway is essential to human biology and health, but genetic influences remain unexplored. The core function of this pathway is the generation of biologically active ceramide from its precursor, dihydroceramide. Dihydroceramides have diverse, often protective, biological roles; conversely, increased ceramide levels are biomarkers of complex disease. To explore the genetics of the ceramide synthesis pathway, we searched for deleterious nonsynonymous variants in the genomes of 1,020 Mexican Americans from extended pedigrees. We identified a Hispanic ancestry-specific rare functional variant, L175Q, in delta 4-desaturase, sphingolipid 1 (DEGS1), a key enzyme in the pathway that converts dihydroceramide to ceramide. This amino acid change was significantly associated with large increases in plasma dihydroceramides. Indexes of DEGS1 enzymatic activity were dramatically reduced in heterozygotes. CRISPR/Cas9 genome editing of HepG2 cells confirmed that the L175Q variant results in a partial loss of function for the DEGS1 enzyme. Understanding the biological role of DEGS1 variants, such as L175Q, in ceramide synthesis may improve the understanding of metabolic-related disorders and spur ongoing research of drug targets along this pathway.

Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population-Ascertained Hyperlipidemias

Background

We asked whether, after excluding familial hypercholesterolemia, individuals with high low‐density lipoprotein cholesterol (LDL‐C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population‐based hyperlipidemias.

Methods and Results

We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first‐degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias (LDL‐C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta‐analysis of the hyperlipidemic families and the population cohort (high LDL‐C: hazard ratio, 1.74 [95% CI, 1.48–2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09–1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid‐lowering medication. In lipidomic profiling, high LDL‐C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P‐value range 0.038–2.3×10⁻⁵⁶). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population (LDL‐C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts).

Conclusions

Hyperlipidemias with family history conferred similar coronary artery disease risk as population‐based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL‐C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population‐ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

Genetics-driven discovery of novel regulators of lipid metabolism

PURPOSE OF REVIEW

Residual cardiovascular disease risk and increasing metabolic syndrome risk underscores a need for novel therapeutics targeting lipid metabolism in humans. Unbiased human genetic screens have proven powerful in identifying novel genomic loci, and this review discusses recent developments in such discovery.

RECENT FINDINGS

Recent human genome-wide association studies have been completed in incredibly large, detailed cohorts, allowing for the identification of more than 300 genomic loci that participate in the regulation of plasma lipid metabolism. However, the discovery of these loci has greatly outpaced the elucidation of the underlying functional mechanisms. The identification of novel roles for long noncoding RNAs, such as CHROME, LeXis, and MeXis, in lipid metabolism suggests that noncoding RNAs should be included in the functional translation of GWAS loci.

SUMMARY

Unbiased genetic studies appear to have unearthed a great deal of novel biology with respect to lipid metabolism, yet translation of these findings into actionable mechanisms has been slow. Increased focus on the translation, rather than the discovery, of these loci, with new attention paid to lncRNAs, can help spur the development of novel therapeutics targeting lipid metabolism.

Exome chip-driven association study of lipidemia in >14,000 Koreans and evaluation of genetic effect on identified variants between different ethnic groups

Lipid levels in blood are widely used to diagnose and monitor chronic diseases. It is essential to identify the genetic traits involved in lipid metabolism for understanding chronic diseases. However, the influence of genetic traits varies depending on race, sex, age, and ethnicity. Therefore, research focusing on populations of individual countries is required, and the results can be used as a basis for comparison of results of other studies at the cross-racial and cross-country levels. In the present study, we selected lipid-related variants and evaluated their effects on lipid-related diseases in more than 14,000 subjects of three cohorts using the Illumina Human Exome Beadchip. A genome-wide association study was conducted using EPACTs after adjusting for age, sex, and recruitment area. A genome-wide significance cutoff was defined as p < 5E-08 in all the three cohorts. Sixteen variants represented the lipid traits and were classified as vulnerable to borderline hypertriglyceridemia, hyper-LDL-cholesterolemia, or hypo-HDL-cholesterolemia. Moreover, we compared the genetic effects of the 16 variants between ethnic groups and identified the missense variants in apolipoprotein A-V, cholesterol ester transfer protein, and apolipoprotein E as Asian-specific. Our study provides candidate genes as markers for chronic diseases through the evaluation of genetic effects.

Hepatic posttranscriptional network comprised of CCR4-NOT deadenylase and FGF21 maintains systemic metabolic homeostasis

Whole-body metabolic homeostasis is tightly controlled by hormone-like factors with systemic or paracrine effects that are derived from nonendocrine organs, including adipose tissue (adipokines) and liver (hepatokines). Fibroblast growth factor 21 (FGF21) is a hormone-like protein, which is emerging as a major regulator of whole-body metabolism and has therapeutic potential for treating metabolic syndrome. However, the mechanisms that control FGF21 levels are not fully understood. Herein, we demonstrate that FGF21 production in the liver is regulated via a posttranscriptional network consisting of the CCR4-NOT deadenylase complex and RNA-binding protein tristetraprolin (TTP). In response to nutrient uptake, CCR4-NOT cooperates with TTP to degrade AU-rich mRNAs that encode pivotal metabolic regulators, including FGF21. Disruption of CCR4-NOT activity in the liver, by deletion of the catalytic subunit CNOT6L, increases serum FGF21 levels, which ameliorates diet-induced metabolic disorders and enhances energy expenditure without disrupting bone homeostasis. Taken together, our study describes a hepatic CCR4-NOT/FGF21 axis as a hitherto unrecognized systemic regulator of metabolism and suggests that hepatic CCR4-NOT may serve as a target for devising therapeutic strategies in metabolic syndrome and related morbidities.