Discovery and refinement of loci associated with lipid levels

Identification of important genes associated with total cholesterol using bioinformatics analysis

AIM

The aim of this study was to identify related genes for total cholesterol (TC) and evaluate the functional relevance to provide evidences for prioritizing these genes.

MATERIALS & METHODS

We performed an initial gene-based association study in about 188,578 individuals. Furthermore, we performed bioinformatics analyses to support the identified genes.

RESULTS

A total of 22,098 genes were analyzed for TC levels in gene-based association analysis and 433 of them were found to be significant after Bonferroni correction (p < 2.3 × 10(-6)).

CONCLUSION

The evidence obtained from the analyses of this study signified the importance of many known genes as well as some novel genes, for example, NR1I2, STARD3 and FN1. The findings might provide more insights into the genetic basis of lipid metabolism.

Genome- and epigenome-wide association study of hypertriglyceridemic waist in Mexican American families

BACKGROUND

There is growing interest in the hypertriglyceridemic waist (HTGW) phenotype, defined as high waist circumference (≥95 cm in males and ≥80 cm in females) combined with high serum triglyceride concentration (≥2.0 mmol/L in males and ≥1.5 mmol/L in females) as a marker of type 2 diabetes (T2D) and cardiovascular disease. However, the prevalence of this phenotype in high-risk populations, its association with T2D, and the genetic or epigenetic influences on HTGW are not well explored. Using data from large, extended families of Mexican Americans (a high-risk minority population in the USA) we aimed to: (1) estimate the prevalence of this phenotype, (2) test its association with T2D and related traits, and (3) dissect out the genetic and epigenetic associations with this phenotype using genome-wide and epigenome-wide studies, respectively.

RESULTS

Data for this study was from 850 Mexican American participants (representing 39 families) recruited under the ongoing San Antonio Family Heart Study, 26 % of these individuals had HTGW. This phenotype was significantly heritable (h (2) r = 0.52, p = 1.1 × 10(-5)) and independently associated with T2D as well as fasting glucose levels and insulin resistance. We conducted genome-wide association analyses using 759,809 single nucleotide polymorphisms (SNPs) and epigenome-wide association analyses using 457,331 CpG sites. There was no evidence of any SNP associated with HTGW at the genome-wide level but two CpG sites (cg00574958 and cg17058475) in CPT1A and one CpG site (cg06500161) in ABCG1 were significantly associated with HTGW and remained significant after adjusting for the closely related components of metabolic syndrome. CPT1A holds a cardinal position in the metabolism of long-chain fatty acids while ABCG1 plays a role in triglyceride metabolism.

CONCLUSIONS

Our results reemphasize the value of HTGW as a marker of T2D. This phenotype shows association with DNA methylation within CPT1A and ABCG1, genes involved in fatty acid and triglyceride metabolism. Our results underscore the importance of epigenetics in a clinically informative phenotype.

Stable liver-specific expression of human IDOL in humanized mice raises plasma cholesterol

AIMS

IDOL (inducible degrader of the low-density lipoprotein receptor, LDLR) is an E3 ubiquitin ligase that promotes the ubiquitination and degradation of the LDLR. IDOL is a potential therapeutic target for the development of a novel class of low-density lipoprotein cholesterol (LDL-C)-lowering therapies. In an attempt to develop a mouse model for testing IDOL inhibitors, we examined the effects of adeno-associated virus (AAV)-mediated stable expression of human IDOL in the livers of mice 'humanized' with regard to lipoprotein metabolism.

METHODS AND RESULTS

Using a liver-specific AAV serotype 8 (AAV8)-mediated delivery, AAV-hIDOL produced a dose-dependent increase in LDL-C levels and a decrease in liver LDLR protein. Furthermore, we expressed hIDOL in a 'humanized' mouse model of heterozygous familial hypercholesterolaemia (LDLR(+/-)/Apobec1(-/-)/hApoB-Tg, LAhB). In this model, total cholesterol (TC) and LDL-C levels were increased by ∼60% starting from 1 week and were sustainable for at least 3 weeks post-injection. Finally, we demonstrate that the effects caused by hIDOL expression are LDLR- dependent given the unchanged plasma lipids in LAhB mice lacking LDLR.

CONCLUSION

In conclusion, our study demonstrates a dose-dependent physiological effect of human IDOL on LDL metabolism in mice. This provides a potential model for preclinical testing of IDOL inhibitors for reduction of LDL-C levels.

Meta-analysis of lipid-traits in Hispanics identifies novel loci, population-specific effects, and tissue-specific enrichment of eQTLs

We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals, and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2, ZNF259/APOA5, KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5, LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol, and GCKR, TRIB1, ZNF259/APOA5 and NCAN/MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol (FN1 and SAMM50), two for HDL cholesterol (LOC100996634 and COPB1) and one for LDL cholesterol (LINC00324/CTC1/PFAS). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.

PHLPP phosphatases as a therapeutic target in insulin resistance-related diseases

INTRODUCTION

Pleckstrin homology domain leucine-rich repeat protein phosphatases (PHLPPs), originally identified as Akt kinase hydrophobic motif specific phosphatases, have subsequently been shown to regulate several molecules recurring within the insulin signaling pathway. This observation suggests that PHLPP phosphatases may have a clinically relevant role in the pathogenesis of insulin resistance-related diseases and may thus represent suitable targets for the treatment of these conditions.

AREAS COVERED

The literature pertaining to PHLPPs substrates is reviewed herein, along with information on the molecular players involved in regulating the activity and expression of PHLPP phosphatases. In the present review, knowledge of genetic variants in the genes that encode for PHLPP isozymes and the surrounding regulatory regions is also summarized. In addition, data from the studies addressing the role of PHLPPs in insulin resistance-related disorders and from those investigating the possibility to manipulate these phosphatases for therapeutic purposes are presented.

EXPERT OPINION

A number of issues should be resolved before PHLPPs are pursued as therapeutic targets including: the mechanisms regulating the specificity of PHLPP isozymes; the possibility of differentially regulating PHLPP family members and the possible impact of PHLPPs modulation on the risk of cancer.

Association between the DOCK7, PCSK9 and GALNT2 Gene Polymorphisms and Serum Lipid levels

This study was to determine the association between several single nucleotide polymorphisms (SNPs) in the dedicator of cytokinesis 7 (DOCK7), proprotein convertase subtilisin/kexin type 9 (PCSK9) and polypeptide N-acetylgalactosaminyltransferase 2 (GALNT2) and serum lipid levels. Genotyping of 9 SNPs was performed in 881 Jing subjects and 988 Han participants. Allele and genotype frequencies of the detected SNPs were different between the two populations. Several SNPs were associated with triglyceride (TG, rs10889332, rs615563, rs7552841, rs1997947, rs2760537, rs4846913 and rs11122316), high-density lipoprotein (HDL) cholesterol (rs1997947), low-density lipoprotein (LDL) cholesterol (rs1168013 and rs7552841), apolipoprotein (Apo) A1 (rs1997947), ApoB (rs10889332 and rs7552841), and ApoA1/ApoB ratio (rs7552841) in Jing minority; and with TG (rs10889332, rs615563, rs7552841, rs11206517, rs1997947, rs4846913 and rs11122316), HDL cholesterol (rs11206517 and rs4846913), LDL cholesterol (rs1168013), ApoA1 (rs11206517 and rs4846913), ApoB (rs7552841), and ApoA1/ApoB ratio (rs4846913) in Han nationality. Strong linkage disequilibria were noted among the SNPs. The commonest haplotype was G-C-G-C-T-G-C-C-G (>10%). The frequencies of C-C-G-C-T-G-T-C-G, G-C-A-C-T-G-C-C-G, G-C-G-C-T-A-C-C-A, G-C-G-C-T-G-C-C-A, G-C-G-C-T-G-T-C-A haplotypes were different between the two populations. Haplotypes could explain much more serum lipid variation than any single SNP alone especially for TG. Differences in lipid profiles between the two populations might partially attribute to these SNPs and their haplotypes.

Genotype Imputation with Millions of Reference Samples

We present a genotype imputation method that scales to millions of reference samples. The imputation method, based on the Li and Stephens model and implemented in Beagle v.4.1, is parallelized and memory efficient, making it well suited to multi-core computer processors. It achieves fast, accurate, and memory-efficient genotype imputation by restricting the probability model to markers that are genotyped in the target samples and by performing linear interpolation to impute ungenotyped variants. We compare Beagle v.4.1 with Impute2 and Minimac3 by using 1000 Genomes Project data, UK10K Project data, and simulated data. All three methods have similar accuracy but different memory requirements and different computation times. When imputing 10 Mb of sequence data from 50,000 reference samples, Beagle's throughput was more than 100× greater than Impute2's throughput on our computer servers. When imputing 10 Mb of sequence data from 200,000 reference samples in VCF format, Minimac3 consumed 26× more memory per computational thread and 15× more CPU time than Beagle. We demonstrate that Beagle v.4.1 scales to much larger reference panels by performing imputation from a simulated reference panel having 5 million samples and a mean marker density of one marker per four base pairs.

Genome-wide meta-analyses identify novel loci associated with n-3 and n-6 polyunsaturated fatty acid levels in Chinese and European-ancestry populations

Epidemiological studies suggest that levels of n-3 and n-6 long-chain polyunsaturated fatty acids are associated with risk of cardio-metabolic outcomes across different ethnic groups. Recent genome-wide association studies in populations of European ancestry have identified several loci associated with plasma and/or erythrocyte polyunsaturated fatty acids. To identify additional novel loci, we carried out a genome-wide association study in two population-based cohorts consisting of 3521 Chinese participants, followed by a trans-ethnic meta-analysis with meta-analysis results from 8962 participants of European ancestry. Four novel loci (MYB, AGPAT4, DGAT2 and PPT2) reached genome-wide significance in the trans-ethnic meta-analysis (log10(Bayes Factor) ≥ 6). Of them, associations of MYB and AGPAT4 with docosatetraenoic acid (log10(Bayes Factor) = 11.5 and 8.69, respectively) also reached genome-wide significance in the Chinese-specific genome-wide association analyses (P = 4.15 × 10(-14) and 4.30 × 10(-12), respectively), while associations of DGAT2 with gamma-linolenic acid (log10(Bayes Factor) = 6.16) and of PPT2 with docosapentaenoic acid (log10(Bayes Factor) = 6.24) were nominally significant in both Chinese- and European-specific genome-wide association analyses (P ≤ 0.003). We also confirmed previously reported loci including FADS1, NTAN1, NRBF2, ELOVL2 and GCKR. Different effect sizes in FADS1 and independent association signals in ELOVL2 were observed. These results provide novel insight into the genetic background of polyunsaturated fatty acids and their differences between Chinese and European populations.

Sequence variants in the PTCH1 gene associate with spine bone mineral density and osteoporotic fractures

Bone mineral density (BMD) is a measure of osteoporosis and is useful in evaluating the risk of fracture. In a genome-wide association study of BMD among 20,100 Icelanders, with follow-up in 10,091 subjects of European and East-Asian descent, we found a new BMD locus that harbours the PTCH1 gene, represented by rs28377268 (freq. 11.4–22.6%) that associates with reduced spine BMD (P=1.0 × 10⁻¹¹, β=−0.09). We also identified a new spine BMD signal in RSPO3, rs577721086 (freq. 6.8%), that associates with increased spine BMD (P=6.6 × 10⁻¹⁰, β=0.14). Importantly, both variants associate with osteoporotic fractures and affect expression of the PTCH1 and RSPO3 genes that is in line with their influence on BMD and known biological function of these genes. Additional new BMD signals were also found at the AXIN1 and SOST loci and a new lead SNP at the EN1 locus.

Bone mineral density (BMD) is the best predictor of osteoporotic fracture risk. Here, the authors perform a genome wide association study in Icelanders and people of European and East-Asian descent, and identify a new allele in intron 15 of the PTCH1 gene that associates with reduced BMD.

The Combined Effect of Common Genetic Risk Variants on Circulating Lipoproteins Is Evident in Childhood: A Longitudinal Analysis of the Cardiovascular Risk in Young Finns Study

Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are modifiable risk factors for cardiovascular disease. Several genetic loci for predisposition to abnormal LDL-C, HDL-C and TG have been identified. However, it remains unclear whether these loci are consistently associated with serum lipid levels at each age or with unique developmental trajectories. Therefore, we assessed the association between genome wide association studies (GWAS) derived polygenic genetic risk scores and LDL-C, HDL-C, and triglyceride trajectories from childhood to adulthood using data available from the 27-year European ‘Cardiovascular Risk in Young Finns’ Study. For 2,442 participants, three weighted genetic risk scores (wGRSs) for HDL-C (38 SNPs), LDL-C (14 SNPs) and triglycerides (24 SNPs) were computed and tested for association with serum lipoprotein levels measured up to 8 times between 1980 and 2011. The categorical analyses revealed no clear divergence of blood lipid trajectories over time between wGRSs categories, with participants in the lower wGRS quartiles tending to have average lipoprotein concentrations 30 to 45% lower than those in the upper-quartile wGRS beginning at age 3 years and continuing through to age 49 years (where the upper-quartile wGRS have 4–7 more risk alleles than the lower wGRS group). Continuous analyses, however, revealed a significant but moderate time-dependent genetic interaction for HDL-C levels, with the association between HDL-C and the continuous HDL-C risk score weakening slightly with age. Conversely, in males, the association between the continuous TG genetic risk score and triglycerides levels tended to be lower in childhood and become more pronounced after the age of 25 years. Although the influence of genetic factors on age-specific lipoprotein values and developmental trajectories is complex, our data show that wGRSs are highly predictive of HDL-C, LDL-C, and triglyceride levels at all ages.

The Relevance of Genomic Signatures at Adhesion GPCR Loci in Humans

Adhesion G protein-coupled receptors (aGPCRs) have a long evolutionary history dating back to very basal unicellular eukaryotes. Almost every vertebrate is equipped with a set of different aGPCRs. Genomic sequence data of several hundred extinct and extant species allows for reconstruction of aGPCR phylogeny in vertebrates and non-vertebrates in general but also provides a detailed view into the recent evolutionary history of human aGPCRs. Mining these sequence sources with bioinformatic tools can unveil many facets of formerly unappreciated aGPCR functions. In this review, we extracted such information from the literature and open public sources and provide insights into the history of aGPCR in humans. This includes comprehensive analyses of signatures of selection, variability of human aGPCR genes, and quantitative traits at human aGPCR loci. As indicated by a large number of genome-wide genotype-phenotype association studies, variations in aGPCR contribute to specific human phenotypes. Our survey demonstrates that aGPCRs are significantly involved in adaptation processes, phenotype variations, and diseases in humans.

PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG)

Association studies have shown and continue to show a substantial amount of success in identifying links between multiple single nucleotide polymorphisms (SNPs) and phenotypes. These studies are also believed to provide insights toward identification of new drug targets and therapies. Albeit of all the success, challenges still remain for applying and prioritizing these associations based on available biological knowledge. Along with single variant association analysis, genetic interactions also play an important role in uncovering the etiology and progression of complex traits. For gene-gene interaction analysis, selection of the variants to test for associations still poses a challenge in identifying epistatic interactions among the large list of variants available in high-throughput, genome-wide datasets. Therefore in this study, we propose a pipeline to identify interactions among genetic variants that are associated with multiple phenotypes by prioritizing previously published results from main effect association analysis (genome-wide and phenome-wide association analysis) based on a-priori biological knowledge in AIDS Clinical Trials Group (ACTG) data. We approached the prioritization and filtration of variants by using the results of a previously published single variant PheWAS and then utilizing biological information from the Roadmap Epigenome project. We removed variants in low functional activity regions based on chromatin states annotation and then conducted an exhaustive pairwise interaction search using linear regression analysis. We performed this analysis in two independent pre-treatment clinical trial datasets from ACTG to allow for both discovery and replication. Using a regression framework, we observed 50,798 associations that replicate at p-value 0.01 for 26 phenotypes, among which 2,176 associations for 212 unique SNPs for fasting blood glucose phenotype reach Bonferroni significance and an additional 9,970 interactions for high-density lipoprotein (HDL) phenotype and fasting blood glucose (total of 12,146 associations) reach FDR significance. We conclude that this method of prioritizing variants to look for epistatic interactions can be used extensively for generating hypotheses for genomewide and phenome-wide interaction analyses. This original Phenome-wide Interaction study (PheWIS) can be applied further to patients enrolled in randomized clinical trials to establish the relationship between patient's response to a particular drug therapy and non-linear combination of variants that might be affecting the outcome.

Is there a causal role for homocysteine concentration in blood pressure? A Mendelian randomization study

BACKGROUND

An understanding of whether homocysteine is a cause or a marker of increased blood pressure is relevant because blood homocysteine can be effectively lowered by safe and inexpensive interventions (e.g., vitamin B-6, B-9, and B-12 supplementation).

OBJECTIVE

The aim was to assess the causal influence of homocysteine on systolic and diastolic blood pressure (SBP and DBP, respectively) in adults with the use of Mendelian randomization (MR).

DESIGN

Data from the 1982 Pelotas Birth Cohort (Brazil) were used. A total of 4297 subjects were evaluated in 2004-2005 (mean age: 22.8 y). The association of homocysteine concentration with SBP and DBP was assessed by conventional ordinary least-squares (OLS) linear regression and 2-stage least-squares (2SLS) regression (MR analysis). The single nucleotide polymorphism (SNP) methylenetetrahydrofolate reductase (MTHFR) C677T (rs1801133) was used as proxy for homocysteine concentration. We also applied MR to data from the International Consortium for Blood Pressure (ICBP) genomewide association studies (>69,000 participants) using rs1801133 and additional homocysteine-associated SNPs as instruments.

RESULTS

In OLS regression, a 1-SD unit increase in log homocysteine concentration was associated with an increase of 0.9 (95% CI: 0.4, 1.4) mm Hg in SBP and of 1.0 (95% CI: 0.6, 1.4) mm Hg in DBP. In 2SLS regression, for the same increase in homocysteine, the coefficients were -1.8 mm Hg for SBP (95% CI: -3.9, 0.4 mm Hg; P = 0.01) and 0.1 mm Hg for DBP (95% CI: -1.5, 1.7 mm Hg; P = 0.24). In the MR analysis of ICBP data, homocysteine concentration was not associated with SBP (β = 0.6 mm Hg for each 1-SD unit increase in log homocysteine; 95% CI: -0.8, 1.9 mm Hg) but was positively associated with DBP (β = 1.1 mm Hg; 95% CI: 0.2, 1.9 mm Hg). The association of genetically increased homocysteine with DBP was not consistent across different SNPs.

CONCLUSION

Overall, the present findings do not corroborate the hypothesis that homocysteine has a causal role in blood pressure, especially in SBP.

TESTING POPULATION-SPECIFIC QUANTITATIVE TRAIT ASSOCIATIONS FOR CLINICAL OUTCOME RELEVANCE IN A BIOREPOSITORY LINKED TO ELECTRONIC HEALTH RECORDS: LPA AND MYOCARDIAL INFARCTION IN AFRICAN AMERICANS

Previous candidate gene and genome-wide association studies have identified common genetic variants in LPA associated with the quantitative trait Lp(a), an emerging risk factor for cardiovascular disease. These associations are population-specific and many have not yet been tested for association with the clinical outcome of interest. To fill this gap in knowledge, we accessed the epidemiologic Third National Health and Nutrition Examination Surveys (NHANES III) and BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified electronic health records (EHRs), including billing codes (ICD-9-CM) and clinical notes, to test population-specific Lp(a)-associated variants for an association with myocardial infarction (MI) among African Americans. We performed electronic phenotyping among African Americans in BioVU≥40 years of age using billing codes. At total of 93 cases and 522 controls were identified in NHANES III and 265 cases and 363 controls were identified in BioVU. We tested five known Lp(a)-associated genetic variants (rs1367211, rs41271028, rs6907156, rs10945682, and rs1652507) in both NHANES III and BioVU for association with myocardial infarction. We also tested LPA rs3798220 (I4399M), previously associated with increased levels of Lp(a), MI, and coronary artery disease in European Americans, in BioVU. After meta-analysis, tests of association using logistic regression assuming an additive genetic model revealed no significant associations (p<0.05) for any of the five LPA variants previously associated with Lp(a) levels in African Americans. Also, I4399M rs3798220 was not associated with MI in African Americans (odds ratio = 0.51; 95% confidence interval: 0.16 - 1.65; p=0.26) despite strong, replicated associations with MI and coronary artery disease in European American genome-wide association studies. These data highlight the challenges in translating quantitative trait associations to clinical outcomes in diverse populations using large epidemiologic and clinic-based collections as envisioned for the Precision Medicine Initiative.

Fatty acid desaturase 1 knockout mice are lean with improved glycemic control and decreased development of atheromatous plaque

Delta-5 desaturase (D5D) and delta-6 desaturase (D6D), encoded by fatty acid desaturase 1 (FADS1) and FADS2 genes, respectively, are enzymes in the synthetic pathways for ω3, ω6, and ω9 polyunsaturated fatty acids (PUFAs). Although PUFAs appear to be involved in mammalian metabolic pathways, the physiologic effect of isolated D5D deficiency on these pathways is unclear. After generating >4,650 knockouts (KOs) of independent mouse genes and analyzing them in our high-throughput phenotypic screen, we found that Fads1 KO mice were among the leanest of 3,651 chow-fed KO lines analyzed for body composition and were among the most glucose tolerant of 2,489 high-fat-diet-fed KO lines analyzed by oral glucose tolerance test. In confirmatory studies, chow- or high-fat-diet-fed Fads1 KO mice were leaner than wild-type (WT) littermates; when data from multiple cohorts of adult mice were combined, body fat was 38% and 31% lower in Fads1 male and female KO mice, respectively. Fads1 KO mice also had lower glucose and insulin excursions during oral glucose tolerance tests along with lower fasting glucose, insulin, triglyceride, and total cholesterol levels. In additional studies using a vascular injury model, Fads1 KO mice had significantly decreased femoral artery intima/media ratios consistent with a decreased inflammatory response in their arterial wall. Based on this result, we bred Fads1 KO and WT mice onto an ApoE KO background and fed them a Western diet for 14 weeks; in this atherogenic environment, aortic trees of Fads1 KO mice had 40% less atheromatous plaque compared to WT littermates. Importantly, PUFA levels measured in brain and liver phospholipid fractions of Fads1 KO mice were consistent with decreased D5D activity and normal D6D activity. The beneficial metabolic phenotype demonstrated in Fads1 KO mice suggests that selective D5D inhibitors may be useful in the treatment of human obesity, diabetes, and atherosclerotic cardiovascular disease.

Recent Positive Selection Drives the Expansion of a Schizophrenia Risk Nonsynonymous Variant at SLC39A8 in Europeans

Natural selection has played important roles in optimizing complex human adaptations. However, schizophrenia poses an evolutionary paradox during human evolution, as the illness has strongly negative effects on fitness, but persists with a prevalence of ~0.5% across global populations. Recent studies have identified numerous risk variations in diverse populations, which might be able to explain the stable and high rate of schizophrenia morbidity in different cultures and regions, but the questions about why the risk alleles derived and maintained in human gene pool still remain unsolved. Here, we studied the evolutionary pattern of a schizophrenia risk variant rs13107325 (P < 5.0 × 10(-8) in Europeans) in the SLC39A8 gene. We found the SNP is monomorphic in Asians and Africans with risk (derived) T-allele totally absent, and further evolutionary analyses showed the T-allele has experienced recent positive selection in Europeans. Subsequent exploratory analyses implicated that the colder environment in Europe was the likely selective pressures, ie, when modern humans migrated "out of Africa" and moved to Europe mainland (a colder and cooler continent than Africa), new alleles derived due to positive selection and protected humans from risk of hypertension and also helped them adapt to the cold environment. The hypothesis was supported by our pleiotropic analyses with hypertension and energy intake as well as obesity in Europeans. Our data thus provides an intriguing example to illustrate a possible mechanism for maintaining schizophrenia risk alleles in the human gene pool, and further supported that schizophrenia is likely a product caused by pleiotropic effect during human evolution.

Zebrafish Models for Dyslipidemia and Atherosclerosis Research

Atherosclerotic cardiovascular disease is the leading cause of death. Elevated circulating concentrations of lipids are a central pathogenetic driver of atherosclerosis. While numerous effective therapies for this condition have been developed, there is substantial unmet need for this pandemic illness. Here, I will review nutritional, physiological, genetic, and pathological discoveries in the emerging zebrafish model for studying dyslipidemia and atherosclerosis. The technical and physiological advantages and the pharmacological potential of this organism for discovery and validation of dyslipidemia and atherosclerosis targets are stressed through summary of recent findings. An emerging literature shows that zebrafish, through retention of a cetp ortholog gene and high sensitivity to ingestion of excess cholesterol, rapidly develops hypercholesterolemia, with a pattern of distribution of lipid species in lipoprotein particles similar to humans. Furthermore, recent studies leveraging the optical transparency of zebrafish larvae to monitor the fate of these ingested lipids have provided exciting insights to the development of dyslipidemia and atherosclerosis. Future directions for investigation are considered, with particular attention to the potential for in vivo cell biological study of atherosclerotic plaques.

Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese

Blood lipids are important risk factors for coronary artery disease (CAD). Here we perform an exome-wide association study by genotyping 12,685 Chinese, using a custom Illumina HumanExome BeadChip, to identify additional loci influencing lipid levels. Single-variant association analysis on 65,671 single nucleotide polymorphisms reveals 19 loci associated with lipids at exome-wide significance (P<2.69 × 10⁻⁷), including three Asian-specific coding variants in known genes (CETP p.Asp459Gly, PCSK9 p.Arg93Cys and LDLR p.Arg257Trp). Furthermore, missense variants at two novel loci—PNPLA3 p.Ile148Met and PKD1L3 p.Thr429Ser—also influence levels of triglycerides and low-density lipoprotein cholesterol, respectively. Another novel gene, TEAD2, is found to be associated with high-density lipoprotein cholesterol through gene-based association analysis. Most of these newly identified coding variants show suggestive association (P<0.05) with CAD. These findings demonstrate that exome-wide genotyping on samples of non-European ancestry can identify additional population-specific possible causal variants, shedding light on novel lipid biology and CAD.

An important risk factor for coronary artery disease is the level of blood lipids. Here the authors conduct an exome-wide association study in Chinese cohorts and identify three novel loci associated with lipid levels as well as three Asian-specific variants in known loci.

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity.

Progress and promise in understanding the genetic basis of common diseases

Susceptibility to common human diseases is influenced by both genetic and environmental factors. The explosive growth of genetic data, and the knowledge that it is generating, are transforming our biological understanding of these diseases. In this review, we describe the technological and analytical advances that have enabled genome-wide association studies to be successful in identifying a large number of genetic variants robustly associated with common disease. We examine the biological insights that these genetic associations are beginning to produce, from functional mechanisms involving individual genes to biological pathways linking associated genes, and the identification of functional annotations, some of which are cell-type-specific, enriched in disease associations. Although most efforts have focused on identifying and interpreting genetic variants that are irrefutably associated with disease, it is increasingly clear that--even at large sample sizes--these represent only the tip of the iceberg of genetic signal, motivating polygenic analyses that consider the effects of genetic variants throughout the genome, including modest effects that are not individually statistically significant. As data from an increasingly large number of diseases and traits are analysed, pleiotropic effects (defined as genetic loci affecting multiple phenotypes) can help integrate our biological understanding. Looking forward, the next generation of population-scale data resources, linking genomic information with health outcomes, will lead to another step-change in our ability to understand, and treat, common diseases.

Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains

Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis.

While recent genetic association studies in human populations have succeeded in identifying genetic loci that contribute to coronary artery disease (CAD) and related phenotypes, these loci explain only a small fraction of the genetic variation in CAD and associated traits. Here, we present a complementary approach using association analysis of atherosclerotic traits among inbred strains of mice. A strength of this approach is that it enables in-depth phenotypic characterization including gene expression and metabolic profiling across a variety of tissues, and integration of these molecular phenotypes with coronary artery disease itself. A striking finding was the large fraction of atherosclerosis that was explained by genetic interactions. Association analysis allowed us to identify genetic loci for atherosclerotic lesion area as well as transcript, cytokine and metabolite levels, and relationships among the traits were examined by correlation and network modeling. The plasma metabolites associated with atherosclerosis in mice, namely, LDL/VLDL-cholesterol, TMAO, arginine, glucose and insulin, overlapped with those observed in humans and accounted for approximately 30 to 40% of the observed variation in atherosclerotic lesion area. In summary, our data provide a detailed overview of the genetic architecture of atherosclerosis in mice and a rich resource for studies of the complex genetic and metabolic interactions that underlie the disease.

Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods

Mendelian randomization is the use of genetic instrumental variables to obtain causal inferences from observational data. Two recent developments for combining information on multiple uncorrelated instrumental variables (IVs) into a single causal estimate are as follows: (i) allele scores, in which individual‐level data on the IVs are aggregated into a univariate score, which is used as a single IV, and (ii) a summary statistic method, in which causal estimates calculated from each IV using summarized data are combined in an inverse‐variance weighted meta‐analysis. To avoid bias from weak instruments, unweighted and externally weighted allele scores have been recommended. Here, we propose equivalent approaches using summarized data and also provide extensions of the methods for use with correlated IVs. We investigate the impact of different choices of weights on the bias and precision of estimates in simulation studies. We show that allele score estimates can be reproduced using summarized data on genetic associations with the risk factor and the outcome. Estimates from the summary statistic method using external weights are biased towards the null when the weights are imprecisely estimated; in contrast, allele score estimates are unbiased. With equal or external weights, both methods provide appropriate tests of the null hypothesis of no causal effect even with large numbers of potentially weak instruments. We illustrate these methods using summarized data on the causal effect of low‐density lipoprotein cholesterol on coronary heart disease risk. It is shown that a more precise causal estimate can be obtained using multiple genetic variants from a single gene region, even if the variants are correlated. © 2015 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Variation in the Phosphoinositide 3-Kinase Gamma Gene Affects Plasma HDL-Cholesterol without Modification of Metabolic or Inflammatory Markers

Objective

Phosphoinositide 3-kinase γ (PI3Kγ) is a G-protein-coupled receptor-activated lipid kinase mainly expressed in leukocytes and cells of the cardiovascular system. PI3Kγ plays an important signaling role in inflammatory processes. Since subclinical inflammation is a hallmark of atherosclerosis, obesity-related insulin resistance, and pancreatic β-cell failure, we asked whether common genetic variation in the PI3Kγ gene (PIK3CG) contributes to body fat content/distribution, serum adipokine/cytokine concentrations, alterations in plasma lipid profiles, insulin sensitivity, insulin release, and glucose homeostasis.

Study Design

Using a tagging single nucleotide polymorphism (SNP) approach, we analyzed genotype-phenotype associations in 2,068 German subjects genotyped for 10 PIK3CG SNPs and characterized by oral glucose tolerance tests. In subgroups, data from hyperinsulinaemic-euglycaemic clamps, magnetic resonance spectroscopy of the liver, whole-body magnetic resonance imaging, and intravenous glucose tolerance tests were available, and peripheral blood mononuclear cells (PBMCs) were used for gene expression analysis.

Results

After appropriate adjustment, none of the PIK3CG tagging SNPs was significantly associated with body fat content/distribution, adipokine/cytokine concentrations, insulin sensitivity, insulin secretion, or blood glucose concentrations (p>0.0127, all; Bonferroni-corrected α-level: 0.0051). However, six non-linked SNPs displayed at least nominal associations with plasma HDL-cholesterol concentrations, two of them (rs4288294 and rs116697954) reaching the level of study-wide significance (p = 0.0003 and p = 0.0004, respectively). More precisely, rs4288294 and rs116697954 influenced HDL2-, but not HDL3-, cholesterol. With respect to the SNPs’ in vivo functionality, rs4288294 was significantly associated with PIK3CG mRNA expression in PBMCs.

Conclusions

We could demonstrate that common genetic variation in the PIK3CG locus, possibly via altered PIK3CG gene expression, determines plasma HDL-cholesterol concentrations. Since HDL2-, but not HDL3-, cholesterol is influenced by PIK3CG variants, PI3Kγ may play a role in HDL clearance rather than in HDL biogenesis. Even though the molecular pathways connecting PI3Kγ and HDL metabolism remain to be further elucidated, this finding could add a novel aspect to the pathophysiological role of PI3Kγ in atherogenesis.

Multiple Hepatic Regulatory Variants at the GALNT2 GWAS Locus Associated with High-Density Lipoprotein Cholesterol

Genome-wide association studies (GWASs) have identified more than 150 loci associated with blood lipid and cholesterol levels; however, the functional and molecular mechanisms for many associations are unknown. We examined the functional regulatory effects of candidate variants at the GALNT2 locus associated with high-density lipoprotein cholesterol (HDL-C). Fine-mapping and conditional analyses in the METSIM study identified a single locus harboring 25 noncoding variants (r(2) > 0.7 with the lead GWAS variants) strongly associated with total cholesterol in medium-sized HDL (e.g., rs17315646, p = 3.5 × 10(-12)). We used luciferase reporter assays in HepG2 cells to test all 25 variants for allelic differences in regulatory enhancer activity. rs2281721 showed allelic differences in transcriptional activity (75-fold [T] versus 27-fold [C] more than the empty-vector control), as did a separate 780-bp segment containing rs4846913, rs2144300, and rs6143660 (49-fold [AT(-) haplotype] versus 16-fold [CC(+) haplotype] more). Using electrophoretic mobility shift assays, we observed differential CEBPB binding to rs4846913, and we confirmed this binding in a native chromatin context by performing chromatin-immunoprecipitation (ChIP) assays in HepG2 and Huh-7 cell lines of differing genotypes. Additionally, sequence reads in HepG2 DNase-I-hypersensitivity and CEBPB ChIP-seq signals spanning rs4846913 showed significant allelic imbalance. Allelic-expression-imbalance assays performed with RNA from primary human hepatocyte samples and expression-quantitative-trait-locus (eQTL) data in human subcutaneous adipose tissue samples confirmed that alleles associated with increased HDL-C are associated with a modest increase in GALNT2 expression. Together, these data suggest that at least rs4846913 and rs2281721 play key roles in influencing GALNT2 expression at this HDL-C locus.

Multiple susceptibility loci at chromosome 11q23.3 are associated with plasma triglyceride in East Asians

Genetic studies of plasma TG levels have identified associations with multiple candidate loci on chromosome11q23.3, which harbors a number of genes, including BUD13, ZNF259, and APOA5-A4-C3-A1. This study aimed to examine whether these multiple candidate genes on the 11q23.3 regions exert independent effects on TG levels or whether their effects are confounded by linkage disequilibrium (LD). We performed a genome-wide association study and consequent fine-mapping analyses on TG levels in two Korean population-based cohorts: the Korea Association Resource study (n = 8,223) and the Healthy Twin study (n = 1,735). A total of 301 loci reached genome-wide significance level in pooled analysis, including 10 SNPs with weak LD (r(2) < 0.06) clustered on 11q23.3: ApoA5 (rs651821, rs2075291); ZNF259 (rs964184, rs603446); BUD13 (rs11216126); Apoa4 (rs7396851); SIK3 (rs12292858); PCSK7 (rs199890178); PAFAH1B2 (rs12420127), and SIDT2 (rs2269399). When the inter-dependence between alleles was examined using conditional models, five loci on BUD13, ZNF259, and ApoA5 showed possible independent associations. A haplotype analysis using five SNPs revealed both hyper- and hypotriglyceridemic haplotypes, which are relatively common in Koreans (haplotype frequency 0.08-0.22). Our findings suggest the presence of multiple functional loci on 11q23.3, which might exert their effects on plasma TG level independently or through complex interactions between functional loci.

Recent Progress in the Understanding of Obesity: Contributions of Genome-Wide Association Studies

Since 2007, discovery of genetic variants associated with general obesity and fat distribution has advanced tremendously through genome-wide association studies (GWAS). Currently, the number of robustly associated loci is 190. Even though these loci explain <3 % of the variance, they have provided us a still emerging picture of genomic localization, frequency and effect size spectra, and hints of functional implications. The translation into biological knowledge has turned out to be an immense task. However, in silico enrichment analyses of genes involved in specific pathways or expressed in specific tissues have the power to suggest biological mechanisms underlying obesity. Inspired by this, we highlight genes in five loci potentially mechanistically linked to leptin-receptor trafficking and signaling in primary cilia. The clinical application of genetic knowledge as prediction, prevention, or treatment strategies is unfortunately still far from reality. Thus, despite major advances, further research is warranted to solve one of the greatest health problems in modern society.

Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis

Heritability analyses of genome-wide association study (GWAS) cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here we analyze the genetic architectures of schizophrenia in 49,806 samples from the PGC and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1-Mb genomic regions harbor ≥1 variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions and in higher-frequency SNPs for both schizophrenia and GERA diseases. In bivariate analyses, we observe significant genetic correlations (ranging from 0.18 to 0.85) for several pairs of GERA diseases; genetic correlations were on average 1.3 tunes stronger than the correlations of overall disease liabilities. To accomplish these analyses, we developed a fast algorithm for multicomponent, multi-trait variance-components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.

Genetics of non-conventional lipoprotein fractions

Lipoprotein subclass measures associate with cardiometabolic disease risk. Currently the information that lipoproteins convey on disease risk over that of traditional demographic and lipid measures is minimal, and so their use is clinics is limited. However, lipoprotein subclass perturbations represent some of the earliest manifestations of metabolic dysfunction, and their etiology is partially distinct from lipids, so information on the genetic etiology of lipoproteins offers promise for improved risk prediction, and unique mechanistic insights into IR and atherosclerosis. Here, I review the genetic variants validated as associating with lipoprotein measures to date, and show that the majority of identified variants have functionality that is best understood as related to lipid measures. Until we focus on the genes as they relate to lipoprotein subclass production, we are limiting our understanding of biological mechanisms underlying cardiometabolic disease.

Mendelian randomization studies: using naturally randomized genetic data to fill evidence gaps

PURPOSE OF REVIEW

Mendelian randomization studies have the potential to transform our understanding of cardiovascular medicine by generating naturally randomized data that can fill evidence gaps when a randomized trial would be either impossible or impractical to conduct. Here, we review recent Mendelian randomization studies evaluating the effect of low-density lipoprotein cholesterol (LDL-C) on the risk of coronary heart disease (CHD).

RECENT FINDINGS

Mendelian randomization studies consistently demonstrate that LDL-C is causally associated with the risk of CHD. Furthermore, exposure to genetically mediated lower LDL-C appears to be associated with a much greater than expected reduction in CHD risk, thus suggesting that LDL-C has a cumulative effect on the risk of CHD. In addition, genetically mediated lower LDL-C is log-linearly associated with the risk of CHD and the effect of polymorphisms in multiple different genes on the risk of CHD is remarkably consistent when measured per unit lower LDL-C.

SUMMARY

The naturally randomized genetic evidence suggests that LDL-C has a causal and cumulative effect on the risk of CHD, and that the clinical benefit of exposure to lower LDL-C is determined by the absolute magnitude of exposure to lower LDL-C independent of the mechanism by which LDL-C is lowered.

The dual and opposite role of the TM6SF2-rs58542926 variant in protecting against cardiovascular disease and conferring risk for nonalcoholic fatty liver: A meta-analysis

The aim of this work was to estimate the strength of the effect of the TM6SF2 E167K (rs58542926 C/T) variant on blood lipid traits and nonalcoholic fatty liver disease (NAFLD) across different populations. We performed a systematic review by a meta-analysis; literature searches identified 10 studies. The rs58542926 exerts a significant role in modulating lipid traits, including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and NAFLD. However, this influence on lipids and NAFLD is opposite between genotypes in the dominant model of inheritance. Pooled estimates of random effects in 101,326 individuals showed that carriers of the minor T allele (EK+KK individuals), compared with subjects homozygous for the ancestral C allele (EE genotype), are protected from cardiovascular disease (CVD), showing lower levels of TC, LDL-C, and TG; the differences in mean ± standard error (mg/dL) are -8.38 ± 1.56, -3.7 ± 0.9, and -9.4 ± 2.1, respectively. The rs58542926 variant was not associated with high-density lipoprotein cholesterol in a large sample (n = 91,937). In contrast, carriers of the T allele showed a moderate effect on the risk of NAFLD (odds ratio: 2.13; 95% confidence interval: 1.36-3.30; P = 0.0009; n = 3273) and approximately ∼2.2% higher lipid fat content when compared with homozygous EE (n = 3,413).

CONCLUSIONS

The rs58542926 appears to be an important modifier of blood lipid traits in different populations. As a challenge for personalized medicine, the C-allele, which has an overall frequency as high as 93%, is associated with higher blood lipids, whereas the T allele confers risk for NAFLD; in turn, CVD and NAFLD are strongly related outcomes. Although the variant confers protection against CVD at the expense of an increased risk of NAFLD, it does not explain the link between these two complex diseases.

GWAS as a Driver of Gene Discovery in Cardiometabolic Diseases

Cardiometabolic diseases represent a common complex disorder with a strong genetic component. Currently, genome-wide association studies (GWAS) have yielded some 755 single-nucleotide polymorphisms (SNPs) encompassing 366 independent loci that may help to decipher the molecular basis of cardiometabolic diseases. Going from a disease SNP to the underlying disease mechanisms is a huge challenge because the associated SNPs rarely disrupt protein function. Many disease SNPs are located in noncoding regions, and therefore attention is now focused on linking genetic SNP variation to effects on gene expression levels. By integrating genetic information with large-scale gene expression data, and with data from epigenetic roadmaps revealing gene regulatory regions, we expect to be able to identify candidate disease genes and the regulatory potential of disease SNPs.

Variation in NAT2 acetylation phenotypes is associated with differences in food-producing subsistence modes and ecoregions in Africa

Background

Dietary changes associated to shifts in subsistence strategies during human evolution may have induced new selective pressures on phenotypes, as currently held for lactase persistence. Similar hypotheses exist for arylamine N-acetyltransferase 2 (NAT2) mediated acetylation capacity, a well-known pharmacogenetic trait with wide inter-individual variation explained by polymorphisms in the NAT2 gene. The environmental causative factor (if any) driving its evolution is as yet unknown, but significant differences in prevalence of acetylation phenotypes are found between hunter-gatherer and food-producing populations, both in sub-Saharan Africa and worldwide, and between agriculturalists and pastoralists in Central Asia. These two subsistence strategies also prevail among sympatric populations of the African Sahel, but knowledge on NAT2 variation among African pastoral nomads was up to now very scarce. Here we addressed the hypothesis of different selective pressures associated to the agriculturalist or pastoralist lifestyles having acted on the evolution of NAT2 by sequencing the gene in 287 individuals from five pastoralist and one agriculturalist Sahelian populations.

Results

We show that the significant NAT2 genetic structure of African populations is mainly due to frequency differences of three major haplotypes, two of which are categorized as decreased function alleles (NAT2*5B and NAT2*6A), particularly common in populations living in arid environments, and one fast allele (NAT2*12A), more frequently detected in populations living in tropical humid environments. This genetic structure does associate more strongly with a classification of populations according to ecoregions than to subsistence strategies, mainly because most Sahelian and East African populations display little to no genetic differentiation between them, although both regions hold nomadic or semi-nomadic pastoralist and sedentary agriculturalist communities. Furthermore, we found significantly higher predicted proportions of slow acetylators in pastoralists than in agriculturalists, but also among food-producing populations living in the Sahelian and dry savanna zones than in those living in humid environments, irrespective of their mode of subsistence.

Conclusion

Our results suggest a possible independent influence of both the dietary habits associated with subsistence modes and the chemical environment associated with climatic zones and biomes on the evolution of NAT2 diversity in sub-Saharan African populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0543-6) contains supplementary material, which is available to authorized users.

Substantial DNA methylation differences between two major neuronal subtypes in human brain

The brain is built from a large number of cell types which have been historically classified using location, morphology and molecular markers. Recent research suggests an important role of epigenetics in shaping and maintaining cell identity in the brain. To elucidate the role of DNA methylation in neuronal differentiation, we developed a new protocol for separation of nuclei from the two major populations of human prefrontal cortex neurons—GABAergic interneurons and glutamatergic (GLU) projection neurons. Major differences between the neuronal subtypes were revealed in CpG, non-CpG and hydroxymethylation (hCpG). A dramatically greater number of undermethylated CpG sites in GLU versus GABA neurons were identified. These differences did not directly translate into differences in gene expression and did not stem from the differences in hCpG methylation, as more hCpG methylation was detected in GLU versus GABA neurons. Notably, a comparable number of undermethylated non-CpG sites were identified in GLU and GABA neurons, and non-CpG methylation was a better predictor of subtype-specific gene expression compared to CpG methylation. Regions that are differentially methylated in GABA and GLU neurons were significantly enriched for schizophrenia risk loci. Collectively, our findings suggest that functional differences between neuronal subtypes are linked to their epigenetic specification.

Genetic Susceptibility to Lipid Levels and Lipid Change Over Time and Risk of Incident Hyperlipidemia in Chinese Populations

BACKGROUND

Multiple genetic loci associated with lipid levels have been identified predominantly in Europeans, and the issue of to what extent these genetic loci can predict blood lipid levels increases over time and the incidence of future hyperlipidemia remains largely unknown.

METHODS AND RESULTS

We conducted a meta-analysis of genome-wide association studies of lipid levels in 8344 subjects followed by replication studies including 14 739 additional individuals. We replicated 17 previously reported loci. We also newly identified 3 Chinese-specific variants in previous regions (HLA-C, LIPG, and LDLR) with genome-wide significance. Almost all the variants contributed to lipid levels change and incident hyperlipidemia >8.1-year follow-up among 6428 individuals of a prospective cohort study. The strongest associations for lipid levels change were detected at LPL, TRIB1, APOA1-C3-A4-A5, LIPC, CETP, and LDLR (P range from 4.84×10(-4) to 4.62×10(-18)), whereas LPL, TRIB1, ABCA1, APOA1-C3-A4-A5, CETP, and APOE displayed significant strongest associations for incident hyperlipidemia (P range from 1.20×10(-3) to 4.67×10(-16)). The 4 lipids genetic risk scores were independently associated with linear increases in their corresponding lipid levels and risk of incident hyperlipidemia. A C-statistics analysis showed significant improvement in the prediction of incident hyperlipidemia on top of traditional risk factors including the baseline lipid levels.

CONCLUSIONS

These findings identified some evidence for allelic heterogeneity in Chinese when compared with Europeans in relation to lipid associations. The individual variants and those cumulative effects were independent risk factors for lipids increase and incident hyperlipidemia.

Fine mapping the CETP region reveals a common intronic insertion associated to HDL-C

BACKGROUND

Individuals with exceptional longevity and their offspring have significantly larger high-density lipoprotein concentrations (HDL-C) particle sizes due to the increased homozygosity for the I405V variant in the cholesteryl ester transfer protein (CETP) gene. In this study, we investigate the association of CETP and HDL-C further to identify novel, independent CETP variants associated with HDL-C in humans.

METHODS

We performed a meta-analysis of HDL-C within the CETP region using 59,432 individuals imputed with 1000 Genomes data. We performed replication in an independent sample of 47,866 individuals and validation was done by Sanger sequencing.

RESULTS

The meta-analysis of HDL-C within the CETP region identified five independent variants, including an exonic variant and a common intronic insertion. We replicated these 5 variants significantly in an independent sample of 47,866 individuals. Sanger sequencing of the insertion within a single family confirmed segregation of this variant. The strongest reported association between HDL-C and CETP variants, was rs3764261; however, after conditioning on the five novel variants we identified the support for rs3764261 was highly reduced (β_unadjusted=3.179 mg/dl (P value=5.25×10^-509), β_adjusted=0.859 mg/dl (P value=9.51×10^-25)), and this finding suggests that these five novel variants may partly explain the association of CETP with HDL-C. Indeed, three of the five novel variants (rs34065661, rs5817082, rs7499892) are independent of rs3764261.

CONCLUSIONS

The causal variants in CETP that account for the association with HDL-C remain unknown. We used studies imputed to the 1000 Genomes reference panel for fine mapping of the CETP region. We identified and validated five variants within this region that may partly account for the association of the known variant (rs3764261), as well as other sources of genetic contribution to HDL-C.

Genetic contribution of SCARB1 variants to lipid traits in African Blacks: a candidate gene association study

Background

High-density lipoprotein cholesterol (HDL-C) exerts many anti-atherogenic properties including its role in reverse cholesterol transport (RCT). Scavenger receptor class B member 1 (SCARB1) plays a key role in RCT by selective uptake of HDL cholesteryl esters. We aimed to explore the genetic contribution of SCARB1 to affecting lipid levels in African Blacks from Nigeria.

Methods

We resequenced 13 exons and exon-intron boundaries of SCARB1 in 95 individuals with extreme HDL-C levels using Sanger method. Then, we genotyped 147 selected variants (78 sequence variants, 69 HapMap tagSNPs, and 2 previously reported relevant variants) in the entire sample of 788 African Blacks using either the iPLEX Gold or TaqMan methods. A total of 137 successfully genotyped variants were further evaluated for association with major lipid traits.

Results

The initial gene-based analysis demonstrated evidence of association with HDL-C and apolipoprotein A-I (ApoA-I). The follow-up single-site analysis revealed nominal evidence of novel associations of nine common variants with HDL-C and/or ApoA-I (P < 0.05). The strongest association was between rs11057851 and HDL-C (P = 0.0043), which remained significant after controlling for multiple testing using false discovery rate. Rare variant association testing revealed a group of 23 rare variants (frequencies ≤1 %) associated with HDL-C (P = 0.0478). Haplotype analysis identified four SCARB1 regions associated with HDL-C (global P < 0.05).

Conclusions

To our knowledge, this is the first report of a comprehensive association study of SCARB1 variations with lipid traits in an African Black population. Our results showed the consistent association of SCARB1 variants with HDL-C across various association analyses, supporting the role of SCARB1 in lipoprotein-lipid regulatory mechanism.

Electronic supplementary material

The online version of this article (doi:10.1186/s12881-015-0250-6) contains supplementary material, which is available to authorized users.

Genetic linkage of hyperglycemia and dyslipidemia in an intercross between BALB/cJ and SM/J Apoe-deficient mouse strains

BACKGROUND

Individuals with dyslipidemia often develop type 2 diabetes, and diabetic patients often have dyslipidemia. It remains to be determined whether there are genetic connections between the 2 disorders.

METHODS

A female F2 cohort, generated from BALB/cJ (BALB) and SM/J (SM) Apoe-deficient (Apoe(-/-)) strains, was started on a Western diet at 6 weeks of age and maintained on the diet for 12 weeks. Fasting plasma glucose and lipid levels were measured before and after 12 weeks of Western diet. 144 genetic markers across the entire genome were used for quantitative trait locus (QTL) analysis.

RESULTS

One significant QTL on chromosome 9, named Bglu17 [26.4 cM, logarithm of odds ratio (LOD): 5.4], and 3 suggestive QTLs were identified for fasting glucose levels. The suggestive QTL near the proximal end of chromosome 9 (2.4 cM, LOD: 3.12) was replicated at both time points and named Bglu16. Bglu17 coincided with a significant QTL for HDL (high-density lipoprotein) and a suggestive QTL for non-HDL cholesterol levels. Plasma glucose levels were inversely correlated with HDL but positively correlated with non-HDL cholesterol levels in F2 mice on either chow or Western diet. A significant correlation between fasting glucose and triglyceride levels was also observed on the Western diet. Haplotype analysis revealed that "lipid genes" Sik3, Apoa1, and Apoc3 were probable candidates for Bglu17.

CONCLUSIONS

We have identified multiple QTLs for fasting glucose and lipid levels. The colocalization of QTLs for both phenotypes and the sharing of potential candidate genes demonstrate genetic connections between dyslipidemia and type 2 diabetes.

Endothelial NOTCH1 is suppressed by circulating lipids and antagonizes inflammation during atherosclerosis

Briot et al. show that inflammatory lipids deriving from a high-fat diet suppress NOTCH1 expression and signaling in adult arterial endothelium and propose that reduction of endothelial NOTCH1 is a predisposing factor in the onset of atherosclerosis.

Although much progress has been made in identifying the mechanisms that trigger endothelial activation and inflammatory cell recruitment during atherosclerosis, less is known about the intrinsic pathways that counteract these events. Here we identified NOTCH1 as an antagonist of endothelial cell (EC) activation. NOTCH1 was constitutively expressed by adult arterial endothelium, but levels were significantly reduced by high-fat diet. Furthermore, treatment of human aortic ECs (HAECs) with inflammatory lipids (oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine [Ox-PAPC]) and proinflammatory cytokines (TNF and IL1β) decreased Notch1 expression and signaling in vitro through a mechanism that requires STAT3 activation. Reduction of NOTCH1 in HAECs by siRNA, in the absence of inflammatory lipids or cytokines, increased inflammatory molecules and binding of monocytes. Conversely, some of the effects mediated by Ox-PAPC were reversed by increased NOTCH1 signaling, suggesting a link between lipid-mediated inflammation and Notch1. Interestingly, reduction of NOTCH1 by Ox-PAPC in HAECs was associated with a genetic variant previously correlated to high-density lipoprotein in a human genome-wide association study. Finally, endothelial Notch1 heterozygous mice showed higher diet-induced atherosclerosis. Based on these findings, we propose that reduction of endothelial NOTCH1 is a predisposing factor in the onset of vascular inflammation and initiation of atherosclerosis.

Two-Variance-Component Model Improves Genetic Prediction in Family Datasets

Genetic prediction based on either identity by state (IBS) sharing or pedigree information has been investigated extensively with best linear unbiased prediction (BLUP) methods. Such methods were pioneered in plant and animal-breeding literature and have since been applied to predict human traits, with the aim of eventual clinical utility. However, methods to combine IBS sharing and pedigree information for genetic prediction in humans have not been explored. We introduce a two-variance-component model for genetic prediction: one component for IBS sharing and one for approximate pedigree structure, both estimated with genetic markers. In simulations using real genotypes from the Candidate-gene Association Resource (CARe) and Framingham Heart Study (FHS) family cohorts, we demonstrate that the two-variance-component model achieves gains in prediction r(2) over standard BLUP at current sample sizes, and we project, based on simulations, that these gains will continue to hold at larger sample sizes. Accordingly, in analyses of four quantitative phenotypes from CARe and two quantitative phenotypes from FHS, the two-variance-component model significantly improves prediction r(2) in each case, with up to a 20% relative improvement. We also find that standard mixed-model association tests can produce inflated test statistics in datasets with related individuals, whereas the two-variance-component model corrects for inflation.

Functional Genomics Analysis of Big Data Identifies Novel Peroxisome Proliferator-Activated Receptor γ Target Single Nucleotide Polymorphisms Showing Association With Cardiometabolic Outcomes

BACKGROUND

Cardiovascular disease and type 2 diabetes mellitus represent overlapping diseases where a large portion of the variation attributable to genetics remains unexplained. An important player in their pathogenesis is peroxisome proliferator-activated receptor γ (PPARγ) that is involved in lipid and glucose metabolism and maintenance of metabolic homeostasis. We used a functional genomics methodology to interrogate human chromatin immunoprecipitation-sequencing, genome-wide association studies, and expression quantitative trait locus data to inform selection of candidate functional single nucleotide polymorphisms (SNPs) falling in PPARγ motifs.

METHODS AND RESULTS

We derived 27 328 chromatin immunoprecipitation-sequencing peaks for PPARγ in human adipocytes through meta-analysis of 3 data sets. The PPARγ consensus motif showed greatest enrichment and mapped to 8637 peaks. We identified 146 SNPs in these motifs. This number was significantly less than would be expected by chance, and Inference of Natural Selection from Interspersed Genomically coHerent elemenTs analysis indicated that these motifs are under weak negative selection. A screen of these SNPs against genome-wide association studies for cardiometabolic traits revealed significant enrichment with 16 SNPs. A screen against the MuTHER expression quantitative trait locus data revealed 8 of these were significantly associated with altered gene expression in human adipose, more than would be expected by chance. Several SNPs fall close, or are linked by expression quantitative trait locus to lipid-metabolism loci including CYP26A1.

CONCLUSIONS

We demonstrated the use of functional genomics to identify SNPs of potential function. Specifically, that SNPs within PPARγ motifs that bind PPARγ in adipocytes are significantly associated with cardiometabolic disease and with the regulation of transcription in adipose. This method may be used to uncover functional SNPs that do not reach significance thresholds in the agnostic approach of genome-wide association studies.

Genetics of coronary heart disease: towards causal mechanisms, novel drug targets and more personalized prevention

Coronary heart disease (CHD) is an archetypical multifactorial disorder that is influenced by genetic susceptibility as well as both modifiable and nonmodifiable risk factors, and their interactions. Advances during recent years in the field of multifactorial genetics, in particular genomewide association studies (GWASs) and their meta-analyses, have provided the statistical power to identify and replicate genetic variants in more than 50 risk loci for CHD and in several hundreds of loci for cardiometabolic risk factors for CHD such as blood lipids and lipoproteins. Although for a great majority of these loci both the causal variants and mechanisms remain unknown, progress in identifying the causal variants and underlying mechanisms has already been made for several genetic loci. Furthermore, identification of rare loss-of-function variants in genes such as PCSK9, NPC1L1, APOC3 and APOA5, which cause a markedly decreased risk of CHD and no adverse side effects, illustrates the power of translating genetic findings into novel mechanistic information and provides some optimism for the future of developing novel drugs, given the many genes associated with CHD in GWASs. Finally, Mendelian randomization can be used to reveal or exclude causal relationships between heritable biomarkers and CHD, and such approaches have already provided evidence of causal relationships between CHD and LDL cholesterol, triglycerides/remnant particles and lipoprotein(a), and indicated a lack of causality for HDL cholesterol, C-reactive protein and lipoprotein-associated phospholipase A2. Together, these genetic findings are beginning to lead to promising new drug targets and novel interventional strategies and thus have great potential to improve prevention, prediction and therapy of CHD.

Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers

We report ∼17.6 million genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from previous sequencing-based compilations and are enriched for predicted functional consequences. Furthermore, ∼76,000 variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. We observe 14 signals, including 2 major new loci, for lipid levels and 19 signals, including 2 new loci, for inflammatory markers. The new associations would have been missed in analyses based on 1000 Genomes Project data, underlining the advantages of large-scale sequencing in this founder population.

Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis

Genome-wide association studies (GWASs) have linked genes to various pathological traits. However, the potential contribution of regulatory noncoding RNAs, such as microRNAs (miRNAs), to a genetic predisposition to pathological conditions has remained unclear. We leveraged GWAS meta-analysis data from >188,000 individuals to identify 69 miRNAs in physical proximity to single-nucleotide polymorphisms (SNPs) associated with abnormal levels of circulating lipids. Several of these miRNAs (miR-128-1, miR-148a, miR-130b, and miR-301b) control the expression of key proteins involved in cholesterol-lipoprotein trafficking, such as the low-density lipoprotein (LDL) receptor (LDLR) and the ATP-binding cassette A1 (ABCA1) cholesterol transporter. Consistent with human liver expression data and genetic links to abnormal blood lipid levels, overexpression and antisense targeting of miR-128-1 or miR-148a in high-fat diet-fed C57BL/6J and Apoe-null mice resulted in altered hepatic expression of proteins involved in lipid trafficking and metabolism, and in modulated levels of circulating lipoprotein-cholesterol and triglycerides. Taken together, these findings support the notion that altered expression of miRNAs may contribute to abnormal blood lipid levels, predisposing individuals to human cardiometabolic disorders.

Deep History of East Asian Populations Revealed Through Genetic Analysis of the Ainu

Despite recent advances in population genomics, much remains to be elucidated with regard to East Asian population history. The Ainu, a hunter-gatherer population of northern Japan and Sakhalin island of Russia, are thought to be key to elucidating the prehistory of Japan and the peopling of East Asia. Here, we study the genetic relationship of the Ainu with other East Asian and Siberian populations outside the Japanese archipelago using genome-wide genotyping data. We find that the Ainu represent a deep branch of East Asian diversity more basal than all present-day East Asian farmers. However, we did not find a genetic connection between the Ainu and populations of the Tibetan plateau, rejecting their long-held hypothetical connection based on Y chromosome data. Unlike all other East Asian populations investigated, the Ainu have a closer genetic relationship with northeast Siberians than with central Siberians, suggesting ancient connections among populations around the Sea of Okhotsk. We also detect a recent genetic contribution of the Ainu to nearby populations, but no evidence for reciprocal recent gene flow is observed. Whole genome sequencing of contemporary and ancient Ainu individuals will be helpful to understand the details of the deep history of East Asians.

Genomic and transcriptomic predictors of triglyceride response to regular exercise

AIM

We performed genome-wide and transcriptome-wide profiling to identify genes and single nucleotide polymorphisms (SNPs) associated with the response of triglycerides (TG) to exercise training.

METHODS

Plasma TG levels were measured before and after a 20-week endurance training programme in 478 white participants from the HERITAGE Family Study. Illumina HumanCNV370-Quad v3.0 BeadChips were genotyped using the Illumina BeadStation 500GX platform. Affymetrix HG-U133+2 arrays were used to quantitate gene expression levels from baseline muscle biopsies of a subset of participants (N=52). Genome-wide association study (GWAS) analysis was performed using MERLIN, while transcriptomic predictor models were developed using the R-package GALGO.

RESULTS

The GWAS results showed that eight SNPs were associated with TG training-response (ΔTG) at p<9.9×10(-6), while another 31 SNPs showed p values <1×10(-4). In multivariate regression models, the top 10 SNPs explained 32.0% of the variance in ΔTG, while conditional heritability analysis showed that four SNPs statistically accounted for all of the heritability of ΔTG. A molecular signature based on the baseline expression of 11 genes predicted 27% of ΔTG in HERITAGE, which was validated in an independent study. A composite SNP score based on the top four SNPs, each from the genomic and transcriptomic analyses, was the strongest predictor of ΔTG (R(2)=0.14, p=3.0×10(-68)).

CONCLUSIONS

Our results indicate that skeletal muscle transcript abundance at 11 genes and SNPs at a number of loci contribute to TG response to exercise training. Combining data from genomics and transcriptomics analyses identified a SNP-based gene signature that should be further tested in independent samples.