Discovery and refinement of loci associated with lipid levels

Rare variant association studies: considerations, challenges and opportunities

Genome-wide association studies (GWASs) have successfully uncovered thousands of robust associations between common variants and complex traits and diseases. Despite these successes, much of the heritability of these traits remains unexplained. Because low-frequency and rare variants are not tagged by conventional genome-wide genotyping arrays, they may represent an important and understudied component of complex trait genetics. In contrast to common variant GWASs, there are many different types of study designs, assays and analytic techniques that can be utilized for rare variant association studies (RVASs). In this review, we briefly present the different technologies available to identify rare genetic variants, including novel exome arrays. We also compare the different study designs for RVASs and argue that the best design will likely be phenotype-dependent. We discuss the main analytical issues relevant to RVASs, including the different statistical methods that can be used to test genetic associations with rare variants and the various bioinformatic approaches to predicting in silico biological functions for variants. Finally, we describe recent rare variant association findings, highlighting the unexpected conclusion that most rare variants have modest-to-small effect sizes on phenotypic variation. This observation has major implications for our understanding of the genetic architecture of complex traits in the context of the unexplained heritability challenge.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

New genetic loci link adipose and insulin biology to body fat distribution

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Following the footprints of polymorphic inversions on SNP data: from detection to association tests

Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease.

Genetics and causality of triglyceride-rich lipoproteins in atherosclerotic cardiovascular disease

Triglycerides represent 1 component of a heterogeneous pool of triglyceride-rich lipoproteins (TGRLs). The reliance on triglycerides or TGRLs as cardiovascular disease (CVD) risk biomarkers prompted investigations into therapies that lower plasma triglycerides as a means to reduce CVD events. Genetic studies identified TGRL components and pathways involved in their synthesis and metabolism. We advocate that only a subset of genetic mechanisms regulating TGRLs contribute to the risk of CVD events. This "omic" approach recently resulted in new targets for reducing CVD events.

Genetic studies of schizophrenia: an update

Schizophrenia (SCZ) is a complex and heterogeneous mental disorder that affects about 1% of global population. In recent years, considerable progress has been made in genetic studies of SCZ. A number of common variants with small effects and rare variants with relatively larger effects have been identified. These variants include risk loci identified by genome-wide association studies, rare copy-number variants identified by comparative genomic analyses, and de novo mutations identified by high-throughput DNA sequencing. Collectively, they contribute to the heterogeneity of the disease. In this review, we update recent discoveries in the field of SCZ genetics, and outline the perspectives of future directions.

Hypertriglyceridemia in the genomic era: a new paradigm

Hypertriglyceridemia (HTG) is a highly prevalent condition that is associated with increased cardiovascular disease risk. HTG may arise as a result of defective metabolism of triglyceride-rich lipoproteins and their remnants, ie, impaired clearance, or increased production, or both. Current categorization of HTG segregates primary and secondary cases, implying genetic and nongenetic causes for each category. Many common and rare variants of the genes encoding factors involved in these pathways have been identified. Although monogenic forms of HTG do occur, most cases are polygenic and often coexist with nongenetic conditions. Cumulative, multiple genetic variants can increase the risks for HTG, whereas environmental and lifestyle factors can force expression of a dyslipidemic phenotype in a genetically susceptible person. HTG states are therefore best viewed as a complex phenotype resulting from the interaction of cumulated multiple susceptibility genes and environmental stressors. In view of the heterogeneity of the HTG states, the absence of a unifying metabolic or genetic abnormality, overlap with the metabolic syndrome and other features of insulin resistance, and evidence in some patients that accumulation of numerous small-effect genetic variants determines whether an individual is susceptible to HTG only or to HTG plus elevated low-density lipoprotein cholesterol, we propose that the diagnosis of primary HTG and further delineation of familial combined hyperlipidemia from familial HTG is neither feasible nor clinically relevant at the present time. The hope is that with greater understanding of genetic and environmental causes and their interaction, therapy can be intelligently targeted in the future.

The association of common polymorphisms in miR-196a2 with waist to hip ratio and miR-1908 with serum lipid and glucose

OBJECTIVE

MicroRNAs (miRNAs) have been implicated in the regulation of cardiometabolic disorders. Given the crucial role of miRNAs in gene expression, genetic variation within miRNA genes is expected to affect miRNA function and substantially contribute to disease risk.

METHODS

2,320 variants in miRNA-encoding sequences were systematically retrieved, and their associations with 17 cardiometabolic traits/diseases were investigated, using genome-wide association studies (GWAS) on glycemic indices, anthropometric measures, lipid traits, blood pressure, coronary artery disease, and type 2 diabetes. Next, target genes of the identified miRNAs that may mediate their effect on the phenotypes were examined. Furthermore, trans- expression quantitative trait loci analysis and luciferase reporter assay to provide functional evidence for our findings were performed.

RESULTS

rs11614913:C/T in miR-196a2 was associated with waist to hip ratio (P-value=1.7 × 10(-5) , β = 0.023). Two target genes, SFMBT1 and HOXC8, which may mediate this association were identfied, and they were shown experimentally as direct targets of miR-196a2. Moreover, rs174561:C/T in miR-1908 was found to be associated with total cholesterol (P-value=6.5 × 10(-16) , β=0.044), LDL-cholesterol (P-value=4.3 × 10(-18) , β=0.049), HDL-cholesterol (P-value=1.7 × 10(-6) , β=0.026), triglyceride (P-value=7.8 × 10(-14) , β=0.038), and fasting glucose (P-value=4.3 × 10(-10) , β=0.02). In addition, a number of miR-1908 target genes were highlighted as potential mediators.

CONCLUSIONS

The results indicated miRNA-dependent regulation of fat distribution by miR-196a2 and of lipid metabolism by miR-1908.

An epidemiological perspective of personalized medicine: the Estonian experience

The Estonian Biobank and several other biobanks established over a decade ago are now starting to yield valuable longitudinal follow-up data for large numbers of individuals. These samples have been used in hundreds of different genome-wide association studies, resulting in the identification of reliable disease-associated variants. The focus of genomic research has started to shift from identifying genetic and nongenetic risk factors associated with common complex diseases to understanding the underlying mechanisms of the diseases and suggesting novel targets for therapy. However, translation of findings from genomic research into medical practice is still lagging, mainly due to insufficient evidence of clinical validity and utility. In this review, we examine the different elements required for the implementation of personalized medicine based on genomic information. First, biobanks and genome centres are required and have been established for the high-throughput genomic screening of large numbers of samples. Secondly, the combination of susceptibility alleles into polygenic risk scores has improved risk prediction of cardiovascular disease, breast cancer and several other diseases. Finally, national health information systems are being developed internationally, to combine data from electronic medical records from different sources, and also to gradually incorporate genomic information. We focus on the experience in Estonia, one of several countries with national goals towards more personalized health care based on genomic information, where the unique combination of elements required to accomplish this goal are already in place.

Genetics of hand grip strength in mid to late life

Hand grip strength (GS) is a predictor of mortality in older adults and is moderately to highly heritable, but no genetic variants have been consistently identified. We aimed to identify single nucleotide polymorphisms (SNPs) associated with GS in middle-aged to older adults using a genome-wide association study (GWAS). GS was measured using handheld dynamometry in community-dwelling men and women aged 55-85 from the Hunter Community Study (HCS, N = 2088) and the Sydney Memory and Ageing Study (Sydney MAS, N = 541). Genotyping was undertaken using Affymetrix microarrays with imputation to HapMap2. Analyses were performed using linear regression. No genome-wide significant results were observed in HCS nor were any of the top signals replicated in Sydney MAS. Gene-based analyses in HCS identified two significant genes (ZNF295, C2CD2), but these results were not replicated in Sydney MAS. One out of eight SNPs previously associated with GS, rs550942, located near the CNTF gene, was significantly associated with GS (p = 0.005) in the HCS cohort only. Study differences may explain the lack of consistent results between the studies, including the smaller sample size of the Sydney MAS cohort. Our modest sample size also had limited power to identify variants of small effect. Our results suggest that similar to various other complex traits, many genetic variants of small effect size may influence GS. Future GWAS using larger samples and consistent measures may prove more fruitful at identifying genetic contributors for GS in middle-aged to older adults.

Genetics of kidney disease and related cardiometabolic phenotypes in Zuni Indians: the Zuni Kidney Project

The objective of this study is to identify genetic factors associated with chronic kidney disease (CKD) and related cardiometabolic phenotypes among participants of the Genetics of Kidney Disease in Zuni Indians study. The study was conducted as a community-based participatory research project in the Zuni Indians, a small endogamous tribe in rural New Mexico. We recruited 998 members from 28 extended multigenerational families, ascertained through probands with CKD who had at least one sibling with CKD. We used the Illumina Infinium Human1M-Duo version 3.0 BeadChips to type 1.1 million single nucleotide polymorphisms (SNPs). Prevalence estimates for CKD, hyperuricemia, diabetes, and hypertension were 24%, 30%, 17% and 34%, respectively. We found a significant (p < 1.58 × 10^-7) association for a SNP in a novel gene for serum creatinine (PTPLAD2). We replicated significant associations for genes with serum uric acid (SLC2A9), triglyceride levels (APOA1, BUD13, ZNF259), and total cholesterol (PVRL2). We found novel suggestive associations (p < 1.58 × 10^-6) for SNPs in genes with systolic (OLFML2B), and diastolic blood pressure (NFIA). We identified a series of genes associated with CKD and related cardiometabolic phenotypes among Zuni Indians, a population with a high prevalence of kidney disease. Illuminating genetic variations that modulate the risk for these disorders may ultimately provide a basis for novel preventive strategies and therapeutic interventions.

Resequencing of LPL in African Blacks and associations with lipoprotein-lipid levels

Genome-wide association studies have identified several loci associated with plasma lipid levels but those common variants together account only for a small proportion of the genetic variance of lipid traits. It has been hypothesized that the remaining heritability may partly be explained by rare variants with strong effect sizes. Here, we have comprehensively investigated the associations of both common and uncommon/rare variants in the lipoprotein lipase (LPL) gene in relation to plasma lipoprotein-lipid levels in African Blacks (ABs). For variant discovery purposes, the entire LPL gene and flanking regions were resequenced in 95 ABs with extreme high-density lipoprotein cholesterol (HDL-C) levels. A total of 308 variants were identified, of which 64 were novel. Selected common tagSNPs and uncommon/rare variants were genotyped in the entire sample (n=788), and 126 QC-passed variants were evaluated for their associations with lipoprotein-lipid levels by using single-site, haplotype and rare variant (SKAT-O) association analyses. We found eight not highly correlated (r(2)<0.40) signals (rs1801177:G>A, rs8176337:G>C, rs74304285:G>A, rs252:delA, rs316:C>A, rs329:A>G, rs12679834:T>C, and rs4921684:C>T) nominally (P<0.05) associated with lipid traits (HDL-C, LDL-C, ApoA1 or ApoB levels) in our sample. The most significant SNP, rs252:delA, represented a novel association observed with LDL-C (P=0.002) and ApoB (P=0.012). For TG and LDL-C, the haplotype analysis was more informative than the single-site analysis. The SKAT-O analysis revealed that the bin (group) containing 22 rare variants with MAF≤0.01 exhibited nominal association with TG (P=0.039) and LDL-C (P=0.027). Our study indicates that both common and uncommon/rare LPL variants/haplotypes may affect plasma lipoprotein-lipid levels in general African population.

HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

BACKGROUND

Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.

METHODS

We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.

FINDINGS

Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials).

INTERPRETATION

The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.

FUNDING

The funding sources are cited at the end of the paper.

DNA methylation of lipid-related genes affects blood lipid levels

BACKGROUND

Epigenetic mechanisms might be involved in the regulation of interindividual lipid level variability and thus may contribute to the cardiovascular risk profile. The aim of this study was to investigate the association between genome-wide DNA methylation and blood lipid levels high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and total cholesterol. Observed DNA methylation changes were also further analyzed to examine their relationship with previous hospitalized myocardial infarction.

METHODS AND RESULTS

Genome-wide DNA methylation patterns were determined in whole blood samples of 1776 subjects of the Cooperative Health Research in the Region of Augsburg F4 cohort using the Infinium HumanMethylation450 BeadChip (Illumina). Ten novel lipid-related CpG sites annotated to various genes including ABCG1, MIR33B/SREBF1, and TNIP1 were identified. CpG cg06500161, located in ABCG1, was associated in opposite directions with both high-density lipoprotein cholesterol (β coefficient=-0.049; P=8.26E-17) and triglyceride levels (β=0.070; P=1.21E-27). Eight associations were confirmed by replication in the Cooperative Health Research in the Region of Augsburg F3 study (n=499) and in the Invecchiare in Chianti, Aging in the Chianti Area study (n=472). Associations between triglyceride levels and SREBF1 and ABCG1 were also found in adipose tissue of the Multiple Tissue Human Expression Resource cohort (n=634). Expression analysis revealed an association between ABCG1 methylation and lipid levels that might be partly mediated by ABCG1 expression. DNA methylation of ABCG1 might also play a role in previous hospitalized myocardial infarction (odds ratio, 1.15; 95% confidence interval=1.06-1.25).

CONCLUSIONS

Epigenetic modifications of the newly identified loci might regulate disturbed blood lipid levels and thus contribute to the development of complex lipid-related diseases.

Serum lipid levels, body mass index, and their role in coronary artery calcification: a polygenic analysis

BACKGROUND

Coronary artery calcification (CAC) is widely regarded as a cumulative lifetime measure of atherosclerosis, but it remains unclear what is the relationship between calcification and traditional risk factors for coronary artery disease (CAD) and myocardial infarction (MI). This study characterizes the genetic architecture of CAC by evaluating the overall impact of common alleles associated with CAD/MI and its traditional risk factors.

METHODS AND RESULTS

On the basis of summary-association results from the CARDIoGRAMplusC4D study of CAD/MI, we calculated polygenic risk scores in 2599 participants of the Dutch and Belgian Lung Cancer Screening (NELSON) trial, in whom quantitative CAC levels (Agatston scores) were determined from chest computerized tomographic imaging data. The most significant polygenic model explained ≈14% of the observed CAC variance (P=1.6×10(-11)), which points to a residual effect because of many as yet unknown loci that overlap between CAD/MI and CAC. In addition, we constructed risk scores based on published single-nucleotide polymorphism associations for traditional cardiovascular risk factors and tested these scores for association with CAC. We found nominally significant associations for genetic risk scores of low-density lipoprotein-cholesterol, total cholesterol, and body mass index, which were successfully replicated in 2182 individuals of the Heinz Nixdorf Recall Study.

CONCLUSIONS

Pervasive polygenic sharing between CAC and CAD/MI suggests that a substantial fraction of the heritable risk for CAD/MI is mediated through arterial calcification. We also provide evidence that genetic variants associated with serum lipid levels and body mass index influence CAC levels.

Mouse-human experimental epigenetic analysis unmasks dietary targets and genetic liability for diabetic phenotypes

Using a functional approach to investigate the epigenetics of type 2 diabetes (T2D), we combine three lines of evidence-diet-induced epigenetic dysregulation in mouse, epigenetic conservation in humans, and T2D clinical risk evidence-to identify genes implicated in T2D pathogenesis through epigenetic mechanisms related to obesity. Beginning with dietary manipulation of genetically homogeneous mice, we identify differentially DNA-methylated genomic regions. We then replicate these results in adipose samples from lean and obese patients pre- and post-Roux-en-Y gastric bypass, identifying regions where both the location and direction of methylation change are conserved. These regions overlap with 27 genetic T2D risk loci, only one of which was deemed significant by GWAS alone. Functional analysis of genes associated with these regions revealed four genes with roles in insulin resistance, demonstrating the potential general utility of this approach for complementing conventional human genetic studies by integrating cross-species epigenomics and clinical genetic risk.

Association Analysis of Genetic Variants with Type 2 Diabetes in a Mongolian Population in China

The large scale genome wide association studies (GWAS) have identified approximately 80 single nucleotide polymorphisms (SNPs) conferring susceptibility to type 2 diabetes (T2D). However, most of these loci have not been replicated in diverse populations and much genetic heterogeneity has been observed across ethnic groups. We tested 28 SNPs previously found to be associated with T2D by GWAS in a Mongolian sample of Northern China (497 diagnosed with T2D and 469 controls) for association with T2D and diabetes related quantitative traits. We replicated T2D association of 11 SNPs, namely, rs7578326 (IRS1), rs1531343 (HMGA2), rs8042680 (PRC1), rs7578597 (THADA), rs1333051 (CDKN2), rs6723108 (TMEM163), rs163182 and rs2237897 (KCNQ1), rs1387153 (MTNR1B), rs243021 (BCL11A), and rs10229583 (PAX4) in our sample. Further, we showed that risk allele of the strongest T2D associated SNP in our sample, rs757832 (IRS1), is associated with increased level of TG. We observed substantial difference of T2D risk allele frequency between the Mongolian sample and the 1000G Caucasian sample for a few SNPs, including rs6723108 (TMEM163) whose risk allele reaches near fixation in the Mongolian sample. Further study of genetic architecture of these variants in susceptibility of T2D is needed to understand the role of these variants in heterogeneous populations.

A genetic risk tool for obesity predisposition assessment and personalized nutrition implementation based on macronutrient intake

There is little evidence about genetic risk score (GRS)-diet interactions in order to provide personalized nutrition based on the genotype. The aim of the study was to assess the value of a GRS on obesity prediction and to further evaluate the interactions between the GRS and dietary intake on obesity. A total of 711 seekers of a Nutrigenetic Service were examined for anthropometric and body composition measurements and also for dietary habits and physical activity. Oral epithelial cells were collected for the identification of 16 SNPs (related with obesity or lipid metabolism) using DNA zip-coded beads. Genotypes were coded as 0, 1 or 2 according to the number of risk alleles, and the GRS was calculated by adding risk alleles with such a criterion. After being adjusted for gender, age, physical activity and energy intake, the GRS demonstrated that individuals carrying >7 risk alleles had in average 0.93 kg/m(2) of BMI, 1.69 % of body fat mass, 1.94 cm of waist circumference and 0.01 waist-to-height ratio more than the individuals with ≤7 risk alleles. Significant interactions for GRS and the consumption of energy, total protein, animal protein, vegetable protein, total fat, saturated fatty acids, polyunsaturated fatty acids, total carbohydrates, complex carbohydrates and fiber intake on adiposity traits were found after adjusted for confounders variables. The GRS confirmed that the high genetic risk group showed greater values of adiposity than the low risk group and demonstrated that macronutrient intake modifies the GRS association with adiposity traits.

Beyond the genetics of HDL: why is HDL cholesterol inversely related to cardiovascular disease?

There is unequivocal evidence that high-density lipoprotein (HDL) cholesterol levels in plasma are inversely associated with the risk of cardiovascular disease (CVD). Studies of families with inherited HDL disorders and genetic association studies in general (and patient) population samples have identified a large number of factors that control HDL cholesterol levels. However, they have not resolved why HDL cholesterol and CVD are inversely related. A growing body of evidence from nongenetic studies shows that HDL in patients at increased risk of CVD has lost its protective properties and that increasing the cholesterol content of HDL does not result in the desired effects. Hopefully, these insights can help improve strategies to successfully intervene in HDL metabolism. It is clear that there is a need to revisit the HDL hypothesis in an unbiased manner. True insights into the molecular mechanisms that regulate plasma HDL cholesterol and triglycerides or control HDL function could provide the handholds that are needed to develop treatment for, e.g., type 2 diabetes and the metabolic syndrome. Especially genome-wide association studies have provided many candidate genes for such studies. In this review we have tried to cover the main molecular studies that have been produced over the past few years. It is clear that we are only at the very start of understanding how the newly identified factors may control HDL metabolism. In addition, the most recent findings underscore the intricate relations between HDL, triglyceride, and glucose metabolism indicating that these parameters need to be studied simultaneously.

Placental genome and maternal-placental genetic interactions: a genome-wide and candidate gene association study of placental abruption

While available evidence supports the role of genetics in the pathogenesis of placental abruption (PA), PA-related placental genome variations and maternal-placental genetic interactions have not been investigated. Maternal blood and placental samples collected from participants in the Peruvian Abruptio Placentae Epidemiology study were genotyped using Illumina's Cardio-Metabochip platform. We examined 118,782 genome-wide SNPs and 333 SNPs in 32 candidate genes from mitochondrial biogenesis and oxidative phosphorylation pathways in placental DNA from 280 PA cases and 244 controls. We assessed maternal-placental interactions in the candidate gene SNPS and two imprinted regions (IGF2/H19 and C19MC). Univariate and penalized logistic regression models were fit to estimate odds ratios. We examined the combined effect of multiple SNPs on PA risk using weighted genetic risk scores (WGRS) with repeated ten-fold cross-validations. A multinomial model was used to investigate maternal-placental genetic interactions. In placental genome-wide and candidate gene analyses, no SNP was significant after false discovery rate correction. The top genome-wide association study (GWAS) hits were rs544201, rs1484464 (CTNNA2), rs4149570 (TNFRSF1A) and rs13055470 (ZNRF3) (p-values: 1.11e-05 to 3.54e-05). The top 200 SNPs of the GWAS overrepresented genes involved in cell cycle, growth and proliferation. The top candidate gene hits were rs16949118 (COX10) and rs7609948 (THRB) (p-values: 6.00e-03 and 8.19e-03). Participants in the highest quartile of WGRS based on cross-validations using SNPs selected from the GWAS and candidate gene analyses had a 8.40-fold (95% CI: 5.8-12.56) and a 4.46-fold (95% CI: 2.94-6.72) higher odds of PA compared to participants in the lowest quartile. We found maternal-placental genetic interactions on PA risk for two SNPs in PPARG (chr3:12313450 and chr3:12412978) and maternal imprinting effects for multiple SNPs in the C19MC and IGF2/H19 regions. Variations in the placental genome and interactions between maternal-placental genetic variations may contribute to PA risk. Larger studies may help advance our understanding of PA pathogenesis.

Comprehensive evaluation of the association of APOE genetic variation with plasma lipoprotein traits in U.S. whites and African blacks

Although common APOE genetic variation has a major influence on plasma LDL-cholesterol, its role in affecting HDL-cholesterol and triglycerides is not well established. Recent genome-wide association studies suggest that APOE also affects plasma variation in HDL-cholesterol and triglycerides. It is thus important to resequence the APOE gene to identify both common and uncommon variants that affect plasma lipid profile. Here, we have sequenced the APOE gene in 190 subjects with extreme HDL-cholesterol levels selected from two well-defined epidemiological samples of U.S. non-Hispanic Whites (NHWs) and African Blacks followed by genotyping of identified variants in the entire datasets (623 NHWs, 788 African Blacks) and association analyses with major lipid traits. We identified a total of 40 sequence variants, of which 10 are novel. A total of 32 variants, including common tagSNPs (≥5% frequency) and all uncommon variants (<5% frequency) were successfully genotyped and considered for genotype-phenotype associations. Other than the established associations of APOE*2 and APOE*4 with LDL-cholesterol, we have identified additional independent associations with LDL-cholesterol. We have also identified multiple associations of uncommon and common APOE variants with HDL-cholesterol and triglycerides. Our comprehensive sequencing and genotype-phenotype analyses indicate that APOE genetic variation impacts HDL-cholesterol and triglycerides in addition to affecting LDL-cholesterol.

Plasma lipoprotein(a) levels are associated with mild renal impairment in type 2 diabetics independent of albuminuria

Background

CKD, an independent risk factor for CV disease, increases mortality in T2DM. Treating modifiable CV risk factors decreases mortality in diabetics with microalbuminuria, but the role of early CV prevention in diabetics with mild CKD by GFR criteria alone remains unclear. The purpose of this study was to probe whether T2DM patients with mild GFR impairment have atherogenic lipid profiles compared to diabetic counterparts with normal renal function.

Methods

In the Penn Diabetes Heart Study (PDHS), a single-center observational cohort of T2DM patients without clinical CVD, cross-sectional analyses were performed for directly measured lipid fractions in 1852 subjects with eGFR>60 mL/min/1.73 m² determined by the CKD-EPI equation (n = 1852). Unadjusted and multivariable analyses of eGFR association with log-transformed lipid parameters in incremental linear and logistic regression models (with eGFR 90 mL/min/1.73 m² as a cut-point) were performed.

Results

Mild GFR impairment (eGFR 60–90 mL/min/1.73 m², median urinary ACR 5.25 mg/g) was associated with higher log-transformed Lp(a) values (OR 1.17, p = 0.005) and with clinically atherogenic Lp(a) levels above 30 mg/dL (OR 1.35, p = 0.013) even after full adjustment for demographics, medications, metabolic parameters, and albuminuria. Logistic regression demonstrated a trend towards significance between worse kidney function and apoB (p = 0.17) as well as apoC-III (p = 0.067) in the fully adjusted model.

Conclusions

Elevated Lp(a) levels have a robust association with mild GFR impairment in type 2 diabetics independent of race, insulin resistance, and albuminuria.

Prioritizing causal disease genes using unbiased genomic features

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits.

RESULTS

To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM.

CONCLUSION

Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

Reducing the burden of disease and death from familial hypercholesterolemia: a call to action

Familial hypercholesterolemia (FH) is a genetic disease characterized by substantial elevations of low-density lipoprotein cholesterol, unrelated to diet or lifestyle. Untreated FH patients have 20 times the risk of developing coronary artery disease, compared with the general population. Estimates indicate that as many as 1 in 500 people of all ethnicities and 1 in 250 people of Northern European descent may have FH; nevertheless, the condition remains largely undiagnosed. In the United States alone, perhaps as little as 1% of FH patients have been diagnosed. Consequently, there are potentially millions of children and adults worldwide who are unaware that they have a life-threatening condition. In countries like the Netherlands, the United Kingdom, and Spain, cascade screening programs have led to dramatic improvements in FH case identification. Given that there are currently no systematic approaches in the United States to identify FH patients or affected relatives, the patient-centric nonprofit FH Foundation convened a national FH Summit in 2013, where participants issued a "call to action" to health care providers, professional organizations, public health programs, patient advocacy groups, and FH experts, in order to bring greater attention to this potentially deadly, but (with proper diagnosis) eminently treatable, condition.

Genetics of metabolic syndrome

Metabolic syndrome (MetS) is a cluster of metabolic traits associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus. Central obesity and insulin resistance are thought to play key roles in the pathogenesis of the MetS. The MetS has a significant genetic component, and therefore linkage analysis, candidate gene approach, and genome-wide association (GWA) studies have been applied in the search of gene variants for the MetS. A few variants have been identified, located mostly in or near genes regulating lipid metabolism. GWA studies for the individual components of the MetS have reported several loci having pleiotropic effects on multiple MetS-related traits. Genetic studies have provided so far only limited evidence for a common genetic background of the MetS. Epigenetic factors (DNA methylation and histone modification) are likely to play important roles in the pathogenesis of the MetS, and they might mediate the effects of environmental exposures on the risk of the MetS. Further research is needed to clarify the role of genetic variation and epigenetic mechanisms in the development of the MetS.

Rare variant APOC3 R19X is associated with cardio-protective profiles in a diverse population-based survey as part of the Epidemiologic Architecture for Genes Linked to Environment Study

BACKGROUND

A founder mutation was recently discovered and described as conferring favorable lipid profiles and reduced subclinical atherosclerotic disease in a Pennsylvania Amish population. Preliminary data have suggested that this null mutation APOC3 R19X (rs76353203) is rare in the general population.

METHODS AND RESULTS

To better describe the frequency and lipid profile in the general population, we as part of the Population Architecture using Genomics and Epidemiology I Study and the Epidemiological Architecture for Genes Linked to Environment Study genotyped rs76353203 in 1113 Amish participants from Ohio and Indiana and 19 613 participants from the National Health and Nutrition Examination Surveys (NHANES III, 1999 to 2002, and 2007 to 2008). We found no carriers among the Ohio and Indiana Amish. Of the 19 613 NHANES participants, we identified 31 participants carrying the 19X allele, for an overall allele frequency of 0.08%. Among fasting adults, the 19X allele was associated with lower triglycerides (n=7603; β=-71.20; P=0.007) and higher high-density lipoprotein cholesterol (n=8891; β=15.65; P=0.0002) and, although not significant, lower low-density lipoprotein cholesterol (n=6502; β= -4.85; P=0.68) after adjustment for age, sex, and race/ethnicity. On average, 19X allele participants had approximately half the triglyceride levels (geometric means, 51.3 to 69.7 versus 134.6 to 141.3 mg/dL), >20% higher high-density lipoprotein cholesterol levels (geometric means, 56.8 to 74.4 versus 50.38 to 53.36 mg/dL), and lower low-density lipoprotein cholesterol levels (geometric means, 104.5 to 128.6 versus 116.1 to 125.7 mg/dL) compared with noncarrier participants.

CONCLUSIONS

These data demonstrate that APOC3 19X exists in the general US population in multiple racial/ethnic groups and is associated with cardio-protective lipid profiles.

On the analysis of a repeated measure design in genome-wide association analysis

Longitudinal data enables detecting the effect of aging/time, and as a repeated measures design is statistically more efficient compared to cross-sectional data if the correlations between repeated measurements are not large. In particular, when genotyping cost is more expensive than phenotyping cost, the collection of longitudinal data can be an efficient strategy for genetic association analysis. However, in spite of these advantages, genome-wide association studies (GWAS) with longitudinal data have rarely been analyzed taking this into account. In this report, we calculate the required sample size to achieve 80% power at the genome-wide significance level for both longitudinal and cross-sectional data, and compare their statistical efficiency. Furthermore, we analyzed the GWAS of eight phenotypes with three observations on each individual in the Korean Association Resource (KARE). A linear mixed model allowing for the correlations between observations for each individual was applied to analyze the longitudinal data, and linear regression was used to analyze the first observation on each individual as cross-sectional data. We found 12 novel genome-wide significant disease susceptibility loci that were then confirmed in the Health Examination cohort, as well as some significant interactions between age/sex and SNPs.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

Cholesterol levels in fragile X syndrome

Fragile X syndrome (FXS) is associated with intellectual disability and behavioral dysfunction, including anxiety, ADHD symptoms, and autistic features. Although individuals with FXS are largely considered healthy and lifespan is not thought to be reduced, very little is known about the long-term medical health of adults with FXS and no systematically collected information is available on standard laboratory measures from metabolic screens. During the course of follow up of a large cohort of patients with FXS we noted that many patients had low cholesterol and high density lipoprotein (HDL) values and thus initiated a systematic chart review of all cholesterol values present in charts from a clinic cohort of over 500 patients with FXS. Total cholesterol (TC), low density lipoprotein (LDL) and HDL were all significantly reduced in males from the FXS cohort relative to age-adjusted population normative data. This finding has relevance for health monitoring in individuals with FXS, for treatments with cholesterol-lowering agents that have been proposed to target the underlying CNS disorder in FXS based on work in animal models, and for potential biomarker development in FXS.

G-protein estrogen receptor as a regulator of low-density lipoprotein cholesterol metabolism: cellular and population genetic studies

OBJECTIVE

Estrogen deficiency is linked with increased low-density lipoprotein (LDL) cholesterol. The hormone receptor mediating this effect is unknown. G-protein estrogen receptor (GPER) is a recently recognized G-protein-coupled receptor that is activated by estrogens. We recently identified a common hypofunctional missense variant of GPER, namely P16L. However, the role of GPER in LDL metabolism is unknown. Therefore, we examined the association of the P16L genotype with plasma LDL cholesterol level. Furthermore, we studied the role of GPER in regulating expression of the LDL receptor and proprotein convertase subtilisin kexin type 9.

APPROACH AND RESULTS

Our discovery cohort was a genetically isolated population of Northern European descent, and our validation cohort consisted of normal, healthy women aged 18 to 56 years from London, Ontario. In addition, we examined the effect of GPER on the regulation of proprotein convertase subtilisin kexin type 9 and LDL receptor expression by the treatment with the GPER agonist, G1. In the discovery cohort, GPER P16L genotype was associated with a significant increase in LDL cholesterol (mean±SEM): 3.18±0.05, 3.25±0.08, and 4.25±0.33 mmol/L, respectively, in subjects with CC (homozygous for P16), CT (heterozygotes), and TT (homozygous for L16) genotypes (P<0.05). In the validation cohort (n=339), the GPER P16L genotype was associated with a similar increase in LDL cholesterol: 2.17±0.05, 2.34±0.06, and 2.42±0.16 mmol/L, respectively, in subjects with CC, CT, and TT genotypes (P<0.05). In the human hepatic carcinoma cell line, the GPER agonist, G1, mediated a concentration-dependent increase in LDL receptor expression, blocked by either pretreatment with the GPER antagonist G15 or by shRNA-mediated GPER downregulation. G1 also mediated a GPER- and concentration-dependent decrease in proprotein convertase subtilisin kexin type 9 expression.

CONCLUSIONS

GPER activation upregulates LDL receptor expression, probably at least, in part, via proprotein convertase subtilisin kexin type 9 downregulation. Furthermore, humans carrying the hypofunctional P16L genetic variant of GPER have increased plasma LDL cholesterol. In aggregate, these data suggest an important role of GPER in the regulation of LDL receptor expression and consequently LDL metabolism.

Association of low-density lipoprotein cholesterol-related genetic variants with aortic valve calcium and incident aortic stenosis

IMPORTANCE

Plasma low-density lipoprotein cholesterol (LDL-C) has been associated with aortic stenosis in observational studies; however, randomized trials with cholesterol-lowering therapies in individuals with established valve disease have failed to demonstrate reduced disease progression.

OBJECTIVE

To evaluate whether genetic data are consistent with an association between LDL-C, high-density lipoprotein cholesterol (HDL-C), or triglycerides (TG) and aortic valve disease.

DESIGN, SETTING, AND PARTICIPANTS

Using a Mendelian randomization study design, we evaluated whether weighted genetic risk scores (GRSs), a measure of the genetic predisposition to elevations in plasma lipids, constructed using single-nucleotide polymorphisms identified in genome-wide association studies for plasma lipids, were associated with aortic valve disease. We included community-based cohorts participating in the CHARGE consortium (n = 6942), including the Framingham Heart Study (cohort inception to last follow-up: 1971-2013; n = 1295), Multi-Ethnic Study of Atherosclerosis (2000-2012; n = 2527), Age Gene/Environment Study-Reykjavik (2000-2012; n = 3120), and the Malmö Diet and Cancer Study (MDCS, 1991-2010; n = 28,461).

MAIN OUTCOMES AND MEASURES

Aortic valve calcium quantified by computed tomography in CHARGE and incident aortic stenosis in the MDCS.

RESULTS

The prevalence of aortic valve calcium across the 3 CHARGE cohorts was 32% (n = 2245). In the MDCS, over a median follow-up time of 16.1 years, aortic stenosis developed in 17 per 1000 participants (n = 473) and aortic valve replacement for aortic stenosis occurred in 7 per 1000 (n = 205). Plasma LDL-C, but not HDL-C or TG, was significantly associated with incident aortic stenosis (hazard ratio [HR] per mmol/L, 1.28; 95% CI, 1.04-1.57; P = .02; aortic stenosis incidence: 1.3% and 2.4% in lowest and highest LDL-C quartiles, respectively). The LDL-C GRS, but not HDL-C or TG GRS, was significantly associated with presence of aortic valve calcium in CHARGE (odds ratio [OR] per GRS increment, 1.38; 95% CI, 1.09-1.74; P = .007) and with incident aortic stenosis in MDCS (HR per GRS increment, 2.78; 95% CI, 1.22-6.37; P = .02; aortic stenosis incidence: 1.9% and 2.6% in lowest and highest GRS quartiles, respectively). In sensitivity analyses excluding variants weakly associated with HDL-C or TG, the LDL-C GRS remained associated with aortic valve calcium (P = .03) and aortic stenosis (P = .009). In instrumental variable analysis, LDL-C was associated with an increase in the risk of incident aortic stenosis (HR per mmol/L, 1.51; 95% CI, 1.07-2.14; P = .02).

CONCLUSIONS AND RELEVANCE

Genetic predisposition to elevated LDL-C was associated with presence of aortic valve calcium and incidence of aortic stenosis, providing evidence supportive of a causal association between LDL-C and aortic valve disease. Whether earlier intervention to reduce LDL-C could prevent aortic valve disease merits further investigation.

The arachidonic acid metabolome serves as a conserved regulator of cholesterol metabolism

Cholesterol metabolism is closely interrelated with cardiovascular disease in humans. Dietary supplementation with omega-6 polyunsaturated fatty acids including arachidonic acid (AA) was shown to favorably affect plasma LDL-C and HDL-C. However, the underlying mechanisms are poorly understood. By combining data from a GWAS screening in >100,000 individuals of European ancestry, mediator lipidomics, and functional validation studies in mice, we identify the AA metabolome as an important regulator of cholesterol homeostasis. Pharmacological modulation of AA metabolism by aspirin induced hepatic generation of leukotrienes (LTs) and lipoxins (LXs), thereby increasing hepatic expression of the bile salt export pump Abcb11. Induction of Abcb11 translated in enhanced reverse cholesterol transport, one key function of HDL. Further characterization of the bioactive AA-derivatives identified LX mimetics to lower plasma LDL-C. Our results define the AA metabolomeasconserved regulator of cholesterol metabolism, and identify AA derivatives as promising therapeutics to treat cardiovascular disease in humans.

Aging and cardiovascular diseases: the role of gene-diet interactions

In the study of longevity, increasing importance is being placed on the concept of healthy aging rather than considering the total number of years lived. Although the concept of healthy lifespan needs to be defined better, we know that cardiovascular diseases (CVDs) are the main age-related diseases. Thus, controlling risk factors will contribute to reducing their incidence, leading to healthy lifespan. CVDs are complex diseases influenced by numerous genetic and environmental factors. Numerous gene variants that are associated with a greater or lesser risk of the different types of CVD and of intermediate phenotypes (i.e., hypercholesterolemia, hypertension, diabetes) have been successfully identified. However, despite the close link between aging and CVD, studies analyzing the genes related to human longevity have not obtained consistent results and there has been little coincidence in the genes identified in both fields. The APOE gene stands out as an exception, given that it has been identified as being relevant in CVD and longevity. This review analyzes the genomic and epigenomic factors that may contribute to this, ranging from identifying longevity genes in model organisms to the importance of gene-diet interactions (outstanding among which is the case of the TCF7L2 gene).

Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis

Variation in body iron is associated with or causes diseases, including anaemia and iron overload. Here, we analyse genetic association data on biochemical markers of iron status from 11 European-population studies, with replication in eight additional cohorts (total up to 48,972 subjects). We find 11 genome-wide-significant (P<5 × 10(-8)) loci, some including known iron-related genes (HFE, SLC40A1, TF, TFR2, TFRC, TMPRSS6) and others novel (ABO, ARNTL, FADS2, NAT2, TEX14). SNPs at ARNTL, TF, and TFR2 affect iron markers in HFE C282Y homozygotes at risk for hemochromatosis. There is substantial overlap between our iron loci and loci affecting erythrocyte and lipid phenotypes. These results will facilitate investigation of the roles of iron in disease.

Association of cholesteryl ester transfer protein (CETP) gene polymorphism, high density lipoprotein cholesterol and risk of coronary artery disease: a meta-analysis using a Mendelian randomization approach

BACKGROUND

Recent randomized controlled trials have challenged the concept that increased high density lipoprotein cholesterol (HDL-C) levels are associated with coronary artery disease (CAD) risk reduction. The causal role of HDL-C in the development of atherosclerosis remains unclear. To increase precision and to minimize residual confounding, we exploited the cholesteryl ester transfer protein (CETP)-TaqIB polymorphism as an instrument based on Mendelian randomization.

METHODS

The Mendelian randomization analysis was performed by two steps. First, we conducted a meta-analysis of 47 studies, including 23,928 cases and 27,068 controls, to quantify the relationship between the TaqIB polymorphism and the CAD risk. Next, the association between the TaqIB polymorphism and HDL-C was assessed among 5,929 Caucasians. We further employed Mendelian randomization to evaluate the causal effect of HDL-C on CAD based on the findings from the meta-analysis.

RESULTS

The overall comparison of the B2 allele with the B1 allele yielded a significant risk reduction of CAD (P < 0.0001; OR = 0.88; 95% CI: 0.84-0.92) with substantial between-study heterogeneity (I² = 55.2%; P(heterogeneity) <0.0001). The result was not materially changed after excluding the Hardy-Weinberg Equilibrium (HWE)-violation studies. Compared with B1B1 homozygotes, Caucasian carriers of the B2 allele had a 0.25 mmol/L increase in HDL-C level (95% CI: 0.20-0.31; P <0.0001; I² = 0; P(heterogeneity) =0.87). However, a 1 standard deviation (SD) elevation in HDL-C levels due to the TaqIB polymorphism, was marginal associated with CAD risk (OR =0.79; 95% CI: 0.54-1.03; P =0.08).

CONCLUSIONS

Taken together, our results lend support to the concept that increased HDL-C cannot be translated into a reduction in CAD risk.

The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10⁻⁸ that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (N_total = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.

A genetic basis for coronary artery disease

CAD and cancer account for over one-half of all deaths in the world. It is claimed that the 21st century is the last century for CAD. This is, in part, because CAD is preventable based on randomized, placebo-controlled clinical trials, which show modifying known risk factors such as cholesterol is associated consistently with 40-60% reduction in morbidity and mortality from CAD. Comprehensive prevention will require modifying genetic risk factors that are claimed to account for 40-60% of predisposition to CAD. The 21st century is meeting this challenge with over 50 genetic risk variants discovered and replicated in large genome-wide association studies involving over 200,000 cases and controls. Similarly, 157 genetic variants have been discovered that regulate plasma lipids including, LDL-C, HDL-C, triglycerides, and total cholesterol. A major finding from these studies is that only 15 of the 50 genetic variants for CAD act through known risk factors. Hence, the pathogenesis of CAD in addition to cholesterol and other known risk factors is due to various other factors, many of which remain unknown. Secondly, genes regulating the plasma triglyceride levels are strongly associated with the pathogenesis of CAD. Thirdly, Mendelian randomization studies show no protection from genes that increase plasma HDL cholesterol. This is contrary to current opinion. These genetic risk variants have provided new targets for the development of novel therapies to prevent CAD. Already a new and potent drug has been developed targeting PCSK9, which is in phase 3 clinical trials and shows great efficacy and safety for prevention of CAD. The 21st century is looking very bright for the prevention of CAD.

Endogenous Production of Long-Chain Polyunsaturated Fatty Acids and Metabolic Disease Risk

Long chain polyunsaturated fatty acids (PUFAs) are important structural components of cellular membranes and are converted into eicosanoids which serve various biological roles. The most common dietary n-6 and n-3 PUFAs are linoleic acid and α-linoleic acid, respectively. These 18-carbon chain fatty acids undergo a series of desaturation and elongation steps to become the 20-carbon fatty acids arachidonic acid and eicosapentaenoic acid, respectively. Evidence from genome wide association studies has consistently demonstrated that plasma and tissue levels of the n-6 long-chain PUFA arachidonic acid and to a lesser extent the n-3 long-chain PUFA eicosapentaenoic acid, are strongly influenced by variation in fatty acid desaturase-1,-2, and elongation of very long chain fatty acid genes. Studies of functional variants in these genes, as well as studies in which desaturase activity has been indirectly estimated by fatty acid product-to -precursor ratios, have suggested that endogenous capacity to synthesize long-chain PUFAs may be associated with metabolic diseases such as diabetes mellitus. Interventional studies are starting to tease out the complicated relationship between dietary intakes of specific fatty acids, variation in desaturase and elongase genes and tissue levels of long chain PUFAs. Thus future studies of dietary PUFA interventions designed to reduce inflammatory and metabolic diseases will need to carefully consider how an individual's genetically-determined endogenous long-chain PUFA synthesis capacity might modify therapeutic response.

Using multivariable Mendelian randomization to disentangle the causal effects of lipid fractions

BACKGROUND

Previous Mendelian randomization studies have suggested that, while low-density lipoprotein cholesterol (LDL-c) and triglycerides are causally implicated in coronary artery disease (CAD) risk, high-density lipoprotein cholesterol (HDL-c) may not be, with causal effect estimates compatible with the null.

PRINCIPAL FINDINGS

The causal effects of these three lipid fractions can be better identified using the extended methods of 'multivariable Mendelian randomization'. We employ this approach using published data on 185 lipid-related genetic variants and their associations with lipid fractions in 188,578 participants, and with CAD risk in 22,233 cases and 64,762 controls. Our results suggest that HDL-c may be causally protective of CAD risk, independently of the effects of LDL-c and triglycerides. Estimated causal odds ratios per standard deviation increase, based on 162 variants not having pleiotropic associations with either blood pressure or body mass index, are 1.57 (95% credible interval 1.45 to 1.70) for LDL-c, 0.91 (0.83 to 0.99, p-value  = 0.028) for HDL-c, and 1.29 (1.16 to 1.43) for triglycerides.

SIGNIFICANCE

Some interventions on HDL-c concentrations may influence risk of CAD, but to a lesser extent than interventions on LDL-c. A causal interpretation of these estimates relies on the assumption that the genetic variants do not have pleiotropic associations with risk factors on other pathways to CAD. If they do, a weaker conclusion is that genetic predictors of LDL-c, HDL-c and triglycerides each have independent associations with CAD risk.

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies

Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.

Impact of genetic variants in human scavenger receptor class B type I (SCARB1) on plasma lipid traits

BACKGROUND

Scavenger receptor class B type 1 (SCARB1) plays an important role in high-density lipoprotein cholesterol (HDL-C) metabolism in selective cholesteryl ester uptake and in free cholesterol cellular efflux.

METHODS AND RESULTS

This study aims to identify common (minor allele frequency ≥5%) and low-frequency/rare (minor allele frequency <5%) variants, using resequencing all 13 exons and exon-intron boundaries of SCARB1 in 95 individuals with extreme HDL-C levels selected from a population-based sample of 623 US non-Hispanic whites. The sequencing step identified 44 variants, of which 11 were novel with minor allele frequency <1%. Seventy-six variants (40 sequence variants, 32 common HapMap tag single nucleotide polymorphisms, and 4 relevant variants) were selected for genotyping in the total sample of 623 subjects followed by association analyses with lipid traits. Seven variants were nominally associated with apolipoprotein B (apoB; n=4) or HDL-C (n=3; P<0.05). Three variants associated with apoB remained significant after controlling false discovery rate. The most significant association was observed between rs4765615 and apoB (P=0.0059), while rs11057844 showed the strongest association with HDL-C (P=0.0035). A set of 17 rare variants (minor allele frequency ≤1%) showed significant association with apoB (P=0.0284). Haplotype analysis revealed 4 regions significantly associated with either apoB or HDL-C.

CONCLUSIONS

Our findings provide new information about the genetic role of SCARB1 in affecting plasma apoB levels in addition to its established role in HDL-C metabolism.

A rare variant in APOC3 is associated with plasma triglyceride and VLDL levels in Europeans

The analysis of rich catalogues of genetic variation from population-based sequencing provides an opportunity to screen for functional effects. Here we report a rare variant in APOC3 (rs138326449-A, minor allele frequency ~0.25% (UK)) associated with plasma triglyceride (TG) levels (-1.43 s.d. (s.e.=0.27 per minor allele (P-value=8.0 × 10(-8))) discovered in 3,202 individuals with low read-depth, whole-genome sequence. We replicate this in 12,831 participants from five additional samples of Northern and Southern European origin (-1.0 s.d. (s.e.=0.173), P-value=7.32 × 10(-9)). This is consistent with an effect between 0.5 and 1.5 mmol l(-1) dependent on population. We show that a single predicted splice donor variant is responsible for association signals and is independent of known common variants. Analyses suggest an independent relationship between rs138326449 and high-density lipoprotein (HDL) levels. This represents one of the first examples of a rare, large effect variant identified from whole-genome sequencing at a population scale.

Adiposity significantly modifies genetic risk for dyslipidemia

Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (P_Interaction = 2.87 × 10⁻⁴) and HDLc (P_Interaction = 1.05 × 10⁻³). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRS_{LDL cholesterol} × adiposity interaction was not significant. Sexual dimorphism was evident for the GRS_HDL on HDLc in obese (P_Interaction = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability.

Mendelian randomization: genetic anchors for causal inference in epidemiological studies

Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research.