Genome-wide association study of blood pressure extremes identifies variant near UMOD associated with hypertension

Genotype imputation for African Americans using data from HapMap phase II versus 1000 genomes projects

Genotype imputation provides imputation of untyped single nucleotide polymorphisms (SNPs) that are present on a reference panel such as those from the HapMap Project. It is popular for increasing statistical power and comparing results across studies using different platforms. Imputation for African American populations is challenging because their linkage disequilibrium blocks are shorter and also because no ideal reference panel is available due to admixture. In this paper, we evaluated three imputation strategies for African Americans. The intersection strategy used a combined panel consisting of SNPs polymorphic in both CEU and YRI. The union strategy used a panel consisting of SNPs polymorphic in either CEU or YRI. The merge strategy merged results from two separate imputations, one using CEU and the other using YRI. Because recent investigators are increasingly using the data from the 1000 Genomes (1KG) Project for genotype imputation, we evaluated both 1KG-based imputations and HapMap-based imputations. We used 23,707 SNPs from chromosomes 21 and 22 on Affymetrix SNP Array 6.0 genotyped for 1,075 HyperGEN African Americans. We found that 1KG-based imputations provided a substantially larger number of variants than HapMap-based imputations, about three times as many common variants and eight times as many rare and low-frequency variants. This higher yield is expected because the 1KG panel includes more SNPs. Accuracy rates using 1KG data were slightly lower than those using HapMap data before filtering, but slightly higher after filtering. The union strategy provided the highest imputation yield with next highest accuracy. The intersection strategy provided the lowest imputation yield but the highest accuracy. The merge strategy provided the lowest imputation accuracy. We observed that SNPs polymorphic only in CEU had much lower accuracy, reducing the accuracy of the union strategy. Our findings suggest that 1KG-based imputations can facilitate discovery of significant associations for SNPs across the whole MAF spectrum. Because the 1KG Project is still under way, we expect that later versions will provide better imputation performance.

Genetic basis of blood pressure and hypertension

Blood pressure (BP) is a complex trait regulated by an intricate network of physiological pathways involving extracellular fluid volume homeostasis, cardiac contractility and vascular tone through renal, neural or endocrine systems. Untreated high BP, or hypertension (HTN), is associated with increased mortality, and thus a better understanding of the pathophysiological and genetic underpinnings of BP regulation will have a major impact on public health. However, identifying genes that contribute to BP and HTN has proved challenging. In this review we describe our current understanding of the genetic architecture of BP and HTN, which has accelerated over the past five years primarily owing to genome-wide association studies (GWAS) and the continuing progress in uncovering rare gene mutations, epigenetic markers and regulatory pathways involved in the physiology of BP. We also look ahead to future studies characterizing novel pathways that affect BP and HTN and discuss strategies for translating current findings to the clinic.

Interactions of several lipid-related gene polymorphisms and cigarette smoking on blood pressure levels

The interactions of single nucleotide polymorphisms (SNPs) and cigarette smoking on blood pressure levels are limited. The present study was undertaken to detect nine lipid-related SNPs and their interactions with cigarette smoking on blood pressure levels. Genotyping of ATP-binding cassette transporter A1 (ABCA-1) V825I, acyl-CoA:cholesterol acyltransferase-1 (ACAT-1) rs1044925, low density lipoprotein receptor (LDL-R) AvaⅡ, hepatic lipase gene (LIPC) -250G>A, endothelial lipase gene (LIPG) 584C>T, methylenetetrahydrofolate reductase (MTHFR) 677C>T, proprotein convertase subtilisin-like kexin type 9 (PCSK9) E670G, peroxisome proliferator-activated receptor delta (PPARD) +294T>C, and Scavenger receptor class B type 1 (SCARB1) rs5888 was performed in 935 nonsmokers and 845 smokers. The interactions were detected by factorial regression analysis. The frequencies of genotypes (ACAT-1 and LIPG), alleles (ABCA-1), and both genotypes and alleles (LDL-R, LIPC, PPARD and SCARB1) were different between nonsmokers and smokers (P < 0.05-0.001). The levels of pulse pressure (PP, ABCA-1), and systolic, diastolic blood pressure (SBP, DBP) and PP (LIPC) in nonsmokers were different among the genotypes (P < 0.01-0.001). The levels of SBP (ABCA-1, ACAT-1, LIPG and PCSK9), DBP (ACAT-1, LDL-R, LIPC, PCSK9 and PPARD), and PP (LIPC, LIPG, MTHFR and PCSK9) in smokers were different among the genotypes (P < 0.01-0.001). The SNPs of ABCA-1, ACAT-1 and PCSK9; ACAT-1, LDL-R, MTHFR and PCSK9; and ABCA-1, LIPC, PCSK9 and PPARD were shown interactions with cigarette smoking to influence SBP, DBP and PP levels (P < 0.05-0.001); respectively. The differences in blood pressure levels between the nonsmokers and smokers might partly result from different interactions of several SNPs and cigarette smoking.

Between candidate genes and whole genomes: time for alternative approaches in blood pressure genetics

Blood pressure has a significant genetic component, but less than 3% of the observed variance has been attributed to genetic variants identified to date. Candidate gene studies of rare, monogenic hypertensive syndromes have conclusively implicated several genes altering renal sodium balance, and studies of essential hypertension have inconsistently implicated over 50 genes in pathways affecting renal sodium balance and other functions. Genome-wide linkage scans have replicated numerous quantitative trait loci throughout the genome, and over 50 single nucleotide polymorphisms (SNPs) have been replicated in multiple genome-wide association studies. These studies provide considerable evidence that epistasis and other interactions play a role in the genetic architecture of blood pressure regulation, but candidate gene studies have limited scope to test for epistasis, and genome-wide studies have low power for both main effects and interactions. This review summarizes the genetic findings to date for blood pressure, and it proposes focused, pathway-based approaches involving epistasis, gene-environment interactions, and next-generation sequencing to further the genetic dissection of blood pressure and hypertension.

Genetics and hypertension: is it time to change my practice?

Recent advances in genotyping technology and in particular a number of large-scale genome-wide association studies have helped to unravel the genetic basis of hypertension. Although our knowledge is still far from being complete it is important to ask how genetic findings could be translated to clinical practice. In a first step we summarize the strategies to dissect the genetics of hypertension from candidate gene studies to genome-wide association studies and recent sequencing experiments. The greatest hope in this context is the development of new drugs that are based on newly discovered pathophysiological principles. We describe examples where significant therapeutic effects are achieved with agents targeting pathways that contribute only small amounts to the genetic variability of a phenotype. There are good reasons to believe that new drugs will be developed based on genetic data in hypertension. We also highlight the potential for pharmacogenetics and risk stratification. The former is not currently supported by a larger body of evidence, but well designed studies are under way. The latter needs to follow the same principles for evaluation of other novel biomarkers of cardiovascular risk and is unlikely to influence clinical practice in the next few years.

Identification of IGF1, SLC4A4, WWOX, and SFMBT1 as hypertension susceptibility genes in Han Chinese with a genome-wide gene-based association study

Hypertension is a complex disorder with high prevalence rates all over the world. We conducted the first genome-wide gene-based association scan for hypertension in a Han Chinese population. By analyzing genome-wide single-nucleotide-polymorphism data of 400 matched pairs of young-onset hypertensive patients and normotensive controls genotyped with the Illumina HumanHap550-Duo BeadChip, 100 susceptibility genes for hypertension were identified and also validated with permutation tests. Seventeen of the 100 genes exhibited differential allelic and expression distributions between patient and control groups. These genes provided a good molecular signature for classifying hypertensive patients and normotensive controls. Among the 17 genes, IGF1, SLC4A4, WWOX, and SFMBT1 were not only identified by our gene-based association scan and gene expression analysis but were also replicated by a gene-based association analysis of the Hong Kong Hypertension Study. Moreover, cis-acting expression quantitative trait loci associated with the differentially expressed genes were found and linked to hypertension. IGF1, which encodes insulin-like growth factor 1, is associated with cardiovascular disorders, metabolic syndrome, decreased body weight/size, and changes of insulin levels in mice. SLC4A4, which encodes the electrogenic sodium bicarbonate cotransporter 1, is associated with decreased body weight/size and abnormal ion homeostasis in mice. WWOX, which encodes the WW domain-containing protein, is related to hypoglycemia and hyperphosphatemia. SFMBT1, which encodes the scm-like with four MBT domains protein 1, is a novel hypertension gene. GRB14, TMEM56 and KIAA1797 exhibited highly significant differential allelic and expressed distributions between hypertensive patients and normotensive controls. GRB14 was also found relevant to blood pressure in a previous genetic association study in East Asian populations. TMEM56 and KIAA1797 may be specific to Taiwanese populations, because they were not validated by the two replication studies. Identification of these genes enriches the collection of hypertension susceptibility genes, thereby shedding light on the etiology of hypertension in Han Chinese populations.

The stroke-prone spontaneously hypertensive rat: still a useful model for post-GWAS genetic studies?

The stroke-prone spontaneously hypertensive rat (SHRSP) is a unique genetic model of severe hypertension and cerebral stroke. SHRSP, as well as the spontaneously hypertensive rat, the parental strain of SHRSP, has made a tremendous contribution to cardiovascular research. However, the genetic mechanisms underlying hypertension and stroke in these rats have not yet been clarified. Recent studies using whole-genome sequencing and comprehensive gene expression analyses combined with classical quantitative trait loci analyses provided several candidate genes, such as Ephx2, Gstm1 and Slc34a1, which still need further evidence to define their pathological roles. Currently, genome-wide association studies can directly identify candidate genes for hypertension in the human genome. Thus, genetic studies in SHRSP and other rat models must be focused on the pathogenetic roles of 'networks of interacting genes' in hypertension, instead of searching for individual candidate genes.

Nonparametric evaluation of quantitative traits in population-based association studies when the genetic model is unknown

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

Genomewide Association Studies in Cardiovascular Disease—An Update 2011

BACKGROUND

Genomewide association studies have led to an enormous boost in the identification of susceptibility genes for cardiovascular diseases. This review aims to summarize the most important findings of recent years.

CONTENT

We have carefully reviewed the current literature (PubMed search terms: “genome wide association studies,” “genetic polymorphism,” “genetic risk factors,” “association study” in connection with the respective diseases, “risk score,” “transcriptome”).

SUMMARY

Multiple novel genetic loci for such important cardiovascular diseases as myocardial infarction, hypertension, heart failure, stroke, and hyperlipidemia have been identified. Given that many novel genetic risk factors lie within hitherto-unsuspected genes or influence gene expression, these findings have inspired discoveries of biological function. Despite these successes, however, only a fraction of the heritability for most cardiovascular diseases has been explained thus far. Forthcoming techniques such as whole-genome sequencing will be important to close the gap of missing heritability.

Genome-wide association studies of hypertension: Achievements, difficulties and strategies

Estimated from family studies, the heritability of hypertension ranges from 31% to 68%. Linkage studies and candidate gene association studies were once widely used to investigate the genetic mechanisms of hypertension. However, results from these studies could only explain 1%-2% heritability. With the technological advances and subsequently the accomplishment of the Human Genome Project, genome-wide association studies (GWA studies) have been applied to find genome-wide significant signals for many common diseases. Current GWA studies of hypertension have identified dozens of hypertension or blood pressure associated variants. However, different GWA study identified different variants and the results could hardly be replicated in other studies. Therefore, a debate took place on whether GWA studies will unlock the genetic basis of hypertension and whether we shall continue throwing millions of dollars on GWA studies. This review gives a short introduction to the history of genetic study on hypertension and summarizes the current findings for GWA studies of hypertension or blood pressure. Finally, we will discuss that debate and try to find alternative strategies and technologies that may hold a greater chance to make progress in understanding the genetic risk factors of hypertension and blood pressure regulation.

Genomewide association study using a high-density single nucleotide polymorphism array and case-control design identifies a novel essential hypertension susceptibility locus in the promoter region of endothelial NO synthase

Essential hypertension is a multifactorial disorder and is the main risk factor for renal and cardiovascular complications. The research on the genetics of hypertension has been frustrated by the small predictive value of the discovered genetic variants. The HYPERGENES Project investigated associations between genetic variants and essential hypertension pursuing a 2-stage study by recruiting cases and controls from extensively characterized cohorts recruited over many years in different European regions. The discovery phase consisted of 1865 cases and 1750 controls genotyped with 1M Illumina array. Best hits were followed up in a validation panel of 1385 cases and 1246 controls that were genotyped with a custom array of 14 055 markers. We identified a new hypertension susceptibility locus (rs3918226) in the promoter region of the endothelial NO synthase gene (odds ratio: 1.54 [95% CI: 1.37-1.73]; combined P=2.58 · 10(-13)). A meta-analysis, using other in silico/de novo genotyping data for a total of 21 714 subjects, resulted in an overall odds ratio of 1.34 (95% CI: 1.25-1.44; P=1.032 · 10(-14)). The quantitative analysis on a population-based sample revealed an effect size of 1.91 (95% CI: 0.16-3.66) for systolic and 1.40 (95% CI: 0.25-2.55) for diastolic blood pressure. We identified in silico a potential binding site for ETS transcription factors directly next to rs3918226, suggesting a potential modulation of endothelial NO synthase expression. Biological evidence links endothelial NO synthase with hypertension, because it is a critical mediator of cardiovascular homeostasis and blood pressure control via vascular tone regulation. This finding supports the hypothesis that there may be a causal genetic variation at this locus.

Blood pressure loci identified with a gene-centric array

Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

Beyond genome-wide association studies: new strategies for identifying genetic determinants of hypertension

Genetic linkage and association methods have long been the most important tools for gene identification in humans. These approaches can either be hypothesis-based (i.e., candidate-gene studies) or hypothesis-free (i.e., genome-wide studies). The first part of this review offers an overview of the latest successes in gene finding for blood pressure (BP) and essential hypertension using these DNA sequence-based discovery techniques. We further emphasize the importance of post-genome-wide association study (post-GWAS) analysis, which aims to prioritize genetic variants for functional follow-up. Whole-genome next-generation sequencing will eventually be necessary to provide a more comprehensive picture of all DNA variants affecting BP and hypertension. The second part of this review discusses promising novel approaches that move beyond the DNA sequence and aim to discover BP genes that are differentially regulated by epigenetic mechanisms, including microRNAs, histone modification, and methylation.

Top Three Pharmacogenomics and Personalized Medicine Applications at the Nexus of Renal Pathophysiology and Cardiovascular Medicine

Pharmacogenomics is a field with origins in the study of monogenic variations in drug metabolism in the 1950s. Perhaps because of these historical underpinnings, there has been an intensive investigation of 'hepatic pharmacogenes' such as CYP450s and liver drug metabolism using pharmacogenomics approaches over the past five decades. Surprisingly, kidney pathophysiology, attendant diseases and treatment outcomes have been vastly under-studied and under-theorized despite their central importance in maintenance of health, susceptibility to disease and rational personalized therapeutics. Indeed, chronic kidney disease (CKD) represents an increasing public health burden worldwide, both in developed and developing countries. Patients with CKD suffer from high cardiovascular morbidity and mortality, which is mainly attributable to cardiovascular events before reaching end-stage renal disease. In this paper, we focus our analyses on renal function before end-stage renal disease, as seen through the lens of pharmacogenomics and human genomic variation. We herein synthesize the recent evidence linking selected Very Important Pharmacogenes (VIP) to renal function, blood pressure and salt-sensitivity in humans, and ways in which these insights might inform rational personalized therapeutics. Notably, we highlight and present the rationale for three applications that we consider as important and actionable therapeutic and preventive focus areas in renal pharmacogenomics: 1) ACE inhibitors, as a confirmed application, 2) VDR agonists, as a promising application, and 3) moderate dietary salt intake, as a suggested novel application. Additionally, we emphasize the putative contributions of gene-environment interactions, discuss the implications of these findings to treat and prevent hypertension and CKD. Finally, we conclude with a strategic agenda and vision required to accelerate advances in this under-studied field of renal pharmacogenomics with vast significance for global public health.

Eicosanoids and tumor necrosis factor-alpha in the kidney

The thick ascending limb of Henle's loop (TAL) is capable of metabolizing arachidonic acid (AA) by cytochrome P450 (CYP450) and cyclooxygenase (COX) pathways and has been identified as a nephron segment that contributes to salt-sensitive hypertension. Previous studies demonstrated a prominent role for CYP450-dependent metabolism of AA to products that inhibited ion transport pathways in the TAL. However, COX-2 is constitutively expressed along all segments of the TAL and is increased in response to diverse stimuli. The ability of Tamm-Horsfall glycoprotein, a selective marker of cortical TAL (cTAL) and medullary (mTAL), to bind TNF and localize it to this nephron segment prompted studies to determine the capacity of mTAL cells to produce TNF and determine its effects on mTAL function. The colocalization of calcium-sensing receptor (CaR) and COX-2 in the TAL supports the notion that activation of CaR induces TNF-dependent COX-2 expression and PGE₂ synthesis in mTAL cells. Additional studies showed that TNF produced by mTAL cells inhibits ⁸⁶Rb uptake, an in vitro correlate of natriuresis, in an autocrine- and COX-2-dependent manner. The molecular mechanism for these effects likely includes inhibition of Na⁺-K⁺-2Cl⁻ cotransporter (NKCC2) expression and trafficking.

Genetic variants and blood pressure in a population-based cohort: the Cardiovascular Risk in Young Finns study

Clinical relevance of a genetic predisposition to elevated blood pressure was quantified during the transition from childhood to adulthood in a population-based Finnish cohort (N=2357). Blood pressure was measured at baseline in 1980 (age 3-18 years) and in follow-ups in 1983, 1986, 2001, and 2007. Thirteen single nucleotide polymorphisms associated with blood pressure were genotyped, and 3 genetic risk scores associated with systolic and diastolic blood pressures and their combination were derived for all of the participants. Effects of the genetic risk score were 0.47 mm Hg for systolic and 0.53 mm Hg for diastolic blood pressures (both P<0.01). The combination genetic risk score was associated with diastolic blood pressure from age 9 years onward (β=0.68 mm Hg; P=0.015). Replications in 1194 participants of the Bogalusa Heart Study showed essentially similar results. The participants in the highest quintile of the combination genetic risk score had a 1.82-fold risk of hypertension in adulthood (P<0.0001) compared with the lowest quintile, independent of a family history of premature hypertension. These findings show that genetic variants are associated with preclinical blood pressure traits in childhood; individuals with several susceptibility alleles have, on average, a 0.5-mm Hg higher blood pressure, and this trajectory continues from childhood to adulthood.

Uromodulin in renal transplant recipients: elevated urinary levels and bimodal association with graft failure

BACKGROUND

Urinary uromodulin (UMOD) predicts renal prognosis in native kidneys, but data are conflicting. We investigated its prognostic impact for graft failure (GF) in renal transplant recipients (RTR; n = 600).

METHODS

UMOD concentration was measured cross-sectionally in RTR at 6.0 years [2.6-11.4] post-transplant, in matched patients with native chronic kidney disease (CKD) and healthy subjects. In 59 cases, RTR allograft biopsies were reviewed.

RESULTS

During a follow-up of 5.3 years [4.5-5.7], GF had occurred in 7% of RTR. Median UMOD excretion (mg/24 h) was 20.4 in RTR, 11.6 in CKD and 5.7 in controls (p < 0.001). There was a curvilinear association between UMOD excretion and baseline renal function (p < 0.003) and death-censored GF, with 5.5, 11.5 and 4.0% of the cases in subsequent UMOD excretion tertiles, respectively (p = 0.002). On multivariate Cox regression analysis, hazard ratios for GF for the 1st and 3rd tertiles were 0.37 (p = 0.01) and 0.21 (p = 0.001), respectively. Interstitial fibrosis and tubular atrophy were more severe in the middle tertile (p = 0.007).

CONCLUSIONS

Urinary UMOD is elevated in RTR and associated with graft function, morphology and outcome in a bimodal fashion. Dissection of the disparate mechanisms of GF prediction by urinary UMOD might provide new clues for its alleged pathogenetic significance in progressive renal function loss.

The rediscovery of uromodulin (Tamm-Horsfall protein): from tubulointerstitial nephropathy to chronic kidney disease

Uromodulin (Tamm-Horsfall protein) is the most abundant protein excreted in the urine under physiological conditions. It is exclusively produced in the kidney and secreted into the urine via proteolytic cleavage. Its biological function is still not fully understood. Uromodulin has been linked to water/electrolyte balance and to kidney innate immunity. Also, studies in knockout mice demonstrated that it has a protective role against urinary tract infections and renal stone formation. Mutations in the gene encoding uromodulin lead to rare autosomal dominant diseases, collectively referred to as uromodulin-associated kidney diseases. They are characterized by progressive tubulointerstitial damage, impaired urinary concentrating ability, hyperuricemia, renal cysts, and progressive renal failure. Novel in vivo studies point at intracellular accumulation of mutant uromodulin as a key primary event in the disease pathogenesis. Recently, genome-wide association studies identified uromodulin as a risk factor for chronic kidney disease (CKD) and hypertension, and suggested that the level of uromodulin in the urine could represent a useful biomarker for the development of CKD. In this review, we summarize these recent investigations, ranging from invalidation studies in mouse to Mendelian disorders and genome-wide associations, which led to a rediscovery of uromodulin and boosted the scientific and clinical interest for this long discovered molecule.

Implications of discoveries from genome-wide association studies in current cardiovascular practice

Genome-wide association studies (GWAS) have identified several genetic variants associated with coronary heart disease (CHD), and variations in plasma lipoproteins and blood pressure (BP). Loci corresponding to CDKN2A/CDKN2B/ANRIL, MTHFD1L, CELSR2, PSRC1 and SORT1 genes have been associated with CHD, and TMEM57, DOCK7, CELSR2, APOB, ABCG5, HMGCR, TRIB1, FADS2/S3, LDLR, NCAN and TOMM40-APOE with total cholesterol. Similarly, CELSR2-PSRC1-SORT1, PCSK9, APOB, HMGCR, NCAN-CILP2-PBX4, LDLR, TOMM40-APOE, and APOC1-APOE are associated with variations in low-density lipoprotein cholesterol levels. Altogether, forty, forty three and twenty loci have been associated with high-density lipoprotein cholesterol, triglycerides and BP phenotypes, respectively. Some of these identified loci are common for all the traits, some do not map to functional genes, and some are located in genes that encode for proteins not previously known to be involved in the biological pathway of the trait. GWAS have been successful at identifying new and unexpected genetic loci common to diseases and traits, thus rapidly providing key novel insights into disease biology. Since genotype information is fixed, with minimum biological variability, it is useful in early life risk prediction. However, these variants explain only a small proportion of the observed variance of these traits. Therefore, the utility of genetic determinants in assessing risk at later stages of life has limited immediate clinical impact. The future application of genetic screening will be in identifying risk groups early in life to direct targeted preventive measures.

Urinary Proteomics for Prediction of Preeclampsia

Preeclampsia is a major determinant of fetal and maternal morbidity and mortality. We used a proteomic strategy to identify urinary biomarkers that predict preeclampsia before the onset of disease. We prospectively collected urine samples from women throughout pregnancy. Samples from gestational weeks 12 to 16 (n=45), 20 (n=50), and 28 (n=18) from women who subsequently had preeclampsia develop were matched to controls (n=86, n=49, and n=17, respectively). We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Disease-specific peptide patterns were generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. From comparison with nonpregnant controls, we defined a panel of 284 pregnancy-specific proteomic biomarkers. Subsequently, we developed a model of 50 biomarkers from specimens obtained at week 28 that was associated with future preeclampsia (classification factor in cases, 1.032±0.411 vs controls, −1.038±0.432; P <0.001). Classification factor increased markedly from week 12 to 16 to 28 in women who subsequently had preeclampsia develop (n=16; from −0.392±0.383 to 1.070±0.383; P <0.001) and decreased slightly in controls (n=16; from −0.647±0.437 to −1.024±0.433; P =0.043). Among the biomarkers are fibrinogen alpha chain, collagen alpha chain, and uromodulin fragments. The markers appear to predict preeclampsia at gestational week 28 with good confidence but not reliably at earlier time points (weeks 12–16 and 20). After prospective validation in other cohorts, these markers may contribute to better prediction, monitoring, and accurate diagnosis of preeclampsia.