High serum uric acid levels are associated with gout, atherosclerosis and cardiovascular disease. Three genes (SLC2A9, ABCG2, and SLC17A3) were reported to be involved in the regulation of uric acid levels.
Design and Methods: SNPs rs2231142 (ABCG2) and rs1165205 (SLC17A3) were genotyped in three cohorts (n = 4492) and combined with previously genotyped SNPs within SLC2A9 (rs6855911, rs7442295, rs6449213, rs12510549).
Each copy of the minor allele decreased uric acid levels by 0.30–0.38 mg/dL for SLC2A9 (p values: 10−20–10−36) and increased levels by 0.34 mg/dL for ABCG2 (p = 1.1×10−16). SLC17A3 influenced uric acid levels only modestly. Together the SNPs showed graded associations with uric acid levels of 0.111 mg/dL per risk allele (p = 3.8×10−42). In addition, we observed a sex-specific interaction of age with the association of SLC2A9 SNPs with uric acid levels, where increasing age strengthened the association of SNPs in women and decreased the association in men.
Genetic variants within SLC2A9, ABCG2 and SLC17A3 show highly significant associations with uric acid levels, and for SNPs within SLC2A9 this association is strongly modified by age and sex.
Epidemiology; Genetics; Uric acid; Copy number variation; Sex-specific effect; Genetic risk score
Two recent genome-wide association studies identified the liver-expressed transmembrane protein adiponutrin to be associated with liver-related phenotypes such as nonalcoholic fatty liver disease and liver function enzymes. These associations were not uniformly reported for various ethnicities. The aim of this study was to investigate a common nonsynonymous variant within adiponutrin (rs738409, exon 3) with parameters of liver function in three independent West-Eurasian study populations including a total of 4290 participants.
The study was performed in 1) the population-based Bruneck Study (n=783), 2) the SAPHIR Study from Austria based on a healthy working population (n=1705), and the Utah Obesity Case-Control Study including a group of 1019 severely obese individuals (average BMI 46.0 kg/m2) and 783 controls from the same geographical region of Utah. Liver enzymes measured were alanine-aminotransferase (ALT), aspartate-aminotransferase (AST) and gamma-glutamyl transferase (GGT).
Results and Discussion
We found a strong recessive association of this polymorphism with age- and gender-adjusted ALT and AST levels: being homozygous for the minor allele resulted in a highly significant increase of ALT levels of 3.53 U/L (p=1.86×10−9) and of AST levels of 2.07 U/L (p=9.58×10−6), respectively. The associations were consistently found in all three study populations. In conclusion, the highly significant associations of this transversion polymorphism within the adiponutrin gene with increased ALT and AST levels support a role for adiponutrin as a susceptibility gene for hepatic dysfunction.
PNPLA3; rs738409; genetic association; hepatic dysfunction
Candidate gene association studies for peripheral artery disease (PAD), including subclinical disease assessed with the ankle-brachial index (ABI), have been limited by the modest number of genes examined. We conducted a two stage meta-analysis of ~50,000 SNPs across ~2100 candidate genes to identify genetic variants for ABI.
Methods and results
We studied subjects of European ancestry from 8 studies (n = 21,547, 55% women, mean age 44–73 years) and African American ancestry from 5 studies (n = 7267, 60% women, mean age 41–73 years) involved in the candidate gene association resource (CARe) consortium. In each ethnic group, additive genetic models were used (with each additional copy of the minor allele corresponding to the given beta) to test each SNP for association with continuous ABI (excluding ABI > 1.40) and PAD (defined as ABI < 0.90) using linear or logistic regression with adjustment for known PAD risk factors and population stratification. We then conducted a fixed-effects inverse-variance weighted meta-analyses considering a p < 2 × 10−6 to denote statistical significance.
In the European ancestry discovery meta-analyses, rs2171209 in SYTL3 (β = −0.007, p = 6.02 × 10−7) and rs290481 in TCF7L2 (β = −0.008, p = 7.01 × 10−7) were significantly associated with ABI. None of the SNP associations for PAD were significant, though a SNP in CYP2B6 (p = 4.99 × 10−5) was among the strongest associations. These 3 genes are linked to key PAD risk factors (lipoprotein(a), type 2 diabetes, and smoking behavior, respectively). We sought replication in 6 population-based and 3 clinical samples (n = 15,440) for rs290481 and rs2171209. However, in the replication stage (rs2171209, p = 0.75; rs290481, p = 0.19) and in the combined discovery and replication analysis the SNP–ABI associations were no longer significant (rs2171209, p = 1.14 × 10−3; rs290481, p = 8.88 × 10−5). In African Americans, none of the SNP associations for ABI or PAD achieved an experiment-wide level of significance.
Genetic determinants of ABI and PAD remain elusive. Follow-up of these preliminary findings may uncover important biology given the known gene-risk factor associations. New and more powerful approaches to PAD gene discovery are warranted.
Ankle brachial index; Peripheral artery disease; Genetics; Candidate gene array; Meta-analysis; Ethnicity
Smoking is a leading global cause of disease and mortality1. We performed a genomewide meta-analytic association study of smoking-related behavioral traits in a total sample of 41,150 individuals drawn from 20 disease, population, and control cohorts. Our analysis confirmed an effect on smoking quantity (SQ) at a locus on 15q25 (P=9.45e-19) that includes three genes encoding neuronal nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, CHRNB4). We used data from the 1000 Genomes project to investigate the region using imputation, which allowed analysis of virtually all common variants in the region and offered a five-fold increase in coverage over the HapMap. This increased the spectrum of potentially causal single nucleotide polymorphisms (SNPs), which included a novel SNP that showed the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.
Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.
Methods and Results
Continuous ABI and PAD (ABI≤0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ~2.5 million SNPs in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed-effects inverse variance weighted meta-analyses. There were a total of 41,692 participants of European ancestry (~60% women, mean ABI 1.02 to 1.19), including 3,409 participants with PAD and with GWAS data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (β= −0.006, p=2.46x10−8). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16,717). The association for rs10757269 strengthened in the combined discovery and replication analysis (p=2.65x10−9). No other SNP associations for ABI or PAD achieved genome-wide significance. However, two previously reported candidate genes for PAD and one SNP associated with coronary artery disease (CAD) were associated with ABI : DAB21P (rs13290547, p=3.6x10−5); CYBA (rs3794624, p=6.3x10−5); and rs1122608 (LDLR, p=0.0026).
GWAS in more than 40,000 individuals identified one genome-wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for CAD are associated with ABI.
cohort study; genetic association; genome-wide association study; meta-analysis; peripheral vascular disease
The late endosomal LAMTOR complex serves as a convergence point for both the RAF/MEK/ERK and the PI3K/AKT/mTOR pathways. Interestingly, both of these signalling cascades play a significant role in the aetiology of breast cancer. Our aim was to address the possible role of genetic polymorphisms in LAMTOR2 and LAMTOR3 as genetic risk factors for breast cancer.
We sequenced the exons and exon–intron boundaries of LAMTOR2 (p14) and LAMTOR3 (MP1) in 50 prospectively collected pairs of cancerous tissue and blood samples from breast cancer patients and compared their genetic variability. We found one single nucleotide polymorphism (SNP) in LAMTOR2 (rs7541) and two SNPs in LAMTOR3 (rs2298735 and rs148972953) in both tumour and blood samples, but no somatic mutations in cancerous tissues. In addition, we genotyped all three SNPs in 296 samples from the Risk Prediction of Breast Cancer Metastasis Study and found evidence of a genetic association between rs148972953 and oestrogen (ER) and progesterone receptor negative status (PR) (ER: OR = 3.60 (1.15–11.28); PR: OR = 4.27 (1.43–12.72)). However, when we additionally genotyped rs148972953 in the MARIE study including 2,715 breast cancer cases and 5,216 controls, we observed neither a difference in genotype frequencies between patients and controls nor was the SNP associated with ER or PR. Finally, all three SNPs were equally frequent in breast cancer samples and female participants (n = 640) of the population-based SAPHIR Study.
The identified polymorphisms in LAMTOR2 and LAMTOR3 do not seem to play a relevant role in breast cancer. Our work does not exclude a role of other not yet identified SNPs or that the here annotated polymorphism may in fact play a relevant role in other diseases. Our results underscore the importance of replication in association studies.
Adiponectin serum concentrations are an important biomarker in cardiovascular epidemiology with heritability etimates of 30–70%. However, known genetic variants in the adiponectin gene locus (ADIPOQ) account for only 2%–8% of its variance. As transcription factors are thought to play an under-acknowledged role in carrying functional variants, we hypothesized that genetic polymorphisms in genes coding for the main transcription factors for the ADIPOQ promoter influence adiponectin levels. Single nucleotide polymorphisms (SNPs) at these genes were selected based on the haplotype block structure and previously published evidence to be associated with adiponectin levels. We performed association analyses of the 24 selected SNPs at forkhead box O1 (FOXO1), sterol-regulatory-element-binding transcription factor 1 (SREBF1), sirtuin 1 (SIRT1), peroxisome-proliferator-activated receptor gamma (PPARG) and transcription factor activating enhancer binding protein 2 beta (TFAP2B) gene loci with adiponectin levels in three different European cohorts: SAPHIR (n = 1742), KORA F3 (n = 1636) and CoLaus (n = 5355). In each study population, the association of SNPs with adiponectin levels on log-scale was tested using linear regression adjusted for age, sex and body mass index, applying both an additive and a recessive genetic model. A pooled effect size was obtained by meta-analysis assuming a fixed effects model. We applied a significance threshold of 0.0033 accounting for the multiple testing situation. A significant association was only found for variants within SREBF1 applying an additive genetic model (smallest p-value for rs1889018 on log(adiponectin) = 0.002, β on original scale = −0.217 µg/ml), explaining ∼0.4% of variation of adiponectin levels. Recessive genetic models or haplotype analyses of the FOXO1, SREBF1, SIRT1, TFAPB2B genes or sex-stratified analyses did not reveal additional information on the regulation of adiponectin levels. The role of genetic variations at the SREBF1 gene in regulating adiponectin needs further investigation by functional studies.
Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors.
rare variants; LASSO; machine learning; random forests; logic regression; binary trees; Poisson regression; ISIS; classification trees; meta-analysis; extreme sampling
Iron-refractory iron deficiency anaemia (IRIDA) is a rare disorder which was linked to mutations in two genes (SLC11A2 and TMPRSS6). Common polymorphisms within these genes were associated with serum iron levels. We identified a family of Serbian origin with asymptomatic non-consanguineous parents with three of four children presenting with IRIDA not responding to oral but to intravenous iron supplementation. After excluding all known causes responsible for iron deficiency anaemia we searched for mutations in SLC11A2 and TMPRSS6 that could explain the severe anaemia in these children.
We sequenced the exons and exon–intron boundaries of SLC11A2 and TMPRSS6 in all six family members. Thereby, we found seven known and fairly common SNPs, but no new mutation. We then genotyped these seven SNPs in the population-based SAPHIR study (n = 1,726) and performed genetic association analysis on iron and ferritin levels. Only two SNPs, which were top-hits from recent GWAS on iron and ferritin, exhibited an effect on iron and ferritin levels in SAPHIR. Six SAPHIR participants carrying the same TMPRSS6 genotypes and haplotype-pairs as one anaemic son showed lower ferritin and iron levels than the average. One individual exhibiting the joint SLC11A2/TMPRSS6 profile of the anaemic son had iron and ferritin levels lying below the 5th percentile of the population's iron and ferritin level distribution. We then checked the genotype constellations in the Nijmegen Biomedical Study (n = 1,832), but the profile of the anaemic son did not occur in this population.
We cannot exclude a gene-gene interaction between SLC11A2 and TMPRSS6, but we can also not confirm it. As in this case candidate gene sequencing did not reveal causative rare mutations, the samples will be subjected to whole exome sequencing.
The common disease/rare variant hypothesis predicts that rare variants with large effects will have a strong impact on corresponding phenotypes. Therefore it is assumed that rare functional variants are enriched in the extremes of the phenotype distribution. In this analysis of the Genetic Analysis Workshop 17 data set, my aim is to detect genes with rare variants that are associated with quantitative traits using two general approaches: analyzing the association with the complete distribution of values by means of linear regression and using statistical tests based on the tails of the distribution (bottom 10% of values versus top 10%). Three methods are used for this extreme phenotype approach: Fisher’s exact test, weighted-sum method, and beta method. Rare variants were collapsed on the gene level. Linear regression including all values provided the highest power to detect rare variants. Of the three methods used in the extreme phenotype approach, the beta method performed best. Furthermore, the sample size was enriched in this approach by adding additional samples with extreme phenotype values. Doubling the sample size using this approach, which corresponds to only 40% of sample size of the original continuous trait, yielded a comparable or even higher power than linear regression. If samples are selected primarily for sequencing, enriching the analysis by gathering a greater proportion of individuals with extreme values in the phenotype of interest rather than in the general population leads to a higher power to detect rare variants compared to analyzing a population-based sample with equivalent sample size.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene–environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10−9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
Circulating serum lipids contribute greatly to the global health by affecting the risk for cardiovascular diseases. Serum lipid levels are partly inherited, and already 95 loci affecting high- and low-density lipoprotein cholesterol, total cholesterol, and triglycerides have been found. Serum lipids are also known to be affected by multiple epidemiological risk factors like body composition, lifestyle, and sex. It has been hypothesized that there are loci modifying the effects between risk factors and serum lipids, but to date only candidate gene studies for interactions have been reported. We conducted a genome-wide screen with meta-analysis approach to identify loci having interactions with epidemiological risk factors on serum lipids with over 30,000 population-based samples. When combining results from our initial datasets and 8 additional replication cohorts (maximum N = 17,102), we found a genome-wide significant locus in chromosome 4p15 with a joint P-value of 4.79×10−9 modifying the effect of waist-to-hip ratio on total cholesterol. In the area surrounding this genetic variant, there were two genes having association between the genotypes and the gene expression in adipose tissue, and we also found enrichment of association in genes belonging to lipid metabolism related functions.
Improved glycemic control reduces complications in patients with diabetes mellitus (DM). However, it is discussed controversially whether patients with diabetes mellitus and end-stage renal disease benefit from strict glycemic control.
We followed 78 patients with DM initiating dialysis treatment of the region of Vorarlberg in a prospective cohort study applying a time-dependent Cox regression analysis using all measured laboratory values for up to more than seven years. This resulted in 880 HbA1c measurements (with one measurement every 3.16 patient months on average) during the entire observation period. Non-linear P-splines were used to allow flexible modeling of the association with mortality and cardiovascular disease (CVD) events.
We observed a decreased mortality risk with increasing HbA1c values (HR = 0.72 per 1% increase, p = 0.024). Adjustment for age and sex and additional adjustment for other CVD risk factors only slightly attenuated the association (HR = 0.71, p = 0.044). A non-linear P-spline showed that the association did not follow a fully linear pattern with a highly significant non-linear component (p = 0.001) with an increased risk of all-cause mortality for HbA1c values up to 6–7%. Causes of death were associated with HbA1c values. The risk for CVD events, however, increased with increasing HbA1c values (HR = 1.24 per 1% increase, p = 0.048) but vanished after extended adjustments.
This study considered the entire information collected on HbA1c over a period of more than seven years. Besides the methodological advantages our data indicate a significant inverse association between HbA1c levels and all-cause mortality. However, for CVD events no significant association could be found.
High levels of the plasma peptides mid-regional pro-adrenomedullin (MR-proADM) and mid-regional pro-atrial natriuretic peptide (MR-proANP) are associated with clinical outcomes in the general population. Data in patients with chronic kidney disease are sparse. We therefore investigated the association of MR-proANP and MR-proADM levels with all-cause and cardiovascular (CV) mortality, CV events and peripheral arterial disease in 201 incident dialysis patients of the INVOR-Study prospectively followed for a period of up to more than 7 years. The overall mortality rate was 43%, thereof 43% due to CV events. Both baseline MR-proANP and MR-proADM were associated with higher risk of all-cause (HR = 1.44, p = 0.001 and HR = 1.32, p = 0.002, respectively) and CV mortality (HR = 1.75, p<0.001 and HR = 1.41, p = 0.007, respectively) after adjustment for age, sex, previous CV events, diabetes mellitus and time-dependent type of renal replacement therapy. We then stratified patients in high risk (both peptides in the upper tertile), intermediate risk (only one of the two peptides in the upper tertile) and low risk (none in the upper tertile). Although demographic, clinical and laboratory variables were similar among the intermediate and high risk group, to be with both parameters in the upper tertile was associated with a 3-fold higher risk for all-cause (HR = 2.87, p<0.001) and CV mortality (HR = 3.58, p = 0.001). In summary, among incident dialysis patients MR-proANP and MR-proADM were shown to be associated with all-cause and CV mortality, with the highest risk when both parameters were in the upper tertiles.
Recent studies demonstrated a strong influence of rare genetic variants on several lipid-related traits. However, their impact on free fatty acid (FFA) plasma concentrations, as well as the role of rare variants in a general population, has not yet been thoroughly addressed. The adipose triglyceride lipase (ATGL) is encoded by the PNPLA2 gene and catalyzes the rate-limiting step of lipolysis. It represents a prominent candidate gene affecting FFA concentrations. We therefore screened the full genomic region of ATGL for mutations in 1,473 randomly selected individuals from the SAPHIR (Salzburg Atherosclerosis Prevention program in subjects at High Individual Risk) Study using a combined Ecotilling and sequencing approach and functionally investigated all detected protein variants by in-vitro studies. We observed 55 novel mostly rare genetic variants in this general population sample. Biochemical evaluation of all non-synonymous variants demonstrated the presence of several mutated but mostly still functional ATGL alleles with largely varying residual lipolytic activity. About one-quarter (3 out of 13) of the investigated variants presented a marked decrease or total loss of catalytic function. Genetic association studies using both continuous and dichotomous approaches showed a shift towards lower plasma FFA concentrations for rare variant carriers and an accumulation of variants in the lower 10%-quantile of the FFA distribution. However, the generally rather small effects suggest either only a secondary role of rare ATGL variants on the FFA levels in the SAPHIR population or a recessive action of ATGL variants. In contrast to these rather small effects, we describe here also the first patient with “neutral lipid storage disease with myopathy” (NLSDM) with a point mutation in the catalytic dyad, but otherwise intact protein.
The nature of the genetic variation underlying common traits is not yet completely understood. Recently, there has been a shift in the genetic research focus towards the elucidation of the influence of rare variants, which are thought to exert a strong impact on common traits. Circulating free fatty acids are immediate products of the triglyceride breakdown and represent a yet poorly addressed phenotype to study the impact of rare variants on lipolysis. Since ATGL (encoded by the PNPLA2 gene) controls the rate limiting step of lipolysis, we screened its whole gene region in 1,473 healthy individuals and found that 1 out of 13 individuals indeed carried at least one rare mutation. Biochemical investigations showed that, even in a healthy population, several missense variants lead to an impaired catalytic activity and 1 variant even produced a completely inactive protein. However, subsequent association studies revealed only small effects on the free fatty acids levels in the population. This suggests an only secondary role of rare ATGL variants on free fatty acids levels. More generally, we conclude that even in a healthy population pronounced allelic heterogeneity due to the presence of several rare variants may be common.
Adiponutrin (PNPLA3) is a predominantly liver-expressed transmembrane protein with phospholipase activity that is regulated by fasting and feeding. Recent genome-wide association studies identified PNPLA3 to be associated with hepatic fat content and liver function, thus pointing to a possible involvement in the hepatic lipoprotein metabolism. The aim of this study was to examine the association between two common variants in the adiponutrin gene and parameters of lipoprotein metabolism in 23 274 participants from eight independent West-Eurasian study populations including six population-based studies [Bruneck (n = 800), KORA S3/F3 (n = 1644), KORA S4/F4 (n = 1814), CoLaus (n = 5435), SHIP (n = 4012), Rotterdam (n = 5967)], the SAPHIR Study as a healthy working population (n = 1738) and the Utah Obesity Case-Control Study including a group of 1037 severely obese individuals (average BMI 46 kg/m2) and 827 controls from the same geographical region of Utah. We observed a strong additive association of a common non-synonymous variant within adiponutrin (rs738409) with age-, gender-, and alanine-aminotransferase-adjusted lipoprotein concentrations: each copy of the minor allele decreased levels of total cholesterol on average by 2.43 mg/dl (P = 8.87 × 10−7), non-HDL cholesterol levels by 2.35 mg/dl (P = 2.27 × 10−6) and LDL cholesterol levels by 1.48 mg/dl (P = 7.99 × 10−4). These associations remained significant after correction for multiple testing. We did not observe clear evidence for associations with HDL cholesterol or triglyceride concentrations. In conclusion, our study suggests that adiponutrin is involved in the metabolism of apoB-containing lipoproteins.
Adiponectin (APM1, ACDC) is an adipocyte-derived protein with downregulated expression in obesity and insulin-resistant states. Several potentially regulatory single nucleotide polymorphisms (SNPs) within the APM1 gene promoter region have been associated with circulating adiponectin levels. None of them have been functionally characterized in adiponectin-expressing cells. Hence, we investigated three SNPs (rs16861194, rs17300539, and rs266729) for their influence on adiponectin promoter activity and their association with circulating adiponectin levels.
RESEARCH DESIGN AND METHODS
Basal and rosiglitazone-induced promoter activity of different SNP combinations (haplotypes) was analyzed in 3T3-L1 adipocytes using luciferase reporter gene assays and DNA binding studies comparing all possible APM1 haplotypes. This functional approach was complemented with analysis of epidemiological population-based data of 1,692 participants of the MONICA/KORA S123 cohort and 696 participants from the KORA S4 cohort for SNP and haplotype association with circulating adiponectin levels.
Major to minor allele replacements of the three SNPs revealed significant effects on promoter activity in luciferase assays. Particularly, a minor variant in rs16861194 resulted in reduced basal and rosiglitazone-induced promoter activity and hypoadiponectinemia in the epidemiological datasets. The haplotype with the minor allele in all three SNPs showed a complete loss of promoter activity, and no subject carried this haplotype in either of the epidemiological samples (combined P value for statistically significant difference from a random sample was 0.006).
Our results clearly demonstrate that promoter variants associated with hypoadiponectinemia in humans substantially affect adiponectin promoter activity in adipocytes. Our combination of functional experiments with epidemiological data overcomes the drawback of each approach alone.
Previously, estimation of genotype misclassification of single nucleotide polymorphisms (SNPs) as encountered in epidemiologic practice and involving thousands of subjects was lacking. The authors collected representative data on approximately 14,000 subjects from 8 studies and 646,558 genotypes assessed in 2005 by means of matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Overall discordance among 57,805 double genotypes from routine quality control was 0.36%. Fitting different misclassification models by maximum likelihood assuming identical misclassification for all SNPs, the estimated misclassification probabilities ranged from 0.0000 to 0.0035. When applying the misclassification simulation and extrapolation (MC-SIMEX) method for the first time to genetic data to account for the misclassification in a reanalysis of adiponectin-encoding (APM1) gene SNP associations with plasma adiponectin in 1,770 subjects, the authors found no impact of this small error on association estimates but increased estimates for a more substantial error. This study is the first to provide large-scale epidemiologic data on SNP genotype misclassification. The estimated misclassification in this example was small and negligible for association estimates, which is reassuring and essential for detecting SNP associations. In situations with more substantial error, the presented approach using duplicate genotyping and the MC-SIMEX method is practical and helpful for quantifying the genotyping error and its impact.
bias (epidemiology); genetics; genotype; likelihood functions; polymorphism, single nucleotide
Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10−8): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×10−11) and MSRA (WC, P = 8.9×10−9). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×10−8). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
Here, we describe a meta-analysis of genome-wide association data from 38,580 individuals, followed by large-scale replication (in up to 70,689 individuals) designed to uncover variants influencing anthropometric measures of central obesity and fat distribution, namely waist circumference (WC) and waist–hip ratio (WHR). This work complements parallel efforts that have been successful in defining variants impacting overall adiposity and focuses on the visceral fat accumulation which has particularly strong relationships to metabolic and cardiovascular disease. Our analyses have identified two loci (TFAP2B and MSRA) associated with WC, and a further locus, near LYPLAL1, which shows gender-specific relationships with WHR (all to levels of genome-wide significance). These loci vary in the strength of their associations with overall adiposity, and LYPLAL1 in particular appears to have a specific effect on patterns of fat distribution. All in all, these three loci provide novel insights into human physiology and the development of obesity.
Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.
Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. The regulation of serum uric acid levels is under a strong genetic control. This study describes the first meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent. We show that common DNA variants at nine different loci are associated with uric acid concentrations, five of which are novel. These variants are located within the genes coding for organic anion transporter 4 (SLC22A11), monocarboxylic acid transporter 9 (SLC16A9), glucokinase regulatory protein (GCKR), Carmil (LRRC16A), and near PDZ domain-containing 1 (PDZK1). Gender-specific effects are shown for variants within the recently identified genes coding for glucose transporter 9 (SLC2A9) and the ATP-binding cassette transporter (ABCG2). Based on screening of 163 metabolites, we show an association of one of the identified variants within SLC16A9 with DL-carnitine and propionyl-L-carnitine. Moreover, DL-carnitine and propionyl-L-carnitine were strongly correlated with serum UA levels, forming a triangle between SNP, metabolites and UA levels. Taken together, these associations highlight pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia.
We investigated the influence of genotyping errors on the type I error rate and empirical power of two haplotype based association methods applied to candidate regions. We compared the performance of the Mantel Statistic Using Haplotype Sharing and the haplotype frequency based score test with that of the Armitage trend test.
Our study is based on 1000 replication of simulated case-control data settings with 500 cases and 500 controls, respectively. One of the examined markers was set to be the disease locus with a simulated odds ratio of 3. Differential and non-differential genotyping errors were introduced following a misclassification model with varying mean error rates per locus in the range of 0.2% to 15.6%.
We found that the type I error rate of all three test statistics hold the nominal significance level in the presence of nondifferential genotyping errors and low error rates. For high and differential error rates, the type I error rate of all three test statistics was inflated, even when genetic markers not in Hardy-Weinberg Equilibrium were removed. The empirical power of all three association test statistics remained high at around 89% to 94% when genotyping error rates were low, but decreased to 48% to 80% for high and nondifferential genotyping error rates.
Currently realistic genotyping error rates for candidate gene analysis (mean error rate per locus of 0.2%) pose no significant problem for the type I error rate as well as the power of all three investigated test statistics.
Rare mutations of the low-density lipoprotein receptor gene (LDLR) cause familial hypercholesterolemia, which increases the risk for coronary artery disease (CAD). Less is known about the implications of common genetic variation in the LDLR gene regarding the variability of cholesterol levels and risk of CAD.
Imputed genotype data at the LDLR locus on 1 644 individuals of a population-based sample were explored for association with LDL-C level. Replication of association with LDL-C level was sought for the most significant single nucleotide polymorphism (SNP) within the LDLR gene in three European samples comprising 6 642 adults and 533 children. Association of this SNP with CAD was examined in six case-control studies involving more than 15 000 individuals.
Each copy of the minor T allele of SNP rs2228671 within LDLR (frequency 11%) was related to a decrease of LDL-C levels by 0.19 mmol/L (95% confidence interval (CI) [0.13–0.24] mmol/L, p = 1.5×10−10). This association with LDL-C was uniformly found in children, men, and women of all samples studied. In parallel, the T allele of rs2228671 was associated with a significantly lower risk of CAD (Odds Ratio per copy of the T allele: 0.82, 95% CI [0.76–0.89], p = 2.1×10−7). Adjustment for LDL-C levels by logistic regression or Mendelian Randomisation models abolished the significant association between rs2228671 with CAD completely, indicating a functional link between the genetic variant at the LDLR gene locus, change in LDL-C and risk of CAD.
A common variant at the LDLR gene locus affects LDL-C levels and, thereby, the risk for CAD.
Statistically reconstructing haplotypes from single nucleotide polymorphism (SNP) genotypes, can lead to falsely classified haplotypes. This can be an issue when interpreting haplotype association results or when selecting subjects with certain haplotypes for subsequent functional studies. It was our aim to quantify haplotype reconstruction error and to provide tools for it.
Methods and Results
By numerous simulation scenarios, we systematically investigated several error measures, including discrepancy, error rate, and R2, and introduced the sensitivity and specificity to this context. We exemplified several measures in the KORA study, a large population-based study from Southern Germany. We find that the specificity is slightly reduced only for common haplotypes, while the sensitivity was decreased for some, but not all rare haplotypes. The overall error rate was generally increasing with increasing number of loci, increasing minor allele frequency of SNPs, decreasing correlation between the alleles and increasing ambiguity.
We conclude that, with the analytical approach presented here, haplotype-specific error measures can be computed to gain insight into the haplotype uncertainty. This method provides the information, if a specific risk haplotype can be expected to be reconstructed with rather no or high misclassification and thus on the magnitude of expected bias in association estimates. We also illustrate that sensitivity and specificity separate two dimensions of the haplotype reconstruction error, which completely describe the misclassification matrix and thus provide the prerequisite for methods accounting for misclassification.