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1.  Systematic identification of trans-eQTLs as putative drivers of known disease associations 
Nature genetics  2013;45(10):1238-1243.
Identifying the downstream effects of disease-associated single nucleotide polymorphisms (SNPs) is challenging: the causal gene is often unknown or it is unclear how the SNP affects the causal gene, making it difficult to design experiments that reveal functional consequences. To help overcome this problem, we performed the largest expression quantitative trait locus (eQTL) meta-analysis so far reported in non-transformed peripheral blood samples of 5,311 individuals, with replication in 2,775 individuals. We identified and replicated trans-eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Although we did not study specific patient cohorts, we identified trait-associated SNPs that affect multiple trans-genes that are known to be markedly altered in patients: for example, systemic lupus erythematosus (SLE) SNP rs49170141 altered C1QB and five type 1 interferon response genes, both hallmarks of SLE2-4. Subsequent ChIP-seq data analysis on these trans-genes implicated transcription factor IKZF1 as the causal gene at this locus, with DeepSAGE RNA-sequencing revealing that rs4917014 strongly alters 3’ UTR levels of IKZF1. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.
doi:10.1038/ng.2756
PMCID: PMC3991562  PMID: 24013639
2.  Genome-wide linkage analysis for human longevity: Genetics of Healthy Ageing Study 
Aging cell  2013;12(2):184-193.
Summary
Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in fifteen study centers of eleven European countries as part of the Genetics of Healthy Ageing (GEHA) project. In the joint linkage analyses we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD=3.47), chromosome 17q12-q22 (LOD=2.95), chromosome 19p13.3-p13.11 (LOD=3.76) and chromosome 19q13.11-q13.32 (LOD=3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1,228 unrelated nonagenarian and 1,907 geographically matched controls. Using a fixed effect meta-analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (p-value=9.6 × 10−8). By combined modeling of linkage and association we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11-q13.32 with p-value=0.02 and p-value=1.0 × 10−5, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12-q22 and 19p13.3-p13.11. Since the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.
doi:10.1111/acel.12039
PMCID: PMC3725963  PMID: 23286790
Human familial longevity; genome-wide linkage analysis; APOE gene; association analysis; nonagenarian sibling pairs
3.  A polymorphism in the protein kinase C gene PRKCB is associated with α2-adrenoceptor-mediated vasoconstriction 
Pharmacogenetics and genomics  2013;23(3):127-134.
Objectives
α2-Adrenoceptors (α2-AR) mediate both constriction and dilatation of blood vessels. There is substantial inter-individual variability in dorsal hand vein (DHV) constriction responses to α2-AR agonist activation. Genetic factors appear to contribute significantly to this variation. The present study was designed to identify genetic factors contributing to the inter-individual variability in α2-AR-mediated vascular constriction induced by the selective α2-AR agonist dexmedetomidine.
Methods
DHV constriction responses to local infusion of dexmedetomidine were assessed by measuring changes in vein diameter with a linear variable differential transformer. The outcome variable was log-transformed dexmedetomidine ED50 for constriction. A genome-wide association study (GWAS) of 433,378 single nucleotide polymorphisms (SNPs) was performed for the sensitivity of DHV responses in 64 healthy Finnish subjects. 20 SNPs were selected based on the GWAS results and their associations with the ED50 of dexmedetomidine were tested in an independent North American study population of 68 healthy individuals.
Results
In both study populations (GWAS and replication samples), the SNP rs9922316 in the gene for protein kinase C type β was consistently associated with dexmedetomidine ED50 for dorsal hand vein constriction (unadjusted p = 0.00016 for the combined population).
Conclusions
Genetic variation in protein kinase C type β may contribute to the inter-individual variation in dorsal hand vein constriction responses to α2-AR activation by the agonist dexmedetomidine.
doi:10.1097/FPC.0b013e32835d247f
PMCID: PMC3912740  PMID: 23337848
receptors, adrenergic, alpha; dorsal hand vein; GWAS; candidate genes; dexmedetomidine
4.  Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons 
PLoS Medicine  2014;11(2):e1001606.
In this study, Würtz and colleagues conducted high-throughput profiling of blood specimens in two large population-based cohorts in order to identify biomarkers for all-cause mortality and enhance risk prediction. The authors found that biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. However, further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers to guide screening and prevention.
Please see later in the article for the Editors' Summary
Background
Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts.
Methods and Findings
106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18–103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1–standard deviation increment, 95% CI 1.53–1.82, p = 5×10−31), albumin (HR 0.70, 95% CI 0.65–0.76, p = 2×10−18), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62–0.77, p = 3×10−12), and citrate (HR 1.33, 95% CI 1.21–1.45, p = 5×10−10). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001).
Conclusions
Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
A biomarker is a biological molecule found in blood, body fluids, or tissues that may signal an abnormal process, a condition, or a disease. The level of a particular biomarker may indicate a patient's risk of disease, or likely response to a treatment. For example, cholesterol levels are measured to assess the risk of heart disease. Most current biomarkers are used to test an individual's risk of developing a specific condition. There are none that accurately assess whether a person is at risk of ill health generally, or likely to die soon from a disease. Early and accurate identification of people who appear healthy but in fact have an underlying serious illness would provide valuable opportunities for preventative treatment.
While most tests measure the levels of a specific biomarker, there are some technologies that allow blood samples to be screened for a wide range of biomarkers. These include nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry. These tools have the potential to be used to screen the general population for a range of different biomarkers.
Why Was This Study Done?
Identifying new biomarkers that provide insight into the risk of death from all causes could be an important step in linking different diseases and assessing patient risk. The authors in this study screened patient samples using NMR spectroscopy for biomarkers that accurately predict the risk of death particularly amongst the general population, rather than amongst people already known to be ill.
What Did the Researchers Do and Find?
The researchers studied two large groups of people, one in Estonia and one in Finland. Both countries have set up health registries that collect and store blood samples and health records over many years. The registries include large numbers of people who are representative of the wider population.
The researchers first tested blood samples from a representative subset of the Estonian group, testing 9,842 samples in total. They looked at 106 different biomarkers in each sample using NMR spectroscopy. They also looked at the health records of this group and found that 508 people died during the follow-up period after the blood sample was taken, the majority from heart disease, cancer, and other diseases. Using statistical analysis, they looked for any links between the levels of different biomarkers in the blood and people's short-term risk of dying. They found that the levels of four biomarkers—plasma albumin, alpha-1-acid glycoprotein, very-low-density lipoprotein (VLDL) particle size, and citrate—appeared to accurately predict short-term risk of death. They repeated this study with the Finnish group, this time with 7,503 individuals (176 of whom died during the five-year follow-up period after giving a blood sample) and found similar results.
The researchers carried out further statistical analyses to take into account other known factors that might have contributed to the risk of life-threatening illness. These included factors such as age, weight, tobacco and alcohol use, cholesterol levels, and pre-existing illness, such as diabetes and cancer. The association between the four biomarkers and short-term risk of death remained the same even when controlling for these other factors.
The analysis also showed that combining the test results for all four biomarkers, to produce a biomarker score, provided a more accurate measure of risk than any of the biomarkers individually. This biomarker score also proved to be the strongest predictor of short-term risk of dying in the Estonian group. Individuals with a biomarker score in the top 20% had a risk of dying within five years that was 19 times greater than that of individuals with a score in the bottom 20% (288 versus 15 deaths).
What Do These Findings Mean?
This study suggests that there are four biomarkers in the blood—alpha-1-acid glycoprotein, albumin, VLDL particle size, and citrate—that can be measured by NMR spectroscopy to assess whether otherwise healthy people are at short-term risk of dying from heart disease, cancer, and other illnesses. However, further validation of these findings is still required, and additional studies should examine the biomarker specificity and associations in settings closer to clinical practice. The combined biomarker score appears to be a more accurate predictor of risk than tests for more commonly known risk factors. Identifying individuals who are at high risk using these biomarkers might help to target preventative medical treatments to those with the greatest need.
However, there are several limitations to this study. As an observational study, it provides evidence of only a correlation between a biomarker score and ill health. It does not identify any underlying causes. Other factors, not detectable by NMR spectroscopy, might be the true cause of serious health problems and would provide a more accurate assessment of risk. Nor does this study identify what kinds of treatment might prove successful in reducing the risks. Therefore, more research is needed to determine whether testing for these biomarkers would provide any clinical benefit.
There were also some technical limitations to the study. NMR spectroscopy does not detect as many biomarkers as mass spectrometry, which might therefore identify further biomarkers for a more accurate risk assessment. In addition, because both study groups were northern European, it is not yet known whether the results would be the same in other ethnic groups or populations with different lifestyles.
In spite of these limitations, the fact that the same four biomarkers are associated with a short-term risk of death from a variety of diseases does suggest that similar underlying mechanisms are taking place. This observation points to some potentially valuable areas of research to understand precisely what's contributing to the increased risk.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001606
The US National Institute of Environmental Health Sciences has information on biomarkers
The US Food and Drug Administration has a Biomarker Qualification Program to help researchers in identifying and evaluating new biomarkers
Further information on the Estonian Biobank is available
The Computational Medicine Research Team of the University of Oulu and the University of Bristol have a webpage that provides further information on high-throughput biomarker profiling by NMR spectroscopy
doi:10.1371/journal.pmed.1001606
PMCID: PMC3934819  PMID: 24586121
5.  Chromosome X-Wide Association Study Identifies Loci for Fasting Insulin and Height and Evidence for Incomplete Dosage Compensation 
PLoS Genetics  2014;10(2):e1004127.
The X chromosome (chrX) represents one potential source for the “missing heritability” for complex phenotypes, which thus far has remained underanalyzed in genome-wide association studies (GWAS). Here we demonstrate the benefits of including chrX in GWAS by assessing the contribution of 404,862 chrX SNPs to levels of twelve commonly studied cardiometabolic and anthropometric traits in 19,697 Finnish and Swedish individuals with replication data on 5,032 additional Finns. By using a linear mixed model, we estimate that on average 2.6% of the additive genetic variance in these twelve traits is attributable to chrX, this being in proportion to the number of SNPs in the chromosome. In a chrX-wide association analysis, we identify three novel loci: two for height (rs182838724 near FGF16/ATRX/MAGT1, joint P-value = 2.71×10−9, and rs1751138 near ITM2A, P-value = 3.03×10−10) and one for fasting insulin (rs139163435 in Xq23, P-value = 5.18×10−9). Further, we find that effect sizes for variants near ITM2A, a gene implicated in cartilage development, show evidence for a lack of dosage compensation. This observation is further supported by a sex-difference in ITM2A expression in whole blood (P-value = 0.00251), and is also in agreement with a previous report showing ITM2A escapes from X chromosome inactivation (XCI) in the majority of women. Hence, our results show one of the first links between phenotypic variation in a population sample and an XCI-escaping locus and pinpoint ITM2A as a potential contributor to the sexual dimorphism in height. In conclusion, our study provides a clear motivation for including chrX in large-scale genetic studies of complex diseases and traits.
Author Summary
The X chromosome (chrX) analyses have often been neglected in large-scale genome-wide association studies. Given that chrX contains a considerable proportion of DNA, we wanted to examine how the variation in the chromosome contributes to commonly studied phenotypes. To this end, we studied the associations of over 400,000 chrX variants with twelve complex phenotypes, such as height, in almost 25,000 Northern European individuals. Demonstrating the value of assessing chrX associations, we found that as a whole the variation in the chromosome influences the levels of many of these phenotypes and further identified three new genomic regions where the variants associate with height or fasting insulin levels. In one of these three associated regions, the region near ITM2A, we observed that there is a sex difference in the genetic effects on height in a manner consistent with a lack of dosage compensation in this locus. Further supporting this observation, ITM2A has been shown to be among those chrX genes where the X chromosome inactivation is incomplete. Identifying phenotype associations in regions like this where chrX allele dosages are not balanced between men and women can be particularly valuable in helping us to understand why some characteristics differ between sexes.
doi:10.1371/journal.pgen.1004127
PMCID: PMC3916240  PMID: 24516404
6.  High Risk Population Isolate Reveals Low Frequency Variants Predisposing to Intracranial Aneurysms 
PLoS Genetics  2014;10(1):e1004134.
3% of the population develops saccular intracranial aneurysms (sIAs), a complex trait, with a sporadic and a familial form. Subarachnoid hemorrhage from sIA (sIA-SAH) is a devastating form of stroke. Certain rare genetic variants are enriched in the Finns, a population isolate with a small founder population and bottleneck events. As the sIA-SAH incidence in Finland is >2× increased, such variants may associate with sIA in the Finnish population. We tested 9.4 million variants for association in 760 Finnish sIA patients (enriched for familial sIA), and in 2,513 matched controls with case-control status and with the number of sIAs. The most promising loci (p<5E-6) were replicated in 858 Finnish sIA patients and 4,048 controls. The frequencies and effect sizes of the replicated variants were compared to a continental European population using 717 Dutch cases and 3,004 controls. We discovered four new high-risk loci with low frequency lead variants. Three were associated with the case-control status: 2q23.3 (MAF 2.1%, OR 1.89, p 1.42×10-9); 5q31.3 (MAF 2.7%, OR 1.66, p 3.17×10-8); 6q24.2 (MAF 2.6%, OR 1.87, p 1.87×10-11) and one with the number of sIAs: 7p22.1 (MAF 3.3%, RR 1.59, p 6.08×-9). Two of the associations (5q31.3, 6q24.2) replicated in the Dutch sample. The 7p22.1 locus was strongly differentiated; the lead variant was more frequent in Finland (4.6%) than in the Netherlands (0.3%). Additionally, we replicated a previously inconclusive locus on 2q33.1 in all samples tested (OR 1.27, p 1.87×10-12). The five loci explain 2.1% of the sIA heritability in Finland, and may relate to, but not explain, the increased incidence of sIA-SAH in Finland. This study illustrates the utility of population isolates, familial enrichment, dense genotype imputation and alternate phenotyping in search for variants associated with complex diseases.
Author Summary
Genome-wide association studies (GWAS) have been extensively used to identify common genetic variants associated with complex diseases. As common genetic variants have explained only a small fraction of the heritability of most complex diseases, there is a growing interest in the role of how low frequency and rare variants contribute to the susceptibility. Low frequency variants are more often specific to populations of distinct ancestries. Saccular intracranial aneurysms (sIA) are balloon-like dilatations in the arteries on the surface of the brain. The rupture of sIA causes life-threatening intracranial bleeding. sIA is a complex disease, which is known to sometimes run in families. Here, we utilize the recent advancements in knowledge of genetic variation in different populations to examine the role of low-frequency variants in sIA disease in the isolated population of Finland where sIA related strokes are more common than in most other populations. By studying >8000 Finns we identify four low-frequency variants associated with the sIA disease. We also show that the association of two of the variants are seen in other European populations as well. Our findings demonstrate that multiple study designs are needed to uncover more comprehensively their genetic background, including population isolates.
doi:10.1371/journal.pgen.1004134
PMCID: PMC3907358  PMID: 24497844
8.  Prevalence of arrhythmia-associated gene mutations and risk of sudden cardiac death in the Finnish population 
Annals of medicine  2013;45(4):328-335.
Background
Sudden cardiac death (SCD) remains a major cause of death in Western Countries. It has a heritable component, but previous molecular studies have mainly focused on common genetic variants. We studied the prevalence, clinical phenotypes, and risk of SCD presented by ten rare mutations previously associated with arrhythmogenic right ventricular cardiomyopathy, long QT syndrome, or catecholaminergic polymorphic ventricular tachycardia.
Methods
The occurrence of ten arrhythmia-associated mutations was determined in four large prospective population cohorts (FINRISK 1992, 1997, 2002, and Health 2000, n = 28,465) and two series of forensic autopsies (The Helsinki Sudden Death Study and The Tampere Autopsy Study, n = 825). Follow-up data was collected from national registries.
Results
The ten mutations showed a combined prevalence of 79 per 10,000 individuals in Finland and six of them showed remarkable geographic clustering. Of a total of 715 SCD cases, seven (1.0%) carried one of the ten mutations assayed: three carried KCNH2 R176W, one KCNH2 L552S, two PKP2 Q59L, and one RYR2 R3570W.
Conclusions
Arrhythmia-associated mutations are prevalent in the general Finnish population but do not seem to present a major risk factor for SCD, at least during a mean of 10-year follow-up of a random adult population sample.
doi:10.3109/07853890.2013.783995
PMCID: PMC3778376  PMID: 23651034
Arrhythmia; Genetic epidemiology; Genetics; Mutation; Sudden cardiac death
9.  A COMMON VARIANT NEAR KCNJ2 GENE IS ASSOCIATED WITH T-PEAK TO T-END INTERVAL 
Background
T-peak to T-end (TPE) interval on the electrocardiogram (ECG) is a measure of myocardial dispersion of repolarization and is associated with increased risk of ventricular arrhythmias. The genetic factors affecting the TPE interval are largely unknown.
Objective
We sought to identify common genetic variants that affect the TPE-interval duration in the general population.
Methods
We performed a genome-wide association study on 1 870 individuals of Finnish origin participating in the Health 2000 Study. TPE interval was measured from T-peak to T-wave end in leads II, V2 and V5 on resting ECGs and the mean of these TPE intervals was adjusted for age, sex and Cornell voltage-duration product. We sought replication for a genome-wide significant result in the 3 745 subjects from the Framingham Heart Study.
Results
We identified a locus on 17q24 that was associated with the TPE interval. The minor allele of the common variant rs7219669 was associated with a 1.8-ms shortening of the TPE interval (P=1.1×10−10). The association was replicated in the Framingham Heart Study (−1.5 ms, P=1.3×10−4).The overall effect estimate of rs7219669 in the two studies was −1.7 ms (P=5.7×10−14). The common variant rs7219669 maps downstream of KCNJ2 gene, in which rare mutations cause congenital Long- and Short-QT syndromes.
Conclusion
The common variant rs7219669 is associated with the TPE interval and is thus a candidate to modify repolarization-related arrhythmia susceptibility in individuals carrying the major allele of this polymorphism.
doi:10.1016/j.hrthm.2012.02.019
PMCID: PMC3690340  PMID: 22342860
Electrocardiography; Repolarization; T wave; Epidemiology; Genetics; Polymorphism
10.  The Molecular Genetic Architecture of Self-Employment 
van der Loos, Matthijs J. H. M. | Rietveld, Cornelius A. | Eklund, Niina | Koellinger, Philipp D. | Rivadeneira, Fernando | Abecasis, Gonçalo R. | Ankra-Badu, Georgina A. | Baumeister, Sebastian E. | Benjamin, Daniel J. | Biffar, Reiner | Blankenberg, Stefan | Boomsma, Dorret I. | Cesarini, David | Cucca, Francesco | de Geus, Eco J. C. | Dedoussis, George | Deloukas, Panos | Dimitriou, Maria | Eiriksdottir, Guðny | Eriksson, Johan | Gieger, Christian | Gudnason, Vilmundur | Höhne, Birgit | Holle, Rolf | Hottenga, Jouke-Jan | Isaacs, Aaron | Järvelin, Marjo-Riitta | Johannesson, Magnus | Kaakinen, Marika | Kähönen, Mika | Kanoni, Stavroula | Laaksonen, Maarit A. | Lahti, Jari | Launer, Lenore J. | Lehtimäki, Terho | Loitfelder, Marisa | Magnusson, Patrik K. E. | Naitza, Silvia | Oostra, Ben A. | Perola, Markus | Petrovic, Katja | Quaye, Lydia | Raitakari, Olli | Ripatti, Samuli | Scheet, Paul | Schlessinger, David | Schmidt, Carsten O. | Schmidt, Helena | Schmidt, Reinhold | Senft, Andrea | Smith, Albert V. | Spector, Timothy D. | Surakka, Ida | Svento, Rauli | Terracciano, Antonio | Tikkanen, Emmi | van Duijn, Cornelia M. | Viikari, Jorma | Völzke, Henry | Wichmann, H. -Erich | Wild, Philipp S. | Willems, Sara M. | Willemsen, Gonneke | van Rooij, Frank J. A. | Groenen, Patrick J. F. | Uitterlinden, André G. | Hofman, Albert | Thurik, A. Roy | Cherny, Stacey
PLoS ONE  2013;8(4):e60542.
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2 = 25%, h2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
doi:10.1371/journal.pone.0060542
PMCID: PMC3617140  PMID: 23593239
11.  Genome-wide association study identifies multiple loci influencing human serum metabolite levels 
Nature genetics  2012;44(3):269-276.
Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.
doi:10.1038/ng.1073
PMCID: PMC3605033  PMID: 22286219
12.  Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways 
Scott, Robert A | Lagou, Vasiliki | Welch, Ryan P | Wheeler, Eleanor | Montasser, May E | Luan, Jian’an | Mägi, Reedik | Strawbridge, Rona J | Rehnberg, Emil | Gustafsson, Stefan | Kanoni, Stavroula | Rasmussen-Torvik, Laura J | Yengo, Loïc | Lecoeur, Cecile | Shungin, Dmitry | Sanna, Serena | Sidore, Carlo | Johnson, Paul C D | Jukema, J Wouter | Johnson, Toby | Mahajan, Anubha | Verweij, Niek | Thorleifsson, Gudmar | Hottenga, Jouke-Jan | Shah, Sonia | Smith, Albert V | Sennblad, Bengt | Gieger, Christian | Salo, Perttu | Perola, Markus | Timpson, Nicholas J | Evans, David M | Pourcain, Beate St | Wu, Ying | Andrews, Jeanette S | Hui, Jennie | Bielak, Lawrence F | Zhao, Wei | Horikoshi, Momoko | Navarro, Pau | Isaacs, Aaron | O’Connell, Jeffrey R | Stirrups, Kathleen | Vitart, Veronique | Hayward, Caroline | Esko, Tönu | Mihailov, Evelin | Fraser, Ross M | Fall, Tove | Voight, Benjamin F | Raychaudhuri, Soumya | Chen, Han | Lindgren, Cecilia M | Morris, Andrew P | Rayner, Nigel W | Robertson, Neil | Rybin, Denis | Liu, Ching-Ti | Beckmann, Jacques S | Willems, Sara M | Chines, Peter S | Jackson, Anne U | Kang, Hyun Min | Stringham, Heather M | Song, Kijoung | Tanaka, Toshiko | Peden, John F | Goel, Anuj | Hicks, Andrew A | An, Ping | Müller-Nurasyid, Martina | Franco-Cereceda, Anders | Folkersen, Lasse | Marullo, Letizia | Jansen, Hanneke | Oldehinkel, Albertine J | Bruinenberg, Marcel | Pankow, James S | North, Kari E | Forouhi, Nita G | Loos, Ruth J F | Edkins, Sarah | Varga, Tibor V | Hallmans, Göran | Oksa, Heikki | Antonella, Mulas | Nagaraja, Ramaiah | Trompet, Stella | Ford, Ian | Bakker, Stephan J L | Kong, Augustine | Kumari, Meena | Gigante, Bruna | Herder, Christian | Munroe, Patricia B | Caulfield, Mark | Antti, Jula | Mangino, Massimo | Small, Kerrin | Miljkovic, Iva | Liu, Yongmei | Atalay, Mustafa | Kiess, Wieland | James, Alan L | Rivadeneira, Fernando | Uitterlinden, Andre G | Palmer, Colin N A | Doney, Alex S F | Willemsen, Gonneke | Smit, Johannes H | Campbell, Susan | Polasek, Ozren | Bonnycastle, Lori L | Hercberg, Serge | Dimitriou, Maria | Bolton, Jennifer L | Fowkes, Gerard R | Kovacs, Peter | Lindström, Jaana | Zemunik, Tatijana | Bandinelli, Stefania | Wild, Sarah H | Basart, Hanneke V | Rathmann, Wolfgang | Grallert, Harald | Maerz, Winfried | Kleber, Marcus E | Boehm, Bernhard O | Peters, Annette | Pramstaller, Peter P | Province, Michael A | Borecki, Ingrid B | Hastie, Nicholas D | Rudan, Igor | Campbell, Harry | Watkins, Hugh | Farrall, Martin | Stumvoll, Michael | Ferrucci, Luigi | Waterworth, Dawn M | Bergman, Richard N | Collins, Francis S | Tuomilehto, Jaakko | Watanabe, Richard M | de Geus, Eco J C | Penninx, Brenda W | Hofman, Albert | Oostra, Ben A | Psaty, Bruce M | Vollenweider, Peter | Wilson, James F | Wright, Alan F | Hovingh, G Kees | Metspalu, Andres | Uusitupa, Matti | Magnusson, Patrik K E | Kyvik, Kirsten O | Kaprio, Jaakko | Price, Jackie F | Dedoussis, George V | Deloukas, Panos | Meneton, Pierre | Lind, Lars | Boehnke, Michael | Shuldiner, Alan R | van Duijn, Cornelia M | Morris, Andrew D | Toenjes, Anke | Peyser, Patricia A | Beilby, John P | Körner, Antje | Kuusisto, Johanna | Laakso, Markku | Bornstein, Stefan R | Schwarz, Peter E H | Lakka, Timo A | Rauramaa, Rainer | Adair, Linda S | Smith, George Davey | Spector, Tim D | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Gudnason, Vilmundur | Kivimaki, Mika | Hingorani, Aroon | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Boomsma, Dorret I | Stefansson, Kari | van der Harst, Pim | Dupuis, Josée | Pedersen, Nancy L | Sattar, Naveed | Harris, Tamara B | Cucca, Francesco | Ripatti, Samuli | Salomaa, Veikko | Mohlke, Karen L | Balkau, Beverley | Froguel, Philippe | Pouta, Anneli | Jarvelin, Marjo-Riitta | Wareham, Nicholas J | Bouatia-Naji, Nabila | McCarthy, Mark I | Franks, Paul W | Meigs, James B | Teslovich, Tanya M | Florez, Jose C | Langenberg, Claudia | Ingelsson, Erik | Prokopenko, Inga | Barroso, Inês
Nature genetics  2012;44(9):991-1005.
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.
doi:10.1038/ng.2385
PMCID: PMC3433394  PMID: 22885924
13.  Toward a roadmap in global biobanking for health 
European Journal of Human Genetics  2012;20(11):1105-1111.
Biobanks can have a pivotal role in elucidating disease etiology, translation, and advancing public health. However, meeting these challenges hinges on a critical shift in the way science is conducted and requires biobank harmonization. There is growing recognition that a common strategy is imperative to develop biobanking globally and effectively. To help guide this strategy, we articulate key principles, goals, and priorities underpinning a roadmap for global biobanking to accelerate health science, patient care, and public health. The need to manage and share very large amounts of data has driven innovations on many fronts. Although technological solutions are allowing biobanks to reach new levels of integration, increasingly powerful data-collection tools, analytical techniques, and the results they generate raise new ethical and legal issues and challenges, necessitating a reconsideration of previous policies, practices, and ethical norms. These manifold advances and the investments that support them are also fueling opportunities for biobanks to ultimately become integral parts of health-care systems in many countries. International harmonization to increase interoperability and sustainability are two strategic priorities for biobanking. Tackling these issues requires an environment favorably inclined toward scientific funding and equipped to address socio-ethical challenges. Cooperation and collaboration must extend beyond systems to enable the exchange of data and samples to strategic alliances between many organizations, including governmental bodies, funding agencies, public and private science enterprises, and other stakeholders, including patients. A common vision is required and we articulate the essential basis of such a vision herein.
doi:10.1038/ejhg.2012.96
PMCID: PMC3477856  PMID: 22713808
14.  Genome-Wide Screen for Metabolic Syndrome Susceptibility Loci Reveals Strong Lipid Gene Contribution but No Evidence for Common Genetic Basis for Clustering of Metabolic Syndrome Traits 
Background
Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in four Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and NMR-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis and built a genetic risk score for MetS.
Methods and Results
A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all four study samples (P=7.23×10−9 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 associated with various VLDL, TG, and HDL metabolites (P=0.024-1.88×10−5). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these associated with lipid phenotypes and none with two or more uncorrelated MetS components. A genetic risk score, calculated as the number of alleles in loci associated with individual MetS traits, was strongly associated with MetS status.
Conclusions
Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits such as hypertension and glucose intolerance.
doi:10.1161/CIRCGENETICS.111.961482
PMCID: PMC3378651  PMID: 22399527
metabolic syndrome; risk factors; genome-wide association study; meta-analysis; lipids
15.  Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis 
PLoS Genetics  2012;8(8):e1002907.
Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.
Author Summary
In this study, we aim to identify novel genetic variants for metabolism, characterize their effects on nearby genes, and show that the nearby genes are associated with metabolism and atherosclerosis. To discover new genetic variants, we use an alternative approach to traditional genome-wide association studies: we leverage the information in phenotype covariance to increase our statistical power. We identify variants at seven novel loci and then show that our top signals drive expression of nearby genes AQP9 and SERPINA1 in multiple tissues. We demonstrate that AQP9 and SERPINA1 gene expression, in turn, is associated with metabolite levels. Finally, we show that the genes are associated with atherosclerosis using mouse atherosclerotic lesion size (AQP9) as well as tissue from healthy human arteries and atherosclerotic plaques (AQP9 and SERPINA1). This study illustrates that multivariate analysis of correlated metabolites can boost power for gene discovery substantially. Further functional work will need to be performed to elucidate the biological role of SERPINA1 and AQP9 in atherosclerosis.
doi:10.1371/journal.pgen.1002907
PMCID: PMC3420921  PMID: 22916037
16.  Associations of Nicotine Intake Measures With CHRN Genes in Finnish Smokers 
Nicotine & Tobacco Research  2011;13(8):686-690.
Introduction:
Genetic effects contribute to individual differences in smoking behavior. Persistence to smoke despite known harmful health effects is mostly driven by nicotine addiction. As the physiological effects of nicotine are mediated by nicotinic acetylcholine receptors (nAChRs), we aimed at examining whether single nucleotide polymorphisms (SNPs) residing in nAChR subunit (CHRN) genes, other than CHRNA3/CHRNA5/CHRNB4 gene cluster previously showing association in our sample, are associated with smoking quantity or serum cotinine levels.
Methods:
The study sample consisted of 485 Finnish adult daily smokers (age 30–75 years, 59% men) assessed for the number of cigarettes smoked per day (CPD) and serum cotinine level. We first studied SNPs residing on selected nAChR subunit genes (CHRNA2, CHRNA4, CHRNA6/CHRNB3, CHRNA7, CHRNA9, CHRNA10, CHRNB2, CHRNG/CHRND) genotyped within a genome-wide association study for single SNP and multiple SNP associations by ordinal regression. Next, we explored individual haplotype associations using sliding window technique.
Results:
At one of the 8 loci studied, CHRNG/CHRND (chr2), single SNP (rs1190452), multiple SNP, and 2-SNP haplotype analyses (SNPs rs4973539–rs1190452) all showed statistically significant association with cotinine level. The median cotinine levels varied between the 2-SNP haplotypes from 220 ng/ml (AA haplotype) to 249 ng/ml (AG haplotype). We did not observe significant associations with CPD.
Conclusions:
These results provide further evidence that the γ−δ nAChR subunit gene region is associated with cotinine levels but not with the number of CPD, illustrating the usefulness of biomarkers in genetic analyses.
doi:10.1093/ntr/ntr059
PMCID: PMC3150688  PMID: 21498873
17.  Geographic Differences in Genetic Susceptibility to IgA Nephropathy: GWAS Replication Study and Geospatial Risk Analysis 
PLoS Genetics  2012;8(6):e1002765.
IgA nephropathy (IgAN), major cause of kidney failure worldwide, is common in Asians, moderately prevalent in Europeans, and rare in Africans. It is not known if these differences represent variation in genes, environment, or ascertainment. In a recent GWAS, we localized five IgAN susceptibility loci on Chr.6p21 (HLA-DQB1/DRB1, PSMB9/TAP1, and DPA1/DPB2 loci), Chr.1q32 (CFHR3/R1 locus), and Chr.22q12 (HORMAD2 locus). These IgAN loci are associated with risk of other immune-mediated disorders such as type I diabetes, multiple sclerosis, or inflammatory bowel disease. We tested association of these loci in eight new independent cohorts of Asian, European, and African-American ancestry (N = 4,789), followed by meta-analysis with risk-score modeling in 12 cohorts (N = 10,755) and geospatial analysis in 85 world populations. Four susceptibility loci robustly replicated and all five loci were genome-wide significant in the combined cohort (P = 5×10−32–3×10−10), with heterogeneity detected only at the PSMB9/TAP1 locus (I2 = 0.60). Conditional analyses identified two new independent risk alleles within the HLA-DQB1/DRB1 locus, defining multiple risk and protective haplotypes within this interval. We also detected a significant genetic interaction, whereby the odds ratio for the HORMAD2 protective allele was reversed in homozygotes for a CFHR3/R1 deletion (P = 2.5×10−4). A seven–SNP genetic risk score, which explained 4.7% of overall IgAN risk, increased sharply with Eastward and Northward distance from Africa (r = 0.30, P = 3×10−128). This model paralleled the known East–West gradient in disease risk. Moreover, the prediction of a South–North axis was confirmed by registry data showing that the prevalence of IgAN–attributable kidney failure is increased in Northern Europe, similar to multiple sclerosis and type I diabetes. Variation at IgAN susceptibility loci correlates with differences in disease prevalence among world populations. These findings inform genetic, biological, and epidemiological investigations of IgAN and permit cross-comparison with other complex traits that share genetic risk loci and geographic patterns with IgAN.
Author Summary
IgA nephropathy (IgAN) is the most common cause of kidney failure in Asia, has lower prevalence in Europe, and is very infrequent among populations of African ancestry. A long-standing question in the field is whether these differences represent variation in genes, environment, or ascertainment. In a recent genome-wide association study of 5,966 individuals, we identified five susceptibility loci for this trait. In this paper, we study the largest IgAN case-control cohort reported to date, composed of 10,775 individuals of European, Asian, and African-American ancestry. We confirm that all five loci are significant contributors to disease risk across this multi-ethnic cohort. In addition, we identify two novel independent susceptibility alleles within the HLA-DQB1/DRB1 locus and a new genetic interaction between loci on Chr.1p36 and Chr.22q22. We develop a seven–SNP genetic risk score that explains nearly 5% of variation in disease risk. In geospatial analysis of 85 world populations, the genetic risk score closely parallels worldwide patterns of disease prevalence. The genetic risk score also predicts an unsuspected Northward risk gradient in Europe. This genetic prediction is verified by examination of registry data demonstrating, similarly to other immune-mediated diseases such as multiple sclerosis and type I diabetes, a previously unrecognized increase in IgAN–attributable kidney failure in Northern European countries.
doi:10.1371/journal.pgen.1002765
PMCID: PMC3380840  PMID: 22737082
18.  Common Genetic Variants, QT Interval and Sudden Cardiac Death in a Finnish Population-Based Study 
Background
Although sudden cardiac death (SCD) is heritable, its genetic underpinnings are poorly characterized. The QT interval appears to have a graded relationship to SCD and 35–45% of its variation is heritable. We examined the relationship among recently reported common genetic variants, QT interval and SCD.
Methods and Results
We genotyped 15 common (minor allele frequency >1%) candidate SNPs, based on association to the QT interval in prior studies, in individuals in 2 cohort studies (Health 2000, n=6,597; Mini-Finland, n=801). After exclusions, we identified 116 incident SCDs from the remaining sample (n=6,808). We constructed a QT genotype score (QTscore) using the allele copy number and previously reported effect estimates for each SNP. Cox proportional hazards models adjusting for age, sex, and geographical area were used time to SCD analyses. The QTscore was a continuous independent predictor of the heart rate-corrected QT interval (P<10−107). Comparing the top to the bottom quintile of QTscore, there was a 15.6 msec higher group mean QT interval (P<10−84). A 10 msec increase in the observed QT was associated with an increased risk of SCD (HR 1.19, 95% CI 1.07–1.32, P=0.002). There was no linear relationship between QTscore and SCD risk; although, in post-hoc secondary analysis there was increased risk in the top compared with the middle QTscore quintile (HR of 1.92, 95% CI 1.05–3.58, P=0.04).
Conclusions
Our study strongly replicates the relationship between common genetic variants and the QT interval, confirms the relationship between the QT interval and SCD, but does not show evidence for a linear relationship between QTscore and SCD risk.
doi:10.1161/CIRCGENETICS.110.959049
PMCID: PMC3119024  PMID: 21511878
death; sudden; genetics; QT interval; electrocardiography; mortality; electrophysiology
19.  Intracranial Aneurysm Risk Locus 5q23.2 Is Associated with Elevated Systolic Blood Pressure 
PLoS Genetics  2012;8(3):e1002563.
Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (nFIN = 11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n = 19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (pFIN = 3.01E-05, pICBP-GWAS = 0.0007, pALL = 8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.
Author Summary
When multiple genes or genetic regions contribute to the inherited risk of a disease, it is referred to as a complex disease. Genome-wide association studies (GWAS) aim to detect common genetic variations that associate with complex traits or diseases. Although GWAS have been successful in identifying strongly associated genetic loci, they lack the means to point out true, but less strong, associations. Studying conditions that are related to the disease of interest can help sort out less strong associations. Intracranial aneurysms (IA) are berry-like dilations in cerebral arteries. Most IAs do not give symptoms until they bleed, causing a highly fatal form of stroke. Half of the people who suffer bleeding of an IA die. IA is a complex disease. Both inherited risk and environmental factors contribute to the risk of developing IA. Women, smokers, those with high alcohol intake or high blood pressure are more prone to develop IA and bleeding. GWAS found 19 genetic regions increasing the risk of IA. Here we show that one of these loci, on the long arm of chromosome 5, in addition to raising IA risk also increases systolic blood pressure. We speculate that the cause is modified vascular wall structure.
doi:10.1371/journal.pgen.1002563
PMCID: PMC3305343  PMID: 22438818
20.  Bayesian Variable Selection in Searching for Additive and Dominant Effects in Genome-Wide Data 
PLoS ONE  2012;7(1):e29115.
Although complex diseases and traits are thought to have multifactorial genetic basis, the common methods in genome-wide association analyses test each variant for association independent of the others. This computational simplification may lead to reduced power to identify variants with small effect sizes and requires correcting for multiple hypothesis tests with complex relationships. However, advances in computational methods and increase in computational resources are enabling the computation of models that adhere more closely to the theory of multifactorial inheritance. Here, a Bayesian variable selection and model averaging approach is formulated for searching for additive and dominant genetic effects. The approach considers simultaneously all available variants for inclusion as predictors in a linear genotype-phenotype mapping and averages over the uncertainty in the variable selection. This leads to naturally interpretable summary quantities on the significances of the variants and their contribution to the genetic basis of the studied trait. We first characterize the behavior of the approach in simulations. The results indicate a gain in the causal variant identification performance when additive and dominant variation are simulated, with a negligible loss of power in purely additive case. An application to the analysis of high- and low-density lipoprotein cholesterol levels in a dataset of 3895 Finns is then presented, demonstrating the feasibility of the approach at the current scale of single-nucleotide polymorphism data. We describe a Markov chain Monte Carlo algorithm for the computation and give suggestions on the specification of prior parameters using commonly available prior information. An open-source software implementing the method is available at http://www.lce.hut.fi/research/mm/bmagwa/ and https://github.com/to-mi/.
doi:10.1371/journal.pone.0029115
PMCID: PMC3250410  PMID: 22235263
21.  Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals 
PLoS Genetics  2011;7(12):e1002439.
Common genetic variants have been shown to explain a fraction of the inherited variation for many common diseases and quantitative traits, including height, a classic polygenic trait. The extent to which common variation determines the phenotype of highly heritable traits such as height is uncertain, as is the extent to which common variation is relevant to individuals with more extreme phenotypes. To address these questions, we studied 1,214 individuals from the top and bottom extremes of the height distribution (tallest and shortest ∼1.5%), drawn from ∼78,000 individuals from the HUNT and FINRISK cohorts. We found that common variants still influence height at the extremes of the distribution: common variants (49/141) were nominally associated with height in the expected direction more often than is expected by chance (p<5×10−28), and the odds ratios in the extreme samples were consistent with the effects estimated previously in population-based data. To examine more closely whether the common variants have the expected effects, we calculated a weighted allele score (WAS), which is a weighted prediction of height for each individual based on the previously estimated effect sizes of the common variants in the overall population. The average WAS is consistent with expectation in the tall individuals, but was not as extreme as expected in the shortest individuals (p<0.006), indicating that some of the short stature is explained by factors other than common genetic variation. The discrepancy was more pronounced (p<10−6) in the most extreme individuals (height<0.25 percentile). The results at the extreme short tails are consistent with a large number of models incorporating either rare genetic non-additive or rare non-genetic factors that decrease height. We conclude that common genetic variants are associated with height at the extremes as well as across the population, but that additional factors become more prominent at the shorter extreme.
Author Summary
Although there are many loci in the human genome that have been discovered to be significantly associated with height, it is unclear if these loci have similar effects in extremely tall and short individuals. Here, we examine hundreds of extremely tall and short individuals in two population-based cohorts to see if these known height determining loci are as predictive as expected in these individuals. We found that these loci are generally as predictive of height as expected in these individuals but that they begin to be less predictive in the most extremely short individuals. We showed that this result is consistent with models that not only include the common variants but also multiple low frequency genetic variants that substantially decrease height. However, this result is also consistent with non-additive genetic effects or rare non-genetic factors that substantially decrease height. This finding suggests the possibility of a major role of low frequency variants, particularly in individuals with extreme phenotypes, and has implications on whole-genome or whole-exome sequencing efforts to discover rare genetic variation associated with complex traits.
doi:10.1371/journal.pgen.1002439
PMCID: PMC3248463  PMID: 22242009
22.  Genetic Association and Interaction Analysis of USF1 and APOA5 on Lipid Levels and Atherosclerosis 
Objective
USF1 is a ubiquitous transcription factor governing the expression of numerous genes of lipid and glucose metabolism. APOA5 is a well-established candidate gene regulating triglyceride (TG) levels and has been identified as a downstream target of upstream stimulatory factor. No detailed studies about the effect of APOA5 on atherosclerotic lesion formation have been conducted, nor has its potential interaction with USF1 been examined.
Methods and Results
We analyzed allelic variants of USF1 and APOA5 in families (n=516) ascertained for atherogenic dyslipidemia and in an autopsy series of middle-aged men (n=300) with precise quantitative measurements of atherosclerotic lesions. The impact of previously associated APOA5 variants on TGs was observed in the dyslipidemic families, and variant rs3135506 was associated with size of fibrotic aortic lesions in the autopsy series. The USF1 variant rs2516839, associated previously with atherosclerotic lesions, showed an effect on TGs in members of the dyslipidemic families with documented coronary artery disease. We provide preliminary evidence of gene-gene interaction between these variants in an autopsy series with a fibrotic lesion area in the abdominal aorta (P=0.0028), with TGs in dyslipidemic coronary artery disease subjects (P=0.03), and with high-density lipoprotein cholesterol (P=0.008) in a large population cohort of coronary artery disease patients (n=1065) in which the interaction for TGs was not replicated.
Conclusion
Our findings in these unique samples reinforce the roles of APOA5 and USF1 variants on cardiovascular phenotypes and suggest that both genes contribute to lipid levels and aortic atherosclerosis individually and possibly through epistatic effects.
doi:10.1161/ATVBAHA.109.188912
PMCID: PMC3224996  PMID: 19910639
genes; USF1; APOA5; lipids; atherosclerosis; epistasis
23.  A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol 
Surakka, Ida | Isaacs, Aaron | Karssen, Lennart C. | Laurila, Pirkka-Pekka P. | Middelberg, Rita P. S. | Tikkanen, Emmi | Ried, Janina S. | Lamina, Claudia | Mangino, Massimo | Igl, Wilmar | Hottenga, Jouke-Jan | Lagou, Vasiliki | van der Harst, Pim | Mateo Leach, Irene | Esko, Tõnu | Kutalik, Zoltán | Wainwright, Nicholas W. | Struchalin, Maksim V. | Sarin, Antti-Pekka | Kangas, Antti J. | Viikari, Jorma S. | Perola, Markus | Rantanen, Taina | Petersen, Ann-Kristin | Soininen, Pasi | Johansson, Åsa | Soranzo, Nicole | Heath, Andrew C. | Papamarkou, Theodore | Prokopenko, Inga | Tönjes, Anke | Kronenberg, Florian | Döring, Angela | Rivadeneira, Fernando | Montgomery, Grant W. | Whitfield, John B. | Kähönen, Mika | Lehtimäki, Terho | Freimer, Nelson B. | Willemsen, Gonneke | de Geus, Eco J. C. | Palotie, Aarno | Sandhu, Manj S. | Waterworth, Dawn M. | Metspalu, Andres | Stumvoll, Michael | Uitterlinden, André G. | Jula, Antti | Navis, Gerjan | Wijmenga, Cisca | Wolffenbuttel, Bruce H. R. | Taskinen, Marja-Riitta | Ala-Korpela, Mika | Kaprio, Jaakko | Kyvik, Kirsten O. | Boomsma, Dorret I. | Pedersen, Nancy L. | Gyllensten, Ulf | Wilson, James F. | Rudan, Igor | Campbell, Harry | Pramstaller, Peter P. | Spector, Tim D. | Witteman, Jacqueline C. M. | Eriksson, Johan G. | Salomaa, Veikko | Oostra, Ben A. | Raitakari, Olli T. | Wichmann, H.-Erich | Gieger, Christian | Järvelin, Marjo-Riitta | Martin, Nicholas G. | Hofman, Albert | McCarthy, Mark I. | Peltonen, Leena | van Duijn, Cornelia M. | Aulchenko, Yurii S. | Ripatti, Samuli | Gibson, Greg
PLoS Genetics  2011;7(10):e1002333.
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.
Author Summary
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.
doi:10.1371/journal.pgen.1002333
PMCID: PMC3197672  PMID: 22028671
24.  CRP gene variation affects early development of Alzheimer's disease-related plaques 
Introduction
We used the Tampere Autopsy Study (TASTY) series (n = 603, age 0-97 yrs), representing an unselected population outside institutions, to investigate the pathogenic involvement of inflammation in Alzheimer's disease-related lesions.
Methods
We studied senile plaque (SP), neurofibrillary tangles (NFT) and SP phenotype associations with 6 reported haplotype tagging single nucleotide polymorphisms (SNPs) in the CRP gene. CRP and Aβ immunohistochemistry was assessed using brain tissue microarrays.
Results
In multivariate analyses (age- and APOE-adjusted), non-neuritic SP were associated with the high-CRP TA-genotype (3.0% prevalence) of rs3091244 and CA-genotype (10.8%) of rs3093075 compared to common genotypes. Conversely, the low-CRP C allele (39.3%) of rs2794521 reduced the risk of harbouring early non-neuritic SP, compared to the TT genotype. CRP haplotype TAGCC (high) associated with non-neuritic SP, whereas haplotype CCGCC offered protection. TT genotypes (high) of rs3091244 and rs1130864 were associated with CRP staining. There were no associations between SNPs or haplotypes and NFT. CRP staining of the hippocampal CA1/2 region correlated with Aβ staining.
Conclusions
CRP gene variation affects early SP development in prodromal Alzheimer's disease, independent of APOE genotype.
doi:10.1186/1742-2094-8-96
PMCID: PMC3168418  PMID: 21831326
25.  Correction: Genome-Wide Association Study Identifies Novel Restless Legs Syndrome Susceptibility Loci on 2p14 and 16q12.1 
PLoS Genetics  2011;7(8):10.1371/annotation/393ad2d3-df4f-4770-87bc-00bfabf79362.
doi:10.1371/annotation/393ad2d3-df4f-4770-87bc-00bfabf79362
PMCID: PMC3154083

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