Next-generation sequencing (NGS) technologies can be a boon to human mutation detection given their high throughput: consequently, many genes and samples may be simultaneously studied with high coverage for accurate detection of heterozygotes. In circumstances requiring the intensive study of a few genes, particularly in clinical applications, a rapid turn-around is another desirable goal. To this end, we assessed the performance of the bench-top 454 GS Junior platform as an optimized solution for mutation detection by amplicon sequencing of three type 3 semaphorin genes SEMA3A, SEMA3C and SEMA3D implicated in Hirschsprung disease (HSCR). We performed mutation detection on 39 PCR amplicons totaling 14,014bp in 47 samples studied in pools of 12 samples. Each 10-hour run was able to generate ∼75,000 reads and ∼28 million high-quality bases at an average read length of 371bp. The overall sequencing error was 0.26 changes per kb at a coverage depth of ≥20 reads. Altogether, 37 sequence variants were found in this study of which 10 were unique to HSCR patients. We identified five missense mutations in these three genes that may potentially be involved in the pathogenesis of HSCR and need to be studied in larger patient samples.

We describe methods for rapid sequencing of the entire human mitochondrial genome (mtgenome), which involve long-range PCR for specific amplification of the mtgenome, pyrosequencing, quantitative mapping of sequence reads to identify sequence variants and heteroplasmy, as well as de novo sequence assembly. These methods have been used to study 40 publicly available HapMap samples of European (CEU) and African (YRI) ancestry to demonstrate a sequencing error rate <5.63×10−4, nucleotide diversity of 1.6×10−3 for CEU and 3.7×10−3 for YRI, patterns of sequence variation consistent with earlier studies, but a higher rate of heteroplasmy varying between 10% and 50%. These results demonstrate that next-generation sequencing technologies allow interrogation of the mitochondrial genome in greater depth than previously possible which may be of value in biology and medicine.

Author Summary

This manuscript details a novel algorithm to evaluate high-throughput DNA sequence data from whole mitochondrial genomes purified from genomic DNA, which also contains multiple fragmented nuclear copies of mtgenomes (numts). 40 samples were selected from 2 distinct reference (HapMap) populations of African (YRI) and European (CEU) origin. While previous technologies did not allow the assessment of individual mitochondrial molecules, next-generation sequencing technology is an excellent tool for obtaining the mtgenome sequence and its heteroplasmic sites rapidly and accurately through deep coverage of the genome. The computational techniques presented optimize reference-based alignments and introduce a new de novo assembly method. An important contribution of our study was obtaining high accuracy of the resulting called bases that we accomplished by quantitative filtering of reads that were error prone. In addition, several sites were experimentally validated and our method has a strong correlation (R2 = 0.96) with the NIST standard reference sample for heteroplasmy. Overall, our findings indicate that one can now confidently genotype mtDNA variants using next-generation sequencing data and reveal low levels of heteroplasmy (>10%). Beyond enriching our understanding and pathology of certain diseases, this development could be considered as a prelude to sequence-based individualized medicine for the mtgenome.

Background.

Frailty is a late-life syndrome of vulnerability to adverse health outcomes characterized by a phenotype that includes muscle weakness, fatigue, and inflammatory pathway activation. The identification of biologically relevant pathways that influence frailty is challenged by its biological complexity and the necessity in separating disease states from the syndrome of frailty. As with longevity research, genetic analyses may help to provide insights into biologically relevant pathways that contribute to frailty.

Methods.

Based on current understanding of the physiological basis of frailty, we hypothesize that variation in genes related to inflammation and muscle maintenance would associate with frailty. One thousand three hundred and fifty-four single-nucleotide polymorphisms were genotyped across 134 candidate genes using the Illumina Genotyping platform, and the rank order by strength of association between frailty and genotype was determined in a cross-sectional study.

Results.

Although no single-nucleotide polymorphism reached study-wide significance after controlling family-wise false-discovery rate at 0.05, single-nucleotide polymorphisms within the 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), Caspase 8 (CASP8), CREB-binding protein (CREBBP), lysine acetyltransferase 2B (KAT2B), and beta-transducin repeat containing (BTRC) loci were among those strongly associated with frailty.

Conclusions.

The apoptosis– and transcription regulation–related pathways highlighted by this preliminary analysis were consistent with prior gene expression studies in a frail mouse model and provide useful etiological insights for future biological studies of frailty.

Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P< 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P< 10−5). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P< 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10−7 for SBP and 7.52 × 10−7 for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genome-wide association studies because of drastically reduced number of tests in the whole genome.

A report on the 'Genomic Disorders 2011 - The Genomics of Rare Diseases' meeting, Wellcome Trust Sanger Institute, Hinxton, UK, 23-26 March 2011

We previously conducted genome-wide association meta-analysis (GWA) of systolic blood pressure (SBP), diastolic blood pressure (DBP) and hypertension in 29,136 people from six cohort studies in the CHARGE Consortium. Here we examine associations of these traits with 30 gene regions encoding known anti-hypertensive drug targets. We find nominal evidence of association of ADRB1, ADRB2, AGT, CACNA1A, CACNA1C, and SLC12A3 polymorphisms with one or more BP traits in the CHARGE GWA meta-analysis. We attempted replication of the top meta-analysis SNPs for these genes in the Global BPgen Consortium (GBPG, n=34,433) and the Women’s Genome Health Study (WGHS, n=23,019), and found significant results for rs1801253 in ADRB1 (Arg389Gly), with the Gly allele associated with a lower mean SBP (beta −0.57 (mmHg), se 0.09, meta-analysis P=4.7×10−10), DBP (beta −0.36, se 0.06, meta-analysis P=9.5×10−10) and prevalence of hypertension (beta −0.06, se 0.02, meta-analysis P=3.3×10−4). Variation in AGT (rs2004776) was associated with SBP (beta 0.42, se 0.09, meta-analysis P=3.8×10−6), as well as DBP (P=5.0×10−8) and hypertension (P=3.7×10−7). A polymorphism in ACE (rs4305) showed modest replication of association with increased hypertension (beta 0.06, se 0.01, meta-analysis P=3.0×10−5). Two loci, ADRB1 and AGT, contain SNPs that reached a genome-wide significance threshold in meta-analysis for the first time. Our findings suggest that these genes warrant further studies of their genetic effects on BP, including pharmacogenetic interactions.

QRS interval on the electrocardiogram reflects ventricular depolarization and conduction time, and is a risk factor for mortality, sudden death, and heart failure. We performed a genome-wide association meta-analysis in 40,407 European-descent individuals from 14 studies, with further genotyping in 7170 additional Europeans, and identified 22 loci associated with QRS duration (P < 5 × 10−8). These loci map in or near genes in pathways with established roles in ventricular conduction such as sodium channels, transcription factors, and calcium-handling proteins, but also point to novel biologic processes, such as kinase inhibitors and genes related to tumorigenesis. We demonstrate that SCN10A, a gene at our most significant locus, is expressed in the mouse ventricular conduction system, and treatment with a selective SCN10A blocker prolongs QRS duration. These findings extend our current knowledge of ventricular depolarization and conduction.

OBJECTIVE

The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS.

RESEARCH DESIGN AND METHODS

Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected.

RESULTS

Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure.

CONCLUSIONS

Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of base pairs in the genome. Genomewide association studies (GWAS) may simultaneously screen for copy number phenotype and single nucleotide polymorphism (SNP) phenotype associations as part of the analytic strategy. However, genomewide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post hoc quality control procedures to exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of biallelic genotype calls from experimental data to estimate batch-specific and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in the quantile-normalized intensities, while the latter illustrates the robustness of our approach to a data set in which approximately 27% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package crlmm at Bioconductor (http:www.bioconductor.org).

Identification and characterization of the genetic variants underlying type 2 diabetes susceptibility can provide important understanding of the etiology and pathogenesis of type 2 diabetes. We previously identified strong evidence of linkage for type 2 diabetes on chromosome 22 among 3,383 Hypertension Genetic Epidemiology Network (HyperGEN) participants from 1,124 families. The checkpoint 2 (CHEK2) gene, an important mediator of cellular responses to DNA damage, is located 0.22 Mb from this linkage peak. In this study, we tested the hypothesis that the CHEK2 gene contains one or more polymorphic variants that are associated with type 2 diabetes in HyperGEN individuals. In addition, we replicated our findings in two other Family Blood Pressure Program (FBPP) populations and in the population-based Atherosclerosis Risk in Communities (ARIC) study. We genotyped 1,584 African-American and 1,531 white HyperGEN participants, 1,843 African-American and 1,569 white GENOA participants, 871 African-American and 1,009 white GenNet participants, and 4,266 African-American and 11,478 white ARIC participants for four single nucleotide polymorphisms (SNPs) in CHEK2. Using additive models, we evaluated the association of CHEK2 SNPs with type 2 diabetes in participants within each study population stratified by race, and in a meta-analysis, adjusting for age, age2, sex, sex-by-age interaction, study center, and relatedness. One CHEK2 variant, rs4035540, was associated with an increased risk of type 2 diabetes in HyperGEN participants, two replication samples, and in the meta-analysis. These results may suggest a new pathway in the pathogenesis of type 2 diabetes that involves pancreatic beta-cell damage and apoptosis.

Though recently they have fallen into some disrepute, genome-wide association studies (GWAS) have been formulated and applied to understanding essential hypertension. The principal goal here is to use data gathered in a GWAS to gauge the extent to which SNPs and their interactions with other features can be combined to predict mean arterial blood pressure (MAP) in 3138 pre-menopausal and naturally post-menopausal white women. More precisely, we quantify the extent to which data as described permit prediction of MAP beyond what is possible from traditional risk factors such as blood cholesterol levels and glucose levels. Of course, these traditional risk factors are genetic, though typically not explicitly so. In all, there were 44 such risk factors/clinical variables measured and 377,790 single nucleotide polymorphisms (SNPs) genotyped. Data for women we studied are from first visit measurements taken as part of the Atherosclerotic Risk in Communities (ARIC) study. We begin by assessing non-SNP features in their abilities to predict MAP, employing a novel regression technique with two stages, first the discovery of main effects and next discovery of their interactions. The long list of SNPs genotyped is reduced to a manageable list for combining with non-SNP features in prediction. We adapted Efron's local false discovery rate to produce this reduced list. Selected non-SNP and SNP features and their interactions are used to predict MAP using adaptive linear regression. We quantify quality of prediction by an estimated coefficient of determination (R2). We compare the accuracy of prediction with and without information from SNPs.

Autism is a complex genetic disorder with multiple etiologies whose molecular genetic basis is not fully understood. Although a number of rare mutations and dosage abnormalities are specific to autism, these explain no more than 10% of all cases. The high heritability of autism and low recurrence risk suggests multifactorial inheritance from numerous loci but other factors also intervene to modulate risk. In this study, we examine the effect of birth rank on disease risk which is not expected for purely hereditary genetic models.

We analyzed the data from three publicly available autism family collections in the USA for potential birth order effects and studied the statistical properties of three tests to show that adequate power to detect these effects exist. We detect statistically significant, yet varying, patterns of birth order effects across these collections. In multiplex families, we identify V-shaped effects where middle births are at high risk; in simplex families, we demonstrate linear effects where risk increases with each additional birth. Moreover, the birth order effect is gender-dependent in the simplex collection. It is currently unknown whether these patterns arise from ascertainment biases or biological factors. Nevertheless, further investigation of parental age-dependent risks yields patterns similar to those observed and could potentially explain part of the increased risk. A search for genes considering these patterns is likely to increase statistical power and uncover novel molecular etiologies.

Hirschsprung disease (HSCR) is a neurocristopathy characterized by absence of intramural ganglion cells along variable lengths of the gastrointestinal tract. The HSCR phenotype is highly variable with respect to gender, length of aganglionosis, familiality and the presence of additional anomalies. By molecular genetic analysis, a minimum of 11 neuro-developmental genes (RET, GDNF, NRTN, SOX10, EDNRB, EDN3, ECE1, ZFHX1B, PHOX2B, KIAA1279, TCF4) are known to harbor rare, high-penetrance mutations that confer a large risk to the bearer. In addition, two other genes (RET, NRG1) harbor common, low-penetrance polymorphisms that contribute only partially to risk and can act as genetic modifiers. To broaden this search, we examined whether a set of 67 proven and candidate HSCR genes harbored additional modifier alleles. In this pilot study, we utilized a custom-designed array CGH with ∼33,000 test probes at an average resolution of ∼185 bp to detect gene-sized or smaller copy number variants (CNVs) within these 67 genes in 18 heterogeneous HSCR patients. Using stringent criteria, we identified CNVs at three loci (MAPK10, ZFHX1B, SOX2) that are novel, involve regulatory and coding sequences of neuro-developmental genes, and show association with HSCR in combination with other congenital anomalies. Additional CNVs are observed under relaxed criteria. Our research suggests a role for CNVs in HSCR and, importantly, emphasizes the role of variation in regulatory sequences. A much larger study will be necessary both for replication and for identifying the full spectrum of small CNV effects.

Studies suggest that diabetes may specifically elevate risk of sudden cardiac death in excess of other heart disease outcomes. In this study, we examined the association of type 2 diabetes with incidence of sudden cardiac death as compared to the incidence of non-sudden cardiac death and non-fatal myocardial infarction (MI). We used data from the Atherosclerosis Risk in Communities (ARIC) study to examine incidence of sudden and non-sudden cardiac death and non-fatal MI among persons with and without diabetes in follow-up from the baseline data collection (1987-1989) through December 31, 2001. There were 209 cases of sudden cardiac death, 119 of non-sudden cardiac death, and 739 of non-fatal MI identified in this cohort over an average 12.4 years of follow-up. In analyses adjusted for age, race/ARIC center, gender, and smoking, the Cox proportional hazard ratio of the association of baseline diabetes was 3.77 (95% CI 2.82, 5.05) for sudden cardiac death, 3.78 (95% CI 2.57, 5.53) for non-sudden cardiac death, and 3.20 (95% CI 2.71, 3.78) for non-fatal MI. Elevated risk for each of the three outcomes associated with diabetes was independent of adjustment for measures of blood pressure, lipids, inflammation, hemostasis, and renal function. Among those with diabetes, the risk of cardiac death, but not of non-fatal MI, was similar for men and women. Findings from this prospective, population-based cohort investigation indicate that diabetes does not confer a specific excess risk of sudden cardiac death. Our results suggest that diabetes attenuates gender-differences in risk of fatal cardiac events.

Objective

This study examines the hypothesis that chronic inflammation is associated with a higher risk of cardiac death compared to the risk of non-fatal myocardial infarction.

Methods

Cardiac death and non-fatal MI events were identified in the ARIC cohort during follow-up from 1987 through 2001. Markers of inflammation and hemostasis were determined at baseline using standardized procedures. Cox proportional hazard regression and polytomous logistic regression were used to estimate associations.

Results

We observed a positive gradient in incidence of sudden cardiac death, non-sudden cardiac death and non-fatal MI in association with decreasing levels of albumin and increasing levels of white blood cell count and of markers of hemostasis (fibrinogen, von Willebrand factor, factor VIIIc). Associations for von Willebrand factor (vWF) and factor VIIIc were stronger for fatal relative to non-fatal events (3rd versus 1st tertile hazard ratios: vWF: SCD 2.67 (95% CI 1.80, 3.96), NSCD 2.11 (95% CI 1.40, 3.19), non-fatal MI 1.40 (95% CI 1.17, 1.67); factor VIIIc: SCD 2.58 (95% CI 1.77, 3.78), NSCD 2.01 (95% CI 1.38, 2.93), non-fatal MI 1.48 (95% CI 1.24, 1.78). Gradients of association for fibrinogen and white blood cell count, examined over tertiles of distribution and per one SD increase, were similar for the three endpoints. All associations were independent of smoking status.

Conclusion

Von Willebrand factor and factor VIIIc are associated with an increased risk of cardiac death as compared to the risk of non-fatal MI.

Coronary heart disease (CHD) is the leading cause of mortality in African Americans. To identify common genetic polymorphisms associated with CHD and its risk factors (LDL- and HDL-cholesterol (LDL-C and HDL-C), hypertension, smoking, and type-2 diabetes) in individuals of African ancestry, we performed a genome-wide association study (GWAS) in 8,090 African Americans from five population-based cohorts. We replicated 17 loci previously associated with CHD or its risk factors in Caucasians. For five of these regions (CHD: CDKN2A/CDKN2B; HDL-C: FADS1-3, PLTP, LPL, and ABCA1), we could leverage the distinct linkage disequilibrium (LD) patterns in African Americans to identify DNA polymorphisms more strongly associated with the phenotypes than the previously reported index SNPs found in Caucasian populations. We also developed a new approach for association testing in admixed populations that uses allelic and local ancestry variation. Using this method, we discovered several loci that would have been missed using the basic allelic and global ancestry information only. Our conclusions suggest that no major loci uniquely explain the high prevalence of CHD in African Americans. Our project has developed resources and methods that address both admixture- and SNP-association to maximize power for genetic discovery in even larger African-American consortia.

Author Summary

To date, most large-scale genome-wide association studies (GWAS) carried out to identify risk factors for complex human diseases and traits have focused on population of European ancestry. It is currently unknown whether the same loci associated with complex diseases and traits in Caucasians will replicate in population of African ancestry. Here, we conducted a large GWAS to identify common DNA polymorphisms associated with coronary heart disease (CHD) and its risk factors (type-2 diabetes, hypertension, smoking status, and LDL- and HDL-cholesterol) in 8,090 African Americans as part of the NHLBI Candidate gene Association Resource (CARe) Project. We replicated 17 associations previously reported in Caucasians, suggesting that the same loci carry common DNA sequence variants associated with CHD and its risk factors in Caucasians and African Americans. At five of these 17 loci, we used the different patterns of linkage disequilibrium between populations of European and African ancestry to identify DNA sequence variants more strongly associated with phenotypes than the index SNPs found in Caucasians, suggesting smaller genomic intervals to search for causal alleles. We also used the CARe data to develop new statistical methods to perform association studies in admixed populations. The CARe Project data represent an extraordinary resource to expand our understanding of the genetics of complex diseases and traits in non-European-derived populations.

Essential hypertension is a major cardiovascular risk factor and a large proportion of this risk is genetic. Identification of genomic regions consistently associated with hypertension has been difficult in association studies to date as this requires large sample sizes.

We previously published a large genome-wide linkage scan in Americans of African (AA) and European (EA) descent in the GenNet Network of the Family Blood Pressure Program (FBPP). A highly significant linkage peak was identified on chr1q spanning a region of 100 cM. In this study, we genotyped 1569 SNPs under this linkage peak in 2379 individuals to identify whether common genetic variants were associated with blood pressure (BP) at this locus.

Our analysis, using two different family-based association tests, provides suggestive evidence (P≤2 × 10−5) for a collection of single nucleotide polymorphisms (SNPs) associated with BP. In EAs, using diastolic BP as a quantitative phenotype, three variants located in or near the GPA33, CD247, and F5 genes, emerge as our top hits; for systolic BP, variants in GPA33, CD247, and REN are our best findings. No variant in AAs came close to suggestive evidence after multiple-test corrections (P≥8 × 10−5).

In summary, we show that systematic follow-up of a linkage signal can help discover candidate variants for essential hypertension that require a follow-up in yet larger samples. The failure to identify common variants is either because of low statistical power or the existence of rare coding variants in specific families or both, which require additional studies to clarify.

The QT interval, a measure of cardiac repolarization, predisposes to ventricular arrhythmias and sudden cardiac death (SCD) when prolonged or shortened. A common variant in NOS1AP is known to influence repolarization. We analyze genome-wide data from five population-based cohorts (ARIC, KORA, SardiNIA, GenNOVA and HNR) with a total of 15,842 individuals of European ancestry, to confirm the NOS1AP association and identify nine additional loci at P < 5 × 10−8. Four loci map near the monogenic long-QT syndrome genes KCNQ1, KCNH2, SCN5A and KCNJ2. Two other loci include ATP1B1 and PLN, genes with established electrophysiological function, whereas three map to RNF207, near LITAF and within NDRG4-GINS3-SETD6-CNOT1, respectively, all of which have not previously been implicated in cardiac electrophysiology. These results, together with an accompanying paper from the QTGEN consortium, identify new candidate genes for ventricular arrhythmias and SCD.

Background

Autism is a common heritable neurodevelopmental disorder with complex etiology. Several genome-wide linkage and association scans have been carried out to identify regions harboring genes related to autism or autism spectrum disorders, with mixed results. Given the overlap in autism features with genetic abnormalities known to be associated with imprinting, one possible reason for lack of consistency would be the influence of parent-of-origin effects that may mask the ability to detect linkage and association.

Methods and Findings

We have performed a genome-wide linkage scan that accounts for potential parent-of-origin effects using 16,311 SNPs among families from the Autism Genetic Resource Exchange (AGRE) and the National Institute of Mental Health (NIMH) autism repository. We report parametric (GH, Genehunter) and allele-sharing linkage (Aspex) results using a broad spectrum disorder case definition. Paternal-origin genome-wide statistically significant linkage was observed on chromosomes 4 (LODGH = 3.79, empirical p<0.005 and LODAspex = 2.96, p = 0.008), 15 (LODGH = 3.09, empirical p<0.005 and LODAspex = 3.62, empirical p = 0.003) and 20 (LODGH = 3.36, empirical p<0.005 and LODAspex = 3.38, empirical p = 0.006).

Conclusions

These regions may harbor imprinted sites associated with the development of autism and offer fruitful domains for molecular investigation into the role of epigenetic mechanisms in autism.

Background

Cardiac repolarization, the process by which cardiomyocytes return to their resting potential after each beat, is a highly regulated process that is critical for heart rhythm stability. Perturbations of cardiac repolarization increase the risk for life-threatening arrhythmias and sudden cardiac death. While genetic studies of familial long QT syndromes have uncovered several key genes in cardiac repolarization, the major heritable contribution to this trait remains unexplained. Identification of additional genes may lead to a better understanding of the underlying biology, aid in identification of patients at risk for sudden death, and potentially enable new treatments for susceptible individuals.

Methods and Results

We extended and refined a zebrafish model of cardiac repolarization by using fluorescent reporters of transmembrane potential. We then conducted a drug-sensitized genetic screen in zebrafish, identifying 15 genes, including GINS3, that affect cardiac repolarization. Testing these genes for human relevance in two concurrently completed genome wide association studies revealed that the human GINS3 ortholog is located in the 16q21 locus which is strongly associated with QT interval.

Conclusions

This sensitized zebrafish screen identified 15 novel myocardial repolarization genes. Among these genes is GINS3, the human ortholog of which is a major locus in two concurrent human genome wide association studies of QT interval. These results reveal a novel network of genes that regulate cardiac repolarization.

Magnesium, potassium, and sodium, cations commonly measured in serum, are involved in many physiological processes including energy metabolism, nerve and muscle function, signal transduction, and fluid and blood pressure regulation. To evaluate the contribution of common genetic variation to normal physiologic variation in serum concentrations of these cations, we conducted genome-wide association studies of serum magnesium, potassium, and sodium concentrations using ∼2.5 million genotyped and imputed common single nucleotide polymorphisms (SNPs) in 15,366 participants of European descent from the international CHARGE Consortium. Study-specific results were combined using fixed-effects inverse-variance weighted meta-analysis. SNPs demonstrating genome-wide significant (p<5×10−8) or suggestive associations (p<4×10−7) were evaluated for replication in an additional 8,463 subjects of European descent. The association of common variants at six genomic regions (in or near MUC1, ATP2B1, DCDC5, TRPM6, SHROOM3, and MDS1) with serum magnesium levels was genome-wide significant when meta-analyzed with the replication dataset. All initially significant SNPs from the CHARGE Consortium showed nominal association with clinically defined hypomagnesemia, two showed association with kidney function, two with bone mineral density, and one of these also associated with fasting glucose levels. Common variants in CNNM2, a magnesium transporter studied only in model systems to date, as well as in CNNM3 and CNNM4, were also associated with magnesium concentrations in this study. We observed no associations with serum sodium or potassium levels exceeding p<4×10−7. Follow-up studies of newly implicated genomic loci may provide additional insights into the regulation and homeostasis of human serum magnesium levels.

Author Summary

Magnesium, potassium, and sodium are involved in important physiological processes. To better understand how common genetic variation may contribute to inter-individual differences in serum concentrations of these electrolytes, we evaluated single nucleotide polymorphisms (SNPs) across the genome in association with serum magnesium, potassium, and sodium levels in 15,366 participants of European descent from the CHARGE Consortium. We then verified the associations in an additional 8,463 study participants. Six different genomic regions contain variants that are reproducibly associated with serum magnesium levels, and only one of the regions had been previously known to influence serum magnesium concentrations in humans. The identified SNPs also show association with clinically defined hypomagnesemia, and some of them with traits that have been linked to serum magnesium levels, including kidney function, fasting glucose, and bone mineral density. We further provide evidence for a physiological role of magnesium transporters in humans which have previously only been studied in model systems. None of the SNPs evaluated in our study are significantly associated with serum levels of sodium or potassium. Additional studies are needed to investigate the underlying molecular mechanisms in order to help us understand the contribution of these newly identified regions to magnesium homeostasis.

Background

Mitochondria contribute to the dynamics of cellular metabolism, the production of reactive oxygen species, and apoptotic pathways. Consequently, mitochondrial function has been hypothesized to influence functional decline and vulnerability to disease in later life. Mitochondrial genetic variation may contribute to altered susceptibility to the frailty syndrome in older adults.

Methodology/Principal Findings

To assess potential mitochondrial genetic contributions to the likelihood of frailty, mitochondrial DNA (mtDNA) variation was compared in frail and non-frail older adults. Associations of selected SNPs with a muscle strength phenotype were also explored. Participants were selected from the Cardiovascular Health Study (CHS), a population-based observational study (1989–1990, 1992–1993). At baseline, frailty was identified as the presence of three or more of five indicators (weakness, slowness, shrinking, low physical activity, and exhaustion). mtDNA variation was assessed in a pilot study, including 315 individuals selected as extremes of the frailty phenotype, using an oligonucleotide sequencing microarray based on the Revised Cambridge Reference Sequence. Three mtDNA SNPs were statistically significantly associated with frailty across all pilot participants or in sex-stratified comparisons: mt146, mt204, and mt228. In addition to pilot participants, 4,459 additional men and women with frailty classifications, and an overlapping subset of 4,453 individuals with grip strength measurements, were included in the study population genotyped at mt204 and mt228. In the study population, the mt204 C allele was associated with greater likelihood of frailty (adjusted odds ratio = 2.04, 95% CI = 1.07–3.60, p = 0.020) and lower grip strength (adjusted coefficient = −2.04, 95% CI = −3.33– −0.74, p = 0.002).

Conclusions

This study supports a role for mitochondrial genetic variation in the frailty syndrome and later life muscle strength, demonstrating the importance of the mitochondrial genome in complex geriatric phenotypes.

Essential hypertension is a major cardiovascular risk factor and a large proportion of this risk is genetic. Identification of genomic regions consistently associated with hypertension has been difficult in association studies to date since this requires large sample sizes.

We previously published a large genome-wide linkage scan in Americans of African (AA) and European (EA) descent in the GenNet Network of the Family Blood Pressure Program (FBPP). A highly significant linkage peak was identified on chr1q spanning a region of 100cM. In the current study, we genotyped 1,569 SNPs under this linkage peak in 2,379 individuals in order to identify whether common genetic variants were associated with blood pressure (BP) at this locus.

Our analysis, using two different family-based association tests, provides suggestive evidence (P≤2×10-5) for a collection of single nucleotide polymorphisms (SNPs) associated with BP. In EAs, using diastolic BP as a quantitative phenotype, three variants located in or near the GPA33, CD247, and F5 genes, emerge as our top hits; for systolic BP, variants in GPA33, CD247, and REN are our best findings. No variant in AAs came close to suggestive evidence (P≥8×10-5) after multiple-test corrections.

In summary, we show that systematic follow-up of a linkage signal can help discover candidate variants for essential hypertension that require follow-up in yet larger samples. The failure to identify common variants is either due to low statistical power or the existence of rare coding variants in specific families or both, that require additional studies to clarify.

BACKGROUND

Recent experimental evidence suggests that DNA damage and cell cycle regulatory proteins are involved in kidney injury and apoptosis. The checkpoint 2 gene (CHEK2) is an important transducer in DNA damage signaling pathways in response to injury, and therefore, CHEK2 variants may affect susceptibility to kidney disease.

METHODS

We used tag-single-nucleotide polymorphisms (tag-SNPs) to evaluate the association of the CHEK2 with kidney function (estimated glomerular filtration rate, eGFR) in 1,549 African-American and 1,423 white Hypertension Genetic Epidemiology Network (HyperGEN) participants. We performed replication analyses in the Genetic Epidemiology Network of Arteriopathy (GENOA) participants (1,746 African Americans and 1,418 whites), GenNet participants (706 whites), and Atherosclerosis Risk in Communities (ARIC) study participants (3,783 African Americans and 10,936 whites). All analyses were race-stratified and used additive genetic models with adjustments for covariates and for family structure, if needed.

RESULTS

One tag-SNP, rs5762764, was associated with eGFR in HyperGEN P = (0.003) and GENOA white participants (P = 0.009), and it was significantly associated with eGFR in meta-analyses (P = 0.002). The associations were independent of type 2 diabetes.

CONCLUSIONS

These results suggest that CHEK2 variants may influence eGFR in the context of hypertension.