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1.  The NIH Toolbox Cognition Battery: Results from a Large Normative Developmental Sample (PING) 
Neuropsychology  2013;28(1):1-10.
Objective
The NIH Toolbox Cognition Battery (NTCB) was designed to provide a brief, efficient computerized test of key neuropsychological functions appropriate for use in children as young as 3 years of age. This report describes the performance of a large group of typically developing children and adolescents and examines the impact of age and sociocultural variables on test performance.
Method
The NTCB was administered to a sample of 1020 typically developing males and females ranging in age from 3 to 20 years, diverse in terms of socioeconomic status (SES) and race/ethnicity, as part of the new publicly accessible Pediatric Imaging, Neurocognition, and Genetics (PING) data resource, at 9 sites across the United States.
Results
General additive models of nonlinear age-functions were estimated from age-differences in test performance on the 8 NTCB subtests while controlling for family SES and genetic ancestry factors (GAFs). Age accounted for the majority of the variance across all NTCB scores, with additional significant contributions of gender on some measures, and of SES and race/ethnicity (GAFs) on all. After adjusting for age and gender, SES and GAFs explained a substantial proportion of the remaining unexplained variance in Picture Vocabulary scores.
Conclusions
The results highlight the sensitivity to developmental effects and efficiency of this new computerized assessment battery for neurodevelopmental research. Limitations are observed in the form of some ceiling effects in older children, some floor effects, particularly on executive function tests in the youngest participants, and evidence for variable measurement sensitivity to cultural/socioeconomic factors.
doi:10.1037/neu0000001
PMCID: PMC3925365  PMID: 24219608
Computerized Assessment; Cognitive Development; Socioeconomic Status
3.  Analysis of 94 Candidate Genes and Twelve Endophenotypes for Schizophrenia from the Consortium on the Genetics of Schizophrenia 
The American journal of psychiatry  2011;168(9):930-946.
Objective
We have used a custom 1,536-SNP array to interrogate 94 functionally relevant candidate genes for schizophrenia and identify associations with 12 heritable neurophysiological and neurocognitive endophenotypes collected as part of the Consortium on the Genetics of Schizophrenia (COGS).
Method
Variance-component association analyses of 534 genotyped subjects from 130 families were conducted using Merlin. A novel bootstrap Total Significance Test was also developed to overcome the limitations of existing genomic multiple testing methods and robustly demonstrate the presence of significant associations in the context of complex family data and possible population stratification effects.
Results
Associations were observed for 46 genes of potential functional significance with 3 SNPs at p<10−4, 27 SNPs at p<10−3, and 147 SNPs at p<0.01. The bootstrap analyses confirmed that the 47 SNP-endophenotype combinations with the strongest evidence of association significantly exceeded (p=0.001) that expected by chance alone with 93% of these findings expected to be true. Many of the genes interact on a molecular level, and eight genes displayed evidence for pleiotropy (e.g., NRG1 and ERBB4), revealing associations with four or more endophenotypes. Our results collectively support a strong role for genes related to glutamate signaling in mediating schizophrenia susceptibility.
Conclusions
This study supports the use of relevant endophenotypes and the bootstrap Total Significance Test for the identification of genetic variation underlying the etiology of schizophrenia. In addition, the observation of extensive pleiotropy for some genes and singular associations for others in our data suggests alternative, independent pathways mediating pathogenesis in the “group of schizophrenias”.
doi:10.1176/appi.ajp.2011.10050723
PMCID: PMC3751972  PMID: 21498463
4.  FMR1, circadian genes and depression: suggestive associations or false discovery? 
Background
There are several indications that malfunctions of the circadian clock contribute to depression. To search for particular circadian gene polymorphisms associated with depression, diverse polymorphisms were genotyped in two samples covering a range of depressed volunteers and participants with normal mood.
Methods
Depression mood self-ratings and DNA were collected independently from a sample of patients presenting to a sleep disorders center (1086 of European origin) and from a separate sample consisting of 399 participants claiming delayed sleep phase symptoms and 406 partly-matched controls. A custom Illumina Golden Gate array of 768 selected single nucleotide polymorphisms (SNPs) was assayed in both samples, supplemented by additional SNPlex and Taqman assays, including assay of 41 ancestry-associated markers (AIMs) to control stratification.
Results
In the Sleep Clinic sample, these assays yielded Bonferroni-significant association with depressed mood in three linked SNPs of the gene FMR1: rs25702 (nominal P=1.77E-05), rs25714 (P=1.83E-05), and rs28900 (P=5.24E-05). This FMR1 association was supported by 8 SNPs with nominal significance and a nominally-significant gene-wise set test. There was no association of depressed mood with FMR1 in the delayed sleep phase case–control sample or in downloaded GWAS data from the GenRED 2 sample contrasting an early-onset recurrent depression sample with controls. No replication was located in other GWAS studies of depression. Our data did weakly replicate a previously-reported association of depression with PPARGC1B rs7732671 (P=0.0235). Suggestive associations not meeting strict criteria for multiple testing and replication were found with GSK3B, NPAS2, RORA, PER3, CRY1, MTNR1A and NR1D1. Notably, 16 SNPs nominally associated with depressed mood (14 in GSK3B) were also nominally associated with delayed sleep phase syndrome (P=3E10-6).
Conclusions
Considering the inconsistencies between samples and the likelihood that the significant three FMR1 SNPs might be linked to complex polymorphisms more functionally related to depression, large gene resequencing studies may be needed to clarify the import for depression of these circadian genes.
doi:10.1186/1740-3391-11-3
PMCID: PMC3627611  PMID: 23521777
Circadian; Depression; DSPS; FMR1; PPARGC1B; GSK3B; NR1D1; rs25702; rs28900; rs7732671
5.  GENETIC VARIANTS AND BLOOD PRESSURE IN A POPULATION-BASED COHORT: THE CARDIOVASCULAR RISK IN YOUNG FINNS STUDY 
Hypertension  2011;58(6):1079-1085.
Clinical relevance of a genetic predisposition to elevated blood pressure was quantified during the transition from childhood to adulthood in a population-based Finnish cohort (N=2,357). Blood pressure was measured at baseline in 1980 (age 3–18 years) and in follow-ups in 1983, 1986, 2001 and 2007. Thirteen single nucleotide polymorphisms associated with blood pressure were genotyped and three genetic risk scores associated with systolic and diastolic blood pressure and their combination were derived for all participants. Effects of the genetic risk score were 0.47 mmHg for systolic and 0.53 mmHg for diastolic blood pressure (both p<0.01). The combination genetic risk score was associated with diastolic blood pressure from age 9 onwards (β=0.68 mmHg, p=0.015). Replications in 1194 participants of the Bogalusa Heart Study showed essentially similar results. The participants in the highest quintile of the combination genetic risk score had a 1.82-fold risk of hypertension in adulthood (p<0.0001) compared with the lowest quintile, independent of a family history of premature hypertension. These findings show that genetic variants are associated with preclinical blood pressure traits in childhood, individuals with several susceptibility alleles have on average a 0.5 mmHg higher blood pressure and this trajectory continues from childhood to adulthood.
doi:10.1161/HYPERTENSIONAHA.111.179291
PMCID: PMC3247907  PMID: 22025373
Epidemiological study; Genetic risk score; Blood Pressure; Cardiovascular disease
6.  Phases-of-illness paradigm: better communication, better outcomes 
Critical Care  2011;15(6):309.
Communication failures are a significant contributor to medical errors that harm patients. Critical care delivery is a complex system of inter-professional work that is distributed across time, space, and multiple disciplines. Because health-care education and delivery remain siloed by profession, we lack a shared framework within which we discuss and subsequently optimize patient care. Furthermore, our disparate professional perspectives and interests often interfere with our ability to effectively prioritize individual care. It is important, therefore, to develop a cognitively shared framework for understanding a patient's severity of illness and plan of care across multiple, traditionally poorly communicating disciplines. We suggest that the 'phases-of-illness paradigm' will facilitate communication about critically ill patients and create a shared mental model for interdisciplinary patient care. In so doing, this paradigm may reduce communication errors, complications, and costs while improving resource utilization and trainee education. Additional research applications are feasible.
doi:10.1186/cc10335
PMCID: PMC3388705  PMID: 22188663
7.  Age-Dependent Brain Gene Expression and Copy Number Anomalies in Autism Suggest Distinct Pathological Processes at Young Versus Mature Ages 
PLoS Genetics  2012;8(3):e1002592.
Autism is a highly heritable neurodevelopmental disorder, yet the genetic underpinnings of the disorder are largely unknown. Aberrant brain overgrowth is a well-replicated observation in the autism literature; but association, linkage, and expression studies have not identified genetic factors that explain this trajectory. Few studies have had sufficient statistical power to investigate whole-genome gene expression and genotypic variation in the autistic brain, especially in regions that display the greatest growth abnormality. Previous functional genomic studies have identified possible alterations in transcript levels of genes related to neurodevelopment and immune function. Thus, there is a need for genetic studies involving key brain regions to replicate these findings and solidify the role of particular functional pathways in autism pathogenesis. We therefore sought to identify abnormal brain gene expression patterns via whole-genome analysis of mRNA levels and copy number variations (CNVs) in autistic and control postmortem brain samples. We focused on prefrontal cortex tissue where excess neuron numbers and cortical overgrowth are pronounced in the majority of autism cases. We found evidence for dysregulation in pathways governing cell number, cortical patterning, and differentiation in young autistic prefrontal cortex. In contrast, adult autistic prefrontal cortex showed dysregulation of signaling and repair pathways. Genes regulating cell cycle also exhibited autism-specific CNVs in DNA derived from prefrontal cortex, and these genes were significantly associated with autism in genome-wide association study datasets. Our results suggest that CNVs and age-dependent gene expression changes in autism may reflect distinct pathological processes in the developing versus the mature autistic prefrontal cortex. Our results raise the hypothesis that genetic dysregulation in the developing brain leads to abnormal regional patterning, excess prefrontal neurons, cortical overgrowth, and neural dysfunction in autism.
Author Summary
Autism is a disorder characterized by aberrant social, communication, and restricted and repetitive behaviors. It develops clinically in the first years of life. Toddlers and children with autism often exhibit early brain enlargement and excess neuron numbers in the prefrontal cortex. Adults with autism generally do not display enlargement but instead may have a smaller brain size. Thus, we investigated DNA and mRNA patterns in prefrontal cortex from young versus adult postmortem individuals with autism to identify age-related gene expression differences as well as possible genetic correlates of abnormal brain enlargement, excess neuron numbers, and abnormal functioning in this disorder. We found abnormalities in genetic pathways governing cell number, neurodevelopment, and cortical lateralization in autism. We also found that the key pathways associated with autism are different between younger and older autistic individuals. These findings suggest that dysregulated gene pathways in the early stages of neurodevelopment could lead to later behavioral and cognitive deficits associated with autism.
doi:10.1371/journal.pgen.1002592
PMCID: PMC3310790  PMID: 22457638
8.  Longitudinal Replication Studies of GWAS Risk SNPs Influencing Body Mass Index over the Course of Childhood and Adulthood 
PLoS ONE  2012;7(2):e31470.
Genome-wide association studies (GWAS) have identified multiple common variants associated with body mass index (BMI). In this study, we tested 23 genotyped GWAS-significant SNPs (p-value<5*10-8) for longitudinal associations with BMI during childhood (3–17 years) and adulthood (18–45 years) for 658 subjects. We also proposed a heuristic forward search for the best joint effect model to explain the longitudinal BMI variation. After using false discovery rate (FDR) to adjust for multiple tests, childhood and adulthood BMI were found to be significantly associated with six SNPs each (q-value<0.05), with one SNP associated with both BMI measurements: KCTD15 rs29941 (q-value<7.6*10-4). These 12 SNPs are located at or near genes either expressed in the brain (BDNF, KCTD15, TMEM18, MTCH2, and FTO) or implicated in cell apoptosis and proliferation (FAIM2, MAP2K5, and TFAP2B). The longitudinal effects of FAIM2 rs7138803 on childhood BMI and MAP2K5 rs2241423 on adulthood BMI decreased as age increased (q-value<0.05). The FTO candidate SNPs, rs6499640 at the 5 ′-end and rs1121980 and rs8050136 downstream, were associated with childhood and adulthood BMI, respectively, and the risk effects of rs6499640 and rs1121980 increased as birth weight decreased. The best joint effect model for childhood and adulthood BMI contained 14 and 15 SNPs each, with 11 in common, and the percentage of explained variance increased from 0.17% and 9.0*10−6% to 2.22% and 2.71%, respectively. In summary, this study evidenced the presence of long-term major effects of genes on obesity development, implicated in pathways related to neural development and cell metabolism, and different sets of genes associated with childhood and adulthood BMI, respectively. The gene effects can vary with age and be modified by prenatal development. The best joint effect model indicated that multiple variants with effects that are weak or absent alone can nevertheless jointly exert a large longitudinal effect on BMI.
doi:10.1371/journal.pone.0031470
PMCID: PMC3280302  PMID: 22355368
9.  Genetic Profiling Using Genome-Wide Significant Coronary Artery Disease Risk Variants Does Not Improve the Prediction of Subclinical Atherosclerosis: The Cardiovascular Risk in Young Finns Study, the Bogalusa Heart Study and the Health 2000 Survey – A Meta-Analysis of Three Independent Studies 
PLoS ONE  2012;7(1):e28931.
Background
Genome-wide association studies (GWASs) have identified a large number of variants (SNPs) associating with an increased risk of coronary artery disease (CAD). Recently, the CARDIoGRAM consortium published a GWAS based on the largest study population so far. They successfully replicated twelve already known associations and discovered thirteen new SNPs associating with CAD. We examined whether the genetic profiling of these variants improves prediction of subclinical atherosclerosis – i.e., carotid intima-media thickness (CIMT) and carotid artery elasticity (CAE) – beyond classical risk factors.
Subjects and Methods
We genotyped 24 variants found in a population of European ancestry and measured CIMT and CAE in 2001 and 2007 from 2,081, and 2,015 subjects (aged 30–45 years in 2007) respectively, participating in the Cardiovascular Risk in Young Finns Study (YFS). The Bogalusa Heart Study (BHS; n = 1179) was used as a replication cohort (mean age of 37.5). For additional replication, a sub-sample of 5 SNPs was genotyped for 1,291 individuals aged 46–76 years participating in the Health 2000 population survey. We tested the impact of genetic risk score (GRS24SNP/CAD) calculated as a weighted (by allelic odds ratios for CAD) sum of CAD risk alleles from the studied 24 variants on CIMT, CAE, the incidence of carotid atherosclerosis and the progression of CIMT and CAE during a 6-year follow-up.
Results
CIMT or CAE did not significantly associate with GRS24SNP/CAD before or after adjusting for classical CAD risk factors (p>0.05 for all) in YFS or in the BHS. CIMT and CAE associated with only one SNP each in the YFS. The findings were not replicated in the replication cohorts. In the meta-analysis CIMT or CAE did not associate with any of the SNPs.
Conclusion
Genetic profiling, by using known CAD risk variants, should not improve risk stratification for subclinical atherosclerosis beyond conventional risk factors among healthy young adults.
doi:10.1371/journal.pone.0028931
PMCID: PMC3266236  PMID: 22295058
10.  Genome-Wide Association of Implantable Cardioverter-Defibrillator Activation With Life-Threatening Arrhythmias 
PLoS ONE  2012;7(1):e25387.
Objectives
To identify genetic factors that would be predictive of individuals who require an implantable cardioverter-defibrillator (ICD), we conducted a genome-wide association study among individuals with an ICD who experienced a life-threatening arrhythmia (LTA; cases) vs. those who did not over at least a 3-year period (controls).
Background
Most individuals that receive implantable cardioverter-defibrillators never experience a life-threatening arrhythmia. Genetic factors may help identify who is most at risk.
Methods
Patients with an ICD and extended follow-up were recruited from 34 clinical sites with the goal of oversampling those who had experienced LTA, with a cumulative 607 cases and 297 controls included in the analysis. A total of 1,006 Caucasian patients were enrolled during a time period of 13 months. Arrhythmia status of 904 patients could be confirmed and their genomic data were included in the analysis. In this cohort, there were 704 males, 200 females, and the average age was 73.3 years. We genotyped DNA samples using the Illumina Human660 W Genotyping BeadChip and tested for association between genotype at common variants and the phenotype of having an LTA.
Results and Conclusions
We did not find any associations reaching genome-wide significance, with the strongest association at chromosome 13, rs11856574 at P = 5×10−6. Loci previously implicated in phenotypes such as QT interval (measure of the time between the start of the Q wave and the end of the T wave as measured by electrocardiogram) were not found to be significantly associated with having an LTA. Although powered to detect such associations, we did not find common genetic variants of large effect associated with having a LTA in those of European descent. This indicates that common gene variants cannot be used at this time to guide ICD risk-stratification.
Trial Registration
ClinicalTrials.gov NCT00664807
doi:10.1371/journal.pone.0025387
PMCID: PMC3256134  PMID: 22247754
11.  Gene expression profiling of human whole blood samples with the Illumina WG-DASL assay 
BMC Genomics  2011;12:412.
Background
Microarray-based gene expression analysis of peripheral whole blood is a common strategy in the development of clinically relevant biomarker panels for a variety of human diseases. However, the results of such an analysis are often plagued by decreased sensitivity and reliability due to the effects of relatively high levels of globin mRNA in whole blood. Globin reduction assays have been shown to overcome such effects, but they require large amounts of total RNA and may induce distinct gene expression profiles. The Illumina whole genome DASL assay can detect gene expression levels using partially degraded RNA samples and has the potential to detect rare transcripts present in highly heterogeneous whole blood samples without the need for globin reduction. We assessed the utility of the whole genome DASL assay in an analysis of peripheral whole blood gene expression profiles.
Results
We find that gene expression detection is significantly increased with the use of whole genome DASL compared to the standard IVT-based direct hybridization. Additionally, globin-probe negative whole genome DASL did not exhibit significant improvements over globin-probe positive whole genome DASL. Globin reduction further increases the detection sensitivity and reliability of both whole genome DASL and IVT-based direct hybridization with little effect on raw intensity correlations. Raw intensity correlations between total RNA and globin reduced RNA were 0.955 for IVT-based direct hybridization and 0.979 for whole genome DASL.
Conclusions
Overall, the detection sensitivity of the whole genome DASL assay is higher than the IVT-based direct hybridization assay, with or without globin reduction, and should be considered in conjunction with globin reduction methods for future blood-based gene expression studies.
doi:10.1186/1471-2164-12-412
PMCID: PMC3175478  PMID: 21843359
12.  Polymorphisms in melatonin synthesis pathways: possible influences on depression 
Background
It has been reported that rs4446909, a single nucleotide polymorphism (SNP) in the promoter of acetylserotonin methyltransferase (ASMT), influences the expression of the ASMT enzyme. The common G allele is associated with lower ASMT activity, and therefore, diminishes conversion of N-acetylserotonin to melatonin. The G allele was associated with recurrent depressive disorder in a Polish group. ASMT might also affect bipolar relapse, given evidence that N-acetylserotonin might stimulate TRKB receptors, and TRKB may influence mood relapse in bipolar disorder. Additionally, arylalkylamine N-acetyltransferase (AANAT) polymorphisms have been reported associated with depression, perhaps through their influence upon N-acetylserotonin or melatonin synthesis.
Results
To replicate and further explore these ideas, rs4446909 was genotyped in four research groups, as part of a panel of 610 SNPs surveyed by an Illumina Golden Gate assay. In 768 cases with delayed sleep phase disorder or matched controls, rs4446909 was indeed associated with the depressive symptoms on a self-report scale (P = 0.01, R2 = 0.007). However, there was no significant association of rs4446909 with self-reported depression in a sleep clinic patient group or with two groups of elderly men and women from multicenter studies, nor was the response to lithium treatment associated with rs4446909 in bipolar patients. No associations of two AANAT SNPs with depression were found.
Conclusions
The evidence did not support a strong influence of rs4446909 upon mood, but the partial replication may be consistent with a modest effect. It is possible that larger or younger subject groups with improved phenotype ascertainment might demonstrate more persuasive replication.
doi:10.1186/1740-3391-9-8
PMCID: PMC3177871  PMID: 21827647
ASMT; N-acetylserotonin; AANAT; melatonin; serotonin; depression; bipolar disorder; lithium
13.  Genome-Wide Association of Bipolar Disorder Suggests an Enrichment of Replicable Associations in Regions near Genes 
PLoS Genetics  2011;7(6):e1002134.
Although a highly heritable and disabling disease, bipolar disorder's (BD) genetic variants have been challenging to identify. We present new genotype data for 1,190 cases and 401 controls and perform a genome-wide association study including additional samples for a total of 2,191 cases and 1,434 controls. We do not detect genome-wide significant associations for individual loci; however, across all SNPs, we show an association between the power to detect effects calculated from a previous genome-wide association study and evidence for replication (P = 1.5×10−7). To demonstrate that this result is not likely to be a false positive, we analyze replication rates in a large meta-analysis of height and show that, in a large enough study, associations replicate as a function of power, approaching a linear relationship. Within BD, SNPs near exons exhibit a greater probability of replication, supporting an enrichment of reproducible associations near functional regions of genes. These results indicate that there is likely common genetic variation associated with BD near exons (±10 kb) that could be identified in larger studies and, further, provide a framework for assessing the potential for replication when combining results from multiple studies.
Author Summary
Bipolar disorder (BD) is a highly heritable disease that has been difficult to characterize genetically. We have genotyped 1,190 BD cases and 401 controls to find regions of the genome associated with BD. After combining these data with previously existing genotyped samples, we did not find any genome-wide significant associations. However, when we used an additional study to prioritize loci for replication and meta-analysis purposes, we found that we were more likely to see an association in our sample with variants for which we had the highest power. We quantified this effect using logistic regression and saw a strong association between power to detect an effect based on an initial study's results and replication P-value in a second study (P = 1.5×10−7), supporting the presence of shared genetic risk factors across the studies. Moreover, this association was stronger when we restricted analysis to SNPs near coding regions, and it was further enriched when SNPs had the same direction of effect in both studies. This result supports the presence of genetic factors underlying BD near exons whose collective effect results in a detectable signal and provides a framework for assessing the potential for replication when combining results from multiple studies.
doi:10.1371/journal.pgen.1002134
PMCID: PMC3128104  PMID: 21738484
14.  Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level 
Genome Biology  2010;11(11):R118.
Background
Targeted re-sequencing of candidate genes in individuals at the extremes of a quantitative phenotype distribution is a method of choice to gain information on the contribution of rare variants to disease susceptibility. The endocannabinoid system mediates signaling in the brain and peripheral tissues involved in the regulation of energy balance, is highly active in obese patients, and represents a strong candidate pathway to examine for genetic association with body mass index (BMI).
Results
We sequenced two intervals (covering 188 kb) encoding the endocannabinoid metabolic enzymes fatty-acid amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal controls and 142 extremely obese cases. After applying quality filters, we called 1,393 high quality single nucleotide variants, 55% of which are rare, and 143 indels. Using single marker tests and collapsed marker tests, we identified four intervals associated with BMI: the FAAH promoter, the MGLL promoter, MGLL intron 2, and MGLL intron 3. Two of these intervals are composed of rare variants and the majority of the associated variants are located in promoter sequences or in predicted transcriptional enhancers, suggesting a regulatory role. The set of rare variants in the FAAH promoter associated with BMI is also associated with increased level of FAAH substrate anandamide, further implicating a functional role in obesity.
Conclusions
Our study, which is one of the first reports of a sequence-based association study using next-generation sequencing of candidate genes, provides insights into study design and analysis approaches and demonstrates the importance of examining regulatory elements rather than exclusively focusing on exon sequences.
doi:10.1186/gb-2010-11-11-r118
PMCID: PMC3156957  PMID: 21118518
15.  Identification of Mendel's White Flower Character 
PLoS ONE  2010;5(10):e13230.
Background
The genetic regulation of flower color has been widely studied, notably as a character used by Mendel and his predecessors in the study of inheritance in pea.
Methodology/Principal Findings
We used the genome sequence of model legumes, together with their known synteny to the pea genome to identify candidate genes for the A and A2 loci in pea. We then used a combination of genetic mapping, fast neutron mutant analysis, allelic diversity, transcript quantification and transient expression complementation studies to confirm the identity of the candidates.
Conclusions/Significance
We have identified the pea genes A and A2. A is the factor determining anthocyanin pigmentation in pea that was used by Gregor Mendel 150 years ago in his study of inheritance. The A gene encodes a bHLH transcription factor. The white flowered mutant allele most likely used by Mendel is a simple G to A transition in a splice donor site that leads to a mis-spliced mRNA with a premature stop codon, and we have identified a second rare mutant allele. The A2 gene encodes a WD40 protein that is part of an evolutionarily conserved regulatory complex.
doi:10.1371/journal.pone.0013230
PMCID: PMC2952588  PMID: 20949001
17.  Longitudinal Genome-Wide Association of Cardiovascular Disease Risk Factors in the Bogalusa Heart Study 
PLoS Genetics  2010;6(9):e1001094.
Cardiovascular disease (CVD) is the leading cause of death worldwide. Recent genome-wide association (GWA) studies have pinpointed many loci associated with CVD risk factors in adults. It is unclear, however, if these loci predict trait levels at all ages, if they are associated with how a trait develops over time, or if they could be used to screen individuals who are pre-symptomatic to provide the opportunity for preventive measures before disease onset. We completed a genome-wide association study on participants in the longitudinal Bogalusa Heart Study (BHS) and have characterized the association between genetic factors and the development of CVD risk factors from childhood to adulthood. We report 7 genome-wide significant associations involving CVD risk factors, two of which have been previously reported. Top regions were tested for replication in the Young Finns Study (YF) and two associations strongly replicated: rs247616 in CETP with HDL levels (combined P = 9.7×10−24), and rs445925 at APOE with LDL levels (combined P = 8.7×10−19). We show that SNPs previously identified in adult cross-sectional studies tend to show age-independent effects in the BHS with effect sizes consistent with previous reports. Previously identified variants were associated with adult trait levels above and beyond those seen in childhood; however, variants with time-dependent effects were also promising predictors. This is the first GWA study to evaluate the role of common genetic variants in the development of CVD risk factors in children as they advance through adulthood and highlights the utility of using longitudinal studies to identify genetic predictors of adult traits in children.
Author Summary
We have studied the association between genetic factors on a whole genome level and cardiovascular disease (CVD) risk factors in a population of individuals studied from childhood through adulthood. The longitudinal study design has enabled the investigation of genetic variation influencing trait values over time. We have identified DNA variants that are associated with CVD trait values consistently over time, and a second set of variants that are associated with CVD trait values in a time-dependent manner. We also show that variants previously identified in adult populations have consistent effects within our population and that these effects are usually similar across childhood through adulthood. The discovery of time-dependent variants that influence CVD trait values over time can potentially be used to screen young individuals who are pre-symptomatic and provide the opportunity for preventive measures decades before disease onset.
doi:10.1371/journal.pgen.1001094
PMCID: PMC2936521  PMID: 20838585
18.  Common vs. Rare Allele Hypotheses for Complex Diseases 
There has been growing debate over the nature of the genetic contribution to individual susceptibility to common complex diseases such as diabetes, osteoporosis, and cancer. The ‘Common Disease, Common Variant (CDCV)’ hypothesis argues that genetic variations with appreciable frequency in the population at large, but relatively low ‘penetrance’ (or the probability that a carrier of the relevant variants will express the disease), are the major contributors to genetic susceptibility to common diseases. The ‘Common Disease, Rare Variant (CDRV)’ hypothesis, on the other hand, argues that multiple rare DNA sequence variations, each with relatively high penetrance, are the major contributors to genetic susceptibility to common diseases. Both hypotheses have their place in current research efforts.
doi:10.1016/j.gde.2009.04.010
PMCID: PMC2914559  PMID: 19481926
19.  Biomarkers of Endocannabinoid System Activation in Severe Obesity 
PLoS ONE  2010;5(1):e8792.
Background
Obesity is a worldwide epidemic, and severe obesity is a risk factor for many diseases, including diabetes, heart disease, stroke, and some cancers. Endocannabinoid system (ECS) signaling in the brain and peripheral tissues is activated in obesity and plays a role in the regulation of body weight. The main research question here was whether quantitative measurement of plasma endocannabinoids, anandamide, and related N-acylethanolamines (NAEs), combined with genotyping for mutations in fatty acid amide hydrolase (FAAH) would identify circulating biomarkers of ECS activation in severe obesity.
Methodology/Principal Findings
Plasma samples were obtained from 96 severely obese subjects with body mass index (BMI) of ≥40 kg/m2, and 48 normal weight subjects with BMI of ≤26 kg/m2. Triple-quadrupole mass spectroscopy methods were used to measure plasma ECS analogs. Subjects were genotyped for human FAAH gene mutations. The principal analysis focused on the FAAH 385 C→A (P129T) mutation by comparing plasma ECS metabolite levels in the FAAH 385 minor A allele carriers versus wild-type C/C carriers in both groups. The main finding was significantly elevated mean plasma levels of anandamide (15.1±1.4 pmol/ml) and related NAEs in study subjects that carried the FAAH 385 A mutant alleles versus normal subjects (13.3±1.0 pmol/ml) with wild-type FAAH genotype (p = 0.04), and significance was maintained after controlling for BMI.
Conclusions/Significance
Significantly increased levels of the endocannabinoid anandamide and related NAEs were found in carriers of the FAAH 385 A mutant alleles compared with wild-type FAAH controls. This evidence supports endocannabinoid system activation due to the effect of FAAH 385 mutant A genotype on plasma AEA and related NAE analogs. This is the first study to document that FAAH 385 A mutant alleles have a direct effect on elevated plasma levels of anandamide and related NAEs in humans. These biomarkers may indicate risk for severe obesity and may suggest novel ECS obesity treatment strategies.
doi:10.1371/journal.pone.0008792
PMCID: PMC2808340  PMID: 20098695
20.  A high resolution HLA and SNP haplotype map for disease association studies in the extended human MHC 
Nature genetics  2006;38(10):1166-1172.
The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and play an essential role in self/non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune disease1. Yet identification of causal variants is problematic due to linkage disequilibrium (LD) that extends across multiple HLA and non-HLA genes in the MHC2,3. We therefore set out to characterize the LD patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common single nucleotide polymorphisms (SNPs) and deletion/insertion polymorphisms (DIPs) across four population samples. The analysis provides informative tag SNPs that capture some of the variation in the MHC region and that could be used in initial disease association studies, and provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.
doi:10.1038/ng1885
PMCID: PMC2670196  PMID: 16998491
21.  Evaluation of next generation sequencing platforms for population targeted sequencing studies 
Genome Biology  2009;10(3):R32.
Human sequence generated from three next-generation sequencing platforms reveals systematic variability in sequence coverage due to local sequence characteristics.
Background
Next generation sequencing (NGS) platforms are currently being utilized for targeted sequencing of candidate genes or genomic intervals to perform sequence-based association studies. To evaluate these platforms for this application, we analyzed human sequence generated by the Roche 454, Illumina GA, and the ABI SOLiD technologies for the same 260 kb in four individuals.
Results
Local sequence characteristics contribute to systematic variability in sequence coverage (>100-fold difference in per-base coverage), resulting in patterns for each NGS technology that are highly correlated between samples. A comparison of the base calls to 88 kb of overlapping ABI 3730xL Sanger sequence generated for the same samples showed that the NGS platforms all have high sensitivity, identifying >95% of variant sites. At high coverage, depth base calling errors are systematic, resulting from local sequence contexts; as the coverage is lowered additional 'random sampling' errors in base calling occur.
Conclusions
Our study provides important insights into systematic biases and data variability that need to be considered when utilizing NGS platforms for population targeted sequencing studies.
doi:10.1186/gb-2009-10-3-r32
PMCID: PMC2691003  PMID: 19327155
22.  Concept, Design and Implementation of a Cardiovascular Gene-Centric 50 K SNP Array for Large-Scale Genomic Association Studies 
PLoS ONE  2008;3(10):e3583.
A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a “cosmopolitan” tagging approach to capture the genetic diversity across ∼2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.
doi:10.1371/journal.pone.0003583
PMCID: PMC2571995  PMID: 18974833
23.  Power to Detect Risk Alleles Using Genome-Wide Tag SNP Panels 
PLoS Genetics  2007;3(10):e170.
Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ∼ 1.8–2.0). Relative risks as low as λ ∼ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data.
Author Summary
Advances in high-throughput genotyping technology and the International HapMap Project have enabled genetic association studies at the whole-genome level. Our paper describes two genome-wide SNP panels that contain tag SNPs derived from the International HapMap Project. Tag SNPs are proxies for groups of highly correlated SNPs. Information can be captured for the entire group of correlated SNPs by genotyping only one representative SNP, the tag SNP. These whole-genome SNP panels also contain additional content thought to be overrepresented in disease, such as amino acid–changing nonsynonymous SNPs and mitochondrial SNPs. We show that these panels cover the genome with very high efficiency as measured by coverage of all HapMap SNPs and a set of SNPs derived from completely resequenced genes from the Seattle SNPs database. We also show that these panels have high power to detect disease risk alleles for both HapMap and non-HapMap SNPs. In complex disease where multiple risk alleles are believed to be involved, we show that the ability to detect at least one risk allele with the tag SNP panels is also high.
doi:10.1371/journal.pgen.0030170
PMCID: PMC2000969  PMID: 17922574
24.  Power to Detect Risk Alleles Using Genome-Wide Tag SNP Panels 
PLoS Genetics  2007;3(10):e170.
Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ∼ 1.8–2.0). Relative risks as low as λ ∼ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data.
Author Summary
Advances in high-throughput genotyping technology and the International HapMap Project have enabled genetic association studies at the whole-genome level. Our paper describes two genome-wide SNP panels that contain tag SNPs derived from the International HapMap Project. Tag SNPs are proxies for groups of highly correlated SNPs. Information can be captured for the entire group of correlated SNPs by genotyping only one representative SNP, the tag SNP. These whole-genome SNP panels also contain additional content thought to be overrepresented in disease, such as amino acid–changing nonsynonymous SNPs and mitochondrial SNPs. We show that these panels cover the genome with very high efficiency as measured by coverage of all HapMap SNPs and a set of SNPs derived from completely resequenced genes from the Seattle SNPs database. We also show that these panels have high power to detect disease risk alleles for both HapMap and non-HapMap SNPs. In complex disease where multiple risk alleles are believed to be involved, we show that the ability to detect at least one risk allele with the tag SNP panels is also high.
doi:10.1371/journal.pgen.0030170
PMCID: PMC2000969  PMID: 17922574
25.  Characterization of the Capsid Protein Glycosylation of Adeno-Associated Virus Type 2 by High-Resolution Mass Spectrometry†  
Journal of Virology  2006;80(12):6171-6176.
Adeno-associated virus type 2 (AAV-2) capsid proteins have eight sequence motifs that are potential sites for O- or N-linked glycosylation. Three are in prominent surface locations, close to the sites of cellular receptor attachment and to neutralizing epitopes on or near protrusions surrounding the three-fold axes, raising the possibility that AAV-2 might use glycosylation as a means of immune escape or for preventing reattachment on release of progeny virus. Peptide mapping and structural analysis by Fourier transform ion cyclotron resonance mass spectrometry demonstrates, however, no glycosylation of the capsid protein for virus prepared in cultured HeLa cells.
doi:10.1128/JVI.02417-05
PMCID: PMC1472596  PMID: 16731956

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