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1.  Copy number variation prevalence in known asthma genes and their impact on asthma susceptibility 
Background
Genetic studies have identified numerous genes reproducibly associated with asthma, yet these studies have focused almost entirely on single nucleotide polymorphisms (SNPs), and virtually ignored another highly prevalent form of genetic variation: Copy Number Variants (CNVs).
Objective
To survey the prevalence of CNVs in genes previously associated with asthma, and to assess whether CNVs represent the functional asthma-susceptibility variants at these loci.
Methods
We genotyped 383 asthmatic trios participating in the Childhood Asthma Management Program (CAMP) using a competitive genomic hybridization (CGH) array designed to interrogate 20,092 CNVs. To ensure comprehensive assessment of all potential asthma candidate genes, we purposely used liberal asthma gene inclusion criteria, resulting in consideration of 270 candidate genes previously implicated in asthma. We performed statistical testing using FBAT-CNV.
Results
Copy number variation in asthma candidate genes was prevalent, with 21% of tested genes residing near or within one of 69 CNVs. In 6 instances, the complete candidate gene sequence resides within the CNV boundaries. On average, asthmatic probands carried 6 asthma-candidate CNVs (range 1–29). However, the vast majority of identified CNVs were of rare frequency (< 5%), and were not statistically associated with asthma. Modest evidence for association with asthma was observed for 2 CNVs near NOS1 and SERPINA3. Linkage disequilibrium analysis suggests that CNV effects are unlikely to explain previously detected SNP associations with asthma.
Conclusions
Although a substantial proportion of asthma-susceptibility genes harbor polymorphic CNVs, the majority of these variants do not confer increased asthma risk. The lack of linkage disequilibrium (LD) between CNVs and asthma-associated SNPs suggests that these CNVs are unlikely to represent the functional variant responsible for most known asthma associations.
doi:10.1111/cea.12060
PMCID: PMC3609036  PMID: 23517041
2.  An integrated clinico-metabolomic model improves prediction of death in sepsis 
Science translational medicine  2013;5(195):195ra95.
Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features, and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would die differed markedly from those who would survive. The different profiles of proteins and metabolites clustered into fatty acid transport and β-oxidation, gluconeogenesis and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of seven metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.
doi:10.1126/scitranslmed.3005893
PMCID: PMC3924586  PMID: 23884467
4.  Metabolomic Derangements Are Associated with Mortality in Critically Ill Adult Patients 
PLoS ONE  2014;9(1):e87538.
Objective
To identify metabolomic biomarkers predictive of Intensive Care Unit (ICU) mortality in adults.
Rationale
Comprehensive metabolomic profiling of plasma at ICU admission to identify biomarkers associated with mortality has recently become feasible.
Methods
We performed metabolomic profiling of plasma from 90 ICU subjects enrolled in the BWH Registry of Critical Illness (RoCI). We tested individual metabolites and a Bayesian Network of metabolites for association with 28-day mortality, using logistic regression in R, and the CGBayesNets Package in MATLAB. Both individual metabolites and the network were tested for replication in an independent cohort of 149 adults enrolled in the Community Acquired Pneumonia and Sepsis Outcome Diagnostics (CAPSOD) study.
Results
We tested variable metabolites for association with 28-day mortality. In RoCI, nearly one third of metabolites differed among ICU survivors versus those who died by day 28 (N = 57 metabolites, p<.05). Associations with 28-day mortality replicated for 31 of these metabolites (with p<.05) in the CAPSOD population. Replicating metabolites included lipids (N = 14), amino acids or amino acid breakdown products (N = 12), carbohydrates (N = 1), nucleotides (N = 3), and 1 peptide. Among 31 replicated metabolites, 25 were higher in subjects who progressed to die; all 6 metabolites that are lower in those who die are lipids. We used Bayesian modeling to form a metabolomic network of 7 metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20:4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine). This network achieved a 91% AUC predicting 28-day mortality in RoCI, and 74% of the AUC in CAPSOD (p<.001 in both populations).
Conclusion
Both individual metabolites and a metabolomic network were associated with 28-day mortality in two independent cohorts. Metabolomic profiling represents a valuable new approach for identifying novel biomarkers in critically ill patients.
doi:10.1371/journal.pone.0087538
PMCID: PMC3907548  PMID: 24498130
5.  Circulating Mitochondrial DNA in Patients in the ICU as a Marker of Mortality: Derivation and Validation 
PLoS Medicine  2013;10(12):e1001577.
In this paper, Choi and colleagues analyzed levels of mitochondrial DNA in two prospective observational cohort studies and found that increased mtDNA levels are associated with ICU mortality, and improve risk prediction in medical ICU patients. The data suggests that mtDNA could serve as a viable plasma biomarker in MICU patients.
Background
Mitochondrial DNA (mtDNA) is a critical activator of inflammation and the innate immune system. However, mtDNA level has not been tested for its role as a biomarker in the intensive care unit (ICU). We hypothesized that circulating cell-free mtDNA levels would be associated with mortality and improve risk prediction in ICU patients.
Methods and Findings
Analyses of mtDNA levels were performed on blood samples obtained from two prospective observational cohort studies of ICU patients (the Brigham and Women's Hospital Registry of Critical Illness [BWH RoCI, n = 200] and Molecular Epidemiology of Acute Respiratory Distress Syndrome [ME ARDS, n = 243]). mtDNA levels in plasma were assessed by measuring the copy number of the NADH dehydrogenase 1 gene using quantitative real-time PCR. Medical ICU patients with an elevated mtDNA level (≥3,200 copies/µl plasma) had increased odds of dying within 28 d of ICU admission in both the BWH RoCI (odds ratio [OR] 7.5, 95% CI 3.6–15.8, p = 1×10−7) and ME ARDS (OR 8.4, 95% CI 2.9–24.2, p = 9×10−5) cohorts, while no evidence for association was noted in non-medical ICU patients. The addition of an elevated mtDNA level improved the net reclassification index (NRI) of 28-d mortality among medical ICU patients when added to clinical models in both the BWH RoCI (NRI 79%, standard error 14%, p<1×10−4) and ME ARDS (NRI 55%, standard error 20%, p = 0.007) cohorts. In the BWH RoCI cohort, those with an elevated mtDNA level had an increased risk of death, even in analyses limited to patients with sepsis or acute respiratory distress syndrome. Study limitations include the lack of data elucidating the concise pathological roles of mtDNA in the patients, and the limited numbers of measurements for some of biomarkers.
Conclusions
Increased mtDNA levels are associated with ICU mortality, and inclusion of mtDNA level improves risk prediction in medical ICU patients. Our data suggest that mtDNA could serve as a viable plasma biomarker in medical ICU patients.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Intensive care units (ICUs, also known as critical care units) are specialist hospital wards that provide care for people with life-threatening injuries and illnesses. In the US alone, more than 5 million people are admitted to ICUs every year. Different types of ICUs treat different types of problems. Medical ICUs treat patients who, for example, have been poisoned or who have a serious infection such as sepsis (blood poisoning) or severe pneumonia (inflammation of the lungs); trauma ICUs treat patients who have sustained a major injury; cardiac ICUs treat patients who have heart problems; and surgical ICUs treat complications arising from operations. Patients admitted to ICUs require constant medical attention and support from a team of specially trained nurses and physicians to prevent organ injury and to keep their bodies functioning. Monitors, intravenous tubes (to supply essential fluids, nutrients, and drugs), breathing machines, catheters (to drain urine), and other equipment also help to keep ICU patients alive.
Why Was This Study Done?
Although many patients admitted to ICUs recover, others do not. ICU specialists use scoring systems (algorithms) based on clinical signs and physiological measurements to predict their patients' likely outcomes. For example, the APACHE II scoring system uses information on heart and breathing rates, temperature, levels of salts in the blood, and other signs and physiological measurements collected during the first 24 hours in the ICU to predict the patient's risk of death. Existing scoring systems are not perfect, however, and “biomarkers” (molecules in bodily fluids that provide information about a disease state) are needed to improve risk prediction for ICU patients. Here, the researchers investigate whether levels of circulating cell-free mitochondrial DNA (mtDNA) are associated with ICU deaths and whether these levels can be used as a biomarker to improve risk prediction in ICU patients. Mitochondria are cellular structures that produce energy. Levels of mtDNA in the plasma (the liquid part of blood) increase in response to trauma and infection. Moreover, mtDNA activates molecular processes that lead to inflammation and organ injury.
What Did the Researchers Do and Find?
The researchers measured mtDNA levels in the plasma of patients enrolled in two prospective observational cohort studies that monitored the outcomes of ICU patients. In the Brigham and Women's Hospital Registry of Critical Illness study, blood was taken from 200 patients within 24 hours of admission into the hospital's medical ICU. In the Molecular Epidemiology of Acute Respiratory Distress Syndrome study (acute respiratory distress syndrome is a life-threatening inflammatory reaction to lung damage or infection), blood was taken from 243 patients within 48 hours of admission into medical and non-medical ICUs at two other US hospitals. Patients admitted to medical ICUs with a raised mtDNA level (3,200 or more copies of a specific mitochondrial gene per microliter of plasma) had a 7- to 8-fold increased risk of dying within 28 days of admission compared to patients with mtDNA levels of less than 3,200 copies/µl plasma. There was no evidence of an association between raised mtDNA levels and death among patients admitted to non-medical ICUs. The addition of an elevated mtDNA level to a clinical model for risk prediction that included the APACHE II score and biomarkers that are already used to predict ICU outcomes improved the net reclassification index (an indicator of the improvement in risk prediction algorithms offered by new biomarkers) of 28-day mortality among medical ICU patients in both studies.
What Do These Findings Mean?
These findings indicate that raised mtDNA plasma levels are associated with death in medical ICUs and show that, among patients in medical ICUs, measurement of mtDNA plasma levels can improve the prediction of the risk of death from the APACHE II scoring system, even when commonly measured biomarkers are taken into account. These findings do not indicate whether circulating cell-free mtDNA increased because of the underlying severity of illness or whether mtDNA actively contributes to the disease process in medical ICU patients. Moreover, they do not provide any evidence that raised mtDNA levels are associated with an increased risk of death among non-medical (mainly surgical) ICU patients. These findings need to be confirmed in additional patients, but given the relative ease and rapidity of mtDNA measurement, the determination of circulating cell-free mtDNA levels could be a valuable addition to the assessment of patients admitted to medical ICUs.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001577.
The UK National Health Service Choices website provides information about intensive care
The Society of Critical Care Medicine provides information for professionals, families, and patients about all aspects of intensive care
MedlinePlus provides links to other resources about intensive care (in English and Spanish)
The UK charity ICUsteps supports patients and their families through recovery from critical illness; its booklet Intensive Care: A Guide for Patients and Families is available in English and ten other languages; its website includes patient experiences and relative experiences of treatment in ICUs
Wikipedia has a page on ICU scoring systems (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001577
PMCID: PMC3876981  PMID: 24391478
6.  Inflammasome-regulated Cytokines Are Critical Mediators of Acute Lung Injury 
Rationale: Despite advances in clinical management, there are currently no reliable diagnostic and therapeutic targets for acute respiratory distress syndrome (ARDS). The inflammasome/caspase-1 pathway regulates the maturation and secretion of proinflammatory cytokines (e.g., IL-18). IL-18 is associated with injury in animal models of systemic inflammation.
Objectives: We sought to determine the contribution of the inflammasome pathway in experimental acute lung injury and human ARDS.
Methods: We performed comprehensive gene expression profiling on peripheral blood from patients with critical illness. Gene expression changes were assessed using real-time polymerase chain reaction, and IL-18 levels were measured in the plasma of the critically ill patients. Wild-type mice or mice genetically deficient in IL-18 or caspase-1 were mechanically ventilated using moderate tidal volume (12 ml/kg). Lung injury parameters were assessed in lung tissue, serum, and bronchoalveolar lavage fluid.
Measurements and Main Results: In mice, mechanical ventilation enhanced IL-18 levels in the lung, serum, and bronchoalveolar lavage fluid. IL-18–neutralizing antibody treatment, or genetic deletion of IL-18 or caspase-1, reduced lung injury in response to mechanical ventilation. In human patients with ARDS, inflammasome-related mRNA transcripts (CASP1, IL1B, and IL18) were increased in peripheral blood. In samples from four clinical centers, IL-18 was elevated in the plasma of patients with ARDS (sepsis or trauma-induced ARDS) and served as a novel biomarker of intensive care unit morbidity and mortality.
Conclusions: The inflammasome pathway and its downstream cytokines play critical roles in ARDS development.
doi:10.1164/rccm.201201-0003OC
PMCID: PMC3373064  PMID: 22461369
acute respiratory distress syndrome; inflammasome; interleukin-18; mechanical ventilation
7.  Copy number variation genotyping using family information 
BMC Bioinformatics  2013;14:157.
Background
In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies.
Results
To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments.
Conclusions
In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs.
doi:10.1186/1471-2105-14-157
PMCID: PMC3668900  PMID: 23656838
8.  On the genome-wide analysis of copy number variants in family-based designs: Methods for combining family-based and population based information for testing dichotomous or quantitative traits, or completely ascertained samples 
Genetic Epidemiology  2010;34(6):582-590.
We propose a new approach for the analysis of copy number variants (CNVs)for genome-wide association studies in family-based designs. Our new overall association test combines the between-family component and the within-family component of the data so that the new test statistic is fully efficient and, at the same time, achieves the complete robustness against population-admixture and stratification, as classical family-based association tests that are based only on the between-family component. Although all data are incorporated into the test statistic, an adjustment for genetic confounding is not needed, not even for the between-family component. The new test statistic is valid for testing either quantitative or dichotomous phenotypes. If external CNV data are available, the approach can also be used in completely ascertained samples. Similar to the approach by Ionita-Laza et al.(1), the proposed test statistic does not required a CNV-calling algorithm and is based directly on the CNV probe intensity data. We show, via simulation studies, that our methodology increases the power of the FBAT statistic to levels comparable to those of population-based designs. The advantages of the approach in practice are demonstrated by an application to a genome-wide association study for body mass index (BMI).
doi:10.1002/gepi.20515
PMCID: PMC3349936  PMID: 20718041
9.  The CD4+ T-cell transcriptome and serum IgE in asthma: IL17RB and the role of sex 
Background
The relationships between total serum IgE levels and gene expression patterns in peripheral blood CD4+ T cells (in all subjects and within each sex specifically) are not known.
Methods
Peripheral blood CD4+ T cells from 223 participants from the Childhood Asthma Management Program (CAMP) with simultaneous measurement of IgE. Total RNA was isolated, and expression profiles were generated with Illumina HumanRef8 v2 BeadChip arrays. Modeling of the relationship between genome-wide gene transcript levels and IgE levels was performed in all subjects, and stratified by sex.
Results
Among all subjects, significant evidence for association between gene transcript abundance and IgE was identified for a single gene, the interleukin 17 receptor B (IL17RB), explaining 12% of the variance (r2) in IgE measurement (p value = 7 × 10-7, 9 × 10-3 after adjustment for multiple testing). Sex stratified analyses revealed that the correlation between IL17RB and IgE was restricted to males only (r2 = 0.19, p value = 8 × 10-8; test for sex-interaction p < 0.05). Significant correlation between gene transcript abundance and IgE level was not found in females. Additionally we demonstrated substantial sex-specific differences in IgE when considering multi-gene models, and in canonical pathway analyses of IgE level.
Conclusions
Our results indicate that IL17RB may be the only gene expressed in CD4+ T cells whose transcript measurement is correlated with the variation in IgE level in asthmatics. These results provide further evidence sex may play a role in the genomic regulation of IgE.
doi:10.1186/1471-2466-11-17
PMCID: PMC3080837  PMID: 21473777
10.  A Role for Wnt Signaling Genes in the Pathogenesis of Impaired Lung Function in Asthma 
Rationale: Animal models demonstrate that aberrant gene expression in utero can result in abnormal pulmonary phenotypes.
Objectives: We sought to identify genes that are differentially expressed during in utero airway development and test the hypothesis that variants in these genes influence lung function in patients with asthma.
Methods: Stage 1 (Gene Expression): Differential gene expression analysis across the pseudoglandular (n = 27) and canalicular (n = 9) stages of human lung development was performed using regularized t tests with multiple comparison adjustments. Stage 2 (Genetic Association): Genetic association analyses of lung function (FEV1, FVC, and FEV1/FVC) for variants in five differentially expressed genes were conducted in 403 parent-child trios from the Childhood Asthma Management Program (CAMP). Associations were replicated in 583 parent-child trios from the Genetics of Asthma in Costa Rica study.
Measurements and Main Results: Of the 1,776 differentially expressed genes between the pseudoglandular (gestational age: 7–16 wk) and the canalicular (gestational age: 17–26 wk) stages, we selected 5 genes in the Wnt pathway for association testing. Thirteen single nucleotide polymorphisms in three genes demonstrated association with lung function in CAMP (P < 0.05), and associations for two of these genes were replicated in the Costa Ricans: Wnt1-inducible signaling pathway protein 1 with FEV1 (combined P = 0.0005) and FVC (combined P = 0.0004), and Wnt inhibitory factor 1 with FVC (combined P = 0.003) and FEV1/FVC (combined P = 0.003).
Conclusions: Wnt signaling genes are associated with impaired lung function in two childhood asthma cohorts. Furthermore, gene expression profiling of human fetal lung development can be used to identify genes implicated in the pathogenesis of lung function impairment in individuals with asthma.
doi:10.1164/rccm.200907-1009OC
PMCID: PMC2822972  PMID: 19926868
asthma; lung development; lung function; genetic variation; gene expression
11.  The interaction of GSTM1 null variants with tobacco smoke exposure and the development of childhood asthma 
Background
The glutathione S-transferase M1 (GSTM1) null variant is a common copy number variant associated with adverse pulmonary outcomes, including asthma and airflow obstruction, with evidence of important gene-by-environment interactions with exposures to oxidative stress.
Objective
To explore the joint interactive effects of GSTM1 copy number and tobacco smoke exposure on the development of asthma and asthma-related phenotypes in a family-based cohort of childhood asthmatics.
Methods
We performed quantitative PCR-based genotyping for GSTM1 copy number in children of self-reported white ancestry with mild to moderate asthma in the Childhood Asthma Management Program. Questionnaire data regarding intrauterine (IUS) and postnatal, longitudinal environmental tobacco smoke exposure were available. We performed both family-based and population-based tests of association for the interaction between GSTM1 copy number and tobacco smoke exposure with asthma and asthma-related phenotypes.
Results
Associations of GSTM1 null variants with asthma (p= .03), younger age of asthma symptom onset (p=.03), and greater airflow obstruction (reduced FEV1/FVC, p=.01) were observed among the 50 children (10% of the cohort) with exposure to IUS. In contrast, no associations were observed between GSTM1 null variants and asthma-related phenotypes among children without IUS exposure. Presence of at least one copy of GSTM1 conferred protection.
Conclusion
These findings support an important gene-by-environment interaction between two common factors: increased risk of asthma and asthma-related phenotypes conferred by GSTM1-null homozygosity in children is restricted to those with a history of IUS exposure.
doi:10.1111/j.1365-2222.2009.03372.x
PMCID: PMC2773694  PMID: 19860819
Asthma; GSTM1; copy number variation (CNV); gene by environment; intrauterine smoke exposure; tobacco smoke
12.  Assessing the Reproducibility of Asthma Candidate Gene Associations, Using Genome-wide Data 
Rationale: Association studies have implicated many genes in asthma pathogenesis, with replicated associations between single-nucleotide polymorphisms (SNPs) and asthma reported for more than 30 genes. Genome-wide genotyping enables simultaneous evaluation of most of this variation, and facilitates more comprehensive analysis of other common genetic variation around these candidate genes for association with asthma.
Objectives: To use available genome-wide genotypic data to assess the reproducibility of previously reported associations with asthma and to evaluate the contribution of additional common genetic variation surrounding these loci to asthma susceptibility.
Methods: Illumina Human Hap 550Kv3 BeadChip (Illumina, San Diego, CA) SNP arrays were genotyped in 422 nuclear families participating in the Childhood Asthma Management Program. Genes with at least one SNP demonstrating prior association with asthma in two or more populations were tested for evidence of association with asthma, using family-based association testing.
Measurements and Main Results: We identified 39 candidate genes from the literature, using prespecified criteria. Of the 160 SNPs previously genotyped in these 39 genes, 10 SNPs in 6 genes were significantly associated with asthma (including the first independent replication for asthma-associated integrin β3 [ITGB3]). Evaluation of 619 additional common variants included in the Illumina 550K array revealed additional evidence of asthma association for 15 genes, although none were significant after adjustment for multiple comparisons.
Conclusions: We replicated asthma associations for a minority of candidate genes. Pooling genome-wide association study results from multiple studies will increase the power to appreciate marginal effects of genes and further clarify which candidates are true “asthma genes.”
doi:10.1164/rccm.200812-1860OC
PMCID: PMC2695495  PMID: 19264973
asthma; replication; single-nucleotide polymorphism; integrin β3; association
13.  Predictors of poor response during asthma therapy differ with definition of outcome 
Pharmacogenomics  2009;10(8):1231-1242.
Aims
To evaluate phenotypic and genetic variables associated with a poor long-term response to inhaled corticosteroid therapy for asthma, based independently on lung function changes or asthma exacerbations.
Materials & methods
We tested 17 phenotypic variables and polymorphisms in FCER2 and CRHR1 in 311 children (aged 5–12 years) randomized to a 4-year course of inhaled corticosteroid during the Childhood Asthma Management Program (CAMP).
Results
Predictors of recurrent asthma exacerbations are distinct from predictors of poor lung function response. A history of prior asthma exacerbations, younger age and a higher IgE level (p < 0.05) are associated with recurrent exacerbations. By contrast, lower bronchodilator response to albuterol and the minor alleles of RS242941 in CRHR1 and T2206C in FCER2 (p < 0.05) are associated with poor lung function response. Poor lung function response does not increase the risk of exacerbations and vice versa (p = 0.72).
Conclusion
Genetic and phenotypic predictors of a poor long-term response to inhaled corticosteroids differ markedly depending on definition of outcome (based on exacerbations vs lung function). These findings are important in comparing outcomes of clinical trials and in designing future pharmacogenetic studies.
doi:10.2217/PGS.09.86
PMCID: PMC2746392  PMID: 19663668
asthma; corticosteroid; exacerbation; lung function; pharmacogenetics
14.  GENETIC ASSOCIATION ANALYSIS OF COPY NUMBER VARIATION (CNVs) IN HUMAN DISEASE PATHOGENESIS 
Genomics  2008;93(1):22-26.
Structural genetic variation, including copy number variation (CNV), constitutes a substantial fraction of total genetic variability and the importance of structural genetic variants in modulating human disease is increasingly being recognized. Early successes in identifying disease-associated CNVs via a candidate gene approach mandate that future disease association studies need to include structural genetic variation. Such analyses should not rely on previously developed methodologies that were designed to evaluate single nucleotide polymorphisms (SNPs). Instead, development of novel technical, statistical, and epidemiologic methods will be necessary to optimally capture this newly-appreciated form of genetic variation in a meaningful manner.
doi:10.1016/j.ygeno.2008.08.012
PMCID: PMC2631358  PMID: 18822366
Copy number variation; CNV; structural genetic variation; disease association study; complex trait

Results 1-14 (14)