African Americans are a genetically diverse population with a high burden of many, common heritable diseases. However, our understanding of genetic variation in African Americans is substandard because of a lack of published population-based genetic studies. We report the distribution of copy-number variation (CNV) in African Americans collected as part of the Hypertension Genetic Epidemiology Network (HyperGEN) using the Affymetrix 6.0 array and the CNV calling algorithms Birdsuite and PennCNV. We present population estimates of CNV from 446 unrelated African-American subjects randomly selected from the 451 families collected within HyperGEN. Although the majority of CNVs discovered were individually rare, we found the frequency of CNVs to be collectively high. We identified a total of 11 070 CNVs greater than 10 kb passing quality control criteria that were called by both algorithms – leading to an average of 24.8 CNVs per person covering 2214 kb (median). We identified 1541 unique copy-number variable regions, 309 of which did not overlap with the Database of Genomic Variants. These results provide further insight into the distribution of CNV in African Americans.

Many rodent experiments have assessed effects of diets, drugs, genes, and other factors on life span. A challenge with such experiments is their long duration, typically over 3.5 years given rodent life spans, thus requiring significant time costs until answers are obtained. We collected longevity data from 15 rodent studies and artificially truncated them at 2 years to assess the extent to which one will obtain the same answer regarding mortality effects. When truncated, the point estimates were not significantly different in any study, implying that in most cases, truncated studies yield similar estimates. The median ratio of variances of coefficients for truncated to full-length studies was 3.4, implying that truncated studies with roughly 3.4 times as many rodents will often have equivalent or greater power. Cost calculations suggest that shorter studies will be more expensive but perhaps not so much to not be worth the reduced time.

Host genetic variation, particularly within the human leukocyte antigen (HLA) loci, reportedly mediates heterogeneity in immune response to certain vaccines; however, no large study of genetic determinants of anthrax vaccine response has been described. We searched for associations between the IgG antibody to protective antigen (AbPA) response to Anthrax Vaccine Adsorbed (AVA) in humans and polymorphisms at HLA class I (HLA-A, -B, and -C) and class II (HLA-DRB1, -DQA1, -DQB1, -DPB1) loci. The study included 794 European-Americans and 200 African-Americans participating in a 43-month, double-blind, placebo-controlled, clinical trial of AVA (clinicaltrials.gov identifier NCT00119067). Among European-Americans, genes from tightly linked HLA-DRB1-DQA1-DQB1 haplotypes displayed significant overall associations with longitudinal variation in AbPA levels at 4, 8, 26, and 30 weeks from baseline in response to vaccination with 3 or 4 doses of AVA (global p=6.53×10−4). In particular, carriage of the DRB1-DQA1-DQB1 haplotypes *1501-*0102-*0602 (p=1.17×10−5), *0101-*0101-*0501 (p=0.009), and *0102-*0101-*0501 (p=0.006) was associated with significantlylower AbPA levels. In carriers of two copies of these haplotypes, lower AbPA levels persisted following subsequent vaccinations. No significant associations were observed amongst African-Americans or for any HLA class I allele/haplotype. Further studies will be required to replicate these findings and to explore the role of host genetic variation outside of the HLA region.

There is growing evidence that much more of the genome than previously thought is required to explain the heritability of complex phenotypes. Recent studies have demonstrated that numerous common variants from across the genome explain portions of genetic variability, spawning various avenues of research directed at explaining the remaining heritability. This polygenic structure is also the motivation for the growing application of pathway and gene set enrichment techniques, which have yielded promising results. These findings suggest that the coordination of genes in pathways that are known to occur at the gene regulatory level also can be detected at the population level. Although genes in these networks interact in complex ways, most population studies have focused on the additive contribution of common variants and the potential of rare variants to explain additional variation. In this brief review, we discuss the potential to explain additional genetic variation through the agglomeration of multiple gene–gene interactions as well as main effects of common variants in terms of a network paradigm. Just as is the case for single-locus contributions, we expect each gene–gene interaction edge in the network to have a small effect, but these effects may be reinforced through hubs and other connectivity structures in the network. We discuss some of the opportunities and challenges of network methods for analyzing genome-wide association studies (GWAS) such as the study of hubs and motifs, and integrating other types of variation and environmental interactions. Such network approaches may unveil hidden variation in GWAS, improve understanding of mechanisms of disease, and possibly fit into a network paradigm of evolutionary genetics.

Background:

Anthropometric-based classification schemes for excess adiposity do not include direct assessment of obesity-related comorbidity and functional status and thus have limited clinical utility. We examined the ability of the Edmonton obesity staging system, a 5-point ordinal classification system that considers comorbidity and functional status, in predicting mortality in a nationally representative US sample.

Methods:

We analyzed data from the National Health and Human Nutrition Examination Surveys (NHANES) III (1988–1994) and the NHANES 1999–2004, with mortality follow-up through to the end of 2006. Adults (age ≥ 20 yr) with overweight or obesity who had been randomized to the morning session at the mobile examination centre were scored according to the Edmonton obesity staging system. We examined the relationship between staging system scores and mortality, and Cox proportional hazards models were adjusted for the presence of the metabolic syndrome or hypertriglyceridemic waist.

Results:

Over 75% of the cohort with overweight or obesity were given scores of 1 or 2. Scores of 4 could not be reliably assigned because specific data elements were lacking. Survival curves clearly diverged when stratified by scores of 0–3, but not when stratified by obesity class alone. Within the data from the NHANES 1988–1994, scores of 2 (hazard ratio [HR] 1.57; 95% confidence interval [CI] 1.16 to 2.13) and 3 (HR 2.69; 95% CI 1.98 to 3.67) were associated with increased mortality compared with scores of 0 or 1, even after adjustment for body mass index and the metabolic syndrome. We found similar results after adjusting for hypertriglyceridemic waist (i.e., waist circumference ≥ 90 cm and a triglyceride level ≥ 2 mmol/L for men; the corresponding values for women were ≥ 85 cm and ≥ 1.5 mmol/L), as well as in a cohort eligible for bariatric surgery.

Interpretation:

The Edmonton obesity staging system independently predicted increased mortality even after adjustment for contemporary methods of classifying adiposity. The Edmonton obesity staging system may offer improved clinical utility in assessing obesity-related risk and prioritizing treatment.

Background

Many large-scale epidemiologic data sources used to evaluate the body mass index (BMI: kg/m2) mortality association have relied on BMI derived from self-reported height and weight. Although measured BMI (BMIM) and self-reported BMI (BMISR) correlate highly, self-reports are systematically biased.

Objective

To rigorously examine how self-reporting bias influences the association between BMI and mortality rate.

Subjects

Samples representing the US non-institutionalized civilian population.

Design and Methods

National Health and Nutrition Examination Survey data (NHANES II: 1976-80; NHANES III: 1988-94) contain BMIM and BMISR. We applied Cox regression to estimate mortality hazard ratios (HRs) for BMIM and BMISR categories, respectively, and compared results. We similarly analyzed subgroups of ostensibly healthy never-smokers.

Results

Misclassification by BMISR among the underweight and obesity ranged from 30–40% despite high correlations between BMIM and BMISR (r>0.9). The reporting bias was moderately correlated with BMIM (r>0.35), but not BMISR (r<0.15). Analyses using BMISR failed to detect six of eight significant mortality HRs detected by BMIM. Significantly biased HRs were detected in the NHANES II full dataset (χ2 = 12.49; p = 0.01) and healthy subgroup (χ2 = 9.93; p = 0.04), but not in the NHANES III full dataset (χ2 = 5.63; p = 0.23) or healthy subgroup (χ2 = 1.52; p = 0.82).

Conclusions

BMISR should not be treated as interchangeable with BMIM in BMI-mortality analyses. Bias and inconsistency introduced by using BMISR in place of BMIM in BMI-mortality estimation and hypothesis tests may account for important discrepancies in published findings.

Background

In 2004, the State of Wisconsin introduced a change to their Medicaid Policy allowing medical care providers to be reimbursed for fluoride varnish treatment provided to Medicaid enrolled children.

Objective

To determine the extent by which a state-level policy change impacted access to fluoride varnish treatment (FVT) for Medicaid enrolled children.

Data Source

The Electronic Data Systems of Medicaid Evaluation and Decision Support database for Wisconsin from 2002 to 2006.

Study Design

We analyzed Wisconsin Medicaid claims for FVT for children between the ages of 1 and 6 years, comparing rates in the prepolicy period (2002–2003) to the period (2004–2006) following the policy change.

Principal Findings

Medicaid claims for FVT in 2002–2003 totaled 3,631. Following the policy change, claims for FVT increased to 28,303, with 38.0 percent submitted by medical care providers. FVT rates increased for children of both sexes and all ages, rising from 1.4 per 1,000 person-years of enrollment in 2002–2003 to 6.6 per 1,000 person-years in 2004–2006. Overall, 48.6 percent of the increase in FVT was attributable to medical care providers. The largest increase was seen in children 1–2 years of age, among whom medical care providers were responsible for 83.5 percent of the increase.

Conclusions

A state-level Medicaid policy change was followed by both a significant involvement of medical care providers and an overall increase in FVT. Children between the ages of 1 and 2 years appear to benefit the most from the involvement of medical care providers.

As genome-wide association studies expand beyond populations of European ancestry, the role of admixture will become increasingly important in the continued discovery and fine-mapping of variation influencing complex traits. Although admixture is commonly viewed as a confounding influence in association studies, approaches such as admixture mapping have demonstrated its ability to highlight disease susceptibility regions of the genome. In this study, we illustrate a powerful two-stage testing strategy designed to uncover trait-associated single nucleotide polymorphisms in the presence of ancestral allele frequency differentiation. In the first stage, we conduct an association scan by using predicted genotypic values based on regional admixture estimates. We then select a subset of promising markers for inclusion in a second-stage analysis, where association is tested between the observed genotype and the phenotype conditional on the predicted genotype. We prove that, under the null hypothesis, the test statistics used in each stage are orthogonal and asymptotically independent. Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture. We apply the proposed procedure to a study of height in 201 African-Americans genotyped at 108 ancestry informative markers. The two-stage procedure identified two statistically significant markers rs1985080 (PTHB1/BBS9) and rs952718 (ABCA12). PTHB1/BBS9 is downregulated by parathyroid hormone in osteoblastic cells and is thought to be involved in parathyroid hormone action in bones and may play a role in height. ABCA12 is a member of the superfamily of ATP-binding cassette transporters and its potential involvement in height is unclear.

Background

In 2004, Wisconsin Medicaid policy changed to allow medical care providers to be reimbursed for fluoride varnish treatment (FVT) to children’s teeth to improve access and utilization. To date, no study has been published on whether geographic and racial/ethnic variation in the provision of FVT in response to this policy change exists.

Objective

To examine the association of rates of FVT for children enrolled in Wisconsin Medicaid with race/ethnicity, Urban Influence Codes (UIC), and Dental Health Professional Shortage Area (DHPSA) designation based on county of residence.

Methods

A retrospective, pre-post design was used based on FVT claims for children in the Wisconsin Medicaid program from 2002 to 2006. Poisson Regression Models were used to evaluate the association of rates of FVT claims with race/ethnicity, UIC, and DHPSA designation.

Results

The rate of FVT claims varied by resident county-type according to UIC and DHPSA designation, age, and race/ethnicity. Post policy, the largest increases were observed for Native Americans residing in none DHPSA counties, enrollees living in rural counties and for Hispanics living in partial and entire DHPSA counties. African-Americans residing in partial DHPSA and metropolitan counties displayed the lowest rates of FVT claims.

Conclusions

Overall access and utilization of fluoride varnish treatment increased, but substantial racial/ethnic and geographic variation in the provision of FVT for children enrolled in Wisconsin Medicaid was observed. Future policies should incorporate measures that will specifically address the racial and geographic variations identified in this study.

Background

This study describes how painful events affect the health related quality of life (HRQL) of children with sickle cell disease (SCD) and determines the responsiveness of a generic HRQL measure in SCD. Our hypotheses were twofold: 1) HRQL is significantly impaired at presentation to the emergency department for a painful event and 2) PedsQL 4.0 Acute Version Generic Core Scales is responsive to change in the evolution of a painful event.

Procedure

This prospective cohort study included 57 children with SCD. HRQL was measured with the Acute Version of the PedsQL 4.0 Generic Core Scales, completed by child (self-report) and caregiver (proxy-report) at presentation and seven days post-discharge. Independent comparisons of HRQL scores were made between children in the study cohort and a published reference sample of children with SCD in baseline health (historical SCD controls).

Results

Median PedsQL scores at presentation were significantly lower than historical SCD controls in all domains for child self-report and all domains except social and school functioning in parent-proxy. Clinically and statistically significant changes in HRQL between presentation and post-discharge resulted in similar HRQL scores at seven days post-discharge to historical SCD controls.

Conclusions

The PedsQL is responsive to change; thus a useful tool to measure the impact of interventions in future SCD clinical trials. Painful events significantly diminish all domains of HRQL and this improves seven days post-discharge.

Since the discovery of the ubiquitous contribution of copy number variation to genetic variability, researchers have commonly used metrics such as r2 to quantify linkage disequilibrium (LD) between copy number variants (CNVs) and single nucleotide polymorphisms (SNPs). However, these reports have been restricted to SNPs outside copy number variable regions (CNVR) as current methods have not been adapted to account for SNPs displaying variable copy number. We show that traditional LD metrics inappropriately quantify SNP/CNV covariance when SNPs lie within CNVR. We derive a new method for measuring LD that solves this issue, and defaults to traditional metrics otherwise. Finally, we present a procedure to estimate CNV–SNP allele frequencies from unphased CNV–SNP genotypes. Our method allows researchers to include all SNPs in SNP/CNV LD measurements, regardless of copy number.

Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the “missing heritability” for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h2 up to 0.83, R2 up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R2 values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (∼0.80), substantial room for improvement remains.

Author Summary

While previous genome-wide association studies have implicated numerous loci associated with complex traits, such loci typically account for a very small proportion of phenotypic variation. However, a recent study using height as a model trait has illustrated that common single nucleotide polymorphisms can explain a large amount of genetic variance when evaluated through whole-genome statistical models. However, it is unclear to what extent higher proportions of explained variance will translate into improved predictive accuracy in future populations. Here we evaluate the predictive ability of whole-genome models for human height while varying the modeling approach, the size of the training population, the validation design, and the number of SNPs. Our results suggest that whole-genome prediction models can yield higher accuracy than what is commonly attained by models based on a few selected SNPs; yet, given the heritability of the trait in question, there exists room for improving prediction accuracy. While gains in predictive accuracy are likely to be small based on more expansive genotyping, our results indicate that more substantial benefits are likely to be gained through larger training populations, as well through the inclusion of related individuals.

Since the discovery of the ubiquitous contribution of copy number variation to genetic variability, researchers have commonly used metrics such as r2 to quantify linkage disequilibrium (LD) between copy number variants (CNVs) and single nucleotide polymorphisms (SNPs). However, these reports have been restricted to SNPs outside copy number variable regions (CNVR) as current methods have not been adapted to account for SNPs displaying variable copy number. We show that traditional LD metrics inappropriately quantify SNP/CNV covariance when SNPs lie within CNVR. We derive a new method for measuring LD that solves this issue, and defaults to traditional metrics otherwise. Finally, we present a procedure to estimate CNV–SNP allele frequencies from unphased CNV–SNP genotypes. Our method allows researchers to include all SNPs in SNP/CNV LD measurements, regardless of copy number.

Background

The role of host genetics in the development of subclinical atherosclerosis in the context of HIV infected persons who are being treated with highly active antiretroviral therapy (HAART) is not well understood.

Methods

The present genome-wide association study (GWAS) is based on 177 HIV-positive Caucasian males receiving HAART who participated in the Fat Redistribution and Metabolic Change in HIV Infection (FRAM) Study. Common and internal carotid intima-media thicknesses (cIMT) measured by B-mode ultrasound were used as a subclinical measure of atherosclerosis. Single nucleotide polymorphisms (SNPs) were assayed using the Illumina HumanCNV370-quad beadchip. Copy Number Variants (CNV) were inferred using a hidden Markov Model (PennCNV). Regression analyses were used to assess the association of common and internal cIMT with individual SNPs and CNVs, adjusting for age, duration of antiretroviral treatment, and principal components to account for potential population stratification.

Results

Two SNPs in tight linkage disequilibrium, rs2229116 (a missense, nonsynonymous polymorphism (IIe to Val)) and rs7177922, located in the Ryanodine receptor (RYR3) gene on chromosome 15 were significantly associated with common cIMT (p-value<1.61×10−7). The RYR gene family has been known to play a role in the etiology of cardiovascular disease and has been shown to be regulated by HIV TAT protein.

Conclusions

These results suggest that in the context of HIV infection and HAART, a functional SNP in a biologically plausible candidate gene, RYR3, is associated with increased common carotid IMT, which is a surrogate for atherosclerosis.

Canonical analysis measures nonlinear selection on latent axes from a rotation of the gamma matrix (γ) of quadratic and correlation selection gradients. Here we document that the conventional method of testing eigenvalues (double regression) under the null hypothesis of no nonlinear selection is incorrect. Through simulation we demonstrate that under the null the expectation of some eigenvalues from canonical analysis will be nonzero, which leads to unacceptably high type 1 error rates. Using a two trait example, we prove that the expectations for both eigenvalues depend on the sampling variability of the estimates in γ. An appropriate test is to slightly modify the double regression method by calculating permutation p-values for the ordered eigenvalues, which maintains correct type 1 error rates. Using simulated data of nonlinear selection on male guppy ornamentation, we show that the statistical power to detect curvature with canonical analysis is higher compared to relying on the estimates from γ alone. We provide a simple R script for permutation testing of the eigenvalues in order to distinguish curvature in the selection surface induced by nonlinear selection from curvature induced by random processes.

As genome-wide association studies expand beyond populations of European ancestry, the role of admixture will become increasingly important in the continued discovery and fine-mapping of variation influencing complex traits. Although admixture is commonly viewed as a confounding influence in association studies, approaches such as admixture mapping have demonstrated its ability to highlight disease susceptibility regions of the genome. In this study, we illustrate a powerful two-stage testing strategy designed to uncover trait-associated single nucleotide polymorphisms in the presence of ancestral allele frequency differentiation. In the first stage, we conduct an association scan by using predicted genotypic values based on regional admixture estimates. We then select a subset of promising markers for inclusion in a second-stage analysis, where association is tested between the observed genotype and the phenotype conditional on the predicted genotype. We prove that, under the null hypothesis, the test statistics used in each stage are orthogonal and asymptotically independent. Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture. We apply the proposed procedure to a study of height in 201 African-Americans genotyped at 108 ancestry informative markers. The two-stage procedure identified two statistically significant markers rs1985080 (PTHB1/BBS9) and rs952718 (ABCA12). PTHB1/BBS9 is downregulated by parathyroid hormone in osteoblastic cells and is thought to be involved in parathyroid hormone action in bones and may play a role in height. ABCA12 is a member of the superfamily of ATP binding cassette transporters and its potential involvement in height is unclear.

Objective

To determine the prevalence of the female athlete triad (low energy availability, menstrual dysfunction and low bone mineral density) in high school varsity athletes in a variety of sports compared with sedentary students/controls.

Design

Prospective study.

Setting

Academic medical center in the Midwest.

Participants

Eighty varsity athletes and eighty sedentary students/controls volunteered for this study.

Intervention

Subjects completed questionnaires, had their blood drawn and underwent bone mineral density testing.

Main Outcome Measures

Each participant completed screening questionnaires assessing eating behavior, menstrual status and physical activity. Each subject completed a 3-day food diary. Serum hormonal, TSH and prolactin levels were determined. Bone mineral density (BMD) and body composition were measured by dual energy x-ray absorptiometry (DXA).

Results

Low energy availability was present in similar numbers of athletes (36%) and sedentary/control subjects (39%; p=0.74). Athletes suffered more menstrual abnormalities (54%) compared with sedentary students/controls (21%) (p=<0.001). DXA revealed that 16% of the athletes and 30% of the sedentary/controls had low BMD (p=0.03). Risk factors for reduced BMD include sedentary control student, low BMI and increased caffeine consumption.

Conclusions

A substantial number of high school athletes (78%) and a surprising number of sedentary students (65%) suffer from one or more components of the triad. Given the high prevalence of triad characteristics in both groups, education in the formative elementary school years has the potential to prevent several of the components in both groups, therefore, improving health and averting long-term complications.

Purpose

The objective of this study was to determine the impact of family income and sickle cell disease on the health-related quality of life (HRQL) of children.

Methods

This was a cross-sectional study of children with and without sickle cell disease. Participants completed the PedsQL™ generic core scales parent-proxy or child self-report questionnaire during a routine clinic visit. HRQL was the primary outcome measured. Family income and sickle cell disease were the primary independent variables of interest.

Results

A total of 104 children with sickle cell disease and 74 without disease participated in the study. After adjusting for family income, patient age, and the presence of co-morbidities, children with severe sickle cell disease had increased odds of worse overall HRQL (parent-proxy HRQL report odds ratio [OR] 4.0) and physical HRQL (parent-proxy report OR 5.67, child self-report OR 3.33) compared to children without sickle cell disease.

Conclusions

Children with sickle cell disease have significantly impaired HRQL, even after considering the potential detrimental effect of family income on HRQL. Targeted interventions to improve these children’s HRQL are warranted.

The objective of this study was to determine the feasibility, reliability and validity of the Pediatric Quality of Life Inventory™ generic core scales (PedsQL™ questionnaire) in children with sickle cell disease. This was a cross-sectional study of children from an urban hospital-based sickle cell disease clinic and an urban primary care clinic. The study participants were children ages 2 to 18 years who presented to clinic for a routine visit. Health-related quality of life (HRQL) was the main outcome. HRQL of children with sickle cell disease were compared to children without disease to test validity. Missing items were used to determine feasibility and Cronbach’s alpha was used to determine reliability. Parents of 178 children (104 with sickle cell disease and 74 without disease) and 118 children (78 with sickle cell disease and 40 without disease) completed HRQL questionnaires. The PedsQL™ questionnaire was feasible and reliable. The parent-proxy and child self-report questionnaire differentiated between children with and without sickle cell disease. The parent proxy-report differentiated well between children with mild and severe sickle cell disease. The questionnaire performed well in children with sickle cell disease and is a feasible, reliable, and valid tool to measure HRQL in children with sickle cell disease.

Background

Caring for a child with a chronic condition, such as sickle cell disease, can have a significant impact on parents and families. In order to provide comprehensive care and support to these families, psychometrically sound instruments are needed as an initial step in measuring the impact of chronic diseases on parents and families. We sought to evaluate the psychometric properties of the PedsQL™ Family Impact Module in populations of children with and without sickle cell disease. In addition, we sought to determine the correlation between parent's well being and their proxy report of their child's health-related quality of life (HRQL).

Methods

We conducted a cross-sectional study of parents of children with and without sickle cell disease who presented to an urban hospital-based sickle cell disease clinic and an urban primary care clinic. We assessed the HRQL and family functioning of both groups of parents utilizing the PedsQL™ Family Impact Module. The reliability, validity and factor structure of the instrument were determined and scores from the instrument were correlated with scores from parent-proxy report of their child's HRQL using the PedsQL™ 4.0 Generic Core Scales.

Results

Parents of 170 children completed the module (97 parents of children with sickle cell disease and 73 parents of children without sickle cell disease). The Family Impact Module had high ceiling effects but was reliable (Cronbach's alpha > 0.80 in all scales). The empirical factor structure was generally consistent with the theoretical factor structure and supported construct validity. The Family Impact Module discriminated between parents of children with severe sickle cell disease from parents of children with mild disease or no disease in the areas of communication and worry. There were no significant differences across any of the subscales between parents of children with mild sickle cell disease and those with no disease. Parents with higher scores, representing better HRQL and family functioning, generally reported higher HRQL scores for their children.

Conclusion

The PedsQL™ Family Impact module was reliable, however it displayed large ceiling effects and did not discriminate well between parents of children with and without sickle cell disease. Future research to evaluate the psychometric properties of the Family Impact Module for parents of healthy children may be helpful.

Purpose

The objective of this study was to determine the impact of family income and sickle cell disease on the health-related quality of life (HRQL) of children.

Methods

This was a cross-sectional study of children with and without sickle cell disease. Participants completed the PedsQL™ generic core scales parent-proxy or child self-report questionnaire during a routine clinic visit. HRQL was the primary outcome measured. Family income and sickle cell disease were the primary independent variables of interest.

Results

A total of 104 children with sickle cell disease and 74 without disease participated in the study. After adjusting for family income, patient age, and the presence of co-morbidities, children with severe sickle cell disease had increased odds of worse overall HRQL (parent-proxy HRQL report odds ratio [OR] 4.0) and physical HRQL (parent-proxy report OR 5.67, child self-report OR 3.33) compared to children without sickle cell disease.

Conclusions

Children with sickle cell disease have significantly impaired HRQL, even after considering the potential detrimental effect of family income on HRQL. Targeted interventions to improve these children’s HRQL are warranted.

In spite of the well-known clustering of multiple autoimmune disorders in families, analyses of specific shared genes and polymorphisms between systemic lupus erythematosus (SLE) and other autoimmune diseases (ADs) have been limited. Therefore, we comprehensively tested autoimmune variants for association with SLE, aiming to identify pleiotropic genetic associations between these diseases. We compiled a list of 446 non–Major Histocompatibility Complex (MHC) variants identified in genome-wide association studies (GWAS) of populations of European ancestry across 17 ADs. We then tested these variants in our combined Caucasian SLE cohorts of 1,500 cases and 5,706 controls. We tested a subset of these polymorphisms in an independent Caucasian replication cohort of 2,085 SLE cases and 2,854 controls, allowing the computation of a meta-analysis between all cohorts. We have uncovered novel shared SLE loci that passed multiple comparisons adjustment, including the VTCN1 (rs12046117, P = 2.02×10−06) region. We observed that the loci shared among the most ADs include IL23R, OLIG3/TNFAIP3, and IL2RA. Given the lack of a universal autoimmune risk locus outside of the MHC and variable specificities for different diseases, our data suggests partial pleiotropy among ADs. Hierarchical clustering of ADs suggested that the most genetically related ADs appear to be type 1 diabetes with rheumatoid arthritis and Crohn's disease with ulcerative colitis. These findings support a relatively distinct genetic susceptibility for SLE. For many of the shared GWAS autoimmune loci, we found no evidence for association with SLE, including IL23R. Also, several established SLE loci are apparently not associated with other ADs, including the ITGAM-ITGAX and TNFSF4 regions. This study represents the most comprehensive evaluation of shared autoimmune loci to date, supports a relatively distinct non–MHC genetic susceptibility for SLE, provides further evidence for previously and newly identified shared genes in SLE, and highlights the value of studies of potentially pleiotropic genes in autoimmune diseases.

Author Summary

It is well known that multiple autoimmune disorders cluster in families. However, all of the genetic variants that explain this clustering have not been discovered, and the specific genetic variants shared between systemic lupus erythematosus (SLE) and other autoimmune diseases (ADs) are not known. In order to better understand the genetic factors that explain this predisposition to autoimmunity, we performed a comprehensive evaluation of shared autoimmune genetic variants. First we considered results from 17 ADs and compiled a list with 446 significant genetic variants from these studies. We identified some genetic variants extensively shared between ADs, as well as the ADs that share the most variants. The genetic overlap between SLE and other ADs was modest. Next we tested how important all the 446 genetic variants were in our collection with a minimum of 1,500 SLE patients. Among the most significant variants in SLE, the majority had already been identified in previous studies, but we also discovered variants in two important immune genes. In summary, our data identified diseases with common genetic risk factors and novel SLE effects, and this supports a relatively distinct genetic susceptibility for SLE. This study helps delineate the genetic architecture of ADs.

African Americans have been understudied in genome wide association studies of diabetes and related traits. In the current study, we examined the joint association of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with fasting insulin and an index of insulin resistance (HOMA-IR) in the HyperGEN study, a family based study with proband ascertainment for hypertension. This analysis is restricted to 1,040 African Americans without diabetes. We generated allele specific CNV genotypes at 872,243 autosomal loci using Birdsuite, a freely available multi-stage program. Joint tests of association for SNPs and CNVs were performed using linear mixed models adjusting for covariates and familial relationships. Our results highlight SNPs associated with fasting insulin and HOMA-IR (rs6576507 and rs8026527, 3.7*10−7≤P≤1.1*10−5) near ATPase, class V, type 10A (ATP10A), and the L Type voltage dependent calcium channel (CACNA1D, rs1401492, P≤5.2*10−6). ATP10A belongs to a family of aminophospholipid-transporting ATPases and has been associated with type 2 diabetes in mice. CACNA1D has been linked to pancreatic beta cell generation in mice. The two most significant copy variable markers (rs10277702 and rs361367; P<2.0*10−4) were in the beta variable region of the T-cell receptor gene (TCRVB). Human and mouse TCR has been shown to mimic insulin and its receptor and could contribute to insulin resistance. Our findings differ from genome wide association studies of fasting insulin and other diabetes related traits in European populations, highlighting the continued need to investigate unique genetic influences for understudied populations such as African Americans.