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1.  Infant Exposures and Development of Type 1 Diabetes Mellitus 
JAMA pediatrics  2013;167(9):808-815.
The incidence of type 1 diabetes mellitus (T1DM) is increasing worldwide, with the most rapid increase among children younger than 5 years of age.
To examine the associations between perinatal and infant exposures, especially early infant diet, and the development of T1DM.
The Diabetes Autoimmunity Study in the Young (DAISY) is a longitudinal, observational study.
Newborn screening for human leukocyte antigen (HLA) was done at St. Joseph’s Hospital in Denver, Colorado. First-degree relatives of individuals with T1DM were recruited from the Denver metropolitan area.
A total of 1835 children at increased genetic risk for T1DM followed up from birth with complete prospective assessment of infant diet. Fifty-three children developed T1DM.
Early (<4 months of age) and late (≥6 months of age) first exposure to solid foods compared with first exposures at 4 to 5 months of age (referent).
Risk for T1DM diagnosed by a physician.
Both early and late first exposure to any solid food predicted development of T1DM (hazard ratio [HR], 1.91; 95% CI, 1.04–3.51, and HR, 3.02; 95% CI, 1.26–7.24, respectively), adjusting for the HLA-DR genotype, first-degree relative with T1DM, maternal education, and delivery type. Specifically, early exposure to fruit and late exposure to rice/oat predicted T1DM (HR, 2.23; 95% CI, 1.14–4.39, and HR, 2.88; 95% CI, 1.36–6.11, respectively), while breastfeeding at the time of introduction to wheat/barley conferred protection (HR, 0.47; 95% CI, 0.26–0.86). Complicated vaginal delivery was also a predictor of T1DM (HR, 1.93; 95% CI, 1.03–3.61).
These results suggest the safest age to introduce solid foods in children at increased genetic risk for T1DM is between 4 and 5 months of age. Breastfeeding while introducing new foods may reduce T1DM risk.
PMCID: PMC4038357  PMID: 23836309
2.  Evidence of Stage- and Age-Related Heterogeneity of Non-HLA SNPs and Risk of Islet Autoimmunity and Type 1 Diabetes: The Diabetes Autoimmunity Study in the Young 
Previously, we examined 20 non-HLA SNPs for association with islet autoimmunity (IA) and/or progression to type 1 diabetes (T1D). Our objective was to investigate fourteen additional non-HLA T1D candidate SNPs for stage- and age-related heterogeneity in the etiology of T1D. Of 1634 non-Hispanic white DAISY children genotyped, 132 developed IA (positive for GAD, insulin, or IA-2 autoantibodies at two or more consecutive visits); 50 IA positive children progressed to T1D. Cox regression was used to analyze risk of IA and progression to T1D in IA positive children. Restricted cubic splines were used to model SNPs when there was evidence that risk was not constant with age. C1QTNF6 (rs229541) predicted increased IA risk (HR: 1.57, CI: 1.20–2.05) but not progression to T1D (HR: 1.13, CI: 0.75–1.71). SNP (rs10517086) appears to exhibit an age-related effect on risk of IA, with increased risk before age 2 years (age 2 HR: 1.67, CI: 1.08–2.56) but not older ages (age 4 HR: 0.84, CI: 0.43–1.62). C1QTNF6 (rs229541), SNP (rs10517086), and UBASH3A (rs3788013) were associated with development of T1D. This prospective investigation of non-HLA T1D candidate loci shows that some SNPs may exhibit stage- and age-related heterogeneity in the etiology of T1D.
PMCID: PMC3866813  PMID: 24367383
3.  Passenger Contact Investigation Associated with a Transport Driver with Pulmonary Tuberculosis 
Public Health Reports  2012;127(2):202-207.
In October 2008, pulmonary tuberculosis (TB) was diagnosed in a driver who had transported 762 passengers in the District of Columbia metropolitan area during his infectious period. A passenger contact investigation was conducted by the six public health jurisdictions because of concern that some passengers might be infected with HIV or have other medical conditions that put them at increased risk for developing TB disease if infected.
Authorities evaluated 92 of 100 passengers with at least 90 minutes of cumulative exposure. Passengers with fewer than 90 minutes of cumulative exposure were evaluated if they had contacted the health department after exposure and had a medical condition that increased their risk of TB. A tuberculin skin test (TST) result of at least 5 millimeters induration was considered positive.
Of 153 passengers who completed TST evaluation, 11 (7%) had positive TST results. TST results were not associated with exposure time or high-risk medical conditions. No TB cases were identified in the passengers.
The investigation yielded insufficient evidence that Mycobacterium tuberculosis transmission to passengers had occurred. TB-control programs should consider transportation-related passenger contact investigations low priority unless exposure is repetitive or single-trip exposure is long.
PMCID: PMC3268805  PMID: 22379220
4.  The Association between IgG4 Antibodies to Dietary Factors, Islet Autoimmunity and Type 1 Diabetes: The Diabetes Autoimmunity Study in the Young 
PLoS ONE  2013;8(2):e57936.
Infant dietary exposures have been linked to type 1 diabetes (T1D) development. IgG4 antibody responses to food antigens are associated with food intolerances but have not been explored prospectively in the period preceding T1D.
Using a case-cohort design, IgG4 antibodies to ß-lactoglobulin, gluten, and ovalbumin were measured in plasma collected annually from 260 DAISY participants. Of those, 77 developed islet autoimmunity (IA), defined as positive for either insulin, GAD65 or IA-2 autoantibodies on two consecutive visits, and 22 developed T1D.
In mixed model analysis adjusting for HLA-DR status, T1D family history, age and ethnicity, higher ß-lactoglobulin IgG4 concentrations were associated with shorter breastfeeding duration (beta = −0.03, 95% Confidence Interval: −0.05, −0.006) and earlier first cow’s milk exposure (beta = −0.04, 95% Confidence Interval: −0.08, 0.00). Higher gluten IgG4 was associated with older age at gluten introduction (beta = 0.06, 95% Confidence Interval: 0.00, 0.13). In proportional hazards analysis adjusting for HLA-DR status, T1D family history and ethnicity, IgG4 against individual or multiple dietary antigens throughout childhood were not associated with IA. In addition, mean antigen-specific IgG4 concentrations in infancy (age <2 years) were not associated with risk of IA nor progression to T1D. Higher ovalbumin IgG4 at first IA positive visit was marginally associated with progression to T1D (Hazard Ratio: 1.39, 95% Confidence Interval: 1.00, 1.92).
We found no association between the IgG4 response to β-lactoglobulin, gluten, and the development of either IA or T1D. The association between higher ovalbumin and progression to T1D in children with IA should be explored in other populations.
PMCID: PMC3585253  PMID: 23469110
5.  Early-Life Predictors of Higher Body Mass Index in Healthy Children 
Childhood obesity tracks into adulthood, and may increase diabetes and cardiovascular disease risk in adulthood. Prospective analyses may better define the pathways between early life factors and greater childhood body mass index (BMI), a measure of obesity.
The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children from birth that are at increased genetic risk for type 1 diabetes. We examined longitudinal data for 1,178 DAISY subjects (mean age at last follow-up: 6.59 years (range: 2.0–11.5 years). Birth size and diabetes exposure in utero were collected in the enrollment interview. Infant diet information was collected via interviews throughout infancy. Infant weight gain and childhood BMI were measured at clinic visits.
Female gender, diabetes exposure in utero, larger size for gestational age, shorter breastfeeding duration, and more rapid infant weight gain predicted higher childhood BMI. Formal mediation analysis suggests the effect of shorter breastfeeding duration on childhood BMI may be mediated by more rapid infant weight gain. Also, the effect of diabetes exposure in utero on childhood BMI may be mediated by larger size for gestational age.
We identified strong interrelationships between early life factors and childhood BMI. Understanding these pathways may aid childhood obesity prevention efforts.
PMCID: PMC2855270  PMID: 19940472
Breastfeeding duration; Infant weight gain; Diabetes exposure in utero; Birth size; Mediator
6.  Bias in trials comparing paired continuous tests can cause researchers to choose the wrong screening modality 
To compare the diagnostic accuracy of two continuous screening tests, a common approach is to test the difference between the areas under the receiver operating characteristic (ROC) curves. After study participants are screened with both screening tests, the disease status is determined as accurately as possible, either by an invasive, sensitive and specific secondary test, or by a less invasive, but less sensitive approach. For most participants, disease status is approximated through the less sensitive approach. The invasive test must be limited to the fraction of the participants whose results on either or both screening tests exceed a threshold of suspicion, or who develop signs and symptoms of the disease after the initial screening tests.
The limitations of this study design lead to a bias in the ROC curves we call paired screening trial bias. This bias reflects the synergistic effects of inappropriate reference standard bias, differential verification bias, and partial verification bias. The absence of a gold reference standard leads to inappropriate reference standard bias. When different reference standards are used to ascertain disease status, it creates differential verification bias. When only suspicious screening test scores trigger a sensitive and specific secondary test, the result is a form of partial verification bias.
For paired screening tests with bivariate normally distributed scores, we give formulae and programs to quantify the effect of paired screening trial bias on a paired comparison of area under the curves. We fix the prevalence of disease, and the chance a diseased subject manifests signs and symptoms. We derive the formulas for true sensitivity and specificity, and those for the sensitivity and specificity observed by the study investigator.
The observed area under the ROC curves is quite different from the true area under the ROC curves. The typical direction of the bias is a strong inflation in sensitivity, paired with a concomitant slight deflation of specificity.
In paired trials of screening tests, when area under the ROC curve is used as the metric, bias may lead researchers to make the wrong decision as to which screening test is better.
PMCID: PMC2657218  PMID: 19154609
7.  Two-Modality Mammography May Confer an Advantage over Either Full-Field Digital Mammography or Screen-Film Mammography 
Academic radiology  2007;14(6):670-676.
Rationale and Objectives
To compare the cancer detection rate and ROC area under the curve of full-field digital mammography, screen-film mammography, and a combined technique that allowed diagnosis if a finding was suspicious on film, on digital, or both.
Materials and Methods
We used the data originally analyzed in Lewin et al. (2002). In that trial, 6,736 paired full-field and digital mammograms were performed in 4,489 women. We used parametric and nonparametric tests to compare the area under the curve for ROC scores of film-screen only, digital mammography only, and the combined test. We used McNemar’s test for paired proportions to compare the cancer detection rates.
With the parametric test, neither the difference in AUC between the film and combined, nor the difference between the digital and combined ROC curves was significant at the Bonferroni-corrected 0.025 alpha level (film vs. combined difference = 0.0563, p = 0.0712; digital vs. combined difference = 0.0894, p = 0.0455). The nonparametric test showed that there was a significant difference between both film and combined (difference = 0.073, p = 0.008) and digital vs. combined ROC curves (difference = 0.1164, p = 0.0008). The continuity corrected McNemar’s test showed a significant increase in the proportion of cancers detected by the combined modality over film (chi squared = 7.111, df = 1, p=0.0077), and over digital (chi squared = 12.071, df =1, p = 0.0005).
Using two mammograms, one film and one digital, significantly increases the detection of breast cancer.
PMCID: PMC1975808  PMID: 17502256
Digital mammography; film mammography; combined test; ROC area under the curve analysis

Results 1-7 (7)