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1.  Oral Cysteamine bitartrate and N-acetylcysteine combination for patients with infantile neuronal ceroid lipofuscinosis:a pilot study 
The Lancet. Neurology  2014;13(8):777-787.
Summary
Background
Infantile neuronal ceroid lipofuscinosis (INCL) is a devastating neurodegenerative lysosomal storage disease caused by mutations in the CLN1 gene encoding palmitoyl-protein thioesterase-1 (PPT1). PPT1-deficiency causes lysosomal ceroid accumulation leading to INCL pathogenesis. Previously, we reported that phosphocysteamine and N-acetylcysteine mediated ceroid depletion in cultured cells from INCL patients. We conducted a pilot study to determine whether a combination of cysteamine bitartrate and N-acetylcysteine is beneficial for these patients.
Methods
Patients (6-month to 3-years old) with any combination of 2 of the 7 most lethal PPT1 mutations were admitted. All patients were recruited from physician referrals and the PPT1 mutations were analyzed prior to admission. Patients were evaluated by electroretinography(ERG), brain MRI and MRS, electroencephalography (EEG), and electron microscopic analyses of leukocytes for granular osmiophilic deposits (GRODs). Patients received oral cysteamine bitartrate (60mg/kg/day) and N-acetylcysteine (60mg/kg/day) and were evaluated every 6 to 12 months until they showed isoelectric EEG attesting to a vegetative state or were too sick to travel. Outcomes were compared with the reported INCL natural history. In two cases, the disease progression was compared with that of a sibling who was above the age limit for inclusion into the protocol.
Findings
Between March, 2001, and June, 2011, we recruited 10 children with INCL but one was lost to follow-up after the first visit. Thus, a total of 9 patients (5 females and 4 males) were studied. At the first follow-up visit, peripheral leukocytes in all 9 patients showed virtually complete depletion of GRODs and 7 of 9 patients manifested less irritability and/or improved alertness based upon parental and physician observations. Evaluation by Denver scale showed acquisition of no new developmental skills and retinal function assessed by ERG progressively declined. Most notably, average time to isoelectric EEG (indicating vegetative state) was significantly longer in our patients compared to that previously reported. MRI studies demonstrated signal abnormalities similar to previous reports. Brain volume and NAA declined steadily, but no published quantitative MRI or MRS studies of INCL patients are available for comparison on these measures. There were no adverse events related to therapy other than a mild gastrointestinal discomfort in 2 of 9 patients, which was eliminated when the liquid preparation of cysteamine bitatrate was replaced with capsules.
Interpretation
The objectively demonstrated benefits in our study are the depletion of GRODs and delay of isoelectric EEG in all patients; in addition, several subjective benefits were suggested, all of which warrant further study. Nevertheless, this report systematically and quantitatively documents the natural history of 9 INCL patients with the most lethal CLN1/PPT1 mutations and thereby provides a benchmark for evaluating future experimental therapies.
Funding
This study was supported in part by a Bench-to-Bedside Award from the Clinical Center of the NIH and by the Intramural Program of the Eunice Kennedy Shriver National Institutes of Child Health and Human Development, NIH.
doi:10.1016/S1474-4422(14)70142-5
PMCID: PMC4139936  PMID: 24997880
2.  Contextual factors are associated with diet quality in youth with type 1 diabetes 
This study examined differences in diet quality by meal type, location, and time of week in youth with type 1 diabetes (T1D). A sample of youth with T1D (n=252; 48% female) age 8 to 18 years (13.2±2.8) with diabetes duration ≥1 year (6.3±3.4) completed 3-day diet records. Multilevel linear regression models tested for differences in diet quality indicators by meal type, location and time of week (weekdays versus weekends). Participants showed greater energy intake and poorer diet quality on weekends relative to weekdays, with lower intake of fruit and vegetables, and higher intake of total and saturated fat. Differences in diet quality were seen across meal types, with higher nutrient density at breakfast and dinner than at lunch and snacks. Participants reported the highest whole grain and lowest fat intake at breakfast, but higher added sugar than at lunch or dinner. Dinner was characterized by the highest fruit intake, lowest added sugar, and lowest glycemic load, but also the highest sodium intake. The poorest nutrient density and highest added sugar occurred during snacks. Diet quality was poorer for meals consumed away from home than those consumed at home for breakfast, dinner, and snacks. Findings regarding lunch meal location were mixed, with higher nutrient density, lower glycemic load, and less added sugar at home lunches, and lower total fat, saturated fat, and sodium at lunches away from home. Findings indicate impacts of meal type, location and time of week on diet quality, suggesting targets for nutrition education and behavioral interventions.
doi:10.1016/j.jand.2014.01.012
PMCID: PMC4111984  PMID: 24651028
Diabetes Mellitus; Type 1; Diet; Children; Adolescents; Contextual Factors
3.  Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models 
Genetic epidemiology  2015;39(4):259-275.
In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case.
doi:10.1002/gepi.21895
PMCID: PMC4443751  PMID: 25809955
pleiotropy analysis; rare variants; common variants; association mapping; quantitative trait loci; complex traits; functional data analysis; multivariate linear models
4.  Longitudinal Association Analysis of Quantitative Traits 
Genetic epidemiology  2012;36(8):856-869.
Longitudinal genetic studies provide a valuable resource for exploring key genetic and environmental factors that affect complex traits over time. Genetic analysis of longitudinal data that incorporate temporal variations is important for understanding genetic architecture and biological variations of common complex diseases. Although they are important, there is a paucity of statistical methods to analyze longitudinal human genetic data. In this article, longitudinal methods are developed for temporal association mapping to analyze population longitudinal data. Both parametric and nonparametric models are proposed. The models can be applied to multiple diallelic genetic markers such as single-nucleotide polymorphisms and multiallelic markers such as microsatellites. By analytical formulae, we show that the models take both the linkage disequilibrium and temporal trends into account simultaneously. Variance-covariance structure is constructed to model the single measurement variation and multiple measurement correlations of an individual based on the theory of stochastic processes. Novel penalized spline models are used to estimate the time-dependent mean functions and regression coefficients. The methods were applied to analyze Framingham Heart Study data of Genetic Analysis Workshop (GAW) 13 and GAW 16. The temporal trends and genetic effects of the systolic blood pressure are successfully detected by the proposed approaches. Simulation studies were performed to find out that the nonparametric penalized linear model is the best choice in fitting real data. The research sheds light on the important area of longitudinal genetic analysis, and it provides a basis for future methodological investigations and practical applications.
doi:10.1002/gepi.21673
PMCID: PMC4444073  PMID: 22965819
association mapping; quantitative trait loci; longitudinal analysis
5.  Improving dietary quality in youth with type 1 diabetes: randomized clinical trial of a family-based behavioral intervention 
Background
Diets of children with type 1 diabetes are low in fruits, vegetables, and whole grains, and high in foods of minimal nutritional value, increasing risk for future adverse health outcomes. This 18-month randomized clinical trial tested the effect of a family-based behavioral intervention integrating motivational interviewing, active learning, and applied problem-solving on the primary outcomes of dietary intake and glycemic control among youth with type 1 diabetes.
Methods
A parallel-group study with equal randomization was conducted at an outpatient, free-standing, multidisciplinary tertiary diabetes center in the United States. Eligible youth were those age 8–16 years with type 1 diabetes diagnosis ≥1 year and hemoglobin A1c (HbA1c) ≥6.5% and ≤10.0%. Participants were 136 parent-youth dyads (treatment n = 66, control n = 70). The intervention consisted of 9 in-clinic sessions delivered to the child and parent; control condition comprised equivalent assessments and number of contacts without dietary advice. Dietary intake was assessed using 3-day diet records at 6 time points across the 18-month study. Dietary outcomes included the Healthy Eating Index-2005 (HEI2005; index measuring conformance to the 2005 United States Dietary Guidelines for Americans) and Whole Plant Food Density (WPFD; number of cup or ounce equivalents per 1000 kcal of whole grains, whole fruit, vegetables, legumes, nuts, and seeds consumed). HbA1c was obtained every 3 months. Overall comparison of outcome variables between intervention and usual care groups was conducted using permutation tests.
Results
There was a positive intervention effect across the study duration for HEI2005 (p = .015) and WPFD (p = .004). At 18 months, HEI2005 was 7.2 greater (mean ± SE 64.6 ± 2.0 versus 57.4 ± 1.6), and WPFD was 0.5 greater (2.2 ± 0.1 versus 1.7 ± 0.1) in the intervention group versus control. There was no difference between groups in HbA1c across the study duration.
Conclusions
This behavioral nutrition intervention improved dietary quality among youth with type 1 diabetes, but did not impact glycemic control. Findings indicate the potential utility of incorporating such strategies into clinical care, and suggest that improvement in diet quality can be achieved in families living with this burdensome disease.
Trial registration
Clinicaltrials.gov registration number: NCT00999375
Electronic supplementary material
The online version of this article (doi:10.1186/s12966-015-0214-4) contains supplementary material, which is available to authorized users.
doi:10.1186/s12966-015-0214-4
PMCID: PMC4436744  PMID: 25952160
Behavioral intervention; Nutrition; Diet; Type 1 diabetes; Children; Adolescents
6.  Longitudinal Data Analysis Using Bayesian-frequentist Hybrid Random Effects Model 
Journal of applied statistics  2014;41(9):2001-2010.
The mixed random effect model is commonly used in longitudinal data analysis within either frequentist or Bayesian framework. Here we consider a case, we have prior knowledge on partial-parameters, while no such information on rest. Thus, we use the hybrid approach on the random-effects model with partial-parameters. The parameters are estimated via Bayesian procedure, and the rest of parameters by the frequentist maximum likelihood estimation (MLE), simultaneously on the same model. In practices, we often know partial prior information such as, covariates of age, gender, and etc. These information can be used, and get accurate estimations in mixed random-effects model. A series of simulation studies were performed to compare the results with the commonly used random-effects model with and without partial prior information. The results in hybrid estimation (HYB) and Maximum likelihood estimation (MLE) were very close each other. The estimated θ values in with partial prior information model (HYB) were more closer to true θ values, and shown less variances than without partial prior information in MLE. To compare with true θ values, the mean square of errors (MSE) are much less in HYB than in MLE. This advantage of HYB is very obvious in longitudinal data with small sample size. The methods of HYB and MLE are applied to a real longitudinal data for illustration.
doi:10.1080/02664763.2014.898137
PMCID: PMC4133133  PMID: 25143663
Hybrid; Longitudinal data; Simulation
7.  SEQUENTIAL TESTING OF MEASUREMENT ERRORS IN INTER-RATER RELIABILITY STUDIES 
Statistica Sinica  2013;23(4):1743-1759.
Inter-rater reliability is usually assessed by means of the intraclass correlation coefficient. Using two-way analysis of variance to model raters and subjects as random effects, we derive group sequential testing procedures for the design and analysis of reliability studies in which multiple raters evaluate multiple subjects. Compared with the conventional fixed sample procedures, the group sequential test has smaller average sample number. The performance of the proposed technique is examined using simulation studies and critical values are tabulated for a range of two-stage design parameters. The methods are exemplified using data from the Physician Reliability Study for diagnosis of endometriosis.
doi:10.5705/ss.2012.036s
PMCID: PMC4267541  PMID: 25525316
Interim analysis; inter-rater reliability; intraclass correlation coefficient; measurement errors; sample size and power; two-way ANOVA
8.  Physical Activity and Sedentary Behaviors Associated With Risk of Progression From Gestational Diabetes Mellitus to Type 2 Diabetes Mellitus 
JAMA internal medicine  2014;174(7):1047-1055.
IMPORTANCE
Women with a history of gestational diabetes mellitus (GDM) are at substantially increased risk of type 2 diabetes mellitus (T2DM). The identification of important modifiable factors could help prevent T2DM in this high-risk population.
OBJECTIVE
To examine the role of physical activity and television watching and other sedentary behaviors, and changes in these behaviors in the progression from GDM to T2DM.
DESIGN, SETTING, AND PARTICIPANTS
Prospective cohort study of 4554 women from the Nurses’ Health Study II who had a history of GDM, as part of the ongoing Diabetes & Women’s Health Study. These women were followed up from 1991 to 2007.
EXPOSURES
Physical activity and television watching and other sedentary behaviors were assessed in 1991, 1997, 2001, and 2005.
MAIN OUTCOMES AND MEASURE
Incident T2DM identified through self-report and confirmed by supplemental questionnaires.
RESULTS
We documented 635 incident T2DM cases during 59287 person-years of follow-up. Each 5–metabolic equivalent hours per week (MET-h/wk) increment of total physical activity, which is equivalent to 100 minutes per week of moderate-intensity physical activity, was related to a 9% lower risk of T2DM (adjusted relative risk [RR], 0.91; 95% CI, 0.88–0.94); this inverse association remained significant after additional adjustment for body mass index (BMI). Moreover, an increase in physical activity was associated with a lower risk of developing T2DM. Compared with women who maintained their total physical activity levels, women who increased their total physical activity levels by 7.5 MET-h/wk or more (equivalent to 150 minutes per week of moderate-intensity physical activity) had a 47% lower risk of T2DM (RR, 0.53; 95% CI, 0.38–0.75); the association remained significant after additional adjustment for BMI. The multivariable adjusted RRs (95% CIs) for T2DM associated with television watching of 0 to 5, 6 to 10, 11 to 20, and 20 or more hours per week were 1 (reference), 1.28 (1.04–1.59), 1.41 (1.11–1.79), and 1.77 (1.28–2.45), respectively (P value for trend <.001); additional adjustment for BMI attenuated the association.
CONCLUSIONS AND RELEVANCE
Increasing physical activity may lower the risk of progression from GDM to T2DM. These findings suggest a hopeful message to women with a history of GDM, although they are at exceptionally high risk for T2DM, promoting an active lifestyle may lower the risk.
doi:10.1001/jamainternmed.2014.1795
PMCID: PMC4209161  PMID: 24841449
9.  Linear combination methods to improve diagnostic/prognostic accuracy on future observations 
Statistical methods in medical research  2013;10.1177/0962280213481053.
Multiple diagnostic tests or biomarkers can be combined to improve diagnostic accuracy. The problem of finding the optimal linear combinations of biomarkers to maximise the area under the receiver operating characteristic curve has been extensively addressed in the literature. The purpose of this article is threefold: (1) to provide an extensive review of the existing methods for biomarker combination; (2) to propose a new combination method, namely, the nonparametric stepwise approach; (3) to use leave-one-pair-out cross-validation method, instead of re-substitution method, which is overoptimistic and hence might lead to wrong conclusion, to empirically evaluate and compare the performance of different linear combination methods in yielding the largest area under receiver operating characteristic curve. A data set of Duchenne muscular dystrophy was analysed to illustrate the applications of the discussed combination methods.
doi:10.1177/0962280213481053
PMCID: PMC4180010  PMID: 23592714
Multiple biomarkers; receiver operating characteristic curve; area under the receiver operating characteristic curve; linear combination; diagnostic/prognostic accuracy
10.  An additive selection of markers to improve diagnostic accuracy based on a discriminatory measure 
Academic radiology  2013;20(7):854-862.
Rationale and Objectives
The estimation of the area under the receiver operating characteristic (ROC) curve (AUC) often relies on the assumption that the truly positive population tends to have higher marker results than the truly negative population. The authors propose a discriminatory measure to relax such an assumption and apply the measure to identify the appropriate set of markers for combination.
Materials and Methods
The proposed measure is based on the maximum of the AUC and 1-AUC. The existing methods are applied to estimate the measure. The subset of markers are selected using a combination method which maximizes a function of the proposed discriminatory score with the number of markers as a penalty in the function.
Results
The properties of the estimators for the proposed measure were studied through large-scale simulation studies. The application was illustrated through a real example to identify the set of markers to combine.
Conclusion
Simulation results showed excellent small-sample performance of the estimators for the proposed measure. The application in the example yielded a reasonable subset of markers for combination.
doi:10.1016/j.acra.2013.02.009
PMCID: PMC4172320  PMID: 23611438
Receiver operating characteristic (ROC); Area under the ROC curves (AUC); Discriminatory score; Box-Cox transformation
11.  Adjusting for Misclassification in a Stratified Biomarker Clinical Trial † 
Statistics in medicine  2014;33(18):3100-3113.
Clinical trials utilizing predictive biomarkers have become a research focus in personalized medicine. We investigate the effects of biomarker misclassification on the design and analysis of stratified biomarker clinical trials. For a variety of inference problems including marker-treatment interaction in particular, we show that marker misclassification may have profound adverse effects on the coverage of confidence intervals, power of the tests, and required sample sizes. For each inferential problem we propose methods to adjust for the classification errors.
doi:10.1002/sim.6164
PMCID: PMC4107031  PMID: 24733510
Biomarkers; classification error; correction for error; personalized medicine; power and sample size; prevalence; randomized controlled clinical trials; sensitivity and specificity
12.  Homogeneity tests of clustered diagnostic markers with applications to the BioCycle Study 
Statistics in medicine  2012;31(28):3638-3648.
Diagnostic trials often require the use of a homogeneity test among several markers. Such a test may be necessary to determine the power both during the design phase and in the initial analysis stage. However, no formal method is available for the power and sample size calculation when the number of markers is greater than two and marker measurements are clustered in subjects. This article presents two procedures for testing the accuracy among clustered diagnostic markers. The first procedure is a test of homogeneity among continuous markers based on a global null hypothesis of the same accuracy. The result under the alternative provides the explicit distribution for the power and sample size calculation. The second procedure is a simultaneous pairwise comparison test based on weighted areas under the receiver operating characteristic curves. This test is particularly useful if a global difference among markers is found by the homogeneity test. We apply our procedures to the BioCycle Study designed to assess and compare the accuracy of hormone and oxidative stress markers in distinguishing women with ovulatory menstrual cycles from those without.
doi:10.1002/sim.5391
PMCID: PMC4084872  PMID: 22733707
ROC curve; biomarker; homogeneity test; sample size
13.  Nonparametric ROC Summary Statistics for Correlated Diagnostic Marker Data 
Statistics in medicine  2012;32(13):2209-2220.
We propose efficient nonparametric statistics to compare medical imaging modalities in multi-reader multi-test data and to compare markers in longitudinal ROC data. The proposed methods are based on the weighted area under the ROC curve which includes the area under the curve and the partial area under the curve as special cases. The methods maximize the local power for detecting the difference between imaging modalities. The asymptotic results of the proposed methods are developed under a complex correlation structure. Our simulation studies show that the proposed statistics result in much better powers than existing statistics. We applied the proposed statistics to an endometriosis diagnosis study.
doi:10.1002/sim.5654
PMCID: PMC3578098  PMID: 23055248
ROC curve; Optimal weights; Wilcoxon statistics; Correlated data
14.  Neuroprotection and lifespan extension in Ppt1−/− mice by NtBuHA: therapeutic implications for INCL 
Nature neuroscience  2013;16(11):10.1038/nn.3526.
Infantile neuronal ceroid lipofuscinosis (INCL) is a devastating childhood neurodegenerative lysosomal storage disease (LSD) that has no effective treatment. It is caused by inactivating mutations in the palmitoyl-protein thioesterase-1 (PPT1) gene. PPT1-deficiency impairs the cleavage of thioester linkage in palmitoylated proteins (constituents of ceroid), preventing degradation by lysosomal hydrolases. Consequently, accumulation of lysosomal ceroid leads to INCL. Thioester linkage is cleaved by nucleophilic attack. Hydroxylamine, a potent nucleophilic cellular metabolite, may have therapeutic potential for INCL but its toxicity precludes clinical application. Here we report that a hydroxylamine-derivative, N-(tert-Butyl) hydroxylamine (NtBuHA), is non-toxic, cleaves thioester linkage in palmitoylated proteins and mediates lysosomal ceroid depletion in cultured cells from INCL patients. Importantly, in Ppt1−/− mice, which mimic INCL, NtBuHA crossed the blood-brain-barrier, depleted lysosomal ceroid, suppressed neuronal apoptosis, slowed neurological deterioration and extended lifespan. Our findings provide the proof of concept that thioesterase-mimetic and antioxidant small molecules like NtBuHA are potential drug-targets for thioesterase deficiency diseases like INCL.
doi:10.1038/nn.3526
PMCID: PMC3812271  PMID: 24056696
15.  Efficient Logistic Regression Designs Under an Imperfect Population Identifier 
Biometrics  2013;70(1):175-184.
Summary
Motivated by actual study designs, this article considers efficient logistic regression designs where the population is identified with a binary test that is subject to diagnostic error. We consider the case where the imperfect test is obtained on all participants, while the gold standard test is measured on a small chosen subsample. Under maximum-likelihood estimation, we evaluate the optimal design in terms of sample selection as well as verification. We show that there may be substantial efficiency gains by choosing a small percentage of individuals who test negative on the imperfect test for inclusion in the sample (e.g., verifying 90% test-positive cases). We also show that a two-stage design may be a good practical alternative to a fixed design in some situations. Under optimal and nearly optimal designs, we compare maximum-likelihood and semi-parametric efficient estimators under correct and misspecified models with simulations. The methodology is illustrated with an analysis from a diabetes behavioral intervention trial.
doi:10.1111/biom.12106
PMCID: PMC3954435  PMID: 24261471
Case-control designs; Diagnostic accuracy; Epidemiologic designs; Misclassification; Measurement error
16.  Anorectal atresia and variants at predicted regulatory sites in candidate genes 
Annals of human genetics  2012;77(1):31-46.
SUMMARY
Anorectal atresia is a serious birth defect of largely unknown etiology but candidate genes have been identified in animal studies and human syndromes. Because alterations in the activity of these genes might lead to anorectal atresia, we selected 71 common variants predicted to be in transcription factor binding sites, CpG windows, splice sites, and miRNA target sites of 25 candidate genes, and tested for their association with anorectal atresia. The study population comprised 150 anorectal atresia cases and 623 control infants without major malformations. Variants predicted to affect transcription factor binding, splicing, and DNA methylation in WNT3A, PCSK5, TCF4, MKKS, GLI2, HOXD12, and BMP4 were associated with anorectal atresia based on a nominal P value <0.05. The GLI2 and BMP4 variants are reported to be moderately associated with gene expression changes (Spearman’s rank correlation coefficients between −0.260 and 0.226). We did not find evidence for interaction between maternal pre-pregnancy obesity and variants in MKKS, a gene previously associated with obesity, on the risk of anorectal atresia. Our results for MKKS support previously suggested associations with anorectal malformations. Our findings suggest that more research is needed to determine whether altered GLI2 and BMP4 expression is important in anorectal atresia in humans.
doi:10.1111/j.1469-1809.2012.00734.x
PMCID: PMC3535506  PMID: 23127126
anorectal malformations; imperforate anus; hindgut; congenital abnormalities
17.  Pancreatic beta-cell function and type 2 diabetes risk: quantify the causal effect using a Mendelian randomization approach based on meta-analyses 
Human Molecular Genetics  2012;21(22):5010-5018.
The objective of the study is to quantify the causal effect of β-cell function on type 2 diabetes by minimizing residual confounding and reverse causation. We employed a Mendelian randomization (MR) approach using TCF7L2 variant rs7903146 as an instrument for lifelong levels of β-cell function. We first conducted two sets of meta-analyses to quantify the association of the TCF7L2 variant with the risk of type 2 diabetes among 55 436 cases and 106 020 controls from 66 studies by calculating pooled odds ratio (OR) and to quantify the associations with multiple direct or indirect measures of β-cell function among 35 052 non-diabetic individuals from 31 studies by calculating pooled mean difference. We further applied the method of MR to obtain the causal estimates for the effect of β-cell function on type 2 diabetes risk based on findings from the meta-analyses. The OR [95% confidence interval (CI)] was 0.87 (0.81–0.93) for each five unit increment in homeostasis model assessment of insulin secretion (HOMA-%B) (P = 3.0 × 10−5). In addition, for measures based on intravenous glucose tolerance test, ORs (95% CI) associated with type 2 diabetes risk were 0.24 (0.08–0.74) (P = 0.01) and 0.14 (0.04–0.48) (P = 0.002) for per 1 standard deviation increment in insulin sensitivity index and disposition index, respectively. Findings from the present study lend support to a causal role of pancreatic β-cell function itself in the etiology of type 2 diabetes.
doi:10.1093/hmg/dds339
PMCID: PMC3607483  PMID: 22936689
18.  Improved Confidence Intervals of a Small Probability from Pooled Testing with Misclassification 
This article concerns construction of confidence intervals for the prevalence of a rare disease using Dorfman’s pooled testing procedure when the disease status is classified with an imperfect biomarker. Such an interval can be derived by converting a confidence interval for the probability that a group is tested positive. Wald confidence intervals based on a normal approximation are shown to be inefficient in terms of coverage probability, even for relatively large number of pools. A few alternatives are proposed and their performance is investigated in terms of coverage probability and length of intervals.
doi:10.3389/fpubh.2013.00039
PMCID: PMC3859966  PMID: 24350208
confidence intervals; coverage probability; exact inference; pooling; prevalence; rare event; sensitivity; specificity
19.  Evaluation of Genes Involved in Limb Development, Angiogenesis, and Coagulation as Risk Factors for Congenital Limb Deficiencies 
We conducted a population-based case-control study of single nucleotide polymorphisms (SNPs) in selected genes to find common variants that play a role in the etiology of limb deficiencies (LD)s. Included in the study were 389 infants with LDs of unknown cause and 980 unaffected controls selected from all births in New York State (NYS) for the years 1998 to 2005. We used cases identified from the NYS Department of Health (DOH) Congenital Malformations Registry. Genotypes were obtained for 132 SNPs in genes involved in limb development (SHH, WNT7A, FGF4, FGF8, FGF10, TBX3, TBX5, SALL4, GREM1, GDF5, CTNNB1, EN1, CYP26A1, CYP26B1), angiogenesis (VEGFA, HIF1A, NOS3), and coagulation (F2, F5, MTHFR). Genotype call rates were >97% and SNPs were tested for departure from Hardy-Weinberg expectations by race/ethnic subgroups. For each SNP, odds ratios (OR)s and confidence intervals (CI)s were estimated and corrected for multiple comparisons for all LDs combined and for LD subtypes. Among non-Hispanic white infants, associations between FGF10 SNPs rs10805683 and rs13170645 and all LDs combined were statistically significant following correction for multiple testing (OR=1.99; 95% CI=1.43-2.77; uncorrected p=0.000043 for rs10805683 heterozygous genotype, and OR=2.37; 95% CI=1.48-3.78; uncorrected p=0.00032 for rs13170645 homozygous minor genotype). We also observed suggestive evidence for associations with SNPs in other genes including CYP26B1 and WNT7A. Animal studies have shown that FGF10 induces formation of the apical ectodermal ridge and is necessary for limb development. Our data suggest that common variants in FGF10 increase the risk for a wide range of non-syndromic limb deficiencies.
doi:10.1002/ajmg.a.35565
PMCID: PMC3448837  PMID: 22965740
limb deficiencies; polymorphisms; FGF10
20.  Association analysis of complex diseases using triads, parent-child dyads and singleton monads 
BMC Genetics  2013;14:78.
Background
Triad families are routinely used to test association between genetic variants and complex diseases. Triad studies are important and popular since they are robust in terms of being less prone to false positives due to population structure. In practice, one may collect not only complete triads, but also incomplete families such as dyads (affected child with one parent) and singleton monads (affected child without parents). Since there is a lack of convenient algorithms and software to analyze the incomplete data, dyads and monads are usually discarded. This may lead to loss of power and insufficient utilization of genetic information in a study.
Results
We develop likelihood-based statistical models and likelihood ratio tests to test for association between complex diseases and genetic markers by using combinations of full triads, parent-child dyads, and affected singleton monads for a unified analysis. A likelihood is calculated directly to facilitate the data analysis without imputation and to avoid computational complexity. This makes it easy to implement the models and to explain the results.
Conclusion
By simulation studies, we show that the proposed models and tests are very robust in terms of accurately controlling type I error evaluations, and are powerful by empirical power evaluations. The methods are applied to test for association between transforming growth factor alpha (TGFA) gene and cleft palate in an Irish study.
doi:10.1186/1471-2156-14-78
PMCID: PMC3844511  PMID: 24007308
Association mapping of complex diseases; Likelihood ratio tests; Transmission disequilibrium tests
21.  Hirschsprung’s disease and variants in genes that regulate enteric neural crest cell proliferation, migration and differentiation 
Journal of human genetics  2012;57(8):485-493.
Hirschsprung’s disease (HSCR) results from failed colonization of the embryonic gut by enteric neural crest cells (ENCCs); colonization requires RET proto-oncogene (RET) signaling. We sequenced RET to identify coding and splice-site variants in a population-based case group and we tested for associations between HSCR and common variants in RET and candidate genes (ASCL1, HOXB5, L1CAM, PHOX2B, PROK1, PROKR1) chosen because they are involved in ENCC proliferation, migration, and differentiation in animal models. We conducted a nested case-control study of 304 HSCR cases and 1 215 controls. Among 38 (12.5%) cases with 34 RET coding and splice-site variants, 18 variants were previously unreported. We confirmed associations with common variants in HOXB5 and PHOX2B but the associations with variants in ASCL1, L1CAM, and PROK1 were not significant after multiple comparisons adjustment. RET variants were strongly associated with HSCR (P values between 10−3 and 10−31) but this differed by race/ethnicity: associations were absent in African-Americans. Our population-based study not only identified novel RET variants in HSCR cases, it showed that common RET variants may not contribute to HSCR in all race/ethnic groups. The findings for HOXB5 and PHOX2B provide supportive evidence that genes regulating ENCC proliferation, migration, and differentiation could be risk factors for HSCR.
doi:10.1038/jhg.2012.54
PMCID: PMC3503526  PMID: 22648184
congenital abnormalities; enteric nervous system; Hirschsprung disease; RET
22.  Clinic-Integrated Behavioral Intervention for Families of Youth With Type 1 Diabetes: Randomized Clinical Trial 
Pediatrics  2012;129(4):e866-e873.
OBJECTIVE:
To test the effect on diabetes management outcomes of a low-intensity, clinic-integrated behavioral intervention for families of youth with type 1 diabetes.
METHODS:
Families (n = 390) obtaining care for type 1 diabetes participated in a 2-year randomized clinical trial of a clinic-integrated behavioral intervention designed to improve family diabetes management practices. Measurement of hemoglobin A1c, the primary outcome, was obtained at each clinic visit and analyzed centrally. Blood glucose meter data were downloaded at each visit. Adherence was assessed by using a semistructured interview at baseline, mid-study, and follow-up. Analyses included 2-sample t tests at predefined time intervals and mixed-effect linear-quadratic models to assess for difference in change in outcomes across the study duration.
RESULTS:
A significant overall intervention effect on change in glycemic control from baseline was observed at the 24-month interval (P = .03). The mixed-effect model showed a significant intervention by age interaction (P < .001). Among participants aged 12 to 14, a significant effect on glycemic control was observed (P = .009 for change from baseline to 24-month interval; P = .035 for mixed-effect model across study duration), but there was no effect among those aged 9 to 11. There was no intervention effect on child or parent report of adherence; however, associations of change in adherence with change in glycemic control were weak.
CONCLUSIONS:
This clinic-integrated behavioral intervention was effective in preventing the deterioration in glycemic control evident during adolescence, offering a potential model for integrating medical and behavioral sciences in clinical care.
doi:10.1542/peds.2011-2858
PMCID: PMC3313642  PMID: 22392172
type 1 diabetes; children; adolescents; adherence; behavioral intervention; glycemic control
23.  Optimality of group testing in the presence of misclassification 
Biometrika  2011;99(1):245-251.
Summary
Several optimality properties of Dorfman’s (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases.
doi:10.1093/biomet/asr064
PMCID: PMC3412609  PMID: 23049137
Binary outcome; Maximum likelihood estimation; Pooling; Prevalence; Sensitivity; Specificity
24.  A Min-Max Combination of Biomarkers to Improve Diagnostic Accuracy † 
Statistics in medicine  2011;30(16):2005-2014.
Diagnostic accuracy can be improved considerably by combining multiple biomarkers. Although the likelihood ratio provides optimal solution to combination of biomarkers, the method is sensitive to distributional assumptions which are often difficult to justify. Alternatively simple linear combinations can be considered whose empirical solution may encounter extensive computation when the number of biomarkers is relatively large. Moreover, the optimal linear combinations derived under multivariate normality may suffer substantial loss of efficiency if the distributions are apart from normality. In this paper we propose a new approach that linearly combines the minimum and maximum values of the biomarkers. Such combination only involves searching for a single combination coefficient that maximizes the area under the receiver operating characteristic (ROC) curves and is thus computation-effective. Simulation results show that the min-max combination may yield larger partial or full area under the ROC curves and is more robust against distributional assumptions. The methods are illustrated using the growth-related hormones data from the Growth and Maturation in Children with Autism or Autistic Spectrum Disorder (ASD) Study (Autism/ASD Study).
doi:10.1002/sim.4238
PMCID: PMC3116024  PMID: 21472763
Area under curves; linear combinations; receiver operating characteristic (ROC) curve; robustness; sensitivity; specificity
25.  Folate and Vitamin B12 Related Genes and Risk for Omphalocele 
Human Genetics  2011;131(5):739-746.
Both taking folic acid-containing vitamins around conception and consuming food fortified with folic acid have been reported to reduce omphalocele rates. Genetic factors are etiologically important in omphalocele as well; our pilot study showed a relationship with the folate metabolic enzyme gene methylenetetrahydrofolate reductase (MTHFR). We studied 169 non-aneuploid omphalocele cases and 761 unaffected, matched controls from all New York State births occurring between 1998 and 2005 to look for associations with single nucleotide polymorphisms (SNPs) known to be important in folate, vitamin B12, or choline metabolism. In the total study population, variants in the transcobalamin receptor gene (TCblR), rs2232775 (Q8R), and the MTHFR gene, rs1801131 (1298A>C), were significantly associated with omphalocele. In African-Americans significant associations were found with SNPs in genes for the vitamin B12 transporter (TCN2) and the vitamin B12 receptor (TCblR). A SNP in the homocysteine-related gene, betaine-homocysteine S-methyltransferase (BHMT), rs3733890 (R239Q), was significantly associated with omphalocele in both African-Americans and Asians. Only the TCblR association in the total population remained statistically significant if Bonferroni correction was applied. The finding that transcobalamin receptor (TCblR) and transporter (TCN2) SNPs and a BHMT SNP were associated with omphalocele suggests that disruption of methylation reactions, in which folate, vitamin B12, and homocysteine play critical parts, may be a risk factor for omphalocele. Our data, if confirmed, suggest that supplements containing both folic acid and vitamin B12 may be beneficial in preventing omphaloceles.
doi:10.1007/s00439-011-1117-3
PMCID: PMC3374579  PMID: 22116453
omphalocele; folate; vitamin B12; homocysteine; transcobalamin; transcobalamin receptor

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