Baseline characteristics of participants in the Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) Program.

OBJECTIVE: The Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) Program is a diabetes prevention trial comparing the diabetes conversion rate at 3 years between the intervention group, which receives the incentivized lifestyle intervention program with stepwise addition of metformin, and the control group, which receives the standard of care. We describe the baseline characteristics and compare Pre-DICTED participants with other diabetes prevention trials cohort. RESEARCH DESIGN AND METHODS: Participants were aged between 21 and 64 years, overweight (body mass index (BMI) ≥23.0 kg/m2), and had pre-diabetes (impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT)). RESULTS: A total of 751 participants (53.1% women) were randomized. At baseline, mean (SD) age was 52.5 (8.5) years and mean BMI (SD) was 29.0 (4.6) kg/m2. Twenty-three per cent had both IFG and IGT, 63.9% had isolated IGT, and 13.3% had isolated IFG. Ethnic Asian Indian participants were more likely to report a family history of diabetes and had a higher waist circumference, compared with Chinese and Malay participants. Women were less likely than men to meet the physical activity recommendations (≥150 min of moderate-intensity physical activity per week), and dietary intake varied with both sex and ethnicity. Compared with other Asian diabetes prevention studies, the Pre-DICTED cohort had a higher mean age and BMI. CONCLUSION: The Pre-DICTED cohort represents subjects at high risk of diabetes conversion. The study will evaluate the effectiveness of a community-based incentivized lifestyle intervention program in an urban Asian context.

CoMM-S4: A Collaborative Mixed Model Using Summary-Level eQTL and GWAS Datasets in Transcriptome-Wide Association Studies.

Motivation: Genome-wide association studies (GWAS) have achieved remarkable success in identifying SNP-trait associations in the last decade. However, it is challenging to identify the mechanisms that connect the genetic variants with complex traits as the majority of GWAS associations are in non-coding regions. Methods that integrate genomic and transcriptomic data allow us to investigate how genetic variants may affect a trait through their effect on gene expression. These include CoMM and CoMM-S2, likelihood-ratio-based methods that integrate GWAS and eQTL studies to assess expression-trait association. However, their reliance on individual-level eQTL data render them inapplicable when only summary-level eQTL results, such as those from large-scale eQTL analyses, are available. Result: We develop an efficient probabilistic model, CoMM-S4, to explore the expression-trait association using summary-level eQTL and GWAS datasets. Compared with CoMM-S2, which uses individual-level eQTL data, CoMM-S4 requires only summary-level eQTL data. To test expression-trait association, an efficient variational Bayesian EM algorithm and a likelihood ratio test were constructed. We applied CoMM-S4 to both simulated and real data. The simulation results demonstrate that CoMM-S4 can perform as well as CoMM-S2 and S-PrediXcan, and analyses using GWAS summary statistics from Biobank Japan and eQTL summary statistics from eQTLGen and GTEx suggest novel susceptibility loci for cardiovascular diseases and osteoporosis. Availability and implementation: The developed R package is available at https://github.com/gordonliu810822/CoMM.

The Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) program: study protocol for a randomized controlled trial.

BACKGROUND: Community-based diabetes prevention programs varied widely in effectiveness, and the intervention strategy consisting of lifestyle interventions, stepwise addition of metformin, and financial incentives has not been studied in real-world clinical practice settings. The Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) trial is a pragmatic trial that aims to compare the effectiveness of a community-based stepwise diabetes prevention program with added financial incentives (intervention) versus the standard of care (control) in reducing the risk of type 2 diabetes over 3 years among overweight or obese individuals with pre-diabetes. METHODS: This is an open-label, 1:1 randomized controlled trial which aims to recruit 846 adult individuals with isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), or both IFG and IGT from Singapore. Intervention arm participants attend 12 group-based sessions (2 nutrition workshops, 9 exercise sessions, and a goal-setting workshop) delivered at community sites (weeks 1 to 6), receive weekly physical activity and nutrition recommendations delivered by printed worksheets (weeks 7 to 12), and receive monthly health tips delivered by text messages (months 4 to 36). From month 6 onwards, intervention arm participants who remain at the highest risk of conversion to diabetes are prescribed metformin. Intervention arm participants are also eligible for a payment/rewards program with incentives tied to attendance at the group sessions and achievement of the weight loss target (5% of baseline weight). All participants are assessed at baseline, month 3, month 6, and every 6 months subsequently till month 36. The primary endpoint is the proportion of participants with diabetes at 3 years. Secondary endpoints include the mean change from baseline at 3 years in fasting plasma glucose, 2-hour plasma glucose, HbA1c, body weight, body mass index, physical activity, and dietary intake. DISCUSSION: The Pre-DICTED trial will provide evidence of the effectiveness and feasibility of a community-based stepwise diabetes prevention program with added financial incentives for individuals with pre-diabetes in Singapore. The study will provide data for a future cost-effectiveness analysis, which will be used to inform policymakers of the value of a nationwide implementation of the diabetes prevention program. TRIAL REGISTRATION: ClinicalTrials.gov NCT03503942 . Retrospectively registered on April 20, 2018. Protocol version: 5.0 Date: 1 March 2019.

MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy.

The proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IVs) for drawing reliable causal relationships between health risk factors and disease outcomes. However, the unique features of GWAS demand that MR methods account for both linkage disequilibrium (LD) and ubiquitously existing horizontal pleiotropy among complex traits, which is the phenomenon wherein a variant affects the outcome through mechanisms other than exclusively through the exposure. Therefore, statistical methods that fail to consider LD and horizontal pleiotropy can lead to biased estimates and false-positive causal relationships. To overcome these limitations, we proposed a probabilistic model for MR analysis in identifying the causal effects between risk factors and disease outcomes using GWAS summary statistics in the presence of LD and to properly account for horizontal pleiotropy among genetic variants (MR-LDP) and develop a computationally efficient algorithm to make the causal inference. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods. Moreover, we used two real exposure-outcome pairs to validate the results from MR-LDP compared with alternative methods, showing that our method is more efficient in using all-instrumental variants in LD. By further applying MR-LDP to lipid traits and body mass index (BMI) as risk factors for complex diseases, we identified multiple pairs of significant causal relationships, including a protective effect of high-density lipoprotein cholesterol on peripheral vascular disease and a positive causal effect of BMI on hemorrhoids.

CoMM: A Collaborative Mixed Model That Integrates GWAS and eQTL Data Sets to Investigate the Genetic Architecture of Complex Traits.

Genome-wide association study (GWAS) analyses have identified thousands of associations between genetic variants and complex traits. However, it is still a challenge to uncover the mechanisms underlying the association. With the growing availability of transcriptome data sets, it has become possible to perform statistical analyses targeted at identifying influential genes whose expression levels correlate with the phenotype. Methods such as PrediXcan and transcriptome-wide association study (TWAS) use the transcriptome data set to fit a predictive model for gene expression, with genetic variants as covariates. The gene expression levels for the GWAS data set are then 'imputed' using the prediction model, and the imputed expression levels are tested for their association with the phenotype. These methods fail to account for the uncertainty in the GWAS imputation step, and we propose a collaborative mixed model (CoMM) that addresses this limitation by jointly modelling the multiple analysis steps. We illustrate CoMM's ability to identify relevant genes in the Northern Finland Birth Cohort 1966 data set and extend the model to handle the more widely available GWAS summary statistics.

Effects of Helicobacter pylori Treatment on Incidence of Gastric Cancer in Older Individuals.

BACKGROUND & AIMS: Although eradication of Helicobacter pylori infection reduces the risk of gastric cancer, few data are available on its effects in older subjects. We compared the age-specific risk of gastric cancer in a large cohort of subjects who received H pylori eradication therapy vs a matched general population. METHODS: We searched the Hospital Authority database of Hong Kong to identify individuals with H pylori infection who had received a course of clarithromycin-containing eradication therapy from January 2003 through December 2012. We compared the gastric cancer incidence in this cohort with the expected incidence for the local general population by retrieving the gastric cancer incidence of the age- and sex-matched population from 2003 through 2014 (the latest available year) from the Hong Kong Cancer Registry. The primary outcome was the incidence of gastric cancer development in the cohort treated for H pylori infection vs the expected number of gastric cancer cases in the general population. Analyses were conducted by a priori age groups of less than 40 years, 40-59 years, and 60 years or older. RESULTS: Among 73,237 subjects infected with H pylori who received eradication therapy, 200 (0.27%) developed gastric cancer during a median follow-up time of 7.6 years. Compared with the matched general population, the gastric cancer risk was significantly lower in subjects 60 years or older who had received H pylori treatment (standardized incidence ratio [SIR], 0.82; 95% confidence interval [CI], 0.69-0.97; P = .02) but not in younger groups. When data were stratified based on time from H pylori treatment (less than 5 years, 5-9 years, and 10 or more years), the risk of gastric cancer was significantly lower than the general population 10 or more years after eradication in the group 40-59 years old (SIR 0.32; 95% CI, 0.08-0.88; P = .04) and the group 60 years or older (SIR, 0.42; 95% CI, 0.42-0.84; P = .02) than the other age groups. CONCLUSIONS: In an analysis of data from a public hospital database on Hong Kong, we associated treatment of H pylori infection with a lower risk of gastric cancer, particularly in older subjects, 10 or more years after treatment.

Two Powerful Tests for Parent-of-Origin Effects at Quantitative Trait Loci on the X Chromosome.

Parent-of-origin effects, which describe an occurrence where the expression of a gene depends on its parental origin, are an important phenomenon in epigenetics. Statistical methods for detecting parent-of-origin effects on autosomes have been investigated for 20 years, but the development of statistical methods for detecting parent-of-origin effects on the X chromosome is relatively new. In the literature, a class of Q-XPAT-type tests are the only tests for the parent-of-origin effects for quantitative traits on the X chromosome. In this paper, we propose two simple and powerful classes of tests to detect parent-of-origin effects for quantitative trait values on the X chromosome. The proposed tests can accommodate complete and incomplete nuclear families with any number of daughters. The simulation study shows that our proposed tests produce empirical type I error rates that are close to their respective nominal levels, as well as powers that are larger than those of the Q-XPAT-type tests. The proposed tests are applied to a real data set on Turner's syndrome, and the proposed tests give a more significant finding than the Q-C-XPAT test.