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Dongfeng-Tongji Cohort

【Source: | Date:2021-11-25 】

Non-communicable disease epidemiology: Dongfeng-Tongji Cohort

China has experienced rapid socioeconomic changes over the past several decades, together with the changes in population structure (e.g., ageing), environment and lifestyles (e.g., diet and physical activity). Although we have made substantial progress in terms of increased life expectancy, a higher burden of chronic non-communicable diseases (NCDs) has quickly become a serious public health problem.

NCDs are clearly multi-factorial diseases with contributions from both environmental exposures and genetic factors. However, their individual and joint roles in the development of NCDs have yet to be determined in the Chinese population. Evidence suggests that Asians, including the Chinese, are more susceptible to diabetes, hypertension, and other chronic diseases than Caucasians for a given age and body mass index (BMI). Recent advances in genome-wide association studies (GWAS) have led to successful identifications of a large number of common variants for chronic diseases, including obesity, diabetes, cardiovascular disease, and cancer. Rapid epidemiologic transitions in China provide a unique opportunity to examine a wide range of factors behind the causes and progression of chronic diseases and the potential role of gene-environment interactions.

To examine the determinants of chronic diseases in a population that is in the midst of rapid epidemiologic transition, we launched the Dongfeng-Tongji cohort (DFTJ cohort).

The Dongfeng-Tongji Cohort study

The Dongfeng-Tongji cohort (DFTJ cohort) started in 2008 and enrolled 27,009 retired employees (44.6% males) from a state-owned automobile enterprise in Shiyan City, Hubei, China from 2008 to 2010. The Dongfeng Motor Corporation (DMC), founded in 1969, is one of the 3 largest auto manufacturers in China. DMC is a state-owned enterprise located in Shiyan City, Hubei province (Figure 1). Most first-generation employees, almost all retired now, emigrated to Hubei province from many parts of China, such as Liaoning, Jilin, Shandong, Jiangsu, and Shanghai. All retired employees are covered by DMC’s health care service system, which consists of five company-owned hospitals, one Center of Disease Control and Prevention (CDC), and one Social Insurance Center. Dongfeng Central Hospital is the largest medical center in the system and provides comprehensive care for all employees including retired employees. The CDC monitors occupational hazards and diagnoses of work-related diseases. The medical insurance system plays a key role in disease registry and management. Retired employees have ready access to the system for general health checkups and medical care.

Figure 1. Locations of Dongfeng Motor Corporation (DMC) in China

 

The participants were recruited between September 2008 and June 2010 at baseline and were followed every 5 years. In 2013, we finished the first follow-up and included 38,295 participants (including 12317 who also participated in the baseline survey and 25,978 who were newly recruited in 2013). The follow-up rate was 96.2%. In 2018, we finished the second follow-up visits with an estimated number of participants of over 50,000 and we are now cleaning the data (Figure 2).

Figure 2. Study plan of the DFTJ cohort

The detailed information on demographics, lifestyle factors, and occupational and environmental exposures was collected at baseline and a biobank (plasma, serum and DNA) for the cohort has been established. In addition, biochemical traits including blood lipids, fasting glucose, hepatic function, renal function, complete blood count, tumor biomarkers, and urine routine were determined for the participants. The main goal of this study is to identify the environmental and genetic risk factors for a wide range of chronic diseases and to investigate gene-environment interactions and novel biomarkers in the prediction of chronic disease incidence and mortality.

After an overnight fast, all participants came to the health examination center at the Dongfeng Central Hospital, where trained physicians, nurses and technicians performed physical examinations including standing height, body weight, waist circumference, and blood pressure. Clinical examinations were conducted for potential conditions in the liver, gallbladder, spleen, kidney, prostate (for males), and the uterus, ovaries, and fallopian tubes (for females) (Table 1).

Table 1. Summary of clinical measures collected at baseline in the DFTJ cohort

Variables

Equipment used

Height and Weight

Dekon DK-08-E, Rayweigh, Beijing,   China

Waist circumference

Hoechstmass, Germany

Resting blood pressure

Mercury sphygmomanometer, China

12-lead electrocardiography

Cardiofax ECG-9020P, NIHO KHDEN,   China

Chest X-ray

Shimadzu UD150L, Shimadzu, Japan

Abdominal B-type   ultrasound inspection

Aplio XG, TOSHIBA, Japan

Fasting plasma glucose

ARCHITECT ci8200, Abbott, USA

Blood lipids

ARCHITECT ci8200, Abbott, USA

Hepatic function

ARCHITECT ci8200, Abbott, USA

Renal function

ARCHITECT ci8200, Abbott, USA

Complete blood count

CELL-DYN 3700, Abbott, USA

Tumor biomarkers

ARCHITECT ci8200, Abbott, USA

Urine routine

Mejer-600, Mejer, China

Trained interviewers administered questionnaires during face-to-face interviews. The questionnaires included demographic information, occupational history, socioeconomic status, family and personal disease histories, smoking history, alcohol use, diet (determined via a simplified semi-quantitative food frequency questionnaire), physical activity, stress, and psychological status (Table 2). Trained investigators entered questionnaire data into the computer twice using EpiData software.

Table 2. Summary of questionnaire data collected at baseline from the DFTJ cohort

Exposure category

Variable/exposure

Demographics and socioeconomics

Birthday, race, religion, housing type, household size, income,   education

Personal health behavior

Smoking, alcohol, tea, afternoon nap, physical activity (at work and   leisure)

Diet

Major food groups, including meats, vegetables, fruits, beans, eggs, and   dairy

Environmental exposure

Occupational history, living environment, passive smoking exposure

Family history

Family history of hypertension,   hyperlipidemia, coronary heart disease, diabetes, stroke, cancers, emphysema,   chronic bronchitis, asthma, pulmonary tuberculosis, cholelithiasis, chronic   hepatitis, nephritis, and arthritis

Past medical history

Diagnosed medical conditions, use of health services, use of medicines   for the most recent two weeks

Reproductive history

Parity and breastfeeding history, menopause status and associated   timing, contraceptive history, history of hormone replacement therapy use,   gynecological diseases

Stress and psychological status

Psychological morbidity scales/stress, anger/hostility, optimism, social   isolation

 

Fifteen miniliters of fasting blood samples were drawn with 3 vacuum tubes (two ethylenediamine tetraacetic acid [EDTA] anticoagulation tubes for plasma and DNA; one coagulation tube for serum). The hospital’s laboratory measured blood lipids (total cholesterol [TC], triglycerides [TG], high density lipoprotein cholesterol [HDL-C], and low density lipoprotein cholesterol [LDL-C]), fasting glucose, hepatic function (bilirubin, alanine aminotransferase [ALT], aspartate aminotransferase [AST], and alkaline phosphatase [ALP]), and renal function (blood urea nitrogen [BUN], creatinine, and uric acid).

The lab also provided a complete blood count and urine routine test (urine pH, nitrite, glucose, vitamin C, white blood cell, urine protein, bilirubin, urobilinogen, urine ketobody, urine specific gravity, and occult blood). Tumor associated antigens (cancer antigen 125 [CA125], squamous cell carcinoma-associated antigen [SCC], cancer antigen 19-9 [CA19-9], carcino-embryonic antigen [CEA], and alpha fetoprotein [AFP]) were determined by immunoassay at the same laboratory. Aliquots of plasma, serum, whole blood cells and DNA were stored at -80°C.

From 2013 April to October, we conducted the first follow-up of the DFTJ cohort. A total of 38,925 subjects were recruited, and 25,978 of them also participated in the baseline population and the follow-up rate was 96.2%. Similar questionnaires and clinical examinations were implemented in the first follow-up compared to baseline survey.

In addition, from 2008 to 2016, we identified and diagnosed the major environment-related disease including CHD, stroke and cancer et al, which enables us to do analysis to investigate the potential etiology, mechanism of these disease.

Main findings from the Dongfeng-Tongji Cohort study

Based on the baseline data and the first follow-up data of the Dongfeng-Tongji cohort, we studied the risk factors of NCDs: including but not limited to diabetes, coronary heart disease, stroke and cancer.

1. Circulating metabolites and risk of incident type 2 diabetes (T2D)

We performed a targeted metabolomics study (52 metabolites) of fasting plasma samples by liquid chromatography-mass spectrometry in two prospective case-control studies nested within the Dongfeng-Tongji (DFTJ) cohort and Jiangsu Non-communicable Disease (JSNCD) cohort. After following for 4.61 and 7.57 years, respectively, 1039 and 520 eligible participants developed incident T2D in these two cohorts, and controls were 1:1 matched with cases by age (6 5 years) and sex. Multivariate conditional logistic regression models were constructed to identify metabolites associated with future T2D risk in both cohorts. We identified four metabolites consistently associated with an increased risk of developing T2D in the two cohorts, including alanine, phenylalanine, tyrosine and palmitoylcarnitine. In the meta-analysis of two cohorts, the odds ratios (95% confidence intervals, CIs) comparing extreme quartiles were 1.79 (1.32–2.42) for alanine, 1.91 (1.41–2.60) for phenylalanine, 1.85 (1.37–2.48) for tyrosine and 1.63 (1.21–2.20) for palmitoylcarnitine (all P trend_0.01). Therefore, we confirmed the association of alanine, phenylalanine and tyrosine with future T2D risk and further identified palmitoylcarnitine as a novel metabolic marker of incident T2D in two prospective cohorts of Chinese adults. Our findings might provide new etiological insight into the development of T2D.

These findings were published in Int J Epidemiol (2016;45(5):1507-1516).

Also, collaboration with other research team and based on the DFTJ cohort, we discovered and validated serum metabolite biomarker panel, which exhibits good diagnostic performance for the early detection of hepatocellular carcinoma from at-risk populations. These finding were published in Hepatology (2017 Sep 28. doi: 10.1002/hep.29561

2. Circulating multiple metals and risk of incident coronary heart disease (CHD)

Circulating metals from both the natural environment and pollution have been linked to cardiovascular disease. However, few prospective studies have investigated the associations between exposure to multiple metals and risk of CHD. Therefore, we conducted a nested case-control study within the prospective Dongfeng-Tongji cohort. A total of 1621 incident CHD cases were identified through December 31, 2013, and controls (n=1621) were randomly selected from participants free of major cardiovascular disease at baseline and follow-up visits, and matched on age (±5 years) and sex. Baseline fasting plasma concentrations of 23 metals were randomly measured by inductively coupled plasma mass spectrometry (ICP-MS). We found that the adjusted odds ratios (OR, 95% CI) across quartiles of metal concentrations were as follows: titanium, 1.00, 1.32, 1.43, 1.43 (1.12-1.83; p=0.007 for trend); arsenic, 1.00, 1.13, 1.12, 1.73 (1.25-2.39; p=0.001); and selenium, 1.00, 0.87, 0.77, 0.64 (0.49-0.82; p<0.001), respectively. Furthermore, significant interactions were observed between metals, where plasma selenium attenuated the increased CHD risk associated with titanium and arsenic (p for interaction = 0.009 and 0.03, respectively). These findings indicated that plasma levels of titanium and arsenic were positively while selenium was inversely associated with incident CHD in a dose response fashion.

This work was published by Environ Health Perspect (2017;125(10):107007).

The association between multiple metals and risk of type 2 diabetes was published on Environment Pollution (2018;237:917-925); and the association between multiple metals and risk of type 2 diabetes was accepted for publication on Stroke.

3. Genome-wide analysis of DNA methylation and acute coronary syndrome (ACS)

Based on the DFTJ cohort, we investigated genome-wide methylation of whole blood in 102 ACS patients and 101 controls using HumanMethylation450 array, and externally replicated significant discoveries in 100 patients and 102 controls. For the replicated loci, we further analyzed their association with ACS in 6 purified leukocyte subsets, their correlation with the expressions of annotated genes, and their association with cardiovascular traits/risk factors. We found novel and reproducible association of ACS with blood methylation at 47 cytosine-phosphoguanine sites (discovery: false discovery rate <0.005; replication: Bonferroni corrected P <0.05). The association of methylation levels at these cytosine-phosphoguanine sites with ACS was further validated in at least 1 of the 6 leukocyte subsets, with predominant contributions from CD8+ T cells, CD4+ T cells, and B cells. Blood methylation of 26 replicated cytosine-phosphoguanine sites showed significant correlation with expressions of annotated genes (including IL6R, FASLG, and CCL18; P<5.9×10-4), and differential gene expression in case versus controls corroborated the observed differential methylation. The replicated loci suggested a role in ACS-relevant functions including chemotaxis, coronary thrombosis, and T-cell-mediated cytotoxicity. Functional analysis using the top ACS-associated methylation loci in purified T and B cells revealed vital pathways related to atherogenic signaling and adaptive immune response. Furthermore, we observed a significant enrichment of the replicated cytosine-phosphoguanine sites associated with smoking and low-density lipoprotein cholesterol (Penrichment1×10-5). These findings were publish in Circ Res 2017;120(11):1754~1767.

4. Mendelian randomization analysis investigating the causal association of gallstone disease with diabetes risk

Gallstone disease (GSD) was reported to be positively associated with diabetes risk. Whether the association is causal remains unclear. This study aimed to examine the potential causal association between GSD and type 2 diabetes risk using a Mendelian randomization analysis.

Observational study was conducted among 16,299 participants who were free of cancer, heart disease, stroke, and diabetes at baseline in the Dongfeng-Tongji cohort study. GSD was diagnosed by experienced physicians by abdominal B-type ultrasound inspection and type 2 diabetes was defined according to the criteria of the American Diabetes Association. Cox proportional hazard regression model was used to examine the association of GSD with type 2 diabetes risk. A genetic risk score (GRS) for GSD was constructed with 8 single nucleotide polymorphisms (SNPs) which were derived from the previous genome-wide association studies. The causal associations of the score for GSD with type2 diabetes were tested among 7,000 participants in Mendelian randomization analysis. In this study the results indicated that GSD could increase 22% of diabetes risk. However, the results failed to provide evidence to support the causal associations of GSD with diabetes risk.

Therefore, the present study supported a positive but not a causal association of GSD with type 2 diabetes risk. More studies are needed to verify our findings in the future. These findings were publish in Hepatology 2018 Dec 4; doi: 10.1002/hep.30403.