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Additional file 1: Supplementary Table 1. Likert question response options. Supplementary Table 2. Differences in behavioral determinants at baseline by study arm. Supplementary Table 3. Baseline, follow-up, and change over study period for behavioral determinants by study arm. Supplementary Table 4. Influence of demographic factors on follow-up use of arsenic-safe water. Supplementary Table 5. Influence of demographic factors on arsenic filter cartridge change.

Over the last 20 years, there has been an explosion of genomic data collected for disease association, functional analyses, and other large-scale discoveries. At the same time, there have been revolutions in cloud computing that enable computational and data science research, while making data accessible to anyone with a web browser and an internet connection. However, students at institutions with limited resources have received relatively little exposure to curricula or professional development opportunities that lead to careers in genomic data science. To broaden participation in genomics research, the scientific community needs to support students, faculty, and administrators at Underserved Institutions (UIs) including Community Colleges, Historically Black Colleges and Universities, Hispanic-Serving Institutions, and Tribal Colleges and Universities in taking advantage of these tools in local educational and research programs. We have formed the Genomic Data Science Community Network (http://www.gdscn.org/) to identify opportunities and support broadening access to cloud-enabled genomic data science. Here, we provide a summary of the priorities for faculty members at UIs, as well as administrators, funders, and R1 researchers to consider as we create a more diverse genomic data science community., 42 pages, 3 figures

The effect of low-moderate levels of arsenic exposure and of arsenic metabolism on mortality remains uncertain. We used data from a prospective cohort study in 3600 men and women aged 45 to 75 years living in Arizona, Oklahoma, and North and South Dakota. The biomarker of inorganic arsenic exposure was the sum of urine inorganic (iAs), monomethylated (MMA) and dimethylated (DMA) arsenic compounds (ƩAs) at baseline. The proportions of urine iAs, MMA and DMA over the ƩiAs, expressed as iAs%, MMA%, and DMA%, respectively, were used as biomarkers of arsenic metabolism. Arsenic exposure and arsenic metabolism were associated with all-cause, cardiovascular, and cancer mortality. For each interquartile range (IQR) increase in ƩAs (12.5 μg/L, overall range 0.7–194.1 μg/L), the adjusted hazard ratios (aHRs) were 1.28 (95% CI 1.16–1.41) for all-cause mortality, 1.28 (1.08–1.52) for cardiovascular mortality and 1.15 (0.92–1.44) for cancer mortality. The aHR for mortality for each IQR increase in MMA%, when iAs% is decreasing, was 1.52 (95% CI 1.16–1.99) for cardiovascular disease, 0.73 (0.55–0.98) for cancer, and 1.03 (0.90–1.19) for all-cause mortality. These findings at low-moderate levels of arsenic exposure highlight the need to implement public health measures to protect populations from involuntary arsenic exposure and for research to advance the biological and clinical understanding of arsenic-related health effects in general populations. Version of record

Additional file 1: is available in .pdf format. The table lists originally proposed study outcomes (developed by academic investigators) and the final study outcomes that were included in the study based on community input with justification for changes.

The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

BACKGROUND: Guidelines for primary prevention of cardiovascular diseases focus on prediction of coronary heart disease and stroke. We assessed whether or not measurement of N-terminal-pro-B-type natriuretic peptide (NT-proBNP) concentration could enable a more integrated approach than at present by predicting heart failure and enhancing coronary heart disease and stroke risk assessment. METHODS: In this individual-participant-data meta-analysis, we generated and harmonised individual-participant data from relevant prospective studies via both de-novo NT-proBNP concentration measurement of stored samples and collection of data from studies identified through a systematic search of the literature (PubMed, Scientific Citation Index Expanded, and Embase) for articles published up to Sept 4, 2014, using search terms related to natriuretic peptide family members and the primary outcomes, with no language restrictions. We calculated risk ratios and measures of risk discrimination and reclassification across predicted 10 year risk categories (ie

A loss-of-function mutation (Q141K, rs2231142) in the ATP-binding cassette, subfamily G, member 2 gene (ABCG2) has been shown to be associated with serum uric acid levels and gout in Asians, Europeans, and European and African Americans; however, less is known about these associations in other populations. Rs2231142 was genotyped in 22,734 European Americans, 9,720 African Americans, 3,849 Mexican Americans, and 3,550 American Indians in the Population Architecture using Genomics and Epidemiology (PAGE) Study (2008–2012). Rs2231142 was significantly associated with serum uric acid levels (P = 2.37 × 10−67, P = 3.98 × 10−5, P = 6.97 × 10−9, and P = 5.33 × 10−4 in European Americans, African Americans, Mexican Americans, and American Indians, respectively) and gout (P = 2.83 × 10−10, P = 0.01, and P = 0.01 in European Americans, African Americans, and Mexican Americans, respectively). Overall, the T allele was associated with a 0.24-mg/dL increase in serum uric acid level (P = 1.37 × 10−80) and a 1.75-fold increase in the odds of gout (P = 1.09 × 10−12). The association between rs2231142 and serum uric acid was significantly stronger in men, postmenopausal women, and hormone therapy users compared with their counterparts. The association with gout was also significantly stronger in men than in women. These results highlight a possible role of sex hormones in the regulation of ABCG2 urate transporter and its potential implications for the prevention, diagnosis, and treatment of hyperuricemia and gout.

Evaluate the quality of care provided patients with acute myocardial infarction and compare with similar national and regional data.Case series.The Strong Heart Study has extensive population-based data related to cardiovascular events among American Indians living in three rural regions of the United States.Acute myocardial infarction cases (72) occurring between 1/1/2001 and 12/31/2006 were identified from a cohort of 4549 participants.The proportion of cases that were provided standard quality of care therapy, as defined by the Healthcare Financing Administration and other national organizations.The provision of quality services, such as administration of aspirin on admission and at discharge, reperfusion therapy within 24 hours, prescription of beta blocker medication at discharge, and smoking cessation counseling were found to be 94%, 91%, 92%, 86% and 71%, respectively. The unadjusted, 30 day mortality rate was 17%.Despite considerable challenges posed by geographic isolation and small facilities, process measures of the quality of acute myocardial infarction care for participants in this American Indian cohort were comparable to that reported for Medicare beneficiaries nationally and within the resident states of this cohort.

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p

Population studies have demonstrated an important role of social, behavioral, and environmental factors in blood pressure levels. Accounting for the genetic interaction of these factors may help to identify common blood pressure susceptibility alleles.

American Indians have a disproportionately high rate of kidney disease likely due to a combination of increased environmental and genetic risk factors. In an attempt to localize genes influencing kidney disease risk factors, we performed a genome wide scan of estimated glomerular filtration rate on participants of the Strong Heart Family Study. Over 3 600 men and women from 13 American Indian tribes were recruited from 3 centers (Arizona, North and South Dakota, Oklahoma). Using SOLAR 2.1.2, multipoint variance component linkage analysis was performed in each center as well as the entire cohort after controlling for center effects. Two modeling strategies were utilized: model 1 incorporated age, sex and interaction terms and model 2 additionally controlled for diabetic status, systolic and diastolic blood pressure, body mass index, low density lipoproteins, high density lipoproteins, triglycerides and smoking status. Significant evidence for linkage in Arizona lay on 12p12.2 at 39cM nearest marker D12S310 (LOD=3.5). Additional loci with suggestive evidence for linkage were detected at 1p36.31 (LOD=2.0–2.3), 2q33.3 (LOD=1.8) and 9q34.2 (LOD=2.4). No significant evidence for additive interaction with diabetes, hypertension or obesity was noted. In conclusion, we found evidence for linkage of a quantitative trait locus influencing estimated glomerular filtration rate to a region of chromosome 12p in a large cohort of American Indians.

ObjectivesThis study was designed to examine whether high-sensitivity C-reactive protein (CRP) and electrocardiographic (ECG) ST-segment depression (STD) have additive utility for predicting cardiovascular disease (CVD) death and all-cause death (ACD).BackgroundC-reactive protein, a marker of systemic inflammation, and ECG STD, an index of myocardial ischemia and hypertrophy, independently predict mortality.MethodsElectrocardiograms and CRP levels were examined in 2,155 American Indian participants in the second Strong Heart Study examination. ST-segment depression ≥50 μV (n = 127) and CRP >7.0 mg/l (defining the upper quartile of CRP levels, n = 540) were considered abnormal.ResultsAfter 5.2 ± 1.2 years follow-up there were 95 CVD deaths and 310 ACD. In univariate Cox analyses, the combination of CRP and ECG STD improved risk stratification compared to either alone, with the presence of both CRP >7.0 and ECG STD associated with a 7.7-fold increased risk of CVD death (95% confidence interval [CI] 3.3 to 18.2) and a 6.5-fold increased risk of ACD (95% CI 4.1 to 10.3). After adjustment for age, gender, and relevant risk factors, the combination of high CRP and STD remained predictive of CVD death and ACD, with the presence of both abnormal CRP and STD associated with the highest risks of CVD death (hazard ratio [HR] 3.2, 95% CI 1.1 to 10.5) and ACD (HR 3.9, 95% CI 2.1 to 7.2) and the presence of either high CRP or abnormal STD associated with intermediate risks of CVD death (HR 2.2, 95% CI 1.4 to 3.4) and ACD (HR 1.5, 95% CI 1.2 to 2.0).ConclusionsThe combination of ECG STD and CRP increases the risk of mortality, demonstrating the additive impacts of active inflammation and preclinical CVD on prognosis.

ObjectivesOur aim was to evaluate the impact of metabolic syndrome (MetS) on cardiac phenotype in adolescents.BackgroundA high prevalence of MetS has been reported in adolescents.MethodsFour hundred forty-six nondiabetic American Indian adolescents (age 14 to 20 years, 238 girls) underwent clinical evaluation, laboratory testing, and Doppler echocardiography. Age- and gender-specific partition values were used to define obesity and hypertension. Metabolic syndrome was defined according to Adult Treatment Panel III criteria, modified for adolescents. Left ventricular (LV) hypertrophy and left atrial (LA) dilation were identified using age- and gender-specific partition values.ResultsOne hundred eleven participants met criteria for MetS. They had a similar age and gender distribution as non-MetS participants. Analysis of covariance, controlling for relevant confounders, demonstrated that participants with MetS had higher LV, LA, and aortic root diameters, higher LV relative wall thickness, and greater LV mass index. Accordingly, MetS participants showed higher prevalences of LV hypertrophy (43.2% vs. 11.7%) and LA dilation (63.1% vs. 21.9%, both p < 0.001) compared with non-MetS participants. In addition, MetS was associated with a reduction in midwall shortening, lower transmitral mitral early to atrial peak velocity ratio, and mildly prolonged mitral early deceleration time (all p < 0.05). In multiple regression analysis, independently of demographics, obesity, blood pressure, and single metabolic components of MetS, clustered MetS was associated with a 2.6-fold higher likelihood of LV hypertrophy and a 2.3-fold higher likelihood of LA dilation (both p ≤ 0.02).ConclusionsIn a population sample of adolescents, MetS is associated with higher prevalences of LV hypertrophy and LA dilation and with reduced LV systolic and diastolic function, independently of individual MetS components.

ObjectivesThe goal here was to examine left ventricular (LV) geometry and function in a large, unselected group of adolescents with different degrees of abnormal body build, and verify whether possibly higher LV mass is compensatory for increased cardiac workload.BackgroundThere is little information on how much the excess of body weight impacts LV geometry and function in populations of adolescents.MethodsAnthropometric, laboratory, and Doppler echocardiographic parameters of cardiac geometry and function were obtained in 460 adolescent participants (age 14 to 20 years, 245 female participants, 27 hypertensive, 10 with diabetes) from the Strong Heart Study. Body build was classified based on 85th and 95th percentiles of body mass index (BMI)-for-age charts.ResultsRange of BMI was 16.3 to 56.5 kg/m2(28.8 ± 8.3 kg/m2); 114 participants (24.9%) fell within the 85th percentile of BMI distribution (normal weight [NW]), 113 (24.6%) fell between 85th and 95th percentile (overweight [OW]), and 223 (48.5%) fell above the 95th percentile (obese [OB]). Obese participants were older than OW and NW subjects (p < 0.01), without differences in heart rate. Both OW and OB had greater LV diameter and mass than NW (all p < 0.05). Left ventricular hypertrophy was more prevalent in the OB (33.5%) and OW (12.4%), as compared with NW participants (3.5%; p < 0.001), largely compensating increased cardiac workload. However, OB subjects had four-fold higher probability of carrying an LV mass exceeding values compensatory for their cardiac workload (p < 0.001), a feature associated with lower ejection fraction, myocardial contractility, and greater force developed by left atrium to complete LV filling (all p < 0.05).ConclusionsWhile in OW adolescents increased levels of LV mass are appropriate to compensate their higher hemodynamic load, in OB increase in LV mass exceeds this need and is associated with mildly reduced LV myocardial performance and increased left atrial force to contribute to LV filling.

BACKGROUND: Metabolism of inorganic arsenic (iAs) is subject to inter-individual variability, which is explained partly by genetic determinants. OBJECTIVES: We investigated the association of genetic variants with arsenic species and principal components of arsenic species in the Strong Heart Family Study (SHFS). METHODS: We examined variants previously associated with cardiometabolic traits (~ 200,000 from Illumina Cardio MetaboChip) or arsenic metabolism and toxicity (670) among 2,428 American Indian participants in the SHFS. Urine arsenic species were measured by high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS), and percent arsenic species [iAs, monomethylarsonate (MMA), and dimethylarsinate (DMA), divided by their sum × 100] were logit transformed. We created two orthogonal principal components that summarized iAs, MMA, and DMA and were also phenotypes for genetic analyses. Linear regression was performed for each phenotype, dependent on allele dosage of the variant. Models accounted for familial relatedness and were adjusted for age, sex, total arsenic levels, and population stratification. Single nucleotide polymorphism (SNP) associations were stratified by study site and were meta-analyzed. Bonferroni correction was used to account for multiple testing. RESULTS: Variants at 10q24 were statistically significant for all percent arsenic species and principal components of arsenic species. The index SNP for iAs%, MMA%, and DMA% (rs12768205) and for the principal components (rs3740394, rs3740393) were located near AS3MT, whose gene product catalyzes methylation of iAs to MMA and DMA. Among the candidate arsenic variant associations, functional SNPs in AS3MT and 10q24 were most significant (p < 9.33 × 10-5). CONCLUSIONS: This hypothesis-driven association study supports the role of common variants in arsenic metabolism, particularly AS3MT and 10q24. Citation: Balakrishnan P, Vaidya D, Franceschini N, Voruganti VS, Gribble MO, Haack K, Laston S, Umans JG, Francesconi KA, Goessler W, North KE, Lee E, Yracheta J, Best LG, MacCluer JW, Kent J Jr., Cole SA, Navas-Acien A. 2017. Association of cardiometabolic genes with arsenic metabolism biomarkers in American Indian communities: the Strong Heart Family Study (SHFS). Environ Health Perspect 125:15-22; http://dx.doi.org/10.1289/EHP251.

The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

Type 2 diabetes is highly prevalent and is the major cause of progressive chronic kidney disease in American Indians. Genome wide association studies identified several loci associated with diabetes but their impact on susceptibility to diabetic complications is unknown. To measure this we studied the association of 18 type 2 diabetes genome wide association single nucleotide polymorphisms (SNPs) with the estimated glomerular filtration rate (eGFR) (MDRD equation) and urine albumin to creatinine ratio in 6,958 individuals in the Strong Heart Study family and cohort participants. Center specific residuals of eGFR and the log urine albumin to creatinine ratio, obtained from linear regression models adjusted for age, sex and body mass index, were regressed onto SNP dosage using variance component in family data and linear regression models in unrelated individuals. Estimates were then combined across centers. Four diabetic loci were associated with eGFR and one locus with the urine albumin to creatinine ratio. A SNP in the WFS1 gene (rs10010131) was associated with higher eGFR in younger individuals and with increased albuminuria. The SNPs of the FTO, KCNJ11 and TCF7L2 genes were associated with lower eGFR, not albuminuria, and were not significant in prospective analyses. Our findings suggest a shared genetic risk for type 2 diabetes, its kidney complications, and a potential role for WFS1 in early onset diabetic nephropathy in American Indian populations.

Background The pathogenesis of atherosclerosis involves both hemostatic and inflammatory mechanisms. Fibrinogen is associated with both risk of thrombosis and inflammation. A recent meta-analysis showed that risk of coronary heart disease may increase 1.8 fold for 1 g/L of increased fibrinogen, independent of traditional risk factors. It is known that fibrinogen levels may be influenced by demographic, environmental and genetic factors. Epidemiologic and candidate gene studies are available; but few genome-wide linkage studies have been conducted, particularly in minority populations. The Strong Heart Study has demonstrated an increased incidence of cardiovascular disease in the American Indian population, and therefore represents an important source for genetic-epidemiological investigations. Methods The Strong Heart Family Study enrolled over 3,600 American Indian participants in large, multi-generational families, ascertained from an ongoing population-based study in the same communities. Fibrinogen was determined using standard technique in a central laboratory and extensive additional phenotypic measures were obtained. Participants were genotyped for 382 short tandem repeat markers distributed throughout the genome; and results were analyzed using a variance decomposition method, as implemented in the SOLAR 2.0 program. Results Data from 3535 participants were included and after step-wise, linear regression analysis, two models were selected for investigation. Basic demographic adjustments constituted model 1, while model 2 considered waist circumference, diabetes mellitus and postmenopausal status as additional covariates. Five LOD scores between 1.82 and 3.02 were identified, with the maximally adjusted model showing the highest score on chromosome 7 at 28 cM. Genes for two key components of the inflammatory response, i.e. interleukin-6 and "signal transducer and activator of transcription 3" (STAT3), were identified within 2 and 8 Mb of this 1 LOD drop interval respectively. A LOD score of 1.82 on chromosome 17 between 68 and 93 cM is supported by reports from two other populations with LOD scores of 1.4 and 1.95. Conclusion In a minority population with a high prevalence of cardiovascular disease, strong evidence for a novel genetic determinant of fibrinogen levels is found on chromosome 7 at 28 cM. Four other loci, some of which have been suggested by previous studies, were also identified.

Background Mannose-binding lectin (MBL) forms an integral part of the innate immune system. Persistent, subclinical infections and chronic inflammatory states are hypothesized to contribute to the pathogenesis of atherosclerosis. MBL gene (MBL2) variants with between 12 to 25% allele frequency in Caucasian and other populations, result in markedly reduced expression of functional protein. Prospective epidemiologic studies, including a nested, case-control study from the present population, have demonstrated the ability of MBL2 genotypes to predict complications of atherosclerosis,. The genetic control of MBL2 expression is complex and genetic background effects in specific populations are largely unknown. Methods The Strong Heart Study is a longitudinal, cohort study of cardiovascular disease among American Indians. A subset of individuals genotyped for the above mentioned case-control study were selected for analysis of circulating MBL levels by double sandwich ELISA method. Mean MBL levels were compared between genotypic groups and multivariate regression was used to determine other independent factors influencing MBL2 expression. Results Our results confirm the effects of variant structural (B, C, and D) and promoter (H and Y) alleles that have been seen in other populations. In addition, MBL levels were found to be positively associated with male gender and hemoglobin A1c levels, but inversely related to triglyceride levels. Correlation was not found between MBL and other markers of inflammation. Conclusion New data is presented concerning the effects of known genetic variants on MBL levels in an American Indian population, as well as the relationship of MBL2 expression to clinical and environmental factors, including inflammatory markers.

Background Recent analyses in a registry of hypertensive patients suggested that preceding left ventricular (LV) hypertrophy (LVH) and/or carotid atherosclerosis are associated with incident type 2 diabetes, independent of confounders. We assess the relation between prevalent cardio-renal target organ damage (TOD) and subsequent incident type 2 diabetes in a population-based study with high prevalence of obesity. Methods We selected 2887 non-diabetic participants from two cohorts of the Strong Heart Study (SHS). Clinical exam, laboratory tests and echocardiograms were performed. Adjudicated TODs were LVH, left atrium (LA) dilatation, and high urine albumin/creatinine ratio (UACR). Multivariable logistic regression models were used to identify variables responsible for the association between initial TODs and incident diabetes at 4-year follow-up (FU). Results After 4 years, 297 new cases of diabetes (10%) were identified, 216 of whom exhibited baseline impaired fasting glucose (IFG, 73%, p Conclusions In this population-based study with high prevalence of obesity, TOD precedes clinical appearance of type 2 diabetes and is related to the preceding metabolic status, body composition and inflammatory status. Trial registration Trial registration number: NCT00005134, Name of registry: Strong Heart Study, URL of registry: https://clinicaltrials.gov/ct2/show/NCT00005134, Date of registration: May 25, 2000, Date of enrolment of the first participant to the trial: September 1988

Deficient plasminogen activator inhibitor-1 (PAI-1) prevented hypertension in mice. Plasma PAI-1 was associated with hypertension in cross-sectional analyses, but the prospective association of PAI-1 with incident hypertension in large epidemiological studies is scarce. Leveraging two longitudinal cohorts of American Indians in the Strong Heart Study (SHS, N = 1019) and the Strong Heart Family Study (SHFS, N = 1502), we examined the prospective association of plasma PAI-1 with incident hypertension by multivariate logistic regression, adjusting for age, sex, study site, smoking, drinking, dietary sodium, obesity, lipids, fasting glucose, kidney function, inflammation, and follow-up years. Family relatedness in the SHFS was accounted for using the GLIMMIX procedure. Plasma PAI-1 level at baseline was measured by immunoassay. All participants were free of hypertension, cardiovascular diseases, and chronic kidney disease at baseline. A total of 305 and 258 participants, respectively, from the SHS (57 ± 7 years) and the SHFS (33 ± 13 years) developed incident hypertension during follow-up. In the SHS, higher level of log-transformed PAI-1 was associated with 1.35-fold increased risk of hypertension [odds ratio (OR) (95% confidence interval): 1.35 (1.06-1.72)]. Analysis using categorical PAI-1 (in tertiles) showed that participants in the highest tertile (≥58 ng/ml) had 63% increased risk for hypertension [OR = 1.63 (1.12-2.37)] compared with those in the lowest tertile (