DHEA is the major precursor of human sex steroid synthesis and is inactivated via sulfonation to DHEAS. A previous genome-wide association study related the single nucleotide polymorphism (SNP) rs2637125, located near the coding region of DHEA sulfotransferase, SULT2A1, to serum DHEAS concentrations. However, the functional relevance of this SNP with regard to DHEA sulfonation is unknown. Using data from 3300 participants of the population-based cohort Study of Health in Pomerania, we identified 43 individuals being homozygote for the minor allele of the SNP rs2637125 (AA) and selected two sex- and age-matched individuals with AG and GG genotype (n=172) respectively. Steroid analysis including measurement of serum DHEA and DHEAS was carried out by liquid chromatography/mass spectrometry, employing steroid oxime analysis for enhancing the sensitivity of DHEA detection. We applied quantile regression models to compare median hormone levels across SULT2A1 genotypes. Median comparisons by SULT2A1 genotype (AA vs AG and GG genotypes respectively) showed no differences in the considered hormones including DHEAS, DHEA, androstenedione, as well as cortisol and cortisone concentrations. SULT2A1 genotype also had no effect on the DHEA/DHEAS ratio. Sex-stratified analyses, as well as alternative use of the SULT2A1 SNP rs182420, yielded similar negative results. Genetic variants of SULT2A1 do not appear to have an effect on individual DHEA and DHEAS concentrations or the DHEA/DHEAS ratio as a marker of DHEA sulfonation capacity.

Background

Insulin-like growth factor I (IGF-I), which is mostly carried in blood by IGF-binding protein 3 (IGFBP-3), was associated to the glomerular filtration rate and chronic kidney disease in a multiethnic study among US adults. The aim of the present study was to investigate whether serum IGF-I or IGFBP-3 are associated with estimated glomerular filtration rate (eGFR) in a population-based study of Caucasian adults.

Methods

Data from 4028 subjects (2048 women) aged 20 to 81 years from the Study of Health in Pomerania (SHIP) were analyzed. Total serum IGF-I and IGFBP-3 concentrations were determined by chemiluminescence immunoassays and categorized into sex- and age-specific quartiles.

Results

After adjusting for age, waist circumference and type 2 diabetes mellitus, analysis of variance (ANOVA) revealed inverse associations between serum IGF-I concentrations and eGFR in men as well as between serum IGFBP-3 concentrations and eGFR in men and women. Logistic regression analyses confirmed these findings and showed that high IGF-I or IGFBP-3 concentrations were associated with an increased risk of decreased eGFR (<60 mL/min/1.73 m2) in men or women. These relations became stronger when lower eGFR cut-offs were used for the analyses.

Conclusion

Our data revealed associations of increased serum IGF-I concentrations and decreased eGFR in men but not in women and an association of increased serum IGFBP-3 concentrations and decreased eGFR in both sexes.

Microarray profiling of gene expression is widely applied in molecular biology and functional genomics. Experimental and technical variations make meta-analysis of different studies challenging. In a total of 3358 samples, all from German population-based cohorts, we investigated the effect of data preprocessing and the variability due to sample processing in whole blood cell and blood monocyte gene expression data, measured on the Illumina HumanHT-12 v3 BeadChip array.

Gene expression signal intensities were similar after applying the log2 or the variance-stabilizing transformation. In all cohorts, the first principal component (PC) explained more than 95% of the total variation. Technical factors substantially influenced signal intensity values, especially the Illumina chip assignment (33–48% of the variance), the RNA amplification batch (12–24%), the RNA isolation batch (16%), and the sample storage time, in particular the time between blood donation and RNA isolation for the whole blood cell samples (2–3%), and the time between RNA isolation and amplification for the monocyte samples (2%). White blood cell composition parameters were the strongest biological factors influencing the expression signal intensities in the whole blood cell samples (3%), followed by sex (1–2%) in both sample types. Known single nucleotide polymorphisms (SNPs) were located in 38% of the analyzed probe sequences and 4% of them included common SNPs (minor allele frequency >5%). Out of the tested SNPs, 1.4% significantly modified the probe-specific expression signals (Bonferroni corrected p-value<0.05), but in almost half of these events the signal intensities were even increased despite the occurrence of the mismatch. Thus, the vast majority of SNPs within probes had no significant effect on hybridization efficiency.

In summary, adjustment for a few selected technical factors greatly improved reliability of gene expression analyses. Such adjustments are particularly required for meta-analyses.

Aim. The aim was to compare the periodontal status of the acromegalic patients with healthy subjects from a large population-based cohort (Study of Health in Pomerania, SHIP). Materials and Methods. We studied 32 acromegalic patients (16 females) and 128 randomly selected SHIP subjects (controls) using a 1 : 4 matching. Serum IGF-I and IGFBP-3 levels were measured using the Immulite 2500 system. Periodontitis was assessed by clinical attachment loss (CAL), probing depth (PD), and number of missing teeth. Linear and logistic regression models were used to assess differences in periodontal variables between acromegalic patients and controls. Results. IGF-I levels were comparable in acromegalic patients and controls, whereas IGFBP-3 levels were significantly higher in acromegalic patients (P = 0.004). In multivariate modelling, both groups did not differ significantly with respect to mean CAL (P = 0.12) and high tooth loss (P = 0.36). Mean PD was higher in acromegalic patients by trend (B = 0.28 (−0.00; 0.56)). Conclusion. In acromegalic patients, periodontal disease severity did not differ from their healthy SHIP controls.

Background

The additional clinical value of clustering cardiovascular risk factors to define the metabolic syndrome (MetS) is still under debate. However, it is unclear which cardiovascular risk factors tend to cluster predominately and how individual risk factor states change over time.

Methods & Results

We used data from 3,187 individuals aged 20–79 years from the population-based Study of Health in Pomerania for a network-based approach to visualize clustered MetS risk factor states and their change over a five-year follow-up period. MetS was defined by harmonized Adult Treatment Panel III criteria, and each individual's risk factor burden was classified according to the five MetS components at baseline and follow-up. We used the map generator to depict 32 (25) different states and highlight the most important transitions between the 1,024 (322) possible states in the weighted directed network. At baseline, we found the largest fraction (19.3%) of all individuals free of any MetS risk factors and identified hypertension (15.4%) and central obesity (6.3%), as well as their combination (19.0%), as the most common MetS risk factors. Analyzing risk factor flow over the five-year follow-up, we found that most individuals remained in their risk factor state and that low high-density lipoprotein cholesterol (HDL) (6.3%) was the most prominent additional risk factor beyond hypertension and central obesity. Also among individuals without any MetS risk factor at baseline, low HDL (3.5%), hypertension (2.1%), and central obesity (1.6%) were the first risk factors to manifest during follow-up.

Conclusions

We identified hypertension and central obesity as the predominant MetS risk factor cluster and low HDL concentrations as the most prominent new onset risk factor.

Abstract

Enabled by diverse high-throughput technologies, the rapidly evolving field of “-omics sciences” offers the potential to study health and disease in breadth and depth at the human population level. We have recently linked genomics and metabolomics to present the first genome-wide association study of metabolic traits in human urine providing new insights into the functional background of chronic kidney disease. We propose systems epidemiology as a novel approach to study the complexities of human pathophysiology by integrating various population-level omic-metrics and to identify new trans-omic biomarkers.

Background

Biomarkers may help clinicians predict cardiovascular risk. We aimed to determine if the addition of endocrine, metabolic, and obesity-associated biomarkers to conventional risk factors improves the prediction of cardiovascular and all-cause mortality.

Methodology/Principal Findings

In a population-based cohort study (the Study of Health in Pomerania) of 3,967 subjects (age 20–80 years) free of cardiovascular disease with a median follow-up of 10.0 years (38,638 person-years), we assessed the predictive value of conventional cardiovascular risk factors and the biomarkers thyrotropin; testosterone (in men only); insulin-like growth factor-1 (IGF-1); hemoglobin A1c (HbA1c); creatinine; high-sensitive C-reactive protein (hsCRP); fibrinogen; urinary albumin-to-creatinine ratio; and waist-to-height ratio (WHtR) on cardiovascular and all-cause death.

During follow-up, we observed 339 all-cause including 103 cardiovascular deaths. In Cox regression models with conventional risk factors, the following biomarkers were retained as significant predictors of cardiovascular death after backward elimination: HbA1c, IGF-1, and hsCRP. IGF-1 and hsCRP were retained as significant predictors of all-cause death.

For cardiovascular death, adding these biomarkers to the conventional risk factors changed the C-statistic from 0.898 to 0.910 (p = 0.02). The net reclassification improvement was 10.6%. For all-cause death, the C-statistic changed from 0.849 to 0.853 (P = 0.09).

Conclusions/Significance

HbA1c, IGF-1, and hsCRP predict cardiovascular death independently of conventional cardiovascular risk factors. These easily assessed endocrine and metabolic biomarkers might improve the ability to predict cardiovascular death.

Insulin-like growth factor-I (IGF-I) and insulin-like growth factor-binding protein-3 (IGFBP-3) are involved in cell replication, proliferation, differentiation, protein synthesis, carbohydrate homeostasis and bone metabolism. Circulating IGF-I and IGFBP-3 concentrations predict anthropometric traits and risk of cancer and cardiovascular disease. In a genome-wide association study of 10 280 middle-aged and older men and women from four community-based cohort studies, we confirmed a known association of single nucleotide polymorphisms in the IGFBP3 gene region on chromosome 7p12.3 with IGFBP-3 concentrations using a significance threshold of P < 5 × 10−8 (P = 3.3 × 10−101). Furthermore, the same IGFBP3 gene locus (e.g. rs11977526) that was associated with IGFBP-3 concentrations was also associated with the opposite direction of effect, with IGF-I concentration after adjustment for IGFBP-3 concentration (P = 1.9 × 10−26). A novel and independent locus on chromosome 7p12.3 (rs700752) had genome-wide significant associations with higher IGFBP-3 (P = 4.4 × 10−21) and higher IGF-I (P = 4.9 × 10−9) concentrations; when the two measurements were adjusted for one another, the IGF-I association was attenuated but the IGFBP-3 association was not. Two additional loci demonstrated genome-wide significant associations with IGFBP-3 concentration (rs1065656, chromosome 16p13.3, P = 1.2 × 10−11, IGFALS, a confirmatory finding; and rs4234798, chromosome 4p16.1, P = 4.5 × 10−10, SORCS2, a novel finding). Together, the four genome-wide significant loci explained 6.5% of the population variation in IGFBP-3 concentration. Furthermore, we observed a borderline statistically significant association between IGF-I concentration and FOXO3 (rs2153960, chromosome 6q21, P = 5.1 × 10−7), a locus associated with longevity. These genetic loci deserve further investigation to elucidate the biological basis for the observed associations and clarify their possible role in IGF-mediated regulation of cell growth and metabolism.

Common risk factors of periodontitis and cardiovascular diseases fuel the debate on interrelationships between them. The aim is to prove whether statins may influence periodontal parameters by affecting either of these factors. Out of the 4,290 subjects of SHIP (Study of Health in Pomerania), we included subjects aged >30 years (219 with statins, 2937 without) and excluded edentulous. We determined periodontal measures, cholesterol fractions, and inflammation markers. Statin use and periodontal risk factors were assessed. Gingival plaque and periodontal attachment loss were associated with systemic LDL cholesterol (P < 0.001) and C-reactive protein CRP (P = 0.019) revealing interaction with statin use. When adjusted for age, sex, smoking, diabetes, education, and dental service, statins were identified as effect modifiers abolishing the relationship between attachment loss and LDL and between gingival plaque and LDL (interactions P < 0.001). No statin-related interaction was detected with increase in CRP. The interaction supports the view of inter-relationships between periodontal and systemic inflammatory mediators.

Testosterone concentrations in men are associated with cardiovascular morbidity, osteoporosis, and mortality and are affected by age, smoking, and obesity. Because of serum testosterone's high heritability, we performed a meta-analysis of genome-wide association data in 8,938 men from seven cohorts and followed up the genome-wide significant findings in one in silico (n = 871) and two de novo replication cohorts (n = 4,620) to identify genetic loci significantly associated with serum testosterone concentration in men. All these loci were also associated with low serum testosterone concentration defined as <300 ng/dl. Two single-nucleotide polymorphisms at the sex hormone-binding globulin (SHBG) locus (17p13-p12) were identified as independently associated with serum testosterone concentration (rs12150660, p = 1.2×10−41 and rs6258, p = 2.3×10−22). Subjects with ≥3 risk alleles of these variants had 6.5-fold higher risk of having low serum testosterone than subjects with no risk allele. The rs5934505 polymorphism near FAM9B on the X chromosome was also associated with testosterone concentrations (p = 5.6×10−16). The rs6258 polymorphism in exon 4 of SHBG affected SHBG's affinity for binding testosterone and the measured free testosterone fraction (p<0.01). Genetic variants in the SHBG locus and on the X chromosome are associated with a substantial variation in testosterone concentrations and increased risk of low testosterone. rs6258 is the first reported SHBG polymorphism, which affects testosterone binding to SHBG and the free testosterone fraction and could therefore influence the calculation of free testosterone using law-of-mass-action equation.

Author Summary

Testosterone is the most important testicular androgen in men. Low serum testosterone concentrations are associated with cardiovascular morbidity, metabolic syndrome, type 2 diabetes mellitus, atherosclerosis, osteoporosis, sarcopenia, and increased mortality risk. Thus, there is growing evidence that serum testosterone is a valuable biomarker of men's overall health status. Studies in male twins indicate that there is a strong heritability of serum testosterone. Here we perform a large-scale genome-wide association study to examine the effects of common genetic variants on serum testosterone concentrations. By examining 14,429 men, we show that genetic variants in the sex hormone-binding globulin (SHBG) locus and on the X chromosome are associated with a substantial variation in serum testosterone concentrations and increased risk of low testosterone. The reported associations may now be used in order to better understand the functional background of recently identified disease associations related to low testosterone. Importantly, we identified the first known genetic variant, which affects SHBG's affinity for binding testosterone and the free testosterone fraction and could therefore influence the calculation of free testosterone. This finding suggests that individual-based SHBG-testosterone affinity constants are required depending on the genotype of this single-nucleotide polymorphism.

Background

C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We aimed to identify genetic variants that are associated with CRP levels.

Methods and Results

We performed a genome wide association (GWA) analysis of CRP in 66,185 participants from 15 population-based studies. We sought replication for the genome wide significant and suggestive loci in a replication panel comprising 16,540 individuals from ten independent studies. We found 18 genome-wide significant loci and we provided evidence of replication for eight of them. Our results confirm seven previously known loci and introduce 11 novel loci that are implicated in pathways related to the metabolic syndrome (APOC1, HNF1A, LEPR, GCKR, HNF4A, and PTPN2), immune system (CRP, IL6R, NLRP3, IL1F10, and IRF1), or that reside in regions previously not known to play a role in chronic inflammation (PPP1R3B, SALL1, PABPC4, ASCL1, RORA, and BCL7B). We found significant interaction of body mass index (BMI) with LEPR (p<2.9×10−6). A weighted genetic risk score that was developed to summarize the effect of risk alleles was strongly associated with CRP levels and explained approximately 5% of the trait variance; however, there was no evidence for these genetic variants explaining the association of CRP with coronary heart disease.

Conclusion

We identified 18 loci that were associated with CRP levels. Our study highlights immune response and metabolic regulatory pathways involved in the regulation of chronic inflammation.

Background

Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association.

Methods

Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7%) occurred. Subjective health was assessed by SF-12 derived physical (PCS-12) and mental component summaries (MCS-12), and a single-item self-rated health (SRH) question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. Variable selection procedures were used to identify a parsimonious set of subjective health measures and biomarkers, whose predictive ability was compared using receiver operating characteristic (ROC) curves, C-statistics, and reclassification methods.

Results

In age- and gender-adjusted Cox models, poor SRH (hazard ratio (HR), 2.07; 95% CI, 1.34-3.20) and low PCS-12 scores (lowest vs. highest quartile: HR, 1.75; 95% CI, 1.31-2.33) were significantly associated with increased risk of all-cause mortality; an association independent of various covariates and biomarkers. Furthermore, selected subjective health measures yielded a significantly higher C-statistic (0.883) compared to the selected biomarker panel (0.872), whereas a combined assessment showed the highest C-statistic (0.887) with a highly significant integrated discrimination improvement of 1.5% (p < 0.01).

Conclusion

Adding biomarker information did not affect the association of subjective health measures with mortality, but significantly improved risk stratification. Thus, a combined assessment of self-reported subjective health and measured biomarkers may be useful to identify high-risk individuals for intensified monitoring.

OBJECTIVE

Infection may be a type 2 diabetes risk factor. Periodontal disease is a chronic infection. We hypothesized that periodontal disease was related to A1C progression in diabetes-free participants.

RESEARCH DESIGN AND METHODS

The Study of Health in Pomerania (SHIP) is a population-based cohort in Germany including 2,973 diabetes-free participants (53% women; aged 20–81 years). Participants were categorized into four groups according to increasing baseline periodontal disease levels (percentage of sites per mouth with attachment loss ≥5 mm, determined a priori); sample sizes for each respective category were 1,122, 488, 463, and 479 (241 participants were edentulous). Mean absolute changes (year 5 minus baseline) in A1C (ΔA1C) were regressed across periodontal categories while adjusting for confounders (e.g., age, sex, smoking, obesity, physical activity, and family history).

RESULTS

Across baseline periodontal disease categories, ΔA1C ± SEM values were 0.023 ± 0.02, 0.023 ± 0.02, 0.065 ± 0.03, and 0.106 ± 0.03 (Ptrend = 0.02), yielding an approximate fivefold increase in the absolute difference in ΔA1C when dentate participants in the highest versus lowest periodontal disease category were compared; these results were markedly stronger among participants with high-sensitivity C-reactive protein ≥1.0 mg/l (Pinteraction = 0.01). When individuals who had neither baseline periodontal disease nor deterioration in periodontal status at 5 years were compared with individuals with both poor baseline periodontal health and longitudinal periodontal deterioration, mean ΔA1C values were 0.005 vs. 0.143% (P = 0.003).

CONCLUSIONS

Periodontal disease was associated with 5-year A1C progression, which was similar to that observed for a 2-SD increase in either waist-to-hip ratio or age in this population.

OBJECTIVE

The aim of this analysis was to assess the prospective association of serum testosterone and dehydroepiandrosterone sulfate (DHEAS) levels with incident metabolic syndrome (MetS) in men.

RESEARCH DESIGN AND METHODS

Data were obtained from the Study of Health in Pomerania (SHIP), a population-based prospective cohort of adults aged 20–79 years. Analyses were conducted in 1,004 men without baseline MetS defined by National Cholesterol Education Program Adult Treatment Panel III guidelines. Testosterone and DHEAS were categorized by age-specific quartiles and Poisson regression models with relative risks (RRs) and 95% CIs were estimated.

RESULTS

After a median follow-up time of 5.0 years, 480 men (47.8%) developed MetS. Testosterone levels decreased with increasing number of MetS components. Testosterone in the lowest quartile predicted MetS (RR 1.38 [95% CI 1.13–1.69]), particularly among men aged 20–39 years (2.06 [1.29–3.29]), even after adjustment for age, smoking, alcohol consumption, physical activity, waist circumference, self-related health, and time of blood sampling. DHEAS levels were not related to incident MetS (0.99 [0.83–1.19]).

CONCLUSIONS

Low testosterone but not DHEAS predicts development of MetS in a population-based cohort of 1,004 men aged 20–79 years. Especially in young men aged 20–39 years, results suggest low testosterone as a strong predictor for incident MetS. Assessment of testosterone in young and middle-age men may allow early interventions in the general population.

Background

Studies from iodine-sufficient areas have shown that a high proportion of patients taking medication for thyroid diseases have thyroid stimulating hormone (TSH) levels outside the reference range. Next to patient compliance, inadequate dosing adjustment resulting in under- and over-treatment of thyroid disease is a major cause of poor therapy outcomes. Using thyroid function tests, we aim to measure the proportions of subjects, who are under- or over-treated with thyroid medication in a previously iodine-deficient area.

Findings

Data from 266 subjects participating in the population-based Study of Health in Pomerania (SHIP) were analysed. All subjects were taking thyroid medication. Serum TSH levels were measured using immunochemiluminescent procedures. TSH levels of < 0.27 or > 2.15 mIU/L in subjects younger than 50 years and < 0.19 or > 2.09 mIU/L in subjects 50 years and older, were defined as decreased or elevated, according to the established reference range for the specific study area. Our analysis revealed that 56 of 190 (29.5%) subjects treated with thyroxine had TSH levels outside the reference range (10.0% elevated, 19.5% decreased). Of the 31 subjects taking antithyroid drugs, 12 (38.7%) had TSH levels outside the reference range (9.7% elevated, 29.0% decreased). These proportions were lower in the 45 subjects receiving iodine supplementation (2.2% elevated, 8.9% decreased). Among the 3,974 SHIP participants not taking thyroid medication, TSH levels outside the reference range (2.8% elevated, 5.9% decreased) were less frequent.

Conclusion

In concordance with previous studies in iodine-sufficient areas, our results indicate that a considerable number of patients taking thyroid medication are either under- or over-treated. Improved monitoring of these patients' TSH levels, compared to the local reference range, is recommended.

It is assumed that testosterone is an important regulator of gender-related differences in ventricular repolarization. Therefore, our aim was to study whether serum levels of testosterone are associated with QTc, QT and RR interval variation. Setting: two independent population-based cohort studies. Participants: 445 male participants (≥55 years) from the Rotterdam study cohort and 1,428 male participants from the study of health in Pomerania (SHIP) with an electrocardiogram who were randomly sampled for assessment of serum testosterone at baseline, after exclusion of participants with testosterone altering drugs, QTc prolonging drugs or dig(it)oxin, left ventricular hypertrophy and left and right bundle branch block. Endpoints: length of the QTc, QT and RR intervals. Analysis: linear regression model, adjusted for the two individual studies and a pooled analysis of both studies. The pooled analysis of the Rotterdam study and SHIP showed that the QTc interval gradually decreased among the tertiles (P value for trend 0.024). The third tertile of serum testosterone was associated with a lower QTc interval compared to the first tertile [−3.4 ms (−6.5; −0.3)]. However, the third tertile of serum testosterone was not associated with a lower QT interval compared to the first tertile [−0.7 ms (−3.1; 1.8)]. The RR interval gradually increased among the tertiles (P value for trend 0.002) and the third tertile of serum testosterone showed an increased RR interval compared to the first tertile [33.5 ms (12.2; 54.8)]. In the pooled analysis of two population-based studies, serum testosterone levels were not associated with the QT interval, which could be due to a lack of power. Lower QTc intervals in men with higher serum testosterone levels could be due to the association of serum testosterone with prolongation of the RR interval.

Background

Patients with halitosis contact primary care practitioners, dentists, and gastroenterologists alike.

Objectives

It is unclear whether gastroesophageal reflux disease (GERD) is a risk factor for halitosis.

Design and Patients/Participants

We studied this possible relationship in the general population using the cross-sectional Study of Health in Pomerania (SHIP). Employing structured interviews, self-reported halitosis was assessed among 417 edentulous (toothless) subjects aged 40 to 81 years and among 2,588 dentate subjects aged 20 to 59 years. The presence of heartburn or acid regurgitation (GERD-related symptoms) at 4 levels (absent, mild, moderate, severe) was taken as exposure and used for logistic regression. Analyses were adjusted for relevant confounders, such as age, sex, depressive symptoms, history of chronic gastritis, history of gastric or duodenal ulcer, smoking, school education, and dental status.

Measurements and Main Results

We found a strong positive association between GERD-related symptoms and halitosis (odds ratio 12.94, 95% confidence interval (CI) 2.66–63.09, P = 0.002 for severe compared to no GERD-related symptoms) in denture-wearing subjects and a moderate, positive association between GERD-related symptoms and halitosis (odds ratio 2.24, 95% CI 1.27–3.92, P = 0.005) in dentate subjects with a clear dose–effect relationship.

Conclusions

The present study provides clear evidence for an association between GERD and halitosis. As there are effective treatments for GERD, these results suggest treatment options, such as proton pump inhibitors, for halitosis. These should be studied in randomized controlled trials.