Collection, Processing, and Storage of Biological Samples in Epidemiologic Studies: Sex Hormones, Carotenoids, Inflammatory Markers, and Proteomics as Examples

Menopausal age, adipokines, and heart failure incidence in postmenopausal women of the Multi-Ethnic Study of Atherosclerosis

OBJECTIVE

The mechanisms through which menopausal age influences heart failure (HF) development are controversial. Adiposity increases after menopause and could affect HF risk by influencing serum adipokine secretion. We investigated the associations of early menopause, and serum adipokines with incident HF in postmenopausal women.

METHODS

We included 746 postmenopausal women from the Multi-Ethnic Study of Atherosclerosis who reported their menopausal age and had data on adipokines and incident HF at the end of follow-up. Multivariable Cox proportional hazards models were used for analysis.

RESULTS

The mean age was 65.1 years. Over a median follow-up period of 17.8 years, 45 HF events occurred. After adjusting for waist circumference, other cardiovascular disease risk factors and myocardial infarction, the hazard ratios (95% confidence intervals) of incident HF attributable to early menopause were 4.50 (1.41-14.3), 4.64 (1.46-14.7), and 5.16 (1.59-16.7) in models that additionally included adiponectin, leptin, and resistin, respectively. In adjusted analyses, adiponectin was independently associated with incident HF 2.20 (1.35-3.57), while leptin and resistin were not. The interaction terms of early menopause with adiponectin, leptin, and resistin for incident HF were not significant ( Pint = 0.08-0.82).

CONCLUSIONS

Early menopause was significantly associated with incident HF. This association did not differ by serum adipokine levels. Only adiponectin was independently associated with incident HF in postmenopausal women when waist circumference, body mass index, and waist-hip ratio were used as the adiposity metric.

Development, characterization, and replication of proteomic aging clocks: Analysis of 2 population-based cohorts

BACKGROUND

Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in white individuals, and they used proteomic measures from only one-time point. In this study, we created de novo PACs and compared their performance to published PACs at 2 different time points in the Atherosclerosis Risk in Communities (ARIC) study of white and black participants (around 75% white and 25% black).

MEDTHODS AND FINDINGS

A total of 4,712 plasma proteins were measured using SomaScan in blood samples collected in 1990 to 1992 from 11,761 midlife participants (aged 46 to 70 years) and in 2011 to 2013 from 5,183 late-life participants (aged 66 to 90 years). The de novo ARIC PACs were constructed by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and validated in the remaining one-third of healthy participants at the corresponding time point. We also computed 3 published PACs. We estimated age acceleration for each PAC as residuals after regressing each PAC on chronological age. We also calculated the change in age acceleration from midlife to late life. We examined the associations of age acceleration and change in age acceleration with mortality through 2019 from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in participants (irrespective of health) after excluding the training set. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. We externally validated the midlife PAC using the Multi-Ethnic Study of Atherosclerosis (MESA) Exam 1 data. The ARIC PACs had a slightly stronger correlation with chronological age than published PACs in healthy participants at each time point. Associations with mortality were similar for the ARIC PACs and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per 1 standard deviation were 1.65 and 1.38 (both p < 0.001) for all-cause mortality, 1.37 and 1.20 (both p < 0.001) for CVD mortality, 1.21 (p = 0.028) and 1.04 (p = 0.280) for cancer mortality, and 1.68 and 1.36 (both p < 0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to the HRs for late-life age acceleration. The association between the change in age acceleration and cancer mortality was not significant. The external validation of the midlife PAC in MESA showed significant associations with mortality, as observed for midlife participants in ARIC. The main limitation is that our PACs were constructed in midlife and late-life participants. It is unknown whether these PACs could be applied to young individuals.

CONCLUSIONS

In this longitudinal study, we found that the ARIC PACs and published PACs were similarly associated with an increased risk of mortality. These findings suggested that PACs show promise as biomarkers of biological age. PACs may be serve as tools to predict mortality and evaluate the effect of anti-aging lifestyle and therapeutic interventions.

Biomarkers of food intake and their relevance to metabolic syndrome

Metabolic syndrome (MetS) constitutes a prevalent risk factor associated with non communicable diseases such as cardiovascular disease and type 2 diabetes. A major factor impacting the etiology of MetS is diet. Dietary patterns and several individual food constituents have been related to the risk of developing MetS or have been proposed as adjuvant treatment. However, traditional methods of dietary assessment such as 24 h recalls rely greatly on intensive user-interaction and are subject to bias. Hence, more objective methods are required for unbiased dietary assessment and efficient prevention. While it is accepted that some dietary-derived constituents in blood plasma are indicators for certain dietary patterns, these may be too unstable (such as vitamin C as a marker for fruits/vegetables) or too broad (e.g. polyphenols for plant-based diets) or reflect too short-term intake only to allow for strong associations with prolonged intake of individual food groups. In the present manuscript, commonly employed biomarkers of intake including those related to specific food items (e.g. genistein for soybean or astaxanthin and EPA for fish intake) and novel emerging ones (e.g. stable isotopes for meat intake or microRNA for plant foods) are emphasized and their suitability as biomarker for food intake discussed. Promising alternatives to plasma measures (e.g. ethyl glucuronide in hair for ethanol intake) are also emphasized. As many biomarkers (i.e. secondary plant metabolites) are not limited to dietary assessment but are also capable of regulating e.g. anti-inflammatory and antioxidant pathways, special attention will be given to biomarkers presenting a double function to assess both dietary patterns and MetS risk.

Biomarkers of Stress and Inflammation in Children

Background: Children are increasingly exposed to stressors that can affect their immune function. Given the possible negative effects of stress and inflammation on health, researchers need to use appropriate biomarkers to measure both the effects of stress and subsequent inflammatory responses. Purpose: The purpose of this paper is to briefly review stress and inflammatory pathways, identify biomarkers used to measure chronic stress and chronic inflammation particularly in children in clinical and community settings, and to discuss methodological considerations when measuring stress and inflammation in children. Discussion: Biomarkers of chronic stress can be classified as central, meaning they are made in the brain, or peripheral, meaning they are made in the peripheral tissues in response to central signals. The peripheral biomarker, cortisol, is most frequently used in the community setting. In addition, indirect measures, such as oxytocin, may complement the assessment of stress. Common biomarkers of chronic inflammation in children are C-reactive protein (CRP), TNF-α, and IL-6. Similarly, indirect biomarkers of chronic inflammation, such as IL-2 and IL-1β, may also be considered. Conclusions: Various types of specimens can be used to measure these biomarkers of stress and inflammation including blood, saliva, urine, sweat, hair, nails, and tears. Each type of specimen has different requirements for collection, storage, and assay. Future research would benefit from standardized biomarker levels across age and development in children and incorporation of other biomarkers.

Development and Characterization of Proteomic Aging Clocks in the Atherosclerosis Risk in Communities (ARIC) Study

Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in White individuals, and they used proteomic measures from only one-time point. In the Atherosclerosis Risk in Communities (ARIC) study of about 12,000 persons followed for 30 years (around 75% White, 25% Black), we created de novo PACs and compared their performance to published PACs at two different time points. We measured 4,712 plasma proteins by SomaScan in 11,761 midlife participants, aged 46-70 years (1990-92), and 5,183 late-life pariticpants, aged 66-90 years (2011-13). All proteins were log2-transformed to correct for skewness. We created de novo PACs by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and compared their performance to three published PACs. We estimated age acceleration (by regressing each PAC on chronological age) and its change from midlife to late life. We examined their associations with mortality from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in all remaining participants irrespective of health. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. The ARIC PACs had a slightly stronger correlation with chronological age than published PACs in healthy participants at each time point. Associations with mortality were similar for the ARIC and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per one standard deviation were 1.65 and 1.38 (both p<0.001) for all-cause mortality, 1.37 and 1.20 (both p<0.001) for CVD mortality, 1.21 (p=0.03) and 1.04 (p=0.19) for cancer mortality, and 1.46 and 1.68 (both p<0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to those observed for late-life age acceleration. The association between the change in age acceleration and cancer mortality was insignificant. In this prospective study, the ARIC and published PACs were similarly associated with an increased risk of mortality and advanced testing in relation to various age-related conditions in future studies is suggested.

Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

BACKGROUND

The MHC class I chain-related protein A (MICA) and protein B (MICB) participate in tumor immunosurveillance and may be important in colorectal cancer, but have not been examined in colorectal cancer development.

METHODS

sMICA and sMICB blood levels were measured by SomaScan in Visit 2 (1990-92, baseline) and Visit 3 (1993-95) samples in cancer-free participants in the Atherosclerosis Risk in Communities Study. We selected rs1051792, rs1063635, rs2516448, rs3763288, rs1131896, rs2596542, and rs2395029 that were located in or in the vicinity of MICA or MICB and were associated with cancer or autoimmune diseases in published studies. SNPs were genotyped by the Affymetrix Genome-Wide Human SNP Array. We applied linear and Cox proportional hazards regressions to examine the associations of preselected SNPs with sMICA and sMICB levels and colorectal cancer risk (236 colorectal cancers, 8,609 participants) and of sMICA and sMICB levels with colorectal cancer risk (312 colorectal cancers, 10,834 participants). In genetic analyses, estimates adjusted for ancestry markers were meta-analyzed.

RESULTS

Rs1051792-A, rs1063635-A, rs2516448-C, rs3763288-A, rs2596542-T, and rs2395029-G were significantly associated with decreased sMICA levels. Rs2395029-G, in the vicinity of MICA and MICB, was also associated with increased sMICB levels. Rs2596542-T was significantly associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males (HR = 0.68; 95% confidence interval, 0.49-0.96) but not in females (Pinteraction = 0.08).

CONCLUSIONS

Rs2596542-T associated with lower sMICA levels was associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males.

IMPACT

These findings support an importance of immunosurveillance in colorectal cancer.

Associations Between Inflammatory Mediators and Bone Outcomes in Postmenopausal Women: A Cross-Sectional Analysis of Baseline Data from the Prune Study

Purpose

Hypoestrogenism triggers increased production of inflammatory mediators, which contribute to bone loss during postmenopausal osteoporosis. This study aimed to investigate the association between circulating inflammatory markers and bone outcomes in postmenopausal women.

Materials and methods

We conducted a cross-sectional, secondary analysis of baseline data from participants who completed a 12-month randomized controlled trial, The Prune Study (NCT02822378), which included healthy postmenopausal women (n=183, 55-75 years old) with bone mineral density (BMD) T-score between 0.0 and -3.0 at any site. BMD was measured using dual-energy X-ray absorptiometry, and bone geometry and strength were measured using peripheral quantitative computed tomography. Blood was collected at baseline to measure (1) serum biomarkers of bone turnover, including procollagen type 1 N-terminal propeptide (P1NP) and C-terminal telopeptide and (2) inflammatory markers, including serum high-sensitivity C-reactive protein (hs-CRP) and plasma pro-inflammatory cytokines, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, IL-8, and monocyte chemoattractant protein (MCP)-1, using enzyme-linked immunosorbent assay. The associations between bone and inflammatory outcomes at baseline were analyzed using correlation and regression analyses.

Results

Serum hs-CRP negatively correlated with P1NP (r=-0.197, p=0.042). Plasma IL-1β, IL-6, IL-8, and TNF-α negatively correlated with trabecular bone score at the lumbar spine (all p<0.05). In normal-weight women, plasma IL-1β, IL-6, and IL-8 negatively correlated (p<0.05) with trabecular and cortical bone area, content, and density at various sites in the tibia and radius. Serum hs-CRP positively predicted lumbar spine BMD (β=0.078, p=0.028). Plasma IL-6 negatively predicted BMD at the total body (β=-0.131, p=0.027) and lumbar spine (β=-0.151, p=0.036), whereas plasma TNF-α negatively predicted total hip BMD (β=-0.114, p=0.028).

Conclusion

At baseline, inflammatory markers were inversely associated with various estimates of bone density, geometry, and strength in postmenopausal women. These findings suggest that inflammatory markers may be an important mediator for postmenopausal bone loss.

Relation between testosterone, cortisol and aggressive behavior in humans

Aggression is an evolutionary behavior as it has a role in survival, increasing one’s access to food, shelter, status and reproduction. Testosterone and Cortisol are hormones often linked to aggressive behavior. We gathered and organized data from the last five years on the relation among Testosterone, Cortisol and aggression, while assessing the methods used by those scientific papers. A systematic review was made according to PRISMA guidelines. The search for indexed articles was performed in January 2019 using the keywords aggress* AND Testosterone AND Cortisol in three databases: Web of Science, SCOPUS and PsycInfo. The specific role of Testosterone and Cortisol in aggressive behavior is not unanimous. However, most articles found either an increase in Testosterone or a decrease in Cortisol associated with this behavior. There is the need for standardizing methods of triggering and assessing aggressive behavior, taking into account the assessment of social desirability and its impacts.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

Stability properties of natural estrogen conjugates in different aqueous samples at room temperature and tips for sample storage

It is important to keep natural estrogen conjugates (C-NEs) intact in aqueous environmental sample before sample preparation; otherwise, this may influence the accurate determination of NEs. Therefore, this work thoroughly investigated the stability of C-NEs in three different aqueous environmental samples under four different storage conditions, room temperature, low temperature of 4 °C, low pH of 3, and addition of HgCl₂ at 2 g/L. Results showed that C-NEs in aqueous sample were easily deconjugated under low temperature of 4 °C, which has been widely used in sample collection and storage. Both the low pH of 3 and addition of HgCl₂ at 2 g/L under room temperature could keep C-NEs intact in domestic wastewaters and river water within 36 h, but the latter could keep C-NEs stable longer. This work is the first to show that low pH of 3 alone could keep C-NEs intact, which suggested that the combined condition at low temperature of 4 °C that has been widely used could be omitted. Meanwhile, compared to pH adjustment, addition of 2 g/L HgCl₂ into aqueous sample is more convenient and practical for 24-h composite sampling, which may be widely applied.

Agreement of aptamer proteomics with standard methods for measuring venous thrombosis biomarkers

BACKGROUND

Venous thromboembolism (VTE) is a complex disease with an incidence rate of about 1 in 1000 per year. Despite the availability of validated biomarkers for VTE, unprovoked events account for 50% of first events. Therefore, emerging high-throughput proteomics are promising methods for the expansion of VTE biomarkers. One such promising high-throughput platform is SomaScan, which uses a large library of synthetic oligonucleotide ligands known as aptamers to measure thousands of proteins.

OBJECTIVE

The aim of this study was to evaluate the viability of the aptamer-based SomaScan platform for VTE studies by examining its agreement with standard laboratory methods.

METHODS

We examined the agreement between eight established VTE biomarkers measured by SomaScan and standard laboratory immunoassay and viscosity-based instruments in 54 individuals (27 cases and 27 controls) from the Thrombophilia, Hypercoagulability and Environmental Risks in Venous Thromboembolism study. We performed the agreement analysis by using a regression model and predicting the estimates and the 95% prediction interval (PI) of the laboratory instrument values using SomaScan values.

RESULTS

SomaScan measurements exhibited overall poor agreement, particularly for D-dimer (average fit, 492.7 ng/mL; 95% PI, 110.0-1998.2) and fibrinogen (average fit, 3.3 g/L; 95% PI, 2.0-4.7).

CONCLUSION

Our results indicate that SomaScan measurement had poor agreement with the standard laboratory measurements. These results may explain why some genome-wide association studies with VTE proteins measured by SomaScan did not confirm previously identified loci. Therefore, SomaScan should be considered with caution in VTE studies.

Serum and Plasma Immunoglobulin G Fc N-Glycosylation Is Stable during Storage

Immunoglobulin G (IgG) glycosylation is studied in biological samples to develop clinical markers for precision medicine, for example, in autoimmune diseases and oncology. Inappropriate storage of proteins, lipids, or metabolites can lead to degradation or modification of biomolecular features, which can have a strong negative impact on accuracy and precision of clinical omics studies. Regarding the preservation of IgG glycosylation, the range of appropriate storage conditions and time frame is understudied. Therefore, we investigated the effect of storage on IgG Fc N-glycosylation in the commonly analyzed biofluids, serum and plasma. Short-term storage and accelerated storage stability were tested by incubating samples from three healthy donors under stress conditions of up to 50 °C for 2 weeks using −80 °C for 2 weeks as the reference condition. All tested IgG glycosylation features—sialylation, galactosylation, bisection, and fucosylation—remained unchanged up to room temperature as well as during multiple freeze–thaw cycles and exposure to light. Only when subjected to 37 °C or 50 °C for 2 weeks, galactosylation and sialylation subtly changed. Therefore, clinical IgG glycosylation analysis does not rely as heavily on mild serum and plasma storage conditions and timely analysis as many other omics analyses.

Testing a method to improve predictions of disease and mortality risk in western lowland gorillas (gorilla gorilla gorilla) using allostatic load

Allostatic load is the wear-and-tear organisms accumulate due to senescence and stress; it is measured by combining biomarkers from multiple somatic systems into allostatic load indices (ALIs). Frequently used in human research, ALIs have shown consistent results across samples despite different biomarkers and methods. However, determining optimal models likely is necessary if ALIs are to be feasible research tools in other species. Herein, we build on prior research in western lowland gorillas to explore one potential method for determining which biomarkers may be best for estimating allostatic load. After narrowing down which biomarkers to include using a combination of forward stepwise regression and independent biomarker associations with project variables, we estimated allostatic load using both the traditional one-tailed quartile method as well as a multi-method approach. There was a significant positive association between allostatic load and triglycerides, but not cholesterol, both of which are commonly used as diagnostic markers of poor health. Using binomial generalized linear models, a one-unit increase in allostatic load was associated with increased risk of all-cause morbidity and mortality, but reduced risk of cardiac disease. Although conclusions were similar, compared to our original ALIs, these new ALIs had weaker effect sizes and poorer relative goodness of fit, suggesting this method for identifying the best possible list of biomarkers to include in an index was not effective. This report continues the development of ALIs as a clinical tool in wildlife while systematically testing one possible method for determining an optimal ALI for a particular species.

The Sri Lankan twin registry biobank: South Asia's first twin biobank

Introduction

Biobanks are a valuable resource for creating advancements in science through cutting-edge omics research. Twin research methods allow us to understand the degree to which genetics and environmental factors contribute to health outcomes.

Methods

The Sri Lankan Twin Registry biobank (SLTR-b) was established in 2015 as part of Colombo Twin and Singleton Follow-up Study. Venous blood and urine were collected from twins and comparative sample of singletons for clinical investigations and biobanking.

Results

The SLTR-b currently houses 3369 DNA and serum samples. Biobank specimens are linked to longitudinal questionnaire data, clinical investigations, anthropometric measurements, and other data.

Discussion

The SLTR-b aims to address gaps in health and genetics research. It will provide opportunities for academic collaborations, local and international, and capacity building of future research leaders in twin and omics research. This paper provides a cohort profile of the SLTR-b and its linked data, and an overview of the strategies used for biobanking.

Mass spectrometry-based metabolomics for an in-depth questioning of human health

Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.

Inflammation-related plasma and CSF biomarkers for multiple sclerosis

Effective biomarkers for multiple sclerosis diagnosis, assessment of prognosis, and treatment responses, in particular those measurable in blood, are largely lacking. We have investigated a broad set of protein biomarkers in cerebrospinal fluid (CSF) and plasma using a highly sensitive proteomic immunoassay. Cases from two independent cohorts were compared with healthy controls and patients with other neurological diseases. We identified and replicated 10 cerebrospinal fluid proteins including IL-12B, CD5, MIP-1a, and CXCL9 which had a combined diagnostic efficacy similar to immunoglobulin G (IgG) index and neurofilament light chain (area under the curve [AUC] = 0.95). Two plasma proteins, OSM and HGF, were also associated with multiple sclerosis in comparison to healthy controls. Sensitivity and specificity of combined CSF and plasma markers for multiple sclerosis were 85.7% and 73.5%, respectively. In the discovery cohort, eotaxin-1 (CCL11) was associated with disease duration particularly in patients who had secondary progressive disease (P _CSF < 4 × 10^-5, P _plasma < 4 × 10^-5), and plasma CCL20 was associated with disease severity (P = 4 × 10^-5), although both require further validation. Treatment with natalizumab and fingolimod showed different compartmental changes in protein levels of CSF and peripheral blood, respectively, including many disease-associated markers (e.g., IL12B, CD5) showing potential application for both diagnosing disease and monitoring treatment efficacy. We report a number of multiple sclerosis biomarkers in CSF and plasma for early disease detection and potential indicators for disease activity. Of particular importance is the set of markers discovered in blood, where validated biomarkers are lacking.

Allostatic Load Indices With Cholesterol and Triglycerides Predict Disease and Mortality Risk in Zoo-Housed Western Lowland Gorillas (Gorilla gorilla gorilla)

Allostatic load, or the physiological dysregulation accumulated due to senescence and stress, is an established predictor of human morbidity and mortality and has been proposed as a tool for monitoring health and welfare in captive wildlife. It is estimated by combining biomarkers from multiple somatic systems into allostatic load indices (ALIs), providing a score representing overall physiological dysregulation. Such ALIs have been shown to predict disease and mortality risk in western lowland gorillas. In these prior analyses, we were unable to include lipid markers, a potential limitation as they are key biomarkers in human models. Recently, we were able to assay serum cholesterol and triglycerides and add them to our previous ALI. We then re-examined associations with health outcomes using binomial generalized linear models. We constructed ALIs using 2 pooling strategies and 2 methods. By itself, a 1-unit increase in allostatic load was associated with higher odds of all-cause morbidity and mortality, but results were mixed for cardiac disease. However, the best fit models for all-cause morbidity and cardiac disease included only age and sex. Allostatic load was retained alongside age in the best fit models for mortality, with a 1-unit increase associated with 23% to 45% higher odds of death. Compared with previous results, ALIs containing cholesterol and triglycerides better predict disease risk in zoo-housed western lowland gorillas, as evidenced by larger effect sizes for some models and better goodness of fit for all ALIs. Based on these results, we address methodology for future allostatic load research on wildlife.

Flavonoid Intake and Plasma Sex Steroid Hormones, Prolactin, and Sex Hormone-Binding Globulin in Premenopausal Women

Background: Flavonoids potentially exert anti-cancer effects, as suggested by their chemical structures and supported by animal studies. In observational studies, however, the association between flavonoids and breast cancer, and potential underlying mechanisms, remain unclear. Objective: To examine the relationship between flavonoid intake and sex hormone levels using timed blood samples in follicular and luteal phases in the Nurses’ Health Study II among premenopausal women. Methods: Plasma concentrations of estrogens, androgens, progesterone, dehydroepiandrosterone (DHEA), DHEA sulfate (DHEAS), prolactin, and sex hormone-binding globulin (SHBG) were measured in samples collected between 1996 and 1999. Average flavonoid were calculated from semiquantitative food frequency questionnaires collected in 1995 and 1999. We used generalized linear models to calculate geometric mean hormone concentrations across categories of the intake of flavonoids and the subclasses. Results: Total flavonoid intake generally was not associated with the hormones of interest. The only significant association was with DHEAS (p-trend = 0.02), which was 11.1% (95% confidence interval (CI): −18.6%, −3.0%) lower comparing the highest vs. lowest quartile of flavonoid intake. In subclass analyses, the highest (vs. lowest) quartile of flavan-3-ol intake was associated with significantly lower DHEAS concentrations (−11.3% with 95% CI: −18.3%, −3.7%, p-trend = 0.01), and anthocyanin intake was associated with a significant inverse trend for DHEA (−18.0% with 95% CI: −27.9%, −6.7%, p-trend = 0.003). Conclusion: Flavonoid intake in this population had limited impact on most plasma sex hormones in premenopausal women. Anthocyanins and flavan-3-ols were associated with lower levels of DHEA and DHEAS.

Inflammation and breast density among female Chinese immigrants: exploring variations across neighborhoods

PURPOSE

We examined associations of inflammation with breast density, a marker of breast cancer risk, among female Chinese immigrants and explored whether associations varied by neighborhood environment.

METHODS

Assessments of serum C-reactive protein (CRP), soluble tumor necrosis factor receptor 2 (sTNFR2), and breast density were performed among 401 Chinese immigrants across the Philadelphia region. Participant addresses were geocoded, with the majority residing in areas representing traditional urban enclaves (i.e., Chinatown and South Philadelphia) or an emerging enclave with a smaller, but rapidly growing Chinese immigrant population (i.e., the Near Northeast). The remainder was classified as residing in non-enclaves.

RESULTS

In multivariable adjusted regression models, CRP was inversely associated with dense breast area (p = 0.01). Levels of sTNFR2 were also inversely associated with dense breast area, but these associations varied by neighborhood (interaction p = 0.01); specifically, inverse associations were observed among women residing in the emerging enclave (p = 0.03), but not other neighborhoods.

CONCLUSIONS

Among Chinese immigrant women, aggregate analyses that do not take neighborhood context into consideration can mask potential variations in association of inflammatory markers with breast density. Future studies should consider how neighborhood contextual factors may contribute to differential risk pathways.

Unbiased data analytic strategies to improve biomarker discovery in precision medicine

Omics technologies promised improved biomarker discovery for precision medicine. The foremost problem of discovered biomarkers is irreproducibility between patient cohorts. From a data analytics perspective, the main reason for these failures is bias in statistical approaches and overfitting resulting from batch effects and confounding factors. The keys to reproducible biomarker discovery are: proper study design, unbiased data preprocessing and quality control analyses, and a knowledgeable application of statistics and machine learning algorithms. In this review, we discuss study design and analysis considerations and suggest standards from an expert point-of-view to promote unbiased decision-making in biomarker discovery in precision medicine.

Circulatory pattern of cytokines, adipokines and bone markers in postmenopausal women with low BMD

Objective: In addition to some well-characterized bone turnover markers (BTMs), cytokines and adipokines have also been suggested to be linked to osteoporosis seen in menopause. However, there is much controversy on the possible association between these markers and bone mineral density (BMD). This study was aimed at measuring circulatory levels of selected cytokines, adipokines and BTMs in postmenopausal women with normal and low BMD. Methods: The study population included 71 post-menopausal women, of whom 25 had normal BMD, 31 had osteopenia and 13 had osteoporosis. Circulatory levels of selected pro-resorptive (TNF-α, IL-1β, IL-6, IL-8, IL-12, IL-17), anti-resorptive (IFN-γ, IL-4, IL-10, IL-13, TGF-β) and five adipokine markers (adiponectin, adipsin, lipocalin-2/NGAL, PAI-1 and resistin) were measured using the Multiplex system and read on the Magpix ELISA platform. Further, two bone turnover markers (PINP, CTX) as well as estradiol levels were assayed from the same samples. Results: While circulatory levels of cytokines were comparable between groups, women with low BMD had statistically significantly higher median circulatory levels of adipokines as compared to those with normal BMD. Further, while levels of CTX were not different between the two groups; PINP, PINP/CTX ratio and estradiol levels were significantly lower in women with low BMD. Levels of adiponectin, PINP, PINP/CTX ratio and estradiol correlated significantly with BMD of the hip and spine. Conclusion: The associations between various markers and BMD are complex and multivariate. Our data provide insights into the possible use of circulatory levels of cytokines, adipokines and bone turnover markers on the pathogenesis of postmenopausal osteoporosis because of the well-documented effects of these molecules on bone tissue and their relevance to osteoporosis.

Mass spectrometry-based intraoperative tumor diagnostics

In surgical oncology, decisions regarding the amount of tissue to be removed can have important consequences: the decision between preserving sufficient healthy tissue and eliminating all tumor cells is one to be made intraoperatively. This review discusses the latest technical innovations for a more accurate tumor margin localization based on mass spectrometry. Highlighting the latest mass spectrometric inventions, real-time diagnosis seems to be within reach; focusing on the intelligent knife, desorption electrospray ionization, picosecond infrared laser and MasSpec pen, the current technical status is evaluated critically concerning its scientific and medical practice.

Reproducibility and Variability of Protein Analytes Measured Using a Multiplexed Modified Aptamer Assay

BACKGROUND

There is growing interest in the use of multiplexed aptamer-based assays for large-scale proteomic studies. However, the analytic, short- and long-term variation of the measured proteins is largely uncharacterized.

METHODS

We quantified 4001 plasma protein analytes from 42 participants in the Atherosclerosis Risk in Communities (ARIC) Study in split samples and at multiple visits using a multiplexed modified aptamer assay. We calculated the CV, Spearman correlation, and intraclass correlation (ICC) between split samples and evaluated the short-term (4-9 weeks) and long-term (approximately 20 years) variability using paired t-tests with log-transformed protein concentrations and Bonferroni-corrected significance thresholds. We performed principal component (PC) analysis of protein analyte concentrations and evaluated their associations with age, sex, race, and estimated glomerular filtration rate (eGFR).

RESULTS

The mean baseline age was 57 years at the first visit, 43% of participants were male and 57% were white. Among 3693 protein analytes that passed quality control, half (n = 1846) had CVs < 5.0%, Spearman correlations > 0.89, and ICCs > 0.96 among the split samples. Over the short term, only 1 analyte had a statistically significant difference between the 2 time points, whereas, over approximately 20 years, 866 analytes (23.4%) had statistically significant differences (P < 1.4 × 10^-5, 681 increased, 185 decreased). PC1 had high correlations with age (-0.73) and eGFR (0.60). PC2 had moderate correlation with male sex (0.18) and white race (0.31).

CONCLUSIONS

Multiplexed modified aptamer technology can assay thousands of proteins with excellent precision. Our results support the potential for large-scale studies of the plasma proteome over the lifespan.

The evolution of methods for urinary steroid metabolomics in clinical investigations particularly in childhood

The metabolites of cortisol, and the intermediates in the pathways from cholesterol to cortisol and the adrenal sex steroids can be analysed in a single separation of steroids by gas chromatography (GC) coupled to MS to give a urinary steroid profile (USP). Steroids individually and in profile are now commonly measured in plasma by liquid chromatography (LC) coupled with MS/MS. The steroid conjugates in urine can be determined after hydrolysis and derivative formation and for the first time without hydrolysis using GC-MS, GC-MS/MS and liquid chromatography with mass spectrometry (LC-MS/MS). The evolution of the technology, practicalities and clinical applications are examined in this review. The patterns and quantities of steroids changes through childhood. Information can be obtained on production rates, from which children with steroid excess and deficiency states can be recognised when presenting with obesity, adrenarche, adrenal suppression, hypertension, adrenal tumours, intersex condition and early puberty, as examples. Genetic defects in steroid production and action can be detected by abnormalities from the GC-MS of steroids in urine. New mechanisms of steroid synthesis and metabolism have been recognised through steroid profiling. GC with tandem mass spectrometry (GC-MS/MS) has been used for the tentative identification of unknown steroids in urine from newborn infants with congenital adrenal hyperplasia. Suggestions are made as to areas for future research and for future applications of steroid profiling. As routine hospital laboratories become more familiar with the problems of chromatographic and MS analysis they can consider steroid profiling in their test repertoire although with LC-MS/MS of urinary steroids this is unlikely to become a routine test because of the availability, cost and purity of the internal standards and the complexity of data interpretation. Steroid profiling with quantitative analysis by mass spectrometry (MS) after chromatography now provides the most versatile of tests of adrenal function in childhood.

Establishing a Twin Register: An Invaluable Resource for (Behavior) Genetic, Epidemiological, Biomarker, and ‘Omics’ Studies

Twin registers are wonderful research resources for research applications in medical and behavioral genetics, epidemiology, psychology, molecular genetics, and other areas of research. New registers continue to be launched all over the world as researchers from different disciplines recognize the potential to boost and widen their research agenda. In this article, we discuss multiple aspects that need to be taken into account when initiating a register, from its preliminary sketch to its actual development. This encompasses aspects related to the strategic planning and key elements of research designs, promotion and management of a twin register, including recruitment and retaining of twins and family members of twins, phenotyping, database organization, and collaborations between registers. We also present information on questions unique to twin registers and twin-biobanks, such as the assessment of zygosity by SNP arrays, the design of (biomarker) studies involving related participants, and the analyses of clustered data. Altogether, we provide a number of basic guidelines and recommendations for reflection when planning a twin register.

Stability of 15 Estrogens and Estrogen Metabolites in Urine Samples under Processing and Storage Conditions Typically Used in Epidemiologic Studies

Background

In preparation for large-scale epidemiologic studies of the role of estrogen metabolism in the etiology of breast and other cancers, we examined the stability of estrogens and estrogen metabolites (EM) in urine during processing and storage protocols.

Methods

Fifteen EM were measured using liquid chromatography–tandem mass spectrometry (LC-MS/MS) in first morning urines from 3 premenopausal women. Linear regression was used to model log EM concentrations for each woman, with and without adding ascorbic acid (0.1% w/v), during storage at 4°C (7–8 time points, up to 48 hours), during long-term storage at –80°C (10 time points, up to 1 year), and by freeze-thaw cycles (up to 3).

Results

Without ascorbic acid, concentrations (pmol/mL) of nearly all EM changed <1% per 24 hours of storage at 4°C, and <1% during storage at –80°C for 1 year; similarly, thawing and refreezing samples 3 times was not consistently associated with losses for any EM. Ascorbic acid had no clear beneficial effect on EM stability in these experiments.

Conclusions

Given the large inter-individual variability in urinary EM concentrations, changes of the magnitude observed here are unlikely to cause substantial misclassification. Furthermore, processing and storage conditions studied here are adequate for use in epidemiologic studies.

Maternal Smoking and Newborn Cytokine and Immunoglobulin Levels

INTRODUCTION

Prenatal smoking exposure may lead to permanent changes in neonatal inflammation and immune response that have lifelong implications, including increased risks for atopy and respiratory disorders.

METHODS

The effect of maternal smoking on neonatal biomarkers of inflammation and immune response was assessed among 3459 singletons and twins in the Upstate KIDS Study. The following inflammatory biomarkers were measured using newborn dried blood spots (DBSs): interleukin (IL)-1α, IL-1 receptor antagonist, IL-6, IL-8, C-reactive protein, and tumor necrosis factor alpha. Immunoglobulins (IgE, IgA, IgM, and IgG subclasses) were also assessed. We used generalized estimating equations to calculate mean differences (β) in biomarker levels by timing of pregnancy smoking, cigarette load, and secondhand smoke exposure after adjusting for sociodemographic and lifestyle factors including maternal body mass index.

RESULTS

Of the 344 (12%) women reporting smoking during pregnancy, about 40% continued throughout pregnancy and 13% reported smoking more than 1 pack per day. After covariate adjustment and Bonferroni correction for multiple comparisons, maternal smoking throughout pregnancy remained significantly associated with increased levels of IL-8 (β = 0.20, 95% confidence interval: 0.07, 0.32; p < .003). No significant associations were found with cigarette load or secondhand smoke exposure. Higher IgG3 levels were also associated with maternal smoking throughout pregnancy, although the association became nominally significant after adjustment for covariates (β = 0.09; 95% confidence interval: 0.0007, 0.17; p < .05).

CONCLUSIONS

Maternal smoking throughout pregnancy was independently associated with increased IL-8 levels in newborns. Importantly, neonates of women who stopped smoking anytime in pregnancy did not have increased IL-8 levels.

IMPLICATIONS

This study evaluated a range of inflammatory biomarkers and immunoglobulins in association with maternal smoking and timing/duration of smoking along with secondhand smoke exposure. By using DBSs, we present data from a large cohort of children born in Upstate New York. Our findings suggest that early differences in immunoregulation of neonates exposed to maternal smoking for full duration in utero may already be detected at birth.

Multiplex assay reliability and long-term intra-individual variation of serologic inflammatory biomarkers

BACKGROUND

Circulating cytokines, chemokines, and soluble cytokine receptors can serve as biomarkers of inflammation and immune dysregulation. Good reliability of multiplex platforms, which allow for simultaneous, comprehensive biomarker assessment, is critical for their utility in epidemiologic studies. We examined the reliability of the Meso-Scale Discovery (MSD) platform to simultaneously quantitate 15 cytokines and chemokines and the Luminex platform (R&D Systems) to quantitate 5 soluble receptors and 2 chemokines and cytokines and evaluated long-term within-person correlation of these biomarkers.

METHODS

The detectability and reliability of these assay systems were assessed using the same external controls across plates and archived sera from 250 HIV^- men in the Multicenter AIDS Cohort Study. Using up to four visits per person from 1984 to 2009, age-adjusted intraclass correlation coefficients (ICC) of biomarkers with >80% detectability (CCL11, CXCL8, CXCL10, CCL2, CCL4, CCL13, CCL17, CXCL13, IL-10, IL-12p70, IL-6, TNF-α, BAFF, sCD14, sCD27, sgp130, sIL-2Rα, and sTNF-R2) were obtained using linear mixed models.

RESULTS

Most biomarkers were detectable in 80% of control samples; IFN-γ, GM-CSF, and IL-2 were undetectable in >20% of samples. Among the HIV-uninfected men, most biomarkers showed fair to strong within-person correlation (ICC>0.40) up to 15years. The ICC for CXCL8 was good in the short term but decreased with increasing time between visits, becoming lower (ICC<0.40) after 8years.

CONCLUSIONS

These multiplexed assays showed acceptable reliability for use in epidemiologic research, despite some technical variability and limitations in cytokine quantitation. Most biomarkers displayed moderate-to-excellent intra-individual variability over the long term, suggesting their utility in prospective studies investigating etiologic associations with diverse chronic conditions.

Metabolic profiling of cholesterol and sex steroid hormones to monitor urological diseases

Cholesterol and sex steroid hormones including androgens and estrogens play a critical role in the development and progression of urological diseases such as prostate cancer. This disease remains the most commonly diagnosed malignant tumor in men and is the leading cause of death from different cancers. Attempts to understand the role of cholesterol and steroid metabolism in urological diseases have been ongoing for many years, but despite this, our mechanistic and translational understanding remains elusive. In order to further evaluate the problem, we have taken an interest in metabolomics; a discipline dedicated to the systematic study of biologically active metabolites in cells, tissues, hair and biofluids. Recently, we provided evidence that a quantitative measurement of cholesterol and sex steroid metabolites can be successfully achieved using hair of human and mouse models. The overall goal of this short review article is to introduce current metabolomic technologies for the quantitative biomarker assay development and also to provide new insight into understanding the underlying mechanisms that trigger the pathological condition. Furthermore, this review will place a particular emphasis on how to prepare biospecimens (e.g., hair fiber), quantify molecular profiles and assess their clinical significance in various urological diseases.

Use of urine biomarker-derived clusters to predict the risk of chronic kidney disease and all-cause mortality in HIV-infected women

BACKGROUND

Although individual urine biomarkers are associated with chronic kidney disease (CKD) incidence and all-cause mortality in the setting of HIV infection, their combined utility for prediction remains unknown.

METHODS

We measured eight urine biomarkers shown previously to be associated with incident CKD and mortality risk among 902 HIV-infected women in the Women's Interagency HIV Study: N-acetyl-β-d-glucosaminidase (NAG), kidney injury molecule-1 (KIM-1), alpha-1 microglobulin (α1m), interleukin 18, neutrophil gelatinase-associated lipocalin, albumin-to-creatinine ratio, liver fatty acid-binding protein and α-1-acid-glycoprotein. A group-based cluster method classified participants into three distinct clusters using the three most distinguishing biomarkers (NAG, KIM-1 and α1m), independent of the study outcomes. We then evaluated associations of each cluster with incident CKD (estimated glomerular filtration rate <60 mL/min/1.73 m(2) by cystatin C) and all-cause mortality, adjusting for traditional and HIV-related risk factors.

RESULTS

Over 8 years of follow-up, 177 CKD events and 128 deaths occurred. The first set of clusters partitioned women into three groups, containing 301 (Cluster 1), 470 (Cluster 2) and 131 (Cluster 3) participants. The rate of CKD incidence was 13, 21 and 50% across the three clusters; mortality rates were 7.3, 13 and 34%. After multivariable adjustment, Cluster 3 remained associated with a nearly 3-fold increased risk of both CKD and mortality, relative to Cluster 1 (both P < 0.001). The addition of the multi-biomarker cluster to the multivariable model improved discrimination for CKD (c-statistic = 0.72-0.76, P = 0.0029), but only modestly for mortality (c = 0.79-0.80, P = 0.099). Clusters derived with all eight markers were no better for discrimination than the three-biomarker clusters.

CONCLUSIONS

For predicting incident CKD in HIV-infected women, clusters developed from three urine-based kidney disease biomarkers were as effective as an eight-marker panel in improving risk discrimination.

Serum cytokine levels in Kleine-Levin syndrome

OBJECTIVE

Kleine-Levin Syndrome (KLS) is a rare sleep disorder causing recurrent symptomatic episodes of severe hypersomnia, cognitive impairment, apathy, and derealization. These episodes are interspersed with long periods of normal sleep, cognition, and behavior. The pathogenesis of KLS is still unknown. The objective of this study was to determine serum cytokine levels in patients with KLS during and between episodes.

PATIENTS/METHODS

Fifty-two typical KLS patients were included in the study of whom 17 patients donated blood samples both during and between episodes. Blood samples were collected in USA, France, and Taiwan in a clinical setting. Processing of the samples was performed at the Stanford Center for Sleep Sciences and Medicine.

RESULTS

We did not observe any changes in serum cytokine levels during KLS episodes compared to between episodes. In a small cohort of asymptomatic KLS patients and age- and gender matched healthy controls (n = 8/group) whose blood samples were all collected and processed at the same day; asymptomatic KLS patients had significantly higher levels of serum sVCAM1 cytokine compared to healthy controls.

CONCLUSION

These data suggest that KLS episodes are not accompanied by an abnormal systemic immune reaction.

The use of biospecimens in population-based research: a review of the National Cancer Institute's Division of Cancer Control and Population Sciences grant portfolio

Over the past two decades, researchers have increasingly used human biospecimens to evaluate hypotheses related to disease risk, outcomes and treatment. We conducted an analysis of population-science cancer research grants funded by the National Cancer Institute (NCI) to gain a more comprehensive understanding of biospecimens and common derivatives involved in those studies and identify opportunities for advancing the field. Data available for 1,018 extramural, peer-reviewed grants (active as of July 2012) supported by the Division of Cancer Control and Population Sciences (DCCPS), the NCI Division that supports cancer control and population-science extramural research grants, were analyzed. 455 of the grants were determined to involve biospecimens or derivatives. The most common specimen types included were whole blood (51% of grants), serum or plasma (40%), tissue (39%), and the biospecimen derivative, DNA (66%). While use of biospecimens in molecular epidemiology has become common, biospecimens for behavioral and social research is emerging, as observed in our analysis. Additionally, we found the majority of grants were using already existing biospecimens (63%). Grants that involved use of existing biospecimens resulted in lower costs (studies that used existing serum/plasma biospecimens were 4.2 times less expensive) and more publications per year (1.4 times) than grants collecting new biospecimens. This analysis serves as a first step at understanding the types of biospecimen collections supported by NCI DCCPS. There is room to encourage increased use of archived biospecimens and new collections of rarer specimen and cancer types, as well as for behavioral and social research. To facilitate these efforts, we are working to better catalogue our funded resources and make that data available to the extramural community.

The influence of sample collection methodology and sample preprocessing on the blood metabolic profile

Aim: Blood serum and plasma have intrinsic differences in their composition and the preprocessing, such as clotting temperature in serum, and storage at room temperature may have further effect on metabolite concentrations. Methods: The influence of sampling preprocessing on the metabolic profiles in serum and different types of plasma was investigated using liquid chromatography and comprehensive 2D gas chromatography coupled to a mass spectrometer. Results: The profiles of polar metabolites were significantly dependent on the type of the sample, while lipid profiles were similar in serum and different types of plasma. Extended storage of plasma at room temperature resulted in degradation of lipids already after 1 day. Serum clotting at room temperature generally resulted in higher metabolite concentration compared with serum clotting on ice.

The metabolomics of necrotising enterocolitis in preterm babies: an exploratory study

OBJECTIVE

No single diagnostic investigation is currently available for necrotising enterocolitis (NEC). We implemented a novel, untargeted, exploratory study to determine whether metabolomics can reveal early biomarker(s) of NEC. The effect of gestational age on the metabolome was also investigated.

METHODS

Two serum samples were obtained from 12 preterm babies (born <30 weeks gestation) and eight term controls: sample "A" at ≤1 week of age and sample "B" once fully fed. Samples were subjected to gas chromatography-mass spectrometry. Metabolomic data was analysed by principal component analysis (PCA), univariate and network analysis.

RESULTS

Sixteen metabolite features significantly differed when B samples were compared between preterm babies who subsequently developed NEC and preterm/term controls (p value <0.05). Of these seven metabolites were linked to up-regulation of IL-1β. Significant differences in 54 metabolite features (p value <0.05) were observed between preterm and term metabolomes. Of these, 12 metabolite features were linked to one network involved in carbohydrate/lipid metabolism (p = 1 × 10(-30)).

CONCLUSIONS

Metabolomic differences were observed in preterm babies at risk of NEC. However, sample sizes were insufficient to confidently identify a biomarker. Network modelling of preterm and term metabolomes suggest possible nutritional deficiency and altered pro-insulin action in preterm babies.

Planned variation in preanalytical conditions to evaluate biospecimen stability in the National Children's Study (NCS)

BACKGROUND

Preanalytical conditions encountered during collection, processing, and storage of biospecimens may influence laboratory results. The National Children's Study (NCS) is a planned prospective cohort study of 100,000 families to examine the influence of a wide variety of exposures on child health. In developing biospecimen collection, processing, and storage procedures for the NCS, we identified several analytes of different biochemical categories for which it was unclear to what extent deviations from NCS procedures could influence measurement results.

METHODS

A pilot study was performed to examine effects of preanalytic sample handling conditions (delays in centrifugation, freezing delays, delays in separation from cells, additive delay, and tube type) on concentrations of eight different analytes. A total of 2825 measurements were made to assess 15 unique combinations of analyte and handling conditions in blood collected from 151 women of childbearing age (≥ 20 individuals per handling condition).

RESULTS

The majority of analytes were stable under the conditions evaluated. However, levels of plasma interleukin-6 and serum insulin were decreased in response to sample centrifugation delays of up to 5.5 h post-collection (p<0.0001). In addition, delays in freezing centrifuged plasma samples (comparing 24, 48 and 72 h to immediate freezing) resulted in increased levels of adrenocorticotropic hormone (p=0.0014).

CONCLUSIONS

Determining stability of proposed analytes in response to preanalytical conditions and handling helps to ensure high-quality specimens for study now and in the future. The results inform development of procedures, plans for measurement of analytes, and interpretation of laboratory results.

Acculturative stress and inflammation among Chinese immigrant women

OBJECTIVE

Among Chinese immigrant populations, increasing duration of US residence is associated with elevated risk for various chronic diseases. Although life-style changes after migration have been extensively studied in immigrant populations, the psychosocial impact of acculturative stress on biological markers of health is less understood. Thus, the purpose of the present study is to examine associations between acculturative stress and inflammatory markers in a Chinese immigrant population.

METHODS

Study participants (n = 407 foreign-born Chinese American women) completed questionnaires assessing levels of stress, including acculturative stress and positive and negative life events in the previous year. Participant height and weight were measured using standard protocols, and blood samples were drawn for assessment of circulating serum levels of C-reactive protein (CRP) and soluble tumor necrosis factor receptor 2 (sTNFR2).

RESULTS

Higher levels of acculturative stress were significantly associated with higher levels of CRP (B = 0.07, 95% confidence interval = 0.01-0.13, p = .031) and sTNFR2 (B = 0.02, 95% confidence interval = 0.004-0.03, p = .012), adjusting for age and body mass index. The latter association was no longer statistically significant when overall acculturation (i.e., identification with American culture) was included in the model. Life events were not associated with CRP or sTNFR2.

CONCLUSIONS

This is one of the first studies to demonstrate that acculturative stress is associated with inflammatory markers in a Chinese immigrant population. Replication in other immigrant samples is needed to fully establish the biological correlates and clinical consequences of acculturative stress.

Sample collection in clinical proteomics--proteolytic activity profile of serum and plasma

PURPOSE

Proteolytic enzymes are promising diagnostic targets since they play key roles in diverse physiological processes and have been implicated in numerous human diseases. Human blood is a relatively noninvasive source for disease-specific protease biomarker detection and subsequent translation into diagnostic tests. However, the choice of serum or plasma, and more specifically, which anticoagulant to choose in plasma preparation, is important to address in the sample preparation phase of biomarker discovery.

EXPERIMENTAL DESIGN

We have previously utilized a combinatorial library of internally quenched fluorogenic probes to successfully map the global proteolytic profiles of various biological fluids. In this study, we utilized the platform to ascertain the impact of three commonly used anticoagulants (EDTA, heparin, and citrate) on the proteolytic activity profile of plasma and serum collected from a healthy Caucasian male.

RESULTS

Serum and plasma citrate were observed to be most proteolytically active, followed by plasma heparin and then plasma EDTA. Detailed analysis of the amino acid distribution of motifs cleaved and not cleaved by the samples offered significant insights in to active proteolytic components within them.

CONCLUSION AND CLINICAL RELEVANCE

Broad quantitative comparison of proteolytic profiles of these samples revealed several novel insights related to the differential substrate recognition of proteases present in these biological fluids.

Reproducibility of estradiol and testosterone levels in postmenopausal women over 5 years: results from the breakthrough generations study

Prospective cohort studies examining sex hormones in relation to cancer risk have generally collected blood samples at 1 time point, with an assumption that hormone levels measured in these samples will be reliable markers of true levels at other times. In postmenopausal women, body fat is a major source of estradiol; therefore, changes in adiposity may affect the correlation of single measurements to more relevant long-term averages. To estimate the intraclass correlation coefficient (ICC) for estradiol and testosterone, we collected repeat blood samples from 119 postmenopausal women (average age = 59.4 (standard deviation, 4.7) years) from the United Kingdom during 2004-2005 and again during 2010-2011. The ICCs (adjusted for assay variation) were 0.73 (95% confidence interval: 0.63, 0.82) for total estradiol and 0.59 (95% confidence interval: 0.47, 0.72) for total testosterone. The ICCs were 3%-5% larger after adjustment for change in body mass index (weight (kg)/height (m)(2)) or leptin, which are 2 markers of change in adiposity. There was no increase in ICCs after adjustment for change in age, alcohol consumption, smoking, exercise, time between waking and blood collection, or season. The results suggest that other factors account for within-woman variation in these sex hormones.

Effect of Multivitamin-Mineral versus Multivitamin Supplementation on Maternal, Newborns' Biochemical Indicators and Birth Size: A Double-Blind Randomized Clinical Trial

OBJECTIVE

Micronutrient deficiency during pregnancy is associated with several complications. This study was designed to determine the effects of received multivitamin-mineral vs. multivitamin supplements on maternal, newborns' biochemical indicators, and birth size.

METHODS

This double-blind randomized-controlled clinical trial was conducted among 48 Iranian pregnant women, primigravida, aged 18-35 years old in their second and third trimester from December 2011 to September 2012. Subjects were randomly assigned to receive either the multivitamin-mineral (n=24) or multivitamin supplements (n=24) for 20 weeks. Fasting blood samples were taken at baseline and after a 20-week intervention of pregnant women as well as umbilical cord blood of the babies immediately after delivery to measure serum calcium, vitamin D, iron, magnesium, zinc and biomarkers of oxidative stress including plasma total antioxidant capacity and total glutathione.

RESULTS

Multivitamin-mineral compared to multivitamin supplementation resulted in a significant increase in maternal serum calcium (0.5 vs. -0.1 mg/dL, p=0.04) and magnesium levels (0.1 vs. -0.2 mg/dL, p<0.001). Furthermore, mean plasma total glutathione levels (1791 ± 566 vs. 1434 ± 622 µmol/l, p=0.04) of the newborns whose mothers received multivitamin-mineral were higher than those whose mothers received multivitamin supplements.

CONCLUSIONS

Overall, multivitamin-mineral compared to multivitamin supplementation for 20 weeks during pregnancy resulted in a significant increase in maternal serum calcium and magnesium levels as well as a significant elevation of newborn plasma total glutathione levels.

Cytokines as biomarkers in rheumatoid arthritis

RA is a complex disease that develops as a series of events often referred to as disease continuum. RA would benefit from novel biomarker development for diagnosis where new biomarkers are still needed (even if progresses have been made with the inclusion of ACPA into the ACR/EULAR 2010 diagnostic criteria) and for prognostic notably in at risk of evolution patients with autoantibody-positive arthralgia. Risk biomarkers for rapid evolution or cardiovascular complications are also highly desirable. Monitoring biomarkers would be useful in predicting relapse. Finally, predictive biomarkers for therapy outcome would allow tailoring therapy to the individual. Increasing numbers of cytokines have been involved in RA pathology. Many have the potential as biomarkers in RA especially as their clinical utility is already established in other diseases and could be easily transferable to rheumatology. We will review the current knowledge's relation to cytokine used as biomarker in RA. However, given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may provide sufficient discrimination; therefore multiple biomarker signatures may represent more realistic approach for the future of personalised medicine in RA.

Recent technical strategies to identify diagnostic biomarkers for ovarian cancer

Ovarian cancer is the fifth leading cause of cancer deaths among North American women. Regrettably, there is currently no reliable circulating biomarker that can detect ovarian cancer in its early stages. The CA125 biomarker is very useful for treatment response monitoring, but its sensitivity is very low for early detection. Thus, there is an urgent need for the identification of new circulating biomarkers/panel of biomarkers that could be used to diagnose ovarian cancer before it becomes clinically detectable and advanced. Unfortunately, the strategies used in the past years to identify such biomarkers have not led to any outstanding candidate. This review summarizes the different approaches used in the last decade and suggests which strategies should be adopted in the near future in order to lead to the successful identification of new ovarian cancer diagnostic biomarkers.

Short-Term Stability of Biomarkers of Oxidative Stress and Antioxidant Status in Human Serum

The oxidation and antioxidant status of serum are often determined in serum samples which have been frozen for some time. The oxidative stress process is prone to fast alterations in the sample because of the possible instability of the reactants. Here one oxidation assay (ROM) and three antioxidant assays (FRAP, TAS, and BAP) have been tested on their performance and stability at short-time storage. The most commonly used temperatures for storage and handling of serum samples (+4 and +20°C) were selected. In three short-term studies in which the storage time varied between 3 and 48 hrs the performance of these assays were tested on human serum samples. The general conclusion is that most assays performed well and gave stable results during 2 days of storage of the samples at both temperatures. Only the FRAP and TAS assays showed a small deviation at some storage conditions. In conclusion, handling of serum samples at +4 and +20°C during short-time periods did not affect the quality and performance of the oxidation and antioxidant assays during day-to-day analyses.

Elevated soluble triggering receptor expressed on myeloid cells (sTREM)-1 levels in maternal serum during term and preterm labor

Background

Infection and inflammation are important mechanisms leading to preterm birth. Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) belongs to a family of cell surface receptors that seems to play an important role in fine-tuning the immune response. It has been demonstrated that sTREM-1 is involved in bacterial infection as well as in non-infectious inflammatory conditions. Few studies have investigated serum sTREM-1 expression during preterm labor. Therefore, the purpose of this study was to assess sTREM-1 concentrations in maternal serum during term and preterm labor.

Methods

This case control study included 176 singleton pregnancies in the following groups: patients in (1) preterm labor, delivered before 34 weeks (PTB) (n = 52); (2) GA matched controls, not in labor, matched for gestational age (GA) with the PTB group (n = 52); (3) at term in labor (n = 40) and (4) at term not in labor (n = 32). sTREM-1 concentrations were determined by enzyme-linked immunoassay.

Results

sTREM-1 was detected in all serum samples. Median sTREM-1 concentrations were significantly higher in women with PTB vs. GA matched controls (367 pg/ml, interquartile range (IQR) 304–483 vs. 273 pg/ml, IQR 208–334; P<0.001) and in women at term in labor vs. at term not in labor (300 pg/ml, IQR 239–353 vs. 228 pg/ml, IQR 174–285; P<0.001). Women with PTB had significantly higher levels of sTREM-1 compared to women at term in labor (P = 0.004). Multiple regression analysis, with groups recoded as three key covariates (labor, preterm and rupture of the membranes), showed significantly higher sTREM-1 concentrations for labor (+30%, P<0.001) and preterm (+15%, P = 0.005) after adjusting for educational level, history of PTB and sample age.

Conclusions

sTREM-1 concentrations in maternal serum were elevated during spontaneous term and preterm labor and sTREM-1 levels were significantly higher in preterm labor.

Metabolomics in epidemiology: sources of variability in metabolite measurements and implications

BACKGROUND

Metabolite levels within an individual vary over time. This within-individual variability, coupled with technical variability, reduces the power for epidemiologic studies to detect associations with disease. Here, the authors assess the variability of a large subset of metabolites and evaluate the implications for epidemiologic studies.

METHODS

Using liquid chromatography/mass spectrometry (LC/MS) and gas chromatography-mass spectroscopy (GC/MS) platforms, 385 metabolites were measured in 60 women at baseline and year-one of the Shanghai Physical Activity Study, and observed patterns were confirmed in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening study.

RESULTS

Although the authors found high technical reliability (median intraclass correlation = 0.8), reliability over time within an individual was low. Taken together, variability in the assay and variability within the individual accounted for the majority of variability for 64% of metabolites. Given this, a metabolite would need, on average, a relative risk of 3 (comparing upper and lower quartiles of "usual" levels) or 2 (comparing quartiles of observed levels) to be detected in 38%, 74%, and 97% of studies including 500, 1,000, and 5,000 individuals. Age, gender, and fasting status factors, which are often of less interest in epidemiologic studies, were associated with 30%, 67%, and 34% of metabolites, respectively, but the associations were weak and explained only a small proportion of the total metabolite variability.

CONCLUSION

Metabolomics will require large, but feasible, sample sizes to detect the moderate effect sizes typical for epidemiologic studies.

IMPACT

We offer guidelines for determining the sample sizes needed to conduct metabolomic studies in epidemiology.

Metabolomics in neonatology: fact or fiction?

The newest 'omics' science is metabolomics, the latest offspring of genomics, considered the most innovative of the 'omics' sciences. Metabolomics, also called the 'new clinical biochemistry', is an approach based on the systematic study of the complete set of metabolites in a biological sample. The metabolome is considered the most predictive phenotype and is capable of considering epigenetic differences. It is so close to the phenotype that it can be considered the phenotype itself. In the last three years about 5000 papers have been listed in PubMed on this topic, but few data are available in the newborn. The aim of this review, after a description of background and technical procedures, is to analyse the clinical applications of metabolomics in neonatology, covering the following points: gestational age, postnatal age, type of delivery, zygosity, perinatal asphyxia, intrauterine growth restriction, prenatal inflammation and brain injury, respiratory, cardiovascular renal, metabolic diseases; sepsis, necrotizing enterocolitis and antibiotic treatment; nutritional studies on maternal milk and formula, pharma-metabolomics, long-term diseases. Pros and cons of metabolomics are also discussed. All this comes about with the non-invasive collection of a few drops of urine (exceptionally important for the neonate, especially those of low birth weight). Only time and large-scale studies to validate initial results will place metabolomics within neonatology. In any case, it is important for perinatologists to learn and understand this new technology to offer their patients the utmost in diagnostic and therapeutic opportunities.

Novel infrastructure for sepsis biomarker research in critically ill neonates and children

INTRODUCTION

Sepsis biomarker research requires an infrastructure to identify septic patients efficiently and to collect and store specimens properly. We developed a novel infrastructure to study biomarkers of sepsis in children.

METHODS

Patients in pediatric and neonatal intensive care units were enrolled prospectively; enrollment information was stored in a secure, remotely accessible database. Researchers were notified of electronic medical record (EMR) orders for blood cultures (a surrogate for a diagnostic evaluation of suspected sepsis) by a page triggered by the order. Staff confirmed patient enrollment and remotely submitted an EMR order for collection of study specimens simultaneous with the blood culture. Specimens were processed and stored by a mobile clinical research unit.

RESULTS

Over 2 years, 2029 patients were admitted; 138 were enrolled. Staff received pages for 95% of blood cultures collected from enrolled patients. The median time between the blood culture order and collection was 34 minutes (range 9-241). Study specimens were collected simultaneously with 41 blood cultures. The median times between specimen collection and storage for flow cytometry and cytokine analysis were 33 minutes (range 0-82) and 52 minutes (range 28-98), respectively.

CONCLUSION

This novel infrastructure facilitated prompt, proper collection and storage of specimens for sepsis biomarker analysis.