Advancing Global Health Surveillance of Mycotoxin Exposures using Minimally Invasive Sampling Techniques: A State-of-the-Science Review.

Mycotoxins are a heterogeneous group of toxins produced by fungi that can grow in staple crops (e.g., maize, cereals), resulting in health risks due to widespread exposure from human consumption and inhalation. Dried blood spot (DBS), dried serum spot (DSS), and volumetric tip microsampling (VTS) assays were developed and validated for several important mycotoxins. This review summarizes studies that have developed these assays to monitor mycotoxin exposures in human biological samples and highlights future directions to facilitate minimally invasive sampling techniques as global public health tools. A systematic search of PubMed (MEDLINE), Embase (Elsevier), and CINAHL (EBSCO) was conducted. Key assay performance metrics were extracted to provide a critical review of the available methods. This search identified 11 published reports related to measuring mycotoxins (ochratoxins, aflatoxins, and fumonisins) using DBS/DSS and VTS assays. Multimycotoxin assays adapted for DBS/DSS and VTS have undergone sufficient laboratory validation for applications in large-scale population health and human biomonitoring studies. Future work should expand the number of mycotoxins that can be measured in multimycotoxin assays, continue to improve multimycotoxin assay sensitivities of several biomarkers with low detection rates, and validate multimycotoxin assays across diverse populations with varying exposure levels. Validated low-cost and ultrasensitive minimally invasive sampling methods should be deployed in human biomonitoring and public health surveillance studies to guide policy interventions to reduce inequities in global mycotoxin exposures.

A state-of-the-science review and guide for measuring environmental exposure biomarkers in dried blood spots.

BACKGROUND: Dried blood spot (DBS) sampling is a simple, cost-effective, and minimally invasive alternative to venipuncture for measuring exposure biomarkers in public health and epidemiological research. DBS sampling provides advantages in field-based studies conducted in low-resource settings and in studies involving infants and children. In addition, DBS samples are routinely collected from newborns after birth (i.e., newborn dried blood spots, NDBS), with many states in the United States permitting access to archived NDBS samples for research purposes. OBJECTIVES: We review the state of the science for analyzing exposure biomarkers in DBS samples, both archived and newly collected, and provide guidance on sample collection, storage, and blood volume requirements associated with individual DBS assays. We discuss recent progress regarding analytical methods, analytical sensitivity, and specificity, sample volume requirements, contamination considerations, estimating extracted blood volumes, assessing stability and analyte recovery, and hematocrit effects. METHODS: A systematic search of PubMed (MEDLINE), Embase (Elsevier), and CINAHL (EBSCO) was conducted in March 2022. DBS method development and application studies were divided into three main chemical classes: environmental tobacco smoke, trace elements (including lead, mercury, cadmium, and arsenic), and industrial chemicals (including endocrine-disrupting chemicals and persistent organic pollutants). DBS method development and validation studies were scored on key quality-control and performance parameters by two members of the review team. RESULTS: Our search identified 47 published reports related to measuring environmental exposure biomarkers in human DBS samples. A total of 28 reports (37 total studies) were on methods development and validation and 19 reports were primarily the application of previously developed DBS assays. High-performing DBS methods have been developed, validated, and applied for detecting environmental exposures to tobacco smoke, trace elements, and several important endocrine-disrupting chemicals and persistent organic pollutants. Additional work is needed for measuring cadmium, arsenic, inorganic mercury, and bisphenol A in DBS and NDBS samples. SIGNIFICANCE: We present an inventory and critical review of available assays for measuring environmental exposure biomarkers in DBS and NDBS samples to help facilitate this sampling medium as an emerging tool for public health (e.g., screening programs, temporal biomonitoring) and environmental epidemiology (e.g., field-based studies).

An Ovarian Steroid Metabolomic Pathway Analysis in Basal and Polycystic Ovary Syndrome (PCOS)-like Gonadotropin Conditions Reveals a Hyperandrogenic Phenotype Measured by Mass Spectrometry.

Prior work has demonstrated that murine ovarian explants and isolated ovarian follicles can recapitulate human-like 28-day cycles in vitro with normal patterns of estradiol and progesterone secretion in response to gonadotropin stimulation. The objective of this study was to manipulate the gonadotropin stimulation protocol to mimic polycystic ovary syndrome (PCOS) and assess the resulting changes in ovarian steroidogenesis. A secondary aim of the study was to develop a high-throughput, sensitive, and specific liquid chromatography with tandem mass spectrometry (LC-MS/MS) assay to measure seven steroid hormones (estrone, estradiol, progesterone, testosterone, androstenedione, dehydroepiandrosterone, and dihydrotestosterone) in conditioned culture media. Ovaries were harvested from 12-day-old CD-1 mice and cultured for 28 days, with ovulation induction on culture day 14. Media were supplemented human chorionic gonadotropin (hCG, a luteinizing hormone analog) and follicle stimulating hormone (FSH) at ratios of 1:0 (standard media), 1:1 (physiologic ratio), and 3:1 (PCOS-like ratio). Ovaries cultured in PCOS-like media displayed hyperandrogenism and impaired ovulation, two key features of a PCOS-like phenotype. Taken together, this first-of-its-kind presentation of hormone levels from single tissues creates a map of the enzymatic steps most acutely affected by gonadotropin dysregulation and may provide opportunities for assessing other potential insults in PCOS pathogenesis.

Human Serum Albumin Cys34 Adducts in Newborn Dried Blood Spots: Associations With Air Pollution Exposure During Pregnancy.

Background: Increasing evidence suggests that exposure to air pollution during pregnancy is associated with adverse pregnancy outcomes. However, biomarkers associated with air pollution exposure are widely lacking and often transient. In addition, ascertaining biospecimens during pregnacy to assess the prenatal environment remains largely infeasible. Objectives: To address these challenges, we investigated relationships between air pollution exposure during pregnancy and human serum albumin Cys34 (HSA-Cys34) adducts in newborn dried blood spots (DBS) samples, which captures an integration of perinatal exposures to small reactive molecules in circulating blood. Methods: Newborn DBS were obtained from a state archive for a cohort of 120 children born at one Kaiser Permanente Southern California (KPSC) hospitals in 2007. These children were selected to maximize the range of residential air pollution exposure during the entire pregnancy to PM2.5, PM10, NO2, O3, based on monthly estimates interpolated from regulatory monitoring sites. HSA-Cys34 adducts were selected based on previously reported relationships with air pollution exposure and oxidative stress. Results: Six adducts measured in newborn DBS samples were associated with air pollution exposures during pregnancy; these included direct oxidation products, adducts formed with small thiol compounds, and adducts formed with reactive aldehydes. Two general trends were identified: Exposure to air pollution late in pregnancy (i.e., in the last 30 days) was associated with increased oxidative stress, and exposure to air pollution earlier in pregnancy (i.e., not in the last 30 days) was associated with decreased oxidative stress around the time of birth. Discussion: Air pollution exposure occurring during pregnancy can alter biology and leave measurable impacts on the developing infant captured in the newborn DBS adductome, which represents a promising tool for investigating adverse birth outcomes in population-based studies.

Arsenic and birth outcomes in a predominately lower income Hispanic pregnancy cohort in Los Angeles.

Prenatal arsenic exposure has been associated with reduced fetal growth and increased risk for preterm birth, but most studies have been conducted in highly exposed populations outside the U.S. or in non-Hispanic populations in the rural U.S. The objectives of the current study were to: 1) examine the impact of early pregnancy exposure to arsenic on birth weight and gestational age at birth in a predominately lower income Hispanic pregnancy cohort in urban Los Angeles and 2) compare multiple biomarkers of arsenic exposure (blood, urine, and hair) assessed in early pregnancy (mean ± SD gestational age at biospecimen collection: 14 ± 4 weeks). Total arsenic (blood, hair) was measured by ICP-MS and speciated arsenic (urine) was measured by HPLC coupled to ICP-MS. Associations between log2-transformed arsenic measures and birth outcomes were evaluated using multivariable linear regression. A doubling in hair arsenic was associated with a 72.2 g (95% CI: -144.3, -0.1, P = 0.05) lower birth weight, after adjusting for potential confounders and gestational age at birth. A similar but non-significant trend was observed for blood arsenic, but not urine arsenic. The inverse association between hair arsenic and birth weight was more pronounced among infants whose mothers gained greater amounts of weight during pregnancy (Pinteraction = 0.02). The association between urinary monomethyl arsenic and GA at birth differed by pre-pregnancy BMI (Pinteraction<0.01). This study provides evidence that even at relatively low levels of exposure, arsenic exposure (measured in hair samples collected in early pregnancy) may adversely affect fetal growth in this understudied population, particularly in combination with greater gestational weight gain. Future studies with larger sample sizes are needed to confirm these findings and to further investigate some of the inconsistencies observed for the different arsenic biomarkers evaluated.

Opportunities for evaluating chemical exposures and child health in the United States: the Environmental influences on Child Health Outcomes (ECHO) Program.

The Environmental Influences on Child Health Outcomes (ECHO) Program will evaluate environmental factors affecting children's health (perinatal, neurodevelopmental, obesity, respiratory, and positive health outcomes) by pooling cohorts composed of >50,000 children in the largest US study of its kind. Our objective was to identify opportunities for studying chemicals and child health using existing or future ECHO chemical exposure data. We described chemical-related information collected by ECHO cohorts and reviewed ECHO-relevant literature on exposure routes, sources, and environmental and human monitoring. Fifty-six ECHO cohorts have existing or planned chemical biomonitoring data for mothers or children. Environmental phenols/parabens, phthalates, metals/metalloids, and tobacco biomarkers are each being measured by ≥15 cohorts, predominantly during pregnancy and childhood, indicating ample opportunities to study child health outcomes. Cohorts are collecting questionnaire data on multiple exposure sources and conducting environmental monitoring including air, dust, and water sample collection that could be used for exposure assessment studies. To supplement existing chemical data, we recommend biomonitoring of emerging chemicals, nontargeted analysis to identify novel chemicals, and expanded measurement of chemicals in alternative biological matrices and dust samples. ECHO's rich data and samples represent an unprecedented opportunity to accelerate environmental chemical research to improve the health of US children.

Metabolomics and adductomics of newborn bloodspots to retrospectively assess the early-life exposome.

PURPOSE OF REVIEW: Exposomics studies can measure health-relevant chemical exposures during a lifetime and estimate the 'internal' environment. However, sampling limitations make these features difficult to capture directly during the critical neonatal time period. RECENT FINDINGS: We review the use of newborn dried bloodspots (DBS) archived from newborn screening programs for exposomic analysis in epidemiological children's health studies. Emerging 'omics technologies such as adductomics and metabolomics have been adapted for DBS analysis, and these technologies can now provide valuable etiological information on the complex interplay between exposures, biological response, and population phenotypes. SUMMARY: Adductomics and metabolomics of DBS can provide robust measurements for retrospective epidemiological investigations. With extensive bioarchiving programs in the United States and other countries, DBS are poised to substantially aid epidemiological studies, particularly for rare and low-frequency childhood diseases and disorders.

Gestational diabetes mellitus, prenatal air pollution exposure, and autism spectrum disorder.

BACKGROUND: Ambient air pollution and maternal diabetes may affect common biological pathways underlying adverse neurodevelopmental effects. However, joint effects of maternal diabetes and air pollution on autism spectrum disorder (ASD) have not been studied. OBJECTIVE: We evaluated whether prenatal and early-life air pollution exposure interacts with maternal diabetes status to affect ASD risk. METHODS: This retrospective cohort study included 246,420 singleton children born in Kaiser Permanente Southern California hospitals in 1999-2009. Children were followed from birth until age 5, during which 2471 ASD cases were diagnosed. Ozone (O3), particulate matter < 2.5 µm (PM2.5) and <10 µm in aerodynamic diameter, and nitrogen dioxide measured at regulatory air monitoring stations were interpolated to estimate exposures during preconception and each pregnancy trimester, and first year of life at each child's birth address. Hazard ratios (HRs) for ASD were estimated adjusting for birth year, KPSC service areas, and relevant maternal and child characteristics. For each exposure window, interactions were tested between pollutants and a 4-category maternal diabetes variable (none, GDM ≥ 24 and <24 weeks' gestation, and pre-existing type 2 diabetes). For an exposure window with statistically significant global interaction between pollutant and diabetes (p < 0.05), pollutant-associated HRs were estimated separately for each category of maternal diabetes. RESULTS: There were associations of ASD with preconception, first and third trimesters, and first year of life PM2.5, but not with other pollutants. There were, however, interactions of maternal diabetes with first trimester and first year of life O3. Increased ASD risk was associated with first trimester O3 among mothers with GDM < 24 weeks' gestation [adjusted HR 1.50 per 15.7 ppb O3 (95% CI: 1.08-2.09)]. No O3 associations with ASD were observed in other categories of maternal diabetes. CONCLUSIONS: GDM onset early in pregnancy may increase children's susceptibility to prenatal O3-associated ASD risk. These novel findings merit further investigation.

Sex-specific associations of autism spectrum disorder with residential air pollution exposure in a large Southern California pregnancy cohort.

Autism spectrum disorder (ASD) affects more boys than girls. Recent animal studies found that early life exposure to ambient particles caused autism-like behaviors only in males. However, there has been little study of sex-specificity of effects on ASD in humans. We evaluated ASD risk associated with prenatal and first year of life exposures to particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) by child sex. This retrospective cohort study included 246,420 singleton children born in Kaiser Permanente Southern California (KPSC) hospitals between 1999 and 2009. The cohort was followed from birth through age five to identify 2471 ASD cases from the electronic medical record. Ambient PM2.5 and other regional air pollution measurements (PM less than 10 µm, ozone, nitrogen dioxide) from regulatory air monitoring stations were interpolated to estimate exposure during each trimester and first year of life at each geocoded birth address. Hazard ratios (HRs) were estimated using Cox regression models to adjust for birth year, KPSC medical center service areas, and relevant maternal and child characteristics. Adjusted HRs per 6.5 µg/m3 PM2.5 were elevated during entire pregnancy [1.17 (95% confidence interval (CI), 1.04-1.33)]; first trimester [1.10 (95% CI, 1.02-1.19)]; third trimester [1.08 (1.00-1.18)]; and first year of life [1.21 (95% CI, 1.05-1.40)]. Only the first trimester association remained robust to adjustment for other exposure windows, and was specific to boys only (HR = 1.18; 95% CI, 1.08-1.27); there was no association in girls (HR = 0.90; 95% CI, 0.76-1.07; interaction p-value 0.03). There were no statistically significant associations with other pollutants. PM2.5-associated ASD risk was stronger in boys, consistent with findings from recent animal studies. Further studies are needed to better understand these sexually dimorphic neurodevelopmental associations.

Associations of gestational diabetes mellitus with residential air pollution exposure in a large Southern California pregnancy cohort.

BACKGROUND: Studies of effects of air pollution on gestational diabetes mellitus (GDM) have not been consistent, and there has been little investigation of effects of exposure preceding pregnancy. In previous studies, the temporal relationship between exposure and GDM onset has been difficult to establish. METHODS: Data were obtained for 239,574 pregnancies between 1999 and 2009 in a population-based health care system with comprehensive electronic medical records. Concentrations of ambient nitrogen dioxide (NO2), particulate matter (PM) ≤2.5 µm in aerodynamic diameter (PM2.5) and ≤10 µm (PM10), and ozone (O3) during preconception and the first trimester of pregnancy at the residential birth address were estimated from regulatory air monitoring stations. Odds ratios (ORs) of GDM diagnosed in the second and third trimesters in association with pollutant exposure were estimated using generalized estimating equation models adjusted for birth year, medical center service areas, maternal age, race/ethnicity, education, census-tract household income, and parity. RESULTS: In single-pollutant models, preconception NO2 was associated with increased risk of GDM (OR = 1.10 per 10.4 ppb, 95% confidence interval [CI]: 1.07, 1.13). First trimester NO2 was weakly associated with GDM, and this was not statistically significant (OR = 1.02 per 10.4 ppb, 95% CI: 0.99, 1.05). Preconception NO2 associations were robust in multi-pollutant models adjusted for first trimester NO2 with another co-pollutant from both exposure windows. In single-pollutant models, preconception PM2.5 and PM10 associations were associated with increased risk of GDM (OR = 1.04 per 6.5 µg/m3, 95% CI: 1.01, 1.06; OR = 1.03 per 16.1 µg/m3, 95% CI: 1.00, 1.06, respectively), but these effect estimates were not robust to adjustment for other pollutants. In single-pollutant models, preconception and first trimester O3 were associated with reduced risk of GDM (OR = 0.94 per 15.7 ppb, 95% CI: 0.92, 0.95; OR = 0.95 per 15.7 ppb, 95% CI: 0.94, 0.97), associations that were robust to adjustment for co-pollutants. CONCLUSIONS: Maternal exposure to NO2 during the preconception trimester may increase risk of GDM.

Expression and Characterization of Human Fragile X Mental Retardation Protein Isoforms and Interacting Proteins in Human Cells.

Fragile X mental retardation protein is an mRNA-binding protein associated with phenotypic manifestations of fragile X syndrome, an X-linked disorder caused by mutation in the FMR1 gene that is the most common inherited cause of intellectual disability. Despite the well-studied genetic mechanism of the disease, the proteoforms of fragile X mental retardation protein have not been thoroughly characterized. Here, we report the expression and mass spectrometric characterization of human fragile X mental retardation protein. FMR1 cDNA clone was transfected into human HEK293 cells to express the full-length human fragile X mental retardation protein. Purified fragile X mental retardation protein was subjected to trypsin digestion and characterized by mass spectrometry. Results show 80.5% protein sequence coverage of fragile X mental retardation protein (Q06787, FMR1_HUMAN) including both the N- and C-terminal peptides, indicating successful expression of the full-length protein. Identified post-translational modifications include N-terminal acetylation, phosphorylation (Ser600), and methylation (Arg290, 471, and 474). In addition to the full-length fragile X mental retardation protein isoform (isoform 6), two endogenous fragile X mental retardation protein alternative splicing isoforms (isoforms 4 and 7), as well as fragile X mental retardation protein interacting proteins, were also identified in the co-purified samples, suggesting the interaction network of the human fragile X mental retardation protein. Quantification was performed at the peptide level, and this information provides important reference for the future development of a targeted assay for quantifying fragile X mental retardation protein in clinical samples. Collectively, this study provides the first comprehensive report of human fragile X mental retardation protein proteoforms and may help advance the mechanistic understanding of fragile X syndrome and related phenotypes associated with the FMR1 mutation.

Human biomarker interpretation: the importance of intra-class correlation coefficients (ICC) and their calculations based on mixed models, ANOVA, and variance estimates.

Human biomonitoring is the foundation of environmental toxicology, community public health evaluation, preclinical health effects assessments, pharmacological drug development and testing, and medical diagnostics. Within this framework, the intra-class correlation coefficient (ICC) serves as an important tool for gaining insight into human variability and responses and for developing risk-based assessments in the face of sparse or highly complex measurement data. The analytical procedures that provide data for clinical and public health efforts are continually evolving to expand our knowledge base of the many thousands of environmental and biomarker chemicals that define human systems biology. These chemicals range from the smallest molecules from energy metabolism (i.e., the metabolome), through larger molecules including enzymes, proteins, RNA, DNA, and adducts. In additiona, the human body contains exogenous environmental chemicals and contributions from the microbiome from gastrointestinal, pulmonary, urogenital, naso-pharyngeal, and skin sources. This complex mixture of biomarker chemicals from environmental, human, and microbiotic sources comprise the human exposome and generally accessed through sampling of blood, breath, and urine. One of the most difficult problems in biomarker assessment is assigning probative value to any given set of measurements as there are generally insufficient data to distinguish among sources of chemicals such as environmental, microbiotic, or human metabolism and also deciding which measurements are remarkable from those that are within normal human variability. The implementation of longitudinal (repeat) measurement strategies has provided new statistical approaches for interpreting such complexities, and use of descriptive statistics based upon intra-class correlation coefficients (ICC) has become a powerful tool in these efforts. This review has two parts; the first focuses on the history of repeat measures of human biomarkers starting with occupational toxicology of the early 1950s through modern applications in interpretation of the human exposome and metabolic adverse outcome pathways (AOPs). The second part reviews different methods for calculating the ICC and explores the strategies and applications in light of different data structures.

Cosmetics and Cancer: Adverse Event Reports Submitted to the Food and Drug Administration.

There have been numerous controversies surrounding cosmetic products and increased cancer risk. Such controversies include associations between parabens and breast cancer, hair dyes and hematologic malignancies, and talc powders and ovarian cancer. Despite the prominent media coverage and numerous scientific investigations, the majority of these associations currently lack conclusive evidence. In 2016, the US Food and Drug Administration (FDA) made publically available all adverse event reports in Center for Food Safety and Applied Nutrition's Adverse Event Reporting System (CAERS), which includes complaints related to cosmetic products. We mined CAERS for cancer-related reports attributed to cosmetics. Between 2004 and 2017, cancer-related reports caused by cosmetics represented 41% of all adverse events related to cosmetics. This yielded 4427 individual reports of cancer related to a cosmetic product. Of these reports, the FDA redacted the specific product names in 95% of cancer-related reports under the Freedom of Information Act exemptions, most likely due to ongoing legal proceedings. For redacted reports, ovarian cancer reports dominated (n = 3992, 90%), followed by mesothelioma (n = 92, 2%) and malignant neoplasm unspecified (n = 46, 1%). For nonredacted reports, or those reports whose product names were not withheld (n = 218), 70% were related to ovarian cancer attributed to talc powders, followed by skin cancer (11%) and breast cancer (5%) attributed to topical moisturizers. Currently, CAERS is of limited utility, with the available data having been subjected to significant reporter bias and a lack of supportive information such as demographic data, medical history, or concomitant product use. Although the system has promise for safeguarding public health, the future utility of the database requires broader reporting participation and more complete reporting, paired with parallel investments in regulatory science and improved molecular methods.

Estimating common parameters of lognormally distributed environmental and biomonitoring data: harmonizing disparate statistics from publications.

The progression of science is driven by the accumulation of knowledge and builds upon published work of others. Another important feature is to place current results into the context of previous observations. The published literature, however, often does not provide sufficient direct information for the reader to interpret the results beyond the scope of that particular article. Authors tend to provide only summary statistics in various forms, such as means and standard deviations, median and range, quartiles, 95% confidence intervals, and so on, rather than providing measurement data. Second, essentially all environmental and biomonitoring measurements have an underlying lognormal distribution, so certain published statistical characterizations may be inappropriate for comparisons. The aim of this study was to review and develop direct conversions of different descriptions of data into a standard format comprised of the geometric mean (GM) and the geometric standard deviation (GSD) and then demonstrate how, under the assumption of lognormal distribution, these parameters are used to answer questions of confidence intervals, exceedance levels, and statistical differences among distributions. A wide variety of real-world measurement data sets was reviewed, and it was demonstrated that these data sets are indeed of lognormal character, thus making them amenable to these methods. Potential errors incurred from making retrospective estimates from disparate summary statistics are described. In addition to providing tools to interpret "other people's data," this review should also be seen as a cautionary tale for publishing one's own data to make it as useful as possible for other researchers.

Environmental and occupational exposure to chemicals and telomere length in human studies.

Telomeres are complexes of tandem repeats of DNA (5'-TTAGGG-3') and protein that cap eukaryotic chromosomes and play a critical role in chromosome stability. Telomeres shorten with aging and this process can be accelerated by increased oxidative stress and episodes of inflammation. Evidence is rapidly growing that telomere length (TL) may be affected by environmental chemicals that have frequently been associated with chronic diseases. In this article, we review the published data on TL in relation to environmental and occupational exposure to several chemicals based on our own and others' studies. The environmental and occupational exposures associated with shorter TL include traffic-related air pollution (ie, particulate matter (PM), black carbon (BC), and benzene and toluene), polycyclic aromatic hydrocarbons (PAHs), N-nitrosamines, pesticides, lead, exposure in car mechanical workshops, and hazardous waste exposure. Arsenic, persistent organic pollutants (POPs) and short-term exposure to PM are associated with longer TL. We discuss the possible reasons for the differences in results, including time- and dose-related issues, study design, and possible mechanisms involved in telomere regulation. We also discuss the future directions and challenges for TL-related environmental and occupational health research, such as investigation of TL in subpopulations of blood leukocytes, and the study of genetic and epigenetic factors that may regulate telomere integrity using longitudinal designs.

Environmental and occupational exposure to chemicals and telomere length in human studies.

Telomeres are complexes of tandem repeats of DNA (5'-TTAGGG-3') and protein that cap eukaryotic chromosomes and play a critical role in chromosome stability. Telomeres shorten with aging and this process can be accelerated by increased oxidative stress and episodes of inflammation. Evidence is rapidly growing that telomere length (TL) may be affected by environmental chemicals that have frequently been associated with chronic diseases. In this article, we review the published data on TL in relation to environmental and occupational exposure to several chemicals based on our own and others' studies. The environmental and occupational exposures associated with shorter TL include traffic-related air pollution (ie, particulate matter (PM), black carbon (BC), and benzene and toluene), polycyclic aromatic hydrocarbons (PAHs), N-nitrosamines, pesticides, lead, exposure in car mechanical workshops, and hazardous waste exposure. Arsenic, persistent organic pollutants (POPs) and short-term exposure to PM are associated with longer TL. We discuss the possible reasons for the differences in results, including time- and dose-related issues, study design, and possible mechanisms involved in telomere regulation. We also discuss the future directions and challenges for TL-related environmental and occupational health research, such as investigation of TL in subpopulations of blood leukocytes, and the study of genetic and epigenetic factors that may regulate telomere integrity using longitudinal designs.

Quantification of arsenic, lead, mercury and cadmium in newborn dried blood spots.

Exposures to heavy metals during fetal and perinatal development are of particular concern. Yet, the health impacts of exposures to toxic metals during these early stages of human development are not well understood due to the paucity of in vivo human data. Dried blood spots (DBS), collected by public health departments to screen for inherited metabolic errors and other disorders, are routinely archived and can be used for exposure assessment. Here we report an improved method for quantifying arsenic, lead, mercury and cadmium in newborn DBS to facilitate epidemiologic research on the health effects of early exposures to toxic metals.

Quantification of anti-Müllerian hormone (AMH) in dried blood spots: validation of a minimally invasive method for assessing ovarian reserve.

BACKGROUND: Biological markers of ovarian reserve have the potential to advance research on fecundability, infertility and reproductive aging. Anti-Müllerian hormone (AMH) has emerged as a clinically useful measure of ovarian reserve, but the requirement for venous blood is an obstacle to application in non-clinical settings. This paper validates a new method for quantifying AMH in dried blood spot (DBS) samples--drops of whole blood collected on filter paper following a simple finger stick. METHODS: Matched serum and DBS samples were obtained from n=101 women of reproductive age, and AMH values were compared using regression analyses and scatter plots. The precision, reliability, linearity, recovery and lower detection limit of the DBS assay were evaluated, as well as the stability of AMH in DBS across a range of storage conditions. RESULTS: There was a strong agreement between AMH concentrations measured in DBS and serum samples across the entire assay range. Analysis of within-assay (percent coefficient of variation, 4.7-6.5%) and between-assay (3.5-7.2%) variability indicated a high level of assay precision and reliability, respectively. The minimum detectable dose of AMH was 0.065 ng/ml. Concentrations of AMH remained stable in DBS samples stored for 2 weeks at room temperature, and for 4 weeks when refrigerated. CONCLUSIONS: The DBS assay performs at a level that is comparable to serum-based methods, with the advantage of lower burdens and costs associated with blood collection that may be advantageous for research in clinical as well as non-clinical settings on the causes and consequences of variation in ovarian reserve.