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Epigenetic age acceleration is considered a measure of biological aging based on genome-wide patterns of DNA methylation. Although age acceleration has been associated with the incidence of diseases and death, less is known about how it is related to lifestyle behaviors. Among 2316 women, we evaluate associations between self-reported alcohol consumption and various metrics of epigenetic age acceleration. Recent average alcohol consumption was defined as the mean number of drinks consumed per week within the past year; lifetime average consumption was estimated as the mean number of drinks per year drinking. Whole-blood genome-wide DNA methylation was measured with HumanMethylation450 BeadChips and used to assess 4 epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) and their corresponding metrics of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Although alcohol consumption showed little association with most age acceleration metrics, both lifetime and recent average consumption measures were positively associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: β = 0.30 years, 95% confidence interval [CI]: 0.11, 0.48, p = .002; recent, per additional 5 drinks/week: β = 0.19 years, 95% CI: 0.01, 0.37, p = .04). In a mutually adjusted model, only average lifetime alcohol consumption remained associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: β = 0.27 years, 95% CI: 0.04, 0.50, p = .02; recent, per 5 additional drinks/week: β = 0.05 years, 95% CI: −0.16, 0.26, p = .64). Although alcohol use does not appear to be strongly associated with biological age measured by most epigenetic clocks, lifetime average consumption is associated with higher biological age assessed by the GrimAge epigenetic clock.

Background Age is one of the strongest predictors of cancer, chronic disease, and mortality, but biological responses to aging differ among people. Epigenetic DNA modifications have been used to estimate “biological age,” which may be a useful predictor of disease risk. We tested this hypothesis for breast cancer. Methods Using a case-cohort approach, we measured baseline blood DNA methylation of 2764 women enrolled in the Sister Study, 1566 of whom subsequently developed breast cancer after an average of 6 years. Using three previously established methylation-based “clocks” (Hannum, Horvath, and Levine), we defined biological age acceleration for each woman by comparing her estimated biological age with her chronological age. Hazard ratios and 95% confidence intervals for breast cancer risk were estimated using Cox regression models. All statistical tests were two-sided. Results Each of the three clocks showed that biological age acceleration was statistically significantly associated with increased risk of developing breast cancer (5-year age acceleration, Hannum’s clock: hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.00 to 1.21, P = .04; Horvath’s clock: HR = 1.08, 95% CI = 1.00 to 1.17, P = .04; Levine’s clock: HR = 1.15, 95% CI = 1.07 to 1.23, P Conclusions DNA methylation-based measures of biological age may be important predictors of breast cancer risk.

Anti-Müllerian hormone (AMH) is required for sexual differentiation in the fetus, and in adult females AMH is produced by growing ovarian follicles. Consequently, AMH levels are correlated with ovarian reserve, declining towards menopause when the oocyte pool is exhausted. A previous genome-wide association study identified three genetic variants in and around the AMH gene that explained 25% of variation in AMH levels in adolescent males but did not identify any genetic associations reaching genome-wide significance in adolescent females. To explore the role of genetic variation in determining AMH levels in women of late reproductive age, we carried out a genome-wide meta-analysis in 3,344 pre-menopausal women from five cohorts (median age 44–48 years at blood draw). A single genetic variant, rs16991615, previously associated with age at menopause, reached genome-wide significance at P=3.48×10−10, with a per allele difference in age-adjusted inverse normal AMH of 0.26 SD (95% CI [0.18,0.34]). We investigated whether genetic determinants of female reproductive lifespan were more generally associated with pre-menopausal AMH levels. Genetically-predicted age at menarche had no robust association but genetically-predicted age at menopause was associated with lower AMH levels by 0.18 SD (95% CI [0.14,0.21]) in age-adjusted inverse normal AMH per one-year earlier age at menopause. Our findings support the hypothesis that AMH is a valid measure of ovarian reserve in pre-menopausal women and suggest that the underlying biology of ovarian reserve results in a causal link between pre-menopausal AMH levels and menopause timing.

Prospective and retrospective studies of vitamin D levels and breast cancer have produced discrepant results. This may be due to variations in serum 25-hydroxyvitamin D (25(OH)D) concentrations over time, including systematic changes after breast cancer diagnosis. We measured total serum 25(OH)D levels in participants from the Sister Study, a US cohort study of sisters of breast cancer patients, who provided samples at baseline (2003–2009) and 4–10 years later (2013–2015). This included 827 women with an intervening breast cancer and 771 women without one. Although 25(OH)D levels were modestly correlated over time (R = 0.42), 25(OH)D concentrations increased in both groups, with larger increases among cases (averaging 31.6 ng/mL at baseline and 43.5 ng/mL at follow-up) than among controls (32.3 ng/mL at baseline, 40.4 ng/mL at follow-up). Consequently, the estimated association between 25(OH)D and breast cancer depended on whether baseline measurements (per 10-ng/mL increase, odds ratio = 0.87, 95% confidence interval: 0.78, 0.98) or measurements from the second blood draw (per 10-ng/mL increase, odds ratio = 1.17, 95% confidence interval: 1.08, 1.26) were used. Concentrations were related to regular use (≥4 times/week) of vitamin D supplements, which became more common over time; increases in regular use were greater in cases (from 56% to 84%) than in controls (from 56% to 77%). Our results do not explain previously observed differences between retrospective and prospective studies, but they do demonstrate how reverse causation and temporal trends in exposure can distort inference.

Motivation: The Illumina HumanMethylation450 BeadChip has been extensively utilized in epigenome-wide association studies. This array and its successor, the MethylationEPIC array, use two types of probes—Infinium I (type I) and Infinium II (type II)—in order to increase genome coverage but differences in probe chemistries result in different type I and II distributions of methylation values. Ignoring the difference in distributions between the two probe types may bias downstream analysis. Results: Here, we developed a novel method, called Regression on Correlated Probes (RCP), which uses the existing correlation between pairs of nearby type I and II probes to adjust the beta values of all type II probes. We evaluate the effect of this adjustment on reducing probe design type bias, reducing technical variation in duplicate samples, improving accuracy of measurements against known standards, and retention of biological signal. We find that RCP is statistically significantly better than unadjusted data or adjustment with alternative methods including SWAN and BMIQ. Availability: We incorporated the method into the R package ENmix , which is freely available from the Bioconductor website ( https://www.bioconductor.org/packages/release/bioc/html/ENmix.html ). Contact: niulg@ucmail.uc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Epigenetic marks are extensively altered in cancer but may also change in normal tissues with age, which is the primary risk factor for most cancers. We conducted an epigenome-wide study to identify age-related methylation sites and examine their relationship to cancer and other underlying epigenetic marks. We analyzed 1006 blood DNA samples of women aged 35-76 years from the Sister Study and found that 7694 (28%) of the 27 578 CpGs assayed were associated with age (false discovery rate, q < 0.05). Using independent data sets, we confirmed 749 'high-confidence' age-related CpG (arCpGs) sites in normal blood. Based on The Cancer Genome Atlas data, we show that these age-related changes are largely concordant in a broad variety of normal tissues and that a significantly higher (71-91%, P < 10(-74)) than expected proportion of increasingly methylated arCpGs (IM-arCpGs) were overmethylated in a wide variety of tumor types. IM-arCpGs sites occurred almost exclusively at CpG islands and were disproportionately marked with the repressive H3K27me3 histone modification (P < 1 × 10(-) (50)). Genes containing these IM-arCpG sites were highly enriched for developmental and signaling pathways (P < 10(-) (10)). Our findings suggest that as cells acquire methylation at age-related sites, they have a lower threshold for malignant transformation that may explain in part the increase in cancer incidence with age.

Breast cancer is the most common cancer in women and the leading cause of cancer mortality for women worldwide (1). According to estimates for 2011, there are an estimated 230480 incident cases and 40000 deaths from the disease each year in the United States (2). The Gail model, based on known risk factors including age and reproductive, medical, and family history, is the best breast cancer risk prediction method currently available for populations, but its predictive accuracy for individuals is only about 58.0% to 59.0% (3,4). Rare inherited mutations of the breast cancer susceptibility genes BRCA1 and BRCA2 are strongly associated with familial breast cancer, but together only account for 5% to 10% of breast cancers in the United States (5). Recent genome-wide association studies (GWASs) have identified common polymorphisms associated with breast cancer risk. A panel of 10 such SNPs have a predictive accuracy of 59.7% (4). Thus the known environmental and common genetic risk factors for breast cancer have limited use in predicting a woman’s risk of disease (4–6). Epigenetic modifications, including DNA methylation, are increasingly recognized as important determinants of gene transcriptional regulation that have both heritable and acquired characteristics (7). Aberrant DNA methylation patterns are among the earliest and most common events in carcinogenesis (8), and genome-wide methylation profiling has recently been extended to retrospectively collected blood samples in case–control studies of ovarian, bladder, and head and neck cancers (9–11). But unlike genotype, which remains constant, epigenetic modifications may differ from cell to cell, over time, and with exposure, making the results of case–control studies subject to a number of potential biases (12). In this study we used genomic arrays of 27578 CpGs and prospectively collected blood samples from women in the Sister Study cohort to compare women who subsequently developed breast cancer to those who remained cancer-free. We use these data to address two questions: Does the epigenetic profile differ between women who subsequently develop cancer vs those who do not? Within the case subject group, is there an effect of time to diagnosis—the interval between blood draw and clinical diagnosis of disease? In addition, we examined the predictive power of blood methylation compared with the Gail model and GWAS single nucleotide polymorphisms (SNPs).

Contains fulltext : 167299.pdf (Publisher’s version ) (Closed access) Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 x 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 x 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 x 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P

Smoking is a known risk factor for bladder cancer. The product of the GSTM1 gene, glutathione S-transferase M1 (GSTM1), is involved in the detoxification of polycyclic aromatic hydrocarbons found in tobacco smoke; a homozygous deletion of this gene in approximately 50% of Caucasians and Asians results in a lack of GSTM1 enzyme activity. Most studies examining the relation between bladder cancer and GSTM1 have reported an increased risk associated with a lack of GSTM1 activity. The authors performed meta- and pooled analyses of published and unpublished, case-control, genotype-based studies that examined this association (17 studies, 2,149 cases, 3,646 controls) and excluded studies conducted in populations with a high prevalence of exposure to known bladder cancer risk factors other than tobacco smoke. Using random effects models in the meta-analysis, the authors obtained a summary odds ratio of 1.44 (95% confidence interval (CI): 1.23, 1.68) for GSTM1 null status with all studies included. Results from studies with at least 100 cases and 100 controls produced a summary odds ratio of 1.42 (95% CI: 1.26, 1.60). Pooled analyses using original data sets from 10 studies (1,496 cases and 1,444 controls) and adjusting for age, sex, and race produced similar results. There was no evidence of multiplicative interaction between the GSTM1 null genotype and ever smoking in relation to bladder cancer, although there was a suggestion of additive interaction (additive interaction = 0.45, 95% CI: -0.03, 0.93). These results indicate that, among populations studied to date, GSTM1 null status is associated with a modest increase in the risk of bladder cancer.

Prostate cancer is the most common malignancy in males and is the second most common cause of cancer mortality in American men. Polymorphisms have been identified in two genes, the 17-hydroxylase cytochrome P450 gene (CYP17) and the steroid 5-reductase type II gene (SRD5A2) that are involved with androgen biosynthesis and metabolism. The CYP17 A2 allele contains a T-->C transition in the 5' promoter region that creates an additional Sp1-type (CCACC box) promoter site. The SRD5A2 valine to leucine (V89L) polymorphism has been correlated with lower dihydroxytestosterone levels. We tested genotypes in 108 prostate cases and 167 controls along with samples (n = 340) from several different ethnic groups. The CYP17 A2 allele (combined A1/A2 and A2/A2 genotypes) occurred at a higher frequency in Caucasian patients with prostate cancer (70%) than in Caucasian clinical control urology patients (57%), suggesting that the A2 allele may convey increased risk for prostate cancer [odds ratio (OR) = 1.7, 95% confidence interval (CI) = 1.0-3.0]. Blacks and Caucasians had a similar frequency of the A2 genotype (16 and 17%, respectively) while Taiwanese had the highest frequency (27%). The SRD5A2 leucine genotype was most frequent in Taiwanese (28%), intermediate in Caucasians (8.5%) and lowest in Blacks (2.5%). Genotypes having a SRD5A2 leucine allele were somewhat more common in prostate cancer cases (56%) than in controls (49%) (OR = 1.4, 95% CI = 0.8-2.2) but this difference was not significant. These results support the hypothesis that some allelic variants of genes involved in androgen biosynthesis and metabolism may be associated with prostate cancer risk.

A symposium of this title was presented at the 37 th Annual Meeting of the Society of Toxicology held in Seattle, Washington during March of 1998. The symposium focused on heritable variations in metabolism, DNA replication, and DNA repair that may predispose humans to environmental diseases. Human metabolic, replication, and repair enzymes function in protective roles. Metabolic enzymes are protective because they detoxify a stream of chemicals to which the body is exposed. Replication and repair enzymes are also protective; they function to maintain the integrity of the human genome. Polymorphisms in the genes that code for some of these enzymes are known to give rise to variations in their protective functions. For example, functional polymorphisms of the N-acetyltransferases, paraoxonases, and microsomal epoxide hydrolases vary in their capacity to metabolize environmental chemicals. Specific isoforms of the N-acetyltransferases and microsomal epoxide hydrolases are increasingly associated with incidences of cancer attributable to exposure to these chemicals. Thus, maintenance of cellular-growth homeostasis, normally and in the face of environmental challenge, is dependent on an inherited assortment of metabolic isoforms. Since replication and repair are also protective cellular functions, and since mutations in genes that code for these functions are associated with tumorigenesis, one can reasonably speculate that common functional polymorphisms of replication and repair enzymes may also impart susceptibility to environmental disease.

Despite the considerable efforts and funds devoted to cancer research over several decades, cancer still remains a mainly lethal disease. Cancer incidence and mortality have not declined at the same rate as other major causes of death, indicating that primary prevention remains a most valuable approach to decrease mortality. There is general agreement that environmental exposures are variously involved in the causation of the majority of cancer cases and that at least half of all cancers could be avoided by applying existing etiologic knowledge. There is disagreement, however, regarding the proportion of cancer risks attributable to specific etiological factors, including diet, occupation and pollution. Estimates of attributable risks are largely based today on unverified assumptions and the calculation of attributable risks involves taking very unequal evidence of various types of factors and treating them equally. Effective primary prevention resulting in a reduction of cancer risk can be obtained by: (i) a reduction in the number of carcinogens to which humans are exposed; or (ii) a reduction of the exposure levels to carcinogens. Exposure levels that could be seen as sufficiently low when based on single agents, may actually not be safe in the context of the many other concomitant carcinogenic and mutagenic exposures. The list of human carcinogens and of their target organs might be quite different if: (i) epidemiological data were available for a larger proportion of human exposures for which there is experimental evidence of carcinogenicity; (ii) more attention was paid to epidemiological evidence that is suggestive of an exposure-cancer association, but is less than sufficient, particularly in identifying target organs; and (iii) experimental evidence of carcinogenicity, supported by mechanistic considerations, were more fully accepted as predictions of human risk.

An inherited variant of the estrogen receptor gene was previously suggested to be a major determinant of a woman's risk of miscarriage. The authors tested this hypothesis in a case-control study of 29 women who had had two or more miscarriages and 29 women with no miscarriages. All of the women had given birth in North Carolina between 1987 and 1990. Estrogen receptor genotype was determined by direct sequencing of DNA. The gene variant that supposedly produced the risk was found to contain only a silent substitution at codon 87. Furthermore, instead of an odds ratio of 25 (predicted by the previous study), the odds ratio found was 1.8 (95% confidence interval 0.3-11). For a hypothesis which now lacks biologic plausibility, this weak association provides little reason for further investigation.

Carcinogenic arylamines are acetylated by the hepatic N-acetyltransferase. This enzyme is polymorphic in humans and in some epidemiological studies, the slow-acetylator phenotype has been associated with higher risk of bladder cancer and lower risk of colorectal cancer. The presence of two germline copies of any of several mutant alleles of the NAT2 gene produces a slow-acetylation phenotype. We used a PCR-RFLP technique to identify three known slow-acetylator alleles (M1, M2 and M3). Comparison of results from PCR-RFLP genotyping with caffeine metabolism phenotyping in 42 individuals suggested that an additional slow-acetylator allele was present in our sampled population. We sequenced the NAT2 gene for several discordant slow-acetylator individuals and found a G > A base-change in codon 64 that caused a Arg > Glu amino acid substitution. This sequence change, termed the 'M4' allele, was found in all of the discordant individuals in our population and apparently causes a slow-acetylation phenotype. In addition, we have determined that NAT2 allele frequencies in 372 Caucasian-Americans (WT = 0.25, M1 = 0.45, M2 = 0.28, M3 = 0.02, and M4 = 0.00) and in 128 African-Americans (WT = 0.36, M1 = 0.30, M2 = 0.22, M3 = 0.02 and M4 = 0.09) are significantly different (P < 0.0001). The M4 allele was not found in 372 unrelated Caucasians and appears to be of African origin.

Glutathione transferase (GT) activity towards trans-stilbene oxide (tSBO), benzo[a]pyrene-4,5-oxide (B[a]PO) and 1-chloro-2,4-dinitrobenzene (CDNB) was measured in human liver and lymphocytes. GT-tSBO activity is catalyzed by GT mu which has polymorphic expression in human lymphocytes. Our results show that activity of GT-tSBO in lymphocytes correlates with its activity in liver (r = 0.7, P less than 0.001). GT activity towards BPO (GT-BPO) also correlated with GT-tSBO in lymphocytes and liver. However, interindividual variation of GT-BPO is less than that of GT-tSBO, suggesting that BPO may not be as specific a substrate for GT mu and therefore other GT isozymes may contribute to BPO conjugation. Conjugation of CDNB by GT was not different using cytosols from either high or low GT mu individuals. The functional significance of the GT-mu polymorphism was evaluated by measuring its effect on benzo[a]pyrene (B[a]P)- and aflatoxin B1 (AFB1)-DNA adduct formation in vitro. Human liver cytosols prepared from persons having low or high GT-tSBO activity were incubated with human liver microsomes, calf thymus DNA and B[a]P or AFB1. HPLC analysis revealed that the major B[a]P adduct was dG(N2)-7 beta, 8 alpha-trihydroxy-7,8,9,10-tetrahydrobenzo[a]pyrene (BPDE-dG). BPDE-dG adducts were decreased equally by cytosols from either low or high conjugators. In contrast, AFB1-DNA binding was inhibited to a greater extent in high conjugators than low conjugators. HPLC analysis demonstrates that adducts formed were AFB1-FAPyr and AFB1-N7-Gua. The correlation between AFB1-DNA adduct concentrations and GT mu activity was highly significant with a correlation coefficient of r = 0.88 at P less than 0.001. These results suggest that GT mu plays an important role in detoxifying DNA reactive metabolites of AFB1 and this enzyme may be a susceptibility marker for AFB1 related liver cancer. Moreover, our data demonstrate that lymphocytes are a reliable surrogate tissue for detecting liver GT mu polymorphisms.

In this issue of the Journal, Ma et al. (1) report the results of a nested case–control study that show an association between colorectal cancer risk in men and elevated plasma levels of insulin-like growth factor-I (IGF-I) and decreased plasma levels of IGF-binding protein-3 (IGFBP-3). Importantly, this study demonstrates these effects by using plasma samples drawn years before the clinical appearance of the tumor, thus minimizing the chance that plasma levels are influenced by the disease process. This study follows reports demonstrating associations between levels of IGF-I and/or IGFBP-3 and the risk for cancers of the breast, prostate, and lung, suggesting that IGF-I is an important indicator of risk for the most prevalent forms of cancer in Western society (2–5). In fact, IGF-I levels appear to have a stronger association than most other risk factors for these common cancers. IGF-I is unique as a peptide growth factor. In addition to autocrine/paracrine functions demonstrated in numerous tissues, it serves as an endocrine hormone promoting postnatal somatic growth and maintaining lean tissue mass (6). IGF-I effects are modulated by a family of high-affinity BPs. IGF-I and its principal carrier protein, IGFBP-3, are produced primarily by the liver. Hepatic IGF-I synthesis is regulated by growth hormone (GH) and caloric intake and serves to integrate anabolic signals from the pituitary with signals related to nutritional status. In contrast to insulin, which is involved in short-term regulation of energy metabolism, changes in IGF-I levels occur over a longer term of days to weeks. Dietary restriction, which decreases the serum concentration of IGF-I in both humans and rodents, reduces the incidence of cancer in many rodent models (7,8). Caloric excess, on the other hand, may increase plasma IGF-I in humans (9). Perhaps part of the link between diet and cancer risk might be due to IGF-I and IGFBP-3. Although Ma et al. find little evidence of an association between cancer risk and plasma measures of either total IGF-I or IGFBP-3 alone, they show by a number of different analyses

The Illumina HumanMethylation450 BeadChip is increasingly utilized in epigenome-wide association studies, however, this array-based measurement of DNA methylation is subject to measurement variation. Appropriate data preprocessing to remove background noise is important for detecting the small changes that may be associated with disease. We developed a novel background correction method, ENmix, that uses a mixture of exponential and truncated normal distributions to flexibly model signal intensity and uses a truncated normal distribution to model background noise. Depending on data availability, we employ three approaches to estimate background normal distribution parameters using (i) internal chip negative controls, (ii) out-of-band Infinium I probe intensities or (iii) combined methylated and unmethylated intensities. We evaluate ENmix against other available methods for both reproducibility among duplicate samples and accuracy of methylation measurement among laboratory control samples. ENmix out-performed other background correction methods for both these measures and substantially reduced the probe-design type bias between Infinium I and II probes. In reanalysis of existing EWAS data we show that ENmix can identify additional CpGs, and results in smaller P-value estimates for previously-validated CpGs. We incorporated the method into R package ENmix, which is freely available from Bioconductor website.

Summary: Genetic association studies increasingly rely on the use of linkage disequilibrium (LD) tag SNPs to reduce genotyping costs. We developed a software package TAGster to select, evaluate and visualize LD tag SNPs both for single and multiple populations. We implement several strategies to improve the efficiency of current LD tag SNP selection algorithms: (1) we modify the tag SNP selection procedure of Carlson et al. to improve selection efficiency and further generalize it to multiple populations. (2) We propose a redundant SNP elimination step to speed up the exhaustive tag SNP search algorithm proposed by Qin et al. (3) We present an additional multiple population tag SNP selection algorithm based on the framework of Howie et al., but using our modified exhaustive search procedure. We evaluate these methods using resequenced candidate gene data from the Environmental Genome Project and show improvements in both computational and tagging efficiency.Availability: The software Package TAGster is freely available at http://www.niehs.nih.gov/research/resources/software/tagster/Contact: taylor@niehs.nih.govSupplementary information: Additional information, including a tutorial, detailed algorithm and detailed evaluation results, is also available from TAGster web site (see above).

An analytical method for the determination of sulfide in human and rat brain is described. It utilizes a continuous flow gas dialysis pretreatment and quantitation by ion chromatography with electrochemical detection. Rat brain sulfide levels were reliably measured after fatal intoxication by intraperitoneal injection of NaHS. By expeditious analysis of samples it was possible to demonstrate the presence of endogenous levels of sulfide in both rat and human brain as well as to measure elevated brain levels of sulfide after intoxication. In postmortem rat brain tissue, elevated sulfide levels could still be reliably demonstrated 96 h after death if the bodies had been refrigerated at 4 degrees C. Two case studies of human hydrogen sulfide inhalation fatalities are presented. The described method was able to measure significantly elevated sulfide levels in both cases.