Altered coordination between sleep timing and cortisol profiles in night working female hospital employees.

BACKGROUND: Cortisol typically peaks in the morning after waking up and declines throughout the day, reaching its lowest levels during nighttime sleep. Shift work can cause misalignment between cortisol levels and sleep-wake timing. We analyzed this misalignment in female shift workers focusing on the timing and extent of these changes. METHODS: We conducted a cross-sectional study involving 68 shift workers (aged 37 ± 10 years) and 21 non-shift workers (aged 45 ± 10 years) from a hospital. Shift workers were monitored through two day shifts and three night shifts, whereas non-shift workers were monitored during two day shifts. Each participant collected six to eight saliva samples (depending on their shift type) and provided sleep timing information, which was recorded via polysomnography and sleep diaries. Generalized additive mixed models were used to estimate shift-specific differences in cortisol smooth curves. Summary measures calculated for the cortisol smooth curves included cortisol awakening response, peak-to-bed slope, and total output. RESULTS: Between shift workers and non-shift workers, we observed similar diurnal cortisol profiles with a steep negative diurnal slope during day shifts. In shift workers on night shifts, a flattened U-shaped cortisol profile after the post-awakening maximum was observed, with a peak-to-bed slope close to zero. When comparing night to day shifts in the group of shift workers, mean cortisol levels were lower between 42 and 56 minutes and 1.8-11.9 hours after waking up, and higher between 14.9 and 22 hours after waking up. CONCLUSION: Our findings indicate altered cortisol profiles in female hospital employees on night shifts. Specifically, cortisol levels were lower at night when higher levels would typically be necessary for work activities, and higher at bedtime after a night shift, when levels should normally be low.

Polymorphisms in genes of melatonin biosynthesis and signaling support the light-at-night hypothesis for breast cancer.

Light-at-night triggers the decline of pineal gland melatonin biosynthesis and secretion and is an IARC-classified probable breast-cancer risk factor. We applied a large-scale molecular epidemiology approach to shed light on the putative role of melatonin in breast cancer. We investigated associations between breast-cancer risk and polymorphisms at genes of melatonin biosynthesis/signaling using a study population of 44,405 women from the Breast Cancer Association Consortium (22,992 cases, 21,413 population-based controls). Genotype data of 97 candidate single nucleotide polymorphisms (SNPs) at 18 defined gene regions were investigated for breast-cancer risk effects. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CI) by logistic regression for the main-effect analysis as well as stratified analyses by estrogen- and progesterone-receptor (ER, PR) status. SNP-SNP interactions were analyzed via a two-step procedure based on logic regression. The Bayesian false-discovery probability (BFDP) was used for all analyses to account for multiple testing. Noteworthy associations (BFDP < 0.8) included 10 linked SNPs in tryptophan hydroxylase 2 (TPH2) (e.g. rs1386492: OR = 1.07, 95% CI 1.02-1.12), and a SNP in the mitogen-activated protein kinase 8 (MAPK8) (rs10857561: OR = 1.11, 95% CI 1.04-1.18). The SNP-SNP interaction analysis revealed noteworthy interaction terms with TPH2- and MAPK-related SNPs (e.g. rs1386483R ∧ rs1473473D ∧ rs3729931D: OR = 1.20, 95% CI 1.09-1.32). In line with the light-at-night hypothesis that links shift work with elevated breast-cancer risks our results point to SNPs in TPH2 and MAPK-genes that may impact the intricate network of circadian regulation.

Investigating the influence of shift work rosters on stress measured as cortisol in hair during the SARS-CoV-2 pandemic.

The COVID-19 pandemic has increased the workload and has affected physical and mental health of many employees. Hair cortisol concentration (HCC) has proven useful as a marker for retrospective assessment of stress in epidemiological studies and was measured here in non-healthcare night-shift workers with standard shifts (8-h shifts) and extended shifts (12-h shifts) before and during the first wave of the COVID-19 pandemic in Germany. Results showed a twofold increase in HCC among shift workers during the first wave of the COVID-19 pandemic compared with previous measurements. Subjectively reported measures of psychosomatic stress were not found to be reliable predictors of HCC. No statistically significant HCC differences were found between rosters. Working 12-h shifts does not appear to be an additional stressor in the already demanding COVID-19 pandemic.

Night work, chronotype and cortisol at awakening in female hospital employees.

To examine the effect of night shift on salivary cortisol at awakening (C1), 30 min later (C2), and on the cortisol awakening response (CAR, the difference between C2 and C1). We compared shift and non-shift workers with a focus on the impact of worker chronotype. Our study included 66 shift-working females (mean age = 37.3 years, SD = 10.2) and 21 non-shift working females (mean age = 47.0 years, SD = 8.9). The shift workers collected their saliva samples at C1 and C2 on each two consecutive day shifts and night shifts. Non-shift workers collected their samples on two consecutive day shifts. We applied linear mixed-effects models (LMM) to determine the effect of night shift on CAR and log-transformed C1 and C2 levels. LMMs were stratified by chronotype group. Compared to non-shift workers, shift workers before day shifts (i.e. after night sleep) showed lower cortisol at C1 (exp [Formula: see text]=0.58, 95% CI 0.42, 0.81) but not at C2. In shift workers, the CARs after night shifts (i.e. after day sleep) were lower compared to CARs before day shifts ([Formula: see text]= - 11.07, 95% CI - 15.64, - 6.50). This effect was most pronounced in early chronotypes (early: [Formula: see text]= - 16.61, 95% CI - 27.87, - 5.35; intermediate: [Formula: see text]= - 11.82, 95% CI - 18.35, - 5.29; late: [Formula: see text]= - 6.27, 95% CI - 14.28, 1.74). Chronotype did not modify the association between night shift and CAR. In our population of shift workers, there was a mismatch between time of waking up and their natural cortisol peak at waking up (CAR) both during day and night shift duties.

Social jetlag and sleep debts are altered in different rosters of night shift work.

BACKGROUND: Night and shift work are suspected to cause various adverse effects on health and sleep. Sleep deprivation through shift work is assumed to be compensated on free days. So far it is not clear how different shift systems and shift lengths affect sleep structure on work and free days. Especially working night shifts disrupts the circadian rhythm but also extended working hours (12h) might affect sleep characteristics. Hitherto, the magnitude of sleep debt, social jetlag, and Locomotor Inactivity During Sleep (LIDS) in different shift systems is unknown. METHODS: Here, we investigated the impact of five different shift rosters on sleep in 129 industrial workers from Germany. Permanent night work with multiple shift systems with and without night shifts and with different shift lengths were compared. Wrist-activity was monitored over 28 days revealing sleep on- and offsets as well as LIDS as proxy for sleep quality. Overall, 3,865 sleep bouts comprising 22,310 hours of sleep were examined. RESULTS: The mean daily age-adjusted sleep duration (including naps) was 6:43h and did not differ between shift workers of different rosters. However, sleep duration on workdays was particularly low in rotational shift systems with 12h-shifts (5:00h), while overall sleep debt was highest. Shift workers showed a median absolute social jetlag of 3:03h, which differed considerably between shift types and rosters (p<0.0001). Permanent night workers had the highest social jetlag (5:08h) and latest mid-sleeps on workdays and free days. Sleep quality was reduced in permanent night shift workers compared with shift workers in other rosters and differed between daytime and nighttime sleep. CONCLUSIONS: Shift work leads to partial sleep deprivation, which particularly affects workers in 12h-shifts and permanent night shifts. Working these shifts resulted in higher sleep debts and larger absolute social jetlag whereas sleep quality was especially reduced in permanent night shift workers compared with shift workers of other rosters.

Impact of shift work on the risk of depression.

We studied the association between shift work and depressive symptoms in the prospective Heinz Nixdorf Recall Study, considering various demographic, lifestyle and work-related factors. Depressive symptoms were assessed using the Center for Epidemiologic Studies-Depression (CES-D)-Scale (≥17 points defined as high symptoms) and the Patient Health Questionnaire (PHQ) with a cutoff ≥9, or prescription of an anti-depressant. The definition of shift work included work hours outside 7:00 to 18:00, whereas night work was defined as a shift including work between 0:00 and 5:00. Poisson regression with robust error variances was calculated to estimate relative risks (RR) and 95% confidence intervals (CI), adjusted for age at follow-up, diurnal preference, monthly household income and education. Analyses were stratified by sex. We performed various sensitivity and stratified analyses to test the robustness of our results. At baseline, 1,500 gainfully employed subjects, 45-73 years of age and without a history of depression, were included. Until the 5-year follow-up, 896 participants were observed, and 486 participants survived through the 10-year follow-up. Although most analyses did not reach the level of formal statistical significance, women working night shifts tended to show increased relative risks for depressive symptoms according to the PHQ (RR = 1.78; 95% CI 0.71-4.45), in particular when working night shifts for ≥20 years (RR = 2.70; 95% CI 0.48-15.4). Stratification by age group revealed no increased risks among women above 60 years of age. Stratified analyses indicated that over-commitment was associated with higher risks for depressive symptoms among women (RR = 4.59; 95% CI 0.95-22.2 in the CES-D and RR = 12.7; 95% CI 2.89-56.1 in the PHQ). Exclusion of subgroups for the purpose of sensitivity analyses generally strengthened associations in women, whereas little evidence for an increased risk of depression remained among male shift workers. In summary, negative effects on depression were suggested among female shift workers, although results were based on small numbers. Among men, we did not identify consistently increased risks for depressive symptoms in relation to shift work.

Associations between shift work and risk of colorectal cancer in two German cohort studies.

The association between shift work and the risk of colorectal cancer (CRC) is still unclear. Therefore, we studied the associations between exposure to shift or night work and incident CRC in two German population-based cohort studies, the Heinz Nixdorf Recall Study (HNR) and the Study of Health in Pomerania (SHIP). Including up to 6,903 participants, we analyzed the cohorts pooled and individually. We estimated incidence rate ratios (IRRs) with adjusted log-linear Poisson regression models with the natural logarithm of person-years as offset and performed subgroup analyses by sex and tumor localization in HNR. The pooled analysis revealed no increased risks for men working in night shifts (IRR: 1.03, 95% CI: 0.62; 1.71). In male HNR participants, we found an increased risk estimate for cancer of the distal colon in shift workers (IRR: 1.60, 95% CI: 0.53; 4.87) and in shift workers who did not perform night work (IRR: 3.93, 95% CI: 0.98; 15.70), but not in night workers. In SHIP, we observed elevated CRC risk estimates for rotating shift work including night work (IRR: 1.45, 95% CI: 0.72; 2.92) and for long-term exposure (IRR: 1.79, 95% CI: 0.81; 3.92) for men. In conclusion, night-shift work was not associated with CRC, although an increased risk was suggested for rotating shift work including nights in SHIP. The heterogeneity of shift-work jobs and schedules and associated lifestyle factors should be taken into account to disentangle a possible relationship between shift work and the risk for CRC in future investigations.

Decreased psychomotor vigilance of female shift workers after working night shifts.

BACKGROUND: We compared psychomotor vigilance in female shift workers of the Bergmannsheil University Hospital in Bochum, Germany (N = 74, 94% nurses) after day and night shifts. METHODS: Participants performed a 3-minute Psychomotor Vigilance Task (PVT) test bout at the end of two consecutive day and three consecutive night shifts, respectively. Psychomotor vigilance was analyzed with respect to mean reaction time, percentage of lapses and false starts, and throughput as an overall performance score, combining reaction time and error frequencies. We also determined the reaction time coefficient of variation (RTCV) to assess relative reaction time variability after day and night shifts. Further, we examined the influence of shift type (night vs. day) by mixed linear models with associated 95% confidence intervals (CI), adjusted for age, chronotype, study day, season, and the presence of obstructive sleep apnea (OSA). RESULTS: At the end of a night shift, reaction times were increased (ß = 7.64; 95% CI 0.94; 14.35) and the number of lapses higher compared to day shifts (exp(ß) = 1.55; 95% CI 1.16-2.08). By contrast, we did not observe differences in the number of false starts between day and night shifts. Throughput was reduced after night shifts (ß = -15.52; 95% CI -27.49; -3.46). Reaction times improved across consecutive day and night shifts, whereas the frequency of lapses decreased after the third night. RTCV remained unaffected by both, night shifts and consecutive shift blocks. DISCUSSION: Our results add to the growing body of literature demonstrating that night-shift work is associated with decreased psychomotor vigilance. As the analysis of RTCV suggests, performance deficits may selectively be driven by few slow reactions at the lower end of the reaction time distribution function. Comparing intra-individual PVT-performances over three consecutive night and two consecutive day shifts, we observed performance improvements after the third night shift. Although a training effect cannot be ruled out, this finding may suggest better adaptation to the night schedule if avoiding fast-changing shift schedules.

Differences in twenty-four-hour profiles of blue-light exposure between day and night shifts in female medical staff.

Light is the strongest zeitgeber currently known for the synchronization of the human circadian timing system. Especially shift workers are exposed to altered daily light profiles. Our objective is the characterization of differences in blue-light exposures between day and night shift taking into consideration modifying factors such as chronotype. We describe 24-hour blue-light profiles as measured with ambient light data loggers (LightWatcher) during up to three consecutive days with either day or night shifts in 100 female hospital staff including 511 observations. Linear mixed models were applied to analyze light profiles and to select time-windows for the analysis of associations between shift work, individual factors, and log mean light exposures as well as the duration of darkness per day. Blue-light profiles reflected different daily activities and were mainly influenced by work time. Except for evening (7-9 p.m.), all time windows showed large differences in blue-light exposures between day and night shifts. Night work reduced the duration of darkness per day by almost 4 h (ß^ = -3:48 hh:mm, 95% CI (-4:27; -3.09)). Late chronotypes had higher light exposures in the morning and evening compared to women with intermediate chronotype (e.g. morning ß^ = 0.50 log(mW/m2/nm), 95% CI (0.08; 0.93)). Women with children had slightly higher light exposures in the afternoon than women without children (ß^ = 0.48, 95% CI (-0.10; 1,06)). Time windows for the description of light should be chosen carefully with regard to timing of shifts. Our results are helpful for future studies to capture relevant light exposure differences and potential collinearities with individual factors. Improvement of well-being of shift workers with altered light profiles may therefore require consideration of both - light at the workplace and outside working hours.

Night Shift Work Affects Urine Metabolite Profiles of Nurses with Early Chronotype.

Night shift work can have a serious impact on health. Here, we assess whether and how night shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424 waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate <0.05) affected in nurses working in night shifts. One metabolite, acylcarnitine C10:2, was consistently identified with all three normalization methods. We further observed 11 and 4 metabolites significantly associated with night shift in early and late chronotype classes, respectively. Increased levels of medium- and long chain acylcarnitines indicate a strong impairment of the fatty acid oxidation. Our results show that night shift work influences acylcarnitines and BCAAs, particularly in nurses in the early chronotype class. Women with intermediate and late chronotypes appear to be less affected by night shift work.

Dilution correction for dynamically influenced urinary analyte data.

Urinary analyte data has to be corrected for the sample specific dilution as the dilution varies intra- and interpersonally dramatically, leading to non-comparable concentration measures. Most methods of dilution correction utilized nowadays like probabilistic quotient normalization or total spectra normalization result in a division of the raw data by a dilution correction factor. Here, however, we show that the implicit assumption behind the application of division, log-linearity between the urinary flow rate and the raw urinary concentration, does not hold for analytes which are not in steady state in blood. We explicate the physiological reason for this short-coming in mathematical terms and demonstrate the empirical consequences via simulations and on multiple time-point metabolomic data, showing the insufficiency of division-based normalization procedures to account for the complex non-linear analyte specific dependencies on the urinary flow rate. By reformulating normalization as a regression problem, we propose an analyte specific way to remove the dilution variance via a flexible non-linear regression methodology which then was shown to be more effective in comparison to division-based normalization procedures. In the progress, we developed several, easily applicable methods of normalization diagnostics to decide on the method of dilution correction in a given sample. On the way, we identified furthermore the time-span since last urination as an important variance factor in urinary metabolome data which is until now completely neglected. In conclusion, we present strong theoretical and empirical evidence that normalization has to be analyte specific in dynamically influenced data. Accordingly, we developed a normalization methodology for removing the dilution variance in urinary data respecting the single analyte kinetics.

Vitamin D supply in shift working nurses.

We studied determinants of Vitamin D in serum of 67 female health care workers (aged 25-60 years), including age, body mass index, physical activity, and shift work. Overall, vitamin D levels were low, ranging from 6 to 51 ng/mL (median: 20 ng/mL). Lower serum levels were found in samples drawn in winter and spring and in obese subjects. Shift work had only small effects on vitamin D levels. The high prevalence of vitamin D undersupply is in line with observations from the German general population. Vitamin D supply particularly in winter and spring should be ensured to avoid health problems.

Night shift work and breast cancer: a pooled analysis of population-based case-control studies with complete work history.

Night shift work has been suspected to increase breast cancer risk but epidemiological studies have been inconsistent due to heterogeneous assessment of exposure to night work. To overcome this limitation, we pooled data of five population-based case-control studies from Australia, Canada, France, Germany, and Spain into a single harmonized dataset using a common definition of night work including 6093 breast cancer cases and 6933 population controls. The odds ratio for breast cancer in women who ever worked at night for at least 3 h between midnight and 5 a.m. as compared to never night workers was 1.12 (95% CI 1.00-1.25). Among pre-menopausal women, this odds ratio was 1.26 [1.06-1.51], increasing to 1.36 [1.07-1.74] for night shifts ≥ 10 h, 1.80 [1.20-2.71] for work ≥ 3 nights/week, and 2.55 [1.03-6.30] for both duration of night work ≥ 10 years and exposure intensity ≥ 3 nights/week. Breast cancer risk in pre-menopausal women was higher in current or recent night workers (OR = 1.41 [1.06-1.88]) than in those who had stopped night work more than 2 years ago. Breast cancer in post-menopausal women was not associated with night work whatever the exposure metric. The increase in risk was restricted to ER+ tumors, particularly those who were both ER+ and HER2+ . These results support the hypothesis that night shift work increases the risk of breast cancer in pre-menopausal women, particularly those with high intensity and long duration of exposure. Risk difference between pre- and post-menopausal women deserves further scrutiny.

Shift work and the incidence of prostate cancer: a 10-year follow-up of a German population-based cohort study.

Objectives We investigated the association of shift and night work with the incidence of prostate cancer using data of the population-based prospective Heinz Nixdorf Recall Study from the highly industrialized Ruhr area in Germany. Methods Participants of the baseline survey were recruited between 2000-2003. A follow-up survey including, a detailed interview on shift and night work, was conducted from 2011-2014. We included 1757 men who did not report a history of prostate cancer at baseline. We assessed shift- and night-work exposure up to time of the baseline interview. Incident prostate cancers were recorded from baseline through September 2014. We calculated hazard ratios (HR) of shift- and night-work exposure using Cox proportional hazards regression with age at event as timescale, adjusting for smoking status, family history of prostate cancer, education (≤13, 14-17, ≥18 years), and equivalent income (low, medium, high). Results We observed a twofold increased HR for prostate cancer among shift and night workers. Ever employment in shift work was associated with HR 2.29, 95% confidence interval (CI) 1.43-3.67 and night work with HR 2.27, 95% CI 1.42-3.64. HR increased steadily with duration of employment in shift or night work. Stratifying analyses by preferred midpoint of sleep, yielded strongly elevated HR among subjects with early sleep preference, although these analyses were limited by small number of cases. Conclusions We identified increased risks for prostate cancer among men with employment in shift or night work. HR were strongly elevated among long-term employed shift workers and men with early preferred midpoint of sleep.

Stability of targeted metabolite profiles of urine samples under different storage conditions.

INTRODUCTION: Few studies have investigated the influence of storage conditions on urine samples and none of them used targeted mass spectrometry (MS). OBJECTIVES: We investigated the stability of metabolite profiles in urine samples under different storage conditions using targeted metabolomics. METHODS: Pooled, fasting urine samples were collected and stored at -80 °C (biobank standard), -20 °C (freezer), 4 °C (fridge), ~9 °C (cool pack), and ~20 °C (room temperature) for 0, 2, 8 and 24 h. Metabolite concentrations were quantified with MS using the AbsoluteIDQ™ p150 assay. We used the Welch-Satterthwaite-test to compare the concentrations of each metabolite. Mixed effects linear regression was used to assess the influence of the interaction of storage time and temperature. RESULTS: The concentrations of 63 investigated metabolites were stable at -20 and 4 °C for up to 24 h when compared to samples immediately stored at -80 °C. When stored at ~9 °C for 24 h, few amino acids (Arg, Val and Leu/Ile) significantly decreased by 40% in concentration (P < 7.9E-04); for an additional three metabolites (Ser, Met, Hexose H1) when stored at ~20 °C reduced up to 60% in concentrations. The concentrations of four more metabolites (Glu, Phe, Pro, and Thr) were found to be significantly influenced when considering the interaction between exposure time and temperature. CONCLUSION: Our findings indicate that 78% of quantified metabolites were stable for all examined storage conditions. Particularly, some amino acid concentrations were sensitive to changes after prolonged storage at room temperature. Shipping or storing urine samples on cool packs or at room temperature for more than 8 h and multiple numbers of freeze and thaw cycles should be avoided.

Polymorphisms in circadian genes, night work and breast cancer: results from the GENICA study.

OBJECTIVES: The role of genetic variants and environmental factors in breast cancer etiology has been intensively studied in the last decades. Gene-environment interactions are now increasingly being investigated to gain more insights into the development of breast cancer, specific subtypes, and therapeutics. Recently, night shift work that involves circadian disruption has gained rising interest as a potential non-genetic breast cancer risk factor. Here, we analyzed genetic polymorphisms in genes of cellular clocks, melatonin biosynthesis and signaling and their association with breast cancer as well as gene-gene and gene-night work interactions in a German case-control study on breast cancer. METHODS: GENICA is a population-based case-control study on breast cancer conducted in the Greater Region of Bonn. Associations between seven polymorphisms in circadian genes (CLOCK, NPAS2, ARTNL, PER2 and CRY2), genes of melatonin biosynthesis and signaling (AANAT and MTNR1B) and breast cancer were analyzed with conditional logistic regression models, adjusted for potential confounders for 1022 cases and 1014 controls. Detailed shift-work information was documented for 857 breast cancer cases and 892 controls. Gene-gene and gene-shiftwork interactions were analyzed using model-based multifactor dimensionality reduction (mbMDR). RESULTS: For combined heterozygotes and rare homozygotes a slightly elevated breast cancer risk was found for rs8150 in gene AANAT (OR 1.17; 95% CI 1.01-1.36), and a reduced risk for rs3816358 in gene ARNTL (OR 0.82; 95% CI 0.69-0.97) in the complete study population. In the subgroup of shift workers, rare homozygotes for rs10462028 in the CLOCK gene had an elevated risk of breast cancer (OR for AA vs. GG: 3.53; 95% CI 1.09-11.42). Shift work and CLOCK gene interactions were observed in the two-way interaction analysis. In addition, gene-shiftwork interactions were detected for MTNR1B with NPAS2 and ARNTL. CONCLUSIONS: In conclusion, the results of our population-based case-control study support a putative role of the CLOCK gene in the development of breast cancer in shift workers. In addition, higher order interaction analyses suggest a potential relevance of MTNR1B with the key transcriptional factor NPAS2 with ARNTL. Hence, in the context of circadian disruption, multivariable models should be preferred that consider a wide range of polymorphisms, e.g. that may influence chronotype or light sensitivity. The investigation of these interactions in larger studies is needed.

CYP2B6*6 is associated with increased breast cancer risk.

The cytochrome P450 2B6 (CYP2B6) is involved in the metabolism of testosterone. Functional changes in this enzyme may influence endogenous hormone exposure, which has been associated with risk of breast cancer. To assess potential associations between two functional polymorphisms CYP2B6_516_G>T (rs3745274) and CYP2B6_785_A>G (rs2279343) and breast cancer risk, we established a specific matrix-assisted laser desorption/ionization time-of-flight mass spectrometry assay. The GENICA breast cancer case-control study showed associations between the variant genotypes CYP2B6_516_TT and CYP2B6_785_GG and breast cancer risk with odds ratios (ORs) of 1.34 (p = 0.001) and 1.31 (p = 0.002), respectively. A similar effect was observed for carriers of the CYP2B6_516_T allele in a validation study including four independent studies from Germany, Sweden and USA. In a pooled analysis of all five studies involving 4,638 breast cancer cases and 3,594 controls of European ancestry, carriers of the CYP2B6_516_G and the CYP2B6_785_G variant had an increased breast cancer risk with ORs of 1.10 (p = 0.027) and 1.10 (p = 0.031), respectively. We conclude that the genetic variants CYP2B6_516_G and CYP2B6_785_G (designated CYP2B6*6), which are known to decrease activity of the CYP2B6 enzyme, contribute to an increased breast cancer risk.

N-acetyltransferase 2 phenotype, occupation, and bladder cancer risk: results from the EPIC cohort.

BACKGROUND: An association between N-acetyltransferase 2 (NAT2) slow acetylation and bladder cancer has been consistently observed in epidemiologic studies. However, evidence has been mainly derived from case-control studies and was sparse from cohort studies. We evaluated the association between NAT2 slow acetylation and bladder cancer in a case-control study nested in the European Prospective Investigation into Cancer and Nutrition. METHODS: Exposure to aromatic amines and polycyclic aromatic hydrocarbons (PAH) could be assessed for 754 cases and 833 controls for whom occupational information was documented. A semiquantitative job-exposure matrix was applied to at-risk occupations to estimate the exposure as low, medium, or high based on tertiles of the distribution of the exposure score in controls. Using a comprehensive genotyping, NAT2 acetylation status could be categorized from 6-single-nucleotide polymorphism genotypes as slow or fast in 607 cases and 695 controls with DNA from archived blood samples. RESULTS: Occupational exposure to aromatic amines and PAH was associated with an increased bladder cancer risk [upper tertile of the distribution of the exposure score: OR = 1.37; 95% confidence interval (CI), 1.02-1.84, and OR = 1.50; 95% CI, 1.09-2.05, respectively]. NAT2 slow acetylation did not modify these risk estimates and was not itself associated with bladder cancer risk (OR = 1.02; 95% CI, 0.81-1.29). CONCLUSIONS: These findings confirm established or suspected occupational risk factors but not the anticipated role of NAT2 slow acetylation in bladder cancer. No interaction was detected between NAT2 and any exposure of interest, including smoking. IMPACT: Genetic testing for NAT2 would be inappropriate in occupational settings.

The UGT1A6_19_GG genotype is a breast cancer risk factor.

Validation of an association between the UGT1A6_19_T>G (rs6759892) polymorphism and overall breast cancer risk. A pilot study included two population-based case-control studies from Germany (MARIE-GENICA). An independent validation study comprised four independent breast cancer case-control studies from Finland (KBCP, OBCS), Germany (BBCC), and Sweden (SASBAC). The pooled analysis included 7418 cases and 8720 controls from all six studies. Participants were of European descent. Genotyping was done by MALDI-TOF MS and statistical analysis was performed by logistic regression adjusted for age and study. The increased overall breast cancer risk for women with the UGT1A6_19_GG genotype which was observed in the pilot study was confirmed in the set of four independent study collections (OR 1.13, 95% CI 1.05-1.22; p = 0.001). The pooled study showed a similar effect (OR 1.09, 95% CI 1.04-1.14; p = 0.001). The risk effect on the basis of allele frequencies was highly significant, the pooled analysis showed an OR of 1.11 (95% CI 1.06-1.16; p = 5.8 × 10(-6)). We confirmed the association of UGT1A6_19_GG with increased overall breast cancer risk and conclude that our result from a well powered multi-stage study adds a novel candidate to the panel of validated breast cancer susceptibility loci.