Evaluation of anterolateral thigh flap dimensions with virtual flap models

Free flaps are commonly used for head and neck reconstruction. However, flap dimensions are still evaluated by visual and tactile assessment. The aim of this study was to enable preoperative planning of flap dimensions for soft tissue reconstruction based on clinical parameters. Computed tomography records from 230 patients dated from 2009 to 2019 were analysed retrospectively. A virtual, three-dimensional anterolateral thigh flap model was standardized, aligned to segmented leg models in two positions, and flap thicknesses and volumes were determined. Associations of flap thickness and volume with clinical parameters were evaluated, and an approximative calculation method was derived. The laterally positioned anterolateral thigh flap showed an average (interquartile range) thickness of 15.6 mm (8.7 mm) and volume of 1.5 cm³ (0.9 cm³) per cm². The medially positioned anterolateral thigh flap showed an average (interquartile range) thickness of 16.3 mm (8.7 mm) and volume of 1.6 cm³ (0.9 cm³) per cm². For both flap positions, leg circumference was the strongest predictor of flap thickness (β = 0.545, P < 0.001 and β = 0.529, P < 0.001) and flap volume (β = 0.523, P < 0.001 and β = 0.480, P < 0.001). Flap dimensions can be calculated based on leg circumference, and this preoperative planning of flap dimensions can help the surgeon to select the appropriate flap.

Performance of several types of beta-binomial models in comparison to standard approaches for meta-analyses with very few studies

BACKGROUND

Meta-analyses are used to summarise the results of several studies on a specific research question. Standard methods for meta-analyses, namely inverse variance random effects models, have unfavourable properties if only very few (2 - 4) studies are available. Therefore, alternative meta-analytic methods are needed. In the case of binary data, the "common-rho" beta-binomial model has shown good results in situations with sparse data or few studies. The major concern of this model is that it ignores the fact that each treatment arm is paired with a respective control arm from the same study. Thus, the randomisation to a study arm of a specific study is disrespected, which may lead to compromised estimates of the treatment effect. Therefore, we extended this model to a version that respects randomisation. The aim of this simulation study was to compare the "common-rho" beta-binomial model and several other beta-binomial models with standard meta-analyses models, including generalised linear mixed models and several inverse variance random effects models.

METHODS

We conducted a simulation study comparing beta-binomial models and various standard meta-analysis methods. The design of the simulation aimed to consider meta-analytic situations occurring in practice.

RESULTS

No method performed well in scenarios with only 2 studies in the random effects scenario. In this situation, a fixed effect model or a qualitative summary of the study results may be preferable. In scenarios with 3 or 4 studies, most methods satisfied the nominal coverage probability. The "common-rho" beta-binomial model showed the highest power under the alternative hypothesis. The beta-binomial model respecting randomisation did not improve performance.

CONCLUSION

The "common-rho" beta-binomial appears to be a good option for meta-analyses of very few studies. As residual concerns about the consequences of disrespecting randomisation may still exist, we recommend a sensitivity analysis with a standard meta-analysis method that respects randomisation.

Deregulation and epigenetic modification of BCL2-family genes cause resistance to venetoclax in hematologic malignancies

The BCL2 inhibitor venetoclax has been approved to treat different hematological malignancies. Because there is no common genetic alteration causing resistance to venetoclax in chronic lymphocytic leukemia (CLL) and B-cell lymphoma, we asked if epigenetic events might be involved in venetoclax resistance. Therefore, we employed whole-exome sequencing, methylated DNA immunoprecipitation sequencing, and genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 screening to investigate venetoclax resistance in aggressive lymphoma and high-risk CLL patients. We identified a regulatory CpG island within the PUMA promoter that is methylated upon venetoclax treatment, mediating PUMA downregulation on transcript and protein level. PUMA expression and sensitivity toward venetoclax can be restored by inhibition of methyltransferases. We can demonstrate that loss of PUMA results in metabolic reprogramming with higher oxidative phosphorylation and adenosine triphosphate production, resembling the metabolic phenotype that is seen upon venetoclax resistance. Although PUMA loss is specific for acquired venetoclax resistance but not for acquired MCL1 resistance and is not seen in CLL patients after chemotherapy-resistance, BAX is essential for sensitivity toward both venetoclax and MCL1 inhibition. As we found loss of BAX in Richter's syndrome patients after venetoclax failure, we defined BAX-mediated apoptosis to be critical for drug resistance but not for disease progression of CLL into aggressive diffuse large B-cell lymphoma in vivo. A compound screen revealed TRAIL-mediated apoptosis as a target to overcome BAX deficiency. Furthermore, antibody or CAR T cells eliminated venetoclax resistant lymphoma cells, paving a clinically applicable way to overcome venetoclax resistance.

Diagnostic accuracy of rapid point-of-care tests for diagnosis of current SARS-CoV-2 infections in children: a systematic review and meta-analysis

OBJECTIVE

To systematically assess the diagnostic accuracy of rapid point-of-care tests for diagnosis of current SARS-CoV-2 infections in children under real-life conditions.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, Embase, Cochrane Database for Systematic Reviews, INAHTA HTA database, preprint servers (via Europe PMC), ClinicalTrials.gov, WHO ICTRP from 1 January 2020 to 7 May 2021; NICE Evidence Search, NICE Guidance, FIND Website from 1 January 2020 to 24 May 2021.

REVIEW METHODS

Diagnostic cross-sectional or cohort studies were eligible for inclusion if they had paediatric study participants and compared rapid point-of care tests for diagnosing current SARS-CoV-2 infections with reverse transcription polymerase chain reaction (RT-PCR) as the reference standard. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to assess the risk of bias and the applicability of the included studies. Bivariate meta-analyses with random effects were performed. Variability was assessed by subgroup analyses.

RESULTS

17 studies with a total of 6355 paediatric study participants were included. All studies compared antigen tests against RT-PCR. Overall, studies evaluated eight antigen tests from six different brands. Only one study was at low risk of bias. The pooled overall diagnostic sensitivity and specificity in paediatric populations was 64.2% (95% CI 57.4% to 70.5%) and 99.1% (95% CI 98.2% to 99.5%), respectively. In symptomatic children, the pooled diagnostic sensitivity was 71.8% (95% CI 63.6% to 78.8%) and the pooled diagnostic specificity was 98.7% (95% CI 96.6% to 99.5%). The pooled diagnostic sensitivity in asymptomatic children was 56.2% (95% CI 47.6% to 64.4%) and the pooled diagnostic specificity was 98.6% (95% CI 97.3% to 99.3%).

CONCLUSIONS

The performance of current antigen tests in paediatric populations under real-life conditions varies broadly. Relevant data were only identified for very few antigen tests on the market, and the risk of bias was mostly unclear due to poor reporting. Additionally, the most common uses of these tests in children (eg, self-testing in schools or parents testing their toddlers before kindergarten) have not been addressed in clinical performance studies yet. The observed low diagnostic sensitivity may impact the planned purpose of the broad implementation of testing programmes.

PROSPERO REGISTRATION NUMBER

CRD42021236313.

Limitations of the incidence density ratio as approximation of the hazard ratio

Background

Incidence density ratios (IDRs) are frequently used to account for varying follow-up times when comparing the risks of adverse events in two treatment groups. The validity of the IDR as approximation of the hazard ratio (HR) is unknown in the situation of differential average follow up by treatment group and non-constant hazard functions. Thus, the use of the IDR when individual patient data are not available might be questionable.

Methods

A simulation study was performed using various survival-time distributions with increasing and decreasing hazard functions and various situations of differential follow up by treatment group. HRs and IDRs were estimated from the simulated survival times and compared with the true HR. A rule of thumb was derived to decide in which data situations the IDR can be used as approximation of the HR.

Results

The results show that the validity of the IDR depends on the survival-time distribution, the difference between the average follow-up durations, the baseline risk, and the sample size. For non-constant hazard functions, the IDR is only an adequate approximation of the HR if the average follow-up durations of the groups are equal and the baseline risk is not larger than 25%. In the case of large differences in the average follow-up durations between the groups and non-constant hazard functions, the IDR represents no valid approximation of the HR.

Conclusions

The proposed rule of thumb allows the use of the IDR as approximation of the HR in specific data situations, when it is not possible to estimate the HR by means of adequate survival-time methods because the required individual patient data are not available. However, in general, adequate survival-time methods should be used to analyze adverse events rather than the simple IDR.

Biometrical issues in the analysis of adverse events within the benefit assessment of drugs

The analysis of adverse events plays an important role in the benefit assessment of drugs. Consequently, results on adverse events are an integral part of reimbursement dossiers submitted by pharmaceutical companies to health policy decision-makers. Methods applied in the analysis of adverse events commonly include simple standard methods for contingency tables. However, the results produced may be misleading if observations are censored at the time of discontinuation due to treatment switching or noncompliance, resulting in unequal follow-up periods. In this paper, we present examples to show that the application of inadequate methods for the analysis of adverse events in the reimbursement dossier can lead to a downgrading of the evidence on a drug's benefit in the subsequent assessment, as greater harm from the drug cannot be excluded with sufficient certainty. Legal regulations on the benefit assessment of drugs in Germany are presented, in particular, with regard to the analysis of adverse events. Differences in safety considerations between the drug approval process and the benefit assessment are discussed. We show that the naive application of simple proportions in reimbursement dossiers frequently leads to uninterpretable results if observations are censored and the average follow-up periods differ between treatment groups. Likewise, the application of incidence rates may be misleading in the case of recurrent events and unequal follow-up periods. To allow for an appropriate benefit assessment of drugs, adequate survival time methods accounting for time dependencies and duration of follow-up are required, not only for time-to-event efficacy endpoints but also for adverse events. © 2016 The Authors. Pharmaceutical Statistics published by John Wiley & Sons Ltd.

No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer

OBJECTIVE

Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370.

METHODS

Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers).

RESULTS

We found no association with risk of ovarian cancer (OR=0.99, 95% CI 0.94-1.04, p=0.74) or breast cancer (OR=0.98, 95% CI 0.94-1.01, p=0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR=1.09, 95% CI 0.97-1.23, p=0.14, breast cancer HR=1.04, 95% CI 0.97-1.12, p=0.27; BRCA2, ovarian cancer HR=0.89, 95% CI 0.71-1.13, p=0.34, breast cancer HR=1.06, 95% CI 0.94-1.19, p=0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR=0.94, 95% CI 0.83-1.07, p=0.38), breast cancer (HR=0.96, 95% CI 0.87-1.06, p=0.38), and all other previously-reported associations.

CONCLUSIONS

rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.

[Birth in Out-of-Hospital Settings--Differences in Maternal and Neonatal Outcome of Women with their Second Child and a Prior Caesarean Section Compared to First Paras]

BACKGROUND

Vaginal birth after Caesarean (VBAC) in out-of-hospital settings is controversial. With increasing Caesarean rates, more women with a prior Caesarean will decide to give birth in midwife-led birth-centres or at home. Therefore the study explores the question about maternal and neonatal outcomes in German out-of-hospital settings.

METHOD

A retrospective study of German out-of-hospital data from 2005 to 2011 was undertaken. Included were 66,437 singleton pregnancies in cephalic presentation at term. This study describes the outcome parameters of first paras compared to mothers with their second child who had a prior Caesarean.

RESULTS

The VBAC rate was 77.8%, and the first para vaginal birth rate was 89.8% (p<0.001). The intrapartum transfer rate of women with a prior Caesarean section was significantly more than for the first paras (38.2 vs. 27.2%; p<0.001). A prolonged first stage was the most frequently documented indication for intrapartal transfer in both groups. There were no significant differences in rates of maternal postpartum complications, or in postpartum hospital transfer rates. Also, neither neonatal transfer rates nor Apgar scores were statistically different between the groups.

DISCUSSION

These results are consistent with other studies which reported that an out-of-hospital setting is an alternative to the clinical setting for women with a prior Caesarean. However, the fact that the intrapartum transfer rate of women with a prior Caesarean was almost 40% should be included in antenatal counselling about the place of labour and birth.

Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk

Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.

[Vaginal birth after caesarean section in out-of-hospital settings: a literature review]

BACKGROUND

Even though vaginal birth after Caesarean section (VBAC) is recommended, an out-of-hospital setting is discussed controversially. First of all, uterine rupture and placental complications are named. Nevertheless, an increasing number of women with a prior Caesarean section decide to give birth in an out-of-hospital setting. What is the maternal and neonatal outcome in international studies in these cases?

METHOD

The databases of Medline, Cinahl, Embase and Cochrane Library on vaginal birth after Caesarean section in out-of-hospital settings were searched. Included are studies in German and English language without a limit on year of publication, which describe maternal and neonatal outcomes.

RESULTS

5 studies were found. All of them describe a high VBAC rate (73.5-98%). Only one study found uterine ruptures. Haemorrhage/placental complications were described in 2 studies (0.5 and 1.7%). None of the studies found maternal deaths. Neonatal death was described in 3 studies in a range from 0 -1.7%.

DISCUSSION

There is a wide difference in the population of the studies. An important difference is the parity of the women and the prior mode of birth. 4 of the 5 studies do not see a reason not to try VBAC in an out-of-hospital setting. Further studies are necessary to inform the increasing number of women who decide to try VBAC in an out-of-hospital setting.

A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10(-8)) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10(-4)) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10(-6). In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer.

Formaldehyde laser-induced fluorescence imaging with a multi-band transmission filter

A method for laser-induced fluorescence (LIF) imaging of formaldehyde (CH2O) that discriminates against the interfering signal from polycyclic aromatic hydrocarbons (PAHs) is presented. This technique uses an interference filter with 11 transmission bands that closely match the most prominent fluorescence features of CH2O upon excitation at 355 nm. The signal increases by a factor of 12 with the multi-band filter compared to a single-band filter. Slight angle-tuning of the filter shifts the transmission maxima to the minima in between the CH2O-LIF features. The pixel-by-pixel difference between the images collected at the two filter angles thus provides CH2O images free of PAH interference, providing the capability for selective single-pulse CH2O-LIF imaging in engine combustion even under fuel-rich conditions.

Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome-wide interaction study

Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case-control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0 × 10(-3) were selected for replication using pooled case-control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9 × 10(-6)), two SNPs in SLC25A21 (combined Pint≤4.8 × 10(-5)), and three SNPs in PLCG2 (combined Pint≤4.5 × 10(-5)). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7 × 10(-5)), one SNP in CD80 (combined Pint≤8.2 × 10(-6)), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10(-6)), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6 × 10(-5)). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.

Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status

OBJECTIVE

There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status.

MATERIAL AND METHODS

Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction.

RESULTS

We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status.

DISCUSSION AND CONCLUSIONS

Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.

Genome-wide association studies identify four ER negative-specific breast cancer risk loci

Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.

A genome-wide association study to identify genetic susceptibility loci that modify ductal and lobular postmenopausal breast cancer risk associated with menopausal hormone therapy use: a two-stage design with replication

Menopausal hormone therapy (MHT) is associated with an elevated risk of breast cancer in postmenopausal women. To identify genetic loci that modify breast cancer risk related to MHT use in postmenopausal women, we conducted a two-stage genome-wide association study (GWAS) with replication. In stage I, we performed a case-only GWAS in 731 invasive breast cancer cases from the German case-control study Mammary Carcinoma Risk Factor Investigation (MARIE). The 1,200 single nucleotide polymorphisms (SNPs) showing the lowest P values for interaction with current MHT use (within 6 months prior to breast cancer diagnosis), were carried forward to stage II, involving pooled case-control analyses including additional MARIE subjects (1,375 cases, 1,974 controls) as well as 795 cases and 764 controls of a Swedish case-control study. A joint P value was calculated for a combined analysis of stages I and II. Replication of the most significant interaction of the combined stage I and II was performed using 5,795 cases and 5,390 controls from nine studies of the Breast Cancer Association Consortium (BCAC). The combined stage I and II yielded five SNPs on chromosomes 2, 7, and 18 with joint P values <6 × 10(-6) for effect modification of current MHT use. The most significant interaction was observed for rs6707272 (P = 3 × 10(-7)) on chromosome 2 but was not replicated in the BCAC studies (P = 0.21). The potentially modifying SNPs are in strong linkage disequilibrium with SNPs in TRIP12 and DNER on chromosome 2 and SETBP1 on chromosome 18, previously linked to carcinogenesis. However, none of the interaction effects reached genome-wide significance. The inability to replicate the top SNP × MHT interaction may be due to limited power of the replication phase. Our study, however, suggests that there are unlikely to be SNPs that interact strongly enough with MHT use to be clinically significant in European women.

A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Using the posterior distribution of deviance to measure evidence of association for rare susceptibility variants

Aitkin recently proposed an integrated Bayesian/likelihood approach that he claims is general and simple. We have applied this method, which does not rely on informative prior probabilities or large-sample results, to investigate the evidence of association between disease and the 16 variants in the KDR gene provided by Genetic Analysis Workshop 17. Based on the likelihood of logistic regression models and considering noninformative uniform prior probabilities on the coefficients of the explanatory variables, we used a random walk Metropolis algorithm to simulate the distributions of deviance and deviance difference. The distribution of probability values and the distribution of the proportions of positive deviance differences showed different locations, but the direction of the shift depended on the genetic factor. For the variant with the highest minor allele frequency and for any rare variant, standard logistic regression showed a higher power than the novel approach. For the two variants with the strongest effects on Q1 under a type I error rate of 1%, the integrated approach showed a higher power than standard logistic regression. The advantages and limitations of the integrated Bayesian/likelihood approach should be investigated using additional regions and considering alternative regression models and collapsing methods.

Association of JAK-STAT pathway related genes with lymphoma risk: results of a European case-control study (EpiLymph)

Previous studies have suggested an important role for the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signalling pathway in tumour development. Therefore, we explored genetic variants in JAK-STAT pathway associated genes with lymphoma risk. In samples of the EpiLymph case-control study we genotyped 1536 single nucleotide polymorphisms (SNPs) using GoldenGate BeadArray™ Technology (Illumina, San Diego, CA, USA). Here, we report the associations between selected SNPs and haplotypes of the JAK-STAT pathway and risk of Hodgkin lymphoma (HL), B-cell non-Hodgkin lymphoma (B-NHL) and most frequent B-NHL subtypes. Among 210 relevant JAK-STAT pathway-related SNPs, polymorphisms in nine genes (BMF, IFNG, IL12A, SOCS1, STAT1, STAT3, STAT5A, STAT6, TP63) were significantly associated with lymphoma risk. At a study-wise significance level, we obtained a risk reduction of 28% among carriers of the heterozygous genotype of the STAT3 variant (rs1053023) for B-NHL. For six other variants within the STAT3 gene we observed an inverse association with different lymphoma subtypes. A reduced risk for HL was observed for the heterozygous genotype of the STAT6 SNP (rs324011). This is an explorative investigation to examine associations between JAK-STAT signalling related genes and lymphoma risk. The results implicate a relevant role of certain pathway-related genes in lymphomagenesis, but still need to be approved by independent studies.

Comprehensive analysis of hormone and genetic variation in 36 genes related to steroid hormone metabolism in pre- and postmenopausal women from the breast and prostate cancer cohort consortium (BPC3)

CONTEXT

Sex steroids play a central role in breast cancer development.

OBJECTIVE

This study aimed to relate polymorphic variants in 36 candidate genes in the sex steroid pathway to serum concentrations of sex steroid hormones and SHBG.

DESIGN

Data on 700 genetic polymorphisms were combined with existing hormone assays and data on breast cancer incidence, within the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Nurses' Health Study (NHS) cohorts; significant findings were reanalyzed in the Multiethnic Cohort (MEC).

SETTING AND PARTICIPANTS

We analyzed data from a pooled sample of 3852 pre- and postmenopausal Caucasian women from EPIC and NHS and 454 postmenopausal women from MEC.

MAIN OUTCOME MEASURES

Outcome measures were SHBG, testosterone, dehydroepiandrosterone (DHEAS), androstenedione, estrone (E1), and estradiol (E2) as well as breast cancer risk.

RESULTS

Globally significant associations were found among pre- and postmenopausal women combined between levels of SHBG and the SHBG gene and between DHEAS and the FSHR and AKR1C3 genes. Among postmenopausal women, serum E1 and E2 were significantly associated with the genes CYP19 and FSHR, and E1 was associated with ESR1. None of the variants related to serum hormone levels showed any significant association with breast cancer risk.

CONCLUSIONS

We confirmed associations between serum levels of SHBG and the SHBG gene and of E1 and E2 and the CYP19 and ESR1 genes. Novel associations were observed between FSHR and DHEAS, E1, and E2 and between AKR1C3 and DHEAS.

Carcinogen metabolism, cigarette smoking, and breast cancer risk: a Bayes model averaging approach

Background

Standard logistic regression with or without stepwise selection has the disadvantage of not incorporating model uncertainty and the dependency of estimates on the underlying model into the final inference. We explore the use of a Bayes Model Averaging approach as an alternative to analyze the influence of genetic variants, environmental effects and their interactions on disease.

Methods

Logistic regression with and without stepwise selection and Bayes Model Averaging were applied to a population-based case-control study exploring the association of genetic variants in tobacco smoke-related carcinogen pathways with breast cancer.

Results

Both regression and Bayes Model Averaging highlighted a significant effect of NAT1*10 on breast cancer, while regression analysis also suggested a significant effect for packyears and for the interaction of packyears and NAT2.

Conclusions

Bayes Model Averaging allows incorporation of model uncertainty, helps reduce dimensionality and avoids the problem of multiple comparisons. It can be used to incorporate biological information, such as pathway data, into the analysis. As with all Bayesian analysis methods, careful consideration must be given to prior specification.

Comprehensive analysis of common genetic variation in 61 genes related to steroid hormone and insulin-like growth factor-I metabolism and breast cancer risk in the NCI breast and prostate cancer cohort consortium

There is extensive evidence that increases in blood and tissue concentrations of steroid hormones and of insulin-like growth factor I (IGF-I) are associated with breast cancer risk. However, studies of common variation in genes involved in steroid hormone and IGF-I metabolism have yet to provide convincing evidence that such variants predict breast cancer risk. The Breast and Prostate Cancer Cohort Consortium (BPC3) is a collaboration of large US and European cohorts. We genotyped 1416 tagging single nucleotide polymorphisms (SNPs) in 37 steroid hormone metabolism genes and 24 IGF-I pathway genes in 6292 cases of breast cancer and 8135 controls, mostly Caucasian, postmenopausal women from the BPC3. We also imputed 3921 additional SNPs in the regions of interest. None of the SNPs tested was significantly associated with breast cancer risk, after correction for multiple comparisons. The results remained null when cases and controls were stratified by age at diagnosis/recruitment, advanced or nonadvanced disease, body mass index, with or without in situ cases; or restricted to Caucasians. Among 770 estrogen receptor-negative cases, an SNP located 3' of growth hormone receptor (GHR) was marginally associated with increased risk after correction for multiple testing (P(trend) = 1.5 × 10(-4)). We found no significant overall associations between breast cancer and common germline variation in 61 genes involved in steroid hormone and IGF-I metabolism in this large, comprehensive study. Although previous studies have shown that variations in these genes can influence endogenous hormone levels, the magnitude of the effect of single SNPs does not appear to be sufficient to alter breast cancer risk.

Representation of genetic association via attributable familial relative risks in order to identify polymorphisms functionally relevant to rheumatoid arthritis

The results from association studies are usually summarized by a measure of evidence of association (frequentist or Bayesian probability values) that does not directly reflect the impact of the detected signals on familial aggregation. This article investigates the possible advantage of a two-dimensional representation of genetic association in order to identify polymorphisms relevant to disease: a measure of evidence of association (the Bayes factor, BF) combined with the estimated contribution to familiality (the attributable sibling relative risk, λ_s). Simulation and data from the North American Rheumatoid Consortium (NARAC) were used to assess the possible benefit under several scenarios. Simulation indicated that the allele frequencies to reach the maximum BF and the maximum attributable λ_s diverged as the size of the genetic effect increased. The representation of BF versus attributable λ_s for selected regions of NARAC data revealed that SNPs involved in replicated associations clearly departed from the bulk of SNPs in these regions. In the 12 investigated regions, and particularly in the low-recombination major histocompatibility region, the ranking of SNPs according to BF differed from the ranking of SNPs according to attributable λ_s. The present results should be generalized using more extensive simulations and additional real data, but they suggest that a characterization of genetic association by both BF and attributable λ_s may result in an improved ranking of variants for further biological analyses.

Monitoring change of body fluids during physical exercise using bioimpedance spectroscopy

During physical exercise body muscles are activated and heat is generated. In intensive physical activity, heat will be released by sweating to protect the body of overheating. Sweating and convection implies a water loss which can lead to dehydration. To avoid health problems as a result of dehydration, the body water content can be monitored to detect changes early in order to rehydrate in time. Bioimpedance Spectroscopy (BIS) is a comfortable measurement method to monitor the body composition under controlled conditions, that is used for different applications, like monitoring dialysis. Unfortunately, the physiological changes due to sportive activities can influence the BIS and complicate the measurement. In this article, a study is presented in which the fluid content of five test persons is monitored during physical exercise, whereas all test persons did not drink anything before and during sport. During training not only the body composition was measured using a BIS device but also the skin temperature was monitored with an infrared camera. As a result, it could be shown that such a combination of measurement systems allow to use BIS devices also during sport as significant monitoring systems for detecting a person's body fluid loss.

Comparison of different haplotype-based association methods for gene-environment (GxE) interactions in case-control studies when haplotype-phase is ambiguous

OBJECTIVE

We compared four haplotype-based approaches for the analysis of gene-environment interactions when haplotype-phase is ambiguous. The methods employ different versions of the expectation maximization algorithm and differ in the choice of the reference group and in the way the risk of disease is modeled (retrospective versus prospective). Furthermore, the methods are based on distinct assumptions (such as Hardy Weinberg equilibrium). The haplotype-based methods were also compared to single-marker logistic regression (LR).

METHODS

We simulated case-control scenarios where the risk variant was directly genotyped (direct scenario) or in linkage disequilibrium with the genotyped markers (indirect scenario).

RESULTS

The retrospective methods tended to be more powerful for detecting interactions than the prospective methods. In the indirect scenarios, the power of all methods was decreased. However, the power of the retrospectives methods was high in some scenarios and the interactions may only be detectable when using these approaches. Furthermore, we observed that the precision of one prospective method was clearly lower than the precision of the retrospective methods.

CONCLUSION

For the analysis of gene-environment (GxE) interactions in case-control data, the investigated retrospective methods can be an attractive alternative to haplotype-based methods which do not account for the retrospective sampling design.

Impact of genotyping errors on the type I error rate and the power of haplotype-based association methods

Background

We investigated the influence of genotyping errors on the type I error rate and empirical power of two haplotype based association methods applied to candidate regions. We compared the performance of the Mantel Statistic Using Haplotype Sharing and the haplotype frequency based score test with that of the Armitage trend test.

Our study is based on 1000 replication of simulated case-control data settings with 500 cases and 500 controls, respectively. One of the examined markers was set to be the disease locus with a simulated odds ratio of 3. Differential and non-differential genotyping errors were introduced following a misclassification model with varying mean error rates per locus in the range of 0.2% to 15.6%.

Results

We found that the type I error rate of all three test statistics hold the nominal significance level in the presence of nondifferential genotyping errors and low error rates. For high and differential error rates, the type I error rate of all three test statistics was inflated, even when genetic markers not in Hardy-Weinberg Equilibrium were removed. The empirical power of all three association test statistics remained high at around 89% to 94% when genotyping error rates were low, but decreased to 48% to 80% for high and nondifferential genotyping error rates.

Conclusion

Currently realistic genotyping error rates for candidate gene analysis (mean error rate per locus of 0.2%) pose no significant problem for the type I error rate as well as the power of all three investigated test statistics.

Matrix metalloproteinase 1 (MMP1) is associated with early-onset lung cancer

Matrix metalloproteinases (MMP) play a key role in the breakdown of extracellular matrix and in inflammatory processes. MMP1 is the most highly expressed interstitial collagenase degrading fibrillar collagens. Overexpression of MMP1 has been shown in tumor tissues and has been suggested to be associated with tumor invasion and metastasis. Nine haplotype tagging and additional two intronic single nucleotide polymorphisms (SNP) of MMP1 were genotyped in a case control sample, consisting of 635 lung cancer cases with onset of disease below 51 years of age and 1,300 age- and sex-matched cancer-free controls. Two regions of linkage disequilibrium (LD) of MMP1 could be observed: a region of low LD comprising the 5' region including the promoter and a region of high LD starting from exon 1 to the end of the gene and including the 3' flanking region. Several SNPs were identified to be individually significantly associated with risk of early-onset lung cancer. The most significant effect was seen for rs1938901 (P = 0.0089), rs193008 (P = 0.0108), and rs996999 (P = 0.0459). For rs996999, significance vanished after correction for multiple testing. For each of these SNPs, the major allele was associated with an increase in risk with an odds ratio between 1.2 and 1.3 (95% confidence interval, 1.0-1.5). The haplotype analysis supported these findings, especially for subgroups with high smoking intensity. In summary, we identified MMP1 to be associated with an increased risk for lung cancer, which was modified by smoking.

Gene-environment interactions for complex traits: definitions, methodological requirements and challenges

Genetic and environmental risk factors and their interactions contribute to the development of complex diseases. In this review, we discuss methodological issues involved in investigating gene-environment (G x E) interactions in genetic-epidemiological studies of complex diseases and their potential relevance for clinical application. Although there are some important examples of interactions and applications, the widespread use of the knowledge about G x E interaction for targeted intervention or personalized treatment (pharmacogenetics) is still beyond current means. This is due to the fact that convincing evidence and high predictive or discriminative power are necessary conditions for usefulness in clinical practice. We attempt to clarify conceptual differences of the term 'interaction' in the statistical and biological sciences, since precise definitions are important for the interpretation of results. We argue that the investigation of G x E interactions is more rewarding for the detailed characterization of identified disease genes (ie at advanced stages of genetic research) and the stratified analysis of environmental effects by genotype or vice versa. Advantages and disadvantages of different epidemiological study designs are given and sample size requirements are exemplified. These issues as well as a critical appraisal of common methodological concerns are finally discussed.

G72 and its association with major depression and neuroticism in large population-based groups from Germany

OBJECTIVE

G72 is among the most frequently replicated vulnerability genes for schizophrenia and bipolar disorder. The authors previously found identical haplotypes of markers M23 and M24 to be associated with schizophrenia, bipolar disorder, and panic disorder. Given both the well-recognized familial clustering across these disorders and recent linkage findings implicating the region harboring G72 in the etiology of major depression and panic disorder, we can hypothesize that G72 should also be involved in the etiology of major depression. Neuroticism, measuring trait anxiety, may be the endophenotypic link underlying genetic associations with G72 across diagnostic boundaries. The authors tested whether the previously observed risk haplotypes are also associated with major depression and neuroticism.

METHOD

The authors performed a standard haplotype analysis in a group of 500 major depression patients and 1,030 population-based comparison subjects. The authors also performed an exploratory analysis on 10 additional G72 markers using a novel haplotype-sharing approach. They performed a quantitative trait haplotype analysis in an independent group of 907 individuals phenotyped for neuroticism.

RESULTS

The previously identified M23-M24 risk haplotype was significantly associated with major depression and high levels of neuroticism. The haplotype-sharing analysis also implicated the same region, whereas more proximal markers showed no association with major depression.

CONCLUSIONS

This is the first study to the authors' knowledge to implicate the G72 locus in the etiology of major depression and neuroticism. The results strengthen the notion of a genetic overlap between diagnoses, commonly conceptualized as distinct entities. Neuroticism may constitute the common underlying endophenotypic link.

Comparison of measures for haplotype similarity

Measuring the association of haplotype similarities with phenotype similarities has been used to develop statistical tests of genetic association. Previously, we applied the general approach of Mantel statistics to correlate genetic and phenotype similarity, where genetic similarity was defined by the number of intervals flanked by markers identical by state for pairs of haplotypes. Here we investigated in the case-control study design the effect on power of the Mantel statistics for five different measures of genetic similarity based on haplotypes: 1) the number of shared intervals, 2) the physical length of the shared intervals, 3) the genetic length of the shared intervals in centimorgans, 4) the genetic length of the shared intervals in linkage disequilibrium units (LDU) and 5) Yu's measure that attaches more weight to the sharing of rare than common alleles. With prior knowledge of the answers of Genetic Analysis Workshop 15 Problem 3, we analyzed the simulated data sets in two genomic regions surrounding the disease loci on chromosomes 6 and 18. For the dense map on chromosome 6, all methods showed a very high power of comparable magnitude. For chromosome 18, we observed a power between 19% and 99% at the pointwise 5% significance level using 1000 cases and 1000 controls for all methods except Yu's measure. While it yielded a much lower power, Yu's measure had 80% power around the disease locus.

Comparison of the power of haplotype-based versus single- and multilocus association methods for gene x environment (gene x sex) interactions and application to gene x smoking and gene x sex interactions in rheumatoid arthritis

Accounting for interactions with environmental factors in association studies may improve the power to detect genetic effects and may help identifying important environmental effect modifiers. The power of unphased genotype-versus haplotype-based methods in regions with high linkage disequilibrium (LD), as measured by D', for analyzing gene x environment (gene x sex) interactions was compared using the Genetic Analysis Workshop 15 (GAW15) simulated data on rheumatoid arthritis with prior knowledge of the answers. Stepwise and regular conditional logistic regression (CLR) was performed using a matched case-control sample for a HLA region interacting with sex. Haplotype-based analyses were performed using a haplotype-sharing-based Mantel statistic and a test for haplotype-trait association in a general linear model framework. A step-down minP algorithm was applied to derive adjusted p-values and to allow for power comparisons. These methods were also applied to the GAW15 real data set for PTPN22.For markers in strong LD, stepwise CLR performed poorly because of the correlation/collinearity between the predictors in the model. The power was high for detecting genetic main effects using simple CLR models and haplotype-based methods and for detecting joint effects using CLR and Mantel statistics. Only the haplotype-trait association test had high power to detect the gene x sex interaction.In the PTPN22 region with markers characterized by strong LD, all methods indicated a significant genotype x sex interaction in a sample of about 1000 subjects. The previously reported R620W single-nucleotide polymorphism was identified using logistic regression, but the haplotype-based methods did not provide any precise location information.

Joint effect between regular use of non-steroidal anti-inflammatory drugs, variants in inflammatory genes and risk of lymphoma

OBJECTIVE

Limited evidence suggests the importance of inflammatory processes for the etiology of lymphomas. To further research in this area, we investigated the role of genetic variants in key inflammatory factors, non-steroidal anti-inflammatory drug [NSAID] use, and their joint effect in lymphomagenesis.

METHODS

The study comprised 710 case-control pairs, matched for gender, age, and study region. We examined the association of regular NSAID use and polymorphisms in prostaglandin-endoperoxide synthase-2 (COX2), prostaglandin E synthase (PTGES), interleukin-1 alpha (IL1A), IL-1 beta (IL1B), and IL-1 receptor antagonist (IL1RA), and lymphoma risk by applying logistic regression to calculate odds ratios (OR) and 95% confidence intervals (95% CI).

RESULTS

Regular NSAID use was associated with a slightly reduced risk of B-NHL (OR = 0.8, 95% CI = 0.6-1.1). For T-NHL, the COX2 rs2745557 A-allele conferred a 2.2-fold (95% CI = 1.1-4.5) and homozygosis for the IL1RN rs454078 T-allele was associated with a 4.5-fold (95% CI = 1.4-13.9) elevated risk, however, based on sparse data. IL1 haplotype 5 was associated with a statistically significant 43% increased risk for B-NHL among non-regular users of NSAIDs, but a 70% decreased risk for regular users (p-value for interaction < 0.001).

CONCLUSIONS

These results suggest the relevance of joint effects between NSAID use and IL1 haplotypes on the risk of B-NHL.