Matching by OS Prognostic Score to Construct External Controls in Lung Cancer Clinical Trials.

External controls (eControls) leverage historical data to create non-randomized control arms. The lack of randomization can result in confounding between the experimental and eControl cohorts. To balance potentially confounding variables between the cohorts, one of the proposed methods is to match on prognostic scores. Still, the performance of prognostic scores to construct eControls in oncology has not been analyzed yet. Using an electronic health record-derived de-identified database, we constructed eControls using one of three methods: ROPRO, a state-of-the-art prognostic score, or either a propensity score composed of five (5Vars) or 27 covariates (ROPROvars). We compared the performance of these methods in estimating the overall survival (OS) hazard ratio (HR) of 11 recent advanced non-small cell lung cancer. The ROPRO eControls had a lower OS HR error (median absolute deviation (MAD), 0.072, confidence interval (CI): 0.036-0.185), than the 5Vars (MAD 0.081, CI: 0.025-0.283) and ROPROvars eControls (MAD 0.087, CI: 0.054-0.383). Notably, the OS HR errors for all methods were even lower in the phase III studies. Moreover, the ROPRO eControl cohorts included, on average, more patients than the 5Vars (6.54%) and ROPROvars cohorts (11.7%). The eControls matched with the prognostic score reproduced the controls more reliably than propensity scores composed of the underlying variables. Additionally, prognostic scores could allow eControls to be built on many prognostic variables without a significant increase in the variability of the propensity score, which would decrease the number of matched patients.

Correlation Between Early Trends of a Prognostic Biomarker and Overall Survival in Non-Small-Cell Lung Cancer Clinical Trials.

PURPOSE: Overall survival (OS) is the primary end point in phase III oncology trials. Given low success rates, surrogate end points, such as progression-free survival or objective response rate, are used in early go/no-go decision making. Here, we investigate whether early trends of OS prognostic biomarkers, such as the ROPRO and DeepROPRO, can also be used for this purpose. METHODS: Using real-world data, we emulated a series of 12 advanced non-small-cell lung cancer (aNSCLC) clinical trials, originally conducted by six different sponsors and evaluated four different mechanisms, in a total of 19,920 individuals. We evaluated early trends (until 6 months) of the OS biomarker alongside early OS within the joint model (JM) framework. Study-level estimates of early OS and ROPRO trends were correlated against the actual final OS hazard ratios (HRs). RESULTS: We observed a strong correlation between the JM estimates and final OS HR at 3 months (adjusted R2 = 0.88) and at 6 months (adjusted R2 = 0.85). In the leave-one-out analysis, there was a low overall prediction error of the OS HR at both 3 months (root-mean-square error [RMSE] = 0.11) and 6 months (RMSE = 0.12). In addition, at 3 months, the absolute prediction error of the OS HR was lower than 0.05 for three trials. CONCLUSION: We describe a pipeline to predict trial OS HRs using emulated aNSCLC studies and their early OS and OS biomarker trends. The method has the potential to accelerate and improve decision making in drug development.

In Vitro-In Vivo Relationship in Mini-Scale-Enabling Formulations of Corallopyronin A.

In vivo studies in mice provide a valuable model to test novel active pharmaceutical ingredients due to their low material need and the fact that mice are frequently used as a species for early efficacy models. However, preclinical in vitro evaluations of formulation principles in mice are still lacking. The development of novel in vitro and in silico models supported the preclinical formulation evaluation for the anti-infective corallopyronin A (CorA). To this end, CorA and solubility-enhanced amorphous solid dispersion formulations, comprising povidone or copovidone, were evaluated regarding biorelevant solubilities and dissolution in mouse-specific media. As an acidic compound, CorA and CorA-ASD formulations showed decreased solubilities in mice when compared with human-specific media. In biorelevant biphasic dissolution experiments CorA-povidone showed a three-fold higher fraction partitioned into the organic phase of the biphasic dissolution, when compared with CorA-copovidone. Bioavailabilities determined by pharmacokinetic studies in BALB/c mice correlated with the biphasic dissolution prediction and resulted in a Level C in vitro-in vivo correlation. In vitro cell experiments excluded intestinal efflux by P-glycoprotein or breast cancer resistance protein. By incorporating in vitro results into a physiologically based pharmacokinetic model, the plasma concentrations of CorA-ASD formulations were predicted and identified dissolution as the limiting factor for bioavailability.

Consistent Assignment of Risk and Benign Allele at rs2303153 in the CF Modifier Gene SCNN1B in Three Independent F508del-CFTR Homozygous Patient Populations.

CFTR encodes for a chloride and bicarbonate channel expressed at the apical membrane of polarized epithelial cells. Transepithelial sodium transport mediated by the amiloride-sensitive sodium channel ENaC is thought to contribute to the manifestation of CF disease. Thus, ENaC is a therapeutic target in CF and a valid cystic fibrosis modifier gene. We have characterized SCNN1B as a genetic modifier in the three independent patient cohorts of F508del-CFTR homozygotes. We could identify a regulatory element at SCNN1B to the genomic segment rs168748-rs2303153-rs4968000 by fine-mapping (Pbest = 0.0177), consistently observing the risk allele rs2303153-C and the contrasting benign allele rs2303153-G in all three patient cohorts. Furthermore, our results show that expression levels of SCNN1B are associated with rs2303153 genotype in intestinal epithelia (p = 0.003). Our data confirm that the well-established biological role of SCNN1B can be recognized by an association study on informative endophenotypes in the rare disease cystic fibrosis and calls attention to reproducible results in association studies obtained from small, albeit carefully characterized patient populations.

Artificial Intelligence for Prognostic Scores in Oncology: a Benchmarking Study.

Introduction: Prognostic scores are important tools in oncology to facilitate clinical decision-making based on patient characteristics. To date, classic survival analysis using Cox proportional hazards regression has been employed in the development of these prognostic scores. With the advance of analytical models, this study aimed to determine if more complex machine-learning algorithms could outperform classical survival analysis methods. Methods: In this benchmarking study, two datasets were used to develop and compare different prognostic models for overall survival in pan-cancer populations: a nationwide EHR-derived de-identified database for training and in-sample testing and the OAK (phase III clinical trial) dataset for out-of-sample testing. A real-world database comprised 136K first-line treated cancer patients across multiple cancer types and was split into a 90% training and 10% testing dataset, respectively. The OAK dataset comprised 1,187 patients diagnosed with non-small cell lung cancer. To assess the effect of the covariate number on prognostic performance, we formed three feature sets with 27, 44 and 88 covariates. In terms of methods, we benchmarked ROPRO, a prognostic score based on the Cox model, against eight complex machine-learning models: regularized Cox, Random Survival Forests (RSF), Gradient Boosting (GB), DeepSurv (DS), Autoencoder (AE) and Super Learner (SL). The C-index was used as the performance metric to compare different models. Results: For in-sample testing on the real-world database the resulting C-index [95% CI] values for RSF 0.720 [0.716, 0.725], GB 0.722 [0.718, 0.727], DS 0.721 [0.717, 0.726] and lastly, SL 0.723 [0.718, 0.728] showed significantly better performance as compared to ROPRO 0.701 [0.696, 0.706]. Similar results were derived across all feature sets. However, for the out-of-sample validation on OAK, the stronger performance of the more complex models was not apparent anymore. Consistently, the increase in the number of prognostic covariates did not lead to an increase in model performance. Discussion: The stronger performance of the more complex models did not generalize when applied to an out-of-sample dataset. We hypothesize that future research may benefit by adding multimodal data to exploit advantages of more complex models.

Predicting cell health phenotypes using image-based morphology profiling.

Genetic and chemical perturbations impact diverse cellular phenotypes, including multiple indicators of cell health. These readouts reveal toxicity and antitumorigenic effects relevant to drug discovery and personalized medicine. We developed two customized microscopy assays, one using four targeted reagents and the other three targeted reagents, to collectively measure 70 specific cell health phenotypes including proliferation, apoptosis, reactive oxygen species, DNA damage, and cell cycle stage. We then tested an approach to predict multiple cell health phenotypes using Cell Painting, an inexpensive and scalable image-based morphology assay. In matched CRISPR perturbations of three cancer cell lines, we collected both Cell Painting and cell health data. We found that simple machine learning algorithms can predict many cell health readouts directly from Cell Painting images, at less than half the cost. We hypothesized that these models can be applied to accurately predict cell health assay outcomes for any future or existing Cell Painting dataset. For Cell Painting images from a set of 1500+ compound perturbations across multiple doses, we validated predictions by orthogonal assay readouts. We provide a web app to browse predictions: http://broad.io/cell-health-app. Our approach can be used to add cell health annotations to Cell Painting datasets.

Deep Learning-based Propensity Scores for Confounding Control in Comparative Effectiveness Research: A Large-scale, Real-world Data Study.

BACKGROUND: Due to the non-randomized nature of real-world data, prognostic factors need to be balanced, which is often done by propensity scores (PSs). This study aimed to investigate whether autoencoders, which are unsupervised deep learning architectures, might be leveraged to compute PS. METHODS: We selected patient-level data of 128,368 first-line treated cancer patients from the Flatiron Health EHR-derived de-identified database. We trained an autoencoder architecture to learn a lower-dimensional patient representation, which we used to compute PS. To compare the performance of an autoencoder-based PS with established methods, we performed a simulation study. We assessed the balancing and adjustment performance using standardized mean differences, root mean square errors (RMSE), percent bias, and confidence interval coverage. To illustrate the application of the autoencoder-based PS, we emulated the PRONOUNCE trial by applying the trial's protocol elements within an observational database setting, comparing two chemotherapy regimens. RESULTS: All methods but the manual variable selection approach led to well-balanced cohorts with average standardized mean differences <0.1. LASSO yielded on average the lowest deviation of resulting estimates (RMSE 0.0205) followed by the autoencoder approach (RMSE 0.0248). Altering the hyperparameter setup in sensitivity analysis, the autoencoder approach led to similar results as LASSO (RMSE 0.0203 and 0.0205, respectively). In the case study, all methods provided a similar conclusion with point estimates clustered around the null (e.g., HRautoencoder 1.01 [95% confidence interval = 0.80, 1.27] vs. HRPRONOUNCE 1.07 [0.83, 1.36]). CONCLUSIONS: Autoencoder-based PS computation was a feasible approach to control for confounding but did not perform better than some established approaches like LASSO.

Prior fluid and electrolyte imbalance is associated with COVID-19 mortality.

Background: The COVID-19 pandemic represents a major public health threat. Risk of death from the infection is associated with age and pre-existing comorbidities such as diabetes, dementia, cancer, and impairment of immunological, hepatic or renal function. It remains incompletely understood why some patients survive the disease, while others do not. As such, we sought to identify novel prognostic factors for COVID-19 mortality. Methods: We performed an unbiased, observational retrospective analysis of real world data. Our multivariable and univariable analyses make use of U.S. electronic health records from 122,250 COVID-19 patients in the early stages of the pandemic. Results: Here we show that a priori diagnoses of fluid, pH and electrolyte imbalance during the year preceding the infection are associated with an increased risk of death independently of age and prior renal comorbidities. Conclusions: We propose that future interventional studies should investigate whether the risk of death can be alleviated by diligent and personalized management of the fluid and electrolyte balance of at-risk individuals during and before COVID-19.

Genetic information from discordant sibling pairs points to ESRP2 as a candidate trans-acting regulator of the CF modifier gene SCNN1B.

SCNN1B encodes the beta subunit of the epithelial sodium channel ENaC. Previously, we reported an association between SNP markers of SCNN1B gene and disease severity in cystic fibrosis-affected sibling pairs. We hypothesized that factors interacting with the SCNN1B genomic sequence are responsible for intrapair discordance. Concordant and discordant pairs differed at six SCNN1B markers (Praw = 0.0075, Pcorr = 0.0397 corrected for multiple testing). To identify the factors binding to these six SCNN1B SNPs, we performed an electrophoretic mobility shift assay and captured the DNA-protein complexes. Based on protein mass spectrometry data, the epithelial splicing regulatory protein ESRP2 was identified when using SCNN1B-derived probes and the ESRP2-SCNN1B interaction was independently confirmed by coimmunoprecipitation assays. We observed an alternative SCNN1B transcript and demonstrated in 16HBE14o- cells that levels of this transcript are decreased upon ESRP2 silencing by siRNA. Furthermore, we confirmed that mildly and severely affected siblings have different ESPR2 genetic backgrounds and that ESRP2 markers are linked to the response of CF patients' nasal epithelium to amiloride, indicating ENaC involvement (Pbest = 0.0131, Pcorr = 0.068 for multiple testing). Our findings demonstrate that sibling pairs clinically discordant for CF can be used to identify meaningful DNA regulatory elements and interacting factors.

Tumstatin fragment selectively inhibits neutrophil infiltration in experimental asthma exacerbation.

BACKGROUND: Asthma is a chronic inflammatory disease with structural changes present. Burgess and colleagues recently found tumstatin markedly reduced in adult asthmatic lung tissue compared with nonasthmatics. ECM fragments such as tumstatin are named matrikines and act independently of the parent molecule. The role of Col IV matrikines in neutrophil inflammation (eg. exacerbation in asthma) has not been investigated to date. Severe adult asthma phenotypes are dominated by neutrophilic inflammation and show a high frequency of severe exacerbations. OBJECTIVE: This study sought to investigate the role of a novel active region within tumstatin (CP17) and its implication in neutrophil inflammatory responses related to asthma exacerbation. METHODS: For reactive oxygen production, isolated neutrophils were preincubated with peptides or vehicle for 1 hour and stimulated (PMA). Luminescence signal was recorded (integration over 10 seconds) for 1.5 hours. Neutrophil migration was performed according to the SiMA protocol. Mice were sensitized to OVA/Alumn by intraperitoneal (i.p.) injections. Mice were then treated with CP17, vehicle (PBS) or scrambled peptide (SP17) after OVA exposure (days 27 and 28, polyI:C stimulation). All animals were killed on day 29 with lung function measurement, histology and lavage. RESULTS: CP17 decreased total ROS production rate to 52.44% (0.5 µmol/L, P < 0.05 vs SP17), reduced the in vitro directionality (vs SP17, P = 1 × 10-6 ) and migration speed (5 µmol/L, P = 1 × 10-3 ). In vivo application of CP17 decreased neutrophil inflammation ~1.8-fold (P < 0.001 vs SP17) and reduced numbers of mucus-producing cells (-29%, P < 0.05). CONCLUSION: CP17 reduced the ROS production rate, migrational speed and selectively inhibited neutrophil accumulation in the lung interstitium and lumen. CLINICAL RELEVANCE: CP17 may serve as a potential precursor for drug development to combat overwhelming neutrophil inflammation.

Single nucleotide polymorphisms in the angiogenic and lymphangiogenic pathways are associated with lymphedema caused by Wuchereria bancrofti.

BACKGROUND: Lymphedema (LE) is a chronic clinical manifestation of filarial nematode infections characterized by lymphatic dysfunction and subsequent accumulation of protein-rich fluid in the interstitial space-lymphatic filariasis. A number of studies have identified single nucleotide polymorphisms (SNPs) associated with primary and secondary LE. To assess SNPs associated with LE caused by lymphatic filariasis, a cross-sectional study of unrelated Ghanaian volunteers was designed to genotype SNPs in 285 LE patients as cases and 682 infected patients without pathology as controls. One hundred thirty-one SNPs in 64 genes were genotyped. The genes were selected based on their roles in inflammatory processes, angiogenesis/lymphangiogenesis, and cell differentiation during tumorigenesis. RESULTS: Genetic associations with nominal significance were identified for five SNPs in three genes: vascular endothelial growth factor receptor-3 (VEGFR-3) rs75614493, two SNPs in matrix metalloprotease-2 (MMP-2) rs1030868 and rs2241145, and two SNPs in carcinoembryonic antigen-related cell adhesion molecule-1 (CEACAM-1) rs8110904 and rs8111171. Pathway analysis revealed an interplay of genes in the angiogenic/lymphangiogenic pathways. Plasma levels of both MMP-2 and CEACAM-1 were significantly higher in LE cases compared to controls. Functional characterization of the associated SNPs identified genotype GG of CEACAM-1 as the variant influencing the expression of plasma concentration, a novel finding observed in this study. CONCLUSION: The SNP associations found in the MMP-2, CEACAM-1, and VEGFR-3 genes indicate that angiogenic/lymphangiogenic pathways are important in LE clinical development.

Tumstatin regulates the angiogenic and inflammatory potential of airway smooth muscle extracellular matrix.

The extracellular matrix (ECM) creates the microenvironment of the tissue; an altered ECM in the asthmatic airway may be central in airway inflammation and remodelling. Tumstatin is a collagen IV-derived matrikine reduced in the asthmatic airway wall that reverses airway inflammation and remodelling in small and large animal models of asthma. This study hypothesized that the mechanisms underlying the broad asthma-resolving effects of tumstatin were due to autocrine remodelling of the ECM. Neutrophils and endothelial cells were seeded on decellularized ECM of non-asthmatic (NA) or asthmatic (A) airway smooth muscle (ASM) cells previously exposed to tumstatin in the presence or absence of a broad matrix metalloproteinase inhibitor, Marimastat. Gene expression in NA and A ASM induced by tumstatin was assessed using RT-PCR arrays. The presence of tumstatin during ECM deposition affected neutrophil and endothelial cell properties on both NA and A ASM-derived matrices and this was only partly due to MMP activity. Gene expression patterns in response to tumstatin in NA and A ASM cells were different. Tumstatin may foster an anti-inflammatory and anti-angiogenic microenvironment by modifying ASM-derived ECM. Further work is required to examine whether restoring tumstatin levels in the asthmatic airway represents a potential novel therapeutic approach.

Meta-analysis identifies novel risk loci and yields systematic insights into the biology of male-pattern baldness.

Male-pattern baldness (MPB) is a common and highly heritable trait characterized by androgen-dependent, progressive hair loss from the scalp. Here, we carry out the largest GWAS meta-analysis of MPB to date, comprising 10,846 early-onset cases and 11,672 controls from eight independent cohorts. We identify 63 MPB-associated loci (P<5 × 10-8, METAL) of which 23 have not been reported previously. The 63 loci explain ∼39% of the phenotypic variance in MPB and highlight several plausible candidate genes (FGF5, IRF4, DKK2) and pathways (melatonin signalling, adipogenesis) that are likely to be implicated in the key-pathophysiological features of MPB and may represent promising targets for the development of novel therapeutic options. The data provide molecular evidence that rather than being an isolated trait, MPB shares a substantial biological basis with numerous other human phenotypes and may deserve evaluation as an early prognostic marker, for example, for prostate cancer, sudden cardiac arrest and neurodegenerative disorders.

Exome sequencing identifies potential novel candidate genes in patients with unexplained colorectal adenomatous polyposis.

In up to 30% of patients with colorectal adenomatous polyposis, no germline mutation in the known genes APC, causing familial adenomatous polyposis, MUTYH, causing MUTYH-associated polyposis, and POLE or POLD1, causing Polymerase-Proofreading-associated polyposis can be identified, although a hereditary etiology is likely. To uncover new causative genes, exome sequencing was performed using DNA from leukocytes and a total of 12 colorectal adenomas from seven unrelated patients with unexplained sporadic adenomatous polyposis. For data analysis and variant filtering, an established bioinformatics pipeline including in-house tools was applied. Variants were filtered for rare truncating point mutations and copy-number variants assuming a dominant, recessive, or tumor suppressor model of inheritance. Subsequently, targeted sequence analysis of the most promising candidate genes was performed in a validation cohort of 191 unrelated patients. All relevant variants were validated by Sanger sequencing. The analysis of exome sequencing data resulted in the identification of rare loss-of-function germline mutations in three promising candidate genes (DSC2, PIEZO1, ZSWIM7). In the validation cohort, further variants predicted to be pathogenic were identified in DSC2 and PIEZO1. According to the somatic mutation spectra, the adenomas in this patient cohort follow the classical pathways of colorectal tumorigenesis. The present study identified three candidate genes which might represent rare causes for a predisposition to colorectal adenoma formation. Especially PIEZO1 (FAM38A) and ZSWIM7 (SWS1) warrant further exploration. To evaluate the clinical relevance of these genes, investigation of larger patient cohorts and functional studies are required.

Low-level APC mutational mosaicism is the underlying cause in a substantial fraction of unexplained colorectal adenomatous polyposis cases.

BACKGROUND: In 30-50% of patients with colorectal adenomatous polyposis, no germline mutation in the known genes APC, causing familial adenomatous polyposis, MUTYH, causing MUTYH-associated polyposis, or POLE or POLD1, causing polymerase-proofreading-associated polyposis can be identified, although a hereditary aetiology is likely. This study aimed to explore the impact of APC mutational mosaicism in unexplained polyposis. METHODS: To comprehensively screen for somatic low-level APC mosaicism, high-coverage next-generation sequencing of the APC gene was performed using DNA from leucocytes and a total of 53 colorectal tumours from 20 unrelated patients with unexplained sporadic adenomatous polyposis. APC mosaicism was assumed if the same loss-of-function APC mutation was present in ≥ 2 anatomically separated colorectal adenomas/carcinomas per patient. All mutations were validated using diverse methods. RESULTS: In 25% (5/20) of patients, somatic mosaicism of a pathogenic APC mutation was identified as underlying cause of the disease. In 2/5 cases, the mosaic level in leucocyte DNA was slightly below the sensitivity threshold of Sanger sequencing; while in 3/5 cases, the allelic fraction was either very low (0.1-1%) or no mutations were detectable. The majority of mosaic mutations were located outside the somatic mutation cluster region of the gene. CONCLUSIONS: The present data indicate a high prevalence of pathogenic mosaic APC mutations below the detection thresholds of routine diagnostics in adenomatous polyposis, even if high-coverage sequencing of leucocyte DNA alone is taken into account. This has important implications for both routine work-up and strategies to identify new causative genes in this patient group.

Evaluation of a supervised multi-modal physical exercise program for prostate cancer survivors in the rehabilitation phase: Rationale and study protocol of the ProCaLife study.

BACKGROUND: After treatment for localized prostate cancer, many survivors experience severe physical and psychological/psychosocial impairments, such as urinary incontinence, erectile dysfunction, fatigue, depressive symptoms and decreased physical functioning. Physical activity and exercise can positively influence such side effects and improve quality of life. However, the majority of prostate cancer survivors are not physically active. Thus, supportive interventions, such as supervised exercise programs, are necessary. But particularly in the post-treatment phase, infrastructure and resources are limited and specific exercise recommendations for prostate cancer survivors do not yet exist. METHODS/DESIGN: The ProCaLife study is a quasi-randomized controlled intervention trial evaluating a specific 26-week physical exercise program for prostate cancer survivors in the rehabilitation phase following medical treatment. Participants are assigned to one of two intervention groups (supervised multi-modal physical exercise including or not including further behavior-oriented techniques) or a control group (not receiving any supervised intervention). Exercise sessions are performed twice weekly and contain specific aerobic, strengthening, flexibility, balance, relaxation and pelvic floor/sphincter exercises as well as mixed games. Behavior-oriented techniques include physical activity-related knowledge transfer and barriers management. The primary endpoint quality of life and secondary psychological/psychosocial, urological, physical fitness and physical activity outcomes are assessed at pre-intervention, post-intervention and follow-up time points. DISCUSSION/CONCLUSION: By evaluating a specific supervised multi-modal physical exercise program, the ProCaLife study contributes to identify effective forms of physical exercise for prostate cancer survivors in the rehabilitation phase. This is of great importance for establishing specific exercise recommendations which are missing so far.

Highly robust transparent and conductive gas diffusion barriers based on tin oxide.

Transparent and electrically conductive gas diffusion barriers are reported. Tin oxide (SnOx ) thin films grown by atomic layer deposition afford extremely low water vapor transmission rates (WVTR) on the order of 10(-6) g (m(2) day)(-1) , six orders of magnitude better than that established with ITO layers. The electrical conductivity of SnOx remains high under damp heat conditions (85 °C/85% relative humidity (RH)), while that of ZnO quickly degrades by more than five orders of magnitude.

Genome-wide meta-analysis in alopecia areata resolves HLA associations and reveals two new susceptibility loci.

Alopecia areata (AA) is a prevalent autoimmune disease with 10 known susceptibility loci. Here we perform the first meta-analysis of research on AA by combining data from two genome-wide association studies (GWAS), and replication with supplemented ImmunoChip data for a total of 3,253 cases and 7,543 controls. The strongest region of association is the major histocompatibility complex, where we fine-map four independent effects, all implicating human leukocyte antigen-DR as a key aetiologic driver. Outside the major histocompatibility complex, we identify two novel loci that exceed the threshold of statistical significance, containing ACOXL/BCL2L11(BIM) (2q13); GARP (LRRC32) (11q13.5), as well as a third nominally significant region SH2B3(LNK)/ATXN2 (12q24.12). Candidate susceptibility gene expression analysis in these regions demonstrates expression in relevant immune cells and the hair follicle. We integrate our results with data from seven other autoimmune diseases and provide insight into the alignment of AA within these disorders. Our findings uncover new molecular pathways disrupted in AA, including autophagy/apoptosis, transforming growth factor beta/Tregs and JAK kinase signalling, and support the causal role of aberrant immune processes in AA.

The CF-modifying gene EHF promotes p.Phe508del-CFTR residual function by altering protein glycosylation and trafficking in epithelial cells.

The three-base-pair deletion c.1521_1523delCTT (p.Phe508del, F508del) in the cystic fibrosis transmembrane conductance regulator (CFTR) is the most frequent disease-causing lesion in cystic fibrosis (CF). The CFTR gene encodes a chloride and bicarbonate channel at the apical membrane of epithelial cells. Altered ion transport of CFTR-expressing epithelia can be used to differentiate manifestations of the so-called CF basic defect. Recently, an 11p13 region has been described as a CF modifier by the North American CF Genetic Modifier Study Consortium. Selecting the epithelial-specific transcription factor EHF (ets homologous factor) as the likely candidate gene on 11p13, we have genotyped two intragenic microsatellites in EHF to replicate the 11p13 finding in the patient cohort of the European CF Twin and Sibling Study. We could observe an association of rare EHF haplotypes among homozygotes for c.1521_1523delCTT in CFTR, which exhibit a CF-untypical manifestation of the CF basic defect such as CFTR-mediated residual chloride secretion and low response to amiloride. We have reviewed transcriptome data obtained from intestinal epithelial samples of homozygotes for c.1521_1523delCTT in CFTR, which were stratified for their EHF genetic background. Transcripts that were upregulated among homozygotes for c.1521_1523delCTT in CFTR, who carry two rare EHF alleles, were enriched for genes that alter protein glycosylation and trafficking, both mechanisms being pivotal for the effective targeting of fully functional p.Phe508del-CFTR to the apical membrane of epithelial cells. We conclude that EHF modifies the CF phenotype by altering capabilities of the epithelial cell to correctly process the folding and trafficking of mutant p.Phe508del-CFTR.

Investigation of four novel male androgenetic alopecia susceptibility loci: no association with female pattern hair loss.

Female pattern hair loss (FPHL) is a common hair loss disorder in women and has a complex mode of inheritance. The etiopathogenesis of FPHL is largely unknown; however, it is hypothesized that FPHL and male pattern baldness [androgenetic alopecia (AGA)] share common genetic susceptibility alleles. Our recent findings indicate that the major AGA locus, an X-chromosome region containing the androgen receptor and the ectodysplasin A2 receptor (EDA2R) genes, may represent a common genetic factor underlying both early-onset FPHL and AGA. This gives further support for the widespread assumption of shared susceptibility loci for FPHL and AGA. However, we could not demonstrate association of further AGA risk loci, including 20p11, 1p36.22, 2q37.3, 7p21.1, 7q11.22, 17q21.31, and 18q21.1, with FPHL. Interestingly, a recent study identified four novel AGA risk loci in chromosomal regions 2q35, 3q25.1, 5q33.3, and 12p12.1. In particular, the 2q35 locus and its gene WNT10A point to an as-yet unknown involvement of the WNT signaling pathway in AGA. We hypothesized that the novel loci and thus also the WNT signaling may have a role in the etiopathogenesis of FPHL and therefore examined the role of these novel AGA risk loci in our FPHL samples comprising 440 German and 145 UK affected patients, 500 German unselected controls (blood donors), and 179 UK supercontrols. Patients and controls were genotyped for the top two single nucleotide polymorphisms at each of the four AGA loci. However, none of the genotyped variants displayed any significant association. In conclusion, the results of this study provide no support for the hypothesis that the novel AGA loci influence susceptibility to FPHL.