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Background: Biopharmaceutical products (BPs) are widely used to treat autoimmune diseases, but immunogenicity limits their efficacy for an important proportion of patients. Our knowledge of patient-related factors influencing the occurrence of antidrug antibodies (ADAs) is still limited., Methods and Findings: The European consortium ABIRISK (Anti-Biopharmaceutical Immunization: prediction and analysis of clinical relevance to minimize the RISK) conducted a clinical and genomic multicohort prospective study of 560 patients with multiple sclerosis (MS, n = 147), rheumatoid arthritis (RA, n = 229), Crohn's disease (n = 148), or ulcerative colitis (n = 36) treated with 8 different biopharmaceuticals (etanercept, n = 84; infliximab, n = 101; adalimumab, n = 153; interferon [IFN]-beta-1a intramuscularly [IM], n = 38; IFN-beta-1a subcutaneously [SC], n = 68; IFN-beta-1b SC, n = 41; rituximab, n = 31; tocilizumab, n = 44) and followed during the first 12 months of therapy for time to ADA development. From the bioclinical data collected, we explored the relationships between patient-related factors and the occurrence of ADAs. Both baseline and time-dependent factors such as concomitant medications were analyzed using Cox proportional hazard regression models. Mean age and disease duration were 35.1 and 0.85 years, respectively, for MS; 54.2 and 3.17 years for RA; and 36.9 and 3.69 years for inflammatory bowel diseases (IBDs). In a multivariate Cox regression model including each of the clinical and genetic factors mentioned hereafter, among the clinical factors, immunosuppressants (adjusted hazard ratio [aHR] = 0.408 [95% confidence interval (CI) 0.253-0.657], p < 0.001) and antibiotics (aHR = 0.121 [0.0437-0.333], p < 0.0001) were independently negatively associated with time to ADA development, whereas infections during the study (aHR = 2.757 [1.616-4.704], p < 0.001) and tobacco smoking (aHR = 2.150 [1.319-3.503], p < 0.01) were positively associated. 351,824 Single-Nucleotide Polymorphisms (SNPs) and 38 imputed Human Leukocyte Antigen (HLA) alleles were analyzed through a genome-wide association study. We found that the HLA-DQA1*05 allele significantly increased the rate of immunogenicity (aHR = 3.9 [1.923-5.976], p < 0.0001 for the homozygotes). Among the 6 genetic variants selected at a 20% false discovery rate (FDR) threshold, the minor allele of rs10508884, which is situated in an intron of the CXCL12 gene, increased the rate of immunogenicity (aHR = 3.804 [2.139-6.764], p < 1 × 10-5 for patients homozygous for the minor allele) and was chosen for validation through a CXCL12 protein enzyme-linked immunosorbent assay (ELISA) on patient serum at baseline before therapy start. CXCL12 protein levels were higher for patients homozygous for the minor allele carrying higher ADA risk (mean: 2,693 pg/ml) than for the other genotypes (mean: 2,317 pg/ml; p = 0.014), and patients with CXCL12 levels above the median in serum were more prone to develop ADAs (aHR = 2.329 [1.106-4.90], p = 0.026). A limitation of the study is the lack of replication; therefore, other studies are required to confirm our findings., Conclusion: In our study, we found that immunosuppressants and antibiotics were associated with decreased risk of ADA development, whereas tobacco smoking and infections during the study were associated with increased risk. We found that the HLA-DQA1*05 allele was associated with an increased rate of immunogenicity. Moreover, our results suggest a relationship between CXCL12 production and ADA development independent of the disease, which is consistent with its known function in affinity maturation of antibodies and plasma cell survival. Our findings may help physicians in the management of patients receiving biotherapies., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: SH, DB, JD, NS, AG, MB, DBM, NDV, ND, AD, SHBH, HPH, KI, PEHJ, ECJ, BK, AL, RL, AL, EM, CM, BMO, MR, FS, CS, DS, PD, AHM, MP, and PB declare no conflict of interest. OA reports grants and personal fees from Bayer HealthCare, Biogen, Genzyme, Novartis, Teva and Viela Bio, and personal fees from Almirall, MedImmune, Merck Serono, and Roche. MA received speaker honoraria and/or travel grants from Biogen, Novartis, Merck Serono, and Sanofi. JA has served on scientific advisory boards for Roche, BMS, Abbvie, Nordic, Boerhinger, and Sanofi-Genzyme; he has received speaking honoraria from Pfizer, MSD, BMS, and Novartis; and he has received research grants from BMS and Pfizer. YB received speaker honoraria from Abbvie, Biogaran, Biogen, Boehringer Ingelheim, Ferring, Fresenius Kabi, Gilead, Hospira, Janssen, Lilly, Mayoli Spindler, Merck, MSD, Norgine, Pfizer, Roche, Sandoz, Sanofi, Shire, Takeda, and UCB. OB has received institutional fees for consultancy or lectures from Wyeth/Pfizer, AbBVIE, Roche, Chugai, Shering Plough, UCB, Swedish Orphan, Genevrier, Smith & Nephew, BMS, MSD, Celgene, novartis, Janssen, Sanofi, and Lilly. GC participated in advisory boards with AAA, Kéocyt, Ipsen, Novartis, Pfizer; he received honoraria for lectures from Ferring, Abbvie, Janssen,Biogen, Amgen, and Sandoz. YC has received institutional fees for consultancy or lectures from Abbvie, Celtrion, Getting, Pfizer, and Takeda. He received research grants from Takeda and Abbvie. MC has received compensation for consulting services and speaking honoraria from Bayer Schering Pharma, Merk Serono, Biogen-Idec, Teva Pharmaceuticals, Sanofi-Aventis, Genzyme, and Novartis. TD’s institution received compensation for his talks and his consultation services on Advisory Boards or Steering Committees of Novartis Pharma, Merck, Biogen, GeNeuro, Mitsubishi Pharma, MedDay, Roche, Actelion, Celgene, and Genzyme; his institution received research support from Biogen, Novartis, and Roche. MG received support and honoraria for research, consultation, lectures and education from Almirall, Bayer, Biogen, Celgene, Genzyme, MedDay, Merck, Novartis, Octapharma, Roche, Sanofi Aventis, Shire and TEVA ratiopharm. EKH: honoraria/research support from Biogen, Merck Serono, Novartis, Roche, and Teva; advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novartis, and Sanofi Genzyme. BH has served on scientific advisory boards for Novartis; he has served as DMSC member for AllergyCare and TG therapeutics; he or his institution have received speaker honoraria from Desitin; he holds part of two patents, one for the detection of antibodies against KIR4.1 in a subpopulation of MS patients and one for genetic determinants of neutralizing antibodies to interferon. All conflicts are not relevant to the topic of the study. TH is a member of the Editorial Board of PLOS Medicine. MK has received funding for travel and speaker honoraria from Bayer, Novartis, Merck, Biogen, Roche, and Teva ratiopharm; serves on scientific advisory boards for Biogen, Merck, and Roche; and received a research grant from Teva ratiopharm. JM has received an unrestricted research grant from Pfizer. XM has received speaking honoraria and travel expenses for scientific meetings and has been a steering committee member of clinical trials or participated in advisory boards of clinical trials in the past years with Bayer Schering Pharma, Biogen Idec, EMD Merck Serono, Genentech, Genzyme, Novartis, Sanofi-Aventis, Teva Phramaceuticals, Almirall, and Roche. MN has received speaking honoraria from Abbvie, Adacyte, Amgen, Biogen, Ferring, Janssen, MSD, and Takeda. PN has received speaking honoraria from Biogen, Novartis, and Roche. CR has received speaking honoraria from Abbvie, Amgen, Astra Zeneca, Janssen, Glenmark, GSK, Lilly, Nordic Pharma, Novartis, Pfizer, and UCB. MS received speaker honoraria and/or travel grants from Roche, Chugai, Abbvie, BMS, UCB, Pfizer, Novartis, Janssen, Amgen, Biogen, laboratoires Fresenius, Lilly France, Medac, MSD, Sandoz, and Janssen. CT has received speaking honoraria from Abbvie, Ferring, Janssen, MSD, and Takeda. AV has received fee for lectures and advisory board from GSK, Novartis, and AstraZeneca in the last two years. CW has received institutional fees for consultancy, speaking, or research from Novartis, Biogen, Sanofi-Genzyme and Roche. SS is a former employee and has stocks and/or stock options in Novartis. TPH is an employee and shareholder of Pfizer Inc. MA has served on scientific advisory boards for Pfizer, Janssen, Celgene, Genentech/Roche, Takeda, Abbvie, MSD, Ferring, Falk, Mayoli, Tillots, Biogen, and Amgen. FD has participated in meetings sponsored by or received honoraria for acting as an advisor/speaker for Alexion, Almirall, Biogen, Celgene, Genzyme-Sanofi, Merck, Novartis Pharma, and Roche. His institution has received research grants from Biogen and Genzyme Sanofi. He is section editor of the MSARD Journal (Multiple Sclerosis and Related Disorders). AFH has received speaker's fees from Pfizer, Biogen, Merck-Serono, and Sanofi-Genzyme. She has served as prinicipal investigator for projects, or received unrestricted research support from, Biogen Idec and Pfizer. XM has served on scientific advisory boards for BMS, GSK, Janssen, Novartis, Pfizer, and UCB.

Introduction: Studies in the general population suggest that determinants of QoL are often sex-dependent. Sex-dependent analyses of QoL in transgender populations have not been performed so far., Aim: To identify sex-specific and potentially modifiable determinants of QoL in transgender patients., Methods: In this cross-sectional multicentre study including 82 transwomen (TW) and 72 transmen (TM) at different treatment stages, we investigated potential determinants for QoL focusing on the impact of mood (BDI, STAI-X), sleep quality (PSQI), chronic pain (GPQ), body image (FBeK) and social support (SSS)., Main Outcome Measure: Health-related quality of life measured with the Short Form (36) Health Survey (SF-36)., Results: The age-adjusted SF-36 total score and its subscales did not significantly differ between TM and TW. Using a multivariate regression analysis approach, we identified common but also sex-dependent determinants for QoL (Adjusted R2 = 0.228; 0.650 respectively). Accounting for general characteristics such as age, BMI and treatment status, sleep quality according to the PSQI was an independent and strong determinant of QoL in both sexes (β = -0.451, p = 0.003 TM; β = -0.320; p = 0.0029 TW). Chronic pain was a significant independent predictor of QoL in TM (β = -0.298; p = 0.042) but not in TW. In contrast, anxiety (β = -0.451; p< 0.001) being unemployed (β = -0.206; p = 0.020) and insecurity about the own appearance (FBeK) (β = -0.261; p = 0.01) were independent predictors of QoL in TW. The rate of those reporting high sleep disturbances (PSQI ≥5) was high with 79.2% in TW and 81.2% in TM. Accordingly, age-adjusted QoL was also significantly lower in those reporting poor sleep in both sexes., Conclusions: Sleep strongly affected QoL in both genders, while other factors, like pain and body image, seem to be gender specific in transgender individuals.

Antibodies against biopharmaceuticals (anti-drug antibodies, ADA) have been a well-integrated part of the clinical care of multiple sclerosis (MS) in several European countries. ADA data generated in Europe during the more than 10 years of ADA monitoring in MS patients treated with interferon beta (IFNβ) and natalizumab have been pooled and characterized through collaboration within a European consortium. The aim of this study was to report on the clinical practice of ADA testing in Europe, considering the number of ADA tests performed and type of ADA assays used, and to determine the frequency of ADA testing against the different drug preparations in different countries. A common database platform (tranSMART) for querying, analyzing and storing retrospective data of MS cohorts was set up to harmonize the data and compare results of ADA tests between different countries. Retrospective data from six countries (Sweden, Austria, Spain, Switzerland, Germany and Denmark) on 20,695 patients and on 42,555 samples were loaded into tranSMART including data points of age, gender, treatment, samples, and ADA results. The previously observed immunogenic difference among the four IFNβ preparations was confirmed in this large dataset. Decreased usage of the more immunogenic preparations IFNβ-1a subcutaneous (s.c.) and IFNβ-1b s.c. in favor of the least immunogenic preparation IFNβ-1a intramuscular (i.m.) was observed. The median time from treatment start to first ADA test correlated with time to first positive test. Shorter times were observed for IFNβ-1b-Extavia s.c. (0.99 and 0.94 years) and natalizumab (0.25 and 0.23 years), which were introduced on the market when ADA testing was already available, as compared to IFNβ-1a i.m. (1.41 and 2.27 years), IFNβ-1b-Betaferon s.c. (2.51 and 1.96 years) and IFNβ-1a s.c. (2.11 and 2.09 years) which were available years before routine testing began. A higher rate of anti-IFNβ ADA was observed in test samples taken from older patients. Testing for ADA varies between different European countries and is highly dependent on the policy within each country. For drugs where routine monitoring of ADA is not in place, there is a risk that some patients remain on treatment for several years despite ADA positivity. For drugs where a strategy of ADA testing is introduced with the release of the drug, there is a reduced risk of having ADA positive patients and thus of less efficient treatment. This indicates that potential savings in health cost might be achieved by routine analysis of ADA., Competing Interests: J. Link, M. Auer, R. Ramanujam, S. Haässler, D. Bachelet, C. Mbogning, P.E. Hyldgaard Jensen, C. Sievers, K. Ingenhoven, N. Fissolo, V. Grummel, M. Pallardy, P. Broeët: have nothing to disclose. M. Ryner: has received research support from Biogen Idec and Sanofi-Aventis, and received speaker honoraria from Biogen Idec. C. Warnke: has received honoraria for consulting from Novartis, Biogen, Bayer and TEVA. D. Buck: has received compensation for activities with Bayer HealthCare, Biogen Idec, MerckSerono, and Novartis and she is supported by the ABIRISK Consortium. R. Lindberg: has received research support from the Swiss MS Society, Swiss National Science Foundation, European FP6 and IMI JU programs, Roche Postdoc Fellowship Program (RPF-program), unrestricted research grants from Novartis and Biogen. M Comabella: has received compensation for consulting services and speaking honoraria from Bayer Schering Pharma, Merk Serono, Biogen-Idec, Teva Pharmaceuticals, Sanofi-Aventis, Genzyme, and Novartis. X. Montalban: has received speaking honoraria and travel expenses for scientific meetings, has been a steering committee member of clinical trials or participated in advisory boards of clinical trials in the past years with Bayer Schering Pharma, Biogen Idec, EMD Merck Serono, Genentech, Genzyme, Novartis, Sanofi-Aventis, Teva Pharmaceuticals, Almirall and Roche. B. Kieseier has received honoraria for lecturing, travel expenses for attending meetings, and financial support for research from Bayer Health Care, Biogen Idec, Genzyme/Sanofi Aventis, Grifols, Merck Serono, Mitsubishi Europe, Novartis, Roche, Talecris, and TEVA. P. S. Sørensen: has served on scientific advisory boards for Biogen Idec, Merck Serono, Novartis, Genzyme, Teva Pharmaceutical Industries Ltd., GlaxoSmithKline, medDay Pharmaceuticals and Forward Pharma; has been on steering committees or independent data monitoring boards in clinical trials sponsored by Merck Serono, Teva Pharmaceutical Industries Ltd., and GlaxoSmithKline; and has received speaker honoraria from Biogen Idec, Merck Serono, Teva Pharmaceutical Industries Ltd., Genzyme, and Novartis. His department has received research support from Biogen Idec, Bayer Schering, Merck Serono, TEVA, Baxter, Sanofi-Aventis, BioMS, Novartis, Bayer, RoFAR, Roche, Genzyme, from the Danish Multiple Sclerosis Society, the Danish Medical Research Council, and the European Union Sixth Framework Programme: Life sciences, Genomics and Biotechnology for health. H-P. Hartung: has received honoraris for consulting, serving on steering committees and speaking from Biogen, GeNeuro, Genzyme, Merck, Novartis, Opexa, Receptos, Roche, Sanofi, Teva with approval by the president of Heinrich-Heine University. T. Derfuss: serves on scientific advisory boards for Novartis Pharmaceuticals, Merck Serono, Biogen Idec, Genzyme, GeNeuro, Mitsubishi Pharma, Teva Pharmaceuticals and Bayer Schering Pharma; has received funding for travel and/or speaker honoraria from Biogen Idec, Genzyme, Novartis, Merck Serono and Bayer Schering Pharma; and receives research support from Biogen Idec, Novartis Pharma, the European Union, the Swiss National Foundation and the Swiss MS Society. B. Hemmer: has served on scientific advisory boards for Roche, Novartis, Bayer Schering, Merck Serono, Biogen Idec, GSK, Chugai Pharmaceuticals, Micromet, Genentech and Genzyme Corporation; serves on the international advisory board of Archives of Neurology and Experimental Neurology; has received speaker honoraria from Bayer Schering, Novartis, Biogen Idec, Merck Serono, Roche, and Teva Pharmaceutical Industries Ltd.; and has received research support from Biogen Idec, Bayer Schering, Merck Serono, Five prime, Metanomics, Chugai Pharmaceuticals and Novartis. He has filed a patent for the detection of antibodies and T cells against KIR4.1 in a subpopulation of MS patients and genetic determinants of neutralizing antibodies to interferon-beta. F. Deisenhammer: participated in meetings sponsored by or received honoraria for acting as an advisor/speaker for Bayer Healthcare, Biogen Idec, Genzyme-Sanofi, Merck, Novartis Pharma, and Roche. A. Fogdell-Hahn: has received funding and speaking honoraria from Biogen Idec and Pfizer. A. Lawton is employed by GlaxoSmithKline. At the time of writing D. Sikkema and J. Davidson were employed by GlaxoSmithKline, in which J. Davidson also held stocks/shares. N. Donnellan is employed by IPSEN. P. Doönnes is an employee of SciCross AB and has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115303, resources of which are composed of financial contribution from the European Union's Seventh Framework Program (FP7/2007–2013) and EFPIA companies' in kind contribution. All the company-employed authors declare that this does not alter their adherence to PLOS ONE policies on sharing data and materials.

Objective: Sexual orientation is usually considered to be determined in early life and stable in the course of adulthood. In contrast, some transgender individuals report a change in sexual orientation. A common reason for this phenomenon is not known., Methods: We included 115 transsexual persons (70 male-to-female "MtF" and 45 female-to-male "FtM") patients from our endocrine outpatient clinic, who completed a questionnaire, retrospectively evaluating the history of their gender transition phase. The questionnaire focused on sexual orientation and recalled time points of changes in sexual orientation in the context of transition. Participants were further asked to provide a personal concept for a potential change in sexual orientation., Results: In total, 32.9% (n = 23) MtF reported a change in sexual orientation in contrast to 22.2% (n = 10) FtM transsexual persons (p = 0.132). Out of these patients, 39.1% (MtF) and 60% (FtM) reported a change in sexual orientation before having undergone any sex reassignment surgery. FtM that had initially been sexually oriented towards males ( = androphilic), were significantly more likely to report on a change in sexual orientation than gynephilic, analloerotic or bisexual FtM (p = 0.012). Similarly, gynephilic MtF reported a change in sexual orientation more frequently than androphilic, analloerotic or bisexual MtF transsexual persons (p =0.05)., Conclusion: In line with earlier reports, we reveal that a change in self-reported sexual orientation is frequent and does not solely occur in the context of particular transition events. Transsexual persons that are attracted by individuals of the opposite biological sex are more likely to change sexual orientation. Qualitative reports suggest that the individual's biography, autogynephilic and autoandrophilic sexual arousal, confusion before and after transitioning, social and self-acceptance, as well as concept of sexual orientation itself may explain this phenomenon.

The development of cancer has been associated with the gradual acquisition of genetic alterations leading to a progressive increase in malignancy. In various cancer types this process is enabled and accelerated by genome instability. While genome sequencing-based analysis of tumor genomes becomes increasingly a standard procedure in human cancer research, the potential necessity of genome instability for tumorigenesis in Drosophila melanogaster has, to our knowledge, never been determined at DNA sequence level. Therefore, we induced formation of tumors by depletion of the Drosophila tumor suppressor Polyhomeotic and subjected them to genome sequencing. To achieve a highly resolved delineation of the genome structure we developed the Deterministic Structural Variation Detection (DSVD) algorithm, which identifies structural variations (SVs) with high accuracy and at single base resolution. The employment of long overlapping paired-end reads enables DSVD to perform a deterministic, i.e. fragment size distribution independent, identification of a large size spectrum of SVs. Application of DSVD and other algorithms to our sequencing data reveals substantial genetic variation with respect to the reference genome reflecting temporal separation of the reference and laboratory strains. The majority of SVs, constituted by small insertions/deletions, is potentially caused by erroneous replication or transposition of mobile elements. Nevertheless, the tumor did not depict a loss of genome integrity compared to the control. Altogether, our results demonstrate that genome stability is not affected inevitably during sustained tumor growth in Drosophila implying that tumorigenesis, in this model organism, can occur irrespective of genome instability and the accumulation of specific genetic alterations.

Objective: Investigating psychopathological profiles of transsexuals raises a very basic methodological question: are control groups, which represent the biological or the phenotypic sex, most suited for an optimal evaluation of psychopathology of transsexuals?, Method: Male-to-female (MtF) (n=52) and female-to-male transsexuals (FtM) (n=32), receiving cross-sex hormone treatment, were compared with age matched healthy subjects of the same genetic sex (n=178) and with the same phenotypic sex (n=178) by means of the Symptom Check List-90-Revisited instrument (SCL-90-R). We performed analyses of covariance (ANCOVA) to test for group and sex effects. Furthermore, we used a profile analysis to determine if psychopathological symptom profiles of transsexuals more closely resemble genotypic sex or phenotypic sex controls., Results: Transsexual patients reported more symptoms of psychopathological distress than did healthy control subjects in all subscales of the SCL-90-R (all p<0.001), regardless of whether they were compared with phenotype or genotype matched controls. Depressive symptoms were more pronounced in MtF than in FtM (SCL-90-R score 0.85 vs. 0.45, p = 0.001). We could demonstrate that FtM primarily reflect the psychopathological profile of biological males rather than that of biological females (r = 0.945), while MtF showed a slightly higher profile similarity with biological females than with biological males (r = 0.698 vs. r = 0.685)., Conclusion: Our findings suggest that phenotypic sex matched controls are potentially more appropriate for comparison with the psychopathology of transsexual patients than are genetic sex matched controls.

The introduction of non-native species into new habitats poses a major threat to native populations. Of particular interest, though often overlooked, are introductions of populations that are not fully reproductively isolated from native individuals and can hybridize with them. To address this important topic we used different approaches in a multi-pronged study, combining the effects of mate choice, shoaling behaviour and genetics. Here we present evidence that behavioural traits such as shoaling and mate choice can promote population mixing if individuals do not distinguish between native and foreign conspecifics. We examined this in the context of two guppy (Poecilia reticulata) populations that have been subject to an introduction and subsequent population mixing event in Trinidad. The introduction of Guanapo River guppies into the Turure River more than 50 years ago led to a marked reduction of the original genotype. In our experiments, female guppies did not distinguish between shoaling partners when given the choice between native and foreign individuals. Introduced fish are therefore likely to benefit from the protection of a shoal and will improve their survival chances as a result. The additional finding that male guppies do not discriminate between females on the basis of origin will further increase the process of population mixing, especially if males encounter mixed shoals. In a mesocosm experiment, in which the native and foreign populations were allowed to mate freely, we found, as expected on the basis of these behavioural interactions, that the distribution of offspring genotypes could be predicted from the proportions of the two types of founding fish. This result suggests that stochastic and environmental processes have reinforced the biological ones to bring about the genetic dominance of the invading population in the Turure River. Re-sampling the Turure for genetic analysis using SNP markers confirmed the population mixing process and showed that it is an on-going process in this river and has led to the nearly complete disappearance of the original genotype.

Prohibitin 1 (PHB1) is a highly conserved protein that together with its homologue prohibitin 2 (PHB2) mainly localizes to the inner mitochondrial membrane. Although it was originally identified by its ability to inhibit G1/S progression in human fibroblasts, its role as tumor suppressor is debated. To determine the function of prohibitins in maintaining cell homeostasis, we generated cancer cell lines expressing prohibitin-directed shRNAs. We show that prohibitin proteins are necessary for the proliferation of cancer cells. Down-regulation of prohibitin expression drastically reduced the rate of cell division. Furthermore, mitochondrial morphology was not affected, but loss of prohibitins did lead to the degradation of the fusion protein OPA1 and, in certain cancer cell lines, to a reduced capability to exhibit anchorage-independent growth. These cancer cells also exhibited reduced adhesion to the extracellular matrix. Taken together, these observations suggest prohibitins play a crucial role in adhesion processes in the cell and thereby sustaining cancer cell propagation and survival.