A randomized controlled trial examining the efficacy of behavior therapy for pediatric trichotillomania was recently completed with 24 participants ranging in age from 7 - 17. The broad age range raised a question about whether young children, older children, and adolescents would respond similarly to intervention. In particular, it is unclear whether the younger children have the cognitive capacity to understand concepts like "urges" and whether they are able to introspect enough to be able to benefit from awareness training, which is a key aspect of behavior therapy for trichotillomania.Participants were randomly assigned to receive either behavior therapy (N = 12) or minimal attention control (N = 12), which was included to control for repeated assessments and the passage of time. Primary outcome measures were the independent evaluator-rated NIMH-Trichotillomania Severity Scale, a semi-structured interview often used in trichotillomania treatment trials, and a post-treatment clinical global impression improvement rating (CGI-I).The correlation between age and change in symptom severity for all patients treated in the trial was small and not statistically significant. A 2  × 2  × 2  ANOVA with independent evaluator-rated symptom severity scores as the continuous dependent variable also detected no main effects for age or for any interactions involving age. In light of the small sample size, the mean symptom severity scores at weeks 0 and 8 for younger and older patients randomized to behavioral therapy were also plotted. Visual inspection of these data indicated that although the groups appeared to have started at similar levels of severity for children ≤ 9 vs. children ≥ 10; the week 8 data show that the three younger children did at least as well as if not slightly better than the nine older children and adolescents.Behavior therapy for pediatric trichotillomania appears to be efficacious even in young children. The developmental and clinical implications of these findings will be discussed.Clinicaltrials.gov NCT00043563. Trichotillomania (TTM) is a chronic impulse-control disorder in which the individual pulls out one's hair to the point of alopecia. TTM is estimated to affect 1% - 3.5% of late adolescents and young adults . SuffereDespite the fact that TTM is a pediatric onset disorder associated with significant morbidity, comorbidity, and functional impairment in adults , very feFollowing from Freeman et al.'s  work, weParticipants were recruited into a randomized controlled trial examining the efficacy of behavior therapy for pediatric TTM that was conducted at the University of Pennsylvania's School of Medicine. Primary inclusion criteria for that study were: 1) ages 7 -17 inclusive; 2) diagnosis of TTM; 3) symptom duration of at least six months; and 4) participant and at least one parent fluent in English. Primary exclusion criteria were: 1) a primary psychiatric diagnosis other than TTM; 2) current bipolar illness, developmental disorder, or thought disorder; and 3) currently receiving either pharmacotherapy or concomitant psychotherapy for TTM. Written informed consent was obtained from all participants for publication of this manuscript and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal. Twenty-four patients were randomized, 12 to each condition. The sample ranged in age from 7 - 17, with a mean age of 12.5 (2.7); 4 of the 24 participants (17%) were ≤ 9 years old, with 3 of those participants randomized to BT. The sample was primarily Caucasian (75%), primarily female (67%), and had a mean age of TTM onset of 8.9 years (3.2). Additional information about participants randomized to BT can be found in Table Diagnostic criteria for TTM were assessed using the Trichotillomania Diagnostic Interview (TDI) , which eBehavior therapy was conducted in accordance with a manual developed in the context of a treatment development grant; this manual has now been published . The acuStudy data were examined using three main approaches. First, the correlation between participants' age and change in TTM symptoms over the course of treatment was calculated. Second, combined plots were created to permit visual inspection of response trends between the older (≥ 10) and younger (≤ 9) participants; this dichotomy was selected based on data from Tourette Syndrome indicating that children ages 9 and lower have more difficulty reliably reporting on concepts such as urges [see ]. Along p = .48) and not supportive of an expected association between age and change in TTM symptom severity over time regardless of treatment received.The correlation between age and change in TTM symptoms  for all 24 participants in the RCT was -.16, which was not significant statistically  × 2  × 2  ANOVA was conducted, with IE-rated NIMH-TSS scores as the dependent variable. No main effect for age was detected, nor did any interactions involving age emerge . Nevertheless, because children ≤ 9 comprised only 17% of the sample, statistical power to detect differences is inherently limited. Although statistical comparisons were not conducted, data on percentages of those with improved or very much improved CGI-I scores are presented in Table In order to further explore the possible influence of developmental factors on behavior therapy outcomes specifically, all NIMH-TSS scores at weeks 0 and 8 for younger and older patients randomized to BT were plotted and visually inspected as evident in Additional File 1 Figure . AlthougThe purpose of the current report was to explore whether developmental factors influenced change in TTM symptoms in a pediatric sample randomly assigned to receive either behavior therapy or a comparison condition designed to control for the effects of time and repeated assessments. Findings indicated that there was a small, negative, and insignificant relationship between participants' age and change in TTM symptoms over the course of the acute phase of the trial. When a mixed ANOVA was employed to further explore the effects of age on treatment outcome, here again no effects for developmental level emerged. Low power could have obscured such effects, however, so inspection of behavior therapy outcomes specifically was warranted in order to generate hypotheses about whether the youngest participants might have experienced attenuated outcomes relative to their older counterparts. The behavior therapy protocol for TTM includes techniques that require at least some ability to introspect , and the tailoring of subsequent treatment strategies such as stimulus control and competing response training rest upon increased awareness of the presence of urges to pull. Our data here were somewhat surprising given initial concerns about the ability of young children to grasp these core concepts in that their outcomes were clearly not attenuated, and were even suggestive of the possibility that children age 7 - 9 might experience more success in BT than their older counterparts.Data emerging from cross-sectional comparisons of TTM in different developmental stages might help explain this seemingly anomalous observation, in that it appears that pulling in younger children might be more "automatic" and less affect-driven than it appears to be in older children and in adults . YoungerAll of the limitations inherent in any study with a sample size this small are applicable here as well, and thus even our preliminary conclusions must be interpreted with considerable caution. Nevertheless, the dearth of published research in pediatric TTM necessitates efforts at empirical hypothesis generation wherever possible, which is what led to the exploration reported above. A second randomized controlled trial funded by the National Institute of Mental Health in the U.S. that compares the efficacy of BT to a more active control condition that equates therapist contact time (Psychoeducation/Supportive Counseling) is underway at Penn but, unfortunately, reviewer concerns about the developmental issues discussed above necessitated a design decision to truncate the age range to 10 - 17. There are very few other sources of knowledge available about treatment efficacy for children with TTM who are younger than age 10, and thus we felt that, despite the obvious caveats, it was important to take the opportunity provided by these data to help stimulate thinking about whether and how best to intervene in young children with TTM.The authors declare that they have no competing interests.ALE wrote the Backgrounds section and was responsible for formatting responsibilities. MEF was the study investigator and authored the majority of the manuscript. MEF and JBF conducted analyses, interpreted the data and revised the manuscript. ALE, MEF and JBF reviewed and approved the final version of the manuscript.


Furukawa TA, Fujita A, Harai H, Yoshimura R, Kitamura T, Takahashi K. Definitions of recovery and outcomes of major depression: results from a 10-year follow-up.Consensus operational definitions for symptomatic remission and recovery of a major depressive episode have been proposed but only irregularly followed.n = 95). Time to recovery and time to recurrence after recovery were estimated by Kaplan–Meier survival analyses for alternative definitions requiring 2, 4, 6 or 12 months of remission to declare recovery.We examined the predictive validity of different definitions of recovery in a multi-center 10-year follow-up study of an inception cohort of untreated unipolar major depressive episodes (The median time to recovery was 3.0, 4.0, 4.0 and 12.0 months respectively. The index episode lasted longer than 24 months in 9.4%, 9.2%, 12.6% and 24.5%. The median time to subthreshold recurrence was 16.0, 32.0, 42.0 and 74.0 months.Either 4- or 6-month duration of remission defined a change point before which the episode was continuous and after which the recurrence was reasonably unlikely.Requiring two months of remission is probably too short to declare recovery because a subthreshold recurrence occurs in more than half of the cohort within a year and a half.If we require 4 or 6 months before we declare recovery, the median time to recovery is 4 months and that to subthreshold recurrence is nearly 3 years.Requiring 12 months of remission before declaring recovery would make the episode discontinuous yet long and inflate the rate of chronicity.The sample size was relatively small and the confidence intervals were accordingly wide.This was a naturalistic study and the treatments were not controlled.Validity of alternative definitions of remission requires a separate study. Confusions and inconsistencies persist in the literature with regard to operational definitions of critical change points in the course of a major depressive episode, such as remission, recovery, relapse and recurrence. It was the US NIMH Collaborative Depression Study (CDS), a landmark long-term cohort study of patients with mood disorder, that first operationalized remission as a state with no more than one or two mild depressive criterion symptoms, and recovery as eight or more weeks of remission . Some haWith regard to the official diagnostic criteria, the definitions in DSM-IV are in line with the CDS definitions because they declare ‘recovery’ if ‘full remission’, which is defined as a period of at least 2 months in which there are not significant symptoms of mania or depression, is attained between two mood episodes . The ICDThis state of confusion is unfortunate not only for the psychiatric sciences because then findings cannot be compared and accumulated, but also for the psychiatric services because then the literature cannot inform the practitioners about how to judge recovery and declare the end of continuation treatment or about whether to recommend maintenance treatment based on knowledge of likelihood of recurrence.It is important to note that, in this framework for long-term treatment of depression , 15, empThe present article therefore sets out to examine the differential predictive validity of the competing definitions of symptomatic recovery. We propose that a more valid definition of recovery should define a change point until which the syndrome is relatively continuous, but after which a return of the syndrome will become reasonably unlikely.Data for this report come from the Group for Longitudinal Affective Disorders Study (GLADS), described in detail elsewhere , 21. BriThe 23 collaborating centers included psychiatric departments of 13 university hospitals and six general hospitals, three mental hospitals and one community mental health center. Participating psychiatrists at each center administered a semi-structured interview, called the Psychiatric Initial Screening for Affective Disorders (PISA)  to a repThe study protocol was approved by the Ethics Committee of the National Center of Neurology and Psychiatry, Japan, as well as those of the participating centers. Written informed consent was obtained from all participants after full disclosure of the purposes and procedures of the study. The patients eligible for and consenting to the study were then interviewed within 1 week of entry by a psychiatrist using the entry version of the Comprehensive Assessment List for Affective Disorders (COALA) . The COAThe present paper focuses on the course of the subset of the cohort who were diagnosed with major depressive disorder according to DSM-IV . We defiThe CDS definition of recovery by 2 months of remission has been criticized for being too short , 26 and not prolong the duration of the index episode too much, lest the episode contains too long well periods in itself;not increase the rates of chronicity (never attaining recovery) too much, lest we give an overly pessimistic impression that depression is a chronic or incurable disease;ensure that the time to recurrence is reasonably long, so that ‘recovery’ once declared can assure the patients that a return of symptoms is reasonably unlikely.spss for Windows 11.5  or recurrent . Fifty-six subjects (59%) were females, and the mean age was 44.3 (SD 15.2). The mean score for the 17-item Hamilton Rating Scale for Depression was 19.9 (SD 8.6) and 14 (15%) were inpatients upon study entry. The major depressive episode was superimposed on pre-existing dysthymia in five (5%). The median length of episode before study entry was 3.0 months (range: 0.5–48.0).A total of 1853 patients were screened at 23 participating centers between December 1992 and December 1995. A total of 466 patients suffered from broadly defined mood disorders, but either failed to meet the other entry criteria or declined consent and 126 entered the study. Of these, 95 met the DSM-IV criteria for major depressive disorder, either single episode  mg/day of imipramine equivalent and only 16 (19%) were on >75 mg/day.This is the first study to examine the predictive validity of different duration requirements of remission to achieve recovery in terms of the length of the index episode, rates of chronicity and the succeeding well interval until recurrence, based on a long-term naturalistic follow-up data. We found that different definitions can give up to fourfold differences in estimates of episode length and time to subthreshold recurrence but not in time to full recurrence.Several recent studies have shown that subthreshold depression is associated with psychosocial disability and more severe future course of the illness and requires treatment , 29. A sGiven our hypotheses regarding the predictive validity of the operational definition of recovery, requiring 12 months would include so much well time before recovery is declared as to draw an unnecessarily chronic picture for the index episode. Requiring only 2 months, on the other hand, would devaluate the significance of recovery because half of the patients so declared would experience a subthreshold recurrence within 1½ years. It is noteworthy that the time to full recurrence remained constant at about 100 months for the three definitions examined. However, given the clinical significance of subthreshold depression noted above, requiring 4- to 6-month remission before declaring recovery appears to be a reasonable definition, as it would not make the index episode unnecessarily chronic, yet assures a relatively low likelihood of subthreshold recurrence once recovery is declared and can provide some indication for ensuing treatments.There are some possible weaknesses of the present study. First, the sample size was relatively small and 95% confidence intervals were sometimes incalculable or very wide, especially with regard to time to full episode recurrence. This may partly explain the apparent lack of differentiation among various definitions of recovery with regard to this variable. Secondly, this was a naturalistic study, in which we did not control the treatment, and the amount of treatment, actually provided was very low. During the continuation phase, 43% were not receiving any antidepressant therapy and a further 37% were on inadequate treatment with <75 mg/day of imipramine equivalent or <600 mg/day of lithium. Six months later, during the maintenance phase, the corresponding figures were 50% and 29% . ThirdlyThe greatest strength of the current study, on the other hand, is the high follow-up rates achieved through serial assessments of a prospective cohort for 10 years. Some drop-outs were inevitable and we adjusted for the censored cases through survival analyses. The current DSM-IV follows the NIMH CDS tradition and requires 2 months of no significant signs or symptoms of the disturbance before declaring ‘full remission’. The naturalistic follow-up data given in the present report along with the functional and prognostic significance of subthreshold depression demonstrated in cross-sectional and longitudinal studies , and the


Klebsiella pneumoniae, and 2) the phagocytic ability of macrophages from these mice.Sex differences have been described in a number of pulmonary diseases. However, the impact of ozone exposure followed by pneumonia infection on sex-related survival and macrophage function have not been reported. The purpose of this study was to determine whether ozone exposure differentially affects: 1) survival of male and female mice infected with 3 or to filtered air (FA) (control) and then infected intratracheally with K. pneumoniae bacteria. Survival was monitored over a 14-day period, and the ability of alveolar macrophages to phagocytize the pathogen in vivo was investigated after 1 h.Male and female C57BL/6 mice were exposed to O3 are significantly more susceptible to K. pneumoniae infection than mice treated with FA; 2) although females appeared to be more resistant to K. pneumoniae than males, O3 exposure significantly increased the susceptibility of females to K. pneumoniae infection to a greater degree than males; 3) alveolar macrophages from O3-exposed male and female mice have impaired phagocytic ability compared to macrophages from FA-exposed mice; and 4) the O3-dependent reduction in phagocytic ability is greater in female mice.1) Both male and female mice exposed to O3 exposure reduces the ability of mice to survive K. pneumoniae infection and the reduced phagocytic ability of alveolar macrophages may be one of the contributing factors. Both events are significantly more pronounced in female mice following exposure to the environmental pollutant, ozone.O Pseudomonas aeruginosa and in cystic fibrosis patients being notable exceptions in which the male has a better outcome ). In cases (n = 14) where mice were moribund with no chance of recovery, these were euthanized to prevent unnecessary suffering according to Penn State University Institutional Animal Care and Use Committee recommendations and are included with the natural deaths. For the analysis shown in Figure Animals were anesthetized with an intramuscular injection of a mixture of Ketamine HCl  and Xylazine . The trachea was surgically exposed and ~450 CFU/mouse were inoculated intratracheally in 50 μl of PBS. Skin incision was closed with 7 mm wound clips. Deaths during the first 12 h post-infection period were considered to be due to surgical procedure rather than infection and those mice were excluded from study. Sixteen independent experiments  were conducted. Each experiment consisted of 10 mice . Five independent experiments were performed, each involved 3 mice exposed to O3 or to FA. To harvest alveolar macrophages, mouse lungs were subjected to bronchoalveolar lavage (BAL) (3× with 0.5 ml of 0.9% NaCl) at 1 h after infection, and kept on ice. If a mouse died within 1 h after infection, the lung was not lavaged and this mouse was excluded from analysis. Alveolar macrophages were prepared as described previously : [954 ± 32]) and 33.4% ± 5.7 (O3: FA = relative areas of [372 ± 53]: [1163 ± 80]) for females. Thus, the risk of dying from pneumonia after O3 exposure is nearly twice as high for female mice as it is for male mice.However, on day 14, relative to control conditions (FA-exposed mice), the survival of O3-exposed mice were significantly lower than those for FA-exposed animals on days 2–14 for males and 3–14 for females, respectively. To assess differences in daily survival between males and females with regard to their ability to survive K. pneumoniae infection, the proportions of O3-exposed males or females surviving to FA-exposed males or females surviving for each day (1–14) were calculated and shown in Figure 3 exposure than males on days 4–14.As shown in Figure K. pneumonia bacteria phagocytized by mouse alveolar macrophages in vivo. The phagocytic index was calculated as described in Methods. The analysis revealed that the phagocytic indices of alveolar macrophages isolated from FA-exposed female mice appeared to exhibit lower activity than those from male mice  . The phagocytic indices from O3-exposed mice differed (p = 0.03) between males and females . The phagocytic index for females was about 64% of that for males (p < 0.05). Thus, the data in Figure 3 exposure causes a significant reduction in the phagocytic index of alveolar macrophages in both sexes, this reduction is greater in females. When the proportions of the phagocytic indices of alveolar macrophages from FA- to O3-exposed male or female mice were determined, the O3-induced decrease in the phagocytic index for males was about 1.9-fold (182 : 97) and for females was 2.2-fold (137 : 62).Figure ) Figure , althougs p < 0.0. Thus, t3 exposure differentially affects the survival of male and female mice with pneumonia. Male and female mice were exposed to either FA (control) or O3 and then infected with pathogenic bacteria immediately after exposure. We studied their cumulative and daily survival over a period of 14 days and assessed the phagocytic capability of alveolar macrophages isolated from O3- or FA-exposed and infected mice. The results showed that: 1) mice, regardless of sex, exhibit reduced survival if exposed to O3 prior to infection; 2) while female mice appear to be more resistant to infection with the pathogenic microorganism, K. pneumoniae, than male mice, they are significantly more sensitive to an injurious environmental stimulus (in this case O3 exposure) and exhibit a greater reduction in their survival rate than male mice; 3) alveolar macrophages isolated from mice exposed to O3 prior to infection exhibit reduced phagocytic activity compared to those that were not exposed to O3; and 4) alveolar macrophages from O3-exposed female mice exhibited a greater reduction in phagocytic activity compared to those from male mice. The findings clearly document the impact of a prior environmental insult to the lung on subsequent infection, sex-related differences in the susceptibility to lung infection, and the role of the alveolar macrophages in the process. Furthermore, the data underscore the importance of considering sex in studies where the impact of environmental pollution on lung infection is being investigated.Several factors have been identified as risk factors in lung disease. Sex is one of the factors that may differentially modulate lung disease susceptibility. In this report, we investigated the hypothesis that OK. pneumoniae than whites of the same age. However, in both, black and white study groups, females were less susceptible to pneumonia, indicating that race is not a factor in this sex difference [K. pneumoniae than FA-exposed male mice.Although both males and females appear to have similar respiratory requirements, numerous studies have documented sexual dimorphism in lung function and lung disease pathogenesis throughout fetal developmental and postnatal life. These have recently been reviewed . A numbefference . Collect3 exposure are consistent with the studies reporting increased vulnerability to environmental insults by females. Based on the present findings and those from published reports, we speculate that environmental pollutants, whether from air pollution or cigarette smoke, have a negative and perhaps a more deleterious impact on females than males. Therefore, taken together, the available information points to a need for gender-based studies when the impact of environmental insults on lung health is being considered.In contrast to pneumonia, when the injurious agent falls in the category of environmental pollutants, the male disadvantage or female advantage appears to reverse. Elderly females have been shown to have a more pronounced response to ambient air pollution than males  and someK. pneumoniae model, used in the present study, showed that normal clearance of K. pneumoniae is primarily dependent on macrophages [3 exposure in the present study severely compromised the ability of the mice to clear the bacteria as assessed by the observed decrease in survival and phagocytic ability of alveolar macrophages. However, the fact that the effects described here were seen after a single acute exposure to O3, rather than the several day exposure to hyperoxia previously reported indicates that different or overlapping mechanisms may be operative, although in both cases it is likely that oxidative mechanisms are involved.Previous work with the rophages  and thatrophages . As with3 resulted previously in increased levels of protein oxidation in BAL at 4 hr or more after O3 exposure [3 exposure followed by the infection. However, even though no increases in total protein oxidation were reported immediately after the termination of O3 exposure, a time frame similar to that used in the present study, specific proteins critical for macrophage phagocytic function, such as SP-A, may be preferentially oxidized. In fact, the oxidation level of SP-A was increased right after O3 exposure [3 exposure of a macrophage-like human cell line caused a decrease in its responsiveness to a subsequent stimulus [in vitro finding of decreased responsiveness is consistent with our present in vivo observations and published findings [3.Exposure of mice to Oexposure . It is texposure . Of intestimulus . This infindings  where thK. pneumoniae, multiple factors including several cytokines [K. pneumoniae. None of these, with the exception of one or two of the cytokines have been examined for evidence of sexual dimorphism.Understanding how the behavior of effector cells, especially alveolar macrophages, are influenced under specified conditions is an important first step. How single or multiple treatment agents can differentially alter phenotype between males and females is exemplified by the observation that spontaneous production of nitric oxide in alveolar macrophages from female mice increases after LPS treatment alone , as doesytokines , lysozymytokines , epithelytokines , and othytokines  are all 3-exposure had a more negative impact on the phagocytic activity of macrophages from female mice. Alveolar macrophages isolated only 1 hr after infection from female mice, exhibited lower activity than those from male mice; this is consistent with the results of the survival study and indicates that alveolar macrophage-mediated mechanisms contribute to the observed sex-based response to K. pneumoniae infection. Although macrophages from female FA-exposed mice appeared to have a lower  activity than macrophages from male mice, this observation indicates that other factors contribute to host defense against K. pneumoniae and the higher survival rate in female mice exposed to FA. Among these may be antibodies, which are expressed at higher levels in females than in males [3 exposure on the phagocytic process, which in turn may contribute to differences in survival.In the current investigation, Oin males . FurtherPseudomonas aeruginosa than males [Mycoplasma pulmonis [Deciphering the overall basis of the observed sex differences in the susceptibility to the lung infection after exposure to ozone may be very complex and may also involve many processes other than phagocytosis, including those that are dependent on the continuing presence of circulating sex hormones, those that are the result of sexual differentiation and may not require the continued presence of hormones, and oxidative as well as other mechanisms that may be involved in lung health. Using a model of post-trauma sepsis it was reported that there is increased damage to the lungs of males versus females, a difference that is abrogated if estrogen and progesterone are given to males . With rean males , while apulmonis . The latpulmonis  demonstrpulmonis ,48. ThesK. pneumoniae than females, exposure to O3 reverses this pattern and renders the females significantly more susceptible, as assessed by the survival studies. We also showed that the in vivo phagocytic function of alveolar macrophages from female mice exposed to O3 prior to infection is significantly lower than those from male mice and therefore macrophage-mediated mechanisms may constitute one of the contributing processes to the observed sex-based differences. Furthermore, these findings in addition to pointing to the complexities of lung disease in response to different types of insults, allow us to speculate that the effect of air pollution, and particularly of ozone, on the immune lung status of patients has a significantly higher negative impact in women than in men. The latter highlights the need to independently assess each sex in experimental models, especially when the role of environmental pollutants in lung health is being investigated. Should these observations translate (in subsequent studies) to comparable findings in the human population, it may warrant a rethinking of what constitutes a sensitive population as ozone exposure standards are being set.In the present study, we demonstrated that although male mice appear to be more susceptible to infection with K. pneumoniae infection than mice exposed to filtered air, and ozone exposure decreases the survival of female mice after K. pneumoniae infection significantly more than it does in males. The ability of alveolar macrophages to phagocytize K. pneumoniae bacteria is also reduced in response to ozone, and the phagocytic ability of macrophages from females is affected more than macrophages from males. The data indicate a greater susceptibility to respiratory infection for females compared to males following exposure to the environmental pollutant, ozone.Mice exposed to ozone are significantly more susceptible to The author(s) declare that they have no competing interests.in vivo phagocytosis model, planned and carried out all experiments, analyzed and interpreted data, and wrote the manuscript. XG participated in experiments of survival study. TMU contributed in all aspects of setting up the ozone exposure model. LM participated in the in vivo phagocytosis experiments. VMC participated in statistical analysis of data for the survival study. DSP contributed in the planning of experiments, interpretation of data, and writing of the manuscript. JF contributed in the design of the project, analysis and interpretation of data, and the writing of the manuscript. All authors read and approved the final manuscript.ANM set up the infection model, the


A video of introductory information about inherited susceptibility to breast cancer was made in consultation with clinicians in four Scottish cancer family clinics. One hundred and twenty-eight women, newly referred for breast cancer risk counselling were randomized to receive the video before (n = 66) or after (n = 62) counselling. Data were collected before randomization at clinic and by postal follow-up at 1 month. The Video Before group had shorter consultations with the breast surgeon (mean = 11.8 min+/-5.4 vs 14.6+/-7.2 for the Video After group). There was no difference between the groups in the accuracy of their risk estimate after counselling, although the Video Before group scored higher for self-reported  and objectively assessed understanding . At 1 month follow-up, the Video Before group were less likely to underestimate their risk estimate , but there was then no difference between the groups in subjective or objective understanding. Use of the video was not associated with increased distress  and was associated with greater satisfaction with the information given at the clinic. This study supports the value of videotape as a method of giving information to prepare women for breast cancer risk counselling. Observations of misunderstandings and distress emphasize the video should be seen as an aid to, not a substitute, for communications at the clinic.


P<0.001). There is growing evidence that short-course chemotherapy, with or without RT, is superior to RT alone in early-stage aggressive NHL, in elderly as well as in younger patients. Increased age alone should not exclude patients from systemic treatment for early-stage aggressive NHL.Historically localised aggressive non-Hodgkin's lymphoma (NHL) has been treated with involved field radiotherapy (RT), chemotherapy, or a combination of both modalities. The current weight of evidence supports a preference for combined modality treatment (CMT). Increased patient age at diagnosis is well recognised as a poor prognostic indicator in NHL, but despite this some perceive CMT as too toxic for use in the elderly. As a result, some older patients continue to be offered RT alone. Here, we present long-term follow-up of 377 adults of all ages treated with RT alone for early-stage diffuse large-cell lymphoma on British National Lymphoma Investigation trials between 1974 and 1997. 10-year cause-specific survival in patients older than 60 years was poor and significantly inferior to that in younger patients (47 and 75% respectively;  Early stage at diagnosis is a significant predictor of improved outcome in aggressive non-Hodgkin's lymphoma . Until rIt has been suggested that the toxicity of chemotherapy is disproportionate to any improvement in outcome in elderly patients, and that short-course RT alone is an adequate treatment for this group. There is some evidence that elderly NHL patients experience more morbidity and mortality from chemotherapy , but perData for stage I aggressive lymphoma patients from the British National Lymphoma Investigation (BNLI) have previously shown 10-year disease-free survival (DFS) and OS rates of 45 and 61%, respectively  were not recorded for the early part of this series and so it was not possible to identify accurately patients with raised LDH. Performance status data were not sufficiently complete for analysis. A number of parameters that were recorded, including ESR, were retrospectively analysed along with age and stage as a surrogate for the modified International Prognostic Index (IPI) (Complete response (CR) was defined as the disappearance of all signs, symptoms and abnormal investigations due to disease for 3 months after completion of initial therapy. Disease-free survival was measured from the start of treatment to the date of recurrence. Recurrence was defined as the development of tumour following a CR to initial treatment. Overall survival included deaths from all causes, whereas cause-specific survival (CSS) was derived by censoring deaths not due to lymphoma or its treatment. Survival was calculated by the life-table method, survival curves were calculated according to the Kaplan–Meier method  and statIn all, 424 patients were treated with RT alone for early-stage diffuse large-cell lymphoma and were registered with the BNLI during the accrual period. 47 individuals were excluded at registration because of previous malignancy, incomplete staging or lack of other baseline data, thus this analysis was confined to the remaining 377 patients. Median follow-up to date for this group is 12.7 years. There were 202 males and 175 females. Median age was 59 years (range 17–89 years). Patient characteristics are outlined in A total of 294 patients (78%) achieved a complete remission. The complete remission rate for patients aged less than 60 years was 80%, and for older patients 77%. The CR rates for stages I and II disease were 85 and 58%, respectively. Of those patients achieving complete remission, 57% remained disease free at 10 years. The percentage of all treated patients remaining disease free at 10 years was 44%. The great majority of relapses occurred within the first 5 years following initial treatment. The OS at 10 years was 51%, rising to 63% when patients dying from causes other than lymphoma or its treatment were excluded.vs I), ESR (⩾40 mm h−1) and serum albumin (<40 g l−1), but not haemoglobin, as factors related to inferior DFS. Lactate dehydrogenase was not recorded for many of the patients in this series. Multivariate Cox's regression analysis of DFS identified age (relative risk (RR) 1.45, 95% confidence interval 1.07–2.00), stage  and ESR  as significant risk factors related to relapse. The DFS at 10 years for the patients aged 60 years and over was 35%, compared to 52% for the younger group. The percentage of patients in each stage and age group remaining disease free following initial RT is shown in Figures 1Univariate analysis of DFS identified age (⩾60 years), stage  did not predict survival in this series. Age , stage  and serum albumin  remained significant following multivariate analysis. The survival curves for patients in each stage and age group are shown in Figures 3Age, stage, ESR and serum albumin were also identified as risk factors related to CSS. Disease site . This suggests that the inferior results for older patients reported here do not merely reflect obsolete standards of diagnosis, treatment or supportive care.This analysis includes 38 patients treated before 1980 and 255 treated before 1990. Disease-free survival, but not OS or CSS, was significantly superior in patients treated more recently (not shown). However, differences between DFS, OS and CSS for the two age groups remained highly significant when only those patients treated since 1990 were analysed (In addition to age and stage, multivariate analysis found ESR to be an adverse predictor of DFS. Like LDH, which was not recorded in the earlier years of this series, ESR is likely to serve as a surrogate for disease activity. Similarly, albumin is an independent predictor of CSS. Like ESR, albumin may correlate with disease activity, but may also integrate a measure of comorbidity, which was not itself recorded but is likely to be a predictor of poor outcome in older patients.The poor outcome in elderly patients treated with RT alone suggests that this group should also be offered systemic therapy. The perception that the elderly respond to and tolerate chemotherapy poorly is not necessarily supported by the evidence . This haA recent comparison of short-course CHOP chemotherapy with or without involved field RT in elderly patients with localised disease showed equivalent overall and CSS in the two groups (The poor outcome reported here for older patients treated with RT alone, even when selected for early stage, indicates that chemotherapy should not be omitted in the elderly for the reason that their age in itself predicts poor outcome. Thus fit older patients with early-stage lymphoma should be offered CMT or even chemotherapy alone.


Traumatic or serious brain injury (BI) has persistent and well documented adverse outcomes, yet 'mild' or 'moderate' BI, which often does not result in hospital treatment, accounts for half the total days of disability attributed to BI. There are currently few data available from community samples on the incidence and correlates of these injuries. Therefore, the study aimed to assess the 1) incidence of self-reported mild  and moderate ) brain injury (BI), 2) causes of injury 3) physical health scores and 4) relationship between BI and problematic alcohol or marijuana use.An Australian community sequential-cohort study  used a survey methodology to assess BI and substance use at baseline and four years later.Of the 7485 wave one participants, 89.7% were re-interviewed at wave two. There were 56 mild (230.8/100000 person-years) and 44 moderate BI (180.5/100000 person-years) reported between waves one and two. Males and those in the 20-24 year cohort had increased risk of BI. Sports injury was the most frequent cause of BI (40/100) with traffic accidents being a greater proportion of moderate (27%) than mild (7%) BI. Neither alcohol nor marijuana problems at wave one were predictors of BI. BI was not a predictor of developing substance use problems by wave two.BI were prevalent in this community sample, though the incidence declined with age. Factors associated with BI in community samples differ from those reported in clinical samples . Further, detailed evaluation of the health consequences of these injuries is warranted. Traumatic brain injury (TBI - in this paper used to differentiate the most serious cases) is a major cause of morbidity and mortality in developed countries, with recent estimates from the USA that there were about 90 TBI-related hospitalizations per 100000 people  althoughIn addition to head trauma resulting in hospitalization, there is an increasing realization that many of those with BI are treated in emergency departments or primary care, possibly after a long delay (weeks to months) or do not receive any medical attention ,10. In tThe relationship between alcohol use and brain injuries has been well documented. Over one-third of patients hospitalized with brain injuries are likely to be intoxicated at admission and 44% to 66% have a history of alcohol abuse . Over a One reason why knowledge on the relationship between substance use and brain injuries may not be representative of the whole population is that data are typically drawn from hospital or rehabilitation settings -16 whereThere are few data from community surveys examining BI or TBI, particularly from outside the United States of America and a lack of longitudinal follow-up. In 2004, a cross-sectional cohort study reported that the life-time prevalence of brain injuries resulting in at least 15 minutes loss of consciousness was approximately 6% with a five year prevalence of 2.5% in those aged 20-24 years, 0.4% in the 40-44 year cohort and 0.2% in the oldest cohort, aged 60-64 years . The aimThe sample for the PATH Through Life Project has previously been described in detail ,22 and hPotential participants were selected at random from the electoral roll and were sent a letter inviting participation and describing the study. A subsequent telephone call was used to arrange a convenient location in which to conduct the interview: generally the home of the participant or the Centre for Mental Health Research. Participants used a palmtop computer to answer the survey questions, with assistance from the interviewer if required. The study was approved by the Australian National University Ethics Committee and all participants provided written consent.Alcohol use was assessed with the Alcohol Use Disorders Identification Test (AUDIT) ,25. The To be eligible for inclusion in the incidence of new BI, participants had to respond "no" to the question "Have you ever had a serious brain injury where you became unconscious for more than 15 minutes?" at the wave one survey: outcomes for the 428 persons who replied "yes" and the 295 who were "uncertain" have previously been reported and are excluded from this analysis of incident cases.  Incident cases at wave two were defined via two questions. BI was identified by those who replied "yes" to "Have you ever had a serious brain injury, that interfered with your memory, made you lose consciousness or caused a blood clot in your brain". Severity was defined as "moderate" for those who said that they had been admitted to hospital for head injury, with the remainder labelled as "mild". In addition, only events where the age at the time of event was within four years of the current age at the wave two survey were eligible. Of those who reported a BI at wave two, 268 were unable to recall their age at the time of the event or gave an age more than four years younger than their current age. These cases together with those reporting a BI at wave one, were excluded from both the numerator and denominator in calculating incidence rates of first time BI.The use of medications was recorded for key areas including, depression , anxiety , pain , memory  and sleep . For each area, the palmtop provided a list of commonly prescribed and over-the-counter medications. The lists ranged from five memory medications to 29 (anti) depression medications. Participants were also prompted to add any that were not already named.Differences between the study groups on demographic and other characteristics were assessed with chi-square  or general linear models (continuous variables). Simultaneous entry logistic regression was used to model the relative risks for brain injury at wave two using wave one predictors: age, sex, alcohol category, marijuana 'problem," use of specific categories of medication . The development of new alcohol or marijuana problems at wave two was modelled using the same wave one variables plus marital status, smoking status, occurrence of BI and either wave one alcohol (for new marijuana problems) or marijuana problems . To control for the five blocks of statistical inference testing, alpha was set to p < 0.01.While there were 6715 (89.7% of wave one participants) people who completed a wave two interview, there were 6093 who were classified with some certainty as having not experienced a BI at wave one  and 44 were moderate  and one case had missing data and was excluded from analysis requiring a severity rating.. Table Across both mild and moderate BI, sports activities was the major cause of brain injury overall  and responsible for the majority of the injuries in the 20-24 year cohort . In the oldest cohort 70% of all BI were attributed to falls while in the 40-44 year group, falls and traffic accidents were each cited in 33.3% of all BI.F  6.05, p = .014: estimated marginal means at wave one and two: BI = 50.2 (SE .7): 47.0 (SE .8), Non-BI = 51.0 (SE .1), 50.2 (SE .1)). There was no significant interaction evident for the SF-12 Mental health component summary scores  .657, p = .418).Those reporting a BI showed a trend towards greater declines on the SF-12 Physical health component summary scores than those without a BI . There were 223 people with marijuana problems, of whom, 82 were new cases. Table The risk factor analysis for BI by W2 was re-run including the 268 people who were unable to recall their age at the time of BI or gave an age more than four years younger than their current age. The same pattern of outcomes as shown in Table Data from this longitudinal community follow-up showed marked differences in the incidence of self-reported brain injuries across age groups and gender: in the youngest males the rate was over 771 per 100000 person-years whilst in the oldest females it was under 25 per 100000 p-y. The major causes of injury also varied by age group and with severity of brain injury. Clinical studies have reported links between brain injuries and alcohol/substance use disorders -15 but iNationally representative population survey data from the USA reported the incidence of mild and moderate BI to be 618 per 100000 p-y . HoweverThe literature shows that among those experiencing TBI, the cause of injury is predominately vehicular trauma and fall, particularly in this adult age range ,18,29. BAn important finding from our study was that neither baseline problematic use of alcohol nor marijuana was associated with incurring BI in the subsequent four years. In contrast, previous research suggests that in a clinical group, a greater proportion (about three times) of those who incur brain injury will be heavy drinkers than would be expected in the sample was drawn from the USA general population . In addiIt has previously been noted that, beyond the age of approximately 65 years, increasing age is associated with increased incidence of BI - thus those aged 85+ have a 10 fold rate of BI requiring hospital treatment than those aged 60-64 years and nearly six times the rate of intracranial injury . Thereford of a standard deviation on the SF-12 Physical health component summary score). In comparison, group norms for those with a serious versus minor physical condition show a difference of over eight points on the SF-12 Physical health component [Those who incurred a BI reported a trend towards worse physical health outcomes than those without a BI. However, it should be noted that the magnitude of this difference was small (three points or approximately 1/3omponent . The difomponent ). It hasomponent , althougomponent . Thus, tUse of pain medication at wave one was a risk factor for BI. We speculate that this is a marker for those who undertake more risky activities and acquire minor injuries that require pain medication. Other medications such as sleeping pills, anti-depressants and anxiolytics that may cause drowsiness, impaired concentration or interfere with the operation of machinery/driving were not implicated in BI.Across the two waves of the study there have been changes to the questions on brain injury. In wave one, the questions opened with serious head injuries defined as being unconscious for more than 15 minutes. At wave two, participants were asked about head injuries that required treatment in an emergency department, hospital or by a general practitioner before they were asked about serious head injuries. As a result some people, who did not report a head injury at wave one, did report a head injury at wave two but reported an age of occurrence indicating that it was prior to wave one. We excluded events where an age could not be recalled: this conservative approach would be likely to lead to an underestimation of the true incident rates. The first sensitivity analysis showed that inclusion of this sub-group did not have a major impact on the identification of risk factors for BI. Further, their inclusion did not alter the factors for developing alcohol disorders. However, the third sensitivity analysis showed that when this sub-group was included, those with BI were at increased risk of developing a marijuana use problem. A possible explanation is that marijuana use has been shown to impair memory, especially on 'real world' memory tasks which may lead to less accurate recall of when the BI occurred ,41. A fuThe main limitation of a community survey on this topic is the lack of data on the severity of the injury, in particular descriptive measures such as Glasgow Coma Scores  and stanIn Australia there were an estimated 21 800 TBI cases in 2004-05 that were treated in hospital . Health The authors declare that they have no competing interests.KA and PB developed the original head injury paper. RT developed the follow-up paper. Analysis and initial manuscript production were by RT. Extensive comment and editorial work by KA and PB. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/10/171/prepub


Multiple functional genomics data for complex human diseases have been published and made available by researchers worldwide. The main goal of these studies is the detailed analysis of a particular aspect of the disease. Complementary, meta-analysis approaches try to extract supersets of disease genes and interaction networks by integrating and combining these individual studies using statistical approaches.Pdk4, Adipoq, Scd, Pik3r1, Socs2 that monitor important hallmarks of T2DM, for example the strong relationship between obesity and insulin resistance, as well as a large fraction (128) of yet barely characterized novel candidate genes. Furthermore, we explored functional information and identified cellular networks associated with this core set of genes such as pathway information, protein-protein interactions and gene regulatory networks. Additionally, we set up a web interface in order to allow users to screen T2DM relevance for any – yet non-associated – gene.Here we report on a meta-analysis approach that integrates data of heterogeneous origin in the domain of type-2 diabetes mellitus (T2DM). Different data sources such as DNA microarrays and, complementing, qualitative data covering several human and mouse tissues are integrated and analyzed with a Bootstrap scoring approach in order to extract disease relevance of the genes. The purpose of the meta-analysis is two-fold: on the one hand it identifies a group of genes with overall disease relevance indicating common, tissue-independent processes related to the disease; on the other hand it identifies genes showing specific alterations with respect to a single study. Using a random sampling approach we computed a core set of 213 T2DM genes across multiple tissues in human and mouse, including well-known genes such as .In our paper we have identified a core set of 213 T2DM candidate genes by a meta-analysis of existing data sources. We have explored the relation of these genes to disease relevant information and – using enrichment analysis – we have identified biological networks on different layers of cellular information such as signaling and metabolic pathways, gene regulatory networks and protein-protein interactions. The web interface is accessible via  Type-2 diabetes mellitus (T2DM) is a rapidly increasing disease with more than 170 million afflicted persons worldwide . T2DM poses a huge burden for the health care systems and is, thus, subject to intensive biomedical research. T2DM is a multigenic disease involving a high number of susceptibility genes and causes alteration of an entire network of genes. Several environmental and nutritional risk factors have been identified for T2DM the most relevant being obesity where multiple molecular mechanisms have been proposed to link obesity to insulin resistance and beta cell failure [In the pathopysiology of T2DM, impaired insulin sensitivity and glucose intolerance are early phenomena, leading to hyperglycemia, hyperlipidemia and, eventually, to a failure of pancreatic beta cells to produce and secrete a sufficient amount of insulin. However, most genes and their associated molecular network contributing to the onset and course of the disease are yet unknown.Genetic variation in the context of diabetes has already been extensively studied, leading to numerous candidate genes. Studies on transgenic and knock-out mice have been valuable to dissect the regulatory network of genes implicated in insulin action and body weight control ,3, howevMultiple studies on the transcriptome level have been performed that emphasize the diversity of the disease and the complex pathophysiological interactions between different tissues, including fat, muscle, liver, pancreatic beta cells and brain . In seveThe goal of this meta-analysis approach is to generate additional value by combining the above-mentioned individual studies and by extracting consistent information. Several meta-analyses studies have been previously applied within other disease domains, such as cancer  or AlzheUsing a Bootstrap  scoring The meta-analysis approach is generic and can be used as a template for studies in other disease domains. It has been completely implemented in the software platform R using the BioConductor package collection -34. Our We present the identification of the T2DM candidate genes, the comparison to previously published T2DM gene lists and results from association and linkage studies as well as the identification of associated molecular networks on different levels.We used Ensembl (version 39) as the annotation reference database. Homology between human and mouse genes was derived via BioMart. The total number of genes under study comprises 15,277 Ensembl mouse genes representing the union of the homologue genes from all data sources. An overview about the T2DM specific datasets is given in Table Serpina1a 11 probes, Ybx1 8, Pdk4 16, Cstb 14, Adipoq 15, Agt 14, Lgals1 11, Serpine2 15, Mt2 10, Gpi1 16 probes).Several of the available resources are based on microarrays. Each individual microarray study was normalized using the GC RMA method of the R/BioConductor package ,34,36. RNumerical scores were computed for all genes in each individual study, the scores were summarized and the summarized scores were compared against a random sample at the 99.9 percentile as described in Materials & Methods. This procedure determines a cut-off score value of 3.05 and identifies a set of 213 genes with a score exceeding this cut-off.Serpina1b has the top score  in our study. This is due to a very high fold-change in a single experiment; consequently, entropy is low . In contrast, other genes show more consistent alterations across many different studies, for example Pdk4  indicated by higher entropy . Differential expression of Pdk4, a major regulator of glucose metabolism, has been found in fat, pancreatic islets and skeletal muscle but not in liver.Randomly, we would expect 15 out of the 15,277 genes to exceed the threshold. Cutting at the 99 percentile results in 943 genes (expecting 153 by chance), cutting at the 98, 97, 96 and 95 percentiles would result in 1352, 1587, 1792 and 1972 selected genes . Thus, the ratio of detected vs. expected significant genes increases with percentile of the random sample from 2.6 to 14.2, indicating a necessary precondition for the validity of our selection procedure [see Figure The thirty genes with highest scores are listed in Table Adipoq) has a score of 6.1  and the high entropy indicates a consistent behavior across data sets. Adipoq is a hormone from adipocytes that modulates insulin sensitivity and thus regulates glucose and lipid metabolism and energy homeostasis. Expression of Adipoq is reduced in obesity, certain genotypes are associated with increased risk of T2DM in humans [Adipoq is an oxidative regulator. The systemic oxidative stress causes the metabolism to share the burden from fat to muscle [Adipoq is also responsible for the crosstalk between the three KEGG pathways 'PPAR signaling', 'Adipocytokine signaling' and 'type II diabetes mellitus'. It has been tested for transcriptional regulation but no binding to the TFs under study could be detected. A negative regulation has been described for Tnf that has not been tested in the underlying studies.Adiponectin  is a critical enzyme for cortisol metabolism. Hsd11b1 is increased in obese subjects and transgenic mice over-expressing Hsd11b1 develop visceral obesity [Hsd11b1 decreases blood glucose in hyperglycaemic mice. Selective antagonists are currently developed and tested as anti-obesity and anti-diabetes drugs.Hydroxysteroid (11-beta) dehydrogenase 1  is the rate-limiting enzyme in monounsaturated fatty acid synthesis. It has been shown to exert a critical role in hepatic lipogenesis and lipid oxidation. Scd1 knock-out mice are lean due to increased energy expenditure, show increased insulin sensitivity and are resistant to diet-induced obesity and liver steatosis.Nnt, 5.5, 12/15,277) is a mitochondrial enzyme involved in proton transport into the mitochondrial matrix. Nnt was identified as a novel candidate gene in a quantitative trait locus for glucose intolerance [Nnt has been recently shown to regulate insulin secretion in pancreatic beta cells. Nnt deficiency results in defective insulin secretion and inappropriate glucose homeostasis [Nnt detoxifies reactive oxygen species [Nnt in regulating ATP production in mitochondria and function of the ATP sensitive K+ channel Kir6.2 (Kcnj11) in insulin producing beta cells.Nicotinamide nucleotide transhydrogenase , what points to the fact that high scoring of these genes was not due to single outlier experiments but that these genes are truly affected by the disease and, thus, exhibit a high potential for further functional experiments.For eighteen genes only limited functional information is available as a basis for assessing a possible relationship to T2DM: Adipoq and the resulting bar plots for two other genes, Pdk4 and Cfd, with lower content of available information. The resource is searchable by gene or protein IDs (for example Ensembl ID or gene symbol). The score distribution is shown as a bar plot and, where available, functional information is displayed. The two rightmost bars show the entropy, indicating uniform or specific score distribution, and the score. The red line at the score bar indicates the cut-off.In order to allow users to screen the disease potential of any given gene of interest we developed T2DM-GeneMiner, a web interface summarizing the results of our work  five gesistance ,46. Inte Project , being a Project , results Project . More se Project . In Tiff Project . This reSlc2a4, Irs2, Ptpn1, Slc2a2 and Irs1. Consistent with previous reports, the insulin-regulated glucose transporter GLUT4 (Slc2a4) is down-regulated in the insulin resistant state in adipose tissue but not in skeletal muscle. Likewise, down-regulation of Irs2 and the glucose transporter GLUT2 (Slc2a2) in pancreatic islets confirms previous reports and reflects deterioration of beta cell function in the course of insulin resistance and diabetes.A variety of genetic studies have been performed in the last decades. At least nineteen genetically engineered mouse models with T2DM phenotype have been studied in detail . Of thosSlc2a2 is also changed in liver. Ptpn1 is expressed in all tissues showing only small fold-changes. Several genes from OMIM or KO-mice do not change at all on the expression level. This indicates that only the complete loss of the associated protein alters the system whereas the gene's expression is not altered in T2DM. For KO-mice we also see a strong tendency to genes only expressed in mice.On the other side Cdkal (score 0),Cdkn2a (score 0)/Cdkn2b , Fto , Hhex , Igf2bp2 , Kcnj11 , Pparg , Slc30a8 , and Tcf7l2  [Pparg and Tcf7l2 are significant on the less restrictive 0.01 level. On the other hand, from the data we could infer that Fto and Hhex act in pancreatic islets indicated by the T2DM-GeneMiner result for these genes. Cdkal1 and Cdkn2a are not expressed in the transcriptional studies. These genes show very low expression levels or might be active in tissues not included in our study. Since our meta-analysis approach takes into account several data sets from DNA microarrays, our candidate genes have a bias towards transcripts whose expression is changed in the context of T2DM. Moreover, the gene variants from association studies may not result in altered gene expression and, for most SNPs found in association studies, there is a lack of functional information since the variation mostly occurs in non-coding regions of the genes. In order to correlate the T2DM genes with genetic variation we plotted the number of known SNPs for the genes [see Figure Pgcp  and Sorbs1 . Particularly interesting is Pgcp, because it has not been related to T2DM before and its functional role is also undetermined.Recently, a total of nine candidate genes for T2DM have been identified and replicated in humans through multiple genome-wide association studies of common variants by using high-density SNP mapping approaches: b 1.925, 65/15277,A further issue of our study was the chromosomal localization of the T2DM genes. The marker genes are scattered over the entire mouse genome [see Figure Enrichment analyses based on the hypergeometric distribution were carried out in order to assess whether our T2DM candidate list is over-represented with respect to a certain functional category Table . CategorInsulin signaling pathway' and the 46 genes annotated with 'type II diabetes mellitus' share 32 genes. The first four pathways help to validate our significant gene set. 'PPAR signaling', 'Adipocytokine signaling' and 'Insulin signaling pathway' are well related to T2DM.As greater parts of the metabolism are affected by T2DM, multiple pathways have a significant enrichment P-value. For example, in KEGG 45 out of 182 pathways have a P-value lower than 0.05. Table Fatty acid metabolism' what is complemented by the BioCyc pathways 'fatty acid elongation – saturated', 'fatty acid elongation – unsaturated' and by the GO categories 'positive regulation of fatty acid biosynthesis', 'positive regulation of fatty acid metabolism', 'fatty acid binding' and 'fatty acid oxidation'. The KEGG pathway 'Complement and coagulation cascades' is complemented by the Reactome pathways 'Initial triggering of complement', 'Complement cascade' and the GO categories 'defense response' and 'complement activation, alternative pathway'.Since we used several pathway resources in parallel, we can compare the findings for consistency, assuming the resources are independent. For example, we found enrichment of the KEGG pathway 'Mapk1 (22 pathways), Pik3r1 (19), Aldh9a1 (15), Mapk9 (11), Sh3glb1 (9), Pla2q12a (9), Pkm2, Nfkbia, Dhrs7, Actb . The importance of Mapk1, Pik3r1, Rasa1 and Socs2 is also supported by Liu et al. as members of an insulin signaling subnet derived from protein-protein-interactions [For 116 T2DM gene candidates there is information on the associated biochemical pathways according to the KEGG database. Whereas most genes (106) are associated with a single or a few (up to five) pathways, some genes exhibit a higher interconnection such as ractions .Insulin signaling", "Type II diabetes mellitus", "PPAR signaling", "Adipocytokine signaling", and "Fatty acid metabolism" pointing to the interplay between obesity and insulin resistance. Another path of signaling action is activation of the RAS/RAF/MEK MAPK cascade resulting in cell growth and gene expression alterations expressed by the crosstalk between "Type II diabetes mellitus" and "MAPK signaling" pathways.In order to identify crosstalk between pathways we scored the pathways according to their counts and their overlap in the T2DM candidate list Figure . An impoMapk1, Pik3r1 and Rela in mouse with more than 15 interactions. The large number of interactions of Mapk1 and Pik3r1 is consistent with their participation in many of the signaling pathways . If we consider the edges between significant genes and their non-significant nearest neighbors we still have 1,471 nodes and 11,378 edges. This shows that the disease genes strongly interact with main physiological triggers and deregulate essential parts of the metabolic network. Reducing the interactions on the 213 T2DM genes we end up with 45 nodes and 167 edges [see Figure Foxa's) and/or ligand binding (e.g. Ppar's). As a result, important core regulators including Onecut1 , Hnf4a , Tcf1 , and Foxa2  are not in our candidate list.In order to study the information content of the set of selected disease genes on gene regulation, we have analyzed a) the TFs present in our significant set and b) known target sets of TFs for enrichment. Analysis is often hampered because TFs are known to be expressed at a very low level and fold changes are commonly low. Moreover, many TFs are regulated by phosphorylation . Pparg is expressed solely in fat where its expression is altered. In total, target sets of 187 TFs have been investigated as gene sets for enrichment analysis. Table Cebpa is highly significant. It is expressed in adipose tissue and modulates the expression of leptin. Cebpa shows some correlation with the level of hyperglycemia in [Collecting TFs from Odom et al. ,18, Trancemia in . AlteratAcly and Fabp4. Target and regulator at the same time is Ipf1.A gene regulatory network comprising the regulatory interactions of the significant genes and the significant and enriched TFs is shown in Figure The first part of our study was devoted to the identification of genes related to T2DM using different heterogeneous data sources in different organisms. Genes have been scored in each individual study according to their disease relevance and an overall score across the different studies has been computed that reflects their total disease relevance. By this approach we were able to identify 213 genes that have a general disease relevance showing high scores in many different studies as well as genes that have a specific disease relevance expressing high scores in only a few studies.In the second part of this work the computed T2DM gene set has been used to identify biological networks on different layers of cellular information such as signaling and metabolic pathways, a comprehensive gene regulatory network and protein-protein interactions.Pparg and Tcf7l2 have been consistently found in recent GWA for T2DM and appear to be moderately significant in our meta-analysis as well.Biological validity of the T2DM candidate set is assessed with a comparison to existing studies and disease gene repositories such as OMIM and genome wide association studies (GWA). The union of the medical reviews ,48, geneIt should furthermore be noted that GWA studies themselves show only little overlap. Two recently published meta-analysis studies on GWA ,51 have Our scoring approach is very general. It combines genome-wide transcriptional studies from the Affymetrix GeneChip platform for obesity-induced T2DM, selective previous knowledge as well as gene lists derived from the biomedical literature.In the study at hand each resource has the same weight in the computation of the score. The entire method, however, could be tuned towards a certain focus by introducing weights and computing weighted scores with weighted random background distributions, for example, if one is particularly interested in a certain tissue or in a certain cellular level of information . In order to weight the fold changes derived from transcriptome data we have used the information on the reproducibility of the signals (coefficient of variation from replicate experiments) and the information whether the gene is expressed in the study samples or not. We have found that this weighting procedure improves results in comparison to simple fold changes because, for example, genes that are not expressed in the study samples might also show high – but senseless – fold changes adding additional noise to the procedure. Alternative weights could be introduced by taking into account the genetic variation as number of SNPs, or the degree in the protein-protein interaction network to separate major players from redundant genes following the hypothesis, that key factors have to be well-connected.In our approach we include both, genes with low but consistent expression changes across the different studies as well as strongly differentially expressed genes with respect to a single study. We used entropy as an indicator for measuring generality and specificity of a candidate gene with respect to the different studies. The correlation between the score and the entropy is 0.80 [a plot of the entropy versus the score is given in Figure Figure Despite these major sources of variation, there are further differences in analyzing microarray data with respect to chip platform and probe annotation. We have used the remapped probe annotation as provided by the R/Bioconductor software  which reAbcc8, Adipoq, Gck, Irs1, Irs2, Irs4, Ptpn1, Slc2a2, Lpl, Pik3r1, Tcf1, Retn, Serpine1, Rbp4, B2m.To assess the reliability of using mouse and human gene expression data we have compared the datasets from the two species separately. This analysis has to be stratified for the tissues under study. For human the data sets include skeletal muscle and pancreas. If we reduce mouse data to the same two tissues and perform the score evaluation on the two species separately we end up with 6,173 genes in total in the intersection and a correlation of 0.64 between the two score vectors. The human meta-analysis generates 91 significant genes and the mouse meta-analysis 31 genes. The overlap has 15 genes: A common approach in meta-analyses is to apply the same statistical test to congeneric studies and combine the resulting P-values by the Fisher method or Z-Score. We found this not practicable in our case, since the experimental sources are too heterogeneous. An extension to the web tool may open the way to introduce weights, chosen by the user.To contrast the different data sources a correlation heatmap is provided [see Figure Many existing T2DM data sets have not been incorporated in this study. For example, all transcriptome studies that were conducted on other microarray platforms than Affymetrix have been discarded because of compatibility issues. With the recent progress in merging gene expression data this limitation is soon questionable. Furthermore the selected data sets have a certain bias towards obesity-induced T2DM what is somewhat justified since obesity is a major risk factor. However, our study can be easily extended with additional sources of T2DM-relevant information. On the genetic level the results of QTL studies or, in human, association studies would upgrade the genetic component of the meta-analysis. Likewise to the OMIM source a sequence change does not necessarily lead to detection by expression change or a different criteria used in the study. E.g. a misfolded protein is not identifiable in this approach.Pparg  is mainly expressed in fat tissue. Our general approach with a restrictive cut-off favors genes with either a consistent or a very strong alteration. However, with a less restrictive cut-off at the 0.01-quantil of the score we retrieve most of the known genes, but would increase the number of false positives to a high extent.Furthermore, valuable information would be results from proteomic or metabolomic studies, but unfortunately data is still very sparse. Although the meta-analysis approach detects disease and candidate genes, it fails for some very specific well-known candidates. If a gene is only active at a medium level in only one tissue it will hardly be in our list. For example, A simple enrichment analysis based on the hypergeometric distribution has been applied in order to characterize the T2DM set on the network level including pathways, regulatory networks and protein-protein interactions. In general, we find a high consistency of the results of the enrichment analysis when screening different databases. For enrichment we used a hypergeometric test and multiple testing corrections based on Q-values to keep the results comparable between the different databases. Alternative approaches might be useful if focusing on specific annotation. Particularly, for the GO database this approach does not take into account the specific graph structure. Furthermore, there is no unique structure available in the pathway databases. Here, for example up- or downregulation of the involved genes and control of the fluxes are important features and could be used to stratify the enrichment.Protein-protein interactions are still very sparse or derived from high-throughput experiments with low overlap and low reproducibility so that results have to be carefully cross-checked. For example, we find a protein complex arising from one experiment of Collins et al.  with vagThe gene regulatory network associated with the T2DM candidate set is generic in the sense that all interactions are displayed regardless whether the genes are expressed in a specific tissue or not. This network can be tuned towards tissue specificity by taking into account tissue-specific gene expression and other characteristics. Using tissue expression data sets  we can aHnf4a 50 genes, Foxa2 13 genes, Usf1 19 genes, Tcf1 11 genes, Creb1 19 genes and Onecut1 11 genes. However, this technique is still error-prone and generates a lot of false positive targets due to the different steps in the experiment. Commonly, we end up with large targets sets containing thousands of genes [There are further limitations in analyzing gene regulatory networks. Information of TF binding sites – besides computationally predicted sites – is sparse and the knowledge on target sets of TFs is limited. In Table of genes ,18. HereWe have identified a core set of 213 T2DM candidate genes by a meta-analysis of existing data sources. We have explored the relation of these genes to disease relevant information and – using enrichment analysis – we have identified biological networks on different layers of cellular information such as signaling and metabolic pathways, gene regulatory networks and protein-protein interactions.Data sets were selected from heterogeneous sources that target different levels of cellular information. For each gene and each source we computed a numerical value that expresses its likelihood for being T2DM relevant. Data categories are either binary or quantitative.Binary data was introduced by incorporating medical reviews, phenotype information (for example from knock-out genes), results from proteome analysis ,44,48,49Quantitative data was incorporated by evaluating data from differential gene expression and time series microarray studies -16. In oGenes do not act as individual units, they collaborate in overlapping pathways, the deregulation of which is a hallmark for the disease under study. In order to integrate pathway information and to derive cellular network information on the selected genes, we added functional annotation from pathway databases such as KEGG, Reactome, BioCyc -30, GO , proteinGenetic variation of a gene was described with the number of associated SNPs. The number of SNPs in the coding and surrounding region of the gene is noted for mouse and human . A partiA central pre-requisite of any meta-analysis approach is the consolidation of the different ID types, for example coming from different organisms and from different versions of chips. We have used the Ensembl database  as the bAffymetrix gene chip annotations were adapted from latest genome annotations  in versiIn order to score the different categories of information, i.e. binary counts and quantitative gene expression values, for each category we summarized the scores of the individual experiments. For binary information the counts were grouped in sub-categories, for example knock-out mice described in two reviews only get a single count.ith gene in the jth study, sij, was computed as follows:For quantitative information, the score of the rij is the fold change, pij is the average detection P-value and eij is the standard error of the ratio derived from the experimental replicates of the study. Thus, the fold change is weighted with its reproducibility across the experimental replicates and with the likelihood of the gene being expressed in the study's target samples. A similar formula applies for correlation studies:Here, cij is the correlation to a certain phenotypic parameter, vij the coefficient of variation of the gene's signal across experimental replicas. The formula is applied on the data of Nadler et al. [Here, r et al. . Mice frThe total score of the gene was computed as the sum across all individual study scores.In order to assess the significance of the overall gene scores we generated random gene scores. For this bootstrap  we draw sij be the score of the ith gene in the jth study, then Ei is a measure for the uniformity of the score distribution over the individual experiments:For each gene, entropy of the score distribution was computed in order to quantify the relative influence of a certain study (for example a particular tissue) on the overall score. Let Entropy is low if a single study has a major contribution on the overall score. On the other hand, entropy is high if most of the studies account equally for the score. A plot of the entropy versus the score is given in Figure Disease related networks were investigated with four different types of network information – biological pathways -30, protThe same method we use in the leave-one-out cross-validation. Our qualitative studies are the benchmark for our scoring approach. The scoring, including a notional candidate set, is calculated without the respective qualitative study. The hypergeometric distribution of the qualitative study gene set and the notional candidate set assigns a P-value. This P-value reflects the success of the score to identify the genes from the qualitative study.T2DM: type-2 diabetes mellitus; GO: gene ontology; TF: transcription factor; ID: identifier; SNP: single nucleotide polymorphism; GWA: genome-wide association.AR collected and processed the data, implemented and conducted the meta-analysis and wrote the manuscript. HA-H contributed with biological interpretation of the results and with writing the manuscript. RH designed and led the study, performed data analysis and contributed to the manuscript.Additional figures. Supplementary figures for the manuscript.Click here for fileCandidate genes. A tabular version of the web tool data for the T2DM candidate gene list of 213 genes.Click here for fileSignificant categories. The significant categories of the enrichment analysis.Click here for fileOverlap of different candidate gene sets. A table showing the overlap of different candidate gene sets for T2DM.Click here for fileSource description. Describing the sources of information used in the web tool and [Additional file Click here for file


We used the Genetic Analysis Workshop 15 Problem 1 data set to search for expression phenotype quantitative trait loci in a highly selected group of genes with a supposedly correlated role in the development of the enteric nervous system. Our strategy was to reduce the level of multiple testing by analyzing at the genome-wide level a limited number of genes considered to be the most promising enteric nervous system candidates on the basis of mouse expression data, and then extend the analysis to a larger number of traits only for a small number of candidate linked regions. Such a study design allowed us to identify a "master regulator" locus for several genes involved in the enteric nervous system, located in 9q31. In particular, one of four traits included in the genome-wide analysis and 2 of 57 from the follow-up single-chromosome analysis showed LOD scores above 2 around position 109 on chromosome 9 by univariate variance-component linkage analysis. Bivariate linkage analysis further supported the presence of a common regulatory locus, with a maximum multipoint LOD score of 5.17 and five additional LOD scores > 3 in the same region. This region is particularly interesting because a susceptibility locus for Hirschsprung disease, a disease characterized by enteric malformation, was previously mapped to 9q31. The proposed strategy of limiting the genome-wide analysis to a small number of well characterized candidate expression phenotypes and following up the most promising results in a larger number of correlated traits may prove successful for other groups of genes involved in a common pathway. However, the extremely large number of phenotypes tested resulted in a severe multiple testing problem, and thus necessitated a rigorous correction with extremely small p-values to avoid inflation of type I error [The Genetic Analysis Workshop 15 (GAW15) Problem 1 data set is based on the proposed approach of considering natural gene expression variation as a quantitative trait influenced by genetic determinants. The resulting phenotypes can thus be used in linkage and association analyses to map loci involved in expression regulation in the genome [a priori on the basis of a hypothesized common biological role. Prompted by our interest in Hirschsprung disease (HSCR), a congenital gut malformation characterized by absence of ganglia in the colon [RET proto-oncogene, expressed throughout enteric neurogenesis, is required for normal ENS development and is the major HSCR gene. We based our trait selection on a recent article that described a microarray comparison between RNA from normal  and Ret mutant (aganglionic) gut tissue in embryonic mouse and that has identified hundreds of candidate ENS-expressed genes [Here we carried out a genome-wide linkage analysis on a small number of traits, chosen he colon , we chosed genes .The GAW15 data provided the expression phenotypes for the human orthologues of several of these genes. We conducted genome-wide variance-component linkage analysis on a highly selected group of four traits to search for candidate linked regions. We then extended the analysis to a larger number of traits focusing only on the region identified as most significant in the genome-wide screen, thus limiting the problem of multiple test significance. Because bivariate analysis has been shown to increase power to detect linkage of related traits to a common QTL, we used bivariate linkage analysis to test for the presence of genes with pleiotropic effects on the selected traits.in situ hybridization for 47 genes selected for further analysis, representing diverse functional classes and either uncharacterized or partially characterized or known ENS marker genes [By using RNA from WT and aganglionic gut tissue and DNA microarrays, Heanue and Pachnis  conducteer genes . The GAW[Data from 194 individuals belonging to 14 three-generation CEPH (Centre d'Etude du Polymorphisme Humain) Utah families have been used for quantitative genetic analysis by means of the variance-component approach. Narrow sense heritability of the traits with its significance, and genetic and environmental correlations between pairs of traits were estimated using SOLAR version 2.1.4  and mark10 of the likelihood ratio of these two models.Multipoint identity-by-descent (IBD) probabilities were estimated by GENEHUNTER and imported into SOLAR to estimate the genetic variance attributable to a hypothetical quantitative trait loci (QTL) linked to any given location. A test for linkage was carried out by testing whether the QTL additive variance was significantly different from 0 by comparing the likelihood of this model with that of a restricted model in which the genetic variance at the same location was fixed at 0. LOD scores reported in the text and the tables are calculated by SOLAR as the logGenome-wide univariate and bivariate linkage analyses were carried out on four highly selected traits presenting non-null heritability. To follow up on the genome-wide results, univariate and bivariate analyses were also performed on a larger number of selected phenotypes only for markers located on chromosome 9..The marker maps used for each chromosome were obtained by a marker position file released with the data and considering 1 cM ≈ 1 Mb. The linkage analysis on chromosome 9 was carried out with both the physical map and the Rutgers genetic map 2 and age2 × sex as covariates. Information about age was taken from the CEPH website .No covariates were taken into account in the genome-wide analysis, while analysis for chromosome 9 was also repeated including sex, age, age × sex, agep-values of the univariate LOD scores were calculated by means of an empirical null distribution obtained by simulation of 10,000 replicates of an unlinked marker. Asymptotic p-values for the bivariate LOD scores were calculated based on a 1/4 p-values.The ormation . No corrh2) , and for trait 202154_x_at at position 99 on chromosome 11 . All other LOD-scores were ≤ 2. There was no linkage evidence of cis regulators for any of the traits  Table  and were Table  ap-value = 0.0005), suggesting the presence of a common regulator for the two traits in this genomic region. Two other traits (203440_at and 218501_at) in combination with 201387_s_at yielded LOD scores > 2 at the same location; however the bivariate LOD scores were lower than the univariate LOD score observed for 201387_s_at alone. Two additional LOD scores > 2 were observed on chromosome 11 in bivariate analyses that included trait 202154_x_at, but were lower than the maximum univariate LOD-score observed for trait 202154_x_at alone.LOD-scores from bivariate genome-wide linkage analysis were similar to those from the univariate analysis Table . The maxTo follow up on the most significant finding, we extended the analysis of chromosome 9 to the other traits potentially involved in the ENS development included in the data set. Among these, 5 presented null heritability and were excluded. Of the remaining 57 traits, 10 had maximum chromosome 9 LOD scores at position 107 or 109 (data not shown). In particular, 2 traits had LOD scores > 2 at these positions .We obtained similar results using the Rutgers chromosome 9 genetic map (data not shown). For instance, trait 209034_at  was mapped at 140 cM with LOD score of 3.52, and trait 201387_s_at (LOD score = 2.66 at position 109) was mapped at 139 cM with LOD score of 2.60. The region from position 107 to 110 in the physical map that we initially used corresponds to the region from 130 to 151 cM in the Rutger's genetic map, and in particular position 109 corresponds to 139 cM.2 and age2 × sex) on variability of all the traits. Overall, at least one of the covariates showed significant effects for 42 of the 67 traits (p < 0.1). Age was more frequently found to have a significant effect on trait variation (35/42), while sex was rarely significant (3/42). After inclusion of the significant covariates, only slight differences were found in the results of the chromosome 9 linkage analyses. Two traits gave the most discordant results (difference in maximum LOD scores > 1): 209267_s_at, for which the highest LOD score at position 116 went from 2.12 to 1.06; and 212120_at, for which the LOD-score at position 11 went from 3.06 to 1.33. Results for the traits that showed LOD scores > 2 around position 109 were consistent with and without covariates.The quantitative analysis was also repeated to estimate the effect of several covariates  declare that they have no competing interests.


Several different drug retreatment protocols were employed to examine the emergence of resistance to MeCCNU in Lewis lung tumours. Previous studies suggested that although the majority of cells in untreated Lewis lung tumours were sensitive to MeCCNU, there was a very small proportion of resistant cells (approximately 0.001%) that limited "tumour cure' with that drug. If such cells were inherently drug resistant then it should be possible to derive highly resistant tumours by repeated drug treatment. In the first experiment tumours were treated with a single high dose of MeCCNU (35 or 40 mgkg-1) and on regrowth, transplanted into fresh mice and tested for drug sensitivity. Using both excision cell survival and growth delay endpoints, only approximately 25% of tumours were significantly resistant to the test dose, suggesting that many tumours resist the effects of the drug for reasons other than the presence of inherently drug resistant cells. One of the tumours (R4), that regrew after the initial treatment and appeared to be resistant to the test treatment, was retreated with a further 30 mgkg-1 MeCCNU and became more resistant. This line, designated R4/1, was cross-resistant to the other nitrosoureas, BCNU and CCNU, but not to cyclophosphamide, melphalan, cis-platinum or ionising radiation. The effect of treatment dose on the kinetics of MeCCNU resistance development was also studied in a retreatment regimen where the tumours were allowed to regrow and then transplanted into fresh hosts for the next treatment. Resistance developed more quickly at an intermediate dose of 15 mgkg-1 than at 7.5 mgkg-1 where the selective pressure was lower, or at 30 mgkg-1 where there was probably extinction of partially resistant cells. Resistance to MeCCNU developed even more quickly when tumours were retreated several times in the same host, although in a similar experiment with cyclophosphamide no resistance occurred.


Gene set analysis is a commonly used method for analysing microarray data by considering groups of functionally related genes instead of individual genes. Here we present the use of two gene set analysis approaches: Globaltest and GOEAST.Eimeria infection.Globaltest is a method for testing whether sets of genes are significantly associated with a variable of interest. GOEAST is a freely accessible web-based tool to test GO term enrichment within given gene sets. The two approaches were applied in the analysis of gene lists obtained from three different contrasts in a microarray experiment conducted to study the host reactions in broilers following The Globaltest identified significantly associated gene sets in one of the three contrasts made in the microarray experiment whereas the functional analysis of the differentially expressed genes using GOEAST revealed enriched GO terms in all three contrasts.Globaltest and GOEAST gave different results, probably due to the different algorithms and the different criteria used for evaluating the significance of GO terms. Several methods have recently been developed for gene set analysis of microarray data ,2. TheseEimeria infection.These approaches were applied in the analysis of gene lists obtained from three different contrasts in a microarray experiment conducted to study the host reactions in broilers following The Globaltest allows different kinds of variables to be tested, based on which it determines the correct model .The Globaltest calculates the p-value using different methods, the most important ones being permutations and the asymptotic distribution. Here the asymptotic distribution was used. All p-values were corrected for multiple testing using Benjamini and Hochberg's False Discovery Rate (FDR) . GO termThe Globaltest package also offers plots to visualize the effects of different genes and different samples on the test result: 1. Sample plot: how good a sample fits to its phenotype, 2. Checkerboard: correlation between samples, and 3. Gene plot: Influence of individual genes to test statistics.R version 2.8.0 was used to run the Globaltest package (version 4.12.0).Globaltest: R: For GOEAST all GO terms with less than 5 probes associated with it on the array are discarded from the test because the statistical analysis would not be appropriate then.The Fisher's exact test available in GOEAST was used separately on the 2-fold upregulated and downregulated gene lists for each of the three contrasts. The p-values were adjusted using Benjamini-Yekutieli method  with cutThe results from GOEAST analysis are presented in 3 ways: an HTML table providing detailed information of enriched GO terms and their associated genes; a plain-text file of enriched GO terms; and separate graphical output files showing the hierarchical relationships of enriched GO terms in the 3 GO categories.2-test as well as other methods for multiple testing correction .Besides the Fisher's exact test, GOEAST also supports hypergeometric test and χThe Globaltest takes into account the entire raw expression data. The overall gene expression profile for the three contrasts  was significantly associated (p < 0.05) with their outcomes, the p-values using the asymptotic method being 0.006, 0.032 and 0.021 respectively. This shows that the overall gene expression pattern of MM8 chicken differs significantly from that of PM8, MA8 and MM24 chicken. Therefore there is a potential in predicting infection from gene expression data.GO terms  were used for gene set analysis. After correction for multiple testing, no significant gene sets (GO terms) were found in MM8-MA8 and MM8-MM24 contrasts. However, in the MM8-PM8 contrast, 527, 331 and 180 out of a total of 1679, 838 and 336 GO-terms, were found to be significant (p < 0.05) for biological process, molecular function and cellular component, respectively. The five most significant terms for each GO category are listed in Table TICAM1 alone. The top 5 GO terms within each GO category that were significantly enriched among differentially expressed genes for the 3 contrasts are presented in Additional file In GOEAST, only differentially expressed genes over 2 fold level within the gene lists from each of the three contrasts were taken into account. The analysis for enriched GO terms by the Fisher's exact test revealed a large number of enriched GO terms at 0.1 FDR level for all three contrasts  a permutation distribution could not generate a unique p-value and therefore the asymptotic distribution was used. Although the asymptotic distribution is correct for large sample sizes, it also gives a good indication for small sample sizes .From GOEAST results, it was noted that several enriched GO terms were associated with only 1 or a few genes in the tested gene lists. Though the terms still appear to be statistically significant, their biological relevance should be carefully looked into.TICAM1, annotated to that term. However, these terms may still be biologically relevant since the TICAM1 gene is known to be involved in innate immunity against invading pathogens and therefore important in the context of the experiment that generated the gene lists.For example, 3 among the top 5 GO 'biological process' terms enriched in the list of down regulated genes of the contrast MM8-MA8 had one and the same gene, We found different results for the two methods probably due to the different algorithms used and also the different criteria used for evaluating the significance of GO terms. Different results achieved by different gene set analysis methods were previously reported by other authors ,9.The Globaltest and GOEAST gave different results, probably due to the different algorithms and also the different criteria used for evaluating the significance of GO terms. This confirms that different gene set analysis methods perform differently and that they do not necessarily lead to the same biological conclusions. A pitfall in interpretation of the results presented here is the lack of sufficient annotation of the probes used in this microarray experiment.FDR: False Discovery Rate; GO: Gene Ontology; GOEAST: Gene Ontology Enrichment Analysis Software Toolkit; KEGG: Kyoto Encyclopedia of Genes and GenomesThe authors declare that they have no competing interests.The three authors contributed equally to this paper.Top 5 GO terms identified by GOEAST for each microarray contrast. This file presents the top 5 GO terms within each GO category identified by Fisher's exact test in GOEAST to be significantly enriched among the >2 fold differentially expressed genes for the 3 contrasts: MM8-PM8, MM8-MA8 and MM8-MM24Click here for file