Background: In rheumatoid arthritis (RA), dysregulation of intestinal microbiota and metabolism as well as associations with comorbidities are a subject of increasing scientific interest. Objectives: The aim of this study was the characterization and correlation of the "OMICS" layers microbiota and metabolome with RA, as well as with developing RA before diagnosis (preRA). Methods: For the analysis the FoodChain Plus (FoCus) cohort (n=1,795 participants) was used, which consists of a cross-sectional survey of the population, as well as subjects with obesity, diabetes and inflammatory diseases. Only subjects with available data for intestinal microbiota (16S rRNA gene sequencing from stool samples grouped in amplicon sequence variants), serum metabolome and nutrition data were included. For every subject with RA and every subject with preRA (no RA at biosampling but known to develop RA during follow-up), two matched controls were assigned. The serum metabolome was measured using direct injection FT-ICR mass spectrometry. The analysis was conducted using a semi-targeted approach and a customized local database (including metabolites from the "Human Metabolome Database" [1]). Identified metabolites were evaluated for the predictive value for RA and preRA by sparse partial least squares-discriminant analysis (sPLS-DA). Results: For every subject with RA (n=60) and every subject with preRA (n=21), two matched controls were assigned. Compared to RA, those with preRA showed a higher BMI (median 28.2 VS 33.1, p<0.05). Chronic respiratory diseases were more prevalent in preRA compared to RA and controls (p<0.001). Significant differences in beta-diversity of the core measurable microbiota (CMM) between RA and preRA, RA and controls and preRA and controls were observed using Jaccard-index (p=0.01), but not in complete microbiota by Bray-Curtis distance (p>0.05). Differences of alpha diversity were not statistically significant when comparing RA and preRA with their matched controls (p>0.05). Via sPLS-DA 50 metabolites that most accurately discriminated RA, preRA and controls were identified. After adjusting by false discovery rate n=12 candidate metabolites remained (Kruskal-Wallis, p<0.05). For 132 subjects metabolome data from urine were available, no significant metabolites remained using the same exploratory approach. Conclusion: Not only subjects with RA, but also those with preRA showed significant differences in gut microbiota composition, serum metabolome and comorbidities. The presented results are preliminary. REFERENCES: [1] Wishart DS, Guo A, Oler E, Wang F, Anjum A, Peters H, Dizon R, Sayeeda Z, Tian S, Lee BL, Berjanskii M, Mah R, Yamamoto M, Jovel J, Torres-Calzada C, Hiebert-Giesbrecht M, Lui VW, Varshavi D, Varshavi D, Allen D, Arndt D, Khetarpal N, Sivakumaran A, Harford K, Sanford S, Yee K, Cao X, Budinski Z, Liigand J, Zhang L, Zheng J, Mandal R, Karu N, Dambrova M, Schiöth HB, Greiner R, Gautam V. HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Res. 2022 Jan 7;50(D1):D622-D631. DOI: 10.1093/nar/gkab1062. Acknowledgements: NIL. Disclosure of Interests: Jan Schirmer: None declared, Kristina Schlicht: None declared, Tobias Demetrowitsch: None declared, Nathalie Rohmann: None declared, Kathrin Türk: None declared, Dominik Schulte: None declared, Katharina Hartmann: None declared, Ute Settgast: None declared, Andre Franke: None declared, Karin Schwarz: None declared, Stefan Schreiber Abbvie, Amgen, Arena, Biogen, BMS, Celgene, Celltrion, Falk, Ferring, Fresenius Kabi, Galapagos, Gilead, HIKMA, IMAB, Janssen, Lilly, MSD, Mylan, Novartis, Pfizer, Protagonist, Provention Bio, Roche, Sandoz/Hexal, Takeda and Theravance, Bimba Franziska Hoyer: None declared, Matthias Laudes: None declared.

Background The association of the gut microbiome with obesity and metabolic diseases as type 2 diabetes (T2D) as well as the influence of environmental factors like nutrition on its composition is well established. In addition, recent studies[1] described the composition of gut microbiota to be altered in inflammatory rheumatic diseases highlighting a pathogenetic link between the microbiome and autoimmune joint diseases. Objectives The aim of this study was to analyze food intake and the composition of the gut microbiota in rheumatoid arthritis (RA) in comparison to healthy controls (adjusted for metabolic conditions known to influence the gut microbiota composition). Methods A subset of the FoCus (Food chain plus) cohort (a cross-sectional survey of the general population in northern Germany) with RA and matched controls without RA (matched for age, gender, body mass index and diagnosis of Type 2 Diabetes mellitus [T2D]) was investigated regarding their nutrition patterns and gut microbiome in a case-control analysis. Nutrition patterns were derived from Food Frequency Questionaires (FFQ) and analyzed by hierarchical cluster analysis. The gut microbiota composition was analyzed by 16S rRNA gene sequence data clustered into operational taxonomic units (OTUs). Microbiome composition was analyzed by alpha- (phylodiversity, Shannon index, Chao index) and beta-diversity measures (Bray-Curtis distance, Jaccard index) and by hurdle-models. Results We identified n = 94 individuals with RA and n = 94 matched controls (mean age 57 years, SD 12.9; mean BMI 31.1, SD 8.9). Interleukin 6 was significantly higher in the RA group compared with controls (p=0.012), while no differences were observed between groups for HOMA-Index, CRP, lipoprotein (a) or triglycerides. Nutrition data from FFQs was used in a hierarchical cluster analysis, resulting in two main clusters (the second one defined by a significantly higher intake of vegetables, fruit and dairy products). Nutrition clusters did not differ significantly between RA cases and controls (p=0.228). When comparing the composition of the intestinal microbiota between RA patients and controls (adjusted for nutrition cluster and IL-6), significant differences in the beta-diversity were detected using Bray-Curtis distance (p=1.82e-9) and Jaccard index (p=1.82e-9). Hurdle model analysis of the core measurable microbiome identified three candidate species OTUs (Flavonifractor and 2x Blautia). No significant differences in alpha diversity was observed when analyzed by species richness (p=0.9), Shannon (p=0.3) and Chao index (p=0.6). Conclusion Participants suffering from RA had significant differences in the composition of the gut microbiome compared to controls matched for age, BMI, gender and T2D after adjusting for nutrition patterns and IL-6. Investigating differences in the functional capacity of the altered gut microbiome in RA may better characterize a possible link of gut microbes to the development of RA. Reference [1]Chu XJ, Cao NW, Zhou HY, Meng X, Guo B, Zhang HY, Li BZ. The oral and gut microbiome in rheumatoid arthritis patients: a systematic review. Rheumatology (Oxford). 2021 Mar 2;60(3):1054-1066. doi: 10.1093/rheumatology/keaa835. PMID: 33450018. Acknowledgements The project was supported by the German Society for Rheumatology (Deutsche Gesellschaft für Rheumatologie/ DGRh) and the Competence Network Rheumatology (Kompetenznetz Rheumatologie)/ DGRh Research Initiative 2020. Disclosure of Interests Jan Schirmer: None declared, Kristina Schlicht: None declared, Carina Knappe: None declared, Kathrin Türk: None declared, Dominik Schulte: None declared, Katharina Hartmann: None declared, Ute Settgast: None declared, Andre Franke: None declared, Stefan Schreiber: None declared, Bimba Hoyer: None declared, Matthias Laudes Speakers bureau: AstraZeneca, Lilly, Bayer, Consultant of: AstraZeneca, Lilly, Bayer.

Effects of a Protein Optimized Diet Combined with Moderate Resistance Training on the Postoperative Course in Older Patients with Hip Fracture

Aims Dipeptidylpeptidase is a key regulator of the incretin system. Initially, it's soluble form (sDPP-4) was described as an adipokine mediating metabolic inflammation. This is recently questioned in mechanistic rodent studies. To further clarify sDPP-4's role in physiology and metabolic diseases, we examined sDPP-4 in a large human cohort and during weight-loss interventions. Like ACE2, sDPP-4 serves as a binding partner for certain corona-like viruses enabling virus entry. As metabolic diseases are major risk factors for the COVID-19 pandemic, we additionally examined sDPP-4 in patients suffering severe Sars-CoV-2 infection.

Introduction & Methods Both Bile Acids (BAs) and nutrition are important factors in the mediation of microbial effects on the human metabolism and metabolic diseases like T2 D. We aim to explore the BA-Host-Microbiome intersection by determining metabolic processes in the gut microbial community (GMC) and their interaction with BA levels.

Zusammenfassung. In diesem Beitrag soll die wechselhafte Geschichte des Gesetzes anhand historischer Quellen sowie eigener Unterlagen und Erinnerungen nachvollzogen werden. Dabei ergeben sich fünf historische Phasen. Zeit des Aufbruchs: In den 1960er Jahren traten durch die Entwicklung der Verhaltenstherapie als einem psychologischen Therapieansatz wesentliche Veränderungen des Selbstverständnisses und der Tätigkeitsbereiche der Klinischen Psychologen ein. Der BDP beschließt, eine gesetzliche Regelung für eine selbstständige Tätigkeit eines „Fachpsychologen für Klinische Psychologie“ anzustreben. 1973 empfiehlt die Psychiatrie Enquete-Kommission ein Gesetz für nichtärztliche Psychotherapeuten als eine der Sofortmaßnahmen. Erster Anlauf (1974 – 1978): Die Bundesregierung beginnt 1974 mit der Arbeit. Die Grundzüge werden allgemein begrüßt. Als erst vier Jahre später der Referentenentwurf vorgestellt wird, wird dieser jedoch mehrheitlich abgelehnt. „Interregnum“ (1978 – 1989): Das BMG stellt die Arbeit am Gesetz ein. Das Bundessozialministerium unternimmt seinerseits Maßnahmen zur Verbesserung der psychotherapeutischen Versorgung. Die Verhaltenstherapie wird Kassenleistung und die KBV fördert und akkreditiert private Ausbildungsinstitute für Verhaltenstherapie. Parallel dazu fördert die Föderation Deutscher Psychologenverbände universitäre Weiterbildungsgänge und akkreditiert diese. Ein von Gesundheitsministerin Ursula Lehr beauftragtes Gutachten empfiehlt 1991 ein Gesetz. Dies zieht Abwehrreaktionen der Ärzteschaft nach sich. Zweiter Anlauf (1993 – 1995): Das BMG beginnt erneut mit der Arbeit, intensiv begleitet von den inzwischen vielfältigen Berufs-und Fachverbänden. Das Gesetz scheitert im Bundesrat an der sogenannten Zuzahlungsregelung. Dritter Anlauf (1996 – 1999): 1997 beginnt das BMG erneut mit der Arbeit, beschränkt auf das Sozialrecht. Die Zuzahlungsregelung wird in einem gesonderten Gesetz geregelt. Am 06.03.98 stimmt als letzte Instanz der Bundesrat zu; der Einspruch gegen das Zuzahlungsgesetz wird mit einer Stimme Mehrheit abgelehnt.

MiRNAs represent a class of small non-coding RNAs which are involved in regulation of protein-coding gene expression. Being implicated in various processes such as development and regulatory circuits of cells, miRNAs also play an important role in the etiology of a variety of diseases. Imbalance of the regulatory processes within immune system development and response may lead to disturbed production of pro-inflammatory cytokines and over-reactivity of the immune cells, thus causing relapsing inflammation, a characteristic feature of inflammatory bowel disease (IBD). Recent studies of colonic miRNAs employed NGS for the distinction between CD, UC and healthy controls, or among different CD subtypes. However, NGS-based profiles of blood-circulating miRNAs have thus far not been investigated in the context of IBD together with other immune-mediated diseases, including ankylosing spondylitis, psoriasis, systemic lupus erythematosus, rheumatoid arthritis and sarcoidosis, as well as non-immune hemolytic-uremic syndrome. Study participants were recruited in Germany and Sweden, where peripheral blood samples (PAXgene) as well as phenotypical and clinical information (such as treatment status, disease activity and location) was collected. Small RNA transcriptomes of 680 individuals (Figure 1) were sequenced using Illumina NGS platform. Small RNA-seq data preprocessing and quantification were performed using cutadapt and miraligner (ref. miRBase v22), respectively. Differential expression analysis (DESeq2) and correlation (Spearman) analysis have been performed to identify disease activity-, trait- and treatment-specific miRNA signatures. These signatures were then utilized in a machine-learning approach to build classification models for IBD diagnostics. The results of multiple pairwise differential expression analyses among different immune-mediated inflammatory conditions and healthy controls revealed inflammation-specific as well and disease-specific deregulation of miRNAs. Correlation analysis identified miRNAs positively and negatively correlated with IBD activity. The preliminary results of machine learning classifiers based on miRNA profiles showed that median Matthews correlation coefficient for all model types showed remarkable predictive performance estimated as being 1.00 (median over main diagnoses), as well as ranging from 0.68 to 0.76 (median over CD location) and from 0.69 to 0.77 (median over UC extent). Immune-mediated inflammatory diseases share common and distinct differentially expressed miRNAs, which have a potential to be used in the diagnostics of IBD, including the evaluation of the disease activity.

Objective: Long-term follow-ups several years after receiving cognitive behavioral therapy (CBT) are scarce and most of the existing literature describes follow-up data of randomized-controlled trials. Thus, very little is known about the long-term effects of CBT in routine care. Methods: We investigated psychological functioning in a sample of 263 former outpatients who had received CBT for a variety of mental disorders such as depression, anxiety-, eating- or somatoform disorders 8.06 (SD 5.08) years after treatment termination. All participants completed a diagnostic interview as well as the Brief-Symptom Inventory (BSI) and the Beck Depression Inventory (BDI). Effect sizes and response rates according to Jacobson and Truax [J Consult Clin Psychol 1991;59:12-9] were calculated from pre- to posttreatment and from pretreatment to follow-up assessment. Results: Pre- to posttreatment effect sizes ranged between 0.75 (BDI) and 0.63 (BSI) and pretreatment to follow-up effect sizes were 0.92 (BDI) and 0.75 (BSI). Of all patients, 29% (BDI) and 17% (BSI) experienced clinically significant change at posttreatment and 42% (BDI) and 24% (BSI) at follow-up. Conclusion: The results point to the long-term effectiveness of CBT under routine conditions for a wide array of problems, especially when compared to the long-term effects of medical treatment. It is noteworthy that the results at follow-up were even better than at posttreatment, indicating further improvement. However, about a quarter of the patients did not respond sufficiently to therapy, neither concerning short-term nor long-term effects.

This paper aims to provide researchers with practical information on sample sizes for accurate estimations of therapist effects (TEs). The investigations are based on an integrated sample of 48,648 patients treated by 1800 therapists. Multilevel modeling and resampling were used to realize varying sample size conditions to generate empirical estimates of TEs. Sample size tables, including varying sample size conditions, were constructed and study examples given. This study gives an insight into the potential size of the TE and provides researchers with a practical guide to aid the planning of future studies in this field.

Introduction: Subjects with Chronic inflammatory diseases (CID) exhibit a profound increase of cardiovascular risk (CVR) resulting in reduced life expectancy. At the same time LDL-cholesterol serum levels seem to be low in these patients suggesting a special type of “rheumatic dyslipidemia”.

BackgroundOne of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology. ObjectiveThe aim of the present study was to identify predictors of dropout from this Web program. MethodsA total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants’ age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method. ResultsThe dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout. ConclusionsWomen with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer them additional support to prevent them from prematurely discontinuing treatment.

Background: Direct psychotherapy measures evaluate treatment outcome in an economic single point measurement. The Bochum Change Questionnaire 2000 (BCQ-2000) was developed for this purpose as a revised and shortened form of the Questionnaire to Assess Changes in Experiencing and Behavior (QCEB; Zielke & Kopf-Mehnert, 1978). Objective: The BCQ-2000 was subjected to a test-theoretical re-analysis with focus on criterion validity and included the definition of critical change values on the basis of a clinical wait-control group. Method: Psychotherapy outcome for n = 205 outpatients was assessed by various instruments to determine treatment success. Based on a wait control group (n = 88), critical change values were calculated. Results: The BCQ-2000 shows a high internal consistency (alpha = .96; 26 items) and meaningful correlations with other psychotherapy outcome measures, especially with measures of goal attainment. Critical change values allow the evaluation of therapy outcome in single cases. Conclusion: The BCQ-2000 is an understandable, economic, reliable, and valid instrument for the direct measurement of psychotherapy outcome.

Background: Most factor-analytic studies on the dimensionality of psychotherapy outcome show so-called method factors. Some studies contrast two-point measurements (pre-post) and single-point measurements (post). This is interpreted as a result of a different time perspective (pre-post versus retrospective measures). Objective: Is a different time perspective of the outcome measures an appropriate explanation for the divergence? Method: An exploratory factor analysis of various evaluation instruments including different types of retrospective approaches is conducted. Results: A two-factor structure with the components "change" and "end state functioning/goal attainment" can be shown. Different types of retrospective approaches can be assigned to different factors. Conclusions: Statistical characteristics of difference scores are in contrast with a subjective heuristic for therapy outcome that focuses goal attainment. Retrospective measures cannot be seen as a coherent class of evaluation strategies.

Theoretischer Hintergrund: In faktorenanalytischen Untersuchungen verschiedener Psychotherapieerfolgswerte resultieren meist sogenannte Methodenfaktoren. Hierbei lassen sich Zwei-Punkt-Messungen (Prä-Post) von Ein-Punkt-Messungen zu Therapieende (Post) trennen. Einige Studien betrachten diese Divergenz der Erfolgswerte als Ergebnis einer unterschiedlichen Zeitperspektive (Veränderungsmaße versus retrospektive Erfolgsbeurteilungen). Fragestellung: Ist die unterschiedliche Zeitperspektive tatsächlich für die Divergenz der Erfolgswerte verantwortlich? Methode: Über vorhandene Studien hinausgehend werden Patienten (N = 59) aufgefordert ihre Prä-Werte zu Therapieende abermals retrospektiv zu schätzen (Retro). Retro-Post Differenzwerte werden als retrospektives Maß der Veränderung zusätzlich in eine Faktorenanalyse verschiedener Erfolgswerte einbezogen. Ergebnisse: Es lässt sich eine zweifaktorielle Struktur mit den Komponenten „Veränderung” und „Restsymptomatik/Zielerreichung” zeigen. Verschiedene retrospektive Strategien müssen unterschiedlichen Faktoren zugeordnet werden. Schlussfolgerungen: Differenzwerte (Prä-Post, Retro-Post) lassen sich komplementär von einer subjektiven Heuristik der Erfolgsbeurteilung abgrenzen, die einen Abgleich von aktuellem Befinden und Zielvorstellungen vornimmt. Hierbei spielt die Retrospektivität der Erhebung–also die Zeitperspektive–nur eine untergeordnete Rolle.

BackgroundPrevious research has demonstrated an association between low motivation to change and an unfavorable treatment outcome in patients with an eating disorder. Consequently, various studies have examined the effects of motivational enhancement therapy (MET) on motivation to change and treatment outcome in eating disorders. In each of these studies, MET was administered in a face-to-face setting. However, because of its anonymity and ease of access, the internet provides several advantages as the format for such an intervention. Therefore, the current study investigated the effects of an internet-based program (‘ESS-KIMO’) to enhance motivation to change in eating disorders.MethodIn total, 212 females were accepted for participation and assigned randomly to the intervention condition (n = 103) or waiting-list control condition (n = 109). The intervention consisted of six online MET sessions. Before and after the intervention or waiting period respectively, participants completed the Eating Disorder Examination Questionnaire (EDE-Q), the Stages of Change Questionnaire for Eating Disorders (SOCQ-ED), the Pros and Cons of Eating Disorders Scale (P-CED), the Self-Efficacy Scale (SES), and the Rosenberg Self-Esteem Scale (RSES). A total of 125 participants completed the assessment post-treatment. Completer analyses and intent-to-treat analyses were performed.ResultsSignificant time × group interactions were found, indicating a stronger increase in motivational aspects and self-esteem, in addition to a stronger symptom reduction on some measures from pre- to post-treatment in the intervention group compared to the control group.ConclusionsInternet-based approaches can be considered as useful for enhancing motivation to change in eating disorders and for yielding initial symptomatic improvement.