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Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
S1P and its receptors have been reported to play important roles in the development of renal fibrosis. Although S1P5 has barely been investigated so far, there are indications that it can influence inflammatory and fibrotic processes. Here, we report the role of S1P5 in renal inflammation and fibrosis. Male S1P5 knockout mice and wild-type mice on a C57BL/6J background were fed with an adenine-rich diet for 7 days or 14 days to induce tubulointerstitial fibrosis. The kidneys of untreated mice served as respective controls. Kidney damage, fibrosis, and inflammation in kidney tissues were analyzed by real-time PCR, Western blot, and histological staining. Renal function was assessed by plasma creatinine ELISA. The S1P5 knockout mice had better renal function and showed less kidney damage, less proinflammatory cytokine release, and less fibrosis after 7 days and 14 days of an adenine-rich diet compared to wild-type mice. S1P5 knockout ameliorates tubular damage and tubulointerstitial fibrosis in a model of adenine-induced nephropathy in mice. Thus, targeting S1P5 might be a promising goal for the pharmacological treatment of kidney diseases.
Despite good clinical functional outcome, deficits in gait biomechanics exist 2 years after total hip replacement surgery. The aims of this research were (1) to group patients showing similar gait adaptations to hip osteoarthritis and (2) to investigate the effect of the surgical treatment on gait kinematics and external joint moments. In a secondary analysis, gait data of 51 patients with unilateral hip osteoarthritis were analyzed. A k-means cluster analysis was performed on scores derived via a principal component analysis of the gait kinematics. Preoperative and postoperative datasets were statistically tested between clusters and 46 healthy controls. The first three principal components incorporated hip flexion/extension, pelvic tilt, foot progression angle and thorax tilt. Two clusters were discriminated best by the peak hip extension during terminal stance. Both clusters deviated from healthy controls in spatio-temporal, kinematic and kinetic parameters. The cluster with less hip extension deviated significantly more. The clusters improved postoperatively but differences to healthy controls were still present one year after surgery. A poor preoperative gait pattern in patients with unilateral hip osteoarthritis is associated with worse gait kinematics after total hip replacement. Further research should focus on the identification of patients who can benefit from an adapted or individualized rehabilitation program.
Background: Treatment options for poorly differentiated (PDTC) and anaplastic (ATC) thyroid carcinoma are unsatisfactory and prognosis is generally poor. Lenvatinib (LEN), a multi-tyrosine kinase inhibitor targeting fibroblast growth factor receptors (FGFR) 1-4 is approved for advanced radioiodine refractory thyroid carcinoma, but response to single agent is poor in ATC. Recent reports of combining LEN with PD-1 inhibitor pembrolizumab (PEM) are promising. Materials and Methods: Primary ATC (n=93) and PDTC (n=47) tissue samples diagnosed 1997-2019 at five German tertiary care centers were assessed for PD-L1 expression by immunohistochemistry using Tumor Proportion Score (TPS). FGFR 1-4 mRNA was quantified in 31 ATC and 14 PDTC with RNAscope in-situ hybridization. Normal thyroid tissue (NT) and papillary thyroid carcinoma (PTC) served as controls. Disease specific survival (DSS) was the primary outcome variable. Results: PD-L1 TPS≥50% was observed in 42% of ATC and 26% of PDTC specimens. Mean PD-L1 expression was significantly higher in ATC (TPS 30%) than in PDTC (5%; p<0.01) and NT (0%, p<0.001). 53% of PDTC samples had PD-L1 expression ≤5%. FGFR mRNA expression was generally low in all samples but combined FGFR1-4 expression was significantly higher in PDTC and ATC compared to NT (each p<0.001). No impact of PD-L1 and FGFR 1-4 expression was observed on DSS. Conclusion: High tumoral expression of PD-L1 in a large proportion of ATCs and a subgroup of PDTCs provides a rationale for immune checkpoint inhibition. FGFR expression is low thyroid tumor cells. The clinically observed synergism of PEM with LEN may be caused by immune modulation.
Cutaneous T cell lymphomas (CTCLs) represent a heterogeneous group of T cell lymphomas that primarily affect the skin. The most frequent forms of CTCL are mycosis fungoides and Sézary syndrome. Both are characterized by frequent recurrence, developing chronic conditions and high mortality with a lack of a curative treatment. In this study, we evaluated the effect of short-chain, cell-permeable C6 Ceramide (C6Cer) on CTCL cell lines and keratinocytes. C6Cer significantly reduced cell viability of CTCL cell lines and induced cell death via apoptosis and necrosis. In contrast, primary human keratinocytes and HaCaT keratinocytes were less affected by C6Cer. Both keratinocyte cell lines showed higher expressions of ceramide catabolizing enzymes and HaCaT keratinocytes were able to metabolize C6Cer faster and more efficiently than CTCL cell lines, which might explain the observed protective effects. Along with other existing skin-directed therapies, C6Cer could be a novel well-tolerated drug for the topical treatment of CTCL.
HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
(2021)
Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10−3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
Objective: Liver stiffness measurement (LSM) is a tool used to screen for significant fibrosis and portal hypertension. The aim of this retrospective multicentre study was to develop an easy tool using LSM for clinical outcomes in advanced chronic liver disease (ACLD) patients.
Design: This international multicentre cohort study included a derivation ACLD patient cohort with valid two-dimensional shear wave elastography (2D-SWE) results. Clinical and laboratory parameters at baseline and during follow-up were recorded. LSM by transient elastography (TE) was also recorded if available. The primary outcome was overall mortality. The secondary outcome was the development of first/further decompensation.
Results: After screening 2148 patients (16 centres), 1827 patients (55 years, 62.4% men) were included in the 2D-SWE cohort, with median liver SWE (L-SWE) 11.8 kPa and a model for end stage liver disease (MELD) score of 8. Combination of MELD score and L-SWE predict independently of mortality (AUC 0.8). L-SWE cut-off at ≥20 kPa combined with MELD ≥10 could stratify the risk of mortality and first/further decompensation in ACLD patients. The 2-year mortality and decompensation rates were 36.9% and 61.8%, respectively, in the 305 (18.3%) high-risk patients (with L-SWE ≥20 kPa and MELD ≥10), while in the 944 (56.6%) low-risk patients, these were 1.1% and 3.5%, respectively. Importantly, this M10LS20 algorithm was validated by TE-based LSM and in an additional cohort of 119 patients with valid point shear SWE-LSM.
Conclusion: The M10LS20 algorithm allows risk stratification of patients with ACLD. Patients with L-SWE ≥20 kPa and MELD ≥10 should be followed closely and receive intensified care, while patients with low risk may be managed at longer intervals.