Efficacy of tyrosine kinase inhibitors examined by a combination of Raman micro-spectroscopy and a deep wavelet scattering-based multivariate analysis framework.

HER2 is a crucial therapeutic target in breast cancer, and the survival rate of breast cancer patients has increased because of this receptor's inhibition. However, tumors have shown resistance to this therapeutic strategy due to oncogenic mutations that decrease the binding of several HER2-targeted drugs, including lapatinib, and confer resistance to this drug. Neratinib can overcome this drug resistance and effectively inhibit HER2 signaling and tumor growth. In the present study, we examined the efficacy of lapatinib and neratinib using breast cancer cells by Raman microscopy combined with a deep wavelet scattering-based multivariate analysis framework. This approach discriminated between control cells and drug-treated cells with high accuracy, compared to classical principal component analysis. Both lapatinib and neratinib induced changes in the cellular biochemical composition. Furthermore, the Raman results were compared with the results of several in vitro assays. For instance, drug-treated cells exhibited (i) inhibition of ERK and AKT phosphorylation, (ii) inhibition of cellular proliferation, (iii) cell-cycle arrest, and (iv) apoptosis as indicated by western blotting, real-time cell analysis (RTCA), cell-cycle analysis, and apoptosis assays. Thus, the observed Raman spectral changes are attributed to cell-cycle arrest and apoptosis. The results also indicated that neratinib is more potent than lapatinib. Moreover, the uptake and distribution of lapatinib in cells were visualized through its label-free marker bands in the fingerprint region using Raman spectral imaging. These results show the prospects of Raman microscopy in drug evaluation and presumably in drug discovery.

Serum neurofilament light chain does not detect self-reported treatment-related fluctuations in chronic inflammatory demyelinating polyneuropathy.

INTRODUCTION: Serum neurofilament light chain (sNfL) is a marker for axonal degeneration. Patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) often report a fluctuation of symptoms throughout one treatment cycle with intravenous immunoglobulins (IVIG). The aim of this study was to determine whether sNfL is suitable to quantify patient-reported symptom fluctuations. METHODS: Twenty-nine patients with the diagnosis of CIDP or a CIDP-variant under treatment with IVIG were recruited in this study and underwent examination before IVIG infusion, in the middle of the treatment interval, and before their next IVIG infusion. Patients were surveyed regarding symptom fluctuations at the last visit and divided into two groups: those with and without fluctuations of symptoms. At the first visit, sociodemographic and disease-specific data were collected. Clinical scores were assessed at every examination. sNfL values were compared between both groups at the different time points after conversion into Z-scores-adjusted for age and body mass index. RESULTS: Patients with CIDP show elevated sNfL Z-scores (median at baseline: 2.14, IQR: 1.0). There was no significant change in sNfL Z-scores or questionnaire scores within the treatment cycle in either group. There was no significant difference in sNfL levels between the patients with and without symptom fluctuations. CONCLUSIONS: CIDP patients show elevated sNfL levels. However, sNfL is not suitable to reflect patient-reported fluctuations of symptoms. This indicates that symptom fluctuations during treatment with IVIG in patients with CIDP are not caused by a neuroaxonal injury. Furthermore, repeated sNfL measurements within one treatment cycle with IVIG seem to have no benefit for symptom monitoring.

Subjective cognitive complaints and blood biomarkers of neurodegenerative diseases: a longitudinal cohort study.

BACKGROUND: Subjective cognitive complaints (SCC) have been mostly studied in the context of Alzheimer's disease in memory clinic settings. The potential of combining SCC with genetic information and blood biomarkers of neurodegenerative diseases for risk assessment of dementia and depression in the absence of dementia among community-dwelling older adults has so far not been explored. METHODS: Data were based on a population-based cohort of 6357 participants with a 17-year follow-up (ESTHER study) and a clinic-based cohort of 422 patients. Participants of both cohorts were grouped according to the diagnosis of dementia (yes/no) and the diagnosis of depression in the absence of dementia (yes/no). Participants without dementia included both cognitively unimpaired participants and cognitively impaired participants. Genetic information (APOE ε4 genotype) and blood-based biomarkers of neurodegenerative diseases (glial fibrillary acidic protein; GFAP, neurofilament light chain; NfL, phosphorylated tau181; p-tau181) were available in the ESTHER study and were determined with Simoa Technology in a nested case-control design. Logistic regression models adjusted for relevant confounders were run for the outcomes of all-cause dementia and depression in the absence of dementia. RESULTS: The results showed that persistent SCC were associated both with increased risk of all-cause dementia and of depression without dementia, independently of the diagnostic setting. However, the results for the ESTHER study also showed that the combination of subjective complaints with APOE ε4 and with increased GFAP concentrations in the blood yielded a substantially increased risk of all-cause dementia (OR 5.35; 95%CI 3.25-8.81, p-value < 0.0001 and OR 7.52; 95%CI 2.79-20.29, p-value < 0.0001, respectively) but not of depression. Associations of NfL and p-tau181 with risk of all-cause dementia and depression were not statistically significant, either alone or in combination with SCC, but increased concentrations of p-tau181 seemed to be associated with an increased risk for depression. CONCLUSION: In community and clinical settings, SCC predict both dementia and depression in the absence of dementia. The addition of GFAP could differentiate between the risk of all-cause dementia and the risk of depression among individuals without dementia.

Assessment of MYC and TERT copy number variations in lung cancer using digital PCR.

OBJECTIVE: Lung cancer is the second most frequent cancer type and the most common cause of cancer-related deaths worldwide. Alteration of gene copy numbers are associated with lung cancer and the determination of copy number variations (CNV) is appropriate for the discrimination between tumor and non-tumor tissue in lung cancer. As telomerase reverse transcriptase (TERT) and v-myc avian myelocytomatosis viral oncogene homolog (MYC) play a role in lung cancer the aims of this study were the verification of our recent results analyzing MYC CNV in tumor and non-tumor tissue of lung cancer patients using an independent study group and the assessment of TERT CNV as an additional marker. RESULTS: TERT and MYC status was analyzed using digital PCR (dPCR) in tumor and adjacent non-tumor tissue samples of 114 lung cancer patients. The difference between tumor and non-tumor samples were statistically significant (p < 0.0001) for TERT and MYC. Using a predefined specificity of 99% a sensitivity of 41% and 51% was observed for TERT and MYC, respectively. For the combination of TERT and MYC the overall sensitivity increased to 60% at 99% specificity. We demonstrated that a combination of markers increases the performance in comparison to individual markers. Additionally, the determination of CNV using dPCR might be an appropriate tool in precision medicine.

Dimensionality reduction for deep learning in infrared microscopy: a comparative computational survey.

While infrared microscopy provides molecular information at spatial resolution in a label-free manner, exploiting both spatial and molecular information for classifying the disease status of tissue samples constitutes a major challenge. One strategy to mitigate this problem is to embed high-dimensional pixel spectra in lower dimensions, aiming to preserve molecular information in a more compact manner, which reduces the amount of data and promises to make subsequent disease classification more accessible for machine learning procedures. In this study, we compare several dimensionality reduction approaches and their effect on identifying cancer in the context of a colon carcinoma study. We observe surprisingly small differences between convolutional neural networks trained on dimensionality reduced spectra compared to utilizing full spectra, indicating a clear tendency of the convolutional networks to focus on spatial rather than spectral information for classifying disease status.

Alzheimer's polygenic risk scores, APOE, Alzheimer's disease risk, and dementia-related blood biomarker levels in a population-based cohort study followed over 17 years.

BACKGROUND: In order to utilize polygenic risk scores (PRSs) for Alzheimer's disease (AD) in a meaningful way, influential factors (i.e. training set) and prediction across groups such as APOE e4 (APOE4) genotype as well as associations to dementia-related biomarkers should be explored. Therefore, we examined the association of APOE4 and various PRSs, based on training sets that utilized differing AD definitions, with incident AD and all-cause dementia (ACD) within 17 years, and with levels of phosphorylated tau181 (P-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) in blood. Secondarily, effect modification by APOE4 status and sex was examined. METHODS: In this prospective, population-based cohort study and nested case-control study, 9,940 participants in Germany were enrolled between 2000 and 2002 by their general practitioners and followed for up to 17 years. Participants were included in this study if dementia status and genetic data were available. A subsample of participants additionally had measurements of P-tau181, NfL, and GFAP obtained from blood samples. Cox and logistic regression analyses were used to assess the association of genetic risk (APOE genotype and PRSnoAPOE) with incident ACD/AD and log-transformed blood levels of P-tau181, NfL, and GFAP. RESULTS: Five thousand seven hundred sixty-five participants (54% female, aged 50-75years at baseline) were included in this study, of whom 464 received an all-cause dementia diagnosis within 17 years. The PRSs were not more predictive of dementia than APOE4. An APOE4 specific relationship was apparent with PRSs only exhibiting associations to dementia among APOE4 carriers. In the nested case-control study including biomarkers (n = 712), APOE4 status and polygenic risk were significantly associated to levels of GFAP in blood. CONCLUSIONS: The use of PRSs may be beneficial for increased precision in risk estimates among APOE4 carriers. While APOE4 may play a crucial etiological role in initial disease processes such as Aß deposition, the PRS may be an indicator of further disease drivers as well as astrocyte activation. Further research is necessary to confirm these findings, especially the association to GFAP.

Fast and label-free automated detection of microsatellite status in early colon cancer using artificial intelligence integrated infrared imaging.

PURPOSE: Microsatellite instability (MSI) due to mismatch repair (MMR) defects accounts for 15-20% of colon cancers (CC). MSI testing is currently standard of care in CC with immunohistochemistry of the four MMR proteins representing the gold standard. Instead, label-free quantum cascade laser (QCL) based infrared (IR) imaging combined with artificial intelligence (AI) may classify MSI/microsatellite stability (MSS) in unstained tissue sections user-independently and tissue preserving. METHODS: Paraffin-embedded unstained tissue sections of early CC from patients participating in the multicentre AIO ColoPredict Plus (CPP) 2.0 registry were analysed after dividing into three groups (training, test, and validation). IR images of tissue sections using QCL-IR microscopes were classified by AI (convolutional neural networks [CNN]) using a two-step approach. The first CNN (modified U-Net) detected areas of cancer while the second CNN (VGG-Net) classified MSI/MSS. End-points were area under receiver operating characteristic (AUROC) and area under precision recall curve (AUPRC). RESULTS: The cancer detection in the first step was based on 629 patients (train n = 273, test n = 138, and validation n = 218). Resulting classification AUROC was 1.0 for the validation dataset. The second step classifying MSI/MSS was performed on 547 patients (train n = 331, test n = 69, and validation n = 147) reaching AUROC and AUPRC of 0.9 and 0.74, respectively, for the validation cohort. CONCLUSION: Our novel label-free digital pathology approach accurately and rapidly classifies MSI vs. MSS. The tissue sections analysed were not processed leaving the sample unmodified for subsequent analyses. Our approach demonstrates an AI-based decision support tool potentially driving improved patient stratification and precision oncology in the future.

Association of Kidney Function With Development of Alzheimer Disease and Other Dementias and Dementia-Related Blood Biomarkers.

Importance: Previous research has suggested an association of kidney function with risk of Alzheimer disease (AD) or other dementias and dementia-related blood biomarkers, but a distinct association remains unclear. Objective: To evaluate the association of kidney function with risk of diagnosis of incident AD or dementia within 17 years and with the blood biomarkers neurofilament light (NfL), phosphorylated tau181 (p-tau181), and glial fibrillary acidic protein (GFAP). Design, Setting, and Participants: In this prospective, population-based cohort study and nested case-control study, 9940 participants in Germany were enrolled between 2000 and 2002 by their general practitioners and followed up for up to 17 years. Participants were included if information on dementia status and creatinine/cystatin C measurements were available. A subsample of participants additionally had measurements of NfL, p-tau181, and GFAP obtained from blood samples. Statistical analysis was performed from January 3 to November 25, 2022. Exposures: Impaired kidney function, based on estimated glomerular filtration rate less than 60 mL/min/1.73 m2 according to the 2021 Chronic Kidney Disease Epidemiology Collaboration creatinine-cystatin C equation. Main Outcomes and Measures: All-cause dementia, AD, and vascular dementia diagnosis, as well as log-transformed levels of NfL, p-tau181, and GFAP in blood. Results: Of 6256 participants (3402 women [54.4%]; mean [SD] age at baseline, 61.7 [6.6] years), 510 received an all-cause dementia diagnosis within 17 years of baseline. The dementia-related blood biomarker nested case-control sample included 766 participants. After adjusting for age and sex, impaired kidney function at baseline was not associated with a higher risk of all-cause dementia (hazard ratio [HR], 0.95; 95% CI, 0.69-1.29), AD (HR, 0.94; 95% CI, 0.55-1.63), or vascular dementia diagnosis (HR, 1.06; 95% CI, 0.65-1.70) within 17 years. In the cross-sectional analysis, after adjusting for age and sex, impaired kidney function was significantly associated with NfL and p-tau181 levels in blood (NfL: ß = 0.47 and P < .001; p-tau181: ß = 0.21 and P = .003). After adjusting for age and sex, significant associations with GFAP levels were evident only among men (men: ß = 0.31 and P = .006; women: ß = -0.12 and P = .11). Conclusions and Relevance: In this population-based study of community-dwelling adults, reduced kidney function was associated with increased levels of dementia-related blood biomarkers but not increased dementia risk. Kidney function might influence the accuracy of dementia-related blood biomarkers and should be considered in clinical translation.

High cholesterol levels change the association of biomarkers of neurodegenerative diseases with dementia risk: Findings from a population-based cohort.

INTRODUCTION: This study assessed whether in a population with comorbidity of neurodegenerative and cerebrovascular disease (mixed pathology) the association of glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau181 (p-tau181) with dementia risk varied depending on levels of total cholesterol and apolipoprotein E (APOE) ε4 genotype. METHODS: Plasma biomarkers were measured using Simoa technology in 768 participants of a nested case-control study embedded within an ongoing population-based cohort. Logistic and spline regression models, and receiver operating characteristic curves were calculated. RESULTS: The strength of the association between GFAP and NfL with risk of a clinical diagnosis of dementia changed depending on cholesterol levels and on APOE ε4 genotype. No significant association was seen with p-tau181. DISCUSSION: In individuals with mixed pathology blood GFAP and NfL are better predictors of dementia risk than p-tau181, and their associations with dementia risk are amplified by hypercholesterolemia, also depending on APOE ε4 genotype. HIGHLIGHTS: Cholesterol levels changed the association of blood biomarkers with dementia risk. Blood biomarkers seem to perform differently in community- and clinic-based cohorts. Neurofilament light chain might be a biomarker candidate for dementia risk after stroke.

Association of plasma biomarkers, p-tau181, glial fibrillary acidic protein, and neurofilament light, with intermediate and long-term clinical Alzheimer's disease risk: Results from a prospective cohort followed over 17 years.

INTRODUCTION: Blood biomarkers for Alzheimer's disease (AD) are the future of AD risk assessment. The aim of this study was to determine the association between plasma-measured phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) levels and risk of clinical AD incidence with consideration to the impact of cardiovascular health. METHODS: Within a community-based cohort, biomarker levels were measured at baseline using single molecule array technology in 768 participants (aged 50-75) followed over 17 years. Associations among biomarkers and AD, vascular dementia, and mixed dementia incidence were assessed. RESULTS: GFAP was associated with clinical AD incidence even more than a decade before diagnosis (9-17 years), while p-tau181 and NfL were associated with more intermediate AD risk (within 9 years). Significant interaction was detected between cardiovascular health and p-tau181/NfL. DISCUSSION: GFAP may be an early AD biomarker increasing before p-tau181 and NfL and the effect modifying role of cardiovascular health should be considered in biomarker risk stratification.

A framework for falsifiable explanations of machine learning models with an application in computational pathology.

In recent years, deep learning has been the key driver of breakthrough developments in computational pathology and other image based approaches that support medical diagnosis and treatment. The underlying neural networks as inherent black boxes lack transparency and are often accompanied by approaches to explain their output. However, formally defining explainability has been a notorious unsolved riddle. Here, we introduce a hypothesis-based framework for falsifiable explanations of machine learning models. A falsifiable explanation is a hypothesis that connects an intermediate space induced by the model with the sample from which the data originate. We instantiate this framework in a computational pathology setting using hyperspectral infrared microscopy. The intermediate space is an activation map, which is trained with an inductive bias to localize tumor. An explanation is constituted by hypothesizing that activation corresponds to tumor and associated structures, which we validate by histological staining as an independent secondary experiment.

Amyloid-beta misfolding and GFAP predict risk of clinical Alzheimer's disease diagnosis within 17 years.

INTRODUCTION: Blood-based biomarkers for Alzheimer's disease (AD) are urgently needed. Here, four plasma biomarkers were measured at baseline in a community-based cohort followed over 17 years, and the association with clinical AD risk was determined. METHODS: Amyloid beta (Aß) misfolding status as a structure-based biomarker as well as phosphorylated tau 181 (P-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) concentration levels were determined at baseline in heparin plasma from 68 participants who were diagnosed with AD and 240 controls without dementia diagnosis throughout follow-up. RESULTS: Aß misfolding exhibited high disease prediction accuracy of AD diagnosis within 17 years. Among the concentration markers, GFAP showed the best performance, followed by NfL and P-tau181. The combination of Aß misfolding and GFAP increased the accuracy. DISCUSSION: Aß misfolding and GFAP showed a strong ability to predict clinical AD risk and may be important early AD risk markers. Aß misfolding illustrated its potential as a prescreening tool for AD risk stratification in older adults.

Update on CSF Biomarkers in Parkinson's Disease.

Progress in developing disease-modifying therapies in Parkinson's disease (PD) can only be achieved through reliable objective markers that help to identify subjects at risk. This includes an early and accurate diagnosis as well as continuous monitoring of disease progression and therapy response. Although PD diagnosis still relies mainly on clinical features, encouragingly, advances in biomarker discovery have been made. The cerebrospinal fluid (CSF) is a biofluid of particular interest to study biomarkers since it is closest to the brain structures and therefore could serve as an ideal source to reflect ongoing pathologic processes. According to the key pathophysiological mechanisms, the CSF status of α-synuclein species, markers of amyloid and tau pathology, neurofilament light chain, lysosomal enzymes and markers of neuroinflammation provide promising preliminary results as candidate biomarkers. Untargeted approaches in the field of metabolomics provide insights into novel and interconnected biological pathways. Markers based on genetic forms of PD can contribute to identifying subgroups suitable for gene-targeted treatment strategies that might also be transferable to sporadic PD. Further validation analyses in large PD cohort studies will identify the CSF biomarker or biomarker combinations with the best value for clinical and research purposes.

Aß misfolding in blood plasma is inversely associated with body mass index even in middle adulthood.

BACKGROUND: To understand the potential for early intervention and prevention measures in Alzheimer's disease, the association between risk factors and early pathological change needs to be assessed. Hence, the aim of this study was to determine whether risk factors of Alzheimer's clinical syndrome (clinical AD), such as body mass index (BMI), are associated with Aß misfolding in blood, a strong risk marker for AD among older adults. METHODS: Information on risk factors and blood samples were collected at baseline in the ESTHER study, a population-based cohort study of older adults (age 50-75 years) in Germany. Aß misfolding in blood plasma was analyzed using an immuno-infrared-sensor in a total of 872 participants in a nested case-control design among incident dementia cases and matched controls. Associations between risk factors and Aß misfolding were assessed by multiple logistic regression. For comparison, the association between the risk factors and AD incidence during 17 years of follow-up was investigated in parallel among 5987 cohort participants. RESULTS: An inverse association with Aß misfolding was seen for BMI at age 50 based on reported weight history (aOR 0.64, 95% CI 0.43-0.96, p = 0.03). Similar but not statistically significant associations were seen for BMI at baseline (i.e., mean age 68) and at age 40. No statistically significant associations with Aß misfolding were found for other risk factors, such as diabetes, smoking, and physical activity. On the other hand, low physical activity was associated with a significantly reduced risk of developing clinical AD compared to physical inactivity. CONCLUSIONS: Our results support that AD pathology may be detectable and associated with reduced weight even in middle adulthood, many years before clinical diagnosis of AD. Physical activity might reduce the risk of onset of AD symptoms.

Shape decomposition algorithms for laser capture microdissection.

BACKGROUND: In the context of biomarker discovery and molecular characterization of diseases, laser capture microdissection is a highly effective approach to extract disease-specific regions from complex, heterogeneous tissue samples. For the extraction to be successful, these regions have to satisfy certain constraints in size and shape and thus have to be decomposed into feasible fragments. RESULTS: We model this problem of constrained shape decomposition as the computation of optimal feasible decompositions of simple polygons. We use a skeleton-based approach and present an algorithmic framework that allows the implementation of various feasibility criteria as well as optimization goals. Motivated by our application, we consider different constraints and examine the resulting fragmentations. We evaluate our algorithm on lung tissue samples in comparison to a heuristic decomposition approach. Our method achieved a success rate of over 95% in the microdissection and tissue yield was increased by 10-30%. CONCLUSION: We present a novel approach for constrained shape decomposition by demonstrating its advantages for the application in the microdissection of tissue samples. In comparison to the previous decomposition approach, the proposed method considerably increases the amount of successfully dissected tissue.

The Ras dimer structure.

Oncogenic mutated Ras is a key player in cancer, but despite intense and expensive approaches its catalytic center seems undruggable. The Ras dimer interface is a possible alternative drug target. Dimerization at the membrane affects cell growth signal transduction. In vivo studies indicate that preventing dimerization of oncogenic mutated Ras inhibits uncontrolled cell growth. Conventional computational drug-screening approaches require a precise atomic dimer model as input to successfully access drug candidates. However, the proposed dimer structural models are controversial. Here, we provide a clear-cut experimentally validated N-Ras dimer structural model. We incorporated unnatural amino acids into Ras to enable the binding of labels at multiple positions via click chemistry. This labeling allowed the determination of multiple distances of the membrane-bound Ras-dimer measured by fluorescence and electron paramagnetic resonance spectroscopy. In combination with protein-protein docking and biomolecular simulations, we identified key residues for dimerization. Site-directed mutations of these residues prevent dimer formation in our experiments, proving our dimer model to be correct. The presented dimer structure enables computational drug-screening studies exploiting the Ras dimer interface as an alternative drug target.

The subcellular arrangement of alpha-synuclein proteoforms in the Parkinson's disease brain as revealed by multicolor STED microscopy.

Various post-translationally modified (PTM) proteoforms of alpha-synuclein (aSyn)-including C-terminally truncated (CTT) and Serine 129 phosphorylated (Ser129-p) aSyn-accumulate in Lewy bodies (LBs) in different regions of the Parkinson's disease (PD) brain. Insight into the distribution of these proteoforms within LBs and subcellular compartments may aid in understanding the orchestration of Lewy pathology in PD. We applied epitope-specific antibodies against CTT and Ser129-p aSyn proteoforms and different aSyn domains in immunohistochemical multiple labelings on post-mortem brain tissue from PD patients and non-neurological, aged controls, which were scanned using high-resolution 3D multicolor confocal and stimulated emission depletion (STED) microscopy. Our multiple labeling setup highlighted a consistent onion skin-type 3D architecture in mature nigral LBs in which an intricate and structured-appearing framework of Ser129-p aSyn and cytoskeletal elements encapsulates a core enriched in CTT aSyn species. By label-free CARS microscopy we found that enrichments of proteins and lipids were mainly localized to the central portion of nigral aSyn-immunopositive (aSyn+) inclusions. Outside LBs, we observed that 122CTT aSyn+ punctae localized at mitochondrial membranes in the cytoplasm of neurons in PD and control brains, suggesting a physiological role for 122CTT aSyn outside of LBs. In contrast, very limited to no Ser129-p aSyn immunoreactivity was observed in brains of non-neurological controls, while the alignment of Ser129-p aSyn in a neuronal cytoplasmic network was characteristic for brains with (incidental) LB disease. Interestingly, Ser129-p aSyn+ network profiles were not only observed in neurons containing LBs but also in neurons without LBs particularly in donors at early disease stage, pointing towards a possible subcellular pathological phenotype preceding LB formation. Together, our high-resolution and 3D multicolor microscopy observations in the post-mortem human brain provide insights into potential mechanisms underlying a regulated LB morphogenesis.

Application of Label-Free Proteomics for Quantitative Analysis of Urothelial Carcinoma and Cystitis Tissue.

A label-free approach based on a highly reproducible and stable workflow allows for quantitative proteome analysis . Due to advantages compared to labeling methods, the label-free approach has the potential to measure unlimited samples from clinical specimen monitoring and comparing thousands of proteins. The presented label-free workflow includes a new sample preparation technique depending on automatic annotation and tissue isolation via FTIR-guided laser microdissection, in-solution digestion, LC-MS/MS analyses, data evaluation by means of Proteome Discoverer and Progenesis software, and verification of differential proteins. We successfully applied this workflow in a proteomics study analyzing human cystitis and high-grade urothelial carcinoma tissue regarding the identification of a diagnostic tissue biomarker. The differential analysis of only 1 mm2 of isolated tissue cells led to 74 significantly differentially abundant proteins.

Genetic predisposition, Aß misfolding in blood plasma, and Alzheimer's disease.

Alzheimer's disease is highly heritable and characterized by amyloid plaques and tau tangles in the brain. The aim of this study was to investigate the association between genetic predisposition, Aß misfolding in blood plasma, a unique marker of Alzheimer associated neuropathological changes, and Alzheimer's disease occurrence within 14 years. Within a German community-based cohort, two polygenic risk scores (clinical Alzheimer's disease and Aß42 based) were calculated, APOE genotype was determined, and Aß misfolding in blood plasma was measured by immuno-infrared sensor in 59 participants diagnosed with Alzheimer's disease during 14 years of follow-up and 581 participants without dementia diagnosis. Associations between each genetic marker and Aß misfolding were assessed through logistic regression and the ability of each genetic marker and Aß misfolding to predict Alzheimer's disease was determined. The Alzheimer's disease polygenic risk score and APOE ε4 presence were associated to Aß misfolding (odds ratio, 95% confidence interval: per standard deviation increase of score: 1.25, 1.03-1.51; APOE ε4 presence: 1.61, 1.04-2.49). No association was evident for the Aß polygenic risk score. All genetic markers were predictive of Alzheimer's disease diagnosis albeit much less so than Aß misfolding (areas under the curve: Aß polygenic risk score: 0.55; AD polygenic risk score: 0.59; APOE ε4: 0.63; Aß misfolding: 0.84). Clinical Alzheimer's genetic risk was associated to early pathological changes (Aß misfolding) measured in blood, however, predicted Alzheimer's disease less accurately than Aß misfolding itself. Genetic predisposition may provide information regarding disease initiation, while Aß misfolding could be important in clinical risk prediction.