Proteomic Analysis of an Induced Pluripotent Stem Cell Model Reveals Strategies to Treat Juvenile Myelomonocytic Leukemia.

Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative neoplasm of early childhood with a poor survival rate, thus there is a requirement for improved treatment strategies. Induced pluripotent stem cells offer the ability to model disease and develop new treatment strategies. JMML is frequently associated with mutations in PTPN11. Children with Noonan syndrome, a development disorder, have an increased incidence of JMML associated with specific germline mutations in PTPN11. We undertook a proteomic assessment of myeloid cells derived from induced pluripotent stem cells obtained from Noonan syndrome patients with PTPN11 mutations, either associated or not associated with an increased incidence of JMML. We report that the proteomic perturbations induced by the leukemia-associated PTPN11 mutations are associated with TP53 and NF-Kκb signaling. We have previously shown that MYC is involved in the differential gene expression observed in Noonan syndrome patients associated with an increased incidence of JMML. Thus, we employed drugs to target these pathways and demonstrate differential effects on clonogenic hematopoietic cells derived from Noonan syndrome patients, who develop JMML and those who do not. Further, we demonstrated these small molecular inhibitors, JQ1 and CBL0137, preferentially extinguish primitive hematopoietic cells from sporadic JMML patients as opposed to cells from healthy individuals.

Application of SWATH mass spectrometry in the identification of circulating proteins does not predict future weight gain in early psychosis.

Weight gain is a common consequence of treatment with antipsychotic drugs in early psychosis, leading to further morbidity and poor treatment adherence. Identifying tools that can predict weight change in early psychosis may contribute to better-individualised treatment and adherence. Recently we showed that proteomic profiling with sequential window acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry (MS) can identify individuals with pre-diabetes more likely to experience weight change in relation to lifestyle change. We investigated whether baseline proteomic profiles predicted weight change over time using data from the BeneMin clinical trial of the anti-inflammatory antibiotic, minocycline, versus placebo. Expression levels for 844 proteins were determined by SWATH proteomics in 83 people (60 men and 23 women). Hierarchical clustering analysis and principal component analysis of baseline proteomics data did not reveal distinct separation between the proteome profiles of participants in different weight change categories. However, individuals with the highest weight loss had higher Positive and Negative Syndrome Scale (PANSS) scores. Our findings imply that mode of treatment i.e. the pharmacological intervention for psychosis may be the determining factor in weight change after diagnosis, rather than predisposing proteomic dynamics.

Identification of a Biomarker Panel for Early Detection of Lung Cancer Patients.

Lung cancer is the most common cause of cancer-related mortality worldwide, characterized by late clinical presentation (49-53% of patients are diagnosed at stage IV) and consequently poor outcomes. One challenge in identifying biomarkers of early disease is the collection of samples from patients prior to symptomatic presentation. We used blood collected during surgical resection of lung tumors in an iTRAQ isobaric tagging experiment to identify proteins effluxing from tumors into pulmonary veins. Forty proteins were identified as having an increased abundance in the vein draining from the tumor compared to "healthy" pulmonary veins. These protein markers were then assessed in a second cohort that utilized the mass spectrometry (MS) technique: Sequential window acquisition of all theoretical fragment ion spectra (SWATH) MS. SWATH-MS was used to measure proteins in serum samples taken from 25 patients <50 months prior to and at lung cancer diagnosis and 25 matched controls. The SWATH-MS analysis alone produced an 11 protein marker panel. A machine learning classification model was generated that could discriminate patient samples from patients within 12 months of lung cancer diagnosis and control samples. The model was evaluated as having a mean AUC of 0.89, with an accuracy of 0.89. This panel was combined with the SWATH-MS data from one of the markers from the first cohort to create a 12 protein panel. The proteome signature developed for lung cancer risk can now be developed on further cohorts.

A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods.

OBJECTIVES: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns. STUDY DESIGN AND SETTING: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns. RESULTS: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation. CONCLUSION: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.

10-year multimorbidity patterns among people with and without rheumatic and musculoskeletal diseases: an observational cohort study using linked electronic health records from Wales, UK.

OBJECTIVES: To compare the patterns of multimorbidity between people with and without rheumatic and musculoskeletal diseases (RMDs) and to describe how these patterns change by age and sex over time, between 2010 and 2019. PARTICIPANTS: 103 426 people with RMDs and 2.9 million comparators registered in 395 Wales general practices (GPs). Each patient with an RMD aged 0-100 years between January 2010 and December 2019 registered in Clinical Practice Research Welsh practices was matched with up to five comparators without an RMD, based on age, gender and GP code. PRIMARY OUTCOME MEASURES: The prevalence of 29 Elixhauser-defined comorbidities in people with RMDs and comparators categorised by age, gender and GP practices. Conditional logistic regression models were fitted to calculate differences (OR, 95% CI) in associations with comorbidities between cohorts. RESULTS: The most prevalent comorbidities were cardiovascular risk factors, hypertension and diabetes. Having an RMD diagnosis was associated with a significantly higher odds for many conditions including deficiency anaemia (OR 1.39, 95% CI (1.32 to 1.46)), hypothyroidism (OR 1.34, 95% CI (1.19 to 1.50)), pulmonary circulation disorders (OR 1.39, 95% CI 1.12 to 1.73) diabetes (OR 1.17, 95% CI (1.11 to 1.23)) and fluid and electrolyte disorders (OR 1.27, 95% CI (1.17 to 1.38)). RMDs have a higher proportion of multimorbidity (two or more conditions in addition to the RMD) compared with non-RMD group (81% and 73%, respectively in 2019) and the mean number of comorbidities was higher in women from the age of 25 and 50 in men than in non-RMDs group. CONCLUSION: People with RMDs are approximately 1.5 times as likely to have multimorbidity as the general population and provide a high-risk group for targeted intervention studies. The individuals with RMDs experience a greater load of coexisting health conditions, which tend to manifest at earlier ages. This phenomenon is particularly pronounced among women. Additionally, there is an under-reporting of comorbidities in individuals with RMDs.

Some patients with irritable bowel syndrome may have exocrine pancreatic insufficiency.

BACKGROUND & AIMS: Patients with irritable bowel syndrome (IBS) might have other underlying pathologies. Pancreatic disease can be elusive-especially in the early stages, and some symptoms overlap with those of IBS. We evaluated the prevalence of exocrine pancreatic insufficiency in diarrhea-predominant IBS (D-IBS) and assessed the effects of pancreatic enzyme supplementation. METHODS: The study included patients who met the Rome II criteria for D-IBS, patients with chronic diarrhea, and subjects without diarrhea (controls). Subjects' baseline weight, stool frequency, stool consistency (using the Bristol score), and fecal elastase-1 (Fel-1) levels were determined. Patients were assessed using British Society of Gastroenterology IBS guidelines. Patients with Fel-1 levels less than 100 microg/g stool (indicating pancreatic exocrine insufficiency; group 1) were compared with age- and sex-matched patients with D-IBS and normal levels of Fel-1 (group 2), given pancreatic enzyme therapy, and reassessed at 12 weeks. RESULTS: Fel-1 levels were less than 100 microg/g in stool from 19 of 314 patients with D-IBS (6.1%; 95% confidence interval [CI], 3.7%-9.3%), none of the 105 patients with chronic diarrhea (95% CI, 0.0%-3.5%), and none of 95 controls (95% CI, 0.0-3.8%) (P < .001). After enzyme supplementation, improvements in stool frequency (P < .001), stool consistency (P < .001), and abdominal pain (P = .003) were observed in patients in group 1, but not in group 2. CONCLUSIONS: Pancreatic exocrine insufficiency was detected in 6.1% of patients who fulfilled the Rome II criteria for D-IBS. In these patients, pancreatic enzyme therapy might reduce diarrhea and abdominal pain. Pancreatic exocrine insufficiency should be considered in patients with D-IBS.