Citations

Abstract Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������

ImportanceA safe and effective treatment for recurrent Clostridioides difficile infection (CDI) is urgently needed. Antibiotics kill toxin-producing bacteria but do not repair the disrupted microbiome, which promotes spore germination and infection recurrence.ObjectivesTo evaluate the safety and rate of CDI recurrence after administration of investigational microbiome therapeutic SER-109 through 24 weeks.Design, Setting, and ParticipantsThis phase 3, single-arm, open-label trial (ECOSPOR IV) was conducted at 72 US and Canadian outpatient sites from October 2017 to April 2022. Adults aged 18 years or older with recurrent CDI were enrolled in 2 cohorts: (1) rollover patients from the ECOSPOR III trial who had CDI recurrence diagnosed by toxin enzyme immunoassay (EIA) and (2) patients with at least 1 CDI recurrence (diagnosed by polymerase chain reaction [PCR] or toxin EIA), inclusive of their acute infection at study entry.InterventionsSER-109 given orally as 4 capsules daily for 3 days following symptom resolution after antibiotic treatment for CDI.Main Outcomes and MeasuresThe main outcomes were safety, measured as the rate of treatment-emergent adverse events (TEAEs) in all patients receiving any amount of SER-109, and cumulative rates of recurrent CDI (toxin-positive diarrhea requiring treatment) through week 24 in the intent-to-treat population.ResultsOf 351 patients screened, 263 were enrolled (180 [68.4%] female; mean [SD] age, 64.0 [15.7] years); 29 were in cohort 1 and 234 in cohort 2. Seventy-seven patients (29.3%) were enrolled with their first CDI recurrence. Overall, 141 patients (53.6%) had TEAEs, which were mostly mild to moderate and gastrointestinal. There were 8 deaths (3.0%) and 33 patients (12.5%) with serious TEAEs; none were considered treatment related by the investigators. Overall, 23 patients (8.7%; 95% CI, 5.6%-12.8%) had recurrent CDI at week 8 (4 of 29 [13.8%; 95% CI, 3.9%-31.7%] in cohort 1 and 19 of 234 [8.1%; 95% CI, 5.0%-12.4%] in cohort 2), and recurrent CDI rates remained low through 24 weeks (36 patients [13.7%; 95% CI, 9.8%-18.4%]). At week 8, recurrent CDI rates in patients with a first recurrence were similarly low (5 of 77 [6.5%; 95% CI, 2.1%-14.5%]) as in patients with 2 or more recurrences (18 of 186 [9.7%; 95% CI, 5.8%-14.9%]). Analyses by select baseline characteristics showed consistently low recurrent CDI rates in patients younger than 65 years vs 65 years or older (5 of 126 [4.0%; 95% CI, 1.3%-9.0%] vs 18 of 137 [13.1%; 95% CI, 8.0%-20.0%]) and patients enrolled based on positive PCR results (3 of 69 [4.3%; 95% CI, 0.9%-12.2%]) vs those with positive toxin EIA results (20 of 192 [10.4%; 95% CI, 6.5%-15.6%]).Conclusions and RelevanceIn this trial, oral SER-109 was well tolerated in a patient population with recurrent CDI and prevalent comorbidities. The rate of recurrent CDI was low regardless of the number of prior recurrences, demographics, or diagnostic approach, supporting the beneficial impact of SER-109 for patients with CDI.Trial RegistrationClinicalTrials.gov identifier: NCT03183141

Carcinoma-associated fibroblasts (CAFs) play an important role in the progression of multiple malignancies. Secretion of cytokines and growth factors underlies the pro-tumoral effect of CAFs. Although this paracrine function has been extensively documented, the molecular mechanisms controlling the expression of these factors remain elusive. In this study, we provide evidence of a novel CAF transcriptional axis regulating the expression of SDF1, a major driver of cancer cell migration, involving the transcription factor GLI1 and histone acetyltransferase p300. We demonstrate that conditioned media from CAFs overexpressing GLI1 induce the migration of pancreatic cancer cells, and this effect is impaired by an SDF1-neutralizing antibody. Using a combination of co-immunoprecipitation, proximity ligation assay and chromatin immunoprecipitation assay, we further demonstrate that GLI1 and p300 physically interact in CAFs to co-occupy and drive SDF1 promoter activity. Mapping experiments highlight the requirement of GLI1 N-terminal for the interaction with p300. Importantly, knockdowns of both GLI1 and p300 reduce SDF1 expression. Further analysis shows that knockdown of GLI1 decreases SDF1 promoter activity, p300 recruitment, and levels of its associated histone marks (H4ac, H3K27ac, and H3K14ac). Finally, we show that the integrity of two GLI binding sites in the SDF1 promoter is required for p300 recruitment. Our findings define a new role for the p300–GLI1 complex in the regulation of SDF1, providing new mechanistic insight into the molecular events controlling pancreatic cancer cells migration.

Abstract There are few causes of treatable neurodevelopmental diseases described to date. Branched-chain ketoacid dehydrogenase kinase (BCKDK) deficiency causes branched-chain amino acid (BCAA) depletion and is linked to a neurodevelopmental disorder characterized by autism, intellectual disability and microcephaly. We report the largest cohort of patients studied, broadening the phenotypic and genotypic spectrum. Moreover, this is the first study to present newborn screening findings and mid-term clinical outcome. In this cross-sectional study, patients with a diagnosis of BCKDK deficiency were recruited via investigators’ practices through a MetabERN initiative. Clinical, biochemical and genetic data were collected. Dried blood spot (DBS) newborn screening (NBS) amino acid profiles were retrieved from collaborating centres and compared to a healthy newborn reference population. Twenty-one patients with BCKDK mutations were included from 13 families. Patients were diagnosed between 8 months and 16 years (mean: 5.8 years, 43% female). At diagnosis, BCAA levels (leucine, valine and isoleucine) were below reference values in plasma and in CSF. All patients had global neurodevelopmental delay; 18/21 had gross motor function (GMF) impairment with GMF III or worse in 5/18, 16/16 intellectual disability, 17/17 language impairment, 12/17 autism spectrum disorder, 9/21 epilepsy, 12/15 clumsiness, 3/21 had sensorineural hearing loss and 4/20 feeding difficulties. No microcephaly was observed at birth, but 17/20 developed microcephaly during follow-up. Regression was reported in six patients. Movement disorder was observed in 3/21 patients: hyperkinetic movements (1), truncal ataxia (1) and dystonia (2). After treatment with a high-protein diet (≥ 2 g/kg/day) and BCAA supplementation (100–250 mg/kg/day), plasma BCAA increased significantly (P &lt; 0.001), motor functions and head circumference stabilized/improved in 13/13 and in 11/15 patients, respectively. Among cases with follow-up data, none of the three patients starting treatment before 2 years of age developed autism at follow-up. The patient with the earliest age of treatment initiation (8 months) showed normal development at 3 years of age. NBS in DBS identified BCAA levels significantly lower than those of the normal population. This work highlights the potential benefits of dietetic treatment, in particular early introduction of BCAA. Therefore, it is of utmost importance to increase awareness about this treatable disease and consider it as a candidate for early detection by NBS programmes.

Abstract Background Biomarkers for predicting the development of Ulcerative Colitis (UC) and disease-related complications are lacking. Anti-integrin αvβ6 IgG autoantibodies (anti-αvβ6) have been recently described in patients diagnosed with UC. Here, we sought to determine if anti-αvβ6 autoantibodies predate UC development and to study associations between anti-αvβ6 and disease outcomes in newly diagnosed UC patients. Methods In a unique pre-clinical IBD cohort from the PRoteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects (PREDICTS), anti-αvβ6 were measured in longitudinal pre-diagnosis serum samples from 82 subjects who later developed UC as well as in 82 matched subjects that did not develop IBD (HC). Sample A was at the time of UC diagnosis, Sample B was at a median of 2 years before Sample A, Sample C was at a median of 4 years before Sample A and Sample D was at a median of 10 years before Sample A. In a distinct, external validation cohort (the Crohn’s and Colitis Canada Genetics Environment Microbial (GEM) Project), we tested samples from 12 subjects who later developed UC and compared those with 49 matched subjects who remained asymptomatic. Further, anti-αvβ6 were measured in 2 incident IBD cohorts (COMPASS, n=55 and OSCCAR, n=104 UC subjects) and associations between anti-αvβ6 and adverse UC-outcomes were defined using Cox proportional-hazards model. Results Anti-αvβ6 were significantly higher in the PREDICTS cohort among individuals who developed UC compared to HC up to 10 years prior to diagnosis (Figure 1A). The anti-αvβ6 seropositivity was 12.2% 10 years before diagnosis and increased to 52.4% at the time of diagnosis in subjects who developed UC compared with 2.7% in controls across the 4 timepoints. Additionally, the predictive performance of anti-αvβ6 autoantibodies as assessed via area under the receiver operator curves (AUROC) with 10-fold cross validation was at least 0.8 up to 10 years before diagnosis (Figure 1B). Elevated levels of anti-αvβ6 in pre-clinical UC samples were further validated in the GEM cohort (Figure 1C). Finally, high anti-αvβ6 were associated with a composite of adverse UC-outcomes including hospitalization, disease extension, colectomy, systemic steroid use and/or escalation to biologic therapy in both incident cohorts (Figure 1D). Conclusion Anti-integrin αvβ6 autoantibodies precede the clinical diagnosis of UC by up to 10 years and are associated with adverse UC-related outcomes.

Brain and spinal tumors affect 1 in 1000 people by 25 years of age, and have diverse histological, biological, anatomical and dissemination characteristics. A mortality of 30–40% means the majority are cured, although two-thirds have life-long disability, linked to accumulated brain injury that is acquired prior to diagnosis, and after surgery or chemo-radiotherapy. Only four drugs have been licensed globally for brain tumors in 40 years and only one for children. Most new cancer drugs in clinical trials do not cross the blood–brain barrier (BBB). Techniques to enhance brain tumor drug delivery are explored in this review, and cover those that augment penetration of the BBB, and those that bypass the BBB. Developing appropriate delivery techniques could improve patient outcomes by ensuring efficacious drug exposure to tumors (including those that are drug-resistant), reducing systemic toxicities and targeting leptomeningeal metastases. Together, this drug delivery strategy seeks to enhance the efficacy of new drugs and enable re-evaluation of existing drugs that might have previously failed because of inadequate delivery. A literature review of repurposed drugs is reported, and a range of preclinical brain tumor models available for translational development are explored.

AbstractBackgroundData on severe acute respiratory distress syndrome coronavirus 2 monoclonal antibody (SARS‐CoV‐2‐specific mAb) use in hematologic malignancy and hematopoietic cell transplantation (HM/HCT) patients are limited. Here, we describe our experience with the use of casirivimab–imdevimab or bamlanivimab for the treatment of coronavirus disease 2019 (COVID‐19) in HM/HCT patients.MethodsThis was a retrospective chart review at the University of Miami Hospital and Sylvester Comprehensive Cancer Center for HM/HCT patients with COVID‐19 who received casirivimab–imdevimab or bamlanivimab from November 21, 2020, to September 30, 2021. Outcomes measured were mortality, hospital admission, and infusion reaction to SARS‐CoV‐2‐specific mAbs.ResultsWe identified 59 HM/HCT patients with mild to moderate COVID‐19 who received casirivimab–imdevimab or bamlanivimab. Median age was 57 years (interquartile range [IQR]: 45–65). Among the 59 patients, 25 (42%) received cellular therapy: 14 (24%) had undergone allogeneic HCT, nine (15%) autologous HCT, and two (3%) received chimeric antigen receptor T‐cell therapy. The median time from COVID‐19 symptom onset to SARS‐CoV‐2‐specific mAb administration was 4 (IQR: 3–6) days. Forty‐six (78%) patients received SARS‐CoV‐2‐specific mAbs as outpatients and 13 (22%) patients received SARS‐CoV‐2‐specific mAbs during hospitalization. Among patients who received SARS‐CoV‐2‐specific mAbs as outpatients, only four (9%) visited the emergency department at days 10, 11, 15, and 35 after SARS‐CoV‐2‐specific mAb administration. None of these four patients required hospital admission. Among the hospitalized patients, five (38%) were admitted to the hospital with neutropenic fever, four (31%) were already hospitalized for transplantation and cellular therapy, three (23%) were admitted for monitoring of COVID‐19 symptoms, and one (8%) was admitted with acute kidney injury. Three hospitalized patients (23%) died at 14, 35, and 59 days after SARS‐CoV‐2‐specific mAb administration; two of these three deaths were attributed to COVID‐19 infection. One patient developed an immediate infusion reaction to bamlanivimab, and no infusion reactions were reported to casirivimab–imdevimab use.ConclusionDuring the alpha and delta variant surges, early administration of bamlanivimab or casirivimab–imdevimab prevented hospitalization and death when given in the outpatient setting. Among patients who received mAbs at or after hospital admission, the risk of COVID‐19 disease progression and death remains significant. Larger studies of the use of mAb therapy to treat COVID‐19 in this population are needed. image

Abstract Background Laboratory medicine has reached the era where promises of artificial intelligence and machine learning (AI/ML) seem palpable. Currently, the primary responsibility for risk-benefit assessment in clinical practice resides with the medical director. Unfortunately, there is no tool or concept that enables diagnostic quality assessment for the various potential AI/ML applications. Specifically, we noted that an operational definition of laboratory diagnostic quality – for the specific purpose of assessing AI/ML improvements – is currently missing. Methods A session at the 3rd Strategic Conference of the European Federation of Laboratory Medicine in 2022 on “ AI in the Laboratory of the Future” prompted an expert roundtable discussion. Here we present a conceptual diagnostic quality framework for the specific purpose of assessing AI/ML implementations. Results The presented framework is termed diagnostic quality model (DQM) and distinguishes AI/ML improvements at the test, procedure, laboratory, or healthcare ecosystem level. The operational definition illustrates the nested relationship among these levels. The model can help to define relevant objectives for implementation and how levels come together to form coherent diagnostics. The affected levels are referred to as scope and we provide a rubric to quantify AI/ML improvements while complying with existing, mandated regulatory standards. We present 4 relevant clinical scenarios including multi-modal diagnostics and compare the model to existing quality management systems. Conclusions A diagnostic quality model is essential to navigate the complexities of clinical AI/ML implementations. The presented diagnostic quality framework can help to specify and communicate the key implications of AI/ML solutions in laboratory diagnostics.

Abstract Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health’s Alzheimer’s Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows.