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Lupus nephritis represents a significant immune-mediated glomerulonephritis, constituting the most important organ involvement induced by systemic lupus erythematosus (SLE), with variable epidemiology and clinical presentation among populations. Objective: to identify clinical and immunological factors associated with the progression of lupus nephritis in a population from the Colombian Caribbean. Methods: we evaluated 401 patients diagnosed with SLE and lupus nephritis, treated at a reference center in the Colombian Caribbean, gathering data recorded in medical records. Results: A proportion of 87% were female, with a median age of 42 years. Most patients presented with proliferative classes (90%), with class IV being the most common (70%). A proportion of 52% of patients did not respond to treatment, which is described as the lack of complete or partial response, while 28% had a complete response. A significant decrease in hemoglobin, glomerular filtration rate, and proteinuria was identified by the third follow-up (p < 0.001), along with an increase in creatinine, urea, and hematuria (p < 0.001). Patients with initial proteinuria > 2 g/day were found to be 27 times more likely to be non-responders (p < 0.001). Mortality was associated with the presence of serum creatinine >1.5 mg/dL (p = 0.01) (OR: 1.61 CI 95% 0.75–3.75) and thrombocytopenia (p = 0.01) (OR: 0.36; CI 95% 0.12–0.81). Conclusions: identifying factors of progression, non-response, and mortality provides an opportunity for more targeted and personalized intervention, thereby improving care and outcomes for patients with lupus nephritis.

Background Clinicians, researchers, and patients alike would greatly benefit from more accessible and inexpensive biomarkers for neural β-amyloid (Aβ). We aimed to assess the performance of fully automated plasma Aβ immunoassays, which correlate significantly with immunoprecipitation mass spectrometry assays, in predicting brain Aβ status as determined by visual read assessment of amyloid positron emission tomography (PET). Methods The plasma Aβ42/Aβ40 ratio was measured using a fully automated immunoassay platform (HISCL series) in two clinical studies (discovery and validation studies). The discovery and validation sample sets were retrospectively and randomly selected from participants with early Alzheimer’s disease (AD) identified during screening for the elenbecestat Phase 3 program. Results We included 197 participants in the discovery study (mean [SD] age 71.1 [8.5] years; 112 females) and 200 in the validation study (age 70.8 [7.9] years; 99 females). The plasma Aβ42/Aβ40 ratio predicted amyloid PET visual read status with areas under the receiver operating characteristic curves of 0.941 (95% confidence interval [CI] 0.910–0.973) and 0.868 (95% CI 0.816–0.920) in the discovery and validation studies, respectively. In the discovery study, a cutoff value of 0.102 was determined based on maximizing the Youden Index, and the sensitivity and specificity were calculated to be 96.0% (95% CI 90.1–98.9%) and 83.5% (95% CI 74.6–90.3%), respectively. Using the same cutoff value, the sensitivity and specificity in the validation study were calculated to be 88.0% (95% CI 80.0–93.6%) and 72.0% (95% CI 62.1–80.5%), respectively. Conclusions The plasma Aβ42/Aβ40 ratio measured using the HISCL series achieved high accuracy in predicting amyloid PET status. Since our blood-based immunoassay system is less invasive and more accessible than amyloid PET and cerebrospinal fluid testing, it may contribute to the diagnosis of AD in routine clinical practice.

BackgroundThis phase 1 first-in-human study aimed to determine the maximum-tolerated dose (MTD), dose-limiting toxicities, and safety of E6201, and to establish recommended dosing in patients with advanced solid tumours, expanded to advanced melanoma.MethodsPart A (dose escalation): sequential cohorts received E6201 intravenously (IV) over 30 min (once-weekly [qw; days (D)1 + 8 + 15 of a 28-day cycle]), starting at 20 mg/m2, increasing to 720 mg/m2 or the MTD. Part B (expansion): patients with BRAF-mutated or wild-type (WT) melanoma received E6201 320 mg/m2 IV over 60 minutes qw (D1 + 8 + 15 of a 28-day cycle) or 160 mg/m2 IV twice-weekly (D1 + 4 + 8 + 11 + 15 + 18 of a 28-day cycle; BRAF-mutated only).ResultsMTD in Part A (n = 25) was 320 mg/m2 qw, confirmed in Part B (n = 30). Adverse events included QT prolongation (n = 4) and eye disorders (n = 3). E6201 exposure was dose-related, with PK characterised by extensive distribution and fast elimination. One patient achieved PR during Part A (BRAF-mutated papillary thyroid cancer; 480 mg/m2 qw) and three during Part B (2 BRAF-mutated melanoma; 1 BRAF-WT melanoma; all receiving 320 mg/m2 qw).ConclusionsAn intermittent regimen of E6201 320 mg/m2 IV qw for the first 3 weeks of a 28-day cycle was feasible and reasonably well-tolerated in patients with advanced solid tumours, including melanoma with brain metastases, with evidence of clinical efficacy.

Objectives Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are well‐established in research settings, but their use in routine clinical practice remains a largely unexploited potential. Here, we examined the relationship between CSF biomarkers, measured by a fully automated immunoassay platform, and brain β‐amyloid (Aβ) deposition status confirmed by amyloid positron emission tomography (PET). Methods One hundred ninety‐nine CSF samples from clinically diagnosed AD patients enrolled in a clinical study and who underwent amyloid PET were used for the measurement of CSF biomarkers Aβ 1–40 (Aβ40), Aβ 1–42 (Aβ42), total tau (t‐Tau), and phosphorylated tau‐181 (p‐Tau181) using the LUMIPULSE system. These biomarkers and their combinations were compared to amyloid PET classification (negative or positive) using visual read assessments. Several combinations were also analyzed with a multivariable logistic regression model. Results Aβ42, t‐Tau, and p‐Tau181, and the ratios of Aβ42 with other biomarkers had a good diagnostic agreement with amyloid PET imaging. The multivariable logistic regression analysis showed that amyloid PET status was associated with Aβ40 and Aβ42, but other factors, such as MMSE, sex, t‐Tau, and p‐Tau181, did not significantly add information to the model. Conclusions CSF biomarkers measured with the LUMIPULSE system showed good agreement with amyloid PET imaging. The ratio of Aβ42 with the other analyzed biomarkers showed a higher correlation with amyloid PET than Aβ42 alone, suggesting that the combinations of biomarkers could be useful in the diagnostic assessment in clinical research and potentially in routine clinical practice.

We have developed an integrated, multidisciplinary methodology, termed systems pathology, to generate highly accurate predictive tools for complex diseases, using prostate cancer for the prototype. To predict the recurrence of prostate cancer following radical prostatectomy, defined by rising serum prostate-specific antigen (PSA), we used machine learning to develop a model based on clinicopathologic variables, histologic tumor characteristics, and cell type-specific quantification of biomarkers. The initial study was based on a cohort of 323 patients and identified that high levels of the androgen receptor, as detected by immunohistochemistry, were associated with a reduced time to PSA recurrence. The model predicted recurrence with high accuracy, as indicated by a concordance index in the validation set of 0.82, sensitivity of 96%, and specificity of 72%. We extended this approach, employing quantitative multiplex immunofluorescence, on an expanded cohort of 682 patients. The model again predicted PSA recurrence with high accuracy, concordance index being 0.77, sensitivity of 77% and specificity of 72%. The androgen receptor was selected, along with 5 clinicopathologic features (seminal vesicle invasion, biopsy Gleason score, extracapsular extension, preoperative PSA, and dominant prostatectomy Gleason grade) as well as 2 histologic features (texture of epithelial nuclei and cytoplasm in tumor only regions). This robust platform has broad applications in patient diagnosis, treatment management, and prognostication.

The goal of this article is to describe a two‐stage design that maximizes the power to detect gene‐disease associations when the principal design constraint is the total cost, represented by the total number of gene evaluations rather than the total number of individuals. In the first stage, all genes of interest are evaluated on a subset of individuals. The most promising genes are then evaluated on additional subjects in the second stage. This will eliminate wastage of resources on genes unlikely to be associated with disease based on the results of the first stage. We consider the case where the genes are correlated and the case where the genes are independent. Using simulation results, it is shown that, as a general guideline when the genes are independent or when the correlation is small, utilizing 75% of the resources in stage 1 to screen all the markers and evaluating the most promising 10% of the markers with the remaining resources provides near‐optimal power for a broad range of parametric configurations. This translates to screening all the markers on approximately one quarter of the required sample size in stage 1.

Background Single analyte blood‐based biomarkers such as p‐tau181 and p‐tau217 are promising biomarkers for identifying Alzheimer's disease (AD) pathology. However, multi‐analyte blood‐based biomarker panels are needed to further improve the detection, differential diagnosis, and screening of AD and to predict disease progression and assess response to therapy. The Alamar NULISASeq CNS Disease Panel (“NULISASeq”) simultaneously profiles 120 proteins associated with neurodegeneration, synaptic, and inflammatory pathways to support these goals. Multiplexed panels also maximize the potential of precious clinical trial biospecimens while also providing the sensitivity required to measure low abundant analytes. Methods Plasma samples were collected during screening from a Phase 3 program for elenbecestat (MissionAD) in early AD and analyzed using NULISASeq. Data normalization was performed using the vendor protocol to form NULISA Protein Quantification (NPQ) units, used for statistical analysis. Analysis of Variance (ANOVA) was used to determine statistical significance of the difference in each target protein level between amyloid+ and amyloid‐ subjects as determined by PET visual read. p‐values were adjusted for multiplicity. Cohen's D was calculated to show the effect size of difference in target protein levels. The correlation of overlapping target protein levels between NULISASeq and other assays was evaluated. Results A total of 124 subjects were included in the statistical analysis (74 amyloid+ and 50 amyloid‐). Statistical significance was observed in 7 plasma proteins (GFAP, MAPT, NEFH, SNAP25, pTau‐181, pTau‐217, pTau‐231) between amyloid+ and amyloid‐ subjects. pTau‐217 showed the largest effect size. In predicting amyloid status, using pTau‐217 alone also resulted in the highest AUC (0.87). Combining these proteins did not result in much improvement in prediction. NULISASeq protein levels of common ATN biomarkers showed high correlation with that of other assays in both plasma and CSF. Conclusion Targeted multiplexed panels such as NULISASeq quantifies multiple analytes in a single run thereby reducing the amount of precious input material and the time required for analysis. This offers advantage over fluid and neuroimaging‐based measurements tailored to singular targets. We have demonstrated the utility of a multiplexed panel for reliable detection of amyloid status as well as highlighted the potential of discovering novel biomarkers associated with AD.

Single analyte blood-based biomarkers such as p-tau181 and p-tau217 are promising biomarkers for identifying Alzheimer's disease (AD) pathology. However, multi-analyte blood-based biomarker panels are needed to further improve the detection, differential diagnosis, and screening of AD and to predict disease progression and assess response to therapy. The Alamar NULISASeq CNS Disease Panel (\"NULISASeq\") simultaneously profiles 120 proteins associated with neurodegeneration, synaptic, and inflammatory pathways to support these goals. Multiplexed panels also maximize the potential of precious clinical trial biospecimens while also providing the sensitivity required to measure low abundant analytes. Plasma samples were collected during screening from a Phase 3 program for elenbecestat (MissionAD) in early AD and analyzed using NULISASeq. Data normalization was performed using the vendor protocol to form NULISA Protein Quantification (NPQ) units, used for statistical analysis. Analysis of Variance (ANOVA) was used to determine statistical significance of the difference in each target protein level between amyloid+ and amyloid- subjects as determined by PET visual read. p-values were adjusted for multiplicity. Cohen's D was calculated to show the effect size of difference in target protein levels. The correlation of overlapping target protein levels between NULISASeq and other assays was evaluated. A total of 124 subjects were included in the statistical analysis (74 amyloid+ and 50 amyloid-). Statistical significance was observed in 7 plasma proteins (GFAP, MAPT, NEFH, SNAP25, pTau-181, pTau-217, pTau-231) between amyloid+ and amyloid- subjects. pTau-217 showed the largest effect size. In predicting amyloid status, using pTau-217 alone also resulted in the highest AUC (0.87). Combining these proteins did not result in much improvement in prediction. NULISASeq protein levels of common ATN biomarkers showed high correlation with that of other assays in both plasma and CSF. Targeted multiplexed panels such as NULISASeq quantifies multiple analytes in a single run thereby reducing the amount of precious input material and the time required for analysis. This offers advantage over fluid and neuroimaging-based measurements tailored to singular targets. We have demonstrated the utility of a multiplexed panel for reliable detection of amyloid status as well as highlighted the potential of discovering novel biomarkers associated with AD.

Background Existing copathologies, such as Lewy body (LB) disease, can introduce heterogeneity to AD pathogenesis and presentation of symptoms and likely influence disease progression. A seed amplification assay (SAA) that detects aggregated, misfolded α‐synuclein (α‐syn) can detect LB. Incorporation of SAA can characterize disease heterogeneity in AD and potentially predict disease progression. Methods A validated SAA was used to characterize α‐syn SAA status (Amprion Clinical Laboratory) in baseline CSF samples collected from a Phase 3 program for elenbecestat in subjects with MCI or mild dementia due to AD (NCT02956486). Samples were selected by PET visual read status. The sample set was enriched using subjects considered to be progressors or non‐progressors based on change in cognition (CDR‐SB) at 18 months, before assessment of SAA status. Results of α‐syn status were reported as Detected, Not Detected, or Indeterminate. The proportion of samples defined as Detected and Not Detected were summarized by amyloid status. Cognition, at baseline and longitudinally, was summarized by amyloid and α‐syn status. Available baseline A/T/N biomarkers were also summarized and compared. Results Among the 201 samples that were included in the analyses, 15% of amyloid+ and 8% of amyloid‐ MCI/early AD subjects were determined to be SAA+ and hence determined to have LB copathology. In comparison, in ADNI, 17% of cognitively unimpaired (CU) subjects; 20% of MCI subjects and 39% of AD subjects had synuclein copathology (Tosun et al Alzheimer's Dement. 2024). In BioFinder2, synuclein copathology was detected in 8%, 17% and 23% of CU, MCI, and AD subjects, respectively (Palmqvist et al and Quadalti et al Nature Medicine 2023). The longitudinal trajectory of amyloid positive subjects with α‐syn copathology seemed to have faster cognitive decline in natural history studies. In the Phase 3 samples, the longitudinal cognitive trajectory showed trend towards faster decline over 18 months in the amyloid+ subjects with α‐syn copathology; however, this did not appear significant. Conclusion LB, a common copathology of AD, may be a source of heterogeneity. Incorporation of SAA, a specific biomarker of LB‐pathology, can help account for disease heterogeneity and potentially improve assessment of treatment response in amyloid and synuclein status confirmed AD target population.

BACKGROUND With the availability of disease‐modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment. METHODS High‐throughput, mass spectrometry‐based assays were used to measure %p‐tau217 and amyloid beta (Aβ)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET. RESULTS The area under the receiver operating characteristic curve (AUC‐ROC) for %p‐tau217 (0.94) was statistically significantly higher than that for p‐tau217 concentration (0.91). The AUC‐ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status. DISCUSSION The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.