Plasma proteomic associations with genetics and health in the UK Biobank

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Independent study demonstrates amyloid probability score accurately indicates amyloid pathology

BACKGROUND

The amyloid probability score (APS) is the model read-out of the analytically validated mass spectrometry-based PrecivityAD^® blood test that incorporates the plasma Aβ42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired individuals being evaluated for Alzheimer's disease.

PURPOSE

This study aimed to provide additional independent evidence that the pre-established APS algorithm, along with its cutoff values, discriminates between amyloid positive and negative individuals.

METHODS

The diagnostic performance of the PrecivityAD test was analyzed in a cohort of 200 nonrandomly selected Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL) study participants, who were either cognitively impaired or healthy controls, and for whom a blood sample and amyloid PET imaging were available.

RESULTS

In a subset of the dataset aligned with the Intended Use population (patients aged 60 and older with CDR ≥0.5), the pre-established APS algorithm predicted amyloid PET with a sensitivity of 84.9% (CI: 72.9-92.1%) and specificity of 96% (CI: 80.5-99.3%), exclusive of 13 individuals for whom the test was inconclusive.

INTERPRETATION

The study shows individuals with a high APS are more likely than those with a low APS to have abnormal amounts of amyloid plaques and be on an amyloid accumulation trajectory, a dynamic and evolving process characteristic of progressive AD pathology. Exploratory data suggest APS retains its diagnostic performance in healthy individuals, supporting further screening studies in the cognitively unimpaired.

Inter-rater Agreement on Final Competency Testing Utilizing Standardized Patients

The purpose of this study was to determine whether licensed physical therapists (n=8) serving as standardized patients (SPs) for practical examinations evaluate physical therapy students (n=51) equivalently to the physical therapy course instructor (n=1).

METHODS

The SPs completed the same assessment based on the evaluation criteria as did the instructor. The scores for the practical examination, answers to three questions, and the documentation note were summarized separately for the SP and the instructor by means and standard deviations. A paired t-test and an intraclass correlation coefficient (ICC) for each aspect of the score were calculated. ICC(1,1) values were reported along with corresponding 95% confidence intervals.

RESULTS

The instructor had significantly higher scores for the practical exam and the overall score compared to the ratings from the SPs. No differences were observed between the instructor and SP scores on the three answers to the questions and documentation note scores.

CONCLUSIONS

Based on the ICC values identified in this study, a physical therapist serving as an SP may not be an adequate replacement for an instructor when it comes to grading physical therapy students on all aspects of their competency tests.

Computer-automated dementia screening using a touch-tone telephone

BACKGROUND

This study investigated the sensitivity and specificity of a computer-automated telephone system to evaluate cognitive impairment in elderly callers to identify signs of early dementia.

METHODS

The Clinical Dementia Rating Scale was used to assess 155 subjects aged 56 to 93 years (n = 74, 27, 42, and 12, with a Clinical Dementia Rating Scale score of 0, 0.5, 1, and 2, respectively). These subjects performed a battery of tests administered by an interactive voice response system using standard Touch-Tone telephones. Seventy-four collateral informants also completed an interactive voice response version of the Symptoms of Dementia Screener.

RESULTS

Sixteen cognitively impaired subjects were unable to complete the telephone call. Performances on 6 of 8 tasks were significantly influenced by Clinical Dementia Rating Scale status. The mean (SD) call length was 12 minutes 27 seconds (2 minutes 32 seconds). A subsample (n = 116) was analyzed using machine-learning methods, producing a scoring algorithm that combined performances across 4 tasks. Results indicated a potential sensitivity of 82.0% and specificity of 85.5%. The scoring model generalized to a validation subsample (n = 39), producing 85.0% sensitivity and 78.9% specificity. The kappa agreement between predicted and actual group membership was 0.64 (P<.001). Of the 16 subjects unable to complete the call, 11 provided sufficient information to permit us to classify them as impaired. Standard scoring of the interactive voice response-administered Symptoms of Dementia Screener (completed by informants) produced a screening sensitivity of 63.5% and 100% specificity. A lower criterion found a 90.4% sensitivity, without lowering specificity.

CONCLUSIONS

Computer-automated telephone screening for early dementia using either informant or direct assessment is feasible. Such systems could provide wide-scale, cost-effective screening, education, and referral services to patients and caregivers.